---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task1_fold1
  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_task1_fold1

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: 0.0669
- Qwk: 0.0233
- Mse: 0.0682

## 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    | 0.9611          | -0.0186 | 0.9691 |
| No log        | 0.6667 | 4    | 0.2075          | -0.0851 | 0.2124 |
| No log        | 1.0    | 6    | 0.1656          | 0.0207  | 0.1701 |
| No log        | 1.3333 | 8    | 0.1145          | 0.0392  | 0.1165 |
| No log        | 1.6667 | 10   | 0.1145          | 0.0165  | 0.1165 |
| No log        | 2.0    | 12   | 0.1921          | 0.0     | 0.1938 |
| No log        | 2.3333 | 14   | 0.2095          | 0.0     | 0.2110 |
| No log        | 2.6667 | 16   | 0.1634          | 0.0     | 0.1651 |
| No log        | 3.0    | 18   | 0.0995          | 0.0     | 0.1002 |
| No log        | 3.3333 | 20   | 0.1102          | 0.0050  | 0.1101 |
| No log        | 3.6667 | 22   | 0.1004          | 0.0165  | 0.1002 |
| No log        | 4.0    | 24   | 0.0724          | 0.0233  | 0.0728 |
| No log        | 4.3333 | 26   | 0.0523          | 0.0233  | 0.0531 |
| No log        | 4.6667 | 28   | 0.0574          | 0.0233  | 0.0583 |
| No log        | 5.0    | 30   | 0.0614          | 0.0233  | 0.0626 |
| No log        | 5.3333 | 32   | 0.0663          | 0.0233  | 0.0676 |
| No log        | 5.6667 | 34   | 0.0729          | 0.0233  | 0.0742 |
| No log        | 6.0    | 36   | 0.0631          | 0.0308  | 0.0641 |
| No log        | 6.3333 | 38   | 0.0561          | 0.0597  | 0.0563 |
| No log        | 6.6667 | 40   | 0.0579          | 0.0870  | 0.0579 |
| No log        | 7.0    | 42   | 0.0563          | 0.0597  | 0.0566 |
| No log        | 7.3333 | 44   | 0.0596          | 0.0308  | 0.0606 |
| No log        | 7.6667 | 46   | 0.0661          | 0.0308  | 0.0673 |
| No log        | 8.0    | 48   | 0.0735          | 0.0050  | 0.0747 |
| No log        | 8.3333 | 50   | 0.0721          | 0.0105  | 0.0733 |
| No log        | 8.6667 | 52   | 0.0679          | 0.0233  | 0.0690 |
| No log        | 9.0    | 54   | 0.0657          | 0.0233  | 0.0669 |
| No log        | 9.3333 | 56   | 0.0652          | 0.0233  | 0.0664 |
| No log        | 9.6667 | 58   | 0.0664          | 0.0233  | 0.0677 |
| No log        | 10.0   | 60   | 0.0669          | 0.0233  | 0.0682 |


### Framework versions

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