---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_grammar_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_grammar_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: 1.0215
- Qwk: 0.4277
- Mse: 1.0149

## 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    | 6.3410          | 0.0064  | 6.3164 |
| No log        | 0.6667 | 4    | 2.8727          | -0.0032 | 2.8725 |
| No log        | 1.0    | 6    | 1.9270          | 0.0637  | 1.9299 |
| No log        | 1.3333 | 8    | 1.0990          | 0.0473  | 1.1001 |
| No log        | 1.6667 | 10   | 0.8012          | 0.1845  | 0.8013 |
| No log        | 2.0    | 12   | 1.1169          | 0.0073  | 1.1140 |
| No log        | 2.3333 | 14   | 1.7714          | 0.0178  | 1.7742 |
| No log        | 2.6667 | 16   | 1.2969          | 0.0732  | 1.2959 |
| No log        | 3.0    | 18   | 0.7829          | 0.1901  | 0.7782 |
| No log        | 3.3333 | 20   | 0.6867          | 0.2424  | 0.6831 |
| No log        | 3.6667 | 22   | 0.7196          | 0.3083  | 0.7164 |
| No log        | 4.0    | 24   | 0.9069          | 0.2976  | 0.9039 |
| No log        | 4.3333 | 26   | 1.0224          | 0.2067  | 1.0193 |
| No log        | 4.6667 | 28   | 1.1040          | 0.2031  | 1.1003 |
| No log        | 5.0    | 30   | 0.9157          | 0.3099  | 0.9103 |
| No log        | 5.3333 | 32   | 0.8876          | 0.3542  | 0.8806 |
| No log        | 5.6667 | 34   | 1.0466          | 0.3092  | 1.0395 |
| No log        | 6.0    | 36   | 1.1926          | 0.2415  | 1.1858 |
| No log        | 6.3333 | 38   | 1.0798          | 0.2979  | 1.0719 |
| No log        | 6.6667 | 40   | 0.9440          | 0.4539  | 0.9342 |
| No log        | 7.0    | 42   | 0.9339          | 0.4539  | 0.9235 |
| No log        | 7.3333 | 44   | 1.0280          | 0.2979  | 1.0189 |
| No log        | 7.6667 | 46   | 1.1837          | 0.2266  | 1.1769 |
| No log        | 8.0    | 48   | 1.2050          | 0.2266  | 1.1989 |
| No log        | 8.3333 | 50   | 1.1372          | 0.3277  | 1.1307 |
| No log        | 8.6667 | 52   | 1.0392          | 0.3092  | 1.0317 |
| No log        | 9.0    | 54   | 0.9980          | 0.4027  | 0.9903 |
| No log        | 9.3333 | 56   | 0.9952          | 0.4027  | 0.9879 |
| No log        | 9.6667 | 58   | 1.0174          | 0.4277  | 1.0106 |
| No log        | 10.0   | 60   | 1.0215          | 0.4277  | 1.0149 |


### Framework versions

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