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# vit_Liveness_detection_v1.0

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: 0.0047
- Accuracy: 0.9988
- F1: 0.9988
- Recall: 0.9988
- Precision: 0.9988

## 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0254        | 0.2048 | 128  | 0.0148          | 0.9946   | 0.9946 | 0.9946 | 0.9946    |
| 0.0256        | 0.4096 | 256  | 0.0180          | 0.9945   | 0.9944 | 0.9945 | 0.9945    |
| 0.0113        | 0.6144 | 384  | 0.0133          | 0.9955   | 0.9955 | 0.9955 | 0.9955    |
| 0.0116        | 0.8192 | 512  | 0.0070          | 0.9976   | 0.9976 | 0.9976 | 0.9976    |
| 0.0084        | 1.024  | 640  | 0.0072          | 0.9976   | 0.9976 | 0.9976 | 0.9976    |
| 0.0048        | 1.2288 | 768  | 0.0084          | 0.9976   | 0.9976 | 0.9976 | 0.9976    |
| 0.0041        | 1.4336 | 896  | 0.0078          | 0.9975   | 0.9975 | 0.9975 | 0.9975    |
| 0.0015        | 1.6384 | 1024 | 0.0049          | 0.9983   | 0.9983 | 0.9983 | 0.9983    |
| 0.0047        | 1.8432 | 1152 | 0.0068          | 0.9977   | 0.9977 | 0.9977 | 0.9977    |
| 0.0012        | 2.048  | 1280 | 0.0075          | 0.9975   | 0.9975 | 0.9975 | 0.9975    |
| 0.0025        | 2.2528 | 1408 | 0.0095          | 0.9971   | 0.9971 | 0.9971 | 0.9971    |
| 0.0013        | 2.4576 | 1536 | 0.0084          | 0.9976   | 0.9976 | 0.9976 | 0.9976    |
| 0.0026        | 2.6624 | 1664 | 0.0056          | 0.9985   | 0.9985 | 0.9985 | 0.9985    |
| 0.0001        | 2.8672 | 1792 | 0.0096          | 0.9976   | 0.9976 | 0.9976 | 0.9976    |
| 0.0001        | 3.072  | 1920 | 0.0049          | 0.9987   | 0.9987 | 0.9987 | 0.9987    |
| 0.0009        | 3.2768 | 2048 | 0.0085          | 0.9978   | 0.9978 | 0.9978 | 0.9978    |
| 0.0003        | 3.4816 | 2176 | 0.0078          | 0.9980   | 0.9980 | 0.9980 | 0.9980    |
| 0.0002        | 3.6864 | 2304 | 0.0057          | 0.9985   | 0.9985 | 0.9985 | 0.9985    |
| 0.0           | 3.8912 | 2432 | 0.0043          | 0.9988   | 0.9988 | 0.9988 | 0.9988    |
| 0.0           | 4.096  | 2560 | 0.0046          | 0.9987   | 0.9987 | 0.9987 | 0.9987    |
| 0.0           | 4.3008 | 2688 | 0.0045          | 0.9988   | 0.9988 | 0.9988 | 0.9988    |
| 0.0           | 4.5056 | 2816 | 0.0046          | 0.9988   | 0.9988 | 0.9988 | 0.9988    |
| 0.0           | 4.7104 | 2944 | 0.0047          | 0.9988   | 0.9988 | 0.9988 | 0.9988    |
| 0.0           | 4.9152 | 3072 | 0.0047          | 0.9988   | 0.9988 | 0.9988 | 0.9988    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1

live spoof