code: def test_validate_with_validations_per_epoch(self):
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      clf = TransformerBasedClassification(
          model_args,
          4,
          multi_label=self.multi_label,
          num_epochs=1,
          mini_batch_size=10,
          validations_per_epoch=2,
      )
  
      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:
          clf.fit(train_set)
  
          self.assertIsNotNone(clf.model)
          self.assertEqual(2, validate_spy.call_count)
          self.assertEqual(3, train_spy.call_count)
          # once per validate (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 10 for calling the _TransformerBasedClassificationTest obj's underlying member method code with example usage: obj.test_validate_with_validations_per_epoch() without return types