luz_callback_keep_best_model {luz} | R Documentation |
Keep the best model
Description
Each epoch, if there's improvement in the monitored metric we serialize the model weights to a temp file. When training is done, we reload weights from the best model.
Usage
luz_callback_keep_best_model(
monitor = "valid_loss",
mode = "min",
min_delta = 0
)
Arguments
monitor |
A string in the format |
mode |
Specifies the direction that is considered an improvement. By default 'min' is used. Can also be 'max' (higher is better) and 'zero' (closer to zero is better). |
min_delta |
Minimum improvement to reset the patience counter. |
See Also
Other luz_callbacks:
luz_callback_auto_resume()
,
luz_callback_csv_logger()
,
luz_callback_early_stopping()
,
luz_callback_interrupt()
,
luz_callback_lr_scheduler()
,
luz_callback_metrics()
,
luz_callback_mixup()
,
luz_callback_model_checkpoint()
,
luz_callback_profile()
,
luz_callback_progress()
,
luz_callback_resume_from_checkpoint()
,
luz_callback_train_valid()
,
luz_callback()
Examples
cb <- luz_callback_keep_best_model()