---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_task1_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_vocabulary_task1_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: 0.6498
- Qwk: 0.6216
- Mse: 0.6722

## 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    | 4.6252          | -0.0554 | 4.6618 |
| No log        | 0.6667 | 4    | 1.9114          | 0.1179  | 1.9451 |
| No log        | 1.0    | 6    | 0.9690          | 0.1617  | 1.0110 |
| No log        | 1.3333 | 8    | 0.8689          | 0.3771  | 0.9143 |
| No log        | 1.6667 | 10   | 0.7767          | 0.3636  | 0.8305 |
| No log        | 2.0    | 12   | 0.7835          | 0.3652  | 0.8429 |
| No log        | 2.3333 | 14   | 0.7429          | 0.5097  | 0.7956 |
| No log        | 2.6667 | 16   | 0.7735          | 0.4543  | 0.8152 |
| No log        | 3.0    | 18   | 0.8347          | 0.4231  | 0.8732 |
| No log        | 3.3333 | 20   | 0.7428          | 0.4755  | 0.7774 |
| No log        | 3.6667 | 22   | 0.7764          | 0.5241  | 0.8145 |
| No log        | 4.0    | 24   | 0.7551          | 0.5241  | 0.7880 |
| No log        | 4.3333 | 26   | 0.7760          | 0.4815  | 0.8052 |
| No log        | 4.6667 | 28   | 0.8464          | 0.4103  | 0.8794 |
| No log        | 5.0    | 30   | 0.7218          | 0.5290  | 0.7519 |
| No log        | 5.3333 | 32   | 0.7204          | 0.5241  | 0.7555 |
| No log        | 5.6667 | 34   | 0.7510          | 0.5634  | 0.7913 |
| No log        | 6.0    | 36   | 0.6866          | 0.5634  | 0.7239 |
| No log        | 6.3333 | 38   | 0.6265          | 0.5592  | 0.6598 |
| No log        | 6.6667 | 40   | 0.6769          | 0.5913  | 0.7100 |
| No log        | 7.0    | 42   | 0.6960          | 0.5913  | 0.7277 |
| No log        | 7.3333 | 44   | 0.6638          | 0.5913  | 0.6914 |
| No log        | 7.6667 | 46   | 0.6521          | 0.5987  | 0.6776 |
| No log        | 8.0    | 48   | 0.6739          | 0.6369  | 0.6999 |
| No log        | 8.3333 | 50   | 0.6666          | 0.6369  | 0.6916 |
| No log        | 8.6667 | 52   | 0.6558          | 0.6655  | 0.6793 |
| No log        | 9.0    | 54   | 0.6498          | 0.6216  | 0.6729 |
| No log        | 9.3333 | 56   | 0.6487          | 0.6216  | 0.6712 |
| No log        | 9.6667 | 58   | 0.6495          | 0.6216  | 0.6718 |
| No log        | 10.0   | 60   | 0.6498          | 0.6216  | 0.6722 |


### Framework versions

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