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# vit-base-patch16-224-ve-U15-b-80

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5357
- Accuracy: 0.8696

## 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: 5.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.05
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.97  | 7    | 1.3872          | 0.1304   |
| 1.3844        | 1.93  | 14   | 1.3826          | 0.1739   |
| 1.3552        | 2.9   | 21   | 1.3500          | 0.2391   |
| 1.3552        | 4.0   | 29   | 1.2528          | 0.2174   |
| 1.2458        | 4.97  | 36   | 1.1474          | 0.2391   |
| 1.0668        | 5.93  | 43   | 1.1376          | 0.3913   |
| 0.9335        | 6.9   | 50   | 1.0063          | 0.4348   |
| 0.9335        | 8.0   | 58   | 0.9238          | 0.5870   |
| 0.8059        | 8.97  | 65   | 0.8241          | 0.8043   |
| 0.6774        | 9.93  | 72   | 0.7625          | 0.7826   |
| 0.6774        | 10.9  | 79   | 0.7096          | 0.8043   |
| 0.5346        | 12.0  | 87   | 0.6368          | 0.8261   |
| 0.4427        | 12.97 | 94   | 0.5741          | 0.8261   |
| 0.3557        | 13.93 | 101  | 0.5441          | 0.8261   |
| 0.3557        | 14.9  | 108  | 0.5258          | 0.8478   |
| 0.2637        | 16.0  | 116  | 0.5430          | 0.8261   |
| 0.2356        | 16.97 | 123  | 0.5773          | 0.8261   |
| 0.1844        | 17.93 | 130  | 0.7222          | 0.7391   |
| 0.1844        | 18.9  | 137  | 0.6537          | 0.7826   |
| 0.1765        | 20.0  | 145  | 0.5458          | 0.8043   |
| 0.1362        | 20.97 | 152  | 0.5777          | 0.8478   |
| 0.1362        | 21.93 | 159  | 0.6256          | 0.7826   |
| 0.1467        | 22.9  | 166  | 0.7330          | 0.7826   |
| 0.1614        | 24.0  | 174  | 0.7743          | 0.7609   |
| 0.1246        | 24.97 | 181  | 0.5763          | 0.8261   |
| 0.1246        | 25.93 | 188  | 0.5994          | 0.8261   |
| 0.1058        | 26.9  | 195  | 0.6926          | 0.8043   |
| 0.0943        | 28.0  | 203  | 0.6406          | 0.8478   |
| 0.1           | 28.97 | 210  | 0.6940          | 0.7609   |
| 0.1           | 29.93 | 217  | 0.6193          | 0.8261   |
| 0.0865        | 30.9  | 224  | 0.5357          | 0.8696   |
| 0.0852        | 32.0  | 232  | 0.8015          | 0.7826   |
| 0.0852        | 32.97 | 239  | 0.6680          | 0.8478   |
| 0.0721        | 33.93 | 246  | 0.8469          | 0.7826   |
| 0.0749        | 34.9  | 253  | 0.6682          | 0.8261   |
| 0.0876        | 36.0  | 261  | 0.7474          | 0.8261   |
| 0.0876        | 36.97 | 268  | 0.6501          | 0.8696   |
| 0.0677        | 37.93 | 275  | 0.6918          | 0.8043   |
| 0.0574        | 38.9  | 282  | 0.7001          | 0.8478   |
| 0.0573        | 40.0  | 290  | 0.7119          | 0.8261   |
| 0.0573        | 40.97 | 297  | 0.8317          | 0.8043   |
| 0.0663        | 41.93 | 304  | 0.7456          | 0.8043   |
| 0.0685        | 42.9  | 311  | 0.7242          | 0.8261   |
| 0.0685        | 44.0  | 319  | 0.6971          | 0.8043   |
| 0.0431        | 44.97 | 326  | 0.7439          | 0.8261   |
| 0.0529        | 45.93 | 333  | 0.8210          | 0.8043   |
| 0.0698        | 46.9  | 340  | 0.7114          | 0.8043   |
| 0.0698        | 48.0  | 348  | 0.6985          | 0.8478   |
| 0.054         | 48.97 | 355  | 0.8860          | 0.8261   |
| 0.0528        | 49.93 | 362  | 0.8942          | 0.8043   |
| 0.0528        | 50.9  | 369  | 0.9411          | 0.8043   |
| 0.0478        | 52.0  | 377  | 0.8705          | 0.7826   |
| 0.041         | 52.97 | 384  | 0.8130          | 0.8261   |
| 0.0321        | 53.93 | 391  | 0.7682          | 0.8043   |
| 0.0321        | 54.9  | 398  | 0.8696          | 0.7826   |
| 0.0318        | 56.0  | 406  | 0.9598          | 0.8043   |
| 0.0416        | 56.97 | 413  | 0.7291          | 0.8261   |
| 0.0477        | 57.93 | 420  | 0.6869          | 0.8478   |
| 0.0477        | 58.9  | 427  | 0.7055          | 0.8478   |
| 0.0307        | 60.0  | 435  | 0.7415          | 0.8478   |
| 0.032         | 60.97 | 442  | 0.8024          | 0.8261   |
| 0.032         | 61.93 | 449  | 0.7856          | 0.8478   |
| 0.0232        | 62.9  | 456  | 0.7251          | 0.8043   |
| 0.0267        | 64.0  | 464  | 0.7231          | 0.8478   |
| 0.0456        | 64.97 | 471  | 0.7326          | 0.8696   |
| 0.0456        | 65.93 | 478  | 0.7300          | 0.8696   |
| 0.0359        | 66.9  | 485  | 0.7293          | 0.8696   |
| 0.0199        | 68.0  | 493  | 0.7361          | 0.8696   |
| 0.0235        | 68.97 | 500  | 0.7362          | 0.8696   |
| 0.0235        | 69.93 | 507  | 0.7513          | 0.8696   |
| 0.0368        | 70.9  | 514  | 0.7513          | 0.8696   |
| 0.0254        | 72.0  | 522  | 0.7586          | 0.8696   |
| 0.0254        | 72.97 | 529  | 0.7574          | 0.8696   |
| 0.029         | 73.93 | 536  | 0.7685          | 0.8478   |
| 0.0302        | 74.9  | 543  | 0.7653          | 0.8478   |
| 0.0305        | 76.0  | 551  | 0.7637          | 0.8261   |
| 0.0305        | 76.97 | 558  | 0.7645          | 0.8478   |
| 0.0301        | 77.24 | 560  | 0.7645          | 0.8478   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0

avanzada leve moderada no dmae