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# vit-base_rvl_cdip-N1K_ce_256

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: 0.4495
- Accuracy: 0.8935
- Brier Loss: 0.1753
- Nll: 1.0235
- F1 Micro: 0.8935
- F1 Macro: 0.8937
- Ece: 0.0696
- Aurc: 0.0181

## 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: 256
- eval_batch_size: 256
- 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   | 63   | 0.3678          | 0.8972   | 0.1554     | 1.1865 | 0.8972   | 0.8975   | 0.0427 | 0.0165 |
| No log        | 2.0   | 126  | 0.3774          | 0.896    | 0.1584     | 1.1527 | 0.8960   | 0.8962   | 0.0470 | 0.0170 |
| No log        | 3.0   | 189  | 0.4050          | 0.892    | 0.1688     | 1.1092 | 0.892    | 0.8924   | 0.0578 | 0.0177 |
| No log        | 4.0   | 252  | 0.4089          | 0.8945   | 0.1675     | 1.0874 | 0.8945   | 0.8948   | 0.0582 | 0.0177 |
| No log        | 5.0   | 315  | 0.4255          | 0.8935   | 0.1704     | 1.0678 | 0.8935   | 0.8936   | 0.0640 | 0.0179 |
| No log        | 6.0   | 378  | 0.4324          | 0.8945   | 0.1715     | 1.0540 | 0.8945   | 0.8948   | 0.0648 | 0.0179 |
| No log        | 7.0   | 441  | 0.4404          | 0.894    | 0.1728     | 1.0302 | 0.894    | 0.8941   | 0.0672 | 0.0181 |
| 0.0579        | 8.0   | 504  | 0.4452          | 0.8932   | 0.1747     | 1.0316 | 0.8932   | 0.8934   | 0.0685 | 0.0180 |
| 0.0579        | 9.0   | 567  | 0.4479          | 0.8935   | 0.1749     | 1.0256 | 0.8935   | 0.8937   | 0.0693 | 0.0181 |
| 0.0579        | 10.0  | 630  | 0.4495          | 0.8935   | 0.1753     | 1.0235 | 0.8935   | 0.8937   | 0.0696 | 0.0181 |


### Framework versions

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

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