In [1]:

    

import keras
from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Conv2D, MaxPooling2D
from keras.optimizers import Adam
from keras.callbacks import ReduceLROnPlateau
import numpy as np
import os
import wandb
from wandb.keras import WandbCallback
import matplotlib.pyplot as plt


    

    




Using TensorFlow backend.

In [2]:

    

wandb.init(project="cifar")
config = wandb.config
config.dropout = 0.25
config.dense_layer_nodes = 100
config.batch_size = 32
config.epochs = 50

class_names = ['airplane','automobile','bird','cat','deer',
               'dog','frog','horse','ship','truck']
num_classes = len(class_names)

(X_train, y_train), (X_test, y_test) = cifar10.load_data()


    

    




W&B Run: https://app.wandb.ai/l2k2/cifar/runs/k9q4itov
Call `%%wandb` in the cell containing your training loop to display live results.

In [3]:

    

# Convert class vectors to binary class matrices.
y_train = keras.utils.to_categorical(y_train, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)

X_train = X_train.astype('float32') / 255.
X_test = X_test.astype('float32') / 255.


    

In [28]:

    

model = Sequential()
model.add(Conv2D(32, (3, 3), padding='same',
                 input_shape=X_train.shape[1:], activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(config.dropout))

model.add(Flatten())
model.add(Dense(config.dense_layer_nodes, activation='relu'))
model.add(Dropout(config.dropout))
model.add(Dense(num_classes, activation='softmax'))


    

In [29]:

    

learn_rate = 0.004
batch_size = 128
model.compile(loss='categorical_crossentropy',
              optimizer=Adam(learn_rate),
              metrics=['accuracy'])


    

In [30]:

    

wandb.init()
model.fit(X_train,y_train,batch_size=batch_size,
                        epochs=300,
                        validation_data=(X_test, y_test),
                        callbacks=[WandbCallback(),ReduceLROnPlateau()]
)


    

    




W&B Run: https://app.wandb.ai/l2k2/cifar/runs/snh4qfgk
Call `%%wandb` in the cell containing your training loop to display live results.
Train on 50000 samples, validate on 10000 samples
Epoch 1/300
50000/50000 [==============================] - 6s 127us/step - loss: 1.7099 - acc: 0.3735 - val_loss: 1.4350 - val_acc: 0.4841
Epoch 2/300
50000/50000 [==============================] - 5s 106us/step - loss: 1.4578 - acc: 0.4704 - val_loss: 1.3006 - val_acc: 0.5401
Epoch 3/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.3725 - acc: 0.5022 - val_loss: 1.2329 - val_acc: 0.5600
Epoch 4/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.3162 - acc: 0.5239 - val_loss: 1.2082 - val_acc: 0.5682
Epoch 5/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.2727 - acc: 0.5380 - val_loss: 1.1415 - val_acc: 0.5951
Epoch 6/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.2365 - acc: 0.5553 - val_loss: 1.1835 - val_acc: 0.5781
Epoch 7/300
50000/50000 [==============================] - 5s 104us/step - loss: 1.2057 - acc: 0.5644 - val_loss: 1.1102 - val_acc: 0.6050
Epoch 8/300
50000/50000 [==============================] - 5s 104us/step - loss: 1.1760 - acc: 0.5718 - val_loss: 1.1041 - val_acc: 0.6117
Epoch 9/300
50000/50000 [==============================] - 5s 106us/step - loss: 1.1667 - acc: 0.5778 - val_loss: 1.1390 - val_acc: 0.6034
Epoch 10/300
50000/50000 [==============================] - 5s 104us/step - loss: 1.1382 - acc: 0.5895 - val_loss: 1.1196 - val_acc: 0.6128
Epoch 11/300
50000/50000 [==============================] - 5s 106us/step - loss: 1.1321 - acc: 0.5915 - val_loss: 1.1606 - val_acc: 0.5999
Epoch 12/300
50000/50000 [==============================] - 5s 104us/step - loss: 1.1130 - acc: 0.5983 - val_loss: 1.1082 - val_acc: 0.6046
Epoch 13/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.1012 - acc: 0.5988 - val_loss: 1.1275 - val_acc: 0.6069
Epoch 14/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.0911 - acc: 0.6036 - val_loss: 1.1093 - val_acc: 0.6038
Epoch 15/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.0777 - acc: 0.6089 - val_loss: 1.0947 - val_acc: 0.6178
Epoch 16/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.0695 - acc: 0.6127 - val_loss: 1.0794 - val_acc: 0.6257
Epoch 17/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.0613 - acc: 0.6146 - val_loss: 1.0882 - val_acc: 0.6129
Epoch 18/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.0497 - acc: 0.6183 - val_loss: 1.0890 - val_acc: 0.6177
Epoch 19/300
50000/50000 [==============================] - 5s 104us/step - loss: 1.0471 - acc: 0.6193 - val_loss: 1.0915 - val_acc: 0.6178
Epoch 20/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.0397 - acc: 0.6215 - val_loss: 1.1324 - val_acc: 0.6094
Epoch 21/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.0316 - acc: 0.6242 - val_loss: 1.0991 - val_acc: 0.6144
Epoch 22/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.0265 - acc: 0.6230 - val_loss: 1.0830 - val_acc: 0.6186
Epoch 23/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.0110 - acc: 0.6288 - val_loss: 1.0751 - val_acc: 0.6203
Epoch 24/300
50000/50000 [==============================] - 5s 103us/step - loss: 1.0094 - acc: 0.6304 - val_loss: 1.0798 - val_acc: 0.6227
Epoch 25/300
50000/50000 [==============================] - 5s 102us/step - loss: 1.0102 - acc: 0.6316 - val_loss: 1.1127 - val_acc: 0.6090
Epoch 26/300
50000/50000 [==============================] - 5s 104us/step - loss: 1.0036 - acc: 0.6329 - val_loss: 1.0788 - val_acc: 0.6251
Epoch 27/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.9962 - acc: 0.6338 - val_loss: 1.0726 - val_acc: 0.6258
Epoch 28/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.9863 - acc: 0.6364 - val_loss: 1.1465 - val_acc: 0.6176
Epoch 29/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.9821 - acc: 0.6412 - val_loss: 1.0737 - val_acc: 0.6249
Epoch 30/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.9711 - acc: 0.6433 - val_loss: 1.0876 - val_acc: 0.6260
Epoch 31/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.9753 - acc: 0.6428 - val_loss: 1.0773 - val_acc: 0.6258
Epoch 32/300
50000/50000 [==============================] - 5s 105us/step - loss: 0.9689 - acc: 0.6457 - val_loss: 1.1027 - val_acc: 0.6172
Epoch 33/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.9572 - acc: 0.6470 - val_loss: 1.0793 - val_acc: 0.6238
Epoch 34/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.9591 - acc: 0.6499 - val_loss: 1.0728 - val_acc: 0.6236
Epoch 35/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.9585 - acc: 0.6500 - val_loss: 1.1268 - val_acc: 0.6123
Epoch 36/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.9480 - acc: 0.6526 - val_loss: 1.1091 - val_acc: 0.6175
Epoch 37/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.9505 - acc: 0.6500 - val_loss: 1.1154 - val_acc: 0.6230
Epoch 38/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8796 - acc: 0.6746 - val_loss: 1.0591 - val_acc: 0.6359
Epoch 39/300
50000/50000 [==============================] - 5s 107us/step - loss: 0.8679 - acc: 0.6804 - val_loss: 1.0630 - val_acc: 0.6348
Epoch 40/300
50000/50000 [==============================] - 5s 107us/step - loss: 0.8672 - acc: 0.6780 - val_loss: 1.0548 - val_acc: 0.6348
Epoch 41/300
50000/50000 [==============================] - 5s 105us/step - loss: 0.8582 - acc: 0.6817 - val_loss: 1.0587 - val_acc: 0.6379
Epoch 42/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8588 - acc: 0.6842 - val_loss: 1.0567 - val_acc: 0.6366
Epoch 43/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8544 - acc: 0.6831 - val_loss: 1.0597 - val_acc: 0.6380
Epoch 44/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8555 - acc: 0.6838 - val_loss: 1.0529 - val_acc: 0.6358
Epoch 45/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8494 - acc: 0.6882 - val_loss: 1.0509 - val_acc: 0.6377
Epoch 46/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8438 - acc: 0.6887 - val_loss: 1.0551 - val_acc: 0.6381
Epoch 47/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8437 - acc: 0.6865 - val_loss: 1.0560 - val_acc: 0.6373
Epoch 48/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8447 - acc: 0.6874 - val_loss: 1.0485 - val_acc: 0.6408
Epoch 49/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8373 - acc: 0.6892 - val_loss: 1.0556 - val_acc: 0.6399
Epoch 50/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8441 - acc: 0.6883 - val_loss: 1.0548 - val_acc: 0.6385
Epoch 51/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8385 - acc: 0.6883 - val_loss: 1.0527 - val_acc: 0.6401
Epoch 52/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8349 - acc: 0.6924 - val_loss: 1.0600 - val_acc: 0.6394
Epoch 53/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8391 - acc: 0.6918 - val_loss: 1.0540 - val_acc: 0.6423
Epoch 54/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8400 - acc: 0.6880 - val_loss: 1.0542 - val_acc: 0.6408
Epoch 55/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8405 - acc: 0.6917 - val_loss: 1.0540 - val_acc: 0.6389
Epoch 56/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8330 - acc: 0.6916 - val_loss: 1.0553 - val_acc: 0.6414
Epoch 57/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8278 - acc: 0.6920 - val_loss: 1.0569 - val_acc: 0.6392
Epoch 58/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8338 - acc: 0.6914 - val_loss: 1.0634 - val_acc: 0.6389
Epoch 59/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8200 - acc: 0.6962 - val_loss: 1.0548 - val_acc: 0.6418
Epoch 60/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8235 - acc: 0.6943 - val_loss: 1.0537 - val_acc: 0.6417
Epoch 61/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8237 - acc: 0.6946 - val_loss: 1.0538 - val_acc: 0.6421
Epoch 62/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8221 - acc: 0.6961 - val_loss: 1.0542 - val_acc: 0.6420
Epoch 63/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8164 - acc: 0.6962 - val_loss: 1.0543 - val_acc: 0.6422
Epoch 64/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8230 - acc: 0.6937 - val_loss: 1.0540 - val_acc: 0.6422
Epoch 65/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8132 - acc: 0.6978 - val_loss: 1.0542 - val_acc: 0.6412
Epoch 66/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8226 - acc: 0.6951 - val_loss: 1.0532 - val_acc: 0.6428
Epoch 67/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8187 - acc: 0.6975 - val_loss: 1.0526 - val_acc: 0.6425
Epoch 68/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8184 - acc: 0.6968 - val_loss: 1.0547 - val_acc: 0.6430
Epoch 69/300
50000/50000 [==============================] - 5s 107us/step - loss: 0.8199 - acc: 0.6954 - val_loss: 1.0537 - val_acc: 0.6426
Epoch 70/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8129 - acc: 0.6971 - val_loss: 1.0535 - val_acc: 0.6420
Epoch 71/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8188 - acc: 0.6967 - val_loss: 1.0535 - val_acc: 0.6417
Epoch 72/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8213 - acc: 0.6971 - val_loss: 1.0534 - val_acc: 0.6415
Epoch 73/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8197 - acc: 0.6950 - val_loss: 1.0534 - val_acc: 0.6415
Epoch 74/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8193 - acc: 0.6958 - val_loss: 1.0533 - val_acc: 0.6414
Epoch 75/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8192 - acc: 0.6941 - val_loss: 1.0530 - val_acc: 0.6417
Epoch 76/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8200 - acc: 0.6992 - val_loss: 1.0531 - val_acc: 0.6421
Epoch 77/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8162 - acc: 0.6976 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 78/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8155 - acc: 0.6968 - val_loss: 1.0530 - val_acc: 0.6415
Epoch 79/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8174 - acc: 0.6992 - val_loss: 1.0530 - val_acc: 0.6416
Epoch 80/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8162 - acc: 0.6970 - val_loss: 1.0530 - val_acc: 0.6417
Epoch 81/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8191 - acc: 0.6995 - val_loss: 1.0530 - val_acc: 0.6418
Epoch 82/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8203 - acc: 0.6949 - val_loss: 1.0531 - val_acc: 0.6417
Epoch 83/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8131 - acc: 0.7005 - val_loss: 1.0531 - val_acc: 0.6417
Epoch 84/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8157 - acc: 0.6977 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 85/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8152 - acc: 0.6968 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 86/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8166 - acc: 0.6969 - val_loss: 1.0531 - val_acc: 0.6417
Epoch 87/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8194 - acc: 0.6921 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 88/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8177 - acc: 0.6967 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 89/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8180 - acc: 0.6979 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 90/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8140 - acc: 0.6981 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 91/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8170 - acc: 0.6954 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 92/300
50000/50000 [==============================] - 5s 105us/step - loss: 0.8145 - acc: 0.6986 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 93/300
50000/50000 [==============================] - 5s 106us/step - loss: 0.8199 - acc: 0.6958 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 94/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8188 - acc: 0.6950 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 95/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8133 - acc: 0.6994 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 96/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8129 - acc: 0.6987 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 97/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8152 - acc: 0.6967 - val_loss: 1.0531 - val_acc: 0.6418
Epoch 98/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8200 - acc: 0.6960 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 99/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8148 - acc: 0.6969 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 100/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8223 - acc: 0.6949 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 101/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8207 - acc: 0.6953 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 102/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8144 - acc: 0.6983 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 103/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8188 - acc: 0.6973 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 104/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8179 - acc: 0.6971 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 105/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8172 - acc: 0.6982 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 106/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8188 - acc: 0.6985 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 107/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8158 - acc: 0.6951 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 108/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8202 - acc: 0.6966 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 109/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8146 - acc: 0.6960 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 110/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8154 - acc: 0.6989 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 111/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8141 - acc: 0.6964 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 112/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8192 - acc: 0.6955 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 113/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8223 - acc: 0.6956 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 114/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8220 - acc: 0.6952 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 115/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8213 - acc: 0.6944 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 116/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8193 - acc: 0.6965 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 117/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8140 - acc: 0.6988 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 118/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8185 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 119/300
50000/50000 [==============================] - 5s 107us/step - loss: 0.8151 - acc: 0.6988 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 120/300
50000/50000 [==============================] - 5s 105us/step - loss: 0.8234 - acc: 0.6930 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 121/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8145 - acc: 0.6985 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 122/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8132 - acc: 0.6988 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 123/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8169 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 124/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8145 - acc: 0.6983 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 125/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8145 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 126/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8111 - acc: 0.6990 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 127/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8201 - acc: 0.6958 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 128/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8167 - acc: 0.6976 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 129/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8189 - acc: 0.6966 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 130/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8233 - acc: 0.6959 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 131/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8200 - acc: 0.6962 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 132/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8160 - acc: 0.6983 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 133/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8240 - acc: 0.6943 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 134/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8200 - acc: 0.6955 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 135/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8133 - acc: 0.7001 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 136/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8153 - acc: 0.6978 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 137/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8168 - acc: 0.6985 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 138/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8162 - acc: 0.6961 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 139/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8082 - acc: 0.6993 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 140/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8215 - acc: 0.6973 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 141/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8140 - acc: 0.6976 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 142/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8186 - acc: 0.6979 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 143/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8214 - acc: 0.6968 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 144/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8227 - acc: 0.6980 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 145/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8194 - acc: 0.6947 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 146/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8206 - acc: 0.6968 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 147/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8146 - acc: 0.6979 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 148/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8128 - acc: 0.6995 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 149/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8206 - acc: 0.6998 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 150/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8127 - acc: 0.6996 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 151/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8151 - acc: 0.6973 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 152/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8193 - acc: 0.6946 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 153/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8151 - acc: 0.6992 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 154/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8197 - acc: 0.6957 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 155/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8192 - acc: 0.6962 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 156/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8192 - acc: 0.6976 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 157/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8205 - acc: 0.6950 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 158/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8190 - acc: 0.6944 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 159/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8191 - acc: 0.6960 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 160/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8157 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 161/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8193 - acc: 0.6964 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 162/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8184 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 163/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8158 - acc: 0.6977 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 164/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8190 - acc: 0.6963 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 165/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8129 - acc: 0.6999 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 166/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8154 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 167/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8232 - acc: 0.6940 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 168/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8211 - acc: 0.6959 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 169/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8221 - acc: 0.6950 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 170/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8115 - acc: 0.7006 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 171/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8163 - acc: 0.6982 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 172/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8178 - acc: 0.6982 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 173/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8215 - acc: 0.6968 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 174/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8144 - acc: 0.6979 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 175/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8215 - acc: 0.6975 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 176/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8201 - acc: 0.6946 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 177/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8213 - acc: 0.6962 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 178/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8225 - acc: 0.6937 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 179/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8143 - acc: 0.6963 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 180/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8144 - acc: 0.6991 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 181/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8112 - acc: 0.7000 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 182/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8160 - acc: 0.6971 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 183/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8162 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 184/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8161 - acc: 0.6974 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 185/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8244 - acc: 0.6951 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 186/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8145 - acc: 0.6978 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 187/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8178 - acc: 0.6961 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 188/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8178 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 189/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8149 - acc: 0.6982 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 190/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8164 - acc: 0.6974 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 191/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8171 - acc: 0.6982 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 192/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8162 - acc: 0.6971 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 193/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8224 - acc: 0.6935 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 194/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8142 - acc: 0.6966 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 195/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8125 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 196/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8149 - acc: 0.6967 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 197/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8147 - acc: 0.6978 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 198/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8152 - acc: 0.6991 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 199/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8167 - acc: 0.6967 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 200/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8198 - acc: 0.6977 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 201/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8133 - acc: 0.6981 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 202/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8154 - acc: 0.6973 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 203/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8189 - acc: 0.6951 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 204/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8218 - acc: 0.6965 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 205/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8160 - acc: 0.6980 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 206/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8149 - acc: 0.6985 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 207/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8192 - acc: 0.6960 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 208/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8204 - acc: 0.6941 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 209/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8183 - acc: 0.6960 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 210/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8164 - acc: 0.6978 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 211/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8193 - acc: 0.6963 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 212/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8162 - acc: 0.6998 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 213/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8170 - acc: 0.6987 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 214/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8100 - acc: 0.7022 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 215/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8161 - acc: 0.6984 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 216/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8200 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 217/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8166 - acc: 0.6998 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 218/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8204 - acc: 0.6945 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 219/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8132 - acc: 0.6988 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 220/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8155 - acc: 0.6959 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 221/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8183 - acc: 0.6982 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 222/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8135 - acc: 0.7000 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 223/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8161 - acc: 0.6952 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 224/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8101 - acc: 0.7006 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 225/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8172 - acc: 0.6993 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 226/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8226 - acc: 0.6945 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 227/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8174 - acc: 0.6977 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 228/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8169 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 229/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8190 - acc: 0.6966 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 230/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8211 - acc: 0.6953 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 231/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8127 - acc: 0.6992 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 232/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8216 - acc: 0.6959 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 233/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8189 - acc: 0.6960 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 234/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8194 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 235/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8189 - acc: 0.6952 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 236/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8125 - acc: 0.6981 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 237/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8196 - acc: 0.6963 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 238/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8108 - acc: 0.7002 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 239/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8219 - acc: 0.6936 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 240/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8123 - acc: 0.6992 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 241/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8188 - acc: 0.6944 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 242/300
50000/50000 [==============================] - 5s 98us/step - loss: 0.8181 - acc: 0.6948 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 243/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8092 - acc: 0.7000 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 244/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8216 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 245/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8175 - acc: 0.6957 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 246/300
50000/50000 [==============================] - 5s 98us/step - loss: 0.8182 - acc: 0.6964 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 247/300
50000/50000 [==============================] - 5s 99us/step - loss: 0.8148 - acc: 0.6961 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 248/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8193 - acc: 0.6961 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 249/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8129 - acc: 0.6992 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 250/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8190 - acc: 0.6959 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 251/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8139 - acc: 0.6994 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 252/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8177 - acc: 0.6957 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 253/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8137 - acc: 0.6941 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 254/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8306 - acc: 0.6905 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 255/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8155 - acc: 0.6968 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 256/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8159 - acc: 0.6956 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 257/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8185 - acc: 0.6974 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 258/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8140 - acc: 0.6959 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 259/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8174 - acc: 0.6978 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 260/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8153 - acc: 0.6971 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 261/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8177 - acc: 0.6973 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 262/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8171 - acc: 0.6964 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 263/300
50000/50000 [==============================] - 5s 105us/step - loss: 0.8164 - acc: 0.6958 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 264/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8191 - acc: 0.6990 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 265/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8180 - acc: 0.6963 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 266/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8171 - acc: 0.6964 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 267/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8165 - acc: 0.6958 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 268/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8160 - acc: 0.6964 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 269/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8167 - acc: 0.6960 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 270/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8178 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 271/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8169 - acc: 0.6965 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 272/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8167 - acc: 0.6968 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 273/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8145 - acc: 0.6972 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 274/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8141 - acc: 0.6996 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 275/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8093 - acc: 0.6998 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 276/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8141 - acc: 0.6996 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 277/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8206 - acc: 0.6971 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 278/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8138 - acc: 0.6987 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 279/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8216 - acc: 0.6955 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 280/300
50000/50000 [==============================] - 5s 105us/step - loss: 0.8155 - acc: 0.6974 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 281/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8173 - acc: 0.6944 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 282/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8137 - acc: 0.6976 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 283/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8183 - acc: 0.6965 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 284/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8156 - acc: 0.6995 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 285/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8142 - acc: 0.6981 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 286/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8125 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 287/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8139 - acc: 0.6982 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 288/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8189 - acc: 0.6980 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 289/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8139 - acc: 0.6990 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 290/300
50000/50000 [==============================] - 5s 106us/step - loss: 0.8103 - acc: 0.6983 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 291/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8158 - acc: 0.6974 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 292/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8148 - acc: 0.6978 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 293/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8171 - acc: 0.6976 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 294/300
50000/50000 [==============================] - 5s 100us/step - loss: 0.8137 - acc: 0.6962 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 295/300
50000/50000 [==============================] - 5s 104us/step - loss: 0.8163 - acc: 0.6979 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 296/300
50000/50000 [==============================] - 5s 107us/step - loss: 0.8168 - acc: 0.6974 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 297/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8153 - acc: 0.6970 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 298/300
50000/50000 [==============================] - 5s 101us/step - loss: 0.8130 - acc: 0.7007 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 299/300
50000/50000 [==============================] - 5s 102us/step - loss: 0.8170 - acc: 0.6979 - val_loss: 1.0531 - val_acc: 0.6419
Epoch 300/300
50000/50000 [==============================] - 5s 103us/step - loss: 0.8178 - acc: 0.6985 - val_loss: 1.0531 - val_acc: 0.6419






    
Out[30]:





<keras.callbacks.History at 0x7fcf0e9cfef0>

In [ ]: