2023-07-04 22:11:33 +08:00
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import AFQMCDataset_V2
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2023-07-06 12:27:41 +08:00
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from opencompass.utils.text_postprocessors import first_capital_postprocess
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2023-07-04 22:11:33 +08:00
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afqmc_reader_cfg = dict(
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input_columns=["sentence1", "sentence2"],
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output_column="label",
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test_split="train")
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afqmc_infer_cfg = dict(
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prompt_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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"语句一：“{sentence1}”\n语句二：“{sentence2}”\n语句一与语句二是关于蚂蚁金融产品的疑问，两者所询问的内容是否完全一致？\nA. 不完全一致\nB. 完全一致\n请从“A”，“B”中进行选择。\n答：",
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),
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]),
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer),
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)
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afqmc_eval_cfg = dict(
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evaluator=dict(type=AccEvaluator),
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pred_role="BOT",
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2023-07-06 12:27:41 +08:00
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pred_postprocessor=dict(type=first_capital_postprocess),
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2023-07-04 22:11:33 +08:00
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)
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afqmc_datasets = [
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dict(
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abbr="afqmc-dev",
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type=AFQMCDataset_V2,
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path="./data/CLUE/AFQMC/dev.json",
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reader_cfg=afqmc_reader_cfg,
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infer_cfg=afqmc_infer_cfg,
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eval_cfg=afqmc_eval_cfg,
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),
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]
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