Блог

     def train(x,x_val,y,y_val,model, lr, epoch, batch_size,callbacks=None):
    opt = tf.keras.optimizers.Adam(learning_rate=lr)
    model.compile(optimizer=opt, loss='mse')
    reduce_lr = tf.keras.callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.5, patience=10, min_lr =1e-7,verbose=1)
    if callbacks is None:
        history=model.fit(x,y, batch_size = batch_size, epochs = epoch, shuffle=True, validation_data=(x_val, y_val))
    else :
        history=model.fit(x,y, batch_size=batch_size, epochs=epoch, shuffle=True, validation_data=(x_val, y_val),callbacks = [reduce_lr])
    loss = history.history['loss']
    val_loss = history.history['val_loss']
    loss_history_df = pd.DataFrame([loss,val_loss]).transpose()
    return loss_history_df

Dataset(x_train /x_val)

np.shape(x_train) --> (20675, 68, 36, 1)

np.shape(x_val) --> (2298, 68, 36, 1)
 

#Вопрос

Что бы вы ни выбрали batch_size, модель поезда всегда работает batch_size=1

Я не знаю причины этого……..

например

 batch_size = 16 or 8 or .. whatever
 

Эпоха 1/4000

 4976/20675 [======>.......................] - ETA: 8s - loss: 124.1429