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---
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 |