---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_fold2
  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_relevance_task1_fold2

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: 0.2831
- Qwk: 0.0
- Mse: 0.2831

## 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    | 1.7758          | 0.0     | 1.7758 |
| No log        | 0.0615 | 4    | 0.4260          | 0.0230  | 0.4260 |
| No log        | 0.0923 | 6    | 0.2683          | 0.0357  | 0.2683 |
| No log        | 0.1231 | 8    | 0.4228          | 0.1279  | 0.4228 |
| No log        | 0.1538 | 10   | 0.3603          | -0.0238 | 0.3603 |
| No log        | 0.1846 | 12   | 0.2737          | 0.0     | 0.2737 |
| No log        | 0.2154 | 14   | 0.2624          | 0.0     | 0.2624 |
| No log        | 0.2462 | 16   | 0.2619          | 0.0     | 0.2619 |
| No log        | 0.2769 | 18   | 0.2688          | 0.0     | 0.2688 |
| No log        | 0.3077 | 20   | 0.2704          | 0.0     | 0.2704 |
| No log        | 0.3385 | 22   | 0.2624          | 0.0     | 0.2624 |
| No log        | 0.3692 | 24   | 0.2623          | 0.0     | 0.2623 |
| No log        | 0.4    | 26   | 0.2679          | 0.0     | 0.2679 |
| No log        | 0.4308 | 28   | 0.2721          | 0.0     | 0.2721 |
| No log        | 0.4615 | 30   | 0.2703          | 0.0     | 0.2703 |
| No log        | 0.4923 | 32   | 0.2734          | 0.0     | 0.2734 |
| No log        | 0.5231 | 34   | 0.2751          | 0.0     | 0.2751 |
| No log        | 0.5538 | 36   | 0.2768          | 0.0     | 0.2768 |
| No log        | 0.5846 | 38   | 0.2791          | 0.0     | 0.2791 |
| No log        | 0.6154 | 40   | 0.2794          | 0.0     | 0.2794 |
| No log        | 0.6462 | 42   | 0.2773          | 0.0     | 0.2773 |
| No log        | 0.6769 | 44   | 0.2716          | 0.0     | 0.2716 |
| No log        | 0.7077 | 46   | 0.2703          | 0.0     | 0.2703 |
| No log        | 0.7385 | 48   | 0.2738          | 0.0     | 0.2738 |
| No log        | 0.7692 | 50   | 0.2740          | 0.0     | 0.2740 |
| No log        | 0.8    | 52   | 0.2800          | 0.0     | 0.2800 |
| No log        | 0.8308 | 54   | 0.2820          | 0.0     | 0.2820 |
| No log        | 0.8615 | 56   | 0.2816          | 0.0     | 0.2816 |
| No log        | 0.8923 | 58   | 0.2830          | 0.0     | 0.2830 |
| No log        | 0.9231 | 60   | 0.2845          | 0.0     | 0.2845 |
| No log        | 0.9538 | 62   | 0.2838          | 0.0     | 0.2838 |
| No log        | 0.9846 | 64   | 0.2831          | 0.0     | 0.2831 |


### Framework versions

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