code: def test_wp_train_effectiveness():
      happy = HappyWordPrediction(
          "DISTILBERT", "distilbert-base-uncased"
      )
      train_args = WPTrainArgs(max_length=512, num_train_epochs=3)
      eval_args = WPEvalArgs(max_length=512)
      before_result = happy.eval(
          "../data/wp/train-eval.txt", args=eval_args
      )
  
      happy.train("../data/wp/train-eval.txt", args=train_args)
      after_result = happy.eval(
          "../data/wp/train-eval.txt", args=eval_args
      )
  
      assert after_result.loss < before_result.loss
  
imports: from pytest import approx
  from happytransformer import HappyWordPrediction, WPTrainArgs, WPEvalArgs
  from happytransformer.happy_word_prediction import WordPredictionResult
  from tests.run_save_load import run_save_load
  import pytest
  from tests import happy_wp
label_desc: Use image node_id 8 for calling a global function with example usage: test_wp_train_effectiveness() without return types