storycloze_gen_7f656a.py 1.51 KB
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from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import storyclozeDataset_V2
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from opencompass.utils.text_postprocessors import first_option_postprocess
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storycloze_reader_cfg = dict(
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    input_columns=['context', 'sentence_quiz1', 'sentence_quiz2'],
    output_column='answer_right_ending',
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)

storycloze_infer_cfg = dict(
    prompt_template=dict(
        type=PromptTemplate,
        template=dict(round=[
            dict(
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                role='HUMAN',
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                prompt=
                "{context}\nQuestion: Which ending makes the most sense?\nA. {sentence_quiz1}\nB. {sentence_quiz2}\nYou may choose between 'A' and 'B'.\nAnswer:",
            ),
        ]),
    ),
    retriever=dict(type=ZeroRetriever),
    inferencer=dict(type=GenInferencer),
)

storycloze_eval_cfg = dict(
    evaluator=dict(type=AccEvaluator),
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    pred_role='BOT',
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    pred_postprocessor=dict(type=first_option_postprocess, options='AB'),
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)

# The original story cloze dataset and repo are not long maintaining.
# Using multilingual version of this dataset.
storycloze_datasets = [
    dict(
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        abbr='story_cloze',
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        type=storyclozeDataset_V2,
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        path='./data/xstory_cloze',
        lang='en',
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        reader_cfg=storycloze_reader_cfg,
        infer_cfg=storycloze_infer_cfg,
        eval_cfg=storycloze_eval_cfg,
    )
]