---
library_name: transformers
base_model: aubmindlab/bert-base-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-arabertv2_D3Tok_EMD_19levels
  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. -->

# bert-base-arabertv2_D3Tok_EMD_19levels

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0306
- Macro F1: 0.4521
- Macro Precision: 0.4818
- Macro Recall: 0.4453
- Accuracy: 0.5291
- Accuracy With Margin: 0.6966
- Distance: 1.1860
- Quadratic weighted kappa: 0.7940
- Accuracy 7: 0.6300
- Accuracy 5: 0.6726
- Accuracy 3: 0.7412

## 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: 12

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy | Accuracy With Margin | Distance | Quadratic weighted kappa | Accuracy 7 | Accuracy 5 | Accuracy 3 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:--------------------:|:--------:|:------------------------:|:----------:|:----------:|:----------:|
| 1.0454        | 1.0   | 857   | 0.9505          | 0.2627   | 0.3239          | 0.3181       | 0.4703   | 0.6428               | 1.3360   | 0.7758                   | 0.6030     | 0.6647     | 0.7330     |
| 0.718         | 2.0   | 1714  | 0.8807          | 0.3647   | 0.3734          | 0.3709       | 0.5175   | 0.6841               | 1.1967   | 0.7981                   | 0.6297     | 0.6787     | 0.7490     |
| 0.5604        | 3.0   | 2571  | 0.9115          | 0.4027   | 0.4449          | 0.3915       | 0.5353   | 0.6837               | 1.1989   | 0.7920                   | 0.6305     | 0.6746     | 0.7393     |
| 0.4615        | 4.0   | 3428  | 0.9439          | 0.4163   | 0.4850          | 0.4124       | 0.5328   | 0.6830               | 1.2074   | 0.7942                   | 0.6256     | 0.6699     | 0.7378     |
| 0.3547        | 5.0   | 4285  | 0.9803          | 0.4059   | 0.4732          | 0.3965       | 0.5215   | 0.6807               | 1.2193   | 0.7864                   | 0.6218     | 0.6655     | 0.7363     |
| 0.2972        | 6.0   | 5142  | 0.9809          | 0.4499   | 0.4851          | 0.4425       | 0.5356   | 0.6856               | 1.2003   | 0.7931                   | 0.6287     | 0.6695     | 0.7393     |
| 0.2529        | 7.0   | 5999  | 0.9922          | 0.4427   | 0.4791          | 0.4293       | 0.5280   | 0.6885               | 1.1907   | 0.7946                   | 0.6268     | 0.6715     | 0.7431     |
| 0.2002        | 8.0   | 6856  | 1.0047          | 0.4516   | 0.4747          | 0.4448       | 0.5316   | 0.6902               | 1.1818   | 0.7974                   | 0.6306     | 0.6731     | 0.7390     |
| 0.1734        | 9.0   | 7713  | 1.0181          | 0.4545   | 0.4949          | 0.4515       | 0.5353   | 0.6951               | 1.1945   | 0.7920                   | 0.6354     | 0.6784     | 0.7440     |
| 0.1466        | 10.0  | 8570  | 1.0184          | 0.4469   | 0.4748          | 0.4414       | 0.5271   | 0.6951               | 1.1871   | 0.7960                   | 0.6312     | 0.6739     | 0.7404     |
| 0.1342        | 11.0  | 9427  | 1.0291          | 0.4496   | 0.4739          | 0.4471       | 0.5287   | 0.6985               | 1.1815   | 0.7980                   | 0.6328     | 0.6770     | 0.7446     |
| 0.1166        | 12.0  | 10284 | 1.0306          | 0.4521   | 0.4818          | 0.4453       | 0.5291   | 0.6966               | 1.1860   | 0.7940                   | 0.6300     | 0.6726     | 0.7412     |


### Framework versions

- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2