docstr: `trainer.__repr__()` prints out the trainer's parameters and a summary of how to use the trainer
  
  Returns:
    The trainer object.
docstr_tok: ["`","trainer.__repr__","(",")","`","prints","out","the","trainer","'s","parameters","and","a","summary","of","how","to","use","the","trainer","Returns",":","The","trainer","object","."]
code: 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.
              """
      )
  
imports: import os
  import textwrap
  import warnings
  from pathlib import Path
  from typing import TYPE_CHECKING, Dict, List, Optional, Union
  from argilla.client.feedback.schemas.records import FeedbackRecord
  from argilla.client.feedback.training.schemas.base import TrainingTaskForTextClassification, TrainingTaskTypes
  from argilla.client.models import Framework, TextClassificationRecord
  from argilla.training.base import ArgillaTrainer
  from argilla.training.base import ArgillaTrainerSkeleton
label_desc: Use image node_id 4 for calling the ArgillaTrainer obj's underlying member method code with example usage: obj.__repr__() and returns: textwrap