| --- |
| base_model: asafaya/bert-base-arabic |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: Improved-Arabic-bert-base |
| 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. --> |
|
|
| # Improved-Arabic-bert-base |
|
|
| This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7595 |
| - Accuracy: 0.86 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - 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 | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.5197 | 0.55 | 50 | 0.3977 | 0.8 | |
| | 0.3323 | 1.1 | 100 | 0.3298 | 0.86 | |
| | 0.2844 | 1.65 | 150 | 0.3401 | 0.84 | |
| | 0.2128 | 2.2 | 200 | 0.4569 | 0.8 | |
| | 0.1539 | 2.75 | 250 | 0.4315 | 0.83 | |
| | 0.1346 | 3.3 | 300 | 0.5178 | 0.81 | |
| | 0.0933 | 3.85 | 350 | 0.5167 | 0.84 | |
| | 0.0641 | 4.4 | 400 | 0.6903 | 0.82 | |
| | 0.0698 | 4.95 | 450 | 0.5628 | 0.85 | |
| | 0.028 | 5.49 | 500 | 0.6472 | 0.86 | |
| | 0.0449 | 6.04 | 550 | 0.6739 | 0.85 | |
| | 0.0133 | 6.59 | 600 | 0.6925 | 0.84 | |
| | 0.0177 | 7.14 | 650 | 0.6716 | 0.87 | |
| | 0.0209 | 7.69 | 700 | 0.6644 | 0.89 | |
| | 0.0226 | 8.24 | 750 | 0.7650 | 0.84 | |
| | 0.0137 | 8.79 | 800 | 0.8186 | 0.86 | |
| | 0.0164 | 9.34 | 850 | 0.7771 | 0.86 | |
| | 0.006 | 9.89 | 900 | 0.7805 | 0.85 | |
| | 0.0069 | 10.44 | 950 | 0.7595 | 0.86 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.34.1 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.7 |
| - Tokenizers 0.14.1 |
|
|
