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# vit-base-patch16-224-RU3-10

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: 0.6241
- Accuracy: 0.7833

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3698        | 0.99  | 19   | 1.1845          | 0.65     |
| 1.1232        | 1.97  | 38   | 0.9393          | 0.65     |
| 0.8168        | 2.96  | 57   | 0.9117          | 0.6333   |
| 0.5992        | 4.0   | 77   | 0.8330          | 0.7333   |
| 0.4258        | 4.99  | 96   | 0.7471          | 0.7      |
| 0.3283        | 5.97  | 115  | 0.6241          | 0.7833   |
| 0.2543        | 6.96  | 134  | 0.5916          | 0.7833   |
| 0.2345        | 8.0   | 154  | 0.6783          | 0.7833   |
| 0.2027        | 8.99  | 173  | 0.6577          | 0.7833   |
| 0.1733        | 9.87  | 190  | 0.6589          | 0.7833   |


### Framework versions

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

avanzada leve moderada no dmae