| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: fine-tuned-arabert-arabGloss-ds |
| 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-arabert-arabGloss-ds |
|
|
| 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: 0.7052 |
| - Accuracy: 0.8295 |
| - Precision: 0.8016 |
| - Recall: 0.6175 |
| - F1: 0.6976 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.4109 | 1.0 | 9494 | 0.4561 | 0.8065 | 0.6987 | 0.6900 | 0.6943 | |
| | 0.297 | 2.0 | 18988 | 0.4803 | 0.8213 | 0.7353 | 0.6855 | 0.7095 | |
| | 0.2316 | 3.0 | 28482 | 0.5530 | 0.8278 | 0.7438 | 0.7007 | 0.7216 | |
| | 0.1885 | 4.0 | 37976 | 0.7052 | 0.8295 | 0.8016 | 0.6175 | 0.6976 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.19.2 |
| - Pytorch 1.11.0+cu113 |
| - Datasets 2.2.1 |
| - Tokenizers 0.12.1 |
|
|
