
<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nguyenkhoaht002/liveness_detection/runs/wt5k0v8b)
# dinov2_Liveness_detection_v2.1.2

This model is a fine-tuned version of [nguyenkhoa/dinov2_Liveness_detection_v2.1.1](https://huggingface.co/nguyenkhoa/dinov2_Liveness_detection_v2.1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0303
- Accuracy: 0.9936
- F1: 0.9936
- Recall: 0.9936
- Precision: 0.9936

## 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: 768
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0746        | 0.6095 | 64   | 0.0390          | 0.9852   | 0.9852 | 0.9852 | 0.9855    |
| 0.034         | 1.2190 | 128  | 0.0360          | 0.9871   | 0.9872 | 0.9871 | 0.9872    |
| 0.0201        | 1.8286 | 192  | 0.0303          | 0.9899   | 0.9899 | 0.9899 | 0.9898    |
| 0.0129        | 2.4381 | 256  | 0.0263          | 0.9912   | 0.9912 | 0.9912 | 0.9913    |
| 0.0105        | 3.0476 | 320  | 0.0232          | 0.9936   | 0.9935 | 0.9936 | 0.9936    |
| 0.0049        | 3.6571 | 384  | 0.0356          | 0.9913   | 0.9913 | 0.9913 | 0.9914    |
| 0.0035        | 4.2667 | 448  | 0.0281          | 0.9933   | 0.9933 | 0.9933 | 0.9933    |
| 0.0015        | 4.8762 | 512  | 0.0303          | 0.9936   | 0.9936 | 0.9936 | 0.9936    |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0

live spoof