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# swinv2-tiny-patch4-window8-256-ve-U13-b-80

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7882
- Accuracy: 0.7391

## 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    | 1.3858          | 0.1304   |
| 1.3856        | 2.0   | 13   | 1.3777          | 0.3696   |
| 1.3856        | 2.92  | 19   | 1.3488          | 0.2391   |
| 1.361         | 4.0   | 26   | 1.2503          | 0.2826   |
| 1.2088        | 4.92  | 32   | 1.1317          | 0.4130   |
| 1.2088        | 6.0   | 39   | 1.0244          | 0.4565   |
| 1.0729        | 6.92  | 45   | 1.0413          | 0.4565   |
| 0.9554        | 8.0   | 52   | 0.9286          | 0.5652   |
| 0.9554        | 8.92  | 58   | 0.9103          | 0.5652   |
| 0.8221        | 10.0  | 65   | 0.8519          | 0.6522   |
| 0.732         | 10.92 | 71   | 0.8300          | 0.5870   |
| 0.732         | 12.0  | 78   | 0.8103          | 0.6304   |
| 0.6491        | 12.92 | 84   | 0.9533          | 0.5870   |
| 0.5724        | 14.0  | 91   | 0.7882          | 0.7391   |
| 0.5724        | 14.92 | 97   | 0.8072          | 0.6957   |
| 0.5305        | 16.0  | 104  | 0.7651          | 0.7391   |
| 0.4879        | 16.92 | 110  | 0.7379          | 0.7174   |
| 0.4879        | 18.0  | 117  | 0.7590          | 0.6739   |
| 0.4346        | 18.92 | 123  | 0.9283          | 0.6739   |
| 0.3671        | 20.0  | 130  | 1.0188          | 0.6304   |
| 0.3671        | 20.92 | 136  | 0.8959          | 0.7391   |
| 0.3725        | 22.0  | 143  | 0.9502          | 0.6957   |
| 0.3725        | 22.92 | 149  | 0.9627          | 0.6522   |
| 0.3321        | 24.0  | 156  | 0.9619          | 0.6957   |
| 0.3376        | 24.92 | 162  | 1.0459          | 0.6739   |
| 0.3376        | 26.0  | 169  | 1.0167          | 0.6522   |
| 0.3699        | 26.92 | 175  | 0.9949          | 0.6304   |
| 0.3098        | 28.0  | 182  | 0.9944          | 0.6739   |
| 0.3098        | 28.92 | 188  | 1.0860          | 0.6304   |
| 0.253         | 30.0  | 195  | 1.1721          | 0.6522   |
| 0.2615        | 30.92 | 201  | 1.1626          | 0.6739   |
| 0.2615        | 32.0  | 208  | 1.2464          | 0.6304   |
| 0.242         | 32.92 | 214  | 1.2179          | 0.6522   |
| 0.2173        | 34.0  | 221  | 1.2407          | 0.6304   |
| 0.2173        | 34.92 | 227  | 1.1585          | 0.6739   |
| 0.2305        | 36.0  | 234  | 1.3048          | 0.6522   |
| 0.2114        | 36.92 | 240  | 1.1776          | 0.6522   |
| 0.2114        | 38.0  | 247  | 1.1460          | 0.6522   |
| 0.2243        | 38.92 | 253  | 1.2424          | 0.6957   |
| 0.1822        | 40.0  | 260  | 1.2804          | 0.6739   |
| 0.1822        | 40.92 | 266  | 1.3472          | 0.6739   |
| 0.2065        | 42.0  | 273  | 1.3632          | 0.6739   |
| 0.2065        | 42.92 | 279  | 1.2832          | 0.6739   |
| 0.1942        | 44.0  | 286  | 1.3500          | 0.6739   |
| 0.1699        | 44.92 | 292  | 1.3242          | 0.6739   |
| 0.1699        | 46.0  | 299  | 1.3189          | 0.6957   |
| 0.1764        | 46.92 | 305  | 1.2840          | 0.6739   |
| 0.1771        | 48.0  | 312  | 1.3069          | 0.6957   |
| 0.1771        | 48.92 | 318  | 1.1585          | 0.6957   |
| 0.2095        | 50.0  | 325  | 1.3702          | 0.6957   |
| 0.1404        | 50.92 | 331  | 1.3539          | 0.6957   |
| 0.1404        | 52.0  | 338  | 1.3723          | 0.6957   |
| 0.1449        | 52.92 | 344  | 1.3877          | 0.6957   |
| 0.1348        | 54.0  | 351  | 1.3381          | 0.6739   |
| 0.1348        | 54.92 | 357  | 1.3700          | 0.6739   |
| 0.1683        | 56.0  | 364  | 1.2871          | 0.6957   |
| 0.1577        | 56.92 | 370  | 1.3214          | 0.6957   |
| 0.1577        | 58.0  | 377  | 1.3992          | 0.6522   |
| 0.1474        | 58.92 | 383  | 1.3800          | 0.6522   |
| 0.1267        | 60.0  | 390  | 1.2535          | 0.6739   |
| 0.1267        | 60.92 | 396  | 1.3200          | 0.6739   |
| 0.1171        | 62.0  | 403  | 1.3730          | 0.6739   |
| 0.1171        | 62.92 | 409  | 1.3678          | 0.6739   |
| 0.1461        | 64.0  | 416  | 1.3788          | 0.6739   |
| 0.1124        | 64.92 | 422  | 1.3944          | 0.6739   |
| 0.1124        | 66.0  | 429  | 1.3724          | 0.6739   |
| 0.1168        | 66.92 | 435  | 1.3553          | 0.6522   |
| 0.1243        | 68.0  | 442  | 1.3829          | 0.6739   |
| 0.1243        | 68.92 | 448  | 1.4040          | 0.6739   |
| 0.1375        | 70.0  | 455  | 1.4127          | 0.6522   |
| 0.1017        | 70.92 | 461  | 1.4070          | 0.6522   |
| 0.1017        | 72.0  | 468  | 1.3989          | 0.6739   |
| 0.1346        | 72.92 | 474  | 1.3995          | 0.6739   |
| 0.1382        | 73.85 | 480  | 1.3988          | 0.6739   |


### Framework versions

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

avanzada leve moderada no dmae