---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_task5_fold0
  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_grammar_task5_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: 0.6836
- Qwk: 0.5644
- Mse: 0.6836

## 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    | 1.8956          | 0.1818 | 1.8956 |
| No log        | 0.6667 | 4    | 1.7327          | 0.0    | 1.7327 |
| No log        | 1.0    | 6    | 1.5736          | 0.0    | 1.5736 |
| No log        | 1.3333 | 8    | 1.4541          | 0.0    | 1.4541 |
| No log        | 1.6667 | 10   | 1.3999          | 0.1860 | 1.3999 |
| No log        | 2.0    | 12   | 1.3873          | 0.2099 | 1.3873 |
| No log        | 2.3333 | 14   | 1.2920          | 0.3077 | 1.2920 |
| No log        | 2.6667 | 16   | 1.1687          | 0.3580 | 1.1687 |
| No log        | 3.0    | 18   | 1.0389          | 0.4651 | 1.0389 |
| No log        | 3.3333 | 20   | 0.9570          | 0.5435 | 0.9570 |
| No log        | 3.6667 | 22   | 0.9091          | 0.5165 | 0.9091 |
| No log        | 4.0    | 24   | 0.8399          | 0.5876 | 0.8399 |
| No log        | 4.3333 | 26   | 0.7899          | 0.5876 | 0.7899 |
| No log        | 4.6667 | 28   | 0.7622          | 0.5876 | 0.7622 |
| No log        | 5.0    | 30   | 0.7525          | 0.5876 | 0.7525 |
| No log        | 5.3333 | 32   | 0.7384          | 0.5876 | 0.7384 |
| No log        | 5.6667 | 34   | 0.7273          | 0.5876 | 0.7273 |
| No log        | 6.0    | 36   | 0.7207          | 0.5625 | 0.7207 |
| No log        | 6.3333 | 38   | 0.7165          | 0.5625 | 0.7165 |
| No log        | 6.6667 | 40   | 0.7152          | 0.5625 | 0.7152 |
| No log        | 7.0    | 42   | 0.6996          | 0.5625 | 0.6996 |
| No log        | 7.3333 | 44   | 0.6893          | 0.5876 | 0.6893 |
| No log        | 7.6667 | 46   | 0.6890          | 0.5876 | 0.6890 |
| No log        | 8.0    | 48   | 0.6887          | 0.5876 | 0.6887 |
| No log        | 8.3333 | 50   | 0.6864          | 0.5625 | 0.6864 |
| No log        | 8.6667 | 52   | 0.6829          | 0.6117 | 0.6829 |
| No log        | 9.0    | 54   | 0.6833          | 0.5644 | 0.6833 |
| No log        | 9.3333 | 56   | 0.6837          | 0.5644 | 0.6837 |
| No log        | 9.6667 | 58   | 0.6836          | 0.5644 | 0.6836 |
| No log        | 10.0   | 60   | 0.6836          | 0.5644 | 0.6836 |


### Framework versions

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