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---
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 |