---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_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_relevance_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: 0.1556
- Qwk: 0.3529
- Mse: 0.1556

## 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    | 0.3146          | 0.1946 | 0.3146 |
| No log        | 0.6667 | 4    | 0.2014          | 0.5139 | 0.2014 |
| No log        | 1.0    | 6    | 0.3227          | 0.2282 | 0.3227 |
| No log        | 1.3333 | 8    | 0.3751          | 0.2780 | 0.3751 |
| No log        | 1.6667 | 10   | 0.1512          | 0.4083 | 0.1512 |
| No log        | 2.0    | 12   | 0.1822          | 0.5139 | 0.1822 |
| No log        | 2.3333 | 14   | 0.2006          | 0.3836 | 0.2006 |
| No log        | 2.6667 | 16   | 0.1882          | 0.1946 | 0.1882 |
| No log        | 3.0    | 18   | 0.1835          | 0.1946 | 0.1835 |
| No log        | 3.3333 | 20   | 0.1790          | 0.2925 | 0.1790 |
| No log        | 3.6667 | 22   | 0.1666          | 0.3365 | 0.1666 |
| No log        | 4.0    | 24   | 0.1570          | 0.4012 | 0.1570 |
| No log        | 4.3333 | 26   | 0.1650          | 0.5139 | 0.1650 |
| No log        | 4.6667 | 28   | 0.1468          | 0.3919 | 0.1468 |
| No log        | 5.0    | 30   | 0.1342          | 0.3919 | 0.1342 |
| No log        | 5.3333 | 32   | 0.1362          | 0.3289 | 0.1362 |
| No log        | 5.6667 | 34   | 0.1387          | 0.3289 | 0.1387 |
| No log        | 6.0    | 36   | 0.1474          | 0.3919 | 0.1474 |
| No log        | 6.3333 | 38   | 0.1652          | 0.3919 | 0.1652 |
| No log        | 6.6667 | 40   | 0.1889          | 0.4483 | 0.1889 |
| No log        | 7.0    | 42   | 0.1978          | 0.4483 | 0.1978 |
| No log        | 7.3333 | 44   | 0.1910          | 0.4483 | 0.1910 |
| No log        | 7.6667 | 46   | 0.1747          | 0.2568 | 0.1747 |
| No log        | 8.0    | 48   | 0.1647          | 0.4083 | 0.1647 |
| No log        | 8.3333 | 50   | 0.1586          | 0.4083 | 0.1586 |
| No log        | 8.6667 | 52   | 0.1552          | 0.3529 | 0.1552 |
| No log        | 9.0    | 54   | 0.1544          | 0.3529 | 0.1544 |
| No log        | 9.3333 | 56   | 0.1548          | 0.3529 | 0.1548 |
| No log        | 9.6667 | 58   | 0.1554          | 0.3529 | 0.1554 |
| No log        | 10.0   | 60   | 0.1556          | 0.3529 | 0.1556 |


### Framework versions

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