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# vit-base-patch16-224-U6-10

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: 0.5473
- Accuracy: 0.8333

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3653        | 1.0   | 16   | 1.2199          | 0.6333   |
| 1.0932        | 2.0   | 32   | 1.0086          | 0.65     |
| 0.9284        | 3.0   | 48   | 0.8466          | 0.6667   |
| 0.6745        | 4.0   | 64   | 0.8237          | 0.7      |
| 0.4775        | 5.0   | 80   | 0.7473          | 0.7667   |
| 0.4194        | 6.0   | 96   | 0.6148          | 0.7833   |
| 0.3043        | 7.0   | 112  | 0.6221          | 0.8167   |
| 0.2947        | 8.0   | 128  | 0.6156          | 0.7667   |
| 0.269         | 9.0   | 144  | 0.5700          | 0.8167   |
| 0.2261        | 10.0  | 160  | 0.5473          | 0.8333   |


### Framework versions

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

avanzada leve moderada no dmae