| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: fine_tuned_mix40k_arabert_cleaned |
| | 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. --> |
| |
|
| | # fine_tuned_mix40k_arabert_cleaned |
| |
|
| | 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: 0.3804 |
| | - Accuracy: 0.8933 |
| | - Precision: 0.9219 |
| | - Recall: 0.8580 |
| | - F1: 0.8888 |
| |
|
| | ## 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: 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: 10 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.3113 | 1.0 | 10794 | 0.2831 | 0.8782 | 0.8802 | 0.8739 | 0.8770 | |
| | | 0.2268 | 2.0 | 21588 | 0.2901 | 0.8861 | 0.9270 | 0.8369 | 0.8796 | |
| | | 0.1788 | 3.0 | 32382 | 0.3294 | 0.8901 | 0.9086 | 0.8660 | 0.8868 | |
| | | 0.1413 | 4.0 | 43176 | 0.3804 | 0.8933 | 0.9219 | 0.8580 | 0.8888 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.19.2 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.2.2 |
| | - Tokenizers 0.12.1 |
| |
|
