sigmoidVsReluModel1

model1 = models.Sequential()
model1.add(layers.Dense(16, activation='relu', input_shape=(10000,)))
model1.add(layers.Dense(16, activation='relu'))
model1.add(layers.Dense(1, activation='sigmoid'))

model1.compile(optimizer='rmsprop',
                loss='binary_crossentropy',
                metrics=['acc'])

history1 = model1.fit(partial_x_train,
                 partial_y_train,
                 epochs=epochs,
                 batch_size=512,
                 validation_data=(x_val, y_val))