
<!-- 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. -->

# vit-base_rvl_cdip-N1K_ce_128

This model is a fine-tuned version of [jordyvl/vit-base_rvl-cdip](https://huggingface.co/jordyvl/vit-base_rvl-cdip) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4776
- Accuracy: 0.8912
- Brier Loss: 0.1798
- Nll: 0.9844
- F1 Micro: 0.8912
- F1 Macro: 0.8915
- Ece: 0.0768
- Aurc: 0.0189

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll    | F1 Micro | F1 Macro | Ece    | Aurc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| No log        | 1.0   | 125  | 0.3896          | 0.893    | 0.1649     | 1.1887 | 0.893    | 0.8933   | 0.0484 | 0.0175 |
| No log        | 2.0   | 250  | 0.3908          | 0.8948   | 0.1606     | 1.1433 | 0.8948   | 0.8950   | 0.0499 | 0.0179 |
| No log        | 3.0   | 375  | 0.4188          | 0.892    | 0.1708     | 1.0860 | 0.892    | 0.8923   | 0.0607 | 0.0184 |
| 0.0953        | 4.0   | 500  | 0.4268          | 0.892    | 0.1707     | 1.0788 | 0.892    | 0.8924   | 0.0654 | 0.0184 |
| 0.0953        | 5.0   | 625  | 0.4414          | 0.8938   | 0.1719     | 1.0502 | 0.8938   | 0.8941   | 0.0664 | 0.0187 |
| 0.0953        | 6.0   | 750  | 0.4570          | 0.8932   | 0.1754     | 1.0253 | 0.8932   | 0.8936   | 0.0714 | 0.0187 |
| 0.0953        | 7.0   | 875  | 0.4681          | 0.891    | 0.1779     | 1.0018 | 0.891    | 0.8912   | 0.0752 | 0.0191 |
| 0.0128        | 8.0   | 1000 | 0.4720          | 0.8902   | 0.1792     | 0.9789 | 0.8902   | 0.8905   | 0.0771 | 0.0188 |
| 0.0128        | 9.0   | 1125 | 0.4757          | 0.8918   | 0.1794     | 0.9865 | 0.8918   | 0.8920   | 0.0760 | 0.0188 |
| 0.0128        | 10.0  | 1250 | 0.4776          | 0.8912   | 0.1798     | 0.9844 | 0.8912   | 0.8915   | 0.0768 | 0.0189 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.2.0.dev20231002
- Datasets 2.7.1
- Tokenizers 0.13.3

letter form email handwritten advertisement scientific_report scientific_publication specification file_folder news_article budget invoice presentation questionnaire resume memo