SuperGLUE_CB_ppl_32adbb.py

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,
    )
]