README.md

metadata

license: cc-by-nc-sa-4.0
pretty_name: AraDiCE -- Culture
dataset_info:
  - config_name: Lebanon
    splits:
      - name: test
        num_examples: 30
  - config_name: Egypt
    splits:
      - name: test
        num_examples: 30
  - config_name: Syria
    splits:
      - name: test
        num_examples: 30
  - config_name: Palestine
    splits:
      - name: test
        num_examples: 30
  - config_name: Jordan
    splits:
      - name: test
        num_examples: 30
  - config_name: Qatar
    splits:
      - name: test
        num_examples: 30
configs:
  - config_name: Lebanon
    data_files:
      - split: test
        path: lebanon/LEBANON.json
  - config_name: Egypt
    data_files:
      - split: test
        path: egypt/EGYPT.json
  - config_name: Syria
    data_files:
      - split: test
        path: syria/SYRIA.json
  - config_name: Palestine
    data_files:
      - split: test
        path: palestine/PALESTINE.json
  - config_name: Jordan
    data_files:
      - split: test
        path: jordan/JORDAN.json
  - config_name: Qatar
    data_files:
      - split: test
        path: qatar/QATAR.json

AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs

Overview

The AraDiCE dataset is designed to evaluate dialectal and cultural capabilities in large language models (LLMs). The dataset consists of post-edited versions of various benchmark datasets, curated for validation in cultural and dialectal contexts relevant to Arabic. In this repository we show the cultural split of the data

Evaluation

We have used lm-harness eval framework to for the benchmarking. We will soon release them. Stay tuned!!

License

The dataset is distributed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). The full license text can be found in the accompanying licenses_by-nc-sa_4.0_legalcode.txt file.

Citation

Please find the paper here.

@article{mousi2024aradicebenchmarksdialectalcultural,
      title={{AraDiCE}: Benchmarks for Dialectal and Cultural Capabilities in LLMs},
      author={Basel Mousi and Nadir Durrani and Fatema Ahmad and Md. Arid Hasan and Maram Hasanain and Tameem Kabbani and Fahim Dalvi and Shammur Absar Chowdhury and Firoj Alam},
      year={2024},
      publisher={arXiv:2409.11404},
      url={https://arxiv.org/abs/2409.11404},
}