langtest.callback.LangTestCallback#

class LangTestCallback(task, config=None, data=None, print_reports=True, save_reports=False, run_each_epoch=False)#

Bases: TrainerCallback

__init__(task, config=None, data=None, print_reports=True, save_reports=False, run_each_epoch=False) → None#

Methods

__init__(task[, config, data, ...])
on_epoch_begin(args, state, control, **kwargs)	Event called at the beginning of an epoch.
on_epoch_end(args, state, control, **kwargs)	Event called at the end of an epoch.
on_evaluate(args, state, control, **kwargs)	Event called after an evaluation phase.
on_init_end(args, state, control, **kwargs)	Event called at the end of the initialization of the [Trainer].
on_log(args, state, control, **kwargs)	Event called after logging the last logs.
on_predict(args, state, control, metrics, ...)	Event called after a successful prediction.
on_prediction_step(args, state, control, ...)	Event called after a prediction step.
on_save(args, state, control, **kwargs)	Event called after a checkpoint save.
on_step_begin(args, state, control, **kwargs)	Event called at the beginning of a training step.
on_step_end(args, state, control, **kwargs)	Event called at the end of a training step.
on_substep_end(args, state, control, **kwargs)	Event called at the end of an substep during gradient accumulation.
on_train_begin(args, state, control, **kwargs)	Event called at the beginning of training.
on_train_end(args, state, control, **kwargs)	Event called at the end of training.

on_epoch_begin(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called at the beginning of an epoch.

on_epoch_end(args, state, control, **kwargs)#

Event called at the end of an epoch.

on_evaluate(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called after an evaluation phase.

on_init_end(args, state, control, **kwargs)#

Event called at the end of the initialization of the [Trainer].

on_log(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called after logging the last logs.

on_predict(args: TrainingArguments, state: TrainerState, control: TrainerControl, metrics, **kwargs)#

Event called after a successful prediction.

on_prediction_step(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called after a prediction step.

on_save(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called after a checkpoint save.

on_step_begin(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called at the beginning of a training step. If using gradient accumulation, one training step might take several inputs.

on_step_end(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called at the end of a training step. If using gradient accumulation, one training step might take several inputs.

on_substep_end(args: TrainingArguments, state: TrainerState, control: TrainerControl, **kwargs)#

Event called at the end of an substep during gradient accumulation.

on_train_begin(args, state, control, **kwargs)#

Event called at the beginning of training.

on_train_end(args, state, control, **kwargs)#

Event called at the end of training.