From c2eadb9465ee45bc5508edae8d7a9145f4d0a541 Mon Sep 17 00:00:00 2001 From: karllzy Date: Mon, 27 Jun 2022 19:03:10 +0800 Subject: [PATCH] Add other optimizers --- 01_preprocess.ipynb | 0 02_model_training.ipynb | 8085 +++++++++--------- 02_model_training_adagrad.ipynb | 7438 +++++++++++++++++ 02_model_training_nadam.ipynb | 7256 ++++++++++++++++ 02_model_training_rmsprop.ipynb | 7250 ++++++++++++++++ 02_model_training_sgd.ipynb | 13253 ++++++++++++++++++++++++++++++ 03_model_evaluating.ipynb | 229 +- 04_model_comparision.ipynb | 4118 +++++++++- models.py | 163 +- 9 files changed, 43694 insertions(+), 4098 deletions(-) mode change 100644 => 100755 01_preprocess.ipynb create mode 100644 02_model_training_adagrad.ipynb create mode 100755 02_model_training_nadam.ipynb create mode 100644 02_model_training_rmsprop.ipynb create mode 100644 02_model_training_sgd.ipynb mode change 100644 => 100755 03_model_evaluating.ipynb mode change 100644 => 100755 models.py diff --git a/01_preprocess.ipynb b/01_preprocess.ipynb old mode 100644 new mode 100755 diff --git a/02_model_training.ipynb b/02_model_training.ipynb index 3a282cc..5cfc6aa 100644 --- a/02_model_training.ipynb +++ b/02_model_training.ipynb @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": { "pycharm": { "name": "#%%\n" @@ -60,7 +60,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": { "pycharm": { "name": "#%%\n" @@ -87,6 +87,7 @@ "tensorflow.random.set_seed(4750)\n", "time1 = time.time()\n", "data = loadmat('dataset/mango/mango_dm_split.mat')\n", + "training_method = \"adam\"\n", "x_train, y_train, x_test, y_test = data['x_train'], data['y_train'], data['x_test'], data['y_test']\n", "x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size=0.3, random_state=12, shuffle=True)\n", "x_train, x_val, x_test = x_train[:, np.newaxis, :], x_val[:, np.newaxis, :], x_test[:, np.newaxis, :]\n", @@ -109,7 +110,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "metadata": { "pycharm": { "name": "#%%\n" @@ -122,7 +123,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 4, "metadata": { "pycharm": { "name": "#%%\n" @@ -133,7 +134,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-06-12 20:45:05.812551: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz\n" + "2022-06-27 18:15:28.328745: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz\n" ] }, { @@ -141,761 +142,761 @@ "output_type": "stream", "text": [ "Epoch 1/1024\n", - "90/90 [==============================] - 1s 4ms/step - loss: 0.0236 - val_loss: 0.0272 - lr: 0.0025\n", + "90/90 [==============================] - 7s 25ms/step - loss: 0.0236 - val_loss: 0.0272 - lr: 0.0025\n", "Epoch 2/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0297 - lr: 0.0025\n", + "90/90 [==============================] - 1s 12ms/step - loss: 0.0188 - val_loss: 0.0297 - lr: 0.0025\n", "Epoch 3/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0301 - lr: 0.0025\n", + "90/90 [==============================] - 1s 15ms/step - loss: 0.0127 - val_loss: 0.0301 - lr: 0.0025\n", "Epoch 4/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0315 - lr: 0.0025\n", + "90/90 [==============================] - 1s 12ms/step - loss: 0.0088 - val_loss: 0.0315 - lr: 0.0025\n", "Epoch 5/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0081 - val_loss: 0.0813 - lr: 0.0025\n", + "90/90 [==============================] - 1s 13ms/step - loss: 0.0081 - val_loss: 0.0813 - lr: 0.0025\n", "Epoch 6/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0309 - lr: 0.0025\n", + "90/90 [==============================] - 1s 10ms/step - loss: 0.0072 - val_loss: 0.0309 - lr: 0.0025\n", "Epoch 7/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0930 - lr: 0.0025\n", + "90/90 [==============================] - 1s 9ms/step - loss: 0.0069 - val_loss: 0.0930 - lr: 0.0025\n", "Epoch 8/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0313 - lr: 0.0025\n", + "90/90 [==============================] - 1s 13ms/step - loss: 0.0066 - val_loss: 0.0313 - lr: 0.0025\n", "Epoch 9/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0058 - val_loss: 0.0597 - lr: 0.0025\n", + "90/90 [==============================] - 1s 9ms/step - loss: 0.0058 - val_loss: 0.0597 - lr: 0.0025\n", "Epoch 10/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0050 - val_loss: 0.0376 - lr: 0.0025\n", + "90/90 [==============================] - 1s 9ms/step - loss: 0.0050 - val_loss: 0.0376 - lr: 0.0025\n", "Epoch 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[==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.2760e-14\n", "Epoch 1019/1024\n", - "90/90 [==============================] - 0s 821us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 7.2760e-14\n", "Epoch 1020/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", "Epoch 1021/1024\n", - "90/90 [==============================] - 0s 845us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", "Epoch 1022/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 7.2760e-14\n", "Epoch 1023/1024\n", - "90/90 [==============================] - 0s 856us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.2760e-14\n", "Epoch 1024/1024\n", - "90/90 [==============================] - 0s 837us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.2760e-14\n" + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.2760e-14\n" ] } ], "source": [ "epoch, batch_size = 1024, 64\n", - "history_plain_11 = plain_11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size)\n", - "history_plain_5 = plain_5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size)" + "history_plain_11 = plain_11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)\n", + "history_plain_5 = plain_5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)" ] }, { @@ -3528,7 +3531,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "metadata": { "pycharm": { "name": "#%%\n" @@ -3554,7 +3557,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "metadata": { "pycharm": { "name": "#%%\n" @@ -3569,7 +3572,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, "metadata": { "pycharm": { "name": "#%%\n" @@ -3584,7 +3587,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "metadata": { "pycharm": { "name": "#%%\n" @@ -3593,10 +3596,8 @@ "outputs": [ { "data": { - "image/png": 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J6z5tXbuWnp7fVtnGjUz1/J7q6z4NGDCA0tJSFnss1R49etClSxe+/34WMIRASkuLqKjoUOU+bdy4kaVLlwKQlpZG69YdgbZ6XmUCuPi4T336MHXqVICE+j+Fuk95npT4tm3bkpmZydSp1f+fAu9TLP5PQ4cOrfK72oGIRGUCTgGe8VseDjxaTfvBwJcB61oDs4CTwvnO/fbbT6LO99+LvPZa9L+nHqmoENm8WeSKK6pv9957IkceKdK7t8iff1bf9o8/9JgJx623imjIRuRf/4q1NDuoqPCJ5T+demp4+5eV+fZxLrqyGglHyGdqNF1MhUAPv+VU4LdQjUVkCrCHc24XAOdcU+Bt4BURiY+OCKC5o99/HzfB6kjgnLre99yzalHArVvhyy+1j8Utt8DZZ8Orr2rW7223acZUsNFZx47VPhvBuOkm8Ly8xB9xGqR2LnhZ73D7APoXuPWqCsOoiWgqiJlAb+dcunOuGXA6MNG/gXNuT+e09KZzLhNoBhR51j0LzBeR/0ZRxtrjHJx0Enz2WawliTgHHqi6DzQ2ce65cN558MYb2hHv2WfhrLMgK0t7bOfm6gPqxRd9te0WLICiIq2WXlFRObZx2WWqZHr21P29rFoVRyVC4jRIDcHjEOEqCOcqKwmLQxjhELUYhIiUOecuBT4DkoDnRKTAOTfKs30ccDJwjnNuO7AFOE1ExJPuOhz42Tn3k+eQN4rIx9GSt1bk5MAdd8Bxx8Vakoiy776a3TR9uiqIK6/UoU6LivRBFFjS6NBDdRo3Th/8AwfCk09q4NSbSnv22VpD6sMPtSrt6afrvu+8o+uKi2HaNBg2DA47rN5PuSpxGqQGVRCByQThKgjv/tu26Xx5efgpskbjJao/Ec8D/eOAdeP85scCY4PsNxWI36FykpMb5CtYcrLqPRF9q99tN13v/QzFqFG6z7hxMGmS9r/w8vPPcPHFcNRRPuUAaoRdeKG6tR5/XBVMTQpi82ZNIrvyyjqdXnjEaU9qCJ7SWhsFEdibOpwhMozGjb1D1JW+fTVXdP/9Yy1JxHGuZqUQbJ/Ro6uuHz4cTj1Vy4EEcsghcOyx+uBq3lzjEv7KJZBZs1ThfPqpKpyoEOcWRCB1VRAN8P3GiAJWaqOunHkmvPderKWIe9q0Ca4cQOMZ3qGiR4+G++4LfZzvvtMChP/5j1opURthz19B/PxzlL6kbkTSgjAFYYSDKYi6kpSkr81W+Swi7Lqrujz+/LPqtvJyjWNMnarK5p//VDfT3XfrSHt//FG37xQJUsm9Tx/f/IIFsGhR3Q4eBXbWgrDOckZtMQWxMwweDJ4OKMbOc+GFcPvtvgSxKVPgggtUGVxyiZbCAujaVVNtzz9fx7545ZXaf9fs2fDww3Dzzb7ALaBR+b59fcueTkzxQLxbEBUV8MsvkT+uERnKy3VwsYcfDt97agpiZzjkEFMQEaRrV61U+/bb8NtvmuX0yCPw4IOVn9mgxlvXrnD11Zpiu2ABLF8OK1YEO7KPrVvVcpgwQRXLNddoxtVTT2lISQQYMMC3Q4hCVcXFvvn66hITyRhENAzfTz7Re/X443U/xrZtjfsvtWCBeq9//z1yx7zvPo3fvfeeltvp21fvUzhYkHpnaNrUXEwRZq+9tPPdq6/CMcdUHr8nFNdfr+WWdt9d+3JccIF27FuxAj74ANat02f+GWfosXv21Pp9X32lIYeLLtL+HosWacrtFf75vJ4SDzt6ljnHv/+tt10E5s2D1FRVGA8+WLvCsYGUllafWRSOBfHnn6qw2rbV0XL9iaYFsWCBWn4PP6wFIV99VR904bJsmdbBzMtTo61/f3jtNU2WOOmkyMq6s6xerdfXP+FtZyko0CzAnj19SnbQIO1rtOuu4R9n40aN+y1frr+XP//U6ZNP9Df6ww8q9/Tpep2TkvR/EwonDahLZVZWluTV9/Cgr7yiVzzefsWNjLIy7Qh21VXQqZO+gXXvruvHjNGH13ffaYihZUtNqfUGz7/5Ro1B0DTfs2deQfoHj/gOfsUV2hswLY0fH/yGub+2Y/hw375Dh+r3vf56+Cm4BQWqoE4/Xd/sVqxQ6yYrS4PxwRg4sGrcfNEiLTIMWpDxhRdUyeTn67HGjPE9yNLSfC6gpUt1kKlIMG6cvvmPGuVTSrfcoteyJj7+WO/NXnvpvt578+ij+mCbOVMVRc+eNR8rWpSW6otFs2Yqx/Tp6u68/vrwhzuvjvnz1YK9/36flfjhh/pu0qyZvryEw8aNcOSR+pJz7bX6olBergon0PpcswbuuktfkMaOraZLQXV1OBJtqpdaTMG44YbYfK9RhQMPFPn1V5HSUl2uqPBt+/FHke3baz7GvJNvDl74COS9jFtDHuPKK0WuvVZk2rTQx378cZGrr9bpxx+1/Y8/inz9tW6/4YbKMvvz739XFem333Tbhg0il10mUl7uW54/X49/9tkq0667+vZ7+WXfcceM0WOPG1f5+2bMELnkkupran3/vcg991Rdf/PNIgsXht5PROTOO0UmTBBZsCD49u3bRVauFHn44eqPU1u+/Vbvw//+F177e+4RWbJE2xcWimzZIvL66yJPP1237y8rE5k1S+dnzxY588zg17iiQuSii0QKCkSKioIfq7BQp6VLRY45RuS++0TOP1/kscf0OwoKqpfF81sLXVOvuo2JNsVMQUyeLPL887H5bqMS8+dH4CBjx4ZUEOWHHBpyt9JS/cNddZXI8uWqqJ59VuTBB/UB/cADIl99Vf1Xv/66yA8/iPz+e9Vt69ZVFWnDBt02ZozIqlXBj1lRIXLNNSJduvj2u+IKkW++EfnkE5HnnhMpKdHTLi72ncsVV+j1fOopkUmTRNav9x1zzRp90N5wQ3Clu3SpnveYMSIff1y5TXm51rt86aXqr4WXSy4R+eADPX8RfViOHCmyaJEub90aWqkGynTPPaqcly0TufRSfdhXx/Llet+Ccd11eh1qUoT+fPGFKvK771aFfM45Kn8o1q8XOflkkdtvr7rt3Xf1+t58s8iJJ/qOs2aNyKZN4csk1TxTzcUUKW69VVNwjMTnySd1mNlgnHqq+pKq4ddfdfS+Nm0gM1NdXh9/rMvXXlv9V2/frq6a/Hx1r7gA43/0aHXpeDn/fP0O0Eyv6ujXz1dY8eef1bW11146TK1zsGSJ9jNp3VrdXddeq26oK6/UTox/+YvGd0Q0vnD66erS8O86EogIfP65lnDZYw/tOPnss+r+Ovzw6uX15913NUaxapWeb69e6qJr0kRdQH/+qcUjvf1qvMybp4lpInD55RqjOvxwjUEtXqydLi+7zNf+6ae17+ugQbp8/fXqpgs8LqjX8YMPtO7YY49VjfmAxsJatdKyM2PHaiysXTu9brm5un/HjjWf/223aXp3u3a6vHix7nvVVbosUvW3UgvMxRR1brkl+PrCQpHFi+tXFmPnePLJkBaEjBxZp0Nu3Rp++fMlS0QeekgkP7/qtssuqyxOcbEasP5v96EYMMC3X7Bjh+LPP/Wt//rrRX7+Wa2h8ePD319EZONGdReNHq1ukLqydq2WnN+2TZenTNG38aIikRtvFJk5Uy2fb7/VNscfr9M116g7J5Abb9TPb75Rd9xHH4lcfrle10svFfnyy9CyVFSolThrlsiLL1bdXlwsMmiQyE8/qRUUaBXWphz+qlV67SZMELn/fpXVa+1FgJDPVMtiihTNm2vRoQED9JXkww/11eGDD/SVzKyLxGHTptDbNm+u0yFrU/dojz3UUrjuOnjgAc008b4hBgYbO3TQ7jjhUNeOct7yJ717q0x9++obbW1o3VqnRx7Zucq9u+yib/1eDj5YJ9AEhJkz9U3dmwn3wAOaCTVvns8q8KdTJ7WkJk/W7CvnNGvolFPUQujWLbQszkGPHjq98YZaN127+rZ/840e86qrtHqx/zaoXRZUly56jPnztX7Zxo1676ONuZgiRXk5LFyo6QgnnKB+gFWr9Nf6+eeaCRPMTjXij4kT9R4Go1OnunfdriXPPaeuqY4dta9H8+aaffTdd742tfn7ZmVpPjzogzQrq/YylZSosgt3LOxY8cMPmnEU+FAOZOtWTa0dOLByHbCaUo4DKSnR98IRIzSrbdMmVVKPPBJ8HI84I6SLyRREpCko0N5bI0boQ6ZlS81Xe+stVRJG/FNRUf2/+uabw8vh3Em8b/lNmmjJ9SVL1Ef+/PO+NrX5+2Zn64MTdNyP7CoDABs7w4wZ2n+hVStVMHffXbOCihNCKghzMUWa/v3ho48qP2C6d9eeK3PnVu6la8QnTZrApZdq5DEYd96pLsOdiAqGg/9PaJdddPrmm8gcz/p3Rp7sbF8nzKKi2nVwi1es1EY0CPb2+cADWt/BSAxq8qGUlNSPHAGMGuXrPX3zzbXb16q5Rp/ddtP3i4agHMAsiPqjSRONSq1dq36BnanJYESfmhTEmjWR6UZbSzp0UC/mvHm1H4HPqrkatcUsiPrk0ks1cvX3v2tZRSN+CVQQgRHLo4/WIk8xoGdPHTCptkOGmgVh1BZTEPVJ+/YawH7+eS02szP5fkZ0CVQQZ50FRxzhW168uHK0OAEwBWHUFlMQ9c2AAZqwvcceWvXLiE8Cu8U2bap+HX+WL683cSKBBamN2mIKIhY4p2mw99zjKydtxBeBFkSzZnD22ZXXrV9fb+JEAn+XVH2NYWEkNqYgYkVKiqZLfv99rCUxghGoIJo21Z7y/gQbHzWO8e95G6PwiZFgmIKIJQMG6EDLZWVamsOIH4JZEGlp8PXXvnUJZkF4x7+A4J3Bg1kVd96poRfzhjZOTEHEkuRkHanmxBM16FlDlVCjHglmQUDlcikNSEHcdZd2+r/wQl/v7GnTdOCfL77QrCn/YVaNxoEpiFhz/PE6lNSVV2qhnfPOsxSTeCAwSO1dTmAF4d95a+3ayttuvlkN2Wef9Y1a99Zbvu0bNsCXX0ZfRiO+MAURD/Ttq59jxmiB/48+iq08RoO3INasCd3OWy01UCFYPkXjwxREvHHQQfDtt1VTKo36JVgMAiqX/NywIaGsPX8F8dFHvhh7YOxh0SLdNndu5fXWt7PxYQoi3mjSBI49VseRePzx2pXrNCJHKAsiKUlLfntZvbr+ZNpJ9tij8vJnn+ln4BAX69Zpcl3gT88siMaHKYh4ZOhQHeswPR2uuSbW0jROQlkQALvv7pv/5Zf6kScC7LabFhv24nUzBSqI4mINUAdiFkTjwxREPHPMMbDvvr6ooVF/BOtJ7SVBFQRoGTAv3qykYBZEsLRWsyAaH6Yg4p2//13dTUb9Eq4F4d8vIgHo2NE3H0pBFBdrxdhAfvvNyoc1NkxBxDtt2lQ/RrIRHULFIKCyn+bNN2HLlvqRKQKEoyBWrFBlAHra3vEntm2rt9FWjTjBFEQi0LOnppZAQgVFE5pAF1N6um/+zDN98+vXw6+/1otIkSAcBeFP796VDSZzMzUuTEEkAsOHa0bTiy/CySdXHc2suBjOOUfnRXS8Q2+KilE3+vf35YWecgpkZfm2tWwJubm+Ze/rdgJQWwUxaBCkpvqWly2LjlxGfBJVBeGcO8o5t9A5t8Q5d0OQ7Wc55+Z4pmnOuQy/bVc45+Y65wqcc/+MppxxT8uW8NBD8PvvMH48jB3r2/b115rplJEBl12mNRNeegkmTky4AGpc0bIl5Odrb7EJE6qOP92tm28+QRVEqCwmf66/vvIw6m+/HR25jPgkakOOOueSgMeBw4FCYKZzbqKI+PcAWwYMEZF1zrmjgaeBbOfcAOAi4ABgG/Cpc+4jEVkcLXnjHuf03wpw8MFwxRXqHJ43T/+127drHuKnn+pr3gMPaPmOhx/2uUt++UWtkOHDtfCcUT3dulVWBIHbvCSQgth9dy0BVlYG//ufGpuhFMQrr8A++8CwYfpzAiva19iIpgVxALBERJaKyDbgNeAE/wYiMk1EvIWHvwe8xuzewPcisllEyoDJwIlRlDWxOOIIuOMOLaAzZox2rktJ0Z5Qo0bBbbdB8+Y6fsGNN2oQtaICnnoK9ttP9/MvxvPcc/XbIW/KFF86zPr1WosqwcpWVFIQCWSptWqlPwEvX31VOQciK0sVwvPP+0It/jEIy5doXETNggC6Ayv8lguB7GraXwB84pmfC9zlnOsEbAGOAfKC7eScGwmMBOjWrRuTJk0CoFevXrRp04b8/HwAOnXqRP/+/ZkyZQoAycnJ5ObmMnv2bDZs2ABAVlYWq1evZsUKFbt3796kpKQw11NzoHPnzvTp04epU6cCkJKSQk5ODnl5eZR44gLZ2dkUFhay0hPN69u3L0lJSczzlM7o2rUr6enpTPe8irVo0YLs7GxmzJjBFk82TE5ODsuWLWPVqlUA9OvXj/LychYuXKgXtnt3UlNTmTFjBgCt8/LIyspi+vTplJaWApCbm8ui9u3Z3rkzux17LG07dWLroEH81LIlTYcNo/+YMbRs2ZLfi4tJ3rSJJjNmsJtzTD3jDMo8ymLw4MEUFBRQVFQEQEZGBhs3bmTp0qUApKWl0bFjR2bPng1Ahw4dyMjIYPKkSez54IMUHXQQA6+7jvz8fNatW0eHWbPYa+VKNrVoweaHHuLPjAx6rFyJnHcexVdeyS8jRiTMfepYVsZAz29w88SJ/DBsWM33qXXr4Pdp0SLWePw9AwYMoLS0lMWL1Vju0aMHXbp0IS9Pf/5t27YlMzOTqVOnUuYZFq629ykjYy9mzOgKwH33FdOv30Zgd8//ZgWjR/+PzMxMli8vZvny5ZSUJAEHA1BSUsakSVMT5j7V6f8UJ/dpx/9p8mREBOccQ4YM2fF/AsjMzKS4WO+T3r/aP/eGDh1KSEQkKhNwCvCM3/Jw4NEQbQ8B5gOd/NZdAMwGpgDjgAdr+s799ttPjBBs2CBSXu5b/uEHXedl5UqRN98UmT696r6zZoU+7rvvimzb5lv+6iuRK6/UY11zjW/9Z5+JPPaYyOrVvnVXXqnrRUQeekhk0aJanVJEKCys236bN4u0bCmitpfIBx9EVq4osmiRT+z27UX23tu3PGFC1fbbtvm2JyWJVFTUv8xGVAn5TI2mi6kQ6OG3nApUcdY65wYCzwAniEiRd72IPCsimSIyGCgGGm/8IRK0aaOuKC/776/rvHTrpkX/P/7Yt+6jj+C99zQILgKzZun6yZNh61Ydw+Lll+G113T9//6n/QLOOUfLmA8YoMuFhepWuuQS6NzZd/z//lfdZaCusaeeqv4ctmyBu++OXG+tmTPhtNPUvVVcXLsR4lq0gFNP9S2/805kZKoHevXyxdzXr4f583W+ZUv429+qtm/a1DdcaXl5NcOV/vEHfPJJiI1GWBQXw+mn63VcvRo8FkysiKaLaSbQ2zmXDqwETgfO9G/gnOsJvAMMF5FFAds6i8gaT5uTgJwoymqABr333FMD4BkZGqeYPVvjGCNHal+M//xHh9488khf2w8+0If7tGn6AO/eXY83YoTGO2bO1JFnqiMlRWtQjR2rD+20NH0SrV+vAxkUFamyAk35veyynT/fjz+Gxx5Tp3uvXvr0u+Ya2Hvv8PY//HDNKoOEcs4nJenwo4EDAJ1wgsYogtGypRavBQ1qV+omIgJz5sDTT6vi3H//yqVja2L+fHj/fb2G2dmqaAYN0heMpKRanVvUmDZNX4hGjNBswvbt9VwjRXm5vmR8+aVmLD7wADzzDJxxhv4+Y0TUFISIlDnnLgU+A5KA50SkwDk3yrN9HHAr0Al4wukrTZmIeBPO3/bEILYDl4gvmG1Ek3PO0R/l55/Duef6rI7DDoN331Vl8M47+icePFi3VVToEydwzGaAk06CVasqWyuhOO446NNHlcxNN+noNaWlevyWLeHHHzXl9L334IUXNBurSR2N4B9+0KfcvvvCkCGqwP78UxXgHXfo07Omh5z/A2LbtrrJEWl+/VWndu1UyYa47rvsUlVBHHxw6MMGKogdw2KsWwdXXQUDB8Kjj2ru7Pjx4ReZvO8+/e1cdJEqigcf1L4+33yjVmckXgR2FhH97R9+ONx6q16Itm31NxPY474urFkD116riuDJJ/U3fddd+nnjjTuvID78UCtE5+Xp/6e0VC33E06oed/q/E/eCeiMZhFdApyPZig1CWff+pwsBtFA+O03kYcfFpk6VZf9YydePvpIZMwYkf/8R6SgQNdt2aKxgeooK9PPG2/0zftz//0io0aJXH55zXJ++KHPOT9okMj27TXvE4pffqkcE6oLy5eLXHyxxnOeeELkH/8QKSoK2jQnxye6d/r009CH7tXL127xYhFZu1av38UX67w/Y8aILF1as7zLlonce2/ldf737957RS65RH8PseS993yxMi+vv67xt51lyxb9va1ZE3z700+L/Phj3Y+/davIUUeJXHSRXsvly/W+XX+9yPffa8ywumd/tRs1ePwZ6i56GrgTuB+YCBQAtwFtqztGfU6mIBoZ8+eL/PSTyHnnicycKXLWWSIvv1y5TWGhyKZNvgD4tdeKvP++yE03BT9mRYU+pJ57LvQT89tvRf75T5EHH/Q9NXv1EnnrrbqdR16eyNVX68P2P/+p3b4ffqjXYflykSuu0AeCl/XrRUaPFikt1eX8fJGbbxYpLpbjjyuvpBy6USiLZ64L+TUDBvja5ueLyAkniNxyi8i8eVUbb9miSqI6li1Teb2yhaK4WOSee6pvE00qKkSuuqrq+u3bRW69VT9rOodgvPeeXqf33hOZNi10u+3bRS67TOTVV2s+5s8/+37X//63vkS98or+vjZu1N+If9vDDhMZN06kmmdqTS6mY4CLRKRKsRnnXDJwHNoRzvpXGvXPXnvp55NPqs/28cfVf7t4sRYN+vhjdYXttpt+Xn21xlneeEPdZ8FwTl1H550H//oX9OsHPfxyLVat0jImt9+u8Qsv3btrp4LNm+Gss6p3fZWVaW/3uXPVRdGunbpaQN1bJSUakwnlvnjrLe3lvX49HHCAr6zKfffpfl7atdPOkqNGwXXXaULBkCFw++2c/EcfJjKaXVjLaJ6kOaWkPb8RBvxHj9u1q8afnnwSbrqJAypWsYQMttKCsuWFGoMaPTq4fM2bq1vQ21kz8Fr88ovep//8p2rNq0A6dNDrMHVq5fImFRWVj7tli36vc7Bxo+7TvLm6utLT4R//gFdf1fjS999ru/R0Tcyoju++C+57S05WV83jj2vp2yefDB4vWbVKr6U/8+bpcX/5ReefeCL09ycnwyOP6HkMG6bftXmzxmoee0z/A0uXqpuqfXuNC44Zo/d++nRt6+3Q4q26CBrfeeMNvb7VUZ32SLTJLAhDDj1U02nfeUffvrxum40b9U3Qa2KHk6u5bJn3DUvZskXkuut8bpvvvvO9Vh94oLpVvv22eivgo4/0GN9+q8uBcsyZo/JnZ/usgW3b9M3wp5/ULXDDDSKffOKTo6hIZQvF9u36Fu7nJnn/zNfkJu6QJxglbVkvmZki8vnnIscdp+61hQvVStq6VeSuu+S/vZ+QK3hQevCLLLj88ZpTkvPy1H3x8MNVt115Ze3euisqRM48U+TSS/XNd/58kZNOEhk/Xs/9559FzjhD7/nbb6tl8tRTajnecIPIs8+qdXb//SLDh+tb9VtvqeVZUlL9d197bXBXpIjej+ef1zTwe+6pei+nTNG39N9/1/u6bZvII4+IXHCB/h6zsz3mWBjMnav73X23WgePPaap1ZMn67Zff/W1XbxYr8uLL6plXTN1czFVaQwHAl8D3wEn1mbf+phMQRiycmVkj3fttfqgqajQB+YPP/i2zZzpUxCZmb71t92mD/Bp01QhePtaPPGEuiVq4o47RGbM0BjCzJnqJnrhBX3wXX993ftu+LF2rUhmy/myK6sF/MTatk3lfvTRSg/xo48WuYIH5V1OkPln3xn+F/33v3rwsWP1AX/nneqaqwslJbrvMceocv72W71GZ5+tcapbbtGHooj69UeN0tiOiC+O5a8QfvlF5L77gn/Xb7+pvOG4dkREJk1SZeHPddfpw/ucc/S8zz9f76fXdVnb2IJXUW3apL/FnYl5VSbkM9WJhC6x4JzrKiKr/JbfQIPUDpgmIvtUb5/UL1lZWeLtyWgYEeHrr7UvR79+aqKfd55v25w5mg4MarJ7R/4T0eyTNm0gJ0dTFwsL4cAD1d0TWPgvFO++CwsWaIZLcuQTDqdOVc9TixbqtarO2zBsmJb8akYpL09I5pTTa5F+Wl6uqaGtWql7Jzc3vKy2UPz6q5bAB02FnjZNXWf+bNqkLqiaUlFvvhnuvNO3fM01eq9Bjxk4kHd1XH21Zjrl5GifoFmz4MIL1dUW30MHh/xB1qQg3gNmAfeJyFbn3NNoyYsK4DwROSjCgu4UpiCMqFBerumW991XuaPAggW+PhN9+oCndAOgSsJfEXj/Z+EqhzhjxAit8+glLU0zoXv3jplIkeGBBzStdulS7Ytx+OEaN1iyBO69t/bHe+IJVU5Nm+pvJl76cVRP3RQEgHPub8AVwAtoMPpMoCUwQUTWVrdvfWMKwqhXli71vWGmpTXowRKeeUa7Kvhz1FENoOP0hg3aox80KSFBFfhOUncFATtKd/8DOBa4S0S+jZxskcMUhFGvFBb6Mpy6dWvQw61t3x484ai4uOZEGCPuCakgqu2G6pw73jk3FQ1Mz0XLZZzonJvgnKuFc84wGiD+T8x46UkdJZo21ezJQPxLdxkNj5rqFNwJHAmcDIwVkfUichVaIuOuaAtnGHFNI1IQAP/+t3ph/OPl995bv0OJGPVLTQriT9RqOB1Y410pIotF5PRoCmYYcU8jUxDNmqmS8FZ/Be3rt86qpDVYalIQJ6IB6TICKrEaRqOnkSkIL3vuqZOX33+PnSxGdKlJQWwVkUdFZJyIbAjWwDnXOth6w2jwJCX5sl4qKjQdtpHgregOpiAaMjUpiPedcw845wY753YkgDvnejnnLnDOfQbUUMzEMBoozjVaK2K33XzzN90UOzmM6FKtghCRQ4GvgIuBAufcn865IuBloCswQkTeir6YhhGnNFIFsWM8CHRojdoMxmckDuH03/8E+FlEVkRbGMNIOOqqIAoLtcduZmbdBz2KIf37V14uKIC//CU2shjRo8ZfpmhPuveiL4phJCB1URArV2ppjv3312FWy8qiIlo0OTMgZWXePO2U/OyzWpIjxkMpGxEi3FeX751z+0dVEsNIROqiIL7+WscvAPj2Wy3ml2B07KhDYnj56Scd+uHCC7Vu08iRMRPNiCDhKohDgOnOuf855+Y45352zs2JpmCGkRD4D9Dz22/h7bNmTeXliRMjJ089cuCBvvkPPtCKsF5efFH7SBiJTbgK4mhgD+CvwN/QkeT+Fi2hDCNh2N/PsPaOClcTgQoiQeuHDRniq9r966/qYvJn2DCYOdN6WicyYSkIEfkFaI8qhb8B7T3rDKNx4+9Lef99He60Jlavrry8YEFCPkWbNYOjjw69feFCHRH1+uvrTyYjsoSlIJxzVwCvAJ0908vOucuiKZhhJASDB1dO6Vm6tOZ9Ai2IjRsTthLssGE1t/EfRyLROf986NxZx4fy8uab+hNo0qR6Y/Dccyu74RKBcF1MFwDZInKriNyKDj16UQ37GEbjYOBA33zgwz8YwdpceSVccglMmhQxseqDk0/WYPWgQZqx+8MP8MUXcNVVvjarV6sObAicey58+mnldQMGwDvv6LtCLIlGMly4CsIB/nUEyqmmhrhhNCo6d/bNB7qPAikpgR9/rLr+rbd0NLK//lVdVQlCkyZwyy0we7aOsLn//nDYYTpQ2157+dotWRI7GSPJ4MGaweXP3ntD3761O87tt+u1GjBAvZQiOkppZqavzeLFsN9+Oj9rlsZ89tsPjjzSV95k6FAd3XbIEHj44TqfVkjCVRDPATOcc/92zv0b+B54NvLiGEYC0qWLb/6LL0K3++03jepWVIRuIwJ33BE52WKIf0G/665rOFZEJLj0Ug3gz52rGc8ffqiDE7ZrpynDAM8/rxbL9u06eulbb6miOP/8yuVN1q+HyZN1SOxIU6OCcM41AWYA5wHFwDp0POqHIi+OYSQg/hbE55/D2hAj8f7f/1Ve9lcs/ixaFBm5Yox/APvLL3X86rffjp088cQ330B2Nuyzj3aLKSjQ9RdeqIqhvBxef107JC5cqIrk8MNh333hzju1I76X006Lnpzh9KSuAB4Qkdki8oiIPCwiQWxkw2ikpKZWXg7mQoKqzutx4/SpCdCihW/9xo2weXPk5IsRI0fqA8/L6tVw+un65twYOO88faAfc0zl9Vu3wj/+oRbBzz/rWN9bt+q2k0/Wcb4//FDdSZ06qVHZv79aFj/9pPt8/rnveK1aETXCdTF97pw72bnGOaK3YVTLoYdWXi4q0s/t2+G55+C22zS7yf+1r1Mn+Nvf9B//wQf66R3fGmqOZSQAycnw9NPw0ks+v31Zmfa0DpbV++efcMMNuv2mm2Ds2MTubPf883pbA4dl9SqDXXbRkJR/ZlPz5hpjGD1aFQxofGPtWpg+XZe3b/dZHNEmnGJ9AFcBrYAy59xWNEAtItI2apIZRqKQnAyjRqlFAFBcrJ/PPKOvigBvvFG5p/XKlTqeRMuWcNxxuq5LF1jhqYm5ahWkp9eP/FHEOTj7bMjJgYwM2LRJR6S78Ua45ho9/ZISyM+HM86AP/6ovP9NN8HFF2uWVFISnHVW5eom9c0ZZ2ii2R9/qOF4222q/C67TB/ixx6rVsNnn4U+Rvv2ajXssw+kpVXuawl6ju+8A0ccocvNmqkSufxyVaJlZfDPf1YtmBgVRKTaCbUyDqqpXTxM++23nxhGTLjxRhF9MRa5/XZdd+KJvnX+U7t2wY9x3HG+Nu+8U2+i1xcnnxz8ctRmysgQWbw41mcSXe67T+Tmm+v1K0M+U2u0IESkwjl3P5ATbWVlGAmLf+6j14II5QfwD2r7062bb37ZssjIFUecfnr4QerhwzVIG1j/MD9fwzbDh2s67ddf66XatEkvX48e0Lat+uVbttSBjXJyfJd20yYNALdvr8deu1bfyJs21fXt2um0dauGheq7EvuJJ2q669df1+/3hiJcF9PnzrmTgXdEErAmgGFEm0AFsXVr6OR//wJ//vh3z736ao3ytm44I/oOGwavvgr33gtz/Ep9tmmjqZ4ZGVouPCND199zD/z3v+ptmzYNli/37fPSSzr5M2tWZOVt0kRva6dOOrVqpS6e0lJVJt5RZkN9iqhbzDs1aVJ52Ts5p/t4JxHtb+FvOyUn6+eWLdreOY1FlJXpp3e+adPKis3b1jvv/dy+Xc+jtLT69OPaxCBaAuUWgzCMIPgriBdf1Id9qP4OoayDQYMqLz//vDq3GxBnnKHT7NlqYB11FOy6qz78AlNgunfXDnde3ngjuimdgVRUaKwhMC4S76xfH7ljhasg2gFnAekicrtzriewWw37GEbjoXv3ysvXXeeb/8tf9BXYS9euwY8RqCDy8yMjWxySmVm513A4+ZGnnqrF/x58UI207ds1yHvIIepWKizU2P+mTb5p3jytj1RSokqodWt9u16/Xt/Kd91VDbrt23X9n3/q1Ly5L9uoMROugngcqEDLfd8ObATeBmwQIcMAfdoNGhS8D8TgwZqzefDBunzPPcGP0aoV3HWXr5vs/PnRkTWBSUuLTEmJ8nJVCMEUU0WFbtu+XRVRUZFaEZs2aeyiZUufu6hJk8rz/uuc0+/xdzsFm7yuKOcq7+tdBnUfOaeKC3Sfpk19U3KyTtu3axcabyDA303lv9y0qSrGUN5OLy6ckIJzbraIZDrnfhSRQZ51+SKSUcN+RwEPA0nAMyJyb8D2swBvMeASYLSI5Hu2tQeeAQYAApwvItOr+76srCzJS9Da+kYD4NdfYffdq65/8011wM+apU7kgw4K/cpcWOjrD9GunT6hEnDMaiOhCGm/hfvL2+6cS0If1DjndkUtitDfqO0fRwcb6gec4ZzrF9BsGTBERAYCdwBP+217GPhURPYCMgB7nTLim549tZypP7vtph3iQLvG5uZW70/p3l0joqC+jnDGlzCMKBGugngEeBfo7Jy7C5gK3F3DPgcAS0RkqYhsA14DTvBvICLTRGSdZ/F7IBXAOdcWGIynIKCIbBOR9WHKahixIytLO8c1b65lPidOrNmO98e5ymN5Tq/WaDaMqBJWDEJEXnHOzQIORc2Rv4tITW/03YEVfsuFQHY17S8APvHM9wLWAs875zKAWcAVIrIpcCfn3EhgJEC3bt2Y5Kmn36tXL9q0aUO+J9DXqVMn+vfvz5QpUwBITk4mNzeX2bNns8EzVmJWVharV69mhac3a+/evUlJSWGup79/586d6dOnD1OnTgUgJSWFnJwc8vLyKCkpASA7O5vCwkJWegaA6du3L0lJScybNw+Arl27kp6eznTPH79FixZkZ2czY8YMtngGss/JyWHZsmWsWrUKgH79+lFeXs7ChQv1wnbvTmpqKjNmzACgdevWZGVlMX36dEpLSwHIzc1l0aJFrPGMPTBgwABKS0tZ7Hkj7dGjB126dMHrkmvbti2ZmZlMnTqVMk9h+cGDB1NQUECRp3RERkYGGzduZKlnUJy0tDQ6duzI7NmzAejQoQMZGRlMnjwZEcE5x5AhQ8jPz2fdOn0PyMzMpLi4mOWenMUGeZ9OOQVOOcV3nzy/yXDvU7M998SbHlg8axbNhg2z+2T/p6jdp6FDhxKKsGIQdcE5dwpwpIhc6FkeDhwgIlXy9pxzhwBPALkiUuScy0ItioNEZIZz7mFgg4jcUt13WgzCaBA89pgvvXXUKHjyydjKYzR0djoGURcKAb/qY6QCvwU2cs4NRIPRJ4hIkd++hSIyw7P8FpAZuK9hNEh23dU3H84IdYYRJaKpIGYCvZ1z6c65ZsDpwET/Bp7+FO8Aw0VkRxF8EVkFrHDOecdpOhSYF0VZDSN+8C/FEWpsCcOoB8LtB1FrRKTMOXcp8Bma5vqciBQ450Z5to8DbgU6AU94KomXiUiW5xCXAa94lMtSdMAiw2j4mAVhxAlRi0HEAotBGA2C1asr97Y+/ngddPiSS4JnRIlomfCOHRtU7Saj3ohJDMIwjLrQqZN21/UycaIW7xsyRDva+bN2rabW7r671pvYZx8tCTp1avBReQyjFpiCMIx4IzlZy5gGWgszZqgymDdPLYbcXI1XeNIiEdEh2N57T8t6HHts9aU6DaMGzMVkGPHKxo06ZuXgwXU/Rk6ODnLcrl3ExDIaHOZiMoyEo00btQTuu6/6dl27arsxY7Tc6S67+LZNn67Lffro+Nh5eToIgGGEgVkQhpEIbNsGkyfD7bdrfAG0nMcrr8BJJ1Vt/+ijOohxMDp10jhFSoqv9vWPP+oY2Mcdp8Ov/fKLlhAtL9fv7tNHy5a3auX77qZNo3KqRr0T0oIwBWEYiYQIjBunlWEvvRT23Td02xdfhCuv9A2BGkmaNVPLpX17LUjYpYsqkvnzVeE0b65B87ZtNabiHSqtWzdt36KFtqlLpVrnKtfX9tbGDjV8Wm3m/eti15X6fqaG+r7A6+JfR9x/3WmnmYIwjEZJRYWO43njjfowsH4VRiAipiAMw0BLiH/9tY47IeIbzaZXL7VKvvxSU2n33lszpJKTdaScKVNUuWzbpiPShBpO1Ug8TEEYhhExRNRttWGDDre2apV27ktKgj331DEtSktVGW3Y4Bu+raJCx7coKVEltHVr3dwxFRWVh2gLNmya97O288HcVIG8+abGX7wuGu94H/68/DIMH177c6srgbL6XxP/yevq859ef90UhGEYRkRIS9NsMP9ssUBat1ZFGA28D/bIjTRoaa6GYRj1TkkJHHqojlm+zz7w/vu6/pZbKg+ufdNN8MgjOn/ffbD//jBwIPzrX7pu+XJ1+/3jH3qsFSuoD8yCMAzDqA3p6dChg7p1Lr4YRo6s2sZrQZSVacymbVv44w8dLXDxYk0jPukk7QVfUQG9e+twtbNmwVtvwVNPqZVw/PFw3XU6nG2vXjBtWuURByNDSAsiatVcDcMwGiTffafpumvWwOGHw157he7tLqIZZFOmqEto5UqN16SlaX+UH3/U5UGDdPnzz3UaNEj3LylRhdKzp9bbirxyqBZTEIZhGLWhWzf97NxZOxxOnuzrlDhqlE5eXnlFCyrOmqWB7bQ0Dc4DXHghjB+vQf7zz9d1Itoj/uKLK3/n8uW+Tor1iMUgDMMwwmXTJl8BxE2b9G1///21ZtZPP1VWDqCZXJ07q3L45ht1LXk58UT49FOYOROOPFLXHXmklkTxBrhXroxp3xWzIAzDMMJl9Wp9sIPGF848E446KnT7s87SNNisLO31vtdevm3NmsEhh2hv9KQkXXfEEdobPSdHl1u31pRZ7/Z6xoLUhmEYsaCiQjOS3nxTg9Sxw9JcDcMw4oZ587RT4aGHxlo5VIu5mAzDMOqbfv1g6dJYS1EjZkEYhmEYQTEFYRiGYQTFFIRhGIYRFFMQhmEYRlBMQRiGYRhBMQVhGIZhBMUUhGEYhhEUUxCGYRhGUExBGIZhGEExBWEYhmEExRSEYRiGERRTEIZhGEZQTEEYhmEYQTEFYRiGYQTFFIRhGIYRlKgqCOfcUc65hc65Jc65G4JsP8s5N8czTXPOZXjWN3fO/eCcy3fOFTjnboumnIZhGEZVojZgkHMuCXgcOBwoBGY65yaKyDy/ZsuAISKyzjl3NPA0kA2UAn8VkRLnXFNgqnPuExH5PlryGoZhGJWJpgVxALBERJaKyDbgNeAE/wYiMk1E1nkWvwdSPetFREo865t6poYzeLZhGEYCEM0hR7sDK/yWC1HrIBQXAJ94FzwWyCxgT+BxEZkRbCfn3EhgJEC3bt2YNGkSAL169aJNmzbk5+cD0KlTJ/r378+UKVMASE5OJjc3l9mzZ7NhwwYAsrKyWL16NStWqNi9e/cmJSWFuXPnAtC5c2f69OnD1KlTAUhJSSEnJ4e8vDxKSlSfZWdnU1hYyMqVKwHo27cvSUlJzJunhlPXrl1JT09n+vTpALRo0YLs7GxmzJjBli1bAMjJyWHZsmWsWrUKgH79+lFeXs7ChQv1wnbvTmpqKjNm6CVp3bo1WVlZTJ8+ndLSUgByc3NZtGgRa9asAWDAgAGUlpayePFiAHr06EGXLl3Iy8sDoG3btmRmZjJ16lTKysoAGDx4MAUFBRQVFQGQkZHBxo0bWeoZKjEtLY2OHTsye/ZsADp06EBGRgaTJ09GRHDOMWTIEPLz81m3Tt8DMjMzKS4uZvny5Xaf7D7ZfYqD+zR06FBC4USi82LunDsFOFJELvQsDwcOEJHLgrQ9BHgCyBWRooBt7YF3gctEZG5135mVlSXeG2QYhmGEhQu1IZoupkKgh99yKvBbYCPn3EDgGeCEQOUAICLrgUnAUVGR0jAMwwhKNBXETKC3cy7dOdcMOB2Y6N/AOdcTeAcYLiKL/Nbv6rEccM61AA4DFkRRVsMwDCOAqMUgRKTMOXcp8BmQBDwnIgXOuVGe7eOAW4FOwBPOOYAyEckCdgNe8MQhmgBviMiH0ZLVMAzDqErUYhCxwGIQhmEYtSZkDCKaWUxxwfbt2yksLGTr1q2xFiUuad68OampqTRt2jTWohiGEWc0eAVRWFhImzZtSEtLw+PGMjyICEVFRRQWFpKenh5rcQzDiDMafC2mrVu30qlTJ1MOQXDO0alTJ7OuDMMISoNXEIAph2qwa2MYRigahYIwDMMwao8piBgxdOhQasq4uvDCC3eUFAjFlClTyMzMJDk5mbfeeqvStqOOOor27dtz3HHH7bS8hmE0PkxBxDHPPPMM/fr1q7ZNz549GT9+PGeeeWaVbddeey0vvfRStMQzDKOB06gUhHPRm0KxfPly9tprL0aMGMHAgQMZNmwYmzdvrtRm9OjRZGVl0b9/f/71r3/tWO9vZbRu3ZqbbrqJjIwMDjzwQFavXg1oga+BAwfSpEnVW3nooYfSpk2bCFw5wzAaI41KQcSKhQsXMnLkSObMmUPbtm154oknKm2/6667yMvLY86cOUyePJk5c+ZUOcamTZs48MADyc/PZ/Dgwfzf//1ffYlvGEYjxRREPdCjRw8OOuggAM4+++wd5Y29vPHGG2RmZjJo0CAKCgqCxh2aNWu2I5aw33777SjvaxiGES0afEc5f2JVVSQwldR/edmyZdx///3MnDmTDh06cO655wbtl9C0adMd+yUlJe2oMW8YhhEtzIKoB3799dcdA5pMmDCB3NzcHds2bNhAq1ataNeuHatXr+aTTz4JdRjDMIx6xRREPbD33nvzwgsvMHDgQIqLixk9evSObRkZGQwaNIj+/ftz/vnn73BFhcvMmTNJTU3lzTff5OKLL6Z///47th188MGccsopfPXVV6SmpvLZZ59F7JwMw2j4NPhqrvPnz2fvvfeOkUSaxXTcccftGGYxHon1NTIMI6bEZEQ5wzAMI4ExBRFl0tLS4tp6MAzDCIUpCMMwDCMopiAMwzCMoJiCMAzDMIJiCsIwDMMIiimIGBGpct/jx49n1113Zd9992XfffflmWeeiaSYhmE0YhpVqY1EI9yH/WmnncZjjz0WZWkMw2hsNC4LIgb1vqNd7tswDCNaNC4FESOiXe777bff3qF8VqxYEfXzMQyjcWAKoh6IZrnvv/3tbyxfvpw5c+Zw2GGHMWLEiOiejGEYjYbGpSBEojdVQzjlvr/66ivmzJnDscceW6ty3506dSIlJQWAiy66iFmzZu3UJTIMw/DSuBREjIhmue/ff/99x/zEiROt6J5hGBHDspjqAW+574svvpjevXszevRoPvjgA6Byue9evXrVutz3I488wsSJE0lOTqZjx46MHz8+CmdgGEZjxMp9Rxkr920YRpxj5b4NwzCM2mEKIspYuW/DMBKVRqEgGpIbLdLYtTEMIxQNXkE0b96coqIiexAGQUQoKiqiefPmsRbFMIw4pMFnMaWmplJYWMjatWtjLUpc0rx5c1JTU2MthmEYcUiDVxBNmzYlPT091mIYhmEkHFF1MTnnjnLOLXTOLXHO3RBk+1nOuTmeaZpzLiPcfQ3DMIzoEjUF4ZxLAh4Hjgb6AWc45/oFNFsGDBGRgcAdwNO12NcwDMOIItG0IA4AlojIUhHZBrwGnODfQESmicg6z+L3QGq4+xqGYRjRJZoxiO6Af+3pQiC7mvYXAN5CRGHv65wbCYz0LJY65xpSp4NdgD9iLUQEsfOJb+x84ptonc+nInJUsA3RVBDBum8HzTV1zh2CKghvFbuw9xWRp/G5pvJEJKv2osYndj7xjZ1PfGPns/NEU0EUAj38llOB3wIbOecGAs8AR4tIUW32NQzDMKJHNGMQM4Hezrl051wz4HRgon8D51xP4B1guIgsqs2+hmEYRnSJmgUhImXOuUuBz4Ak4DkRKXDOjfJsHwfcCnQCnvAMhlMmIlmh9g3ja5+OxrnEEDuf+MbOJ76x89lJGlS5b8MwDCNyNPhaTIZhGEbdMAVhGIZhBKVBKIhELMvhnHvOObfGv9+Gc66jc+4L59xiz2cHv21jPOe30Dl3ZGykDo1zrodz7hvn3HznXIFz7grP+oQ8J+dcc+fcD865fM/53OZZn5DnA1qhwDn3o3PuQ89ywp4LgHNuuXPuZ+fcT865PM+6hD0n51x759xbzrkFnv9RTszPR0QSekKD2P8DegHNgHygX6zlCkPuwUAmMNdv3X+AGzzzNwBjPfP9POeVAqR7zjcp1ucQcD67AZme+TbAIo/cCXlOaF+c1p75psAM4MBEPR+PjFcBrwIfJvrvzSPncmCXgHUJe07AC8CFnvlmQPtYn09DsCASsiyHiEwBigNWn4D+SPB8/t1v/WsiUioiy4Al6HnHDSLyu4jM9sxvBOajPeIT8pxEKfEsNvVMQoKej3MuFTgW7XPkJSHPpQYS8pycc23Rl8ZnAURkm4isJ8bn0xAURLCyHN1jJMvO0kVEfgd94AKdPesT6hydc2nAIPStO2HPyeOS+QlYA3whIol8Pg8B1wEVfusS9Vy8CPC5c26Wp+QOJO459QLWAs973IDPOOdaEePzaQgKIuyyHAlMwpyjc6418DbwTxHZUF3TIOvi6pxEpFxE9kV78h/gnBtQTfO4PR/n3HHAGhGZFe4uQdbFxbkEcJCIZKJVny9xzg2upm28n1My6nJ+UkQGAZtQl1Io6uV8GoKCaEhlOVY753YD8Hyu8axPiHN0zjVFlcMrIvKOZ3VCnxOAx9SfBBxFYp7PQcDxzrnlqAv2r865l0nMc9mBiPzm+VwDvIu6WBL1nAqBQo+VCvAWqjBiej4NQUE0pLIcE4ERnvkRwPt+6093zqU459KB3sAPMZAvJE67wj8LzBeR//ptSshzcs7t6pxr75lvARwGLCABz0dExohIqoikof+Pr0XkbBLwXLw451o559p454EjgLkk6DmJyCpghXOur2fVocA8Yn0+sY7cRyj6fwyaNfM/4KZYyxOmzBOA34Ht6NvABWjZka+AxZ7Pjn7tb/Kc30K0sGHMzyHgfHJRE3cO8JNnOiZRzwkYCPzoOZ+5wK2e9Ql5Pn4yDsWXxZSw54L67PM9U4H3f5/g57QvkOf5zb0HdIj1+VipDcMwDCMoDcHFZBiGYUQBUxCGYRhGUExBGIZhGEExBWEYhmEExRSEYRiGERRTEIYRAZxz0zyfac65M2Mtj2FEAlMQhhEBROQvntk0oFYKwjmXFHGBDCMCmIIwjAjgnPNWfr0XONgzRsGVnoJ/9znnZjrn5jjnLva0H+p0/IxXgZ9jJrhhVENyrAUwjAbGDcA1InIcgKfK6J8isr9zLgX4zjn3uaftAcAA0XLNhhF3mIIwjOhyBDDQOTfMs9wOrZuzDfjBlIMRz5iCMIzo4oDLROSzSiudG4qWdDaMuMViEIYRWTaiQ656+QwY7SmFjnOuj6f6qGHEPWZBGEZkmQOUOefygfHAw2hm02xPSfS1+IaNNIy4xqq5GoZhGEExF5NhGIYRFFMQhmEYRlBMQRiGYRhBMQVhGIZhBMUUhGEYhhEUUxCGYRhGUExBGIZhGEH5f3clUCTn/ErjAAAAAElFTkSuQmCC", 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\n" }, "metadata": { "needs_background": "light" @@ -3629,7 +3630,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 9, "metadata": { "pycharm": { "name": "#%%\n" @@ -3642,7 +3643,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 10, "metadata": { "pycharm": { "name": "#%%\n" @@ -3655,7 +3656,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 11, "metadata": { "pycharm": { "name": "#%%\n" @@ -3667,11 +3668,11 @@ "output_type": "stream", "text": [ "Epoch 1/1024\n", - "90/90 [==============================] - 1s 3ms/step - loss: 0.0219 - val_loss: 0.0283 - lr: 0.0025\n", + "90/90 [==============================] - 2s 6ms/step - loss: 0.0219 - val_loss: 0.0283 - lr: 0.0025\n", "Epoch 2/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0270 - lr: 0.0025\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0270 - lr: 0.0025\n", "Epoch 3/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0267 - lr: 0.0025\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0137 - val_loss: 0.0267 - lr: 0.0025\n", "Epoch 4/1024\n", "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0280 - lr: 0.0025\n", "Epoch 5/1024\n", @@ -3679,963 +3680,2269 @@ "Epoch 6/1024\n", "90/90 [==============================] - 0s 2ms/step - loss: 0.0059 - val_loss: 0.1138 - lr: 0.0025\n", "Epoch 7/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0048 - val_loss: 0.1172 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0048 - val_loss: 0.1172 - lr: 0.0025\n", "Epoch 8/1024\n", "90/90 [==============================] - 0s 2ms/step - loss: 0.0047 - val_loss: 0.0186 - lr: 0.0025\n", "Epoch 9/1024\n", - "90/90 [==============================] - 0s 2ms/step - loss: 0.0046 - val_loss: 0.2067 - lr: 0.0025\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0046 - val_loss: 0.2067 - lr: 0.0025\n", "Epoch 10/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0044 - val_loss: 0.2280 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0044 - val_loss: 0.2280 - lr: 0.0025\n", "Epoch 11/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0044 - val_loss: 0.2274 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0044 - val_loss: 0.2274 - lr: 0.0025\n", "Epoch 12/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0043 - val_loss: 0.3251 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0043 - val_loss: 0.3251 - lr: 0.0025\n", "Epoch 13/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0043 - val_loss: 0.2281 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0043 - val_loss: 0.2281 - lr: 0.0025\n", "Epoch 14/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0043 - val_loss: 0.1210 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0043 - val_loss: 0.1210 - lr: 0.0025\n", "Epoch 15/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0041 - val_loss: 0.0582 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0041 - val_loss: 0.0582 - lr: 0.0025\n", "Epoch 16/1024\n", "90/90 [==============================] - 0s 2ms/step - loss: 0.0043 - val_loss: 0.2277 - lr: 0.0025\n", "Epoch 17/1024\n", "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.2268 - lr: 0.0025\n", "Epoch 18/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0044 - val_loss: 0.2283 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0044 - val_loss: 0.2283 - lr: 0.0025\n", "Epoch 19/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0040 - val_loss: 0.3142 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.3142 - lr: 0.0025\n", "Epoch 20/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0039 - val_loss: 0.0752 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0039 - val_loss: 0.0752 - lr: 0.0025\n", "Epoch 21/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0038 - val_loss: 0.0617 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0038 - val_loss: 0.0617 - lr: 0.0025\n", "Epoch 22/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0040 - val_loss: 0.0920 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.0920 - lr: 0.0025\n", "Epoch 23/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0040 - val_loss: 0.3005 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.3005 - lr: 0.0025\n", "Epoch 24/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0038 - val_loss: 0.2490 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0038 - val_loss: 0.2490 - lr: 0.0025\n", "Epoch 25/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0038 - val_loss: 0.0489 - lr: 0.0025\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0038 - val_loss: 0.0489 - lr: 0.0025\n", "Epoch 26/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0039 - val_loss: 0.2725 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0039 - val_loss: 0.2725 - lr: 0.0025\n", "Epoch 27/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0038 - val_loss: 0.2280 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0038 - val_loss: 0.2280 - lr: 0.0025\n", "Epoch 28/1024\n", "90/90 [==============================] - 0s 2ms/step - loss: 0.0038 - val_loss: 0.3246 - lr: 0.0025\n", "Epoch 29/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0040 - val_loss: 0.2171 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.2171 - lr: 0.0025\n", "Epoch 30/1024\n", "90/90 [==============================] - 0s 2ms/step - loss: 0.0037 - val_loss: 0.3298 - lr: 0.0025\n", "Epoch 31/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0042 - val_loss: 0.2163 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0042 - val_loss: 0.2163 - lr: 0.0025\n", "Epoch 32/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0038 - val_loss: 0.2283 - lr: 0.0025\n", + "90/90 [==============================] - 0s 2ms/step - 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0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 594/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 595/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 596/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 597/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 598/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 599/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 600/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 601/1024\n", 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0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 609/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 610/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 611/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 612/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 613/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 614/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 615/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 616/1024\n", 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0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 624/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 625/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 626/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 627/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 628/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 629/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 630/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 631/1024\n", 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0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 639/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 640/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 641/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 642/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 643/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 644/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 645/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 646/1024\n", 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val_loss: 0.2216 - lr: 3.1250e-04\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0030 - val_loss: 0.0257 - lr: 3.1250e-04\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.1788 - lr: 3.1250e-04\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0308 - lr: 3.1250e-04\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0030 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.2607 - lr: 3.1250e-04\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.2670 - lr: 3.1250e-04\n", + "Epoch 115/1024\n", + "90/90 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val_loss: 0.1282 - lr: 1.5625e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.1617 - lr: 1.5625e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1587 - lr: 1.5625e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0652 - lr: 1.5625e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1194 - lr: 1.5625e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0069 - lr: 1.5625e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0030 - val_loss: 0.2232 - lr: 1.5625e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0199 - lr: 1.5625e-04\n", + "Epoch 145/1024\n", + "90/90 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val_loss: 0.0945 - lr: 7.8125e-05\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0241 - lr: 7.8125e-05\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0289 - lr: 7.8125e-05\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0380 - lr: 7.8125e-05\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0557 - lr: 7.8125e-05\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0217 - lr: 7.8125e-05\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0129 - lr: 7.8125e-05\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0220 - lr: 7.8125e-05\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0950 - lr: 7.8125e-05\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0053 - lr: 7.8125e-05\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0113 - lr: 7.8125e-05\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0521 - lr: 7.8125e-05\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0489 - lr: 7.8125e-05\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0030 - val_loss: 0.0217 - lr: 7.8125e-05\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0189 - lr: 7.8125e-05\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.1240 - lr: 7.8125e-05\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0183 - lr: 7.8125e-05\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1380 - lr: 7.8125e-05\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0104 - lr: 7.8125e-05\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0049 - lr: 7.8125e-05\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0705 - lr: 7.8125e-05\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0130 - lr: 7.8125e-05\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0066 - lr: 7.8125e-05\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1058 - lr: 7.8125e-05\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0491 - lr: 7.8125e-05\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0252 - lr: 7.8125e-05\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0052 - lr: 7.8125e-05\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0645 - lr: 7.8125e-05\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0465 - lr: 7.8125e-05\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0429 - lr: 7.8125e-05\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0272 - lr: 7.8125e-05\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0577 - lr: 7.8125e-05\n", + "Epoch 191/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0040 - lr: 7.8125e-05\n", + "Epoch 192/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0437 - lr: 7.8125e-05\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 7.8125e-05\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0055 - lr: 7.8125e-05\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0131 - lr: 7.8125e-05\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0290 - lr: 7.8125e-05\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0913 - lr: 7.8125e-05\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0460 - lr: 7.8125e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1060 - lr: 7.8125e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0051 - lr: 7.8125e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0334 - lr: 7.8125e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0753 - lr: 7.8125e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0238 - lr: 7.8125e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0136 - lr: 7.8125e-05\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.2139 - lr: 7.8125e-05\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.1455 - lr: 7.8125e-05\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0175 - lr: 7.8125e-05\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0451 - lr: 7.8125e-05\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1155 - lr: 7.8125e-05\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1050 - lr: 7.8125e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0601 - lr: 7.8125e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0444 - lr: 7.8125e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.1996 - lr: 7.8125e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0211 - lr: 7.8125e-05\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0245 - lr: 7.8125e-05\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0044 - lr: 3.9062e-05\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0474 - lr: 3.9062e-05\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0457 - lr: 3.9062e-05\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0045 - lr: 3.9062e-05\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0230 - lr: 3.9062e-05\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0180 - lr: 3.9062e-05\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0337 - lr: 3.9062e-05\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0289 - lr: 3.9062e-05\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 3.9062e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0044 - lr: 3.9062e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0188 - lr: 3.9062e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0352 - lr: 3.9062e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0164 - lr: 3.9062e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0092 - lr: 3.9062e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0099 - lr: 3.9062e-05\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0117 - lr: 3.9062e-05\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0290 - lr: 3.9062e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0302 - lr: 3.9062e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0401 - lr: 3.9062e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.1169 - lr: 3.9062e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0076 - lr: 3.9062e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0303 - lr: 3.9062e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0102 - lr: 3.9062e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0545 - lr: 3.9062e-05\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 3.9062e-05\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0135 - lr: 3.9062e-05\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0045 - lr: 3.9062e-05\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0153 - lr: 3.9062e-05\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0092 - lr: 3.9062e-05\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0083 - lr: 3.9062e-05\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0221 - lr: 3.9062e-05\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 3.9062e-05\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0411 - lr: 3.9062e-05\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0529 - lr: 3.9062e-05\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0063 - lr: 3.9062e-05\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 3.9062e-05\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0308 - lr: 3.9062e-05\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0085 - lr: 3.9062e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0068 - lr: 3.9062e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0074 - lr: 3.9062e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0079 - lr: 3.9062e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0109 - lr: 3.9062e-05\n", + "Epoch 265/1024\n", + "90/90 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val_loss: 0.0146 - lr: 3.9062e-05\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0307 - lr: 3.9062e-05\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0197 - lr: 3.9062e-05\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0057 - lr: 3.9062e-05\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0204 - lr: 3.9062e-05\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0130 - lr: 3.9062e-05\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0049 - lr: 3.9062e-05\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 280/1024\n", + "90/90 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val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0045 - lr: 1.9531e-05\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 1.9531e-05\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0048 - lr: 1.9531e-05\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0063 - lr: 1.9531e-05\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 295/1024\n", + "90/90 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val_loss: 0.0133 - lr: 1.9531e-05\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0037 - lr: 1.9531e-05\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0066 - lr: 1.9531e-05\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0033 - lr: 1.9531e-05\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0067 - lr: 1.9531e-05\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0045 - lr: 1.9531e-05\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 312/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0043 - lr: 1.9531e-05\n", + "Epoch 313/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 314/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0108 - lr: 1.9531e-05\n", + "Epoch 315/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.9531e-05\n", + "Epoch 316/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 1.9531e-05\n", + "Epoch 317/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 318/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0052 - lr: 1.9531e-05\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0112 - lr: 1.9531e-05\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0205 - lr: 1.9531e-05\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0102 - lr: 1.9531e-05\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 324/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0063 - lr: 1.9531e-05\n", + "Epoch 326/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0166 - lr: 1.9531e-05\n", + "Epoch 327/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0035 - lr: 1.9531e-05\n", + "Epoch 328/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0055 - lr: 1.9531e-05\n", + "Epoch 329/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0091 - lr: 1.9531e-05\n", + "Epoch 330/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0143 - lr: 1.9531e-05\n", + "Epoch 331/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0056 - lr: 1.9531e-05\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0045 - lr: 1.9531e-05\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0048 - lr: 1.9531e-05\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0057 - lr: 1.9531e-05\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0142 - lr: 1.9531e-05\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0052 - lr: 1.9531e-05\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0054 - lr: 1.9531e-05\n", + "Epoch 339/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 340/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0034 - lr: 1.9531e-05\n", + "Epoch 341/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 342/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 343/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0063 - lr: 9.7656e-06\n", + "Epoch 344/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 345/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 346/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0050 - lr: 9.7656e-06\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0051 - lr: 9.7656e-06\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 354/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0040 - lr: 9.7656e-06\n", + "Epoch 355/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 356/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 357/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 358/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0048 - lr: 9.7656e-06\n", + "Epoch 359/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0062 - lr: 9.7656e-06\n", + "Epoch 360/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 361/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0054 - lr: 9.7656e-06\n", + "Epoch 362/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 363/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 364/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 365/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 366/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 4.8828e-06\n", + "Epoch 367/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 368/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0035 - lr: 4.8828e-06\n", + "Epoch 369/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 370/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 371/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 372/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 373/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 4.8828e-06\n", + "Epoch 374/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 375/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 4.8828e-06\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0041 - lr: 4.8828e-06\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0033 - lr: 4.8828e-06\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 385/1024\n", + "90/90 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0.0025\n", - "Epoch 26/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0039 - val_loss: 0.1589 - lr: 0.0025\n", - "Epoch 27/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0037 - val_loss: 0.0401 - lr: 0.0025\n", - "Epoch 28/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0037 - val_loss: 0.0640 - lr: 0.0025\n", - "Epoch 29/1024\n", - "90/90 [==============================] - 0s 862us/step - loss: 0.0038 - val_loss: 0.3123 - lr: 0.0025\n", - "Epoch 30/1024\n", - "90/90 [==============================] - 0s 865us/step - loss: 0.0037 - val_loss: 0.1451 - lr: 0.0025\n", - "Epoch 31/1024\n", - "90/90 [==============================] - 0s 903us/step - loss: 0.0041 - val_loss: 0.2279 - lr: 0.0025\n", - "Epoch 32/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0036 - val_loss: 0.0576 - lr: 0.0012\n", - "Epoch 33/1024\n", - "90/90 [==============================] - 0s 1ms/step - 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6.2500e-04\n", - "Epoch 79/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0032 - val_loss: 0.0431 - lr: 6.2500e-04\n", - "Epoch 80/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0031 - val_loss: 0.0944 - lr: 6.2500e-04\n", - "Epoch 81/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0031 - val_loss: 0.1827 - lr: 6.2500e-04\n", - "Epoch 82/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0031 - val_loss: 0.1524 - lr: 6.2500e-04\n", - "Epoch 83/1024\n", - "90/90 [==============================] - 0s 864us/step - loss: 0.0030 - val_loss: 0.0833 - lr: 6.2500e-04\n", - "Epoch 84/1024\n", - "90/90 [==============================] - 0s 858us/step - loss: 0.0031 - val_loss: 0.0131 - lr: 3.1250e-04\n", - "Epoch 85/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0030 - val_loss: 0.0984 - lr: 3.1250e-04\n", - "Epoch 86/1024\n", - "90/90 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7.8125e-05\n", - "Epoch 153/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0028 - val_loss: 0.0241 - lr: 7.8125e-05\n", - "Epoch 154/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0028 - val_loss: 0.0100 - lr: 7.8125e-05\n", - "Epoch 155/1024\n", - "90/90 [==============================] - 0s 916us/step - loss: 0.0028 - val_loss: 0.0289 - lr: 7.8125e-05\n", - "Epoch 156/1024\n", - "90/90 [==============================] - 0s 864us/step - loss: 0.0029 - val_loss: 0.0380 - lr: 7.8125e-05\n", - "Epoch 157/1024\n", - "90/90 [==============================] - 0s 860us/step - loss: 0.0029 - val_loss: 0.0557 - lr: 7.8125e-05\n", - "Epoch 158/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0029 - val_loss: 0.0217 - lr: 7.8125e-05\n", - "Epoch 159/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0129 - lr: 7.8125e-05\n", - "Epoch 160/1024\n", - "90/90 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0.0028 - val_loss: 0.0489 - lr: 7.8125e-05\n", - "Epoch 168/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0030 - val_loss: 0.0217 - lr: 7.8125e-05\n", - "Epoch 169/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0157 - lr: 7.8125e-05\n", - "Epoch 170/1024\n", - "90/90 [==============================] - 0s 862us/step - loss: 0.0028 - val_loss: 0.0189 - lr: 7.8125e-05\n", - "Epoch 171/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0028 - val_loss: 0.0087 - lr: 7.8125e-05\n", - "Epoch 172/1024\n", - "90/90 [==============================] - 0s 864us/step - loss: 0.0029 - val_loss: 0.1240 - lr: 7.8125e-05\n", - "Epoch 173/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0183 - lr: 7.8125e-05\n", - "Epoch 174/1024\n", - "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.1380 - lr: 7.8125e-05\n", - "Epoch 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0s 869us/step - loss: 0.0029 - val_loss: 0.0491 - lr: 7.8125e-05\n", - "Epoch 183/1024\n", - "90/90 [==============================] - 0s 876us/step - loss: 0.0029 - val_loss: 0.0252 - lr: 7.8125e-05\n", - "Epoch 184/1024\n", - "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0125 - lr: 7.8125e-05\n", - "Epoch 185/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0052 - lr: 7.8125e-05\n", - "Epoch 186/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0645 - lr: 7.8125e-05\n", - "Epoch 187/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0029 - val_loss: 0.0465 - lr: 7.8125e-05\n", - "Epoch 188/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0429 - lr: 7.8125e-05\n", - "Epoch 189/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0272 - lr: 7.8125e-05\n", - "Epoch 190/1024\n", - "90/90 [==============================] - 0s 862us/step - loss: 0.0028 - val_loss: 0.0577 - lr: 7.8125e-05\n", - "Epoch 191/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0029 - val_loss: 0.0040 - lr: 7.8125e-05\n", - "Epoch 192/1024\n", - "90/90 [==============================] - 0s 893us/step - loss: 0.0028 - val_loss: 0.0437 - lr: 7.8125e-05\n", - "Epoch 193/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 7.8125e-05\n", - "Epoch 194/1024\n", - "90/90 [==============================] - 0s 888us/step - loss: 0.0028 - val_loss: 0.0055 - lr: 7.8125e-05\n", - "Epoch 195/1024\n", - "90/90 [==============================] - 0s 858us/step - loss: 0.0029 - val_loss: 0.0131 - lr: 7.8125e-05\n", - "Epoch 196/1024\n", - "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.0290 - lr: 7.8125e-05\n", - "Epoch 197/1024\n", - "90/90 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0.0029 - val_loss: 0.0136 - lr: 7.8125e-05\n", - "Epoch 205/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0028 - val_loss: 0.2139 - lr: 7.8125e-05\n", - "Epoch 206/1024\n", - "90/90 [==============================] - 0s 881us/step - loss: 0.0028 - val_loss: 0.0143 - lr: 7.8125e-05\n", - "Epoch 207/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0029 - val_loss: 0.1455 - lr: 7.8125e-05\n", - "Epoch 208/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0175 - lr: 7.8125e-05\n", - "Epoch 209/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0028 - val_loss: 0.0451 - lr: 7.8125e-05\n", - "Epoch 210/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0028 - val_loss: 0.1155 - lr: 7.8125e-05\n", - "Epoch 211/1024\n", - "90/90 [==============================] - 0s 861us/step - loss: 0.0028 - val_loss: 0.0095 - lr: 7.8125e-05\n", - "Epoch 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0s 872us/step - loss: 0.0029 - val_loss: 0.0044 - lr: 3.9062e-05\n", - "Epoch 220/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0029 - val_loss: 0.0474 - lr: 3.9062e-05\n", - "Epoch 221/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0028 - val_loss: 0.0457 - lr: 3.9062e-05\n", - "Epoch 222/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0029 - val_loss: 0.0045 - lr: 3.9062e-05\n", - "Epoch 223/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0230 - lr: 3.9062e-05\n", - "Epoch 224/1024\n", - "90/90 [==============================] - 0s 878us/step - loss: 0.0028 - val_loss: 0.0180 - lr: 3.9062e-05\n", - "Epoch 225/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0028 - val_loss: 0.0337 - lr: 3.9062e-05\n", - "Epoch 226/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0289 - lr: 3.9062e-05\n", - "Epoch 227/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 3.9062e-05\n", - "Epoch 228/1024\n", - "90/90 [==============================] - 0s 907us/step - loss: 0.0029 - val_loss: 0.0044 - lr: 3.9062e-05\n", - "Epoch 229/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0188 - lr: 3.9062e-05\n", - "Epoch 230/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0028 - val_loss: 0.0352 - lr: 3.9062e-05\n", - "Epoch 231/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0028 - val_loss: 0.0164 - lr: 3.9062e-05\n", - "Epoch 232/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0092 - lr: 3.9062e-05\n", - "Epoch 233/1024\n", - "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0099 - lr: 3.9062e-05\n", - "Epoch 234/1024\n", - "90/90 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"Epoch 249/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0092 - lr: 3.9062e-05\n", - "Epoch 250/1024\n", - "90/90 [==============================] - 0s 991us/step - loss: 0.0030 - val_loss: 0.0083 - lr: 3.9062e-05\n", - "Epoch 251/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0221 - lr: 3.9062e-05\n", - "Epoch 252/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0028 - val_loss: 0.0097 - lr: 3.9062e-05\n", - "Epoch 253/1024\n", - "90/90 [==============================] - 0s 859us/step - loss: 0.0028 - val_loss: 0.0062 - lr: 3.9062e-05\n", - "Epoch 254/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 3.9062e-05\n", - "Epoch 255/1024\n", - "90/90 [==============================] - 0s 905us/step - loss: 0.0028 - val_loss: 0.0411 - lr: 3.9062e-05\n", - "Epoch 256/1024\n", - "90/90 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0s 863us/step - loss: 0.0028 - val_loss: 0.0107 - lr: 1.9531e-05\n", - "Epoch 301/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0028 - val_loss: 0.0060 - lr: 1.9531e-05\n", - "Epoch 302/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0028 - val_loss: 0.0133 - lr: 1.9531e-05\n", - "Epoch 303/1024\n", - "90/90 [==============================] - 0s 857us/step - loss: 0.0028 - val_loss: 0.0037 - lr: 1.9531e-05\n", - "Epoch 304/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0028 - val_loss: 0.0066 - lr: 1.9531e-05\n", - "Epoch 305/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", - "Epoch 306/1024\n", - "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", - "Epoch 307/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0033 - lr: 1.9531e-05\n", - "Epoch 308/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0039 - lr: 1.9531e-05\n", - "Epoch 309/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0067 - lr: 1.9531e-05\n", - "Epoch 310/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0029 - val_loss: 0.0045 - lr: 1.9531e-05\n", - "Epoch 311/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0028 - val_loss: 0.0039 - lr: 1.9531e-05\n", - "Epoch 312/1024\n", - "90/90 [==============================] - 0s 900us/step - loss: 0.0028 - val_loss: 0.0043 - lr: 1.9531e-05\n", - "Epoch 313/1024\n", - "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0040 - lr: 1.9531e-05\n", - "Epoch 314/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0108 - lr: 1.9531e-05\n", - "Epoch 315/1024\n", - "90/90 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0.0028 - val_loss: 0.0042 - lr: 1.9531e-05\n", - "Epoch 323/1024\n", - "90/90 [==============================] - 0s 876us/step - loss: 0.0027 - val_loss: 0.0031 - lr: 1.9531e-05\n", - "Epoch 324/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0031 - lr: 1.9531e-05\n", - "Epoch 325/1024\n", - "90/90 [==============================] - 0s 883us/step - loss: 0.0027 - val_loss: 0.0063 - lr: 1.9531e-05\n", - "Epoch 326/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0028 - val_loss: 0.0166 - lr: 1.9531e-05\n", - "Epoch 327/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0028 - val_loss: 0.0035 - lr: 1.9531e-05\n", - "Epoch 328/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0055 - lr: 1.9531e-05\n", - "Epoch 329/1024\n", - "90/90 [==============================] - 0s 888us/step - loss: 0.0028 - val_loss: 0.0091 - lr: 1.9531e-05\n", - "Epoch 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9.7656e-06\n", - "Epoch 345/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0028 - val_loss: 0.0037 - lr: 9.7656e-06\n", - "Epoch 346/1024\n", - "90/90 [==============================] - 0s 876us/step - loss: 0.0027 - val_loss: 0.0050 - lr: 9.7656e-06\n", - "Epoch 347/1024\n", - "90/90 [==============================] - 0s 881us/step - loss: 0.0028 - val_loss: 0.0042 - lr: 9.7656e-06\n", - "Epoch 348/1024\n", - "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", - "Epoch 349/1024\n", - "90/90 [==============================] - 0s 886us/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", - "Epoch 350/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0032 - lr: 9.7656e-06\n", - "Epoch 351/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", - "Epoch 352/1024\n", - "90/90 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0.0027 - val_loss: 0.0062 - lr: 9.7656e-06\n", - "Epoch 360/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0030 - lr: 9.7656e-06\n", - "Epoch 361/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0028 - val_loss: 0.0054 - lr: 9.7656e-06\n", - "Epoch 362/1024\n", - "90/90 [==============================] - 0s 884us/step - loss: 0.0029 - val_loss: 0.0031 - lr: 9.7656e-06\n", - "Epoch 363/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", - "Epoch 364/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", - "Epoch 365/1024\n", - "90/90 [==============================] - 0s 881us/step - loss: 0.0026 - val_loss: 0.0033 - lr: 9.7656e-06\n", - "Epoch 366/1024\n", - "90/90 [==============================] - 0s 882us/step - loss: 0.0028 - val_loss: 0.0041 - lr: 4.8828e-06\n", - "Epoch 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0s 874us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", - "Epoch 375/1024\n", - "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.0032 - lr: 4.8828e-06\n", - "Epoch 376/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", - "Epoch 377/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", - "Epoch 378/1024\n", - "90/90 [==============================] - 0s 904us/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", - "Epoch 379/1024\n", - "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", - "Epoch 380/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", - "Epoch 381/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0041 - lr: 4.8828e-06\n", - "Epoch 382/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0033 - lr: 4.8828e-06\n", - "Epoch 383/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", - "Epoch 384/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0031 - lr: 4.8828e-06\n", - "Epoch 385/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", - "Epoch 386/1024\n", - "90/90 [==============================] - ETA: 0s - loss: 0.002 - 0s 896us/step - loss: 0.0029 - val_loss: 0.0027 - lr: 4.8828e-06\n", - "Epoch 387/1024\n", - "90/90 [==============================] - 0s 880us/step - loss: 0.0027 - val_loss: 0.0029 - lr: 4.8828e-06\n", - "Epoch 388/1024\n", - "90/90 [==============================] - 0s 875us/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", - "Epoch 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0s 863us/step - loss: 0.0027 - val_loss: 0.0033 - lr: 4.8828e-06\n", - "Epoch 397/1024\n", - "90/90 [==============================] - 0s 864us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", - "Epoch 398/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", - "Epoch 399/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", - "Epoch 400/1024\n", - "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0030 - lr: 4.8828e-06\n", - "Epoch 401/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", - "Epoch 402/1024\n", - "90/90 [==============================] - 0s 882us/step - loss: 0.0029 - val_loss: 0.0027 - lr: 4.8828e-06\n", - "Epoch 403/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0029 - val_loss: 0.0030 - lr: 4.8828e-06\n", - "Epoch 404/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0029 - val_loss: 0.0026 - lr: 4.8828e-06\n", - "Epoch 405/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 4.8828e-06\n", - "Epoch 406/1024\n", - "90/90 [==============================] - 0s 888us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", - "Epoch 407/1024\n", - "90/90 [==============================] - 0s 895us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 4.8828e-06\n", - "Epoch 408/1024\n", - "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0033 - lr: 4.8828e-06\n", - "Epoch 409/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", - "Epoch 410/1024\n", - "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", - "Epoch 411/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 412/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 2.4414e-06\n", - "Epoch 413/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 414/1024\n", - "90/90 [==============================] - 0s 880us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 415/1024\n", - "90/90 [==============================] - 0s 878us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 416/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 417/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", - "Epoch 418/1024\n", - "90/90 [==============================] - 0s 906us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 419/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 420/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", - "Epoch 421/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 422/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 2.4414e-06\n", - "Epoch 423/1024\n", - "90/90 [==============================] - 0s 876us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 424/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", - "Epoch 425/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 426/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", - "Epoch 427/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 428/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 429/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 430/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 2.4414e-06\n", - "Epoch 431/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 432/1024\n", - "90/90 [==============================] - 0s 859us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 433/1024\n", - "90/90 [==============================] 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2.4414e-06\n", - "Epoch 441/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 442/1024\n", - "90/90 [==============================] - 0s 879us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", - "Epoch 443/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 444/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 445/1024\n", - "90/90 [==============================] - 0s 881us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 446/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 447/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 448/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 449/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 450/1024\n", - "90/90 [==============================] - 0s 885us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 451/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 452/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 453/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 454/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 455/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 456/1024\n", - "90/90 [==============================] - 0s 889us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 457/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 458/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 459/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 460/1024\n", - "90/90 [==============================] - 0s 878us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 461/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 462/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 463/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 464/1024\n", - "90/90 [==============================] - 0s 862us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 465/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", - "Epoch 466/1024\n", - "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 467/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", - "Epoch 468/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 469/1024\n", - "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 470/1024\n", - "90/90 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0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 478/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 479/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 480/1024\n", - "90/90 [==============================] - 0s 881us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 481/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 482/1024\n", - "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 483/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 484/1024\n", - "90/90 [==============================] - 0s 879us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 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0s 877us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 493/1024\n", - "90/90 [==============================] - 0s 929us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 494/1024\n", - "90/90 [==============================] - 0s 976us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 495/1024\n", - "90/90 [==============================] - 0s 863us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", - "Epoch 496/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 497/1024\n", - "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 498/1024\n", - "90/90 [==============================] - 0s 879us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 499/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 500/1024\n", - "90/90 [==============================] - 0s 938us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 501/1024\n", - "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 502/1024\n", - "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 503/1024\n", - "90/90 [==============================] - 0s 867us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 504/1024\n", - "90/90 [==============================] - 0s 898us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 505/1024\n", - "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 506/1024\n", - "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 507/1024\n", - "90/90 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0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 515/1024\n", - "90/90 [==============================] - 0s 986us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 516/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 517/1024\n", - "90/90 [==============================] - 0s 879us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 518/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 519/1024\n", - "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 520/1024\n", - "90/90 [==============================] - 0s 883us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", - "Epoch 521/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 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1.5259e-07\n", - "Epoch 537/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 538/1024\n", - "90/90 [==============================] - 0s 880us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 539/1024\n", - "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 540/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 541/1024\n", - "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 542/1024\n", - "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 543/1024\n", - "90/90 [==============================] - 0s 878us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", - "Epoch 544/1024\n", - "90/90 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[==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n", "Epoch 1022/1024\n", - "90/90 [==============================] - 0s 884us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.4552e-13\n", "Epoch 1023/1024\n", - "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n", "Epoch 1024/1024\n", - "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n" + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n" ] } ], "source": [ "epoch, batch_size = 1024, 64\n", - "history_shortcut_11 = shortcut11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size)\n", - "history_shortcut_5 = shortcut5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size)" + "history_shortcut_11 = shortcut11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)\n", + "history_shortcut_5 = shortcut5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 12, "metadata": { "pycharm": { "name": "#%%\n" @@ -7040,10 +7041,8 @@ "outputs": [ { "data": { - "image/png": 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", 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\n" }, "metadata": { "needs_background": "light" @@ -7075,7 +7074,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 13, "metadata": { "pycharm": { "name": "#%%\n" @@ -7088,7 +7087,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "metadata": { "pycharm": { "name": "#%%\n" @@ -7097,19 +7096,41 @@ "outputs": [], "source": [ "import os\n", - "time_spent = (time.time() - time1) /60\n" + "time_spent = (time.time() - time1) /60" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "pycharm": { "name": "#%%\n" } }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "16.816816703478494 min\n" + ] + } + ], + "source": [ + "print(time_spent, \"min\")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, "outputs": [], - "source": [] + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } } ], "metadata": { @@ -7136,4 +7157,4 @@ }, "nbformat": 4, "nbformat_minor": 1 -} +} \ No newline at end of file diff --git a/02_model_training_adagrad.ipynb b/02_model_training_adagrad.ipynb new file mode 100644 index 0000000..abd85e5 --- /dev/null +++ b/02_model_training_adagrad.ipynb @@ -0,0 +1,7438 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Model training Experiment" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "In order to provide the experimental evidence to back up the statement in the section 2.3.2 that our shortcut block can prevent degration problem.\n", + "\n", + "Plain Networks. We first evaluate 5-layer and 11-layer plain nets. Comparing to the 5-layer one, the 11-layer one has three times convolutional layers." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import pickle\n", + "import time\n", + "\n", + "import numpy as np\n", + "from matplotlib import ticker\n", + "from scipy.io import loadmat\n", + "from models import Plain5, Plain11, ShortCut5, ShortCut11\n", + "from sklearn.model_selection import train_test_split\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib notebook" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Load data\n", + "load data and split them into train, val, test" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape of data:\n", + "x_train: (5728, 1, 102), y_train: (5728, 1),\n", + "x_val: (2455, 1, 102), y_val: (2455, 1)\n", + "x_test: (3508, 1, 102), y_test: (3508, 1)\n" + ] + } + ], + "source": [ + "import random\n", + "from numpy.random import seed\n", + "import tensorflow\n", + "import time\n", + "seed(2800)\n", + "tensorflow.random.set_seed(2800)\n", + "time1 = time.time()\n", + "data = loadmat('dataset/mango/mango_dm_split.mat')\n", + "training_method = \"adagrad\"\n", + "x_train, y_train, x_test, y_test = data['x_train'], data['y_train'], data['x_test'], data['y_test']\n", + "x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size=0.3, random_state=12, shuffle=True)\n", + "x_train, x_val, x_test = x_train[:, np.newaxis, :], x_val[:, np.newaxis, :], x_test[:, np.newaxis, :]\n", + "print(f\"shape of data:\\n\"\n", + " f\"x_train: {x_train.shape}, y_train: {y_train.shape},\\n\"\n", + " f\"x_val: {x_val.shape}, y_val: {y_val.shape}\\n\"\n", + " f\"x_test: {x_test.shape}, y_test: {y_test.shape}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Build Plain networks and Training" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "plain_5, plain_11 = Plain5(input_shape=(1, 102)), Plain11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-06-27 14:34:16.347234: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/1024\n", + "90/90 [==============================] - 3s 11ms/step - loss: 0.0292 - val_loss: 0.0286 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0256 - val_loss: 0.0281 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0240 - val_loss: 0.0278 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0232 - val_loss: 0.0276 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0226 - val_loss: 0.0279 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0222 - val_loss: 0.0263 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0221 - val_loss: 0.0248 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0218 - val_loss: 0.0245 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0218 - val_loss: 0.0257 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0218 - val_loss: 0.0253 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0214 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0212 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0212 - val_loss: 0.0258 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0212 - val_loss: 0.0235 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0211 - val_loss: 0.0237 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0210 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0208 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0208 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0210 - val_loss: 0.0337 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0208 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0208 - val_loss: 0.0228 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0207 - val_loss: 0.0259 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0206 - val_loss: 0.0221 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0207 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0204 - val_loss: 0.0273 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0239 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0203 - val_loss: 0.0224 - lr: 0.0025\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0205 - val_loss: 0.0247 - lr: 0.0025\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0247 - lr: 0.0025\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0203 - val_loss: 0.0222 - lr: 0.0025\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0201 - val_loss: 0.0214 - lr: 0.0025\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0201 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0199 - val_loss: 0.0258 - lr: 0.0025\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0201 - val_loss: 0.0237 - lr: 0.0025\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0198 - val_loss: 0.0257 - lr: 0.0025\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0199 - val_loss: 0.0264 - lr: 0.0025\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0228 - lr: 0.0025\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0196 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0214 - lr: 0.0025\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 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0s 4ms/step - loss: 0.0182 - val_loss: 0.0281 - lr: 0.0025\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0186 - val_loss: 0.0354 - lr: 0.0025\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0184 - val_loss: 0.0238 - lr: 0.0025\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0183 - val_loss: 0.0248 - lr: 0.0025\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0182 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0182 - val_loss: 0.0370 - lr: 0.0025\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0182 - val_loss: 0.0372 - lr: 0.0025\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0181 - val_loss: 0.0381 - lr: 0.0025\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0181 - val_loss: 0.0386 - lr: 0.0025\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0178 - val_loss: 0.0310 - lr: 0.0025\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0179 - val_loss: 0.0344 - lr: 0.0025\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0178 - val_loss: 0.0307 - lr: 0.0012\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0178 - val_loss: 0.0356 - lr: 0.0012\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0178 - val_loss: 0.0340 - lr: 0.0012\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0175 - val_loss: 0.0375 - lr: 0.0012\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0176 - val_loss: 0.0337 - lr: 0.0012\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0174 - val_loss: 0.0366 - lr: 0.0012\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0174 - val_loss: 0.0316 - lr: 0.0012\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0175 - val_loss: 0.0213 - lr: 0.0012\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0171 - val_loss: 0.0337 - lr: 0.0012\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0172 - val_loss: 0.0270 - lr: 0.0012\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0171 - val_loss: 0.0340 - lr: 0.0012\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0173 - val_loss: 0.0327 - lr: 0.0012\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0168 - val_loss: 0.0329 - lr: 0.0012\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0171 - val_loss: 0.0345 - lr: 0.0012\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0170 - val_loss: 0.0391 - lr: 0.0012\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0171 - val_loss: 0.0243 - lr: 0.0012\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0171 - val_loss: 0.0232 - lr: 0.0012\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0169 - val_loss: 0.0330 - lr: 0.0012\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0167 - val_loss: 0.0359 - lr: 0.0012\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0166 - val_loss: 0.0299 - lr: 0.0012\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0165 - val_loss: 0.0244 - lr: 0.0012\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0169 - val_loss: 0.0368 - lr: 0.0012\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0168 - val_loss: 0.0235 - lr: 0.0012\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0165 - val_loss: 0.0225 - lr: 0.0012\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0165 - val_loss: 0.0180 - lr: 0.0012\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0168 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0167 - val_loss: 0.0376 - lr: 0.0012\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0167 - val_loss: 0.0221 - lr: 0.0012\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0164 - val_loss: 0.0279 - lr: 0.0012\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0163 - val_loss: 0.0234 - lr: 0.0012\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0162 - val_loss: 0.0191 - lr: 0.0012\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0212 - lr: 0.0012\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0164 - val_loss: 0.0238 - lr: 0.0012\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0164 - val_loss: 0.0327 - lr: 0.0012\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0161 - val_loss: 0.0360 - lr: 0.0012\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0161 - val_loss: 0.0310 - lr: 0.0012\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0161 - val_loss: 0.0236 - lr: 0.0012\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0161 - val_loss: 0.0255 - lr: 0.0012\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0161 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0159 - val_loss: 0.0304 - lr: 0.0012\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0160 - val_loss: 0.0163 - lr: 0.0012\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0162 - val_loss: 0.0275 - lr: 0.0012\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0159 - val_loss: 0.0167 - lr: 0.0012\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0158 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0157 - val_loss: 0.0170 - lr: 0.0012\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0154 - val_loss: 0.0298 - lr: 0.0012\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0154 - val_loss: 0.0193 - lr: 0.0012\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0156 - val_loss: 0.0179 - lr: 0.0012\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0157 - val_loss: 0.0281 - lr: 0.0012\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0154 - val_loss: 0.0218 - lr: 0.0012\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0155 - val_loss: 0.0176 - lr: 0.0012\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0153 - val_loss: 0.0218 - lr: 0.0012\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0152 - val_loss: 0.0277 - lr: 0.0012\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0154 - val_loss: 0.0164 - lr: 0.0012\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0152 - val_loss: 0.0173 - lr: 0.0012\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 0.0012\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0152 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0155 - val_loss: 0.0182 - lr: 0.0012\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0151 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0150 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0151 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0149 - val_loss: 0.0328 - lr: 0.0012\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0150 - val_loss: 0.0299 - lr: 0.0012\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0149 - val_loss: 0.0341 - lr: 0.0012\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 0.0012\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0146 - val_loss: 0.0228 - lr: 0.0012\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0145 - val_loss: 0.0168 - lr: 0.0012\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0147 - val_loss: 0.0251 - lr: 0.0012\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0148 - val_loss: 0.0181 - lr: 0.0012\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0145 - val_loss: 0.0172 - lr: 0.0012\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0147 - val_loss: 0.0182 - lr: 0.0012\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0145 - val_loss: 0.0181 - lr: 0.0012\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0145 - val_loss: 0.0180 - lr: 0.0012\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0145 - val_loss: 0.0209 - lr: 0.0012\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0144 - val_loss: 0.0237 - lr: 0.0012\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0146 - val_loss: 0.0268 - lr: 0.0012\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0145 - val_loss: 0.0171 - lr: 0.0012\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0141 - val_loss: 0.0143 - lr: 0.0012\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0141 - val_loss: 0.0157 - lr: 0.0012\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0138 - val_loss: 0.0262 - lr: 0.0012\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0142 - val_loss: 0.0234 - lr: 0.0012\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0141 - val_loss: 0.0240 - lr: 0.0012\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0139 - val_loss: 0.0264 - lr: 0.0012\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0137 - val_loss: 0.0358 - lr: 0.0012\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0139 - val_loss: 0.0181 - lr: 0.0012\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 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0s 4ms/step - loss: 0.0121 - val_loss: 0.0160 - lr: 6.2500e-04\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0170 - lr: 6.2500e-04\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0120 - val_loss: 0.0120 - lr: 6.2500e-04\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0127 - lr: 6.2500e-04\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0125 - lr: 6.2500e-04\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0118 - val_loss: 0.0140 - lr: 6.2500e-04\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0117 - val_loss: 0.0199 - lr: 6.2500e-04\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0122 - val_loss: 0.0150 - lr: 6.2500e-04\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0130 - lr: 6.2500e-04\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0119 - val_loss: 0.0308 - lr: 6.2500e-04\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0120 - val_loss: 0.0199 - lr: 6.2500e-04\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0119 - val_loss: 0.0151 - lr: 6.2500e-04\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0117 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0125 - lr: 6.2500e-04\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0118 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0120 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0130 - lr: 6.2500e-04\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 6.2500e-04\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0118 - val_loss: 0.0144 - lr: 6.2500e-04\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0119 - val_loss: 0.0175 - lr: 6.2500e-04\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0117 - val_loss: 0.0132 - lr: 6.2500e-04\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0117 - val_loss: 0.0122 - lr: 6.2500e-04\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0116 - val_loss: 0.0235 - lr: 6.2500e-04\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0118 - val_loss: 0.0141 - lr: 6.2500e-04\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0118 - val_loss: 0.0199 - lr: 6.2500e-04\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0115 - val_loss: 0.0137 - lr: 6.2500e-04\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0118 - val_loss: 0.0147 - lr: 6.2500e-04\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0118 - val_loss: 0.0185 - lr: 6.2500e-04\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0115 - val_loss: 0.0138 - lr: 6.2500e-04\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0118 - val_loss: 0.0160 - lr: 6.2500e-04\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0115 - val_loss: 0.0239 - lr: 6.2500e-04\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0117 - val_loss: 0.0129 - lr: 6.2500e-04\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0116 - val_loss: 0.0274 - lr: 6.2500e-04\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0116 - val_loss: 0.0115 - lr: 6.2500e-04\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0117 - val_loss: 0.0148 - lr: 6.2500e-04\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0115 - val_loss: 0.0161 - lr: 6.2500e-04\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0136 - lr: 6.2500e-04\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0152 - lr: 6.2500e-04\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0116 - val_loss: 0.0214 - lr: 6.2500e-04\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0115 - val_loss: 0.0117 - lr: 6.2500e-04\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0113 - val_loss: 0.0124 - lr: 6.2500e-04\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0117 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0111 - val_loss: 0.0127 - lr: 6.2500e-04\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0115 - val_loss: 0.0338 - lr: 6.2500e-04\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0113 - val_loss: 0.0168 - lr: 6.2500e-04\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0113 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0153 - lr: 6.2500e-04\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0129 - lr: 6.2500e-04\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0112 - val_loss: 0.0112 - lr: 6.2500e-04\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0113 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0314 - lr: 6.2500e-04\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0113 - val_loss: 0.0305 - lr: 6.2500e-04\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0193 - lr: 6.2500e-04\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0112 - val_loss: 0.0166 - lr: 6.2500e-04\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0112 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0111 - val_loss: 0.0157 - lr: 6.2500e-04\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0164 - lr: 6.2500e-04\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0111 - val_loss: 0.0126 - lr: 6.2500e-04\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0112 - val_loss: 0.0140 - lr: 6.2500e-04\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0112 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0111 - val_loss: 0.0155 - lr: 6.2500e-04\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0109 - val_loss: 0.0134 - lr: 6.2500e-04\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0111 - val_loss: 0.0126 - lr: 6.2500e-04\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0171 - lr: 6.2500e-04\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0113 - val_loss: 0.0147 - lr: 6.2500e-04\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0110 - val_loss: 0.0144 - lr: 6.2500e-04\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0111 - val_loss: 0.0168 - lr: 6.2500e-04\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0111 - val_loss: 0.0153 - lr: 6.2500e-04\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0115 - lr: 6.2500e-04\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 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0s 4ms/step - loss: 0.0103 - val_loss: 0.0128 - lr: 6.2500e-04\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0103 - val_loss: 0.0144 - lr: 6.2500e-04\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0103 - val_loss: 0.0110 - lr: 6.2500e-04\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0101 - val_loss: 0.0104 - lr: 6.2500e-04\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0134 - lr: 6.2500e-04\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0101 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0104 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0102 - val_loss: 0.0119 - lr: 3.1250e-04\n", + "Epoch 385/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0102 - val_loss: 0.0147 - lr: 3.1250e-04\n", + "Epoch 386/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0102 - val_loss: 0.0124 - lr: 3.1250e-04\n", + "Epoch 387/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0104 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0102 - val_loss: 0.0105 - lr: 3.1250e-04\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0103 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0127 - lr: 3.1250e-04\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0102 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0102 - val_loss: 0.0122 - lr: 3.1250e-04\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0103 - val_loss: 0.0127 - lr: 3.1250e-04\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0129 - lr: 3.1250e-04\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0112 - lr: 3.1250e-04\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0116 - lr: 3.1250e-04\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0103 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0113 - lr: 3.1250e-04\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0104 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0103 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0105 - lr: 3.1250e-04\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0114 - lr: 3.1250e-04\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0118 - lr: 3.1250e-04\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0118 - lr: 3.1250e-04\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0112 - lr: 3.1250e-04\n", + "Epoch 432/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 433/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0114 - lr: 3.1250e-04\n", + "Epoch 434/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0129 - lr: 3.1250e-04\n", + "Epoch 435/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 436/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0102 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 437/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0131 - lr: 3.1250e-04\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0103 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0103 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0114 - lr: 3.1250e-04\n", + "Epoch 442/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 443/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 444/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 445/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 446/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 447/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 448/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 449/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 450/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 451/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 458/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 459/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 460/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 461/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0102 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 462/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 463/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 464/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 465/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 466/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 467/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0100 - val_loss: 0.0105 - lr: 3.1250e-04\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0122 - lr: 3.1250e-04\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0101 - val_loss: 0.0138 - lr: 3.1250e-04\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 474/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0116 - lr: 3.1250e-04\n", + "Epoch 475/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 476/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 477/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 478/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 479/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 480/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 481/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 482/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 485/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 486/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0102 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 487/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 489/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0117 - lr: 3.1250e-04\n", + "Epoch 490/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 491/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 492/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 493/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0138 - lr: 3.1250e-04\n", + "Epoch 494/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 495/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 496/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0113 - lr: 3.1250e-04\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0095 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 504/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 505/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 506/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 507/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0104 - lr: 1.5625e-04\n", + "Epoch 508/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 509/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0106 - lr: 1.5625e-04\n", + "Epoch 510/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 511/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0101 - lr: 1.5625e-04\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0096 - val_loss: 0.0105 - lr: 1.5625e-04\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0101 - lr: 1.5625e-04\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 520/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0100 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 521/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 522/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 523/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 524/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 525/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0096 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 526/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0095 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 536/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 537/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 538/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 539/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 540/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 541/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 550/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 551/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 552/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 565/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 566/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 567/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 568/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 569/1024\n", + "90/90 [==============================] - 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0s 4ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 626/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 627/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 628/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 629/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 630/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 631/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 632/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 633/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 634/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 635/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 636/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 637/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 638/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 639/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 640/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 641/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 642/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 643/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 644/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 645/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 646/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 647/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 648/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0100 - val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 649/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 650/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 651/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 652/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 653/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 3.9062e-05\n", + "Epoch 654/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 655/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 656/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 657/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 658/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 659/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 660/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0099 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 661/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 662/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0094 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 663/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 664/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 665/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 666/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 667/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 668/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 669/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 670/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 671/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 672/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 673/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 674/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 675/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 676/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 677/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 678/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 679/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 9.7656e-06\n", + "Epoch 680/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 9.7656e-06\n", + "Epoch 681/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0204 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0205 - val_loss: 0.0215 - lr: 0.0025\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0206 - val_loss: 0.0215 - lr: 0.0025\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0205 - val_loss: 0.0218 - lr: 0.0025\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0205 - val_loss: 0.0215 - lr: 0.0025\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0205 - val_loss: 0.0212 - lr: 0.0025\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0215 - lr: 0.0025\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0204 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0208 - lr: 0.0025\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0203 - val_loss: 0.0212 - lr: 0.0025\n", + "Epoch 49/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0215 - lr: 0.0025\n", + "Epoch 50/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 51/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0210 - lr: 0.0025\n", + "Epoch 52/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0215 - lr: 0.0025\n", + "Epoch 53/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0208 - lr: 0.0025\n", + "Epoch 54/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0201 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 55/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0207 - lr: 0.0025\n", + "Epoch 56/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0204 - lr: 0.0025\n", + "Epoch 57/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0199 - val_loss: 0.0203 - lr: 0.0025\n", + "Epoch 58/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0199 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0199 - val_loss: 0.0210 - lr: 0.0025\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0207 - lr: 0.0025\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0212 - lr: 0.0025\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0208 - lr: 0.0025\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0202 - lr: 0.0025\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0211 - lr: 0.0025\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0194 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0203 - lr: 0.0025\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0193 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0210 - lr: 0.0025\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0193 - val_loss: 0.0204 - lr: 0.0025\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0212 - lr: 0.0025\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0211 - lr: 0.0025\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0192 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0213 - lr: 0.0025\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0208 - lr: 0.0025\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0217 - lr: 0.0025\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0213 - lr: 0.0025\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0272 - lr: 0.0025\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0221 - lr: 0.0025\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0250 - lr: 0.0025\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0295 - lr: 0.0025\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0263 - lr: 0.0025\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0288 - lr: 0.0025\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0283 - lr: 0.0025\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0170 - val_loss: 0.0414 - lr: 0.0025\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0168 - val_loss: 0.0440 - lr: 0.0025\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0588 - lr: 0.0025\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0411 - lr: 0.0012\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0262 - lr: 0.0012\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0313 - lr: 0.0012\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0332 - lr: 0.0012\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0161 - val_loss: 0.0377 - lr: 0.0012\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0160 - val_loss: 0.0454 - lr: 0.0012\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0159 - val_loss: 0.0459 - lr: 0.0012\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0400 - lr: 0.0012\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0158 - val_loss: 0.0507 - lr: 0.0012\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0155 - val_loss: 0.0452 - lr: 0.0012\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0153 - val_loss: 0.0413 - lr: 0.0012\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0153 - val_loss: 0.0590 - lr: 0.0012\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0463 - lr: 0.0012\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0153 - val_loss: 0.0503 - lr: 0.0012\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0152 - val_loss: 0.0425 - lr: 0.0012\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0151 - val_loss: 0.0740 - lr: 0.0012\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0793 - lr: 0.0012\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0149 - val_loss: 0.0869 - lr: 0.0012\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0852 - lr: 0.0012\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0775 - lr: 0.0012\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0147 - val_loss: 0.0708 - lr: 0.0012\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0147 - val_loss: 0.0689 - lr: 0.0012\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0144 - val_loss: 0.0498 - lr: 0.0012\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0670 - lr: 0.0012\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0145 - val_loss: 0.0696 - lr: 0.0012\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0144 - val_loss: 0.0498 - lr: 6.2500e-04\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0141 - val_loss: 0.0420 - lr: 6.2500e-04\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0144 - val_loss: 0.0335 - lr: 6.2500e-04\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0141 - val_loss: 0.0244 - lr: 6.2500e-04\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0142 - val_loss: 0.0266 - lr: 6.2500e-04\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0142 - val_loss: 0.0238 - lr: 6.2500e-04\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0141 - val_loss: 0.0361 - lr: 6.2500e-04\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0138 - val_loss: 0.0279 - lr: 6.2500e-04\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0275 - lr: 6.2500e-04\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.0373 - lr: 6.2500e-04\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0371 - lr: 6.2500e-04\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0140 - val_loss: 0.0393 - lr: 6.2500e-04\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.0332 - lr: 6.2500e-04\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0375 - lr: 6.2500e-04\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0138 - val_loss: 0.0354 - lr: 6.2500e-04\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0138 - val_loss: 0.0455 - lr: 6.2500e-04\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0138 - val_loss: 0.0377 - lr: 6.2500e-04\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0136 - val_loss: 0.0423 - lr: 6.2500e-04\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0136 - val_loss: 0.0455 - lr: 6.2500e-04\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0139 - val_loss: 0.0414 - lr: 6.2500e-04\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0136 - val_loss: 0.0358 - lr: 6.2500e-04\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0136 - val_loss: 0.0299 - lr: 6.2500e-04\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0136 - val_loss: 0.0360 - lr: 6.2500e-04\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0135 - val_loss: 0.0370 - lr: 6.2500e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0303 - lr: 6.2500e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0134 - val_loss: 0.0235 - lr: 3.1250e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0136 - val_loss: 0.0224 - lr: 3.1250e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0134 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0134 - val_loss: 0.0184 - lr: 3.1250e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0135 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0132 - val_loss: 0.0164 - lr: 3.1250e-04\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0135 - val_loss: 0.0222 - lr: 3.1250e-04\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0134 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0175 - lr: 3.1250e-04\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0134 - val_loss: 0.0223 - lr: 3.1250e-04\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0225 - lr: 3.1250e-04\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0133 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0171 - lr: 3.1250e-04\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0134 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0131 - val_loss: 0.0162 - lr: 3.1250e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0133 - val_loss: 0.0184 - lr: 3.1250e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0133 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0133 - val_loss: 0.0178 - lr: 3.1250e-04\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0131 - val_loss: 0.0165 - lr: 3.1250e-04\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0131 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0132 - val_loss: 0.0151 - lr: 3.1250e-04\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0130 - val_loss: 0.0200 - lr: 3.1250e-04\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0131 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0130 - val_loss: 0.0164 - lr: 3.1250e-04\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0131 - val_loss: 0.0171 - lr: 3.1250e-04\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0130 - val_loss: 0.0219 - lr: 3.1250e-04\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0130 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0130 - val_loss: 0.0171 - lr: 3.1250e-04\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0129 - val_loss: 0.0179 - lr: 3.1250e-04\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0184 - lr: 3.1250e-04\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0179 - lr: 3.1250e-04\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0227 - lr: 3.1250e-04\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0130 - val_loss: 0.0200 - lr: 3.1250e-04\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0131 - val_loss: 0.0176 - lr: 3.1250e-04\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0178 - lr: 3.1250e-04\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0175 - lr: 3.1250e-04\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0181 - lr: 3.1250e-04\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0160 - lr: 3.1250e-04\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0172 - lr: 3.1250e-04\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0170 - lr: 3.1250e-04\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0127 - val_loss: 0.0152 - lr: 3.1250e-04\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0127 - val_loss: 0.0146 - lr: 3.1250e-04\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0128 - val_loss: 0.0146 - lr: 3.1250e-04\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0130 - val_loss: 0.0147 - lr: 3.1250e-04\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0127 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0128 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0126 - val_loss: 0.0159 - lr: 3.1250e-04\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0126 - val_loss: 0.0174 - lr: 3.1250e-04\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0127 - val_loss: 0.0178 - lr: 3.1250e-04\n", + "Epoch 191/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0126 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 192/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0126 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0128 - val_loss: 0.0152 - lr: 3.1250e-04\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0159 - lr: 3.1250e-04\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0126 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0124 - val_loss: 0.0181 - lr: 3.1250e-04\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0157 - lr: 3.1250e-04\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0126 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0154 - lr: 3.1250e-04\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0143 - lr: 3.1250e-04\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0124 - val_loss: 0.0156 - lr: 3.1250e-04\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0126 - val_loss: 0.0143 - lr: 3.1250e-04\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0137 - lr: 3.1250e-04\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0146 - lr: 3.1250e-04\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0172 - lr: 3.1250e-04\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0163 - lr: 3.1250e-04\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0124 - val_loss: 0.0178 - lr: 3.1250e-04\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0144 - lr: 3.1250e-04\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0173 - lr: 3.1250e-04\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0151 - lr: 3.1250e-04\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0165 - lr: 3.1250e-04\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0170 - lr: 3.1250e-04\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0151 - lr: 3.1250e-04\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0158 - lr: 3.1250e-04\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0138 - lr: 3.1250e-04\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0140 - lr: 3.1250e-04\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0154 - lr: 3.1250e-04\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0154 - lr: 3.1250e-04\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0175 - lr: 3.1250e-04\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0123 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0161 - lr: 3.1250e-04\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0157 - lr: 3.1250e-04\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0149 - lr: 3.1250e-04\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0148 - lr: 3.1250e-04\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0156 - lr: 3.1250e-04\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0120 - val_loss: 0.0130 - lr: 1.5625e-04\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0121 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0120 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0121 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0130 - lr: 1.5625e-04\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0121 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0120 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0120 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0120 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0121 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0121 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0123 - lr: 1.5625e-04\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0130 - lr: 1.5625e-04\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0120 - val_loss: 0.0130 - lr: 1.5625e-04\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0119 - val_loss: 0.0130 - lr: 1.5625e-04\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0125 - lr: 1.5625e-04\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0116 - val_loss: 0.0121 - lr: 1.5625e-04\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0116 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0125 - lr: 1.5625e-04\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0121 - lr: 1.5625e-04\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0120 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0125 - lr: 1.5625e-04\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0116 - val_loss: 0.0123 - lr: 1.5625e-04\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0117 - val_loss: 0.0125 - lr: 1.5625e-04\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0116 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0125 - lr: 1.5625e-04\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0125 - lr: 1.5625e-04\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0121 - lr: 1.5625e-04\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0116 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0114 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0114 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0114 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0116 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0114 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0115 - val_loss: 0.0121 - lr: 1.5625e-04\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0114 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0114 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 298/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 299/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 300/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0121 - lr: 1.5625e-04\n", + "Epoch 301/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0112 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 302/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0112 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0112 - val_loss: 0.0123 - lr: 1.5625e-04\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0123 - lr: 1.5625e-04\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0112 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0112 - val_loss: 0.0117 - lr: 1.5625e-04\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0110 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0111 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0111 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 312/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 313/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0111 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 314/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0119 - lr: 1.5625e-04\n", + "Epoch 315/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0119 - lr: 1.5625e-04\n", + "Epoch 316/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0109 - val_loss: 0.0119 - lr: 1.5625e-04\n", + "Epoch 317/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0111 - val_loss: 0.0115 - lr: 1.5625e-04\n", + "Epoch 318/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0114 - lr: 1.5625e-04\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0123 - lr: 1.5625e-04\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0114 - lr: 1.5625e-04\n", + "Epoch 324/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 326/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 327/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 328/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0113 - lr: 1.5625e-04\n", + "Epoch 329/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0115 - lr: 1.5625e-04\n", + "Epoch 330/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 331/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0124 - lr: 1.5625e-04\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0123 - lr: 1.5625e-04\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0113 - lr: 1.5625e-04\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0107 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0115 - lr: 1.5625e-04\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0109 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 339/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 340/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0108 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 341/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 342/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 343/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0114 - lr: 1.5625e-04\n", + "Epoch 344/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 345/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0107 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 346/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0111 - lr: 1.5625e-04\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0113 - lr: 1.5625e-04\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0105 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0106 - val_loss: 0.0109 - lr: 1.5625e-04\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0108 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 354/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 355/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 356/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 357/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 358/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0111 - lr: 1.5625e-04\n", + "Epoch 359/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 360/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 361/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 362/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0113 - lr: 1.5625e-04\n", + "Epoch 363/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0109 - lr: 1.5625e-04\n", + "Epoch 364/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0104 - val_loss: 0.0106 - lr: 1.5625e-04\n", + "Epoch 365/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 366/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 367/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0105 - val_loss: 0.0106 - lr: 1.5625e-04\n", + "Epoch 368/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0106 - lr: 1.5625e-04\n", + "Epoch 369/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 370/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 371/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0109 - lr: 1.5625e-04\n", + "Epoch 372/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0111 - lr: 1.5625e-04\n", + "Epoch 373/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 374/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0114 - lr: 1.5625e-04\n", + "Epoch 375/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0113 - lr: 1.5625e-04\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0123 - lr: 1.5625e-04\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0114 - lr: 1.5625e-04\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0105 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0109 - lr: 1.5625e-04\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 385/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 386/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 387/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0112 - lr: 1.5625e-04\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0103 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0106 - lr: 1.5625e-04\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0109 - lr: 1.5625e-04\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0109 - lr: 1.5625e-04\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0114 - lr: 1.5625e-04\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0104 - lr: 1.5625e-04\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0111 - lr: 1.5625e-04\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0111 - lr: 1.5625e-04\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0108 - lr: 1.5625e-04\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0105 - lr: 1.5625e-04\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0103 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0103 - lr: 7.8125e-05\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0103 - lr: 7.8125e-05\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0103 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0103 - lr: 7.8125e-05\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 432/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 433/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 434/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 435/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 436/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 437/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 442/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 443/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 444/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 445/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 446/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 447/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 448/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 449/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 450/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 451/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 458/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 459/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 460/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0101 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 461/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 462/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 463/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 464/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 7.8125e-05\n", + "Epoch 465/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 466/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 467/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 474/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 475/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 476/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 477/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 478/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 479/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 480/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 481/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 482/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 485/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 486/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 487/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 489/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 490/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 491/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 492/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 493/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 494/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 495/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 496/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 504/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 505/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 506/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 507/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 508/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 509/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 510/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 511/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 520/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 521/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 522/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 523/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 524/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 525/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 526/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 536/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 537/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 538/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 539/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 540/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 541/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 550/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 551/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 552/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 565/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 566/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 567/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 568/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 569/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 570/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 571/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 579/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 580/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 581/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 582/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 583/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 584/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 585/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 586/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 587/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 588/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 589/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 590/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 591/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 592/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 593/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 594/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 595/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 596/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 597/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 598/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 599/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 600/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 601/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 602/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 603/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 604/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 605/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 606/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 607/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 608/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 609/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 610/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 611/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 612/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 613/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 614/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 615/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 616/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 617/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 618/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 619/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 620/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 621/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 622/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 623/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 624/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 625/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 626/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 627/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 628/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 629/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 630/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 631/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 632/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 633/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 634/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 635/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 636/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 637/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 638/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 639/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 640/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 641/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 642/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 643/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 644/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 645/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 646/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 647/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 648/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 649/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 650/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 651/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 652/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 653/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 654/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 655/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 656/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 657/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 658/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 659/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 660/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 661/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 662/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 663/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0095 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 664/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 665/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 666/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 667/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 668/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 669/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 670/1024\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 711/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 712/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 713/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 714/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 715/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 716/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 717/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 718/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 719/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 720/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 721/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0092 - lr: 7.8125e-05\n", + "Epoch 722/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 723/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 724/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 725/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 726/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 727/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 728/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 729/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 730/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 731/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 732/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 733/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 734/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 735/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 736/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 737/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 738/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 739/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 740/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 741/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 742/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 743/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 744/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 745/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 746/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 747/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 748/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 749/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 750/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 751/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 752/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 753/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 754/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 755/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 756/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 757/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 758/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 759/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 760/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 761/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 762/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 763/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 764/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 765/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 766/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 767/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 768/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 769/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 770/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 771/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 772/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 773/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 774/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 775/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 776/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 777/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 778/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 779/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0090 - lr: 7.8125e-05\n", + "Epoch 780/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0089 - lr: 7.8125e-05\n", + "Epoch 781/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 782/1024\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0088 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 823/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 824/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 825/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 826/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 827/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 828/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 829/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 830/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 831/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 832/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 833/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 834/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 835/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 836/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 837/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 838/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 839/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 840/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 841/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 842/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 843/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 844/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 845/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 846/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 847/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 848/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 849/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 850/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 851/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 852/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 853/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 854/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 855/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 856/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 857/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 858/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 859/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 860/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 861/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 862/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 863/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 864/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 865/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 866/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 867/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 868/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 869/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 870/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 871/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 872/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 873/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 874/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 875/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 876/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 877/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 878/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 879/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 880/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 881/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 882/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 883/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 884/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 885/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 886/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 887/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 888/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 889/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 890/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 891/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 892/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 893/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 894/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 895/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 896/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 897/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 898/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 899/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 900/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 901/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 902/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 903/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 904/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 905/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 906/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 907/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 908/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 909/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 910/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0086 - lr: 7.8125e-05\n", + "Epoch 911/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 912/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 913/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 914/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 915/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 916/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 917/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 918/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 919/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 920/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 921/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 922/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 923/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 924/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 925/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 926/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 927/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 928/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 929/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 930/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 931/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 932/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 933/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 934/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 935/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 936/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 937/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 938/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 939/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 940/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 941/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 942/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 943/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 944/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 945/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0088 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 946/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 947/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 948/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 949/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 950/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0088 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 951/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 952/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 953/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 954/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 955/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 956/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 957/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 958/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 959/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 960/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 961/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 962/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 963/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 964/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 965/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 966/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 967/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 968/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 969/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 970/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 971/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 972/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 973/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 974/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 975/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 976/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 977/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 978/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 979/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 980/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 981/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 982/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 983/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 984/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 985/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 986/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 987/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 988/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 989/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 990/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 991/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 992/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 993/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 994/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 995/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 996/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 997/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 998/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 999/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1000/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0083 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 1001/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1002/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1003/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1004/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1005/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1006/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0082 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1007/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0083 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1008/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1009/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1010/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1011/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1012/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0082 - lr: 7.8125e-05\n", + "Epoch 1013/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 1014/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1015/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0082 - lr: 7.8125e-05\n", + "Epoch 1016/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1017/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1018/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0083 - lr: 7.8125e-05\n", + "Epoch 1019/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0086 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 1020/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0082 - lr: 7.8125e-05\n", + "Epoch 1021/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0084 - val_loss: 0.0082 - lr: 7.8125e-05\n", + "Epoch 1022/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0082 - lr: 7.8125e-05\n", + "Epoch 1023/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0085 - val_loss: 0.0082 - lr: 7.8125e-05\n", + "Epoch 1024/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0085 - val_loss: 0.0082 - lr: 7.8125e-05\n" + ] + } + ], + "source": [ + "epoch, batch_size = 1024, 64\n", + "history_plain_11 = plain_11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)\n", + "history_plain_5 = plain_5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Save the result to history.p" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# import pickle\n", + "# with open('history.p', 'wb') as f:\n", + "# pickle.dump({'history_11': history_plain_11, 'history_5':history_plain_5}, f)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Post analysis and drawing" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# with open(\"history.p\", 'rb') as f:\n", + "# data = pickle.load(f)\n", + "# history_plain_11, history_plain_5 = data['history_11'], data['history_5']" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "smoothing_windows = 16\n", + "def moving_average(x, w):\n", + " return np.convolve(x, np.ones(w), 'valid') / w" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain11', c='b')\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_plain_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain5', c='r')\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, min(len(history_plain_5.history['loss']), len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.set_ylim(0.8,2)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (540, 0.267), c='b')\n", + "ax.annotate(\"5-layer\", (540, 0.245), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# plt.savefig(fname=\"fig1.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "seed(1224)\n", + "tensorflow.random.set_seed(1224)\n", + "shortcut5, shortcut11 = ShortCut5(input_shape=(1, 102)), ShortCut11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/1024\n", + "90/90 [==============================] - 2s 9ms/step - loss: 0.0234 - val_loss: 0.0264 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0221 - val_loss: 0.0265 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0217 - val_loss: 0.0267 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0213 - val_loss: 0.0267 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0210 - val_loss: 0.0286 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0203 - val_loss: 0.0291 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0259 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0198 - val_loss: 0.0240 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0279 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0257 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0187 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0187 - val_loss: 0.0233 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0185 - val_loss: 0.0277 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0299 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0492 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0330 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0252 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0240 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0170 - val_loss: 0.0260 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0169 - val_loss: 0.0438 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0168 - val_loss: 0.0375 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0249 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0282 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0307 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0161 - val_loss: 0.0595 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0159 - val_loss: 0.0214 - lr: 0.0025\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0159 - val_loss: 0.0588 - lr: 0.0025\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0157 - val_loss: 0.0253 - lr: 0.0025\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0156 - val_loss: 0.0391 - lr: 0.0025\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0155 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0151 - val_loss: 0.0366 - lr: 0.0025\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0150 - val_loss: 0.0188 - lr: 0.0025\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0148 - val_loss: 0.0293 - lr: 0.0025\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0144 - val_loss: 0.0214 - lr: 0.0025\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0144 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0143 - val_loss: 0.0315 - lr: 0.0025\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0141 - val_loss: 0.0308 - lr: 0.0025\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0139 - val_loss: 0.0298 - lr: 0.0025\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0135 - val_loss: 0.0297 - lr: 0.0025\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0139 - val_loss: 0.0337 - lr: 0.0025\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0135 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0498 - lr: 0.0025\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0131 - val_loss: 0.0396 - lr: 0.0025\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0243 - lr: 0.0025\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 2ms/step - 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[==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0162 - lr: 0.0025\n", + "Epoch 55/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0747 - lr: 0.0025\n", + "Epoch 56/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0674 - lr: 0.0025\n", + "Epoch 57/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0341 - lr: 0.0025\n", + "Epoch 58/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0110 - val_loss: 0.0612 - lr: 0.0025\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0108 - val_loss: 0.1348 - lr: 0.0025\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0107 - val_loss: 0.0324 - lr: 0.0025\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0647 - lr: 0.0025\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0628 - lr: 0.0025\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0828 - lr: 0.0025\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0971 - lr: 0.0025\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0105 - val_loss: 0.0473 - lr: 0.0025\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0102 - val_loss: 0.0844 - lr: 0.0025\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0405 - lr: 0.0025\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0100 - val_loss: 0.0906 - lr: 0.0025\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0245 - lr: 0.0025\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0099 - val_loss: 0.0127 - lr: 0.0025\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0829 - lr: 0.0025\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0698 - lr: 0.0025\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0871 - lr: 0.0025\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0557 - lr: 0.0025\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0183 - lr: 0.0025\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0236 - lr: 0.0025\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0955 - lr: 0.0025\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0355 - lr: 0.0025\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0502 - lr: 0.0025\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0448 - lr: 0.0025\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0203 - lr: 0.0025\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0661 - lr: 0.0025\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0755 - lr: 0.0025\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0090 - val_loss: 0.0278 - lr: 0.0025\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0280 - lr: 0.0025\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0301 - lr: 0.0025\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0327 - lr: 0.0025\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0626 - lr: 0.0025\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0087 - val_loss: 0.0255 - lr: 0.0025\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0084 - val_loss: 0.0485 - lr: 0.0025\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0158 - lr: 0.0025\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0084 - val_loss: 0.0256 - lr: 0.0025\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0087 - val_loss: 0.0529 - lr: 0.0025\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0581 - lr: 0.0025\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0082 - val_loss: 0.0286 - lr: 0.0012\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0086 - val_loss: 0.0265 - lr: 0.0012\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0085 - val_loss: 0.0107 - lr: 0.0012\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0082 - val_loss: 0.0139 - lr: 0.0012\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0082 - val_loss: 0.0150 - lr: 0.0012\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0084 - val_loss: 0.0304 - lr: 0.0012\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0083 - val_loss: 0.0368 - lr: 0.0012\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0084 - val_loss: 0.0137 - lr: 0.0012\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0083 - val_loss: 0.0221 - lr: 0.0012\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0391 - lr: 0.0012\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0084 - val_loss: 0.0156 - lr: 0.0012\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0082 - val_loss: 0.0169 - lr: 0.0012\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0082 - val_loss: 0.0411 - lr: 0.0012\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0081 - val_loss: 0.0292 - lr: 0.0012\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0080 - val_loss: 0.0116 - lr: 0.0012\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0330 - lr: 0.0012\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0081 - val_loss: 0.0092 - lr: 0.0012\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0096 - lr: 0.0012\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0080 - val_loss: 0.0123 - lr: 0.0012\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0081 - val_loss: 0.0170 - lr: 0.0012\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0081 - val_loss: 0.0686 - lr: 0.0012\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0359 - lr: 0.0012\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0444 - lr: 0.0012\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0080 - val_loss: 0.0231 - lr: 0.0012\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0107 - lr: 0.0012\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0077 - val_loss: 0.0249 - lr: 0.0012\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0710 - lr: 0.0012\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0079 - val_loss: 0.0138 - lr: 0.0012\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0078 - val_loss: 0.0367 - lr: 0.0012\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0075 - val_loss: 0.0243 - lr: 0.0012\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0078 - val_loss: 0.0462 - lr: 0.0012\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0078 - val_loss: 0.0082 - lr: 0.0012\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0078 - val_loss: 0.0407 - lr: 0.0012\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0078 - val_loss: 0.0120 - lr: 0.0012\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0077 - val_loss: 0.0120 - lr: 0.0012\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0077 - val_loss: 0.0148 - lr: 0.0012\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0077 - val_loss: 0.0303 - lr: 0.0012\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0078 - val_loss: 0.0082 - lr: 0.0012\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0076 - val_loss: 0.0888 - lr: 0.0012\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0077 - val_loss: 0.0507 - lr: 0.0012\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0077 - val_loss: 0.0260 - lr: 0.0012\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0077 - val_loss: 0.0459 - lr: 0.0012\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0075 - val_loss: 0.0400 - lr: 0.0012\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0075 - val_loss: 0.0550 - lr: 0.0012\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0075 - val_loss: 0.0169 - lr: 0.0012\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0076 - val_loss: 0.0104 - lr: 0.0012\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0075 - val_loss: 0.0091 - lr: 0.0012\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0074 - val_loss: 0.0291 - lr: 0.0012\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0076 - val_loss: 0.0271 - lr: 0.0012\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0076 - val_loss: 0.0442 - lr: 0.0012\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0466 - lr: 0.0012\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0077 - val_loss: 0.0784 - lr: 0.0012\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0076 - val_loss: 0.0350 - lr: 0.0012\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0194 - lr: 0.0012\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0104 - lr: 0.0012\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0511 - lr: 0.0012\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0074 - val_loss: 0.0144 - lr: 0.0012\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0125 - lr: 6.2500e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0077 - lr: 6.2500e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0075 - val_loss: 0.0230 - lr: 6.2500e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0074 - val_loss: 0.0086 - lr: 6.2500e-04\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0075 - val_loss: 0.0443 - lr: 6.2500e-04\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0255 - lr: 6.2500e-04\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0096 - lr: 6.2500e-04\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0199 - lr: 6.2500e-04\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0082 - lr: 6.2500e-04\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0092 - lr: 6.2500e-04\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0210 - lr: 6.2500e-04\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0111 - lr: 6.2500e-04\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0071 - lr: 6.2500e-04\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0196 - lr: 6.2500e-04\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0299 - lr: 6.2500e-04\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0155 - lr: 6.2500e-04\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0255 - lr: 6.2500e-04\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0083 - lr: 6.2500e-04\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0092 - lr: 6.2500e-04\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0292 - lr: 6.2500e-04\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0138 - lr: 6.2500e-04\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0103 - lr: 6.2500e-04\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0084 - lr: 6.2500e-04\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0236 - lr: 6.2500e-04\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0072 - lr: 6.2500e-04\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0073 - lr: 6.2500e-04\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0075 - lr: 6.2500e-04\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0387 - lr: 6.2500e-04\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0096 - lr: 6.2500e-04\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0139 - lr: 6.2500e-04\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0092 - lr: 6.2500e-04\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0080 - lr: 6.2500e-04\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0279 - lr: 6.2500e-04\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0167 - lr: 6.2500e-04\n", + "Epoch 191/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0143 - lr: 6.2500e-04\n", + "Epoch 192/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0074 - lr: 6.2500e-04\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0071 - lr: 3.1250e-04\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0089 - lr: 3.1250e-04\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0147 - lr: 3.1250e-04\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0081 - lr: 3.1250e-04\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0072 - val_loss: 0.0071 - lr: 3.1250e-04\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0095 - lr: 3.1250e-04\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0071 - lr: 3.1250e-04\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0079 - lr: 3.1250e-04\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0080 - lr: 3.1250e-04\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0077 - lr: 3.1250e-04\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0135 - lr: 3.1250e-04\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0094 - lr: 3.1250e-04\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0071 - lr: 3.1250e-04\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.1250e-04\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0089 - lr: 3.1250e-04\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0073 - lr: 3.1250e-04\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0092 - lr: 3.1250e-04\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0088 - lr: 3.1250e-04\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0122 - lr: 3.1250e-04\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0075 - lr: 3.1250e-04\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0070 - lr: 3.1250e-04\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0074 - lr: 3.1250e-04\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0119 - lr: 3.1250e-04\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 3.1250e-04\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0073 - lr: 3.1250e-04\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 3.1250e-04\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0073 - lr: 3.1250e-04\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 3.1250e-04\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0087 - lr: 3.1250e-04\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0160 - lr: 3.1250e-04\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 3.1250e-04\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0112 - lr: 3.1250e-04\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0071 - lr: 3.1250e-04\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0110 - lr: 3.1250e-04\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 3.1250e-04\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 1.5625e-04\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5625e-04\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0071 - lr: 1.5625e-04\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0071 - lr: 1.5625e-04\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0070 - lr: 1.5625e-04\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0070 - lr: 1.5625e-04\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5625e-04\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0079 - lr: 1.5625e-04\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0071 - lr: 1.5625e-04\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0073 - lr: 1.5625e-04\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0073 - lr: 1.5625e-04\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0075 - lr: 1.5625e-04\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0071 - lr: 1.5625e-04\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0070 - lr: 1.5625e-04\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0073 - lr: 1.5625e-04\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0077 - lr: 1.5625e-04\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0074 - lr: 1.5625e-04\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0084 - lr: 1.5625e-04\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0072 - lr: 1.5625e-04\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5625e-04\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0073 - lr: 1.5625e-04\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0072 - lr: 1.5625e-04\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0074 - lr: 1.5625e-04\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5625e-04\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0073 - lr: 7.8125e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0071 - lr: 7.8125e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0072 - lr: 7.8125e-05\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0075 - lr: 7.8125e-05\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0072 - lr: 7.8125e-05\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0071 - lr: 7.8125e-05\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0076 - lr: 7.8125e-05\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0071 - lr: 7.8125e-05\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0075 - lr: 7.8125e-05\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0071 - lr: 7.8125e-05\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0070 - lr: 3.9062e-05\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0070 - lr: 3.9062e-05\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0070 - lr: 3.9062e-05\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 298/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 299/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 300/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 301/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 302/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0071 - lr: 3.9062e-05\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0072 - lr: 3.9062e-05\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 312/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 313/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 314/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 315/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 316/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 317/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 318/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0070 - lr: 3.9062e-05\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 324/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 326/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 327/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 328/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 329/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 330/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 331/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0070 - lr: 3.9062e-05\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 339/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 340/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 341/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 342/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 343/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 344/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 345/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 346/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 354/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 355/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 356/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 357/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 358/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 359/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 360/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 361/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 362/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 363/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 364/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 365/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 366/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 367/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 368/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 369/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 370/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 371/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 372/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 373/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 374/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 375/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 385/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 386/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 387/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 432/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 433/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 434/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 435/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 436/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 437/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 9.7656e-06\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 442/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 443/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 444/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 445/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 446/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 447/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 448/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 449/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 450/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 451/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0073 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 458/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 459/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 460/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 461/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 462/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 463/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 464/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 465/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 466/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 467/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 4.8828e-06\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 474/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 475/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 476/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 477/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 478/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 479/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 480/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 481/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 482/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 485/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 486/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 487/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 489/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 490/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 491/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 492/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 493/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 494/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 495/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 496/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 2.4414e-06\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 504/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 505/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 506/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 507/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 508/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 509/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 510/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 511/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 520/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 521/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 522/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.2207e-06\n", + "Epoch 523/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 524/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 525/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 526/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 536/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 537/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 538/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 539/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 540/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 541/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 6.1035e-07\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 550/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 551/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 552/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 565/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 566/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 567/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 568/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 569/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 570/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 571/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.0518e-07\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 579/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 580/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 581/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 582/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 583/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 584/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 585/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 586/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 587/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 588/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 589/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0067 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 590/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 591/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 592/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 593/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 594/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 595/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 596/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 597/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 1.5259e-07\n", + "Epoch 598/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 599/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 600/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 601/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 602/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 603/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 604/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 605/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 606/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 607/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 608/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 609/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 610/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 611/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 612/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 613/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 614/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 615/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 616/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 617/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 618/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 619/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 620/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 621/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 622/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 7.6294e-08\n", + "Epoch 623/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 624/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 625/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 626/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 627/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 628/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 629/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 630/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 631/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 632/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 633/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 634/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 635/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 636/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 637/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0068 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 638/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 639/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 640/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 641/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 642/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 643/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0069 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 644/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 645/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0070 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 646/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 647/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0071 - val_loss: 0.0069 - lr: 3.8147e-08\n", + "Epoch 1/1024\n", + "90/90 [==============================] - 1s 4ms/step - loss: 0.0316 - val_loss: 0.0274 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0251 - val_loss: 0.0276 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0231 - val_loss: 0.0278 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0225 - val_loss: 0.0269 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0220 - val_loss: 0.0255 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0217 - val_loss: 0.0248 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0214 - val_loss: 0.0248 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0214 - val_loss: 0.0253 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0213 - val_loss: 0.0250 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0211 - val_loss: 0.0253 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0209 - val_loss: 0.0245 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0206 - val_loss: 0.0233 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0205 - val_loss: 0.0217 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0205 - val_loss: 0.0218 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0205 - val_loss: 0.0221 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0204 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0203 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0204 - val_loss: 0.0214 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0201 - val_loss: 0.0276 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0202 - val_loss: 0.0207 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0201 - val_loss: 0.0236 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0200 - val_loss: 0.0214 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0199 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0199 - val_loss: 0.0235 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0197 - val_loss: 0.0205 - lr: 0.0025\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0198 - val_loss: 0.0223 - lr: 0.0025\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0209 - lr: 0.0025\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0197 - val_loss: 0.0212 - lr: 0.0025\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0197 - val_loss: 0.0392 - lr: 0.0025\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0203 - lr: 0.0025\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0245 - lr: 0.0025\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0195 - val_loss: 0.0205 - lr: 0.0025\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0194 - val_loss: 0.0284 - lr: 0.0025\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0194 - val_loss: 0.0242 - lr: 0.0025\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0025\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0194 - val_loss: 0.0218 - lr: 0.0025\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0193 - val_loss: 0.0198 - lr: 0.0025\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0194 - val_loss: 0.0222 - lr: 0.0025\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0193 - val_loss: 0.0211 - lr: 0.0025\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0193 - val_loss: 0.0206 - lr: 0.0025\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0192 - val_loss: 0.0208 - lr: 0.0025\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0352 - lr: 0.0025\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0204 - lr: 0.0025\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0025\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0192 - val_loss: 0.0260 - lr: 0.0025\n", + "Epoch 49/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0271 - lr: 0.0025\n", + "Epoch 50/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0258 - lr: 0.0025\n", + "Epoch 51/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0213 - lr: 0.0025\n", + "Epoch 52/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0272 - lr: 0.0025\n", + "Epoch 53/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0187 - val_loss: 0.0257 - lr: 0.0025\n", + "Epoch 54/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0255 - lr: 0.0025\n", + "Epoch 55/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0189 - val_loss: 0.0210 - lr: 0.0025\n", + "Epoch 56/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0270 - lr: 0.0025\n", + "Epoch 57/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0271 - lr: 0.0025\n", + "Epoch 58/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0187 - val_loss: 0.0226 - lr: 0.0025\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0187 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0186 - val_loss: 0.0266 - lr: 0.0025\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0186 - val_loss: 0.0271 - lr: 0.0025\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0336 - lr: 0.0025\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0247 - lr: 0.0025\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0222 - lr: 0.0025\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0257 - lr: 0.0025\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0218 - lr: 0.0012\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0196 - lr: 0.0012\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0196 - lr: 0.0012\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0180 - val_loss: 0.0215 - lr: 0.0012\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0181 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0191 - lr: 0.0012\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0209 - lr: 0.0012\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0201 - lr: 0.0012\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0202 - lr: 0.0012\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0196 - lr: 0.0012\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0195 - lr: 0.0012\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0210 - lr: 0.0012\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0179 - val_loss: 0.0195 - lr: 0.0012\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0181 - val_loss: 0.0211 - lr: 0.0012\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0179 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0179 - val_loss: 0.0194 - lr: 0.0012\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0201 - lr: 0.0012\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0192 - lr: 0.0012\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0179 - val_loss: 0.0193 - lr: 0.0012\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0199 - lr: 0.0012\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0194 - lr: 0.0012\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0192 - lr: 0.0012\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0196 - lr: 0.0012\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0177 - val_loss: 0.0206 - lr: 0.0012\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0218 - lr: 0.0012\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0177 - val_loss: 0.0204 - lr: 0.0012\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0177 - val_loss: 0.0206 - lr: 0.0012\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0177 - val_loss: 0.0205 - lr: 0.0012\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0211 - lr: 0.0012\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0206 - lr: 0.0012\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0200 - lr: 0.0012\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0200 - lr: 0.0012\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0204 - lr: 0.0012\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0182 - lr: 0.0012\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0196 - lr: 0.0012\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0189 - lr: 0.0012\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0205 - lr: 0.0012\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0190 - lr: 0.0012\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0177 - lr: 0.0012\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0177 - lr: 0.0012\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0199 - lr: 0.0012\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0189 - lr: 0.0012\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0175 - lr: 0.0012\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0194 - lr: 0.0012\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0211 - lr: 0.0012\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0195 - lr: 0.0012\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0193 - lr: 0.0012\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0177 - lr: 0.0012\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0179 - lr: 0.0012\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0191 - lr: 0.0012\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0224 - lr: 0.0012\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0181 - lr: 0.0012\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0178 - lr: 0.0012\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0220 - lr: 0.0012\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0177 - lr: 0.0012\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0182 - lr: 0.0012\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0171 - lr: 0.0012\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0169 - lr: 0.0012\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0174 - lr: 0.0012\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0176 - lr: 0.0012\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0180 - lr: 0.0012\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0159 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0190 - lr: 0.0012\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0192 - lr: 0.0012\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0168 - lr: 0.0012\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0182 - lr: 0.0012\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0154 - val_loss: 0.0166 - lr: 0.0012\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0164 - lr: 0.0012\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 0.0012\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0163 - lr: 0.0012\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0218 - lr: 0.0012\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0192 - lr: 0.0012\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0168 - lr: 0.0012\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0174 - lr: 0.0012\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0165 - lr: 0.0012\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0178 - lr: 0.0012\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0180 - lr: 0.0012\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0170 - lr: 0.0012\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0143 - val_loss: 0.0169 - lr: 0.0012\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0143 - val_loss: 0.0237 - lr: 0.0012\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.0171 - lr: 0.0012\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0143 - val_loss: 0.0200 - lr: 0.0012\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.0222 - lr: 0.0012\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0181 - lr: 0.0012\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0221 - lr: 0.0012\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0263 - lr: 0.0012\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0205 - lr: 0.0012\n", + "Epoch 181/1024\n", + "90/90 [==============================] 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- loss: 0.0080 - val_loss: 0.0081 - lr: 6.2500e-04\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0078 - val_loss: 0.0096 - lr: 6.2500e-04\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0080 - val_loss: 0.0091 - lr: 6.2500e-04\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0078 - val_loss: 0.0102 - lr: 6.2500e-04\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0079 - val_loss: 0.0084 - lr: 6.2500e-04\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0078 - val_loss: 0.0107 - lr: 6.2500e-04\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0077 - val_loss: 0.0080 - lr: 6.2500e-04\n", + "Epoch 458/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0078 - val_loss: 0.0170 - lr: 6.2500e-04\n", + "Epoch 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- loss: 0.0075 - val_loss: 0.0081 - lr: 6.2500e-04\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0074 - val_loss: 0.0083 - lr: 6.2500e-04\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0077 - lr: 6.2500e-04\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0074 - val_loss: 0.0083 - lr: 6.2500e-04\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0080 - lr: 6.2500e-04\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0074 - lr: 6.2500e-04\n", + "Epoch 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- loss: 0.0074 - val_loss: 0.0080 - lr: 6.2500e-04\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0083 - lr: 6.2500e-04\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0076 - lr: 6.2500e-04\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0076 - lr: 6.2500e-04\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0085 - lr: 6.2500e-04\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0080 - lr: 6.2500e-04\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0084 - lr: 6.2500e-04\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0074 - val_loss: 0.0091 - lr: 6.2500e-04\n", + "Epoch 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- loss: 0.0074 - val_loss: 0.0094 - lr: 6.2500e-04\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0073 - val_loss: 0.0093 - lr: 6.2500e-04\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0071 - lr: 6.2500e-04\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0146 - lr: 6.2500e-04\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0102 - lr: 6.2500e-04\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0074 - lr: 6.2500e-04\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0089 - lr: 6.2500e-04\n", + "Epoch 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- loss: 0.0071 - val_loss: 0.0095 - lr: 6.2500e-04\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0073 - lr: 6.2500e-04\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0072 - lr: 6.2500e-04\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0071 - lr: 6.2500e-04\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0086 - lr: 6.2500e-04\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0070 - val_loss: 0.0071 - lr: 6.2500e-04\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0083 - lr: 6.2500e-04\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0072 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 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- loss: 0.0069 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0107 - lr: 6.2500e-04\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0070 - val_loss: 0.0078 - lr: 6.2500e-04\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0103 - lr: 6.2500e-04\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0084 - lr: 6.2500e-04\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0071 - val_loss: 0.0075 - lr: 6.2500e-04\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0072 - lr: 6.2500e-04\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0088 - lr: 6.2500e-04\n", + "Epoch 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- loss: 0.0069 - val_loss: 0.0070 - lr: 6.2500e-04\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0072 - lr: 6.2500e-04\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0078 - lr: 6.2500e-04\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0087 - lr: 6.2500e-04\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0098 - lr: 6.2500e-04\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0082 - lr: 6.2500e-04\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0074 - lr: 6.2500e-04\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0081 - lr: 6.2500e-04\n", + "Epoch 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- loss: 0.0068 - val_loss: 0.0080 - lr: 6.2500e-04\n", + "Epoch 587/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0074 - lr: 6.2500e-04\n", + "Epoch 588/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0073 - lr: 6.2500e-04\n", + "Epoch 589/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0076 - lr: 6.2500e-04\n", + "Epoch 590/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0068 - val_loss: 0.0073 - lr: 6.2500e-04\n", + "Epoch 591/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0069 - val_loss: 0.0074 - lr: 3.1250e-04\n", + "Epoch 592/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0067 - val_loss: 0.0072 - lr: 3.1250e-04\n", + "Epoch 593/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0067 - val_loss: 0.0076 - lr: 3.1250e-04\n", + "Epoch 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- loss: 0.0067 - val_loss: 0.0065 - lr: 3.1250e-04\n", + "Epoch 662/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0069 - lr: 3.1250e-04\n", + "Epoch 663/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 664/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0068 - lr: 3.1250e-04\n", + "Epoch 665/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0076 - lr: 3.1250e-04\n", + "Epoch 666/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0067 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 667/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0067 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 668/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0067 - lr: 3.1250e-04\n", + "Epoch 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- loss: 0.0066 - val_loss: 0.0067 - lr: 3.1250e-04\n", + "Epoch 677/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0068 - lr: 3.1250e-04\n", + "Epoch 678/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0072 - lr: 3.1250e-04\n", + "Epoch 679/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0072 - lr: 3.1250e-04\n", + "Epoch 680/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0074 - lr: 3.1250e-04\n", + "Epoch 681/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0069 - lr: 3.1250e-04\n", + "Epoch 682/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0084 - lr: 3.1250e-04\n", + "Epoch 683/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 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- loss: 0.0066 - val_loss: 0.0069 - lr: 3.1250e-04\n", + "Epoch 692/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0067 - val_loss: 0.0067 - lr: 3.1250e-04\n", + "Epoch 693/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 694/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0067 - lr: 3.1250e-04\n", + "Epoch 695/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0071 - lr: 3.1250e-04\n", + "Epoch 696/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 697/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0068 - lr: 3.1250e-04\n", + "Epoch 698/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0090 - lr: 3.1250e-04\n", + "Epoch 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- loss: 0.0065 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 707/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0068 - lr: 3.1250e-04\n", + "Epoch 708/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0065 - val_loss: 0.0078 - lr: 3.1250e-04\n", + "Epoch 709/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0068 - lr: 3.1250e-04\n", + "Epoch 710/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0068 - lr: 3.1250e-04\n", + "Epoch 711/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0071 - lr: 3.1250e-04\n", + "Epoch 712/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0067 - val_loss: 0.0064 - lr: 3.1250e-04\n", + "Epoch 713/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0066 - lr: 3.1250e-04\n", + "Epoch 714/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0074 - lr: 3.1250e-04\n", + "Epoch 715/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0067 - lr: 3.1250e-04\n", + "Epoch 716/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0075 - lr: 3.1250e-04\n", + "Epoch 717/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0065 - lr: 3.1250e-04\n", + "Epoch 718/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0064 - lr: 3.1250e-04\n", + "Epoch 719/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0064 - lr: 3.1250e-04\n", + "Epoch 720/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0068 - lr: 3.1250e-04\n", + "Epoch 721/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0064 - lr: 3.1250e-04\n", + "Epoch 722/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0064 - lr: 3.1250e-04\n", + "Epoch 723/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0073 - lr: 3.1250e-04\n", + "Epoch 724/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0069 - lr: 3.1250e-04\n", + "Epoch 725/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0078 - lr: 3.1250e-04\n", + "Epoch 726/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0069 - lr: 3.1250e-04\n", + "Epoch 727/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0070 - lr: 3.1250e-04\n", + "Epoch 728/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0064 - lr: 3.1250e-04\n", + "Epoch 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- loss: 0.0064 - val_loss: 0.0064 - lr: 1.5625e-04\n", + "Epoch 782/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0064 - lr: 1.5625e-04\n", + "Epoch 783/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0064 - lr: 1.5625e-04\n", + "Epoch 784/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0064 - lr: 1.5625e-04\n", + "Epoch 785/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 1.5625e-04\n", + "Epoch 786/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0066 - lr: 1.5625e-04\n", + "Epoch 787/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 1.5625e-04\n", + "Epoch 788/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0064 - lr: 1.5625e-04\n", + "Epoch 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- loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 797/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 798/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 799/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 800/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 801/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 802/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 803/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 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- loss: 0.0065 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 812/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 813/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 814/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0066 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 815/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 816/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 817/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 818/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 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- loss: 0.0065 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 827/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 828/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 829/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 830/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 831/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 832/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 833/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 834/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 835/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 836/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 837/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 838/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 839/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 840/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 841/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 842/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 843/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 844/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 845/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 846/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 847/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 848/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 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- loss: 0.0062 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 902/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 903/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 904/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 905/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 906/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 907/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0061 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 908/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 909/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 910/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 911/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 912/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 913/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 914/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 915/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 916/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 917/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 918/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 919/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 920/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 921/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 922/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 923/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 924/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 925/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 926/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 927/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 928/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 929/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 930/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 931/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 932/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 933/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 934/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 935/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 936/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 937/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 938/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 939/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 940/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 941/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 942/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 943/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 944/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 945/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 946/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 947/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 948/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0065 - lr: 7.8125e-05\n", + "Epoch 949/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 950/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0061 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 951/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 952/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0064 - lr: 7.8125e-05\n", + "Epoch 953/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 954/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0061 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 955/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 956/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 957/1024\n", + "90/90 [==============================] - 1s 13ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 958/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0061 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 959/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 960/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 961/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 962/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 963/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 964/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 965/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 3.9062e-05\n", + "Epoch 966/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 3.9062e-05\n", + "Epoch 967/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 968/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 969/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 970/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 971/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0065 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 972/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 973/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 974/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 975/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 976/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 977/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 978/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 979/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 980/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 981/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0063 - lr: 3.9062e-05\n", + "Epoch 982/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 983/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0063 - lr: 3.9062e-05\n", + "Epoch 984/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 985/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 986/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 987/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 988/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 989/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 990/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 991/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 992/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 993/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 994/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 995/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 996/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 997/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 998/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 999/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1000/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1001/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1002/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0061 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1003/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1004/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1005/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1006/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1007/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1008/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0061 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1009/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1010/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1011/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1012/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0061 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1013/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1014/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1015/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1016/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1017/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1018/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1019/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1020/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1021/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0063 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1022/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0062 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 1023/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0061 - val_loss: 0.0062 - lr: 9.7656e-06\n", + "Epoch 1024/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0064 - val_loss: 0.0062 - lr: 9.7656e-06\n" + ] + } + ], + "source": [ + "epoch, batch_size = 1024, 64\n", + "history_shortcut_11 = shortcut11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)\n", + "history_shortcut_5 = shortcut5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_shortcut_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN11', c='b')\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_shortcut_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN5', c='r')\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, min(len(history_shortcut_5.history['loss']), len(history_shortcut_11.history['loss']) - smoothing_windows + 1))\n", + "# ax.set_ylim(0.37, 1)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (500, 0.24), c='b')\n", + "ax.annotate(\"5-layer\", (500, 0.255), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# plt.savefig(fname=\"fig2.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import os\n", + "time_spent = (time.time() - time1) /60" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "19.09573165178299 min\n" + ] + } + ], + "source": [ + "print(time_spent, \"min\")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + } + ], + "metadata": { + "interpreter": { + "hash": "7f619fc91ee8bdab81d49e7c14228037474662e3f2d607687ae505108922fa06" + }, + "kernelspec": { + "display_name": "Python 3.9.7 64-bit ('base': conda)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} \ No newline at end of file diff --git a/02_model_training_nadam.ipynb b/02_model_training_nadam.ipynb new file mode 100755 index 0000000..e96dd68 --- /dev/null +++ b/02_model_training_nadam.ipynb @@ -0,0 +1,7256 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Model training Experiment" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "In order to provide the experimental evidence to back up the statement in the section 2.3.2 that our shortcut block can prevent degration problem.\n", + "\n", + "Plain Networks. We first evaluate 5-layer and 11-layer plain nets. Comparing to the 5-layer one, the 11-layer one has three times convolutional layers." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import pickle\n", + "import time\n", + "\n", + "import numpy as np\n", + "from matplotlib import ticker\n", + "from scipy.io import loadmat\n", + "from models import Plain5, Plain11, ShortCut5, ShortCut11\n", + "from sklearn.model_selection import train_test_split\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib notebook" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Load data\n", + "load data and split them into train, val, test" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape of data:\n", + "x_train: (5728, 1, 102), y_train: (5728, 1),\n", + "x_val: (2455, 1, 102), y_val: (2455, 1)\n", + "x_test: (3508, 1, 102), y_test: (3508, 1)\n" + ] + } + ], + "source": [ + "import random\n", + "from numpy.random import seed\n", + "import tensorflow\n", + "import time\n", + "seed(2750)\n", + "tensorflow.random.set_seed(2750)\n", + "time1 = time.time()\n", + "data = loadmat('dataset/mango/mango_dm_split.mat')\n", + "training_method = \"nadam\"\n", + "x_train, y_train, x_test, y_test = data['x_train'], data['y_train'], data['x_test'], data['y_test']\n", + "x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size=0.3, random_state=12, shuffle=True)\n", + "x_train, x_val, x_test = x_train[:, np.newaxis, :], x_val[:, np.newaxis, :], x_test[:, np.newaxis, :]\n", + "print(f\"shape of data:\\n\"\n", + " f\"x_train: {x_train.shape}, y_train: {y_train.shape},\\n\"\n", + " f\"x_val: {x_val.shape}, y_val: {y_val.shape}\\n\"\n", + " f\"x_test: {x_test.shape}, y_test: {y_test.shape}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Build Plain networks and Training" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "plain_5, plain_11 = Plain5(input_shape=(1, 102)), Plain11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-06-27 14:33:59.456288: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/1024\n", + "90/90 [==============================] - 3s 6ms/step - loss: 0.0195 - val_loss: 0.0269 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0113 - val_loss: 0.0306 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0089 - val_loss: 0.0282 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0076 - val_loss: 0.0420 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.2797 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0061 - val_loss: 0.0573 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0057 - val_loss: 0.3248 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0052 - val_loss: 0.0652 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0051 - val_loss: 0.0539 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0050 - val_loss: 0.3124 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0049 - val_loss: 0.2981 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0050 - val_loss: 0.1575 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0046 - val_loss: 0.3290 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0046 - val_loss: 0.2020 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0044 - val_loss: 0.2263 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0044 - val_loss: 0.1640 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0046 - val_loss: 0.3251 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0044 - val_loss: 0.1552 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0042 - val_loss: 0.2003 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0042 - val_loss: 0.2845 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0041 - val_loss: 0.3258 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0043 - val_loss: 0.1390 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0042 - val_loss: 0.2158 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0041 - val_loss: 0.2158 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0041 - val_loss: 0.2599 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0040 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0040 - val_loss: 0.1886 - lr: 0.0012\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0040 - val_loss: 0.1866 - lr: 0.0012\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0038 - val_loss: 0.1335 - lr: 0.0012\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0039 - val_loss: 0.1366 - lr: 0.0012\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0039 - val_loss: 0.1104 - lr: 0.0012\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - val_loss: 0.1381 - lr: 0.0012\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0038 - val_loss: 0.0471 - lr: 0.0012\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0038 - val_loss: 0.1386 - lr: 0.0012\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - val_loss: 0.0363 - lr: 0.0012\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.2797 - lr: 0.0012\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0038 - val_loss: 0.2271 - lr: 0.0012\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0038 - val_loss: 0.2174 - lr: 0.0012\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0038 - val_loss: 0.2247 - lr: 0.0012\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0038 - val_loss: 0.3289 - lr: 0.0012\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - val_loss: 0.2250 - lr: 0.0012\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0037 - val_loss: 0.0412 - lr: 0.0012\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0036 - val_loss: 0.0669 - lr: 0.0012\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0038 - val_loss: 0.1742 - lr: 0.0012\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0037 - val_loss: 0.1423 - lr: 0.0012\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - val_loss: 0.1878 - lr: 0.0012\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - val_loss: 0.1666 - lr: 0.0012\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - val_loss: 0.3291 - lr: 0.0012\n", + "Epoch 49/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0036 - val_loss: 0.2814 - lr: 0.0012\n", + "Epoch 50/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.0404 - lr: 0.0012\n", + "Epoch 51/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.0512 - lr: 0.0012\n", + "Epoch 52/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.3063 - lr: 6.2500e-04\n", + "Epoch 53/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.2505 - lr: 6.2500e-04\n", + "Epoch 54/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.2432 - lr: 6.2500e-04\n", + "Epoch 55/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.2175 - lr: 6.2500e-04\n", + "Epoch 56/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.0279 - lr: 6.2500e-04\n", + "Epoch 57/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.0741 - lr: 6.2500e-04\n", + "Epoch 58/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0036 - val_loss: 0.1194 - lr: 6.2500e-04\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.2005 - lr: 6.2500e-04\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.2246 - lr: 6.2500e-04\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.1561 - lr: 6.2500e-04\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.0488 - lr: 6.2500e-04\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.1496 - lr: 6.2500e-04\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.1135 - lr: 6.2500e-04\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.1467 - lr: 6.2500e-04\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.1604 - lr: 6.2500e-04\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.1111 - lr: 6.2500e-04\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.2787 - lr: 6.2500e-04\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.1976 - lr: 6.2500e-04\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.2056 - lr: 6.2500e-04\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.0082 - lr: 6.2500e-04\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.2994 - lr: 6.2500e-04\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.1221 - lr: 6.2500e-04\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.1249 - lr: 6.2500e-04\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.0924 - lr: 6.2500e-04\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0036 - val_loss: 0.0854 - lr: 6.2500e-04\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.0996 - lr: 6.2500e-04\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.0486 - lr: 6.2500e-04\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.2045 - lr: 6.2500e-04\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.1386 - lr: 6.2500e-04\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.1423 - lr: 6.2500e-04\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.1797 - lr: 6.2500e-04\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.1582 - lr: 6.2500e-04\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.0894 - lr: 6.2500e-04\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1367 - lr: 6.2500e-04\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0036 - val_loss: 0.0485 - lr: 6.2500e-04\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0871 - lr: 6.2500e-04\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.0498 - lr: 6.2500e-04\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.2915 - lr: 6.2500e-04\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1644 - lr: 6.2500e-04\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.3032 - lr: 6.2500e-04\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.0835 - lr: 6.2500e-04\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.0596 - lr: 6.2500e-04\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.2761 - lr: 6.2500e-04\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0244 - lr: 6.2500e-04\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.0643 - lr: 6.2500e-04\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1067 - lr: 3.1250e-04\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0034 - val_loss: 0.0454 - lr: 3.1250e-04\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.1180 - lr: 3.1250e-04\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1303 - lr: 3.1250e-04\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0614 - lr: 3.1250e-04\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.0792 - lr: 3.1250e-04\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.2973 - lr: 3.1250e-04\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.1039 - lr: 3.1250e-04\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 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0s 5ms/step - loss: 0.0033 - val_loss: 0.2181 - lr: 3.1250e-04\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0585 - lr: 1.5625e-04\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0776 - lr: 1.5625e-04\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0188 - lr: 1.5625e-04\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.1303 - lr: 1.5625e-04\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0956 - lr: 1.5625e-04\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0875 - lr: 1.5625e-04\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1891 - lr: 1.5625e-04\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0998 - lr: 1.5625e-04\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1442 - lr: 1.5625e-04\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0245 - lr: 1.5625e-04\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1282 - lr: 1.5625e-04\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1317 - lr: 1.5625e-04\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.1941 - lr: 1.5625e-04\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0667 - lr: 1.5625e-04\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0882 - lr: 1.5625e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0514 - lr: 1.5625e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0361 - lr: 1.5625e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0344 - lr: 1.5625e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0613 - lr: 1.5625e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1208 - lr: 1.5625e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.1505 - lr: 1.5625e-04\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1506 - lr: 1.5625e-04\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0457 - lr: 1.5625e-04\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0494 - lr: 7.8125e-05\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0623 - lr: 7.8125e-05\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0487 - lr: 7.8125e-05\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0460 - lr: 7.8125e-05\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0422 - lr: 7.8125e-05\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0211 - lr: 7.8125e-05\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0576 - lr: 7.8125e-05\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0139 - lr: 7.8125e-05\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0212 - lr: 7.8125e-05\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0215 - lr: 7.8125e-05\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0080 - lr: 7.8125e-05\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0107 - lr: 7.8125e-05\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0412 - lr: 7.8125e-05\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0165 - lr: 7.8125e-05\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.1028 - lr: 7.8125e-05\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0274 - lr: 7.8125e-05\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.1518 - lr: 7.8125e-05\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0479 - lr: 7.8125e-05\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0137 - lr: 7.8125e-05\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0770 - lr: 7.8125e-05\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0851 - lr: 7.8125e-05\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0071 - lr: 7.8125e-05\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0107 - lr: 7.8125e-05\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0726 - lr: 7.8125e-05\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0318 - lr: 7.8125e-05\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0645 - lr: 7.8125e-05\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0129 - lr: 7.8125e-05\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0263 - lr: 7.8125e-05\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0511 - lr: 7.8125e-05\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1266 - lr: 7.8125e-05\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0126 - lr: 7.8125e-05\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0073 - lr: 7.8125e-05\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0271 - lr: 7.8125e-05\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0488 - lr: 7.8125e-05\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0039 - lr: 7.8125e-05\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0301 - lr: 7.8125e-05\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0232 - lr: 7.8125e-05\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1690 - lr: 7.8125e-05\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0505 - lr: 7.8125e-05\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1135 - lr: 7.8125e-05\n", + "Epoch 191/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0114 - lr: 7.8125e-05\n", + "Epoch 192/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1401 - lr: 7.8125e-05\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0106 - lr: 7.8125e-05\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.1013 - lr: 7.8125e-05\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0985 - lr: 7.8125e-05\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0232 - lr: 7.8125e-05\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0394 - lr: 7.8125e-05\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0570 - lr: 7.8125e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0184 - lr: 7.8125e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0950 - lr: 7.8125e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0942 - lr: 7.8125e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0905 - lr: 7.8125e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0411 - lr: 7.8125e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0316 - lr: 7.8125e-05\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0465 - lr: 7.8125e-05\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0756 - lr: 7.8125e-05\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0033 - val_loss: 0.0193 - lr: 7.8125e-05\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 1s 17ms/step - loss: 0.0032 - val_loss: 0.0564 - lr: 7.8125e-05\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 1s 12ms/step - loss: 0.0032 - val_loss: 0.0309 - lr: 7.8125e-05\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 1s 9ms/step - loss: 0.0032 - val_loss: 0.0732 - lr: 7.8125e-05\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0031 - val_loss: 0.0063 - lr: 3.9062e-05\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0032 - val_loss: 0.0306 - lr: 3.9062e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0043 - lr: 3.9062e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0222 - lr: 3.9062e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0067 - lr: 3.9062e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 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0s 5ms/step - loss: 0.0031 - val_loss: 0.0040 - lr: 3.9062e-05\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0292 - lr: 3.9062e-05\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0132 - lr: 3.9062e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0085 - lr: 3.9062e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0044 - lr: 3.9062e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0222 - lr: 3.9062e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0049 - lr: 3.9062e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0122 - lr: 3.9062e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 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0s 5ms/step - loss: 0.0032 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0045 - lr: 1.9531e-05\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0061 - lr: 1.9531e-05\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0072 - lr: 1.9531e-05\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0046 - lr: 1.9531e-05\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0109 - lr: 1.9531e-05\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0066 - lr: 9.7656e-06\n", + "Epoch 298/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0044 - lr: 9.7656e-06\n", + "Epoch 299/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0054 - lr: 9.7656e-06\n", + "Epoch 300/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 301/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 302/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0057 - lr: 9.7656e-06\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0059 - lr: 9.7656e-06\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0039 - lr: 9.7656e-06\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0030 - val_loss: 0.0062 - lr: 9.7656e-06\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0040 - lr: 9.7656e-06\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0033 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 312/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 313/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0046 - lr: 9.7656e-06\n", + "Epoch 314/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0089 - lr: 9.7656e-06\n", + "Epoch 315/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0048 - lr: 9.7656e-06\n", + "Epoch 316/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 317/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0044 - lr: 9.7656e-06\n", + "Epoch 318/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0032 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0050 - lr: 4.8828e-06\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0040 - lr: 4.8828e-06\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 324/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0035 - lr: 4.8828e-06\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0031 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 326/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 327/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0039 - lr: 4.8828e-06\n", + "Epoch 328/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 329/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 330/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0031 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 331/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0031 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0033 - val_loss: 0.0036 - lr: 4.8828e-06\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0033 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0032 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0032 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0037 - lr: 4.8828e-06\n", + "Epoch 339/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0041 - lr: 4.8828e-06\n", + "Epoch 340/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0032 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 341/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0033 - lr: 4.8828e-06\n", + "Epoch 342/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0034 - lr: 4.8828e-06\n", + "Epoch 343/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 344/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 345/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 346/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0030 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 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0s 5ms/step - loss: 0.0031 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 482/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0032 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 485/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 486/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 487/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 6.1035e-07\n", + "Epoch 489/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0032 - val_loss: 0.1871 - lr: 6.2500e-04\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0820 - lr: 6.2500e-04\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0599 - lr: 6.2500e-04\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2202 - lr: 6.2500e-04\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1225 - lr: 6.2500e-04\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1028 - lr: 6.2500e-04\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0478 - lr: 6.2500e-04\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1392 - lr: 6.2500e-04\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0579 - lr: 6.2500e-04\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0854 - lr: 6.2500e-04\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.1743 - lr: 6.2500e-04\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0812 - lr: 6.2500e-04\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2282 - lr: 6.2500e-04\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.2258 - lr: 6.2500e-04\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1311 - lr: 6.2500e-04\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0849 - lr: 6.2500e-04\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.2272 - lr: 6.2500e-04\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1044 - lr: 6.2500e-04\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0814 - lr: 6.2500e-04\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2136 - lr: 6.2500e-04\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0209 - lr: 6.2500e-04\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2026 - lr: 6.2500e-04\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0709 - lr: 6.2500e-04\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.2205 - lr: 6.2500e-04\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1009 - lr: 6.2500e-04\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0085 - lr: 6.2500e-04\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0424 - lr: 6.2500e-04\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1412 - lr: 6.2500e-04\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1702 - lr: 6.2500e-04\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1170 - lr: 6.2500e-04\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2230 - lr: 6.2500e-04\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1023 - lr: 6.2500e-04\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.2213 - lr: 6.2500e-04\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0923 - lr: 6.2500e-04\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0454 - lr: 6.2500e-04\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.2172 - lr: 6.2500e-04\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1217 - lr: 6.2500e-04\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0606 - lr: 6.2500e-04\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2075 - lr: 6.2500e-04\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0625 - lr: 6.2500e-04\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0298 - lr: 6.2500e-04\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1503 - lr: 6.2500e-04\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0737 - lr: 6.2500e-04\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0594 - lr: 6.2500e-04\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0100 - lr: 6.2500e-04\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0538 - lr: 6.2500e-04\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0421 - lr: 6.2500e-04\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.1989 - lr: 6.2500e-04\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1871 - lr: 6.2500e-04\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0633 - lr: 6.2500e-04\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1713 - lr: 6.2500e-04\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1781 - lr: 3.1250e-04\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0732 - lr: 3.1250e-04\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1649 - lr: 3.1250e-04\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0611 - lr: 3.1250e-04\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0619 - lr: 3.1250e-04\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1832 - lr: 3.1250e-04\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0535 - lr: 3.1250e-04\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1102 - lr: 3.1250e-04\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0860 - lr: 3.1250e-04\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.2174 - lr: 3.1250e-04\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0330 - lr: 3.1250e-04\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1957 - lr: 3.1250e-04\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.2069 - lr: 3.1250e-04\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1690 - lr: 3.1250e-04\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1390 - lr: 3.1250e-04\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1432 - lr: 3.1250e-04\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0339 - lr: 3.1250e-04\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.2045 - lr: 3.1250e-04\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1591 - lr: 3.1250e-04\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0776 - lr: 3.1250e-04\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1097 - lr: 3.1250e-04\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.2214 - lr: 3.1250e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1543 - lr: 3.1250e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1395 - lr: 1.5625e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0382 - lr: 1.5625e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0535 - lr: 1.5625e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0217 - lr: 1.5625e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0644 - lr: 1.5625e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0395 - lr: 1.5625e-04\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1602 - lr: 1.5625e-04\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1149 - lr: 1.5625e-04\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0616 - lr: 1.5625e-04\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.2143 - lr: 1.5625e-04\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0271 - lr: 1.5625e-04\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0064 - lr: 1.5625e-04\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1151 - lr: 1.5625e-04\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0403 - lr: 1.5625e-04\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0599 - lr: 1.5625e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0073 - lr: 1.5625e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0226 - lr: 1.5625e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0438 - lr: 1.5625e-04\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1353 - lr: 1.5625e-04\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0409 - lr: 1.5625e-04\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0651 - lr: 1.5625e-04\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0669 - lr: 1.5625e-04\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0538 - lr: 1.5625e-04\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0461 - lr: 1.5625e-04\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.1081 - lr: 1.5625e-04\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1461 - lr: 1.5625e-04\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0188 - lr: 1.5625e-04\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0296 - lr: 1.5625e-04\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0263 - lr: 1.5625e-04\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0560 - lr: 1.5625e-04\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0078 - lr: 1.5625e-04\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0404 - lr: 1.5625e-04\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0942 - lr: 1.5625e-04\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0717 - lr: 1.5625e-04\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0399 - lr: 1.5625e-04\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0058 - lr: 7.8125e-05\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0665 - lr: 7.8125e-05\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0495 - lr: 7.8125e-05\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0411 - lr: 7.8125e-05\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0049 - lr: 7.8125e-05\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0357 - lr: 7.8125e-05\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0773 - lr: 7.8125e-05\n", + "Epoch 192/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1626 - lr: 7.8125e-05\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0052 - lr: 7.8125e-05\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0724 - lr: 7.8125e-05\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0061 - lr: 7.8125e-05\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0401 - lr: 7.8125e-05\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1298 - lr: 7.8125e-05\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0253 - lr: 7.8125e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0041 - lr: 7.8125e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0706 - lr: 7.8125e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0038 - lr: 7.8125e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0137 - lr: 7.8125e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0173 - lr: 7.8125e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0670 - lr: 7.8125e-05\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0203 - lr: 7.8125e-05\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0700 - lr: 7.8125e-05\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0637 - lr: 7.8125e-05\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0296 - lr: 7.8125e-05\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0279 - lr: 7.8125e-05\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0077 - lr: 7.8125e-05\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0663 - lr: 7.8125e-05\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0337 - lr: 7.8125e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0132 - lr: 7.8125e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0080 - lr: 7.8125e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0069 - lr: 7.8125e-05\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0540 - lr: 7.8125e-05\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0767 - lr: 7.8125e-05\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0206 - lr: 7.8125e-05\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0100 - lr: 7.8125e-05\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1665 - lr: 7.8125e-05\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0066 - lr: 7.8125e-05\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0183 - lr: 7.8125e-05\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0051 - lr: 7.8125e-05\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0080 - lr: 3.9062e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0082 - lr: 3.9062e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 3.9062e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0038 - lr: 3.9062e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0057 - lr: 3.9062e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0153 - lr: 3.9062e-05\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0066 - lr: 3.9062e-05\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0147 - lr: 3.9062e-05\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0081 - lr: 3.9062e-05\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0173 - lr: 3.9062e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0122 - lr: 3.9062e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0420 - lr: 3.9062e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0075 - lr: 3.9062e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0322 - lr: 3.9062e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0043 - lr: 3.9062e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0236 - lr: 3.9062e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0296 - lr: 3.9062e-05\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0146 - lr: 3.9062e-05\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0239 - lr: 3.9062e-05\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0037 - lr: 3.9062e-05\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0545 - lr: 3.9062e-05\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0609 - lr: 3.9062e-05\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0113 - lr: 3.9062e-05\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0430 - lr: 3.9062e-05\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0247 - lr: 3.9062e-05\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0042 - lr: 3.9062e-05\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0185 - lr: 3.9062e-05\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0119 - lr: 1.9531e-05\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0064 - lr: 1.9531e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 1.9531e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0219 - lr: 1.9531e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0041 - lr: 1.9531e-05\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0112 - lr: 1.9531e-05\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0059 - lr: 1.9531e-05\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0043 - lr: 1.9531e-05\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0038 - lr: 1.9531e-05\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0177 - lr: 1.9531e-05\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0074 - lr: 1.9531e-05\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0044 - lr: 1.9531e-05\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0066 - lr: 1.9531e-05\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0082 - lr: 1.9531e-05\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0080 - lr: 1.9531e-05\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0060 - lr: 9.7656e-06\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0084 - lr: 9.7656e-06\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0101 - lr: 9.7656e-06\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0107 - lr: 9.7656e-06\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0051 - lr: 9.7656e-06\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0027 - val_loss: 0.0038 - lr: 9.7656e-06\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0046 - lr: 9.7656e-06\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 2.4414e-06\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0028 - lr: 2.4414e-06\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 504/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 505/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 506/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 507/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 508/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 509/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 510/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 511/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 520/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 521/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 522/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 523/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 524/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 525/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 526/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 536/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 537/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 538/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 539/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 540/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 541/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 550/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 551/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 552/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 565/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 566/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 567/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 696/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 697/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 698/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 699/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 700/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 701/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 702/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.9605e-10\n", + "Epoch 703/1024\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 768/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 769/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 770/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 771/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 772/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 773/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 774/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 775/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 776/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 777/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 778/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 779/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 780/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 781/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 782/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 783/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 784/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 785/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 786/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 787/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 788/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 789/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 790/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 791/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 792/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 793/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 794/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 795/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 796/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 797/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 798/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 799/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 800/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 801/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 802/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 803/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 804/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 805/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 806/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 807/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 808/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 809/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 810/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 811/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.7253e-11\n", + "Epoch 812/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 813/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 814/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 815/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 816/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 817/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 818/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 819/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 820/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 821/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 822/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 823/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 824/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 825/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 826/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 827/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 828/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 829/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 830/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 831/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 896/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 897/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 898/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 899/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 900/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 901/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 902/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 903/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 904/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 905/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 906/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 907/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 908/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 909/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 910/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 911/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 912/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 913/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 914/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 915/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 916/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 917/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 918/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 919/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 920/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 921/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 922/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 923/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 924/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 925/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 926/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 927/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 928/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 929/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 930/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 931/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 932/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 933/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 934/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 935/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 936/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 937/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 938/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 939/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 940/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 941/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 942/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 943/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 944/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 945/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 946/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 947/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 948/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 949/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 950/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 951/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 952/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 953/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 954/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 955/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 956/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 957/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 958/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 959/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 960/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 961/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 962/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 963/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 964/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 965/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 966/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 967/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 968/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 969/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 970/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 971/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 972/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 973/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 974/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 975/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 976/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 977/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 978/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 979/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 980/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 981/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 982/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 983/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 984/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 985/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 986/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 987/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 988/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 989/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 990/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 991/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 992/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 993/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 994/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 995/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 996/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 997/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 998/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 999/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1000/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1001/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1002/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1003/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1004/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1005/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1006/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1007/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1008/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1009/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1010/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1011/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4552e-13\n", + "Epoch 1012/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1013/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1014/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1015/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1016/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1017/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1018/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1019/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1020/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1021/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1022/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1023/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n", + "Epoch 1024/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.2760e-14\n" + ] + } + ], + "source": [ + "epoch, batch_size = 1024, 64\n", + "history_plain_11 = plain_11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)\n", + "history_plain_5 = plain_5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Save the result to history.p" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# import pickle\n", + "# with open('history.p', 'wb') as f:\n", + "# pickle.dump({'history_11': history_plain_11, 'history_5':history_plain_5}, f)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Post analysis and drawing" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# with open(\"history.p\", 'rb') as f:\n", + "# data = pickle.load(f)\n", + "# history_plain_11, history_plain_5 = data['history_11'], data['history_5']" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "smoothing_windows = 16\n", + "def moving_average(x, w):\n", + " return np.convolve(x, np.ones(w), 'valid') / w" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
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YPHgQ11yzkhNO+JnERKn1fRLJBAIaY/78Kfz2t4ezdOlSVq1qAvQEID+/gMmTZ+++Tx06dGC2L0OhZcvg+wQwZMgQFi5cSL4vxzczM5Pt24PvU5s2gfvUunVrMjMzmTJlCiKCc46hQ4cyb948Nm/eDEBWVhabNm1ipS/BY2//T//4Ry9SU/fh0EOFJk2WkZm5da/uUzz+n/b2PrVrl8Hrr3fio49+5owzVld7ny66qBt33rmQFi0OZv367bz3XiklJQncf38Z7drV7j4NGzaMcHASpbxK59yZwHARGeVbPh8YKCIh/TnOuSHAbSJytGddC2AKcK+IjK/pnNnZ2eK/WRFFBG64QaPDnjfPxkJBgXYmy8ysue327drZbOpUzTxu00bLrWdnq6XyxhuaQprke0156in4zW+0/+PEiRpf6dEDMjLUA1hern1JQvHww3qsFSs0vHTRRcF9FsJl/nyYNk0TApo98yhcqSGyxxPGcnm5lvctLNRuNyUl8MUX8M47tT/PeedpbMiP96/3738HAuCjRsHTT9f++PHKihXw6adqbT7xhH5/99yj1ZQNfRn55Rd48kk491zNZmzZUq3wUKxdq51xMzNh0SL9zffpA4ceqvk4t91WaxHCeqhF0yjMA7p6ltOBKv05IjIV+I1zbl8A51wT4F3g1XAURVRxTn04vreIxkaLFuEpCgj0Sh48GBYs0IfeSy+pN2/sWP0qkzz27CWX6MPk7rv1QXL++aooxo9Xk/z//k/b+PuP+Fm/XgeFyshQpXHwwXr8227TB2+4iMBzz+kf9uuvQdIC9n/bhM275ydPhk8+0Qf50KF71gXHG/v4+9+Dt6WkBOYj5faKF157TYcKBhgzRh+K770XW5niiWeegf/+V9PdMzP1peGHH6puP3u2Vp5evRrOPFMzH087TUeGLi6OXr+qaCqLWUBP51yGcy4ZOAuY4G3gnNvfOX1Vd85lAclAvm/ds8BiEflHFGUMn5Ej4c03Yy1FvSE5Ge68Uy2JJk20ftURR1Ru55wG0gcN0hjKkCFw1ln6Br58ub5pjRunisPL44+rVXLaaap8jjwSevaEu+7SeMu2beGNaz1pkg4wNXq0WgsPvRHoIdeJQH3y447T7ffco+nIr72mCqw21ey9SiAjI3hbQ1QWJSX6HaWmBlt8bdpoMkU4D7X168P/PuJhZIFdu3YbpmGzYoXu401yEFFr+4UXKrf/7jvo3x/uuKNyQsnIkfrSFQ2ipixEpBQYC0wCFgNvichC59xlzjl/xvnpwALn3Fw0c+p3on6xw4HzgSN9abVznXPHR0vWsGjVSp+A9SiNtr7gHDz7bPC6Jk00YH7mmfqg6dZNlc/KlWqyl5UFBwETElRRgCqfq67STKuqBhT6z3/UtTRxopZJadpU33ivuLfj7jbtytdV2u+ee9SKeecdfbP729/Cv07vQ8+rHCoux7Oy2LYN/vQneP11tciq44kn9MEW6uHZv79aGTWNNXbnnfDoo+HJds45tRvHfNMmePtttYCvukot0nvvDX//iixfrunpIoRd2v6vf9WMworsv79ayt9+G/x7KCrSqWnT0MfLzo5iUVERaTDTgAEDJKosXizy0kvRPYcRkm3bRA46SGTUKJF77xWZMKH69uXl+rlypcj11wdvW7xYZMgQkd//XmT16go7rlsnov93yXdt/LNBk4hISYl+3n677hIOw4YFjvH88yK7dgWO9eqrgW0jRoR3vNrg/z5ERMrKRN5/X7/Tbdt03bx5IgUFIi+8UP1xbrlF5NNPRa68UmTcOJH//Cd0u7Iykeuuq/o4u3aJ7NhR+d54mTFD5I039JzvvCNy2mkimzeHbrtzp8hxx4k8/LCeu6REZOtWkYkTRU4+WeSHH0Q2bBCZM0dk40bddsklIlOmiPzznyrP3XfrMS69tObfl5fiYpGffhIZOzbwfb7/vshll4mcd55+r6HIz9fvMBTl5SKrVol89JHIl1+KFBbq+i++EJk0qXp5HnpI5MMPdR/vfa+GsJ6v0cyGanj07h3+K4MRUdLStFxG9+7htffnIey3n+6zdKkOR5ubqynAr7+u7pGK6azsuy+SkIArL6eNbCKZYkpIqXj43eXFr7lGrZfDDtPK9tXhfUP8/nt1I4C6Wrxv2DVZFsXF+lber592//HLUpHCQliyRH3ckybpdTunuRoHHaQDaP36q1pLTz+toy8uWKAuw1BJBU88oW6Wo4/WCdS/fuihwfWtQM9ZXZ+bpCSdmjZVd5X3fDNmQFaWvvXfdx8ce6wmTNx3n6675BLdZ/lyDSVOmaIxpfvv1z5Af/qTppB27Ajt22sP/Kee0uUZM3Tf8nL9DocMCaRu33KLxq4++ECD8MOHV51c4eWRR9QyvOKKQMzulFNUtjVrNO42cqTGu7y8+aZuC4VzkJ6u1vN556m8d9yhiQI33VS9PH/8o1ZxuPpqHXnxhhsCLmD/SI1V/WaqJVytUh+mqFsWIvoquX179M9jRIydO/UN7/TT9fONN2rYoVOn3a/5Xfk5pGVRkeuuC1gK33+vb6zbtukb+Pz5Is88I7LvvoFjzJyp05o1us+NNwa2HXZY9eI9+6zIggUi330ncsUVIrfdpm+hJSXBb5IffSQyfLjITTfpm/m994o89pjOi6hltWWLyA036JvwZ5+JPP20yiUSfKxffhF58MHKshQU6Bv6r78G1m3Zom+3GzdWfx0iaj289lpguaxM5KKLVOZPP63c/qabRF55ReTqq/XN/b//1e9g6tRAm8JCkfHjg/e75Ra9Rxs2qCV4003Vv3VPm1a9dbFmjX6Pc+aI/Otf1V9jebnIHXeIzJ0beHT8+mv1lpeXq6/W39azz4p8/HF4+4iIbNqkv8Ebbwyse+wxkTFjKl17WM/XqKXOxoKopc56ycvT15urrorueYyIsnOnWiZnnRVG46wsdbYDA5nBLAYGbQ71l/nwQ+2gmJOjP422bfWncvPN+ubbqpWWkl+8WNvPm6d+ez8zZwaq0B50kKbzhkIErrtOO0f6lz//XGMwJSUaz7nzTs2qGTtWrYbmzXVatUrLtRx0UGDfipnga9dqJlq/fmptDBumWWdNm6p/3f/m7CU/X885dqzuu2SJvgm/+GKV33AQjz6qcl16qSYcbtkCJ54Yuu0996g19PDD6rs/91w19ps3r/4cX36p1kK4aaXl5ZqZ16qVnrOiBXrDDRqoLyzUe5xUg49m0yZN9li7VjP//vc/tVrqokPqrbeqVfLee/Djj3rOadPUajnySOjVK7zU2ZhbA5Gc6sSyENHXFKPhctxxu1/zT+I/YVkWO3eKnHWWvmXOmKFvbn5Lw8/++weO8cMPwdvmzg1sa9++atFef11k8uTQ20pL9W3y2mtFLr5YZNGi8C/ZyzXX6Jv3zz+LzJoV3j5vvy1yxBF63uJikby82p1z40a1EK68UvevirVrNb6yJ5SW1q79zp0a3/L+3T/8UOQvf9GY055w881qSZ13XtXxl0jzyCN6PydODHwHfivy5JNFJMznq8Us9oSkJHXe7pHjz4h7OgYyojpSOSOqoo8dNP5x++06YuFAnyFS8W0z3GyohATNNOrUSa0Pf5FBEc2OeeCB0GInJuob8MCB6m+vqWREVfTvr9ZEt246hcPIkXoNJ5yg8nsLI4bDvvuqRZafX32coGPHoNtTK2pbCiM1VeMOLVvq9/7mm2pN3HJLaAsrHIYODWTuVawVFi1GjtQMQW+m15FHakzJ20m0JswNtSdMmAAdOgT8BkbD4uabNZoKTOQ4TmBi0OZNm0IExsOgY8dAZ741ayoPetSjh85366Z/7PXr1S1z8MGwYQMcf7y2O/PMPbimWlBSou6ycDtiNnREtBPcYYdpULw+smVLaOXkWx+WG8osiz0hN1e7XZqyaJh4BsU+no/I4WumE0jt2bFjz5RFbfpZnHeezq9fr+8mgwern/yDD2p/3tqSnGyKwotzmk1VVd+G+kBVVkxtrBurAbkntGmjUbYPP9TeYUbDwl9K18ez/CFoeUbIkpbVs2NHoHNgQoKWUPFSVae8Dh00VfTYYzV4XJ8fWPWZ1NRGWRYuCFMWe8pRR2niufW7aHhUeN3qRvA4p6NH166nMGi/Dr/Ht3fvyn75cHpw72kMwjAigSmLPeXYYzUX7eefw69HYNQPKlgWqRQGLW/apJVya8Oddwbm/amrXupLuQ+j8WLKYk9xTrOh7rhDfQwrVsRaIiNSVFAWCb4R8y6/PLBu3TrN3AkX39ABQOg+BElJAYVRXq41sAwjnjBlEQkuuUQryjWgzLJGTRVRv4oj665dG7JZJXbtClYW555buY1zms7op2KVXcOINaYsIsG++2o+4+OPx1oSIxJUsCxAc9V799aezX7WVe6CEZLNgWExaNu26qFFB3o6iu/JeBmGEU1MWUSKI4/U5Pl4KKpv7B0VLIuyhKTdAyr17RtYv25deMbkpk2BeU9WbiW8JStqG0A3jGhjyiKSZGdrV0+jfpOSElREKLG8lHZt9SXA23v4/PPVSjjiCK1TVBXhKotmzQLzO3bUVmjDiC6mLCLJscfq2JtG/efOO4PrdfjGRO3atXLTadOqL5r3+uuBebMsjPqKKYtI0ry5vRI2JFJTA/O+fNbf/S50XaDqqsSO94wgX13NJK9lYcrCiDdMWUSaI4/UDnu1yas04pMQnR/S07UkuHdMaai64N68eRrK8vOnP1V9Oq9lYe8cRrxhyiLSHH20Dih9zz2xlsTYW6roKZedrSPKeakqr+H77wPzp50WukOeH7MsjHjGlEU06N5dI6EFBbGWxNgbqulW3bGjlq/2U5Ul4O2ruf/+1Z/OLAsjnjFlES369w9+rTTqHzXU4PiDp75gVZaAV1lkZFR/OrMsjHjGlEW0OOQQHZqzuFhHSDfqH15lESI3NhxLYE+VhVkWRrxhyiJadOyovbbuvx9eeKHy9m3brJtuvFODZRFpZWGps0Y8Y8oimhQUqDtq0yYNeK9ZE+jy++STcOGF1okvnqlBWdTkNtq1C/LydN452G+/6k/nTcndutVKjRnxhY2UF03+8Y/A/Pjx2jsrL09TYrZsgREj4OuvYcCAmIloVEMtLIsJEyrv/ssvgSypzp0rj45XkWbNdFCkggLtA7hly56NyGcY0cCURV1x2mn6uXCh9sFIT9ce39dfr6+QjX0YrnjEOyxdiKqBXmVRVgY//RQ8zsXq1YH5qvphVKRjR/jxx8ApTVkY8YK5oeqavn1hyBBVFKBPkY8/jq1MRmi8psBFF8GGDUGbK/bknj07eHnLlsB8uA/9Tp0C8+FWtTWMusCURay59FJ1RRnxR0W/0dSpQYsVO9hVzFfwjmERoup5SLyFCsMdL8Mw6gJTFrEmKUlLl1r6S/xRsRfd1q1Bi0lJcPPNgeWKloC3ebjKYt99A/PecTAMI9aYsogHzj4bXnst1lIYFalYyMlrKvjwZjh5lcXmzfDww4HlcJVFkyaBeeueY8QTpizigQMO0OioEV+0aQO33hpYvvrqSr6hUG6j0lId9c4fqIY9Uxa7dtVSXsOIIqYs4oXOneHnn2MthVGRli2DlysMxO1VFn7L4qefghUFhK8svENomGVhxBOmLOKFiy6Cu++2FJh4o6KyePdd7QjxwQeweXNIZeHviOfFlIVR3zFlES+0aKGd+J5+OtaSGF5CjXR03HFw0klwwgm0bxfoZr1hg/a38Pav8GPKwqjvRFVZOOdGOOeWOOd+dM7dEGL7uc65+b7pa+dcpmfblc65Bc65hc65P0dTzrihZcvqB3M26p6KlgXoOKoA06eTclAv0ltrYajycvj1V1MWRsMkasrCOZcIPAYcB/QBznbO9anQbAUwVET6A3cDT/n27QdcAgwEMoETnXM9oyVrXHHssXDbbbGWwvATSll4+fFHxiQ/u3vx4othzpzKzSzAbdR3omlZDAR+FJHlIlICvAGc4m0gIl+LiD+b/Bsg3Td/IPCNiOwUkVJgCjAyirLGD0OHquvD2/3XiB1hdL0+Rd7fPT9xIrzzTuU2ZlkY9Z1o1obqAqzyLOcBg6pp/wfgI9/8AuBe51xboBA4Hpgdaifn3GhgNEDnzp2ZPHkyAD169CAtLY158+YB0LZtW/r27ctUXy/cpKQkcnNzmTNnDtt8+fPZ2dmsX7+eVatU7J49e5KSksIC3xia7du3p1evXkzzuSFSUlLIyclh9uzZFPhGxRs0aBB5eXms9vkievfuTWJiIosWLQKgY8eOZGRkMH36dABSU1MZNGgQM2bMoLCwEIDDsrNZ/8Yb/OQbiq1Pnz6UlZWxZMkS/WK7dCE9PZ0ZM2YA0KJFC7Kzs5k+fTrFvoJ3ubm5LF26lA2+EhX9+vWjuLiYZcuWAdC1a1c6dOjAbF+NipYtW5KVlcW0adMo9T2lhgwZwsKFC8n3jSeemZnJ9u3bWb58OQDdu3enTZs2zPG9Srdu3ZrMzEymTJmCiOCcY+jQocybN4/Nvh5mWVlZbNq0iZUrV9aL+/TtkiUcFuqH5yGhaypsqL7N999PY+PGpjXep6KibKAFACtX5vHTT8V2n/by/5STk8OKFStY58tAsP9T8H0aNmwY4eAkSnWQnXNnAsNFZJRv+XxgoIhcEaLtb4HHgVwRyfet+wNwOVAALAIKReSq6s6ZnZ0tsysW6KmPlJXBOedodlSvXrGWpnFTUlJzudgzzuD1097mnHOqblJaComJNZ/uscdg7Fid/+MfddkwokxYVUyj6YbKA7p6ltOBNRUbOef6A88Ap/gVBYCIPCsiWSIyBNgELIuirPFFYiLceCP873/w9ts2PGssSU6uuc369Zx9Nlx+edVNwlEUYDELI36JprKYBfR0zmU455KBs4Cgqv/OuW7AeOB8EVlaYVt7T5vTgNejKGv8kZkJn38OK1fC88/D5MmwfXuspTJC4XNNHHPM3h/KYhZGvBK1mIWIlDrnxgKTgETgORFZ6Jy7zLf9SeA2oC3wuNPxHEpFJNt3iHd9MYtdwOWeQHjjwDk44QS44AL47381J/OOO/SJNGiQDXQQT/jKzXbvHnpzamr4hzJlYcQrYcUsfG/5hwOd0YDzAmC2iJRHV7za0WBiFlUhotXp1q+HceNiLU3j4S9/gQceqL5NcTFbdiYH6fDLL4flyzUTevDg8E712mtw7rk6b/UljTpi72MWzrnfOucmAR+i/SU6oX0mbgG+d87d6ZyrIRHdiBjOwVVX6eBJ9hSpO+64Aw48sPo2GzfSqpWObQU6ptXDD2sqbbiKAoItC4tZGPFETTGL44FLRORQERktIreIyLUicjLaWe47IAKeWqNWHH+8vrJ+8kmsJWkcNGtWc0dJnyvq3XdVt3zwQfCDP1ysRLkRr1SrLETkOhH5pYptpSLyvoi8Gx3RjGq55RYNgEcp9dmoQJcu1W/3Bbl794bbb688il64WMzCiFdqlQ3lnBvsnPvcOfeVc65x9KiOZ/r2BV/HIiPKdO5c/fYVKyJyGlMWRrxSU8yiY4VVVwMnAyOAu6IllBEmv/0t3HUX/OEPpjSiTadOldf18ZQ6++yziJzGYhZGvFKTZfGkc+5W51xT3/IW4Bzgd0DlMSaNuiU9HQ4/XLv5PvdcrKVp2DRrVrnA00knBebffRdefHGvT2OWhRGv1BSzOBWYC3zgK9fxZ6AcaAacGl3RjLC4/HJo2hR+8xvtvOcvn21Eno4VDG1/jqufF17Y61NYgNuIV2qMWYjIf4HhQCu0t/USEXlURDZGWTajNlx4oT7MJk4MBL3XrAFfITQjApx+emA+KUljRv/8Z2Ddtr03ts2yMOKVapP7nHMnA38ByoA7gJeB25xzfwRuEZGfoi6hER7JyTqC286dcOWV+oq6ahW0a6epthMnauey/HwtGzJ0aKwlrn+MGQPPPKPDqr77LiQkwFFHBbbv2LHXp9gbZZGXp0OEt28Pjz5ac/1Dw6gNNWWC3wPkAKnARBEZCFztG4joXrTekxFPnH66Tn7r4ptvtIrtTTfBk0/C1q36FOnTRxWJET7p6fpELiwMDIrUokVgu6+s9t6wNwHuf/4T3n9f55s311F6DSNS1KQstqIKIRVPxX4RWYYpivjG+Xrw5+QE1olo3evOneHqq2HzZu1m3LVryEMYIWjSJDiw0Lx5YD4ClsXexCzeeCMw/9BD8Le/7VnHQMMIRU0xi5FoMLsUzYIy6jP33AMHHKBvxf/6FzzyCLz3XtXti4rg66/rTr76SISVhffh7hvfJ2x+85vg5Ztv3mtxDGM3NSmLIhH5p4g8KSIho3fOuRah1htxTtOm6lb55ReYOVP98ddeC59+Gnjo/eMf8PLLtT/2l1/qoEGNgeTkwBN+1669vu6KloBvALggduxQHf/wwxpC2blT1/sGS9vNQw9VXmcYe0pNRup/nHNzgf8A34rIDgDnXA/gt8D/AU8DIUYdNuoFxx4Lb72lo/K1bQs33AAvvaSZVe3a6fZ779WYR1GR7lNdze2ff9Yn2euvqxM93FF/6ivOqXWxdasu79gR3oBJVZCWFrz817/CBM8oMOvXw2GHaWkwP/PmQXl55U7ku3bBv/+txzCMvaXGEuXOueOBc9ES5a1Rl9QStBLtsyKyLtpChkuDL1Fel3zxhaaGtm8PkyYFFEhZGfTrB6NGabuVK6FVK7VIPvxQayhdeSX88AOsXq3B9m3bYN99Y3k1kUMkEA/yk56u1wpqqe1lDOjwwwPev169gjvnX3st/P3v4R8rOxtmzdorcYyGT8SGVf0IuEFEuovIPiLSVkQOE5F740lRGBHmt79VRQEwfLi6o/7+d/V9bNmiHQALCuDSS+G882DuXHVbJSbqfkccoa/B550H11+v/T1KSjTlVASmTtX5+sb//Z8Od+slwnGLdzx2ut9g8VPbENLs2dpX8Msv91osI1x+/jnWEkSFcAc/+lZEBtSBPHuFWRZ1yIwZOqbGTTdp+qj3gell0ybYuFFrJyUmqr8kLU19J9nZuu8JJ+y5HCUl2vmwfXstyREtRFRJbN6s1z5uXCB1KSsLvvtO57/4AoYN26tT7dgRyMht2lQzdQGWLtWqtuHQqpXqdC8vv6y624gijzyipmC3burSrQ3vvqs36f77a77RO3bof+6JJ9S6P/ts/S906AD77VdbqSNmWQB845w7tLYSGA2YQYP0j9GhQ9WKAqBNG/3hz5+vgzyMGaOdBUeNgt/9Th+un32mMY4HH9ThY7ds0ThJTWOO5+drFPfVV7Vke1nZnl3L4sXaB6WqfhL5+aocvv4aTjsNRo7U8S02bdLt3nrk48fvmQwemjULhHqKigIx84cfDm7nr5reowf07Kl9BAFyc+HQEP/W88+PYcB7zhy9kHUN2BmxZo2+DD3+uA57HO6L66RJ6l9MStL850ceqazpK3L88fDjj9rv5+CDYcoUdYU+8ED0uv6LSI0TsAiNVfwEzAe+B+aHs29dTgMGDBAjjtmxo/K6NWtEnn9eZL/9RCZMEBk5UuSuu0T+9jeRceNExo8PfazycpHDDxe5/XZdnjRJ5L33RNaurb1cN9wgMm2afn70kcj//ieybZvIypUipaUit9wi8s03wfts3Chy8cUi330n8umnImp7iBxwQO3P7+fmm0W2bBERkTZtAofMyhLp2zewDCJjxlTefcECkQcfFFm1SuT774PbV7df1Fm4UE983HEiF1wgsmxZDISoA8aNE1m3TufLy0X+/GeRDRuq32fJEpGrrgpel58vcu+9Ve+zbJnIX/+q/5O8vMrHu+uu2koenh4IqxHsF2oK9yR1NZmyqMeceqp+lpcH1r30ksgxx4icc44+wL3Mm6fbCwt1ubRU5I9/FPnTn0TmzAn/vFu3itxzT+CYb74pcuWVIqNGiTzxhMgJJ6jiCsWGDSIPPSSyc6dIcnLgiTx/fvjn98pxxRUiDzwgIiKdOoV+2PunzZtrPmRJicjEifp8HszXAiKJiSI//1x78faY0lJ9aBYV6fzGjSKjR6tmixeKivRef/yxato9YedOkZtuCl737beqJEtLQ++zY4d+F7/8UnnbLbeIFBfrC0tFnngi9D5+br9dX3bCJ3LKQlRhZAJjfVNmuPvV5WTKoh7jf+iHYvp0VQRey+Tuu0W2b6/ctrxc39DD5aWXKj+4Pv5Y5MUXA8erDv/b47HHBp7k3bvrn/Xrr1X5ePnuO13v5eGHRU47TbfdeafIihXVKoqjcou03d1368Ok4ttlBcpef1P+lzxCMvlOUtkhDz9c47cSGebMETn33MrKu6REZOzY8I7x+ef6tlwbtm0TWb9e5PXX9Xdz1lkiP/6oSvzjj4PbFhXpy8Hs2SLPPBN4aakN69bp9YR6sE+bJnLSSSJLlwavLy5WRVKVlfXoo/ric8EFwcqmtFTlrY7ly1UJbd0a7hWE9XwNqxiAc+5K4BK06izAK865p0Tkn9XsZhjh07Rp1dsGD9ag8nHHafmSo48OjgJ7cU59tj/8oPGDsWMDdZy8iC8FdsECdeZ7GT48+HjVcfvtOuh2ixYaaCgr08DAEUfodMABWjY+O1v99S+8oP1U2rXTLtcPPACHHKJjZWRmagBizBiGcz5TGUIhqXjjj82awfN9H9RIdfv22hN/5Uq4806NH3lZswa++IKE+fOZcuEL5Dw1nrN4g2YLToOLntAYUdu21V+fl+++U9kffljLs3/yicoRKhhbUqIZc48/Xvn7b9JEv49HH9X7k5AQvN9f/6rfZ9eu6pffvBmuuqrm0QqvvVZjSs8+C99+C089pcs//qjfU1qaBoFKSyEjQ39D//qX3r+MDBgwQLMJ5s/XIFB1/Yn8iGhdlbvv1qyCihx+OLz9tpbXefDBwDEXLtTf9f77hz7uFVfo53//q/XdnntOf5cpKTBiRPUyZWRozO+OO2DtWv1eBvjyk7Zu1YST/ffX72hA+HlL4WZDzQdyJNAprzkwXUT6h32mOsCyoRo4/iq6//sfHHhg5foWfoqL9UHUurVmphx9dEABFBRon5H33tMgfa9e8Pvf771sZWUwcKAGcgEuukj/4CL6x12+HPr31+hz//6qJLZuhVNP1V52XpYu5dGrV1Ly4Se0ZjP/6Px3pi9uxfffQ/+VE0hruiu4XPrmzXDjjTr5M2FKS/VB3L07HHMMf588gGuvhVy+5IG+LzL4k7u0x15OTs0PH9DruOgifdBcc43m995/v6ZOX3219snxPwiXL9eu5336qCIMRVGRtpk5U1Or/XzxhcrerZsGbI84Qu/nNddossQddwTK6foV/qZNqsi++koVw7PPBioE+/n0U304Aixbpr+NsjJ90HsLcq1fr7+P5cv1vrVpU/33MmGCyuN9wQjFihWauXTvvXq+l17S775nz+r327FD788xx2gixbp1mhzilbk6yss1K+tvf9Pv68orVQlv3qwpvscfD+eeG1Y2VLguqO+Bpp7lpsD34ZovdTWZG8qoRGlpwJe8caPIjTfq8uLFld1Be8vttwd8RSeeGFhfXh46uF8N69aJ/OUvIu88kqeuroce0uNUDIb6KSrSmMdzz6nr5sILg4LyTz8dEO2ii3wrr7tO/d+vvaYxmqlTRW67rXJQdtEiDeK/805lt9zcuSI5OXrtixeLzJyprpzrrgvvQu+8U6SgQI+7aZMGdkO5FwsKNGr//PO6vHmzyPHHa1LC9dfrNVQVG/CyZYue55ZbqnfTLF2qbqnqKC3V+1GTq9LP/Pl6H8vK9OaGI6+IyFtvhdeuKh59VOSSS9Q1NX16YP327SLduomE+XwN17K4CrgQ8FedOxV4QUQeDk+91Q1mWRghGTcOTjlF3/QvuEB7oEeDadP0TRjUypgxI3LHvv56tZBKS9UdF4qFC/Ut+6uvdARFT+2Qt9/W/oSgnpmg/pCPPKK90N9/X/NxBw7U9OCSEnXJfPSRvmn/+9+hB8koK9NjfPedXv+ZZ+qbezgsXarurOJifdvt0kWtgqq49VZ9s77zTrjvPi2M1aNHeOeqLRdfrJba7bdX3vbLL/pWfuedwVZeTTz0kLoHhw3bu/5FtWHXLrXihgypvG3CBDj55LAsi3DKfSQAg4EiIBd1oE4Vke9qK3O0MWVhhKSwUMcpP/DA6P5Bf/wx4FbYb7/Idmr4/HO46y51we1B3fFPP9UyXwBHHqldWyqxa5e6dW6/XX3Z48eru+Ppp2s+Z1mZuncOOKDWsvH66xqj8I5pXhX33acP27/9LbqdMEE7nU6ZojXOKtb7+sc/9KXjqKMaQv2zyCgLAOfcdBHJqbFhjDFlYcSUbds0UA3qv9+xo+YAeW3YtKlmH3oVzJypIRpQPVDt3+SuuzQ28cgjasnsRWHEes+KFRqfue46XX7wQejUSb/Ahx6KrWyRI6wfabivKJ84504Hxks42sUwGiNpafpgLSlRa6aoKLyMmnDZQ0UBAR0Ggc7B/vhwJc47j81PvskT4xLYsiWZoUPVM7V2rSbaJCVF9rLimowM2LBBLYz8fLUc09PrzoUUR4RrWWwHmqO9uItQTSQiEiInMXaYZWHEnDZt1PcOWrqkNqmpUWTrVg0jeP/uycnqRdlnH61kkpOjmbA7dmiCWFVDczinpYheeSWyhlNcc/nlei/vuivWkkSDiMYsckTkq0hIFU1MWRgxx1uu/OefNQU0Thg4MLLlyr/8UjOBGwXFxdofJNyU1fpFZAoJikg58OBei2MYjYEIlyuPJNUlGYVDxT5nRxyhsfC5c/fuuPWClJSGqijCxmIWhhFJvMrCP95pnHDhhTp+1fjxGrdITtZsWb+YI0ZoH0b/iHtPPKEJSh9+qP0IBw/W/m7+ca9AvTJ33QWXXKKdsps0UbdWerp2KO/WrRG5qho4tYlZNAPKsJiFYVRNbq72cwANiobKbY8jFizQzNXTTgtUfli9WjNhQ3nQNm/Witi//BLe8TMytH9Hr16qQDp21DhxcrJ2Lk9N1UovKSlVZ6AWFGi2bEGBZtg2baoDL0Y7c9aLiGYWJyUFVyeJFSKq5IuK9HtLTtYpMXGPlHNEs6H2QYdWzRCRu5xz3YBOtRbJMBo6cWxZhKJfP61A4cU/TkYoWrfWslv+MXq8Y4GHYsUKbRcOSUmqCFJTNZZcXq4ZWKGGNXFOk88yMgL9/5zTh2hJiT5EvVN5ud4a54KnhITg5cREtY6c04S2nTv1/Fu3BgL+/odz06Yqg39q2VK37doVPJWUaAZyeXmgHCRULhFZXq5KurxcJ78syckBmbZv1wztbdv02KG+l6ZNA1Pbtipbs2b6mZSk4ZetWwPH+emnMO9PeM14DCgHjgTuArYD7wI2IJJhePG+7sZZzCJSpKbC6NE6lZVpb/DPP9f5khJNAvvhB1UUtXFal5aq9VBQoN08qkNEH3Tz5u3dtewJZWWqSAoLA4lv8YJIQDZQZRspwlUWg0Qkyzn3nQokm51zNfbUcc6NAB4BEoFnRGRche3nAv4qYgXAGBGZ59vWCngG6AcIcLGITA9TXsOIDfXMsthbEhPVzeQvJeJl40aNj/z8sw7olpen7qRmzfTN1u9G8U9VkZKiBWdbtlT9W1iox6nr6Km/qHC84LfCysoCVky0BsmD8JXFLudcIvrQxjnXDrU0qsTX/jHgGCAPmOWcmyAiizzNVgBDfcrnOOApwNfPlEeAj0XkDJ9iqkMPpWHsIXGcDVXXtGunRWnDwR8TKCpSJbJxo7pUOndWN1NFP3xpqb7VL1+u7b2KIyUl2BXTtGngjTuU68e77H/wlperUmvWTOMk++wTqKJfWhrod7l9e8A1tH277u91Hfnn/bEOr8sLKrvAEhICcQevEvDL5Hd3paWFrupfVqZupqIi/fnl5+v3s2OHylheHkhCaNkyuLNmTYSrLB5Fiwi2d87dC5wB3FLDPgOBH0VkOYBz7g3gFHSIVgBE5GtP+2+AdF/blsAQtHghIlICVNFFyDDiCK8bqhFYFpHCuUCQtmVLDYRXR1KSKqN27epGPi9+JdC8uQba44nExICSa9NGq5FHirCUhYi86pz7FjgKjZyfKiKLa9itC7DKs5xHwGoIxR+Aj3zzPYCNwPPOuUzgW+BK8Y2n4cU5NxoYDdC5c2cmT56sB+jRg7S0NOb5nJpt27alb9++TJ06FYCkpCRyc3OZM2cO27ZtAyA7O5v169ezapWK3bNnT1JSUliwYAEA7du3p1evXkybNg2AlJQUcnJymD17NgUFBQAMGjSIvLw8Vvs6ZvXu3ZvExEQWLVId2bFjRzIyMpg+XT1qqampDBo0iBkzZlDoczTm5OSwYsUK1vkGt+/Tpw9lZWUsWbJEv9guXUhPT2eGr6ppixYtyM7OZvr06RQXFwOQm5vL0qVL2bBhAwD9+vWjuLiYZcuWAdC1a1c6dOiAP3usZcuWZGVlMW3aNEp9tuyQIUNYuHAh+fn5AGRmZrJ9+3aW+6Ka3bt3p02bNszxjeHQunVrMjMzmTJlipY0do6hQ4cyb948Nvucu1lZWWzatImVviJ7De0+pYrgr/Wav3IlzQoL7T7F4X2y/1PgPg0bNoxwCCt1dk9wzp0JDBeRUb7l84GBInJFiLa/BR4HckUk3zmXjVoah4vIDOfcI8A2Ebm1unNa6qwRcx57TAcdAi1x/eyzsZXHMGomMj2494I8wGsEpQNrKjZyzvVHA9mniEi+Z988EfEPCPAOkBVFWQ0jMmRkBOb9vdsMowEQTWUxC+jpnMvwBajPAiZ4G/j6a4wHzheRpf71IrIOWOWc8w/uexSeWIdhxC3egXhMWRgNiKgpCxEpBcYCk4DFwFsistA5d5lz7jJfs9uAtsDjzrm5zjmvD+kK4FXf+N8HA/dFS1bDiBjduwdSXX75JZDwbkSNiy+G9u2DB0B8+20dFjwhofqxOy68UIerMGomqh3XRWSiiPQSkd+IyL2+dU+KyJO++VEi0lpEDvZN2Z5954pItoj0F5FTRSTOur8YRgiaNg2MlldeDovMII42F14IH38cvK5fP+3jEetqK9Hs91DXxEGVE8NoYPTvH5iPRRfjRsaQIZXHhTrwQOjdO3T7qrjrLjj0UFU0o0drv4uffoIsT7R02bJADa1vv4WhQ3V5+PBAb+lhw+Cmm3TbI4/s8WXFHaYsDCPSeJXF/Pmxk8OoFWPH6ngfCxao9/CDD+A3v9GOa/4y7M8/r5bMrl1wxRXqwvr2W3WF3Xxz4FhbtmgdyWuuicGFRAlTFoYRaSKhLMrKdDi65s3h3HPrvrZFI+SLL3Sc8oMO0lpXCxfq+lGjVEmUlcGbb8I552gp9wUL4JhjtArvPfdoORM/v/tdTC4hqpiyMIxI41UWexqz+PhjeOMN7QX+2msw3cqiRYKLLtKH+/HHB68vKoI//lEthe+/1/E5/PWqTj8dPvpILY0BA7SSq4gG0OfO1en77+GTTwLH81Z9aSiYsjCMSJOeHhj0YP36qgezropdu3TEIS/+11xjr3j+eX24T5wYvN6vGPbdV6veejOkmjbVmMSYMapsQOMhGzcGdPiuXQ3/FpmyMIxI06SJDhPnJ5w60UVF+jp7wAFaIOmJJ4K3//BDZGVsQJx9NuTkqGsoPV07zb/3ns5Pnw4nnKAP++po1Uq//oMOglNP1UC3l3PP1YzoY4/V5eRkVSjXXw+ZmWqtfP01DZqolfuIBVbuw4gbDj00kOA/bRocfnjVbSdN0jFNq+P44ytbG0ad8eCDWlb97rtjLUlUiHm5D8NovKSnB+Y//TQwX1AQXLp8/vyaFQXAl19GTjajVowcCS+9BFdeGWtJYospC8OIBt7eYG+9pZ+vvAKdOmldbV9lUb74oupjZGcH5rdvVx+Ir/qqUXe8957q9HgrR17XmLIwjGhwwQWB+cWL1Xo4/3y1LAoLVRGUl6uj3UufPhq/WLYMZs7URH8/n36qFsthh8GRR8L779fJpRgGmLIwjOjQpk3wyDyTJgVvF9GHvVdZ/PnP8M03OtTb/vtrRPWGGyofe/p0tUhGjgxYKIYRZUxZGEa06N69+u3vvRfsVho1SsfL9DJqlOZoVkXFHFDDiBKmLAwjWhx3XPBycnJwLOOVV4Iti6rGCN13XzjvvNDbnnzSencbdYIpC8OIFtdfr92CBw/WJPziYnjggarbV6yG5+WllzT2kZ8Pq1YFyqCvXg3jxkVWbsMIgfWzMIy6ZMsWtSBC1a6uzX/R248jJ6fh9wgzoon1szCMuKNVK3joocpdhGvL448H5pcurbqdYUQIUxaGUdeMHatpsX/8454fY8AAzZoCdU05B/ffHxn5DCMEpiwMI1Zcf71WqQO47rra7ZuQAL16Ba+74QYdT9QwooApC8OIFd26aazhlVfgzjtrv//tt6tby8v//R/85S8wdWpERDQMPxbgNoz6THm5urRycipvO/poLaE6cODex0iMhkxYAW5TFobREHjmGa2xXR1du6olMmCA9vdo3RpSU3Uwhg0bdNyNpCTtD1JYCNu26X6dO2vp9LQ0Lb+ekgItWugIP4mJUb80I+qYsjCMRoO/fMgrr8D48XV33tRUHaS6bVtVNMXFqnxattSg+65dGl+pODVpooqmpETb+D/97ZOSdP/y8sqTc7q/q/CMq7hcG5zTKSEh8Flx3jslJ6sMIoGUZ/98VeuqQkTHbC0t1eurbv+yMh09sbAwsC4xUb+vJk00BpaaGvyZkKD7+afS0uDladNMWRhGoyQ/X2tRLVwIX30FU6bEWiIjnhEJS1kkRVsOwzDqmLZt4ZxzAstbtuhY4Kmp8OuvWohw8WJ9Q925U99MO3QIuKRKSvSNdJ999M1z5Urty+F/+y8u1jE5Cgqs1EgjwpSFYTR0WrXSsuZ+jjkmMsctL1dls3WrWjPl5eqeSUpSBeV3j4hUdiWVlKgiSk4OuHT8+4qoUoLQLqDy8sB2P6GUlkj4rim/jF5ZQ60rL1e5/YrT777yn8e7HGpdVSQl6ffljwFVtX9CAjRrpso8MTEgW2mpylRUpC4q/6ffXeW/F/5zeKcwMWVhGMaekZCgge4WLaBLl1hLY0QZ62dhGIZh1IgpC8MwDKNGTFkYhmEYNWLKwjAMw6gRC3AbhlG/6d5de5f7M35C9bVq0UJTfY09xpSFYRj1ny++0OFnY4G/h3VCw3bUNOyrMwzD8FJQAEcdBVlZcNBB8J//6Ppbb4VHHgm0u/lmePRRnX/gAS3E2L+/VvoF7ah44IE6JklWlg5128Cxch+GYdRvMjK0KKJzcOmlMHp05TZ+N1RpqXYkbNlSe7MPHgzLlsHPP8Npp8GcOdrJrWdPreb77bfwzjvw73+r9XDyyVoCvls36NFDS8wPHlz31xxZYl/uwzk3AngESASeEZFxFbafC1zvWywAxojIPOdcU2AqkOKT8R0RuT2ashqGUU/56iutjLthg/ZOP+AAraobChG46SYd7yMhAVavhvXrNe7Rti18950uH3KILn/yiU6HHKL7FxSocunWDfbbryEoirCJmrJwziUCjwHHAHnALOfcBBFZ5Gm2AhgqIpudc8cBTwGDgGLgSBEpcM41AaY55z4SkW+iJa9hGPWUzp31s317GDlSCyf+6U+67rLLdPLz6quwcaNaDE2aqJIoKtJto0bBCy/AunVw8cW6TgRuvFEtFi8rV2qJ9kZENGMWA4EfRWS5iJQAbwCneBuIyNcistm3+A2Q7lsvIuJPXWjimxqOv8wwjMiwYwds3x6Y/+QTjS/MnauTV1GA1rFq314VxRdfqPvJz8iR8PHHMGsWDB+u64YPh+eeC2RSrV6tFkwjJJpuqC6AN+qTh1oNVfEH4CP/gs8y+RbYH3hMRGaE2sk5NxoYDdC5c2cmT54MQI8ePUhLS2PevHkAtG3blr59+zLVN9xkUlISubm5zJkzh22+QV6ys7NZv349q3zBqp49e5KSksKCBQsAaN++Pb169WLatGkApKSkkJOTw+zZsynw/ZgGDRpEXl4eq1evBqB3794kJiayaJEaVB07diQjI4Pp06cDkJqayqBBg5gxYwaFhYUA5OTksGLFCtatWwdAnz59KCsrY8mSJfrFdulCeno6M2boV9KiRQuys7OZPn06xcXFAOTm5rJ06VI2+H7Y/fr1o7i4mGXLlgHQtWtXOnTogD/G07JlS7Kyspg2bRqlpaUADBkyhIULF5Kfnw9AZmYm27dvZ/ny5QB0796dNm3aMGfOHABat25NZmYmU6ZMQURwzjF06FDmzZvH5s36TpCVlcWmTZtYuXKl3Se7T3t9n7ru2kXGNdewc8cOXFkZm0aMoOuIEZXuUxMRpk6eTJPu3Rn48stIZib56em07NaNDStW0LFDB2bMmEGv3r1xrVvTKTFR71NyMl0OPZT9Bw+muKSE4iZNWHzTTfQ68EDSSkv5yve8qc/3adiwYYRD1ALczrkzgeEiMsq3fD4wUESuCNH2t8DjQK6I5FfY1gp4D7hCRBZUd04LcBuGsceUl2tm09tva4C78RBWgDuabqg8oKtnOR1YU7GRc64/8AxwSkVFASAiW4DJwIioSGkYhrFoEey/v6bVNi5FETbRdEPNAno65zKA1cBZwDneBs65bsB44HwRWepZ3w7YJSJbnHOpwNHA/VGU1TCMxkyfPuBzBxmhiZqyEJFS59xYYBKaOvuciCx0zl3m2/4kcBvQFnjc6UAfpSKSDXQCXvTFLRKAt0Tkg2jJahiGYVSPdcozDMNo3MS+U148sGvXLvLy8ijy51IbQTRt2pT09HSaNGkSa1EMw4hjGryyyMvLIy0tje7du+PCHY+3kSAi5Ofnk5eXR0ZGRqzFMQwjjmnwhQSLiopo27atKYoQOOdo27atWV2GYdRIg1cWgCmKarDvxjCMcGgUysIwDMPYO0xZxIhhw4ZRU+bWqFGjdpc1qIqpU6eSlZVFUlIS77zzTtC2ESNG0KpVK0488cS9ltcwjMaNKYs45plnnqFPnz7VtunWrRsvvPAC55xzTqVt1113HS+//HK0xDMMoxHRqJSFc9GbqmLlypUccMABXHDBBfTv358zzjiDnTt3BrUZM2YM2dnZ9O3bl9tvDwzb4bU+WrRowc0330xmZiaDBw9m/fr1gBYf69+/PwkhhnQ86qijSEtLi8A3ZxhGY6dRKYtYsWTJEkaPHs38+fNp2bIljz/+eND2e++9l9mzZzN//nymTJnC/PnzKx1jx44dDB48mHnz5jFkyBCefvrpuhLfMAzDlEVd0LVrVw4//HAAzjvvvN0lmf289dZbZGVlccghh7Bw4cKQcYrk5OTdsYcBAwbsLklsGIZRFzT4TnleYlXZpGJ6qnd5xYoVPPjgg8yaNYvWrVtz4YUXhuz30KRJk937JSYm7q6RbxiGUReYZVEH/PLLL7sH0Xn99dfJzc3dvW3btm00b96cffbZh/Xr1/PRRx9VdRjDMIyYYcqiDjjwwAN58cUX6d+/P5s2bWLMmDG7t2VmZnLIIYfQt29fLr744t3uqnCZNWsW6enpvP3221x66aX07dt397YjjjiCM888k88++4z09HQmTZoUsWsyDKNx0eCrzi5evJgDDzwwRhJpNtSJJ564eyjJeCTW35FhGDEl5iPlGYZhGA0EUxZRpnv37nFtVRiGYYSDKQvDMAyjRkxZGIZhGDViysIwDMOoEVMWhmEYRo2YsogRkSpR/sILL9CuXTsOPvhgDj74YJ555plIimkYhgE0snIf9Y1wH/y/+93v+Ne//hVlaQzDaMw0LssiBjXKo12i3DAMoy5oXMoiRkS7RPm77767WxGtWrUq6tdjGEbjw5RFHRDNEuUnnXQSK1euZP78+Rx99NFccMEF0b0YwzAaJY1LWYhEb6qGcEqUf/bZZ8yfP58TTjihViXK27ZtS0pKCgCXXHIJ33777V59RYZhGKFoXMoiRkSzRPnatWt3z0+YMMEKAhqGERUsG6oO8Jcov/TSS+nZsydjxozhv//9LxBcorxHjx61LlH+6KOPMmHCBJKSkmjTpg0vvPBCFK7AMIzGjpUojzJWotwwjDjHSpQbhmEYkcGURZSxEuWGYTQEGoWyaEiutkhj341hGOHQ4JVF06ZNyc/Pt4diCESE/Px8mjZtGmtRDMOIcxp8NlR6ejp5eXls3Lgx1qLEJU2bNiU9PT3WYhiGEec0eGXRpEkTMjIyYi2GYRhGvSaqbijn3Ajn3BLn3I/OuRtCbD/XOTffN33tnMsMd1/DMAyj7oiasnDOJQKPAccBfYCznXN9KjRbAQwVkf7A3cBTtdjXMAzDqCOiaVkMBH4UkeUiUgK8AZzibSAiX4vIZt/iN0B6uPsahmEYdUc0YxZdAG+97DxgUDXt/wD4CyOFva9zbjQw2rdY7Jyrj50a9gV+jbUQe4jJHhtM9thQX2WvTu6PRWRETQeIprII1YU8ZP6qc+63qLLwV9gLe18ReYqA+2q2iGTXXtTYUl/lBpM9VpjssaG+yh4JuaOpLPKArp7ldGBNxUbOuf7AM8BxIpJfm30NwzCMuiGaMYtZQE/nXIZzLhk4C5jgbeCc6waMB84XkaW12dcwDMOoO6JmWYhIqXNuLDAJSASeE5GFzrnLfNufBG4D2gKP+wb2KRWR7Kr2DeO0T0XjWuqA+io3mOyxwmSPDfVV9r2Wu0GVKDcMwzCiQ4OvDWUYhmHsPaYsDMMwjBppEMoi3kuDOOeec85t8PYBcc61cc596pxb5vts7dl2o+9aljjnhsdGanDOdXXOfeGcW+ycW+icu7Ieyd7UOTfTOTfPJ/ud9UV2jzyJzrnvnHMf+JbrhezOuZXOue+dc3Odc7N96+qL7K2cc+84537w/e5z6oPszrnevu/bP21zzv05orKLSL2e0AD4T0APIBmYB/SJtVwVZBwCZAELPOv+Btzgm78BuN8338d3DSlAhu/aEmMkdycgyzefBiz1yVcfZHdAC998E2AGMLg+yO65hquB14AP6stvxifPSmDfCuvqi+wvAqN888lAq/oiu+caEoF1wH6RlD2mFxWhLyYHmORZvhG4MdZyhZCzO8HKYgnQyTffCVgSSn40Iywn1vL7ZPkPcEx9kx1oBsxBqwDUC9nRvkWfAUd6lEV9kT2Usoh72YGWaL06V99kryDvscBXkZa9IbihQpUG6RIjWWpDBxFZC+D7bO9bH5fX45zrDhyCvqHXC9l9bpy5wAbgUxGpN7IDDwN/Aco96+qL7AJ84pz71leOB+qH7D2AjcDzPvffM8655tQP2b2cBbzum4+Y7A1BWYRdGqSeEHfX45xrAbwL/FlEtlXXNMS6mMkuImUicjD6lj7QOdevmuZxI7tz7kRgg4h8G+4uIdbF8jdzuIhkoVWjL3fODammbTzJnoS6i58QkUOAHajrpiriSXYAfJ2YTwberqlpiHXVyt4QlEV9LQ2y3jnXCcD3ucG3Pq6uxznXBFUUr4rIeN/qeiG7HxHZAkwGRlA/ZD8cONk5txKtuHykc+4V6ofsiMga3+cG4D20inR9kD0PyPNZoADvoMqjPsju5zhgjois9y1HTPaGoCzqa2mQCcAFvvkL0HiAf/1ZzrkU51wG0BOYGQP5cM454FlgsYj8w7OpPsjezjnXyjefChwN/EA9kF1EbhSRdBHpjv6ePxeR86gHsjvnmjvn0vzzqP98AfVAdhFZB6xyzvX2rToKWEQ9kN3D2QRcUBBJ2WMdjIlQQOd4NFPnJ+DmWMsTQr7XgbXALlSj/wEtc/IZsMz32cbT/mbftSxBCyzGSu5c1DSdD8z1TcfXE9n7A9/5ZF8A3OZbH/eyV7iOYQQC3HEvO+r3n+ebFvr/j/VBdp8sBwOzfb+b94HW9Uj2ZkA+sI9nXcRkt3IfhmEYRo00BDeUYRiGEWVMWRiGYRg1YsrCMAzDqBFTFoZhGEaNmLIwDMMwasSUhWFEAOfc177P7s65c2Itj2FEGlMWhhEBROQw32x3oFbKwjmXGHGBDCPCmLIwjAjgnCvwzY4DjvCNKXCVr5jhA865Wc65+c65S33thzkdK+Q14PuYCW4YYZIUawEMo4FxA3CtiJwI4Ku6ulVEDnXOpQBfOec+8bUdCPQTkRUxktUwwsaUhWFEl2OB/s65M3zL+6B1eEqAmaYojPqCKQvDiC4OuEJEJgWtdG4YWgLbMOoFFrMwjMiyHR2C1s8kYIyv1DvOuV6+aqyGUa8wy8IwIst8oNQ5Nw94AXgEzZCa4yv5vhE4NVbCGcaeYlVnDcMwjBoxN5RhGIZRI6YsDMMwjBoxZWEYhmHUiCkLwzAMo0ZMWRiGYRg1YsrCMAzDqBFTFoZhGEaN/D9cELZ1rDM50gAAAABJRU5ErkJggg==\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain11', c='b')\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_plain_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain5', c='r')\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, min(len(history_plain_5.history['loss']), len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.set_ylim(0.20, 0.35)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (540, 0.252), c='b')\n", + "ax.annotate(\"5-layer\", (540, 0.230), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# plt.savefig(fname=\"fig1.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "shortcut5, shortcut11 = ShortCut5(input_shape=(1, 102)), ShortCut11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/1024\n", + "90/90 [==============================] - 4s 10ms/step - loss: 0.0195 - val_loss: 0.0297 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0109 - val_loss: 0.0370 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0086 - val_loss: 0.0330 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0070 - val_loss: 0.0620 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0058 - val_loss: 0.0435 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0052 - val_loss: 0.0888 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0048 - val_loss: 0.2214 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0046 - val_loss: 0.3246 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0046 - val_loss: 0.0465 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0043 - val_loss: 0.2278 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0043 - val_loss: 0.1194 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0044 - val_loss: 0.2280 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0041 - val_loss: 0.1382 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0041 - val_loss: 0.2272 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0041 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0039 - val_loss: 0.1941 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0041 - val_loss: 0.0935 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0040 - val_loss: 0.2019 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0040 - val_loss: 0.0174 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0039 - val_loss: 0.2676 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0038 - val_loss: 0.2173 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0040 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0039 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.0514 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0039 - val_loss: 0.2520 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.2222 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0040 - val_loss: 0.3297 - lr: 0.0025\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0038 - val_loss: 0.1340 - lr: 0.0025\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.0273 - lr: 0.0025\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.0410 - lr: 0.0025\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.0883 - lr: 0.0025\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.3284 - lr: 0.0025\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.2029 - lr: 0.0025\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.0360 - lr: 0.0025\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.3175 - lr: 0.0025\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.1809 - lr: 0.0025\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.1148 - lr: 0.0025\n", + "Epoch 39/1024\n", + "90/90 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0.1374 - lr: 6.2500e-04\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.2231 - lr: 6.2500e-04\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0269 - lr: 6.2500e-04\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0343 - lr: 6.2500e-04\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.1531 - lr: 6.2500e-04\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0299 - lr: 6.2500e-04\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.2062 - lr: 6.2500e-04\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.2226 - lr: 6.2500e-04\n", + "Epoch 100/1024\n", + "90/90 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val_loss: 0.1588 - lr: 1.5625e-04\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.2174 - lr: 1.5625e-04\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0600 - lr: 1.5625e-04\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0664 - lr: 1.5625e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.1178 - lr: 1.5625e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0619 - lr: 1.5625e-04\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.1825 - lr: 1.5625e-04\n", + "Epoch 160/1024\n", + "90/90 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val_loss: 0.0430 - lr: 7.8125e-05\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0430 - lr: 7.8125e-05\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0203 - lr: 7.8125e-05\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0429 - lr: 7.8125e-05\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0562 - lr: 7.8125e-05\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0488 - lr: 7.8125e-05\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0104 - lr: 7.8125e-05\n", + "Epoch 175/1024\n", + "90/90 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val_loss: 0.0103 - lr: 7.8125e-05\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0296 - lr: 7.8125e-05\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0487 - lr: 7.8125e-05\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0026 - val_loss: 0.1229 - lr: 7.8125e-05\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0871 - lr: 7.8125e-05\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0050 - lr: 7.8125e-05\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0053 - lr: 7.8125e-05\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.1140 - lr: 7.8125e-05\n", + "Epoch 190/1024\n", + "90/90 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val_loss: 0.1418 - lr: 7.8125e-05\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0796 - lr: 7.8125e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0328 - lr: 7.8125e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0208 - lr: 7.8125e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0210 - lr: 7.8125e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0412 - lr: 7.8125e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0076 - lr: 7.8125e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0296 - lr: 7.8125e-05\n", + "Epoch 205/1024\n", + "90/90 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val_loss: 0.0052 - lr: 7.8125e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0353 - lr: 3.9062e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0252 - lr: 3.9062e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0057 - lr: 3.9062e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0038 - lr: 3.9062e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0058 - lr: 3.9062e-05\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0114 - lr: 3.9062e-05\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0025 - val_loss: 0.0033 - lr: 3.9062e-05\n", + "Epoch 220/1024\n", + "90/90 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val_loss: 0.0491 - lr: 3.9062e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0260 - lr: 3.9062e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0130 - lr: 3.9062e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0046 - lr: 3.9062e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0046 - lr: 3.9062e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0312 - lr: 3.9062e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0403 - lr: 3.9062e-05\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0244 - lr: 3.9062e-05\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0044 - lr: 3.9062e-05\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0088 - lr: 3.9062e-05\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0058 - lr: 3.9062e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0083 - lr: 3.9062e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0048 - lr: 3.9062e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0068 - lr: 3.9062e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0050 - lr: 3.9062e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0190 - lr: 3.9062e-05\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0029 - lr: 1.9531e-05\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.9531e-05\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0038 - lr: 1.9531e-05\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0065 - lr: 1.9531e-05\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0029 - lr: 1.9531e-05\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0066 - lr: 1.9531e-05\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0060 - lr: 1.9531e-05\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0054 - lr: 1.9531e-05\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0045 - lr: 1.9531e-05\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0135 - lr: 1.9531e-05\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0044 - lr: 1.9531e-05\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0035 - lr: 1.9531e-05\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0088 - lr: 1.9531e-05\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0055 - lr: 1.9531e-05\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0033 - lr: 1.9531e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0239 - lr: 1.9531e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 1.9531e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0057 - lr: 1.9531e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0060 - lr: 1.9531e-05\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0117 - lr: 1.9531e-05\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0121 - lr: 1.9531e-05\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0108 - lr: 1.9531e-05\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0055 - lr: 9.7656e-06\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0025 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0025 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0026 - val_loss: 0.0047 - lr: 9.7656e-06\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 1s 9ms/step - loss: 0.0027 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 1s 10ms/step - loss: 0.0026 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0068 - lr: 9.7656e-06\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0111 - lr: 9.7656e-06\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 295/1024\n", + "90/90 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val_loss: 0.0053 - lr: 9.7656e-06\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0035 - lr: 9.7656e-06\n", + "Epoch 310/1024\n", + "90/90 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val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 400/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 415/1024\n", + "90/90 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val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 430/1024\n", + "90/90 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val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 442/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 443/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 444/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 445/1024\n", + "90/90 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val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 474/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 475/1024\n", + "90/90 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val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 485/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 486/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 487/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 489/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 490/1024\n", + "90/90 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val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 504/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 505/1024\n", + "90/90 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val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 1s 9ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 520/1024\n", + "90/90 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val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 535/1024\n", + "90/90 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val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 550/1024\n", + "90/90 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val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 565/1024\n", + "90/90 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val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 579/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 580/1024\n", + "90/90 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val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 588/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 589/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 590/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 591/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 592/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 593/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 594/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 595/1024\n", + "90/90 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val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 603/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 604/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 605/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 606/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 607/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 608/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 609/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 610/1024\n", + "90/90 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val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 618/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 619/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 620/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 621/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 622/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 623/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 624/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 625/1024\n", + "90/90 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0.0398 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0093 - val_loss: 0.0760 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0073 - val_loss: 0.0270 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0060 - val_loss: 0.2214 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0057 - val_loss: 0.3185 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0049 - val_loss: 0.1407 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0049 - val_loss: 0.1174 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0047 - val_loss: 0.2102 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0043 - val_loss: 0.0942 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0043 - val_loss: 0.3266 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0044 - val_loss: 0.2110 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0042 - val_loss: 0.0694 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0042 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0041 - val_loss: 0.2280 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0040 - val_loss: 0.1514 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0040 - val_loss: 0.3065 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0040 - val_loss: 0.2089 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0040 - val_loss: 0.3281 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0039 - val_loss: 0.2602 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0039 - val_loss: 0.0936 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0040 - val_loss: 0.2273 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0039 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0038 - val_loss: 0.0390 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0039 - val_loss: 0.0289 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0040 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0038 - val_loss: 0.3239 - lr: 0.0025\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0038 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.3271 - lr: 0.0012\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0036 - val_loss: 0.1068 - lr: 0.0012\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2516 - lr: 0.0012\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.3225 - lr: 0.0012\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0035 - val_loss: 0.2283 - lr: 0.0012\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2599 - lr: 0.0012\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.3292 - lr: 0.0012\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.0546 - lr: 0.0012\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.1195 - lr: 0.0012\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.2280 - lr: 0.0012\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.3298 - lr: 0.0012\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.3283 - lr: 0.0012\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.0243 - lr: 0.0012\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0763 - lr: 0.0012\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.1597 - lr: 0.0012\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.3298 - lr: 0.0012\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.3297 - lr: 0.0012\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.1892 - lr: 0.0012\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2290 - lr: 0.0012\n", + "Epoch 49/1024\n", + "90/90 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"Epoch 57/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0340 - lr: 0.0012\n", + "Epoch 58/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.3298 - lr: 0.0012\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.3297 - lr: 0.0012\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.3298 - lr: 0.0012\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.1741 - lr: 0.0012\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.3029 - lr: 0.0012\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.3135 - lr: 0.0012\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.1411 - lr: 0.0012\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.2472 - lr: 0.0012\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1987 - lr: 0.0012\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.1880 - lr: 0.0012\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.3090 - lr: 6.2500e-04\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.2940 - lr: 6.2500e-04\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0421 - lr: 6.2500e-04\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.2919 - lr: 6.2500e-04\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 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val_loss: 0.0228 - lr: 7.8125e-05\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0392 - lr: 7.8125e-05\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0619 - lr: 7.8125e-05\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0169 - lr: 7.8125e-05\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0177 - lr: 7.8125e-05\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0700 - lr: 7.8125e-05\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0264 - lr: 7.8125e-05\n", + "Epoch 185/1024\n", + "90/90 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val_loss: 0.0890 - lr: 7.8125e-05\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0377 - lr: 7.8125e-05\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0701 - lr: 7.8125e-05\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0665 - lr: 7.8125e-05\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0743 - lr: 7.8125e-05\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0976 - lr: 7.8125e-05\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0384 - lr: 7.8125e-05\n", + "Epoch 200/1024\n", + "90/90 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val_loss: 0.0046 - lr: 3.9062e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0072 - lr: 3.9062e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0134 - lr: 3.9062e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0080 - lr: 1.9531e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0054 - lr: 1.9531e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0091 - lr: 1.9531e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0046 - lr: 1.9531e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 245/1024\n", + "90/90 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val_loss: 0.0028 - lr: 1.9531e-05\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0088 - lr: 1.9531e-05\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0053 - lr: 1.9531e-05\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0049 - lr: 1.9531e-05\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0092 - lr: 1.9531e-05\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0068 - lr: 1.9531e-05\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0106 - lr: 1.9531e-05\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0051 - lr: 1.9531e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0052 - lr: 1.9531e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0036 - lr: 1.9531e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0102 - lr: 1.9531e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 1.9531e-05\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 1.9531e-05\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0100 - lr: 1.9531e-05\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0029 - lr: 1.9531e-05\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0033 - lr: 1.9531e-05\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0079 - lr: 1.9531e-05\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0084 - lr: 1.9531e-05\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0254 - lr: 1.9531e-05\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0043 - lr: 1.9531e-05\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0238 - lr: 1.9531e-05\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0052 - lr: 1.9531e-05\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0087 - lr: 1.9531e-05\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0054 - lr: 1.9531e-05\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 1.9531e-05\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0085 - lr: 1.9531e-05\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0295 - lr: 1.9531e-05\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0046 - lr: 1.9531e-05\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0062 - lr: 1.9531e-05\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0041 - lr: 1.9531e-05\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0050 - lr: 1.9531e-05\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0066 - lr: 1.9531e-05\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0045 - lr: 1.9531e-05\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0065 - lr: 1.9531e-05\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0291 - lr: 1.9531e-05\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0119 - lr: 1.9531e-05\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0095 - lr: 1.9531e-05\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0347 - lr: 1.9531e-05\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0074 - lr: 1.9531e-05\n", + "Epoch 298/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0051 - lr: 1.9531e-05\n", + "Epoch 299/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0064 - lr: 1.9531e-05\n", + "Epoch 300/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0133 - lr: 1.9531e-05\n", + "Epoch 301/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0097 - lr: 1.9531e-05\n", + "Epoch 302/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0088 - lr: 1.9531e-05\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0055 - lr: 1.9531e-05\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 1.9531e-05\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0063 - lr: 1.9531e-05\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0046 - lr: 1.9531e-05\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0043 - lr: 1.9531e-05\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0047 - lr: 1.9531e-05\n", + "Epoch 312/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0049 - lr: 1.9531e-05\n", + "Epoch 313/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 1.9531e-05\n", + "Epoch 314/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0052 - lr: 9.7656e-06\n", + "Epoch 315/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0040 - lr: 9.7656e-06\n", + "Epoch 316/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 317/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 318/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 324/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 326/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 327/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 328/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 329/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 330/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0038 - lr: 9.7656e-06\n", + "Epoch 331/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0061 - lr: 9.7656e-06\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0068 - lr: 9.7656e-06\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0079 - lr: 9.7656e-06\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 339/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 340/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0044 - lr: 9.7656e-06\n", + "Epoch 341/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0047 - lr: 9.7656e-06\n", + "Epoch 342/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0059 - lr: 9.7656e-06\n", + "Epoch 343/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 344/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 345/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 346/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 350/1024\n", + "90/90 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val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 373/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0036 - lr: 4.8828e-06\n", + "Epoch 374/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 375/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 4.8828e-06\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 380/1024\n", + "90/90 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val_loss: 0.0036 - lr: 4.8828e-06\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0032 - lr: 4.8828e-06\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 1s 10ms/step - loss: 0.0029 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 4.8828e-06\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0031 - lr: 4.8828e-06\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0035 - lr: 4.8828e-06\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 2.4414e-06\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 432/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 433/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 434/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 435/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 436/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 437/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 442/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 443/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 444/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 445/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 446/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 447/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 448/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 449/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 450/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 451/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 458/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 459/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 460/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 461/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 462/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 463/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 464/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 465/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 2.4414e-06\n", + "Epoch 466/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 2.4414e-06\n", + "Epoch 467/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 2.4414e-06\n", + "Epoch 474/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 475/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 476/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 477/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 478/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 479/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 480/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 481/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 482/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 485/1024\n", + "90/90 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val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 560/1024\n", + "90/90 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val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 568/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 569/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 570/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 3.0518e-07\n", + "Epoch 571/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 575/1024\n", + "90/90 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val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 583/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 584/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 585/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 586/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 587/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 588/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 589/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.5259e-07\n", + "Epoch 590/1024\n", + "90/90 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val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 598/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 599/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 600/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 601/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 602/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 603/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 604/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 7.6294e-08\n", + "Epoch 605/1024\n", + "90/90 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val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 703/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 704/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 705/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 706/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 707/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 708/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 709/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 9.5367e-09\n", + "Epoch 710/1024\n", + "90/90 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val_loss: 0.0026 - lr: 4.7684e-09\n", + "Epoch 733/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.7684e-09\n", + "Epoch 734/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.7684e-09\n", + "Epoch 735/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.7684e-09\n", + "Epoch 736/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 4.7684e-09\n", + "Epoch 737/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 4.7684e-09\n", + "Epoch 738/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 4.7684e-09\n", + "Epoch 739/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.3842e-09\n", + "Epoch 740/1024\n", + "90/90 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val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1003/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1004/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1005/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1006/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1007/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1008/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1009/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1010/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1011/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1012/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1013/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 2.3283e-12\n", + "Epoch 1014/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1015/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1016/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1017/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1018/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1019/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1020/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1021/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1022/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1023/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.1642e-12\n", + "Epoch 1024/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 1.1642e-12\n" + ] + } + ], + "source": [ + "epoch, batch_size = 1024, 64\n", + "history_shortcut_11 = shortcut11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)\n", + "history_shortcut_5 = shortcut5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_shortcut_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN11', c='b')\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_shortcut_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN5', c='r')\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, min(len(history_shortcut_5.history['loss']), len(history_shortcut_11.history['loss']) - smoothing_windows + 1))\n", + "ax.set_ylim(0.20, 0.35)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (500, 0.24), c='b')\n", + "ax.annotate(\"5-layer\", (500, 0.262), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# plt.savefig(fname=\"fig2.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import os\n", + "time_spent = (time.time() - time1) /60" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "19.134213467439015 min\n" + ] + } + ], + "source": [ + "print(time_spent, \"min\")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + } + ], + "metadata": { + "interpreter": { + "hash": "7f619fc91ee8bdab81d49e7c14228037474662e3f2d607687ae505108922fa06" + }, + "kernelspec": { + "display_name": "Python 3.9.7 64-bit ('base': conda)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} \ No newline at end of file diff --git a/02_model_training_rmsprop.ipynb b/02_model_training_rmsprop.ipynb new file mode 100644 index 0000000..b1ee6ec --- /dev/null +++ b/02_model_training_rmsprop.ipynb @@ -0,0 +1,7250 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Model training Experiment" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "In order to provide the experimental evidence to back up the statement in the section 2.3.2 that our shortcut block can prevent degration problem.\n", + "\n", + "Plain Networks. We first evaluate 5-layer and 11-layer plain nets. Comparing to the 5-layer one, the 11-layer one has three times convolutional layers." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import pickle\n", + "import time\n", + "\n", + "import numpy as np\n", + "from matplotlib import ticker\n", + "from scipy.io import loadmat\n", + "from models import Plain5, Plain11, ShortCut5, ShortCut11\n", + "from sklearn.model_selection import train_test_split\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib notebook" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Load data\n", + "load data and split them into train, val, test" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape of data:\n", + "x_train: (5728, 1, 102), y_train: (5728, 1),\n", + "x_val: (2455, 1, 102), y_val: (2455, 1)\n", + "x_test: (3508, 1, 102), y_test: (3508, 1)\n" + ] + } + ], + "source": [ + "import random\n", + "from numpy.random import seed\n", + "import tensorflow\n", + "import time\n", + "seed(1900)\n", + "tensorflow.random.set_seed(1900)\n", + "time1 = time.time()\n", + "data = loadmat('dataset/mango/mango_dm_split.mat')\n", + "training_method = \"rmsprop\"\n", + "x_train, y_train, x_test, y_test = data['x_train'], data['y_train'], data['x_test'], data['y_test']\n", + "x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size=0.3, random_state=12, shuffle=True)\n", + "x_train, x_val, x_test = x_train[:, np.newaxis, :], x_val[:, np.newaxis, :], x_test[:, np.newaxis, :]\n", + "print(f\"shape of data:\\n\"\n", + " f\"x_train: {x_train.shape}, y_train: {y_train.shape},\\n\"\n", + " f\"x_val: {x_val.shape}, y_val: {y_val.shape}\\n\"\n", + " f\"x_test: {x_test.shape}, y_test: {y_test.shape}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Build Plain networks and Training" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "plain_5, plain_11 = Plain5(input_shape=(1, 102)), Plain11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-06-27 14:33:42.405210: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/1024\n", + "90/90 [==============================] - 3s 8ms/step - loss: 0.0198 - val_loss: 0.0270 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0114 - val_loss: 0.0273 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0087 - val_loss: 0.0316 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0071 - val_loss: 0.3171 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0060 - val_loss: 0.2319 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0056 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0055 - val_loss: 0.3246 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0052 - val_loss: 0.0285 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0052 - val_loss: 0.1045 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0049 - val_loss: 0.3297 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0049 - val_loss: 0.2305 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0048 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0048 - val_loss: 0.1098 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0045 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0046 - val_loss: 0.2088 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0044 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0046 - val_loss: 0.0896 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0044 - val_loss: 0.1106 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0044 - val_loss: 0.1194 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0043 - val_loss: 0.1093 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0042 - val_loss: 0.3263 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0044 - val_loss: 0.2587 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0044 - val_loss: 0.2294 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0042 - val_loss: 0.0672 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0042 - val_loss: 0.1227 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0042 - val_loss: 0.1618 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0039 - val_loss: 0.1375 - lr: 0.0012\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0039 - val_loss: 0.3298 - lr: 0.0012\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0037 - val_loss: 0.1718 - lr: 0.0012\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0038 - val_loss: 0.0339 - lr: 0.0012\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0036 - val_loss: 0.0251 - lr: 0.0012\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0038 - val_loss: 0.0774 - lr: 0.0012\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0037 - val_loss: 0.1870 - lr: 0.0012\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.3287 - lr: 0.0012\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0038 - val_loss: 0.1729 - lr: 0.0012\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0038 - val_loss: 0.1035 - lr: 0.0012\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0037 - val_loss: 0.3068 - lr: 0.0012\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.3297 - lr: 0.0012\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0038 - val_loss: 0.0264 - lr: 0.0012\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0037 - val_loss: 0.0777 - lr: 0.0012\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.3036 - lr: 0.0012\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0037 - val_loss: 0.0416 - lr: 0.0012\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.0212 - lr: 0.0012\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.0694 - lr: 0.0012\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0037 - val_loss: 0.0271 - lr: 0.0012\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0037 - val_loss: 0.0884 - lr: 0.0012\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.1792 - lr: 0.0012\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0037 - val_loss: 0.1832 - lr: 0.0012\n", + "Epoch 49/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.1116 - lr: 0.0012\n", + "Epoch 50/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.0808 - lr: 0.0012\n", + "Epoch 51/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.0581 - lr: 0.0012\n", + "Epoch 52/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.2975 - lr: 0.0012\n", + "Epoch 53/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.3298 - lr: 0.0012\n", + "Epoch 54/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.1062 - lr: 0.0012\n", + "Epoch 55/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.2787 - lr: 0.0012\n", + "Epoch 56/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.2698 - lr: 0.0012\n", + "Epoch 57/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.1503 - lr: 0.0012\n", + "Epoch 58/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.1154 - lr: 0.0012\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.3291 - lr: 0.0012\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.1021 - lr: 0.0012\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.3290 - lr: 0.0012\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0037 - val_loss: 0.1179 - lr: 0.0012\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.2032 - lr: 0.0012\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.2272 - lr: 0.0012\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.0712 - lr: 0.0012\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.0486 - lr: 0.0012\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.0588 - lr: 0.0012\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.2248 - lr: 0.0012\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0816 - lr: 6.2500e-04\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.2215 - lr: 6.2500e-04\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0740 - lr: 6.2500e-04\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.1668 - lr: 6.2500e-04\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.0555 - lr: 6.2500e-04\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.1026 - lr: 6.2500e-04\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.3258 - lr: 6.2500e-04\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.2715 - lr: 6.2500e-04\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.0951 - lr: 6.2500e-04\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0033 - val_loss: 0.0430 - lr: 6.2500e-04\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0033 - val_loss: 0.0836 - lr: 6.2500e-04\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.1372 - lr: 6.2500e-04\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1639 - lr: 6.2500e-04\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.2082 - lr: 6.2500e-04\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0034 - val_loss: 0.1799 - lr: 6.2500e-04\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.2539 - lr: 6.2500e-04\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0264 - lr: 6.2500e-04\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.3204 - lr: 6.2500e-04\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.1539 - lr: 6.2500e-04\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.1970 - lr: 6.2500e-04\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.3258 - lr: 6.2500e-04\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0034 - val_loss: 0.0241 - lr: 6.2500e-04\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.1025 - lr: 6.2500e-04\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.0581 - lr: 6.2500e-04\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.1295 - lr: 6.2500e-04\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.0380 - lr: 3.1250e-04\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1295 - lr: 3.1250e-04\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0032 - val_loss: 0.1576 - lr: 3.1250e-04\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0032 - val_loss: 0.0818 - lr: 3.1250e-04\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.1004 - lr: 3.1250e-04\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.1926 - lr: 3.1250e-04\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0031 - val_loss: 0.0154 - lr: 3.1250e-04\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0317 - lr: 3.1250e-04\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.2041 - lr: 3.1250e-04\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.1458 - lr: 3.1250e-04\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0564 - lr: 3.1250e-04\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.1855 - lr: 3.1250e-04\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0720 - lr: 3.1250e-04\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0563 - lr: 3.1250e-04\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1351 - lr: 3.1250e-04\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.2901 - lr: 3.1250e-04\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0184 - lr: 3.1250e-04\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1113 - lr: 3.1250e-04\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0638 - lr: 3.1250e-04\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.1021 - lr: 3.1250e-04\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.2921 - lr: 3.1250e-04\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0032 - val_loss: 0.0303 - lr: 3.1250e-04\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0222 - lr: 3.1250e-04\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.1348 - lr: 3.1250e-04\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0883 - lr: 3.1250e-04\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0580 - lr: 3.1250e-04\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1161 - lr: 3.1250e-04\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.1477 - lr: 3.1250e-04\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.2017 - lr: 3.1250e-04\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0487 - lr: 3.1250e-04\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0363 - lr: 3.1250e-04\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0388 - lr: 1.5625e-04\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0081 - lr: 1.5625e-04\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0058 - lr: 1.5625e-04\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0787 - lr: 1.5625e-04\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0035 - lr: 1.5625e-04\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0213 - lr: 1.5625e-04\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.1167 - lr: 1.5625e-04\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0346 - lr: 1.5625e-04\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0195 - lr: 1.5625e-04\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0259 - lr: 1.5625e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.1509 - lr: 1.5625e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1390 - lr: 1.5625e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0427 - lr: 1.5625e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0566 - lr: 1.5625e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0936 - lr: 1.5625e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0484 - lr: 1.5625e-04\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 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0s 4ms/step - loss: 0.0031 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0605 - lr: 1.5625e-04\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0188 - lr: 1.5625e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.2129 - lr: 1.5625e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0112 - lr: 7.8125e-05\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0066 - lr: 7.8125e-05\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0242 - lr: 7.8125e-05\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 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0s 5ms/step - loss: 0.0030 - val_loss: 0.0047 - lr: 3.9062e-05\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0071 - lr: 3.9062e-05\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0094 - lr: 3.9062e-05\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0370 - lr: 3.9062e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0294 - lr: 3.9062e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0049 - lr: 3.9062e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0050 - lr: 3.9062e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0250 - lr: 3.9062e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0110 - lr: 3.9062e-05\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0129 - lr: 3.9062e-05\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0041 - lr: 3.9062e-05\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0090 - lr: 3.9062e-05\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0064 - lr: 3.9062e-05\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0186 - lr: 3.9062e-05\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0029 - lr: 1.9531e-05\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0061 - lr: 1.9531e-05\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0036 - lr: 1.9531e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0038 - lr: 1.9531e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0054 - lr: 1.9531e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0046 - lr: 1.9531e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0059 - lr: 1.9531e-05\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0053 - lr: 1.9531e-05\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0063 - lr: 1.9531e-05\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0066 - lr: 1.9531e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0050 - lr: 1.9531e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0043 - lr: 1.9531e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0075 - lr: 1.9531e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0080 - lr: 1.9531e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0050 - lr: 1.9531e-05\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0033 - lr: 1.9531e-05\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 1.9531e-05\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0034 - lr: 1.9531e-05\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0038 - lr: 9.7656e-06\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0044 - lr: 9.7656e-06\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0031 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0038 - lr: 9.7656e-06\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0035 - lr: 9.7656e-06\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 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0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 634/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 635/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 636/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 637/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 638/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 639/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 640/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 641/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 642/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 643/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 644/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 645/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 646/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 647/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 648/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 649/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 650/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 651/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0031 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 652/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 653/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 654/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0030 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 655/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 1/1024\n", + "90/90 [==============================] - 2s 6ms/step - loss: 0.0207 - val_loss: 0.0283 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0696 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0074 - val_loss: 0.0785 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0065 - val_loss: 0.0864 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0056 - val_loss: 0.0482 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0052 - val_loss: 0.2884 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0050 - val_loss: 0.1310 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0048 - val_loss: 0.0609 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0048 - val_loss: 0.2213 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0045 - val_loss: 0.0551 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0047 - val_loss: 0.2143 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0044 - val_loss: 0.3298 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0045 - val_loss: 0.0287 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0043 - val_loss: 0.3180 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0043 - val_loss: 0.0358 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0042 - val_loss: 0.1368 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0043 - val_loss: 0.1200 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0041 - val_loss: 0.0494 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0041 - val_loss: 0.2281 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.2631 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0039 - val_loss: 0.3297 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0041 - val_loss: 0.2029 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0041 - val_loss: 0.0936 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.1149 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0039 - val_loss: 0.1352 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0040 - val_loss: 0.1189 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.0832 - lr: 0.0012\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0037 - val_loss: 0.0720 - lr: 0.0012\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.2276 - lr: 0.0012\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.2282 - lr: 0.0012\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.2270 - lr: 0.0012\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.3186 - lr: 0.0012\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.2281 - lr: 0.0012\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.0243 - lr: 0.0012\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0036 - val_loss: 0.2274 - lr: 0.0012\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.1110 - lr: 0.0012\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.0749 - lr: 0.0012\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.1473 - lr: 0.0012\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0036 - val_loss: 0.2074 - lr: 0.0012\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.1604 - lr: 0.0012\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.1541 - lr: 0.0012\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.2220 - lr: 0.0012\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.1884 - lr: 0.0012\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.2450 - lr: 0.0012\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.3236 - lr: 0.0012\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.1010 - lr: 0.0012\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.2125 - lr: 0.0012\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.2005 - lr: 0.0012\n", + "Epoch 49/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2269 - lr: 0.0012\n", + "Epoch 50/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.1559 - lr: 0.0012\n", + "Epoch 51/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.0870 - lr: 0.0012\n", + "Epoch 52/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2260 - lr: 0.0012\n", + "Epoch 53/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.3201 - lr: 0.0012\n", + "Epoch 54/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2205 - lr: 0.0012\n", + "Epoch 55/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2277 - lr: 0.0012\n", + "Epoch 56/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0340 - lr: 0.0012\n", + "Epoch 57/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.0148 - lr: 0.0012\n", + "Epoch 58/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.1359 - lr: 0.0012\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.3196 - lr: 0.0012\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.1481 - lr: 0.0012\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2695 - lr: 0.0012\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.1954 - lr: 0.0012\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.0340 - lr: 0.0012\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2283 - lr: 0.0012\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.1202 - lr: 0.0012\n", + "Epoch 66/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.0304 - lr: 0.0012\n", + "Epoch 67/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0793 - lr: 0.0012\n", + "Epoch 68/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0035 - val_loss: 0.1576 - lr: 0.0012\n", + "Epoch 69/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2251 - lr: 0.0012\n", + "Epoch 70/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0411 - lr: 0.0012\n", + "Epoch 71/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 72/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0033 - val_loss: 0.2281 - lr: 0.0012\n", + "Epoch 73/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.1713 - lr: 0.0012\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0222 - lr: 0.0012\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.3127 - lr: 0.0012\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0033 - val_loss: 0.0137 - lr: 0.0012\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.1090 - lr: 0.0012\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.0799 - lr: 0.0012\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.1102 - lr: 0.0012\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0035 - val_loss: 0.2145 - lr: 0.0012\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.1553 - lr: 0.0012\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.1595 - lr: 0.0012\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.1483 - lr: 0.0012\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0032 - val_loss: 0.2261 - lr: 0.0012\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2011 - lr: 0.0012\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0032 - val_loss: 0.2764 - lr: 0.0012\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2279 - lr: 0.0012\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0361 - lr: 0.0012\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2057 - lr: 0.0012\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.3079 - lr: 0.0012\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2283 - lr: 0.0012\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.0898 - lr: 0.0012\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0615 - lr: 0.0012\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.2653 - lr: 0.0012\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.0635 - lr: 0.0012\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0032 - val_loss: 0.3185 - lr: 0.0012\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 0.1530 - lr: 0.0012\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.2868 - lr: 0.0012\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.2256 - lr: 0.0012\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0031 - val_loss: 0.1929 - lr: 0.0012\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0031 - val_loss: 0.3201 - lr: 0.0012\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0030 - val_loss: 0.1670 - lr: 6.2500e-04\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0031 - val_loss: 0.0959 - lr: 6.2500e-04\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0031 - val_loss: 0.2233 - lr: 6.2500e-04\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0030 - val_loss: 0.0878 - lr: 6.2500e-04\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0030 - val_loss: 0.0340 - lr: 6.2500e-04\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0206 - lr: 6.2500e-04\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2278 - lr: 6.2500e-04\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.1677 - lr: 6.2500e-04\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0371 - lr: 6.2500e-04\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.2278 - lr: 6.2500e-04\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0905 - lr: 6.2500e-04\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0100 - lr: 6.2500e-04\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1231 - lr: 6.2500e-04\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.2395 - lr: 6.2500e-04\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0781 - lr: 6.2500e-04\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0293 - lr: 6.2500e-04\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0032 - val_loss: 0.0756 - lr: 6.2500e-04\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0030 - val_loss: 0.0174 - lr: 6.2500e-04\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1331 - lr: 6.2500e-04\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0700 - lr: 6.2500e-04\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0368 - lr: 6.2500e-04\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1642 - lr: 6.2500e-04\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0462 - lr: 6.2500e-04\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.2501 - lr: 6.2500e-04\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1292 - lr: 6.2500e-04\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.3043 - lr: 6.2500e-04\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0137 - lr: 6.2500e-04\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.1234 - lr: 6.2500e-04\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.2189 - lr: 6.2500e-04\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.1432 - lr: 6.2500e-04\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1098 - lr: 6.2500e-04\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0336 - lr: 6.2500e-04\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0404 - lr: 6.2500e-04\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0392 - lr: 6.2500e-04\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0031 - val_loss: 0.0341 - lr: 6.2500e-04\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1559 - lr: 6.2500e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0746 - lr: 6.2500e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1492 - lr: 3.1250e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1595 - lr: 3.1250e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0052 - lr: 3.1250e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0072 - lr: 3.1250e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0708 - lr: 3.1250e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.2029 - lr: 3.1250e-04\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0623 - lr: 3.1250e-04\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0137 - lr: 3.1250e-04\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0334 - lr: 3.1250e-04\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1248 - lr: 3.1250e-04\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0180 - lr: 3.1250e-04\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0117 - lr: 3.1250e-04\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1500 - lr: 3.1250e-04\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0389 - lr: 3.1250e-04\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0253 - lr: 3.1250e-04\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0846 - lr: 3.1250e-04\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0921 - lr: 3.1250e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0594 - lr: 3.1250e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.1702 - lr: 3.1250e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0073 - lr: 3.1250e-04\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0257 - lr: 3.1250e-04\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.2634 - lr: 3.1250e-04\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0272 - lr: 3.1250e-04\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1345 - lr: 3.1250e-04\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0145 - lr: 3.1250e-04\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0575 - lr: 3.1250e-04\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.1492 - lr: 3.1250e-04\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0387 - lr: 3.1250e-04\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0803 - lr: 1.5625e-04\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0309 - lr: 1.5625e-04\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0299 - lr: 1.5625e-04\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0084 - lr: 1.5625e-04\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0277 - lr: 1.5625e-04\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0238 - lr: 1.5625e-04\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0301 - lr: 1.5625e-04\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0422 - lr: 1.5625e-04\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0281 - lr: 1.5625e-04\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0057 - lr: 1.5625e-04\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0265 - lr: 1.5625e-04\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0078 - lr: 1.5625e-04\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0079 - lr: 1.5625e-04\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0075 - lr: 1.5625e-04\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0128 - lr: 7.8125e-05\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0434 - lr: 7.8125e-05\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0111 - lr: 7.8125e-05\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0076 - lr: 7.8125e-05\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0139 - lr: 7.8125e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0110 - lr: 7.8125e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0053 - lr: 7.8125e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0189 - lr: 7.8125e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0268 - lr: 7.8125e-05\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0190 - lr: 7.8125e-05\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0105 - lr: 7.8125e-05\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0113 - lr: 7.8125e-05\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0076 - lr: 7.8125e-05\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0215 - lr: 7.8125e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.1120 - lr: 7.8125e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0049 - lr: 7.8125e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0039 - lr: 7.8125e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0129 - lr: 7.8125e-05\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0131 - lr: 7.8125e-05\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0392 - lr: 7.8125e-05\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0503 - lr: 7.8125e-05\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0065 - lr: 7.8125e-05\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 7.8125e-05\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0065 - lr: 7.8125e-05\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0113 - lr: 7.8125e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0057 - lr: 7.8125e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 7.8125e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0059 - lr: 7.8125e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 7.8125e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0140 - lr: 7.8125e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0042 - lr: 7.8125e-05\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0051 - lr: 7.8125e-05\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0121 - lr: 7.8125e-05\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0180 - lr: 7.8125e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0079 - lr: 7.8125e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0075 - lr: 7.8125e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0706 - lr: 7.8125e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0275 - lr: 7.8125e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0263 - lr: 7.8125e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0338 - lr: 7.8125e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0275 - lr: 7.8125e-05\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0300 - lr: 7.8125e-05\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0170 - lr: 7.8125e-05\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0133 - lr: 7.8125e-05\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0235 - lr: 7.8125e-05\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0089 - lr: 3.9062e-05\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0138 - lr: 3.9062e-05\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0514 - lr: 3.9062e-05\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0054 - lr: 3.9062e-05\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0138 - lr: 3.9062e-05\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0044 - lr: 3.9062e-05\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0084 - lr: 3.9062e-05\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0137 - lr: 3.9062e-05\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0033 - lr: 3.9062e-05\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0114 - lr: 3.9062e-05\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0045 - lr: 3.9062e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0273 - lr: 3.9062e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 3.9062e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0042 - lr: 3.9062e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0057 - lr: 3.9062e-05\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0114 - lr: 3.9062e-05\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0071 - lr: 3.9062e-05\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0091 - lr: 3.9062e-05\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0048 - lr: 3.9062e-05\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0390 - lr: 3.9062e-05\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0061 - lr: 3.9062e-05\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0102 - lr: 3.9062e-05\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0058 - lr: 3.9062e-05\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0090 - lr: 3.9062e-05\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 3.9062e-05\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0152 - lr: 3.9062e-05\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0043 - lr: 3.9062e-05\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0047 - lr: 3.9062e-05\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0073 - lr: 3.9062e-05\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0344 - lr: 3.9062e-05\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0290 - lr: 3.9062e-05\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0242 - lr: 3.9062e-05\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0041 - lr: 3.9062e-05\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0031 - lr: 3.9062e-05\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0041 - lr: 3.9062e-05\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0053 - lr: 3.9062e-05\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0027 - lr: 3.9062e-05\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0083 - lr: 3.9062e-05\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0036 - lr: 3.9062e-05\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0068 - lr: 3.9062e-05\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0307 - lr: 3.9062e-05\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0053 - lr: 3.9062e-05\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0218 - lr: 3.9062e-05\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 3.9062e-05\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0057 - lr: 3.9062e-05\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0052 - lr: 3.9062e-05\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 3.9062e-05\n", + "Epoch 298/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0268 - lr: 3.9062e-05\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0033 - lr: 3.9062e-05\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0095 - lr: 3.9062e-05\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0100 - lr: 3.9062e-05\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0051 - lr: 3.9062e-05\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0082 - lr: 3.9062e-05\n", + "Epoch 312/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0181 - lr: 3.9062e-05\n", + "Epoch 313/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 3.9062e-05\n", + "Epoch 314/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 385/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 386/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0043 - lr: 9.7656e-06\n", + "Epoch 387/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0041 - lr: 9.7656e-06\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 9.7656e-06\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.8828e-06\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.8828e-06\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.8828e-06\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 432/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 433/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.4414e-06\n", + "Epoch 434/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 491/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.2207e-06\n", + "Epoch 492/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 493/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 494/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 495/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 496/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 504/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 505/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 506/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 507/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 508/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 509/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 510/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 511/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 6.1035e-07\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 520/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 521/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 522/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 523/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 524/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0030 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 525/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 526/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 536/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 537/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 538/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 539/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 540/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 541/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.0518e-07\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 550/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 551/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 552/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 565/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 566/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.5259e-07\n", + "Epoch 567/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 568/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 569/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 570/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 571/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 579/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 580/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 581/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 582/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 583/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 584/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 585/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.6294e-08\n", + "Epoch 586/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 611/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 612/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 613/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 614/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 615/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 616/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 3.8147e-08\n", + "Epoch 617/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 618/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 627/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 628/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 629/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 630/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 631/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 632/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 633/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 634/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 635/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 636/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 637/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 638/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 639/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 640/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 641/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.9073e-08\n", + "Epoch 642/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 643/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 644/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 645/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 646/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 647/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 648/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 649/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 650/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 651/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 652/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 653/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 654/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 655/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 656/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 657/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 658/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 659/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 660/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 661/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 662/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 663/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 664/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 665/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 666/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.5367e-09\n", + "Epoch 667/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 668/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 669/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 670/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 671/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 672/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 673/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 674/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 675/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 676/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 677/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 678/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 679/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 680/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 681/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 682/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 683/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 684/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 685/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 686/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 687/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 688/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 689/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 690/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 691/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.7684e-09\n", + "Epoch 692/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 693/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 694/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 695/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0025 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 696/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 697/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 698/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 699/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 700/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 701/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 702/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 703/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 704/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 705/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3842e-09\n", + "Epoch 706/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 779/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 780/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 781/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 782/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 783/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 784/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 785/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 2.9802e-10\n", + "Epoch 786/1024\n", + "90/90 [==============================] - 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0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 795/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 796/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 797/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 798/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 799/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 800/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 801/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.4901e-10\n", + "Epoch 802/1024\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 827/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 828/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 829/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 830/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 831/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 832/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 833/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 7.4506e-11\n", + "Epoch 834/1024\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 875/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 876/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 877/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 878/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 879/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 880/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 881/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 882/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 883/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 884/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 885/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 886/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 887/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 888/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 889/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 890/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 891/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.8626e-11\n", + "Epoch 892/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 893/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 894/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 895/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 896/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 897/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 898/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 899/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 900/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 901/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 902/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 903/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 904/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 905/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 906/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 907/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 908/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 909/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 910/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 911/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 912/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 913/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 914/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 915/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 916/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 9.3132e-12\n", + "Epoch 917/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 918/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 919/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 920/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 921/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 922/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 923/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 924/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 925/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 926/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 927/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 928/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 929/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 930/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 931/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 932/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 933/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 934/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 935/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 936/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 937/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 938/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 939/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 940/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 941/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 4.6566e-12\n", + "Epoch 942/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 943/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 944/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 945/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 946/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 947/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 948/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 949/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 950/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 951/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 952/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 953/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 954/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 955/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 956/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 957/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 958/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 959/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 960/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 961/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 962/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 963/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 964/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 965/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 966/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.3283e-12\n", + "Epoch 967/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 968/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 969/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 970/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 971/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 972/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 973/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 974/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 975/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 976/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 977/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 978/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 979/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 980/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 981/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 982/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 983/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 984/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 985/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 986/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 987/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 988/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 989/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 990/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 991/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 1.1642e-12\n", + "Epoch 992/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 993/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 994/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 995/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 996/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 997/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 998/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 999/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1000/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1001/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1002/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1003/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1004/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1005/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1006/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1007/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1008/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1009/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1010/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1011/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1012/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1013/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1014/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1015/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1016/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 5.8208e-13\n", + "Epoch 1017/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 1018/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 1019/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 1020/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 1021/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 1022/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 1023/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0024 - lr: 2.9104e-13\n", + "Epoch 1024/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0024 - lr: 2.9104e-13\n" + ] + } + ], + "source": [ + "epoch, batch_size = 1024, 64\n", + "history_plain_11 = plain_11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)\n", + "history_plain_5 = plain_5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Save the result to history.p" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# import pickle\n", + "# with open('history.p', 'wb') as f:\n", + "# pickle.dump({'history_11': history_plain_11, 'history_5':history_plain_5}, f)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Post analysis and drawing" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# with open(\"history.p\", 'rb') as f:\n", + "# data = pickle.load(f)\n", + "# history_plain_11, history_plain_5 = data['history_11'], data['history_5']" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "smoothing_windows = 16\n", + "def moving_average(x, w):\n", + " return np.convolve(x, np.ones(w), 'valid') / w" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain11', c='b')\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_plain_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain5', c='r')\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, min(len(history_plain_5.history['loss']), len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.set_ylim(0.23, 0.35)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (540, 0.257), c='b')\n", + "ax.annotate(\"5-layer\", (540, 0.245), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# plt.savefig(fname=\"fig1.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "seed(1050)\n", + "tensorflow.random.set_seed(1050)\n", + "shortcut5, shortcut11 = ShortCut5(input_shape=(1, 102)), ShortCut11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + 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"Epoch 23/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0040 - val_loss: 0.0580 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0041 - val_loss: 0.0845 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0042 - val_loss: 0.0505 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0041 - val_loss: 0.3296 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0037 - val_loss: 0.3286 - lr: 0.0012\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.1891 - lr: 0.0012\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0035 - val_loss: 0.2283 - lr: 0.0012\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0036 - val_loss: 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168/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.1070 - lr: 1.5625e-04\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0088 - lr: 1.5625e-04\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0599 - lr: 1.5625e-04\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.1704 - lr: 1.5625e-04\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0699 - lr: 1.5625e-04\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0718 - lr: 1.5625e-04\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 4ms/step 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183/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0242 - lr: 7.8125e-05\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0328 - lr: 7.8125e-05\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0452 - lr: 7.8125e-05\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0079 - lr: 7.8125e-05\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0407 - lr: 7.8125e-05\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0376 - lr: 7.8125e-05\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 5ms/step 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198/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0682 - lr: 7.8125e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0137 - lr: 7.8125e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0077 - lr: 7.8125e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0581 - lr: 7.8125e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0119 - lr: 7.8125e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0249 - lr: 7.8125e-05\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0126 - lr: 7.8125e-05\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0122 - lr: 7.8125e-05\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0791 - lr: 7.8125e-05\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0397 - lr: 7.8125e-05\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0831 - lr: 7.8125e-05\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0736 - lr: 7.8125e-05\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0428 - lr: 7.8125e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0077 - lr: 7.8125e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.1123 - lr: 7.8125e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0065 - lr: 7.8125e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0168 - lr: 7.8125e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0437 - lr: 7.8125e-05\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0087 - lr: 7.8125e-05\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0072 - lr: 7.8125e-05\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 7.8125e-05\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0216 - lr: 7.8125e-05\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0290 - lr: 7.8125e-05\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0245 - lr: 7.8125e-05\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0479 - lr: 7.8125e-05\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.1105 - lr: 7.8125e-05\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0056 - lr: 7.8125e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0070 - lr: 7.8125e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0242 - lr: 7.8125e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0062 - lr: 7.8125e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0433 - lr: 7.8125e-05\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0807 - lr: 7.8125e-05\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0177 - lr: 7.8125e-05\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0063 - lr: 7.8125e-05\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0230 - lr: 7.8125e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0808 - lr: 7.8125e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0511 - lr: 7.8125e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0167 - lr: 7.8125e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0216 - lr: 7.8125e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.1013 - lr: 7.8125e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0058 - lr: 7.8125e-05\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0088 - lr: 7.8125e-05\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0068 - lr: 7.8125e-05\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0106 - lr: 3.9062e-05\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0330 - lr: 3.9062e-05\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0045 - lr: 3.9062e-05\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0048 - lr: 3.9062e-05\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0083 - lr: 3.9062e-05\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0279 - lr: 3.9062e-05\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0042 - lr: 3.9062e-05\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 3.9062e-05\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0138 - lr: 3.9062e-05\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0035 - lr: 3.9062e-05\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0168 - lr: 3.9062e-05\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0049 - lr: 3.9062e-05\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 3.9062e-05\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0062 - lr: 3.9062e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0213 - lr: 3.9062e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0273 - lr: 3.9062e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0244 - lr: 3.9062e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0029 - val_loss: 0.0085 - lr: 3.9062e-05\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0075 - lr: 3.9062e-05\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0136 - lr: 3.9062e-05\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 3.9062e-05\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0153 - lr: 3.9062e-05\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0244 - lr: 3.9062e-05\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 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303/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0029 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0044 - lr: 9.7656e-06\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0029 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 4ms/step 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318/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 324/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 9.7656e-06\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 0s 3ms/step 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333/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 339/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 340/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 341/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 342/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 343/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 344/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 345/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 346/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 354/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 355/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 356/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0041 - lr: 9.7656e-06\n", + "Epoch 357/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 358/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 359/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 360/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0042 - lr: 9.7656e-06\n", + "Epoch 361/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 362/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0039 - lr: 9.7656e-06\n", + "Epoch 363/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0035 - lr: 9.7656e-06\n", + "Epoch 364/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 365/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 366/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0048 - lr: 9.7656e-06\n", + "Epoch 367/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 368/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 369/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 370/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 371/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 372/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 373/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0034 - lr: 4.8828e-06\n", + "Epoch 374/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 375/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 385/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 386/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0033 - lr: 4.8828e-06\n", + "Epoch 387/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 3ms/step 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528/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 4ms/step 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663/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 664/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 665/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 666/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 667/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 668/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 669/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 670/1024\n", + "90/90 [==============================] - 0s 4ms/step 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- loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 701/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 1/1024\n", + "90/90 [==============================] - 1s 5ms/step - loss: 0.0200 - val_loss: 0.0445 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0112 - val_loss: 0.0580 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0072 - val_loss: 0.0416 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0060 - val_loss: 0.0334 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0058 - val_loss: 0.1844 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0055 - val_loss: 0.1286 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 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lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0040 - val_loss: 0.0669 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0040 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0041 - val_loss: 0.2805 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0040 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0039 - val_loss: 0.1420 - lr: 0.0025\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0038 - val_loss: 0.2679 - lr: 0.0025\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0038 - val_loss: 0.1820 - lr: 0.0025\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 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"Epoch 46/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2283 - lr: 0.0012\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.2258 - lr: 0.0012\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.1109 - lr: 0.0012\n", + "Epoch 49/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0034 - val_loss: 0.1298 - lr: 0.0012\n", + "Epoch 50/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.1794 - lr: 0.0012\n", + "Epoch 51/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0033 - val_loss: 0.2858 - lr: 0.0012\n", + "Epoch 52/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0034 - val_loss: 0.1916 - lr: 0.0012\n", + "Epoch 53/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0033 - val_loss: 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val_loss: 0.0230 - lr: 7.8125e-05\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0689 - lr: 7.8125e-05\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0188 - lr: 7.8125e-05\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0118 - lr: 7.8125e-05\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0091 - lr: 7.8125e-05\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0065 - lr: 7.8125e-05\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0847 - lr: 7.8125e-05\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0205 - lr: 7.8125e-05\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0109 - lr: 7.8125e-05\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0397 - lr: 7.8125e-05\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0490 - lr: 7.8125e-05\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0317 - lr: 7.8125e-05\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0138 - lr: 7.8125e-05\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0121 - lr: 7.8125e-05\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0222 - lr: 7.8125e-05\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0434 - lr: 7.8125e-05\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0994 - lr: 7.8125e-05\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0131 - lr: 7.8125e-05\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0397 - lr: 7.8125e-05\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0112 - lr: 7.8125e-05\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0292 - lr: 7.8125e-05\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 3.9062e-05\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0178 - lr: 3.9062e-05\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0405 - lr: 3.9062e-05\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0060 - lr: 3.9062e-05\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0201 - lr: 3.9062e-05\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0094 - lr: 3.9062e-05\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0213 - lr: 3.9062e-05\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0244 - lr: 3.9062e-05\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0076 - lr: 3.9062e-05\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0373 - lr: 3.9062e-05\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0100 - lr: 3.9062e-05\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0081 - lr: 3.9062e-05\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0427 - lr: 3.9062e-05\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0158 - lr: 3.9062e-05\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0069 - lr: 3.9062e-05\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0413 - lr: 3.9062e-05\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0095 - lr: 3.9062e-05\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0095 - lr: 3.9062e-05\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0075 - lr: 3.9062e-05\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0052 - lr: 3.9062e-05\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0082 - lr: 3.9062e-05\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0077 - lr: 3.9062e-05\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0077 - lr: 3.9062e-05\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0191 - lr: 3.9062e-05\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0122 - lr: 1.9531e-05\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0030 - lr: 1.9531e-05\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0046 - lr: 1.9531e-05\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0035 - lr: 1.9531e-05\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 1.9531e-05\n", + "Epoch 191/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.9531e-05\n", + "Epoch 192/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0056 - lr: 1.9531e-05\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0084 - lr: 1.9531e-05\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0111 - lr: 1.9531e-05\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0038 - lr: 1.9531e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0035 - lr: 1.9531e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 1.9531e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0033 - lr: 1.9531e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 1.9531e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0053 - lr: 1.9531e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0044 - lr: 1.9531e-05\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0035 - lr: 1.9531e-05\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0044 - lr: 1.9531e-05\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0032 - lr: 1.9531e-05\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0090 - lr: 1.9531e-05\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0089 - lr: 1.9531e-05\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0071 - lr: 1.9531e-05\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0100 - lr: 1.9531e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0058 - lr: 1.9531e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0051 - lr: 9.7656e-06\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0082 - lr: 9.7656e-06\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0065 - lr: 9.7656e-06\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0032 - lr: 9.7656e-06\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0039 - lr: 9.7656e-06\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0049 - lr: 9.7656e-06\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0038 - lr: 9.7656e-06\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0038 - lr: 9.7656e-06\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0052 - lr: 9.7656e-06\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 249/1024\n", + "90/90 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val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0035 - lr: 4.8828e-06\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0032 - lr: 4.8828e-06\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 264/1024\n", + "90/90 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val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 279/1024\n", + "90/90 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val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 294/1024\n", + "90/90 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val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 302/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 309/1024\n", + "90/90 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val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 317/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 318/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 324/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 339/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.2207e-06\n", + "Epoch 354/1024\n", + "90/90 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val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 362/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 363/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 364/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 365/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 366/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 367/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 368/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 369/1024\n", + "90/90 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val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 384/1024\n", + "90/90 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val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 399/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 414/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 429/1024\n", + "90/90 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val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 437/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 442/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 443/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 444/1024\n", + "90/90 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val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 458/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 459/1024\n", + "90/90 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val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 467/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 474/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 482/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 485/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 486/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 487/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 489/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 504/1024\n", + "90/90 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val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 519/1024\n", + "90/90 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val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 579/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 587/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 588/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 589/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 590/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 591/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 592/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 593/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 594/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 602/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 603/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 604/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 605/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 606/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 607/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 608/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 609/1024\n", + "90/90 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val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 617/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 618/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 619/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 620/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 621/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 622/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 623/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 624/1024\n", + "90/90 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val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 632/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 633/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 634/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 635/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 636/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 637/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 638/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 639/1024\n", + "90/90 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val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 647/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 648/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 649/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 650/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 651/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 652/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 653/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 654/1024\n", + "90/90 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val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 692/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 693/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 694/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 695/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 696/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 697/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 698/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 699/1024\n", + "90/90 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val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 707/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 708/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 709/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 710/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 711/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 712/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 713/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 714/1024\n", + "90/90 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val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 722/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 723/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 724/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 725/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 726/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 727/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 728/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 729/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 737/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 738/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 739/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 740/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 741/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 742/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 743/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 744/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 752/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 753/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 754/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 755/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 756/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 757/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 758/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 759/1024\n", + "90/90 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val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 767/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 768/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 769/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 770/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 771/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 772/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 773/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 774/1024\n", + "90/90 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val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 782/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 783/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 784/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 785/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 786/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 787/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 788/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 789/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 857/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 858/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 859/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 860/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 861/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 862/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 863/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 864/1024\n", + "90/90 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val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 872/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 873/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 874/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 875/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 876/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 877/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 878/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 879/1024\n", + "90/90 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val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 887/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 888/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 889/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 890/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 891/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 892/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 893/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 894/1024\n", + "90/90 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val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 902/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 903/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 904/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 905/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 906/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 907/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 908/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 909/1024\n", + "90/90 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val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 917/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 918/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 919/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 920/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 921/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 922/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 923/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4552e-13\n", + "Epoch 924/1024\n", + "90/90 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val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 947/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 948/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 949/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 950/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 951/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 952/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 953/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.2760e-14\n", + "Epoch 954/1024\n", + "90/90 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val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 962/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 963/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 964/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 965/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 966/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 967/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 968/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 969/1024\n", + "90/90 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val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 977/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 978/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 979/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 980/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 981/1024\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 982/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.6380e-14\n", + "Epoch 983/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 984/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 985/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 986/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 987/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 988/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 989/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 990/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 991/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 992/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 993/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 994/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 995/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 996/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 997/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 998/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 999/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1000/1024\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1001/1024\n", + "90/90 [==============================] - 1s 11ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1002/1024\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1003/1024\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1004/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1005/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1006/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1007/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8190e-14\n", + "Epoch 1008/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1009/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1010/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1011/1024\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1012/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1013/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1014/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1015/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1016/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1017/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1018/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1019/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1020/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1021/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1022/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1023/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0029 - val_loss: 0.0025 - lr: 9.0949e-15\n", + "Epoch 1024/1024\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.0949e-15\n" + ] + } + ], + "source": [ + "epoch, batch_size = 1024, 64\n", + "history_shortcut_11 = shortcut11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)\n", + "history_shortcut_5 = shortcut5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_shortcut_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN11', c='b')\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_shortcut_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN5', c='r')\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, min(len(history_shortcut_5.history['loss']), len(history_shortcut_11.history['loss']) - smoothing_windows + 1))\n", + "ax.set_ylim(0.23, 0.35)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (540, 0.238), c='b')\n", + "ax.annotate(\"5-layer\", (540, 0.255), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "plt.savefig(fname=\"fig2_rmsprop.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import os\n", + "time_spent = (time.time() - time1) /60" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17.224380719661713 min\n" + ] + } + ], + "source": [ + "print(time_spent, \"min\")" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + } + ], + "metadata": { + "interpreter": { + "hash": "7f619fc91ee8bdab81d49e7c14228037474662e3f2d607687ae505108922fa06" + }, + "kernelspec": { + "display_name": "Python 3.9.7 64-bit ('base': conda)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} \ No newline at end of file diff --git a/02_model_training_sgd.ipynb b/02_model_training_sgd.ipynb new file mode 100644 index 0000000..69721dc --- /dev/null +++ b/02_model_training_sgd.ipynb @@ -0,0 +1,13253 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Model training Experiment" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "In order to provide the experimental evidence to back up the statement in the section 2.3.2 that our shortcut block can prevent degration problem.\n", + "\n", + "Plain Networks. We first evaluate 5-layer and 11-layer plain nets. Comparing to the 5-layer one, the 11-layer one has three times convolutional layers." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import pickle\n", + "import time\n", + "\n", + "import numpy as np\n", + "from matplotlib import ticker\n", + "from scipy.io import loadmat\n", + "from models import Plain5, Plain11, ShortCut5, ShortCut11\n", + "from sklearn.model_selection import train_test_split\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib notebook" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Load data\n", + "load data and split them into train, val, test" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape of data:\n", + "x_train: (5728, 1, 102), y_train: (5728, 1),\n", + "x_val: (2455, 1, 102), y_val: (2455, 1)\n", + "x_test: (3508, 1, 102), y_test: (3508, 1)\n" + ] + } + ], + "source": [ + "import random\n", + "from numpy.random import seed\n", + "import tensorflow\n", + "import time\n", + "seed(2718)\n", + "tensorflow.random.set_seed(2718)\n", + "time1 = time.time()\n", + "data = loadmat('dataset/mango/mango_dm_split.mat')\n", + "training_method = \"sgd\"\n", + "x_train, y_train, x_test, y_test = data['x_train'], data['y_train'], data['x_test'], data['y_test']\n", + "x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size=0.3, random_state=12, shuffle=True)\n", + "x_train, x_val, x_test = x_train[:, np.newaxis, :], x_val[:, np.newaxis, :], x_test[:, np.newaxis, :]\n", + "print(f\"shape of data:\\n\"\n", + " f\"x_train: {x_train.shape}, y_train: {y_train.shape},\\n\"\n", + " f\"x_val: {x_val.shape}, y_val: {y_val.shape}\\n\"\n", + " f\"x_test: {x_test.shape}, y_test: {y_test.shape}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Build Plain networks and Training" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "plain_5, plain_11 = Plain5(input_shape=(1, 102)), Plain11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/2000\n", + "90/90 [==============================] - 3s 10ms/step - loss: 0.0285 - val_loss: 0.0286 - lr: 0.0025\n", + "Epoch 2/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0273 - val_loss: 0.0287 - lr: 0.0025\n", + "Epoch 3/2000\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0266 - val_loss: 0.0292 - lr: 0.0025\n", + "Epoch 4/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0264 - val_loss: 0.0292 - lr: 0.0025\n", + "Epoch 5/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0258 - val_loss: 0.0289 - lr: 0.0025\n", + "Epoch 6/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0253 - val_loss: 0.0283 - lr: 0.0025\n", + "Epoch 7/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0251 - val_loss: 0.0269 - lr: 0.0025\n", + "Epoch 8/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0249 - val_loss: 0.0263 - lr: 0.0025\n", + "Epoch 9/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0247 - val_loss: 0.0263 - lr: 0.0025\n", + "Epoch 10/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0244 - val_loss: 0.0254 - lr: 0.0025\n", + "Epoch 11/2000\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0243 - val_loss: 0.0253 - lr: 0.0025\n", + "Epoch 12/2000\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0243 - val_loss: 0.0250 - lr: 0.0025\n", + "Epoch 13/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0240 - val_loss: 0.0259 - lr: 0.0025\n", + "Epoch 14/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0239 - val_loss: 0.0246 - lr: 0.0025\n", + "Epoch 15/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0237 - val_loss: 0.0251 - lr: 0.0025\n", + "Epoch 16/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0236 - val_loss: 0.0241 - lr: 0.0025\n", + "Epoch 17/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0234 - val_loss: 0.0241 - lr: 0.0025\n", + "Epoch 18/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0236 - val_loss: 0.0241 - lr: 0.0025\n", + "Epoch 19/2000\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0235 - val_loss: 0.0237 - lr: 0.0025\n", + "Epoch 20/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0234 - val_loss: 0.0235 - lr: 0.0025\n", + "Epoch 21/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0233 - val_loss: 0.0238 - lr: 0.0025\n", + "Epoch 22/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0233 - val_loss: 0.0238 - lr: 0.0025\n", + "Epoch 23/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0233 - val_loss: 0.0243 - lr: 0.0025\n", + "Epoch 24/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0231 - val_loss: 0.0233 - lr: 0.0025\n", + "Epoch 25/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0230 - val_loss: 0.0238 - lr: 0.0025\n", + "Epoch 26/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0229 - val_loss: 0.0241 - lr: 0.0025\n", + "Epoch 27/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0228 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 28/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0228 - val_loss: 0.0246 - lr: 0.0025\n", + "Epoch 29/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0230 - val_loss: 0.0229 - lr: 0.0025\n", + "Epoch 30/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0230 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 31/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0229 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 32/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0227 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 33/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0228 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 34/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0225 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 35/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0224 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 36/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0225 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 37/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0225 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 38/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0226 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 39/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0224 - val_loss: 0.0226 - lr: 0.0025\n", + "Epoch 40/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0224 - val_loss: 0.0243 - lr: 0.0025\n", + "Epoch 41/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0225 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 42/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 43/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0224 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 44/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0224 - val_loss: 0.0237 - lr: 0.0025\n", + "Epoch 45/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0224 - val_loss: 0.0242 - lr: 0.0025\n", + "Epoch 46/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0223 - val_loss: 0.0241 - lr: 0.0025\n", + "Epoch 47/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0219 - val_loss: 0.0237 - lr: 0.0025\n", + "Epoch 48/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0236 - lr: 0.0025\n", + "Epoch 49/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0240 - lr: 0.0025\n", + "Epoch 50/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0220 - val_loss: 0.0218 - lr: 0.0025\n", + "Epoch 51/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0221 - val_loss: 0.0228 - lr: 0.0025\n", + "Epoch 52/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0222 - val_loss: 0.0224 - lr: 0.0025\n", + "Epoch 53/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0221 - val_loss: 0.0228 - lr: 0.0025\n", + "Epoch 54/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0222 - val_loss: 0.0223 - lr: 0.0025\n", + "Epoch 55/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 56/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0221 - val_loss: 0.0225 - lr: 0.0025\n", + "Epoch 57/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0228 - lr: 0.0025\n", + "Epoch 58/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0219 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 59/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0219 - val_loss: 0.0227 - lr: 0.0025\n", + "Epoch 60/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 61/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0238 - lr: 0.0025\n", + "Epoch 62/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0217 - val_loss: 0.0236 - lr: 0.0025\n", + "Epoch 63/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0218 - val_loss: 0.0239 - lr: 0.0025\n", + "Epoch 64/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0220 - val_loss: 0.0250 - lr: 0.0025\n", + "Epoch 65/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0218 - val_loss: 0.0224 - lr: 0.0025\n", + "Epoch 66/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0219 - val_loss: 0.0222 - lr: 0.0025\n", + "Epoch 67/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0219 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 68/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0219 - val_loss: 0.0225 - lr: 0.0025\n", + "Epoch 69/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0218 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 70/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0217 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 71/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0217 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 72/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0219 - val_loss: 0.0223 - lr: 0.0025\n", + "Epoch 73/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0217 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 74/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0215 - val_loss: 0.0244 - lr: 0.0025\n", + "Epoch 75/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0216 - val_loss: 0.0217 - lr: 0.0025\n", + "Epoch 76/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0218 - val_loss: 0.0226 - lr: 0.0025\n", + "Epoch 77/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0215 - val_loss: 0.0264 - lr: 0.0025\n", + "Epoch 78/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0216 - val_loss: 0.0221 - lr: 0.0025\n", + "Epoch 79/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0216 - val_loss: 0.0227 - lr: 0.0025\n", + "Epoch 80/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0213 - val_loss: 0.0223 - lr: 0.0025\n", + "Epoch 81/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0217 - val_loss: 0.0246 - lr: 0.0025\n", + "Epoch 82/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0213 - val_loss: 0.0224 - lr: 0.0025\n", + "Epoch 83/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0214 - val_loss: 0.0217 - lr: 0.0025\n", + "Epoch 84/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0214 - val_loss: 0.0237 - lr: 0.0025\n", + "Epoch 85/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0212 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 86/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0215 - val_loss: 0.0233 - lr: 0.0025\n", + "Epoch 87/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0213 - val_loss: 0.0245 - lr: 0.0025\n", + "Epoch 88/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0214 - val_loss: 0.0258 - lr: 0.0025\n", + "Epoch 89/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0213 - val_loss: 0.0226 - lr: 0.0025\n", + "Epoch 90/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0219 - lr: 0.0025\n", + "Epoch 91/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0214 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 92/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0214 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 93/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0213 - val_loss: 0.0225 - lr: 0.0025\n", + "Epoch 94/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0212 - val_loss: 0.0226 - lr: 0.0025\n", + "Epoch 95/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0212 - val_loss: 0.0213 - lr: 0.0025\n", + "Epoch 96/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 97/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0211 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 98/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 99/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0213 - val_loss: 0.0241 - lr: 0.0025\n", + "Epoch 100/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0212 - val_loss: 0.0239 - lr: 0.0025\n", + "Epoch 101/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0242 - lr: 0.0025\n", + "Epoch 102/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0211 - val_loss: 0.0249 - lr: 0.0025\n", + "Epoch 103/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0211 - val_loss: 0.0252 - lr: 0.0025\n", + "Epoch 104/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0211 - val_loss: 0.0221 - lr: 0.0025\n", + "Epoch 105/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 106/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0222 - lr: 0.0025\n", + "Epoch 107/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0210 - val_loss: 0.0263 - lr: 0.0025\n", + "Epoch 108/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0275 - lr: 0.0025\n", + "Epoch 109/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0212 - val_loss: 0.0218 - lr: 0.0025\n", + "Epoch 110/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0209 - val_loss: 0.0217 - lr: 0.0025\n", + "Epoch 111/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0208 - val_loss: 0.0226 - lr: 0.0025\n", + "Epoch 112/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0211 - val_loss: 0.0213 - lr: 0.0025\n", + "Epoch 113/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0210 - val_loss: 0.0221 - lr: 0.0025\n", + "Epoch 114/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0209 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 115/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0208 - val_loss: 0.0235 - lr: 0.0025\n", + "Epoch 116/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 117/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0209 - val_loss: 0.0213 - lr: 0.0025\n", + "Epoch 118/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0208 - val_loss: 0.0264 - lr: 0.0025\n", + "Epoch 119/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0208 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 120/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0205 - val_loss: 0.0218 - lr: 0.0025\n", + "Epoch 121/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0208 - val_loss: 0.0221 - lr: 0.0025\n", + "Epoch 122/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0207 - val_loss: 0.0216 - lr: 0.0025\n", + "Epoch 123/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0208 - val_loss: 0.0224 - lr: 0.0025\n", + "Epoch 124/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0206 - val_loss: 0.0227 - lr: 0.0025\n", + "Epoch 125/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0210 - val_loss: 0.0290 - lr: 0.0025\n", + "Epoch 126/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0210 - val_loss: 0.0236 - lr: 0.0025\n", + "Epoch 127/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0209 - val_loss: 0.0230 - lr: 0.0025\n", + "Epoch 128/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0206 - val_loss: 0.0231 - lr: 0.0025\n", + "Epoch 129/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0206 - val_loss: 0.0233 - lr: 0.0025\n", + "Epoch 130/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0206 - val_loss: 0.0220 - lr: 0.0025\n", + "Epoch 131/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0207 - val_loss: 0.0218 - lr: 0.0025\n", + "Epoch 132/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0205 - val_loss: 0.0233 - lr: 0.0025\n", + "Epoch 133/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0207 - val_loss: 0.0225 - lr: 0.0025\n", + "Epoch 134/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0206 - val_loss: 0.0264 - lr: 0.0025\n", + "Epoch 135/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0204 - val_loss: 0.0227 - lr: 0.0025\n", + "Epoch 136/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0204 - val_loss: 0.0222 - lr: 0.0025\n", + "Epoch 137/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0215 - lr: 0.0025\n", + "Epoch 138/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0205 - val_loss: 0.0214 - lr: 0.0012\n", + "Epoch 139/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0205 - val_loss: 0.0212 - lr: 0.0012\n", + "Epoch 140/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0207 - val_loss: 0.0210 - lr: 0.0012\n", + "Epoch 141/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0206 - val_loss: 0.0230 - lr: 0.0012\n", + "Epoch 142/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0213 - lr: 0.0012\n", + "Epoch 143/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0213 - lr: 0.0012\n", + "Epoch 144/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0202 - val_loss: 0.0216 - lr: 0.0012\n", + "Epoch 145/2000\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0203 - val_loss: 0.0209 - lr: 0.0012\n", + "Epoch 146/2000\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0202 - val_loss: 0.0219 - lr: 0.0012\n", + "Epoch 147/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0205 - val_loss: 0.0258 - lr: 0.0012\n", + "Epoch 148/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0222 - lr: 0.0012\n", + "Epoch 149/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0205 - val_loss: 0.0216 - lr: 0.0012\n", + "Epoch 150/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0205 - val_loss: 0.0213 - lr: 0.0012\n", + "Epoch 151/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0206 - val_loss: 0.0210 - lr: 0.0012\n", + "Epoch 152/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0205 - val_loss: 0.0210 - lr: 0.0012\n", + "Epoch 153/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0203 - val_loss: 0.0226 - lr: 0.0012\n", + "Epoch 154/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0204 - val_loss: 0.0209 - lr: 0.0012\n", + "Epoch 155/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0262 - lr: 0.0012\n", + "Epoch 156/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0203 - val_loss: 0.0215 - lr: 0.0012\n", + "Epoch 157/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0203 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 158/2000\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0202 - val_loss: 0.0205 - lr: 0.0012\n", + "Epoch 159/2000\n", + "90/90 [==============================] - 1s 10ms/step - loss: 0.0206 - val_loss: 0.0215 - lr: 0.0012\n", + "Epoch 160/2000\n", + "90/90 [==============================] - 1s 13ms/step - loss: 0.0202 - val_loss: 0.0215 - lr: 0.0012\n", + "Epoch 161/2000\n", + "90/90 [==============================] - 1s 8ms/step - loss: 0.0204 - val_loss: 0.0211 - lr: 0.0012\n", + "Epoch 162/2000\n", + "90/90 [==============================] - 1s 7ms/step - loss: 0.0203 - val_loss: 0.0217 - lr: 0.0012\n", + "Epoch 163/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0202 - val_loss: 0.0217 - lr: 0.0012\n", + "Epoch 164/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0214 - lr: 0.0012\n", + "Epoch 165/2000\n", + "90/90 [==============================] - 0s 6ms/step - loss: 0.0201 - val_loss: 0.0212 - lr: 0.0012\n", + "Epoch 166/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0202 - val_loss: 0.0206 - lr: 0.0012\n", + "Epoch 167/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0200 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 168/2000\n", + "90/90 [==============================] - 0s 5ms/step - loss: 0.0202 - val_loss: 0.0225 - lr: 0.0012\n", + "Epoch 169/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0202 - val_loss: 0.0216 - lr: 0.0012\n", + "Epoch 170/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0201 - val_loss: 0.0213 - lr: 0.0012\n", + "Epoch 171/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0202 - val_loss: 0.0220 - lr: 0.0012\n", + "Epoch 172/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0203 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 173/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0201 - val_loss: 0.0220 - lr: 0.0012\n", + "Epoch 174/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0202 - val_loss: 0.0217 - lr: 0.0012\n", + "Epoch 175/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0203 - val_loss: 0.0232 - lr: 0.0012\n", + "Epoch 176/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0201 - val_loss: 0.0211 - lr: 0.0012\n", + "Epoch 177/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0012\n", + "Epoch 178/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0204 - val_loss: 0.0267 - lr: 0.0012\n", + "Epoch 179/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0202 - val_loss: 0.0207 - lr: 0.0012\n", + "Epoch 180/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0201 - val_loss: 0.0207 - lr: 0.0012\n", + "Epoch 181/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0212 - lr: 0.0012\n", + "Epoch 182/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0227 - lr: 0.0012\n", + "Epoch 183/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0216 - lr: 0.0012\n", + "Epoch 184/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0201 - val_loss: 0.0218 - lr: 0.0012\n", + "Epoch 185/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0202 - val_loss: 0.0225 - lr: 0.0012\n", + "Epoch 186/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0210 - lr: 0.0012\n", + "Epoch 187/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0218 - lr: 0.0012\n", + "Epoch 188/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0201 - val_loss: 0.0228 - lr: 0.0012\n", + "Epoch 189/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0203 - val_loss: 0.0209 - lr: 0.0012\n", + "Epoch 190/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0201 - val_loss: 0.0220 - lr: 0.0012\n", + "Epoch 191/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0200 - val_loss: 0.0200 - lr: 0.0012\n", + "Epoch 192/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 193/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 194/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0220 - lr: 0.0012\n", + "Epoch 195/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0213 - lr: 0.0012\n", + "Epoch 196/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0201 - val_loss: 0.0249 - lr: 0.0012\n", + "Epoch 197/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0199 - val_loss: 0.0224 - lr: 0.0012\n", + "Epoch 198/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 199/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0201 - val_loss: 0.0203 - lr: 0.0012\n", + "Epoch 200/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0220 - lr: 0.0012\n", + "Epoch 201/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0223 - lr: 0.0012\n", + "Epoch 202/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0200 - lr: 0.0012\n", + "Epoch 203/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0200 - val_loss: 0.0211 - lr: 0.0012\n", + "Epoch 204/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0200 - val_loss: 0.0211 - lr: 0.0012\n", + "Epoch 205/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0199 - val_loss: 0.0207 - lr: 0.0012\n", + "Epoch 206/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0206 - lr: 0.0012\n", + "Epoch 207/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0204 - lr: 0.0012\n", + "Epoch 208/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 209/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0216 - lr: 0.0012\n", + "Epoch 210/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0207 - lr: 0.0012\n", + "Epoch 211/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0204 - lr: 0.0012\n", + "Epoch 212/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0207 - lr: 0.0012\n", + "Epoch 213/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0216 - lr: 0.0012\n", + "Epoch 214/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0215 - lr: 0.0012\n", + "Epoch 215/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0215 - lr: 0.0012\n", + "Epoch 216/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0229 - lr: 0.0012\n", + "Epoch 217/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0205 - lr: 6.2500e-04\n", + "Epoch 218/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0216 - lr: 6.2500e-04\n", + "Epoch 219/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0204 - lr: 6.2500e-04\n", + "Epoch 220/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0210 - lr: 6.2500e-04\n", + "Epoch 221/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0212 - lr: 6.2500e-04\n", + "Epoch 222/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0208 - lr: 6.2500e-04\n", + "Epoch 223/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0218 - lr: 6.2500e-04\n", + "Epoch 224/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0211 - lr: 6.2500e-04\n", + "Epoch 225/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0205 - lr: 6.2500e-04\n", + "Epoch 226/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0203 - lr: 6.2500e-04\n", + "Epoch 227/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0205 - lr: 6.2500e-04\n", + "Epoch 228/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0198 - val_loss: 0.0212 - lr: 6.2500e-04\n", + "Epoch 229/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0200 - lr: 6.2500e-04\n", + "Epoch 230/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0195 - lr: 6.2500e-04\n", + "Epoch 231/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0204 - lr: 6.2500e-04\n", + "Epoch 232/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 6.2500e-04\n", + "Epoch 233/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0207 - lr: 6.2500e-04\n", + "Epoch 234/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0196 - val_loss: 0.0198 - lr: 6.2500e-04\n", + "Epoch 235/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0203 - lr: 6.2500e-04\n", + "Epoch 236/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0200 - lr: 6.2500e-04\n", + "Epoch 237/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0196 - val_loss: 0.0200 - lr: 6.2500e-04\n", + "Epoch 238/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0198 - lr: 6.2500e-04\n", + "Epoch 239/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0207 - lr: 6.2500e-04\n", + "Epoch 240/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0200 - lr: 6.2500e-04\n", + "Epoch 241/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0193 - val_loss: 0.0196 - lr: 6.2500e-04\n", + "Epoch 242/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0196 - lr: 6.2500e-04\n", + "Epoch 243/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0206 - lr: 6.2500e-04\n", + "Epoch 244/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0195 - val_loss: 0.0197 - lr: 6.2500e-04\n", + "Epoch 245/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0195 - val_loss: 0.0202 - lr: 6.2500e-04\n", + "Epoch 246/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 6.2500e-04\n", + "Epoch 247/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0196 - val_loss: 0.0207 - lr: 6.2500e-04\n", + "Epoch 248/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0195 - val_loss: 0.0208 - lr: 6.2500e-04\n", + "Epoch 249/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0197 - val_loss: 0.0206 - lr: 6.2500e-04\n", + "Epoch 250/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0206 - lr: 6.2500e-04\n", + "Epoch 251/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0195 - val_loss: 0.0198 - lr: 6.2500e-04\n", + "Epoch 252/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0194 - val_loss: 0.0196 - lr: 6.2500e-04\n", + "Epoch 253/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0192 - val_loss: 0.0207 - lr: 6.2500e-04\n", + "Epoch 254/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 6.2500e-04\n", + "Epoch 255/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 6.2500e-04\n", + "Epoch 256/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 257/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0195 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 258/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0194 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 259/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 260/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 261/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0195 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 262/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 263/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 264/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 265/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0191 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 266/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 267/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0192 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 268/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 269/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 270/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0192 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 271/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0193 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 272/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0193 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 273/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 274/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 275/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 276/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 277/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 278/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0192 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 279/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0192 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 280/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0193 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 281/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0191 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 282/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 283/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 284/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0195 - val_loss: 0.0200 - lr: 3.1250e-04\n", + "Epoch 285/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 286/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0193 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 287/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 288/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0194 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 289/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 290/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 291/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 292/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 293/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0190 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 294/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 295/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0192 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 296/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 297/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 298/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 299/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 300/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 301/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 302/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0189 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 303/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 304/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 305/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 306/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 307/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 308/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 309/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 310/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 311/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 312/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 313/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 314/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 315/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 316/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0192 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 317/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 318/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0193 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 319/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 320/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 321/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 322/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 323/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0191 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 324/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 325/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 326/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 327/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 328/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0192 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 329/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 330/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 331/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 332/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 333/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 334/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 335/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 336/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 337/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 338/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 339/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 340/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 341/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 342/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0189 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 343/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 344/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 345/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0191 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 346/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0188 - val_loss: 0.0187 - lr: 3.1250e-04\n", + "Epoch 347/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 348/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 349/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 350/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 351/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 352/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 353/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 354/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 355/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 356/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 357/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 358/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 359/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 360/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 361/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 362/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 363/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0187 - val_loss: 0.0185 - lr: 3.1250e-04\n", + "Epoch 364/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 365/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0187 - lr: 3.1250e-04\n", + "Epoch 366/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 367/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 368/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 369/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 370/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 371/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 372/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 373/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 374/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 375/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 376/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 377/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 378/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 379/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0186 - lr: 3.1250e-04\n", + "Epoch 380/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 381/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 382/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 383/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 384/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 385/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 386/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 387/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0184 - lr: 3.1250e-04\n", + "Epoch 388/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0186 - lr: 3.1250e-04\n", + "Epoch 389/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 390/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 391/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 392/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 393/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0188 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 394/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 395/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0187 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 396/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 397/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 398/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 399/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 400/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 401/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 402/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0186 - val_loss: 0.0183 - lr: 3.1250e-04\n", + "Epoch 403/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0186 - lr: 3.1250e-04\n", + "Epoch 404/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 405/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 406/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 407/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0212 - lr: 3.1250e-04\n", + "Epoch 408/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 409/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0197 - lr: 3.1250e-04\n", + "Epoch 410/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 411/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0183 - lr: 3.1250e-04\n", + "Epoch 412/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 413/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 414/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0200 - lr: 3.1250e-04\n", + "Epoch 415/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 416/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 417/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 418/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 419/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 420/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0184 - val_loss: 0.0181 - lr: 3.1250e-04\n", + "Epoch 421/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0185 - lr: 3.1250e-04\n", + "Epoch 422/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0194 - lr: 3.1250e-04\n", + "Epoch 423/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0187 - lr: 3.1250e-04\n", + "Epoch 424/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0187 - lr: 3.1250e-04\n", + "Epoch 425/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0183 - lr: 3.1250e-04\n", + "Epoch 426/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0185 - lr: 3.1250e-04\n", + "Epoch 427/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 428/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0191 - lr: 3.1250e-04\n", + "Epoch 429/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 430/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 431/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0183 - lr: 3.1250e-04\n", + "Epoch 432/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0186 - val_loss: 0.0185 - lr: 3.1250e-04\n", + "Epoch 433/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0186 - lr: 3.1250e-04\n", + "Epoch 434/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0185 - lr: 3.1250e-04\n", + "Epoch 435/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 436/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0185 - lr: 3.1250e-04\n", + "Epoch 437/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0183 - lr: 3.1250e-04\n", + "Epoch 438/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0182 - val_loss: 0.0179 - lr: 3.1250e-04\n", + "Epoch 439/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 440/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 441/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0187 - lr: 3.1250e-04\n", + "Epoch 442/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 443/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0193 - lr: 3.1250e-04\n", + "Epoch 444/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 445/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0196 - lr: 3.1250e-04\n", + "Epoch 446/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0183 - lr: 3.1250e-04\n", + "Epoch 447/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0180 - lr: 3.1250e-04\n", + "Epoch 448/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 449/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0195 - lr: 3.1250e-04\n", + "Epoch 450/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0200 - lr: 3.1250e-04\n", + "Epoch 451/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0186 - lr: 3.1250e-04\n", + "Epoch 452/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0186 - lr: 3.1250e-04\n", + "Epoch 453/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0188 - lr: 3.1250e-04\n", + "Epoch 454/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0183 - lr: 3.1250e-04\n", + "Epoch 455/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0189 - lr: 3.1250e-04\n", + "Epoch 456/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 457/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0199 - lr: 3.1250e-04\n", + "Epoch 458/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 459/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0186 - lr: 3.1250e-04\n", + "Epoch 460/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0182 - lr: 3.1250e-04\n", + "Epoch 461/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0198 - lr: 3.1250e-04\n", + "Epoch 462/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0185 - lr: 3.1250e-04\n", + "Epoch 463/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0184 - lr: 3.1250e-04\n", + "Epoch 464/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0185 - lr: 1.5625e-04\n", + "Epoch 465/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 466/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 467/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0195 - lr: 1.5625e-04\n", + "Epoch 468/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0189 - lr: 1.5625e-04\n", + "Epoch 469/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0180 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 470/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0182 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 471/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 472/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 473/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 474/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 475/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 476/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 477/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0180 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 478/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0189 - lr: 1.5625e-04\n", + "Epoch 479/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 480/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 481/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 482/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0185 - lr: 1.5625e-04\n", + "Epoch 483/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 484/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 485/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 486/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0182 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 487/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0190 - lr: 1.5625e-04\n", + "Epoch 488/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 489/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0179 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 490/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0185 - lr: 1.5625e-04\n", + "Epoch 491/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 492/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0179 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 493/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 494/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 495/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 496/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 497/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0183 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 498/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 499/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 500/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 501/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0179 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 502/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 503/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 504/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 505/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 506/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 507/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 508/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 509/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 510/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 511/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 512/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 513/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 514/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 515/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 516/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 517/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 518/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0185 - lr: 1.5625e-04\n", + "Epoch 519/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0189 - lr: 1.5625e-04\n", + "Epoch 520/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0192 - lr: 1.5625e-04\n", + "Epoch 521/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0186 - lr: 1.5625e-04\n", + "Epoch 522/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 523/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0187 - lr: 1.5625e-04\n", + "Epoch 524/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 525/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 526/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0178 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 527/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0178 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 528/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 529/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 530/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 531/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 532/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0177 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 533/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0181 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 534/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 535/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0179 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 536/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 537/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 538/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 539/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 540/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0180 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 541/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 542/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 543/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 544/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 545/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0191 - lr: 1.5625e-04\n", + "Epoch 546/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0186 - lr: 1.5625e-04\n", + "Epoch 547/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 548/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 549/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 550/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 551/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 552/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 553/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 554/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 555/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 556/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 557/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0179 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 558/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 559/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0176 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 560/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 561/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 562/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0186 - lr: 1.5625e-04\n", + "Epoch 563/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 564/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0193 - lr: 1.5625e-04\n", + "Epoch 565/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 566/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0188 - lr: 1.5625e-04\n", + "Epoch 567/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 568/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0174 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 569/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 570/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 571/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0174 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 572/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 573/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 574/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 575/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 576/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 577/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 578/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 579/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0175 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 580/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 581/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 582/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 583/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 584/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 585/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 586/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 587/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 588/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 589/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0186 - lr: 1.5625e-04\n", + "Epoch 590/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0191 - lr: 1.5625e-04\n", + "Epoch 591/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 592/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 593/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 594/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 595/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 596/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 597/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 598/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 599/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0176 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 600/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 601/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0174 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 602/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 603/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 604/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0177 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 605/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 606/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 607/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 608/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 609/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 610/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 611/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 612/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0185 - lr: 1.5625e-04\n", + "Epoch 613/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 614/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 615/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 616/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 617/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 618/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 619/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 620/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 621/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 622/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0191 - lr: 1.5625e-04\n", + "Epoch 623/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 624/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 625/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 626/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 627/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 628/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 629/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 630/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 631/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 632/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0174 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 633/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0175 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 634/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0170 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 635/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 636/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 637/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 638/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 639/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 640/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 641/2000\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0173 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 650/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 651/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 652/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 653/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 654/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0185 - lr: 1.5625e-04\n", + "Epoch 655/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 656/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 657/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 658/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 659/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 660/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 661/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 662/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 663/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 664/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 665/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 666/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0169 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 667/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0170 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 668/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 669/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 670/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 671/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 672/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 673/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0170 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 674/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0186 - lr: 1.5625e-04\n", + "Epoch 675/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 676/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 677/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 678/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0192 - lr: 1.5625e-04\n", + "Epoch 679/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 680/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0187 - lr: 1.5625e-04\n", + "Epoch 681/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 682/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0172 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 683/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 684/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 685/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 686/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 687/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 688/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 689/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 690/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 691/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0168 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 692/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 693/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 694/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 695/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0170 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 696/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 697/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 698/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 699/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 700/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 701/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 702/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 703/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 704/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 705/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 706/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 707/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0188 - lr: 1.5625e-04\n", + "Epoch 708/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0170 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 709/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0171 - val_loss: 0.0187 - lr: 1.5625e-04\n", + "Epoch 710/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 711/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 712/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 713/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 714/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 715/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 716/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 717/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 718/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 719/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 720/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 721/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 722/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 723/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 724/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 725/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 726/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 727/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 728/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 729/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 730/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 731/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 732/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 733/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 734/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 735/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 736/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 737/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 738/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 739/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 740/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 741/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 742/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 743/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 744/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 745/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 746/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 747/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 748/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 749/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 750/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 751/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0169 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 752/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 753/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 754/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 755/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 756/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 757/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0190 - lr: 1.5625e-04\n", + "Epoch 758/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 759/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 760/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0168 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 761/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 762/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 763/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 764/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0164 - lr: 7.8125e-05\n", + "Epoch 765/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0166 - lr: 7.8125e-05\n", + "Epoch 766/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0164 - lr: 7.8125e-05\n", + "Epoch 767/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0161 - lr: 7.8125e-05\n", + "Epoch 768/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0161 - lr: 7.8125e-05\n", + "Epoch 769/2000\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0165 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 826/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 827/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 828/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 829/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0163 - lr: 3.9062e-05\n", + "Epoch 830/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 831/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 832/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 833/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 834/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 835/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 836/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 837/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 838/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 839/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 840/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 841/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 842/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 843/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 844/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 845/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 846/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 847/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 848/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 849/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 850/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 851/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 852/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 853/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 854/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 855/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 856/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 857/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 858/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 859/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 860/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 861/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 862/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 863/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 864/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 865/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 866/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0168 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 867/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 868/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 869/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 870/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 871/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 872/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 873/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 874/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 875/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 876/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 877/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 878/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 879/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 880/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 881/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 882/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 883/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 884/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 885/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 886/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 887/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 888/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 889/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 890/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 891/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 892/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 893/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 894/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 895/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 896/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 897/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 898/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 899/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 900/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 901/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 902/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0162 - lr: 3.9062e-05\n", + "Epoch 903/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 904/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 905/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 906/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 907/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 908/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 909/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 910/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 3.9062e-05\n", + "Epoch 911/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0161 - lr: 3.9062e-05\n", + "Epoch 912/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 3.9062e-05\n", + "Epoch 913/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 914/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 915/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 916/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 917/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 918/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 919/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 920/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 921/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 922/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 923/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 924/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 925/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 926/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 927/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0160 - lr: 1.9531e-05\n", + "Epoch 928/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 929/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 930/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 931/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 932/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 933/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 934/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 935/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 936/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 937/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 938/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.9531e-05\n", + "Epoch 939/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.9531e-05\n", + "Epoch 940/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0160 - lr: 1.9531e-05\n", + "Epoch 941/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 942/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 943/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0160 - lr: 1.9531e-05\n", + "Epoch 944/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0160 - lr: 1.9531e-05\n", + "Epoch 945/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 946/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 947/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.9531e-05\n", + "Epoch 948/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 949/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 950/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.9531e-05\n", + "Epoch 951/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 952/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 953/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 954/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 955/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 956/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 957/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 958/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 959/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 960/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 961/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 962/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.9531e-05\n", + "Epoch 963/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.9531e-05\n", + "Epoch 964/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9531e-05\n", + "Epoch 965/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 966/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 967/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 968/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 969/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 970/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 971/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 972/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 973/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 974/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 975/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 976/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 977/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 978/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 979/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 980/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 981/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0168 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 982/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 983/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 984/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 985/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 986/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 987/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 988/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 989/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 990/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 991/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 992/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 993/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 994/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0162 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 995/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 996/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 997/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 998/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 999/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1000/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1001/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1002/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1003/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1004/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1005/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1006/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0168 - val_loss: 0.0158 - lr: 9.7656e-06\n", + "Epoch 1007/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 9.7656e-06\n", + "Epoch 1008/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1009/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1010/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1011/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 4.8828e-06\n", + "Epoch 1012/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 4.8828e-06\n", + "Epoch 1013/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 4.8828e-06\n", + "Epoch 1014/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1015/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1016/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1017/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1018/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1019/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1020/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1021/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1022/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 4.8828e-06\n", + "Epoch 1023/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 4.8828e-06\n", + "Epoch 1024/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 4.8828e-06\n", + "Epoch 1025/2000\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1074/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1075/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1076/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.2207e-06\n", + "Epoch 1077/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1078/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1079/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1080/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1081/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1082/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 1.2207e-06\n", + "Epoch 1083/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1084/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.2207e-06\n", + "Epoch 1085/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.2207e-06\n", + "Epoch 1086/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1087/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1088/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1089/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1090/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.2207e-06\n", + "Epoch 1091/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.2207e-06\n", + "Epoch 1092/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1093/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1094/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 6.1035e-07\n", + "Epoch 1095/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 6.1035e-07\n", + "Epoch 1096/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 6.1035e-07\n", + "Epoch 1097/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1098/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1099/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1100/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1101/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1102/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1103/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1104/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1105/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1106/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1107/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1108/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1109/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 6.1035e-07\n", + "Epoch 1110/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1111/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1112/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1113/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1114/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1115/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1116/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 6.1035e-07\n", + "Epoch 1117/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1118/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1119/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1120/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1121/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1122/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1123/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1124/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1125/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1126/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1127/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1128/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1129/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 3.0518e-07\n", + "Epoch 1130/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1131/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1132/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1133/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1134/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1135/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1136/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1137/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1138/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1139/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1140/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1141/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.0518e-07\n", + "Epoch 1142/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1143/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1144/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1145/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1146/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1147/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1148/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1149/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1150/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1151/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1152/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1153/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1154/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1155/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1156/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1157/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1158/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.5259e-07\n", + "Epoch 1159/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1160/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1161/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1162/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1163/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1164/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1165/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1166/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.5259e-07\n", + "Epoch 1167/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1168/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1169/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1170/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1171/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1172/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1173/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1174/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1175/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1176/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1177/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1178/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1179/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1180/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1181/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1182/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1183/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1184/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1185/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1186/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1187/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1188/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1189/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1190/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1191/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 7.6294e-08\n", + "Epoch 1192/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 3.8147e-08\n", + "Epoch 1193/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1194/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1195/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1196/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1197/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1198/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1199/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1200/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1201/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1202/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 3.8147e-08\n", + "Epoch 1203/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1204/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1205/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1206/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1207/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1208/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1209/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1210/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1211/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1212/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1213/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1214/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1215/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1216/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1217/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1218/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1219/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1220/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1221/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1222/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 3.8147e-08\n", + "Epoch 1223/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1224/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.9073e-08\n", + "Epoch 1225/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1226/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1227/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1228/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1229/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1230/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1231/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1232/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1233/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1234/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1235/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1236/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1237/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1238/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1239/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1240/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1241/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 1.9073e-08\n", + "Epoch 1242/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1243/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1244/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1245/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.9073e-08\n", + "Epoch 1246/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1247/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 1.9073e-08\n", + "Epoch 1248/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 9.5367e-09\n", + "Epoch 1249/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1250/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1251/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1252/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 9.5367e-09\n", + "Epoch 1253/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1254/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1255/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1256/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1257/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1258/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0171 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1259/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1260/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1261/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1262/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1263/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 9.5367e-09\n", + "Epoch 1264/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 9.5367e-09\n", + "Epoch 1265/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 9.5367e-09\n", + "Epoch 1266/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1267/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1268/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1269/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1270/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1271/2000\n", + "90/90 [==============================] - 1s 6ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 9.5367e-09\n", + "Epoch 1272/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0168 - val_loss: 0.0158 - lr: 9.5367e-09\n", + "Epoch 1273/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1274/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1275/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 4.7684e-09\n", + "Epoch 1276/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1277/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1278/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1279/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1280/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 4.7684e-09\n", + "Epoch 1281/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1282/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1283/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1284/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1285/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1286/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1287/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1288/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1289/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1290/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1291/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1292/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1293/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1294/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1295/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1296/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 4.7684e-09\n", + "Epoch 1297/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0159 - lr: 4.7684e-09\n", + "Epoch 1298/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1299/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1300/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1301/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1302/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1303/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1304/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1305/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1306/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1307/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1308/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1309/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1310/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1311/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1312/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1313/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1314/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1315/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1316/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1317/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1318/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1319/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1320/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1321/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 2.3842e-09\n", + "Epoch 1322/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 2.3842e-09\n", + "Epoch 1323/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1324/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0159 - lr: 1.1921e-09\n", + "Epoch 1325/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 1.1921e-09\n", + "Epoch 1326/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1327/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.1921e-09\n", + "Epoch 1328/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1329/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1330/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1331/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1332/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1333/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1334/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1335/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.1921e-09\n", + "Epoch 1336/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 1.1921e-09\n", + "Epoch 1337/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1338/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1339/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1340/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1341/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1342/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1343/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1344/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0161 - val_loss: 0.0159 - lr: 1.1921e-09\n", + "Epoch 1345/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 1.1921e-09\n", + "Epoch 1346/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0161 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1347/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 1.1921e-09\n", + "Epoch 1348/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0159 - lr: 5.9605e-10\n", + "Epoch 1349/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1350/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1351/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1352/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1353/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1354/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1355/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1356/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1357/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1358/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1359/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1360/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1361/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1362/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1363/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 5.9605e-10\n", + "Epoch 1364/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1365/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1366/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0159 - lr: 5.9605e-10\n", + "Epoch 1367/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0159 - lr: 5.9605e-10\n", + "Epoch 1368/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1369/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1370/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1371/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1372/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 5.9605e-10\n", + "Epoch 1373/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1374/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1375/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1376/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1377/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1378/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1379/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1380/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1381/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1382/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1383/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1384/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1385/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1386/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1387/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0167 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1388/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0163 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1389/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0169 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1390/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1391/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1392/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1393/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1394/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0162 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1395/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0164 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1396/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0166 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1397/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0165 - val_loss: 0.0158 - lr: 2.9802e-10\n", + "Epoch 1/2000\n", + "90/90 [==============================] - 1s 3ms/step - loss: 0.0331 - val_loss: 0.0290 - lr: 0.0025\n", + "Epoch 2/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0311 - val_loss: 0.0290 - lr: 0.0025\n", + "Epoch 3/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0299 - val_loss: 0.0290 - lr: 0.0025\n", + "Epoch 4/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0291 - val_loss: 0.0295 - lr: 0.0025\n", + "Epoch 5/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0283 - val_loss: 0.0307 - lr: 0.0025\n", + "Epoch 6/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0279 - val_loss: 0.0302 - lr: 0.0025\n", + "Epoch 7/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0273 - val_loss: 0.0288 - lr: 0.0025\n", + "Epoch 8/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0270 - val_loss: 0.0277 - lr: 0.0025\n", + "Epoch 9/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0267 - val_loss: 0.0271 - lr: 0.0025\n", + "Epoch 10/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0262 - val_loss: 0.0269 - lr: 0.0025\n", + "Epoch 11/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0260 - val_loss: 0.0266 - lr: 0.0025\n", + "Epoch 12/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0257 - val_loss: 0.0265 - lr: 0.0025\n", + "Epoch 13/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0255 - val_loss: 0.0264 - lr: 0.0025\n", + "Epoch 14/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0251 - val_loss: 0.0261 - lr: 0.0025\n", + "Epoch 15/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0251 - val_loss: 0.0259 - lr: 0.0025\n", + "Epoch 16/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0249 - val_loss: 0.0257 - lr: 0.0025\n", + "Epoch 17/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0247 - val_loss: 0.0255 - lr: 0.0025\n", + "Epoch 18/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0246 - val_loss: 0.0254 - lr: 0.0025\n", + "Epoch 19/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0244 - val_loss: 0.0254 - lr: 0.0025\n", + "Epoch 20/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0244 - val_loss: 0.0252 - lr: 0.0025\n", + "Epoch 21/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0241 - val_loss: 0.0252 - lr: 0.0025\n", + "Epoch 22/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0238 - val_loss: 0.0251 - lr: 0.0025\n", + "Epoch 23/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0240 - val_loss: 0.0251 - lr: 0.0025\n", + "Epoch 24/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0237 - val_loss: 0.0253 - lr: 0.0025\n", + "Epoch 25/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0235 - val_loss: 0.0249 - lr: 0.0025\n", + "Epoch 26/2000\n", + "90/90 [==============================] - 0s 937us/step - loss: 0.0234 - val_loss: 0.0249 - lr: 0.0025\n", + "Epoch 27/2000\n", + "90/90 [==============================] - 0s 909us/step - loss: 0.0233 - val_loss: 0.0249 - lr: 0.0025\n", + "Epoch 28/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0229 - val_loss: 0.0236 - lr: 0.0025\n", + "Epoch 29/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0231 - val_loss: 0.0235 - lr: 0.0025\n", + "Epoch 30/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0228 - val_loss: 0.0233 - lr: 0.0025\n", + "Epoch 31/2000\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0225 - val_loss: 0.0303 - lr: 0.0025\n", + "Epoch 32/2000\n", + "90/90 [==============================] - 0s 802us/step - loss: 0.0225 - val_loss: 0.0258 - lr: 0.0025\n", + "Epoch 33/2000\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0223 - val_loss: 0.0338 - lr: 0.0025\n", + "Epoch 34/2000\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0225 - val_loss: 0.0274 - lr: 0.0025\n", + "Epoch 35/2000\n", + "90/90 [==============================] - 0s 966us/step - loss: 0.0224 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 36/2000\n", + "90/90 [==============================] - 0s 876us/step - loss: 0.0221 - val_loss: 0.0232 - lr: 0.0025\n", + "Epoch 37/2000\n", + "90/90 [==============================] - 0s 886us/step - loss: 0.0221 - val_loss: 0.0368 - lr: 0.0025\n", + "Epoch 38/2000\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0219 - val_loss: 0.0433 - lr: 0.0025\n", + "Epoch 39/2000\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0219 - val_loss: 0.0234 - lr: 0.0025\n", + "Epoch 40/2000\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0218 - val_loss: 0.0276 - lr: 0.0025\n", + "Epoch 41/2000\n", + "90/90 [==============================] - 0s 885us/step - loss: 0.0217 - val_loss: 0.0346 - lr: 0.0025\n", + "Epoch 42/2000\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0215 - val_loss: 0.0298 - lr: 0.0025\n", + "Epoch 43/2000\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0215 - val_loss: 0.0409 - lr: 0.0025\n", + "Epoch 44/2000\n", + "90/90 [==============================] - 0s 882us/step - loss: 0.0214 - val_loss: 0.0381 - lr: 0.0025\n", + "Epoch 45/2000\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0213 - val_loss: 0.0420 - lr: 0.0025\n", + "Epoch 46/2000\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0212 - val_loss: 0.0606 - lr: 0.0025\n", + "Epoch 47/2000\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0212 - val_loss: 0.0244 - lr: 0.0025\n", + "Epoch 48/2000\n", + "90/90 [==============================] - 0s 919us/step - loss: 0.0210 - val_loss: 0.0278 - lr: 0.0025\n", + "Epoch 49/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0210 - val_loss: 0.0310 - lr: 0.0025\n", + "Epoch 50/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0208 - val_loss: 0.0422 - lr: 0.0025\n", + "Epoch 51/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0210 - val_loss: 0.0353 - lr: 0.0025\n", + "Epoch 52/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0207 - val_loss: 0.0661 - lr: 0.0025\n", + "Epoch 53/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0805 - lr: 0.0025\n", + "Epoch 54/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0207 - val_loss: 0.0608 - lr: 0.0025\n", + "Epoch 55/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0319 - lr: 0.0025\n", + "Epoch 56/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0204 - val_loss: 0.0478 - lr: 0.0025\n", + "Epoch 57/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0882 - lr: 0.0025\n", + "Epoch 58/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0574 - lr: 0.0025\n", + "Epoch 59/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0427 - lr: 0.0025\n", + "Epoch 60/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0964 - lr: 0.0025\n", + "Epoch 61/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0616 - lr: 0.0012\n", + "Epoch 62/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0474 - lr: 0.0012\n", + "Epoch 63/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0820 - lr: 0.0012\n", + "Epoch 64/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0812 - lr: 0.0012\n", + "Epoch 65/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0495 - lr: 0.0012\n", + "Epoch 66/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0275 - lr: 0.0012\n", + "Epoch 67/2000\n", + "90/90 [==============================] - 0s 924us/step - loss: 0.0198 - val_loss: 0.0722 - lr: 0.0012\n", + "Epoch 68/2000\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0197 - val_loss: 0.0592 - lr: 0.0012\n", + "Epoch 69/2000\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0196 - val_loss: 0.0621 - lr: 0.0012\n", + "Epoch 70/2000\n", + "90/90 [==============================] - 0s 810us/step - loss: 0.0195 - val_loss: 0.0778 - lr: 0.0012\n", + "Epoch 71/2000\n", + "90/90 [==============================] - 0s 808us/step - loss: 0.0196 - val_loss: 0.0601 - lr: 0.0012\n", + "Epoch 72/2000\n", + "90/90 [==============================] - 0s 801us/step - loss: 0.0194 - val_loss: 0.0792 - lr: 0.0012\n", + "Epoch 73/2000\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0196 - val_loss: 0.0790 - lr: 0.0012\n", + "Epoch 74/2000\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0194 - val_loss: 0.0979 - lr: 0.0012\n", + "Epoch 75/2000\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0192 - val_loss: 0.0958 - lr: 0.0012\n", + "Epoch 76/2000\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0192 - val_loss: 0.0708 - lr: 0.0012\n", + "Epoch 77/2000\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0191 - val_loss: 0.1278 - lr: 0.0012\n", + "Epoch 78/2000\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0190 - val_loss: 0.0856 - lr: 0.0012\n", + "Epoch 79/2000\n", + "90/90 [==============================] - 0s 790us/step - loss: 0.0191 - val_loss: 0.0968 - lr: 0.0012\n", + "Epoch 80/2000\n", + "90/90 [==============================] - 0s 808us/step - loss: 0.0190 - val_loss: 0.1149 - lr: 0.0012\n", + "Epoch 81/2000\n", + "90/90 [==============================] - 0s 803us/step - loss: 0.0190 - val_loss: 0.0948 - lr: 0.0012\n", + "Epoch 82/2000\n", + "90/90 [==============================] - 0s 812us/step - loss: 0.0189 - val_loss: 0.0955 - lr: 0.0012\n", + "Epoch 83/2000\n", + "90/90 [==============================] - 0s 809us/step - loss: 0.0189 - val_loss: 0.1571 - lr: 0.0012\n", + "Epoch 84/2000\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0187 - val_loss: 0.1345 - lr: 0.0012\n", + "Epoch 85/2000\n", + "90/90 [==============================] - 0s 797us/step - loss: 0.0186 - val_loss: 0.1416 - lr: 0.0012\n", + "Epoch 86/2000\n", + "90/90 [==============================] - 0s 788us/step - loss: 0.0186 - val_loss: 0.1060 - lr: 6.2500e-04\n", + "Epoch 87/2000\n", + "90/90 [==============================] - 0s 813us/step - loss: 0.0188 - val_loss: 0.0760 - lr: 6.2500e-04\n", + "Epoch 88/2000\n", + "90/90 [==============================] - 0s 798us/step - loss: 0.0187 - val_loss: 0.0422 - lr: 6.2500e-04\n", + "Epoch 89/2000\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0185 - val_loss: 0.0698 - lr: 6.2500e-04\n", + "Epoch 90/2000\n", + "90/90 [==============================] - 0s 805us/step - loss: 0.0185 - val_loss: 0.0438 - lr: 6.2500e-04\n", + "Epoch 91/2000\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0188 - val_loss: 0.0578 - lr: 6.2500e-04\n", + "Epoch 92/2000\n", + "90/90 [==============================] - 0s 902us/step - loss: 0.0184 - val_loss: 0.0723 - lr: 6.2500e-04\n", + "Epoch 93/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0184 - val_loss: 0.0576 - lr: 6.2500e-04\n", + "Epoch 94/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0465 - lr: 6.2500e-04\n", + "Epoch 95/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0548 - lr: 6.2500e-04\n", + "Epoch 96/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0737 - lr: 6.2500e-04\n", + "Epoch 97/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0677 - lr: 6.2500e-04\n", + "Epoch 98/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0554 - lr: 6.2500e-04\n", + "Epoch 99/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0183 - val_loss: 0.0455 - lr: 6.2500e-04\n", + "Epoch 100/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0639 - lr: 6.2500e-04\n", + "Epoch 101/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0875 - lr: 6.2500e-04\n", + "Epoch 102/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0183 - val_loss: 0.0558 - lr: 6.2500e-04\n", + "Epoch 103/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0880 - lr: 6.2500e-04\n", + "Epoch 104/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0895 - lr: 6.2500e-04\n", + "Epoch 105/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0676 - lr: 6.2500e-04\n", + "Epoch 106/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0995 - lr: 6.2500e-04\n", + "Epoch 107/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0779 - lr: 6.2500e-04\n", + "Epoch 108/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0568 - lr: 6.2500e-04\n", + "Epoch 109/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0557 - lr: 6.2500e-04\n", + "Epoch 110/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0179 - val_loss: 0.0757 - lr: 6.2500e-04\n", + "Epoch 111/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0711 - lr: 3.1250e-04\n", + "Epoch 112/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0179 - val_loss: 0.0298 - lr: 3.1250e-04\n", + "Epoch 113/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0177 - val_loss: 0.0224 - lr: 3.1250e-04\n", + "Epoch 114/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0176 - val_loss: 0.0308 - lr: 3.1250e-04\n", + "Epoch 115/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0350 - lr: 3.1250e-04\n", + "Epoch 116/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0179 - val_loss: 0.0454 - lr: 3.1250e-04\n", + "Epoch 117/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0329 - lr: 3.1250e-04\n", + "Epoch 118/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0179 - val_loss: 0.0478 - lr: 3.1250e-04\n", + "Epoch 119/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0269 - lr: 3.1250e-04\n", + "Epoch 120/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0308 - lr: 3.1250e-04\n", + "Epoch 121/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0177 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 122/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0259 - lr: 3.1250e-04\n", + "Epoch 123/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0335 - lr: 3.1250e-04\n", + "Epoch 124/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0274 - lr: 3.1250e-04\n", + "Epoch 125/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0322 - lr: 3.1250e-04\n", + "Epoch 126/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0377 - lr: 3.1250e-04\n", + "Epoch 127/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0417 - lr: 3.1250e-04\n", + "Epoch 128/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0245 - lr: 3.1250e-04\n", + "Epoch 129/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0348 - lr: 3.1250e-04\n", + "Epoch 130/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0467 - lr: 3.1250e-04\n", + "Epoch 131/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0453 - lr: 3.1250e-04\n", + "Epoch 132/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0254 - lr: 3.1250e-04\n", + "Epoch 133/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0306 - lr: 3.1250e-04\n", + "Epoch 134/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0177 - lr: 3.1250e-04\n", + "Epoch 135/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0380 - lr: 3.1250e-04\n", + "Epoch 136/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0217 - lr: 3.1250e-04\n", + "Epoch 137/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0362 - lr: 3.1250e-04\n", + "Epoch 138/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0332 - lr: 3.1250e-04\n", + "Epoch 139/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0247 - lr: 3.1250e-04\n", + "Epoch 140/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0385 - lr: 3.1250e-04\n", + "Epoch 141/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0238 - lr: 3.1250e-04\n", + "Epoch 142/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0192 - lr: 3.1250e-04\n", + "Epoch 143/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0272 - lr: 3.1250e-04\n", + "Epoch 144/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0289 - lr: 3.1250e-04\n", + "Epoch 145/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0337 - lr: 3.1250e-04\n", + "Epoch 146/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0375 - lr: 3.1250e-04\n", + "Epoch 147/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0350 - lr: 3.1250e-04\n", + "Epoch 148/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0374 - lr: 3.1250e-04\n", + "Epoch 149/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0213 - lr: 3.1250e-04\n", + "Epoch 150/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0190 - lr: 3.1250e-04\n", + "Epoch 151/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0360 - lr: 3.1250e-04\n", + "Epoch 152/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0182 - lr: 3.1250e-04\n", + "Epoch 153/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0318 - lr: 3.1250e-04\n", + "Epoch 154/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0277 - lr: 3.1250e-04\n", + "Epoch 155/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0239 - lr: 3.1250e-04\n", + "Epoch 156/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0409 - lr: 3.1250e-04\n", + "Epoch 157/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0324 - lr: 3.1250e-04\n", + "Epoch 158/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0293 - lr: 3.1250e-04\n", + "Epoch 159/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0431 - lr: 3.1250e-04\n", + "Epoch 160/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0233 - lr: 1.5625e-04\n", + "Epoch 161/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 162/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0227 - lr: 1.5625e-04\n", + "Epoch 163/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 164/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0183 - lr: 1.5625e-04\n", + "Epoch 165/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0187 - lr: 1.5625e-04\n", + "Epoch 166/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 167/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 168/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 169/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 170/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 171/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 172/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 173/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0199 - lr: 1.5625e-04\n", + "Epoch 174/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0234 - lr: 1.5625e-04\n", + "Epoch 175/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0196 - lr: 1.5625e-04\n", + "Epoch 176/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 177/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0219 - lr: 1.5625e-04\n", + "Epoch 178/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 179/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 180/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 181/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 182/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0208 - lr: 1.5625e-04\n", + "Epoch 183/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 184/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 185/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 186/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 187/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 188/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 189/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 190/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0216 - lr: 1.5625e-04\n", + "Epoch 191/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0213 - lr: 1.5625e-04\n", + "Epoch 192/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 193/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0165 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 194/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0208 - lr: 1.5625e-04\n", + "Epoch 195/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 196/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 197/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 198/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 199/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 200/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0164 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 201/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 202/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 203/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 204/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0186 - lr: 1.5625e-04\n", + "Epoch 205/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 206/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 207/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0164 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 208/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 209/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 210/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0185 - lr: 1.5625e-04\n", + "Epoch 211/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 212/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 213/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0165 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 214/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 215/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0164 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 216/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0165 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 217/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 218/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0164 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 219/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0164 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 220/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0165 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 221/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 222/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 223/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 224/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 225/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 226/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 227/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 228/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0165 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 229/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0192 - lr: 1.5625e-04\n", + "Epoch 230/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 231/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 232/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 233/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 234/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 235/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0193 - lr: 1.5625e-04\n", + "Epoch 236/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 237/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0164 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 238/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 239/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 240/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 241/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 242/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 243/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 244/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 245/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 246/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 247/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 248/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 249/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 250/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 251/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0161 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 252/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 253/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 254/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0161 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 255/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 256/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 257/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 258/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 259/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 260/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 261/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 262/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0189 - lr: 1.5625e-04\n", + "Epoch 263/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 264/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 265/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 266/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 267/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0181 - lr: 1.5625e-04\n", + "Epoch 268/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 269/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 270/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 271/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0161 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 272/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0170 - lr: 1.5625e-04\n", + "Epoch 273/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 274/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 275/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 276/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0207 - lr: 1.5625e-04\n", + "Epoch 277/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 278/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 279/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 280/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 281/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 282/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 283/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 284/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 285/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 286/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 287/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 288/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 289/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 290/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 291/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 292/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 293/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 294/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 295/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 296/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0175 - lr: 1.5625e-04\n", + "Epoch 297/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 298/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 299/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 300/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 301/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 302/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 303/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 304/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 305/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0187 - lr: 1.5625e-04\n", + "Epoch 306/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 307/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 308/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 309/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 310/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 311/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 312/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 313/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 314/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 315/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 316/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 317/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 318/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 319/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0169 - lr: 1.5625e-04\n", + "Epoch 320/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0230 - lr: 1.5625e-04\n", + "Epoch 321/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 322/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 323/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 324/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 325/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0179 - lr: 1.5625e-04\n", + "Epoch 326/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 327/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 328/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 329/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 330/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 331/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 332/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 333/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 334/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 335/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 336/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 337/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 338/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 339/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 340/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 341/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 342/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 343/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 344/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 345/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 346/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 347/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 348/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 349/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 350/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 351/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 352/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0176 - lr: 1.5625e-04\n", + "Epoch 353/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 354/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 355/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 356/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 357/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 358/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 359/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 360/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 361/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 362/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 363/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 364/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 365/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 366/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 367/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0153 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 368/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0151 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 369/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0153 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 370/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 371/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 372/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 373/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 374/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 375/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0151 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 376/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 377/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0153 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 378/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0151 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 379/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 380/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 381/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 382/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 383/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 384/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0149 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 385/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 386/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 387/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0149 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 388/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 389/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 390/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 391/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 392/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 393/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 394/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 395/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 396/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 397/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 398/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 399/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 400/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 401/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 402/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 403/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 404/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 405/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 406/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0194 - lr: 1.5625e-04\n", + "Epoch 407/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 408/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 409/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0148 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 410/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 411/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 412/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 413/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 414/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 415/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 416/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 417/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 418/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 419/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 420/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 421/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 422/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 423/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 424/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 425/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 426/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 427/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 428/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 429/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 430/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 431/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 432/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 433/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 434/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 435/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 436/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 437/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 438/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 439/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 440/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 441/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 442/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 443/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 444/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 445/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 446/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 447/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 448/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0173 - lr: 1.5625e-04\n", + "Epoch 449/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0143 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 450/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 451/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 452/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 453/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 454/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0174 - lr: 1.5625e-04\n", + "Epoch 455/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 456/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 457/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 458/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 459/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 460/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 461/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 462/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 463/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 464/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 465/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 466/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 467/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 468/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 469/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 470/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 471/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0142 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 472/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 473/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 474/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 475/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 476/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 477/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 478/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0143 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 479/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 480/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 481/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 482/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 483/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 484/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 485/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 486/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 487/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 488/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0182 - lr: 1.5625e-04\n", + "Epoch 489/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 490/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 491/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 492/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 493/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 494/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0184 - lr: 1.5625e-04\n", + "Epoch 495/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 496/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 497/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 498/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 499/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 500/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 501/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 502/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 503/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0213 - lr: 1.5625e-04\n", + "Epoch 504/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 505/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 506/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0190 - lr: 1.5625e-04\n", + "Epoch 507/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 508/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0178 - lr: 1.5625e-04\n", + "Epoch 509/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0140 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 510/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 511/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 512/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 513/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 514/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 515/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 516/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 517/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 518/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 519/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 520/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 521/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 522/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 523/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 524/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 525/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 526/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 527/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 528/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 529/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 530/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 531/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0166 - lr: 1.5625e-04\n", + "Epoch 532/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 533/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 534/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 535/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 536/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 537/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 538/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 539/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 540/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 541/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 542/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 543/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 544/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 545/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 546/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 547/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 548/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 549/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 550/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 551/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 552/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 553/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 554/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0157 - lr: 1.5625e-04\n", + "Epoch 555/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 556/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 557/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 558/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0153 - lr: 1.5625e-04\n", + "Epoch 559/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 560/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 561/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0158 - lr: 1.5625e-04\n", + "Epoch 562/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0138 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 563/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 564/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 565/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0149 - lr: 1.5625e-04\n", + "Epoch 566/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 567/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 568/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0138 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 569/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 570/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 571/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 572/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 573/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0206 - lr: 1.5625e-04\n", + "Epoch 574/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 575/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 576/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 577/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0138 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 578/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 579/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 580/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 581/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 582/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 583/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 584/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 585/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 586/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0151 - lr: 1.5625e-04\n", + "Epoch 587/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 588/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0135 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 589/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 590/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 591/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 592/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0136 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 593/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 594/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 595/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 596/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 597/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 598/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 599/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 600/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 601/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 602/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 603/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 604/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 605/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0148 - lr: 1.5625e-04\n", + "Epoch 606/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 607/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 608/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 609/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 610/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 611/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 612/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0156 - lr: 1.5625e-04\n", + "Epoch 613/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 614/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 615/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 616/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 617/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 618/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 619/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 620/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 621/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0171 - lr: 1.5625e-04\n", + "Epoch 622/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 623/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 624/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 625/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 626/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0145 - lr: 1.5625e-04\n", + "Epoch 627/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 628/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 629/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 630/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0131 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 631/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 632/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 633/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0133 - val_loss: 0.0143 - lr: 1.5625e-04\n", + "Epoch 634/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0133 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 635/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0132 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 636/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 637/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0133 - val_loss: 0.0155 - lr: 1.5625e-04\n", + "Epoch 638/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 639/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0180 - lr: 1.5625e-04\n", + "Epoch 640/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0132 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 641/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0133 - val_loss: 0.0152 - lr: 1.5625e-04\n", + "Epoch 642/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0134 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 643/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0132 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 644/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 645/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 646/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0129 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 647/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 648/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 649/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0132 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 650/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0133 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 651/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 652/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0150 - lr: 1.5625e-04\n", + "Epoch 653/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 654/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0132 - val_loss: 0.0141 - lr: 1.5625e-04\n", + "Epoch 655/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0130 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 656/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0131 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 657/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0133 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 658/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0132 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 659/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0128 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 660/2000\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0129 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 701/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 702/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0177 - lr: 1.5625e-04\n", + "Epoch 703/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0128 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 704/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 705/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 706/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 707/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 708/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 709/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0131 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 710/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 711/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 712/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 713/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 714/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 715/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 716/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 717/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 718/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 719/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 720/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 721/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0154 - lr: 1.5625e-04\n", + "Epoch 722/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 723/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 724/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 725/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 726/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0168 - lr: 1.5625e-04\n", + "Epoch 727/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0134 - lr: 1.5625e-04\n", + "Epoch 728/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 729/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0138 - lr: 1.5625e-04\n", + "Epoch 730/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 731/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 732/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 733/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0167 - lr: 1.5625e-04\n", + "Epoch 734/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 735/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 736/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 737/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 738/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0139 - lr: 1.5625e-04\n", + "Epoch 739/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 740/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0140 - lr: 1.5625e-04\n", + "Epoch 741/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 742/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0133 - lr: 1.5625e-04\n", + "Epoch 743/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0146 - lr: 1.5625e-04\n", + "Epoch 744/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 745/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 746/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0132 - lr: 1.5625e-04\n", + "Epoch 747/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 748/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0130 - lr: 1.5625e-04\n", + "Epoch 749/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 750/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0135 - lr: 1.5625e-04\n", + "Epoch 751/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 752/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0136 - lr: 1.5625e-04\n", + "Epoch 753/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 754/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0125 - lr: 1.5625e-04\n", + "Epoch 755/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0147 - lr: 1.5625e-04\n", + "Epoch 756/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0172 - lr: 1.5625e-04\n", + "Epoch 757/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 758/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 759/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 760/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 761/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 762/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0126 - val_loss: 0.0130 - lr: 1.5625e-04\n", + "Epoch 763/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 764/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0142 - lr: 1.5625e-04\n", + "Epoch 765/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0129 - lr: 1.5625e-04\n", + "Epoch 766/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0125 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 767/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0128 - lr: 1.5625e-04\n", + "Epoch 768/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0137 - lr: 1.5625e-04\n", + "Epoch 769/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 770/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0131 - lr: 1.5625e-04\n", + "Epoch 771/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0127 - val_loss: 0.0126 - lr: 1.5625e-04\n", + "Epoch 772/2000\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0125 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 781/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0128 - lr: 7.8125e-05\n", + "Epoch 782/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 783/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 784/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 785/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0135 - lr: 7.8125e-05\n", + "Epoch 786/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 787/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0128 - lr: 7.8125e-05\n", + "Epoch 788/2000\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 813/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 814/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0128 - lr: 7.8125e-05\n", + "Epoch 815/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0136 - lr: 7.8125e-05\n", + "Epoch 816/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 817/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 818/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0123 - lr: 7.8125e-05\n", + "Epoch 819/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0129 - lr: 7.8125e-05\n", + "Epoch 820/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0126 - val_loss: 0.0128 - lr: 7.8125e-05\n", + "Epoch 821/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 822/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 823/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0127 - lr: 7.8125e-05\n", + "Epoch 824/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 825/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 826/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0125 - lr: 7.8125e-05\n", + "Epoch 827/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0138 - lr: 7.8125e-05\n", + "Epoch 828/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0128 - lr: 7.8125e-05\n", + "Epoch 829/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0140 - lr: 7.8125e-05\n", + "Epoch 830/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 831/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 832/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 833/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 834/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0130 - lr: 7.8125e-05\n", + "Epoch 835/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 7.8125e-05\n", + "Epoch 836/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0129 - lr: 7.8125e-05\n", + "Epoch 837/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 838/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0132 - lr: 7.8125e-05\n", + "Epoch 839/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.8125e-05\n", + "Epoch 840/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0129 - lr: 7.8125e-05\n", + "Epoch 841/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 842/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0127 - lr: 7.8125e-05\n", + "Epoch 843/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 7.8125e-05\n", + "Epoch 844/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0129 - lr: 3.9062e-05\n", + "Epoch 845/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 846/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 847/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 848/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 849/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 850/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 851/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0131 - lr: 3.9062e-05\n", + "Epoch 852/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0131 - lr: 3.9062e-05\n", + "Epoch 853/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 854/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 855/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 856/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 857/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 858/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0130 - lr: 3.9062e-05\n", + "Epoch 859/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 860/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 861/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 862/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0130 - lr: 3.9062e-05\n", + "Epoch 863/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 864/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 865/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 866/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 867/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 868/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 869/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 870/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0132 - lr: 3.9062e-05\n", + "Epoch 871/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 872/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 873/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 874/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 875/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 876/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 877/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 878/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 879/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 880/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 881/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 882/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 883/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 884/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 885/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 886/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 887/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 888/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 889/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 890/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0129 - lr: 3.9062e-05\n", + "Epoch 891/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 892/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0129 - lr: 3.9062e-05\n", + "Epoch 893/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 894/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0132 - lr: 3.9062e-05\n", + "Epoch 895/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 896/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 897/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 898/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 899/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0129 - lr: 3.9062e-05\n", + "Epoch 900/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0123 - lr: 3.9062e-05\n", + "Epoch 901/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0128 - lr: 3.9062e-05\n", + "Epoch 902/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 3.9062e-05\n", + "Epoch 903/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 3.9062e-05\n", + "Epoch 904/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 905/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 906/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 3.9062e-05\n", + "Epoch 907/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.9062e-05\n", + "Epoch 908/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0125 - val_loss: 0.0129 - lr: 3.9062e-05\n", + "Epoch 909/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9531e-05\n", + "Epoch 910/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 1.9531e-05\n", + "Epoch 911/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 1.9531e-05\n", + "Epoch 912/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 1.9531e-05\n", + "Epoch 913/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 1.9531e-05\n", + "Epoch 914/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 1.9531e-05\n", + "Epoch 915/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0127 - lr: 1.9531e-05\n", + "Epoch 916/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.9531e-05\n", + "Epoch 917/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9531e-05\n", + "Epoch 918/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0128 - lr: 1.9531e-05\n", + "Epoch 919/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 1.9531e-05\n", + "Epoch 920/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0123 - lr: 1.9531e-05\n", + "Epoch 921/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0124 - lr: 1.9531e-05\n", + "Epoch 922/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 1.9531e-05\n", + "Epoch 923/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9531e-05\n", + "Epoch 924/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 1.9531e-05\n", + "Epoch 925/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.9531e-05\n", + "Epoch 926/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9531e-05\n", + "Epoch 927/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.9531e-05\n", + "Epoch 928/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 1.9531e-05\n", + "Epoch 929/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0128 - lr: 1.9531e-05\n", + "Epoch 930/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0129 - lr: 1.9531e-05\n", + "Epoch 931/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0124 - lr: 1.9531e-05\n", + "Epoch 932/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0123 - lr: 1.9531e-05\n", + "Epoch 933/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 1.9531e-05\n", + "Epoch 934/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0128 - lr: 9.7656e-06\n", + "Epoch 935/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0127 - lr: 9.7656e-06\n", + "Epoch 936/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 937/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 938/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 939/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 940/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 941/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0125 - lr: 9.7656e-06\n", + "Epoch 942/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 943/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 944/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 9.7656e-06\n", + "Epoch 945/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0127 - lr: 9.7656e-06\n", + "Epoch 946/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 947/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 948/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 9.7656e-06\n", + "Epoch 949/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0125 - lr: 9.7656e-06\n", + "Epoch 950/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 951/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 952/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 9.7656e-06\n", + "Epoch 953/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 9.7656e-06\n", + "Epoch 954/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 955/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 956/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 9.7656e-06\n", + "Epoch 957/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 9.7656e-06\n", + "Epoch 958/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 9.7656e-06\n", + "Epoch 959/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 960/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 961/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 962/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 963/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 964/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 965/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 966/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 967/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 968/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 969/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 970/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 971/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 972/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0127 - lr: 4.8828e-06\n", + "Epoch 973/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 974/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 975/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 976/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 977/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 978/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0127 - lr: 4.8828e-06\n", + "Epoch 979/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 980/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 981/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 982/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.8828e-06\n", + "Epoch 983/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 4.8828e-06\n", + "Epoch 984/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 985/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 986/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 987/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 988/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 989/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 990/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 991/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 2.4414e-06\n", + "Epoch 992/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 993/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 994/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 995/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 996/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 997/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 998/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 999/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1000/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1001/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1002/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1003/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1004/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1005/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1006/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1007/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.4414e-06\n", + "Epoch 1008/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0125 - lr: 2.4414e-06\n", + "Epoch 1009/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1010/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1011/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1012/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1013/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1014/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1015/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1016/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1017/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1018/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1019/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1020/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1021/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1022/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1023/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1024/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1025/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1026/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1027/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1028/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1029/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1030/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1031/2000\n", + "90/90 [==============================] - 0s 3ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1032/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1033/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.2207e-06\n", + "Epoch 1034/2000\n", + "90/90 [==============================] - 0s 4ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1035/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1036/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1037/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1038/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1039/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1040/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1041/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1042/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1043/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 6.1035e-07\n", + "Epoch 1044/2000\n", + "90/90 [==============================] - 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0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 1.5259e-07\n", + "Epoch 1085/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1086/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1087/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1088/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 1.5259e-07\n", + "Epoch 1089/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1090/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1091/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1092/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1093/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1094/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1095/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1096/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1097/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1098/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1099/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1100/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1101/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1102/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1103/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1104/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1105/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1106/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1107/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1108/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.5259e-07\n", + "Epoch 1109/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1110/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1111/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1112/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1113/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1114/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1115/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1116/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1117/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1118/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1119/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1120/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1121/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1122/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1123/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1124/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1125/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1126/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1127/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1128/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1129/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1130/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1131/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1132/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1133/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.6294e-08\n", + "Epoch 1134/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1135/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1136/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1137/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1138/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1139/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1140/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1141/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1142/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1143/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1144/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1145/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1146/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1147/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1148/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1149/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1150/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1151/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1152/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1153/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1154/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1155/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1156/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1157/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 3.8147e-08\n", + "Epoch 1158/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.8147e-08\n", + "Epoch 1159/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1160/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1161/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1162/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1163/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1164/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1165/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1166/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1167/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1168/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1169/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1170/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1171/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1172/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1173/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1174/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1175/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1176/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1177/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1178/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1179/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1180/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1181/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1182/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0118 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1183/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.9073e-08\n", + "Epoch 1184/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1185/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1186/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1187/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1188/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0127 - lr: 9.5367e-09\n", + "Epoch 1189/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1190/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1191/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1192/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1193/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1194/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1195/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1196/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1197/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1198/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1199/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1200/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1201/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1202/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1203/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0127 - lr: 9.5367e-09\n", + "Epoch 1204/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1205/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1206/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1207/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1208/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.5367e-09\n", + "Epoch 1209/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1210/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1211/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1212/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1213/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1214/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0125 - lr: 4.7684e-09\n", + "Epoch 1215/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1216/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1217/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1218/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1219/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1220/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1221/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1222/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1223/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1224/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1225/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1226/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1227/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1228/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1229/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1230/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1231/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1232/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1233/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.7684e-09\n", + "Epoch 1234/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1235/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1236/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1237/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1238/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0127 - lr: 2.3842e-09\n", + "Epoch 1239/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1240/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1241/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1242/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1243/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1244/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1245/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1246/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1247/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1248/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1249/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1250/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1251/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1252/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1253/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 2.3842e-09\n", + "Epoch 1254/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1255/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1256/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1257/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1258/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.3842e-09\n", + "Epoch 1259/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1260/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1261/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1262/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1263/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1264/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1265/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 1.1921e-09\n", + "Epoch 1266/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1267/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1268/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1269/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1270/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1271/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1272/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1273/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1274/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1275/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1276/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1277/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1278/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1279/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1280/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1281/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1282/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1283/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1921e-09\n", + "Epoch 1284/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1285/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1286/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1287/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1288/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1289/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1290/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1291/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1292/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1293/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1294/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1295/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1296/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1297/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1298/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1299/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1300/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1301/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1302/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1303/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1304/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1305/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1306/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1307/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1308/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.9605e-10\n", + "Epoch 1309/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1310/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1311/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1312/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1313/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1314/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1315/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0127 - lr: 2.9802e-10\n", + "Epoch 1316/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1317/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1318/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1319/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1320/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1321/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1322/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1323/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1324/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1325/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1326/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1327/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1328/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1329/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1330/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1331/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1332/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0125 - lr: 2.9802e-10\n", + "Epoch 1333/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9802e-10\n", + "Epoch 1334/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1335/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1336/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1337/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1338/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1339/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1340/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1341/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1342/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1343/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1344/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1345/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1346/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1347/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1348/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1349/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1350/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1351/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1352/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1353/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1354/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1355/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1356/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1357/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1358/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4901e-10\n", + "Epoch 1359/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1360/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1361/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1362/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1363/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1364/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1365/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1366/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1367/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1368/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1369/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1370/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1371/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1372/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1373/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1374/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1375/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1376/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1377/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1378/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1379/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1380/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1381/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1382/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1383/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.4506e-11\n", + "Epoch 1384/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1385/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1386/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1387/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1388/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1389/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1390/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1391/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1392/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1393/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1394/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1395/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1396/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1397/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1398/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1399/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1400/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1401/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1402/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1403/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1404/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1405/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1406/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1407/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1408/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.7253e-11\n", + "Epoch 1409/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1410/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1411/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1412/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1413/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1414/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1415/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1416/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 1.8626e-11\n", + "Epoch 1417/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1418/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1419/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1420/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1421/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1422/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1423/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1424/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1425/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1426/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1427/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1428/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1429/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 1.8626e-11\n", + "Epoch 1430/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1431/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1432/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1433/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8626e-11\n", + "Epoch 1434/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1435/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1436/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1437/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 9.3132e-12\n", + "Epoch 1438/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 9.3132e-12\n", + "Epoch 1439/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1440/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1441/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1442/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1443/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1444/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1445/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1446/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1447/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1448/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1449/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 9.3132e-12\n", + "Epoch 1450/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1451/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1452/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1453/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1454/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1455/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1456/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1457/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1458/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.3132e-12\n", + "Epoch 1459/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1460/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1461/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1462/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1463/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1464/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1465/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1466/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1467/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1468/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1469/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1470/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 4.6566e-12\n", + "Epoch 1471/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1472/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1473/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1474/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1475/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1476/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1477/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1478/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1479/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1480/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 4.6566e-12\n", + "Epoch 1481/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1482/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.6566e-12\n", + "Epoch 1483/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 4.6566e-12\n", + "Epoch 1484/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1485/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1486/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1487/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1488/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1489/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1490/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1491/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1492/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1493/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1494/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1495/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1496/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1497/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1498/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1499/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1500/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1501/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1502/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1503/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1504/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1505/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 2.3283e-12\n", + "Epoch 1506/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1507/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1508/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.3283e-12\n", + "Epoch 1509/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1510/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1511/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1512/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 1.1642e-12\n", + "Epoch 1513/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1514/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1515/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1516/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1517/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1518/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1519/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1520/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1521/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1522/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1523/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1524/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1525/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1526/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1527/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1528/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1529/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1530/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1531/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1532/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1533/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1642e-12\n", + "Epoch 1534/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1535/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1536/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1537/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1538/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 5.8208e-13\n", + "Epoch 1539/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1540/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1541/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1542/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1543/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1544/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1545/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1546/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 5.8208e-13\n", + "Epoch 1547/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 5.8208e-13\n", + "Epoch 1548/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1549/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1550/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1551/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1552/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1553/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1554/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1555/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1556/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1557/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1558/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.8208e-13\n", + "Epoch 1559/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1560/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1561/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1562/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1563/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1564/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1565/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1566/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1567/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1568/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1569/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1570/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1571/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 2.9104e-13\n", + "Epoch 1572/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1573/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1574/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1575/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1576/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1577/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1578/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1579/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1580/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1581/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1582/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1583/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.9104e-13\n", + "Epoch 1584/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1585/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1586/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1587/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1588/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1589/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1590/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0125 - lr: 1.4552e-13\n", + "Epoch 1591/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1592/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1593/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1594/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1595/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1596/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1597/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1598/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1599/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1600/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1601/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1602/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1603/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1604/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1605/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1606/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1607/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1608/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4552e-13\n", + "Epoch 1609/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1610/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1611/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1612/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1613/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1614/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1615/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1616/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1617/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1618/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1619/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1620/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1621/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1622/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1623/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1624/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1625/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1626/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1627/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1628/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1629/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1630/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1631/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1632/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1633/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.2760e-14\n", + "Epoch 1634/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1635/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1636/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1637/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1638/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1639/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1640/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1641/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1642/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1643/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1644/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1645/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1646/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1647/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1648/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1649/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1650/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1651/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1652/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1653/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1654/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1655/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1656/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1657/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1658/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 3.6380e-14\n", + "Epoch 1659/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1660/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1661/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1662/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1663/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1664/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1665/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1666/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1667/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1668/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1669/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1670/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 1.8190e-14\n", + "Epoch 1671/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1672/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1673/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1674/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1675/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1676/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1677/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1678/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1679/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1680/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1681/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1682/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1683/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.8190e-14\n", + "Epoch 1684/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1685/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1686/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1687/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1688/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1689/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1690/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1691/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0125 - lr: 9.0949e-15\n", + "Epoch 1692/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1693/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1694/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1695/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1696/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1697/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1698/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1699/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1700/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 9.0949e-15\n", + "Epoch 1701/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1702/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1703/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1704/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1705/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1706/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1707/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1708/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 9.0949e-15\n", + "Epoch 1709/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1710/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1711/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1712/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1713/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1714/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1715/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1716/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1717/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1718/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1719/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1720/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1721/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1722/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1723/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1724/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1725/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1726/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1727/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1728/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1729/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1730/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1731/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1732/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1733/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 4.5475e-15\n", + "Epoch 1734/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1735/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1736/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1737/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1738/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1739/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1740/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1741/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1742/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1743/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1744/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1745/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1746/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1747/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1748/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1749/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1750/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1751/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1752/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1753/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1754/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1755/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1756/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1757/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1758/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.2737e-15\n", + "Epoch 1759/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1760/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1761/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1762/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1763/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1764/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 1.1369e-15\n", + "Epoch 1765/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1766/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1767/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1768/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1769/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1770/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1771/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1772/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1773/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1774/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1775/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1776/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1777/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1778/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1779/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1780/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1781/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1782/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1783/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.1369e-15\n", + "Epoch 1784/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1785/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1786/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1787/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1788/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1789/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1790/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1791/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1792/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1793/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1794/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1795/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1796/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1797/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1798/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1799/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1800/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1801/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1802/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1803/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1804/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1805/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1806/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1807/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1808/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 5.6843e-16\n", + "Epoch 1809/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1810/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1811/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1812/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1813/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1814/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1815/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1816/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1817/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1818/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1819/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1820/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1821/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1822/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1823/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1824/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1825/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1826/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1827/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1828/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1829/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1830/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1831/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1832/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1833/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 2.8422e-16\n", + "Epoch 1834/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1835/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1836/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1837/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1838/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1839/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1840/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0127 - lr: 1.4211e-16\n", + "Epoch 1841/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1842/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1843/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1844/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1845/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0125 - lr: 1.4211e-16\n", + "Epoch 1846/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1847/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1848/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1849/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1850/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1851/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1852/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1853/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1854/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1855/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1856/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1857/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1858/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 1.4211e-16\n", + "Epoch 1859/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1860/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1861/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1862/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1863/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1864/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1865/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0120 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1866/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1867/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1868/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1869/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1870/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1871/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1872/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1873/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1874/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1875/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0124 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1876/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1877/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1878/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1879/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0122 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1880/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0125 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1881/2000\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1882/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0126 - lr: 7.1054e-17\n", + "Epoch 1883/2000\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0126 - lr: 7.1054e-17\n" + ] + } + ], + "source": [ + "epoch, batch_size = 2000, 64\n", + "history_plain_11 = plain_11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)\n", + "history_plain_5 = plain_5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size,\n", + " method=training_method)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Save the result to history.p" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# import pickle\n", + "# with open('history.p', 'wb') as f:\n", + "# pickle.dump({'history_11': history_plain_11, 'history_5':history_plain_5}, f)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Post analysis and drawing" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# with open(\"history.p\", 'rb') as f:\n", + "# data = pickle.load(f)\n", + "# history_plain_11, history_plain_5 = data['history_11'], data['history_5']" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "smoothing_windows = 16\n", + "def moving_average(x, w):\n", + " return np.convolve(x, np.ones(w), 'valid') / w" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain11', c='b')\n", + "ax.plot(x, 100*moving_average(history_plain_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_plain_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='plain5', c='r')\n", + "ax.plot(x, 100*moving_average(history_plain_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, min(len(history_plain_5.history['loss']), len(history_plain_11.history['loss']) - smoothing_windows + 1))\n", + "ax.set_ylim(1.1, 2)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (540, 0.267), c='b')\n", + "ax.annotate(\"5-layer\", (540, 0.245), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# plt.savefig(fname=\"fig1.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "seed(9999)\n", + "tensorflow.random.set_seed(9999)\n", + "shortcut5, shortcut11 = ShortCut5(input_shape=(1, 102)), ShortCut11(input_shape=(1, 102))" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/2000\n", + "45/45 [==============================] - 1s 7ms/step - loss: 0.0267 - val_loss: 0.0272 - lr: 0.0050\n", + "Epoch 2/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0255 - val_loss: 0.0267 - lr: 0.0050\n", + "Epoch 3/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0247 - val_loss: 0.0266 - lr: 0.0050\n", + "Epoch 4/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0244 - val_loss: 0.0264 - lr: 0.0050\n", + "Epoch 5/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0241 - val_loss: 0.0262 - lr: 0.0050\n", + "Epoch 6/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0238 - val_loss: 0.0261 - lr: 0.0050\n", + "Epoch 7/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0234 - val_loss: 0.0256 - lr: 0.0050\n", + "Epoch 8/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0232 - val_loss: 0.0254 - lr: 0.0050\n", + "Epoch 9/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0231 - val_loss: 0.0251 - lr: 0.0050\n", + "Epoch 10/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0227 - val_loss: 0.0252 - lr: 0.0050\n", + "Epoch 11/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0223 - val_loss: 0.0248 - lr: 0.0050\n", + "Epoch 12/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0221 - val_loss: 0.0245 - lr: 0.0050\n", + "Epoch 13/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0220 - val_loss: 0.0249 - lr: 0.0050\n", + "Epoch 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0.0221 - lr: 0.0050\n", + "Epoch 84/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0248 - lr: 0.0050\n", + "Epoch 85/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 86/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0180 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 87/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0180 - val_loss: 0.0219 - lr: 0.0050\n", + "Epoch 88/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0179 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 89/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0180 - val_loss: 0.0219 - lr: 0.0050\n", + "Epoch 90/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0180 - val_loss: 0.0216 - lr: 0.0050\n", + "Epoch 91/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0215 - lr: 0.0050\n", + "Epoch 92/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0178 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 93/2000\n", + "45/45 [==============================] - 0s 4ms/step - loss: 0.0178 - val_loss: 0.0187 - lr: 0.0050\n", + "Epoch 94/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0178 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 95/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0225 - lr: 0.0050\n", + "Epoch 96/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0195 - lr: 0.0050\n", + "Epoch 97/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0233 - lr: 0.0050\n", + "Epoch 98/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0239 - lr: 0.0050\n", + "Epoch 99/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0186 - lr: 0.0050\n", + "Epoch 100/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0232 - lr: 0.0050\n", + "Epoch 101/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0173 - val_loss: 0.0259 - lr: 0.0050\n", + "Epoch 102/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0173 - val_loss: 0.0184 - lr: 0.0050\n", + "Epoch 103/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 104/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0182 - lr: 0.0050\n", + "Epoch 105/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0213 - lr: 0.0050\n", + "Epoch 106/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0237 - lr: 0.0050\n", + "Epoch 107/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 108/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0170 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 109/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0194 - lr: 0.0050\n", + "Epoch 110/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 111/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0224 - lr: 0.0050\n", + "Epoch 112/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0174 - lr: 0.0050\n", + "Epoch 113/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0168 - val_loss: 0.0277 - lr: 0.0050\n", + "Epoch 114/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0224 - lr: 0.0050\n", + "Epoch 115/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0242 - lr: 0.0050\n", + "Epoch 116/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0193 - lr: 0.0050\n", + "Epoch 117/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0181 - lr: 0.0050\n", + "Epoch 118/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 119/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0223 - lr: 0.0050\n", + "Epoch 120/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0162 - val_loss: 0.0187 - lr: 0.0050\n", + "Epoch 121/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0160 - val_loss: 0.0165 - lr: 0.0050\n", + "Epoch 122/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0161 - val_loss: 0.0296 - lr: 0.0050\n", + "Epoch 123/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0159 - val_loss: 0.0190 - lr: 0.0050\n", + "Epoch 124/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0159 - val_loss: 0.0173 - lr: 0.0050\n", + "Epoch 125/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0211 - lr: 0.0050\n", + "Epoch 126/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0191 - lr: 0.0050\n", + "Epoch 127/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 128/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0154 - val_loss: 0.0334 - lr: 0.0050\n", + "Epoch 129/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0154 - val_loss: 0.0581 - lr: 0.0050\n", + "Epoch 130/2000\n", + "45/45 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+ "Epoch 138/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0439 - lr: 0.0050\n", + "Epoch 139/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 140/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0899 - lr: 0.0050\n", + "Epoch 141/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.1044 - lr: 0.0050\n", + "Epoch 142/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0190 - lr: 0.0050\n", + "Epoch 143/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0709 - lr: 0.0050\n", + "Epoch 144/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0142 - val_loss: 0.0244 - lr: 0.0050\n", + "Epoch 145/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0142 - val_loss: 0.0614 - lr: 0.0050\n", + "Epoch 146/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.1001 - lr: 0.0050\n", + "Epoch 147/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.1007 - lr: 0.0025\n", + "Epoch 148/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.1631 - lr: 0.0025\n", + "Epoch 149/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0139 - val_loss: 0.0954 - lr: 0.0025\n", + "Epoch 150/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0698 - lr: 0.0025\n", + "Epoch 151/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0137 - val_loss: 0.0661 - lr: 0.0025\n", + "Epoch 152/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0138 - val_loss: 0.0759 - lr: 0.0025\n", + "Epoch 153/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.1115 - lr: 0.0025\n", + "Epoch 154/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0494 - lr: 0.0025\n", + "Epoch 155/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0496 - lr: 0.0025\n", + "Epoch 156/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0894 - lr: 0.0025\n", + "Epoch 157/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.0923 - lr: 0.0025\n", + "Epoch 158/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0136 - val_loss: 0.0771 - lr: 0.0025\n", + "Epoch 159/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0649 - lr: 0.0025\n", + "Epoch 160/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0135 - val_loss: 0.1209 - lr: 0.0025\n", + "Epoch 161/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.0996 - lr: 0.0025\n", + "Epoch 162/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0735 - lr: 0.0025\n", + "Epoch 163/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.0246 - lr: 0.0025\n", + "Epoch 164/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0134 - val_loss: 0.1147 - lr: 0.0025\n", + "Epoch 165/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0133 - val_loss: 0.1186 - lr: 0.0025\n", + "Epoch 166/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0132 - val_loss: 0.0291 - lr: 0.0025\n", + "Epoch 167/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0131 - val_loss: 0.1191 - lr: 0.0025\n", + "Epoch 168/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0131 - val_loss: 0.0387 - lr: 0.0025\n", + "Epoch 169/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0662 - lr: 0.0025\n", + "Epoch 170/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0442 - lr: 0.0025\n", + "Epoch 171/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0130 - val_loss: 0.0408 - lr: 0.0025\n", + "Epoch 172/2000\n", + "45/45 [==============================] - 0s 6ms/step - loss: 0.0128 - val_loss: 0.0635 - lr: 0.0012\n", + "Epoch 173/2000\n", + "45/45 [==============================] - 0s 4ms/step - loss: 0.0130 - val_loss: 0.0345 - lr: 0.0012\n", + "Epoch 174/2000\n", + "45/45 [==============================] - 0s 6ms/step - loss: 0.0129 - val_loss: 0.0813 - lr: 0.0012\n", + "Epoch 175/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0129 - val_loss: 0.0309 - lr: 0.0012\n", + "Epoch 176/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 177/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0361 - lr: 0.0012\n", + "Epoch 178/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0179 - lr: 0.0012\n", + "Epoch 179/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0129 - val_loss: 0.0166 - lr: 0.0012\n", + "Epoch 180/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 181/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0171 - lr: 0.0012\n", + "Epoch 182/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0494 - lr: 0.0012\n", + "Epoch 183/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0398 - lr: 0.0012\n", + "Epoch 184/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0128 - val_loss: 0.0146 - lr: 0.0012\n", + "Epoch 185/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0572 - lr: 0.0012\n", + "Epoch 186/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0171 - lr: 0.0012\n", + "Epoch 187/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0364 - lr: 0.0012\n", + "Epoch 188/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0125 - val_loss: 0.0129 - lr: 0.0012\n", + "Epoch 189/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0380 - lr: 0.0012\n", + "Epoch 190/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0349 - lr: 0.0012\n", + "Epoch 191/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0176 - lr: 0.0012\n", + "Epoch 192/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0369 - lr: 0.0012\n", + "Epoch 193/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0315 - lr: 0.0012\n", + "Epoch 194/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0146 - lr: 0.0012\n", + "Epoch 195/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0125 - val_loss: 0.0589 - lr: 0.0012\n", + "Epoch 196/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0127 - val_loss: 0.0440 - lr: 0.0012\n", + "Epoch 197/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0301 - lr: 0.0012\n", + "Epoch 198/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0544 - lr: 0.0012\n", + "Epoch 199/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0789 - lr: 0.0012\n", + "Epoch 200/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0261 - lr: 0.0012\n", + "Epoch 201/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0126 - val_loss: 0.0173 - lr: 0.0012\n", + "Epoch 202/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0319 - lr: 0.0012\n", + "Epoch 203/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0132 - lr: 0.0012\n", + "Epoch 204/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0708 - lr: 0.0012\n", + "Epoch 205/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0237 - lr: 0.0012\n", + "Epoch 206/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0230 - lr: 0.0012\n", + "Epoch 207/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0124 - val_loss: 0.0208 - lr: 0.0012\n", + "Epoch 208/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0270 - lr: 0.0012\n", + "Epoch 209/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0137 - lr: 0.0012\n", + "Epoch 210/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0149 - lr: 0.0012\n", + "Epoch 211/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0163 - lr: 0.0012\n", + "Epoch 212/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0133 - lr: 0.0012\n", + "Epoch 213/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0244 - lr: 0.0012\n", + "Epoch 214/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0138 - lr: 6.2500e-04\n", + "Epoch 215/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0123 - val_loss: 0.0123 - lr: 6.2500e-04\n", + "Epoch 216/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0151 - lr: 6.2500e-04\n", + "Epoch 217/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 218/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0122 - val_loss: 0.0163 - lr: 6.2500e-04\n", + "Epoch 219/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0149 - lr: 6.2500e-04\n", + "Epoch 220/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0123 - lr: 6.2500e-04\n", + "Epoch 221/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0204 - lr: 6.2500e-04\n", + "Epoch 222/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0149 - lr: 6.2500e-04\n", + "Epoch 223/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0143 - lr: 6.2500e-04\n", + "Epoch 224/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0121 - val_loss: 0.0146 - lr: 6.2500e-04\n", + "Epoch 225/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0129 - lr: 6.2500e-04\n", + "Epoch 226/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0122 - lr: 6.2500e-04\n", + "Epoch 227/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0189 - lr: 6.2500e-04\n", + "Epoch 228/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0198 - lr: 6.2500e-04\n", + "Epoch 229/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0128 - lr: 6.2500e-04\n", + "Epoch 230/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0172 - lr: 6.2500e-04\n", + "Epoch 231/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0132 - lr: 6.2500e-04\n", + "Epoch 232/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0142 - lr: 6.2500e-04\n", + "Epoch 233/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0123 - lr: 6.2500e-04\n", + "Epoch 234/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0134 - lr: 6.2500e-04\n", + "Epoch 235/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0187 - lr: 6.2500e-04\n", + "Epoch 236/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0123 - lr: 6.2500e-04\n", + "Epoch 237/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0162 - lr: 6.2500e-04\n", + "Epoch 238/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0186 - lr: 6.2500e-04\n", + "Epoch 239/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0123 - lr: 6.2500e-04\n", + "Epoch 240/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0246 - lr: 6.2500e-04\n", + "Epoch 241/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 242/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 243/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0120 - val_loss: 0.0188 - lr: 6.2500e-04\n", + "Epoch 244/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0119 - val_loss: 0.0152 - lr: 6.2500e-04\n", + "Epoch 245/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0124 - lr: 6.2500e-04\n", + "Epoch 246/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0231 - lr: 6.2500e-04\n", + "Epoch 247/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 248/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0123 - lr: 6.2500e-04\n", + "Epoch 249/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0120 - lr: 6.2500e-04\n", + "Epoch 250/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0120 - lr: 6.2500e-04\n", + "Epoch 251/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0150 - lr: 6.2500e-04\n", + "Epoch 252/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 253/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0118 - val_loss: 0.0126 - lr: 6.2500e-04\n", + "Epoch 254/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0135 - lr: 6.2500e-04\n", + "Epoch 255/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0133 - lr: 6.2500e-04\n", + "Epoch 256/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0120 - lr: 6.2500e-04\n", + "Epoch 257/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0214 - lr: 6.2500e-04\n", + "Epoch 258/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0160 - lr: 6.2500e-04\n", + "Epoch 259/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0116 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 260/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0118 - val_loss: 0.0260 - lr: 6.2500e-04\n", + "Epoch 261/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0126 - lr: 6.2500e-04\n", + "Epoch 262/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0213 - lr: 6.2500e-04\n", + "Epoch 263/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 264/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 265/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0260 - lr: 6.2500e-04\n", + "Epoch 266/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 267/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 268/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0144 - lr: 6.2500e-04\n", + "Epoch 269/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0122 - lr: 6.2500e-04\n", + "Epoch 270/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0214 - lr: 6.2500e-04\n", + "Epoch 271/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0145 - lr: 6.2500e-04\n", + "Epoch 272/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0138 - lr: 6.2500e-04\n", + "Epoch 273/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0231 - lr: 6.2500e-04\n", + "Epoch 274/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0185 - lr: 6.2500e-04\n", + "Epoch 275/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 276/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0200 - lr: 6.2500e-04\n", + "Epoch 277/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0126 - lr: 6.2500e-04\n", + "Epoch 278/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0116 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 279/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0152 - lr: 6.2500e-04\n", + "Epoch 280/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0143 - lr: 6.2500e-04\n", + "Epoch 281/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0117 - val_loss: 0.0117 - lr: 6.2500e-04\n", + "Epoch 282/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0169 - lr: 6.2500e-04\n", + "Epoch 283/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0125 - lr: 6.2500e-04\n", + "Epoch 284/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0120 - lr: 6.2500e-04\n", + "Epoch 285/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0125 - lr: 6.2500e-04\n", + "Epoch 286/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 287/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0136 - lr: 6.2500e-04\n", + "Epoch 288/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0115 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 289/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0112 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 290/2000\n", + "45/45 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val_loss: 0.0122 - lr: 6.2500e-04\n", + "Epoch 298/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 299/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 300/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0115 - lr: 6.2500e-04\n", + "Epoch 301/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0194 - lr: 6.2500e-04\n", + "Epoch 302/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 303/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0112 - val_loss: 0.0387 - lr: 6.2500e-04\n", + "Epoch 304/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 305/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0150 - lr: 6.2500e-04\n", + "Epoch 306/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0114 - val_loss: 0.0184 - lr: 6.2500e-04\n", + "Epoch 307/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0250 - lr: 6.2500e-04\n", + "Epoch 308/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0138 - lr: 6.2500e-04\n", + "Epoch 309/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0112 - val_loss: 0.0134 - lr: 6.2500e-04\n", + "Epoch 310/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0117 - lr: 6.2500e-04\n", + "Epoch 311/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0134 - lr: 6.2500e-04\n", + "Epoch 312/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0112 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 313/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 314/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0113 - val_loss: 0.0115 - lr: 6.2500e-04\n", + "Epoch 315/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0112 - val_loss: 0.0148 - lr: 6.2500e-04\n", + "Epoch 316/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0112 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 317/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0111 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 318/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 319/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0118 - lr: 6.2500e-04\n", + "Epoch 320/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 321/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 322/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0137 - lr: 6.2500e-04\n", + "Epoch 323/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0133 - lr: 6.2500e-04\n", + "Epoch 324/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0242 - lr: 6.2500e-04\n", + "Epoch 325/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0203 - lr: 6.2500e-04\n", + "Epoch 326/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0121 - lr: 6.2500e-04\n", + "Epoch 327/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0157 - lr: 6.2500e-04\n", + "Epoch 328/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0150 - lr: 6.2500e-04\n", + "Epoch 329/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0127 - lr: 6.2500e-04\n", + "Epoch 330/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0115 - lr: 6.2500e-04\n", + "Epoch 331/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 332/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 333/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0149 - lr: 6.2500e-04\n", + "Epoch 334/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0176 - lr: 6.2500e-04\n", + "Epoch 335/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0110 - lr: 6.2500e-04\n", + "Epoch 336/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0110 - lr: 6.2500e-04\n", + "Epoch 337/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0121 - lr: 6.2500e-04\n", + "Epoch 338/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 339/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 340/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 341/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0110 - val_loss: 0.0120 - lr: 6.2500e-04\n", + "Epoch 342/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0181 - lr: 6.2500e-04\n", + "Epoch 343/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0145 - lr: 6.2500e-04\n", + "Epoch 344/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0157 - lr: 6.2500e-04\n", + "Epoch 345/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0127 - lr: 6.2500e-04\n", + "Epoch 346/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0180 - lr: 6.2500e-04\n", + "Epoch 347/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0111 - val_loss: 0.0171 - lr: 6.2500e-04\n", + "Epoch 348/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0109 - val_loss: 0.0112 - lr: 6.2500e-04\n", + "Epoch 349/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0166 - lr: 6.2500e-04\n", + "Epoch 350/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0137 - lr: 6.2500e-04\n", + "Epoch 351/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0122 - lr: 6.2500e-04\n", + "Epoch 352/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0153 - lr: 6.2500e-04\n", + "Epoch 353/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0110 - lr: 6.2500e-04\n", + "Epoch 354/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0120 - lr: 6.2500e-04\n", + "Epoch 355/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0112 - lr: 6.2500e-04\n", + "Epoch 356/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0206 - lr: 6.2500e-04\n", + "Epoch 357/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0109 - lr: 6.2500e-04\n", + "Epoch 358/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0117 - lr: 6.2500e-04\n", + "Epoch 359/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0108 - lr: 6.2500e-04\n", + "Epoch 360/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0159 - lr: 6.2500e-04\n", + "Epoch 361/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0192 - lr: 6.2500e-04\n", + "Epoch 362/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0110 - lr: 6.2500e-04\n", + "Epoch 363/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0271 - lr: 6.2500e-04\n", + "Epoch 364/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0198 - lr: 6.2500e-04\n", + "Epoch 365/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0208 - lr: 6.2500e-04\n", + "Epoch 366/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0108 - val_loss: 0.0170 - lr: 6.2500e-04\n", + "Epoch 367/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0119 - lr: 6.2500e-04\n", + "Epoch 368/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 369/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0173 - lr: 6.2500e-04\n", + "Epoch 370/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0177 - lr: 6.2500e-04\n", + "Epoch 371/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0158 - lr: 6.2500e-04\n", + "Epoch 372/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0139 - lr: 6.2500e-04\n", + "Epoch 373/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0145 - lr: 6.2500e-04\n", + "Epoch 374/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0108 - lr: 6.2500e-04\n", + "Epoch 375/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0107 - lr: 6.2500e-04\n", + "Epoch 376/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0143 - lr: 6.2500e-04\n", + "Epoch 377/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0121 - lr: 6.2500e-04\n", + "Epoch 378/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0106 - lr: 6.2500e-04\n", + "Epoch 379/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0107 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 380/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0141 - lr: 6.2500e-04\n", + "Epoch 381/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0106 - lr: 6.2500e-04\n", + "Epoch 382/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 383/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 384/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0108 - lr: 6.2500e-04\n", + "Epoch 385/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0285 - lr: 6.2500e-04\n", + "Epoch 386/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 387/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0106 - lr: 6.2500e-04\n", + "Epoch 388/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0129 - lr: 6.2500e-04\n", + "Epoch 389/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0191 - lr: 6.2500e-04\n", + "Epoch 390/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0144 - lr: 6.2500e-04\n", + "Epoch 391/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0254 - lr: 6.2500e-04\n", + "Epoch 392/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0107 - lr: 6.2500e-04\n", + "Epoch 393/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0106 - lr: 6.2500e-04\n", + "Epoch 394/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 395/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 396/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0106 - val_loss: 0.0184 - lr: 6.2500e-04\n", + "Epoch 397/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0171 - lr: 6.2500e-04\n", + "Epoch 398/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 399/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0105 - val_loss: 0.0112 - lr: 6.2500e-04\n", + "Epoch 400/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0142 - lr: 6.2500e-04\n", + "Epoch 401/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 402/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0206 - lr: 6.2500e-04\n", + "Epoch 403/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 404/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0217 - lr: 6.2500e-04\n", + "Epoch 405/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 406/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0104 - lr: 6.2500e-04\n", + "Epoch 407/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0134 - lr: 6.2500e-04\n", + "Epoch 408/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0111 - lr: 6.2500e-04\n", + "Epoch 409/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0116 - lr: 6.2500e-04\n", + "Epoch 410/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 411/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0137 - lr: 6.2500e-04\n", + "Epoch 412/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0114 - lr: 6.2500e-04\n", + "Epoch 413/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 414/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0185 - lr: 6.2500e-04\n", + "Epoch 415/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0128 - lr: 6.2500e-04\n", + "Epoch 416/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0134 - lr: 6.2500e-04\n", + "Epoch 417/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0110 - lr: 6.2500e-04\n", + "Epoch 418/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0108 - lr: 6.2500e-04\n", + "Epoch 419/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0109 - lr: 6.2500e-04\n", + "Epoch 420/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0106 - lr: 6.2500e-04\n", + "Epoch 421/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0128 - lr: 6.2500e-04\n", + "Epoch 422/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0107 - lr: 6.2500e-04\n", + "Epoch 423/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 424/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0103 - lr: 6.2500e-04\n", + "Epoch 425/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0275 - lr: 6.2500e-04\n", + "Epoch 426/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0104 - val_loss: 0.0249 - lr: 6.2500e-04\n", + "Epoch 427/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0149 - lr: 6.2500e-04\n", + "Epoch 428/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0109 - lr: 6.2500e-04\n", + "Epoch 429/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0146 - lr: 6.2500e-04\n", + "Epoch 430/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0108 - lr: 6.2500e-04\n", + "Epoch 431/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0104 - lr: 6.2500e-04\n", + "Epoch 432/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0184 - lr: 6.2500e-04\n", + "Epoch 433/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0103 - lr: 6.2500e-04\n", + "Epoch 434/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0136 - lr: 6.2500e-04\n", + "Epoch 435/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0132 - lr: 6.2500e-04\n", + "Epoch 436/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0121 - lr: 6.2500e-04\n", + "Epoch 437/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0102 - lr: 6.2500e-04\n", + "Epoch 438/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0142 - lr: 6.2500e-04\n", + "Epoch 439/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0102 - lr: 6.2500e-04\n", + "Epoch 440/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 441/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 6.2500e-04\n", + "Epoch 442/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0155 - lr: 6.2500e-04\n", + "Epoch 443/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0103 - val_loss: 0.0146 - lr: 6.2500e-04\n", + "Epoch 444/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0112 - lr: 6.2500e-04\n", + "Epoch 445/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0101 - lr: 6.2500e-04\n", + "Epoch 446/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0141 - lr: 6.2500e-04\n", + "Epoch 447/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0102 - val_loss: 0.0187 - lr: 6.2500e-04\n", + "Epoch 448/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0104 - lr: 6.2500e-04\n", + "Epoch 449/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0301 - lr: 6.2500e-04\n", + "Epoch 450/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0103 - lr: 6.2500e-04\n", + "Epoch 451/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0156 - lr: 6.2500e-04\n", + "Epoch 452/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0171 - lr: 6.2500e-04\n", + "Epoch 453/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0249 - lr: 6.2500e-04\n", + "Epoch 454/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0130 - lr: 6.2500e-04\n", + "Epoch 455/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0126 - lr: 6.2500e-04\n", + "Epoch 456/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0153 - lr: 6.2500e-04\n", + "Epoch 457/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0102 - lr: 6.2500e-04\n", + "Epoch 458/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0189 - lr: 6.2500e-04\n", + "Epoch 459/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0170 - lr: 6.2500e-04\n", + "Epoch 460/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0113 - lr: 6.2500e-04\n", + "Epoch 461/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0256 - lr: 6.2500e-04\n", + "Epoch 462/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 463/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 464/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0130 - lr: 6.2500e-04\n", + "Epoch 465/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0131 - lr: 6.2500e-04\n", + "Epoch 466/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0101 - val_loss: 0.0172 - lr: 6.2500e-04\n", + "Epoch 467/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0232 - lr: 6.2500e-04\n", + "Epoch 468/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0110 - lr: 6.2500e-04\n", + "Epoch 469/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0240 - lr: 6.2500e-04\n", + "Epoch 470/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0105 - lr: 6.2500e-04\n", + "Epoch 471/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0112 - lr: 3.1250e-04\n", + "Epoch 472/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0100 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 473/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 474/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 475/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0132 - lr: 3.1250e-04\n", + "Epoch 476/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0154 - lr: 3.1250e-04\n", + "Epoch 477/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 478/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 479/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 480/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0151 - lr: 3.1250e-04\n", + "Epoch 481/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 482/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 483/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 484/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0098 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 485/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 486/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0125 - lr: 3.1250e-04\n", + "Epoch 487/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 488/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0182 - lr: 3.1250e-04\n", + "Epoch 489/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 490/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0114 - lr: 3.1250e-04\n", + "Epoch 491/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0105 - lr: 3.1250e-04\n", + "Epoch 492/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 493/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 494/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0127 - lr: 3.1250e-04\n", + "Epoch 495/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 496/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0123 - lr: 3.1250e-04\n", + "Epoch 497/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 498/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 499/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0114 - lr: 3.1250e-04\n", + "Epoch 500/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0132 - lr: 3.1250e-04\n", + "Epoch 501/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 502/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0113 - lr: 3.1250e-04\n", + "Epoch 503/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 504/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0107 - lr: 3.1250e-04\n", + "Epoch 505/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0121 - lr: 3.1250e-04\n", + "Epoch 506/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0099 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 507/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0097 - val_loss: 0.0127 - lr: 3.1250e-04\n", + "Epoch 508/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 509/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 510/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0150 - lr: 3.1250e-04\n", + "Epoch 511/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0119 - lr: 3.1250e-04\n", + "Epoch 512/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0116 - lr: 3.1250e-04\n", + "Epoch 513/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 514/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 515/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 516/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 517/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 518/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 519/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0153 - lr: 3.1250e-04\n", + "Epoch 520/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 521/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0157 - lr: 3.1250e-04\n", + "Epoch 522/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 523/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0163 - lr: 3.1250e-04\n", + "Epoch 524/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 525/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 526/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 527/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 528/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 529/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 530/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 531/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 532/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 533/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 534/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 535/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 536/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0161 - lr: 3.1250e-04\n", + "Epoch 537/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 538/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0267 - lr: 3.1250e-04\n", + "Epoch 539/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 540/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0120 - lr: 3.1250e-04\n", + "Epoch 541/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0119 - lr: 3.1250e-04\n", + "Epoch 542/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0122 - lr: 3.1250e-04\n", + "Epoch 543/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 544/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 545/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0116 - lr: 3.1250e-04\n", + "Epoch 546/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 547/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 548/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0132 - lr: 3.1250e-04\n", + "Epoch 549/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 550/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0156 - lr: 3.1250e-04\n", + "Epoch 551/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0122 - lr: 3.1250e-04\n", + "Epoch 552/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0135 - lr: 3.1250e-04\n", + "Epoch 553/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0124 - lr: 3.1250e-04\n", + "Epoch 554/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0125 - lr: 3.1250e-04\n", + "Epoch 555/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 556/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0105 - lr: 3.1250e-04\n", + "Epoch 557/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0144 - lr: 3.1250e-04\n", + "Epoch 558/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 559/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 560/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 561/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 562/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0105 - lr: 3.1250e-04\n", + "Epoch 563/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 564/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 565/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 566/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 567/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 568/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 569/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0098 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 570/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 571/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 572/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 573/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 574/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0139 - lr: 3.1250e-04\n", + "Epoch 575/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0280 - lr: 3.1250e-04\n", + "Epoch 576/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 577/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 578/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 579/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 580/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 581/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0097 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 582/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 583/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 584/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 585/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 586/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 587/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0110 - lr: 3.1250e-04\n", + "Epoch 588/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0110 - lr: 3.1250e-04\n", + "Epoch 589/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 590/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 591/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 592/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 593/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 594/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 595/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 596/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 597/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0122 - lr: 3.1250e-04\n", + "Epoch 598/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0120 - lr: 3.1250e-04\n", + "Epoch 599/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 600/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 601/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0115 - lr: 3.1250e-04\n", + "Epoch 602/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 603/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 604/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0112 - lr: 3.1250e-04\n", + "Epoch 605/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 606/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 607/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0121 - lr: 3.1250e-04\n", + "Epoch 608/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 609/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 610/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 611/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0105 - lr: 3.1250e-04\n", + "Epoch 612/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 613/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 614/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 615/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0125 - lr: 3.1250e-04\n", + "Epoch 616/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0125 - lr: 3.1250e-04\n", + "Epoch 617/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 618/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0147 - lr: 3.1250e-04\n", + "Epoch 619/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0113 - lr: 3.1250e-04\n", + "Epoch 620/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 621/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 622/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0116 - lr: 3.1250e-04\n", + "Epoch 623/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 624/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 625/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 626/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 627/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 628/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0119 - lr: 3.1250e-04\n", + "Epoch 629/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 630/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 631/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0128 - lr: 3.1250e-04\n", + "Epoch 632/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0134 - lr: 3.1250e-04\n", + "Epoch 633/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0124 - lr: 3.1250e-04\n", + "Epoch 634/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0148 - lr: 3.1250e-04\n", + "Epoch 635/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 636/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0134 - lr: 3.1250e-04\n", + "Epoch 637/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0127 - lr: 3.1250e-04\n", + "Epoch 638/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 639/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 640/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0139 - lr: 3.1250e-04\n", + "Epoch 641/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 642/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0109 - lr: 3.1250e-04\n", + "Epoch 643/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0116 - lr: 3.1250e-04\n", + "Epoch 644/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 645/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 646/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 647/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0141 - lr: 3.1250e-04\n", + "Epoch 648/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0096 - val_loss: 0.0132 - lr: 3.1250e-04\n", + "Epoch 649/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 650/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0095 - lr: 3.1250e-04\n", + "Epoch 651/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0110 - lr: 3.1250e-04\n", + "Epoch 652/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0113 - lr: 3.1250e-04\n", + "Epoch 653/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0094 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 654/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0116 - lr: 3.1250e-04\n", + "Epoch 655/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0095 - lr: 3.1250e-04\n", + "Epoch 656/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 657/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0119 - lr: 3.1250e-04\n", + "Epoch 658/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 659/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0160 - lr: 3.1250e-04\n", + "Epoch 660/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0103 - lr: 3.1250e-04\n", + "Epoch 661/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 662/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 663/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0108 - lr: 3.1250e-04\n", + "Epoch 664/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0094 - lr: 3.1250e-04\n", + "Epoch 665/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 666/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0110 - lr: 3.1250e-04\n", + "Epoch 667/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 668/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 669/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 670/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 671/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0099 - lr: 3.1250e-04\n", + "Epoch 672/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 673/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 674/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 675/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0111 - lr: 3.1250e-04\n", + "Epoch 676/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0153 - lr: 3.1250e-04\n", + "Epoch 677/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0121 - lr: 3.1250e-04\n", + "Epoch 678/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 679/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0098 - lr: 3.1250e-04\n", + "Epoch 680/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0124 - lr: 3.1250e-04\n", + "Epoch 681/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0101 - lr: 3.1250e-04\n", + "Epoch 682/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 683/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0113 - lr: 3.1250e-04\n", + "Epoch 684/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0106 - lr: 3.1250e-04\n", + "Epoch 685/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0118 - lr: 3.1250e-04\n", + "Epoch 686/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0096 - lr: 3.1250e-04\n", + "Epoch 687/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0094 - val_loss: 0.0104 - lr: 3.1250e-04\n", + "Epoch 688/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0097 - lr: 3.1250e-04\n", + "Epoch 689/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0102 - lr: 3.1250e-04\n", + "Epoch 690/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 691/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 692/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 693/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 694/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0095 - val_loss: 0.0103 - lr: 1.5625e-04\n", + "Epoch 695/2000\n", + "45/45 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val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 703/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0096 - lr: 1.5625e-04\n", + "Epoch 704/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0105 - lr: 1.5625e-04\n", + "Epoch 705/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0095 - lr: 1.5625e-04\n", + "Epoch 706/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 707/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0116 - lr: 1.5625e-04\n", + "Epoch 708/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0117 - lr: 1.5625e-04\n", + "Epoch 709/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 710/2000\n", + "45/45 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val_loss: 0.0103 - lr: 1.5625e-04\n", + "Epoch 718/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 719/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 720/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 721/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 722/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 723/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0095 - lr: 1.5625e-04\n", + "Epoch 724/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 725/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0096 - lr: 1.5625e-04\n", + "Epoch 726/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0103 - lr: 1.5625e-04\n", + "Epoch 727/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 728/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0101 - lr: 1.5625e-04\n", + "Epoch 729/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0104 - lr: 1.5625e-04\n", + "Epoch 730/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 731/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 732/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 733/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0105 - lr: 1.5625e-04\n", + "Epoch 734/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 735/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0103 - lr: 1.5625e-04\n", + "Epoch 736/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0120 - lr: 1.5625e-04\n", + "Epoch 737/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 738/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 739/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0127 - lr: 1.5625e-04\n", + "Epoch 740/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 741/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0100 - lr: 1.5625e-04\n", + "Epoch 742/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 743/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0096 - lr: 1.5625e-04\n", + "Epoch 744/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 745/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0095 - lr: 1.5625e-04\n", + "Epoch 746/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 747/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 748/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 749/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 750/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 751/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 752/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 753/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 754/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 755/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0107 - lr: 1.5625e-04\n", + "Epoch 756/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0105 - lr: 1.5625e-04\n", + "Epoch 757/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0122 - lr: 1.5625e-04\n", + "Epoch 758/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 759/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 760/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 761/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0097 - lr: 1.5625e-04\n", + "Epoch 762/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 763/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0096 - lr: 1.5625e-04\n", + "Epoch 764/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0098 - lr: 1.5625e-04\n", + "Epoch 765/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.5625e-04\n", + "Epoch 766/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0096 - lr: 1.5625e-04\n", + "Epoch 767/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 768/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 769/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 1.5625e-04\n", + "Epoch 770/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0095 - lr: 1.5625e-04\n", + "Epoch 771/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0110 - lr: 1.5625e-04\n", + "Epoch 772/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0118 - lr: 1.5625e-04\n", + "Epoch 773/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0096 - lr: 1.5625e-04\n", + "Epoch 774/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0099 - lr: 1.5625e-04\n", + "Epoch 775/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 776/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 777/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 778/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 779/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 780/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 781/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 782/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 783/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 784/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 785/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 786/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 787/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 788/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 789/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 790/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 791/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0099 - lr: 7.8125e-05\n", + "Epoch 792/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 793/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 794/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 795/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0095 - lr: 7.8125e-05\n", + "Epoch 796/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 797/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 798/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 799/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0105 - lr: 7.8125e-05\n", + "Epoch 800/2000\n", + "45/45 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val_loss: 0.0096 - lr: 7.8125e-05\n", + "Epoch 808/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0097 - lr: 7.8125e-05\n", + "Epoch 809/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.8125e-05\n", + "Epoch 810/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 811/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0101 - lr: 7.8125e-05\n", + "Epoch 812/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0094 - lr: 7.8125e-05\n", + "Epoch 813/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 814/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 815/2000\n", + "45/45 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val_loss: 0.0096 - lr: 3.9062e-05\n", + "Epoch 838/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 839/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 840/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 841/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 842/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 843/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 844/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 845/2000\n", + "45/45 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val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 853/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 854/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 855/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 856/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 857/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 858/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 859/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 3.9062e-05\n", + "Epoch 860/2000\n", + "45/45 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val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 868/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 869/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 870/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0096 - lr: 1.9531e-05\n", + "Epoch 871/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 872/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0094 - lr: 1.9531e-05\n", + "Epoch 873/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0094 - lr: 1.9531e-05\n", + "Epoch 874/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 875/2000\n", + "45/45 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val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 883/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0094 - lr: 1.9531e-05\n", + "Epoch 884/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 885/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 886/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 887/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 888/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 889/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.9531e-05\n", + "Epoch 890/2000\n", + "45/45 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val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 898/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 899/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 900/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 901/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 902/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 903/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 904/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 905/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 906/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 907/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 908/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 909/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 910/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 911/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 912/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 913/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 914/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 9.7656e-06\n", + "Epoch 915/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 916/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 917/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 918/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 919/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 920/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 921/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 922/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 923/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 924/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 925/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 926/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 927/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 928/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 929/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 930/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 931/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 932/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 933/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 934/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 4.8828e-06\n", + "Epoch 935/2000\n", + "45/45 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val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1003/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1004/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1005/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1006/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1007/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1008/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1009/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 6.1035e-07\n", + "Epoch 1010/2000\n", + 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2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1033/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1034/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1035/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1036/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1037/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1038/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1039/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1040/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1041/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1042/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1043/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1044/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1045/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1046/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.0518e-07\n", + "Epoch 1047/2000\n", + "45/45 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- val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1055/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1056/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1057/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1058/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1059/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1060/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1061/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1062/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1063/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1064/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1065/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1066/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1067/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1068/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1069/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1070/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1071/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1072/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1073/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 1.5259e-07\n", + "Epoch 1074/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1075/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1076/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1077/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1078/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1079/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1080/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1081/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1082/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1083/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1084/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1085/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1086/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1087/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1088/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1089/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1090/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1091/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0093 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1092/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1093/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1094/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1095/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1096/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1097/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1098/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 7.6294e-08\n", + "Epoch 1099/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1100/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1101/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1102/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1103/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1104/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1105/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1106/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1107/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1108/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1109/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1110/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1111/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1112/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1113/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1114/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1115/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1116/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1117/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1118/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0090 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1119/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1120/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1121/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0089 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1122/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0092 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1123/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0091 - val_loss: 0.0093 - lr: 3.8147e-08\n", + "Epoch 1/2000\n", + "45/45 [==============================] - 1s 19ms/step - loss: 0.0300 - val_loss: 0.0279 - lr: 0.0050\n", + "Epoch 2/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0275 - val_loss: 0.0292 - lr: 0.0050\n", + "Epoch 3/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0257 - val_loss: 0.0299 - lr: 0.0050\n", + "Epoch 4/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0245 - val_loss: 0.0306 - lr: 0.0050\n", + "Epoch 5/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0238 - val_loss: 0.0309 - lr: 0.0050\n", + "Epoch 6/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0233 - val_loss: 0.0311 - lr: 0.0050\n", + "Epoch 7/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0230 - val_loss: 0.0311 - lr: 0.0050\n", + "Epoch 8/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0228 - val_loss: 0.0309 - lr: 0.0050\n", + "Epoch 9/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0226 - val_loss: 0.0304 - lr: 0.0050\n", + "Epoch 10/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0225 - val_loss: 0.0294 - lr: 0.0050\n", + "Epoch 11/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0224 - val_loss: 0.0283 - lr: 0.0050\n", + "Epoch 12/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0222 - val_loss: 0.0270 - lr: 0.0050\n", + "Epoch 13/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0221 - val_loss: 0.0262 - lr: 0.0050\n", + "Epoch 14/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0221 - val_loss: 0.0253 - lr: 0.0050\n", + "Epoch 15/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0220 - val_loss: 0.0243 - lr: 0.0050\n", + "Epoch 16/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0219 - val_loss: 0.0234 - lr: 0.0050\n", + "Epoch 17/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0219 - val_loss: 0.0228 - lr: 0.0050\n", + "Epoch 18/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0218 - val_loss: 0.0228 - lr: 0.0050\n", + "Epoch 19/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0218 - val_loss: 0.0225 - lr: 0.0050\n", + "Epoch 20/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0217 - val_loss: 0.0223 - lr: 0.0050\n", + "Epoch 21/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0216 - val_loss: 0.0222 - lr: 0.0050\n", + "Epoch 22/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0216 - val_loss: 0.0220 - lr: 0.0050\n", + "Epoch 23/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0215 - val_loss: 0.0220 - lr: 0.0050\n", + "Epoch 24/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0215 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 25/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0213 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 26/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0214 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 27/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0213 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 28/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0213 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 29/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0214 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 30/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0213 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 31/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0213 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 32/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0212 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 33/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0212 - val_loss: 0.0219 - lr: 0.0050\n", + "Epoch 34/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0211 - val_loss: 0.0218 - lr: 0.0050\n", + "Epoch 35/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0211 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 36/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0210 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 37/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0211 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 38/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0210 - val_loss: 0.0220 - lr: 0.0050\n", + "Epoch 39/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0211 - val_loss: 0.0219 - lr: 0.0050\n", + "Epoch 40/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0211 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 41/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0209 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 42/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0210 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 43/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0209 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 44/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0209 - val_loss: 0.0216 - lr: 0.0050\n", + "Epoch 45/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0209 - val_loss: 0.0216 - lr: 0.0050\n", + "Epoch 46/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0208 - val_loss: 0.0216 - lr: 0.0050\n", + "Epoch 47/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0208 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 48/2000\n", + "45/45 [==============================] - 0s 956us/step - loss: 0.0208 - val_loss: 0.0215 - lr: 0.0050\n", + "Epoch 49/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0208 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 50/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0209 - val_loss: 0.0213 - lr: 0.0050\n", + "Epoch 51/2000\n", + "45/45 [==============================] - 0s 924us/step - loss: 0.0207 - val_loss: 0.0215 - lr: 0.0050\n", + "Epoch 52/2000\n", + "45/45 [==============================] - 0s 891us/step - loss: 0.0207 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 53/2000\n", + "45/45 [==============================] - 0s 916us/step - loss: 0.0207 - val_loss: 0.0217 - lr: 0.0050\n", + "Epoch 54/2000\n", + "45/45 [==============================] - 0s 905us/step - loss: 0.0207 - val_loss: 0.0215 - lr: 0.0050\n", + "Epoch 55/2000\n", + "45/45 [==============================] - 0s 908us/step - loss: 0.0208 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 56/2000\n", + "45/45 [==============================] - 0s 879us/step - loss: 0.0208 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 57/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0207 - val_loss: 0.0212 - lr: 0.0050\n", + "Epoch 58/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0212 - lr: 0.0050\n", + "Epoch 59/2000\n", + "45/45 [==============================] - 0s 920us/step - loss: 0.0205 - val_loss: 0.0212 - lr: 0.0050\n", + "Epoch 60/2000\n", + "45/45 [==============================] - 0s 965us/step - loss: 0.0206 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 61/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 62/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0214 - lr: 0.0050\n", + "Epoch 63/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0213 - lr: 0.0050\n", + "Epoch 64/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0211 - lr: 0.0050\n", + "Epoch 65/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0211 - lr: 0.0050\n", + "Epoch 66/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0211 - lr: 0.0050\n", + "Epoch 67/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0207 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 68/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 69/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0211 - lr: 0.0050\n", + "Epoch 70/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 71/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 72/2000\n", + "45/45 [==============================] - 0s 991us/step - loss: 0.0206 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 73/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 74/2000\n", + "45/45 [==============================] - 0s 996us/step - loss: 0.0206 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 75/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0211 - lr: 0.0050\n", + "Epoch 76/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0206 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 77/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0204 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 78/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 79/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0204 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 80/2000\n", + "45/45 [==============================] - 0s 981us/step - loss: 0.0205 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 81/2000\n", + "45/45 [==============================] - 0s 938us/step - loss: 0.0205 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 82/2000\n", + "45/45 [==============================] - 0s 926us/step - loss: 0.0203 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 83/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0205 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 84/2000\n", + "45/45 [==============================] - 0s 958us/step - loss: 0.0204 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 85/2000\n", + "45/45 [==============================] - 0s 923us/step - loss: 0.0204 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 86/2000\n", + "45/45 [==============================] - 0s 921us/step - loss: 0.0203 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 87/2000\n", + "45/45 [==============================] - 0s 909us/step - loss: 0.0204 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 88/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 89/2000\n", + "45/45 [==============================] - 0s 914us/step - loss: 0.0204 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 90/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0204 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 91/2000\n", + "45/45 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0.0050\n", + "Epoch 99/2000\n", + "45/45 [==============================] - 0s 930us/step - loss: 0.0203 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 100/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 101/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 102/2000\n", + "45/45 [==============================] - 0s 893us/step - loss: 0.0202 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 103/2000\n", + "45/45 [==============================] - 0s 883us/step - loss: 0.0203 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 104/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 105/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 106/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 107/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 108/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 109/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 110/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0210 - lr: 0.0050\n", + "Epoch 111/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 112/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0209 - lr: 0.0050\n", + "Epoch 113/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 114/2000\n", + "45/45 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+ "Epoch 122/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 123/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 124/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 125/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 126/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0203 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 127/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 128/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 129/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 130/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 131/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0208 - lr: 0.0050\n", + "Epoch 132/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 133/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 134/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 135/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 136/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 137/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 138/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 139/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 140/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 141/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 142/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 143/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0202 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 144/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 145/2000\n", + "45/45 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+ "Epoch 153/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 154/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 155/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 156/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 157/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 158/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0201 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 159/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 160/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 161/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 162/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 163/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 164/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 165/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 166/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 167/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 168/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 169/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 170/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 171/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 172/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 173/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 174/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 175/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 176/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 177/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 178/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 179/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0200 - val_loss: 0.0207 - lr: 0.0050\n", + "Epoch 180/2000\n", + "45/45 [==============================] - 0s 992us/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 181/2000\n", + "45/45 [==============================] - 0s 929us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 182/2000\n", + "45/45 [==============================] - 0s 911us/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 183/2000\n", + "45/45 [==============================] - 0s 914us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 184/2000\n", + "45/45 [==============================] - 0s 916us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 185/2000\n", + "45/45 [==============================] - 0s 891us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 186/2000\n", + "45/45 [==============================] - 0s 906us/step - loss: 0.0201 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 187/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 188/2000\n", + "45/45 [==============================] - 0s 901us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 189/2000\n", + "45/45 [==============================] - 0s 923us/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 190/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 191/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 192/2000\n", + "45/45 [==============================] - 0s 948us/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 193/2000\n", + "45/45 [==============================] - 0s 892us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 194/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 195/2000\n", + "45/45 [==============================] - 0s 915us/step - loss: 0.0200 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 196/2000\n", + "45/45 [==============================] - 0s 930us/step - loss: 0.0200 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 197/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0206 - lr: 0.0050\n", + "Epoch 198/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 199/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 200/2000\n", + "45/45 [==============================] - 0s 984us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 201/2000\n", + "45/45 [==============================] - 0s 947us/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 202/2000\n", + "45/45 [==============================] - 0s 978us/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 203/2000\n", + "45/45 [==============================] - 0s 916us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 204/2000\n", + "45/45 [==============================] - 0s 911us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 205/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 206/2000\n", + "45/45 [==============================] - 0s 913us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 207/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 208/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 209/2000\n", + "45/45 [==============================] - 0s 921us/step - loss: 0.0199 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 210/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 211/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 212/2000\n", + "45/45 [==============================] - 0s 934us/step - loss: 0.0199 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 213/2000\n", + "45/45 [==============================] - 0s 927us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 214/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 215/2000\n", + "45/45 [==============================] - 0s 904us/step - loss: 0.0199 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 216/2000\n", + "45/45 [==============================] - 0s 907us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 217/2000\n", + "45/45 [==============================] - 0s 893us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 218/2000\n", + "45/45 [==============================] - 0s 908us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 219/2000\n", + "45/45 [==============================] - 0s 925us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 220/2000\n", + "45/45 [==============================] - 0s 906us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 221/2000\n", + "45/45 [==============================] - 0s 939us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 222/2000\n", + "45/45 [==============================] - 0s 949us/step - loss: 0.0197 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 223/2000\n", + "45/45 [==============================] - 0s 908us/step - loss: 0.0197 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 224/2000\n", + "45/45 [==============================] - 0s 884us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 225/2000\n", + "45/45 [==============================] - 0s 897us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 226/2000\n", + "45/45 [==============================] - 0s 941us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 227/2000\n", + "45/45 [==============================] - 0s 993us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 228/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 229/2000\n", + "45/45 [==============================] - 0s 924us/step - loss: 0.0198 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+ "Epoch 245/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 246/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 247/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 248/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 249/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 250/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 251/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 252/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0198 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 253/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 254/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 255/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 256/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 257/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 258/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 259/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 260/2000\n", + "45/45 [==============================] 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+ "Epoch 276/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 277/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 278/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 279/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 280/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 281/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 282/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 283/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 284/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 285/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 286/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 287/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 288/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0197 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 289/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 290/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 291/2000\n", + "45/45 [==============================] 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+ "Epoch 307/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 308/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 309/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 310/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 311/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 312/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 313/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 314/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 315/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 316/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 317/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 318/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 319/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 320/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0196 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 321/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 322/2000\n", + "45/45 [==============================] 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+ "Epoch 338/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 339/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 340/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 341/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 342/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 343/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 344/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 345/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 346/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 347/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 348/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 349/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 350/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 351/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 352/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 353/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 354/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 355/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 356/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 357/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 358/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 359/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 360/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 361/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 362/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 363/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 364/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 365/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 366/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 367/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 368/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 369/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 370/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 371/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 372/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 373/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 374/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 375/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 376/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 377/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 378/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 379/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 380/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 381/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 382/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 383/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 384/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 385/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 386/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 387/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 388/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 389/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 390/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 391/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 392/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 393/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 394/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 395/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 396/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 397/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 398/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 399/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 400/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 401/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 402/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 403/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 404/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 405/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 406/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 407/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 408/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 409/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 410/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 411/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 412/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 413/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 414/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 415/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 416/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 417/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 418/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 419/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 420/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 421/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 422/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 423/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 424/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 425/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 426/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 427/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 428/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 429/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 430/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 431/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 432/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 433/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0192 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 434/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 435/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 436/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 437/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 438/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 439/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 440/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 441/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 442/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 443/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 444/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 445/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 446/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 447/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 448/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 449/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 450/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 451/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 452/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 453/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 454/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 455/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 456/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 457/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 458/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 459/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 460/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 461/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 462/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 463/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 464/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 465/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 466/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 467/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 468/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 469/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 470/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 471/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 472/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 473/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 474/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 475/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 476/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 477/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 478/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 479/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 480/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 481/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 482/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 483/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 484/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 485/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 486/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 487/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 488/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 489/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 490/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 491/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 492/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 493/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 494/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 495/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 496/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 497/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 498/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 499/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 500/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 501/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0190 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 502/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 503/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 504/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 505/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 506/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 507/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0189 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 508/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 509/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0189 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 510/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0189 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 511/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 512/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 513/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 514/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0190 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 515/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 516/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 517/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0189 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 518/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 519/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0189 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 520/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0189 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 521/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0189 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 522/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 523/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0187 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 524/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0190 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 525/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 526/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 527/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 528/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 529/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 530/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 531/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 532/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 533/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0187 - val_loss: 0.0195 - lr: 0.0050\n", + "Epoch 534/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 535/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 536/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0202 - lr: 0.0050\n", + "Epoch 537/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 538/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 539/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 540/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0200 - lr: 0.0050\n", + "Epoch 541/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 542/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 543/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 544/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 545/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 546/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 547/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 548/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 549/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0188 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 550/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0186 - val_loss: 0.0194 - lr: 0.0050\n", + "Epoch 551/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 552/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 553/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 554/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 555/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0189 - val_loss: 0.0204 - lr: 0.0050\n", + "Epoch 556/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 557/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 558/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 559/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 560/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 561/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 562/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0199 - lr: 0.0050\n", + "Epoch 563/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 564/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0201 - lr: 0.0050\n", + "Epoch 565/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 566/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 567/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0197 - lr: 0.0050\n", + "Epoch 568/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0187 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 569/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0188 - val_loss: 0.0195 - lr: 0.0050\n", + "Epoch 570/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0195 - lr: 0.0050\n", + "Epoch 571/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0195 - lr: 0.0050\n", + "Epoch 572/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0186 - val_loss: 0.0196 - lr: 0.0050\n", + "Epoch 573/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0198 - lr: 0.0050\n", + "Epoch 574/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0186 - val_loss: 0.0203 - lr: 0.0050\n", + "Epoch 575/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0205 - lr: 0.0050\n", + "Epoch 576/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0200 - lr: 0.0025\n", + "Epoch 577/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0196 - lr: 0.0025\n", + "Epoch 578/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 579/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 580/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0196 - lr: 0.0025\n", + "Epoch 581/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0186 - val_loss: 0.0197 - lr: 0.0025\n", + "Epoch 582/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 583/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 584/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0184 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 585/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 586/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 587/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 588/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 589/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 590/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0186 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 591/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 592/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 593/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 594/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0196 - lr: 0.0025\n", + "Epoch 595/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 596/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 597/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 598/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0184 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 599/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 600/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0184 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 601/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 602/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0191 - lr: 0.0025\n", + "Epoch 603/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 604/2000\n", + "45/45 [==============================] - 0s 3ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 605/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0184 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 606/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 607/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 608/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0184 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 609/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0185 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 610/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0182 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 611/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0184 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 612/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0183 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 613/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0184 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 614/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0191 - lr: 0.0025\n", + "Epoch 615/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0183 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 616/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0184 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 617/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 618/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 619/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0183 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 620/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0183 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 621/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 622/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 623/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 624/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 625/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 626/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0182 - val_loss: 0.0191 - lr: 0.0025\n", + "Epoch 627/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0191 - lr: 0.0025\n", + "Epoch 628/2000\n", + "45/45 [==============================] - 0s 944us/step - loss: 0.0182 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 629/2000\n", + "45/45 [==============================] - 0s 999us/step - loss: 0.0181 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 630/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 631/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0196 - lr: 0.0025\n", + "Epoch 632/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 633/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 634/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 635/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 636/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 637/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 638/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 639/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 640/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0179 - val_loss: 0.0197 - lr: 0.0025\n", + "Epoch 641/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0179 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 642/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0179 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 643/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0180 - val_loss: 0.0187 - lr: 0.0025\n", + "Epoch 644/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0189 - lr: 0.0025\n", + "Epoch 645/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0180 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 646/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0191 - lr: 0.0025\n", + "Epoch 647/2000\n", + "45/45 [==============================] - 0s 1000us/step - loss: 0.0180 - val_loss: 0.0188 - lr: 0.0025\n", + "Epoch 648/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0181 - val_loss: 0.0187 - lr: 0.0025\n", + "Epoch 649/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 650/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0190 - lr: 0.0025\n", + "Epoch 651/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0189 - lr: 0.0025\n", + "Epoch 652/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0191 - lr: 0.0025\n", + "Epoch 653/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0189 - lr: 0.0025\n", + "Epoch 654/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0196 - lr: 0.0025\n", + "Epoch 655/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0199 - lr: 0.0025\n", + "Epoch 656/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0178 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 657/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0198 - lr: 0.0025\n", + "Epoch 658/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0194 - lr: 0.0025\n", + "Epoch 659/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 660/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 661/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0177 - val_loss: 0.0198 - lr: 0.0025\n", + "Epoch 662/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0177 - val_loss: 0.0196 - lr: 0.0025\n", + "Epoch 663/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0176 - val_loss: 0.0195 - lr: 0.0025\n", + "Epoch 664/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0176 - val_loss: 0.0203 - lr: 0.0025\n", + "Epoch 665/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0176 - val_loss: 0.0192 - lr: 0.0025\n", + "Epoch 666/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0176 - val_loss: 0.0193 - lr: 0.0025\n", + "Epoch 667/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0200 - lr: 0.0025\n", + "Epoch 668/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0204 - lr: 0.0025\n", + "Epoch 669/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0196 - lr: 0.0012\n", + "Epoch 670/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0176 - val_loss: 0.0197 - lr: 0.0012\n", + "Epoch 671/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0190 - lr: 0.0012\n", + "Epoch 672/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0191 - lr: 0.0012\n", + "Epoch 673/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 674/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 675/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 676/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0175 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 677/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0176 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 678/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 679/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 680/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 681/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 682/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 683/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0175 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 684/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 685/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 686/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 687/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0182 - lr: 0.0012\n", + "Epoch 688/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0174 - val_loss: 0.0183 - lr: 0.0012\n", + "Epoch 689/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 690/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 691/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0191 - lr: 0.0012\n", + "Epoch 692/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0194 - lr: 0.0012\n", + "Epoch 693/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 694/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0174 - val_loss: 0.0190 - lr: 0.0012\n", + "Epoch 695/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0189 - lr: 0.0012\n", + "Epoch 696/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 697/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 698/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 699/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 700/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 701/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0189 - lr: 0.0012\n", + "Epoch 702/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0173 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 703/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 704/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 705/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0189 - lr: 0.0012\n", + "Epoch 706/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0184 - lr: 0.0012\n", + "Epoch 707/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 708/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 709/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0191 - lr: 0.0012\n", + "Epoch 710/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 711/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0172 - val_loss: 0.0180 - lr: 0.0012\n", + "Epoch 712/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0172 - val_loss: 0.0181 - lr: 0.0012\n", + "Epoch 713/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 714/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 715/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 716/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0186 - lr: 0.0012\n", + "Epoch 717/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0181 - lr: 0.0012\n", + "Epoch 718/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0171 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 719/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 720/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0185 - lr: 0.0012\n", + "Epoch 721/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 722/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0192 - lr: 0.0012\n", + "Epoch 723/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0190 - lr: 0.0012\n", + "Epoch 724/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 725/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 726/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0192 - lr: 0.0012\n", + "Epoch 727/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0194 - lr: 0.0012\n", + "Epoch 728/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0188 - lr: 0.0012\n", + "Epoch 729/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0187 - lr: 0.0012\n", + "Epoch 730/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0170 - val_loss: 0.0198 - lr: 0.0012\n", + "Epoch 731/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0197 - lr: 0.0012\n", + "Epoch 732/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0199 - lr: 0.0012\n", + "Epoch 733/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0204 - lr: 0.0012\n", + "Epoch 734/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0210 - lr: 0.0012\n", + "Epoch 735/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0190 - lr: 0.0012\n", + "Epoch 736/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0169 - val_loss: 0.0194 - lr: 0.0012\n", + "Epoch 737/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0185 - lr: 6.2500e-04\n", + "Epoch 738/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 739/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0180 - lr: 6.2500e-04\n", + "Epoch 740/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 741/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0177 - lr: 6.2500e-04\n", + "Epoch 742/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0169 - val_loss: 0.0177 - lr: 6.2500e-04\n", + "Epoch 743/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 744/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0181 - lr: 6.2500e-04\n", + "Epoch 745/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0183 - lr: 6.2500e-04\n", + "Epoch 746/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0180 - lr: 6.2500e-04\n", + "Epoch 747/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 748/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 749/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0168 - val_loss: 0.0180 - lr: 6.2500e-04\n", + "Epoch 750/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 751/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0181 - lr: 6.2500e-04\n", + "Epoch 752/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 753/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0180 - lr: 6.2500e-04\n", + "Epoch 754/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 755/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 756/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0175 - lr: 6.2500e-04\n", + "Epoch 757/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0175 - lr: 6.2500e-04\n", + "Epoch 758/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0175 - lr: 6.2500e-04\n", + "Epoch 759/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0167 - val_loss: 0.0175 - lr: 6.2500e-04\n", + "Epoch 760/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0177 - lr: 6.2500e-04\n", + "Epoch 761/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 762/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 763/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0182 - lr: 6.2500e-04\n", + "Epoch 764/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0181 - lr: 6.2500e-04\n", + "Epoch 765/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 766/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 767/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0167 - val_loss: 0.0176 - lr: 6.2500e-04\n", + "Epoch 768/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0166 - val_loss: 0.0174 - lr: 6.2500e-04\n", + "Epoch 769/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0164 - val_loss: 0.0177 - lr: 6.2500e-04\n", + "Epoch 770/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0177 - lr: 6.2500e-04\n", + "Epoch 771/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0176 - lr: 6.2500e-04\n", + "Epoch 772/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0165 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 773/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0165 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 774/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0178 - lr: 6.2500e-04\n", + "Epoch 775/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0184 - lr: 6.2500e-04\n", + "Epoch 776/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0165 - val_loss: 0.0183 - lr: 6.2500e-04\n", + "Epoch 777/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0166 - val_loss: 0.0179 - lr: 6.2500e-04\n", + "Epoch 778/2000\n", 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0.0162 - val_loss: 0.0171 - lr: 3.1250e-04\n", + "Epoch 831/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0163 - val_loss: 0.0170 - lr: 3.1250e-04\n", + "Epoch 832/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 833/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 834/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 835/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0170 - lr: 3.1250e-04\n", + "Epoch 836/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0163 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 837/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0162 - val_loss: 0.0170 - lr: 3.1250e-04\n", + "Epoch 838/2000\n", 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0.0161 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 891/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 892/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0170 - lr: 3.1250e-04\n", + "Epoch 893/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 894/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 895/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 896/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0161 - val_loss: 0.0169 - lr: 3.1250e-04\n", + "Epoch 897/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0159 - val_loss: 0.0171 - lr: 3.1250e-04\n", + "Epoch 898/2000\n", 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0.0161 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 906/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 907/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0166 - lr: 3.1250e-04\n", + "Epoch 908/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 909/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0166 - lr: 3.1250e-04\n", + "Epoch 910/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 911/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 912/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 913/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 914/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0166 - lr: 3.1250e-04\n", + "Epoch 915/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 916/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0160 - val_loss: 0.0166 - lr: 3.1250e-04\n", + "Epoch 917/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 918/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0168 - lr: 3.1250e-04\n", + "Epoch 919/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 920/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 921/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0166 - lr: 3.1250e-04\n", + "Epoch 922/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 923/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 924/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0166 - lr: 3.1250e-04\n", + "Epoch 925/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 926/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0167 - lr: 3.1250e-04\n", + "Epoch 927/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 928/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 929/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0165 - lr: 1.5625e-04\n", + "Epoch 930/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 931/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 932/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 933/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0159 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 934/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 935/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 936/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 937/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 938/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 939/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 940/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 941/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 942/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 943/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 944/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 945/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 946/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 947/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 948/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 949/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 950/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 951/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 952/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0159 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 953/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 954/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 955/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 956/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 957/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 958/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0164 - lr: 1.5625e-04\n", + "Epoch 959/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 960/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 961/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 962/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 963/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 964/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 965/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 966/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 967/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 968/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0158 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 969/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 970/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 971/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 972/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 973/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 974/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 975/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 976/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 977/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 978/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 979/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 980/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 981/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 982/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 983/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 984/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 985/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 986/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 987/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 988/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 989/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 990/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 991/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 992/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 993/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 994/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 995/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 996/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 997/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 998/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0163 - lr: 1.5625e-04\n", + "Epoch 999/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1000/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1001/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1002/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1003/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1004/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1005/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1006/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1007/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1008/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1009/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1010/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1011/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1012/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1013/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1014/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1015/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1016/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1017/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1018/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1019/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1020/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1021/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0158 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1022/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1023/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1024/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1025/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1026/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1027/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1028/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0157 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1029/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1030/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1031/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1032/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 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+ "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1041/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1042/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0157 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1043/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1044/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1045/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1046/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1047/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1048/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1049/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1050/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1051/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1052/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1053/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1054/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1055/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1056/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1057/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1058/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1059/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0162 - lr: 1.5625e-04\n", + "Epoch 1060/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1061/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1062/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1063/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1064/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1065/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1066/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1067/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1068/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1069/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1070/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1071/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0156 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1072/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1073/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0156 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1074/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1075/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1076/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1077/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1078/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1079/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1080/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1081/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1082/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1083/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1084/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1085/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1086/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1087/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0154 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1088/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1089/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1090/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1091/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1092/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1093/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0155 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1094/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0154 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1095/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1096/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1097/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1098/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1099/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1100/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1101/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1102/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1103/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1104/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1105/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1106/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1107/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0154 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1108/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1109/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1110/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0161 - lr: 1.5625e-04\n", + "Epoch 1111/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1112/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1113/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1114/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1115/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0159 - lr: 1.5625e-04\n", + "Epoch 1116/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1117/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1118/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1119/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0160 - lr: 1.5625e-04\n", + "Epoch 1120/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0159 - lr: 7.8125e-05\n", + "Epoch 1121/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0159 - lr: 7.8125e-05\n", + "Epoch 1122/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1123/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0153 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1124/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0154 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1125/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1126/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1127/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1128/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1129/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1130/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1131/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1132/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1133/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1134/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1135/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1136/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1137/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1138/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1139/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1140/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1141/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1142/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1143/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0158 - lr: 7.8125e-05\n", + "Epoch 1144/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1145/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1146/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1147/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1148/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1149/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1150/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1151/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1152/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1153/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1154/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1155/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1156/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1157/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1158/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1159/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1160/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1161/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1162/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1163/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1164/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1165/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1166/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1167/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1168/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1169/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1170/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1171/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1172/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1173/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1174/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1175/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1176/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1177/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1178/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1179/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0153 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1180/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1181/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1182/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1183/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1184/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1185/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0157 - lr: 7.8125e-05\n", + "Epoch 1186/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1187/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1188/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1189/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1190/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1191/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1192/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1193/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1194/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1195/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1196/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1197/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1198/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1199/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1200/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1201/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1202/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1203/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1204/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1205/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1206/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1207/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1208/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1209/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1210/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1211/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1212/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1213/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1214/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1215/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1216/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1217/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1218/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1219/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1220/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1221/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1222/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1223/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1224/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1225/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1226/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1227/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1228/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1229/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1230/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1231/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1232/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1233/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1234/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1235/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1236/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1237/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1238/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1239/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1240/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1241/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1242/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1243/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1244/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1245/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1246/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1247/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1248/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1249/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0152 - val_loss: 0.0156 - lr: 7.8125e-05\n", + "Epoch 1250/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1251/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1252/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1253/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1254/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1255/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0152 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1256/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1257/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1258/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1259/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1260/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1261/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1262/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1263/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1264/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1265/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1266/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1267/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1268/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1269/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1270/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1271/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1272/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1273/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1274/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1275/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1276/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1277/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1278/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1279/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1280/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1281/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1282/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1283/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1284/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1285/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1286/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1287/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1288/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1289/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1290/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1291/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1292/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0155 - lr: 7.8125e-05\n", + "Epoch 1293/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1294/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1295/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1296/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1297/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1298/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1299/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1300/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1301/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1302/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1303/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1304/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1305/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1306/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1307/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1308/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0151 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1309/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1310/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1311/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1312/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1313/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1314/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1315/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1316/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1317/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1318/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0151 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1319/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1320/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1321/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1322/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1323/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1324/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1325/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1326/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1327/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1328/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1329/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1330/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1331/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1332/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1333/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1334/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1335/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1336/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1337/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1338/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1339/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1340/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1341/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1342/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1343/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1344/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1345/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1346/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1347/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1348/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1349/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1350/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1351/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1352/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1353/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1354/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1355/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1356/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1357/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1358/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0150 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1359/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0154 - lr: 7.8125e-05\n", + "Epoch 1360/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1361/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1362/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1363/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1364/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1365/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1366/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1367/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1368/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1369/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1370/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1371/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1372/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1373/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1374/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1375/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1376/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1377/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1378/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1379/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0150 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1380/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1381/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1382/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1383/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1384/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1385/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1386/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1387/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1388/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1389/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1390/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1391/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1392/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1393/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1394/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1395/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1396/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1397/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1398/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1399/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1400/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1401/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1402/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1403/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0153 - lr: 7.8125e-05\n", + "Epoch 1404/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1405/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1406/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0149 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1407/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1408/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1409/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1410/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1411/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1412/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1413/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1414/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1415/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1416/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1417/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1418/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1419/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1420/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1421/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1422/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1423/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1424/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1425/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1426/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1427/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1428/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1429/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1430/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1431/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1432/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1433/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1434/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1435/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1436/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1437/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1438/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1439/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1440/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1441/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1442/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1443/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1444/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1445/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1446/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1447/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1448/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1449/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1450/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1451/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1452/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1453/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1454/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1455/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1456/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1457/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1458/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1459/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1460/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1461/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1462/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1463/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1464/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1465/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1466/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0152 - lr: 7.8125e-05\n", + "Epoch 1467/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1468/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1469/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1470/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1471/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1472/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1473/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1474/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1475/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1476/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1477/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1478/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1479/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1480/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1481/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1482/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1483/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1484/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0148 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1485/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1486/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1487/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1488/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1489/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1490/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1491/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1492/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1493/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1494/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1495/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1496/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1497/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1498/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1499/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1500/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1501/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1502/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1503/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1504/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1505/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1506/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1507/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1508/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1509/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1510/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0151 - lr: 7.8125e-05\n", + "Epoch 1511/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1512/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1513/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1514/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1515/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1516/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1517/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1518/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1519/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1520/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1521/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1522/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1523/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1524/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1525/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1526/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1527/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1528/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1529/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1530/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1531/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1532/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1533/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1534/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1535/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1536/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1537/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1538/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1539/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1540/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0147 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1541/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1542/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1543/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1544/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1545/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1546/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1547/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1548/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1549/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1550/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1551/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1552/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0150 - lr: 7.8125e-05\n", + "Epoch 1553/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1554/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1555/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1556/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1557/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1558/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1559/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1560/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1561/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1562/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1563/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1564/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1565/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1566/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1567/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1568/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1569/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1570/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1571/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1572/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1573/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1574/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1575/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1576/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1577/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0146 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1578/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1579/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1580/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1581/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1582/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1583/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1584/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1585/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1586/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1587/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1588/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1589/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1590/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1591/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1592/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1593/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1594/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1595/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1596/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1597/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1598/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1599/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1600/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1601/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1602/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1603/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1604/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1605/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1606/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1607/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0147 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1608/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1609/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1610/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0149 - lr: 7.8125e-05\n", + "Epoch 1611/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1612/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1613/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1614/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1615/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1616/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1617/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1618/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1619/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1620/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1621/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1622/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1623/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1624/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1625/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1626/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1627/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1628/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1629/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1630/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1631/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1632/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1633/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1634/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1635/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1636/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1637/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1638/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1639/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1640/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1641/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1642/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1643/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1644/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1645/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1646/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1647/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1648/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1649/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1650/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1651/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1652/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1653/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1654/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1655/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1656/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1657/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1658/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1659/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1660/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1661/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1662/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1663/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1664/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0148 - lr: 7.8125e-05\n", + "Epoch 1665/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1666/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1667/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0145 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1668/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1669/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1670/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1671/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1672/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1673/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1674/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1675/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1676/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1677/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1678/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1679/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1680/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1681/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1682/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1683/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1684/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1685/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1686/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1687/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1688/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1689/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1690/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1691/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1692/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1693/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1694/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1695/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1696/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1697/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1698/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1699/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1700/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1701/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1702/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1703/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1704/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1705/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1706/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1707/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1708/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1709/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1710/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1711/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1712/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1713/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1714/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1715/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1716/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1717/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1718/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1719/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1720/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0144 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1721/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1722/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1723/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1724/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1725/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1726/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1727/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1728/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0147 - lr: 7.8125e-05\n", + "Epoch 1729/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1730/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1731/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1732/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1733/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1734/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1735/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1736/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1737/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1738/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1739/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1740/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1741/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1742/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1743/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1744/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1745/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1746/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1747/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1748/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1749/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1750/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1751/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1752/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1753/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1754/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1755/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1756/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1757/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1758/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1759/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1760/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1761/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1762/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1763/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1764/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1765/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1766/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1767/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1768/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1769/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1770/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1771/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0143 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1772/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1773/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1774/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1775/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1776/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1777/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0146 - lr: 7.8125e-05\n", + "Epoch 1778/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1779/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1780/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1781/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1782/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1783/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1784/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1785/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1786/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1787/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1788/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1789/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1790/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1791/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1792/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1793/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1794/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1795/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1796/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1797/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1798/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1799/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1800/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1801/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1802/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1803/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1804/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1805/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1806/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1807/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1808/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1809/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1810/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1811/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1812/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1813/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1814/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1815/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1816/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1817/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1818/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1819/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1820/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1821/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1822/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1823/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1824/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1825/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1826/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1827/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1828/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1829/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1830/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0145 - lr: 7.8125e-05\n", + "Epoch 1831/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1832/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1833/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1834/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0142 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1835/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1836/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1837/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1838/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1839/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1840/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1841/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1842/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1843/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1844/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1845/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1846/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1847/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1848/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1849/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1850/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1851/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1852/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1853/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1854/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1855/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1856/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1857/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1858/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1859/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1860/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1861/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1862/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1863/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1864/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1865/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1866/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1867/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1868/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1869/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1870/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1871/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1872/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1873/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1874/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0141 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1875/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1876/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1877/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1878/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1879/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0144 - lr: 7.8125e-05\n", + "Epoch 1880/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1881/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1882/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1883/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1884/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1885/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1886/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1887/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1888/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1889/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1890/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1891/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1892/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1893/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1894/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1895/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1896/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1897/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1898/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1899/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1900/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1901/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1902/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1903/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1904/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1905/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1906/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1907/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1908/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1909/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1910/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1911/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1912/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1913/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1914/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1915/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1916/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1917/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1918/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1919/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1920/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1921/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1922/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1923/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1924/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1925/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1926/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1927/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1928/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0143 - lr: 7.8125e-05\n", + "Epoch 1929/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1930/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1931/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1932/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1933/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1934/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1935/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1936/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1937/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1938/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1939/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1940/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1941/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1942/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1943/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1944/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1945/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1946/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1947/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1948/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1949/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1950/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1951/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1952/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1953/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1954/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1955/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1956/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1957/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1958/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1959/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1960/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1961/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1962/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1963/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1964/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1965/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1966/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1967/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1968/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1969/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0140 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1970/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1971/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1972/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1973/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1974/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1975/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1976/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1977/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1978/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1979/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0136 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1980/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0139 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1981/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1982/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0142 - lr: 7.8125e-05\n", + "Epoch 1983/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1984/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1985/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1986/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1987/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1988/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1989/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1990/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1991/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1992/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1993/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1994/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1995/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1996/2000\n", + "45/45 [==============================] - 0s 2ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1997/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0138 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1998/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 1999/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n", + "Epoch 2000/2000\n", + "45/45 [==============================] - 0s 1ms/step - loss: 0.0137 - val_loss: 0.0141 - lr: 7.8125e-05\n" + ] + } + ], + "source": [ + "epoch, batch_size = 2000, 128\n", + "history_shortcut_11 = shortcut11.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)\n", + "history_shortcut_5 = shortcut5.fit(x_train, y_train, x_val, y_val, epoch=epoch, batch_size=batch_size, method=training_method)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "x = np.array(range(len(history_shortcut_11.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN11', c='b')\n", + "ax.plot(x, 100*moving_average(history_shortcut_11.history[\"loss\"], smoothing_windows), linewidth=.5, c='b')\n", + "x = np.array(range(len(history_shortcut_5.history['loss']) - smoothing_windows + 1))\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"val_loss\"], smoothing_windows), linewidth=3.0, label='SCCNN5', c='r')\n", + "ax.plot(x, 100*moving_average(history_shortcut_5.history[\"loss\"], smoothing_windows), linewidth=.5, c='r')\n", + "ax.set_xlabel(\"iter\")\n", + "ax.set_ylabel(\"error(%)\")\n", + "ax.set_xlim(0, 2000)\n", + "ax.set_ylim(0.5, 1.7)\n", + "ax.spines[\"top\"].set_visible(False)\n", + "ax.spines[\"right\"].set_visible(False)\n", + "ax.yaxis.set_major_locator(ticker.LinearLocator(numticks=6))\n", + "ax.grid(axis='y', linestyle='--')\n", + "ax.annotate(\"11-layer\", (500, 0.24), c='b')\n", + "ax.annotate(\"5-layer\", (500, 0.255), c='r')\n", + "plt.legend(loc=3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# plt.savefig(fname=\"fig2.png\", dpi=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import os\n", + "time_spent = (time.time() - time1) /60" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "18.78054288228353 min\n" + ] + } + ], + "source": [ + "print(time_spent, \"min\")" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + } + ], + "metadata": { + "interpreter": { + "hash": "7f619fc91ee8bdab81d49e7c14228037474662e3f2d607687ae505108922fa06" + }, + "kernelspec": { + "display_name": "Python 3.9.7 64-bit ('base': conda)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} \ No newline at end of file diff --git a/03_model_evaluating.ipynb b/03_model_evaluating.ipynb old mode 100644 new mode 100755 index a9b35c4..568442e --- a/03_model_evaluating.ipynb +++ b/03_model_evaluating.ipynb @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 2, "metadata": { "collapsed": false, "pycharm": { @@ -57,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 4, "metadata": { "collapsed": false, "pycharm": { @@ -92,7 +92,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 11, "metadata": { "collapsed": false, "pycharm": { @@ -104,18 +104,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "plain 5 mse : 0.05133910188824081\n", - "plain 5 Dry matter content error 0.7758644362065223\n", - "plain 5 r^2 : 0.902928516828363\n", - "plain 11 mse : 0.05200769624271875\n", - "plain 11 Dry matter content error 0.7859685978067217\n", - "plain 11 r^2 : 0.9003837097594369\n", - "shortcut 5 mse : 0.051382735052895194\n", - "shortcut 5 Dry matter content error 0.7765238443272209\n", - "shortcut 5 r^2 : 0.9027634443691182\n", - "shortcut11 mse : 0.05078784364469306\n", - "shortcut11 Dry matter content error 0.7675335217455442\n", - "shortcut11 r^2 : 0.9050019525259844\n" + "plain 5 mse: 0.007162414257423199\n", + "plain 5 rmse : 0.08463104783365971\n", + "plain 5 Dry matter content error 1.278990434152287\n", + "plain 5 r^2 : 0.7362122841198271\n", + "plain 11 mse: 0.027140651722534437\n", + "plain 11 rmse : 0.16474420087679698\n", + "plain 11 Dry matter content error 2.4897039844954327\n", + "plain 11 r^2 : 0.0004249589491984729\n", + "shortcut 5 mse: 0.007429169596940547\n", + "shortcut 5 rmse : 0.08619263075774254\n", + "shortcut 5 Dry matter content error 1.3025899248021375\n", + "shortcut 5 r^2 : 0.7263878339859644\n", + "shortcut11 mse: 0.007825262774295792\n", + "shortcut11 rmse : 0.08846051534043757\n", + "shortcut11 Dry matter content error 1.3368634303450377\n", + "shortcut11 r^2 : 0.7117999435379954\n" ] } ], @@ -128,23 +132,208 @@ "models = {'plain 5': plain_5, 'plain 11': plain_11, 'shortcut 5': shortcut5, 'shortcut11': shortcut11}\n", "results = {model_name: model.predict(x_test).reshape((-1, )) for model_name, model in models.items()}\n", "for model_name, model_result in results.items():\n", - " rmse = np.sqrt(mean_squared_error(y_test, model_result))\n", - " print(model_name, \"mse : \", rmse)\n", + " mse = mean_squared_error(y_test, model_result)\n", + " rmse = np.sqrt(mse)\n", + " print(model_name, \"mse: \", mse)\n", + " print(model_name, \"rmse : \", rmse)\n", " print(model_name, \"Dry matter content error\", retransform(rmse))\n", " print(model_name, \"r^2 :\", r2_score(y_test, model_result))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "plain 5 nadam mse: 0.0025042022303828344\n", + "plain 5 nadam rmse : 0.0500420046599138\n", + "plain 5 nadam Dry matter content error 0.7562619972711523\n", + "plain 5 nadam r^2 : 0.9077716308058986\n", + "plain 11 nadam mse: 0.0027148425657891745\n", + "plain 11 nadam rmse : 0.05210415113778531\n", + "plain 11 nadam Dry matter content error 0.7874262766524306\n", + "plain 11 nadam r^2 : 0.900013864925283\n", + "shortcut 5 nadam mse: 0.0026949613632585197\n", + "shortcut 5 nadam rmse : 0.051913017281396\n", + "shortcut 5 nadam Dry matter content error 0.7845377578378575\n", + "shortcut 5 nadam r^2 : 0.9007460785080253\n", + "shortcut11 nadam mse: 0.002492666414101387\n", + "shortcut11 nadam rmse : 0.049926610280504595\n", + "shortcut11 nadam Dry matter content error 0.754518094634978\n", + "shortcut11 nadam r^2 : 0.9081964884751603\n" + ] + } + ], + "source": [ + "plain_5, plain_11 = load_model('./checkpoints/plain5_nadam.hdf5'), load_model('./checkpoints/plain11_nadam.hdf5')\n", + "shortcut5, shortcut11 = load_model('./checkpoints/shortcut5_nadam.hdf5'), load_model('./checkpoints/shortcut11_nadam.hdf5')\n", + "models = {'plain 5 nadam': plain_5, 'plain 11 nadam': plain_11, 'shortcut 5 nadam': shortcut5, 'shortcut11 nadam': shortcut11}\n", + "results = {model_name: model.predict(x_test).reshape((-1, )) for model_name, model in models.items()}\n", + "for model_name, model_result in results.items():\n", + " mse = mean_squared_error(y_test, model_result)\n", + " rmse = np.sqrt(mse)\n", + " print(model_name, \"mse: \", mse)\n", + " print(model_name, \"rmse : \", rmse)\n", + " print(model_name, \"Dry matter content error\", retransform(rmse))\n", + " print(model_name, \"r^2 :\", r2_score(y_test, model_result))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "plain 5 rmsprop mse: 0.0025762880890505646\n", + "plain 5 rmsprop rmse : 0.05075714815718634\n", + "plain 5 rmsprop Dry matter content error 0.7670696348399975\n", + "plain 5 rmsprop r^2 : 0.905116748901307\n", + "plain 11 rmsprop mse: 0.0026627965381971945\n", + "plain 11 rmsprop rmse : 0.051602291985891426\n", + "plain 11 rmsprop Dry matter content error 0.7798419081376315\n", + "plain 11 rmsprop r^2 : 0.9019306910464329\n", + "shortcut 5 rmsprop mse: 0.002591777512557128\n", + "shortcut 5 rmsprop rmse : 0.0509095031654909\n", + "shortcut 5 rmsprop Dry matter content error 0.7693721066066205\n", + "shortcut 5 rmsprop r^2 : 0.9045462820865926\n", + "shortcut11 rmsprop mse: 0.0025523285716201384\n", + "shortcut11 rmsprop rmse : 0.050520575725343214\n", + "shortcut11 rmsprop Dry matter content error 0.7634944235545812\n", + "shortcut11 rmsprop r^2 : 0.9059991645434926\n" + ] + } + ], + "source": [ + "plain_5, plain_11 = load_model('./checkpoints/plain5_rmsprop.hdf5'), load_model('./checkpoints/plain11_rmsprop.hdf5')\n", + "shortcut5, shortcut11 = load_model('./checkpoints/shortcut5_rmsprop.hdf5'), load_model('./checkpoints/shortcut11_rmsprop.hdf5')\n", + "models = {'plain 5 rmsprop': plain_5, 'plain 11 rmsprop': plain_11, 'shortcut 5 rmsprop': shortcut5, 'shortcut11 rmsprop': shortcut11}\n", + "results = {model_name: model.predict(x_test).reshape((-1, )) for model_name, model in models.items()}\n", + "for model_name, model_result in results.items():\n", + " mse = mean_squared_error(y_test, model_result)\n", + " rmse = np.sqrt(mse)\n", + " print(model_name, \"mse: \", mse)\n", + " print(model_name, \"rmse : \", rmse)\n", + " print(model_name, \"Dry matter content error\", retransform(rmse))\n", + " print(model_name, \"r^2 :\", r2_score(y_test, model_result))" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 9, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "plain 5 sgd mse : 0.11134143767715826\n", + "plain 5 sgd Dry matter content error 1.682652375919312\n", + "plain 5 sgd r^2 : 0.543428518577538\n", + "plain 11 sgd mse : 0.1281311162291065\n", + "plain 11 sgd Dry matter content error 1.936387131781486\n", + "plain 11 sgd r^2 : 0.3953495916351124\n", + "shortcut 5 sgd mse : 0.07824195777158978\n", + "shortcut 5 sgd Dry matter content error 1.1824350294692925\n", + "shortcut 5 sgd r^2 : 0.7745373801958391\n", + "shortcut11 sgd mse : 0.09167697720606416\n", + "shortcut11 sgd Dry matter content error 1.3854723518136416\n", + "shortcut11 sgd r^2 : 0.690460767243821\n" + ] + } + ], + "source": [ + "plain_5, plain_11 = load_model('./checkpoints/plain5_sgd.hdf5'), load_model('./checkpoints/plain11_sgd.hdf5')\n", + "shortcut5, shortcut11 = load_model('./checkpoints/shortcut5_sgd.hdf5'), load_model('./checkpoints/shortcut11_sgd.hdf5')\n", + "models = {'plain 5 sgd': plain_5, 'plain 11 sgd': plain_11, 'shortcut 5 sgd': shortcut5, 'shortcut11 sgd': shortcut11}\n", + "results = {model_name: model.predict(x_test).reshape((-1, )) for model_name, model in models.items()}\n", + "for model_name, model_result in results.items():\n", + " rmse = np.sqrt(mean_squared_error(y_test, model_result))\n", + " print(model_name, \"mse : \", rmse)\n", + " print(model_name, \"Dry matter content error\", retransform(rmse))\n", + " print(model_name, \"r^2 :\", r2_score(y_test, model_result))" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 10, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "plain 5 adagrad mse : 0.09175815616893311\n", + "plain 5 adagrad Dry matter content error 1.3866991724618731\n", + "plain 5 adagrad r^2 : 0.6899123373115493\n", + "plain 11 adagrad mse : 0.10080308998502606\n", + "plain 11 adagrad Dry matter content error 1.5233911327346656\n", + "plain 11 adagrad r^2 : 0.6257663620335936\n", + "shortcut 5 adagrad mse : 0.07867384574842859\n", + "shortcut 5 adagrad Dry matter content error 1.18896195552234\n", + "shortcut 5 adagrad r^2 : 0.7720414471534031\n", + "shortcut11 adagrad mse : 0.08402036572248298\n", + "shortcut11 adagrad Dry matter content error 1.2697614738771157\n", + "shortcut11 adagrad r^2 : 0.7400054367232816\n" + ] + } + ], + "source": [ + "plain_5, plain_11 = load_model('./checkpoints/plain5_adagrad.hdf5'), load_model('./checkpoints/plain11_adagrad.hdf5')\n", + "shortcut5, shortcut11 = load_model('./checkpoints/shortcut5_adagrad.hdf5'), load_model('./checkpoints/shortcut11_adagrad.hdf5')\n", + "models = {'plain 5 adagrad': plain_5, 'plain 11 adagrad': plain_11, 'shortcut 5 adagrad': shortcut5, 'shortcut11 adagrad': shortcut11}\n", + "results = {model_name: model.predict(x_test).reshape((-1, )) for model_name, model in models.items()}\n", + "for model_name, model_result in results.items():\n", + " rmse = np.sqrt(mean_squared_error(y_test, model_result))\n", + " print(model_name, \"mse : \", rmse)\n", + " print(model_name, \"Dry matter content error\", retransform(rmse))\n", + " print(model_name, \"r^2 :\", r2_score(y_test, model_result))" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": null, "outputs": [], - "source": [] + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } } ], "metadata": { @@ -171,4 +360,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} +} \ No newline at end of file diff --git a/04_model_comparision.ipynb b/04_model_comparision.ipynb index 083b34b..bcf9e0f 100644 --- a/04_model_comparision.ipynb +++ b/04_model_comparision.ipynb @@ -12,21 +12,9 @@ "# Model comparison" ] }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": false, - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "## PLS" - ] - }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 11, "metadata": { "collapsed": false, "pycharm": { @@ -35,6 +23,8 @@ }, "outputs": [], "source": [ + "from keras.models import load_model\n", + "from sklearn.model_selection import train_test_split\n", "from sklearn.neural_network import MLPRegressor\n", "from sklearn.svm import SVR\n", "import numpy as np\n", @@ -42,14 +32,42 @@ "from sklearn.cross_decomposition import PLSRegression\n", "from sklearn.metrics import mean_squared_error, r2_score\n", "\n", - "data = loadmat('./dataset/mango/mango_dm_split.mat')\n", - "min_value, max_value = data['min_y'][-1][-1], data['max_y'][-1][-1]\n", - "retransform = lambda x: x * (max_value - min_value)" + "from models import Residual5, DNN\n", + "import tensorflow\n", + "from random import seed\n", + "\n", + "seed(85679)\n", + "tensorflow.random.set_seed(85679)" ] }, + { + "cell_type": "markdown", + "source": [ + "## PLS" + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 12, + "outputs": [], + "source": [ + "data = loadmat('./dataset/mango/mango_dm_split.mat')\n", + "min_value, max_value = data['min_y'][-1][-1], data['max_y'][-1][-1]\n", + "retransform = lambda x: x * (max_value - min_value)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -71,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 14, "metadata": { "collapsed": false, "pycharm": { @@ -89,9 +107,9 @@ "SVR RMSE: 0.1139650997574326\n", "SVR Dry matter content error 1.7223025845485895\n", "SVR R^2: 0.5216575965112935\n", - "MLP RMSE: 0.15508626630172465\n", - "MLP Dry matter content error 2.343748023280531\n", - "MLP R^2: 0.11418748397100065\n" + "MLP RMSE: 0.15231159655301899\n", + "MLP Dry matter content error 2.3018157046177476\n", + "MLP R^2: 0.14560032918931198\n" ] } ], @@ -114,15 +132,4065 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, + "outputs": [], + "source": [ + "epoch, batch_size = 1024, 64\n", + "resnet = Residual5(input_shape=(1, 102))\n", + "dnn = DNN(input_shape=(1, 102))\n", + "x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size=0.3, random_state=12, shuffle=True)\n", + "x_train, x_val, x_test = x_train[:, np.newaxis, :], x_val[:, np.newaxis, :], x_test[:, np.newaxis, :]" + ], "metadata": { "collapsed": false, "pycharm": { "name": "#%%\n" } - }, + } + }, + { + "cell_type": "code", + "execution_count": 16, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/1024\n", + "90/90 [==============================] - 1s 2ms/step - loss: 0.0167 - val_loss: 0.0340 - lr: 0.0025\n", + "Epoch 2/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0071 - val_loss: 0.0264 - lr: 0.0025\n", + "Epoch 3/1024\n", + "90/90 [==============================] - 0s 943us/step - loss: 0.0052 - val_loss: 0.0701 - lr: 0.0025\n", + "Epoch 4/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0048 - val_loss: 0.0245 - lr: 0.0025\n", + "Epoch 5/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0043 - val_loss: 0.0236 - lr: 0.0025\n", + "Epoch 6/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0044 - val_loss: 0.1782 - lr: 0.0025\n", + "Epoch 7/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0045 - val_loss: 0.2228 - lr: 0.0025\n", + "Epoch 8/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0039 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 9/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0043 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 10/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0042 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 11/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0043 - val_loss: 0.0493 - lr: 0.0025\n", + "Epoch 12/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0041 - val_loss: 0.0649 - lr: 0.0025\n", + "Epoch 13/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0041 - val_loss: 0.0343 - lr: 0.0025\n", + "Epoch 14/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0040 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 15/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0039 - val_loss: 0.2269 - lr: 0.0025\n", + "Epoch 16/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0038 - val_loss: 0.1035 - lr: 0.0025\n", + "Epoch 17/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0038 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 18/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0037 - val_loss: 0.0301 - lr: 0.0025\n", + "Epoch 19/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0038 - val_loss: 0.0420 - lr: 0.0025\n", + "Epoch 20/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0039 - val_loss: 0.0846 - lr: 0.0025\n", + "Epoch 21/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0038 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 22/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0037 - val_loss: 0.0576 - lr: 0.0025\n", + "Epoch 23/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0037 - val_loss: 0.0379 - lr: 0.0025\n", + "Epoch 24/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0035 - val_loss: 0.1732 - lr: 0.0025\n", + "Epoch 25/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0037 - val_loss: 0.1935 - lr: 0.0025\n", + "Epoch 26/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0036 - val_loss: 0.2671 - lr: 0.0025\n", + "Epoch 27/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0035 - val_loss: 0.2283 - lr: 0.0025\n", + "Epoch 28/1024\n", + "90/90 [==============================] - 0s 982us/step - loss: 0.0036 - val_loss: 0.0684 - lr: 0.0025\n", + "Epoch 29/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0036 - val_loss: 0.2190 - lr: 0.0025\n", + "Epoch 30/1024\n", + "90/90 [==============================] - 0s 902us/step - loss: 0.0035 - val_loss: 0.1134 - lr: 0.0025\n", + "Epoch 31/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0033 - val_loss: 0.2281 - lr: 0.0012\n", + "Epoch 32/1024\n", + "90/90 [==============================] - 0s 919us/step - loss: 0.0034 - val_loss: 0.0794 - lr: 0.0012\n", + "Epoch 33/1024\n", + "90/90 [==============================] - 0s 884us/step - loss: 0.0032 - val_loss: 0.2143 - lr: 0.0012\n", + "Epoch 34/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0032 - val_loss: 0.2283 - lr: 0.0012\n", + "Epoch 35/1024\n", + "90/90 [==============================] - 0s 901us/step - loss: 0.0034 - val_loss: 0.2281 - lr: 0.0012\n", + "Epoch 36/1024\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0032 - val_loss: 0.1494 - lr: 0.0012\n", + "Epoch 37/1024\n", + "90/90 [==============================] - 0s 890us/step - loss: 0.0034 - val_loss: 0.2266 - lr: 0.0012\n", + "Epoch 38/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0033 - val_loss: 0.1443 - lr: 0.0012\n", + "Epoch 39/1024\n", + "90/90 [==============================] - 0s 935us/step - loss: 0.0032 - val_loss: 0.1796 - lr: 0.0012\n", + "Epoch 40/1024\n", + "90/90 [==============================] - 0s 921us/step - loss: 0.0033 - val_loss: 0.0800 - lr: 0.0012\n", + "Epoch 41/1024\n", + "90/90 [==============================] - 0s 907us/step - loss: 0.0033 - val_loss: 0.2227 - lr: 0.0012\n", + "Epoch 42/1024\n", + "90/90 [==============================] - 0s 902us/step - loss: 0.0033 - val_loss: 0.2677 - lr: 0.0012\n", + "Epoch 43/1024\n", + "90/90 [==============================] - 0s 882us/step - loss: 0.0032 - val_loss: 0.2487 - lr: 0.0012\n", + "Epoch 44/1024\n", + "90/90 [==============================] - 0s 950us/step - loss: 0.0032 - val_loss: 0.1352 - lr: 0.0012\n", + "Epoch 45/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0032 - val_loss: 0.0269 - lr: 0.0012\n", + "Epoch 46/1024\n", + "90/90 [==============================] - 0s 887us/step - loss: 0.0032 - val_loss: 0.2283 - lr: 0.0012\n", + "Epoch 47/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0031 - val_loss: 0.0531 - lr: 0.0012\n", + "Epoch 48/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0033 - val_loss: 0.2113 - lr: 0.0012\n", + "Epoch 49/1024\n", + "90/90 [==============================] - 0s 883us/step - loss: 0.0032 - val_loss: 0.2867 - lr: 0.0012\n", + "Epoch 50/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0033 - val_loss: 0.2256 - lr: 0.0012\n", + "Epoch 51/1024\n", + "90/90 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- lr: 6.2500e-04\n", + "Epoch 59/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0030 - val_loss: 0.1172 - lr: 6.2500e-04\n", + "Epoch 60/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0032 - val_loss: 0.0666 - lr: 6.2500e-04\n", + "Epoch 61/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0031 - val_loss: 0.2274 - lr: 6.2500e-04\n", + "Epoch 62/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0030 - val_loss: 0.2281 - lr: 6.2500e-04\n", + "Epoch 63/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0031 - val_loss: 0.0223 - lr: 6.2500e-04\n", + "Epoch 64/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0030 - val_loss: 0.0198 - lr: 6.2500e-04\n", + "Epoch 65/1024\n", + "90/90 [==============================] - 0s 901us/step - loss: 0.0031 - val_loss: 0.2653 - lr: 6.2500e-04\n", + "Epoch 66/1024\n", + "90/90 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0.0030 - val_loss: 0.1097 - lr: 6.2500e-04\n", + "Epoch 74/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0031 - val_loss: 0.2122 - lr: 6.2500e-04\n", + "Epoch 75/1024\n", + "90/90 [==============================] - 0s 880us/step - loss: 0.0029 - val_loss: 0.1301 - lr: 6.2500e-04\n", + "Epoch 76/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0031 - val_loss: 0.1501 - lr: 6.2500e-04\n", + "Epoch 77/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0029 - val_loss: 0.0649 - lr: 6.2500e-04\n", + "Epoch 78/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0030 - val_loss: 0.0068 - lr: 6.2500e-04\n", + "Epoch 79/1024\n", + "90/90 [==============================] - 0s 888us/step - loss: 0.0030 - val_loss: 0.2262 - lr: 6.2500e-04\n", + "Epoch 80/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0029 - val_loss: 0.2600 - lr: 6.2500e-04\n", + "Epoch 81/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0029 - val_loss: 0.1309 - lr: 6.2500e-04\n", + "Epoch 82/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0030 - val_loss: 0.1772 - lr: 6.2500e-04\n", + "Epoch 83/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0031 - val_loss: 0.1081 - lr: 6.2500e-04\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0030 - val_loss: 0.0616 - lr: 6.2500e-04\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0029 - val_loss: 0.0060 - lr: 6.2500e-04\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 882us/step - loss: 0.0031 - val_loss: 0.0451 - lr: 6.2500e-04\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0030 - val_loss: 0.2253 - lr: 6.2500e-04\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0029 - val_loss: 0.2117 - lr: 6.2500e-04\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0030 - val_loss: 0.2233 - lr: 6.2500e-04\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0029 - val_loss: 0.2401 - lr: 6.2500e-04\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0029 - val_loss: 0.2282 - lr: 6.2500e-04\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0030 - val_loss: 0.0903 - lr: 6.2500e-04\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0031 - val_loss: 0.0258 - lr: 6.2500e-04\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0030 - val_loss: 0.1164 - lr: 6.2500e-04\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 948us/step - loss: 0.0029 - val_loss: 0.2695 - lr: 6.2500e-04\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0029 - val_loss: 0.2250 - lr: 6.2500e-04\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0030 - val_loss: 0.2260 - lr: 6.2500e-04\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0030 - val_loss: 0.2178 - lr: 6.2500e-04\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0030 - val_loss: 0.2361 - lr: 6.2500e-04\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0029 - val_loss: 0.2062 - lr: 6.2500e-04\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0029 - val_loss: 0.2279 - lr: 6.2500e-04\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0029 - val_loss: 0.0951 - lr: 6.2500e-04\n", + "Epoch 103/1024\n", + "90/90 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loss: 0.0030 - val_loss: 0.2718 - lr: 6.2500e-04\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 884us/step - loss: 0.0029 - val_loss: 0.0398 - lr: 3.1250e-04\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0028 - val_loss: 0.0100 - lr: 3.1250e-04\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 888us/step - loss: 0.0028 - val_loss: 0.0759 - lr: 3.1250e-04\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0029 - val_loss: 0.2235 - lr: 3.1250e-04\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0029 - val_loss: 0.2088 - lr: 3.1250e-04\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0029 - val_loss: 0.0364 - lr: 3.1250e-04\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 888us/step - loss: 0.0029 - val_loss: 0.1786 - lr: 3.1250e-04\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0029 - val_loss: 0.0177 - lr: 3.1250e-04\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.0449 - lr: 3.1250e-04\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0029 - val_loss: 0.0819 - lr: 3.1250e-04\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 880us/step - loss: 0.0028 - val_loss: 0.2216 - lr: 3.1250e-04\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0029 - val_loss: 0.1911 - lr: 3.1250e-04\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0029 - val_loss: 0.1622 - lr: 3.1250e-04\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0028 - val_loss: 0.0495 - lr: 3.1250e-04\n", + "Epoch 125/1024\n", + "90/90 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loss: 0.0028 - val_loss: 0.1866 - lr: 3.1250e-04\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0029 - val_loss: 0.2443 - lr: 3.1250e-04\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0029 - val_loss: 0.0675 - lr: 3.1250e-04\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0028 - val_loss: 0.2234 - lr: 3.1250e-04\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0029 - val_loss: 0.0189 - lr: 1.5625e-04\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0028 - val_loss: 0.1075 - lr: 1.5625e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.2533 - lr: 1.5625e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0039 - lr: 1.5625e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0029 - val_loss: 0.0105 - lr: 1.5625e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0028 - val_loss: 0.0964 - lr: 1.5625e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0027 - val_loss: 0.0864 - lr: 1.5625e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0028 - val_loss: 0.0102 - lr: 1.5625e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0028 - val_loss: 0.0066 - lr: 1.5625e-04\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0029 - val_loss: 0.1261 - lr: 1.5625e-04\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.1917 - lr: 1.5625e-04\n", + "Epoch 147/1024\n", + "90/90 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loss: 0.0028 - val_loss: 0.1938 - lr: 1.5625e-04\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0028 - val_loss: 0.0117 - lr: 1.5625e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0028 - val_loss: 0.0372 - lr: 1.5625e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0028 - val_loss: 0.2618 - lr: 1.5625e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0047 - lr: 1.5625e-04\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0028 - val_loss: 0.1115 - lr: 1.5625e-04\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0028 - val_loss: 0.0194 - lr: 1.5625e-04\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0028 - val_loss: 0.0144 - lr: 1.5625e-04\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0028 - val_loss: 0.0443 - lr: 1.5625e-04\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.1957 - lr: 1.5625e-04\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0028 - val_loss: 0.0070 - lr: 1.5625e-04\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0027 - val_loss: 0.0061 - lr: 7.8125e-05\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0028 - val_loss: 0.0066 - lr: 7.8125e-05\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0055 - lr: 7.8125e-05\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0027 - val_loss: 0.0098 - lr: 7.8125e-05\n", + "Epoch 169/1024\n", + "90/90 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0.0027 - val_loss: 0.0140 - lr: 7.8125e-05\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0065 - lr: 7.8125e-05\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.1320 - lr: 7.8125e-05\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0084 - lr: 7.8125e-05\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0274 - lr: 7.8125e-05\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0029 - val_loss: 0.1547 - lr: 7.8125e-05\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0233 - lr: 7.8125e-05\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0131 - lr: 7.8125e-05\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0028 - val_loss: 0.0042 - lr: 7.8125e-05\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0027 - val_loss: 0.0760 - lr: 7.8125e-05\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0027 - val_loss: 0.0085 - lr: 7.8125e-05\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0027 - val_loss: 0.0359 - lr: 7.8125e-05\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0205 - lr: 7.8125e-05\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0028 - val_loss: 0.0381 - lr: 7.8125e-05\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0764 - lr: 7.8125e-05\n", + "Epoch 191/1024\n", + "90/90 [==============================] 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3.9062e-05\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0027 - val_loss: 0.0081 - lr: 3.9062e-05\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0029 - val_loss: 0.0172 - lr: 3.9062e-05\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0028 - val_loss: 0.0244 - lr: 3.9062e-05\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0031 - lr: 3.9062e-05\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0089 - lr: 3.9062e-05\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0026 - val_loss: 0.0043 - lr: 3.9062e-05\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0027 - val_loss: 0.0049 - lr: 3.9062e-05\n", + "Epoch 206/1024\n", + "90/90 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0.0027 - val_loss: 0.0104 - lr: 3.9062e-05\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0026 - val_loss: 0.0036 - lr: 3.9062e-05\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0027 - val_loss: 0.0351 - lr: 3.9062e-05\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0027 - val_loss: 0.0037 - lr: 3.9062e-05\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0041 - lr: 3.9062e-05\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0027 - val_loss: 0.0377 - lr: 3.9062e-05\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0168 - lr: 3.9062e-05\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0027 - val_loss: 0.0031 - lr: 3.9062e-05\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0027 - val_loss: 0.0092 - lr: 3.9062e-05\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0028 - val_loss: 0.0081 - lr: 3.9062e-05\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0028 - val_loss: 0.0033 - lr: 3.9062e-05\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0310 - lr: 3.9062e-05\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0028 - val_loss: 0.0224 - lr: 3.9062e-05\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0028 - val_loss: 0.0176 - lr: 3.9062e-05\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0027 - val_loss: 0.0038 - lr: 3.9062e-05\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0028 - val_loss: 0.0294 - lr: 3.9062e-05\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0036 - lr: 3.9062e-05\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0370 - lr: 3.9062e-05\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0027 - val_loss: 0.0109 - lr: 3.9062e-05\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0046 - lr: 3.9062e-05\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0026 - val_loss: 0.0035 - lr: 1.9531e-05\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0026 - val_loss: 0.0085 - lr: 1.9531e-05\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0027 - val_loss: 0.0094 - lr: 1.9531e-05\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0031 - lr: 1.9531e-05\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0027 - val_loss: 0.0074 - lr: 1.9531e-05\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0026 - lr: 1.9531e-05\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0026 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0028 - val_loss: 0.0066 - lr: 1.9531e-05\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 1.9531e-05\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0027 - val_loss: 0.0038 - lr: 1.9531e-05\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0066 - lr: 1.9531e-05\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0027 - val_loss: 0.0053 - lr: 1.9531e-05\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0027 - val_loss: 0.0039 - lr: 1.9531e-05\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0028 - val_loss: 0.0069 - lr: 1.9531e-05\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0104 - lr: 1.9531e-05\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0027 - val_loss: 0.0280 - lr: 1.9531e-05\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0027 - val_loss: 0.0073 - lr: 1.9531e-05\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0074 - lr: 1.9531e-05\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0028 - val_loss: 0.0045 - lr: 1.9531e-05\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0034 - lr: 1.9531e-05\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 812us/step - loss: 0.0027 - val_loss: 0.0042 - lr: 1.9531e-05\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0044 - lr: 1.9531e-05\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0054 - lr: 1.9531e-05\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0077 - lr: 1.9531e-05\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 1.9531e-05\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0027 - val_loss: 0.0043 - lr: 1.9531e-05\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0028 - val_loss: 0.0043 - lr: 1.9531e-05\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0027 - val_loss: 0.0044 - lr: 1.9531e-05\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0027 - val_loss: 0.0034 - lr: 1.9531e-05\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0026 - val_loss: 0.0040 - lr: 1.9531e-05\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0027 - val_loss: 0.0033 - lr: 9.7656e-06\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0027 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0028 - val_loss: 0.0076 - lr: 9.7656e-06\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0028 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0027 - val_loss: 0.0031 - lr: 9.7656e-06\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0029 - lr: 9.7656e-06\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0052 - lr: 9.7656e-06\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0027 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0043 - lr: 9.7656e-06\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0027 - val_loss: 0.0027 - lr: 9.7656e-06\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0027 - val_loss: 0.0038 - lr: 9.7656e-06\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0028 - val_loss: 0.0036 - lr: 9.7656e-06\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0027 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0028 - val_loss: 0.0040 - lr: 9.7656e-06\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0026 - val_loss: 0.0037 - lr: 9.7656e-06\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0035 - lr: 9.7656e-06\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0028 - val_loss: 0.0030 - lr: 9.7656e-06\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.7656e-06\n", + "Epoch 298/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0028 - val_loss: 0.0044 - lr: 9.7656e-06\n", + "Epoch 299/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 9.7656e-06\n", + "Epoch 300/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 9.7656e-06\n", + "Epoch 301/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0027 - val_loss: 0.0034 - lr: 9.7656e-06\n", + "Epoch 302/1024\n", + "90/90 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1ms/step - loss: 0.0027 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 326/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 327/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 328/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0027 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 329/1024\n", + "90/90 [==============================] - 0s 919us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 330/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0027 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 331/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 339/1024\n", + "90/90 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loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 884us/step - loss: 0.0028 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0026 - val_loss: 0.0030 - lr: 4.8828e-06\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0028 - val_loss: 0.0027 - lr: 4.8828e-06\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 354/1024\n", + "90/90 [==============================] - 0s 885us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 355/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0028 - lr: 4.8828e-06\n", + "Epoch 356/1024\n", + "90/90 [==============================] - 0s 944us/step - loss: 0.0028 - val_loss: 0.0029 - lr: 4.8828e-06\n", + "Epoch 357/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 358/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 4.8828e-06\n", + "Epoch 359/1024\n", + "90/90 [==============================] - 0s 902us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.8828e-06\n", + "Epoch 360/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 361/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 362/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 363/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 364/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 365/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 366/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 367/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 368/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 369/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 370/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 371/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 372/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0028 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 373/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0028 - val_loss: 0.0027 - lr: 2.4414e-06\n", + "Epoch 374/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0028 - val_loss: 0.0028 - lr: 2.4414e-06\n", + "Epoch 375/1024\n", + "90/90 [==============================] - 0s 913us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0026 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0028 - val_loss: 0.0034 - lr: 2.4414e-06\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0026 - lr: 2.4414e-06\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 890us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 385/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 386/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 387/1024\n", + "90/90 [==============================] - 0s 893us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.4414e-06\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 952us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 968us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 892us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0025 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.2207e-06\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 908us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 949us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 432/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 433/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 434/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 435/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 436/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 437/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 6.1035e-07\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 442/1024\n", + "90/90 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loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 450/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 451/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 967us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 458/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 459/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 460/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 461/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 462/1024\n", + "90/90 [==============================] - 0s 928us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.0518e-07\n", + "Epoch 463/1024\n", + "90/90 [==============================] - 0s 995us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 464/1024\n", + "90/90 [==============================] - 0s 894us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 465/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 466/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 467/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 883us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 894us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 903us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 474/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 475/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 476/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 477/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 478/1024\n", + "90/90 [==============================] - 0s 896us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 479/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 480/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 481/1024\n", + "90/90 [==============================] - 0s 894us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 482/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 483/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 484/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 485/1024\n", + "90/90 [==============================] - 0s 914us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 486/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 487/1024\n", + "90/90 [==============================] - 0s 890us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.5259e-07\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 489/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 490/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 491/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 492/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 493/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 494/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 495/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 496/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 964us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 921us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 502/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 503/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 504/1024\n", + "90/90 [==============================] - 0s 876us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 505/1024\n", + "90/90 [==============================] - 0s 887us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 506/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 507/1024\n", + "90/90 [==============================] - 0s 948us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 508/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 509/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 510/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 511/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.6294e-08\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 520/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 521/1024\n", + "90/90 [==============================] - 0s 882us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 522/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 523/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 524/1024\n", + "90/90 [==============================] - 0s 960us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 525/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 526/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 885us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 536/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 537/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.8147e-08\n", + "Epoch 538/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 539/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 540/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 541/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 550/1024\n", + "90/90 [==============================] - 0s 885us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 551/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 552/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 907us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 954us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.9073e-08\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 565/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 566/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 567/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 568/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 569/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 570/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 571/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 889us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 0s 887us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 886us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 579/1024\n", + "90/90 [==============================] - 0s 885us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 580/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 581/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.5367e-09\n", + "Epoch 582/1024\n", + "90/90 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loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 590/1024\n", + "90/90 [==============================] - 0s 904us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 591/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 592/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 593/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 594/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 595/1024\n", + "90/90 [==============================] - 0s 929us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 596/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 597/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 598/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 599/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 600/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 601/1024\n", + "90/90 [==============================] - 0s 958us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 602/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 603/1024\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 604/1024\n", + "90/90 [==============================] 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4.7684e-09\n", + "Epoch 612/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.7684e-09\n", + "Epoch 613/1024\n", + "90/90 [==============================] - 0s 892us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 614/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 615/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 616/1024\n", + "90/90 [==============================] - 0s 894us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 617/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 618/1024\n", + "90/90 [==============================] - 0s 897us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 619/1024\n", + "90/90 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loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 627/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 628/1024\n", + "90/90 [==============================] - 0s 994us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 629/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 630/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 631/1024\n", + "90/90 [==============================] - 0s 887us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 632/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 633/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 634/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 635/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 636/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 637/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3842e-09\n", + "Epoch 638/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 639/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 640/1024\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 641/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 642/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 643/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 644/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 645/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 646/1024\n", + "90/90 [==============================] - 0s 986us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 647/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 648/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 649/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 650/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 651/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 652/1024\n", + "90/90 [==============================] - 0s 876us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 653/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 654/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 655/1024\n", + "90/90 [==============================] - 0s 945us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 656/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 657/1024\n", + "90/90 [==============================] - 0s 912us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 658/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 659/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 660/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 661/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 662/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1921e-09\n", + "Epoch 663/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 664/1024\n", + "90/90 [==============================] - 0s 895us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 665/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 666/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 667/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 668/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 669/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 670/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 671/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 672/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 673/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 674/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 675/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 676/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 677/1024\n", + "90/90 [==============================] - 0s 882us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 678/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 679/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 680/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 681/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 682/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 683/1024\n", + "90/90 [==============================] - 0s 901us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 684/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 685/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 686/1024\n", + "90/90 [==============================] - 0s 993us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 687/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.9605e-10\n", + "Epoch 688/1024\n", + "90/90 [==============================] - 0s 894us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 689/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 690/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 691/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 692/1024\n", + "90/90 [==============================] - 0s 906us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 693/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 694/1024\n", + "90/90 [==============================] - 0s 886us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 695/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 696/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 697/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 698/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 699/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 700/1024\n", + "90/90 [==============================] 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2.9802e-10\n", + "Epoch 708/1024\n", + "90/90 [==============================] - 0s 891us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 709/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 710/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 711/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 712/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9802e-10\n", + "Epoch 713/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 714/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 715/1024\n", + "90/90 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0.0027 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 723/1024\n", + "90/90 [==============================] - 0s 890us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 724/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 725/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 726/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 727/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 728/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 729/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.4901e-10\n", + "Epoch 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7.4506e-11\n", + "Epoch 745/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 746/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 747/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 748/1024\n", + "90/90 [==============================] - 0s 882us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 749/1024\n", + "90/90 [==============================] - 0s 889us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 750/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 751/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 752/1024\n", + "90/90 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0.0028 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 760/1024\n", + "90/90 [==============================] - 0s 883us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 761/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 762/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 7.4506e-11\n", + "Epoch 763/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 764/1024\n", + "90/90 [==============================] - 0s 874us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 765/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 766/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 767/1024\n", + "90/90 [==============================] - 0s 887us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 768/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 769/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 770/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 771/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 772/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 773/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 774/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 775/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 776/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 777/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 778/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 779/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 780/1024\n", + "90/90 [==============================] - 0s 888us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 781/1024\n", + "90/90 [==============================] - 0s 943us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 782/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 783/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 784/1024\n", + "90/90 [==============================] - 0s 930us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 785/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 786/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 787/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 3.7253e-11\n", + "Epoch 788/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 789/1024\n", + "90/90 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loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 797/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 798/1024\n", + "90/90 [==============================] - 0s 876us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 799/1024\n", + "90/90 [==============================] - 0s 880us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 800/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 801/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 802/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 803/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 804/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 805/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 806/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 807/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 808/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 809/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 810/1024\n", + "90/90 [==============================] - 0s 911us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.8626e-11\n", + "Epoch 811/1024\n", + "90/90 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0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 819/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 820/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 821/1024\n", + "90/90 [==============================] - 0s 883us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 822/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 823/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 824/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 825/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 826/1024\n", + "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 827/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 828/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 829/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 830/1024\n", + "90/90 [==============================] - 0s 883us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 831/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 832/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 833/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 834/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 835/1024\n", + "90/90 [==============================] - 0s 888us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 836/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 837/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 9.3132e-12\n", + "Epoch 838/1024\n", + "90/90 [==============================] - 0s 902us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 839/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 840/1024\n", + "90/90 [==============================] - 0s 927us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 841/1024\n", + "90/90 [==============================] - 0s 876us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 842/1024\n", + "90/90 [==============================] - 0s 940us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 843/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 844/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 845/1024\n", + "90/90 [==============================] - 0s 978us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 846/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 847/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 848/1024\n", + "90/90 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loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 856/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 857/1024\n", + "90/90 [==============================] - 0s 884us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 858/1024\n", + "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 859/1024\n", + "90/90 [==============================] - 0s 876us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 860/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 861/1024\n", + "90/90 [==============================] - 0s 958us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 862/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 4.6566e-12\n", + "Epoch 863/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 864/1024\n", + "90/90 [==============================] - 0s 884us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 865/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 866/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 867/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 868/1024\n", + "90/90 [==============================] - 0s 905us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 869/1024\n", + "90/90 [==============================] - 0s 874us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 870/1024\n", + "90/90 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0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 878/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 879/1024\n", + "90/90 [==============================] - 0s 895us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 880/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 881/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 882/1024\n", + "90/90 [==============================] - 0s 884us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 883/1024\n", + "90/90 [==============================] - 0s 905us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 884/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 885/1024\n", + "90/90 [==============================] - 0s 892us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 886/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 887/1024\n", + "90/90 [==============================] - 0s 926us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.3283e-12\n", + "Epoch 888/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 889/1024\n", + "90/90 [==============================] - 0s 936us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 890/1024\n", + "90/90 [==============================] - 0s 893us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 891/1024\n", + "90/90 [==============================] - 0s 902us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 892/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 893/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 894/1024\n", + "90/90 [==============================] - 0s 921us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 895/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 896/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 897/1024\n", + "90/90 [==============================] - 0s 890us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 898/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 899/1024\n", + "90/90 [==============================] - 0s 893us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 900/1024\n", + "90/90 [==============================] - 0s 948us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 901/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 902/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 903/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 904/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0028 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 905/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 906/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 907/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 908/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 909/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 910/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 911/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 912/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 1.1642e-12\n", + "Epoch 913/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 914/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 915/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 916/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 917/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 918/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 919/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 920/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 921/1024\n", + "90/90 [==============================] - 0s 887us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 922/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 923/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 924/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 925/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 926/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 927/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 928/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 929/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 930/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 931/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 932/1024\n", + "90/90 [==============================] - 0s 887us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 933/1024\n", + "90/90 [==============================] - 0s 920us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 934/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 935/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 936/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0027 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 937/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 5.8208e-13\n", + "Epoch 938/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 939/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 940/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 941/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 942/1024\n", + "90/90 [==============================] - 0s 875us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 943/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 944/1024\n", + "90/90 [==============================] - 0s 880us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 945/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 946/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 947/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 948/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0028 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 949/1024\n", + "90/90 [==============================] - 0s 883us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 950/1024\n", + "90/90 [==============================] - 0s 868us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 951/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 952/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 953/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 954/1024\n", + "90/90 [==============================] - 0s 877us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 955/1024\n", + "90/90 [==============================] - 0s 872us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 956/1024\n", + "90/90 [==============================] - 0s 889us/step - loss: 0.0027 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 957/1024\n", + "90/90 [==============================] - 0s 874us/step - loss: 0.0026 - val_loss: 0.0025 - lr: 2.9104e-13\n", + "Epoch 958/1024\n", + "90/90 [==============================] - 0s 880us/step - loss: 0.0029 - val_loss: 0.0025 - lr: 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"90/90 [==============================] - 0s 842us/step - loss: 0.0218 - val_loss: 0.0229 - lr: 0.0012\n", + "Epoch 84/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0218 - val_loss: 0.0228 - lr: 0.0012\n", + "Epoch 85/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0220 - val_loss: 0.0228 - lr: 0.0012\n", + "Epoch 86/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0218 - val_loss: 0.0227 - lr: 6.2500e-04\n", + "Epoch 87/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0218 - val_loss: 0.0226 - lr: 6.2500e-04\n", + "Epoch 88/1024\n", + "90/90 [==============================] - 0s 818us/step - loss: 0.0217 - val_loss: 0.0227 - lr: 6.2500e-04\n", + "Epoch 89/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0217 - val_loss: 0.0228 - lr: 6.2500e-04\n", + "Epoch 90/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0217 - val_loss: 0.0226 - lr: 6.2500e-04\n", + "Epoch 91/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0218 - val_loss: 0.0230 - lr: 6.2500e-04\n", + "Epoch 92/1024\n", + "90/90 [==============================] - 0s 818us/step - loss: 0.0217 - val_loss: 0.0226 - lr: 6.2500e-04\n", + "Epoch 93/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0217 - val_loss: 0.0226 - lr: 6.2500e-04\n", + "Epoch 94/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0217 - val_loss: 0.0227 - lr: 6.2500e-04\n", + "Epoch 95/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0217 - val_loss: 0.0227 - lr: 6.2500e-04\n", + "Epoch 96/1024\n", + "90/90 [==============================] - 0s 813us/step - loss: 0.0217 - val_loss: 0.0225 - lr: 6.2500e-04\n", + "Epoch 97/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0216 - val_loss: 0.0237 - lr: 6.2500e-04\n", + "Epoch 98/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0217 - val_loss: 0.0227 - lr: 6.2500e-04\n", + "Epoch 99/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0216 - val_loss: 0.0225 - lr: 6.2500e-04\n", + "Epoch 100/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0217 - val_loss: 0.0225 - lr: 6.2500e-04\n", + "Epoch 101/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0216 - val_loss: 0.0224 - lr: 6.2500e-04\n", + "Epoch 102/1024\n", + "90/90 [==============================] - 0s 817us/step - loss: 0.0215 - val_loss: 0.0224 - lr: 6.2500e-04\n", + "Epoch 103/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0216 - val_loss: 0.0226 - lr: 6.2500e-04\n", + "Epoch 104/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0216 - val_loss: 0.0225 - lr: 6.2500e-04\n", + "Epoch 105/1024\n", + "90/90 [==============================] - 0s 815us/step - loss: 0.0215 - val_loss: 0.0223 - lr: 6.2500e-04\n", + "Epoch 106/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0215 - val_loss: 0.0225 - lr: 6.2500e-04\n", + "Epoch 107/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0215 - val_loss: 0.0222 - lr: 6.2500e-04\n", + "Epoch 108/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0215 - val_loss: 0.0222 - lr: 6.2500e-04\n", + "Epoch 109/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0214 - val_loss: 0.0221 - lr: 6.2500e-04\n", + "Epoch 110/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0214 - val_loss: 0.0220 - lr: 6.2500e-04\n", + "Epoch 111/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0213 - val_loss: 0.0221 - lr: 3.1250e-04\n", + "Epoch 112/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0212 - val_loss: 0.0222 - lr: 3.1250e-04\n", + "Epoch 113/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0212 - val_loss: 0.0220 - lr: 3.1250e-04\n", + "Epoch 114/1024\n", + "90/90 [==============================] - 0s 930us/step - loss: 0.0213 - val_loss: 0.0220 - lr: 3.1250e-04\n", + "Epoch 115/1024\n", + "90/90 [==============================] - 0s 926us/step - loss: 0.0212 - val_loss: 0.0219 - lr: 3.1250e-04\n", + "Epoch 116/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0211 - val_loss: 0.0220 - lr: 3.1250e-04\n", + "Epoch 117/1024\n", + "90/90 [==============================] - 0s 907us/step - loss: 0.0211 - val_loss: 0.0219 - lr: 3.1250e-04\n", + "Epoch 118/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0211 - val_loss: 0.0220 - lr: 3.1250e-04\n", + "Epoch 119/1024\n", + "90/90 [==============================] - 0s 904us/step - loss: 0.0211 - val_loss: 0.0219 - lr: 3.1250e-04\n", + "Epoch 120/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0211 - val_loss: 0.0219 - lr: 3.1250e-04\n", + "Epoch 121/1024\n", + "90/90 [==============================] - 0s 812us/step - loss: 0.0211 - val_loss: 0.0219 - lr: 3.1250e-04\n", + "Epoch 122/1024\n", + "90/90 [==============================] - 0s 890us/step - loss: 0.0211 - val_loss: 0.0218 - lr: 3.1250e-04\n", + "Epoch 123/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0211 - val_loss: 0.0220 - lr: 3.1250e-04\n", + "Epoch 124/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0211 - val_loss: 0.0218 - lr: 3.1250e-04\n", + "Epoch 125/1024\n", + "90/90 [==============================] - 0s 916us/step - loss: 0.0211 - val_loss: 0.0218 - lr: 3.1250e-04\n", + "Epoch 126/1024\n", + "90/90 [==============================] - 0s 906us/step - loss: 0.0210 - val_loss: 0.0218 - lr: 3.1250e-04\n", + "Epoch 127/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0210 - val_loss: 0.0218 - lr: 3.1250e-04\n", + "Epoch 128/1024\n", + "90/90 [==============================] - 0s 908us/step - loss: 0.0210 - val_loss: 0.0217 - lr: 3.1250e-04\n", + "Epoch 129/1024\n", + "90/90 [==============================] - 0s 914us/step - loss: 0.0210 - val_loss: 0.0217 - lr: 3.1250e-04\n", + "Epoch 130/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0209 - val_loss: 0.0217 - lr: 3.1250e-04\n", + "Epoch 131/1024\n", + "90/90 [==============================] - 0s 919us/step - loss: 0.0209 - val_loss: 0.0216 - lr: 3.1250e-04\n", + "Epoch 132/1024\n", + "90/90 [==============================] - 0s 894us/step - loss: 0.0209 - val_loss: 0.0216 - lr: 3.1250e-04\n", + "Epoch 133/1024\n", + "90/90 [==============================] - 0s 910us/step - loss: 0.0208 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 134/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0209 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 135/1024\n", + "90/90 [==============================] - 0s 897us/step - loss: 0.0209 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 136/1024\n", + "90/90 [==============================] - 0s 909us/step - loss: 0.0208 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 137/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0208 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 138/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0208 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 139/1024\n", + "90/90 [==============================] - 0s 912us/step - loss: 0.0208 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 140/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0208 - val_loss: 0.0215 - lr: 3.1250e-04\n", + "Epoch 141/1024\n", + "90/90 [==============================] - 0s 906us/step - loss: 0.0207 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 142/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0207 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 143/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0207 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 144/1024\n", + "90/90 [==============================] - 0s 916us/step - loss: 0.0207 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 145/1024\n", + "90/90 [==============================] - 0s 907us/step - loss: 0.0207 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 146/1024\n", + "90/90 [==============================] - 0s 942us/step - loss: 0.0207 - val_loss: 0.0213 - lr: 3.1250e-04\n", + "Epoch 147/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0206 - val_loss: 0.0213 - lr: 3.1250e-04\n", + "Epoch 148/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0206 - val_loss: 0.0213 - lr: 3.1250e-04\n", + "Epoch 149/1024\n", + "90/90 [==============================] - 0s 911us/step - loss: 0.0207 - val_loss: 0.0213 - lr: 3.1250e-04\n", + "Epoch 150/1024\n", + "90/90 [==============================] - 0s 915us/step - loss: 0.0206 - val_loss: 0.0212 - lr: 3.1250e-04\n", + "Epoch 151/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0206 - val_loss: 0.0213 - lr: 3.1250e-04\n", + "Epoch 152/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0205 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 153/1024\n", + "90/90 [==============================] - 0s 909us/step - loss: 0.0205 - val_loss: 0.0211 - lr: 3.1250e-04\n", + "Epoch 154/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0205 - val_loss: 0.0214 - lr: 3.1250e-04\n", + "Epoch 155/1024\n", + "90/90 [==============================] - 0s 912us/step - loss: 0.0205 - val_loss: 0.0211 - lr: 3.1250e-04\n", + "Epoch 156/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0205 - val_loss: 0.0212 - lr: 3.1250e-04\n", + "Epoch 157/1024\n", + "90/90 [==============================] - 0s 906us/step - loss: 0.0205 - val_loss: 0.0211 - lr: 3.1250e-04\n", + "Epoch 158/1024\n", + "90/90 [==============================] - 0s 937us/step - loss: 0.0206 - val_loss: 0.0212 - lr: 3.1250e-04\n", + "Epoch 159/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0204 - val_loss: 0.0211 - lr: 3.1250e-04\n", + "Epoch 160/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0204 - val_loss: 0.0211 - lr: 3.1250e-04\n", + "Epoch 161/1024\n", + "90/90 [==============================] - 0s 934us/step - loss: 0.0204 - val_loss: 0.0211 - lr: 3.1250e-04\n", + "Epoch 162/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0204 - val_loss: 0.0212 - lr: 3.1250e-04\n", + "Epoch 163/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0204 - val_loss: 0.0212 - lr: 3.1250e-04\n", + "Epoch 164/1024\n", + "90/90 [==============================] - 0s 932us/step - loss: 0.0204 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 165/1024\n", + "90/90 [==============================] - 0s 925us/step - loss: 0.0204 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 166/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0203 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 167/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0203 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 168/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0203 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 169/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0203 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 170/1024\n", + "90/90 [==============================] - 0s 904us/step - loss: 0.0203 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 171/1024\n", + "90/90 [==============================] - 0s 952us/step - loss: 0.0203 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 172/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0203 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 173/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0202 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 174/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0204 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 175/1024\n", + "90/90 [==============================] - 0s 909us/step - loss: 0.0202 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 176/1024\n", + "90/90 [==============================] - 0s 922us/step - loss: 0.0203 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 177/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0203 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 178/1024\n", + "90/90 [==============================] - 0s 914us/step - loss: 0.0202 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 179/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0202 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 180/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0202 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 181/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0202 - val_loss: 0.0210 - lr: 3.1250e-04\n", + "Epoch 182/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0202 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 183/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0201 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 184/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0202 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 185/1024\n", + "90/90 [==============================] - 0s 910us/step - loss: 0.0202 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 186/1024\n", + "90/90 [==============================] - 0s 906us/step - loss: 0.0202 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 187/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0201 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 188/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0201 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 189/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0202 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 190/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0202 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 191/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0202 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 192/1024\n", + "90/90 [==============================] - 0s 908us/step - loss: 0.0201 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 193/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0202 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 194/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0201 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 195/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0201 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 196/1024\n", + "90/90 [==============================] - 0s 922us/step - loss: 0.0201 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 197/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0201 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 198/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0200 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 199/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0200 - val_loss: 0.0208 - lr: 3.1250e-04\n", + "Epoch 200/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0200 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 201/1024\n", + "90/90 [==============================] - 0s 901us/step - loss: 0.0201 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 202/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0201 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 203/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0199 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 204/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0200 - val_loss: 0.0209 - lr: 3.1250e-04\n", + "Epoch 205/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0200 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 206/1024\n", + "90/90 [==============================] - 0s 901us/step - loss: 0.0200 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 207/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0200 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 208/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0200 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 209/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0199 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 210/1024\n", + "90/90 [==============================] - 0s 896us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 211/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0200 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 212/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 213/1024\n", + "90/90 [==============================] - 0s 896us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 214/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0199 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 215/1024\n", + "90/90 [==============================] - 0s 920us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 216/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0199 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 217/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 218/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0199 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 219/1024\n", + "90/90 [==============================] - 0s 897us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 220/1024\n", + "90/90 [==============================] - 0s 883us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 221/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0199 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 222/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0198 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 223/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0200 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 224/1024\n", + "90/90 [==============================] - 0s 890us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 225/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 226/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 227/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 228/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 229/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0198 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 230/1024\n", + "90/90 [==============================] - 0s 772us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 231/1024\n", + "90/90 [==============================] - 0s 714us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 232/1024\n", + "90/90 [==============================] - 0s 738us/step - loss: 0.0199 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 233/1024\n", + "90/90 [==============================] - 0s 884us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 234/1024\n", + "90/90 [==============================] - 0s 728us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 235/1024\n", + "90/90 [==============================] - 0s 726us/step - loss: 0.0198 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 236/1024\n", + "90/90 [==============================] - 0s 893us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 237/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0198 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 238/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0198 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 239/1024\n", + "90/90 [==============================] - 0s 901us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 240/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0199 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 241/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 242/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0199 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 243/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 244/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 245/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 246/1024\n", + "90/90 [==============================] - 0s 929us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 247/1024\n", + "90/90 [==============================] - 0s 813us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 248/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0198 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 249/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 250/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0198 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 251/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0198 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 252/1024\n", + "90/90 [==============================] - 0s 895us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 253/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 254/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0197 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 255/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 256/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0198 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 257/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 258/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 259/1024\n", + "90/90 [==============================] - 0s 818us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 260/1024\n", + "90/90 [==============================] - 0s 817us/step - loss: 0.0198 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 261/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 262/1024\n", + "90/90 [==============================] - 0s 945us/step - loss: 0.0198 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 263/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0197 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 264/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0198 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 265/1024\n", + "90/90 [==============================] - 0s 918us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 266/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0197 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 267/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0197 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 268/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0198 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 269/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 270/1024\n", + "90/90 [==============================] - 0s 815us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 271/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 272/1024\n", + "90/90 [==============================] - 0s 812us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 273/1024\n", + "90/90 [==============================] - 0s 892us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 274/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0197 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 275/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 276/1024\n", + "90/90 [==============================] - 0s 917us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 277/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 278/1024\n", + "90/90 [==============================] - 0s 923us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 279/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0198 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 280/1024\n", + "90/90 [==============================] - 0s 919us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 281/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 282/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 283/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 284/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 285/1024\n", + "90/90 [==============================] - 0s 818us/step - loss: 0.0197 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 286/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 287/1024\n", + "90/90 [==============================] - 0s 907us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 288/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0196 - val_loss: 0.0207 - lr: 3.1250e-04\n", + "Epoch 289/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 290/1024\n", + "90/90 [==============================] - 0s 899us/step - loss: 0.0198 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 291/1024\n", + "90/90 [==============================] - 0s 908us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 292/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 293/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0196 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 294/1024\n", + "90/90 [==============================] - 0s 930us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 295/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 296/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 297/1024\n", + "90/90 [==============================] - 0s 817us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 298/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 299/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 300/1024\n", + "90/90 [==============================] - 0s 909us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 301/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 302/1024\n", + "90/90 [==============================] - 0s 810us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 303/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 304/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0197 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 305/1024\n", + "90/90 [==============================] - 0s 812us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 306/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 307/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0196 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 308/1024\n", + "90/90 [==============================] - 0s 931us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 309/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 310/1024\n", + "90/90 [==============================] - 0s 812us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 311/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 312/1024\n", + "90/90 [==============================] - 0s 892us/step - loss: 0.0196 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 313/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 314/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0196 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 315/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 316/1024\n", + "90/90 [==============================] - 0s 818us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 317/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0195 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 318/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0197 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 319/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 320/1024\n", + "90/90 [==============================] - 0s 813us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 321/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0195 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 322/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 323/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 324/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0196 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 325/1024\n", + "90/90 [==============================] - 0s 902us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 326/1024\n", + "90/90 [==============================] - 0s 810us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 327/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0196 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 328/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 329/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 330/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 331/1024\n", + "90/90 [==============================] - 0s 941us/step - loss: 0.0196 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 332/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 333/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 334/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 335/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 336/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 337/1024\n", + "90/90 [==============================] - 0s 817us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 338/1024\n", + "90/90 [==============================] - 0s 815us/step - loss: 0.0195 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 339/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0196 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 340/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 341/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 342/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 343/1024\n", + "90/90 [==============================] - 0s 812us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 344/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0195 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 345/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 346/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 347/1024\n", + "90/90 [==============================] - 0s 918us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 348/1024\n", + "90/90 [==============================] - 0s 809us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 349/1024\n", + "90/90 [==============================] - 0s 893us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 350/1024\n", + "90/90 [==============================] - 0s 903us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 351/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 352/1024\n", + "90/90 [==============================] - 0s 813us/step - loss: 0.0195 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 353/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 354/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 355/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 356/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 357/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 358/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 359/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0196 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 360/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 361/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 362/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 363/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0198 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 364/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 365/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 366/1024\n", + "90/90 [==============================] - 0s 906us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 367/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 368/1024\n", + "90/90 [==============================] - 0s 898us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 369/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0195 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 370/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0194 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 371/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0196 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 372/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 373/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0195 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 374/1024\n", + "90/90 [==============================] - 0s 818us/step - loss: 0.0194 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 375/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 376/1024\n", + "90/90 [==============================] - 0s 907us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 377/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 378/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 379/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0194 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 380/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 381/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 382/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 383/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0194 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 384/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 385/1024\n", + "90/90 [==============================] - 0s 816us/step - loss: 0.0194 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 386/1024\n", + "90/90 [==============================] - 0s 817us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 387/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 388/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 389/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0194 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 390/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 391/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 392/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 393/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 394/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 395/1024\n", + "90/90 [==============================] - 0s 881us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 396/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 397/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0195 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 398/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 399/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 400/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 401/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 402/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 403/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0194 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 404/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 405/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 406/1024\n", + "90/90 [==============================] - 0s 817us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 407/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 408/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 409/1024\n", + "90/90 [==============================] - 0s 925us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 410/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 411/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 412/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 413/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 414/1024\n", + "90/90 [==============================] - 0s 814us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 415/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 416/1024\n", + "90/90 [==============================] - 0s 993us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 417/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 418/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0194 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 419/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0195 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 420/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 421/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 422/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0194 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 423/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0194 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 424/1024\n", + "90/90 [==============================] - 0s 823us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 425/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 426/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 427/1024\n", + "90/90 [==============================] - 0s 900us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 428/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 429/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 430/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 431/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 432/1024\n", + "90/90 [==============================] - 0s 908us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 433/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0193 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 434/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 435/1024\n", + "90/90 [==============================] - 0s 873us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 436/1024\n", + "90/90 [==============================] - 0s 867us/step - loss: 0.0194 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 437/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 438/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 439/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 440/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0193 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 441/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0193 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 442/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 443/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 444/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0194 - val_loss: 0.0205 - lr: 3.1250e-04\n", + "Epoch 445/1024\n", + "90/90 [==============================] - 0s 863us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 446/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 447/1024\n", + "90/90 [==============================] - 0s 927us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 448/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 449/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0193 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 450/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 451/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 452/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0193 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 453/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0193 - val_loss: 0.0206 - lr: 3.1250e-04\n", + "Epoch 454/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 455/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 456/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 457/1024\n", + "90/90 [==============================] - 0s 894us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 458/1024\n", + "90/90 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loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 466/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 467/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0195 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 468/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 469/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0194 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 470/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0194 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 471/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0194 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 472/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 473/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0193 - val_loss: 0.0204 - lr: 3.1250e-04\n", + "Epoch 474/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 475/1024\n", + "90/90 [==============================] - 0s 822us/step - loss: 0.0193 - val_loss: 0.0203 - lr: 3.1250e-04\n", + "Epoch 476/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 477/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0194 - val_loss: 0.0202 - lr: 3.1250e-04\n", + "Epoch 478/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 479/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 3.1250e-04\n", + "Epoch 480/1024\n", + "90/90 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loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 488/1024\n", + "90/90 [==============================] - 0s 819us/step - loss: 0.0193 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 489/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 490/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 491/1024\n", + "90/90 [==============================] - 0s 913us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 492/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 493/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 494/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 495/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 496/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 497/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 498/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 499/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 500/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 501/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 502/1024\n", + "90/90 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loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 510/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 511/1024\n", + "90/90 [==============================] - 0s 924us/step - loss: 0.0193 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 512/1024\n", + "90/90 [==============================] - 0s 820us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 513/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 514/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 515/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 516/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 517/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0192 - val_loss: 0.0203 - lr: 1.5625e-04\n", + "Epoch 518/1024\n", + "90/90 [==============================] - 0s 821us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 519/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 520/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 521/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 522/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0192 - val_loss: 0.0203 - lr: 1.5625e-04\n", + "Epoch 523/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 524/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 525/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 526/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 527/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 528/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 529/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 530/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 531/1024\n", + "90/90 [==============================] - 0s 928us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 532/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 533/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 534/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 535/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 536/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 537/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 538/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 539/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 540/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0193 - val_loss: 0.0203 - lr: 1.5625e-04\n", + "Epoch 541/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 542/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 543/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 544/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 545/1024\n", + "90/90 [==============================] - 0s 904us/step - loss: 0.0192 - val_loss: 0.0200 - lr: 1.5625e-04\n", + "Epoch 546/1024\n", + "90/90 [==============================] - 0s 824us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 547/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 548/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0192 - val_loss: 0.0203 - lr: 1.5625e-04\n", + "Epoch 549/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 550/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 551/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0192 - val_loss: 0.0203 - lr: 1.5625e-04\n", + "Epoch 552/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 553/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 554/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 555/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 556/1024\n", + "90/90 [==============================] - 0s 864us/step - loss: 0.0192 - val_loss: 0.0203 - lr: 1.5625e-04\n", + "Epoch 557/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 558/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 559/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 560/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0192 - val_loss: 0.0202 - lr: 1.5625e-04\n", + "Epoch 561/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 562/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0192 - val_loss: 0.0200 - lr: 1.5625e-04\n", + "Epoch 563/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 564/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 565/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 566/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 567/1024\n", + "90/90 [==============================] - 0s 825us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 568/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0192 - val_loss: 0.0200 - lr: 1.5625e-04\n", + "Epoch 569/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 1.5625e-04\n", + "Epoch 570/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5625e-04\n", + "Epoch 571/1024\n", + "90/90 [==============================] - 0s 918us/step - loss: 0.0192 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 572/1024\n", + "90/90 [==============================] - 0s 911us/step - loss: 0.0192 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 573/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 574/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0192 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 575/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 576/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 577/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 578/1024\n", + "90/90 [==============================] - 0s 866us/step - loss: 0.0192 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 579/1024\n", + "90/90 [==============================] - 0s 919us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 580/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 581/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 582/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0192 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 583/1024\n", + "90/90 [==============================] 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7.8125e-05\n", + "Epoch 591/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 592/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 593/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 594/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 595/1024\n", + "90/90 [==============================] - 0s 828us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 596/1024\n", + "90/90 [==============================] - 0s 862us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 597/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 598/1024\n", + "90/90 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7.8125e-05\n", + "Epoch 650/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0192 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 651/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 652/1024\n", + "90/90 [==============================] - 0s 829us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 653/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 654/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 655/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 7.8125e-05\n", + "Epoch 656/1024\n", + "90/90 [==============================] - 0s 895us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 7.8125e-05\n", + "Epoch 657/1024\n", + "90/90 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0.0191 - val_loss: 0.0201 - lr: 3.9062e-05\n", + "Epoch 665/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 666/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 667/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 668/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0191 - val_loss: 0.0201 - lr: 3.9062e-05\n", + "Epoch 669/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 670/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 671/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 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3.9062e-05\n", + "Epoch 687/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 688/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.9062e-05\n", + "Epoch 689/1024\n", + "90/90 [==============================] - 0s 831us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.9531e-05\n", + "Epoch 690/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.9531e-05\n", + "Epoch 691/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.9531e-05\n", + "Epoch 692/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.9531e-05\n", + "Epoch 693/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.9531e-05\n", + "Epoch 694/1024\n", + "90/90 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0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 820/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 821/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 822/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 823/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 824/1024\n", + "90/90 [==============================] - 0s 834us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 825/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 826/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 827/1024\n", + "90/90 [==============================] - 0s 827us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 828/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 829/1024\n", + "90/90 [==============================] - 0s 865us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 830/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 831/1024\n", + "90/90 [==============================] - 0s 833us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 832/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 833/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 834/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 835/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 836/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 2.4414e-06\n", + "Epoch 837/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 838/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 839/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 840/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 841/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 842/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 843/1024\n", + "90/90 [==============================] - 0s 861us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 844/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 845/1024\n", + "90/90 [==============================] - 0s 832us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 846/1024\n", + "90/90 [==============================] - 0s 878us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 847/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 848/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 849/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 850/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 851/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 852/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 853/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 854/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 855/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 856/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 857/1024\n", + "90/90 [==============================] - 0s 848us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 858/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 859/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 860/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 861/1024\n", + "90/90 [==============================] - 0s 826us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.2207e-06\n", + "Epoch 862/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 863/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 864/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 865/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 866/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 867/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 868/1024\n", + "90/90 [==============================] - 0s 860us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 869/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 870/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 871/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 872/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 873/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 874/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 875/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 876/1024\n", + "90/90 [==============================] - 0s 840us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 877/1024\n", + "90/90 [==============================] - 0s 869us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 878/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 879/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 880/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 881/1024\n", + "90/90 [==============================] - 0s 2ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 882/1024\n", + "90/90 [==============================] - 0s 1ms/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 883/1024\n", + "90/90 [==============================] - 0s 830us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 884/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 885/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 886/1024\n", + "90/90 [==============================] - 0s 856us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 6.1035e-07\n", + "Epoch 887/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 888/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 889/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 890/1024\n", + "90/90 [==============================] - 0s 838us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 891/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 892/1024\n", + "90/90 [==============================] - 0s 933us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 893/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 894/1024\n", + "90/90 [==============================] - 0s 839us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 895/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 896/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 897/1024\n", + "90/90 [==============================] - 0s 836us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 898/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 899/1024\n", + "90/90 [==============================] - 0s 851us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 900/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 901/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 902/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 903/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 904/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 905/1024\n", + "90/90 [==============================] - 0s 843us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 906/1024\n", + "90/90 [==============================] - 0s 879us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 907/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 908/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 909/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 910/1024\n", + "90/90 [==============================] - 0s 853us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 911/1024\n", + "90/90 [==============================] - 0s 870us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 3.0518e-07\n", + "Epoch 912/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 913/1024\n", + "90/90 [==============================] - 0s 835us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 914/1024\n", + "90/90 [==============================] - 0s 857us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 915/1024\n", + "90/90 [==============================] - 0s 847us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 916/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 917/1024\n", + "90/90 [==============================] - 0s 858us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 918/1024\n", + "90/90 [==============================] - 0s 854us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 919/1024\n", + "90/90 [==============================] - 0s 842us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 920/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 921/1024\n", + "90/90 [==============================] - 0s 855us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 922/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 923/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 924/1024\n", + "90/90 [==============================] - 0s 850us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 925/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 926/1024\n", + "90/90 [==============================] - 0s 846us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 927/1024\n", + "90/90 [==============================] - 0s 849us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 928/1024\n", + "90/90 [==============================] - 0s 852us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 929/1024\n", + "90/90 [==============================] - 0s 841us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 930/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 931/1024\n", + "90/90 [==============================] - 0s 844us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 932/1024\n", + "90/90 [==============================] - 0s 871us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 933/1024\n", + "90/90 [==============================] - 0s 837us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 934/1024\n", + "90/90 [==============================] - 0s 874us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 935/1024\n", + "90/90 [==============================] - 0s 845us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n", + "Epoch 936/1024\n", + "90/90 [==============================] - 0s 859us/step - loss: 0.0191 - val_loss: 0.0200 - lr: 1.5259e-07\n" + ] + } + ], + "source": [ + "_ = dnn.fit(x_train, y_train, x_val, y_val, batch_size=batch_size, epoch=epoch)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 21, "outputs": [], - "source": [] + "source": [ + "resnet = load_model(\"checkpoints/res5.hdf5\")\n", + "cnn = load_model(\"checkpoints/plain11.hdf5\")\n", + "dnn = load_model(\"checkpoints/dnn.hdf5\")" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 22, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "====================\n", + "resnet rmse : 0.05082896493225598\n", + "resnet Dry matter content error 0.7681549690131755\n", + "resnet r^2 : 0.9048480565064634\n", + "====================\n", + "cnn rmse : 0.05200769624271875\n", + "cnn Dry matter content error 0.7859685978067217\n", + "cnn r^2 : 0.9003837097594369\n", + "====================\n", + "dnn rmse : 0.14165380273751216\n", + "dnn Dry matter content error 2.1407493266379727\n", + "dnn r^2 : 0.2609878018465487\n" + ] + } + ], + "source": [ + "models = {'resnet': resnet, 'cnn': cnn, 'dnn': dnn}\n", + "results = {model_name: model.predict(x_test).reshape((-1, )) for model_name, model in models.items()}\n", + "for model_name, model_result in results.items():\n", + " rmse = np.sqrt(mean_squared_error(y_test, model_result))\n", + " print(\"=\"*20)\n", + " print(model_name, \"rmse : \", rmse)\n", + " print(model_name, \"Dry matter content error\", retransform(rmse))\n", + " print(model_name, \"r^2 :\", r2_score(y_test, model_result))" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 19, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } } ], "metadata": { @@ -149,4 +4217,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} +} \ No newline at end of file diff --git a/models.py b/models.py old mode 100644 new mode 100755 index 9bef846..8325ae8 --- a/models.py +++ b/models.py @@ -2,7 +2,8 @@ from tkinter import N import keras.callbacks import keras.layers as KL from keras import Model -from keras.optimizers import adam_v2 +from keras.optimizers import adam_v2, nadam_v2, adagrad_v2 +from tensorflow.keras.optimizers import SGD, RMSprop class Plain5(object): @@ -33,9 +34,22 @@ class Plain5(object): model = Model(input_layer, x) return model - def fit(self, x, y, x_val, y_val, epoch, batch_size): - self.model.compile(loss='mse', optimizer=adam_v2.Adam(learning_rate=0.01 * (batch_size / 256))) - checkpoint = keras.callbacks.ModelCheckpoint(filepath='checkpoints/plain5.hdf5', monitor='val_loss', + def fit(self, x, y, x_val, y_val, epoch, batch_size, method='adam'): + save = f'checkpoints/plain5_{method}.hdf5' + if method == "adam": + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'nadam': + optimizer = nadam_v2.Nadam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'adagrad': + optimizer = adagrad_v2.Adagrad(learning_rate=0.01 * (batch_size / 256)) + elif method == 'sgd': + optimizer = SGD(learning_rate=0.01 * (batch_size / 256)) + elif method == 'rmsprop': + optimizer = RMSprop(learning_rate=0.01 * (batch_size / 256)) + else: + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + self.model.compile(loss='mse', optimizer=optimizer) + checkpoint = keras.callbacks.ModelCheckpoint(filepath=save, monitor='val_loss', mode="min", save_best_only=True) early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=0, patience=1000, verbose=0, mode='auto') @@ -77,12 +91,25 @@ class Residual5(object): model = Model(input_layer, x) return model - def fit(self, x, y, x_val, y_val, epoch, batch_size): - self.model.compile(loss='mse', optimizer=adam_v2.Adam(learning_rate=0.01 * (batch_size / 256))) - checkpoint = keras.callbacks.ModelCheckpoint(filepath='checkpoints/res5.hdf5', monitor='val_loss', + def fit(self, x, y, x_val, y_val, epoch, batch_size, method='adam'): + save = f'checkpoints/res5_{method}.hdf5' + if method == "adam": + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'nadam': + optimizer = nadam_v2.Nadam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'adagrad': + optimizer = adagrad_v2.Adagrad(learning_rate=0.01 * (batch_size / 256)) + elif method == 'sgd': + optimizer = SGD(learning_rate=0.01 * (batch_size / 256)) + elif method == 'rmsprop': + optimizer = RMSprop(learning_rate=0.01 * (batch_size / 256)) + else: + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + self.model.compile(loss='mse', optimizer=optimizer) + checkpoint = keras.callbacks.ModelCheckpoint(filepath=save, monitor='val_loss', mode="min", save_best_only=True) - early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=0, - patience=1000, verbose=0, mode='auto') + early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=0, patience=1000, + verbose=0, mode='auto') lr_decay = keras.callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.5, patience=25, min_delta=1e-6) callbacks = [checkpoint, early_stop, lr_decay] history = self.model.fit(x, y, validation_data=(x_val, y_val), epochs=epoch, verbose=1, @@ -120,10 +147,22 @@ class ShortCut5(object): model = Model(input_layer, x) return model - def fit(self, x, y, x_val, y_val, epoch, batch_size): - self.model.compile(loss='mse', optimizer=adam_v2.Adam(learning_rate=0.01 * (batch_size / 256))) - - checkpoint = keras.callbacks.ModelCheckpoint(filepath='checkpoints/shortcut5.hdf5', monitor='val_loss', + def fit(self, x, y, x_val, y_val, epoch, batch_size, method='adam'): + save = f'checkpoints/shortcut5_{method}.hdf5' + if method == "adam": + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'nadam': + optimizer = nadam_v2.Nadam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'adagrad': + optimizer = adagrad_v2.Adagrad(learning_rate=0.01 * (batch_size / 256)) + elif method == 'sgd': + optimizer = SGD(learning_rate=0.01 * (batch_size / 256)) + elif method == 'rmsprop': + optimizer = RMSprop(learning_rate=0.01 * (batch_size / 256)) + else: + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + self.model.compile(loss='mse', optimizer=optimizer) + checkpoint = keras.callbacks.ModelCheckpoint(filepath=save, monitor='val_loss', mode="min", save_best_only=True) early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=0, patience=1000, verbose=0, mode='auto') @@ -183,8 +222,22 @@ class ShortCut11(object): model = Model(input_layer, x) return model - def fit(self, x, y, x_val, y_val, epoch, batch_size, save='checkpoints/shortcut11.hdf5', is_show=True): - self.model.compile(loss='mse', optimizer=adam_v2.Adam(learning_rate=0.01 * (batch_size / 256))) + def fit(self, x, y, x_val, y_val, epoch, batch_size, is_show=True, + method='adam'): + save = f'checkpoints/shortcut11_{method}.hdf5' + if method == "adam": + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'nadam': + optimizer = nadam_v2.Nadam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'adagrad': + optimizer = adagrad_v2.Adagrad(learning_rate=0.01 * (batch_size / 256)) + elif method == 'sgd': + optimizer = SGD(learning_rate=0.01 * (batch_size / 256)) + elif method == 'rmsprop': + optimizer = RMSprop(learning_rate=0.01 * (batch_size / 256)) + else: + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + self.model.compile(loss='mse', optimizer=optimizer) callbacks = [] checkpoint = keras.callbacks.ModelCheckpoint(filepath=save, monitor='val_loss', mode="min", save_best_only=True) @@ -248,9 +301,23 @@ class Plain11(object): model = Model(input_layer, x) return model - def fit(self, x, y, x_val, y_val, epoch, batch_size): - self.model.compile(loss='mse', optimizer=adam_v2.Adam(learning_rate=0.01 * (batch_size / 256))) - checkpoint = keras.callbacks.ModelCheckpoint(filepath='checkpoints/plain11.hdf5', monitor='val_loss', + def fit(self, x, y, x_val, y_val, epoch, batch_size, method='adam'): + save = f'checkpoints/plain11_{method}.hdf5' + if method == "adam": + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'nadam': + optimizer = nadam_v2.Nadam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'adagrad': + optimizer = adagrad_v2.Adagrad(learning_rate=0.01 * (batch_size / 256)) + elif method == 'sgd': + optimizer = SGD(learning_rate=0.01 * (batch_size / 256)) + elif method == 'rmsprop': + optimizer = RMSprop(learning_rate=0.01 * (batch_size / 256)) + else: + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + self.model.compile(loss='mse', optimizer=optimizer) + + checkpoint = keras.callbacks.ModelCheckpoint(filepath=save, monitor='val_loss', mode="min", save_best_only=True) early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=1e-6, patience=200, verbose=0, mode='auto') @@ -294,9 +361,21 @@ class SimpleCNN(object): model = Model(input_layer, x) return model - def fit(self, x, y, x_val, y_val, epoch, batch_size): - self.model.compile(loss='mse', optimizer=adam_v2.Adam(learning_rate=0.01 * (batch_size / 256))) - checkpoint = keras.callbacks.ModelCheckpoint(filepath='checkpoints/plain5.hdf5', monitor='val_loss', + def fit(self, x, y, x_val, y_val, epoch, batch_size, method='adam'): + if method == "adam": + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'nadam': + optimizer = nadam_v2.Nadam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'adagrad': + optimizer = adagrad_v2.Adagrad(learning_rate=0.01 * (batch_size / 256)) + elif method == 'sgd': + optimizer = SGD(learning_rate=0.01 * (batch_size / 256)) + elif method == 'rmsprop': + optimizer = RMSprop(learning_rate=0.01 * (batch_size / 256)) + else: + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + self.model.compile(loss='mse', optimizer=optimizer) + checkpoint = keras.callbacks.ModelCheckpoint(filepath='checkpoints/simplecnn.hdf5', monitor='val_loss', mode="min", save_best_only=True) early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=0, patience=1000, verbose=0, mode='auto') @@ -307,6 +386,48 @@ class SimpleCNN(object): return history +class DNN(object): + def __init__(self, model_path=None, input_shape=None): + self.model = None + self.input_shape = input_shape + if model_path is not None: + pass + else: + self.model = self.build_model() + + def build_model(self): + input_layer = KL.Input(self.input_shape, name='input') + x = KL.Dense(200, activation='relu', name="dense0")(input_layer) + x = KL.Dense(100, activation='relu', name='dense1')(x) + x = KL.Dense(1, activation='sigmoid', name='output')(x) + model = Model(input_layer, x) + return model + + def fit(self, x, y, x_val, y_val, epoch, batch_size, method='adam'): + if method == "adam": + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'nadam': + optimizer = nadam_v2.Nadam(learning_rate=0.01 * (batch_size / 256)) + elif method == 'adagrad': + optimizer = adagrad_v2.Adagrad(learning_rate=0.01 * (batch_size / 256)) + elif method == 'sgd': + optimizer = SGD(learning_rate=0.01 * (batch_size / 256)) + elif method == 'rmsprop': + optimizer = RMSprop(learning_rate=0.01 * (batch_size / 256)) + else: + optimizer = adam_v2.Adam(learning_rate=0.01 * (batch_size / 256)) + self.model.compile(loss='mse', optimizer=optimizer) + checkpoint = keras.callbacks.ModelCheckpoint(filepath='checkpoints/dnn.hdf5', monitor='val_loss', + mode="min", save_best_only=True) + early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=1e-6, + patience=200, verbose=0, mode='auto') + lr_decay = keras.callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.5, + patience=25, min_delta=1e-6) + callbacks = [checkpoint, early_stop, lr_decay] + history = self.model.fit(x, y, validation_data=(x_val, y_val), epochs=epoch, verbose=1, + callbacks=callbacks, batch_size=batch_size) + return history + if __name__ == '__main__': # plain5 = Plain5(model_path=None, input_shape=(1, 102))