code: def compute_f1_score(
      predicted_answers, groundtruth_answer, exp_name="default"
  ):
      """Evaluating F1 Score"""
      print(len(predicted_answers), len(groundtruth_answer))
      if len(predicted_answers) != len(groundtruth_answer):
          groundtruth_answer = groundtruth_answer[
              : len(predicted_answers)
          ]
  
      guess_list = []
      answer_list = []
  
      assert len(guess_list) == len(
          answer_list
      ), "lengths of guess and answer are different!"
  
      for pred, ans in zip(predicted_answers, groundtruth_answer):
          pred = pred.strip()
          if type(ans) == str:
              ans = ans.strip()
          elif type(ans) == dict:
              ans = ans["text"].strip()
          elif ans == None:
              continue
          if "<|endoftext|>" in pred:
              pred = pred.replace("<|endoftext|>", "")
          if ans == "no_passages_used":
              ans = ""
          guess_list.append(pred)
          answer_list.append(ans)
  
      precision, recall, f1 = F1Metric.compute_all_pairs(
          guess_list, answer_list
      )
      print(
          "Method: %s; Precision: %.4f; recall: %.4f; f1: %.4f"
          % (exp_name, precision, recall, f1)
      )
  
file_path: megatron-lm/tools/retro/text_generation/evaluate.py
imports: import sys
  import os
  from tqdm import tqdm
  import string
  import json
  import regex
  import numpy
  from tools.retro.text_generation.metrics import F1Metric
label_desc: Use image node_id 2 for calling a global function with example usage: compute_f1_score(predicted_answers, groundtruth_answer, exp_name) without return types