HeshamHaroon/arabic-dialect-dpo

Arabic Dialect DPO Dataset - Egyptian & Saudi

The first large-scale Arabic dialect preference dataset for DPO/ORPO/GRPO alignment training. Contains 22,538 preference triples across two major Arabic dialects: Egyptian (Masry) and Saudi (Najdi).

Dataset Summary

Config	Dialect	Rows	Language Code
egyptian	Egyptian Arabic (مصري)	11,038	ar-EG
saudi	Saudi Arabic (سعودي نجدي)	11,500	ar-SA
Total		22,538

Usage

from datasets import load_dataset

# Load Egyptian Arabic
egyptian = load_dataset("HeshamHaroon/arabic-dialect-dpo", "egyptian")

# Load Saudi Arabic
saudi = load_dataset("HeshamHaroon/arabic-dialect-dpo", "saudi")

# Load both
egyptian_train = load_dataset("HeshamHaroon/arabic-dialect-dpo", "egyptian", split="train")
saudi_train = load_dataset("HeshamHaroon/arabic-dialect-dpo", "saudi", split="train")

Format

Each row contains a DPO preference triple:

Field	Description
prompt	User question/request in dialect Arabic
chosen	High-quality response in natural dialect (preferred)
rejected	Low-quality response in formal/generic Arabic (dispreferred)
category	Topic category
language	Language code (ar-EG or ar-SA)
dialect	Dialect name

Examples

Egyptian Arabic

Prompt: ازاي أعمل CV كويس يلفت نظر الشركات؟
Chosen: أول حاجة لازم تعملها إن الـ CV يكون منظم وواضح. خليه صفحة واحدة أو اتنين بالكتير...
Rejected: يمكنك إنشاء سيرة ذاتية احترافية من خلال اتباع بعض الإرشادات العامة...

Saudi Arabic

Prompt: وش أحسن طريقة أطور فيها مهاراتي عشان رؤية 2030؟
Chosen: يالله أبشرك، رؤية 2030 فتحت أبواب كثيرة للتطوير. أول شيء حدد المجال اللي يناسبك...
Rejected: يمكنك تطوير مهاراتك من خلال البحث عن الدورات التدريبية المتاحة عبر الإنترنت...

Key Contrast

The preference signal is based on:

• Chosen: Natural dialect, culturally relevant, detailed, practical, locally grounded
• Rejected: Formal Arabic (فصحى), generic, short, culturally disconnected, "search the internet" style

Categories

Egyptian (12 categories)

daily_life, career_advice, technology, education, health_fitness, relationships, finance, culture_entertainment, parenting, customer_service, religion_ethics, problem_solving

Saudi (12 categories)

daily_life, career_jobs, technology, education, health_fitness, relationships, finance, culture_tourism, parenting, customer_service, religion_values, driving_cars

Generation Details

Aspect	Detail
Generation	Synthetic via large language models
Deduplication	Exact prompt matching
Quality control	Length filtering + dialect authenticity checks

Use Cases

• DPO training for Arabic dialect models
• ORPO/GRPO alignment for Egyptian or Saudi Arabic
• Reward model training with clear preference signals
• Arabic dialect research comparing Egyptian vs Saudi
• Cultural NLP studying how dialect affects AI helpfulness

Limitations

• Synthetically generated (not human conversations)
• May not capture all subdialects within Egyptian/Saudi Arabic
• Rejected responses are intentionally generic, not adversarial

Citation

@dataset{arabic_dialect_dpo_2026,
  title={Arabic Dialect DPO Dataset - Egyptian & Saudi},
  author={Hesham Haroon},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/HeshamHaroon/arabic-dialect-dpo}
}

License

Apache 2.0