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"280/280 [==============================] - 0s 62us/step - loss: 0.4716 - acc: 0.8893\n",
"Epoch 47/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.4650 - acc: 0.8893\n",
"Epoch 48/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.4586 - acc: 0.8893\n",
"Epoch 49/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.4524 - acc: 0.9036\n",
"Epoch 50/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.4461 - acc: 0.9000\n",
"Epoch 51/100\n",
"280/280 [==============================] - 0s 67us/step - loss: 0.4399 - acc: 0.9000\n",
"Epoch 52/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.4335 - acc: 0.9000\n",
"Epoch 53/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.4273 - acc: 0.9036\n",
"Epoch 54/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.4213 - acc: 0.9071\n",
"Epoch 55/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.4154 - acc: 0.9179\n",
"Epoch 56/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.4095 - acc: 0.9143\n",
"Epoch 57/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.4038 - acc: 0.9214\n",
"Epoch 58/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.3983 - acc: 0.9214\n",
"Epoch 59/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.3925 - acc: 0.9250\n",
"Epoch 60/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3868 - acc: 0.9250\n",
"Epoch 61/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3810 - acc: 0.9357\n",
"Epoch 62/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.3755 - acc: 0.9321\n",
"Epoch 63/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.3703 - acc: 0.9429\n",
"Epoch 64/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3650 - acc: 0.9500\n",
"Epoch 65/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3602 - acc: 0.9357\n",
"Epoch 66/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.3553 - acc: 0.9429\n",
"Epoch 67/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.3506 - acc: 0.9536\n",
"Epoch 68/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.3462 - acc: 0.9464\n",
"Epoch 69/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3418 - acc: 0.9464\n",
"Epoch 70/100\n",
"280/280 [==============================] - 0s 65us/step - loss: 0.3375 - acc: 0.9500\n",
"Epoch 71/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3331 - acc: 0.9536\n",
"Epoch 72/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.3288 - acc: 0.9536\n",
"Epoch 73/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.3244 - acc: 0.9571\n",
"Epoch 74/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.3202 - acc: 0.9643\n",
"Epoch 75/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3159 - acc: 0.9607\n",
"Epoch 76/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.3119 - acc: 0.9607\n",
"Epoch 77/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.3080 - acc: 0.9607\n",
"Epoch 78/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.3038 - acc: 0.9607\n",
"Epoch 79/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.3001 - acc: 0.9607\n",
"Epoch 80/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.2963 - acc: 0.9607\n",
"Epoch 81/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.2925 - acc: 0.9571\n",
"Epoch 82/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.2888 - acc: 0.9643\n",
"Epoch 83/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.2852 - acc: 0.9643\n",
"Epoch 84/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.2815 - acc: 0.9679\n",
"Epoch 85/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.2782 - acc: 0.9643\n",
"Epoch 86/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.2747 - acc: 0.9643\n",
"Epoch 87/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.2716 - acc: 0.9643\n",
"Epoch 88/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.2682 - acc: 0.9679\n",
"Epoch 89/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.2651 - acc: 0.9679\n",
"Epoch 90/100\n",
"280/280 [==============================] - 0s 65us/step - loss: 0.2620 - acc: 0.9679\n",
"Epoch 91/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.2592 - acc: 0.9679\n",
"Epoch 92/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.2561 - acc: 0.9679\n",
"Epoch 93/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.2533 - acc: 0.9714\n",
"Epoch 94/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.2504 - acc: 0.9714\n",
"Epoch 95/100\n",
"280/280 [==============================] - 0s 91us/step - loss: 0.2474 - acc: 0.9714\n",
"Epoch 96/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.2449 - acc: 0.9714\n",
"Epoch 97/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.2424 - acc: 0.9679\n",
"Epoch 98/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.2396 - acc: 0.9714\n",
"Epoch 99/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.2371 - acc: 0.9750\n",
"Epoch 100/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.2348 - acc: 0.9714\n",
"70/70 [==============================] - 0s 3ms/step\n",
"Epoch 1/100\n",
"280/280 [==============================] - 1s 4ms/step - loss: 0.6880 - acc: 0.5214\n",
"Epoch 2/100\n",
"280/280 [==============================] - 0s 79us/step - loss: 0.6785 - acc: 0.5429\n",
"Epoch 3/100\n",
"280/280 [==============================] - 0s 76us/step - loss: 0.6711 - acc: 0.5679\n",
"Epoch 4/100\n",
"280/280 [==============================] - 0s 76us/step - loss: 0.6646 - acc: 0.6214\n",
"Epoch 5/100\n",
"280/280 [==============================] - 0s 77us/step - loss: 0.6586 - acc: 0.6429\n",
"Epoch 6/100\n",
"280/280 [==============================] - 0s 82us/step - loss: 0.6525 - acc: 0.6714\n",
"Epoch 7/100\n",
"280/280 [==============================] - 0s 80us/step - loss: 0.6468 - acc: 0.6821\n",
"Epoch 8/100\n",
"280/280 [==============================] - 0s 79us/step - loss: 0.6413 - acc: 0.6929\n",
"Epoch 9/100\n",
"280/280 [==============================] - 0s 82us/step - loss: 0.6358 - acc: 0.7107\n",
"Epoch 10/100\n",
"280/280 [==============================] - 0s 100us/step - loss: 0.6304 - acc: 0.7393\n",
"Epoch 11/100\n",
"280/280 [==============================] - 0s 93us/step - loss: 0.6249 - acc: 0.7607\n",
"Epoch 12/100\n",
"280/280 [==============================] - 0s 89us/step - loss: 0.6196 - acc: 0.7750\n",
"Epoch 13/100\n",
"280/280 [==============================] - 0s 89us/step - loss: 0.6144 - acc: 0.7929\n",
"Epoch 14/100\n",
"280/280 [==============================] - 0s 94us/step - loss: 0.6095 - acc: 0.8000\n",
"Epoch 15/100\n",
"280/280 [==============================] - 0s 77us/step - loss: 0.6048 - acc: 0.8143\n",
"Epoch 16/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"280/280 [==============================] - 0s 73us/step - loss: 0.6001 - acc: 0.8143\n",
"Epoch 17/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.5954 - acc: 0.8214\n",
"Epoch 18/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.5906 - acc: 0.8250\n",
"Epoch 19/100\n",
"280/280 [==============================] - 0s 59us/step - loss: 0.5860 - acc: 0.8179\n",
"Epoch 20/100\n",
"280/280 [==============================] - 0s 57us/step - loss: 0.5814 - acc: 0.8250\n",
"Epoch 21/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.5769 - acc: 0.8250\n",
"Epoch 22/100\n",
"280/280 [==============================] - 0s 58us/step - loss: 0.5724 - acc: 0.8214\n",
"Epoch 23/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.5680 - acc: 0.8179\n",
"Epoch 24/100\n",
"280/280 [==============================] - 0s 80us/step - loss: 0.5634 - acc: 0.8107\n",
"Epoch 25/100\n",
"280/280 [==============================] - 0s 77us/step - loss: 0.5590 - acc: 0.8143\n",
"Epoch 26/100\n",
"280/280 [==============================] - 0s 96us/step - loss: 0.5550 - acc: 0.8107\n",
"Epoch 27/100\n",
"280/280 [==============================] - ETA: 0s - loss: 0.5588 - acc: 0.750 - 0s 79us/step - loss: 0.5508 - acc: 0.8071\n",
"Epoch 28/100\n",
"280/280 [==============================] - 0s 85us/step - loss: 0.5466 - acc: 0.8036\n",
"Epoch 29/100\n",
"280/280 [==============================] - 0s 79us/step - loss: 0.5425 - acc: 0.8071\n",
"Epoch 30/100\n",
"280/280 [==============================] - 0s 76us/step - loss: 0.5382 - acc: 0.8107\n",
"Epoch 31/100\n",
"280/280 [==============================] - 0s 75us/step - loss: 0.5341 - acc: 0.8071\n",
"Epoch 32/100\n",
"280/280 [==============================] - 0s 68us/step - loss: 0.5300 - acc: 0.8071\n",
"Epoch 33/100\n",
"280/280 [==============================] - 0s 58us/step - loss: 0.5259 - acc: 0.8071\n",
"Epoch 34/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.5218 - acc: 0.8071\n",
"Epoch 35/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.5176 - acc: 0.8107\n",
"Epoch 36/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.5133 - acc: 0.8143\n",
"Epoch 37/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.5091 - acc: 0.8143\n",
"Epoch 38/100\n",
"280/280 [==============================] - 0s 63us/step - loss: 0.5050 - acc: 0.8107\n",
"Epoch 39/100\n",
"280/280 [==============================] - 0s 76us/step - loss: 0.5008 - acc: 0.8107\n",
"Epoch 40/100\n",
"280/280 [==============================] - 0s 65us/step - loss: 0.4970 - acc: 0.8143\n",
"Epoch 41/100\n",
"280/280 [==============================] - 0s 76us/step - loss: 0.4929 - acc: 0.8143\n",
"Epoch 42/100\n",
"280/280 [==============================] - 0s 102us/step - loss: 0.4890 - acc: 0.8179\n",
"Epoch 43/100\n",
"280/280 [==============================] - 0s 104us/step - loss: 0.4850 - acc: 0.8107\n",
"Epoch 44/100\n",
"280/280 [==============================] - 0s 74us/step - loss: 0.4813 - acc: 0.8107\n",
"Epoch 45/100\n",
"280/280 [==============================] - 0s 74us/step - loss: 0.4776 - acc: 0.8143\n",
"Epoch 46/100\n",
"280/280 [==============================] - 0s 81us/step - loss: 0.4741 - acc: 0.8143\n",
"Epoch 47/100\n",
"280/280 [==============================] - 0s 91us/step - loss: 0.4706 - acc: 0.8107\n",
"Epoch 48/100\n",
"280/280 [==============================] - 0s 77us/step - loss: 0.4669 - acc: 0.8107\n",
"Epoch 49/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.4633 - acc: 0.8143\n",
"Epoch 50/100\n",
"280/280 [==============================] - 0s 65us/step - loss: 0.4597 - acc: 0.8250\n",
"Epoch 51/100\n",
"280/280 [==============================] - 0s 67us/step - loss: 0.4562 - acc: 0.8321\n",
"Epoch 52/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.4529 - acc: 0.8286\n",
"Epoch 53/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.4493 - acc: 0.8250\n",
"Epoch 54/100\n",
"280/280 [==============================] - 0s 69us/step - loss: 0.4458 - acc: 0.8321\n",
"Epoch 55/100\n",
"280/280 [==============================] - 0s 65us/step - loss: 0.4421 - acc: 0.8321\n",
"Epoch 56/100\n",
"280/280 [==============================] - 0s 71us/step - loss: 0.4385 - acc: 0.8393\n",
"Epoch 57/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.4348 - acc: 0.8393\n",
"Epoch 58/100\n",
"280/280 [==============================] - 0s 67us/step - loss: 0.4313 - acc: 0.8464\n",
"Epoch 59/100\n",
"280/280 [==============================] - 0s 66us/step - loss: 0.4278 - acc: 0.8464\n",
"Epoch 60/100\n",
"280/280 [==============================] - 0s 57us/step - loss: 0.4244 - acc: 0.8500\n",
"Epoch 61/100\n",
"280/280 [==============================] - 0s 58us/step - loss: 0.4214 - acc: 0.8429\n",
"Epoch 62/100\n",
"280/280 [==============================] - 0s 58us/step - loss: 0.4188 - acc: 0.8500\n",
"Epoch 63/100\n",
"280/280 [==============================] - 0s 64us/step - loss: 0.4156 - acc: 0.8536\n",
"Epoch 64/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.4130 - acc: 0.8571\n",
"Epoch 65/100\n",
"280/280 [==============================] - 0s 57us/step - loss: 0.4104 - acc: 0.8571\n",
"Epoch 66/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.4075 - acc: 0.8571\n",
"Epoch 67/100\n",
"280/280 [==============================] - 0s 90us/step - loss: 0.4048 - acc: 0.8607\n",
"Epoch 68/100\n",
"280/280 [==============================] - 0s 62us/step - loss: 0.4021 - acc: 0.8607\n",
"Epoch 69/100\n",
"280/280 [==============================] - 0s 59us/step - loss: 0.3992 - acc: 0.8643\n",
"Epoch 70/100\n",
"280/280 [==============================] - 0s 66us/step - loss: 0.3962 - acc: 0.8643\n",
"Epoch 71/100\n",
"280/280 [==============================] - 0s 58us/step - loss: 0.3936 - acc: 0.8643\n",
"Epoch 72/100\n",
"280/280 [==============================] - 0s 57us/step - loss: 0.3904 - acc: 0.8679\n",
"Epoch 73/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.3877 - acc: 0.8643\n",
"Epoch 74/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.3850 - acc: 0.8607\n",
"Epoch 75/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.3824 - acc: 0.8643\n",
"Epoch 76/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.3798 - acc: 0.8750\n",
"Epoch 77/100\n",
"280/280 [==============================] - 0s 66us/step - loss: 0.3773 - acc: 0.8679\n",
"Epoch 78/100\n",
"280/280 [==============================] - 0s 59us/step - loss: 0.3750 - acc: 0.8714\n",
"Epoch 79/100\n",
"280/280 [==============================] - 0s 72us/step - loss: 0.3723 - acc: 0.8714\n",
"Epoch 80/100\n",
"280/280 [==============================] - 0s 69us/step - loss: 0.3698 - acc: 0.8679\n",
"Epoch 81/100\n",
"280/280 [==============================] - 0s 68us/step - loss: 0.3671 - acc: 0.8714\n",
"Epoch 82/100\n",
"280/280 [==============================] - 0s 68us/step - loss: 0.3647 - acc: 0.8786\n",
"Epoch 83/100\n",
"280/280 [==============================] - 0s 74us/step - loss: 0.3627 - acc: 0.8786\n",
"Epoch 84/100\n",
"280/280 [==============================] - 0s 74us/step - loss: 0.3602 - acc: 0.8786\n",
"Epoch 85/100\n",
"280/280 [==============================] - 0s 72us/step - loss: 0.3579 - acc: 0.8786\n",
"Epoch 86/100\n",
"280/280 [==============================] - 0s 97us/step - loss: 0.3556 - acc: 0.8821\n",
"Epoch 87/100\n",
"280/280 [==============================] - 0s 80us/step - loss: 0.3535 - acc: 0.8821\n",
"Epoch 88/100\n",
"280/280 [==============================] - 0s 79us/step - loss: 0.3513 - acc: 0.8821\n",
"Epoch 89/100\n",
"280/280 [==============================] - 0s 72us/step - loss: 0.3490 - acc: 0.8786\n",
"Epoch 90/100\n",
"280/280 [==============================] - 0s 72us/step - loss: 0.3468 - acc: 0.8786\n",
"Epoch 91/100\n",
"280/280 [==============================] - 0s 83us/step - loss: 0.3445 - acc: 0.8893\n",
"Epoch 92/100\n",
"280/280 [==============================] - 0s 71us/step - loss: 0.3424 - acc: 0.8857\n",
"Epoch 93/100\n",
"280/280 [==============================] - 0s 72us/step - loss: 0.3402 - acc: 0.8857\n",
"Epoch 94/100\n",
"280/280 [==============================] - 0s 67us/step - loss: 0.3382 - acc: 0.8929\n",
"Epoch 95/100\n",
"280/280 [==============================] - 0s 71us/step - loss: 0.3358 - acc: 0.8929\n",
"Epoch 96/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.3339 - acc: 0.8929\n",
"Epoch 97/100\n",
"280/280 [==============================] - 0s 61us/step - loss: 0.3320 - acc: 0.8929\n",
"Epoch 98/100\n",
"280/280 [==============================] - 0s 60us/step - loss: 0.3304 - acc: 0.8929\n",
"Epoch 99/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"280/280 [==============================] - 0s 62us/step - loss: 0.3281 - acc: 0.8964\n",
"Epoch 100/100\n",
"280/280 [==============================] - 0s 71us/step - loss: 0.3263 - acc: 0.9000\n",
"70/70 [==============================] - 0s 4ms/step\n"
]
},
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# We wrap the Keras model we created above with KerasClassifier\n",
"from keras.wrappers.scikit_learn import KerasClassifier \n",
"from sklearn.model_selection import cross_val_score\n",
"model_scikit = KerasClassifier(build_fn=a_simple_NN, epochs=num_epochs)\n",
"cross_validation = cross_val_score(model_scikit, X_train, y_train, cv=5)\n",
"np.mean(cross_validation)"
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Might Remove the following: This beer example is not good for neural networks. Basically the dataset is far too small**"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(225, 4)"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Revisiting the beer example\n",
"\n",
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"from keras.models import Sequential\n",
"\n",
"# Loading the beer data\n",
"beer = pd.read_csv(\"beers.csv\")\n",
"\n",
"# Extracting the features and labels\n",
"#beer_data.describe()\n",
"features = beer.iloc[:, :-1]\n",
"labels = beer.iloc[:, -1]\n",
"features.shape"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [],
"source": [
"# Revisiting the beer example\n",
"\n",
"# Loading and preparing the data\n",
"\n",
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"\n",
"# Loading the beer data\n",
"beer = pd.read_csv(\"beers.csv\")\n",
"\n",
"# Extracting the features and labels\n",
"#beer_data.describe()\n",
"features = beer.iloc[:, :-1]\n",
"labels = beer.iloc[:, -1]\n",
"\n",
"# Here we split the dataset into training (70%) and validation sets (30%) \n",
"#X_train, X_test, y_train, y_test = train_test_split(features, labels, test_size=0.5, random_state=42)\n",
"X_train, X_test, y_train, y_test = train_test_split(features, labels, test_size=0.3)\n",
"\n",
"# Scaling the data\n",
"# NOTE: The features should be normalized before being fed into the neural network\n",
"scaling = MinMaxScaler()\n",
"scaling.fit(X_train)\n",
"\n",
"X_train_scaled = scaling.transform(X_train)\n",
"X_test_scaled = scaling.transform(X_test)"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 157 samples, validate on 68 samples\n",
"Epoch 1/1000\n",
"157/157 [==============================] - 1s 6ms/step - loss: 0.6730 - acc: 0.5350 - val_loss: 0.6769 - val_acc: 0.5147\n",
"Epoch 2/1000\n",
"157/157 [==============================] - 0s 406us/step - loss: 0.6704 - acc: 0.5350 - val_loss: 0.6754 - val_acc: 0.5147\n",
"Epoch 3/1000\n",
"157/157 [==============================] - 0s 256us/step - loss: 0.6693 - acc: 0.5350 - val_loss: 0.6740 - val_acc: 0.5147\n",
"Epoch 4/1000\n",
"157/157 [==============================] - 0s 215us/step - loss: 0.6679 - acc: 0.5350 - val_loss: 0.6728 - val_acc: 0.5147\n",
"Epoch 5/1000\n",
"157/157 [==============================] - 0s 168us/step - loss: 0.6668 - acc: 0.5350 - val_loss: 0.6716 - val_acc: 0.5147\n",
"Epoch 6/1000\n",
"157/157 [==============================] - 0s 107us/step - loss: 0.6658 - acc: 0.5350 - val_loss: 0.6704 - val_acc: 0.5147\n",
"Epoch 7/1000\n",
"157/157 [==============================] - 0s 303us/step - loss: 0.6652 - acc: 0.5350 - val_loss: 0.6693 - val_acc: 0.5147\n",
"Epoch 8/1000\n",
"157/157 [==============================] - 0s 98us/step - loss: 0.6637 - acc: 0.5350 - val_loss: 0.6682 - val_acc: 0.5147\n",
"Epoch 9/1000\n",
"157/157 [==============================] - 0s 92us/step - loss: 0.6626 - acc: 0.5350 - val_loss: 0.6670 - val_acc: 0.5147\n",
"Epoch 10/1000\n",
"157/157 [==============================] - 0s 90us/step - loss: 0.6616 - acc: 0.5350 - val_loss: 0.6657 - val_acc: 0.5147\n",
"Epoch 11/1000\n",
"157/157 [==============================] - 0s 92us/step - loss: 0.6605 - acc: 0.5350 - val_loss: 0.6644 - val_acc: 0.5147\n",
"Epoch 12/1000\n",
"157/157 [==============================] - 0s 305us/step - loss: 0.6596 - acc: 0.5350 - val_loss: 0.6633 - val_acc: 0.5147\n",
"Epoch 13/1000\n",
"157/157 [==============================] - 0s 142us/step - loss: 0.6587 - acc: 0.5350 - val_loss: 0.6622 - val_acc: 0.5147\n",
"Epoch 14/1000\n",
"157/157 [==============================] - 0s 144us/step - loss: 0.6578 - acc: 0.5350 - val_loss: 0.6612 - val_acc: 0.5147\n",
"Epoch 15/1000\n",
"157/157 [==============================] - 0s 137us/step - loss: 0.6567 - acc: 0.5350 - val_loss: 0.6601 - val_acc: 0.5147\n",
"Epoch 16/1000\n",
"157/157 [==============================] - 0s 179us/step - loss: 0.6558 - acc: 0.5350 - val_loss: 0.6591 - val_acc: 0.5147\n",
"Epoch 17/1000\n",
"157/157 [==============================] - 0s 98us/step - loss: 0.6551 - acc: 0.5350 - val_loss: 0.6580 - val_acc: 0.5147\n",
"Epoch 18/1000\n",
"157/157 [==============================] - 0s 106us/step - loss: 0.6540 - acc: 0.5350 - val_loss: 0.6570 - val_acc: 0.5147\n",
"Epoch 19/1000\n",
"157/157 [==============================] - 0s 97us/step - loss: 0.6531 - acc: 0.5350 - val_loss: 0.6559 - val_acc: 0.5147\n",
"Epoch 20/1000\n",
"157/157 [==============================] - 0s 131us/step - loss: 0.6523 - acc: 0.5350 - val_loss: 0.6549 - val_acc: 0.5147\n",
"Epoch 21/1000\n",
"157/157 [==============================] - 0s 141us/step - loss: 0.6512 - acc: 0.5350 - val_loss: 0.6537 - val_acc: 0.5147\n",
"Epoch 22/1000\n",
"157/157 [==============================] - 0s 288us/step - loss: 0.6506 - acc: 0.5350 - val_loss: 0.6527 - val_acc: 0.5147\n",
"Epoch 23/1000\n",
"157/157 [==============================] - 0s 128us/step - loss: 0.6496 - acc: 0.5414 - val_loss: 0.6517 - val_acc: 0.5147\n",
"Epoch 24/1000\n",
"157/157 [==============================] - 0s 257us/step - loss: 0.6486 - acc: 0.5414 - val_loss: 0.6506 - val_acc: 0.5147\n",
"Epoch 25/1000\n",
"157/157 [==============================] - 0s 95us/step - loss: 0.6477 - acc: 0.5478 - val_loss: 0.6495 - val_acc: 0.5147\n",
"Epoch 26/1000\n",
"157/157 [==============================] - 0s 112us/step - loss: 0.6466 - acc: 0.5414 - val_loss: 0.6483 - val_acc: 0.5147\n",
"Epoch 27/1000\n",
"157/157 [==============================] - 0s 168us/step - loss: 0.6458 - acc: 0.5541 - val_loss: 0.6472 - val_acc: 0.5147\n",
"Epoch 28/1000\n",
"157/157 [==============================] - 0s 257us/step - loss: 0.6447 - acc: 0.5541 - val_loss: 0.6461 - val_acc: 0.5147\n",
"Epoch 29/1000\n",
"157/157 [==============================] - 0s 134us/step - loss: 0.6437 - acc: 0.5541 - val_loss: 0.6449 - val_acc: 0.5147\n",
"Epoch 30/1000\n",
"157/157 [==============================] - 0s 111us/step - loss: 0.6427 - acc: 0.5669 - val_loss: 0.6438 - val_acc: 0.5147\n",
"Epoch 31/1000\n",
"157/157 [==============================] - 0s 153us/step - loss: 0.6417 - acc: 0.5669 - val_loss: 0.6426 - val_acc: 0.5147\n",
"Epoch 32/1000\n",
"157/157 [==============================] - 0s 103us/step - loss: 0.6407 - acc: 0.5669 - val_loss: 0.6414 - val_acc: 0.5147\n",
"Epoch 33/1000\n",
"157/157 [==============================] - 0s 269us/step - loss: 0.6394 - acc: 0.5732 - val_loss: 0.6401 - val_acc: 0.5294\n",
"Epoch 34/1000\n",
"157/157 [==============================] - 0s 119us/step - loss: 0.6384 - acc: 0.5732 - val_loss: 0.6387 - val_acc: 0.5294\n",
"Epoch 35/1000\n",
"157/157 [==============================] - 0s 92us/step - loss: 0.6371 - acc: 0.5732 - val_loss: 0.6373 - val_acc: 0.5294\n",
"Epoch 36/1000\n",
"157/157 [==============================] - 0s 298us/step - loss: 0.6361 - acc: 0.5796 - val_loss: 0.6360 - val_acc: 0.5294\n",
"Epoch 37/1000\n",
"157/157 [==============================] - 0s 193us/step - loss: 0.6349 - acc: 0.5860 - val_loss: 0.6347 - val_acc: 0.5441\n",
"Epoch 38/1000\n",
"157/157 [==============================] - 0s 122us/step - loss: 0.6336 - acc: 0.5860 - val_loss: 0.6333 - val_acc: 0.5441\n",
"Epoch 39/1000\n",
"157/157 [==============================] - 0s 194us/step - loss: 0.6323 - acc: 0.5860 - val_loss: 0.6318 - val_acc: 0.5441\n",
"Epoch 40/1000\n",
"157/157 [==============================] - 0s 321us/step - loss: 0.6310 - acc: 0.5860 - val_loss: 0.6302 - val_acc: 0.5441\n",
"Epoch 41/1000\n",
"157/157 [==============================] - 0s 151us/step - loss: 0.6297 - acc: 0.5924 - val_loss: 0.6286 - val_acc: 0.5441\n",
"Epoch 42/1000\n",
"157/157 [==============================] - 0s 229us/step - loss: 0.6285 - acc: 0.5924 - val_loss: 0.6273 - val_acc: 0.5441\n",
"Epoch 43/1000\n",
"157/157 [==============================] - 0s 201us/step - loss: 0.6271 - acc: 0.5924 - val_loss: 0.6258 - val_acc: 0.5441\n",
"Epoch 44/1000\n",
"157/157 [==============================] - 0s 129us/step - loss: 0.6260 - acc: 0.5924 - val_loss: 0.6243 - val_acc: 0.5441\n",
"Epoch 45/1000\n",
"157/157 [==============================] - 0s 149us/step - loss: 0.6245 - acc: 0.5987 - val_loss: 0.6228 - val_acc: 0.5588\n",
"Epoch 46/1000\n",
"157/157 [==============================] - 0s 113us/step - loss: 0.6234 - acc: 0.6051 - val_loss: 0.6213 - val_acc: 0.5588\n",
"Epoch 47/1000\n",
"157/157 [==============================] - 0s 537us/step - loss: 0.6218 - acc: 0.6178 - val_loss: 0.6197 - val_acc: 0.5588\n",
"Epoch 48/1000\n",
"157/157 [==============================] - 0s 117us/step - loss: 0.6205 - acc: 0.6178 - val_loss: 0.6181 - val_acc: 0.5588\n",
"Epoch 49/1000\n",
"157/157 [==============================] - 0s 146us/step - loss: 0.6191 - acc: 0.6178 - val_loss: 0.6164 - val_acc: 0.5735\n",
"Epoch 50/1000\n",
"157/157 [==============================] - 0s 200us/step - loss: 0.6176 - acc: 0.6178 - val_loss: 0.6146 - val_acc: 0.5882\n",
"Epoch 51/1000\n",
"157/157 [==============================] - 0s 286us/step - loss: 0.6165 - acc: 0.6178 - val_loss: 0.6130 - val_acc: 0.5882\n",
"Epoch 52/1000\n",
"157/157 [==============================] - 0s 254us/step - loss: 0.6152 - acc: 0.6242 - val_loss: 0.6116 - val_acc: 0.6029\n",
"Epoch 53/1000\n",
"157/157 [==============================] - 0s 156us/step - loss: 0.6136 - acc: 0.6242 - val_loss: 0.6100 - val_acc: 0.6029\n",
"Epoch 54/1000\n",
"157/157 [==============================] - 0s 202us/step - loss: 0.6127 - acc: 0.6242 - val_loss: 0.6085 - val_acc: 0.6029\n",
"Epoch 55/1000\n",
"157/157 [==============================] - 0s 108us/step - loss: 0.6114 - acc: 0.6242 - val_loss: 0.6070 - val_acc: 0.6029\n",
"Epoch 56/1000\n",
"157/157 [==============================] - 0s 157us/step - loss: 0.6098 - acc: 0.6242 - val_loss: 0.6053 - val_acc: 0.6029\n",
"Epoch 57/1000\n",
"157/157 [==============================] - 0s 118us/step - loss: 0.6085 - acc: 0.6242 - val_loss: 0.6036 - val_acc: 0.6029\n",
"Epoch 58/1000\n",
"157/157 [==============================] - 0s 128us/step - loss: 0.6070 - acc: 0.6242 - val_loss: 0.6018 - val_acc: 0.6029\n",
"Epoch 59/1000\n",
"157/157 [==============================] - 0s 165us/step - loss: 0.6057 - acc: 0.6242 - val_loss: 0.6001 - val_acc: 0.6029\n",
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"157/157 [==============================] - 0s 263us/step - loss: 0.6039 - acc: 0.6242 - val_loss: 0.5982 - val_acc: 0.6176\n",
"Epoch 61/1000\n",
"157/157 [==============================] - 0s 244us/step - loss: 0.6023 - acc: 0.6242 - val_loss: 0.5963 - val_acc: 0.6176\n",
"Epoch 62/1000\n",
"157/157 [==============================] - 0s 409us/step - loss: 0.6006 - acc: 0.6306 - val_loss: 0.5943 - val_acc: 0.6176\n",
"Epoch 63/1000\n",
"157/157 [==============================] - 0s 104us/step - loss: 0.5991 - acc: 0.6306 - val_loss: 0.5922 - val_acc: 0.6324\n",
"Epoch 64/1000\n",
"157/157 [==============================] - 0s 193us/step - loss: 0.5981 - acc: 0.6369 - val_loss: 0.5906 - val_acc: 0.6324\n",
"Epoch 65/1000\n",
"157/157 [==============================] - 0s 104us/step - loss: 0.5958 - acc: 0.6433 - val_loss: 0.5889 - val_acc: 0.6471\n",
"Epoch 66/1000\n",
"157/157 [==============================] - 0s 172us/step - loss: 0.5945 - acc: 0.6433 - val_loss: 0.5871 - val_acc: 0.6471\n",
"Epoch 67/1000\n",
"157/157 [==============================] - 0s 378us/step - loss: 0.5929 - acc: 0.6433 - val_loss: 0.5852 - val_acc: 0.6471\n",
"Epoch 68/1000\n",
"157/157 [==============================] - 0s 193us/step - loss: 0.5917 - acc: 0.6497 - val_loss: 0.5836 - val_acc: 0.6471\n",
"Epoch 69/1000\n",
"157/157 [==============================] - 0s 155us/step - loss: 0.5901 - acc: 0.6497 - val_loss: 0.5816 - val_acc: 0.6471\n",
"Epoch 70/1000\n",
"157/157 [==============================] - 0s 180us/step - loss: 0.5885 - acc: 0.6497 - val_loss: 0.5797 - val_acc: 0.6765\n",
"Epoch 71/1000\n",
"157/157 [==============================] - 0s 208us/step - loss: 0.5867 - acc: 0.6561 - val_loss: 0.5778 - val_acc: 0.6765\n",
"Epoch 72/1000\n",
"157/157 [==============================] - 0s 200us/step - loss: 0.5850 - acc: 0.6561 - val_loss: 0.5755 - val_acc: 0.6765\n",
"Epoch 73/1000\n",
"157/157 [==============================] - 0s 279us/step - loss: 0.5831 - acc: 0.6624 - val_loss: 0.5733 - val_acc: 0.6765\n",
"Epoch 74/1000\n",
"157/157 [==============================] - 0s 263us/step - loss: 0.5812 - acc: 0.6688 - val_loss: 0.5712 - val_acc: 0.6912\n",
"Epoch 75/1000\n",
"157/157 [==============================] - 0s 263us/step - loss: 0.5791 - acc: 0.6752 - val_loss: 0.5688 - val_acc: 0.7059\n",
"Epoch 76/1000\n",
"157/157 [==============================] - 0s 223us/step - loss: 0.5771 - acc: 0.6752 - val_loss: 0.5665 - val_acc: 0.7059\n",
"Epoch 77/1000\n",
"157/157 [==============================] - 0s 252us/step - loss: 0.5750 - acc: 0.6879 - val_loss: 0.5643 - val_acc: 0.7059\n",
"Epoch 78/1000\n",
"157/157 [==============================] - 0s 217us/step - loss: 0.5728 - acc: 0.6879 - val_loss: 0.5619 - val_acc: 0.7059\n",
"Epoch 79/1000\n",
"157/157 [==============================] - 0s 123us/step - loss: 0.5708 - acc: 0.6943 - val_loss: 0.5596 - val_acc: 0.7059\n",
"Epoch 80/1000\n",
"157/157 [==============================] - 0s 149us/step - loss: 0.5687 - acc: 0.7006 - val_loss: 0.5570 - val_acc: 0.7206\n",
"Epoch 81/1000\n",
"157/157 [==============================] - 0s 181us/step - loss: 0.5666 - acc: 0.7070 - val_loss: 0.5545 - val_acc: 0.7206\n",
"Epoch 82/1000\n",
"157/157 [==============================] - 0s 109us/step - loss: 0.5643 - acc: 0.7006 - val_loss: 0.5519 - val_acc: 0.7206\n",
"Epoch 83/1000\n",
"157/157 [==============================] - 0s 258us/step - loss: 0.5623 - acc: 0.7134 - val_loss: 0.5495 - val_acc: 0.7206\n",
"Epoch 84/1000\n",
"157/157 [==============================] - 0s 123us/step - loss: 0.5600 - acc: 0.7197 - val_loss: 0.5469 - val_acc: 0.7206\n",
"Epoch 85/1000\n",
"157/157 [==============================] - 0s 120us/step - loss: 0.5577 - acc: 0.7197 - val_loss: 0.5443 - val_acc: 0.7206\n",
"Epoch 86/1000\n",
"157/157 [==============================] - 0s 166us/step - loss: 0.5550 - acc: 0.7197 - val_loss: 0.5411 - val_acc: 0.7353\n",
"Epoch 87/1000\n",
"157/157 [==============================] - 0s 134us/step - loss: 0.5529 - acc: 0.7325 - val_loss: 0.5383 - val_acc: 0.7353\n",
"Epoch 88/1000\n",
"157/157 [==============================] - 0s 185us/step - loss: 0.5498 - acc: 0.7325 - val_loss: 0.5347 - val_acc: 0.7353\n",
"Epoch 89/1000\n",
"157/157 [==============================] - 0s 194us/step - loss: 0.5471 - acc: 0.7516 - val_loss: 0.5314 - val_acc: 0.7647\n",
"Epoch 90/1000\n",
"157/157 [==============================] - 0s 163us/step - loss: 0.5451 - acc: 0.7452 - val_loss: 0.5283 - val_acc: 0.7941\n",
"Epoch 91/1000\n",
"157/157 [==============================] - 0s 292us/step - loss: 0.5430 - acc: 0.7580 - val_loss: 0.5258 - val_acc: 0.8088\n",
"Epoch 92/1000\n",
"157/157 [==============================] - 0s 137us/step - loss: 0.5399 - acc: 0.7580 - val_loss: 0.5234 - val_acc: 0.8088\n",
"Epoch 93/1000\n",
"157/157 [==============================] - 0s 193us/step - loss: 0.5383 - acc: 0.7643 - val_loss: 0.5210 - val_acc: 0.8088\n",
"Epoch 94/1000\n",
"157/157 [==============================] - 0s 231us/step - loss: 0.5356 - acc: 0.7643 - val_loss: 0.5184 - val_acc: 0.8088\n",
"Epoch 95/1000\n",
"157/157 [==============================] - 0s 96us/step - loss: 0.5334 - acc: 0.7643 - val_loss: 0.5158 - val_acc: 0.8235\n",
"Epoch 96/1000\n",
"157/157 [==============================] - 0s 196us/step - loss: 0.5309 - acc: 0.7707 - val_loss: 0.5128 - val_acc: 0.8235\n",
"Epoch 97/1000\n",
"157/157 [==============================] - 0s 214us/step - loss: 0.5291 - acc: 0.7898 - val_loss: 0.5100 - val_acc: 0.8235\n",
"Epoch 98/1000\n",
"157/157 [==============================] - 0s 179us/step - loss: 0.5263 - acc: 0.7898 - val_loss: 0.5074 - val_acc: 0.8235\n",
"Epoch 99/1000\n",
"157/157 [==============================] - 0s 182us/step - loss: 0.5243 - acc: 0.7962 - val_loss: 0.5044 - val_acc: 0.8088\n",
"Epoch 100/1000\n",
"157/157 [==============================] - 0s 144us/step - loss: 0.5234 - acc: 0.7834 - val_loss: 0.5024 - val_acc: 0.8088\n",
"Epoch 101/1000\n",
"157/157 [==============================] - 0s 154us/step - loss: 0.5198 - acc: 0.8025 - val_loss: 0.5002 - val_acc: 0.8088\n",
"Epoch 102/1000\n",
"157/157 [==============================] - 0s 320us/step - loss: 0.5184 - acc: 0.7962 - val_loss: 0.4978 - val_acc: 0.8088\n",
"Epoch 103/1000\n",
"157/157 [==============================] - 0s 142us/step - loss: 0.5162 - acc: 0.8025 - val_loss: 0.4956 - val_acc: 0.8088\n",
"Epoch 104/1000\n",
"157/157 [==============================] - 0s 131us/step - loss: 0.5136 - acc: 0.8025 - val_loss: 0.4932 - val_acc: 0.8088\n",
"Epoch 105/1000\n",
"157/157 [==============================] - 0s 142us/step - loss: 0.5115 - acc: 0.7962 - val_loss: 0.4903 - val_acc: 0.8235\n",
"Epoch 106/1000\n",
"157/157 [==============================] - 0s 144us/step - loss: 0.5091 - acc: 0.8025 - val_loss: 0.4877 - val_acc: 0.8382\n",
"Epoch 107/1000\n",
"157/157 [==============================] - 0s 351us/step - loss: 0.5065 - acc: 0.8089 - val_loss: 0.4851 - val_acc: 0.8382\n",
"Epoch 108/1000\n",
"157/157 [==============================] - 0s 370us/step - loss: 0.5041 - acc: 0.8025 - val_loss: 0.4822 - val_acc: 0.8529\n",
"Epoch 109/1000\n",
"157/157 [==============================] - 0s 345us/step - loss: 0.5016 - acc: 0.8089 - val_loss: 0.4795 - val_acc: 0.8529\n",
"Epoch 110/1000\n",
"157/157 [==============================] - 0s 121us/step - loss: 0.4996 - acc: 0.8025 - val_loss: 0.4765 - val_acc: 0.8529\n",
"Epoch 111/1000\n",
"157/157 [==============================] - 0s 135us/step - loss: 0.4972 - acc: 0.8089 - val_loss: 0.4739 - val_acc: 0.8529\n",
"Epoch 112/1000\n",
"157/157 [==============================] - 0s 266us/step - loss: 0.4944 - acc: 0.8280 - val_loss: 0.4716 - val_acc: 0.8529\n",
"Epoch 113/1000\n",
"157/157 [==============================] - 0s 218us/step - loss: 0.4918 - acc: 0.8153 - val_loss: 0.4686 - val_acc: 0.8529\n",
"Epoch 114/1000\n",
"157/157 [==============================] - 0s 174us/step - loss: 0.4894 - acc: 0.8471 - val_loss: 0.4656 - val_acc: 0.8529\n",
"Epoch 115/1000\n",
"157/157 [==============================] - 0s 157us/step - loss: 0.4869 - acc: 0.8408 - val_loss: 0.4624 - val_acc: 0.8676\n",
"Epoch 116/1000\n",
"157/157 [==============================] - 0s 276us/step - loss: 0.4846 - acc: 0.8089 - val_loss: 0.4592 - val_acc: 0.8676\n",
"Epoch 117/1000\n",
"157/157 [==============================] - 0s 146us/step - loss: 0.4818 - acc: 0.8408 - val_loss: 0.4565 - val_acc: 0.8676\n",
"Epoch 118/1000\n",
"157/157 [==============================] - 0s 246us/step - loss: 0.4792 - acc: 0.8535 - val_loss: 0.4539 - val_acc: 0.8676\n",
"Epoch 119/1000\n",
"157/157 [==============================] - 0s 116us/step - loss: 0.4768 - acc: 0.8408 - val_loss: 0.4506 - val_acc: 0.8676\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 120/1000\n",
"157/157 [==============================] - 0s 229us/step - loss: 0.4756 - acc: 0.8471 - val_loss: 0.4482 - val_acc: 0.8676\n",
"Epoch 121/1000\n",
"157/157 [==============================] - 0s 204us/step - loss: 0.4726 - acc: 0.8599 - val_loss: 0.4463 - val_acc: 0.8676\n",
"Epoch 122/1000\n",
"157/157 [==============================] - 0s 162us/step - loss: 0.4708 - acc: 0.8471 - val_loss: 0.4438 - val_acc: 0.8676\n",
"Epoch 123/1000\n",
"157/157 [==============================] - 0s 245us/step - loss: 0.4682 - acc: 0.8599 - val_loss: 0.4415 - val_acc: 0.8676\n",
"Epoch 124/1000\n",
"157/157 [==============================] - 0s 200us/step - loss: 0.4658 - acc: 0.8535 - val_loss: 0.4390 - val_acc: 0.8676\n",
"Epoch 125/1000\n",
"157/157 [==============================] - 0s 178us/step - loss: 0.4635 - acc: 0.8599 - val_loss: 0.4361 - val_acc: 0.8824\n",
"Epoch 126/1000\n",
"157/157 [==============================] - 0s 156us/step - loss: 0.4614 - acc: 0.8535 - val_loss: 0.4332 - val_acc: 0.8824\n",
"Epoch 127/1000\n",
"157/157 [==============================] - 0s 327us/step - loss: 0.4584 - acc: 0.8726 - val_loss: 0.4307 - val_acc: 0.8824\n",
"Epoch 128/1000\n",
"157/157 [==============================] - 0s 181us/step - loss: 0.4571 - acc: 0.8535 - val_loss: 0.4279 - val_acc: 0.8824\n",
"Epoch 129/1000\n",
"157/157 [==============================] - 0s 268us/step - loss: 0.4550 - acc: 0.8726 - val_loss: 0.4258 - val_acc: 0.8824\n",
"Epoch 130/1000\n",
"157/157 [==============================] - 0s 176us/step - loss: 0.4517 - acc: 0.8599 - val_loss: 0.4230 - val_acc: 0.8824\n",
"Epoch 131/1000\n",
"157/157 [==============================] - 0s 281us/step - loss: 0.4497 - acc: 0.8726 - val_loss: 0.4204 - val_acc: 0.8824\n",
"Epoch 132/1000\n",
"157/157 [==============================] - 0s 149us/step - loss: 0.4476 - acc: 0.8662 - val_loss: 0.4178 - val_acc: 0.8824\n",
"Epoch 133/1000\n",
"157/157 [==============================] - 0s 177us/step - loss: 0.4456 - acc: 0.8726 - val_loss: 0.4153 - val_acc: 0.8824\n",
"Epoch 134/1000\n",
"157/157 [==============================] - 0s 137us/step - loss: 0.4433 - acc: 0.8790 - val_loss: 0.4131 - val_acc: 0.8824\n",
"Epoch 135/1000\n",
"157/157 [==============================] - 0s 121us/step - loss: 0.4409 - acc: 0.8854 - val_loss: 0.4108 - val_acc: 0.8824\n",
"Epoch 136/1000\n",
"157/157 [==============================] - 0s 167us/step - loss: 0.4381 - acc: 0.8726 - val_loss: 0.4082 - val_acc: 0.8824\n",
"Epoch 137/1000\n",
"157/157 [==============================] - 0s 272us/step - loss: 0.4357 - acc: 0.8854 - val_loss: 0.4053 - val_acc: 0.8824\n",
"Epoch 138/1000\n",
"157/157 [==============================] - 0s 286us/step - loss: 0.4338 - acc: 0.8726 - val_loss: 0.4025 - val_acc: 0.8824\n",
"Epoch 139/1000\n",
"157/157 [==============================] - 0s 164us/step - loss: 0.4308 - acc: 0.8726 - val_loss: 0.3994 - val_acc: 0.8824\n",
"Epoch 140/1000\n",
"157/157 [==============================] - 0s 160us/step - loss: 0.4286 - acc: 0.8790 - val_loss: 0.3968 - val_acc: 0.8824\n",
"Epoch 141/1000\n",
"157/157 [==============================] - 0s 196us/step - loss: 0.4266 - acc: 0.8726 - val_loss: 0.3944 - val_acc: 0.8824\n",
"Epoch 142/1000\n",
"157/157 [==============================] - 0s 285us/step - loss: 0.4241 - acc: 0.8790 - val_loss: 0.3924 - val_acc: 0.8824\n",
"Epoch 143/1000\n",
"157/157 [==============================] - 0s 136us/step - loss: 0.4224 - acc: 0.8726 - val_loss: 0.3902 - val_acc: 0.8824\n",
"Epoch 144/1000\n",
"157/157 [==============================] - 0s 243us/step - loss: 0.4204 - acc: 0.8726 - val_loss: 0.3882 - val_acc: 0.8824\n",
"Epoch 145/1000\n",
"157/157 [==============================] - 0s 155us/step - loss: 0.4177 - acc: 0.8726 - val_loss: 0.3860 - val_acc: 0.8824\n",
"Epoch 146/1000\n",
"157/157 [==============================] - 0s 210us/step - loss: 0.4167 - acc: 0.8854 - val_loss: 0.3840 - val_acc: 0.8824\n",
"Epoch 147/1000\n",
"157/157 [==============================] - 0s 155us/step - loss: 0.4133 - acc: 0.8726 - val_loss: 0.3815 - val_acc: 0.8824\n",
"Epoch 148/1000\n",
"157/157 [==============================] - 0s 150us/step - loss: 0.4112 - acc: 0.8790 - val_loss: 0.3791 - val_acc: 0.8824\n",
"Epoch 149/1000\n",
"157/157 [==============================] - 0s 274us/step - loss: 0.4098 - acc: 0.8854 - val_loss: 0.3771 - val_acc: 0.8824\n",
"Epoch 150/1000\n",
"157/157 [==============================] - 0s 162us/step - loss: 0.4075 - acc: 0.8726 - val_loss: 0.3743 - val_acc: 0.8824\n",
"Epoch 151/1000\n",
"157/157 [==============================] - 0s 141us/step - loss: 0.4047 - acc: 0.8854 - val_loss: 0.3721 - val_acc: 0.8824\n",
"Epoch 152/1000\n",
"157/157 [==============================] - 0s 282us/step - loss: 0.4033 - acc: 0.8726 - val_loss: 0.3694 - val_acc: 0.8824\n",
"Epoch 153/1000\n",
"157/157 [==============================] - 0s 167us/step - loss: 0.4013 - acc: 0.9108 - val_loss: 0.3680 - val_acc: 0.8824\n",
"Epoch 154/1000\n",
"157/157 [==============================] - 0s 313us/step - loss: 0.3985 - acc: 0.8854 - val_loss: 0.3655 - val_acc: 0.8824\n",
"Epoch 155/1000\n",
"157/157 [==============================] - 0s 150us/step - loss: 0.3970 - acc: 0.8981 - val_loss: 0.3635 - val_acc: 0.8824\n",
"Epoch 156/1000\n",
"157/157 [==============================] - 0s 156us/step - loss: 0.3944 - acc: 0.8981 - val_loss: 0.3613 - val_acc: 0.8824\n",
"Epoch 157/1000\n",
"157/157 [==============================] - 0s 124us/step - loss: 0.3928 - acc: 0.8981 - val_loss: 0.3594 - val_acc: 0.8824\n",
"Epoch 158/1000\n",
"157/157 [==============================] - 0s 163us/step - loss: 0.3903 - acc: 0.8917 - val_loss: 0.3567 - val_acc: 0.8824\n",
"Epoch 159/1000\n",
"157/157 [==============================] - 0s 128us/step - loss: 0.3881 - acc: 0.8981 - val_loss: 0.3543 - val_acc: 0.8824\n",
"Epoch 160/1000\n",
"157/157 [==============================] - 0s 128us/step - loss: 0.3871 - acc: 0.8917 - val_loss: 0.3523 - val_acc: 0.8824\n",
"Epoch 161/1000\n",
"157/157 [==============================] - 0s 123us/step - loss: 0.3840 - acc: 0.9108 - val_loss: 0.3503 - val_acc: 0.8824\n",
"Epoch 162/1000\n",
"157/157 [==============================] - 0s 133us/step - loss: 0.3833 - acc: 0.8854 - val_loss: 0.3481 - val_acc: 0.8971\n",
"Epoch 163/1000\n",
"157/157 [==============================] - 0s 222us/step - loss: 0.3810 - acc: 0.8917 - val_loss: 0.3463 - val_acc: 0.8971\n",
"Epoch 164/1000\n",
"157/157 [==============================] - 0s 210us/step - loss: 0.3785 - acc: 0.9236 - val_loss: 0.3449 - val_acc: 0.8824\n",
"Epoch 165/1000\n",
"157/157 [==============================] - 0s 278us/step - loss: 0.3774 - acc: 0.9045 - val_loss: 0.3431 - val_acc: 0.8971\n",
"Epoch 166/1000\n",
"157/157 [==============================] - 0s 163us/step - loss: 0.3751 - acc: 0.8917 - val_loss: 0.3406 - val_acc: 0.8971\n",
"Epoch 167/1000\n",
"157/157 [==============================] - 0s 183us/step - loss: 0.3735 - acc: 0.8981 - val_loss: 0.3388 - val_acc: 0.8971\n",
"Epoch 168/1000\n",
"157/157 [==============================] - 0s 144us/step - loss: 0.3711 - acc: 0.9172 - val_loss: 0.3368 - val_acc: 0.8971\n",
"Epoch 169/1000\n",
"157/157 [==============================] - 0s 304us/step - loss: 0.3701 - acc: 0.9108 - val_loss: 0.3346 - val_acc: 0.8971\n",
"Epoch 170/1000\n",
"157/157 [==============================] - 0s 162us/step - loss: 0.3674 - acc: 0.9236 - val_loss: 0.3330 - val_acc: 0.8971\n",
"Epoch 171/1000\n",
"157/157 [==============================] - 0s 287us/step - loss: 0.3666 - acc: 0.9172 - val_loss: 0.3312 - val_acc: 0.8971\n",
"Epoch 172/1000\n",
"157/157 [==============================] - 0s 189us/step - loss: 0.3638 - acc: 0.9108 - val_loss: 0.3291 - val_acc: 0.8971\n",
"Epoch 173/1000\n",
"157/157 [==============================] - 0s 154us/step - loss: 0.3617 - acc: 0.9236 - val_loss: 0.3275 - val_acc: 0.8971\n",
"Epoch 174/1000\n",
"157/157 [==============================] - 0s 136us/step - loss: 0.3595 - acc: 0.9236 - val_loss: 0.3257 - val_acc: 0.8971\n",
"Epoch 175/1000\n",
"157/157 [==============================] - 0s 154us/step - loss: 0.3579 - acc: 0.9236 - val_loss: 0.3240 - val_acc: 0.8971\n",
"Epoch 176/1000\n",
"157/157 [==============================] - 0s 129us/step - loss: 0.3565 - acc: 0.9172 - val_loss: 0.3219 - val_acc: 0.8971\n",
"Epoch 177/1000\n",
"157/157 [==============================] - 0s 191us/step - loss: 0.3540 - acc: 0.9236 - val_loss: 0.3205 - val_acc: 0.8971\n",
"Epoch 178/1000\n",
"157/157 [==============================] - 0s 374us/step - loss: 0.3529 - acc: 0.9108 - val_loss: 0.3181 - val_acc: 0.8971\n",
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"157/157 [==============================] - 0s 307us/step - loss: 0.3500 - acc: 0.9236 - val_loss: 0.3156 - val_acc: 0.8971\n",
"Epoch 180/1000\n",
"157/157 [==============================] - 0s 319us/step - loss: 0.3485 - acc: 0.9236 - val_loss: 0.3136 - val_acc: 0.8971\n",
"Epoch 181/1000\n",
"157/157 [==============================] - 0s 166us/step - loss: 0.3467 - acc: 0.9236 - val_loss: 0.3116 - val_acc: 0.8971\n",
"Epoch 182/1000\n",
"157/157 [==============================] - 0s 186us/step - loss: 0.3450 - acc: 0.9236 - val_loss: 0.3103 - val_acc: 0.8971\n",
"Epoch 183/1000\n",
"157/157 [==============================] - 0s 282us/step - loss: 0.3439 - acc: 0.9172 - val_loss: 0.3084 - val_acc: 0.8971\n",
"Epoch 184/1000\n",
"157/157 [==============================] - 0s 287us/step - loss: 0.3413 - acc: 0.9172 - val_loss: 0.3064 - val_acc: 0.8971\n",
"Epoch 185/1000\n",
"157/157 [==============================] - 0s 153us/step - loss: 0.3405 - acc: 0.9108 - val_loss: 0.3047 - val_acc: 0.9118\n",
"Epoch 186/1000\n",
"157/157 [==============================] - 0s 238us/step - loss: 0.3376 - acc: 0.9236 - val_loss: 0.3028 - val_acc: 0.9118\n",
"Epoch 187/1000\n",
"157/157 [==============================] - 0s 291us/step - loss: 0.3358 - acc: 0.9299 - val_loss: 0.3014 - val_acc: 0.9118\n",
"Epoch 188/1000\n",
"157/157 [==============================] - 0s 191us/step - loss: 0.3347 - acc: 0.9236 - val_loss: 0.2989 - val_acc: 0.9118\n",
"Epoch 189/1000\n",
"157/157 [==============================] - 0s 231us/step - loss: 0.3334 - acc: 0.9299 - val_loss: 0.2972 - val_acc: 0.9118\n",
"Epoch 190/1000\n",
"157/157 [==============================] - 0s 208us/step - loss: 0.3302 - acc: 0.9299 - val_loss: 0.2961 - val_acc: 0.8971\n",
"Epoch 191/1000\n",
"157/157 [==============================] - 0s 213us/step - loss: 0.3284 - acc: 0.9299 - val_loss: 0.2943 - val_acc: 0.8971\n",
"Epoch 192/1000\n",
"157/157 [==============================] - 0s 184us/step - loss: 0.3265 - acc: 0.9299 - val_loss: 0.2917 - val_acc: 0.9118\n",
"Epoch 193/1000\n",
"157/157 [==============================] - 0s 369us/step - loss: 0.3259 - acc: 0.9299 - val_loss: 0.2908 - val_acc: 0.8971\n",
"Epoch 194/1000\n",
"157/157 [==============================] - 0s 218us/step - loss: 0.3226 - acc: 0.9299 - val_loss: 0.2889 - val_acc: 0.8971\n",
"Epoch 195/1000\n",
"157/157 [==============================] - 0s 203us/step - loss: 0.3237 - acc: 0.9236 - val_loss: 0.2873 - val_acc: 0.8971\n",
"Epoch 196/1000\n",
"157/157 [==============================] - 0s 207us/step - loss: 0.3194 - acc: 0.9236 - val_loss: 0.2857 - val_acc: 0.8971\n",
"Epoch 197/1000\n",
"157/157 [==============================] - 0s 291us/step - loss: 0.3173 - acc: 0.9236 - val_loss: 0.2830 - val_acc: 0.9118\n",
"Epoch 198/1000\n",
"157/157 [==============================] - 0s 235us/step - loss: 0.3165 - acc: 0.9299 - val_loss: 0.2819 - val_acc: 0.9118\n",
"Epoch 199/1000\n",
"157/157 [==============================] - 0s 160us/step - loss: 0.3166 - acc: 0.9236 - val_loss: 0.2805 - val_acc: 0.8971\n",
"Epoch 200/1000\n",
"157/157 [==============================] - 0s 308us/step - loss: 0.3128 - acc: 0.9236 - val_loss: 0.2790 - val_acc: 0.9118\n",
"Epoch 201/1000\n",
"157/157 [==============================] - 0s 149us/step - loss: 0.3109 - acc: 0.9299 - val_loss: 0.2772 - val_acc: 0.9118\n",
"Epoch 202/1000\n",
"157/157 [==============================] - 0s 189us/step - loss: 0.3092 - acc: 0.9236 - val_loss: 0.2755 - val_acc: 0.9118\n",
"Epoch 203/1000\n",
"157/157 [==============================] - 0s 230us/step - loss: 0.3076 - acc: 0.9236 - val_loss: 0.2736 - val_acc: 0.9118\n",
"Epoch 204/1000\n",
"157/157 [==============================] - 0s 123us/step - loss: 0.3056 - acc: 0.9236 - val_loss: 0.2724 - val_acc: 0.9118\n",
"Epoch 205/1000\n",
"157/157 [==============================] - 0s 118us/step - loss: 0.3046 - acc: 0.9236 - val_loss: 0.2703 - val_acc: 0.9118\n",
"Epoch 206/1000\n",
"157/157 [==============================] - 0s 319us/step - loss: 0.3018 - acc: 0.9299 - val_loss: 0.2682 - val_acc: 0.9118\n",
"Epoch 207/1000\n",
"157/157 [==============================] - 0s 156us/step - loss: 0.2998 - acc: 0.9427 - val_loss: 0.2670 - val_acc: 0.9118\n",
"Epoch 208/1000\n",
"157/157 [==============================] - 0s 128us/step - loss: 0.2988 - acc: 0.9299 - val_loss: 0.2651 - val_acc: 0.9118\n",
"Epoch 209/1000\n",
"157/157 [==============================] - 0s 188us/step - loss: 0.2970 - acc: 0.9299 - val_loss: 0.2626 - val_acc: 0.9118\n",
"Epoch 210/1000\n",
"157/157 [==============================] - 0s 141us/step - loss: 0.2945 - acc: 0.9427 - val_loss: 0.2626 - val_acc: 0.8971\n",
"Epoch 211/1000\n",
"157/157 [==============================] - 0s 152us/step - loss: 0.2932 - acc: 0.9299 - val_loss: 0.2599 - val_acc: 0.9118\n",
"Epoch 212/1000\n",
"157/157 [==============================] - 0s 317us/step - loss: 0.2919 - acc: 0.9427 - val_loss: 0.2590 - val_acc: 0.8971\n",
"Epoch 213/1000\n",
"157/157 [==============================] - 0s 241us/step - loss: 0.2898 - acc: 0.9236 - val_loss: 0.2560 - val_acc: 0.9118\n",
"Epoch 214/1000\n",
"157/157 [==============================] - 0s 396us/step - loss: 0.2892 - acc: 0.9427 - val_loss: 0.2547 - val_acc: 0.9118\n",
"Epoch 215/1000\n",
"157/157 [==============================] - 0s 317us/step - loss: 0.2863 - acc: 0.9427 - val_loss: 0.2529 - val_acc: 0.9118\n",
"Epoch 216/1000\n",
"157/157 [==============================] - 0s 254us/step - loss: 0.2870 - acc: 0.9363 - val_loss: 0.2518 - val_acc: 0.9118\n",
"Epoch 217/1000\n",
"157/157 [==============================] - 0s 255us/step - loss: 0.2839 - acc: 0.9363 - val_loss: 0.2511 - val_acc: 0.9118\n",
"Epoch 218/1000\n",
"157/157 [==============================] - 0s 144us/step - loss: 0.2816 - acc: 0.9363 - val_loss: 0.2490 - val_acc: 0.9118\n",
"Epoch 219/1000\n",
"157/157 [==============================] - 0s 228us/step - loss: 0.2807 - acc: 0.9427 - val_loss: 0.2484 - val_acc: 0.9118\n",
"Epoch 220/1000\n",
"157/157 [==============================] - 0s 140us/step - loss: 0.2789 - acc: 0.9427 - val_loss: 0.2471 - val_acc: 0.9118\n",
"Epoch 221/1000\n",
"157/157 [==============================] - 0s 267us/step - loss: 0.2770 - acc: 0.9363 - val_loss: 0.2438 - val_acc: 0.9118\n",
"Epoch 222/1000\n",
"157/157 [==============================] - 0s 251us/step - loss: 0.2760 - acc: 0.9427 - val_loss: 0.2423 - val_acc: 0.9118\n",
"Epoch 223/1000\n",
"157/157 [==============================] - 0s 298us/step - loss: 0.2745 - acc: 0.9299 - val_loss: 0.2407 - val_acc: 0.9118\n",
"Epoch 224/1000\n",
"157/157 [==============================] - 0s 218us/step - loss: 0.2726 - acc: 0.9490 - val_loss: 0.2411 - val_acc: 0.9118\n",
"Epoch 225/1000\n",
"157/157 [==============================] - 0s 293us/step - loss: 0.2707 - acc: 0.9363 - val_loss: 0.2380 - val_acc: 0.9118\n",
"Epoch 226/1000\n",
"157/157 [==============================] - 0s 157us/step - loss: 0.2703 - acc: 0.9427 - val_loss: 0.2386 - val_acc: 0.9118\n",
"Epoch 227/1000\n",
"157/157 [==============================] - 0s 213us/step - loss: 0.2681 - acc: 0.9490 - val_loss: 0.2374 - val_acc: 0.9118\n",
"Epoch 228/1000\n",
"157/157 [==============================] - 0s 149us/step - loss: 0.2680 - acc: 0.9363 - val_loss: 0.2365 - val_acc: 0.9118\n",
"Epoch 229/1000\n",
"157/157 [==============================] - 0s 156us/step - loss: 0.2668 - acc: 0.9236 - val_loss: 0.2342 - val_acc: 0.9118\n",
"Epoch 230/1000\n",
"157/157 [==============================] - 0s 213us/step - loss: 0.2652 - acc: 0.9363 - val_loss: 0.2324 - val_acc: 0.9118\n",
"Epoch 231/1000\n",
"157/157 [==============================] - 0s 170us/step - loss: 0.2634 - acc: 0.9490 - val_loss: 0.2320 - val_acc: 0.9118\n",
"Epoch 232/1000\n",
"157/157 [==============================] - 0s 258us/step - loss: 0.2624 - acc: 0.9427 - val_loss: 0.2310 - val_acc: 0.9118\n",
"Epoch 233/1000\n",
"157/157 [==============================] - 0s 245us/step - loss: 0.2627 - acc: 0.9427 - val_loss: 0.2299 - val_acc: 0.9118\n",
"Epoch 234/1000\n",
"157/157 [==============================] - 0s 396us/step - loss: 0.2597 - acc: 0.9490 - val_loss: 0.2293 - val_acc: 0.9118\n",
"Epoch 235/1000\n",
"157/157 [==============================] - 0s 192us/step - loss: 0.2584 - acc: 0.9490 - val_loss: 0.2292 - val_acc: 0.9118\n",
"Epoch 236/1000\n",
"157/157 [==============================] - 0s 294us/step - loss: 0.2579 - acc: 0.9427 - val_loss: 0.2271 - val_acc: 0.9118\n",
"Epoch 237/1000\n",
"157/157 [==============================] - 0s 200us/step - loss: 0.2564 - acc: 0.9427 - val_loss: 0.2262 - val_acc: 0.9118\n",
"Epoch 238/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"157/157 [==============================] - 0s 251us/step - loss: 0.2542 - acc: 0.9490 - val_loss: 0.2261 - val_acc: 0.9118\n",
"Epoch 239/1000\n",
"157/157 [==============================] - 0s 183us/step - loss: 0.2552 - acc: 0.9363 - val_loss: 0.2241 - val_acc: 0.9118\n",
"Epoch 240/1000\n",
"157/157 [==============================] - 0s 281us/step - loss: 0.2531 - acc: 0.9490 - val_loss: 0.2243 - val_acc: 0.9118\n",
"Epoch 241/1000\n",
"157/157 [==============================] - 0s 158us/step - loss: 0.2508 - acc: 0.9490 - val_loss: 0.2222 - val_acc: 0.9118\n",
"Epoch 242/1000\n",
"157/157 [==============================] - 0s 171us/step - loss: 0.2530 - acc: 0.9427 - val_loss: 0.2201 - val_acc: 0.9118\n",
"Epoch 243/1000\n",
"157/157 [==============================] - 0s 185us/step - loss: 0.2502 - acc: 0.9554 - val_loss: 0.2198 - val_acc: 0.9118\n",
"Epoch 244/1000\n",
"157/157 [==============================] - 0s 125us/step - loss: 0.2478 - acc: 0.9490 - val_loss: 0.2190 - val_acc: 0.9118\n",
"Epoch 245/1000\n",
"157/157 [==============================] - 0s 247us/step - loss: 0.2477 - acc: 0.9490 - val_loss: 0.2185 - val_acc: 0.9118\n",
"Epoch 246/1000\n",
"157/157 [==============================] - 0s 164us/step - loss: 0.2458 - acc: 0.9490 - val_loss: 0.2167 - val_acc: 0.9118\n",
"Epoch 247/1000\n",
"157/157 [==============================] - 0s 188us/step - loss: 0.2445 - acc: 0.9490 - val_loss: 0.2152 - val_acc: 0.9118\n",
"Epoch 248/1000\n",
"157/157 [==============================] - 0s 215us/step - loss: 0.2437 - acc: 0.9299 - val_loss: 0.2130 - val_acc: 0.9118\n",
"Epoch 249/1000\n",
"157/157 [==============================] - 0s 228us/step - loss: 0.2420 - acc: 0.9554 - val_loss: 0.2124 - val_acc: 0.9118\n",
"Epoch 250/1000\n",
"157/157 [==============================] - 0s 305us/step - loss: 0.2404 - acc: 0.9490 - val_loss: 0.2109 - val_acc: 0.9118\n",
"Epoch 251/1000\n",
"157/157 [==============================] - 0s 237us/step - loss: 0.2428 - acc: 0.9618 - val_loss: 0.2121 - val_acc: 0.9118\n",
"Epoch 252/1000\n",
"157/157 [==============================] - 0s 129us/step - loss: 0.2383 - acc: 0.9490 - val_loss: 0.2106 - val_acc: 0.9118\n",
"Epoch 253/1000\n",
"157/157 [==============================] - 0s 235us/step - loss: 0.2370 - acc: 0.9618 - val_loss: 0.2111 - val_acc: 0.9118\n",
"Epoch 254/1000\n",
"157/157 [==============================] - 0s 196us/step - loss: 0.2370 - acc: 0.9490 - val_loss: 0.2096 - val_acc: 0.9118\n",
"Epoch 255/1000\n",
"157/157 [==============================] - 0s 137us/step - loss: 0.2390 - acc: 0.9172 - val_loss: 0.2082 - val_acc: 0.9118\n",
"Epoch 256/1000\n",
"157/157 [==============================] - 0s 151us/step - loss: 0.2338 - acc: 0.9490 - val_loss: 0.2063 - val_acc: 0.9118\n",
"Epoch 257/1000\n",
"157/157 [==============================] - 0s 153us/step - loss: 0.2332 - acc: 0.9554 - val_loss: 0.2063 - val_acc: 0.9118\n",
"Epoch 258/1000\n",
"157/157 [==============================] - 0s 135us/step - loss: 0.2319 - acc: 0.9490 - val_loss: 0.2060 - val_acc: 0.9118\n",
"Epoch 259/1000\n",
"157/157 [==============================] - 0s 214us/step - loss: 0.2329 - acc: 0.9299 - val_loss: 0.2034 - val_acc: 0.9118\n",
"Epoch 260/1000\n",
"157/157 [==============================] - 0s 194us/step - loss: 0.2304 - acc: 0.9490 - val_loss: 0.2044 - val_acc: 0.9118\n",
"Epoch 261/1000\n",
"157/157 [==============================] - 0s 151us/step - loss: 0.2307 - acc: 0.9554 - val_loss: 0.2025 - val_acc: 0.9118\n",
"Epoch 262/1000\n",
"157/157 [==============================] - 0s 205us/step - loss: 0.2277 - acc: 0.9554 - val_loss: 0.2018 - val_acc: 0.9118\n",
"Epoch 263/1000\n",
"157/157 [==============================] - 0s 118us/step - loss: 0.2265 - acc: 0.9554 - val_loss: 0.2022 - val_acc: 0.9118\n",
"Epoch 264/1000\n",
"157/157 [==============================] - 0s 112us/step - loss: 0.2261 - acc: 0.9490 - val_loss: 0.2007 - val_acc: 0.9118\n",
"Epoch 265/1000\n",
"157/157 [==============================] - 0s 183us/step - loss: 0.2256 - acc: 0.9554 - val_loss: 0.1985 - val_acc: 0.9118\n",
"Epoch 266/1000\n",
"157/157 [==============================] - 0s 125us/step - loss: 0.2233 - acc: 0.9618 - val_loss: 0.1982 - val_acc: 0.9118\n",
"Epoch 267/1000\n",
"157/157 [==============================] - 0s 202us/step - loss: 0.2220 - acc: 0.9554 - val_loss: 0.1957 - val_acc: 0.9118\n",
"Epoch 268/1000\n",
"157/157 [==============================] - 0s 125us/step - loss: 0.2226 - acc: 0.9554 - val_loss: 0.1957 - val_acc: 0.9118\n",
"Epoch 269/1000\n",
"157/157 [==============================] - 0s 131us/step - loss: 0.2213 - acc: 0.9554 - val_loss: 0.1935 - val_acc: 0.9118\n",
"Epoch 270/1000\n",
"157/157 [==============================] - 0s 140us/step - loss: 0.2214 - acc: 0.9554 - val_loss: 0.1968 - val_acc: 0.9118\n",
"Epoch 271/1000\n",
"157/157 [==============================] - 0s 165us/step - loss: 0.2187 - acc: 0.9554 - val_loss: 0.1965 - val_acc: 0.9118\n",
"Epoch 272/1000\n",
"157/157 [==============================] - 0s 222us/step - loss: 0.2174 - acc: 0.9490 - val_loss: 0.1925 - val_acc: 0.9118\n",
"Epoch 273/1000\n",
"157/157 [==============================] - 0s 130us/step - loss: 0.2188 - acc: 0.9618 - val_loss: 0.1925 - val_acc: 0.9118\n",
"Epoch 274/1000\n",
"157/157 [==============================] - 0s 112us/step - loss: 0.2157 - acc: 0.9554 - val_loss: 0.1923 - val_acc: 0.9118\n",
"Epoch 275/1000\n",
"157/157 [==============================] - 0s 120us/step - loss: 0.2170 - acc: 0.9490 - val_loss: 0.1908 - val_acc: 0.9118\n",
"Epoch 276/1000\n",
"157/157 [==============================] - 0s 201us/step - loss: 0.2149 - acc: 0.9618 - val_loss: 0.1918 - val_acc: 0.9118\n",
"Epoch 277/1000\n",
"157/157 [==============================] - 0s 128us/step - loss: 0.2140 - acc: 0.9618 - val_loss: 0.1924 - val_acc: 0.9118\n",
"Epoch 278/1000\n",
"157/157 [==============================] - 0s 121us/step - loss: 0.2128 - acc: 0.9554 - val_loss: 0.1899 - val_acc: 0.9118\n",
"Epoch 279/1000\n",