OpenCompass/configs/datasets/hellaswag/hellaswag_10shot_ppl_59c85e.py
2024-03-04 14:42:36 +08:00

46 lines
1.6 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import FixKRetriever
from opencompass.openicl.icl_inferencer import PPLInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import hellaswagDatasetwithICE
from opencompass.utils.text_postprocessors import first_capital_postprocess
hellaswag_reader_cfg = dict(
input_columns=["ctx", "A", "B", "C", "D"],
output_column="label",
train_split="train",
test_split="val",
)
hint = "Continue the following text without adding any additional information or formatting:"
question_and_options = "{ctx}\nA) {A}\nB) {B}\nC) {C}\nD) {D}\nWhat is the right option?"
hellaswag_infer_cfg = dict(
ice_template=dict(
type=PromptTemplate,
template={answer: f'{question_and_options}\n{answer}\n' for answer in ["A", "B", "C", "D"]},
),
prompt_template=dict(
type=PromptTemplate,
template={answer: f"{hint}\n</E>{question_and_options}\n{answer}" for answer in ["A", "B", "C", "D"]},
ice_token="</E>",
),
retriever=dict(type=FixKRetriever, fix_id_list=list(range(10))),
inferencer=dict(type=PPLInferencer),
)
hellaswag_eval_cfg = dict(
evaluator=dict(type=AccEvaluator),
pred_postprocessor=dict(type=first_capital_postprocess),
)
hellaswag_datasets = [
dict(
abbr="hellaswag",
type=hellaswagDatasetwithICE,
path="./data/hellaswag/",
reader_cfg=hellaswag_reader_cfg,
infer_cfg=hellaswag_infer_cfg,
eval_cfg=hellaswag_eval_cfg,
)
]