OpenCompass/configs/datasets/subjective_cmp/alignment_bench.py

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from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import LMEvaluator
from opencompass.datasets import AlignmentBenchDataset
from mmengine.config import read_base
subjective_reader_cfg = dict(
input_columns=['question', 'capability', 'prefix', 'suffix'],
output_column='judge',
)
subjective_all_sets = [
"alignment_bench",
]
data_path ="data/subjective/alignment_bench"
alignment_bench_config_path = "data/subjective/alignment_bench/"
alignment_bench_config_name = 'config/multi-dimension'
subjective_datasets = []
for _name in subjective_all_sets:
subjective_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role='HUMAN',
prompt="{question}"
),
]),
),
retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer, max_out_len=1024),
)
subjective_eval_cfg = dict(
evaluator=dict(
type=LMEvaluator,
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role='HUMAN',
prompt = "{prefix}[助手的答案开始]\n{prediction}\n[助手的答案结束]\n"
),
]),
),
),
pred_role="BOT",
)
subjective_datasets.append(
dict(
abbr=f"{_name}",
type=AlignmentBenchDataset,
path=data_path,
name=_name,
alignment_bench_config_path=alignment_bench_config_path,
alignment_bench_config_name=alignment_bench_config_name,
reader_cfg=subjective_reader_cfg,
infer_cfg=subjective_infer_cfg,
eval_cfg=subjective_eval_cfg
))