---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_relevance_task2_fold0
  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_task2_fold0

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: 0.1850
- Qwk: 0.0597
- Mse: 0.1935

## 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    | 0.9871          | 0.0205  | 0.9763 |
| No log        | 0.6667 | 4    | 0.1822          | 0.1049  | 0.1846 |
| No log        | 1.0    | 6    | 0.2694          | -0.0176 | 0.2773 |
| No log        | 1.3333 | 8    | 0.2612          | -0.0791 | 0.2700 |
| No log        | 1.6667 | 10   | 0.2291          | 0.0187  | 0.2405 |
| No log        | 2.0    | 12   | 0.1605          | 0.0755  | 0.1675 |
| No log        | 2.3333 | 14   | 0.1556          | 0.1049  | 0.1617 |
| No log        | 2.6667 | 16   | 0.1455          | 0.1370  | 0.1500 |
| No log        | 3.0    | 18   | 0.1386          | 0.0     | 0.1414 |
| No log        | 3.3333 | 20   | 0.1423          | 0.0     | 0.1448 |
| No log        | 3.6667 | 22   | 0.1393          | 0.0     | 0.1429 |
| No log        | 4.0    | 24   | 0.1807          | 0.4815  | 0.1875 |
| No log        | 4.3333 | 26   | 0.2622          | 0.0     | 0.2718 |
| No log        | 4.6667 | 28   | 0.2372          | 0.0     | 0.2476 |
| No log        | 5.0    | 30   | 0.1765          | -0.1290 | 0.1845 |
| No log        | 5.3333 | 32   | 0.1633          | 0.0483  | 0.1688 |
| No log        | 5.6667 | 34   | 0.1551          | 0.0755  | 0.1613 |
| No log        | 6.0    | 36   | 0.1689          | 0.1674  | 0.1757 |
| No log        | 6.3333 | 38   | 0.1736          | 0.2687  | 0.1798 |
| No log        | 6.6667 | 40   | 0.1678          | 0.2150  | 0.1732 |
| No log        | 7.0    | 42   | 0.1581          | 0.1250  | 0.1631 |
| No log        | 7.3333 | 44   | 0.1540          | 0.0526  | 0.1591 |
| No log        | 7.6667 | 46   | 0.1536          | 0.0526  | 0.1590 |
| No log        | 8.0    | 48   | 0.1603          | 0.1250  | 0.1666 |
| No log        | 8.3333 | 50   | 0.1716          | 0.2150  | 0.1790 |
| No log        | 8.6667 | 52   | 0.1797          | 0.0597  | 0.1878 |
| No log        | 9.0    | 54   | 0.1828          | 0.0597  | 0.1911 |
| No log        | 9.3333 | 56   | 0.1841          | 0.0597  | 0.1925 |
| No log        | 9.6667 | 58   | 0.1849          | 0.0597  | 0.1933 |
| No log        | 10.0   | 60   | 0.1850          | 0.0597  | 0.1935 |


### Framework versions

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