metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 19levels_8753
results: []
19levels_8753
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: 1.7915
- Macro F1: 0.3258
- Macro Precision: 0.3345
- Macro Recall: 0.3364
- Accuracy: 0.4580
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 | 137 | 1.8187 | 0.1550 | 0.2171 | 0.1882 | 0.3745 |
| No log | 2.0 | 274 | 1.6123 | 0.2977 | 0.3201 | 0.3114 | 0.4463 |
| No log | 3.0 | 411 | 1.6219 | 0.3108 | 0.3318 | 0.3180 | 0.4547 |
| 1.5447 | 4.0 | 548 | 1.6591 | 0.3152 | 0.3471 | 0.3254 | 0.4598 |
| 1.5447 | 5.0 | 685 | 1.7619 | 0.3240 | 0.3323 | 0.3340 | 0.4582 |
| 1.5447 | 6.0 | 822 | 1.7915 | 0.3258 | 0.3345 | 0.3364 | 0.4580 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.19.1