MLflow and YOLOv8 about ultralytics HOT 2 OPEN

import mlflow
from ultralytics import YOLO

# Set experiment
mlflow.set_experiment('YOLOv8_Training')

# Start MLflow run
with mlflow.start_run():

    # Set parameters
    params = {'epochs': 10, 'batch_size': 16}
    mlflow.log_params(params)

    # Load model
    model = YOLO('yolov8n.yaml').load('yolov8n.pt')

    # Train the model
    train_results = model.train(data='coco128.yaml', epochs=params['epochs'], batch_size=params['batch_size'])

    # Log metrics
    mlflow.log_metrics({'mAP': train_results.map, 'precision': train_results.precision, 'recall': train_results.recall})

    # Save model artifact
    model.save('/path/to/save/model')
    mlflow.log_artifact('/path/to/save/model')

If you need detailed control or troubleshooting, the official [MLflow documentation](https://www.mlflow.org/docs/latest/index.html) provides comprehensive guides and scenarios.

Feel free to share specific issues you're encountering; this will help in providing more targeted assistance. Happy training!