code: def test_init(self):
      model_args = TransformerModelArguments("bert-base-uncased")
      num_classes = 2
      classifier = TransformerBasedClassification(
          model_args, num_classes
      )
      self.assertEqual(num_classes, classifier.num_classes)
      self.assertFalse(classifier.multi_label)
      self.assertEqual(10, classifier.num_epochs)
      self.assertEqual(2e-5, classifier.lr)
      self.assertEqual(12, classifier.mini_batch_size)
      self.assertIsNone(classifier.criterion)
      self.assertEqual(0.1, classifier.validation_set_size)
      self.assertEqual(1, classifier.validations_per_epoch)
      self.assertEqual(5, classifier.early_stopping_no_improvement)
      self.assertEqual(-1, classifier.early_stopping_acc)
      self.assertTrue(classifier.model_selection)
      self.assertIsNone(classifier.fine_tuning_arguments)
      self.assertIsNotNone(classifier.device)
      self.assertEqual(1, classifier.memory_fix)
      self.assertIsNone(classifier.class_weight)
      self.assertEqual(VERBOSITY_MORE_VERBOSE, classifier.verbosity)
      self.assertEqual(
          ".active_learning_lib_cache/", classifier.cache_dir
      )
  
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 1 for calling the TestTransformerBasedClassification obj's underlying member method code with example usage: obj.test_init() without return types