| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: fine-tuned-arabert_mixdata_latest |
| 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_mixdata_latest |
|
|
| 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: 0.1937 |
| - Accuracy: 0.9572 |
| - Precision: 0.9695 |
| - Recall: 0.9612 |
| - F1: 0.9653 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.159 | 1.0 | 64776 | 0.1417 | 0.9537 | 0.9620 | 0.9633 | 0.9627 | |
| | 0.1303 | 2.0 | 129552 | 0.1743 | 0.9551 | 0.9697 | 0.9575 | 0.9636 | |
| | 0.1135 | 3.0 | 194328 | 0.1615 | 0.9570 | 0.9652 | 0.9654 | 0.9653 | |
| | 0.0957 | 4.0 | 259104 | 0.1937 | 0.9572 | 0.9695 | 0.9612 | 0.9653 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.19.3 |
| - Pytorch 1.11.0+cu113 |
| - Datasets 2.2.2 |
| - Tokenizers 0.12.1 |
|
|
