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# vit-base_rvl_cdip_entropy2_softmax

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: 0.8809
- Accuracy: 0.8968
- Brier Loss: 0.1890
- Nll: 1.1526
- F1 Micro: 0.8968
- F1 Macro: 0.8969
- Ece: 0.0923
- Aurc: 0.0205

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| 0.3547        | 1.0   | 2500  | 0.7036          | 0.8958   | 0.1806     | 0.9568 | 0.8958   | 0.8955   | 0.0815 | 0.0174 |
| 0.3049        | 2.0   | 5000  | 0.7030          | 0.8972   | 0.1784     | 1.0077 | 0.8972   | 0.8975   | 0.0825 | 0.0168 |
| 0.2103        | 3.0   | 7500  | 0.7465          | 0.8946   | 0.1857     | 1.0229 | 0.8946   | 0.8954   | 0.0883 | 0.0178 |
| 0.1548        | 4.0   | 10000 | 0.7640          | 0.8957   | 0.1860     | 1.0530 | 0.8957   | 0.8960   | 0.0893 | 0.0182 |
| 0.1077        | 5.0   | 12500 | 0.7964          | 0.8955   | 0.1877     | 1.0743 | 0.8955   | 0.8955   | 0.0903 | 0.0182 |
| 0.0742        | 6.0   | 15000 | 0.8253          | 0.8959   | 0.1887     | 1.0996 | 0.8959   | 0.8967   | 0.0919 | 0.0202 |
| 0.0495        | 7.0   | 17500 | 0.8505          | 0.8964   | 0.1884     | 1.1281 | 0.8964   | 0.8963   | 0.0920 | 0.0201 |
| 0.0352        | 8.0   | 20000 | 0.8645          | 0.8964   | 0.1895     | 1.1397 | 0.8964   | 0.8964   | 0.0931 | 0.0207 |
| 0.0235        | 9.0   | 22500 | 0.8733          | 0.8984   | 0.1876     | 1.1365 | 0.8984   | 0.8986   | 0.0914 | 0.0204 |
| 0.0176        | 10.0  | 25000 | 0.8809          | 0.8968   | 0.1890     | 1.1526 | 0.8968   | 0.8969   | 0.0923 | 0.0205 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2

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