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edab1c07ba
* add ceval, gsm8k modelscope surpport * update race, mmlu, arc, cmmlu, commonsenseqa, humaneval and unittest * update bbh, flores, obqa, siqa, storycloze, summedits, winogrande, xsum datasets * format file * format file * update dataset format * support ms_dataset * udpate dataset for modelscope support * merge myl_dev and update test_ms_dataset * udpate dataset for modelscope support * update readme * update eval_api_zhipu_v2 * remove unused code * add get_data_path function * update readme * remove tydiqa japanese subset * add ceval, gsm8k modelscope surpport * update race, mmlu, arc, cmmlu, commonsenseqa, humaneval and unittest * update bbh, flores, obqa, siqa, storycloze, summedits, winogrande, xsum datasets * format file * format file * update dataset format * support ms_dataset * udpate dataset for modelscope support * merge myl_dev and update test_ms_dataset * update readme * udpate dataset for modelscope support * update eval_api_zhipu_v2 * remove unused code * add get_data_path function * remove tydiqa japanese subset * update util * remove .DS_Store * fix md format * move util into package * update docs/get_started.md * restore eval_api_zhipu_v2.py, add environment setting * Update dataset * Update * Update * Update * Update --------- Co-authored-by: Yun lin <yunlin@U-Q9X2K4QV-1904.local> Co-authored-by: Yunnglin <mao.looper@qq.com> Co-authored-by: Yun lin <yunlin@laptop.local> Co-authored-by: Yunnglin <maoyl@smail.nju.edu.cn> Co-authored-by: zhangsongyang <zhangsongyang@pjlab.org.cn>
69 lines
2.1 KiB
Python
69 lines
2.1 KiB
Python
import re
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import json
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from datasets import Dataset, DatasetDict
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from opencompass.registry import LOAD_DATASET, TEXT_POSTPROCESSORS, ICL_EVALUATORS
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from opencompass.utils import get_data_path
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from opencompass.openicl.icl_evaluator import BaseEvaluator
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from ..base import BaseDataset
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from . import utils
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from tqdm import tqdm
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@LOAD_DATASET.register_module()
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class TheoremQADatasetV3(BaseDataset):
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@staticmethod
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def load(path: str):
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path = get_data_path(path, local_mode=True)
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with open(path, 'r') as f:
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data = json.load(f)
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for item in data:
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item['Answer'] = str(item['Answer'])
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dataset = Dataset.from_list(data)
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return dataset
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def TheoremQA_postprocess_v3(text: str) -> str:
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answer = utils.answer_clean(["The answer is:", "The answer is", "the answer is"], text)
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return answer
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@ICL_EVALUATORS.register_module()
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class TheoremQAEvaluatorV3(BaseEvaluator):
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def score(self, predictions, references, test_set):
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if len(predictions) != len(references):
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return {"error": "preds and refrs have different length"}
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details = []
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correct, wrong = 0, 0
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for index in tqdm(range(len(predictions))):
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answer = predictions[index]
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groundtruth = references[index]
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answer_type = test_set[index]['Answer_type']
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if answer_type in ['float', 'integer', 'bool']:
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groundtruth = [groundtruth, eval(groundtruth)]
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else:
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groundtruth = [groundtruth, None]
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if utils.compare_answer_with_groundtruth(answer, *groundtruth):
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correct += 1
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is_correct = True
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else:
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wrong += 1
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is_correct = False
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details.append(
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{
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# "question": question,
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# "solution": output,
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"correct": groundtruth,
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"pred": answer,
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"is_correct": is_correct,
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}
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)
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score = correct / (correct + wrong) * 100
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return {'score': score, 'details': details}
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