---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task5_fold0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_baseline_relevance_task5_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: 0.3678
- Qwk: 0.2949
- Mse: 0.3678

## 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    | 0.4684          | 0.1304 | 0.4684 |
| No log        | 0.6667 | 4    | 0.4252          | 0.0    | 0.4252 |
| No log        | 1.0    | 6    | 0.4179          | 0.0    | 0.4179 |
| No log        | 1.3333 | 8    | 0.4231          | 0.0    | 0.4231 |
| No log        | 1.6667 | 10   | 0.4130          | 0.0    | 0.4130 |
| No log        | 2.0    | 12   | 0.4098          | 0.0    | 0.4098 |
| No log        | 2.3333 | 14   | 0.4153          | 0.0551 | 0.4153 |
| No log        | 2.6667 | 16   | 0.4026          | 0.0551 | 0.4026 |
| No log        | 3.0    | 18   | 0.3622          | 0.1837 | 0.3622 |
| No log        | 3.3333 | 20   | 0.3561          | 0.1837 | 0.3561 |
| No log        | 3.6667 | 22   | 0.3628          | 0.1837 | 0.3628 |
| No log        | 4.0    | 24   | 0.3773          | 0.1837 | 0.3773 |
| No log        | 4.3333 | 26   | 0.3744          | 0.1837 | 0.3744 |
| No log        | 4.6667 | 28   | 0.3673          | 0.1837 | 0.3673 |
| No log        | 5.0    | 30   | 0.3744          | 0.1837 | 0.3744 |
| No log        | 5.3333 | 32   | 0.3730          | 0.1837 | 0.3730 |
| No log        | 5.6667 | 34   | 0.3589          | 0.1333 | 0.3589 |
| No log        | 6.0    | 36   | 0.3503          | 0.3464 | 0.3503 |
| No log        | 6.3333 | 38   | 0.3556          | 0.2949 | 0.3556 |
| No log        | 6.6667 | 40   | 0.3713          | 0.2949 | 0.3713 |
| No log        | 7.0    | 42   | 0.3743          | 0.2949 | 0.3743 |
| No log        | 7.3333 | 44   | 0.3742          | 0.2949 | 0.3742 |
| No log        | 7.6667 | 46   | 0.3719          | 0.2949 | 0.3719 |
| No log        | 8.0    | 48   | 0.3699          | 0.2949 | 0.3699 |
| No log        | 8.3333 | 50   | 0.3712          | 0.2949 | 0.3712 |
| No log        | 8.6667 | 52   | 0.3661          | 0.2949 | 0.3661 |
| No log        | 9.0    | 54   | 0.3649          | 0.2157 | 0.3649 |
| No log        | 9.3333 | 56   | 0.3664          | 0.1333 | 0.3664 |
| No log        | 9.6667 | 58   | 0.3674          | 0.2157 | 0.3674 |
| No log        | 10.0   | 60   | 0.3678          | 0.2949 | 0.3678 |


### Framework versions

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