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# beit-base-patch16-224-dmae-va-U5-42

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on Augusto777/dmae-ve-U5 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0039
- Accuracy: 0.8167

## 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    | 1.3471          | 0.4667   |
| 1.6023        | 1.94  | 15   | 1.0873          | 0.5833   |
| 1.1509        | 2.97  | 23   | 0.9948          | 0.5833   |
| 0.826         | 4.0   | 31   | 0.7244          | 0.7167   |
| 0.826         | 4.9   | 38   | 0.5741          | 0.7333   |
| 0.5551        | 5.94  | 46   | 0.6569          | 0.75     |
| 0.3649        | 6.97  | 54   | 0.6322          | 0.7167   |
| 0.2592        | 8.0   | 62   | 0.6994          | 0.7333   |
| 0.2592        | 8.9   | 69   | 0.6590          | 0.7333   |
| 0.1958        | 9.94  | 77   | 0.6846          | 0.7667   |
| 0.1664        | 10.97 | 85   | 0.7166          | 0.7667   |
| 0.1571        | 12.0  | 93   | 0.7842          | 0.7833   |
| 0.1174        | 12.9  | 100  | 0.8465          | 0.8      |
| 0.1174        | 13.94 | 108  | 0.9116          | 0.7667   |
| 0.0956        | 14.97 | 116  | 0.9741          | 0.75     |
| 0.1252        | 16.0  | 124  | 0.7760          | 0.8      |
| 0.0933        | 16.9  | 131  | 0.9424          | 0.7833   |
| 0.0933        | 17.94 | 139  | 1.0445          | 0.7333   |
| 0.1455        | 18.97 | 147  | 0.8525          | 0.7333   |
| 0.1034        | 20.0  | 155  | 0.8222          | 0.7667   |
| 0.0855        | 20.9  | 162  | 0.8991          | 0.7833   |
| 0.0985        | 21.94 | 170  | 0.8955          | 0.8      |
| 0.0985        | 22.97 | 178  | 0.9603          | 0.7667   |
| 0.087         | 24.0  | 186  | 0.9932          | 0.7833   |
| 0.0832        | 24.9  | 193  | 1.0100          | 0.7833   |
| 0.0632        | 25.94 | 201  | 0.9393          | 0.7667   |
| 0.0632        | 26.97 | 209  | 0.9062          | 0.7833   |
| 0.0778        | 28.0  | 217  | 0.9339          | 0.8      |
| 0.0627        | 28.9  | 224  | 1.0039          | 0.8167   |
| 0.0837        | 29.94 | 232  | 1.0636          | 0.7333   |
| 0.0595        | 30.97 | 240  | 1.0424          | 0.75     |
| 0.0595        | 32.0  | 248  | 1.0514          | 0.8      |
| 0.0706        | 32.9  | 255  | 1.0639          | 0.7833   |
| 0.0565        | 33.94 | 263  | 1.0494          | 0.7667   |
| 0.0515        | 34.97 | 271  | 1.0628          | 0.7667   |
| 0.0515        | 36.0  | 279  | 1.1089          | 0.7667   |
| 0.0614        | 36.9  | 286  | 1.0861          | 0.8      |
| 0.0496        | 37.94 | 294  | 1.0713          | 0.8      |


### Framework versions

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