将每个批次或时期的验证精度打印到控制台(Keras)

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

# 假设你已经有了一个模型和一个数据集
model = Sequential()
# 添加你的层...

# 编译模型
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])

# 创建一个ModelCheckpoint回调，但不保存模型，只是用来获取验证精度
checkpoint = ModelCheckpoint(filepath=None, monitor='val_accuracy', verbose=1, save_best_only=False)

# 自定义回调来打印验证精度
class PrintValidationAccuracy(keras.callbacks.Callback):
    def on_epoch_end(self, epoch, logs=None):
        print(f'\nEpoch {epoch + 1} validation accuracy: {logs["val_accuracy"]}')

# 训练模型时使用回调
model.fit(x_train, y_train, epochs=10, batch_size=32, validation_data=(x_val, y_val), callbacks=[checkpoint, PrintValidationAccuracy()])