callback_early_stopping | R Documentation |
Stop training when a monitored quantity has stopped improving.
callback_early_stopping(
monitor = "val_loss",
min_delta = 0,
patience = 0,
verbose = 0,
mode = c("auto", "min", "max"),
baseline = NULL,
restore_best_weights = FALSE
)
monitor |
quantity to be monitored. |
min_delta |
minimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement. |
patience |
number of epochs with no improvement after which training will be stopped. |
verbose |
verbosity mode, 0 or 1. |
mode |
one of "auto", "min", "max". In |
baseline |
Baseline value for the monitored quantity to reach. Training will stop if the model doesn't show improvement over the baseline. |
restore_best_weights |
Whether to restore model weights from
the epoch with the best value of the monitored quantity.
If |
Other callbacks:
callback_csv_logger()
,
callback_lambda()
,
callback_learning_rate_scheduler()
,
callback_model_checkpoint()
,
callback_progbar_logger()
,
callback_reduce_lr_on_plateau()
,
callback_remote_monitor()
,
callback_tensorboard()
,
callback_terminate_on_naan()
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