11levels_26977
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: 1.2826
- Macro F1: 0.5615
- Macro Precision: 0.5598
- Macro Recall: 0.5707
- Accuracy: 0.6702
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 | 422 | 1.0239 | 0.5139 | 0.5318 | 0.5450 | 0.6583 |
| 1.2083 | 2.0 | 844 | 0.9638 | 0.5598 | 0.5557 | 0.5921 | 0.6787 |
| 0.8027 | 3.0 | 1266 | 0.9719 | 0.5608 | 0.5761 | 0.5539 | 0.6833 |
| 0.5643 | 4.0 | 1688 | 1.1153 | 0.5600 | 0.5591 | 0.5718 | 0.6714 |
| 0.3806 | 5.0 | 2110 | 1.2091 | 0.5698 | 0.5705 | 0.5789 | 0.6712 |
| 0.2509 | 6.0 | 2532 | 1.2826 | 0.5615 | 0.5598 | 0.5707 | 0.6702 |
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