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51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
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from typing import List
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from datasets import Dataset
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from opencompass.openicl import BaseEvaluator
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from opencompass.registry import ICL_EVALUATORS, LOAD_DATASET
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from ..base import BaseDataset
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from .utils import iter_jsonl
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@LOAD_DATASET.register_module()
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class InfiniteBenchendiaDataset(BaseDataset):
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@staticmethod
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def load(path: str):
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dataset = list(iter_jsonl(path))
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raw_data = []
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for item in dataset:
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context = item['context']
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question = item['input']
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answer = item['answer']
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raw_data.append({
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'context': context,
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'question': question,
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'answer': answer
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})
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dataset = Dataset.from_list(raw_data)
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return dataset
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@ICL_EVALUATORS.register_module()
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class InfiniteBenchendiaEvaluator(BaseEvaluator):
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def score(self, predictions: List, references: List) -> dict:
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score = 0.
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for i in range(len(predictions)):
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prediction = predictions[i]
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reference = references[i][0]
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for c in ['\n', ':', '"', "'", '.', ',', '?', '!', '{', '}']:
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prediction = prediction.replace(c, ' ')
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words = prediction.split()
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words = [x.upper() for x in words]
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if reference in words:
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score += 1
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score = score / len(predictions) * 100
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return {'score': score}
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