---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task5_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_task5_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: 0.7184
- Qwk: 0.5361
- Mse: 0.7182

## 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        | 0.0351 | 2    | 6.4993          | -0.0053 | 6.4959 |
| No log        | 0.0702 | 4    | 4.3274          | 0.0546  | 4.3230 |
| No log        | 0.1053 | 6    | 2.0332          | 0.1163  | 2.0309 |
| No log        | 0.1404 | 8    | 1.3322          | 0.1284  | 1.3306 |
| No log        | 0.1754 | 10   | 0.9326          | 0.2426  | 0.9313 |
| No log        | 0.2105 | 12   | 0.9842          | 0.2847  | 0.9820 |
| No log        | 0.2456 | 14   | 1.2941          | 0.2170  | 1.2916 |
| No log        | 0.2807 | 16   | 1.0180          | 0.3371  | 1.0161 |
| No log        | 0.3158 | 18   | 0.7295          | 0.4967  | 0.7284 |
| No log        | 0.3509 | 20   | 0.6802          | 0.5540  | 0.6795 |
| No log        | 0.3860 | 22   | 0.7502          | 0.5261  | 0.7494 |
| No log        | 0.4211 | 24   | 0.7871          | 0.5160  | 0.7862 |
| No log        | 0.4561 | 26   | 0.7535          | 0.5296  | 0.7529 |
| No log        | 0.4912 | 28   | 0.7088          | 0.5404  | 0.7085 |
| No log        | 0.5263 | 30   | 0.7579          | 0.4308  | 0.7577 |
| No log        | 0.5614 | 32   | 0.7816          | 0.4014  | 0.7814 |
| No log        | 0.5965 | 34   | 0.7506          | 0.4588  | 0.7504 |
| No log        | 0.6316 | 36   | 0.7024          | 0.5120  | 0.7022 |
| No log        | 0.6667 | 38   | 0.6632          | 0.5751  | 0.6631 |
| No log        | 0.7018 | 40   | 0.6681          | 0.5840  | 0.6681 |
| No log        | 0.7368 | 42   | 0.6746          | 0.5890  | 0.6745 |
| No log        | 0.7719 | 44   | 0.6782          | 0.5883  | 0.6781 |
| No log        | 0.8070 | 46   | 0.6889          | 0.5642  | 0.6887 |
| No log        | 0.8421 | 48   | 0.7117          | 0.5524  | 0.7115 |
| No log        | 0.8772 | 50   | 0.7291          | 0.5388  | 0.7288 |
| No log        | 0.9123 | 52   | 0.7256          | 0.5334  | 0.7253 |
| No log        | 0.9474 | 54   | 0.7224          | 0.5334  | 0.7222 |
| No log        | 0.9825 | 56   | 0.7184          | 0.5361  | 0.7182 |


### Framework versions

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