---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task8_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_baseline_relevance_task8_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: 0.2901
- Qwk: 0.4096
- Mse: 0.2901

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Qwk     | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| No log        | 0.5   | 2    | 0.6071          | -0.1667 | 0.6071 |
| No log        | 1.0   | 4    | 0.6292          | -0.0548 | 0.6292 |
| No log        | 1.5   | 6    | 0.5112          | 0.3467  | 0.5112 |
| No log        | 2.0   | 8    | 0.2941          | 0.2000  | 0.2941 |
| No log        | 2.5   | 10   | 0.2595          | 0.3171  | 0.2595 |
| No log        | 3.0   | 12   | 0.3011          | 0.3171  | 0.3011 |
| No log        | 3.5   | 14   | 0.2934          | 0.3171  | 0.2934 |
| No log        | 4.0   | 16   | 0.2489          | 0.3171  | 0.2489 |
| No log        | 4.5   | 18   | 0.2716          | 0.4096  | 0.2716 |
| No log        | 5.0   | 20   | 0.3200          | 0.3099  | 0.3200 |
| No log        | 5.5   | 22   | 0.3416          | 0.2000  | 0.3416 |
| No log        | 6.0   | 24   | 0.3237          | 0.4096  | 0.3237 |
| No log        | 6.5   | 26   | 0.2949          | 0.4096  | 0.2949 |
| No log        | 7.0   | 28   | 0.2821          | 0.4096  | 0.2821 |
| No log        | 7.5   | 30   | 0.2766          | 0.4096  | 0.2766 |
| No log        | 8.0   | 32   | 0.2780          | 0.4096  | 0.2780 |
| No log        | 8.5   | 34   | 0.2807          | 0.4096  | 0.2807 |
| No log        | 9.0   | 36   | 0.2841          | 0.4096  | 0.2841 |
| No log        | 9.5   | 38   | 0.2889          | 0.4096  | 0.2889 |
| No log        | 10.0  | 40   | 0.2901          | 0.4096  | 0.2901 |


### Framework versions

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