callback_model_checkpoint | R Documentation |
filepath
can contain named formatting options, which will be filled the
value of epoch
and keys in logs
(passed in on_epoch_end
). For example:
if filepath
is weights.{epoch:02d}-{val_loss:.2f}.hdf5
, then the model
checkpoints will be saved with the epoch number and the validation loss in
the filename.
callback_model_checkpoint(
filepath,
monitor = "val_loss",
verbose = 0,
save_best_only = FALSE,
save_weights_only = FALSE,
mode = c("auto", "min", "max"),
period = NULL,
save_freq = "epoch"
)
filepath |
string, path to save the model file. |
monitor |
quantity to monitor. |
verbose |
verbosity mode, 0 or 1. |
save_best_only |
if |
save_weights_only |
if |
mode |
one of "auto", "min", "max". If |
period |
Interval (number of epochs) between checkpoints. |
save_freq |
|
if filepath
is
weights.{epoch:02d}-{val_loss:.2f}.hdf5
,: then the model checkpoints will
be saved with the epoch number and the validation loss in the filename.
Other callbacks:
callback_csv_logger()
,
callback_early_stopping()
,
callback_lambda()
,
callback_learning_rate_scheduler()
,
callback_progbar_logger()
,
callback_reduce_lr_on_plateau()
,
callback_remote_monitor()
,
callback_tensorboard()
,
callback_terminate_on_naan()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.