---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task4_fold6
  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_task4_fold6

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: 0.3809
- Qwk: 0.7212
- Mse: 0.3803

## 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        | 0.0290 | 2    | 3.5915          | 0.0135 | 3.5774 |
| No log        | 0.0580 | 4    | 1.6728          | 0.1066 | 1.6543 |
| No log        | 0.0870 | 6    | 0.9207          | 0.3071 | 0.9146 |
| No log        | 0.1159 | 8    | 0.9451          | 0.4183 | 0.9392 |
| No log        | 0.1449 | 10   | 1.0092          | 0.4761 | 1.0019 |
| No log        | 0.1739 | 12   | 0.8467          | 0.4077 | 0.8353 |
| No log        | 0.2029 | 14   | 0.7589          | 0.4123 | 0.7471 |
| No log        | 0.2319 | 16   | 0.6332          | 0.4728 | 0.6243 |
| No log        | 0.2609 | 18   | 0.6097          | 0.5641 | 0.6051 |
| No log        | 0.2899 | 20   | 0.5389          | 0.5141 | 0.5354 |
| No log        | 0.3188 | 22   | 0.5073          | 0.5047 | 0.5034 |
| No log        | 0.3478 | 24   | 0.4996          | 0.5613 | 0.4954 |
| No log        | 0.3768 | 26   | 0.4724          | 0.5931 | 0.4689 |
| No log        | 0.4058 | 28   | 0.4067          | 0.6836 | 0.4044 |
| No log        | 0.4348 | 30   | 0.4385          | 0.8033 | 0.4374 |
| No log        | 0.4638 | 32   | 0.4624          | 0.8118 | 0.4616 |
| No log        | 0.4928 | 34   | 0.4385          | 0.7922 | 0.4378 |
| No log        | 0.5217 | 36   | 0.4184          | 0.6922 | 0.4169 |
| No log        | 0.5507 | 38   | 0.4874          | 0.6033 | 0.4851 |
| No log        | 0.5797 | 40   | 0.6206          | 0.5584 | 0.6172 |
| No log        | 0.6087 | 42   | 0.7056          | 0.5187 | 0.7018 |
| No log        | 0.6377 | 44   | 0.6335          | 0.5490 | 0.6305 |
| No log        | 0.6667 | 46   | 0.4625          | 0.6195 | 0.4610 |
| No log        | 0.6957 | 48   | 0.3971          | 0.7571 | 0.3968 |
| No log        | 0.7246 | 50   | 0.4158          | 0.7849 | 0.4158 |
| No log        | 0.7536 | 52   | 0.4127          | 0.7821 | 0.4127 |
| No log        | 0.7826 | 54   | 0.4163          | 0.7855 | 0.4162 |
| No log        | 0.8116 | 56   | 0.4055          | 0.7826 | 0.4053 |
| No log        | 0.8406 | 58   | 0.3891          | 0.7730 | 0.3888 |
| No log        | 0.8696 | 60   | 0.3833          | 0.7639 | 0.3829 |
| No log        | 0.8986 | 62   | 0.3800          | 0.7588 | 0.3795 |
| No log        | 0.9275 | 64   | 0.3788          | 0.7357 | 0.3783 |
| No log        | 0.9565 | 66   | 0.3800          | 0.7299 | 0.3795 |
| No log        | 0.9855 | 68   | 0.3809          | 0.7212 | 0.3803 |


### Framework versions

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