---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_fold1
  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_fold1

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: 0.3646
- Qwk: 0.0454
- Mse: 0.3647

## 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        | 0.0323 | 2    | 0.3884          | -0.0193 | 0.3901 |
| No log        | 0.0645 | 4    | 0.5676          | 0.0570  | 0.5677 |
| No log        | 0.0968 | 6    | 0.6160          | 0.1181  | 0.6161 |
| No log        | 0.1290 | 8    | 0.3914          | 0.0326  | 0.3913 |
| No log        | 0.1613 | 10   | 0.2970          | 0.0245  | 0.2972 |
| No log        | 0.1935 | 12   | 0.3016          | 0.0122  | 0.3018 |
| No log        | 0.2258 | 14   | 0.2905          | 0.0122  | 0.2908 |
| No log        | 0.2581 | 16   | 0.3013          | 0.0491  | 0.3016 |
| No log        | 0.2903 | 18   | 0.3427          | 0.0284  | 0.3429 |
| No log        | 0.3226 | 20   | 0.4170          | 0.0059  | 0.4170 |
| No log        | 0.3548 | 22   | 0.4971          | 0.0518  | 0.4971 |
| No log        | 0.3871 | 24   | 0.4934          | 0.0958  | 0.4933 |
| No log        | 0.4194 | 26   | 0.4203          | -0.0430 | 0.4203 |
| No log        | 0.4516 | 28   | 0.3668          | -0.0521 | 0.3669 |
| No log        | 0.4839 | 30   | 0.3462          | -0.0092 | 0.3463 |
| No log        | 0.5161 | 32   | 0.3500          | -0.0092 | 0.3500 |
| No log        | 0.5484 | 34   | 0.3623          | -0.0010 | 0.3623 |
| No log        | 0.5806 | 36   | 0.3911          | -0.0188 | 0.3911 |
| No log        | 0.6129 | 38   | 0.3635          | -0.0135 | 0.3634 |
| No log        | 0.6452 | 40   | 0.3500          | -0.0092 | 0.3500 |
| No log        | 0.6774 | 42   | 0.3369          | -0.0048 | 0.3369 |
| No log        | 0.7097 | 44   | 0.3357          | -0.0048 | 0.3358 |
| No log        | 0.7419 | 46   | 0.3574          | 0.0537  | 0.3574 |
| No log        | 0.7742 | 48   | 0.3901          | 0.0370  | 0.3901 |
| No log        | 0.8065 | 50   | 0.3986          | 0.0723  | 0.3985 |
| No log        | 0.8387 | 52   | 0.3875          | 0.0544  | 0.3875 |
| No log        | 0.8710 | 54   | 0.3792          | 0.0586  | 0.3792 |
| No log        | 0.9032 | 56   | 0.3727          | 0.0412  | 0.3727 |
| No log        | 0.9355 | 58   | 0.3667          | 0.0454  | 0.3667 |
| No log        | 0.9677 | 60   | 0.3648          | 0.0454  | 0.3648 |
| No log        | 1.0    | 62   | 0.3646          | 0.0454  | 0.3647 |


### Framework versions

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