content_BARECX
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: 1.5934
- Macro F1: 0.5262
- Macro Precision: 0.5513
- Macro Recall: 0.5114
- Accuracy: 0.5369
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 |
|---|---|---|---|---|---|---|---|
| 1.339 | 1.0 | 835 | 1.2243 | 0.5097 | 0.5587 | 0.4976 | 0.5204 |
| 1.0053 | 2.0 | 1670 | 1.1786 | 0.5246 | 0.5523 | 0.5095 | 0.5367 |
| 0.7992 | 3.0 | 2505 | 1.2449 | 0.5330 | 0.5564 | 0.5236 | 0.5417 |
| 0.6304 | 4.0 | 3340 | 1.3653 | 0.5256 | 0.5470 | 0.5161 | 0.5331 |
| 0.5 | 5.0 | 4175 | 1.4955 | 0.5232 | 0.5544 | 0.5034 | 0.5341 |
| 0.4214 | 6.0 | 5010 | 1.5934 | 0.5262 | 0.5513 | 0.5114 | 0.5369 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu118
- Datasets 3.0.2
- Tokenizers 0.19.1
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Base model
aubmindlab/bert-base-arabertv02