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# swin-tiny-patch4-window7-224-dmae-va-U5-42

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on Augusto777/dmae-ve-U5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6653
- Accuracy: 0.75

## Model description

Model for multiclass detection of age-related macular degeneration.

## Intended uses & limitations

Destined to support medical diagnosis.

## 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: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.3831          | 0.45     |
| 1.3852        | 1.94  | 15   | 1.3624          | 0.45     |
| 1.3728        | 2.97  | 23   | 1.2927          | 0.4667   |
| 1.2791        | 4.0   | 31   | 1.1182          | 0.4833   |
| 1.2791        | 4.9   | 38   | 1.0065          | 0.4667   |
| 1.094         | 5.94  | 46   | 0.8931          | 0.6      |
| 0.9601        | 6.97  | 54   | 0.9210          | 0.4833   |
| 0.8598        | 8.0   | 62   | 0.9478          | 0.5167   |
| 0.8598        | 8.9   | 69   | 0.8558          | 0.5833   |
| 0.7558        | 9.94  | 77   | 0.9259          | 0.65     |
| 0.6696        | 10.97 | 85   | 0.7953          | 0.6167   |
| 0.6079        | 12.0  | 93   | 0.7281          | 0.7      |
| 0.516         | 12.9  | 100  | 0.8552          | 0.6667   |
| 0.516         | 13.94 | 108  | 0.6653          | 0.75     |
| 0.4475        | 14.97 | 116  | 0.7548          | 0.6833   |
| 0.4152        | 16.0  | 124  | 0.7556          | 0.7167   |
| 0.3759        | 16.9  | 131  | 0.7038          | 0.7333   |
| 0.3759        | 17.94 | 139  | 0.7356          | 0.7167   |
| 0.3366        | 18.97 | 147  | 0.6650          | 0.75     |
| 0.3212        | 20.0  | 155  | 0.7668          | 0.7167   |
| 0.2903        | 20.9  | 162  | 0.7997          | 0.6833   |
| 0.312         | 21.94 | 170  | 0.7473          | 0.7167   |
| 0.312         | 22.97 | 178  | 0.8479          | 0.7      |
| 0.2488        | 24.0  | 186  | 0.8070          | 0.7      |
| 0.283         | 24.9  | 193  | 0.8080          | 0.6833   |
| 0.2109        | 25.94 | 201  | 0.8220          | 0.7      |
| 0.2109        | 26.97 | 209  | 0.8354          | 0.7167   |
| 0.2215        | 28.0  | 217  | 0.8668          | 0.7      |
| 0.2067        | 28.9  | 224  | 0.8479          | 0.75     |
| 0.1967        | 29.94 | 232  | 0.8868          | 0.7167   |
| 0.1948        | 30.97 | 240  | 0.8883          | 0.7      |
| 0.1948        | 32.0  | 248  | 0.8612          | 0.7333   |
| 0.186         | 32.9  | 255  | 0.8860          | 0.7333   |
| 0.1662        | 33.94 | 263  | 0.9057          | 0.75     |
| 0.1773        | 34.97 | 271  | 0.9140          | 0.7167   |
| 0.1773        | 36.0  | 279  | 0.9013          | 0.7333   |
| 0.1519        | 36.9  | 286  | 0.8869          | 0.75     |
| 0.1775        | 37.94 | 294  | 0.8840          | 0.7333   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
avanzada leve moderada no dmae