Learn more about sweeps

​

Academic papers

​

Sweeps experiments

• Drought Watch Benchmark Progress
  • Description: Developing the baseline and exploring submissions to the Drought Watch benchmark.
• Tuning Safety Penalties in Reinforcement Learning
  • Description: Examines agents trained with different side effect penalties on three different tasks: pattern creation, pattern removal, and navigation.
• Meaning and Noise in Hyperparameter Search with Weights & Biases Stacey Svetlichnaya
  • Description: How do you distinguish signal from pareidolia (imaginary patterns)? This article showcases what’s possible with Weights & Biases and aims to inspire further exploration.
• Who is Them? Text Disambiguation with Transformers
  • Description: Using Hugging Face to explore models for natural language understanding.
• DeepChem: Molecular Solubility
  • Description: Predict chemical properties from molecular structure with random forests and deep nets.
• Intro to MLOps: Hyperparameter Tuning
  • Description: Explore why hyperparameter optimization matters and examine three algorithms to automate hyperparameter tuning for your machine learning models.

​

How-to guide

• Sweeps with XGBoost
  • Description: How to use Sweeps for hyperparameter tuning using XGBoost.

​

Sweeps GitHub repository