---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task7_fold1
  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_task7_fold1

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: 0.3701
- Qwk: 0.7283
- Mse: 0.3603

## 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    | 0.7720          | 0.3388 | 0.7758 |
| No log        | 0.6667 | 4    | 0.5488          | 0.6361 | 0.5756 |
| No log        | 1.0    | 6    | 0.6199          | 0.6083 | 0.6502 |
| No log        | 1.3333 | 8    | 0.5891          | 0.3780 | 0.5962 |
| No log        | 1.6667 | 10   | 0.5013          | 0.5556 | 0.5111 |
| No log        | 2.0    | 12   | 0.4841          | 0.7640 | 0.4991 |
| No log        | 2.3333 | 14   | 0.4386          | 0.784  | 0.4514 |
| No log        | 2.6667 | 16   | 0.4343          | 0.6667 | 0.4393 |
| No log        | 3.0    | 18   | 0.4876          | 0.6206 | 0.4868 |
| No log        | 3.3333 | 20   | 0.4572          | 0.6294 | 0.4528 |
| No log        | 3.6667 | 22   | 0.3651          | 0.6769 | 0.3604 |
| No log        | 4.0    | 24   | 0.3743          | 0.6434 | 0.3662 |
| No log        | 4.3333 | 26   | 0.4705          | 0.6261 | 0.4557 |
| No log        | 4.6667 | 28   | 0.5940          | 0.5033 | 0.5754 |
| No log        | 5.0    | 30   | 0.5564          | 0.5650 | 0.5374 |
| No log        | 5.3333 | 32   | 0.4207          | 0.6607 | 0.4059 |
| No log        | 5.6667 | 34   | 0.3696          | 0.6637 | 0.3577 |
| No log        | 6.0    | 36   | 0.3816          | 0.6607 | 0.3687 |
| No log        | 6.3333 | 38   | 0.4231          | 0.6261 | 0.4080 |
| No log        | 6.6667 | 40   | 0.4191          | 0.6261 | 0.4044 |
| No log        | 7.0    | 42   | 0.4158          | 0.6261 | 0.4016 |
| No log        | 7.3333 | 44   | 0.4009          | 0.6261 | 0.3875 |
| No log        | 7.6667 | 46   | 0.3811          | 0.6474 | 0.3694 |
| No log        | 8.0    | 48   | 0.3746          | 0.6810 | 0.3639 |
| No log        | 8.3333 | 50   | 0.3601          | 0.7283 | 0.3514 |
| No log        | 8.6667 | 52   | 0.3557          | 0.7283 | 0.3474 |
| No log        | 9.0    | 54   | 0.3591          | 0.7283 | 0.3506 |
| No log        | 9.3333 | 56   | 0.3648          | 0.7283 | 0.3558 |
| No log        | 9.6667 | 58   | 0.3690          | 0.7283 | 0.3593 |
| No log        | 10.0   | 60   | 0.3701          | 0.7283 | 0.3603 |


### Framework versions

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