vit-base-patch16-224-in21k Open Source Face Recognition Model - Achieve Nearly Perfect and Accurate Face Recognition

Vit Base Patch16 224 In21k Face Recognition

Developed by jayanta

This model is a face recognition model fine-tuned on an image folder dataset based on Google's ViT architecture, achieving near-perfect accuracy on the evaluation set.

Face-related

Transformers

Open Source License:Apache-2.0 #High-precision face recognition #ViT Vision Transformer #Fine-tuned pre-trained model

Downloads 216

Release Time : 10/30/2023

Model Overview

This model uses the Vision Transformer (ViT) architecture, specifically designed for face recognition tasks, capable of efficiently and accurately identifying and classifying facial images.

Model Features

High Accuracy

Achieved an accuracy of 0.9999 on the evaluation set, demonstrating excellent performance

Based on ViT Architecture

Utilizes the Vision Transformer architecture, offering powerful image processing capabilities

Efficient Fine-tuning

Fine-tuned on a pre-trained model, ensuring high training efficiency

Model Capabilities

Face recognition

Image classification

Feature extraction

Use Cases

Security & Surveillance

Access Control Systems

Used in face recognition access control systems to verify personnel identity

Accuracy as high as 99.99%

Social Media

Photo Auto-tagging

Automatically identifies and tags people in photos

Property	Details
Model Type	vit-base-patch16-224-in21k-face-recognition
Training Datasets	imagefolder, custom
Metrics	accuracy, precision, roc_auc, recall

Task Type	Dataset Name	Split	Metrics	Value
Image Classification	imagefolder	train	Accuracy	0.999957997311828
Image Classification	custom	test	Precision	1.0
Image Classification	custom	test	AUC	0.908055
Image Classification	custom	test	Recall	1.0

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0368	1.0	372	0.0346	1.0000
0.0094	2.0	744	0.0092	1.0000
0.0046	3.0	1116	0.0047	1.0000
0.0029	4.0	1488	0.0029	1.0
0.0022	5.0	1860	0.0023	0.9999
0.0017	6.0	2232	0.0017	1.0
0.0015	7.0	2604	0.0015	1.0
0.0014	8.0	2976	0.0015	1.0000

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Vit Base Patch16 224 In21k Face Recognition

Model Overview

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Use Cases

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