11levels_6744
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: 1.3594
- Macro F1: 0.4733
- Macro Precision: 0.4858
- Macro Recall: 0.4850
- Accuracy: 0.6031
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 | 106 | 1.3470 | 0.3576 | 0.4073 | 0.3513 | 0.5338 |
| No log | 2.0 | 212 | 1.1845 | 0.4366 | 0.4635 | 0.4424 | 0.5905 |
| No log | 3.0 | 318 | 1.2118 | 0.4664 | 0.4698 | 0.4803 | 0.5949 |
| No log | 4.0 | 424 | 1.2322 | 0.4685 | 0.4940 | 0.4662 | 0.6111 |
| 1.0486 | 5.0 | 530 | 1.3453 | 0.4674 | 0.4882 | 0.4771 | 0.5963 |
| 1.0486 | 6.0 | 636 | 1.3594 | 0.4733 | 0.4858 | 0.4850 | 0.6031 |
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