11levels_3372
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: 1.3686
- Macro F1: 0.4277
- Macro Precision: 0.4433
- Macro Recall: 0.4288
- Accuracy: 0.5517
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 | 53 | 1.6062 | 0.2015 | 0.2503 | 0.2305 | 0.4299 |
| No log | 2.0 | 106 | 1.4079 | 0.3293 | 0.4840 | 0.3286 | 0.4994 |
| No log | 3.0 | 159 | 1.3273 | 0.3848 | 0.4387 | 0.3805 | 0.5311 |
| No log | 4.0 | 212 | 1.3519 | 0.4151 | 0.4376 | 0.4271 | 0.5399 |
| No log | 5.0 | 265 | 1.3516 | 0.4235 | 0.4483 | 0.4244 | 0.5503 |
| No log | 6.0 | 318 | 1.3686 | 0.4277 | 0.4433 | 0.4288 | 0.5517 |
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