Datasets:
metadata
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
- multiple-choice
- question-answering
language:
- zh
pretty_name: C-Eval
size_categories:
- 10K<n<100K
configs:
- config_name: accountant
data_files:
- split: test
path: accountant/test-*
- split: val
path: accountant/val-*
- split: dev
path: accountant/dev-*
- config_name: advanced_mathematics
data_files:
- split: test
path: advanced_mathematics/test-*
- split: val
path: advanced_mathematics/val-*
- split: dev
path: advanced_mathematics/dev-*
- config_name: art_studies
data_files:
- split: test
path: art_studies/test-*
- split: val
path: art_studies/val-*
- split: dev
path: art_studies/dev-*
- config_name: basic_medicine
data_files:
- split: test
path: basic_medicine/test-*
- split: val
path: basic_medicine/val-*
- split: dev
path: basic_medicine/dev-*
- config_name: business_administration
data_files:
- split: test
path: business_administration/test-*
- split: val
path: business_administration/val-*
- split: dev
path: business_administration/dev-*
- config_name: chinese_language_and_literature
data_files:
- split: test
path: chinese_language_and_literature/test-*
- split: val
path: chinese_language_and_literature/val-*
- split: dev
path: chinese_language_and_literature/dev-*
- config_name: civil_servant
data_files:
- split: test
path: civil_servant/test-*
- split: val
path: civil_servant/val-*
- split: dev
path: civil_servant/dev-*
- config_name: clinical_medicine
data_files:
- split: test
path: clinical_medicine/test-*
- split: val
path: clinical_medicine/val-*
- split: dev
path: clinical_medicine/dev-*
dataset_info:
- config_name: accountant
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 176917
num_examples: 443
- name: val
num_bytes: 19549
num_examples: 49
- name: dev
num_bytes: 3414
num_examples: 5
download_size: 151233
dataset_size: 199880
- config_name: advanced_mathematics
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 50031
num_examples: 173
- name: val
num_bytes: 5331
num_examples: 19
- name: dev
num_bytes: 7012
num_examples: 5
download_size: 50962
dataset_size: 62374
- config_name: art_studies
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 41227
num_examples: 298
- name: val
num_bytes: 4581
num_examples: 33
- name: dev
num_bytes: 1439
num_examples: 5
download_size: 46524
dataset_size: 47247
- config_name: basic_medicine
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 28820
num_examples: 175
- name: val
num_bytes: 2627
num_examples: 19
- name: dev
num_bytes: 1825
num_examples: 5
download_size: 37360
dataset_size: 33272
- config_name: business_administration
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 78387
num_examples: 301
- name: val
num_bytes: 9225
num_examples: 33
- name: dev
num_bytes: 3155
num_examples: 5
download_size: 75885
dataset_size: 90767
- config_name: chinese_language_and_literature
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 32328
num_examples: 209
- name: val
num_bytes: 3446
num_examples: 23
- name: dev
num_bytes: 1892
num_examples: 5
download_size: 42310
dataset_size: 37666
- config_name: civil_servant
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 181504
num_examples: 429
- name: val
num_bytes: 21273
num_examples: 47
- name: dev
num_bytes: 4576
num_examples: 5
download_size: 179936
dataset_size: 207353
- config_name: clinical_medicine
features:
- name: id
dtype: int32
- name: question
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: answer
dtype: string
- name: explanation
dtype: string
splits:
- name: test
num_bytes: 42161
num_examples: 200
- name: val
num_bytes: 4167
num_examples: 22
- name: dev
num_bytes: 1951
num_examples: 5
download_size: 48689
dataset_size: 48279
C-Eval is a comprehensive Chinese evaluation suite for foundation models. It consists of 13948 multi-choice questions spanning 52 diverse disciplines and four difficulty levels. Please visit our website and GitHub or check our paper for more details.
Each subject consists of three splits: dev, val, and test. The dev set per subject consists of five exemplars with explanations for few-shot evaluation. The val set is intended to be used for hyperparameter tuning. And the test set is for model evaluation. Labels on the test split are not released, users are required to submit their results to automatically obtain test accuracy. How to submit?
Load the data
from datasets import load_dataset
dataset=load_dataset(r"ceval/ceval-exam",name="computer_network")
print(dataset['val'][0])
# {'id': 0, 'question': '使用位填充方法，以01111110为位首flag，数据为011011111111111111110010，求问传送时要添加几个0____', 'A': '1', 'B': '2', 'C': '3', 'D': '4', 'answer': 'C', 'explanation': ''}
More details on loading and using the data are at our github page.
Please cite our paper if you use our dataset.
@article{huang2023ceval,
title={C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models},
author={Huang, Yuzhen and Bai, Yuzhuo and Zhu, Zhihao and Zhang, Junlei and Zhang, Jinghan and Su, Tangjun and Liu, Junteng and Lv, Chuancheng and Zhang, Yikai and Lei, Jiayi and Fu, Yao and Sun, Maosong and He, Junxian},
journal={arXiv preprint arXiv:2305.08322},
year={2023}
}