---
base_model: ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA
tags:
- generated_from_trainer
model-index:
- name: AraElectra-QA-EgyLaw-Squad
  results: []
license: mit
datasets:
- BoodyAhmedHamdy/EgyLaw-Squad
language:
- ar
metrics:
- f1
- exact_match
library_name: transformers
pipeline_tag: question-answering
---

<!-- 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. -->

# AraElectra-QA-EgyLaw-Squad

This model is a fine-tuned version of [ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA](https://huggingface.co/ZeyadAhmed/AraElectra-Arabic-SQuADv2-QA) on the [Egyption Law Squad](https://huggingface.co/datasets/BoodyAhmedHamdy/EgyLaw-Squad) dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0008

## Model description

Araelctra model for Question Answering Task in Egyption law specially Personal Status Law (قانون الاحوال الشخصية)

this Model was created for a Graduation Project in Computers and Artificial intellgence at Helwan University under supervisation from [Dr.Ensaf Hossen](https://scholar.google.com/citations?user=eeYSe3sAAAAJ&hl=en)

## About Team
- [Abdelrahman Ahmed Hamdy](https://github.com/Boodyahmedhamdy)
- [Shehab Gamal-elden](https://github.com/000Shehab000)
- [Mohsen Hisham Mohamed](https://github.com/Mohsen-Hesham)
- [Maya Ahmed Abdelsatar](https://github.com/mayaahmed2002)
- [Nancy Ahmed Mostafa](https://github.com/Nancyahmedmustafa)
- [Nour Khaled Ali](https://github.com/NourSewafy)


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 89   | 3.2762          |
| 3.9126        | 2.0   | 178  | 3.0150          |
| 2.5679        | 3.0   | 267  | 2.8324          |
| 1.7576        | 4.0   | 356  | 2.9655          |
| 1.1946        | 5.0   | 445  | 3.1643          |
| 0.8854        | 6.0   | 534  | 3.0778          |
| 0.7387        | 7.0   | 623  | 3.2814          |
| 0.6067        | 8.0   | 712  | 3.2391          |
| 0.5201        | 9.0   | 801  | 3.3717          |
| 0.5201        | 10.0  | 890  | 3.5752          |
| 0.4377        | 11.0  | 979  | 3.6657          |
| 0.4025        | 12.0  | 1068 | 3.8178          |
| 0.4077        | 13.0  | 1157 | 3.7404          |
| 0.3355        | 14.0  | 1246 | 3.7566          |
| 0.3627        | 15.0  | 1335 | 3.9959          |
| 0.3376        | 16.0  | 1424 | 3.8815          |
| 0.3676        | 17.0  | 1513 | 3.9674          |
| 0.3165        | 18.0  | 1602 | 3.9368          |
| 0.3165        | 19.0  | 1691 | 3.9836          |
| 0.3148        | 20.0  | 1780 | 4.0008          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2