11levels_25544
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: 1.6832
- Macro F1: 0.3143
- Macro Precision: 0.3674
- Macro Recall: 0.2995
- Accuracy: 0.6106
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 | 400 | 1.0144 | 0.2804 | 0.4785 | 0.2674 | 0.6045 |
| 1.0633 | 2.0 | 800 | 1.0019 | 0.3203 | 0.3562 | 0.3262 | 0.6254 |
| 0.7665 | 3.0 | 1200 | 1.0820 | 0.2915 | 0.3303 | 0.2830 | 0.6350 |
| 0.5046 | 4.0 | 1600 | 1.3068 | 0.3038 | 0.3376 | 0.2954 | 0.6146 |
| 0.3056 | 5.0 | 2000 | 1.5869 | 0.3071 | 0.3570 | 0.2916 | 0.6125 |
| 0.3056 | 6.0 | 2400 | 1.6832 | 0.3143 | 0.3674 | 0.2995 | 0.6106 |
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