OpenCompass/opencompass/configs/datasets/xgpqa/gpqa_gen_015262.py
2025-02-10 03:27:55 +01:00

47 lines
1.7 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import GPQADataset, GPQAEvaluator
from opencompass.utils import first_option_postprocess
gpqa_reader_cfg = dict(
input_columns=['question', 'A', 'B', 'C', 'D'],
output_column='answer')
gpqa_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(
round=[
dict(role='HUMAN', prompt='What is the correct answer to this question: {question}\nChoices:\n'
'(A){A}\n'
'(B){B}\n'
'(C){C}\n'
'(D){D}\n'
'Format your response as follows: "The correct answer is (insert answer here)"'),
], )),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer))
gpqa_eval_cfg = dict(evaluator=dict(type=GPQAEvaluator),
pred_postprocessor=dict(type=first_option_postprocess, options='ABCD'))
gpqa_datasets = []
gpqa_subsets = {
'extended': 'gpqa_extended.csv',
'main': 'gpqa_main.csv',
'diamond': 'gpqa_diamond.csv'
}
for split in list(gpqa_subsets.keys()):
gpqa_datasets.append(
dict(
abbr='GPQA_' + split,
type=GPQADataset,
path='./data/gpqa/',
name=gpqa_subsets[split],
reader_cfg=gpqa_reader_cfg,
infer_cfg=gpqa_infer_cfg,
eval_cfg=gpqa_eval_cfg)
)