
<!-- 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_4

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: 0.9480
- Accuracy: 0.8792
- Brier Loss: 0.2240
- Nll: 1.0075
- F1 Micro: 0.8793
- F1 Macro: 0.8794
- Ece: 0.1101
- Aurc: 0.0274

## 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: 4
- eval_batch_size: 4
- 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   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| 0.4172        | 1.0   | 4000  | 0.6321          | 0.8475   | 0.2427     | 1.1862 | 0.8475   | 0.8484   | 0.0957 | 0.0352 |
| 0.3421        | 2.0   | 8000  | 0.6729          | 0.8645   | 0.2301     | 1.1766 | 0.8645   | 0.8642   | 0.1020 | 0.0295 |
| 0.2091        | 3.0   | 12000 | 0.7988          | 0.854    | 0.2563     | 1.1608 | 0.854    | 0.8555   | 0.1183 | 0.0352 |
| 0.1319        | 4.0   | 16000 | 0.8683          | 0.861    | 0.2503     | 1.1575 | 0.861    | 0.8617   | 0.1188 | 0.0354 |
| 0.0673        | 5.0   | 20000 | 0.9057          | 0.8642   | 0.2479     | 1.1524 | 0.8643   | 0.8635   | 0.1195 | 0.0314 |
| 0.0333        | 6.0   | 24000 | 0.9553          | 0.8605   | 0.2524     | 1.1006 | 0.8605   | 0.8600   | 0.1226 | 0.0366 |
| 0.0223        | 7.0   | 28000 | 0.9393          | 0.8708   | 0.2350     | 1.1027 | 0.8708   | 0.8713   | 0.1159 | 0.0274 |
| 0.0194        | 8.0   | 32000 | 1.0108          | 0.8705   | 0.2407     | 1.0850 | 0.8705   | 0.8704   | 0.1169 | 0.0309 |
| 0.0015        | 9.0   | 36000 | 0.9412          | 0.876    | 0.2291     | 1.0136 | 0.8760   | 0.8763   | 0.1123 | 0.0270 |
| 0.004         | 10.0  | 40000 | 0.9480          | 0.8792   | 0.2240     | 1.0075 | 0.8793   | 0.8794   | 0.1101 | 0.0274 |


### 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