---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_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_vocabulary_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: 0.5505
- Qwk: 0.6767
- Mse: 0.5505

## 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    | 3.3545          | 0.0255 | 3.3545 |
| No log        | 0.6667 | 4    | 1.6087          | 0.0    | 1.6087 |
| No log        | 1.0    | 6    | 0.8536          | 0.2689 | 0.8536 |
| No log        | 1.3333 | 8    | 0.7544          | 0.2289 | 0.7544 |
| No log        | 1.6667 | 10   | 0.6504          | 0.2689 | 0.6504 |
| No log        | 2.0    | 12   | 0.5598          | 0.3623 | 0.5598 |
| No log        | 2.3333 | 14   | 0.5291          | 0.3623 | 0.5291 |
| No log        | 2.6667 | 16   | 0.6356          | 0.4179 | 0.6356 |
| No log        | 3.0    | 18   | 0.8795          | 0.2857 | 0.8795 |
| No log        | 3.3333 | 20   | 0.7838          | 0.4434 | 0.7838 |
| No log        | 3.6667 | 22   | 0.5344          | 0.6809 | 0.5344 |
| No log        | 4.0    | 24   | 0.5107          | 0.6822 | 0.5107 |
| No log        | 4.3333 | 26   | 0.5455          | 0.6822 | 0.5455 |
| No log        | 4.6667 | 28   | 0.5959          | 0.6822 | 0.5959 |
| No log        | 5.0    | 30   | 0.6155          | 0.6091 | 0.6155 |
| No log        | 5.3333 | 32   | 0.5993          | 0.6146 | 0.5993 |
| No log        | 5.6667 | 34   | 0.6037          | 0.7028 | 0.6037 |
| No log        | 6.0    | 36   | 0.6613          | 0.6767 | 0.6613 |
| No log        | 6.3333 | 38   | 0.6632          | 0.7005 | 0.6632 |
| No log        | 6.6667 | 40   | 0.6185          | 0.6822 | 0.6185 |
| No log        | 7.0    | 42   | 0.5683          | 0.7028 | 0.5683 |
| No log        | 7.3333 | 44   | 0.5821          | 0.6040 | 0.5821 |
| No log        | 7.6667 | 46   | 0.5844          | 0.6040 | 0.5844 |
| No log        | 8.0    | 48   | 0.5500          | 0.6844 | 0.5500 |
| No log        | 8.3333 | 50   | 0.5326          | 0.7028 | 0.5326 |
| No log        | 8.6667 | 52   | 0.5428          | 0.6767 | 0.5428 |
| No log        | 9.0    | 54   | 0.5510          | 0.6767 | 0.5510 |
| No log        | 9.3333 | 56   | 0.5525          | 0.6767 | 0.5525 |
| No log        | 9.6667 | 58   | 0.5510          | 0.6767 | 0.5510 |
| No log        | 10.0   | 60   | 0.5505          | 0.6767 | 0.5505 |


### Framework versions

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