---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_development_task5_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_development_task5_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: 0.5703
- Qwk: 0.7312
- Mse: 0.5703

## 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    | 2.7370          | -0.0412 | 2.7370 |
| No log        | 0.6667 | 4    | 1.1106          | 0.0254  | 1.1106 |
| No log        | 1.0    | 6    | 0.8018          | 0.3448  | 0.8018 |
| No log        | 1.3333 | 8    | 0.7112          | 0.4203  | 0.7112 |
| No log        | 1.6667 | 10   | 0.7153          | 0.2778  | 0.7153 |
| No log        | 2.0    | 12   | 0.6181          | 0.3333  | 0.6181 |
| No log        | 2.3333 | 14   | 0.5263          | 0.4379  | 0.5263 |
| No log        | 2.6667 | 16   | 0.5056          | 0.4444  | 0.5056 |
| No log        | 3.0    | 18   | 0.4721          | 0.4318  | 0.4721 |
| No log        | 3.3333 | 20   | 0.4560          | 0.5251  | 0.4560 |
| No log        | 3.6667 | 22   | 0.4550          | 0.5506  | 0.4550 |
| No log        | 4.0    | 24   | 0.5190          | 0.7399  | 0.5190 |
| No log        | 4.3333 | 26   | 0.5822          | 0.7568  | 0.5822 |
| No log        | 4.6667 | 28   | 0.5363          | 0.6328  | 0.5363 |
| No log        | 5.0    | 30   | 0.5203          | 0.4382  | 0.5203 |
| No log        | 5.3333 | 32   | 0.5859          | 0.4388  | 0.5859 |
| No log        | 5.6667 | 34   | 0.5248          | 0.3956  | 0.5248 |
| No log        | 6.0    | 36   | 0.5042          | 0.5977  | 0.5042 |
| No log        | 6.3333 | 38   | 0.5446          | 0.6667  | 0.5446 |
| No log        | 6.6667 | 40   | 0.5984          | 0.7312  | 0.5984 |
| No log        | 7.0    | 42   | 0.6002          | 0.7312  | 0.6002 |
| No log        | 7.3333 | 44   | 0.5662          | 0.7312  | 0.5662 |
| No log        | 7.6667 | 46   | 0.5376          | 0.6667  | 0.5376 |
| No log        | 8.0    | 48   | 0.5417          | 0.6667  | 0.5417 |
| No log        | 8.3333 | 50   | 0.5612          | 0.7312  | 0.5612 |
| No log        | 8.6667 | 52   | 0.5739          | 0.7312  | 0.5739 |
| No log        | 9.0    | 54   | 0.5740          | 0.7312  | 0.5740 |
| No log        | 9.3333 | 56   | 0.5707          | 0.7312  | 0.5707 |
| No log        | 9.6667 | 58   | 0.5714          | 0.7312  | 0.5714 |
| No log        | 10.0   | 60   | 0.5703          | 0.7312  | 0.5703 |


### Framework versions

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