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metga97/egytriplet-e5-large-instruct
egytriplet-e5-large-instruct is a machine learning model from metga97. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This model is a fine-tuned version of the multilingual-e5-large for semantic embedding tasks in Egyptian Arabic and Modern Standard Arabic (MSA).
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From the Hugging Face model README
This model is a fine-tuned version of the multilingual-e5-large for semantic embedding tasks in Egyptian Arabic and Modern Standard Arabic (MSA).
It was trained using the EgyTriplets - 2M dataset, a large-scale triplet dataset built using an automated pipeline involving translation, quality scoring, and hard-negative mining.
| Setting | Value |
|---|---|
| Base Model | multilingual-e5-large / multilingual-e5-large-instruct |
| Dataset | EgyTriplets - 2M |
| Loss Function | TripletMarginLoss (margin = 0.3) |
| Batch Size | 16 |
| Epochs | 3 |
| Learning Rate | 2e-5 |
| Hardware | NVIDIA A100 40GB |
| Model | Final Triplet Loss |
|---|---|
| egytriplet-e5-large | 0.107 |
| egytriplet-e5-large-instruct | 0.103 |
Lower loss = better semantic alignment.
This model is best suited for:
CC BY 4.0 — free to use, adapt, and share with attribution.
If you use this model in your work, please cite:
@misc{egytriplets2024,
author = {Mohammad Essam},
title = {EgyTriplets: Generating 2 Million Egyptian Arabic Triplets via Transformer-Based Translation and Retrieval},
year = {2024},
url = {https://huggingface.co/datasets/metga97/egytriplets-2m}
}