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Mo-Abdalkader/Egyptian-Arabic-English-Parallel-Corpus
Egyptian-Arabic-English-Parallel-Corpus is a machine learning model from Mo-Abdalkader. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-4.0.
Author: Mohamed Abdalkader · LinkedIn · GitHub
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Updated Jul 26, 2026
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.jsonl6.1 MB · 54%
From the Hugging Face model README
Author: Mohamed Abdalkader · LinkedIn · GitHub
A comprehensive Egyptian Arabic → English parallel corpus covering 1,800 topics from daily Egyptian life. Designed for fine-tuning large language models on Egyptian Arabic dialect translation and generation.
egyptian-arabic-english-parallel-corpus/
├── SFT/
│ ├── Train/
│ │ ├── topics/ # 1,800 individual topic JSON files
│ │ └── merged/ # Merged JSONL + CSV
│ └── Test/
│ ├── topics/ # 1,800 topic files (10 samples each)
│ └── merged/ # Merged JSONL + CSV
├── DPO/
│ ├── topics/ # 1,800 topic files with preference pairs
│ └── merged/ # Merged JSONL + CSV
├── metadata.json
├── dataset_infos.json
├── README.md
├── LICENSE
└── docs/
└── dataset_statistics.md
| Split | Samples | Sentences | Description |
|---|---|---|---|
| SFT Train | 277,319 | 554,638 | Input → Output pairs |
| SFT Test | 18,000 | 36,000 | Input → Output pairs (10/topic) |
| DPO | 124,681 | 498,724 | Preference pairs (chosen/rejected) |
| Total | 420,000 | 1,089,362 |
Each sample has a unique ID: {split_id:02d}-{topic:05d}-{sample:04d}
| Prefix | Split | Example |
|---|---|---|
01 | SFT Train | 01-00001-0001 = Topic 1, Sample 1 |
02 | SFT Test | 02-01624-0010 = Topic 1624, Sample 10 |
03 | DPO | 03-01800-0050 = Topic 1800, Sample 50 |
import json
# Load a specific topic
with open("SFT/Train/topics/0001-First-day-at-school.json") as f:
data = json.load(f)
# Load merged file
with open("SFT/Train/merged/train.jsonl") as f:
lines = [json.loads(line) for line in f]
from datasets import load_dataset
dataset = load_dataset("json", data_files={
"train": "SFT/Train/merged/train.jsonl",
"test": "SFT/Test/merged/test.jsonl"
})
Each topic file is a JSON array of samples:
[
{
"id": "01-00001-0001",
"category": "First-day-at-school",
"input": "...Egyptian Arabic...",
"output": "...English translation..."
}
]
DPO topic files have chosen_input, chosen_output, rejected_input, rejected_output instead.
CC BY 4.0 — see LICENSE for details.
@misc{abdalkader2026egyptian,
author = {Mohamed Abdalkader},
title = {Egyptian Arabic-English Parallel Corpus: A +1M-Sentence Dataset},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/Mo-Abdalkader/Egyptian-Arabic-English-Parallel-Corpus}
}