dinov2_Liveness_detection_v2.2.1

This model is a fine-tuned version of nguyenkhoa/dinov2_Liveness_detection_v2.1.4 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0301
• Accuracy: 0.9910
• F1: 0.9910
• Recall: 0.9910
• Precision: 0.9910

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
0.4052	0.3232	64	0.0775	0.9712	0.9713	0.9712	0.9712
0.0784	0.6465	128	0.0545	0.9803	0.9803	0.9803	0.9804
0.0639	0.9697	192	0.0615	0.9771	0.9772	0.9771	0.9772
0.0479	1.2929	256	0.0572	0.9795	0.9794	0.9795	0.9800
0.0439	1.6162	320	0.0422	0.9844	0.9844	0.9844	0.9844
0.0392	1.9394	384	0.0564	0.9803	0.9801	0.9803	0.9810
0.0374	2.2626	448	0.0464	0.9837	0.9837	0.9837	0.9837
0.0273	2.5859	512	0.0378	0.9861	0.9861	0.9861	0.9861
0.0271	2.9091	576	0.0336	0.9883	0.9883	0.9883	0.9884
0.021	3.2323	640	0.0418	0.9859	0.9859	0.9859	0.9859
0.019	3.5556	704	0.0454	0.9848	0.9849	0.9848	0.9849
0.0177	3.8788	768	0.0359	0.9883	0.9883	0.9883	0.9883
0.0134	4.2020	832	0.0410	0.9874	0.9874	0.9874	0.9877
0.0102	4.5253	896	0.0314	0.9910	0.9910	0.9910	0.9910
0.0103	4.8485	960	0.0301	0.9910	0.9910	0.9910	0.9910

Evaluate results

• Accuracy: 0.8626
• F1: 0.8909
• Recall: 0.9924
• Precision: 0.6903
• APCER: 0.1940
• BPCER: 0.0076
• ACER: 0.1008

Framework versions

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