OpenCompass/opencompass/configs/datasets/mmlu_pro/mmlu_pro_0shot_gen.py
2025-02-19 09:50:46 -05:00

65 lines
1.9 KiB
Python

from mmengine.config import read_base
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 MMLUProDataset
from opencompass.utils.text_postprocessors import match_answer_pattern
with read_base():
from .mmlu_pro_categories import categories
QUERY_TEMPLATE = """
Answer the following multiple choice question. Your response should be of the following format: 'ANSWER: $LETTER' (without quotes) where LETTER is one of Options(e.g. one of ABCDEFGHIJKLMNOP). Please answer directly without additional explanations.
Question:\n
{question}
Options:\n
{options_str}
""".strip()
mmlu_pro_datasets = []
for category in categories:
mmlu_pro_reader_cfg = dict(
input_columns=['question', 'cot_content', 'options_str'],
output_column='answer',
train_split='validation',
test_split='test',
)
mmlu_pro_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(
round=[
dict(role='HUMAN',
prompt=QUERY_TEMPLATE),
],
),
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer),
)
mmlu_pro_eval_cfg = dict(
evaluator=dict(type=AccEvaluator),
pred_postprocessor=dict(
type=match_answer_pattern,
answer_pattern=r'(?i)ANSWER\s*:\s*([A-P])')
)
mmlu_pro_datasets.append(
dict(
abbr=f'mmlu_pro_{category.replace(" ", "_")}',
type=MMLUProDataset,
path='opencompass/mmlu_pro',
category=category,
reader_cfg=mmlu_pro_reader_cfg,
infer_cfg=mmlu_pro_infer_cfg,
eval_cfg=mmlu_pro_eval_cfg,
))