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from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import FixKRetriever
from opencompass.openicl.icl_inferencer import PPLInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import HFDataset
_hint = "The following are text classification questions. \n" \
"Please determine whether the following sentence is linguistically acceptable: " \
"0 means unacceptable, 1 means acceptable.\n"
CoLA_infer_cfg = dict(
ice_template=dict(
type=PromptTemplate,
template="Sentence: {sentence}\nResult: {label}",
),
prompt_template=dict(
type=PromptTemplate,
template={
answer:
f"{_hint}</E>Sentence: {{sentence}}\nResult: {answer}"
for answer in [0, 1]
},
ice_token='</E>',
),
retriever=dict(type=FixKRetriever, fix_id_list=[17, 18, 19, 20, 21]),
inferencer=dict(type=PPLInferencer))
CoLA_eval_cfg = dict(evaluator=dict(type=AccEvaluator), )
CoLA_datasets = []
for _split in ["validation"]:
CoLA_reader_cfg = dict(
input_columns=['sentence'],
output_column='label',
test_split=_split
)
CoLA_datasets.append(
dict(
abbr=f'CoLA-{_split}',
type=HFDataset,
path='glue',
name='cola',
reader_cfg=CoLA_reader_cfg,
infer_cfg=CoLA_infer_cfg,
eval_cfg=CoLA_eval_cfg
)
)
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