---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_task1_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_task1_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: 0.7080
- Qwk: 0.6596
- Mse: 0.7206

## 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    | 4.7375          | -0.0187 | 4.6528 |
| No log        | 0.6667 | 4    | 2.9523          | 0.0354  | 2.8976 |
| No log        | 1.0    | 6    | 1.9933          | 0.0369  | 1.9520 |
| No log        | 1.3333 | 8    | 1.4358          | 0.1414  | 1.4243 |
| No log        | 1.6667 | 10   | 1.3507          | 0.0742  | 1.3574 |
| No log        | 2.0    | 12   | 1.2869          | 0.3309  | 1.2992 |
| No log        | 2.3333 | 14   | 1.3060          | 0.4324  | 1.3235 |
| No log        | 2.6667 | 16   | 1.2124          | 0.4085  | 1.2278 |
| No log        | 3.0    | 18   | 1.0567          | 0.4854  | 1.0647 |
| No log        | 3.3333 | 20   | 0.9500          | 0.4639  | 0.9565 |
| No log        | 3.6667 | 22   | 0.8719          | 0.5769  | 0.8846 |
| No log        | 4.0    | 24   | 0.7991          | 0.5769  | 0.8115 |
| No log        | 4.3333 | 26   | 0.7537          | 0.5769  | 0.7666 |
| No log        | 4.6667 | 28   | 0.7147          | 0.5514  | 0.7274 |
| No log        | 5.0    | 30   | 0.6387          | 0.5811  | 0.6471 |
| No log        | 5.3333 | 32   | 0.6221          | 0.5748  | 0.6286 |
| No log        | 5.6667 | 34   | 0.6363          | 0.5811  | 0.6453 |
| No log        | 6.0    | 36   | 0.6849          | 0.5811  | 0.6955 |
| No log        | 6.3333 | 38   | 0.6868          | 0.5811  | 0.6971 |
| No log        | 6.6667 | 40   | 0.6843          | 0.5435  | 0.6932 |
| No log        | 7.0    | 42   | 0.7048          | 0.5081  | 0.7131 |
| No log        | 7.3333 | 44   | 0.7116          | 0.5804  | 0.7201 |
| No log        | 7.6667 | 46   | 0.7162          | 0.5779  | 0.7250 |
| No log        | 8.0    | 48   | 0.7262          | 0.5779  | 0.7360 |
| No log        | 8.3333 | 50   | 0.7157          | 0.5779  | 0.7258 |
| No log        | 8.6667 | 52   | 0.7189          | 0.5779  | 0.7301 |
| No log        | 9.0    | 54   | 0.7090          | 0.6547  | 0.7206 |
| No log        | 9.3333 | 56   | 0.7059          | 0.6547  | 0.7179 |
| No log        | 9.6667 | 58   | 0.7067          | 0.6547  | 0.7191 |
| No log        | 10.0   | 60   | 0.7080          | 0.6596  | 0.7206 |


### Framework versions

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