Masrawy English-Arabic Translation Model - Open-source and free, a translation tool optimized specifically for Egyptian dialects

Masrawy English Arabic Translator

Developed by oddadmix

An English-Arabic translation model fine-tuned from Helsinki-NLP/opus-mt-en-ar, specifically optimized for Egyptian dialect

Machine Translation

TensorBoard

Supports Multiple LanguagesOpen Source License:Apache-2.0 #English-Arabic translation #Egyptian dialect optimization #Low-resource fine-tuning

Downloads 14

Release Time : 11/20/2024

Model Overview

This model specializes in English-to-Arabic translation tasks, with particular optimization for Egyptian dialect. Based on Transformer architecture, suitable for daily language and basic text translation scenarios.

Model Features

Egyptian Dialect Optimization

Specially optimized for Egyptian Arabic dialect, better handling of dialect expressions

Efficient Fine-tuning

Efficient fine-tuning based on pre-trained models, achieving good performance with limited data

Easy to Use

Provides standard Hugging Face interface, easy to integrate into various applications

Model Capabilities

English to Arabic text translation

Egyptian dialect processing

Batch text conversion

Use Cases

Content Localization

Website Content Translation

Translate English website content into Arabic (Egyptian dialect)

Social Media Content

Generate localized social media content for Arabic users

Business Applications

Business Email Translation

Facilitate business communication between English and Arabic users

🚀 masrawy-english-arabic-translator

This model is a fine - tuned English - Arabic translator. It is based on [Helsinki - NLP/opus - mt - en - ar](https://huggingface.co/Helsinki - NLP/opus - mt - en - ar) and trained on an unknown dataset, achieving a loss of 2.3696 on the evaluation set.

🚀 Quick Start

This model can be used for English - Arabic translation tasks. You can load it using the Hugging Face Transformers library.

✨ Features

Fine - tuned from [Helsinki - NLP/opus - mt - en - ar](https://huggingface.co/Helsinki - NLP/opus - mt - en - ar).
Achieved a loss of 2.3696 on the evaluation set.

📚 Documentation

Model Information

Property	Details
Model Type	Fine - tuned translation model
Base Model	[Helsinki - NLP/opus - mt - en - ar](https://huggingface.co/Helsinki - NLP/opus - mt - en - ar)
Datasets	oddadmix/english - arabic - translations
Language	English, Arabic
Pipeline Tag	Translation

Training Procedure

Training Hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e - 05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
lr_scheduler_type: linear
num_epochs: 30
mixed_precision_training: Native AMP

Training Results

Training Loss	Epoch	Step	Validation Loss
3.2491	1.0	1198	2.9310
2.8555	2.0	2396	2.7350
2.6079	3.0	3594	2.6380
2.5038	4.0	4792	2.5691
2.3559	5.0	5990	2.5271
2.2868	6.0	7188	2.4843
2.1985	7.0	8386	2.4646
2.1517	8.0	9584	2.4430
2.0742	9.0	10782	2.4295
2.0326	10.0	11980	2.4169
1.9601	11.0	13178	2.4055
1.9361	12.0	14376	2.4044
1.9269	13.0	15574	2.3900
1.876	14.0	16772	2.3922
1.8449	15.0	17970	2.3801
1.7911	16.0	19168	2.3793
1.7514	17.0	20366	2.3745
1.7356	18.0	21564	2.3725
1.717	19.0	22762	2.3729
1.7136	20.0	23960	2.3731
1.6919	21.0	25158	2.3699
1.6693	22.0	26356	2.3720
1.6447	23.0	27554	2.3699
1.6159	24.0	28752	2.3684
1.6053	25.0	29950	2.3705
1.6269	26.0	31148	2.3705
1.6141	27.0	32346	2.3712
1.6109	28.0	33544	2.3704
1.6066	29.0	34742	2.3699
1.5936	30.0	35940	2.3696

Framework Versions

Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.14.5
Tokenizers 0.15.1

📄 License

This model is licensed under the Apache 2.0 license.

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