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 textwrap.dedent(
            f"""\
            ArgillaBaseTrainer info:
            _________________________________________________________________
            These baseline params are fixed:
                dataset: {self._dataset}
                task: {self._task}
                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/client/feedback/training/base.py