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metadata
language:
  - ar
license: apache-2.0
size_categories:
  - n<1K
task_categories:
  - multiple-choice
pretty_name: 'CIDAR-MCQ-100 '
dataset_info:
  features:
    - name: Question
      dtype: string
    - name: A
      dtype: string
    - name: B
      dtype: string
    - name: C
      dtype: string
    - name: D
      dtype: string
    - name: answer
      dtype: string
  splits:
    - name: test
      num_bytes: 18899
      num_examples: 100
  download_size: 13287
  dataset_size: 18899
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*

Dataset Card for "CIDAR-MCQ-100"

CIDAR-MCQ-100

CIDAR-MCQ-100 contains 100 multiple-choice questions and answers about the Arabic culture.

๐Ÿ“š Datasets Summary

Name Explanation
CIDAR 10,000 instructions and responses in Arabic
CIDAR-EVAL-100 100 instructions to evaluate LLMs on cultural relevance
CIDAR-MCQ-100 100 Multiple choice questions and answers to evaluate LLMs on cultural relevance
Category CIDAR-EVAL-100 CIDAR-MCQ-100
Food&Drinks 14 8
Names 14 8
Animals 2 4
Language 10 20
Jokes&Puzzles 3 7
Religion 5 10
Business 6 7
Cloths 4 5
Science 3 4
Sports&Games 4 2
Tradition 4 10
Weather 4 2
Geography 7 8
General 4 3
Fonts 5 2
Literature 10 2
Plants 3 0
Total 100 100

๐Ÿ“‹ Dataset Structure

  • Question(str): Question about the Arabic culture.
  • A(str): First choice.
  • B(str): Second choice.
  • C(str): Third choice.
  • D(str): Fourth choice.
  • answer(str): The correct choice from A,B,C, and D.

๐Ÿ“ Loading The Dataset

You can download the dataset directly from HuggingFace or use the following code:

from datasets import load_dataset
cidar = load_dataset('arbml/CIDAR-MCQ-100')

๐Ÿ“„ Sample From The Dataset:

Question: ุญุฏุฏ ุญูŠูˆุงู† ู…ุดู‡ูˆุฑ ููŠ ุงู„ู…ู†ุทู‚ุฉ

A: ุงู„ุฌู…ู„ B: ุงู„ู„ุงู…ุง C: ุงู„ูƒุงู†ุบุฑูˆ D: ุงู„ุฏุจ ุงู„ู‚ุทุจูŠ answer: A

๐Ÿ”‘ License

The dataset is licensed under Apache-2.0. Apache-2.0.

Citation

@misc{alyafeai2024cidar,
      title={{CIDAR: Culturally Relevant Instruction Dataset For Arabic}}, 
      author={Zaid Alyafeai and Khalid Almubarak and Ahmed Ashraf and Deema Alnuhait and Saied Alshahrani and Gubran A. Q. Abdulrahman and Gamil Ahmed and Qais Gawah and Zead Saleh and Mustafa Ghaleb and Yousef Ali and Maged S. Al-Shaibani},
      year={2024},
      eprint={2402.03177},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}