code: def test_fit_with_early_stopping_and_fall_back_simultaneously(self):
      dataset = random_transformer_dataset(10)
  
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      early_stopping = EarlyStopping(Metric("val_loss"))
  
      classifier = TransformerBasedClassification(
          model_args, 2, early_stopping_no_improvement=7
      )
      with self.assertWarnsRegex(
          UserWarning, r"Both the fit\(\) argument early_stopping"
      ):
          classifier.fit(dataset, early_stopping=early_stopping)
  
      classifier = TransformerBasedClassification(
          model_args, 2, early_stopping_acc=0.98
      )
      with self.assertWarnsRegex(
          UserWarning, r"Both the fit\(\) argument early_stopping"
      ):
          classifier.fit(dataset, early_stopping=early_stopping)
  
imports: import unittest
  import pytest
  import numpy
  from unittest.mock import patch
  from small_text.base import LABEL_UNLABELED
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from small_text.training.early_stopping import EarlyStopping, EarlyStoppingOrCondition
  from small_text.training.metrics import Metric
  from small_text.utils.logging import VERBOSITY_MORE_VERBOSE
label_desc: Use image node_id 11 for calling the TestTransformerBasedClassification obj's underlying member method code with example usage: obj.test_fit_with_early_stopping_and_fall_back_simultaneously() without return types