---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_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_vocabulary_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: 0.4495
- Qwk: 0.5070
- Mse: 0.4537

## 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    | 6.1233          | -0.0049 | 6.0762 |
| No log        | 0.6667 | 4    | 2.5238          | 0.0438  | 2.5221 |
| No log        | 1.0    | 6    | 1.6945          | 0.0677  | 1.7016 |
| No log        | 1.3333 | 8    | 0.6878          | 0.2489  | 0.6921 |
| No log        | 1.6667 | 10   | 0.5146          | 0.2759  | 0.5204 |
| No log        | 2.0    | 12   | 0.6279          | 0.2036  | 0.6327 |
| No log        | 2.3333 | 14   | 1.1313          | 0.0888  | 1.1412 |
| No log        | 2.6667 | 16   | 0.8112          | 0.1508  | 0.8178 |
| No log        | 3.0    | 18   | 0.5968          | 0.3475  | 0.6025 |
| No log        | 3.3333 | 20   | 0.5587          | 0.3475  | 0.5649 |
| No log        | 3.6667 | 22   | 0.3908          | 0.4828  | 0.3937 |
| No log        | 4.0    | 24   | 0.3808          | 0.4828  | 0.3836 |
| No log        | 4.3333 | 26   | 0.5135          | 0.4190  | 0.5196 |
| No log        | 4.6667 | 28   | 0.7114          | 0.2825  | 0.7220 |
| No log        | 5.0    | 30   | 0.6755          | 0.3456  | 0.6851 |
| No log        | 5.3333 | 32   | 0.4917          | 0.5259  | 0.4969 |
| No log        | 5.6667 | 34   | 0.4653          | 0.5679  | 0.4693 |
| No log        | 6.0    | 36   | 0.4650          | 0.5917  | 0.4695 |
| No log        | 6.3333 | 38   | 0.4511          | 0.5817  | 0.4552 |
| No log        | 6.6667 | 40   | 0.4643          | 0.4296  | 0.4687 |
| No log        | 7.0    | 42   | 0.4888          | 0.3970  | 0.4933 |
| No log        | 7.3333 | 44   | 0.4987          | 0.3970  | 0.5033 |
| No log        | 7.6667 | 46   | 0.4509          | 0.5191  | 0.4546 |
| No log        | 8.0    | 48   | 0.3997          | 0.5917  | 0.4021 |
| No log        | 8.3333 | 50   | 0.4026          | 0.5917  | 0.4048 |
| No log        | 8.6667 | 52   | 0.4048          | 0.5817  | 0.4074 |
| No log        | 9.0    | 54   | 0.4217          | 0.5366  | 0.4250 |
| No log        | 9.3333 | 56   | 0.4348          | 0.5366  | 0.4386 |
| No log        | 9.6667 | 58   | 0.4485          | 0.5070  | 0.4527 |
| No log        | 10.0   | 60   | 0.4495          | 0.5070  | 0.4537 |


### Framework versions

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