code: def test_train_stsb(
      distilroberta_base_ce_model: CrossEncoder,
      sts_resource: Tuple[List[InputExample], List[InputExample]],
  ) -> None:
      model = distilroberta_base_ce_model
      sts_train_samples, sts_test_samples = sts_resource
      train_dataloader = DataLoader(
          sts_train_samples[:500], shuffle=True, batch_size=16
      )
      model.fit(
          train_dataloader=train_dataloader,
          epochs=1,
          warmup_steps=int(len(train_dataloader) * 0.1),
      )
      evaluate_stsb_test(
          model, 50, sts_test_samples, num_test_samples=100
      )
  
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 5 for calling a global function with example usage: test_train_stsb(distilroberta_base_ce_model, sts_resource) without return types