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# vit-base-patch16-224-U8-10

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: 0.5606
- Accuracy: 0.8833

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2473        | 1.0   | 20   | 1.1804          | 0.5833   |
| 0.9555        | 2.0   | 40   | 0.9370          | 0.65     |
| 0.727         | 3.0   | 60   | 0.7202          | 0.6833   |
| 0.5288        | 4.0   | 80   | 0.5606          | 0.8833   |
| 0.3876        | 5.0   | 100  | 0.6482          | 0.7667   |
| 0.296         | 6.0   | 120  | 0.7458          | 0.7167   |
| 0.236         | 7.0   | 140  | 0.4677          | 0.8833   |
| 0.2129        | 8.0   | 160  | 0.5138          | 0.8333   |
| 0.1781        | 9.0   | 180  | 0.4736          | 0.85     |
| 0.1854        | 10.0  | 200  | 0.4801          | 0.8      |


### Framework versions

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

avanzada leve moderada no dmae