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# vit-base_rvl_cdip-N1K_ce_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: 1.1280
- Accuracy: 0.871
- Brier Loss: 0.2424
- Nll: 1.0979
- F1 Micro: 0.871
- F1 Macro: 0.8714
- Ece: 0.1202
- Aurc: 0.0321

## 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   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| 0.6617        | 1.0   | 8000  | 0.8187          | 0.8305   | 0.2858     | 1.3679 | 0.8305   | 0.8317   | 0.1182 | 0.0482 |
| 0.4446        | 2.0   | 16000 | 0.7450          | 0.8598   | 0.2427     | 1.2010 | 0.8598   | 0.8593   | 0.1100 | 0.0344 |
| 0.3853        | 3.0   | 24000 | 0.9422          | 0.8452   | 0.2771     | 1.3313 | 0.8452   | 0.8459   | 0.1288 | 0.0413 |
| 0.2259        | 4.0   | 32000 | 0.9828          | 0.8498   | 0.2702     | 1.3463 | 0.8498   | 0.8475   | 0.1267 | 0.0426 |
| 0.1824        | 5.0   | 40000 | 1.0204          | 0.8578   | 0.2603     | 1.2439 | 0.8578   | 0.8580   | 0.1263 | 0.0369 |
| 0.0343        | 6.0   | 48000 | 1.1306          | 0.8532   | 0.2716     | 1.1966 | 0.8532   | 0.8533   | 0.1340 | 0.0367 |
| 0.0288        | 7.0   | 56000 | 1.1081          | 0.8638   | 0.2552     | 1.2206 | 0.8638   | 0.8642   | 0.1243 | 0.0345 |
| 0.0122        | 8.0   | 64000 | 1.1533          | 0.8625   | 0.2579     | 1.2019 | 0.8625   | 0.8620   | 0.1260 | 0.0348 |
| 0.004         | 9.0   | 72000 | 1.1360          | 0.868    | 0.2487     | 1.0798 | 0.868    | 0.8691   | 0.1228 | 0.0330 |
| 0.0027        | 10.0  | 80000 | 1.1280          | 0.871    | 0.2424     | 1.0979 | 0.871    | 0.8714   | 0.1202 | 0.0321 |


### Framework versions

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

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