OpenCompass/configs/datasets/xiezhi/xiezhi_gen_b86cf5.py
Leymore e7fc54baf1
[Feature] Add Xiezhi SQuAD2.0 ANLI (#101)
* add Xiezhi SQuAD2.0 ANLI; update WSC

* update

* update

* update doc string
2023-08-10 14:04:18 +08:00

51 lines
1.7 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import XiezhiDataset, XiezhiRetriever
from opencompass.utils.text_postprocessors import first_capital_postprocess
xiezhi_datasets = []
for split in ["spec_eng", "spec_chn", "inter_eng", "inter_chn"]:
if 'chn' in split:
q_hint, a_hint = "题目", "答案"
else:
q_hint, a_hint = "Question", "Answer"
xiezhi_reader_cfg = dict(
input_columns=["question", "A", "B", "C", "D", "labels"],
output_column="answer",
train_split="train",
test_split='test',
)
xiezhi_infer_cfg = dict(
ice_template=dict(
type=PromptTemplate,
template=dict(
begin="</E>",
round=[
dict(role="HUMAN", prompt=f"{q_hint}: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n{a_hint}: "),
dict(role="BOT", prompt="{answer}"),
]
),
ice_token="</E>",
),
retriever=dict(type=XiezhiRetriever, ice_num=3),
inferencer=dict(type=GenInferencer),
)
xiezhi_eval_cfg = dict(evaluator=dict(type=AccEvaluator),
pred_role="BOT",
pred_postprocessor=dict(type=first_capital_postprocess))
xiezhi_datasets.append(
dict(
type=XiezhiDataset,
abbr=f"xiezhi-{split}",
path="./data/xiezhi/",
name="xiezhi_" + split,
reader_cfg=xiezhi_reader_cfg,
infer_cfg=xiezhi_infer_cfg,
eval_cfg=xiezhi_eval_cfg,
))