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b5beb60 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | from ...smp import *
import os
def report_acc_hrbench(df):
cycle_group = df.groupby('cycle_category')
result_dic = defaultdict(list)
avg_dic = defaultdict(int)
count = 0
for key, data_value in cycle_group:
count += 1
_, resp_dic = hrbench_score(data_value)
for task_type, accuracy in resp_dic.items():
result_dic['cycle'].append(key)
result_dic['type'].append(task_type)
result_dic['accuracy'].append(accuracy)
avg_dic[task_type] += accuracy
for task_type, accuracy in avg_dic.items():
result_dic['cycle'].append('Average')
result_dic['type'].append(task_type)
result_dic['accuracy'].append(accuracy / count)
result_pd = pd.DataFrame(result_dic)
return result_pd
def hrbench_score(data):
ret = defaultdict(list)
resp_dic = {}
category_list = set(data['category'])
score_dict = defaultdict(list)
for i in range(len(data)):
d = data.iloc[i]
category = d['category']
gpt_score = d['hit']
score_dict[category].append(gpt_score)
score_dict['all'].append(gpt_score)
all_acc = np.mean(score_dict['all'])
ret['type'].append('all')
ret['acc'].append(all_acc)
resp_dic['all'] = all_acc
for cate in category_list:
acc = np.mean(score_dict[cate])
ret['type'].append(cate)
ret['acc'].append(acc)
resp_dic[cate] = acc
return pd.DataFrame(ret), resp_dic
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