---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_task1_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_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: 0.5311
- Qwk: 0.5882
- Mse: 0.5332

## 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    | 4.8751          | -0.0497 | 4.7777 |
| No log        | 0.6667 | 4    | 1.9817          | 0.0263  | 1.9110 |
| No log        | 1.0    | 6    | 1.0160          | 0.1348  | 0.9761 |
| No log        | 1.3333 | 8    | 0.8888          | 0.2611  | 0.8614 |
| No log        | 1.6667 | 10   | 0.7375          | 0.4340  | 0.7296 |
| No log        | 2.0    | 12   | 0.9526          | 0.2222  | 0.9430 |
| No log        | 2.3333 | 14   | 0.8202          | 0.3636  | 0.8111 |
| No log        | 2.6667 | 16   | 0.6506          | 0.4324  | 0.6405 |
| No log        | 3.0    | 18   | 0.7279          | 0.4290  | 0.7066 |
| No log        | 3.3333 | 20   | 0.8689          | 0.3668  | 0.8447 |
| No log        | 3.6667 | 22   | 0.7419          | 0.4119  | 0.7226 |
| No log        | 4.0    | 24   | 0.6583          | 0.5051  | 0.6408 |
| No log        | 4.3333 | 26   | 0.6672          | 0.4726  | 0.6487 |
| No log        | 4.6667 | 28   | 0.6625          | 0.4373  | 0.6466 |
| No log        | 5.0    | 30   | 0.6519          | 0.4061  | 0.6397 |
| No log        | 5.3333 | 32   | 0.6430          | 0.4358  | 0.6321 |
| No log        | 5.6667 | 34   | 0.6395          | 0.4358  | 0.6295 |
| No log        | 6.0    | 36   | 0.6008          | 0.5051  | 0.5923 |
| No log        | 6.3333 | 38   | 0.5776          | 0.5051  | 0.5691 |
| No log        | 6.6667 | 40   | 0.5657          | 0.5051  | 0.5566 |
| No log        | 7.0    | 42   | 0.5537          | 0.5051  | 0.5464 |
| No log        | 7.3333 | 44   | 0.5474          | 0.5051  | 0.5417 |
| No log        | 7.6667 | 46   | 0.5355          | 0.5051  | 0.5321 |
| No log        | 8.0    | 48   | 0.5261          | 0.5051  | 0.5245 |
| No log        | 8.3333 | 50   | 0.5235          | 0.5882  | 0.5233 |
| No log        | 8.6667 | 52   | 0.5271          | 0.5882  | 0.5280 |
| No log        | 9.0    | 54   | 0.5282          | 0.5882  | 0.5300 |
| No log        | 9.3333 | 56   | 0.5296          | 0.5882  | 0.5318 |
| No log        | 9.6667 | 58   | 0.5304          | 0.5882  | 0.5327 |
| No log        | 10.0   | 60   | 0.5311          | 0.5882  | 0.5332 |


### Framework versions

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