---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task6_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_task6_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: 0.4868
- Qwk: 0.6478
- Mse: 0.4856

## 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        | 0.0308 | 2    | 2.1344          | 0.0845 | 2.1260 |
| No log        | 0.0615 | 4    | 1.0808          | 0.2961 | 1.0693 |
| No log        | 0.0923 | 6    | 1.3454          | 0.2890 | 1.3254 |
| No log        | 0.1231 | 8    | 0.6739          | 0.5314 | 0.6662 |
| No log        | 0.1538 | 10   | 0.5779          | 0.6649 | 0.5736 |
| No log        | 0.1846 | 12   | 0.5912          | 0.7569 | 0.5902 |
| No log        | 0.2154 | 14   | 0.5775          | 0.7630 | 0.5772 |
| No log        | 0.2462 | 16   | 0.5694          | 0.6622 | 0.5684 |
| No log        | 0.2769 | 18   | 0.7642          | 0.5844 | 0.7634 |
| No log        | 0.3077 | 20   | 1.2490          | 0.4005 | 1.2461 |
| No log        | 0.3385 | 22   | 1.2661          | 0.3780 | 1.2624 |
| No log        | 0.3692 | 24   | 0.8020          | 0.5334 | 0.8002 |
| No log        | 0.4    | 26   | 0.6377          | 0.6083 | 0.6361 |
| No log        | 0.4308 | 28   | 0.5794          | 0.6047 | 0.5774 |
| No log        | 0.4615 | 30   | 0.5299          | 0.6342 | 0.5280 |
| No log        | 0.4923 | 32   | 0.4877          | 0.6511 | 0.4861 |
| No log        | 0.5231 | 34   | 0.4827          | 0.6483 | 0.4810 |
| No log        | 0.5538 | 36   | 0.4477          | 0.7136 | 0.4467 |
| No log        | 0.5846 | 38   | 0.4513          | 0.6644 | 0.4498 |
| No log        | 0.6154 | 40   | 0.4864          | 0.6268 | 0.4842 |
| No log        | 0.6462 | 42   | 0.5576          | 0.5786 | 0.5544 |
| No log        | 0.6769 | 44   | 0.6809          | 0.4995 | 0.6764 |
| No log        | 0.7077 | 46   | 0.7399          | 0.4954 | 0.7349 |
| No log        | 0.7385 | 48   | 0.6881          | 0.4918 | 0.6838 |
| No log        | 0.7692 | 50   | 0.6232          | 0.5309 | 0.6197 |
| No log        | 0.8    | 52   | 0.5631          | 0.5592 | 0.5605 |
| No log        | 0.8308 | 54   | 0.5054          | 0.6188 | 0.5036 |
| No log        | 0.8615 | 56   | 0.4969          | 0.6158 | 0.4954 |
| No log        | 0.8923 | 58   | 0.4962          | 0.6158 | 0.4947 |
| No log        | 0.9231 | 60   | 0.4915          | 0.6233 | 0.4901 |
| No log        | 0.9538 | 62   | 0.4898          | 0.6318 | 0.4885 |
| No log        | 0.9846 | 64   | 0.4868          | 0.6478 | 0.4856 |


### Framework versions

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