| --- |
| library_name: transformers |
| base_model: aubmindlab/bert-base-arabertv02 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert |
| 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 |
|
|
| This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9191 |
| - Macro F1: 0.3349 |
| - Macro Precision: 0.3782 |
| - Macro Recall: 0.3232 |
| - Accuracy: 0.4557 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 16 |
| - 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: 6 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:| |
| | 1.8594 | 1.0 | 857 | 1.5842 | 0.2852 | 0.3360 | 0.2880 | 0.4542 | |
| | 1.3775 | 2.0 | 1714 | 1.5581 | 0.3394 | 0.3959 | 0.3210 | 0.4575 | |
| | 1.1436 | 3.0 | 2571 | 1.5983 | 0.3272 | 0.4183 | 0.3139 | 0.4631 | |
| | 0.9682 | 4.0 | 3428 | 1.7181 | 0.3383 | 0.3793 | 0.3254 | 0.4688 | |
| | 0.7683 | 5.0 | 4285 | 1.8410 | 0.3318 | 0.3755 | 0.3173 | 0.4535 | |
| | 0.6693 | 6.0 | 5142 | 1.9191 | 0.3349 | 0.3782 | 0.3232 | 0.4557 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.53.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 2.14.4 |
| - Tokenizers 0.21.2 |
|
|
