---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task5_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_task5_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: 0.1845
- Qwk: 0.3789
- Mse: 0.1845

## 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        | 0.3333 | 2    | 0.7186          | -0.0682 | 0.7186 |
| No log        | 0.6667 | 4    | 0.2563          | 0.0     | 0.2563 |
| No log        | 1.0    | 6    | 0.1977          | 0.0551  | 0.1977 |
| No log        | 1.3333 | 8    | 0.1845          | 0.2373  | 0.1845 |
| No log        | 1.6667 | 10   | 0.1961          | 0.2361  | 0.1961 |
| No log        | 2.0    | 12   | 0.2108          | 0.1960  | 0.2108 |
| No log        | 2.3333 | 14   | 0.2096          | 0.2347  | 0.2096 |
| No log        | 2.6667 | 16   | 0.2117          | 0.2814  | 0.2117 |
| No log        | 3.0    | 18   | 0.2125          | 0.2814  | 0.2125 |
| No log        | 3.3333 | 20   | 0.2086          | 0.3789  | 0.2086 |
| No log        | 3.6667 | 22   | 0.2136          | 0.2547  | 0.2136 |
| No log        | 4.0    | 24   | 0.2106          | 0.3293  | 0.2106 |
| No log        | 4.3333 | 26   | 0.1994          | 0.3293  | 0.1994 |
| No log        | 4.6667 | 28   | 0.1978          | 0.1477  | 0.1978 |
| No log        | 5.0    | 30   | 0.2011          | 0.2353  | 0.2011 |
| No log        | 5.3333 | 32   | 0.2091          | 0.2258  | 0.2091 |
| No log        | 5.6667 | 34   | 0.2215          | 0.2763  | 0.2215 |
| No log        | 6.0    | 36   | 0.2177          | 0.2763  | 0.2177 |
| No log        | 6.3333 | 38   | 0.2103          | 0.2763  | 0.2103 |
| No log        | 6.6667 | 40   | 0.1968          | 0.4304  | 0.1968 |
| No log        | 7.0    | 42   | 0.1868          | 0.3789  | 0.1868 |
| No log        | 7.3333 | 44   | 0.1820          | 0.3789  | 0.1820 |
| No log        | 7.6667 | 46   | 0.1813          | 0.3789  | 0.1813 |
| No log        | 8.0    | 48   | 0.1828          | 0.3789  | 0.1828 |
| No log        | 8.3333 | 50   | 0.1865          | 0.3789  | 0.1865 |
| No log        | 8.6667 | 52   | 0.1900          | 0.4304  | 0.1900 |
| No log        | 9.0    | 54   | 0.1886          | 0.4304  | 0.1886 |
| No log        | 9.3333 | 56   | 0.1873          | 0.3789  | 0.1873 |
| No log        | 9.6667 | 58   | 0.1853          | 0.3789  | 0.1853 |
| No log        | 10.0   | 60   | 0.1845          | 0.3789  | 0.1845 |


### Framework versions

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