code: def test_fit_with_invalid_sample_weights(self):
      dataset = random_transformer_dataset(10)
  
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      classifier = TransformerBasedClassification(model_args, 2)
  
      weights = np.random.randn(len(dataset))
      weights[0] = -1
  
      with self.assertRaisesRegex(
          ValueError, "Weights must be greater zero."
      ):
          classifier.fit(dataset, weights=weights)
  
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 8 for calling the TestTransformerBasedClassification obj's underlying member method code with example usage: obj.test_fit_with_invalid_sample_weights() without return types