
<!-- 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_16

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: 0.6681
- Accuracy: 0.89
- Brier Loss: 0.2001
- Nll: 0.9073
- F1 Micro: 0.89
- F1 Macro: 0.8905
- Ece: 0.0923
- Aurc: 0.0219

## 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
- 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   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| 0.209         | 1.0   | 1000  | 0.4595          | 0.8775   | 0.1885     | 1.1949 | 0.8775   | 0.8784   | 0.0616 | 0.0237 |
| 0.1707        | 2.0   | 2000  | 0.4835          | 0.881    | 0.1887     | 1.1366 | 0.881    | 0.8803   | 0.0720 | 0.0237 |
| 0.0893        | 3.0   | 3000  | 0.5434          | 0.8808   | 0.1991     | 1.0313 | 0.8808   | 0.8805   | 0.0830 | 0.0237 |
| 0.0442        | 4.0   | 4000  | 0.5746          | 0.8845   | 0.1964     | 0.9971 | 0.8845   | 0.8850   | 0.0858 | 0.0234 |
| 0.0176        | 5.0   | 5000  | 0.6168          | 0.8802   | 0.2062     | 1.0035 | 0.8802   | 0.8799   | 0.0935 | 0.0241 |
| 0.0098        | 6.0   | 6000  | 0.6533          | 0.882    | 0.2074     | 0.9667 | 0.882    | 0.8829   | 0.0953 | 0.0237 |
| 0.0066        | 7.0   | 7000  | 0.6557          | 0.8838   | 0.2041     | 0.9568 | 0.8838   | 0.8833   | 0.0942 | 0.0235 |
| 0.0049        | 8.0   | 8000  | 0.6557          | 0.8878   | 0.1995     | 0.9076 | 0.8878   | 0.8883   | 0.0934 | 0.0220 |
| 0.0027        | 9.0   | 9000  | 0.6693          | 0.8882   | 0.2024     | 0.9127 | 0.8882   | 0.8888   | 0.0939 | 0.0222 |
| 0.0031        | 10.0  | 10000 | 0.6681          | 0.89     | 0.2001     | 0.9073 | 0.89     | 0.8905   | 0.0923 | 0.0219 |


### 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