optuna and orion
Optuna is a mature, general-purpose hyperparameter optimization framework that serves as a direct competitor to Orion, though Orion specializes in asynchronous distributed optimization with a focus on MongoDB-backed trial storage and experiment tracking, making it a niche alternative rather than a complement.
About optuna
optuna/optuna
A hyperparameter optimization framework
This tool helps machine learning practitioners fine-tune their models. You define your model's parameters and a performance metric, and Optuna automatically runs many experiments to find the best combination of settings. This results in highly optimized models without extensive manual trial and error.
About orion
Epistimio/orion
Asynchronous Distributed Hyperparameter Optimization.
This tool helps machine learning researchers and practitioners efficiently find the best settings (hyperparameters) for their models or training processes. You provide your existing model training script, and it intelligently explores different configurations to output optimized hyperparameters and improved model performance. It's designed for anyone regularly experimenting with and optimizing machine learning models.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work