---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_task5_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_grammar_task5_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: 0.4829
- Qwk: 0.6262
- Mse: 0.4829

## 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    | 2.4374          | 0.0250  | 2.4374 |
| No log        | 0.6667 | 4    | 0.9732          | -0.0090 | 0.9732 |
| No log        | 1.0    | 6    | 0.5943          | 0.3165  | 0.5943 |
| No log        | 1.3333 | 8    | 0.5108          | 0.3182  | 0.5108 |
| No log        | 1.6667 | 10   | 0.4747          | 0.3137  | 0.4747 |
| No log        | 2.0    | 12   | 0.4634          | 0.3165  | 0.4634 |
| No log        | 2.3333 | 14   | 0.4798          | 0.4509  | 0.4798 |
| No log        | 2.6667 | 16   | 0.4795          | 0.4737  | 0.4795 |
| No log        | 3.0    | 18   | 0.5467          | 0.5327  | 0.5467 |
| No log        | 3.3333 | 20   | 0.5831          | 0.5327  | 0.5831 |
| No log        | 3.6667 | 22   | 0.5213          | 0.6269  | 0.5213 |
| No log        | 4.0    | 24   | 0.6213          | 0.7087  | 0.6213 |
| No log        | 4.3333 | 26   | 0.6774          | 0.7236  | 0.6774 |
| No log        | 4.6667 | 28   | 0.6694          | 0.7236  | 0.6694 |
| No log        | 5.0    | 30   | 0.5668          | 0.7     | 0.5668 |
| No log        | 5.3333 | 32   | 0.5235          | 0.7059  | 0.5235 |
| No log        | 5.6667 | 34   | 0.5216          | 0.7059  | 0.5216 |
| No log        | 6.0    | 36   | 0.5070          | 0.5957  | 0.5070 |
| No log        | 6.3333 | 38   | 0.5038          | 0.6047  | 0.5038 |
| No log        | 6.6667 | 40   | 0.5220          | 0.6606  | 0.5220 |
| No log        | 7.0    | 42   | 0.5420          | 0.6377  | 0.5420 |
| No log        | 7.3333 | 44   | 0.5474          | 0.6667  | 0.5474 |
| No log        | 7.6667 | 46   | 0.5400          | 0.6262  | 0.5400 |
| No log        | 8.0    | 48   | 0.5341          | 0.6262  | 0.5341 |
| No log        | 8.3333 | 50   | 0.5282          | 0.6262  | 0.5282 |
| No log        | 8.6667 | 52   | 0.5146          | 0.6262  | 0.5146 |
| No log        | 9.0    | 54   | 0.4982          | 0.6262  | 0.4982 |
| No log        | 9.3333 | 56   | 0.4857          | 0.6262  | 0.4857 |
| No log        | 9.6667 | 58   | 0.4846          | 0.6262  | 0.4846 |
| No log        | 10.0   | 60   | 0.4829          | 0.6262  | 0.4829 |


### Framework versions

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