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# vit-base-patch16-224-dmae-va-U5-42B

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on Augusto777/dmae-ve-U5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7215
- Accuracy: 0.85

## 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    | 1.3101          | 0.4667   |
| 1.408         | 1.94  | 15   | 1.1884          | 0.4833   |
| 1.1286        | 2.97  | 23   | 0.9476          | 0.5167   |
| 0.7589        | 4.0   | 31   | 0.7637          | 0.75     |
| 0.7589        | 4.9   | 38   | 0.7186          | 0.6833   |
| 0.4786        | 5.94  | 46   | 0.6192          | 0.7833   |
| 0.2874        | 6.97  | 54   | 0.6195          | 0.7833   |
| 0.2027        | 8.0   | 62   | 0.5959          | 0.7833   |
| 0.2027        | 8.9   | 69   | 0.6104          | 0.7667   |
| 0.1662        | 9.94  | 77   | 0.7297          | 0.75     |
| 0.1462        | 10.97 | 85   | 0.7852          | 0.7667   |
| 0.1419        | 12.0  | 93   | 0.8637          | 0.7167   |
| 0.1199        | 12.9  | 100  | 0.6797          | 0.7333   |
| 0.1199        | 13.94 | 108  | 0.7660          | 0.7667   |
| 0.0949        | 14.97 | 116  | 0.7386          | 0.7167   |
| 0.0901        | 16.0  | 124  | 1.0126          | 0.7      |
| 0.0808        | 16.9  | 131  | 0.7060          | 0.8      |
| 0.0808        | 17.94 | 139  | 0.7857          | 0.7833   |
| 0.102         | 18.97 | 147  | 0.7411          | 0.8      |
| 0.0706        | 20.0  | 155  | 0.7340          | 0.8167   |
| 0.0582        | 20.9  | 162  | 0.8589          | 0.75     |
| 0.0687        | 21.94 | 170  | 0.8546          | 0.7667   |
| 0.0687        | 22.97 | 178  | 0.7761          | 0.7667   |
| 0.0633        | 24.0  | 186  | 0.8112          | 0.7667   |
| 0.0626        | 24.9  | 193  | 0.6943          | 0.8333   |
| 0.0578        | 25.94 | 201  | 0.8593          | 0.7833   |
| 0.0578        | 26.97 | 209  | 0.7215          | 0.85     |
| 0.0434        | 28.0  | 217  | 0.8150          | 0.8      |
| 0.0492        | 28.9  | 224  | 0.7834          | 0.7833   |
| 0.0582        | 29.94 | 232  | 0.7844          | 0.7833   |
| 0.0515        | 30.97 | 240  | 0.7973          | 0.7667   |
| 0.0515        | 32.0  | 248  | 0.7744          | 0.8      |
| 0.0487        | 32.9  | 255  | 0.8614          | 0.75     |
| 0.0455        | 33.94 | 263  | 0.8195          | 0.7667   |
| 0.0329        | 34.97 | 271  | 0.8327          | 0.7667   |
| 0.0329        | 36.0  | 279  | 0.8889          | 0.7667   |
| 0.0447        | 36.9  | 286  | 0.8705          | 0.7667   |
| 0.0445        | 37.94 | 294  | 0.8695          | 0.7667   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
avanzada leve moderada no dmae