metadata
base_model: aubmindlab/bert-base-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetunning
results: []
finetunning
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3308
- Accuracy: 0.9494
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2049 | 1.0 | 1250 | 0.1725 | 0.9478 |
| 0.1392 | 2.0 | 2500 | 0.1712 | 0.9456 |
| 0.0982 | 3.0 | 3750 | 0.1812 | 0.9476 |
| 0.0769 | 4.0 | 5000 | 0.2262 | 0.9472 |
| 0.0454 | 5.0 | 6250 | 0.2438 | 0.9504 |
| 0.0364 | 6.0 | 7500 | 0.2611 | 0.9496 |
| 0.0235 | 7.0 | 8750 | 0.3145 | 0.9476 |
| 0.015 | 8.0 | 10000 | 0.3103 | 0.9494 |
| 0.0131 | 9.0 | 11250 | 0.3279 | 0.9492 |
| 0.0082 | 10.0 | 12500 | 0.3308 | 0.9494 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2