model.compile(loss='binary_crossentropy',optimizer='adam', metrics=['accuracy'])

​

history = model.fit(X, Y, epochs=150,batch_size=10)

​

for score_fun in history.history.keys():

  plt.plot(history.history[score_fun])

  plt.title(f'model {score_fun}')

  plt.ylabel(score_fun)

  plt.xlabel('epoch')

  plt.legend([score_fun], loc='upper left')

  plt.show()