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# vit-base-patch16-224-dmae-va-U5-10-45-5e-05

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9129
- Accuracy: 0.75

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.3457          | 0.5167   |
| 1.3687        | 1.94  | 15   | 1.2405          | 0.6      |
| 1.2688        | 2.97  | 23   | 1.1549          | 0.6167   |
| 1.1325        | 4.0   | 31   | 1.0675          | 0.5833   |
| 1.1325        | 4.9   | 38   | 1.0208          | 0.65     |
| 1.0211        | 5.94  | 46   | 0.9604          | 0.6      |
| 0.9458        | 6.97  | 54   | 0.9329          | 0.7      |
| 0.9048        | 8.0   | 62   | 0.9206          | 0.7167   |
| 0.9048        | 8.9   | 69   | 0.9129          | 0.75     |
| 0.8618        | 9.03  | 70   | 0.9127          | 0.75     |


### Framework versions

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

avanzada leve moderada no dmae