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

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: 0.7710
- 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: 4e-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    | 1.6333          | 0.1087   |
| 1.4981        | 2.0   | 13   | 1.6225          | 0.1087   |
| 1.4981        | 2.92  | 19   | 1.5921          | 0.1087   |
| 1.4704        | 4.0   | 26   | 1.5001          | 0.1087   |
| 1.4116        | 4.92  | 32   | 1.4078          | 0.1087   |
| 1.4116        | 6.0   | 39   | 1.2960          | 0.3478   |
| 1.3094        | 6.92  | 45   | 1.2926          | 0.3043   |
| 1.2014        | 8.0   | 52   | 1.1532          | 0.5435   |
| 1.2014        | 8.92  | 58   | 1.1059          | 0.4783   |
| 1.0577        | 10.0  | 65   | 0.9510          | 0.6304   |
| 0.9185        | 10.92 | 71   | 0.9695          | 0.4783   |
| 0.9185        | 12.0  | 78   | 0.8792          | 0.6087   |
| 0.8369        | 12.92 | 84   | 0.8616          | 0.6957   |
| 0.7406        | 14.0  | 91   | 0.7816          | 0.6957   |
| 0.7406        | 14.92 | 97   | 0.7638          | 0.7609   |
| 0.6929        | 16.0  | 104  | 0.7710          | 0.7826   |
| 0.6192        | 16.92 | 110  | 0.7471          | 0.6957   |
| 0.6192        | 18.0  | 117  | 0.7265          | 0.7391   |
| 0.5936        | 18.92 | 123  | 0.7841          | 0.7609   |
| 0.5125        | 20.0  | 130  | 0.9320          | 0.6739   |
| 0.5125        | 20.92 | 136  | 0.7512          | 0.7609   |
| 0.4905        | 22.0  | 143  | 0.7466          | 0.6957   |
| 0.4905        | 22.92 | 149  | 0.8030          | 0.6957   |
| 0.4315        | 24.0  | 156  | 0.8184          | 0.7391   |
| 0.4272        | 24.92 | 162  | 0.8196          | 0.6957   |
| 0.4272        | 26.0  | 169  | 0.8712          | 0.6957   |
| 0.4261        | 26.92 | 175  | 0.7834          | 0.6957   |
| 0.4217        | 28.0  | 182  | 0.8394          | 0.6739   |
| 0.4217        | 28.92 | 188  | 0.9941          | 0.6739   |
| 0.3502        | 30.0  | 195  | 0.8909          | 0.7174   |
| 0.368         | 30.92 | 201  | 0.9995          | 0.7174   |
| 0.368         | 32.0  | 208  | 0.9418          | 0.6739   |
| 0.3473        | 32.92 | 214  | 0.8595          | 0.6739   |
| 0.3079        | 34.0  | 221  | 0.9562          | 0.6957   |
| 0.3079        | 34.92 | 227  | 0.8992          | 0.6739   |
| 0.3226        | 36.0  | 234  | 0.9908          | 0.6739   |
| 0.2603        | 36.92 | 240  | 0.9469          | 0.6957   |
| 0.2603        | 38.0  | 247  | 0.9942          | 0.6739   |
| 0.3028        | 38.92 | 253  | 1.0084          | 0.6739   |
| 0.2576        | 40.0  | 260  | 0.9908          | 0.6957   |
| 0.2576        | 40.92 | 266  | 1.0661          | 0.6957   |
| 0.2713        | 42.0  | 273  | 1.1347          | 0.6522   |
| 0.2713        | 42.92 | 279  | 1.1054          | 0.6739   |
| 0.2578        | 44.0  | 286  | 1.1089          | 0.6957   |
| 0.2367        | 44.92 | 292  | 1.1452          | 0.6739   |
| 0.2367        | 46.0  | 299  | 1.0272          | 0.6957   |
| 0.2301        | 46.92 | 305  | 1.1043          | 0.6739   |
| 0.2191        | 48.0  | 312  | 1.0815          | 0.6739   |
| 0.2191        | 48.92 | 318  | 0.9934          | 0.6957   |
| 0.2635        | 50.0  | 325  | 1.0866          | 0.6957   |
| 0.1874        | 50.92 | 331  | 1.0507          | 0.7174   |
| 0.1874        | 52.0  | 338  | 1.1002          | 0.7174   |
| 0.2057        | 52.92 | 344  | 1.0400          | 0.6739   |
| 0.1808        | 54.0  | 351  | 1.1092          | 0.7174   |
| 0.1808        | 54.92 | 357  | 1.1550          | 0.7174   |
| 0.2107        | 56.0  | 364  | 1.0579          | 0.6957   |
| 0.2149        | 56.92 | 370  | 1.0936          | 0.6957   |
| 0.2149        | 58.0  | 377  | 1.1692          | 0.6957   |
| 0.1865        | 58.92 | 383  | 1.1357          | 0.7174   |
| 0.1832        | 60.0  | 390  | 1.1549          | 0.6739   |
| 0.1832        | 60.92 | 396  | 1.1631          | 0.6957   |
| 0.1732        | 62.0  | 403  | 1.1312          | 0.6957   |
| 0.1732        | 62.92 | 409  | 1.1210          | 0.6957   |
| 0.1856        | 64.0  | 416  | 1.1835          | 0.6739   |
| 0.1503        | 64.92 | 422  | 1.1892          | 0.7174   |
| 0.1503        | 66.0  | 429  | 1.1865          | 0.6739   |
| 0.1713        | 66.92 | 435  | 1.1608          | 0.6739   |
| 0.1804        | 68.0  | 442  | 1.1699          | 0.6739   |
| 0.1804        | 68.92 | 448  | 1.1694          | 0.7174   |
| 0.1761        | 70.0  | 455  | 1.1744          | 0.6957   |
| 0.1619        | 70.92 | 461  | 1.1783          | 0.6957   |
| 0.1619        | 72.0  | 468  | 1.1797          | 0.6957   |
| 0.1649        | 72.92 | 474  | 1.1788          | 0.6957   |
| 0.1843        | 73.85 | 480  | 1.1780          | 0.6957   |


### Framework versions

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

avanzada leve moderada no dmae