Saves model topology, losses & metrics

WandbCallback(
  log = "gradients",
  log_preds = TRUE,
  log_model = TRUE,
  log_dataset = FALSE,
  dataset_name = NULL,
  valid_dl = NULL,
  n_preds = 36,
  seed = 12345,
  reorder = TRUE
)

Arguments

log

"gradients" (default), "parameters", "all" or None. Losses & metrics are always logged.

log_preds

whether we want to log prediction samples (default to True).

log_model

whether we want to log our model (default to True). This also requires SaveModelCallback.

log_dataset

Options: - False (default) - True will log folder referenced by learn.dls.path. - a path can be defined explicitly to reference which folder to log. Note: subfolder "models" is always ignored.

dataset_name

name of logged dataset (default to folder name).

valid_dl

DataLoaders containing items used for prediction samples (default to random items from learn.dls.valid.

n_preds

number of logged predictions (default to 36).

seed

used for defining random samples.

reorder

reorder or not

Value

None