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# vit-base-patch16-224-ve-U11-12

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5924
- Accuracy: 0.8478

## 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: 5.5e-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: 0.05
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3668        | 0.96  | 16   | 1.2319          | 0.5652   |
| 1.1102        | 1.97  | 33   | 0.9996          | 0.6957   |
| 0.8257        | 2.99  | 50   | 0.8429          | 0.6304   |
| 0.68          | 4.0   | 67   | 0.6906          | 0.8043   |
| 0.4763        | 4.96  | 83   | 0.6871          | 0.7609   |
| 0.341         | 5.97  | 100  | 0.5924          | 0.8478   |
| 0.2956        | 6.99  | 117  | 0.4863          | 0.8478   |
| 0.2376        | 8.0   | 134  | 0.5947          | 0.7826   |
| 0.2098        | 8.96  | 150  | 0.5579          | 0.8043   |
| 0.2213        | 9.97  | 167  | 0.6474          | 0.7609   |
| 0.1767        | 10.99 | 184  | 0.6015          | 0.7826   |
| 0.1757        | 11.46 | 192  | 0.5928          | 0.7609   |


### Framework versions

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

avanzada leve moderada no dmae