---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_task2_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_vocabulary_task2_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: 0.5031
- Qwk: 0.5714
- Mse: 0.5016

## 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    | 4.1484          | 0.0038 | 4.1936 |
| No log        | 0.6667 | 4    | 1.4862          | 0.0810 | 1.5068 |
| No log        | 1.0    | 6    | 0.7072          | 0.0    | 0.7085 |
| No log        | 1.3333 | 8    | 0.5919          | 0.0    | 0.5727 |
| No log        | 1.6667 | 10   | 0.7019          | 0.0    | 0.6799 |
| No log        | 2.0    | 12   | 0.4359          | 0.2329 | 0.4303 |
| No log        | 2.3333 | 14   | 0.4598          | 0.1250 | 0.4561 |
| No log        | 2.6667 | 16   | 0.4071          | 0.5145 | 0.3971 |
| No log        | 3.0    | 18   | 0.5588          | 0.1732 | 0.5418 |
| No log        | 3.3333 | 20   | 0.6199          | 0.1732 | 0.6015 |
| No log        | 3.6667 | 22   | 0.4817          | 0.4400 | 0.4688 |
| No log        | 4.0    | 24   | 0.3891          | 0.2959 | 0.3830 |
| No log        | 4.3333 | 26   | 0.4411          | 0.1777 | 0.4351 |
| No log        | 4.6667 | 28   | 0.4012          | 0.3959 | 0.3959 |
| No log        | 5.0    | 30   | 0.4347          | 0.4765 | 0.4291 |
| No log        | 5.3333 | 32   | 0.6742          | 0.4970 | 0.6581 |
| No log        | 5.6667 | 34   | 0.7767          | 0.5273 | 0.7561 |
| No log        | 6.0    | 36   | 0.7418          | 0.5836 | 0.7250 |
| No log        | 6.3333 | 38   | 0.6070          | 0.4706 | 0.5993 |
| No log        | 6.6667 | 40   | 0.4832          | 0.5714 | 0.4805 |
| No log        | 7.0    | 42   | 0.4590          | 0.6196 | 0.4554 |
| No log        | 7.3333 | 44   | 0.4604          | 0.6196 | 0.4573 |
| No log        | 7.6667 | 46   | 0.4911          | 0.5714 | 0.4888 |
| No log        | 8.0    | 48   | 0.5594          | 0.4415 | 0.5549 |
| No log        | 8.3333 | 50   | 0.5973          | 0.5215 | 0.5910 |
| No log        | 8.6667 | 52   | 0.5945          | 0.4415 | 0.5886 |
| No log        | 9.0    | 54   | 0.5659          | 0.4415 | 0.5617 |
| No log        | 9.3333 | 56   | 0.5343          | 0.5215 | 0.5317 |
| No log        | 9.6667 | 58   | 0.5134          | 0.4976 | 0.5116 |
| No log        | 10.0   | 60   | 0.5031          | 0.5714 | 0.5016 |


### Framework versions

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