metadata
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert
results: []
bert
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: 1.9191
- Macro F1: 0.3349
- Macro Precision: 0.3782
- Macro Recall: 0.3232
- Accuracy: 0.4557
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.8594 | 1.0 | 857 | 1.5842 | 0.2852 | 0.3360 | 0.2880 | 0.4542 |
| 1.3775 | 2.0 | 1714 | 1.5581 | 0.3394 | 0.3959 | 0.3210 | 0.4575 |
| 1.1436 | 3.0 | 2571 | 1.5983 | 0.3272 | 0.4183 | 0.3139 | 0.4631 |
| 0.9682 | 4.0 | 3428 | 1.7181 | 0.3383 | 0.3793 | 0.3254 | 0.4688 |
| 0.7683 | 5.0 | 4285 | 1.8410 | 0.3318 | 0.3755 | 0.3173 | 0.4535 |
| 0.6693 | 6.0 | 5142 | 1.9191 | 0.3349 | 0.3782 | 0.3232 | 0.4557 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.2