OpenCompass/opencompass/configs/datasets/judge/rewardbench.py
2025-04-21 09:00:52 +00:00

49 lines
1.9 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.openicl.icl_evaluator import JudgeEvaluator
from opencompass.datasets import RewardBenchDataset
subjective_reader_cfg = dict(
input_columns=['prompt'],
output_column='judge',
)
data_path = './data/judgeeval/rewardbench'
subjective_all_sets = ['llmbar-natural.json', 'llmbar-adver-GPTInst.json', 'hep-go.json', 'refusals-dangerous.json', 'hep-cpp.json', 'mt-bench-easy.json', 'alpacaeval-length.json', 'llmbar-adver-neighbor.json', 'alpacaeval-easy.json', 'hep-java.json', 'llmbar-adver-GPTOut.json', 'mt-bench-hard.json', 'xstest-should-respond.json', 'xstest-should-refuse.json', 'hep-python.json', 'refusals-offensive.json', 'alpacaeval-hard.json', 'llmbar-adver-manual.json', 'hep-js.json', 'math-prm.json', 'hep-rust.json', 'mt-bench-med.json', 'donotanswer.json']
get_rewardbench_datasets = []
for _name in subjective_all_sets:
subjective_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role='HUMAN',
prompt='{prompt}'
),
]),
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=4096),
)
rewardbench_eval_cfg = dict(
evaluator=dict(
type=JudgeEvaluator,
),
)
get_rewardbench_datasets.append(
dict(
abbr=f'{_name.split(".")[0]}',
type=RewardBenchDataset,
path=data_path,
name=_name,
reader_cfg=subjective_reader_cfg,
infer_cfg=subjective_infer_cfg,
eval_cfg=rewardbench_eval_cfg,
mode='singlescore',
))