code: def test_validate_with_validations_per_epoch_too_large(self):
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      clf = TransformerBasedClassification(
          model_args,
          4,
          multi_label=self.multi_label,
          num_epochs=2,
          mini_batch_size=20,
          validations_per_epoch=3,
      )
  
      train_set = self._get_dataset(num_samples=20)
  
      with patch.object(
          clf, "validate", wraps=clf.validate
      ) as validate_spy, patch(
          "torch.nn.modules.module.Module.eval"
      ) as eval_spy, patch(
          "torch.nn.modules.module.Module.train"
      ) as train_spy, warnings.catch_warnings(
          record=True
      ) as w:
          clf.fit(train_set)
          self.assertIsNotNone(clf.model)
  
          # 2 since we have 2 epochs with 1 batches (and one validate call) each
          self.assertEqual(2, validate_spy.call_count)
  
          expected_warning = (
              "validations_per_epoch=3 is greater than the maximum "
              "possible batches of 1"
          )
          found_warning = np.any(
              [
                  str(w_.message) == expected_warning
                  and w_.category == RuntimeWarning
                  for w_ in w
              ]
          )
          self.assertTrue(found_warning)
          self.assertEqual(4, train_spy.call_count)
          # once per epoch (after the call to validate) plus one call during initialization in from_pretrained()
          self.assertEqual(3, eval_spy.call_count)
  
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 11 for calling the _TransformerBasedClassificationTest obj's underlying member method code with example usage: obj.test_validate_with_validations_per_epoch_too_large() without return types