code: def test_fbeta_worst_score():
      preds = [[0.7, 0.7, 0.7], [1, 0, 0], [0.9, 0.8, 0]]
      actuals = [[0, 0, 0], [0, 1, 0], [0, 0, 1]]
  
      for avg_val in ["micro", "macro", "weighted"]:
          for beta in [0.5, 1.0, 2.0]:
              _test_fbeta_score(
                  actuals, preds, None, avg_val, beta, 0.0, 0.66
              )
  
file_path: rasa/tests/utils/tensorflow/test_metrics.py
imports: import numpy
  import pytest
  import tensorflow
  from rasa.utils.tensorflow.metrics import FBetaScore, F1Score
label_desc: Use image node_id 5 for calling a global function with example usage: test_fbeta_worst_score() without return types