---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task1_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_task1_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: 0.5100
- Qwk: 0.6698
- Mse: 0.5053

## 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    | 5.4651          | -0.0419 | 5.4241 |
| No log        | 0.6667 | 4    | 2.3074          | 0.1693  | 2.2743 |
| No log        | 1.0    | 6    | 1.2115          | 0.1561  | 1.2001 |
| No log        | 1.3333 | 8    | 0.9959          | 0.4358  | 0.9923 |
| No log        | 1.6667 | 10   | 0.7290          | 0.4921  | 0.7317 |
| No log        | 2.0    | 12   | 0.7145          | 0.5587  | 0.7193 |
| No log        | 2.3333 | 14   | 0.7329          | 0.5435  | 0.7351 |
| No log        | 2.6667 | 16   | 0.7694          | 0.5219  | 0.7660 |
| No log        | 3.0    | 18   | 0.9233          | 0.4358  | 0.9210 |
| No log        | 3.3333 | 20   | 0.8596          | 0.4516  | 0.8545 |
| No log        | 3.6667 | 22   | 0.7445          | 0.5743  | 0.7322 |
| No log        | 4.0    | 24   | 0.7760          | 0.4773  | 0.7614 |
| No log        | 4.3333 | 26   | 0.6783          | 0.5743  | 0.6684 |
| No log        | 4.6667 | 28   | 0.7836          | 0.5152  | 0.7834 |
| No log        | 5.0    | 30   | 0.7387          | 0.5188  | 0.7401 |
| No log        | 5.3333 | 32   | 0.5679          | 0.5743  | 0.5656 |
| No log        | 5.6667 | 34   | 0.5183          | 0.5743  | 0.5136 |
| No log        | 6.0    | 36   | 0.5055          | 0.5743  | 0.5017 |
| No log        | 6.3333 | 38   | 0.5518          | 0.5188  | 0.5511 |
| No log        | 6.6667 | 40   | 0.6558          | 0.5188  | 0.6585 |
| No log        | 7.0    | 42   | 0.6773          | 0.6025  | 0.6812 |
| No log        | 7.3333 | 44   | 0.6216          | 0.6025  | 0.6242 |
| No log        | 7.6667 | 46   | 0.5382          | 0.6698  | 0.5375 |
| No log        | 8.0    | 48   | 0.5083          | 0.6698  | 0.5056 |
| No log        | 8.3333 | 50   | 0.5045          | 0.6698  | 0.5004 |
| No log        | 8.6667 | 52   | 0.5059          | 0.7151  | 0.5009 |
| No log        | 9.0    | 54   | 0.5070          | 0.7151  | 0.5018 |
| No log        | 9.3333 | 56   | 0.5069          | 0.7151  | 0.5016 |
| No log        | 9.6667 | 58   | 0.5086          | 0.7151  | 0.5037 |
| No log        | 10.0   | 60   | 0.5100          | 0.6698  | 0.5053 |


### Framework versions

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