---
base_model: UBC-NLP/AraT5v2-base-1024
tags:
- generated_from_trainer
model-index:
- name: bi-msa-egyptian-translator-masrawy
  results: []
language:
- ar
metrics:
- bleu
pipeline_tag: translation
library_name: transformers
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Masrawy-BiLingual-v1

**Masrawy-BiLingual-v1** is a bidirectional Arabic translation model designed to translate between **Modern Standard Arabic (MSA)** and **Egyptian Arabic**. This model was trained on a total of **360,000 sentences**, covering both directions (MSA → Egyptian and Egyptian → MSA).

---

## Evaluation Dataset

The model was evaluated using held-out test sets consisting of **diverse, high-quality sentences** in both MSA and Egyptian Arabic. The evaluation datasets included:

* **150 general conversational sentences** covering everyday topics.
* **50 business and professional sentences** including emails, reports, and announcements.
* **50 science and educational sentences** covering basic scientific concepts and educational content.
* **50 entertainment and media sentences** including movie, TV, and music contexts.
* **20 multi-sentence examples for each category** (assorted topics) to test contextual translation quality.

This resulted in **thousands of sentences** across various domains to comprehensively assess the model's performance in realistic scenarios.

---

## Evaluation Results

The model was evaluated on the above test sets for both translation directions. The results are as follows:

| Task           | BLEU   | METEOR | CHRF  |
| -------------- | ------ | ------ | ----- |
| MSA → Egyptian | 0.5806 | 0.7690 | 81.02 |
| Egyptian → MSA | 0.5842 | 0.7901 | 79.83 |

These metrics indicate strong performance in both directions for Egyptian↔MSA translation.

---

## Usage

When using the model, it is important to **append a postfix** to the input text to indicate the desired translation direction:

* To translate to **Egyptian Arabic**, append `<arz>` to the input.
* To translate to **MSA**, append `<ar>` to the input.

### Example in Python (using Hugging Face `translation` pipeline)

```python
from transformers import pipeline

model_name = "oddadmix/Masrawy-BiLingual-v1"
translator = pipeline("translation", model=model_name, tokenizer=model_name)

# Example: Translate MSA → Egyptian
input_text = "أنا أحب القراءة في المكتبة. <arz>"
translation = translator(input_text)[0]['translation_text']
print("MSA → Egyptian:", translation)

# Example: Translate Egyptian → MSA
input_text = "أنا بحب أقرا في المكتبة. <ar>"
translation = translator(input_text)[0]['translation_text']
print("Egyptian → MSA:", translation)
```