face2

Model Overview

Architecture: YOLOv11
Training Epochs: 75
Batch Size: 32
Optimizer: auto
Learning Rate: 0.0005
Data Augmentation Level: Moderate

Training Metrics

[email protected]: 0.99373

Class IDs

Class ID	Class Name
0	Face

Datasets Used

face-detection-mik1i_v24
faces-bfigz_v3
head-qug6h_v2

Class Image Counts

Class Name	Image Count
Face	15349

Description

This model was trained using the YOLOv11 architecture on a custom dataset. The training process involved 75 epochs with a batch size of 32. The optimizer used was auto with an initial learning rate of 0.0005. Data augmentation was set to the Moderate level to enhance model robustness.

Usage

To use this model for inference, follow the instructions below:

from ultralytics import YOLO

# Load the trained model
model = YOLO('face2.pt')

# Perform inference on an image
results = model('path_to_image.jpg')

# Display results
results.show()