docstr: Initialize the `ArgillaSpaCyTransformersTrainer` class.
  
  Args:
      update_transformer: A `bool` indicating whether to update the transformer
          weights during the training. Defaults to True.
      **kwargs: The `ArgillaSpaCyTrainerBase` arguments.
docstr_tok: ["Initialize","the","`","ArgillaSpaCyTransformersTrainer","`","class",".","Args",":","update_transformer",":","A","`","bool","`","indicating","whether","to","update","the","transformer","weights","during","the","training",".","Defaults","to","True",".","*","*","kwargs",":","The","`","ArgillaSpaCyTrainerBase","`","arguments","."]
code: def __init__(self, update_transformer: bool = True, **kwargs) -> None:
      """Initialize the `ArgillaSpaCyTransformersTrainer` class.
  
      Args:
          update_transformer: A `bool` indicating whether to update the transformer
              weights during the training. Defaults to True.
          **kwargs: The `ArgillaSpaCyTrainerBase` arguments.
      """
      self.update_transformer = update_transformer
      _ArgillaSpaCyTrainerBase.__init__(self, **kwargs)
  
imports: import logging
  from pathlib import Path
  from tempfile import TemporaryDirectory
  from typing import TYPE_CHECKING, Optional
  from typing_extensions import Literal
  from argilla.client.feedback.training.base import ArgillaTrainerSkeleton
  from argilla.client.models import TextClassificationRecord, TokenClassificationRecord
  from argilla.training.spacy import ArgillaSpaCyTrainer
  from argilla.training.spacy import ArgillaSpaCyTransformersTrainer
  from argilla.training.spacy import _ArgillaSpaCyTrainerBase
  from argilla.utils.dependency import require_dependencies, requires_dependencies
label_desc: Use image node_id 1 to create a new ArgillaSpaCyTransformersTrainer object from inherited base classes: ArgillaSpaCyTransformersTrainerV1, _ArgillaSpaCyTrainerBase with example: obj = ArgillaSpaCyTransformersTrainer(update_transformer)