OpenCompass/configs/datasets/subjective/multiround/mtbench_single_judge_diff_temp.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 ChatInferencer, GenInferencer
from opencompass.openicl.icl_evaluator import LMEvaluator
from opencompass.datasets import MTBenchDataset
subjective_reader_cfg = dict(
input_columns=['dialogue', 'capability', 'system_prompt', 'prompt_template'],
output_column='judge',
)
subjective_all_sets = [
"mtbench_0.0","mtbench_0.1","mtbench_0.7"
]
data_path ="data/subjective/mtbench"
subjective_datasets = []
for _name in subjective_all_sets:
temperature = float(_name.split('_')[1])
do_sample = False if temperature == 0.0 else True
subjective_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template="""{dialogue}""",
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=ChatInferencer, max_seq_len=4096, max_out_len=512, temperature=temperature, do_sample=do_sample,infer_mode='every'),
)
subjective_eval_cfg = dict(
evaluator=dict(
type=LMEvaluator,
prompt_template=dict(
type=PromptTemplate,
template=dict(
begin=[
dict(
role='SYSTEM',
fallback_role='HUMAN',
prompt="{system_prompt}")
],
round=[
dict(
role='HUMAN',
prompt = "{prompt_template}"
),
]),
),
),
pred_role="BOT",
)
subjective_datasets.append(
dict(
abbr=f"{_name}",
type=MTBenchDataset,
path=data_path,
name=_name,
reader_cfg=subjective_reader_cfg,
infer_cfg=subjective_infer_cfg,
eval_cfg=subjective_eval_cfg
))