Downloads · 30 days
102
2% of all-time downloads
dinov2_Liveness_detection_v2.2.3
nguyenkhoa/dinov2_Liveness_detection_v2.2.3
dinov2_Liveness_detection_v2.2.3 is a image classification model from nguyenkhoa. Use it when you need a label for an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
4.5K
Public
Parameters
22.1M
706 MB on disk
Likes
2
Public
Repo makeup
Click a slice to open those files.
.safetensors88.3 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- Model type
- dinov2
- Access
- Public
- Created
- Jan 23, 2025
- Updated
- Jan 24, 2025
- SHA
- 11a214b2
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
dinov2_Liveness_detection_v2.2.3
This model is a fine-tuned version of nguyenkhoa/dinov2_Liveness_detection_v2.2.2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0224
- Accuracy: 0.9932
- F1: 0.9932
- Recall: 0.9932
- Precision: 0.9933
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 |
|---|---|---|---|---|---|---|---|
| 0.0562 | 0.5872 | 64 | 0.0385 | 0.9860 | 0.9860 | 0.9860 | 0.9860 |
| 0.0328 | 1.1743 | 128 | 0.0350 | 0.9884 | 0.9884 | 0.9884 | 0.9885 |
| 0.0251 | 1.7615 | 192 | 0.0311 | 0.9879 | 0.9879 | 0.9879 | 0.9879 |
| 0.0185 | 2.3486 | 256 | 0.0296 | 0.9895 | 0.9895 | 0.9895 | 0.9895 |
| 0.0166 | 2.9358 | 320 | 0.0328 | 0.9897 | 0.9897 | 0.9897 | 0.9898 |
| 0.0109 | 3.5229 | 384 | 0.0336 | 0.9906 | 0.9906 | 0.9906 | 0.9907 |
| 0.0098 | 4.1101 | 448 | 0.0249 | 0.9917 | 0.9917 | 0.9917 | 0.9917 |
| 0.0069 | 4.6972 | 512 | 0.0224 | 0.9932 | 0.9932 | 0.9932 | 0.9933 |
Evaluate results
- APCER: 0.1827
- BPCER: 0.0089
- ACER: 0.0958
- Accuracy: 0.8700
- F1: 0.8975
- Recall: 0.9911
- Precision: 0.7026
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Image Classification
- Library
- transformers
- Type
- dinov2
- Created
- Jan 23, 2025
- Updated
- Jan 24, 2025