11levels_13488
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: 1.3312
- Macro F1: 0.5278
- Macro Precision: 0.5233
- Macro Recall: 0.5514
- Accuracy: 0.6426
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 | 211 | 1.1548 | 0.4236 | 0.4279 | 0.4607 | 0.6031 |
| No log | 2.0 | 422 | 1.1477 | 0.4975 | 0.5239 | 0.5065 | 0.6322 |
| 1.1584 | 3.0 | 633 | 1.0954 | 0.5242 | 0.5301 | 0.5396 | 0.6448 |
| 1.1584 | 4.0 | 844 | 1.2075 | 0.5194 | 0.5140 | 0.5488 | 0.6443 |
| 0.5527 | 5.0 | 1055 | 1.2827 | 0.5218 | 0.5177 | 0.5432 | 0.6404 |
| 0.5527 | 6.0 | 1266 | 1.3312 | 0.5278 | 0.5233 | 0.5514 | 0.6426 |
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