---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_baseline_organization_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_organization_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: 0.6217
- Qwk: 0.4969
- Mse: 0.6213

## 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    | 1.0245          | 0.3758 | 1.0297 |
| No log        | 0.6667 | 4    | 0.7919          | 0.5312 | 0.8059 |
| No log        | 1.0    | 6    | 0.8469          | 0.6400 | 0.8626 |
| No log        | 1.3333 | 8    | 0.7621          | 0.3793 | 0.7785 |
| No log        | 1.6667 | 10   | 0.8831          | 0.2326 | 0.8970 |
| No log        | 2.0    | 12   | 0.7493          | 0.4    | 0.7628 |
| No log        | 2.3333 | 14   | 0.4924          | 0.6165 | 0.5052 |
| No log        | 2.6667 | 16   | 0.4499          | 0.6571 | 0.4612 |
| No log        | 3.0    | 18   | 0.4936          | 0.6203 | 0.5029 |
| No log        | 3.3333 | 20   | 0.7252          | 0.4224 | 0.7311 |
| No log        | 3.6667 | 22   | 0.9227          | 0.3657 | 0.9263 |
| No log        | 4.0    | 24   | 0.8957          | 0.3657 | 0.8980 |
| No log        | 4.3333 | 26   | 0.7242          | 0.4211 | 0.7260 |
| No log        | 4.6667 | 28   | 0.5595          | 0.6203 | 0.5620 |
| No log        | 5.0    | 30   | 0.4521          | 0.6024 | 0.4559 |
| No log        | 5.3333 | 32   | 0.4402          | 0.6786 | 0.4437 |
| No log        | 5.6667 | 34   | 0.4703          | 0.6909 | 0.4728 |
| No log        | 6.0    | 36   | 0.6144          | 0.5    | 0.6153 |
| No log        | 6.3333 | 38   | 0.7150          | 0.4969 | 0.7150 |
| No log        | 6.6667 | 40   | 0.7022          | 0.4969 | 0.7024 |
| No log        | 7.0    | 42   | 0.6409          | 0.5    | 0.6418 |
| No log        | 7.3333 | 44   | 0.5912          | 0.5    | 0.5923 |
| No log        | 7.6667 | 46   | 0.5457          | 0.6341 | 0.5469 |
| No log        | 8.0    | 48   | 0.5073          | 0.6909 | 0.5089 |
| No log        | 8.3333 | 50   | 0.5143          | 0.6909 | 0.5157 |
| No log        | 8.6667 | 52   | 0.5540          | 0.6341 | 0.5549 |
| No log        | 9.0    | 54   | 0.5883          | 0.6272 | 0.5886 |
| No log        | 9.3333 | 56   | 0.6103          | 0.4969 | 0.6102 |
| No log        | 9.6667 | 58   | 0.6204          | 0.4969 | 0.6200 |
| No log        | 10.0   | 60   | 0.6217          | 0.4969 | 0.6213 |


### Framework versions

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