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# swin-tiny-patch4-window7-224-ve-U13-b-80b

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: 0.6122
- 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: 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        | 0.92  | 6    | 1.3855          | 0.1304   |
| 1.3852        | 2.0   | 13   | 1.3762          | 0.2826   |
| 1.3852        | 2.92  | 19   | 1.3521          | 0.2826   |
| 1.3565        | 4.0   | 26   | 1.2510          | 0.3478   |
| 1.2024        | 4.92  | 32   | 1.1528          | 0.3478   |
| 1.2024        | 6.0   | 39   | 1.0294          | 0.5      |
| 1.0453        | 6.92  | 45   | 0.9608          | 0.5217   |
| 0.8827        | 8.0   | 52   | 0.8801          | 0.6087   |
| 0.8827        | 8.92  | 58   | 0.9884          | 0.5652   |
| 0.7887        | 10.0  | 65   | 0.7927          | 0.6522   |
| 0.6795        | 10.92 | 71   | 0.7237          | 0.6522   |
| 0.6795        | 12.0  | 78   | 0.7250          | 0.6739   |
| 0.5777        | 12.92 | 84   | 0.7140          | 0.6957   |
| 0.496         | 14.0  | 91   | 0.8014          | 0.6957   |
| 0.496         | 14.92 | 97   | 0.8701          | 0.6739   |
| 0.4224        | 16.0  | 104  | 0.9384          | 0.6522   |
| 0.3744        | 16.92 | 110  | 0.7594          | 0.7174   |
| 0.3744        | 18.0  | 117  | 0.6122          | 0.7826   |
| 0.3775        | 18.92 | 123  | 0.8143          | 0.7174   |
| 0.3275        | 20.0  | 130  | 0.9981          | 0.6522   |
| 0.3275        | 20.92 | 136  | 0.8603          | 0.7174   |
| 0.3202        | 22.0  | 143  | 0.8412          | 0.6957   |
| 0.3202        | 22.92 | 149  | 0.8654          | 0.7174   |
| 0.2849        | 24.0  | 156  | 0.9650          | 0.6957   |
| 0.2518        | 24.92 | 162  | 0.8102          | 0.7609   |
| 0.2518        | 26.0  | 169  | 0.7203          | 0.7826   |
| 0.2467        | 26.92 | 175  | 0.9435          | 0.7391   |
| 0.2218        | 28.0  | 182  | 0.8905          | 0.7391   |
| 0.2218        | 28.92 | 188  | 1.0828          | 0.6957   |
| 0.2075        | 30.0  | 195  | 0.8936          | 0.7174   |
| 0.1893        | 30.92 | 201  | 0.8836          | 0.7826   |
| 0.1893        | 32.0  | 208  | 0.9692          | 0.7174   |
| 0.194         | 32.92 | 214  | 1.0390          | 0.7609   |
| 0.1739        | 34.0  | 221  | 0.8695          | 0.7609   |
| 0.1739        | 34.92 | 227  | 1.1836          | 0.6739   |
| 0.1895        | 36.0  | 234  | 1.0131          | 0.7391   |
| 0.1428        | 36.92 | 240  | 0.9618          | 0.7609   |
| 0.1428        | 38.0  | 247  | 0.9950          | 0.7609   |
| 0.1443        | 38.92 | 253  | 0.9113          | 0.7826   |
| 0.1574        | 40.0  | 260  | 0.9213          | 0.7174   |
| 0.1574        | 40.92 | 266  | 0.9437          | 0.7391   |
| 0.1442        | 42.0  | 273  | 0.9226          | 0.7609   |
| 0.1442        | 42.92 | 279  | 0.9430          | 0.7391   |
| 0.1186        | 44.0  | 286  | 0.9759          | 0.7826   |
| 0.1135        | 44.92 | 292  | 0.9651          | 0.7391   |
| 0.1135        | 46.0  | 299  | 0.9536          | 0.7609   |
| 0.1299        | 46.92 | 305  | 0.9118          | 0.7609   |
| 0.134         | 48.0  | 312  | 0.9848          | 0.7826   |
| 0.134         | 48.92 | 318  | 0.8641          | 0.7609   |
| 0.1418        | 50.0  | 325  | 1.0553          | 0.7609   |
| 0.1074        | 50.92 | 331  | 1.2511          | 0.6957   |
| 0.1074        | 52.0  | 338  | 1.0186          | 0.7391   |
| 0.1144        | 52.92 | 344  | 1.0467          | 0.7174   |
| 0.0999        | 54.0  | 351  | 0.9898          | 0.7391   |
| 0.0999        | 54.92 | 357  | 1.1780          | 0.7391   |
| 0.1131        | 56.0  | 364  | 1.0015          | 0.7609   |
| 0.1152        | 56.92 | 370  | 1.0759          | 0.7609   |
| 0.1152        | 58.0  | 377  | 1.1294          | 0.7174   |
| 0.1012        | 58.92 | 383  | 1.0894          | 0.7391   |
| 0.0938        | 60.0  | 390  | 1.0764          | 0.7391   |
| 0.0938        | 60.92 | 396  | 1.1784          | 0.7174   |
| 0.0944        | 62.0  | 403  | 1.1581          | 0.7174   |
| 0.0944        | 62.92 | 409  | 1.0444          | 0.7391   |
| 0.1015        | 64.0  | 416  | 1.0996          | 0.7391   |
| 0.0762        | 64.92 | 422  | 1.1235          | 0.7609   |
| 0.0762        | 66.0  | 429  | 1.0999          | 0.7391   |
| 0.0775        | 66.92 | 435  | 1.0776          | 0.7391   |
| 0.0787        | 68.0  | 442  | 1.0879          | 0.7391   |
| 0.0787        | 68.92 | 448  | 1.0913          | 0.7391   |
| 0.081         | 70.0  | 455  | 1.0558          | 0.7391   |
| 0.0749        | 70.92 | 461  | 1.0401          | 0.7391   |
| 0.0749        | 72.0  | 468  | 1.0539          | 0.7391   |
| 0.0841        | 72.92 | 474  | 1.0663          | 0.7391   |
| 0.0928        | 73.85 | 480  | 1.0712          | 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