---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task5_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_task5_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: 0.4351
- Qwk: 0.7772
- Mse: 0.4351

## 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    | 3.0281          | 0.0186 | 3.0281 |
| No log        | 0.6667 | 4    | 1.1102          | 0.0    | 1.1102 |
| No log        | 1.0    | 6    | 0.6207          | 0.3478 | 0.6207 |
| No log        | 1.3333 | 8    | 0.5268          | 0.3462 | 0.5268 |
| No log        | 1.6667 | 10   | 0.5443          | 0.2941 | 0.5443 |
| No log        | 2.0    | 12   | 0.4954          | 0.2941 | 0.4954 |
| No log        | 2.3333 | 14   | 0.3975          | 0.3314 | 0.3975 |
| No log        | 2.6667 | 16   | 0.3492          | 0.4828 | 0.3492 |
| No log        | 3.0    | 18   | 0.3545          | 0.5238 | 0.3545 |
| No log        | 3.3333 | 20   | 0.3763          | 0.6839 | 0.3763 |
| No log        | 3.6667 | 22   | 0.4022          | 0.7472 | 0.4022 |
| No log        | 4.0    | 24   | 0.4557          | 0.7772 | 0.4557 |
| No log        | 4.3333 | 26   | 0.4928          | 0.7549 | 0.4928 |
| No log        | 4.6667 | 28   | 0.4922          | 0.7549 | 0.4922 |
| No log        | 5.0    | 30   | 0.4857          | 0.6939 | 0.4857 |
| No log        | 5.3333 | 32   | 0.4759          | 0.6939 | 0.4759 |
| No log        | 5.6667 | 34   | 0.4948          | 0.7549 | 0.4948 |
| No log        | 6.0    | 36   | 0.4684          | 0.7772 | 0.4684 |
| No log        | 6.3333 | 38   | 0.4446          | 0.7772 | 0.4446 |
| No log        | 6.6667 | 40   | 0.4305          | 0.7772 | 0.4305 |
| No log        | 7.0    | 42   | 0.4345          | 0.7222 | 0.4345 |
| No log        | 7.3333 | 44   | 0.4345          | 0.6324 | 0.4345 |
| No log        | 7.6667 | 46   | 0.4215          | 0.75   | 0.4215 |
| No log        | 8.0    | 48   | 0.4192          | 0.7772 | 0.4192 |
| No log        | 8.3333 | 50   | 0.4335          | 0.7772 | 0.4335 |
| No log        | 8.6667 | 52   | 0.4440          | 0.7549 | 0.4440 |
| No log        | 9.0    | 54   | 0.4449          | 0.7549 | 0.4449 |
| No log        | 9.3333 | 56   | 0.4405          | 0.7549 | 0.4405 |
| No log        | 9.6667 | 58   | 0.4375          | 0.7772 | 0.4375 |
| No log        | 10.0   | 60   | 0.4351          | 0.7772 | 0.4351 |


### Framework versions

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