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# vit-base_rvl_cdip-N1K_aAURC_2

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: 0.3354
- Accuracy: 0.8788
- Brier Loss: 0.2243
- Nll: 1.0945
- F1 Micro: 0.8788
- F1 Macro: 0.8793
- Ece: 0.1094
- Aurc: 0.0303

## 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: 2
- eval_batch_size: 2
- 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   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| 0.1996        | 1.0   | 8000  | 0.2395          | 0.8413   | 0.2593     | 1.3668 | 0.8413   | 0.8446   | 0.1016 | 0.0414 |
| 0.1357        | 2.0   | 16000 | 0.2446          | 0.8545   | 0.2435     | 1.2587 | 0.8545   | 0.8550   | 0.1066 | 0.0364 |
| 0.1083        | 3.0   | 24000 | 0.2702          | 0.8515   | 0.2584     | 1.2968 | 0.8515   | 0.8528   | 0.1126 | 0.0379 |
| 0.0578        | 4.0   | 32000 | 0.3397          | 0.8327   | 0.2931     | 1.3827 | 0.8327   | 0.8322   | 0.1391 | 0.0494 |
| 0.0294        | 5.0   | 40000 | 0.3407          | 0.8538   | 0.2662     | 1.3685 | 0.8537   | 0.8536   | 0.1280 | 0.0378 |
| 0.0099        | 6.0   | 48000 | 0.3489          | 0.8585   | 0.2602     | 1.2438 | 0.8585   | 0.8599   | 0.1254 | 0.0350 |
| 0.0058        | 7.0   | 56000 | 0.3433          | 0.868    | 0.2418     | 1.2328 | 0.868    | 0.8666   | 0.1172 | 0.0362 |
| 0.0026        | 8.0   | 64000 | 0.3414          | 0.87     | 0.2401     | 1.1910 | 0.87     | 0.8704   | 0.1162 | 0.0304 |
| 0.0026        | 9.0   | 72000 | 0.3460          | 0.8728   | 0.2357     | 1.1567 | 0.8728   | 0.8729   | 0.1143 | 0.0308 |
| 0.0024        | 10.0  | 80000 | 0.3354          | 0.8788   | 0.2243     | 1.0945 | 0.8788   | 0.8793   | 0.1094 | 0.0303 |


### Framework versions

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

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