OpenCompass/configs/datasets/subjective/followbench/followbench_llmeval.py
bittersweet1999 fa54aa62f6
[Feature] Add Judgerbench and reorg subeval (#1593)
* fix pip version

* fix pip version

* update (#1522)

Co-authored-by: zhulin1 <zhulin1@pjlab.org.cn>

* [Feature] Update Models (#1518)

* Update Models

* Update

* Update humanevalx

* Update

* Update

* [Feature] Dataset prompts update for ARC, BoolQ, Race (#1527)

add judgerbench and reorg sub

add judgerbench and reorg subeval

add judgerbench and reorg subeval

* add judgerbench and reorg subeval

* add judgerbench and reorg subeval

* add judgerbench and reorg subeval

* add judgerbench and reorg subeval

---------

Co-authored-by: zhulinJulia24 <145004780+zhulinJulia24@users.noreply.github.com>
Co-authored-by: zhulin1 <zhulin1@pjlab.org.cn>
Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com>
Co-authored-by: Linchen Xiao <xxllcc1993@gmail.com>
2024-10-15 16:36:05 +08:00

63 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 LMEvaluator
from opencompass.datasets import FollowBenchDataset, followbench_postprocess
subjective_reader_cfg = dict(
input_columns=['instruction', 'judge_prompt',],
output_column='judge',
)
subjective_all_sets = [
'followbench_llmeval_cn', 'followbench_llmeval_en',
]
data_path ='data/subjective/followbench/converted_data'
followbench_llmeval_datasets = []
for _name in subjective_all_sets:
subjective_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role='HUMAN',
prompt='{instruction}'
),
]),
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=2048),
)
subjective_eval_cfg = dict(
evaluator=dict(
type=LMEvaluator,
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role='HUMAN',
prompt = '{judge_prompt}'
),
]),
),
dict_postprocessor=dict(type=followbench_postprocess),
),
pred_role='BOT',
)
followbench_llmeval_datasets.append(
dict(
abbr=f'{_name}',
type=FollowBenchDataset,
path=data_path,
name=_name,
mode='singlescore',
cate='llm',
reader_cfg=subjective_reader_cfg,
infer_cfg=subjective_infer_cfg,
eval_cfg=subjective_eval_cfg,
))