model=models.Sequential()

model.add(layers.Dense(16,activation="relu",input_shape=(10000,)))
model.add(layers.Dense(16,activation="relu"))
model.add(layers.Dense(1,activation="sigmoid"))

model.compile(optimizer="rmsprop",loss="binary_crossentropy",metrics=["accuracy"])

model.fit(x_train,y_train,epochs=4,batch_size=512)
results=model.evaluate(x_test,y_test)