---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task5_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_task5_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: 0.3506
- Qwk: -0.0164
- Mse: 0.3512

## 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        | 0.0317 | 2    | 0.4906          | -0.0037 | 0.4920 |
| No log        | 0.0635 | 4    | 0.3371          | -0.0172 | 0.3371 |
| No log        | 0.0952 | 6    | 0.3335          | -0.0128 | 0.3335 |
| No log        | 0.1270 | 8    | 0.2836          | 0.0122  | 0.2837 |
| No log        | 0.1587 | 10   | 0.3153          | 0.0     | 0.3156 |
| No log        | 0.1905 | 12   | 0.2834          | 0.0     | 0.2838 |
| No log        | 0.2222 | 14   | 0.2992          | 0.0     | 0.2996 |
| No log        | 0.2540 | 16   | 0.3898          | 0.0454  | 0.3898 |
| No log        | 0.2857 | 18   | 0.4736          | 0.0608  | 0.4735 |
| No log        | 0.3175 | 20   | 0.4950          | -0.0251 | 0.4949 |
| No log        | 0.3492 | 22   | 0.4696          | -0.0281 | 0.4697 |
| No log        | 0.3810 | 24   | 0.4030          | -0.0521 | 0.4033 |
| No log        | 0.4127 | 26   | 0.3436          | 0.0122  | 0.3443 |
| No log        | 0.4444 | 28   | 0.3297          | 0.0122  | 0.3305 |
| No log        | 0.4762 | 30   | 0.3336          | 0.0122  | 0.3344 |
| No log        | 0.5079 | 32   | 0.3536          | 0.0122  | 0.3541 |
| No log        | 0.5397 | 34   | 0.3706          | -0.0042 | 0.3710 |
| No log        | 0.5714 | 36   | 0.3495          | 0.0     | 0.3500 |
| No log        | 0.6032 | 38   | 0.3317          | 0.0     | 0.3323 |
| No log        | 0.6349 | 40   | 0.3188          | 0.0     | 0.3196 |
| No log        | 0.6667 | 42   | 0.3182          | 0.0     | 0.3190 |
| No log        | 0.6984 | 44   | 0.3248          | 0.0     | 0.3256 |
| No log        | 0.7302 | 46   | 0.3286          | 0.0     | 0.3294 |
| No log        | 0.7619 | 48   | 0.3328          | -0.0164 | 0.3336 |
| No log        | 0.7937 | 50   | 0.3347          | -0.0164 | 0.3354 |
| No log        | 0.8254 | 52   | 0.3404          | -0.0164 | 0.3411 |
| No log        | 0.8571 | 54   | 0.3437          | -0.0164 | 0.3444 |
| No log        | 0.8889 | 56   | 0.3441          | -0.0164 | 0.3448 |
| No log        | 0.9206 | 58   | 0.3444          | -0.0164 | 0.3450 |
| No log        | 0.9524 | 60   | 0.3482          | -0.0164 | 0.3488 |
| No log        | 0.9841 | 62   | 0.3506          | -0.0164 | 0.3512 |


### Framework versions

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