| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: AraBERT_token_classification_Araieval24_binary_all_data |
| 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. --> |
|
|
| # AraBERT_token_classification_Araieval24_binary_all_data |
|
|
| 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: 0.6550 |
| - Precision: 0.1699 |
| - Recall: 0.2317 |
| - F1: 0.1960 |
| - Accuracy: 0.7589 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.4925 | 1.0 | 1495 | 0.5219 | 0.1768 | 0.1444 | 0.1589 | 0.7688 | |
| | 0.4596 | 2.0 | 2990 | 0.5213 | 0.1275 | 0.1950 | 0.1542 | 0.7560 | |
| | 0.4273 | 3.0 | 4485 | 0.5231 | 0.1459 | 0.2094 | 0.1720 | 0.7658 | |
| | 0.4008 | 4.0 | 5980 | 0.5287 | 0.1722 | 0.1925 | 0.1818 | 0.7709 | |
| | 0.3783 | 5.0 | 7475 | 0.5650 | 0.1667 | 0.2242 | 0.1913 | 0.7646 | |
| | 0.3592 | 6.0 | 8970 | 0.6256 | 0.1763 | 0.2289 | 0.1992 | 0.7647 | |
| | 0.3427 | 7.0 | 10465 | 0.6223 | 0.1756 | 0.2256 | 0.1975 | 0.7651 | |
| | 0.3273 | 8.0 | 11960 | 0.5932 | 0.1691 | 0.2244 | 0.1929 | 0.7608 | |
| | 0.3199 | 9.0 | 13455 | 0.6602 | 0.1789 | 0.2207 | 0.1976 | 0.7647 | |
| | 0.3067 | 10.0 | 14950 | 0.6550 | 0.1699 | 0.2317 | 0.1960 | 0.7589 | |
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| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.13.3 |
|
|
