code: def test_fit_validate(self):
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      clf = TransformerBasedClassification(
          model_args,
          4,
          multi_label=self.multi_label,
          class_weight="balanced",
          num_epochs=1,
      )
  
      train_set = self._get_dataset(num_samples=20)
      valid_set = self._get_dataset(num_samples=5)
  
      clf.fit(train_set)
  
      with mock.patch.object(
          clf.model, "eval", wraps=clf.model.eval
      ) as model_eval_spy, mock.patch.object(
          clf.model, "train", wraps=clf.model.train
      ) as model_train_spy:
          valid_loss, valid_acc = clf.validate(valid_set)
  
          model_eval_spy.assert_called()
          model_train_spy.assert_called_once_with(False)
  
      self.assertTrue(valid_loss >= 0)
      self.assertTrue(0.0 <= valid_acc <= 1.0)
  
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 9 for calling the _TransformerBasedClassificationTest obj's underlying member method code with example usage: obj.test_fit_validate() without return types