---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task7_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_task7_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: 0.4980
- Qwk: 0.5556
- Mse: 0.4980

## 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    | 1.5251          | 0.0993 | 1.5251 |
| No log        | 0.6667 | 4    | 0.8432          | 0.4389 | 0.8432 |
| No log        | 1.0    | 6    | 1.0961          | 0.4310 | 1.0961 |
| No log        | 1.3333 | 8    | 1.4643          | 0.4246 | 1.4643 |
| No log        | 1.6667 | 10   | 0.7875          | 0.4595 | 0.7875 |
| No log        | 2.0    | 12   | 0.5137          | 0.6346 | 0.5137 |
| No log        | 2.3333 | 14   | 0.6935          | 0.5893 | 0.6935 |
| No log        | 2.6667 | 16   | 0.6820          | 0.5547 | 0.6820 |
| No log        | 3.0    | 18   | 0.8761          | 0.4868 | 0.8761 |
| No log        | 3.3333 | 20   | 1.0195          | 0.4553 | 1.0195 |
| No log        | 3.6667 | 22   | 0.7568          | 0.4924 | 0.7568 |
| No log        | 4.0    | 24   | 0.5131          | 0.5471 | 0.5131 |
| No log        | 4.3333 | 26   | 0.4657          | 0.5627 | 0.4657 |
| No log        | 4.6667 | 28   | 0.4764          | 0.5471 | 0.4764 |
| No log        | 5.0    | 30   | 0.5337          | 0.4983 | 0.5337 |
| No log        | 5.3333 | 32   | 0.6627          | 0.4983 | 0.6627 |
| No log        | 5.6667 | 34   | 0.6382          | 0.4983 | 0.6382 |
| No log        | 6.0    | 36   | 0.5386          | 0.4983 | 0.5386 |
| No log        | 6.3333 | 38   | 0.4986          | 0.5398 | 0.4986 |
| No log        | 6.6667 | 40   | 0.4838          | 0.5471 | 0.4838 |
| No log        | 7.0    | 42   | 0.4885          | 0.5471 | 0.4885 |
| No log        | 7.3333 | 44   | 0.5346          | 0.5398 | 0.5346 |
| No log        | 7.6667 | 46   | 0.6171          | 0.5090 | 0.6171 |
| No log        | 8.0    | 48   | 0.6649          | 0.5090 | 0.6649 |
| No log        | 8.3333 | 50   | 0.6483          | 0.5090 | 0.6483 |
| No log        | 8.6667 | 52   | 0.5915          | 0.5090 | 0.5915 |
| No log        | 9.0    | 54   | 0.5598          | 0.4983 | 0.5598 |
| No log        | 9.3333 | 56   | 0.5257          | 0.5556 | 0.5257 |
| No log        | 9.6667 | 58   | 0.5073          | 0.5556 | 0.5073 |
| No log        | 10.0   | 60   | 0.4980          | 0.5556 | 0.4980 |


### Framework versions

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