---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task2_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_task2_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: 0.6287
- Qwk: 0.2903
- Mse: 0.6083

## 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    | 5.5617          | -0.0100 | 5.5560 |
| No log        | 0.6667 | 4    | 2.6178          | 0.0539  | 2.6238 |
| No log        | 1.0    | 6    | 1.5516          | 0.0077  | 1.5429 |
| No log        | 1.3333 | 8    | 0.8363          | 0.0192  | 0.8282 |
| No log        | 1.6667 | 10   | 0.8891          | 0.0     | 0.8810 |
| No log        | 2.0    | 12   | 1.0515          | 0.0     | 1.0369 |
| No log        | 2.3333 | 14   | 1.0120          | 0.0187  | 0.9900 |
| No log        | 2.6667 | 16   | 0.9023          | 0.0597  | 0.8789 |
| No log        | 3.0    | 18   | 1.1300          | 0.1259  | 1.1065 |
| No log        | 3.3333 | 20   | 1.0224          | 0.2296  | 0.9998 |
| No log        | 3.6667 | 22   | 0.7522          | 0.3247  | 0.7319 |
| No log        | 4.0    | 24   | 0.7846          | 0.125   | 0.7714 |
| No log        | 4.3333 | 26   | 0.8034          | 0.2092  | 0.7904 |
| No log        | 4.6667 | 28   | 0.7718          | 0.3046  | 0.7530 |
| No log        | 5.0    | 30   | 0.7274          | 0.3046  | 0.7075 |
| No log        | 5.3333 | 32   | 0.7003          | 0.3046  | 0.6801 |
| No log        | 5.6667 | 34   | 0.6891          | 0.3046  | 0.6689 |
| No log        | 6.0    | 36   | 0.6395          | 0.2025  | 0.6184 |
| No log        | 6.3333 | 38   | 0.6234          | 0.2734  | 0.6015 |
| No log        | 6.6667 | 40   | 0.6182          | 0.2734  | 0.5966 |
| No log        | 7.0    | 42   | 0.6234          | 0.3383  | 0.6022 |
| No log        | 7.3333 | 44   | 0.6278          | 0.3383  | 0.6070 |
| No log        | 7.6667 | 46   | 0.6152          | 0.2785  | 0.5942 |
| No log        | 8.0    | 48   | 0.6021          | 0.2785  | 0.5810 |
| No log        | 8.3333 | 50   | 0.6118          | 0.2045  | 0.5911 |
| No log        | 8.6667 | 52   | 0.6193          | 0.2903  | 0.5987 |
| No log        | 9.0    | 54   | 0.6218          | 0.2903  | 0.6012 |
| No log        | 9.3333 | 56   | 0.6223          | 0.2903  | 0.6017 |
| No log        | 9.6667 | 58   | 0.6276          | 0.2903  | 0.6071 |
| No log        | 10.0   | 60   | 0.6287          | 0.2903  | 0.6083 |


### Framework versions

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