code: def evaluate_stsb_test(
      distilroberta_base_ce_model: CrossEncoder,
      expected_score: float,
      test_samples: List[InputExample],
      num_test_samples: int = -1,
  ) -> None:
      model = distilroberta_base_ce_model
      evaluator = CECorrelationEvaluator.from_input_examples(
          test_samples[:num_test_samples], name="sts-test"
      )
      score = evaluator(model) * 100
      print(
          "STS-Test Performance: {:.2f} vs. exp: {:.2f}".format(
              score, expected_score
          )
      )
      assert score > expected_score or abs(score - expected_score) < 0.1
  
file_path: sentence-transformers/tests/test_cross_encoder.py
imports: import csv
  import gzip
  import os
  import pytest
  from torch.utils.data import DataLoader
  from sentence_transformers import CrossEncoder, util
  from sentence_transformers.cross_encoder.evaluation import CECorrelationEvaluator
  from sentence_transformers.readers import InputExample
  from typing import Generator, List, Tuple
label_desc: Use image node_id 2 for calling a global function with example usage: evaluate_stsb_test(distilroberta_base_ce_model, expected_score, test_samples, num_test_samples) without return types