2levels_13130
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: 0.9816
- Macro F1: 0.8006
- Macro Precision: 0.8137
- Macro Recall: 0.8036
- Accuracy: 0.8020
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 | 206 | 0.4875 | 0.7866 | 0.8010 | 0.7899 | 0.7883 |
| No log | 2.0 | 412 | 0.4121 | 0.8189 | 0.8210 | 0.8197 | 0.8190 |
| 0.3409 | 3.0 | 618 | 0.5835 | 0.8053 | 0.8184 | 0.8082 | 0.8066 |
| 0.3409 | 4.0 | 824 | 0.7163 | 0.7948 | 0.8131 | 0.7987 | 0.7969 |
| 0.1054 | 5.0 | 1030 | 0.8684 | 0.8000 | 0.8132 | 0.8030 | 0.8014 |
| 0.1054 | 6.0 | 1236 | 0.9816 | 0.8006 | 0.8137 | 0.8036 | 0.8020 |
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