docstr: Returns dictionary with formatted evaluation scores 
docstr_tok: ["Returns","dictionary","with","formatted","evaluation","scores"]
code: def make_eval_dict(exact_scores, f1_scores, prefix=""):
      """Returns dictionary with formatted evaluation scores"""
  
      total = len(exact_scores)
      return collections.OrderedDict(
          [
              (
                  f"{prefix}exact",
                  (100.0 * sum(exact_scores.values()) / total)
                  if total != 0
                  else 0.0,
              ),
              (
                  f"{prefix}f1",
                  (100.0 * sum(f1_scores.values()) / total)
                  if total != 0
                  else 0.0,
              ),
              (f"{prefix}total", float(total)),
          ]
      )
  
imports: import collections
  import json
  import re
  import string
  import torch
  from tqdm import tqdm
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.utils import logging
label_desc: Use image node_id 10 for calling the QAMetrics obj's underlying member method code with example usage: obj.make_eval_dict(exact_scores, f1_scores, prefix) and returns: collections