What is the Callbacks class in transformers?

This recipe explains what is Callbacks class in transformers.

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Recipe Objective - What is the Callbacks class in transformers?

Callbacks are objects which will customize the behavior of the training cycle in PyTorch Trainer (this feature isn't yet implemented in TensorFlow), and may check the status of the training cycle (get progress reports, log in to TensorBoard or other ML platforms) and make decisions (for example early stopping).

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By default a Trainer will use the subsequent callbacks:
1. DefaultFlowCallback which handles the default behavior for logging, saving and evaluation.
2. PrinterCallback or ProgressCallback to display progress and print the logs (the first one is used if you deactivate tqdm through the TrainingArguments, otherwise it’s the second one).
3. TensorBoardCallback if tensorboard is accessible (either through PyTorch >= 1.4 or tensorboardX).
4. WandbCallback if wandb is installed.
5. CometCallback if comet_ml is installed.
6. MLflowCallback if mlflow is installed.
7. AzureMLCallback if azureml-sdk is installed.

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