def __repr__(self) -> str:
        """
        `trainer.__repr__()` prints out the trainer's parameters and a summary of how to use the trainer

        Returns:
          The trainer object.
        """
        return f"""\
ArgillaBaseTrainer info:
_________________________________________________________________
These baseline params are fixed:
    dataset: {self._name}
    task: {self._rg_dataset_type.__name__}
    multi_label: {self._multi_label}
    train_size: {self._train_size}
    seed: {self._seed}

{self._trainer.__class__} info:
_________________________________________________________________
The parameters are configurable via `trainer.update_config()`:
    {self._trainer}

Using the trainer:
_________________________________________________________________
`trainer.train(output_dir)` to train to start training. `output_dir` is the directory to save the model automatically.
`trainer.predict(text, as_argilla_records=True)` to make predictions.
`trainer.save(output_dir)` to save the model manually."""

        `trainer.__repr__()` prints out the trainer's parameters and a summary of how to use the trainer

        Returns:
          The trainer object.
        
argilla-v1/src/argilla_v1/training/base.py