2levels_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: 0.9906
- Macro F1: 0.8031
- Macro Precision: 0.8191
- Macro Recall: 0.8065
- Accuracy: 0.8047
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 | 0.4004 | 0.8111 | 0.8211 | 0.8134 | 0.8120 |
| 0.4173 | 2.0 | 822 | 0.4100 | 0.8204 | 0.8321 | 0.8229 | 0.8214 |
| 0.2747 | 3.0 | 1233 | 0.5065 | 0.8178 | 0.8298 | 0.8204 | 0.8189 |
| 0.1498 | 4.0 | 1644 | 0.6896 | 0.8100 | 0.8197 | 0.8123 | 0.8109 |
| 0.0747 | 5.0 | 2055 | 0.9460 | 0.8000 | 0.8182 | 0.8038 | 0.8020 |
| 0.0747 | 6.0 | 2466 | 0.9906 | 0.8031 | 0.8191 | 0.8065 | 0.8047 |
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