11levels_4496
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: 1.3730
- Macro F1: 0.4629
- Macro Precision: 0.4680
- Macro Recall: 0.4717
- Accuracy: 0.5716
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 | 71 | 1.5393 | 0.2414 | 0.3507 | 0.2753 | 0.4422 |
| No log | 2.0 | 142 | 1.3162 | 0.3943 | 0.4494 | 0.4174 | 0.5355 |
| No log | 3.0 | 213 | 1.2946 | 0.4139 | 0.5197 | 0.4300 | 0.5549 |
| No log | 4.0 | 284 | 1.3114 | 0.4436 | 0.4740 | 0.4541 | 0.5677 |
| No log | 5.0 | 355 | 1.3352 | 0.4515 | 0.4538 | 0.4594 | 0.5682 |
| No log | 6.0 | 426 | 1.3730 | 0.4629 | 0.4680 | 0.4717 | 0.5716 |
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