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
- [email protected]: 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:
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()