---
library_name: peft
base_model: aubmindlab/bert-base-arabertv02
tags:
- base_model:adapter:aubmindlab/bert-base-arabertv02
- lora
- transformers
metrics:
- accuracy
model-index:
- name: saudi-eou-bert-classifier
  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. -->

# saudi-eou-bert-classifier

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3407
- Accuracy: 0.864
- Auc: 0.921

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.712         | 1.0   | 295  | 0.6541          | 0.619    | 0.685 |
| 0.5634        | 2.0   | 590  | 0.4838          | 0.781    | 0.845 |
| 0.4258        | 3.0   | 885  | 0.4189          | 0.819    | 0.883 |
| 0.3619        | 4.0   | 1180 | 0.3920          | 0.837    | 0.897 |
| 0.3366        | 5.0   | 1475 | 0.3684          | 0.853    | 0.907 |
| 0.3309        | 6.0   | 1770 | 0.3650          | 0.854    | 0.912 |
| 0.3191        | 7.0   | 2065 | 0.3555          | 0.856    | 0.916 |
| 0.3028        | 8.0   | 2360 | 0.3432          | 0.864    | 0.919 |
| 0.3018        | 9.0   | 2655 | 0.3437          | 0.859    | 0.92  |
| 0.2987        | 10.0  | 2950 | 0.3407          | 0.864    | 0.921 |


### Framework versions

- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1