---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task5_fold0
  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. -->

# arabert_baseline_style_task5_fold0

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6425
- Qwk: 0.6667
- Mse: 0.6425

## 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: 16
- eval_batch_size: 16
- 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 | Qwk    | Mse    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| No log        | 0.3333 | 2    | 1.7460          | 0.1985 | 1.7460 |
| No log        | 0.6667 | 4    | 1.5870          | 0.0    | 1.5870 |
| No log        | 1.0    | 6    | 1.4018          | 0.0    | 1.4018 |
| No log        | 1.3333 | 8    | 1.2599          | 0.0    | 1.2599 |
| No log        | 1.6667 | 10   | 1.2011          | 0.1294 | 1.2011 |
| No log        | 2.0    | 12   | 1.1822          | 0.2077 | 1.1822 |
| No log        | 2.3333 | 14   | 1.1032          | 0.3860 | 1.1032 |
| No log        | 2.6667 | 16   | 1.0087          | 0.3860 | 1.0087 |
| No log        | 3.0    | 18   | 0.9075          | 0.5652 | 0.9075 |
| No log        | 3.3333 | 20   | 0.8395          | 0.4898 | 0.8395 |
| No log        | 3.6667 | 22   | 0.7981          | 0.4898 | 0.7981 |
| No log        | 4.0    | 24   | 0.7479          | 0.5455 | 0.7479 |
| No log        | 4.3333 | 26   | 0.7093          | 0.5455 | 0.7093 |
| No log        | 4.6667 | 28   | 0.6855          | 0.6222 | 0.6855 |
| No log        | 5.0    | 30   | 0.6929          | 0.5614 | 0.6929 |
| No log        | 5.3333 | 32   | 0.7079          | 0.4813 | 0.7079 |
| No log        | 5.6667 | 34   | 0.6704          | 0.6222 | 0.6704 |
| No log        | 6.0    | 36   | 0.6443          | 0.5946 | 0.6443 |
| No log        | 6.3333 | 38   | 0.6496          | 0.5946 | 0.6496 |
| No log        | 6.6667 | 40   | 0.6556          | 0.6119 | 0.6556 |
| No log        | 7.0    | 42   | 0.6527          | 0.5946 | 0.6527 |
| No log        | 7.3333 | 44   | 0.6454          | 0.5946 | 0.6454 |
| No log        | 7.6667 | 46   | 0.6421          | 0.6186 | 0.6421 |
| No log        | 8.0    | 48   | 0.6433          | 0.6186 | 0.6433 |
| No log        | 8.3333 | 50   | 0.6419          | 0.6352 | 0.6419 |
| No log        | 8.6667 | 52   | 0.6369          | 0.6352 | 0.6369 |
| No log        | 9.0    | 54   | 0.6384          | 0.6667 | 0.6384 |
| No log        | 9.3333 | 56   | 0.6431          | 0.6667 | 0.6431 |
| No log        | 9.6667 | 58   | 0.6432          | 0.6667 | 0.6432 |
| No log        | 10.0   | 60   | 0.6425          | 0.6667 | 0.6425 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1