---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_mechanics_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_mechanics_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: 0.5507
- Qwk: 0.4324
- Mse: 0.5505

## 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    | 4.9042          | 0.0     | 4.9234 |
| No log        | 0.6667 | 4    | 2.0020          | -0.0299 | 2.0282 |
| No log        | 1.0    | 6    | 1.2914          | 0.0769  | 1.3136 |
| No log        | 1.3333 | 8    | 1.0020          | 0.0500  | 1.0184 |
| No log        | 1.6667 | 10   | 0.7738          | 0.125   | 0.7839 |
| No log        | 2.0    | 12   | 0.8249          | 0.2105  | 0.8327 |
| No log        | 2.3333 | 14   | 1.0118          | 0.0851  | 1.0228 |
| No log        | 2.6667 | 16   | 0.7586          | 0.1905  | 0.7651 |
| No log        | 3.0    | 18   | 0.4977          | 0.375   | 0.5025 |
| No log        | 3.3333 | 20   | 0.5065          | 0.3429  | 0.5107 |
| No log        | 3.6667 | 22   | 0.5186          | 0.4118  | 0.5205 |
| No log        | 4.0    | 24   | 0.7202          | 0.2564  | 0.7199 |
| No log        | 4.3333 | 26   | 0.6120          | 0.3889  | 0.6080 |
| No log        | 4.6667 | 28   | 0.5684          | 0.3784  | 0.5637 |
| No log        | 5.0    | 30   | 0.5531          | 0.3889  | 0.5482 |
| No log        | 5.3333 | 32   | 0.6399          | 0.3784  | 0.6320 |
| No log        | 5.6667 | 34   | 0.8218          | 0.2632  | 0.8129 |
| No log        | 6.0    | 36   | 0.8057          | 0.2632  | 0.7976 |
| No log        | 6.3333 | 38   | 0.6262          | 0.3784  | 0.6183 |
| No log        | 6.6667 | 40   | 0.6028          | 0.3889  | 0.5950 |
| No log        | 7.0    | 42   | 0.6011          | 0.3889  | 0.5943 |
| No log        | 7.3333 | 44   | 0.6488          | 0.3158  | 0.6438 |
| No log        | 7.6667 | 46   | 0.5939          | 0.3158  | 0.5907 |
| No log        | 8.0    | 48   | 0.5456          | 0.4324  | 0.5440 |
| No log        | 8.3333 | 50   | 0.5191          | 0.4324  | 0.5183 |
| No log        | 8.6667 | 52   | 0.4890          | 0.4324  | 0.4889 |
| No log        | 9.0    | 54   | 0.4994          | 0.4324  | 0.4996 |
| No log        | 9.3333 | 56   | 0.5265          | 0.4324  | 0.5267 |
| No log        | 9.6667 | 58   | 0.5469          | 0.4324  | 0.5468 |
| No log        | 10.0   | 60   | 0.5507          | 0.4324  | 0.5505 |


### Framework versions

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