---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task7_fold3
  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_task7_fold3

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: 0.7581
- Qwk: 0.0
- Mse: 0.7581

## 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    | 7.8306          | -0.0005 | 7.8306 |
| No log        | 0.0615 | 4    | 4.1936          | 0.0     | 4.1936 |
| No log        | 0.0923 | 6    | 2.0851          | 0.0593  | 2.0851 |
| No log        | 0.1231 | 8    | 1.2404          | 0.0     | 1.2404 |
| No log        | 0.1538 | 10   | 0.8586          | 0.0093  | 0.8586 |
| No log        | 0.1846 | 12   | 0.7508          | 0.0707  | 0.7508 |
| No log        | 0.2154 | 14   | 0.7356          | 0.0372  | 0.7356 |
| No log        | 0.2462 | 16   | 0.8138          | 0.1082  | 0.8138 |
| No log        | 0.2769 | 18   | 0.9262          | -0.0080 | 0.9262 |
| No log        | 0.3077 | 20   | 0.8710          | -0.0045 | 0.8710 |
| No log        | 0.3385 | 22   | 0.7502          | -0.0408 | 0.7502 |
| No log        | 0.3692 | 24   | 0.7389          | 0.0     | 0.7389 |
| No log        | 0.4    | 26   | 0.7855          | 0.0     | 0.7855 |
| No log        | 0.4308 | 28   | 0.7754          | 0.0     | 0.7754 |
| No log        | 0.4615 | 30   | 0.7485          | 0.0     | 0.7485 |
| No log        | 0.4923 | 32   | 0.7451          | 0.0     | 0.7451 |
| No log        | 0.5231 | 34   | 0.7615          | 0.0     | 0.7615 |
| No log        | 0.5538 | 36   | 0.7804          | 0.0     | 0.7804 |
| No log        | 0.5846 | 38   | 0.7731          | 0.0     | 0.7731 |
| No log        | 0.6154 | 40   | 0.7812          | 0.0     | 0.7812 |
| No log        | 0.6462 | 42   | 0.8026          | 0.0     | 0.8026 |
| No log        | 0.6769 | 44   | 0.8454          | 0.0     | 0.8454 |
| No log        | 0.7077 | 46   | 0.8541          | 0.0     | 0.8541 |
| No log        | 0.7385 | 48   | 0.8250          | 0.0     | 0.8250 |
| No log        | 0.7692 | 50   | 0.8021          | 0.0     | 0.8021 |
| No log        | 0.8    | 52   | 0.7828          | 0.0     | 0.7828 |
| No log        | 0.8308 | 54   | 0.7701          | 0.0     | 0.7701 |
| No log        | 0.8615 | 56   | 0.7633          | 0.0     | 0.7633 |
| No log        | 0.8923 | 58   | 0.7561          | 0.0     | 0.7561 |
| No log        | 0.9231 | 60   | 0.7554          | 0.0     | 0.7554 |
| No log        | 0.9538 | 62   | 0.7563          | 0.0     | 0.7563 |
| No log        | 0.9846 | 64   | 0.7581          | 0.0     | 0.7581 |


### Framework versions

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