---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_style_task1_fold1
  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_style_task1_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: 0.4983
- Qwk: 0.5052
- Mse: 0.4984

## 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    | 5.8113          | -0.0102 | 5.7669 |
| No log        | 0.6667 | 4    | 2.3576          | 0.0342  | 2.3554 |
| No log        | 1.0    | 6    | 1.4911          | 0.0652  | 1.4969 |
| No log        | 1.3333 | 8    | 0.7580          | 0.1021  | 0.7628 |
| No log        | 1.6667 | 10   | 0.5619          | 0.2851  | 0.5662 |
| No log        | 2.0    | 12   | 0.6485          | 0.0870  | 0.6536 |
| No log        | 2.3333 | 14   | 1.0404          | 0.1138  | 1.0530 |
| No log        | 2.6667 | 16   | 0.6654          | 0.2646  | 0.6722 |
| No log        | 3.0    | 18   | 0.4343          | 0.3425  | 0.4348 |
| No log        | 3.3333 | 20   | 0.4318          | 0.4057  | 0.4340 |
| No log        | 3.6667 | 22   | 0.4542          | 0.4057  | 0.4579 |
| No log        | 4.0    | 24   | 0.5421          | 0.3191  | 0.5486 |
| No log        | 4.3333 | 26   | 0.4470          | 0.3780  | 0.4507 |
| No log        | 4.6667 | 28   | 0.4369          | 0.5130  | 0.4397 |
| No log        | 5.0    | 30   | 0.4435          | 0.5130  | 0.4458 |
| No log        | 5.3333 | 32   | 0.4758          | 0.6488  | 0.4772 |
| No log        | 5.6667 | 34   | 0.5072          | 0.5130  | 0.5092 |
| No log        | 6.0    | 36   | 0.5982          | 0.4160  | 0.6024 |
| No log        | 6.3333 | 38   | 0.6201          | 0.3368  | 0.6243 |
| No log        | 6.6667 | 40   | 0.5336          | 0.4731  | 0.5349 |
| No log        | 7.0    | 42   | 0.5080          | 0.6613  | 0.5072 |
| No log        | 7.3333 | 44   | 0.4953          | 0.6613  | 0.4944 |
| No log        | 7.6667 | 46   | 0.4884          | 0.5689  | 0.4879 |
| No log        | 8.0    | 48   | 0.4997          | 0.5052  | 0.4999 |
| No log        | 8.3333 | 50   | 0.5187          | 0.4731  | 0.5194 |
| No log        | 8.6667 | 52   | 0.5092          | 0.4731  | 0.5095 |
| No log        | 9.0    | 54   | 0.4978          | 0.5052  | 0.4977 |
| No log        | 9.3333 | 56   | 0.4999          | 0.5052  | 0.5000 |
| No log        | 9.6667 | 58   | 0.5004          | 0.5052  | 0.5006 |
| No log        | 10.0   | 60   | 0.4983          | 0.5052  | 0.4984 |


### Framework versions

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