def _f1_score(target, prediction):
  """Computes token f1 score for a single target and prediction."""
  prediction_tokens = prediction.split()
  target_tokens = target.split()
  common = (collections.Counter(prediction_tokens) &
            collections.Counter(target_tokens))
  num_same = sum(common.values())
  if num_same == 0:
    return 0
  precision = 1.0 * num_same / len(prediction_tokens)
  recall = 1.0 * num_same / len(target_tokens)
  f1 = (2 * precision * recall) / (precision + recall)
  return f1
Computes token f1 score for a single target and prediction.
llm_retriever/src/evaluation/qa_utils.py