OpenCompass/configs/datasets/summedits/summedits_ppl_f2bd6e.py
2023-07-05 03:15:31 +00:00

59 lines
2.0 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import PPLInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import HFDataset
summedits_reader_cfg = dict(
input_columns=['doc', 'summary'],
output_column='label',
test_split='train')
summedits_prompt1 = "Given the document below, you have to determine if 'Yes' or 'No', the summary is factually consistent with the document."
summedits_prompt2 = "Document:\n{doc}\nSummary:\n{summary}\nIs the summary factually consistent with the document? "
summedits_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template={
0:
dict(
begin=[
dict(
role='SYSTEM',
fallback_role='HUMAN',
prompt=summedits_prompt1)
],
round=[
dict(role="HUMAN", prompt=summedits_prompt2),
dict(role="BOT", prompt="No")
]),
1:
dict(
begin=[
dict(
role='SYSTEM',
fallback_role='HUMAN',
prompt=summedits_prompt1)
],
round=[
dict(role="HUMAN", prompt=summedits_prompt2),
dict(role="BOT", prompt="Yes")
]),
}),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=PPLInferencer))
summedits_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
summedits_datasets = [
dict(
type=HFDataset,
abbr='summedits',
path='json',
split='train',
data_files='./data/summedits/summedits.jsonl',
reader_cfg=summedits_reader_cfg,
infer_cfg=summedits_infer_cfg,
eval_cfg=summedits_eval_cfg)
]