---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_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_organization_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: 0.4765
- Qwk: 0.5051
- Mse: 0.4812

## 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    | 3.4785          | 0.0139 | 3.4271 |
| No log        | 0.6667 | 4    | 1.3527          | 0.0988 | 1.3438 |
| No log        | 1.0    | 6    | 0.9762          | 0.0466 | 0.9710 |
| No log        | 1.3333 | 8    | 0.5845          | 0.3068 | 0.5906 |
| No log        | 1.6667 | 10   | 0.6355          | 0.4901 | 0.6479 |
| No log        | 2.0    | 12   | 0.6002          | 0.4901 | 0.6080 |
| No log        | 2.3333 | 14   | 0.5521          | 0.3591 | 0.5519 |
| No log        | 2.6667 | 16   | 0.5671          | 0.5312 | 0.5733 |
| No log        | 3.0    | 18   | 0.5298          | 0.5351 | 0.5340 |
| No log        | 3.3333 | 20   | 0.5071          | 0.3871 | 0.4996 |
| No log        | 3.6667 | 22   | 0.4892          | 0.3871 | 0.4817 |
| No log        | 4.0    | 24   | 0.4557          | 0.5051 | 0.4597 |
| No log        | 4.3333 | 26   | 0.5421          | 0.5205 | 0.5533 |
| No log        | 4.6667 | 28   | 0.5017          | 0.5263 | 0.5115 |
| No log        | 5.0    | 30   | 0.4329          | 0.5365 | 0.4364 |
| No log        | 5.3333 | 32   | 0.4203          | 0.4431 | 0.4190 |
| No log        | 5.6667 | 34   | 0.4083          | 0.4848 | 0.4015 |
| No log        | 6.0    | 36   | 0.4520          | 0.4167 | 0.4366 |
| No log        | 6.3333 | 38   | 0.4291          | 0.4396 | 0.4158 |
| No log        | 6.6667 | 40   | 0.4230          | 0.4324 | 0.4110 |
| No log        | 7.0    | 42   | 0.4029          | 0.4848 | 0.3965 |
| No log        | 7.3333 | 44   | 0.4095          | 0.4848 | 0.4043 |
| No log        | 7.6667 | 46   | 0.4194          | 0.4149 | 0.4149 |
| No log        | 8.0    | 48   | 0.4324          | 0.5051 | 0.4317 |
| No log        | 8.3333 | 50   | 0.4591          | 0.5051 | 0.4628 |
| No log        | 8.6667 | 52   | 0.4758          | 0.4652 | 0.4811 |
| No log        | 9.0    | 54   | 0.4791          | 0.4652 | 0.4844 |
| No log        | 9.3333 | 56   | 0.4781          | 0.4652 | 0.4831 |
| No log        | 9.6667 | 58   | 0.4760          | 0.5051 | 0.4806 |
| No log        | 10.0   | 60   | 0.4765          | 0.5051 | 0.4812 |


### Framework versions

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