如何使用Keras获取val_loss和val_acc指标

from keras.models import Sequential
from keras.layers import Dense
from keras.callbacks import Callback

model = Sequential()
model.add(Dense(64, activation='relu', input_dim=100))
model.add(Dense(64, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

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

class MetricsCallback(Callback):
    def on_epoch_end(self, epoch, logs=None):
        val_loss = logs['val_loss']
        val_acc = logs['val_acc']
        print("val_loss: {:.4f} - val_acc: {:.4f}".format(val_loss, val_acc))

model.fit(x_train, y_train, validation_data=(x_val, y_val), epochs=10, callbacks=[MetricsCallback()])