---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task5_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_task5_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: 0.4885
- Qwk: 0.6405
- Mse: 0.4871

## 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    | 1.7653          | 0.0854 | 1.7539 |
| No log        | 0.0656 | 4    | 0.9960          | 0.2694 | 0.9869 |
| No log        | 0.0984 | 6    | 1.0209          | 0.4489 | 1.0210 |
| No log        | 0.1311 | 8    | 1.2656          | 0.2397 | 1.2659 |
| No log        | 0.1639 | 10   | 1.1746          | 0.1146 | 1.1733 |
| No log        | 0.1967 | 12   | 1.0616          | 0.1286 | 1.0603 |
| No log        | 0.2295 | 14   | 0.9704          | 0.1900 | 0.9690 |
| No log        | 0.2623 | 16   | 0.8921          | 0.2622 | 0.8910 |
| No log        | 0.2951 | 18   | 0.8267          | 0.4004 | 0.8262 |
| No log        | 0.3279 | 20   | 0.7715          | 0.4447 | 0.7714 |
| No log        | 0.3607 | 22   | 0.7094          | 0.4821 | 0.7095 |
| No log        | 0.3934 | 24   | 0.6609          | 0.5270 | 0.6611 |
| No log        | 0.4262 | 26   | 0.6404          | 0.5798 | 0.6403 |
| No log        | 0.4590 | 28   | 0.6536          | 0.6218 | 0.6535 |
| No log        | 0.4918 | 30   | 0.6622          | 0.6382 | 0.6618 |
| No log        | 0.5246 | 32   | 0.6200          | 0.6334 | 0.6191 |
| No log        | 0.5574 | 34   | 0.6047          | 0.6457 | 0.6038 |
| No log        | 0.5902 | 36   | 0.6135          | 0.6481 | 0.6127 |
| No log        | 0.6230 | 38   | 0.6735          | 0.6781 | 0.6730 |
| No log        | 0.6557 | 40   | 0.6993          | 0.6904 | 0.6989 |
| No log        | 0.6885 | 42   | 0.6637          | 0.6940 | 0.6631 |
| No log        | 0.7213 | 44   | 0.6006          | 0.7091 | 0.5995 |
| No log        | 0.7541 | 46   | 0.5531          | 0.7057 | 0.5517 |
| No log        | 0.7869 | 48   | 0.5246          | 0.6740 | 0.5231 |
| No log        | 0.8197 | 50   | 0.5072          | 0.6225 | 0.5054 |
| No log        | 0.8525 | 52   | 0.5048          | 0.5882 | 0.5030 |
| No log        | 0.8852 | 54   | 0.5019          | 0.5965 | 0.5002 |
| No log        | 0.9180 | 56   | 0.4958          | 0.6015 | 0.4942 |
| No log        | 0.9508 | 58   | 0.4908          | 0.6094 | 0.4893 |
| No log        | 0.9836 | 60   | 0.4885          | 0.6405 | 0.4871 |


### Framework versions

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