---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_task2_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_vocabulary_task2_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: 0.5710
- Qwk: 0.0911
- Mse: 0.5727

## 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    | 5.7084          | -0.0071 | 5.7092 |
| No log        | 0.6667 | 4    | 2.7119          | 0.0524  | 2.7198 |
| No log        | 1.0    | 6    | 1.4034          | -0.0198 | 1.4046 |
| No log        | 1.3333 | 8    | 0.6439          | 0.0396  | 0.6441 |
| No log        | 1.6667 | 10   | 0.6138          | 0.0     | 0.6150 |
| No log        | 2.0    | 12   | 0.6664          | 0.0     | 0.6682 |
| No log        | 2.3333 | 14   | 0.6604          | -0.0925 | 0.6596 |
| No log        | 2.6667 | 16   | 0.5976          | 0.0526  | 0.5979 |
| No log        | 3.0    | 18   | 0.6250          | 0.1747  | 0.6254 |
| No log        | 3.3333 | 20   | 0.6646          | 0.1021  | 0.6644 |
| No log        | 3.6667 | 22   | 0.5974          | 0.2396  | 0.5967 |
| No log        | 4.0    | 24   | 0.5442          | 0.0911  | 0.5440 |
| No log        | 4.3333 | 26   | 0.5490          | 0.0289  | 0.5512 |
| No log        | 4.6667 | 28   | 0.5728          | 0.0     | 0.5758 |
| No log        | 5.0    | 30   | 0.5435          | 0.0     | 0.5463 |
| No log        | 5.3333 | 32   | 0.4958          | 0.2794  | 0.4980 |
| No log        | 5.6667 | 34   | 0.4795          | 0.2105  | 0.4813 |
| No log        | 6.0    | 36   | 0.4887          | 0.2167  | 0.4894 |
| No log        | 6.3333 | 38   | 0.4972          | 0.2222  | 0.4980 |
| No log        | 6.6667 | 40   | 0.5094          | 0.2222  | 0.5094 |
| No log        | 7.0    | 42   | 0.5328          | 0.1198  | 0.5321 |
| No log        | 7.3333 | 44   | 0.5401          | 0.1064  | 0.5397 |
| No log        | 7.6667 | 46   | 0.5403          | 0.1064  | 0.5409 |
| No log        | 8.0    | 48   | 0.5495          | 0.0911  | 0.5517 |
| No log        | 8.3333 | 50   | 0.5683          | 0.0735  | 0.5711 |
| No log        | 8.6667 | 52   | 0.5763          | 0.0735  | 0.5791 |
| No log        | 9.0    | 54   | 0.5754          | 0.0911  | 0.5779 |
| No log        | 9.3333 | 56   | 0.5725          | 0.0911  | 0.5748 |
| No log        | 9.6667 | 58   | 0.5717          | 0.0911  | 0.5736 |
| No log        | 10.0   | 60   | 0.5710          | 0.0911  | 0.5727 |


### Framework versions

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