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wuhp/
test4

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rolo_yolo_fast2

Model Overview

Architecture: YOLOv11
Training Epochs: 50
Batch Size: 16
Optimizer: auto
Learning Rate: 0.001
Data Augmentation Level: Basic

Training Metrics

mAP@0.5: 0.995

Class IDs

Class ID	Class Name
0	Panadol
1	Revanin

Datasets Used

Drug Classification

Class Image Counts

Class Name	Image Count
Panadol	116
Revanin	122

Description

This model was trained using the YOLOv11 architecture on a custom dataset. The training process involved 50 epochs with a batch size of 16. The optimizer used was auto with an initial learning rate of 0.001. Data augmentation was set to the Basic level to enhance model robustness.

Usage

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

python

from ultralytics import YOLO

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

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

# Display results
results.show()

wuhp/test4