---
base_model: aubmindlab/bert-base-arabert
tags:
- generated_from_trainer
model-index:
- name: QA_FineTuned_Arabertr
  results: []
---

<!-- 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. -->

# QA_FineTuned_Arabertr

This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8357

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.518         | 0.13  | 10   | 4.3573          |
| 4.254         | 0.27  | 20   | 3.8054          |
| 3.9915        | 0.4   | 30   | 3.5788          |
| 3.836         | 0.53  | 40   | 3.4054          |
| 3.6733        | 0.67  | 50   | 3.2506          |
| 3.4425        | 0.8   | 60   | 3.0882          |
| 3.2917        | 0.93  | 70   | 2.9934          |
| 2.9622        | 1.07  | 80   | 3.0029          |
| 2.3228        | 1.2   | 90   | 3.1190          |
| 2.4004        | 1.33  | 100  | 2.8613          |
| 2.3946        | 1.47  | 110  | 2.8983          |
| 2.3108        | 1.6   | 120  | 2.7711          |
| 2.3778        | 1.73  | 130  | 2.7062          |
| 2.3335        | 1.87  | 140  | 2.9916          |
| 2.4273        | 2.0   | 150  | 2.6713          |
| 1.4165        | 2.13  | 160  | 2.8003          |
| 1.1488        | 2.27  | 170  | 2.7959          |
| 1.2044        | 2.4   | 180  | 3.1311          |
| 1.2715        | 2.53  | 190  | 2.8319          |
| 1.1309        | 2.67  | 200  | 2.8048          |
| 1.3421        | 2.8   | 210  | 2.8158          |
| 0.9567        | 2.93  | 220  | 2.8357          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2