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# vit-base-patch16-224-dmae-va-U5-20-45-5e-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: 0.5800
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.3607          | 0.4833   |
| 1.3752        | 1.94  | 15   | 1.2550          | 0.5833   |
| 1.2809        | 2.97  | 23   | 1.1436          | 0.65     |
| 1.1273        | 4.0   | 31   | 1.0381          | 0.5833   |
| 1.1273        | 4.9   | 38   | 0.9620          | 0.6833   |
| 0.9919        | 5.94  | 46   | 0.9154          | 0.65     |
| 0.8971        | 6.97  | 54   | 0.8502          | 0.7667   |
| 0.8049        | 8.0   | 62   | 0.8644          | 0.75     |
| 0.8049        | 8.9   | 69   | 0.8010          | 0.7833   |
| 0.7119        | 9.94  | 77   | 0.7276          | 0.8333   |
| 0.6172        | 10.97 | 85   | 0.6699          | 0.8167   |
| 0.5294        | 12.0  | 93   | 0.6532          | 0.8167   |
| 0.4696        | 12.9  | 100  | 0.6265          | 0.85     |
| 0.4696        | 13.94 | 108  | 0.6012          | 0.85     |
| 0.4074        | 14.97 | 116  | 0.5800          | 0.8833   |
| 0.3822        | 16.0  | 124  | 0.5692          | 0.8667   |
| 0.3651        | 16.9  | 131  | 0.6065          | 0.8      |
| 0.3651        | 17.94 | 139  | 0.5681          | 0.8667   |
| 0.3731        | 18.06 | 140  | 0.5675          | 0.8667   |


### Framework versions

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

avanzada leve moderada no dmae