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* [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * Update mmlu-cf * Update mmlu-cf * Update mmlu-cf * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * [Feature] Support MMLU-CF Benchmark * Remove outside configs --------- Co-authored-by: liushz <qq1791167085@163.com>
65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
from mmengine.config import read_base
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import FixKRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.openicl.icl_evaluator import AccwithDetailsEvaluator
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from opencompass.datasets import MMLUCFDataset
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from opencompass.utils.text_postprocessors import first_option_postprocess
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with read_base():
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from .mmlu_cf_categories import categories
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mmlu_cf_reader_cfg = dict(
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input_columns=['input', 'A', 'B', 'C', 'D'],
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output_column='target',
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train_split='dev')
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mmlu_cf_datasets = []
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for _name in categories:
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_hint = f'There is a single choice question. Answer the question by replying A, B, C or D.'
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mmlu_cf_infer_cfg = dict(
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ice_template=dict(
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type=PromptTemplate,
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template=dict(round=[
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dict(
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role='HUMAN',
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prompt=
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f'{_hint}\nQuestion: {{input}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nAnswer: '
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),
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dict(role='BOT', prompt='{target}\n')
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]),
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),
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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begin='</E>',
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round=[
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dict(
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role='HUMAN',
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prompt=f'{_hint}\nQuestion: {{input}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nAnswer: '
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),
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],
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),
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ice_token='</E>',
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),
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retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
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inferencer=dict(type=GenInferencer),
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)
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mmlu_cf_eval_cfg = dict(
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evaluator=dict(type=AccwithDetailsEvaluator),
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pred_postprocessor=dict(type=first_option_postprocess, options='ABCD'))
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mmlu_cf_datasets.append(
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dict(
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abbr=f'mmlu_cf_{_name}',
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type=MMLUCFDataset,
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path='microsoft/MMLU-CF',
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name=_name,
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reader_cfg=mmlu_cf_reader_cfg,
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infer_cfg=mmlu_cf_infer_cfg,
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eval_cfg=mmlu_cf_eval_cfg,
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))
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del _name, _hint
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