19levels_26260
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9035
- Macro F1: 0.3446
- Macro Precision: 0.3492
- Macro Recall: 0.3616
- Accuracy: 0.4837
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 411 | 1.5486 | 0.2608 | 0.2886 | 0.2876 | 0.4562 |
| 1.755 | 2.0 | 822 | 1.4731 | 0.3154 | 0.3627 | 0.3177 | 0.4848 |
| 1.2824 | 3.0 | 1233 | 1.5223 | 0.3562 | 0.3659 | 0.3733 | 0.4918 |
| 0.9466 | 4.0 | 1644 | 1.6962 | 0.3501 | 0.3416 | 0.3811 | 0.4828 |
| 0.6635 | 5.0 | 2055 | 1.8199 | 0.3556 | 0.3535 | 0.3803 | 0.4846 |
| 0.6635 | 6.0 | 2466 | 1.9035 | 0.3446 | 0.3492 | 0.3616 | 0.4837 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.19.1
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Base model
aubmindlab/bert-base-arabertv02