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# swin-tiny-patch4-window7-224-ve-U11-b-40

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: 0.6121
- Accuracy: 0.8261

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.5799          | 0.4783   |
| 2.1773        | 2.0   | 13   | 1.5648          | 0.3478   |
| 2.1773        | 2.92  | 19   | 1.5182          | 0.3261   |
| 2.1773        | 4.0   | 26   | 1.4232          | 0.3261   |
| 1.8993        | 4.92  | 32   | 1.3505          | 0.3913   |
| 1.8993        | 6.0   | 39   | 1.2747          | 0.3696   |
| 1.5045        | 6.92  | 45   | 1.2452          | 0.3696   |
| 1.2431        | 8.0   | 52   | 1.1982          | 0.2826   |
| 1.2431        | 8.92  | 58   | 1.2112          | 0.3043   |
| 1.1225        | 10.0  | 65   | 1.0160          | 0.5      |
| 0.9942        | 10.92 | 71   | 1.0138          | 0.4783   |
| 0.9942        | 12.0  | 78   | 0.9094          | 0.5652   |
| 0.9212        | 12.92 | 84   | 0.8860          | 0.5217   |
| 0.816         | 14.0  | 91   | 0.7693          | 0.6739   |
| 0.816         | 14.92 | 97   | 0.8290          | 0.6304   |
| 0.741         | 16.0  | 104  | 0.7810          | 0.6739   |
| 0.631         | 16.92 | 110  | 0.6342          | 0.7826   |
| 0.631         | 18.0  | 117  | 0.7677          | 0.6957   |
| 0.6402        | 18.92 | 123  | 0.6283          | 0.7391   |
| 0.5477        | 20.0  | 130  | 0.6687          | 0.7174   |
| 0.5477        | 20.92 | 136  | 0.6369          | 0.7826   |
| 0.5023        | 22.0  | 143  | 0.6334          | 0.7609   |
| 0.5023        | 22.92 | 149  | 0.6355          | 0.8043   |
| 0.4802        | 24.0  | 156  | 0.5976          | 0.8043   |
| 0.4336        | 24.92 | 162  | 0.6112          | 0.7609   |
| 0.4336        | 26.0  | 169  | 0.6148          | 0.8043   |
| 0.4203        | 26.92 | 175  | 0.6380          | 0.7391   |
| 0.429         | 28.0  | 182  | 0.6032          | 0.8043   |
| 0.429         | 28.92 | 188  | 0.6348          | 0.7391   |
| 0.4013        | 30.0  | 195  | 0.6121          | 0.8261   |
| 0.3747        | 30.92 | 201  | 0.6521          | 0.7391   |
| 0.3747        | 32.0  | 208  | 0.6424          | 0.7609   |
| 0.3668        | 32.92 | 214  | 0.6149          | 0.8261   |
| 0.3287        | 34.0  | 221  | 0.6426          | 0.7826   |
| 0.3287        | 34.92 | 227  | 0.6379          | 0.8043   |
| 0.372         | 36.0  | 234  | 0.6435          | 0.8043   |
| 0.3236        | 36.92 | 240  | 0.6450          | 0.8043   |


### Framework versions

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

avanzada leve moderada no dmae