OpenCompass/opencompass/configs/datasets/OpenHuEval/HuLifeQA.py
2025-02-01 14:18:05 +08:00

71 lines
2.1 KiB
Python

from opencompass.datasets import WildBenchDataset
from opencompass.openicl.icl_evaluator import LMEvaluator
from opencompass.openicl.icl_inferencer import ChatInferencer
from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
hu_life_qa_reader_cfg = dict(
input_columns=["dialogue", "prompt"],
output_column="judge",
)
data_path ="/mnt/hwfile/opendatalab/yanghaote/share/HuLifeQA_20250131.jsonl"
hu_life_qa_datasets = []
hu_life_qa_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,
infer_mode="last",
),
)
hu_life_qa_eval_cfg = dict(
evaluator=dict(
type=LMEvaluator,
prompt_template=dict(
type=PromptTemplate,
template="""{prompt}"""
),
),
pred_role="BOT",
)
hu_life_qa_datasets.append(
dict(
abbr="hu_life_qa",
type=WildBenchDataset,
path=data_path,
reader_cfg=hu_life_qa_reader_cfg,
infer_cfg=hu_life_qa_infer_cfg,
eval_cfg=hu_life_qa_eval_cfg,
)
)
task_group_new = {
"life_culture_custom": "life_culture_custom",
"childbearing and education": "life_culture_custom",
"culture and community": "life_culture_custom",
'culture and customs': "life_culture_custom",
"food and drink": "life_culture_custom",
"health": "life_culture_custom",
"holidays": "life_culture_custom",
"home": "life_culture_custom",
"person": "life_culture_custom",
"transport": "life_culture_custom",
"science": "life_culture_custom",
"travel": "life_culture_custom",
"business_finance": "business_finance",
"business and finance": "business_finance",
"education_profession": "education_profession",
"public education and courses": "education_profession",
"politics_policy_law": "politics_policy_law",
"politics": "politics_policy_law",
}