OpenCompass/configs/datasets/race/race_ppl_04e06a.py
2023-07-04 21:34:55 +08:00

49 lines
1.5 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import PPLInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import RaceDataset
race_reader_cfg = dict(
input_columns=['article', 'question', 'A', 'B', 'C', 'D'],
output_column='answer')
race_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template={
ans: dict(round=[
dict(
role="HUMAN",
prompt=
"Read the article, and answer the question by replying A, B, C or D.\n\nArticle:\n{article}\n\nQ: {question}\n\nA. {A}\nB. {B}\nC. {C}\nD. {D}"
),
dict(role="BOT", prompt=ans_token),
])
for ans, ans_token in [["A", "{A}"], ["B", "{B}"], ["C", "{C}"],
["D", "{D}"]]
}),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=PPLInferencer))
race_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
race_datasets = [
dict(
type=RaceDataset,
abbr='race-middle',
path='race',
name='middle',
reader_cfg=race_reader_cfg,
infer_cfg=race_infer_cfg,
eval_cfg=race_eval_cfg),
dict(
type=RaceDataset,
abbr='race-high',
path='race',
name='high',
reader_cfg=race_reader_cfg,
infer_cfg=race_infer_cfg,
eval_cfg=race_eval_cfg)
]