OpenCompass/configs/datasets/SuperGLUE_CB/SuperGLUE_CB_ppl_32adbb.py
2023-07-04 21:34:55 +08:00

63 lines
1.8 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
CB_reader_cfg = dict(
input_columns=["premise", "hypothesis"],
output_column="label",
)
CB_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template={
"contradiction":
dict(round=[
dict(
role="HUMAN",
prompt=
"{premise}\n{hypothesis}\nWhat is the relation between the two sentences?"
),
dict(role="BOT", prompt="Contradiction"),
]),
"entailment":
dict(round=[
dict(
role="HUMAN",
prompt=
"{premise}\n{hypothesis}\nWhat is the relation between the two sentences?"
),
dict(role="BOT", prompt="Entailment"),
]),
"neutral":
dict(round=[
dict(
role="HUMAN",
prompt=
"{premise}\n{hypothesis}\nWhat is the relation between the two sentences?"
),
dict(role="BOT", prompt="Neutral"),
]),
},
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=PPLInferencer),
)
CB_eval_cfg = dict(evaluator=dict(type=AccEvaluator), )
CB_datasets = [
dict(
type=HFDataset,
abbr="CB",
path="json",
split="train",
data_files="./data/SuperGLUE/CB/val.jsonl",
reader_cfg=CB_reader_cfg,
infer_cfg=CB_infer_cfg,
eval_cfg=CB_eval_cfg,
)
]