  logs (the first one is used if you deactivate tqdm through the [TrainingArguments], otherwise
  it's the second one).
[~integrations.TensorBoardCallback] if tensorboard is accessible (either through PyTorch >= 1.4
  or tensorboardX).
[~integrations.WandbCallback] if wandb is installed.
[~integrations.CometCallback] if comet_ml is installed.
[~integrations.MLflowCallback] if mlflow is installed.
[~integrations.AzureMLCallback] if azureml-sdk is
  installed.
The main class that implements callbacks is [TrainerCallback]. It gets the
[TrainingArguments] used to instantiate the [Trainer], can access that
Trainer's internal state via [TrainerState], and can take some actions on the training loop via
[TrainerControl].
Available Callbacks
Here is the list of the available [TrainerCallback] in the library:
