---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: dinov2_Liveness_detection_v2.2.1
  results: []
---

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[<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/wo6b0psl)
# dinov2_Liveness_detection_v2.2.1

This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0671
- Accuracy: 0.9869
- F1: 0.9868
- Recall: 0.9869
- Precision: 0.9870

## 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: 512
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.183         | 0.8153 | 128  | 0.2473          | 0.9016   | 0.9039 | 0.9016 | 0.9123    |
| 0.1022        | 1.6306 | 256  | 0.0750          | 0.9729   | 0.9727 | 0.9729 | 0.9737    |
| 0.0432        | 2.4459 | 384  | 0.0575          | 0.9820   | 0.9820 | 0.9820 | 0.9823    |
| 0.0247        | 3.2611 | 512  | 0.0507          | 0.9832   | 0.9832 | 0.9832 | 0.9833    |
| 0.0115        | 4.0764 | 640  | 0.0536          | 0.9865   | 0.9864 | 0.9865 | 0.9866    |
| 0.002         | 4.8917 | 768  | 0.0671          | 0.9869   | 0.9868 | 0.9869 | 0.9870    |


### Framework versions

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