| --- |
| base_model: aubmindlab/bert-base-arabertv2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: article_classification_modelv12 |
| 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. --> |
|
|
| # article_classification_modelv12 |
|
|
| This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0733 |
| - Accuracy: 0.9884 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Accuracy | Validation Loss | |
| |:-------------:|:-----:|:-----:|:--------:|:---------------:| |
| | 0.2914 | 1.0 | 5554 | 0.9158 | 0.2781 | |
| | 0.2064 | 2.0 | 11108 | 0.9223 | 0.2741 | |
| | 0.1649 | 3.0 | 16662 | 0.9248 | 0.2919 | |
| | 0.1396 | 4.0 | 22216 | 0.9296 | 0.3014 | |
| | 0.1008 | 5.0 | 27770 | 0.9291 | 0.3584 | |
| | 0.0806 | 6.0 | 33324 | 0.9290 | 0.4003 | |
| | 0.0872 | 7.0 | 38878 | 0.9239 | 0.4435 | |
| | 0.0399 | 8.0 | 44432 | 0.9262 | 0.4933 | |
| | 0.0302 | 9.0 | 49986 | 0.9269 | 0.5392 | |
| | 0.0678 | 10.0 | 55540 | 0.9889 | 0.0564 | |
| | 0.0332 | 11.0 | 61094 | 0.9886 | 0.0650 | |
| | 0.0315 | 12.0 | 66648 | 0.9886 | 0.0666 | |
| | 0.0174 | 13.0 | 72202 | 0.9885 | 0.0701 | |
| | 0.0158 | 14.0 | 77756 | 0.9881 | 0.0742 | |
| | 0.0054 | 15.0 | 83310 | 0.0733 | 0.9884 | |
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| ### Framework versions |
|
|
| - Transformers 4.40.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
|
|
