---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_fold4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_cross_vocabulary_task7_fold4

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: 0.9341
- Qwk: 0.8036
- Mse: 0.9341

## 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    | 3.7363          | 0.0136 | 3.7363 |
| No log        | 0.0702 | 4    | 2.3106          | 0.1619 | 2.3106 |
| No log        | 0.1053 | 6    | 1.8172          | 0.1692 | 1.8172 |
| No log        | 0.1404 | 8    | 1.6116          | 0.2787 | 1.6116 |
| No log        | 0.1754 | 10   | 1.8910          | 0.3258 | 1.8910 |
| No log        | 0.2105 | 12   | 1.8785          | 0.4430 | 1.8785 |
| No log        | 0.2456 | 14   | 1.8131          | 0.4299 | 1.8131 |
| No log        | 0.2807 | 16   | 2.0288          | 0.5063 | 2.0288 |
| No log        | 0.3158 | 18   | 1.6252          | 0.5783 | 1.6252 |
| No log        | 0.3509 | 20   | 1.4668          | 0.6465 | 1.4668 |
| No log        | 0.3860 | 22   | 1.1133          | 0.6929 | 1.1133 |
| No log        | 0.4211 | 24   | 0.8668          | 0.7249 | 0.8668 |
| No log        | 0.4561 | 26   | 0.9262          | 0.7457 | 0.9262 |
| No log        | 0.4912 | 28   | 1.0096          | 0.7462 | 1.0096 |
| No log        | 0.5263 | 30   | 1.0968          | 0.7380 | 1.0968 |
| No log        | 0.5614 | 32   | 1.1232          | 0.7473 | 1.1232 |
| No log        | 0.5965 | 34   | 1.1632          | 0.7453 | 1.1632 |
| No log        | 0.6316 | 36   | 1.1137          | 0.7662 | 1.1137 |
| No log        | 0.6667 | 38   | 1.0328          | 0.7794 | 1.0328 |
| No log        | 0.7018 | 40   | 0.8546          | 0.8110 | 0.8546 |
| No log        | 0.7368 | 42   | 0.7276          | 0.7840 | 0.7276 |
| No log        | 0.7719 | 44   | 0.6916          | 0.7793 | 0.6916 |
| No log        | 0.8070 | 46   | 0.7025          | 0.7855 | 0.7025 |
| No log        | 0.8421 | 48   | 0.7202          | 0.7971 | 0.7202 |
| No log        | 0.8772 | 50   | 0.7770          | 0.8095 | 0.7770 |
| No log        | 0.9123 | 52   | 0.8545          | 0.8154 | 0.8545 |
| No log        | 0.9474 | 54   | 0.9105          | 0.8088 | 0.9105 |
| No log        | 0.9825 | 56   | 0.9341          | 0.8036 | 0.9341 |


### Framework versions

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