OpenCompass/configs/datasets/truthfulqa/truthfulqa_gen_5ddc62.py

45 lines
1.6 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.datasets import TruthfulQADataset, TruthfulQAEvaluator
truthfulqa_reader_cfg = dict(
input_columns=['question'],
output_column='reference',
train_split='validation',
test_split='validation')
# TODO: allow empty output-column
truthfulqa_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(round=[dict(role="HUMAN", prompt="{question}")])),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer))
# Metrics such as 'truth' and 'info' needs
# OPENAI_API_KEY with finetuned models in it.
# Please use your own finetuned openai model with keys and refers to
# the source code of `TruthfulQAEvaluator` for more details.
#
# If you cannot provide available models for 'truth' and 'info',
# and want to perform basic metric eval, please set
# `metrics=('bleurt', 'rouge', 'bleu')`
# When key is set to "ENV", the key will be fetched from the environment
# variable $OPENAI_API_KEY. Otherwise, set key in here directly.
truthfulqa_eval_cfg = dict(
evaluator=dict(
type=TruthfulQAEvaluator, metrics=('truth', 'info'), key='ENV'), )
truthfulqa_datasets = [
dict(
abbr='truthful_qa',
type=TruthfulQADataset,
path='truthful_qa',
name='generation',
reader_cfg=truthfulqa_reader_cfg,
infer_cfg=truthfulqa_infer_cfg,
eval_cfg=truthfulqa_eval_cfg)
]