Saving during training with checkpoint_callback

[Ecostate]

Hello everyone,

I need your help. I'm using the NBEATSx model and I want to save my model during training based on the valid_loss.
Therefore, I'm using the following callback:

checkpoint_callback = ModelCheckpoint(
monitor='valid_loss',
dirpath='checkpoints',
filename='alpha{epoch:02d}-{valid_loss:.5f}',
save_top_k=1,
verbose=True,
mode='min',

model = NBEATSx(
h=step_forward,
callbacks=[checkpoint_callback],
enable_checkpointing=True,
…
lr_scheduler=torch.optim.lr_scheduler.StepLR,
lr_scheduler_kwargs={
'step_size': step_by_epoch,
'gamma': 0.1
},
….
nf = NeuralForecast(
models=[model],
freq=240
)
nf.fit(df=train_data, val_size=valid_size)_

When I try to load my model with :
checkpoint = NeuralForecast.load(path='./checkpoints/test_run', verbose=True)

I get the following message:

Found more than one stateful callback of type EarlyStopping. In the current configuration, this callback does not support being saved alongside other instances of the same type. Please consult the documentation of EarlyStopping regarding valid settings for the callback state to be checkpointable. HINT: The callback.state_key must be unique among all callbacks in the Trainer.

How can I fix this problem? Thank you very much!