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# swin-tiny-patch4-window7-224-ve-U11-b-80

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7088
- Accuracy: 0.7826

## 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: 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: 0.1
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3860          | 0.1304   |
| 1.3859        | 2.0   | 13   | 1.3832          | 0.2609   |
| 1.3859        | 2.92  | 19   | 1.3773          | 0.2609   |
| 1.3791        | 4.0   | 26   | 1.3569          | 0.2174   |
| 1.3347        | 4.92  | 32   | 1.3177          | 0.2609   |
| 1.3347        | 6.0   | 39   | 1.2093          | 0.3913   |
| 1.2088        | 6.92  | 45   | 1.1083          | 0.4348   |
| 1.0456        | 8.0   | 52   | 1.0340          | 0.4565   |
| 1.0456        | 8.92  | 58   | 1.0120          | 0.5      |
| 0.9278        | 10.0  | 65   | 0.9282          | 0.5652   |
| 0.847         | 10.92 | 71   | 0.9934          | 0.5217   |
| 0.847         | 12.0  | 78   | 1.0171          | 0.4783   |
| 0.7142        | 12.92 | 84   | 0.8889          | 0.5870   |
| 0.5959        | 14.0  | 91   | 0.9392          | 0.5870   |
| 0.5959        | 14.92 | 97   | 0.9018          | 0.6304   |
| 0.5344        | 16.0  | 104  | 0.8327          | 0.6739   |
| 0.4438        | 16.92 | 110  | 0.7308          | 0.7391   |
| 0.4438        | 18.0  | 117  | 0.6834          | 0.7174   |
| 0.4419        | 18.92 | 123  | 0.7909          | 0.6304   |
| 0.3989        | 20.0  | 130  | 0.9103          | 0.6739   |
| 0.3989        | 20.92 | 136  | 0.7534          | 0.7391   |
| 0.3534        | 22.0  | 143  | 0.8043          | 0.7391   |
| 0.3534        | 22.92 | 149  | 0.7648          | 0.7174   |
| 0.3265        | 24.0  | 156  | 0.7088          | 0.7826   |
| 0.2808        | 24.92 | 162  | 0.8845          | 0.6957   |
| 0.2808        | 26.0  | 169  | 0.7756          | 0.7609   |
| 0.2753        | 26.92 | 175  | 0.9944          | 0.6087   |
| 0.2837        | 28.0  | 182  | 0.8091          | 0.7174   |
| 0.2837        | 28.92 | 188  | 0.9966          | 0.6739   |
| 0.2667        | 30.0  | 195  | 0.7711          | 0.7826   |
| 0.2325        | 30.92 | 201  | 0.8946          | 0.6957   |
| 0.2325        | 32.0  | 208  | 0.9079          | 0.6739   |
| 0.2096        | 32.92 | 214  | 1.0338          | 0.6522   |
| 0.1733        | 34.0  | 221  | 0.8191          | 0.7391   |
| 0.1733        | 34.92 | 227  | 1.0068          | 0.6957   |
| 0.1975        | 36.0  | 234  | 0.8644          | 0.7174   |
| 0.1844        | 36.92 | 240  | 0.8682          | 0.6739   |
| 0.1844        | 38.0  | 247  | 0.7915          | 0.7609   |
| 0.1701        | 38.92 | 253  | 0.7554          | 0.7609   |
| 0.1696        | 40.0  | 260  | 0.8762          | 0.7174   |
| 0.1696        | 40.92 | 266  | 1.0173          | 0.6739   |
| 0.1556        | 42.0  | 273  | 0.9080          | 0.7174   |
| 0.1556        | 42.92 | 279  | 1.2456          | 0.6739   |
| 0.153         | 44.0  | 286  | 0.9820          | 0.7391   |
| 0.1343        | 44.92 | 292  | 0.9908          | 0.7174   |
| 0.1343        | 46.0  | 299  | 0.9435          | 0.7391   |
| 0.1513        | 46.92 | 305  | 0.8842          | 0.7826   |
| 0.1402        | 48.0  | 312  | 1.0207          | 0.6739   |
| 0.1402        | 48.92 | 318  | 0.9915          | 0.7174   |
| 0.1648        | 50.0  | 325  | 1.1576          | 0.6739   |
| 0.1047        | 50.92 | 331  | 1.2283          | 0.6739   |
| 0.1047        | 52.0  | 338  | 1.0869          | 0.6957   |
| 0.1223        | 52.92 | 344  | 1.1203          | 0.7174   |
| 0.1223        | 54.0  | 351  | 0.9685          | 0.7174   |
| 0.1223        | 54.92 | 357  | 1.1926          | 0.7174   |
| 0.1236        | 56.0  | 364  | 1.0088          | 0.7174   |
| 0.1115        | 56.92 | 370  | 0.9149          | 0.7391   |
| 0.1115        | 58.0  | 377  | 0.8820          | 0.7391   |
| 0.1173        | 58.92 | 383  | 0.9653          | 0.7391   |
| 0.102         | 60.0  | 390  | 1.0046          | 0.7174   |
| 0.102         | 60.92 | 396  | 1.0585          | 0.6957   |
| 0.1206        | 62.0  | 403  | 1.0490          | 0.6957   |
| 0.1206        | 62.92 | 409  | 0.9683          | 0.7609   |
| 0.1124        | 64.0  | 416  | 0.9627          | 0.7609   |
| 0.0927        | 64.92 | 422  | 0.9771          | 0.7609   |
| 0.0927        | 66.0  | 429  | 1.0002          | 0.7174   |
| 0.0906        | 66.92 | 435  | 0.9607          | 0.7391   |
| 0.084         | 68.0  | 442  | 0.9414          | 0.7391   |
| 0.084         | 68.92 | 448  | 0.9863          | 0.7174   |
| 0.0866        | 70.0  | 455  | 0.9930          | 0.7174   |
| 0.0944        | 70.92 | 461  | 0.9981          | 0.7174   |
| 0.0944        | 72.0  | 468  | 1.0039          | 0.7174   |
| 0.1064        | 72.92 | 474  | 0.9987          | 0.7174   |
| 0.1074        | 73.85 | 480  | 0.9964          | 0.7174   |


### Framework versions

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

avanzada leve moderada no dmae