vit_Liveness_detection_v1.0

nguyenkhoa/vit_Liveness_detection_v1.0

vit_Liveness_detection_v1.0 is a image classification model from nguyenkhoa. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: vit
Access: Public
Created: Jan 8, 2025
Updated: Jan 8, 2025
SHA: b2a7ff5e

Base models

google/vit-base-patch16-224

Model card

From the Hugging Face model README

vit_Liveness_detection_v1.0

This model is a fine-tuned version of 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

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jan 8, 2025
Updated: Jan 8, 2025