---
library_name: transformers
base_model: asafaya/bert-base-arabic
tags:
- generated_from_trainer
model-index:
- name: bert-base-arabic-TunDC
  results: []
language:
- ar
---

<!-- 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. -->

# bert-base-arabic-TunDC

This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5931

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4712        | 1.0   | 1754 | 0.5598          |
| 0.3853        | 2.0   | 3508 | 0.5205          |
| 0.434         | 3.0   | 5262 | 0.5253          |
| 0.6624        | 4.0   | 7016 | 0.6354          |
| 0.374         | 5.0   | 8770 | 0.5931          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0

### Classification Report

| Metric        | Precision | Recall | F1-Score | Support |
|--------------|-----------|--------|----------|---------|
| **Class 0**  | 0.81      | 0.83   | 0.82     | 3311    |
| **Class 1**  | 0.78      | 0.77   | 0.78     | 2703    |
| **Accuracy** |           |        | 0.80     | 6014    |
| **Macro Avg** | 0.80      | 0.80   | 0.80     | 6014    |
| **Weighted Avg** | 0.80  | 0.80   | 0.80     | 6014    |


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