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# swin-tiny-patch4-window7-224-ve-U13-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: 0.9190
- Accuracy: 0.8043

## 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    | 1.3859          | 0.1304   |
| 1.3859        | 2.0   | 13   | 1.3828          | 0.2826   |
| 1.3859        | 2.92  | 19   | 1.3769          | 0.3261   |
| 1.379         | 4.0   | 26   | 1.3566          | 0.2826   |
| 1.3356        | 4.92  | 32   | 1.3162          | 0.2391   |
| 1.3356        | 6.0   | 39   | 1.2093          | 0.3478   |
| 1.2023        | 6.92  | 45   | 1.1349          | 0.4565   |
| 1.0274        | 8.0   | 52   | 1.0414          | 0.4783   |
| 1.0274        | 8.92  | 58   | 0.9788          | 0.5217   |
| 0.9125        | 10.0  | 65   | 1.0071          | 0.4348   |
| 0.7688        | 10.92 | 71   | 1.0416          | 0.5217   |
| 0.7688        | 12.0  | 78   | 1.0480          | 0.4130   |
| 0.6891        | 12.92 | 84   | 0.9351          | 0.5870   |
| 0.5795        | 14.0  | 91   | 1.0683          | 0.6304   |
| 0.5795        | 14.92 | 97   | 1.0698          | 0.6087   |
| 0.5337        | 16.0  | 104  | 0.9603          | 0.6304   |
| 0.4337        | 16.92 | 110  | 0.7188          | 0.6957   |
| 0.4337        | 18.0  | 117  | 0.7620          | 0.6739   |
| 0.4258        | 18.92 | 123  | 0.9433          | 0.6739   |
| 0.4045        | 20.0  | 130  | 1.0823          | 0.6522   |
| 0.4045        | 20.92 | 136  | 0.7059          | 0.7174   |
| 0.4135        | 22.0  | 143  | 0.7467          | 0.7391   |
| 0.4135        | 22.92 | 149  | 0.7637          | 0.7391   |
| 0.3525        | 24.0  | 156  | 0.8157          | 0.7391   |
| 0.263         | 24.92 | 162  | 0.9995          | 0.7174   |
| 0.263         | 26.0  | 169  | 0.8719          | 0.7609   |
| 0.272         | 26.92 | 175  | 0.9939          | 0.6957   |
| 0.262         | 28.0  | 182  | 0.8639          | 0.7174   |
| 0.262         | 28.92 | 188  | 1.0737          | 0.6522   |
| 0.2282        | 30.0  | 195  | 0.8416          | 0.7174   |
| 0.2098        | 30.92 | 201  | 0.9744          | 0.6739   |
| 0.2098        | 32.0  | 208  | 1.0593          | 0.6087   |
| 0.2141        | 32.92 | 214  | 1.0997          | 0.7174   |
| 0.1759        | 34.0  | 221  | 0.9735          | 0.5870   |
| 0.1759        | 34.92 | 227  | 1.0789          | 0.6957   |
| 0.2042        | 36.0  | 234  | 1.0664          | 0.6957   |
| 0.1591        | 36.92 | 240  | 0.9417          | 0.7609   |
| 0.1591        | 38.0  | 247  | 1.1042          | 0.6739   |
| 0.1579        | 38.92 | 253  | 0.9732          | 0.7609   |
| 0.1626        | 40.0  | 260  | 0.9960          | 0.6957   |
| 0.1626        | 40.92 | 266  | 0.9763          | 0.7391   |
| 0.1458        | 42.0  | 273  | 0.9790          | 0.7391   |
| 0.1458        | 42.92 | 279  | 1.0952          | 0.7174   |
| 0.1317        | 44.0  | 286  | 0.9190          | 0.8043   |
| 0.1255        | 44.92 | 292  | 0.9420          | 0.7391   |
| 0.1255        | 46.0  | 299  | 0.9085          | 0.7391   |
| 0.1352        | 46.92 | 305  | 0.9184          | 0.7174   |
| 0.1311        | 48.0  | 312  | 1.0567          | 0.7609   |
| 0.1311        | 48.92 | 318  | 1.1507          | 0.7174   |
| 0.1501        | 50.0  | 325  | 1.2068          | 0.7174   |
| 0.1088        | 50.92 | 331  | 1.4607          | 0.6957   |
| 0.1088        | 52.0  | 338  | 1.1036          | 0.6739   |
| 0.1152        | 52.92 | 344  | 1.1081          | 0.6957   |
| 0.1141        | 54.0  | 351  | 1.1006          | 0.6957   |
| 0.1141        | 54.92 | 357  | 1.1470          | 0.7174   |
| 0.1307        | 56.0  | 364  | 1.0715          | 0.7609   |
| 0.1273        | 56.92 | 370  | 1.1021          | 0.7174   |
| 0.1273        | 58.0  | 377  | 1.1176          | 0.6957   |
| 0.1066        | 58.92 | 383  | 1.0948          | 0.7174   |
| 0.1046        | 60.0  | 390  | 1.0563          | 0.7391   |
| 0.1046        | 60.92 | 396  | 1.1155          | 0.6957   |
| 0.1129        | 62.0  | 403  | 1.0922          | 0.6957   |
| 0.1129        | 62.92 | 409  | 1.0364          | 0.6957   |
| 0.1031        | 64.0  | 416  | 1.0675          | 0.7174   |
| 0.0808        | 64.92 | 422  | 1.1133          | 0.6957   |
| 0.0808        | 66.0  | 429  | 1.2029          | 0.7174   |
| 0.0783        | 66.92 | 435  | 1.1453          | 0.7174   |
| 0.09          | 68.0  | 442  | 1.0925          | 0.6957   |
| 0.09          | 68.92 | 448  | 1.0999          | 0.7174   |
| 0.0796        | 70.0  | 455  | 1.0971          | 0.7391   |
| 0.0828        | 70.92 | 461  | 1.0923          | 0.7391   |
| 0.0828        | 72.0  | 468  | 1.1061          | 0.7391   |
| 0.0923        | 72.92 | 474  | 1.1173          | 0.7391   |
| 0.092         | 73.85 | 480  | 1.1208          | 0.7391   |


### Framework versions

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

avanzada leve moderada no dmae