OpenCompass/configs/datasets/subjective_ir/ir_judgedby_gpt4.py
bittersweet1999 2163f9398f
[Feature] add subject ir dataset (#755)
* add subject ir

* Add ir dataset

* Add ir dataset
2024-01-05 12:00:57 +00:00

60 lines
1.7 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 IRDataset
subjective_reader_cfg = dict(
input_columns=['question', 'capability', 'gpt4_prefix', 'gpt4_suffix', 'ref'],
output_column='judge',
)
subjective_all_sets = [
"information_retrieval",
]
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=512),
)
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=IRDataset,
path=data_path,
name=_name,
reader_cfg=subjective_reader_cfg,
infer_cfg=subjective_infer_cfg,
eval_cfg=subjective_eval_cfg
))