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42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
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.datasets import TruthfulQADataset, TruthfulQAEvaluator
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truthfulqa_reader_cfg = dict(
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input_columns=['question'],
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output_column='reference',
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train_split='validation',
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test_split='validation')
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# TODO: allow empty output-column
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truthfulqa_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(round=[dict(role='HUMAN', prompt='{question}')])),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer))
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# Metrics such as 'truth' and 'info' needs
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# extra judge models.
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# Please use your own finetuned model and refers to
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# the source code of `TruthfulQAEvaluator` for more details.
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# If you cannot provide available models for 'truth' and 'info',
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# and want to perform basic metric eval, please set
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# `metrics=('bleurt', 'rouge', 'bleu')`
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truthfulqa_eval_cfg = dict(
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evaluator=dict(
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type=TruthfulQAEvaluator, metrics=('bleu'), key='ENV'), )
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truthfulqa_datasets = [
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dict(
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abbr='truthful_qa',
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type=TruthfulQADataset,
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path='truthful_qa',
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name='generation',
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reader_cfg=truthfulqa_reader_cfg,
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infer_cfg=truthfulqa_infer_cfg,
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eval_cfg=truthfulqa_eval_cfg)
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]
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