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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: 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 |