---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_relevance_task1_fold0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# arabert_cross_relevance_task1_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: 0.1989
- Qwk: 0.0319
- Mse: 0.1989

## 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        | 0.0351 | 2    | 0.4878          | 0.0163 | 0.4878 |
| No log        | 0.0702 | 4    | 0.1886          | 0.0202 | 0.1886 |
| No log        | 0.1053 | 6    | 0.1831          | 0.0185 | 0.1831 |
| No log        | 0.1404 | 8    | 0.2686          | 0.0273 | 0.2686 |
| No log        | 0.1754 | 10   | 0.2485          | 0.0273 | 0.2485 |
| No log        | 0.2105 | 12   | 0.2552          | 0.0273 | 0.2552 |
| No log        | 0.2456 | 14   | 0.2716          | 0.0254 | 0.2716 |
| No log        | 0.2807 | 16   | 0.3347          | 0.0217 | 0.3347 |
| No log        | 0.3158 | 18   | 0.3725          | 0.0323 | 0.3725 |
| No log        | 0.3509 | 20   | 0.3182          | 0.0361 | 0.3182 |
| No log        | 0.3860 | 22   | 0.2412          | 0.0319 | 0.2412 |
| No log        | 0.4211 | 24   | 0.1936          | 0.0319 | 0.1936 |
| No log        | 0.4561 | 26   | 0.1659          | 0.0319 | 0.1659 |
| No log        | 0.4912 | 28   | 0.1540          | 0.0339 | 0.1540 |
| No log        | 0.5263 | 30   | 0.1483          | 0.0254 | 0.1483 |
| No log        | 0.5614 | 32   | 0.1525          | 0.0273 | 0.1525 |
| No log        | 0.5965 | 34   | 0.1560          | 0.0359 | 0.1560 |
| No log        | 0.6316 | 36   | 0.1603          | 0.0339 | 0.1603 |
| No log        | 0.6667 | 38   | 0.1720          | 0.0319 | 0.1720 |
| No log        | 0.7018 | 40   | 0.1847          | 0.0319 | 0.1847 |
| No log        | 0.7368 | 42   | 0.2033          | 0.0319 | 0.2033 |
| No log        | 0.7719 | 44   | 0.2175          | 0.0319 | 0.2175 |
| No log        | 0.8070 | 46   | 0.2213          | 0.0319 | 0.2213 |
| No log        | 0.8421 | 48   | 0.2184          | 0.0319 | 0.2184 |
| No log        | 0.8772 | 50   | 0.2126          | 0.0319 | 0.2126 |
| No log        | 0.9123 | 52   | 0.2064          | 0.0319 | 0.2064 |
| No log        | 0.9474 | 54   | 0.2016          | 0.0319 | 0.2016 |
| No log        | 0.9825 | 56   | 0.1989          | 0.0319 | 0.1989 |


### Framework versions

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