---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_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_task7_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: 0.4590
- Qwk: 0.6447
- Mse: 0.4579

## 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    | 2.4310          | 0.0444 | 2.4182 |
| No log        | 0.0656 | 4    | 1.0755          | 0.2942 | 1.0701 |
| No log        | 0.0984 | 6    | 1.4087          | 0.2913 | 1.3952 |
| No log        | 0.1311 | 8    | 1.4088          | 0.2931 | 1.3955 |
| No log        | 0.1639 | 10   | 0.6928          | 0.4909 | 0.6873 |
| No log        | 0.1967 | 12   | 0.5750          | 0.6609 | 0.5725 |
| No log        | 0.2295 | 14   | 0.5006          | 0.6728 | 0.4989 |
| No log        | 0.2623 | 16   | 0.4822          | 0.6065 | 0.4795 |
| No log        | 0.2951 | 18   | 0.6545          | 0.5276 | 0.6499 |
| No log        | 0.3279 | 20   | 1.0487          | 0.4061 | 1.0399 |
| No log        | 0.3607 | 22   | 1.1184          | 0.3952 | 1.1077 |
| No log        | 0.3934 | 24   | 1.0170          | 0.4299 | 1.0071 |
| No log        | 0.4262 | 26   | 0.5774          | 0.5919 | 0.5737 |
| No log        | 0.4590 | 28   | 0.4451          | 0.7458 | 0.4443 |
| No log        | 0.4918 | 30   | 0.4414          | 0.7776 | 0.4412 |
| No log        | 0.5246 | 32   | 0.4240          | 0.7423 | 0.4235 |
| No log        | 0.5574 | 34   | 0.4446          | 0.6969 | 0.4439 |
| No log        | 0.5902 | 36   | 0.6573          | 0.5608 | 0.6550 |
| No log        | 0.6230 | 38   | 0.7881          | 0.4856 | 0.7846 |
| No log        | 0.6557 | 40   | 0.7588          | 0.5118 | 0.7557 |
| No log        | 0.6885 | 42   | 0.6330          | 0.5988 | 0.6310 |
| No log        | 0.7213 | 44   | 0.5004          | 0.6314 | 0.4993 |
| No log        | 0.7541 | 46   | 0.4319          | 0.6887 | 0.4312 |
| No log        | 0.7869 | 48   | 0.4075          | 0.7028 | 0.4070 |
| No log        | 0.8197 | 50   | 0.4010          | 0.7041 | 0.4005 |
| No log        | 0.8525 | 52   | 0.3999          | 0.7089 | 0.3994 |
| No log        | 0.8852 | 54   | 0.4118          | 0.6952 | 0.4111 |
| No log        | 0.9180 | 56   | 0.4319          | 0.6733 | 0.4310 |
| No log        | 0.9508 | 58   | 0.4484          | 0.6528 | 0.4474 |
| No log        | 0.9836 | 60   | 0.4590          | 0.6447 | 0.4579 |


### Framework versions

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