metadata
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: shared-task_content_bert
results: []
shared-task_content_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: 1.6166
- Macro F1: 0.5238
- Macro Precision: 0.5506
- Macro Recall: 0.5088
- Accuracy: 0.5373
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 |
|---|---|---|---|---|---|---|---|
| 1.3557 | 1.0 | 857 | 1.1959 | 0.5085 | 0.5507 | 0.4906 | 0.5293 |
| 1.006 | 2.0 | 1714 | 1.1857 | 0.5130 | 0.5522 | 0.5042 | 0.5339 |
| 0.8063 | 3.0 | 2571 | 1.2605 | 0.5181 | 0.5385 | 0.5079 | 0.5321 |
| 0.6613 | 4.0 | 3428 | 1.3541 | 0.5206 | 0.5486 | 0.5064 | 0.5346 |
| 0.5106 | 5.0 | 4285 | 1.5204 | 0.5151 | 0.5460 | 0.4981 | 0.5304 |
| 0.4373 | 6.0 | 5142 | 1.6166 | 0.5238 | 0.5506 | 0.5088 | 0.5373 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.2