code: def test_fit_with_model_selection_default(self):
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      classifier = TransformerBasedClassification(
          model_args,
          4,
          multi_label=self.multi_label,
          class_weight="balanced",
          num_epochs=1,
      )
  
      train_set = self._get_dataset(num_samples=10)
      validation_set = self._get_dataset(num_samples=10)
  
      with patch.object(
          classifier, "_fit_main", wraps=classifier._fit_main
      ) as fit_main_spy:
          classifier.fit(train_set, validation_set=validation_set)
  
          self.assertEqual(1, fit_main_spy.call_count)
          early_stopping_arg = fit_main_spy.call_args_list[0].args[4]
          self.assertTrue(
              isinstance(early_stopping_arg, ModelSelection)
          )
  
imports: import unittest
  import pytest
  import warnings
  import numpy
  from unittest import mock
  from unittest.mock import patch, Mock
  from parameterized import parameterized_class
  from scipy.sparse import issparse
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from small_text.training.early_stopping import EarlyStopping, NoopEarlyStopping
  from small_text.training.metrics import Metric
  from small_text.training.model_selection import ModelSelection, NoopModelSelection
  from tests.utils.datasets import twenty_news_transformers
  from tests.utils.testing import assert_array_not_equal
label_desc: Use image node_id 16 for calling the _TransformerBasedClassificationTest obj's underlying member method code with example usage: obj.test_fit_with_model_selection_default() without return types