ceval-exam / README.md
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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-*
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

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}
}