1. 데이터셋 생성하기- 원본 데이터를 불러오거나 시뮬레이션을 통해 데이터를 생성합니다.
- 데이터로부터 훈련셋, 검증셋, 시험셋을 생성합니다.
- 이 때 딥러닝 모델의 학습 및 평가를 할 수 있도록 포맷 변환을 합니다.
X_train (50000, 28, 28)
X_train (50000,)
X_train (10000, 28, 28)
X_train (10000,)
2. 모델 구성하기- 시퀀스 모델을 생성한 뒤 필요한 레이어를 추가하여 구성합니다.
- 좀 더 복잡한 모델이 필요할 때는 케라스 함수 API를 사용합니다.
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 64) 50240
_________________________________________________________________
dense_1 (Dense) (None, 10) 650
=================================================================
Total params: 50,890
Trainable params: 50,890
Non-trainable params: 0
_________________________________________________________________
3. 모델 학습과정 설정하기- 학습하기 전에 학습에 대한 설정을 수행합니다.
- 손실 함수 및 최적화 방법을 정의합니다.
- 케라스에서는 compile() 함수를 사용합니다.
4. 모델 학습시키기- 훈련셋을 이용하여 구성한 모델로 학습시킵니다.
- 케라스에서는 fit() 함수를 사용합니다. #### 4.1 배치사이즈
- 몇 개를 처리하고 해답을 맞추는지를 의미함
- 100 : 100개를 처리하고 해답을 맞춤
- 1: 1개를 처리하고 해답을 맞춤
- 배치사이즈가 작을수록 갱신이 자주 발생함 #### 4.2 에폭
- 같은 데이터셋으로 반복적으로 가중치를 갱신하면서 학습
- 서로 다른 20문제를 1번 푸는 경우보다 같은 1문제를 20번 푸는 경우 정확도가 높다.
Train on 700 samples, validate on 300 samples
Epoch 1/1000
700/700 [==============================] - 1s 863us/sample - loss: 2.0943 - accuracy: 0.3229 - val_loss: 1.8196 - val_accuracy: 0.5200
Epoch 2/1000
700/700 [==============================] - 0s 225us/sample - loss: 1.6207 - accuracy: 0.6114 - val_loss: 1.4456 - val_accuracy: 0.6533
Epoch 3/1000
700/700 [==============================] - 0s 225us/sample - loss: 1.2658 - accuracy: 0.7100 - val_loss: 1.1702 - val_accuracy: 0.6933
Epoch 4/1000
700/700 [==============================] - 0s 231us/sample - loss: 1.0268 - accuracy: 0.7571 - val_loss: 1.0025 - val_accuracy: 0.7300
Epoch 5/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.8638 - accuracy: 0.7986 - val_loss: 0.8610 - val_accuracy: 0.7767
Epoch 6/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.7519 - accuracy: 0.8343 - val_loss: 0.7909 - val_accuracy: 0.7800
Epoch 7/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.6639 - accuracy: 0.8443 - val_loss: 0.7236 - val_accuracy: 0.8167
Epoch 8/1000
700/700 [==============================] - 0s 212us/sample - loss: 0.6037 - accuracy: 0.8586 - val_loss: 0.6915 - val_accuracy: 0.8067
Epoch 9/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.5489 - accuracy: 0.8743 - val_loss: 0.6389 - val_accuracy: 0.8333
Epoch 10/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.5093 - accuracy: 0.8786 - val_loss: 0.6091 - val_accuracy: 0.8500
Epoch 11/1000
700/700 [==============================] - 0s 235us/sample - loss: 0.4702 - accuracy: 0.8971 - val_loss: 0.5866 - val_accuracy: 0.8300
Epoch 12/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.4384 - accuracy: 0.9057 - val_loss: 0.5723 - val_accuracy: 0.8400
Epoch 13/1000
700/700 [==============================] - 0s 229us/sample - loss: 0.4153 - accuracy: 0.9100 - val_loss: 0.5589 - val_accuracy: 0.8333
Epoch 14/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.3880 - accuracy: 0.9243 - val_loss: 0.5365 - val_accuracy: 0.8400
Epoch 15/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.3690 - accuracy: 0.9186 - val_loss: 0.5218 - val_accuracy: 0.8367
Epoch 16/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.3497 - accuracy: 0.9329 - val_loss: 0.5167 - val_accuracy: 0.8333
Epoch 17/1000
700/700 [==============================] - 0s 212us/sample - loss: 0.3328 - accuracy: 0.9343 - val_loss: 0.5095 - val_accuracy: 0.8400
Epoch 18/1000
700/700 [==============================] - 0s 228us/sample - loss: 0.3165 - accuracy: 0.9414 - val_loss: 0.5019 - val_accuracy: 0.8300
Epoch 19/1000
700/700 [==============================] - 0s 224us/sample - loss: 0.3043 - accuracy: 0.9371 - val_loss: 0.4977 - val_accuracy: 0.8367
Epoch 20/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.2893 - accuracy: 0.9443 - val_loss: 0.4949 - val_accuracy: 0.8333
Epoch 21/1000
700/700 [==============================] - 0s 219us/sample - loss: 0.2765 - accuracy: 0.9443 - val_loss: 0.4894 - val_accuracy: 0.8367
Epoch 22/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.2639 - accuracy: 0.9514 - val_loss: 0.4856 - val_accuracy: 0.8400
Epoch 23/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.2556 - accuracy: 0.9529 - val_loss: 0.4870 - val_accuracy: 0.8267
Epoch 24/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.2435 - accuracy: 0.9514 - val_loss: 0.4845 - val_accuracy: 0.8300
Epoch 25/1000
700/700 [==============================] - 0s 228us/sample - loss: 0.2349 - accuracy: 0.9500 - val_loss: 0.4698 - val_accuracy: 0.8400
Epoch 26/1000
700/700 [==============================] - 0s 214us/sample - loss: 0.2254 - accuracy: 0.9586 - val_loss: 0.4820 - val_accuracy: 0.8300
Epoch 27/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.2177 - accuracy: 0.9557 - val_loss: 0.4720 - val_accuracy: 0.8400
Epoch 28/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.2080 - accuracy: 0.9600 - val_loss: 0.4739 - val_accuracy: 0.8367
Epoch 29/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.2031 - accuracy: 0.9600 - val_loss: 0.4700 - val_accuracy: 0.8333
Epoch 30/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.1952 - accuracy: 0.9643 - val_loss: 0.4737 - val_accuracy: 0.8333
Epoch 31/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.1865 - accuracy: 0.9671 - val_loss: 0.4670 - val_accuracy: 0.8400
Epoch 32/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.1817 - accuracy: 0.9671 - val_loss: 0.4693 - val_accuracy: 0.8300
Epoch 33/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.1748 - accuracy: 0.9671 - val_loss: 0.4678 - val_accuracy: 0.8333
Epoch 34/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.1690 - accuracy: 0.9700 - val_loss: 0.4681 - val_accuracy: 0.8400
Epoch 35/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.1627 - accuracy: 0.9700 - val_loss: 0.4740 - val_accuracy: 0.8300
Epoch 36/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.1577 - accuracy: 0.9743 - val_loss: 0.4705 - val_accuracy: 0.8533
Epoch 37/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.1529 - accuracy: 0.9714 - val_loss: 0.4738 - val_accuracy: 0.8500
Epoch 38/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.1477 - accuracy: 0.9771 - val_loss: 0.4736 - val_accuracy: 0.8500
Epoch 39/1000
700/700 [==============================] - 0s 217us/sample - loss: 0.1434 - accuracy: 0.9771 - val_loss: 0.4644 - val_accuracy: 0.8433
Epoch 40/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.1394 - accuracy: 0.9800 - val_loss: 0.4674 - val_accuracy: 0.8433
Epoch 41/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.1346 - accuracy: 0.9814 - val_loss: 0.4708 - val_accuracy: 0.8367
Epoch 42/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.1314 - accuracy: 0.9800 - val_loss: 0.4703 - val_accuracy: 0.8333
Epoch 43/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.1267 - accuracy: 0.9843 - val_loss: 0.4714 - val_accuracy: 0.8400
Epoch 44/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.1224 - accuracy: 0.9814 - val_loss: 0.4714 - val_accuracy: 0.8367
Epoch 45/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.1195 - accuracy: 0.9843 - val_loss: 0.4722 - val_accuracy: 0.8467
Epoch 46/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.1154 - accuracy: 0.9857 - val_loss: 0.4748 - val_accuracy: 0.8433
Epoch 47/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.1116 - accuracy: 0.9900 - val_loss: 0.4697 - val_accuracy: 0.8433
Epoch 48/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.1095 - accuracy: 0.9857 - val_loss: 0.4736 - val_accuracy: 0.8367
Epoch 49/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.1055 - accuracy: 0.9886 - val_loss: 0.4774 - val_accuracy: 0.8400
Epoch 50/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.1026 - accuracy: 0.9929 - val_loss: 0.4735 - val_accuracy: 0.8500
Epoch 51/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.1005 - accuracy: 0.9886 - val_loss: 0.4733 - val_accuracy: 0.8467
Epoch 52/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0972 - accuracy: 0.9914 - val_loss: 0.4748 - val_accuracy: 0.8400
Epoch 53/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0944 - accuracy: 0.9943 - val_loss: 0.4733 - val_accuracy: 0.8400
Epoch 54/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0926 - accuracy: 0.9943 - val_loss: 0.4712 - val_accuracy: 0.8467
Epoch 55/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0897 - accuracy: 0.9929 - val_loss: 0.4763 - val_accuracy: 0.8500
Epoch 56/1000
700/700 [==============================] - 0s 208us/sample - loss: 0.0871 - accuracy: 0.9943 - val_loss: 0.4812 - val_accuracy: 0.8433
Epoch 57/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0846 - accuracy: 0.9957 - val_loss: 0.4817 - val_accuracy: 0.8433
Epoch 58/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0831 - accuracy: 0.9971 - val_loss: 0.4809 - val_accuracy: 0.8433
Epoch 59/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0805 - accuracy: 0.9986 - val_loss: 0.4822 - val_accuracy: 0.8467
Epoch 60/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0787 - accuracy: 0.9986 - val_loss: 0.4793 - val_accuracy: 0.8500
Epoch 61/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0766 - accuracy: 0.9971 - val_loss: 0.4874 - val_accuracy: 0.8433
Epoch 62/1000
700/700 [==============================] - 0s 221us/sample - loss: 0.0749 - accuracy: 0.9971 - val_loss: 0.4861 - val_accuracy: 0.8467
Epoch 63/1000
700/700 [==============================] - 0s 221us/sample - loss: 0.0731 - accuracy: 0.9986 - val_loss: 0.4881 - val_accuracy: 0.8400
Epoch 64/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0712 - accuracy: 0.9986 - val_loss: 0.4875 - val_accuracy: 0.8467
Epoch 65/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0697 - accuracy: 0.9986 - val_loss: 0.4876 - val_accuracy: 0.8467
Epoch 66/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0677 - accuracy: 1.0000 - val_loss: 0.4935 - val_accuracy: 0.8467
Epoch 67/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0664 - accuracy: 1.0000 - val_loss: 0.4917 - val_accuracy: 0.8367
Epoch 68/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0651 - accuracy: 1.0000 - val_loss: 0.4915 - val_accuracy: 0.8467
Epoch 69/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0635 - accuracy: 1.0000 - val_loss: 0.4936 - val_accuracy: 0.8433
Epoch 70/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0619 - accuracy: 1.0000 - val_loss: 0.4899 - val_accuracy: 0.8467
Epoch 71/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0607 - accuracy: 1.0000 - val_loss: 0.4953 - val_accuracy: 0.8367
Epoch 72/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0595 - accuracy: 1.0000 - val_loss: 0.4920 - val_accuracy: 0.8467
Epoch 73/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0580 - accuracy: 1.0000 - val_loss: 0.4913 - val_accuracy: 0.8533
Epoch 74/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0570 - accuracy: 1.0000 - val_loss: 0.4934 - val_accuracy: 0.8467
Epoch 75/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0557 - accuracy: 1.0000 - val_loss: 0.4985 - val_accuracy: 0.8367
Epoch 76/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0546 - accuracy: 1.0000 - val_loss: 0.4956 - val_accuracy: 0.8500
Epoch 77/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0536 - accuracy: 1.0000 - val_loss: 0.4965 - val_accuracy: 0.8467
Epoch 78/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0525 - accuracy: 1.0000 - val_loss: 0.5003 - val_accuracy: 0.8467
Epoch 79/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0511 - accuracy: 1.0000 - val_loss: 0.4995 - val_accuracy: 0.8367
Epoch 80/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0503 - accuracy: 1.0000 - val_loss: 0.5021 - val_accuracy: 0.8467
Epoch 81/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0493 - accuracy: 1.0000 - val_loss: 0.5032 - val_accuracy: 0.8400
Epoch 82/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0483 - accuracy: 1.0000 - val_loss: 0.5022 - val_accuracy: 0.8433
Epoch 83/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0473 - accuracy: 1.0000 - val_loss: 0.5018 - val_accuracy: 0.8433
Epoch 84/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0465 - accuracy: 1.0000 - val_loss: 0.5014 - val_accuracy: 0.8433
Epoch 85/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0457 - accuracy: 1.0000 - val_loss: 0.5054 - val_accuracy: 0.8467
Epoch 86/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0449 - accuracy: 1.0000 - val_loss: 0.5042 - val_accuracy: 0.8467
Epoch 87/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0441 - accuracy: 1.0000 - val_loss: 0.5035 - val_accuracy: 0.8467
Epoch 88/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0431 - accuracy: 1.0000 - val_loss: 0.5060 - val_accuracy: 0.8467
Epoch 89/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0426 - accuracy: 1.0000 - val_loss: 0.5073 - val_accuracy: 0.8400
Epoch 90/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0419 - accuracy: 1.0000 - val_loss: 0.5077 - val_accuracy: 0.8400
Epoch 91/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0410 - accuracy: 1.0000 - val_loss: 0.5099 - val_accuracy: 0.8467
Epoch 92/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0405 - accuracy: 1.0000 - val_loss: 0.5087 - val_accuracy: 0.8400
Epoch 93/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0396 - accuracy: 1.0000 - val_loss: 0.5108 - val_accuracy: 0.8400
Epoch 94/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0390 - accuracy: 1.0000 - val_loss: 0.5091 - val_accuracy: 0.8433
Epoch 95/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0384 - accuracy: 1.0000 - val_loss: 0.5111 - val_accuracy: 0.8433
Epoch 96/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0378 - accuracy: 1.0000 - val_loss: 0.5137 - val_accuracy: 0.8433
Epoch 97/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0369 - accuracy: 1.0000 - val_loss: 0.5123 - val_accuracy: 0.8533
Epoch 98/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0366 - accuracy: 1.0000 - val_loss: 0.5151 - val_accuracy: 0.8400
Epoch 99/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0360 - accuracy: 1.0000 - val_loss: 0.5151 - val_accuracy: 0.8467
Epoch 100/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0355 - accuracy: 1.0000 - val_loss: 0.5135 - val_accuracy: 0.8433
Epoch 101/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0349 - accuracy: 1.0000 - val_loss: 0.5163 - val_accuracy: 0.8433
Epoch 102/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0344 - accuracy: 1.0000 - val_loss: 0.5165 - val_accuracy: 0.8467
Epoch 103/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0339 - accuracy: 1.0000 - val_loss: 0.5157 - val_accuracy: 0.8467
Epoch 104/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0333 - accuracy: 1.0000 - val_loss: 0.5163 - val_accuracy: 0.8433
Epoch 105/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0328 - accuracy: 1.0000 - val_loss: 0.5163 - val_accuracy: 0.8433
Epoch 106/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0322 - accuracy: 1.0000 - val_loss: 0.5163 - val_accuracy: 0.8500
Epoch 107/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0319 - accuracy: 1.0000 - val_loss: 0.5176 - val_accuracy: 0.8400
Epoch 108/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0314 - accuracy: 1.0000 - val_loss: 0.5197 - val_accuracy: 0.8367
Epoch 109/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0310 - accuracy: 1.0000 - val_loss: 0.5203 - val_accuracy: 0.8400
Epoch 110/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0306 - accuracy: 1.0000 - val_loss: 0.5205 - val_accuracy: 0.8433
Epoch 111/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0301 - accuracy: 1.0000 - val_loss: 0.5217 - val_accuracy: 0.8433
Epoch 112/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0298 - accuracy: 1.0000 - val_loss: 0.5207 - val_accuracy: 0.8400
Epoch 113/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0293 - accuracy: 1.0000 - val_loss: 0.5231 - val_accuracy: 0.8433
Epoch 114/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0289 - accuracy: 1.0000 - val_loss: 0.5219 - val_accuracy: 0.8433
Epoch 115/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0285 - accuracy: 1.0000 - val_loss: 0.5247 - val_accuracy: 0.8433
Epoch 116/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0282 - accuracy: 1.0000 - val_loss: 0.5248 - val_accuracy: 0.8467
Epoch 117/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0278 - accuracy: 1.0000 - val_loss: 0.5240 - val_accuracy: 0.8433
Epoch 118/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0273 - accuracy: 1.0000 - val_loss: 0.5252 - val_accuracy: 0.8500
Epoch 119/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0271 - accuracy: 1.0000 - val_loss: 0.5253 - val_accuracy: 0.8467
Epoch 120/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0267 - accuracy: 1.0000 - val_loss: 0.5268 - val_accuracy: 0.8500
Epoch 121/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0264 - accuracy: 1.0000 - val_loss: 0.5270 - val_accuracy: 0.8500
Epoch 122/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0261 - accuracy: 1.0000 - val_loss: 0.5278 - val_accuracy: 0.8467
Epoch 123/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0257 - accuracy: 1.0000 - val_loss: 0.5295 - val_accuracy: 0.8400
Epoch 124/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0254 - accuracy: 1.0000 - val_loss: 0.5298 - val_accuracy: 0.8467
Epoch 125/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0251 - accuracy: 1.0000 - val_loss: 0.5290 - val_accuracy: 0.8467
Epoch 126/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0248 - accuracy: 1.0000 - val_loss: 0.5298 - val_accuracy: 0.8467
Epoch 127/1000
700/700 [==============================] - 0s 211us/sample - loss: 0.0245 - accuracy: 1.0000 - val_loss: 0.5311 - val_accuracy: 0.8467
Epoch 128/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0243 - accuracy: 1.0000 - val_loss: 0.5323 - val_accuracy: 0.8467
Epoch 129/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0239 - accuracy: 1.0000 - val_loss: 0.5336 - val_accuracy: 0.8533
Epoch 130/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0237 - accuracy: 1.0000 - val_loss: 0.5324 - val_accuracy: 0.8467
Epoch 131/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0234 - accuracy: 1.0000 - val_loss: 0.5340 - val_accuracy: 0.8500
Epoch 132/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0231 - accuracy: 1.0000 - val_loss: 0.5341 - val_accuracy: 0.8433
Epoch 133/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0228 - accuracy: 1.0000 - val_loss: 0.5339 - val_accuracy: 0.8400
Epoch 134/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0226 - accuracy: 1.0000 - val_loss: 0.5353 - val_accuracy: 0.8433
Epoch 135/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0223 - accuracy: 1.0000 - val_loss: 0.5357 - val_accuracy: 0.8400
Epoch 136/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0221 - accuracy: 1.0000 - val_loss: 0.5360 - val_accuracy: 0.8433
Epoch 137/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0219 - accuracy: 1.0000 - val_loss: 0.5356 - val_accuracy: 0.8433
Epoch 138/1000
700/700 [==============================] - 0s 224us/sample - loss: 0.0216 - accuracy: 1.0000 - val_loss: 0.5364 - val_accuracy: 0.8467
Epoch 139/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0214 - accuracy: 1.0000 - val_loss: 0.5363 - val_accuracy: 0.8433
Epoch 140/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0211 - accuracy: 1.0000 - val_loss: 0.5389 - val_accuracy: 0.8433
Epoch 141/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0209 - accuracy: 1.0000 - val_loss: 0.5379 - val_accuracy: 0.8500
Epoch 142/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0207 - accuracy: 1.0000 - val_loss: 0.5383 - val_accuracy: 0.8433
Epoch 143/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0205 - accuracy: 1.0000 - val_loss: 0.5391 - val_accuracy: 0.8467
Epoch 144/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0203 - accuracy: 1.0000 - val_loss: 0.5403 - val_accuracy: 0.8467
Epoch 145/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0201 - accuracy: 1.0000 - val_loss: 0.5404 - val_accuracy: 0.8433
Epoch 146/1000
700/700 [==============================] - 0s 211us/sample - loss: 0.0198 - accuracy: 1.0000 - val_loss: 0.5402 - val_accuracy: 0.8433
Epoch 147/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0196 - accuracy: 1.0000 - val_loss: 0.5411 - val_accuracy: 0.8500
Epoch 148/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0194 - accuracy: 1.0000 - val_loss: 0.5415 - val_accuracy: 0.8433
Epoch 149/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0192 - accuracy: 1.0000 - val_loss: 0.5430 - val_accuracy: 0.8467
Epoch 150/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0191 - accuracy: 1.0000 - val_loss: 0.5437 - val_accuracy: 0.8500
Epoch 151/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0189 - accuracy: 1.0000 - val_loss: 0.5431 - val_accuracy: 0.8433
Epoch 152/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0187 - accuracy: 1.0000 - val_loss: 0.5447 - val_accuracy: 0.8467
Epoch 153/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0185 - accuracy: 1.0000 - val_loss: 0.5451 - val_accuracy: 0.8467
Epoch 154/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0183 - accuracy: 1.0000 - val_loss: 0.5458 - val_accuracy: 0.8467
Epoch 155/1000
700/700 [==============================] - 0s 228us/sample - loss: 0.0181 - accuracy: 1.0000 - val_loss: 0.5451 - val_accuracy: 0.8500
Epoch 156/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.0180 - accuracy: 1.0000 - val_loss: 0.5463 - val_accuracy: 0.8500
Epoch 157/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0178 - accuracy: 1.0000 - val_loss: 0.5463 - val_accuracy: 0.8500
Epoch 158/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0176 - accuracy: 1.0000 - val_loss: 0.5486 - val_accuracy: 0.8500
Epoch 159/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0175 - accuracy: 1.0000 - val_loss: 0.5479 - val_accuracy: 0.8500
Epoch 160/1000
700/700 [==============================] - 0s 214us/sample - loss: 0.0173 - accuracy: 1.0000 - val_loss: 0.5492 - val_accuracy: 0.8467
Epoch 161/1000
700/700 [==============================] - 0s 219us/sample - loss: 0.0172 - accuracy: 1.0000 - val_loss: 0.5491 - val_accuracy: 0.8500
Epoch 162/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0170 - accuracy: 1.0000 - val_loss: 0.5489 - val_accuracy: 0.8500
Epoch 163/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0168 - accuracy: 1.0000 - val_loss: 0.5489 - val_accuracy: 0.8467
Epoch 164/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0167 - accuracy: 1.0000 - val_loss: 0.5489 - val_accuracy: 0.8467
Epoch 165/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0166 - accuracy: 1.0000 - val_loss: 0.5515 - val_accuracy: 0.8467
Epoch 166/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0164 - accuracy: 1.0000 - val_loss: 0.5521 - val_accuracy: 0.8467
Epoch 167/1000
700/700 [==============================] - 0s 225us/sample - loss: 0.0162 - accuracy: 1.0000 - val_loss: 0.5525 - val_accuracy: 0.8467
Epoch 168/1000
700/700 [==============================] - 0s 239us/sample - loss: 0.0161 - accuracy: 1.0000 - val_loss: 0.5527 - val_accuracy: 0.8500
Epoch 169/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0160 - accuracy: 1.0000 - val_loss: 0.5534 - val_accuracy: 0.8467
Epoch 170/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0158 - accuracy: 1.0000 - val_loss: 0.5539 - val_accuracy: 0.8467
Epoch 171/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0157 - accuracy: 1.0000 - val_loss: 0.5536 - val_accuracy: 0.8467
Epoch 172/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0155 - accuracy: 1.0000 - val_loss: 0.5538 - val_accuracy: 0.8467
Epoch 173/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0154 - accuracy: 1.0000 - val_loss: 0.5542 - val_accuracy: 0.8467
Epoch 174/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0153 - accuracy: 1.0000 - val_loss: 0.5544 - val_accuracy: 0.8467
Epoch 175/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0152 - accuracy: 1.0000 - val_loss: 0.5550 - val_accuracy: 0.8467
Epoch 176/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0150 - accuracy: 1.0000 - val_loss: 0.5550 - val_accuracy: 0.8467
Epoch 177/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0149 - accuracy: 1.0000 - val_loss: 0.5559 - val_accuracy: 0.8467
Epoch 178/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0148 - accuracy: 1.0000 - val_loss: 0.5561 - val_accuracy: 0.8500
Epoch 179/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0147 - accuracy: 1.0000 - val_loss: 0.5567 - val_accuracy: 0.8467
Epoch 180/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0145 - accuracy: 1.0000 - val_loss: 0.5578 - val_accuracy: 0.8467
Epoch 181/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0144 - accuracy: 1.0000 - val_loss: 0.5568 - val_accuracy: 0.8467
Epoch 182/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0143 - accuracy: 1.0000 - val_loss: 0.5585 - val_accuracy: 0.8500
Epoch 183/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0142 - accuracy: 1.0000 - val_loss: 0.5594 - val_accuracy: 0.8467
Epoch 184/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0141 - accuracy: 1.0000 - val_loss: 0.5593 - val_accuracy: 0.8467
Epoch 185/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0140 - accuracy: 1.0000 - val_loss: 0.5600 - val_accuracy: 0.8467
Epoch 186/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0139 - accuracy: 1.0000 - val_loss: 0.5605 - val_accuracy: 0.8467
Epoch 187/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0138 - accuracy: 1.0000 - val_loss: 0.5605 - val_accuracy: 0.8467
Epoch 188/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0137 - accuracy: 1.0000 - val_loss: 0.5611 - val_accuracy: 0.8467
Epoch 189/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0136 - accuracy: 1.0000 - val_loss: 0.5613 - val_accuracy: 0.8467
Epoch 190/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0134 - accuracy: 1.0000 - val_loss: 0.5621 - val_accuracy: 0.8467
Epoch 191/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0134 - accuracy: 1.0000 - val_loss: 0.5628 - val_accuracy: 0.8467
Epoch 192/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0133 - accuracy: 1.0000 - val_loss: 0.5630 - val_accuracy: 0.8467
Epoch 193/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0131 - accuracy: 1.0000 - val_loss: 0.5629 - val_accuracy: 0.8500
Epoch 194/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0131 - accuracy: 1.0000 - val_loss: 0.5629 - val_accuracy: 0.8533
Epoch 195/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0129 - accuracy: 1.0000 - val_loss: 0.5639 - val_accuracy: 0.8467
Epoch 196/1000
700/700 [==============================] - 0s 212us/sample - loss: 0.0129 - accuracy: 1.0000 - val_loss: 0.5637 - val_accuracy: 0.8467
Epoch 197/1000
700/700 [==============================] - 0s 248us/sample - loss: 0.0128 - accuracy: 1.0000 - val_loss: 0.5649 - val_accuracy: 0.8500
Epoch 198/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0127 - accuracy: 1.0000 - val_loss: 0.5654 - val_accuracy: 0.8467
Epoch 199/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0126 - accuracy: 1.0000 - val_loss: 0.5656 - val_accuracy: 0.8467
Epoch 200/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0125 - accuracy: 1.0000 - val_loss: 0.5664 - val_accuracy: 0.8467
Epoch 201/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0124 - accuracy: 1.0000 - val_loss: 0.5663 - val_accuracy: 0.8467
Epoch 202/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0123 - accuracy: 1.0000 - val_loss: 0.5662 - val_accuracy: 0.8467
Epoch 203/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0122 - accuracy: 1.0000 - val_loss: 0.5670 - val_accuracy: 0.8467
Epoch 204/1000
700/700 [==============================] - 0s 214us/sample - loss: 0.0121 - accuracy: 1.0000 - val_loss: 0.5676 - val_accuracy: 0.8467
Epoch 205/1000
700/700 [==============================] - 0s 224us/sample - loss: 0.0121 - accuracy: 1.0000 - val_loss: 0.5681 - val_accuracy: 0.8500
Epoch 206/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0120 - accuracy: 1.0000 - val_loss: 0.5681 - val_accuracy: 0.8500
Epoch 207/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0119 - accuracy: 1.0000 - val_loss: 0.5676 - val_accuracy: 0.8500
Epoch 208/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0118 - accuracy: 1.0000 - val_loss: 0.5684 - val_accuracy: 0.8500
Epoch 209/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0117 - accuracy: 1.0000 - val_loss: 0.5694 - val_accuracy: 0.8467
Epoch 210/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0116 - accuracy: 1.0000 - val_loss: 0.5700 - val_accuracy: 0.8467
Epoch 211/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0116 - accuracy: 1.0000 - val_loss: 0.5703 - val_accuracy: 0.8467
Epoch 212/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0115 - accuracy: 1.0000 - val_loss: 0.5710 - val_accuracy: 0.8433
Epoch 213/1000
700/700 [==============================] - 0s 211us/sample - loss: 0.0114 - accuracy: 1.0000 - val_loss: 0.5712 - val_accuracy: 0.8467
Epoch 214/1000
700/700 [==============================] - 0s 208us/sample - loss: 0.0113 - accuracy: 1.0000 - val_loss: 0.5710 - val_accuracy: 0.8467
Epoch 215/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0113 - accuracy: 1.0000 - val_loss: 0.5717 - val_accuracy: 0.8467
Epoch 216/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0112 - accuracy: 1.0000 - val_loss: 0.5721 - val_accuracy: 0.8533
Epoch 217/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0111 - accuracy: 1.0000 - val_loss: 0.5730 - val_accuracy: 0.8467
Epoch 218/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0110 - accuracy: 1.0000 - val_loss: 0.5730 - val_accuracy: 0.8467
Epoch 219/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0110 - accuracy: 1.0000 - val_loss: 0.5734 - val_accuracy: 0.8500
Epoch 220/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0109 - accuracy: 1.0000 - val_loss: 0.5738 - val_accuracy: 0.8500
Epoch 221/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0108 - accuracy: 1.0000 - val_loss: 0.5732 - val_accuracy: 0.8500
Epoch 222/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0108 - accuracy: 1.0000 - val_loss: 0.5739 - val_accuracy: 0.8500
Epoch 223/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0107 - accuracy: 1.0000 - val_loss: 0.5752 - val_accuracy: 0.8467
Epoch 224/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0106 - accuracy: 1.0000 - val_loss: 0.5752 - val_accuracy: 0.8533
Epoch 225/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0105 - accuracy: 1.0000 - val_loss: 0.5755 - val_accuracy: 0.8533
Epoch 226/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0105 - accuracy: 1.0000 - val_loss: 0.5755 - val_accuracy: 0.8500
Epoch 227/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0104 - accuracy: 1.0000 - val_loss: 0.5759 - val_accuracy: 0.8467
Epoch 228/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0104 - accuracy: 1.0000 - val_loss: 0.5760 - val_accuracy: 0.8467
Epoch 229/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0103 - accuracy: 1.0000 - val_loss: 0.5758 - val_accuracy: 0.8500
Epoch 230/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0102 - accuracy: 1.0000 - val_loss: 0.5764 - val_accuracy: 0.8467
Epoch 231/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0102 - accuracy: 1.0000 - val_loss: 0.5770 - val_accuracy: 0.8500
Epoch 232/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0101 - accuracy: 1.0000 - val_loss: 0.5772 - val_accuracy: 0.8533
Epoch 233/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0100 - accuracy: 1.0000 - val_loss: 0.5774 - val_accuracy: 0.8500
Epoch 234/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0100 - accuracy: 1.0000 - val_loss: 0.5778 - val_accuracy: 0.8500
Epoch 235/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0099 - accuracy: 1.0000 - val_loss: 0.5789 - val_accuracy: 0.8500
Epoch 236/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0099 - accuracy: 1.0000 - val_loss: 0.5791 - val_accuracy: 0.8467
Epoch 237/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0098 - accuracy: 1.0000 - val_loss: 0.5793 - val_accuracy: 0.8533
Epoch 238/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0097 - accuracy: 1.0000 - val_loss: 0.5796 - val_accuracy: 0.8467
Epoch 239/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0097 - accuracy: 1.0000 - val_loss: 0.5799 - val_accuracy: 0.8500
Epoch 240/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0096 - accuracy: 1.0000 - val_loss: 0.5803 - val_accuracy: 0.8500
Epoch 241/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0096 - accuracy: 1.0000 - val_loss: 0.5801 - val_accuracy: 0.8500
Epoch 242/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0095 - accuracy: 1.0000 - val_loss: 0.5806 - val_accuracy: 0.8500
Epoch 243/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0095 - accuracy: 1.0000 - val_loss: 0.5812 - val_accuracy: 0.8467
Epoch 244/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0094 - accuracy: 1.0000 - val_loss: 0.5821 - val_accuracy: 0.8500
Epoch 245/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0094 - accuracy: 1.0000 - val_loss: 0.5819 - val_accuracy: 0.8500
Epoch 246/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0093 - accuracy: 1.0000 - val_loss: 0.5821 - val_accuracy: 0.8500
Epoch 247/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0093 - accuracy: 1.0000 - val_loss: 0.5828 - val_accuracy: 0.8500
Epoch 248/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0092 - accuracy: 1.0000 - val_loss: 0.5832 - val_accuracy: 0.8467
Epoch 249/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0091 - accuracy: 1.0000 - val_loss: 0.5830 - val_accuracy: 0.8533
Epoch 250/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0091 - accuracy: 1.0000 - val_loss: 0.5837 - val_accuracy: 0.8533
Epoch 251/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0090 - accuracy: 1.0000 - val_loss: 0.5836 - val_accuracy: 0.8500
Epoch 252/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0090 - accuracy: 1.0000 - val_loss: 0.5837 - val_accuracy: 0.8533
Epoch 253/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0089 - accuracy: 1.0000 - val_loss: 0.5841 - val_accuracy: 0.8533
Epoch 254/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0089 - accuracy: 1.0000 - val_loss: 0.5848 - val_accuracy: 0.8500
Epoch 255/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0089 - accuracy: 1.0000 - val_loss: 0.5854 - val_accuracy: 0.8500
Epoch 256/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0088 - accuracy: 1.0000 - val_loss: 0.5856 - val_accuracy: 0.8500
Epoch 257/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0087 - accuracy: 1.0000 - val_loss: 0.5855 - val_accuracy: 0.8500
Epoch 258/1000
700/700 [==============================] - 0s 208us/sample - loss: 0.0087 - accuracy: 1.0000 - val_loss: 0.5862 - val_accuracy: 0.8500
Epoch 259/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0087 - accuracy: 1.0000 - val_loss: 0.5866 - val_accuracy: 0.8500
Epoch 260/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0086 - accuracy: 1.0000 - val_loss: 0.5869 - val_accuracy: 0.8467
Epoch 261/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0086 - accuracy: 1.0000 - val_loss: 0.5869 - val_accuracy: 0.8500
Epoch 262/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0085 - accuracy: 1.0000 - val_loss: 0.5871 - val_accuracy: 0.8500
Epoch 263/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0085 - accuracy: 1.0000 - val_loss: 0.5873 - val_accuracy: 0.8533
Epoch 264/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0084 - accuracy: 1.0000 - val_loss: 0.5875 - val_accuracy: 0.8533
Epoch 265/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0084 - accuracy: 1.0000 - val_loss: 0.5884 - val_accuracy: 0.8500
Epoch 266/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0083 - accuracy: 1.0000 - val_loss: 0.5886 - val_accuracy: 0.8500
Epoch 267/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0083 - accuracy: 1.0000 - val_loss: 0.5892 - val_accuracy: 0.8500
Epoch 268/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0083 - accuracy: 1.0000 - val_loss: 0.5893 - val_accuracy: 0.8500
Epoch 269/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0082 - accuracy: 1.0000 - val_loss: 0.5892 - val_accuracy: 0.8500
Epoch 270/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0082 - accuracy: 1.0000 - val_loss: 0.5897 - val_accuracy: 0.8500
Epoch 271/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0081 - accuracy: 1.0000 - val_loss: 0.5902 - val_accuracy: 0.8500
Epoch 272/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0081 - accuracy: 1.0000 - val_loss: 0.5905 - val_accuracy: 0.8500
Epoch 273/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0080 - accuracy: 1.0000 - val_loss: 0.5909 - val_accuracy: 0.8500
Epoch 274/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0080 - accuracy: 1.0000 - val_loss: 0.5912 - val_accuracy: 0.8500
Epoch 275/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0080 - accuracy: 1.0000 - val_loss: 0.5916 - val_accuracy: 0.8500
Epoch 276/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0079 - accuracy: 1.0000 - val_loss: 0.5916 - val_accuracy: 0.8500
Epoch 277/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0079 - accuracy: 1.0000 - val_loss: 0.5920 - val_accuracy: 0.8500
Epoch 278/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0078 - accuracy: 1.0000 - val_loss: 0.5923 - val_accuracy: 0.8500
Epoch 279/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0078 - accuracy: 1.0000 - val_loss: 0.5926 - val_accuracy: 0.8500
Epoch 280/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0078 - accuracy: 1.0000 - val_loss: 0.5931 - val_accuracy: 0.8500
Epoch 281/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0077 - accuracy: 1.0000 - val_loss: 0.5936 - val_accuracy: 0.8500
Epoch 282/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0077 - accuracy: 1.0000 - val_loss: 0.5934 - val_accuracy: 0.8500
Epoch 283/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0077 - accuracy: 1.0000 - val_loss: 0.5940 - val_accuracy: 0.8500
Epoch 284/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0076 - accuracy: 1.0000 - val_loss: 0.5944 - val_accuracy: 0.8500
Epoch 285/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0076 - accuracy: 1.0000 - val_loss: 0.5946 - val_accuracy: 0.8500
Epoch 286/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0075 - accuracy: 1.0000 - val_loss: 0.5952 - val_accuracy: 0.8500
Epoch 287/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0075 - accuracy: 1.0000 - val_loss: 0.5952 - val_accuracy: 0.8500
Epoch 288/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0075 - accuracy: 1.0000 - val_loss: 0.5950 - val_accuracy: 0.8500
Epoch 289/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0074 - accuracy: 1.0000 - val_loss: 0.5957 - val_accuracy: 0.8500
Epoch 290/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0074 - accuracy: 1.0000 - val_loss: 0.5958 - val_accuracy: 0.8500
Epoch 291/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0074 - accuracy: 1.0000 - val_loss: 0.5960 - val_accuracy: 0.8500
Epoch 292/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0073 - accuracy: 1.0000 - val_loss: 0.5961 - val_accuracy: 0.8500
Epoch 293/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0073 - accuracy: 1.0000 - val_loss: 0.5966 - val_accuracy: 0.8500
Epoch 294/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0073 - accuracy: 1.0000 - val_loss: 0.5968 - val_accuracy: 0.8500
Epoch 295/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0072 - accuracy: 1.0000 - val_loss: 0.5969 - val_accuracy: 0.8500
Epoch 296/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0072 - accuracy: 1.0000 - val_loss: 0.5971 - val_accuracy: 0.8500
Epoch 297/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0072 - accuracy: 1.0000 - val_loss: 0.5973 - val_accuracy: 0.8500
Epoch 298/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0071 - accuracy: 1.0000 - val_loss: 0.5977 - val_accuracy: 0.8500
Epoch 299/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0071 - accuracy: 1.0000 - val_loss: 0.5979 - val_accuracy: 0.8500
Epoch 300/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0071 - accuracy: 1.0000 - val_loss: 0.5984 - val_accuracy: 0.8500
Epoch 301/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0070 - accuracy: 1.0000 - val_loss: 0.5993 - val_accuracy: 0.8500
Epoch 302/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0070 - accuracy: 1.0000 - val_loss: 0.5991 - val_accuracy: 0.8500
Epoch 303/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0070 - accuracy: 1.0000 - val_loss: 0.5992 - val_accuracy: 0.8500
Epoch 304/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0069 - accuracy: 1.0000 - val_loss: 0.5995 - val_accuracy: 0.8500
Epoch 305/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0069 - accuracy: 1.0000 - val_loss: 0.5998 - val_accuracy: 0.8500
Epoch 306/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0069 - accuracy: 1.0000 - val_loss: 0.5999 - val_accuracy: 0.8500
Epoch 307/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0068 - accuracy: 1.0000 - val_loss: 0.6003 - val_accuracy: 0.8500
Epoch 308/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0068 - accuracy: 1.0000 - val_loss: 0.6004 - val_accuracy: 0.8500
Epoch 309/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0068 - accuracy: 1.0000 - val_loss: 0.6006 - val_accuracy: 0.8500
Epoch 310/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0068 - accuracy: 1.0000 - val_loss: 0.6010 - val_accuracy: 0.8500
Epoch 311/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0067 - accuracy: 1.0000 - val_loss: 0.6013 - val_accuracy: 0.8500
Epoch 312/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0067 - accuracy: 1.0000 - val_loss: 0.6014 - val_accuracy: 0.8500
Epoch 313/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0067 - accuracy: 1.0000 - val_loss: 0.6015 - val_accuracy: 0.8500
Epoch 314/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0066 - accuracy: 1.0000 - val_loss: 0.6020 - val_accuracy: 0.8500
Epoch 315/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0066 - accuracy: 1.0000 - val_loss: 0.6026 - val_accuracy: 0.8500
Epoch 316/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0066 - accuracy: 1.0000 - val_loss: 0.6030 - val_accuracy: 0.8500
Epoch 317/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0065 - accuracy: 1.0000 - val_loss: 0.6031 - val_accuracy: 0.8500
Epoch 318/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0065 - accuracy: 1.0000 - val_loss: 0.6034 - val_accuracy: 0.8500
Epoch 319/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0065 - accuracy: 1.0000 - val_loss: 0.6035 - val_accuracy: 0.8500
Epoch 320/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0065 - accuracy: 1.0000 - val_loss: 0.6036 - val_accuracy: 0.8500
Epoch 321/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0064 - accuracy: 1.0000 - val_loss: 0.6043 - val_accuracy: 0.8500
Epoch 322/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0064 - accuracy: 1.0000 - val_loss: 0.6044 - val_accuracy: 0.8500
Epoch 323/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0064 - accuracy: 1.0000 - val_loss: 0.6046 - val_accuracy: 0.8500
Epoch 324/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0064 - accuracy: 1.0000 - val_loss: 0.6047 - val_accuracy: 0.8500
Epoch 325/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0063 - accuracy: 1.0000 - val_loss: 0.6051 - val_accuracy: 0.8500
Epoch 326/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0063 - accuracy: 1.0000 - val_loss: 0.6052 - val_accuracy: 0.8500
Epoch 327/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0063 - accuracy: 1.0000 - val_loss: 0.6057 - val_accuracy: 0.8500
Epoch 328/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0063 - accuracy: 1.0000 - val_loss: 0.6057 - val_accuracy: 0.8500
Epoch 329/1000
700/700 [==============================] - 0s 228us/sample - loss: 0.0062 - accuracy: 1.0000 - val_loss: 0.6061 - val_accuracy: 0.8500
Epoch 330/1000
700/700 [==============================] - 0s 208us/sample - loss: 0.0062 - accuracy: 1.0000 - val_loss: 0.6062 - val_accuracy: 0.8500
Epoch 331/1000
700/700 [==============================] - 0s 218us/sample - loss: 0.0062 - accuracy: 1.0000 - val_loss: 0.6061 - val_accuracy: 0.8500
Epoch 332/1000
700/700 [==============================] - 0s 227us/sample - loss: 0.0061 - accuracy: 1.0000 - val_loss: 0.6063 - val_accuracy: 0.8500
Epoch 333/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0061 - accuracy: 1.0000 - val_loss: 0.6067 - val_accuracy: 0.8500
Epoch 334/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0061 - accuracy: 1.0000 - val_loss: 0.6068 - val_accuracy: 0.8500
Epoch 335/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0061 - accuracy: 1.0000 - val_loss: 0.6075 - val_accuracy: 0.8500
Epoch 336/1000
700/700 [==============================] - 0s 219us/sample - loss: 0.0061 - accuracy: 1.0000 - val_loss: 0.6079 - val_accuracy: 0.8500
Epoch 337/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0060 - accuracy: 1.0000 - val_loss: 0.6081 - val_accuracy: 0.8500
Epoch 338/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0060 - accuracy: 1.0000 - val_loss: 0.6084 - val_accuracy: 0.8500
Epoch 339/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0060 - accuracy: 1.0000 - val_loss: 0.6084 - val_accuracy: 0.8500
Epoch 340/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.0060 - accuracy: 1.0000 - val_loss: 0.6087 - val_accuracy: 0.8500
Epoch 341/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0059 - accuracy: 1.0000 - val_loss: 0.6090 - val_accuracy: 0.8500
Epoch 342/1000
700/700 [==============================] - 0s 228us/sample - loss: 0.0059 - accuracy: 1.0000 - val_loss: 0.6094 - val_accuracy: 0.8500
Epoch 343/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0059 - accuracy: 1.0000 - val_loss: 0.6097 - val_accuracy: 0.8500
Epoch 344/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0059 - accuracy: 1.0000 - val_loss: 0.6097 - val_accuracy: 0.8500
Epoch 345/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0058 - accuracy: 1.0000 - val_loss: 0.6101 - val_accuracy: 0.8500
Epoch 346/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0058 - accuracy: 1.0000 - val_loss: 0.6103 - val_accuracy: 0.8500
Epoch 347/1000
700/700 [==============================] - 0s 214us/sample - loss: 0.0058 - accuracy: 1.0000 - val_loss: 0.6102 - val_accuracy: 0.8500
Epoch 348/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0058 - accuracy: 1.0000 - val_loss: 0.6104 - val_accuracy: 0.8500
Epoch 349/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0057 - accuracy: 1.0000 - val_loss: 0.6110 - val_accuracy: 0.8500
Epoch 350/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0057 - accuracy: 1.0000 - val_loss: 0.6113 - val_accuracy: 0.8500
Epoch 351/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0057 - accuracy: 1.0000 - val_loss: 0.6115 - val_accuracy: 0.8500
Epoch 352/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0057 - accuracy: 1.0000 - val_loss: 0.6116 - val_accuracy: 0.8500
Epoch 353/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0057 - accuracy: 1.0000 - val_loss: 0.6119 - val_accuracy: 0.8500
Epoch 354/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0056 - accuracy: 1.0000 - val_loss: 0.6123 - val_accuracy: 0.8500
Epoch 355/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0056 - accuracy: 1.0000 - val_loss: 0.6124 - val_accuracy: 0.8500
Epoch 356/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0056 - accuracy: 1.0000 - val_loss: 0.6126 - val_accuracy: 0.8500
Epoch 357/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0056 - accuracy: 1.0000 - val_loss: 0.6127 - val_accuracy: 0.8500
Epoch 358/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0055 - accuracy: 1.0000 - val_loss: 0.6129 - val_accuracy: 0.8500
Epoch 359/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0055 - accuracy: 1.0000 - val_loss: 0.6131 - val_accuracy: 0.8500
Epoch 360/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0055 - accuracy: 1.0000 - val_loss: 0.6130 - val_accuracy: 0.8500
Epoch 361/1000
700/700 [==============================] - 0s 238us/sample - loss: 0.0055 - accuracy: 1.0000 - val_loss: 0.6137 - val_accuracy: 0.8500
Epoch 362/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0055 - accuracy: 1.0000 - val_loss: 0.6139 - val_accuracy: 0.8500
Epoch 363/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0054 - accuracy: 1.0000 - val_loss: 0.6141 - val_accuracy: 0.8500
Epoch 364/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0054 - accuracy: 1.0000 - val_loss: 0.6143 - val_accuracy: 0.8500
Epoch 365/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0054 - accuracy: 1.0000 - val_loss: 0.6145 - val_accuracy: 0.8500
Epoch 366/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0054 - accuracy: 1.0000 - val_loss: 0.6148 - val_accuracy: 0.8500
Epoch 367/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0054 - accuracy: 1.0000 - val_loss: 0.6149 - val_accuracy: 0.8500
Epoch 368/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0053 - accuracy: 1.0000 - val_loss: 0.6152 - val_accuracy: 0.8500
Epoch 369/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0053 - accuracy: 1.0000 - val_loss: 0.6154 - val_accuracy: 0.8500
Epoch 370/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0053 - accuracy: 1.0000 - val_loss: 0.6155 - val_accuracy: 0.8500
Epoch 371/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0053 - accuracy: 1.0000 - val_loss: 0.6155 - val_accuracy: 0.8500
Epoch 372/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0053 - accuracy: 1.0000 - val_loss: 0.6158 - val_accuracy: 0.8500
Epoch 373/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0053 - accuracy: 1.0000 - val_loss: 0.6161 - val_accuracy: 0.8500
Epoch 374/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0052 - accuracy: 1.0000 - val_loss: 0.6163 - val_accuracy: 0.8500
Epoch 375/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0052 - accuracy: 1.0000 - val_loss: 0.6165 - val_accuracy: 0.8500
Epoch 376/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0052 - accuracy: 1.0000 - val_loss: 0.6171 - val_accuracy: 0.8500
Epoch 377/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0052 - accuracy: 1.0000 - val_loss: 0.6174 - val_accuracy: 0.8500
Epoch 378/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0052 - accuracy: 1.0000 - val_loss: 0.6175 - val_accuracy: 0.8500
Epoch 379/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0051 - accuracy: 1.0000 - val_loss: 0.6175 - val_accuracy: 0.8500
Epoch 380/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0051 - accuracy: 1.0000 - val_loss: 0.6178 - val_accuracy: 0.8500
Epoch 381/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0051 - accuracy: 1.0000 - val_loss: 0.6179 - val_accuracy: 0.8500
Epoch 382/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0051 - accuracy: 1.0000 - val_loss: 0.6182 - val_accuracy: 0.8500
Epoch 383/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0051 - accuracy: 1.0000 - val_loss: 0.6182 - val_accuracy: 0.8500
Epoch 384/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0051 - accuracy: 1.0000 - val_loss: 0.6187 - val_accuracy: 0.8500
Epoch 385/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0050 - accuracy: 1.0000 - val_loss: 0.6188 - val_accuracy: 0.8500
Epoch 386/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0050 - accuracy: 1.0000 - val_loss: 0.6191 - val_accuracy: 0.8500
Epoch 387/1000
700/700 [==============================] - 0s 232us/sample - loss: 0.0050 - accuracy: 1.0000 - val_loss: 0.6193 - val_accuracy: 0.8500
Epoch 388/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0050 - accuracy: 1.0000 - val_loss: 0.6195 - val_accuracy: 0.8500
Epoch 389/1000
700/700 [==============================] - 0s 211us/sample - loss: 0.0050 - accuracy: 1.0000 - val_loss: 0.6196 - val_accuracy: 0.8500
Epoch 390/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0050 - accuracy: 1.0000 - val_loss: 0.6195 - val_accuracy: 0.8500
Epoch 391/1000
700/700 [==============================] - 0s 229us/sample - loss: 0.0049 - accuracy: 1.0000 - val_loss: 0.6198 - val_accuracy: 0.8500
Epoch 392/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0049 - accuracy: 1.0000 - val_loss: 0.6200 - val_accuracy: 0.8500
Epoch 393/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0049 - accuracy: 1.0000 - val_loss: 0.6201 - val_accuracy: 0.8500
Epoch 394/1000
700/700 [==============================] - 0s 211us/sample - loss: 0.0049 - accuracy: 1.0000 - val_loss: 0.6202 - val_accuracy: 0.8500
Epoch 395/1000
700/700 [==============================] - 0s 212us/sample - loss: 0.0049 - accuracy: 1.0000 - val_loss: 0.6205 - val_accuracy: 0.8500
Epoch 396/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0049 - accuracy: 1.0000 - val_loss: 0.6208 - val_accuracy: 0.8500
Epoch 397/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0048 - accuracy: 1.0000 - val_loss: 0.6213 - val_accuracy: 0.8500
Epoch 398/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0048 - accuracy: 1.0000 - val_loss: 0.6217 - val_accuracy: 0.8500
Epoch 399/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0048 - accuracy: 1.0000 - val_loss: 0.6219 - val_accuracy: 0.8500
Epoch 400/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0048 - accuracy: 1.0000 - val_loss: 0.6222 - val_accuracy: 0.8500
Epoch 401/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0048 - accuracy: 1.0000 - val_loss: 0.6225 - val_accuracy: 0.8500
Epoch 402/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.0048 - accuracy: 1.0000 - val_loss: 0.6225 - val_accuracy: 0.8500
Epoch 403/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0047 - accuracy: 1.0000 - val_loss: 0.6225 - val_accuracy: 0.8500
Epoch 404/1000
700/700 [==============================] - 0s 208us/sample - loss: 0.0047 - accuracy: 1.0000 - val_loss: 0.6226 - val_accuracy: 0.8500
Epoch 405/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0047 - accuracy: 1.0000 - val_loss: 0.6227 - val_accuracy: 0.8500
Epoch 406/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0047 - accuracy: 1.0000 - val_loss: 0.6231 - val_accuracy: 0.8500
Epoch 407/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0047 - accuracy: 1.0000 - val_loss: 0.6235 - val_accuracy: 0.8500
Epoch 408/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0047 - accuracy: 1.0000 - val_loss: 0.6237 - val_accuracy: 0.8500
Epoch 409/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0046 - accuracy: 1.0000 - val_loss: 0.6237 - val_accuracy: 0.8500
Epoch 410/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0046 - accuracy: 1.0000 - val_loss: 0.6239 - val_accuracy: 0.8500
Epoch 411/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0046 - accuracy: 1.0000 - val_loss: 0.6242 - val_accuracy: 0.8500
Epoch 412/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0046 - accuracy: 1.0000 - val_loss: 0.6245 - val_accuracy: 0.8500
Epoch 413/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0046 - accuracy: 1.0000 - val_loss: 0.6245 - val_accuracy: 0.8500
Epoch 414/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0046 - accuracy: 1.0000 - val_loss: 0.6247 - val_accuracy: 0.8500
Epoch 415/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0046 - accuracy: 1.0000 - val_loss: 0.6250 - val_accuracy: 0.8500
Epoch 416/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0045 - accuracy: 1.0000 - val_loss: 0.6251 - val_accuracy: 0.8500
Epoch 417/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0045 - accuracy: 1.0000 - val_loss: 0.6253 - val_accuracy: 0.8500
Epoch 418/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0045 - accuracy: 1.0000 - val_loss: 0.6254 - val_accuracy: 0.8500
Epoch 419/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0045 - accuracy: 1.0000 - val_loss: 0.6256 - val_accuracy: 0.8500
Epoch 420/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0045 - accuracy: 1.0000 - val_loss: 0.6260 - val_accuracy: 0.8500
Epoch 421/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0045 - accuracy: 1.0000 - val_loss: 0.6262 - val_accuracy: 0.8500
Epoch 422/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0045 - accuracy: 1.0000 - val_loss: 0.6264 - val_accuracy: 0.8500
Epoch 423/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.6265 - val_accuracy: 0.8500
Epoch 424/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.6267 - val_accuracy: 0.8500
Epoch 425/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.6270 - val_accuracy: 0.8500
Epoch 426/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.6273 - val_accuracy: 0.8500
Epoch 427/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.6273 - val_accuracy: 0.8500
Epoch 428/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.6275 - val_accuracy: 0.8500
Epoch 429/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.6279 - val_accuracy: 0.8500
Epoch 430/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6278 - val_accuracy: 0.8500
Epoch 431/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6282 - val_accuracy: 0.8500
Epoch 432/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6281 - val_accuracy: 0.8500
Epoch 433/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6285 - val_accuracy: 0.8500
Epoch 434/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6286 - val_accuracy: 0.8500
Epoch 435/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6288 - val_accuracy: 0.8500
Epoch 436/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6290 - val_accuracy: 0.8500
Epoch 437/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0043 - accuracy: 1.0000 - val_loss: 0.6291 - val_accuracy: 0.8500
Epoch 438/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6295 - val_accuracy: 0.8500
Epoch 439/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6296 - val_accuracy: 0.8500
Epoch 440/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6298 - val_accuracy: 0.8500
Epoch 441/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6301 - val_accuracy: 0.8500
Epoch 442/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6301 - val_accuracy: 0.8500
Epoch 443/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6304 - val_accuracy: 0.8500
Epoch 444/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6306 - val_accuracy: 0.8500
Epoch 445/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.6306 - val_accuracy: 0.8500
Epoch 446/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6309 - val_accuracy: 0.8500
Epoch 447/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6311 - val_accuracy: 0.8500
Epoch 448/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6312 - val_accuracy: 0.8500
Epoch 449/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6312 - val_accuracy: 0.8500
Epoch 450/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6313 - val_accuracy: 0.8500
Epoch 451/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6317 - val_accuracy: 0.8500
Epoch 452/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6320 - val_accuracy: 0.8500
Epoch 453/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0041 - accuracy: 1.0000 - val_loss: 0.6322 - val_accuracy: 0.8500
Epoch 454/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6323 - val_accuracy: 0.8500
Epoch 455/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6327 - val_accuracy: 0.8500
Epoch 456/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6326 - val_accuracy: 0.8500
Epoch 457/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6329 - val_accuracy: 0.8500
Epoch 458/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6331 - val_accuracy: 0.8500
Epoch 459/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6331 - val_accuracy: 0.8500
Epoch 460/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6334 - val_accuracy: 0.8500
Epoch 461/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6335 - val_accuracy: 0.8500
Epoch 462/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0040 - accuracy: 1.0000 - val_loss: 0.6337 - val_accuracy: 0.8500
Epoch 463/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6338 - val_accuracy: 0.8500
Epoch 464/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6338 - val_accuracy: 0.8500
Epoch 465/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6341 - val_accuracy: 0.8500
Epoch 466/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6343 - val_accuracy: 0.8500
Epoch 467/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6346 - val_accuracy: 0.8500
Epoch 468/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6347 - val_accuracy: 0.8500
Epoch 469/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6347 - val_accuracy: 0.8500
Epoch 470/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6350 - val_accuracy: 0.8500
Epoch 471/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6352 - val_accuracy: 0.8500
Epoch 472/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6355 - val_accuracy: 0.8500
Epoch 473/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6357 - val_accuracy: 0.8500
Epoch 474/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6358 - val_accuracy: 0.8500
Epoch 475/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6360 - val_accuracy: 0.8500
Epoch 476/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6362 - val_accuracy: 0.8500
Epoch 477/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6363 - val_accuracy: 0.8500
Epoch 478/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6366 - val_accuracy: 0.8500
Epoch 479/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6368 - val_accuracy: 0.8500
Epoch 480/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6371 - val_accuracy: 0.8500
Epoch 481/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.6371 - val_accuracy: 0.8500
Epoch 482/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6372 - val_accuracy: 0.8500
Epoch 483/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6375 - val_accuracy: 0.8500
Epoch 484/1000
700/700 [==============================] - 0s 208us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6377 - val_accuracy: 0.8500
Epoch 485/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6378 - val_accuracy: 0.8500
Epoch 486/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6381 - val_accuracy: 0.8500
Epoch 487/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6382 - val_accuracy: 0.8500
Epoch 488/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6383 - val_accuracy: 0.8500
Epoch 489/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6383 - val_accuracy: 0.8500
Epoch 490/1000
700/700 [==============================] - 0s 209us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6386 - val_accuracy: 0.8500
Epoch 491/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0037 - accuracy: 1.0000 - val_loss: 0.6387 - val_accuracy: 0.8500
Epoch 492/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6388 - val_accuracy: 0.8500
Epoch 493/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6389 - val_accuracy: 0.8500
Epoch 494/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6391 - val_accuracy: 0.8500
Epoch 495/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6395 - val_accuracy: 0.8500
Epoch 496/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6397 - val_accuracy: 0.8500
Epoch 497/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6397 - val_accuracy: 0.8500
Epoch 498/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6401 - val_accuracy: 0.8533
Epoch 499/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6403 - val_accuracy: 0.8533
Epoch 500/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6405 - val_accuracy: 0.8533
Epoch 501/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0036 - accuracy: 1.0000 - val_loss: 0.6406 - val_accuracy: 0.8533
Epoch 502/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6406 - val_accuracy: 0.8533
Epoch 503/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6409 - val_accuracy: 0.8533
Epoch 504/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6409 - val_accuracy: 0.8533
Epoch 505/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6411 - val_accuracy: 0.8533
Epoch 506/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6412 - val_accuracy: 0.8533
Epoch 507/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6414 - val_accuracy: 0.8533
Epoch 508/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6415 - val_accuracy: 0.8533
Epoch 509/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6417 - val_accuracy: 0.8533
Epoch 510/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6420 - val_accuracy: 0.8533
Epoch 511/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6422 - val_accuracy: 0.8533
Epoch 512/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0035 - accuracy: 1.0000 - val_loss: 0.6424 - val_accuracy: 0.8533
Epoch 513/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6426 - val_accuracy: 0.8533
Epoch 514/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6426 - val_accuracy: 0.8533
Epoch 515/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6427 - val_accuracy: 0.8533
Epoch 516/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6429 - val_accuracy: 0.8533
Epoch 517/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6431 - val_accuracy: 0.8533
Epoch 518/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6433 - val_accuracy: 0.8533
Epoch 519/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6433 - val_accuracy: 0.8533
Epoch 520/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6436 - val_accuracy: 0.8533
Epoch 521/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6437 - val_accuracy: 0.8533
Epoch 522/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6438 - val_accuracy: 0.8533
Epoch 523/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6440 - val_accuracy: 0.8533
Epoch 524/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0034 - accuracy: 1.0000 - val_loss: 0.6441 - val_accuracy: 0.8533
Epoch 525/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6441 - val_accuracy: 0.8533
Epoch 526/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6443 - val_accuracy: 0.8533
Epoch 527/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6447 - val_accuracy: 0.8533
Epoch 528/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6449 - val_accuracy: 0.8533
Epoch 529/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6449 - val_accuracy: 0.8533
Epoch 530/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6450 - val_accuracy: 0.8533
Epoch 531/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6452 - val_accuracy: 0.8533
Epoch 532/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6454 - val_accuracy: 0.8533
Epoch 533/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6457 - val_accuracy: 0.8533
Epoch 534/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6460 - val_accuracy: 0.8533
Epoch 535/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6461 - val_accuracy: 0.8533
Epoch 536/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.6462 - val_accuracy: 0.8533
Epoch 537/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6463 - val_accuracy: 0.8533
Epoch 538/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6465 - val_accuracy: 0.8533
Epoch 539/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6465 - val_accuracy: 0.8533
Epoch 540/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6466 - val_accuracy: 0.8533
Epoch 541/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6469 - val_accuracy: 0.8533
Epoch 542/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6471 - val_accuracy: 0.8533
Epoch 543/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6472 - val_accuracy: 0.8533
Epoch 544/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6475 - val_accuracy: 0.8533
Epoch 545/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6476 - val_accuracy: 0.8533
Epoch 546/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6477 - val_accuracy: 0.8533
Epoch 547/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6478 - val_accuracy: 0.8533
Epoch 548/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6479 - val_accuracy: 0.8533
Epoch 549/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6481 - val_accuracy: 0.8533
Epoch 550/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0032 - accuracy: 1.0000 - val_loss: 0.6483 - val_accuracy: 0.8533
Epoch 551/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6484 - val_accuracy: 0.8533
Epoch 552/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6485 - val_accuracy: 0.8533
Epoch 553/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6486 - val_accuracy: 0.8533
Epoch 554/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6488 - val_accuracy: 0.8533
Epoch 555/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6489 - val_accuracy: 0.8533
Epoch 556/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6491 - val_accuracy: 0.8533
Epoch 557/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6492 - val_accuracy: 0.8533
Epoch 558/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6494 - val_accuracy: 0.8533
Epoch 559/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6495 - val_accuracy: 0.8533
Epoch 560/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6496 - val_accuracy: 0.8533
Epoch 561/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6498 - val_accuracy: 0.8533
Epoch 562/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6500 - val_accuracy: 0.8533
Epoch 563/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0031 - accuracy: 1.0000 - val_loss: 0.6503 - val_accuracy: 0.8533
Epoch 564/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6502 - val_accuracy: 0.8533
Epoch 565/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6504 - val_accuracy: 0.8533
Epoch 566/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6505 - val_accuracy: 0.8533
Epoch 567/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6507 - val_accuracy: 0.8533
Epoch 568/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6508 - val_accuracy: 0.8533
Epoch 569/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6511 - val_accuracy: 0.8533
Epoch 570/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6512 - val_accuracy: 0.8533
Epoch 571/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6513 - val_accuracy: 0.8533
Epoch 572/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6515 - val_accuracy: 0.8533
Epoch 573/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6516 - val_accuracy: 0.8533
Epoch 574/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6518 - val_accuracy: 0.8533
Epoch 575/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6519 - val_accuracy: 0.8533
Epoch 576/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6522 - val_accuracy: 0.8533
Epoch 577/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6521 - val_accuracy: 0.8533
Epoch 578/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0030 - accuracy: 1.0000 - val_loss: 0.6523 - val_accuracy: 0.8533
Epoch 579/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6524 - val_accuracy: 0.8533
Epoch 580/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6525 - val_accuracy: 0.8533
Epoch 581/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6527 - val_accuracy: 0.8533
Epoch 582/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6527 - val_accuracy: 0.8533
Epoch 583/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6528 - val_accuracy: 0.8533
Epoch 584/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6530 - val_accuracy: 0.8533
Epoch 585/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6531 - val_accuracy: 0.8533
Epoch 586/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6532 - val_accuracy: 0.8533
Epoch 587/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6535 - val_accuracy: 0.8533
Epoch 588/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6536 - val_accuracy: 0.8533
Epoch 589/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6537 - val_accuracy: 0.8533
Epoch 590/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6539 - val_accuracy: 0.8533
Epoch 591/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6543 - val_accuracy: 0.8533
Epoch 592/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6544 - val_accuracy: 0.8533
Epoch 593/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6544 - val_accuracy: 0.8533
Epoch 594/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.6545 - val_accuracy: 0.8533
Epoch 595/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6547 - val_accuracy: 0.8533
Epoch 596/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6549 - val_accuracy: 0.8533
Epoch 597/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6550 - val_accuracy: 0.8533
Epoch 598/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6552 - val_accuracy: 0.8533
Epoch 599/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6553 - val_accuracy: 0.8533
Epoch 600/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6555 - val_accuracy: 0.8533
Epoch 601/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6556 - val_accuracy: 0.8533
Epoch 602/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6558 - val_accuracy: 0.8533
Epoch 603/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6559 - val_accuracy: 0.8533
Epoch 604/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6560 - val_accuracy: 0.8533
Epoch 605/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6561 - val_accuracy: 0.8533
Epoch 606/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6562 - val_accuracy: 0.8533
Epoch 607/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6563 - val_accuracy: 0.8533
Epoch 608/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6564 - val_accuracy: 0.8533
Epoch 609/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6567 - val_accuracy: 0.8533
Epoch 610/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0028 - accuracy: 1.0000 - val_loss: 0.6568 - val_accuracy: 0.8533
Epoch 611/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6570 - val_accuracy: 0.8533
Epoch 612/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6571 - val_accuracy: 0.8533
Epoch 613/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6572 - val_accuracy: 0.8533
Epoch 614/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6573 - val_accuracy: 0.8533
Epoch 615/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6574 - val_accuracy: 0.8533
Epoch 616/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6576 - val_accuracy: 0.8533
Epoch 617/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6578 - val_accuracy: 0.8533
Epoch 618/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6579 - val_accuracy: 0.8533
Epoch 619/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6580 - val_accuracy: 0.8533
Epoch 620/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6580 - val_accuracy: 0.8533
Epoch 621/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6583 - val_accuracy: 0.8533
Epoch 622/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6585 - val_accuracy: 0.8533
Epoch 623/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6585 - val_accuracy: 0.8533
Epoch 624/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6586 - val_accuracy: 0.8533
Epoch 625/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6587 - val_accuracy: 0.8533
Epoch 626/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6589 - val_accuracy: 0.8533
Epoch 627/1000
700/700 [==============================] - 0s 211us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6590 - val_accuracy: 0.8533
Epoch 628/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0027 - accuracy: 1.0000 - val_loss: 0.6591 - val_accuracy: 0.8533
Epoch 629/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6593 - val_accuracy: 0.8533
Epoch 630/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6593 - val_accuracy: 0.8533
Epoch 631/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6595 - val_accuracy: 0.8533
Epoch 632/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6595 - val_accuracy: 0.8533
Epoch 633/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6596 - val_accuracy: 0.8533
Epoch 634/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6599 - val_accuracy: 0.8533
Epoch 635/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6599 - val_accuracy: 0.8533
Epoch 636/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6602 - val_accuracy: 0.8533
Epoch 637/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6603 - val_accuracy: 0.8533
Epoch 638/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6604 - val_accuracy: 0.8533
Epoch 639/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6605 - val_accuracy: 0.8533
Epoch 640/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6606 - val_accuracy: 0.8533
Epoch 641/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6608 - val_accuracy: 0.8533
Epoch 642/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6610 - val_accuracy: 0.8533
Epoch 643/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6611 - val_accuracy: 0.8533
Epoch 644/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6611 - val_accuracy: 0.8533
Epoch 645/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6612 - val_accuracy: 0.8533
Epoch 646/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6613 - val_accuracy: 0.8533
Epoch 647/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.6615 - val_accuracy: 0.8533
Epoch 648/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6618 - val_accuracy: 0.8533
Epoch 649/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6618 - val_accuracy: 0.8533
Epoch 650/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6619 - val_accuracy: 0.8533
Epoch 651/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6620 - val_accuracy: 0.8533
Epoch 652/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6622 - val_accuracy: 0.8533
Epoch 653/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6622 - val_accuracy: 0.8533
Epoch 654/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6624 - val_accuracy: 0.8533
Epoch 655/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6625 - val_accuracy: 0.8533
Epoch 656/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6626 - val_accuracy: 0.8533
Epoch 657/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6627 - val_accuracy: 0.8533
Epoch 658/1000
700/700 [==============================] - 0s 190us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6628 - val_accuracy: 0.8533
Epoch 659/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6630 - val_accuracy: 0.8533
Epoch 660/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6631 - val_accuracy: 0.8533
Epoch 661/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6633 - val_accuracy: 0.8533
Epoch 662/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6633 - val_accuracy: 0.8533
Epoch 663/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6634 - val_accuracy: 0.8533
Epoch 664/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6636 - val_accuracy: 0.8533
Epoch 665/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6637 - val_accuracy: 0.8533
Epoch 666/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6638 - val_accuracy: 0.8533
Epoch 667/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6639 - val_accuracy: 0.8533
Epoch 668/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0025 - accuracy: 1.0000 - val_loss: 0.6640 - val_accuracy: 0.8533
Epoch 669/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6643 - val_accuracy: 0.8533
Epoch 670/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6643 - val_accuracy: 0.8533
Epoch 671/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6645 - val_accuracy: 0.8533
Epoch 672/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6646 - val_accuracy: 0.8533
Epoch 673/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6647 - val_accuracy: 0.8533
Epoch 674/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6648 - val_accuracy: 0.8533
Epoch 675/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6650 - val_accuracy: 0.8533
Epoch 676/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6651 - val_accuracy: 0.8533
Epoch 677/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6652 - val_accuracy: 0.8533
Epoch 678/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6653 - val_accuracy: 0.8533
Epoch 679/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6653 - val_accuracy: 0.8533
Epoch 680/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6654 - val_accuracy: 0.8533
Epoch 681/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6657 - val_accuracy: 0.8533
Epoch 682/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6657 - val_accuracy: 0.8533
Epoch 683/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6659 - val_accuracy: 0.8533
Epoch 684/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6661 - val_accuracy: 0.8533
Epoch 685/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6661 - val_accuracy: 0.8533
Epoch 686/1000
700/700 [==============================] - 0s 224us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6662 - val_accuracy: 0.8533
Epoch 687/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6664 - val_accuracy: 0.8533
Epoch 688/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6665 - val_accuracy: 0.8533
Epoch 689/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6667 - val_accuracy: 0.8533
Epoch 690/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0024 - accuracy: 1.0000 - val_loss: 0.6668 - val_accuracy: 0.8533
Epoch 691/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6670 - val_accuracy: 0.8533
Epoch 692/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6670 - val_accuracy: 0.8533
Epoch 693/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6671 - val_accuracy: 0.8533
Epoch 694/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6673 - val_accuracy: 0.8533
Epoch 695/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6674 - val_accuracy: 0.8533
Epoch 696/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6676 - val_accuracy: 0.8533
Epoch 697/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6677 - val_accuracy: 0.8533
Epoch 698/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6678 - val_accuracy: 0.8533
Epoch 699/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6680 - val_accuracy: 0.8533
Epoch 700/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6681 - val_accuracy: 0.8533
Epoch 701/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6682 - val_accuracy: 0.8533
Epoch 702/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6682 - val_accuracy: 0.8533
Epoch 703/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6684 - val_accuracy: 0.8533
Epoch 704/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6685 - val_accuracy: 0.8533
Epoch 705/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6687 - val_accuracy: 0.8533
Epoch 706/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6687 - val_accuracy: 0.8533
Epoch 707/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6688 - val_accuracy: 0.8533
Epoch 708/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6689 - val_accuracy: 0.8533
Epoch 709/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6691 - val_accuracy: 0.8533
Epoch 710/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6692 - val_accuracy: 0.8533
Epoch 711/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6693 - val_accuracy: 0.8533
Epoch 712/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6694 - val_accuracy: 0.8533
Epoch 713/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6695 - val_accuracy: 0.8533
Epoch 714/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.6696 - val_accuracy: 0.8533
Epoch 715/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6698 - val_accuracy: 0.8533
Epoch 716/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6699 - val_accuracy: 0.8533
Epoch 717/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6700 - val_accuracy: 0.8533
Epoch 718/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6701 - val_accuracy: 0.8533
Epoch 719/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6702 - val_accuracy: 0.8533
Epoch 720/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6704 - val_accuracy: 0.8533
Epoch 721/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6705 - val_accuracy: 0.8533
Epoch 722/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6707 - val_accuracy: 0.8533
Epoch 723/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6708 - val_accuracy: 0.8533
Epoch 724/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6708 - val_accuracy: 0.8533
Epoch 725/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6709 - val_accuracy: 0.8533
Epoch 726/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6709 - val_accuracy: 0.8533
Epoch 727/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6711 - val_accuracy: 0.8533
Epoch 728/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6712 - val_accuracy: 0.8533
Epoch 729/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6714 - val_accuracy: 0.8533
Epoch 730/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6715 - val_accuracy: 0.8533
Epoch 731/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6717 - val_accuracy: 0.8533
Epoch 732/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6718 - val_accuracy: 0.8533
Epoch 733/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6719 - val_accuracy: 0.8533
Epoch 734/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6719 - val_accuracy: 0.8533
Epoch 735/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6722 - val_accuracy: 0.8533
Epoch 736/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6722 - val_accuracy: 0.8533
Epoch 737/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6723 - val_accuracy: 0.8533
Epoch 738/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6724 - val_accuracy: 0.8533
Epoch 739/1000
700/700 [==============================] - 0s 217us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6724 - val_accuracy: 0.8533
Epoch 740/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.6726 - val_accuracy: 0.8533
Epoch 741/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6727 - val_accuracy: 0.8533
Epoch 742/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6729 - val_accuracy: 0.8533
Epoch 743/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6730 - val_accuracy: 0.8533
Epoch 744/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6731 - val_accuracy: 0.8533
Epoch 745/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6732 - val_accuracy: 0.8533
Epoch 746/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6732 - val_accuracy: 0.8533
Epoch 747/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6734 - val_accuracy: 0.8533
Epoch 748/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6735 - val_accuracy: 0.8533
Epoch 749/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6736 - val_accuracy: 0.8533
Epoch 750/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6738 - val_accuracy: 0.8533
Epoch 751/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6739 - val_accuracy: 0.8533
Epoch 752/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6740 - val_accuracy: 0.8533
Epoch 753/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6741 - val_accuracy: 0.8533
Epoch 754/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6742 - val_accuracy: 0.8533
Epoch 755/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6744 - val_accuracy: 0.8533
Epoch 756/1000
700/700 [==============================] - 0s 201us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6744 - val_accuracy: 0.8533
Epoch 757/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6745 - val_accuracy: 0.8533
Epoch 758/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6746 - val_accuracy: 0.8533
Epoch 759/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6747 - val_accuracy: 0.8533
Epoch 760/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6748 - val_accuracy: 0.8533
Epoch 761/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6749 - val_accuracy: 0.8533
Epoch 762/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6750 - val_accuracy: 0.8533
Epoch 763/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6751 - val_accuracy: 0.8533
Epoch 764/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6752 - val_accuracy: 0.8533
Epoch 765/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6753 - val_accuracy: 0.8533
Epoch 766/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6754 - val_accuracy: 0.8533
Epoch 767/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6755 - val_accuracy: 0.8533
Epoch 768/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.6756 - val_accuracy: 0.8533
Epoch 769/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6756 - val_accuracy: 0.8533
Epoch 770/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6758 - val_accuracy: 0.8533
Epoch 771/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6760 - val_accuracy: 0.8533
Epoch 772/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6760 - val_accuracy: 0.8533
Epoch 773/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6761 - val_accuracy: 0.8533
Epoch 774/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6762 - val_accuracy: 0.8533
Epoch 775/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6764 - val_accuracy: 0.8533
Epoch 776/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6765 - val_accuracy: 0.8533
Epoch 777/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6766 - val_accuracy: 0.8533
Epoch 778/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6767 - val_accuracy: 0.8533
Epoch 779/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6769 - val_accuracy: 0.8533
Epoch 780/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6770 - val_accuracy: 0.8533
Epoch 781/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6771 - val_accuracy: 0.8533
Epoch 782/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6772 - val_accuracy: 0.8533
Epoch 783/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6772 - val_accuracy: 0.8533
Epoch 784/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6773 - val_accuracy: 0.8533
Epoch 785/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6775 - val_accuracy: 0.8533
Epoch 786/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6775 - val_accuracy: 0.8533
Epoch 787/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6776 - val_accuracy: 0.8533
Epoch 788/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6777 - val_accuracy: 0.8533
Epoch 789/1000
700/700 [==============================] - 0s 219us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6778 - val_accuracy: 0.8533
Epoch 790/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6779 - val_accuracy: 0.8533
Epoch 791/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6781 - val_accuracy: 0.8533
Epoch 792/1000
700/700 [==============================] - 0s 217us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6782 - val_accuracy: 0.8533
Epoch 793/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6783 - val_accuracy: 0.8533
Epoch 794/1000
700/700 [==============================] - 0s 224us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6784 - val_accuracy: 0.8533
Epoch 795/1000
700/700 [==============================] - 0s 199us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6786 - val_accuracy: 0.8533
Epoch 796/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6787 - val_accuracy: 0.8533
Epoch 797/1000
700/700 [==============================] - 0s 222us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6787 - val_accuracy: 0.8533
Epoch 798/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6788 - val_accuracy: 0.8533
Epoch 799/1000
700/700 [==============================] - 0s 225us/sample - loss: 0.0020 - accuracy: 1.0000 - val_loss: 0.6789 - val_accuracy: 0.8533
Epoch 800/1000
700/700 [==============================] - 0s 205us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6791 - val_accuracy: 0.8533
Epoch 801/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6792 - val_accuracy: 0.8533
Epoch 802/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6793 - val_accuracy: 0.8533
Epoch 803/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6794 - val_accuracy: 0.8533
Epoch 804/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6795 - val_accuracy: 0.8533
Epoch 805/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6796 - val_accuracy: 0.8533
Epoch 806/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6797 - val_accuracy: 0.8533
Epoch 807/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6798 - val_accuracy: 0.8533
Epoch 808/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6799 - val_accuracy: 0.8533
Epoch 809/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6801 - val_accuracy: 0.8533
Epoch 810/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6802 - val_accuracy: 0.8533
Epoch 811/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6803 - val_accuracy: 0.8533
Epoch 812/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6803 - val_accuracy: 0.8533
Epoch 813/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6804 - val_accuracy: 0.8533
Epoch 814/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6805 - val_accuracy: 0.8533
Epoch 815/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6805 - val_accuracy: 0.8533
Epoch 816/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6806 - val_accuracy: 0.8533
Epoch 817/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6807 - val_accuracy: 0.8533
Epoch 818/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6809 - val_accuracy: 0.8533
Epoch 819/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6810 - val_accuracy: 0.8533
Epoch 820/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6811 - val_accuracy: 0.8533
Epoch 821/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6812 - val_accuracy: 0.8533
Epoch 822/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6813 - val_accuracy: 0.8533
Epoch 823/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6814 - val_accuracy: 0.8533
Epoch 824/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6815 - val_accuracy: 0.8533
Epoch 825/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6816 - val_accuracy: 0.8533
Epoch 826/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6817 - val_accuracy: 0.8533
Epoch 827/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6817 - val_accuracy: 0.8533
Epoch 828/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6818 - val_accuracy: 0.8533
Epoch 829/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6819 - val_accuracy: 0.8533
Epoch 830/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6820 - val_accuracy: 0.8533
Epoch 831/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6821 - val_accuracy: 0.8533
Epoch 832/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6822 - val_accuracy: 0.8533
Epoch 833/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.6824 - val_accuracy: 0.8533
Epoch 834/1000
700/700 [==============================] - 0s 217us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6825 - val_accuracy: 0.8533
Epoch 835/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6826 - val_accuracy: 0.8533
Epoch 836/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6827 - val_accuracy: 0.8533
Epoch 837/1000
700/700 [==============================] - 0s 215us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6828 - val_accuracy: 0.8533
Epoch 838/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6828 - val_accuracy: 0.8533
Epoch 839/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6829 - val_accuracy: 0.8533
Epoch 840/1000
700/700 [==============================] - 0s 202us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6830 - val_accuracy: 0.8533
Epoch 841/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6831 - val_accuracy: 0.8533
Epoch 842/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6832 - val_accuracy: 0.8533
Epoch 843/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6833 - val_accuracy: 0.8533
Epoch 844/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6835 - val_accuracy: 0.8533
Epoch 845/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6835 - val_accuracy: 0.8533
Epoch 846/1000
700/700 [==============================] - 0s 198us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6837 - val_accuracy: 0.8533
Epoch 847/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6838 - val_accuracy: 0.8533
Epoch 848/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6839 - val_accuracy: 0.8533
Epoch 849/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6841 - val_accuracy: 0.8533
Epoch 850/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6841 - val_accuracy: 0.8533
Epoch 851/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6843 - val_accuracy: 0.8533
Epoch 852/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6843 - val_accuracy: 0.8533
Epoch 853/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6844 - val_accuracy: 0.8533
Epoch 854/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6845 - val_accuracy: 0.8533
Epoch 855/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6845 - val_accuracy: 0.8533
Epoch 856/1000
700/700 [==============================] - 0s 204us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6846 - val_accuracy: 0.8533
Epoch 857/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6848 - val_accuracy: 0.8533
Epoch 858/1000
700/700 [==============================] - 0s 197us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6849 - val_accuracy: 0.8533
Epoch 859/1000
700/700 [==============================] - 0s 192us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6850 - val_accuracy: 0.8533
Epoch 860/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6851 - val_accuracy: 0.8533
Epoch 861/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6852 - val_accuracy: 0.8533
Epoch 862/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6853 - val_accuracy: 0.8533
Epoch 863/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6854 - val_accuracy: 0.8533
Epoch 864/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6855 - val_accuracy: 0.8533
Epoch 865/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6855 - val_accuracy: 0.8533
Epoch 866/1000
700/700 [==============================] - 0s 194us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6856 - val_accuracy: 0.8533
Epoch 867/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6857 - val_accuracy: 0.8533
Epoch 868/1000
700/700 [==============================] - 0s 207us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6858 - val_accuracy: 0.8533
Epoch 869/1000
700/700 [==============================] - 0s 262us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6859 - val_accuracy: 0.8533
Epoch 870/1000
700/700 [==============================] - 0s 227us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6861 - val_accuracy: 0.8533
Epoch 871/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0018 - accuracy: 1.0000 - val_loss: 0.6862 - val_accuracy: 0.8533
Epoch 872/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6862 - val_accuracy: 0.8533
Epoch 873/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6863 - val_accuracy: 0.8533
Epoch 874/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6865 - val_accuracy: 0.8533
Epoch 875/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6866 - val_accuracy: 0.8533
Epoch 876/1000
700/700 [==============================] - 0s 174us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6866 - val_accuracy: 0.8533
Epoch 877/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6868 - val_accuracy: 0.8533
Epoch 878/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6868 - val_accuracy: 0.8533
Epoch 879/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6869 - val_accuracy: 0.8533
Epoch 880/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6870 - val_accuracy: 0.8533
Epoch 881/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6871 - val_accuracy: 0.8533
Epoch 882/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6872 - val_accuracy: 0.8533
Epoch 883/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6873 - val_accuracy: 0.8533
Epoch 884/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6874 - val_accuracy: 0.8533
Epoch 885/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6875 - val_accuracy: 0.8533
Epoch 886/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6876 - val_accuracy: 0.8533
Epoch 887/1000
700/700 [==============================] - 0s 174us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6877 - val_accuracy: 0.8533
Epoch 888/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6877 - val_accuracy: 0.8533
Epoch 889/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6879 - val_accuracy: 0.8533
Epoch 890/1000
700/700 [==============================] - 0s 174us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6879 - val_accuracy: 0.8533
Epoch 891/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6880 - val_accuracy: 0.8533
Epoch 892/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6881 - val_accuracy: 0.8533
Epoch 893/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6882 - val_accuracy: 0.8533
Epoch 894/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6883 - val_accuracy: 0.8533
Epoch 895/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6884 - val_accuracy: 0.8533
Epoch 896/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6885 - val_accuracy: 0.8533
Epoch 897/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6887 - val_accuracy: 0.8533
Epoch 898/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6887 - val_accuracy: 0.8533
Epoch 899/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6888 - val_accuracy: 0.8533
Epoch 900/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6889 - val_accuracy: 0.8533
Epoch 901/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6890 - val_accuracy: 0.8533
Epoch 902/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6891 - val_accuracy: 0.8533
Epoch 903/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6892 - val_accuracy: 0.8533
Epoch 904/1000
700/700 [==============================] - 0s 191us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6893 - val_accuracy: 0.8533
Epoch 905/1000
700/700 [==============================] - 0s 189us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6893 - val_accuracy: 0.8533
Epoch 906/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6894 - val_accuracy: 0.8533
Epoch 907/1000
700/700 [==============================] - 0s 174us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6895 - val_accuracy: 0.8533
Epoch 908/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6896 - val_accuracy: 0.8533
Epoch 909/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6897 - val_accuracy: 0.8533
Epoch 910/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6898 - val_accuracy: 0.8533
Epoch 911/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6899 - val_accuracy: 0.8533
Epoch 912/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6899 - val_accuracy: 0.8533
Epoch 913/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0017 - accuracy: 1.0000 - val_loss: 0.6901 - val_accuracy: 0.8533
Epoch 914/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6902 - val_accuracy: 0.8533
Epoch 915/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6902 - val_accuracy: 0.8533
Epoch 916/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6904 - val_accuracy: 0.8533
Epoch 917/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6905 - val_accuracy: 0.8533
Epoch 918/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6906 - val_accuracy: 0.8533
Epoch 919/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6906 - val_accuracy: 0.8533
Epoch 920/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6907 - val_accuracy: 0.8533
Epoch 921/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6908 - val_accuracy: 0.8533
Epoch 922/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6908 - val_accuracy: 0.8533
Epoch 923/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6909 - val_accuracy: 0.8533
Epoch 924/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6911 - val_accuracy: 0.8533
Epoch 925/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6910 - val_accuracy: 0.8533
Epoch 926/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6912 - val_accuracy: 0.8533
Epoch 927/1000
700/700 [==============================] - 0s 187us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6914 - val_accuracy: 0.8533
Epoch 928/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6915 - val_accuracy: 0.8533
Epoch 929/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6916 - val_accuracy: 0.8533
Epoch 930/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6916 - val_accuracy: 0.8533
Epoch 931/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6917 - val_accuracy: 0.8533
Epoch 932/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6918 - val_accuracy: 0.8533
Epoch 933/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6919 - val_accuracy: 0.8533
Epoch 934/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6919 - val_accuracy: 0.8533
Epoch 935/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6920 - val_accuracy: 0.8533
Epoch 936/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6921 - val_accuracy: 0.8533
Epoch 937/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6921 - val_accuracy: 0.8533
Epoch 938/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6923 - val_accuracy: 0.8533
Epoch 939/1000
700/700 [==============================] - 0s 195us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6924 - val_accuracy: 0.8533
Epoch 940/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6925 - val_accuracy: 0.8533
Epoch 941/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6925 - val_accuracy: 0.8533
Epoch 942/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6926 - val_accuracy: 0.8533
Epoch 943/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6927 - val_accuracy: 0.8533
Epoch 944/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6928 - val_accuracy: 0.8533
Epoch 945/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6929 - val_accuracy: 0.8533
Epoch 946/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6930 - val_accuracy: 0.8533
Epoch 947/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6931 - val_accuracy: 0.8533
Epoch 948/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6932 - val_accuracy: 0.8533
Epoch 949/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6933 - val_accuracy: 0.8533
Epoch 950/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6933 - val_accuracy: 0.8533
Epoch 951/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6934 - val_accuracy: 0.8533
Epoch 952/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6934 - val_accuracy: 0.8533
Epoch 953/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6935 - val_accuracy: 0.8533
Epoch 954/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6937 - val_accuracy: 0.8533
Epoch 955/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6938 - val_accuracy: 0.8533
Epoch 956/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6938 - val_accuracy: 0.8533
Epoch 957/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6939 - val_accuracy: 0.8533
Epoch 958/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6940 - val_accuracy: 0.8533
Epoch 959/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6941 - val_accuracy: 0.8533
Epoch 960/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0016 - accuracy: 1.0000 - val_loss: 0.6942 - val_accuracy: 0.8533
Epoch 961/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6943 - val_accuracy: 0.8533
Epoch 962/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6943 - val_accuracy: 0.8533
Epoch 963/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6945 - val_accuracy: 0.8533
Epoch 964/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6946 - val_accuracy: 0.8533
Epoch 965/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6946 - val_accuracy: 0.8533
Epoch 966/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6947 - val_accuracy: 0.8533
Epoch 967/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6948 - val_accuracy: 0.8533
Epoch 968/1000
700/700 [==============================] - 0s 188us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6949 - val_accuracy: 0.8533
Epoch 969/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6949 - val_accuracy: 0.8533
Epoch 970/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6950 - val_accuracy: 0.8533
Epoch 971/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6952 - val_accuracy: 0.8533
Epoch 972/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6953 - val_accuracy: 0.8533
Epoch 973/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6954 - val_accuracy: 0.8533
Epoch 974/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6954 - val_accuracy: 0.8533
Epoch 975/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6955 - val_accuracy: 0.8533
Epoch 976/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6956 - val_accuracy: 0.8533
Epoch 977/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6957 - val_accuracy: 0.8533
Epoch 978/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6958 - val_accuracy: 0.8533
Epoch 979/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6959 - val_accuracy: 0.8533
Epoch 980/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6959 - val_accuracy: 0.8533
Epoch 981/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6960 - val_accuracy: 0.8533
Epoch 982/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6961 - val_accuracy: 0.8533
Epoch 983/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6962 - val_accuracy: 0.8533
Epoch 984/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6963 - val_accuracy: 0.8533
Epoch 985/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6964 - val_accuracy: 0.8533
Epoch 986/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6965 - val_accuracy: 0.8533
Epoch 987/1000
700/700 [==============================] - 0s 185us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6965 - val_accuracy: 0.8533
Epoch 988/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6966 - val_accuracy: 0.8533
Epoch 989/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6967 - val_accuracy: 0.8533
Epoch 990/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6968 - val_accuracy: 0.8533
Epoch 991/1000
700/700 [==============================] - 0s 175us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6968 - val_accuracy: 0.8533
Epoch 992/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6970 - val_accuracy: 0.8533
Epoch 993/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6970 - val_accuracy: 0.8533
Epoch 994/1000
700/700 [==============================] - 0s 182us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6971 - val_accuracy: 0.8533
Epoch 995/1000
700/700 [==============================] - 0s 180us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6972 - val_accuracy: 0.8533
Epoch 996/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6973 - val_accuracy: 0.8533
Epoch 997/1000
700/700 [==============================] - 0s 178us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6974 - val_accuracy: 0.8533
Epoch 998/1000
700/700 [==============================] - 0s 181us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6975 - val_accuracy: 0.8533
Epoch 999/1000
700/700 [==============================] - 0s 177us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6975 - val_accuracy: 0.8533
Epoch 1000/1000
700/700 [==============================] - 0s 184us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.6976 - val_accuracy: 0.8533
5. 학습과정 그래프로 확인- 히스토리 객체 생성
- 매 에포크 마다의 훈련 손실값 (loss)
- 매 에포크 마다의 훈련 정확도 (acc)
- 에포크 마다의 검증 손실값 (val_loss)
- 에포크 마다의 검증 정확도 (val_acc)
6. 학습과정 살펴보기- 모델 학습 시 훈련셋, 검증셋의 손실 및 정확도를 측정합니다.
- 반복횟수에 따른 손실 및 정확도 추이를 보면서 학습 상황을 판단합니다.
## training loss and accuracy ##
[2.094333384718214, 1.6206669415746415, 1.265817721400942, 1.0268088792051588, 0.8637722487960543, 0.7518548714263099, 0.6639163249305317, 0.60365726181439, 0.548935664338725, 0.5093365945986339, 0.4701830217880862, 0.43842070017542156, 0.41534744181803296, 0.387991143230881, 0.36898505889943667, 0.34972150921821593, 0.3327591172818627, 0.31652836474989143, 0.30433943260993274, 0.289253520326955, 0.27648831659129686, 0.263886878320149, 0.2556346504815987, 0.2434970013265099, 0.23487781834389482, 0.22537463270127772, 0.2176638954452106, 0.20797166983996118, 0.20314245814723628, 0.1952360065387828, 0.18653059351657117, 0.18165873794683388, 0.17483686065035206, 0.168954823538661, 0.16274823030190808, 0.15773739692355906, 0.15287050024739335, 0.14771598439131464, 0.14335842435913426, 0.13936555510652918, 0.1345637387995209, 0.13140704073011875, 0.12674353854464634, 0.12235806531139783, 0.11950114624840873, 0.11538613749934094, 0.11156859134456941, 0.10948964261582919, 0.10549160929928933, 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7. 모델 평가하기- 준비된 시험셋으로 학습한 모델을 평가합니다.
- 케라스에서는 evaluate() 함수를 사용합니다.
10000/10000 [==============================] - 0s 45us/sample - loss: 0.5471 - accuracy: 0.8798
## evaluation loss and_metrics ##
[0.5470691438039764, 0.8798]
8. 모델 사용하기- 임의의 입력으로 모델의 출력을 얻습니다.
- 케라스에서는 predict() 함수를 사용합니다.
## yhat ##
[[3.7283603e-09 5.7813845e-13 2.7963407e-09 7.2410611e-09 2.8661476e-11
4.2531459e-10 6.6161357e-14 9.9999976e-01 5.0808435e-10 2.5218134e-07]]
Out[12]:
|