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60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
import json
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from datasets import Dataset
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from opencompass.openicl.icl_evaluator import BaseEvaluator
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from opencompass.registry import LOAD_DATASET
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from .base import BaseDataset
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@LOAD_DATASET.register_module()
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class QuALITYDataset(BaseDataset):
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@staticmethod
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def load(path: str):
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dataset_list = []
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with open(path, 'r', encoding='utf-8') as f:
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for line in f:
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line = json.loads(line)
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for question in line['questions']:
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dataset_list.append({
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'article':
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line['article'],
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'question':
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question['question'],
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'A':
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question['options'][0],
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'B':
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question['options'][1],
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'C':
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question['options'][2],
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'D':
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question['options'][3],
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'gold_label':
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'ABCD'[question['gold_label'] - 1],
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'difficult':
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question['difficult']
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})
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return Dataset.from_list(dataset_list)
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class QuALITYEvaluator(BaseEvaluator):
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def score(self, predictions, references, test_set):
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assert len(predictions) == len(references)
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easy, hard, all = [], [], []
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for pred, refer, test in zip(predictions, references, test_set):
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if pred == refer:
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answer = True
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else:
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answer = False
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all.append(answer)
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if test['difficult'] == 0:
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easy.append(answer)
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else:
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hard.append(answer)
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return dict(easy_acc=sum(easy) / len(easy) * 100,
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hard_acc=sum(hard) / len(easy) * 100,
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all_acc=sum(all) / len(all) * 100)
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