---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task5_fold4
  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_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: 0.5724
- Qwk: 0.8274
- Mse: 0.5724

## 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        | 0.0323 | 2    | 4.0786          | -0.0202 | 4.0786 |
| No log        | 0.0645 | 4    | 2.3283          | 0.0109  | 2.3283 |
| No log        | 0.0968 | 6    | 1.2785          | 0.2841  | 1.2785 |
| No log        | 0.1290 | 8    | 0.8433          | 0.4083  | 0.8433 |
| No log        | 0.1613 | 10   | 1.0059          | 0.5899  | 1.0059 |
| No log        | 0.1935 | 12   | 1.1298          | 0.6125  | 1.1298 |
| No log        | 0.2258 | 14   | 0.8824          | 0.7014  | 0.8824 |
| No log        | 0.2581 | 16   | 0.9194          | 0.7028  | 0.9194 |
| No log        | 0.2903 | 18   | 0.9116          | 0.7100  | 0.9116 |
| No log        | 0.3226 | 20   | 0.6668          | 0.7739  | 0.6668 |
| No log        | 0.3548 | 22   | 0.4256          | 0.7812  | 0.4256 |
| No log        | 0.3871 | 24   | 0.4050          | 0.7574  | 0.4050 |
| No log        | 0.4194 | 26   | 0.5814          | 0.7955  | 0.5814 |
| No log        | 0.4516 | 28   | 1.0279          | 0.7514  | 1.0279 |
| No log        | 0.4839 | 30   | 1.0452          | 0.7607  | 1.0452 |
| No log        | 0.5161 | 32   | 0.7165          | 0.8089  | 0.7165 |
| No log        | 0.5484 | 34   | 0.4458          | 0.7951  | 0.4458 |
| No log        | 0.5806 | 36   | 0.3735          | 0.7660  | 0.3735 |
| No log        | 0.6129 | 38   | 0.3982          | 0.7985  | 0.3982 |
| No log        | 0.6452 | 40   | 0.5173          | 0.8081  | 0.5173 |
| No log        | 0.6774 | 42   | 0.7723          | 0.7985  | 0.7723 |
| No log        | 0.7097 | 44   | 0.9254          | 0.7695  | 0.9254 |
| No log        | 0.7419 | 46   | 1.0677          | 0.7448  | 1.0677 |
| No log        | 0.7742 | 48   | 1.0524          | 0.7448  | 1.0524 |
| No log        | 0.8065 | 50   | 0.9408          | 0.7762  | 0.9408 |
| No log        | 0.8387 | 52   | 0.8100          | 0.7901  | 0.8100 |
| No log        | 0.8710 | 54   | 0.7061          | 0.8033  | 0.7061 |
| No log        | 0.9032 | 56   | 0.6220          | 0.8252  | 0.6220 |
| No log        | 0.9355 | 58   | 0.5830          | 0.8299  | 0.5830 |
| No log        | 0.9677 | 60   | 0.5721          | 0.8239  | 0.5721 |
| No log        | 1.0    | 62   | 0.5724          | 0.8274  | 0.5724 |


### Framework versions

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