pytorchtoolsο
Module containing EarlyStopping
to track when the training of a model should stop.
Source: https://github.com/Bjarten/early-stopping-pytorch
- class EarlyStopping(patience: int = 7, verbose: bool = False, delta: float = 0.0, path: str | ~pathlib.Path = 'checkpoint.pt', trace_func: ~typing.Callable[[...], None] = <built-in function print>, external_save: bool = False)ο
Early stops the training if validation loss doesnβt improve after a given patience.
- early_stopο
Will be
True
if early stopping is triggered bypatience
number of validation epochs with worsening validation losses consecutively.- Type:
- Parameters:
patience (int) β How long to wait after last time validation loss improved. Default:
7
verbose (bool) β If
True
, prints a message for each validation loss improvement. Default:False
delta (float) β Minimum change in the monitored quantity to qualify as an improvement. Default:
0
path (str) β Path for the checkpoint to be saved to. Default:
'checkpoint.pt'
trace_func (Callable[..., None]) β Trace print function. Default:
print()
external_save (bool) β If True, will not save the model here, but will activate a
save_model
flag indicating that the model should be saved by the user. If False, will save the model automaticallly usingtorch
.