OpenCompass/opencompass/configs/datasets/subjective/creationbench/creationbench_judgeby_gpt4.py
Songyang Zhang 46cc7894e1
[Feature] Support import configs/models/summarizers from whl (#1376)
* [Feature] Support import configs/models/summarizers from whl

* Update LCBench configs

* Update

* Update

* Update

* Update

* update

* Update

* Update

* Update

* Update

* Update
2024-08-01 00:42:48 +08:00

61 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 GenInferencer
from opencompass.openicl.icl_evaluator import LMEvaluator
from opencompass.datasets import CreationBenchDataset
subjective_reader_cfg = dict(
input_columns=['question', 'capability', 'gpt4_prefix', 'gpt4_suffix'],
output_column='judge',
)
subjective_all_sets = [
'creationbench',
]
data_path ='data/subjective/'
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),
inferencer=dict(type=GenInferencer, max_seq_len=4096, max_out_len=2048),
)
subjective_eval_cfg = dict(
evaluator=dict(
type=LMEvaluator,
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[
dict(
role='HUMAN',
prompt = '{gpt4_prefix}{prediction}{gpt4_suffix}'
),
]),
),
),
pred_role='BOT',
)
subjective_datasets.append(
dict(
abbr=f'{_name}',
type=CreationBenchDataset,
multi_dimension=True,
path=data_path,
name=_name,
reader_cfg=subjective_reader_cfg,
infer_cfg=subjective_infer_cfg,
eval_cfg=subjective_eval_cfg
))