NAMAA-Space/masrawy-english-to-egyptian-arabic-translator-v2.9
This model is a fine-tuned version of Helsinki-NLP/opus-mt-tc-big-en-ar. It achieves the following results on the evaluation set:
- Loss: 1.2957
Model description
This model is finetuned on Helsinki-NLP/opus-mt-tc-big-en-ar for English to Egyptian dialect translations. It was trained on more than 150,000 rows with more than 10 Million tokens
Usage
from transformers import pipeline
modelName = "NAMAA-Space/masrawy-english-to-egyptian-arabic-translator-v2.9"
translator = pipeline("translation", model=modelName)
output = translator("Where is the nearest pharmacy")
print(output[0]['translation_text'])
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.15.1
Benchmarks
- This model ranks second after
openai/gpt-4o
in Egyptian translation leaderboard
Citation
If you use NAMAA-Space/masrawy-english-to-egyptian-arabic-translator-v2.9, please cite it as follows:
@article{namaa_01_2025,
title={Masrawy English to Egyptian Translator},
url={https://huggingface.co/NAMAA-Space/masrawy-english-to-egyptian-arabic-translator-v2.9},
publisher={NAMAA},
author={NAMAA Team},
year={2025}
}
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Model tree for NAMAA-Space/masrawy-english-to-egyptian-arabic-translator-v2.9
Base model
Helsinki-NLP/opus-mt-tc-big-en-ar