Sentiment.py 文件源码

def train_model(self, batch_size=32, nb_epoch=50,load_data = False,old_weight_path=''):
        print("start training model...")

        if load_data:
            train_data, train_labels, valid_data, valid_labels = self.load_data()
        else:
            train_data, train_labels, valid_data, valid_labels = self.prepare_train_data()

        model = self.baseModel()

        if old_weight_path != '':
            print("load last epoch model to continue train")
            model.load_weights(old_weight_path)

        model.fit(train_data, train_labels, batch_size=batch_size,
                  epochs=nb_epoch,
                  validation_data=(valid_data, valid_labels),
                  callbacks=[ModelCheckpoint("output/weights.{epoch:02d}-{val_loss:.2f}.hdf5",
                                             monitor='val_loss',
                                             verbose=1,
                                             save_best_only=True, save_weights_only=False, mode='min', period=2),
                             ProgbarLogger()])

        return model