---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task3_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_cross_vocabulary_task3_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: 0.5285
- Qwk: 0.4405
- Mse: 0.5285

## 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: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Qwk     | Mse    |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
| No log        | 0.0317 | 2    | 8.4052          | 0.0     | 8.4052 |
| No log        | 0.0635 | 4    | 5.1861          | -0.0063 | 5.1861 |
| No log        | 0.0952 | 6    | 2.9254          | 0.0185  | 2.9254 |
| No log        | 0.1270 | 8    | 1.8370          | 0.0864  | 1.8370 |
| No log        | 0.1587 | 10   | 1.1161          | 0.0869  | 1.1161 |
| No log        | 0.1905 | 12   | 0.8855          | 0.1061  | 0.8855 |
| No log        | 0.2222 | 14   | 1.2541          | 0.1523  | 1.2541 |
| No log        | 0.2540 | 16   | 1.9970          | 0.1566  | 1.9970 |
| No log        | 0.2857 | 18   | 1.0435          | 0.2378  | 1.0435 |
| No log        | 0.3175 | 20   | 0.6890          | 0.3618  | 0.6890 |
| No log        | 0.3492 | 22   | 0.5804          | 0.4399  | 0.5804 |
| No log        | 0.3810 | 24   | 0.5528          | 0.4709  | 0.5528 |
| No log        | 0.4127 | 26   | 0.5886          | 0.4445  | 0.5886 |
| No log        | 0.4444 | 28   | 0.8824          | 0.37    | 0.8824 |
| No log        | 0.4762 | 30   | 0.8947          | 0.3615  | 0.8947 |
| No log        | 0.5079 | 32   | 0.6729          | 0.4052  | 0.6729 |
| No log        | 0.5397 | 34   | 0.5355          | 0.4536  | 0.5355 |
| No log        | 0.5714 | 36   | 0.4786          | 0.4846  | 0.4786 |
| No log        | 0.6032 | 38   | 0.4704          | 0.4846  | 0.4704 |
| No log        | 0.6349 | 40   | 0.4945          | 0.4637  | 0.4945 |
| No log        | 0.6667 | 42   | 0.6100          | 0.4202  | 0.6100 |
| No log        | 0.6984 | 44   | 0.6733          | 0.3645  | 0.6733 |
| No log        | 0.7302 | 46   | 0.6704          | 0.3694  | 0.6704 |
| No log        | 0.7619 | 48   | 0.6390          | 0.3820  | 0.6390 |
| No log        | 0.7937 | 50   | 0.5726          | 0.4157  | 0.5726 |
| No log        | 0.8254 | 52   | 0.5435          | 0.4449  | 0.5435 |
| No log        | 0.8571 | 54   | 0.5097          | 0.4543  | 0.5097 |
| No log        | 0.8889 | 56   | 0.5010          | 0.4503  | 0.5010 |
| No log        | 0.9206 | 58   | 0.5122          | 0.4418  | 0.5122 |
| No log        | 0.9524 | 60   | 0.5275          | 0.4351  | 0.5275 |
| No log        | 0.9841 | 62   | 0.5285          | 0.4405  | 0.5285 |


### Framework versions

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