---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task7_fold1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_baseline_relevance_task7_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: 0.1811
- Qwk: 0.4857
- Mse: 0.1829

## 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    | 0.2365          | 0.3424 | 0.2296 |
| No log        | 0.6667 | 4    | 0.2621          | 0.4112 | 0.2567 |
| No log        | 1.0    | 6    | 0.3169          | 0.5670 | 0.3168 |
| No log        | 1.3333 | 8    | 0.3023          | 0.5145 | 0.2938 |
| No log        | 1.6667 | 10   | 0.2629          | 0.2310 | 0.2513 |
| No log        | 2.0    | 12   | 0.2208          | 0.4676 | 0.2109 |
| No log        | 2.3333 | 14   | 0.2071          | 0.5410 | 0.2005 |
| No log        | 2.6667 | 16   | 0.1961          | 0.5410 | 0.1905 |
| No log        | 3.0    | 18   | 0.1888          | 0.5093 | 0.1831 |
| No log        | 3.3333 | 20   | 0.1855          | 0.5093 | 0.1806 |
| No log        | 3.6667 | 22   | 0.1838          | 0.4967 | 0.1793 |
| No log        | 4.0    | 24   | 0.1870          | 0.4857 | 0.1820 |
| No log        | 4.3333 | 26   | 0.1864          | 0.4857 | 0.1822 |
| No log        | 4.6667 | 28   | 0.1812          | 0.4857 | 0.1788 |
| No log        | 5.0    | 30   | 0.1754          | 0.4857 | 0.1742 |
| No log        | 5.3333 | 32   | 0.1723          | 0.4967 | 0.1722 |
| No log        | 5.6667 | 34   | 0.1695          | 0.5695 | 0.1704 |
| No log        | 6.0    | 36   | 0.1654          | 0.5695 | 0.1667 |
| No log        | 6.3333 | 38   | 0.1652          | 0.5093 | 0.1667 |
| No log        | 6.6667 | 40   | 0.1707          | 0.4857 | 0.1722 |
| No log        | 7.0    | 42   | 0.1771          | 0.4857 | 0.1786 |
| No log        | 7.3333 | 44   | 0.1814          | 0.4857 | 0.1829 |
| No log        | 7.6667 | 46   | 0.1782          | 0.4857 | 0.1801 |
| No log        | 8.0    | 48   | 0.1775          | 0.5389 | 0.1799 |
| No log        | 8.3333 | 50   | 0.1799          | 0.5389 | 0.1824 |
| No log        | 8.6667 | 52   | 0.1801          | 0.5389 | 0.1825 |
| No log        | 9.0    | 54   | 0.1806          | 0.4857 | 0.1828 |
| No log        | 9.3333 | 56   | 0.1816          | 0.4857 | 0.1837 |
| No log        | 9.6667 | 58   | 0.1812          | 0.4857 | 0.1831 |
| No log        | 10.0   | 60   | 0.1811          | 0.4857 | 0.1829 |


### Framework versions

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