---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task3_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_cross_vocabulary_task3_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: 0.6808
- Qwk: 0.5680
- Mse: 0.6804

## 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        | 0.0323 | 2    | 4.4744          | -0.0256 | 4.4706 |
| No log        | 0.0645 | 4    | 2.3045          | 0.0249  | 2.3004 |
| No log        | 0.0968 | 6    | 1.2805          | 0.1391  | 1.2779 |
| No log        | 0.1290 | 8    | 1.0125          | 0.1335  | 1.0109 |
| No log        | 0.1613 | 10   | 1.0701          | 0.1914  | 1.0686 |
| No log        | 0.1935 | 12   | 1.2785          | 0.2037  | 1.2768 |
| No log        | 0.2258 | 14   | 1.2274          | 0.2479  | 1.2257 |
| No log        | 0.2581 | 16   | 1.0548          | 0.3135  | 1.0534 |
| No log        | 0.2903 | 18   | 0.9068          | 0.4200  | 0.9058 |
| No log        | 0.3226 | 20   | 0.8042          | 0.4719  | 0.8035 |
| No log        | 0.3548 | 22   | 0.7409          | 0.5318  | 0.7404 |
| No log        | 0.3871 | 24   | 0.7832          | 0.5356  | 0.7827 |
| No log        | 0.4194 | 26   | 0.8927          | 0.5031  | 0.8924 |
| No log        | 0.4516 | 28   | 1.1506          | 0.4441  | 1.1505 |
| No log        | 0.4839 | 30   | 1.4202          | 0.3909  | 1.4201 |
| No log        | 0.5161 | 32   | 1.1610          | 0.4441  | 1.1608 |
| No log        | 0.5484 | 34   | 0.8093          | 0.5444  | 0.8088 |
| No log        | 0.5806 | 36   | 0.6806          | 0.5981  | 0.6803 |
| No log        | 0.6129 | 38   | 0.6480          | 0.5752  | 0.6477 |
| No log        | 0.6452 | 40   | 0.6549          | 0.5691  | 0.6546 |
| No log        | 0.6774 | 42   | 0.7025          | 0.5317  | 0.7021 |
| No log        | 0.7097 | 44   | 0.7321          | 0.5105  | 0.7317 |
| No log        | 0.7419 | 46   | 0.7334          | 0.5066  | 0.7330 |
| No log        | 0.7742 | 48   | 0.7273          | 0.5221  | 0.7269 |
| No log        | 0.8065 | 50   | 0.7075          | 0.5309  | 0.7071 |
| No log        | 0.8387 | 52   | 0.6855          | 0.5374  | 0.6852 |
| No log        | 0.8710 | 54   | 0.6736          | 0.5635  | 0.6733 |
| No log        | 0.9032 | 56   | 0.6784          | 0.5680  | 0.6781 |
| No log        | 0.9355 | 58   | 0.6858          | 0.5657  | 0.6855 |
| No log        | 0.9677 | 60   | 0.6828          | 0.5669  | 0.6825 |
| No log        | 1.0    | 62   | 0.6808          | 0.5680  | 0.6804 |


### Framework versions

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