OpenCompass/configs/datasets/hellaswag/hellaswag_gen_6faab5.py
Fengzhe Zhou 689ffe5b63
[Feature] Use dataset in local path (#570)
* update commonsenseqa

* update drop

* update flores_first100

* update gsm8k

* update humaneval

* update lambda

* update obqa

* update piqa

* update race

* update siqa

* update story_cloze

* update strategyqa

* update tydiqa

* update winogrande

* update doc

* update hellaswag

* fix obqa

* update collections

* update .zip name
2023-11-13 13:00:37 +08:00

45 lines
1.4 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 AccEvaluator
from opencompass.datasets import hellaswagDataset_V2
from opencompass.utils.text_postprocessors import first_option_postprocess
hellaswag_reader_cfg = dict(
input_columns=["ctx", "A", "B", "C", "D"],
output_column="label",
)
hellaswag_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role="HUMAN",
prompt=("{ctx}\nQuestion: Which ending makes the most sense?\n"
"A. {A}\nB. {B}\nC. {C}\nD. {D}\n"
"You may choose from 'A', 'B', 'C', 'D'.\n"
"Answer:"),
),
]),
),
retriever=dict(type=ZeroRetriever, ),
inferencer=dict(type=GenInferencer),
)
hellaswag_eval_cfg = dict(
evaluator=dict(type=AccEvaluator),
pred_role="BOT",
pred_postprocessor=dict(type=first_option_postprocess, options='ABCD'),
)
hellaswag_datasets = [
dict(
abbr='hellaswag',
type=hellaswagDataset_V2,
path='./data/hellaswag/hellaswag.jsonl',
reader_cfg=hellaswag_reader_cfg,
infer_cfg=hellaswag_infer_cfg,
eval_cfg=hellaswag_eval_cfg)
]