---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task6_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_task6_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: 0.6146
- Qwk: 0.4250
- Mse: 0.6146

## 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        | 0.0328 | 2    | 3.4679          | 0.0168 | 3.4679 |
| No log        | 0.0656 | 4    | 1.6537          | 0.0514 | 1.6537 |
| No log        | 0.0984 | 6    | 1.1313          | 0.1099 | 1.1313 |
| No log        | 0.1311 | 8    | 0.9535          | 0.1805 | 0.9535 |
| No log        | 0.1639 | 10   | 1.0794          | 0.3174 | 1.0794 |
| No log        | 0.1967 | 12   | 0.6168          | 0.4395 | 0.6168 |
| No log        | 0.2295 | 14   | 0.6033          | 0.4645 | 0.6033 |
| No log        | 0.2623 | 16   | 0.6737          | 0.4499 | 0.6737 |
| No log        | 0.2951 | 18   | 1.0668          | 0.3641 | 1.0668 |
| No log        | 0.3279 | 20   | 1.3034          | 0.3203 | 1.3034 |
| No log        | 0.3607 | 22   | 1.0248          | 0.3778 | 1.0248 |
| No log        | 0.3934 | 24   | 0.6797          | 0.4447 | 0.6797 |
| No log        | 0.4262 | 26   | 0.6365          | 0.4647 | 0.6365 |
| No log        | 0.4590 | 28   | 0.7543          | 0.4079 | 0.7543 |
| No log        | 0.4918 | 30   | 1.0103          | 0.3524 | 1.0103 |
| No log        | 0.5246 | 32   | 0.8599          | 0.3860 | 0.8599 |
| No log        | 0.5574 | 34   | 0.6772          | 0.4252 | 0.6772 |
| No log        | 0.5902 | 36   | 0.5781          | 0.4282 | 0.5781 |
| No log        | 0.6230 | 38   | 0.5748          | 0.4282 | 0.5748 |
| No log        | 0.6557 | 40   | 0.6074          | 0.4195 | 0.6074 |
| No log        | 0.6885 | 42   | 0.6402          | 0.3992 | 0.6402 |
| No log        | 0.7213 | 44   | 0.7139          | 0.3932 | 0.7139 |
| No log        | 0.7541 | 46   | 0.7877          | 0.3858 | 0.7877 |
| No log        | 0.7869 | 48   | 0.7654          | 0.3896 | 0.7654 |
| No log        | 0.8197 | 50   | 0.6949          | 0.4032 | 0.6949 |
| No log        | 0.8525 | 52   | 0.6439          | 0.4209 | 0.6439 |
| No log        | 0.8852 | 54   | 0.6372          | 0.4216 | 0.6372 |
| No log        | 0.9180 | 56   | 0.6231          | 0.4191 | 0.6231 |
| No log        | 0.9508 | 58   | 0.6184          | 0.4250 | 0.6184 |
| No log        | 0.9836 | 60   | 0.6146          | 0.4250 | 0.6146 |


### Framework versions

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