---
base_model: asafaya/bert-base-arabic
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-base-arabic-finetuned
  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. -->

# bert-base-arabic-finetuned

This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1660
- F1: 0.7561
- Roc Auc: 0.8464
- Accuracy: 0.7180

## 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: 2e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1932        | 1.0   | 1133 | 0.1840          | 0.7144 | 0.8252  | 0.6703   |
| 0.1397        | 2.0   | 2266 | 0.1660          | 0.7561 | 0.8464  | 0.7180   |
| 0.0887        | 3.0   | 3399 | 0.1835          | 0.7487 | 0.8508  | 0.7269   |
| 0.0572        | 4.0   | 4532 | 0.2149          | 0.7356 | 0.8434  | 0.7200   |
| 0.0351        | 5.0   | 5665 | 0.2297          | 0.7377 | 0.8453  | 0.7249   |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2