---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_vocabulary_task7_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_vocabulary_task7_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: 0.4434
- Qwk: 0.7306
- Mse: 0.4409

## 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    | 1.1716          | 0.2597 | 1.1767 |
| No log        | 0.6667 | 4    | 0.7370          | 0.5706 | 0.7641 |
| No log        | 1.0    | 6    | 0.7497          | 0.5562 | 0.7703 |
| No log        | 1.3333 | 8    | 0.6581          | 0.5987 | 0.6708 |
| No log        | 1.6667 | 10   | 0.6557          | 0.4    | 0.6660 |
| No log        | 2.0    | 12   | 0.4981          | 0.7242 | 0.5095 |
| No log        | 2.3333 | 14   | 0.5966          | 0.5490 | 0.6027 |
| No log        | 2.6667 | 16   | 0.7334          | 0.5273 | 0.7340 |
| No log        | 3.0    | 18   | 0.7026          | 0.5268 | 0.7001 |
| No log        | 3.3333 | 20   | 0.5537          | 0.6360 | 0.5517 |
| No log        | 3.6667 | 22   | 0.5745          | 0.6402 | 0.5704 |
| No log        | 4.0    | 24   | 0.6711          | 0.5418 | 0.6622 |
| No log        | 4.3333 | 26   | 0.6481          | 0.5418 | 0.6370 |
| No log        | 4.6667 | 28   | 0.5399          | 0.6015 | 0.5315 |
| No log        | 5.0    | 30   | 0.4583          | 0.6890 | 0.4538 |
| No log        | 5.3333 | 32   | 0.4300          | 0.7379 | 0.4272 |
| No log        | 5.6667 | 34   | 0.4490          | 0.6402 | 0.4450 |
| No log        | 6.0    | 36   | 0.5299          | 0.6360 | 0.5222 |
| No log        | 6.3333 | 38   | 0.5460          | 0.5268 | 0.5387 |
| No log        | 6.6667 | 40   | 0.4926          | 0.6360 | 0.4893 |
| No log        | 7.0    | 42   | 0.4501          | 0.6402 | 0.4494 |
| No log        | 7.3333 | 44   | 0.4428          | 0.7379 | 0.4421 |
| No log        | 7.6667 | 46   | 0.4707          | 0.6360 | 0.4684 |
| No log        | 8.0    | 48   | 0.4833          | 0.6360 | 0.4804 |
| No log        | 8.3333 | 50   | 0.5033          | 0.6360 | 0.4988 |
| No log        | 8.6667 | 52   | 0.5001          | 0.6360 | 0.4953 |
| No log        | 9.0    | 54   | 0.4748          | 0.6833 | 0.4711 |
| No log        | 9.3333 | 56   | 0.4541          | 0.6833 | 0.4512 |
| No log        | 9.6667 | 58   | 0.4462          | 0.6833 | 0.4437 |
| No log        | 10.0   | 60   | 0.4434          | 0.7306 | 0.4409 |


### Framework versions

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