---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_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_relevance_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: 0.2708
- Qwk: 0.2181
- Mse: 0.2714

## 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    | 0.3997          | 0.1409 | 0.4004 |
| No log        | 0.0615 | 4    | 0.3224          | 0.1635 | 0.3230 |
| No log        | 0.0923 | 6    | 0.3114          | 0.1336 | 0.3118 |
| No log        | 0.1231 | 8    | 0.2792          | 0.1434 | 0.2797 |
| No log        | 0.1538 | 10   | 0.5126          | 0.1528 | 0.5116 |
| No log        | 0.1846 | 12   | 0.5725          | 0.1322 | 0.5710 |
| No log        | 0.2154 | 14   | 0.3291          | 0.2313 | 0.3295 |
| No log        | 0.2462 | 16   | 0.2709          | 0.2220 | 0.2712 |
| No log        | 0.2769 | 18   | 0.2704          | 0.1746 | 0.2703 |
| No log        | 0.3077 | 20   | 0.2714          | 0.1858 | 0.2712 |
| No log        | 0.3385 | 22   | 0.2684          | 0.2083 | 0.2682 |
| No log        | 0.3692 | 24   | 0.2725          | 0.2135 | 0.2725 |
| No log        | 0.4    | 26   | 0.2759          | 0.2135 | 0.2760 |
| No log        | 0.4308 | 28   | 0.2785          | 0.2173 | 0.2789 |
| No log        | 0.4615 | 30   | 0.2798          | 0.1719 | 0.2803 |
| No log        | 0.4923 | 32   | 0.2835          | 0.1711 | 0.2841 |
| No log        | 0.5231 | 34   | 0.2859          | 0.1750 | 0.2866 |
| No log        | 0.5538 | 36   | 0.2843          | 0.1681 | 0.2850 |
| No log        | 0.5846 | 38   | 0.2824          | 0.1738 | 0.2833 |
| No log        | 0.6154 | 40   | 0.2828          | 0.2186 | 0.2837 |
| No log        | 0.6462 | 42   | 0.2811          | 0.2161 | 0.2821 |
| No log        | 0.6769 | 44   | 0.2826          | 0.2239 | 0.2836 |
| No log        | 0.7077 | 46   | 0.2875          | 0.2181 | 0.2884 |
| No log        | 0.7385 | 48   | 0.2931          | 0.2181 | 0.2940 |
| No log        | 0.7692 | 50   | 0.2938          | 0.2181 | 0.2947 |
| No log        | 0.8    | 52   | 0.2942          | 0.2266 | 0.2950 |
| No log        | 0.8308 | 54   | 0.2868          | 0.2266 | 0.2876 |
| No log        | 0.8615 | 56   | 0.2800          | 0.2224 | 0.2808 |
| No log        | 0.8923 | 58   | 0.2751          | 0.2181 | 0.2758 |
| No log        | 0.9231 | 60   | 0.2725          | 0.2181 | 0.2732 |
| No log        | 0.9538 | 62   | 0.2712          | 0.2181 | 0.2718 |
| No log        | 0.9846 | 64   | 0.2708          | 0.2181 | 0.2714 |


### Framework versions

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