OpenCompass/opencompass/datasets/hellaswag.py
Leymore 14332e08fd
[Feature] add llama-oriented dataset configs (#82)
* add llama-oriented dataset configs

* update

* revert cvalues & update llama_example
2023-08-11 12:48:05 +08:00

65 lines
1.7 KiB
Python

import json
from datasets import Dataset, load_dataset
from opencompass.registry import LOAD_DATASET
from .base import BaseDataset
@LOAD_DATASET.register_module()
class hellaswagDataset(BaseDataset):
@staticmethod
def load(**kwargs):
dataset = load_dataset(**kwargs)
def preprocess(example):
for i in range(4):
example[chr(ord('A') + i)] = example['endings'][i]
return example
dataset = dataset.map(preprocess).remove_columns(['endings'])
return dataset
@LOAD_DATASET.register_module()
class hellaswagDataset_V2(BaseDataset):
@staticmethod
def load(**kwargs):
dataset = load_dataset(**kwargs)
def preprocess(example):
for i in range(4):
example[chr(ord('A') + i)] = example['endings'][i]
if example['label']:
example['label'] = 'ABCD'[int(example['label'])]
else:
example['label'] = 'NULL'
return example
dataset = dataset.map(preprocess).remove_columns(['endings'])
return dataset
@LOAD_DATASET.register_module()
class hellaswagDataset_V3(BaseDataset):
@staticmethod
def load(path):
dataset = []
with open(path, 'r') as f:
for line in f:
data = json.loads(line)
dataset.append({
'query': data['query'],
'A': data['choices'][0],
'B': data['choices'][1],
'C': data['choices'][2],
'D': data['choices'][3],
'gold': data['gold'],
})
dataset = Dataset.from_list(dataset)
return dataset