
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-base-patch16-224-R1-10

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: 1.2451
- Accuracy: 0.7049

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1675        | 0.99  | 38   | 0.9972          | 0.6393   |
| 0.5606        | 1.99  | 76   | 0.7603          | 0.6885   |
| 0.3159        | 2.98  | 114  | 0.8954          | 0.6885   |
| 0.2253        | 4.0   | 153  | 1.0227          | 0.6885   |
| 0.17          | 4.99  | 191  | 1.1025          | 0.7213   |
| 0.1174        | 5.99  | 229  | 1.1453          | 0.7377   |
| 0.1032        | 6.98  | 267  | 1.0995          | 0.6885   |
| 0.1051        | 8.0   | 306  | 1.2167          | 0.7049   |
| 0.0853        | 8.99  | 344  | 1.2042          | 0.7377   |
| 0.0802        | 9.93  | 380  | 1.2451          | 0.7049   |


### Framework versions

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

avanzada leve moderada no dmae