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

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: 1.1555
- Accuracy: 0.791
- Auc: 0.865

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Auc   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----:|
| 0.5875        | 1.0   | 622   | 0.4866          | 0.75     | 0.845 |
| 0.4703        | 2.0   | 1244  | 0.5337          | 0.76     | 0.855 |
| 0.4097        | 3.0   | 1866  | 0.5273          | 0.785    | 0.869 |
| 0.3598        | 4.0   | 2488  | 0.5383          | 0.795    | 0.868 |
| 0.3278        | 5.0   | 3110  | 0.6127          | 0.803    | 0.878 |
| 0.3019        | 6.0   | 3732  | 0.6487          | 0.804    | 0.878 |
| 0.2616        | 7.0   | 4354  | 0.7659          | 0.801    | 0.874 |
| 0.2451        | 8.0   | 4976  | 0.8012          | 0.793    | 0.871 |
| 0.2241        | 9.0   | 5598  | 0.8936          | 0.802    | 0.87  |
| 0.2044        | 10.0  | 6220  | 0.9513          | 0.8      | 0.869 |
| 0.2015        | 11.0  | 6842  | 0.9689          | 0.802    | 0.869 |
| 0.1834        | 12.0  | 7464  | 0.9756          | 0.799    | 0.869 |
| 0.1731        | 13.0  | 8086  | 0.9917          | 0.796    | 0.866 |
| 0.1455        | 14.0  | 8708  | 1.0958          | 0.794    | 0.863 |
| 0.1557        | 15.0  | 9330  | 1.0042          | 0.796    | 0.869 |
| 0.1316        | 16.0  | 9952  | 1.0996          | 0.796    | 0.865 |
| 0.1335        | 17.0  | 10574 | 1.2024          | 0.794    | 0.863 |
| 0.1201        | 18.0  | 11196 | 1.1508          | 0.791    | 0.865 |
| 0.1204        | 19.0  | 11818 | 1.1580          | 0.798    | 0.865 |
| 0.1137        | 20.0  | 12440 | 1.1555          | 0.791    | 0.865 |


### Framework versions

- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.22.1