finetunning / README.md
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---
base_model: aubmindlab/bert-base-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetunning
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetunning
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/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