---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_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_organization_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: 0.6156
- Qwk: 0.7263
- Mse: 0.5866

## 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    | 4.0016          | -0.0094 | 4.0420 |
| No log        | 0.6667 | 4    | 1.5678          | 0.0597  | 1.6106 |
| No log        | 1.0    | 6    | 1.1107          | 0.125   | 1.1443 |
| No log        | 1.3333 | 8    | 0.6987          | 0.2286  | 0.7156 |
| No log        | 1.6667 | 10   | 0.6381          | 0.4661  | 0.6469 |
| No log        | 2.0    | 12   | 0.5798          | 0.3984  | 0.5877 |
| No log        | 2.3333 | 14   | 0.4646          | 0.552   | 0.4642 |
| No log        | 2.6667 | 16   | 0.4683          | 0.6379  | 0.4526 |
| No log        | 3.0    | 18   | 0.4347          | 0.7154  | 0.4182 |
| No log        | 3.3333 | 20   | 0.4464          | 0.5977  | 0.4400 |
| No log        | 3.6667 | 22   | 0.4523          | 0.6957  | 0.4373 |
| No log        | 4.0    | 24   | 0.6917          | 0.7616  | 0.6664 |
| No log        | 4.3333 | 26   | 0.8197          | 0.7485  | 0.7888 |
| No log        | 4.6667 | 28   | 0.7131          | 0.7701  | 0.6829 |
| No log        | 5.0    | 30   | 0.7249          | 0.7154  | 0.6941 |
| No log        | 5.3333 | 32   | 0.8136          | 0.7572  | 0.7780 |
| No log        | 5.6667 | 34   | 0.9048          | 0.7347  | 0.8646 |
| No log        | 6.0    | 36   | 0.8073          | 0.7347  | 0.7664 |
| No log        | 6.3333 | 38   | 0.7257          | 0.7840  | 0.6853 |
| No log        | 6.6667 | 40   | 0.7345          | 0.7840  | 0.6936 |
| No log        | 7.0    | 42   | 0.7184          | 0.7263  | 0.6797 |
| No log        | 7.3333 | 44   | 0.6757          | 0.7263  | 0.6409 |
| No log        | 7.6667 | 46   | 0.7056          | 0.7042  | 0.6701 |
| No log        | 8.0    | 48   | 0.7177          | 0.7515  | 0.6822 |
| No log        | 8.3333 | 50   | 0.7076          | 0.7515  | 0.6730 |
| No log        | 8.6667 | 52   | 0.7003          | 0.7515  | 0.6663 |
| No log        | 9.0    | 54   | 0.6732          | 0.7515  | 0.6407 |
| No log        | 9.3333 | 56   | 0.6412          | 0.7042  | 0.6104 |
| No log        | 9.6667 | 58   | 0.6207          | 0.7263  | 0.5913 |
| No log        | 10.0   | 60   | 0.6156          | 0.7263  | 0.5866 |


### Framework versions

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