ModelRefs / Model Soup — AI Glossary
Model Soup — AI Glossary
Weight-averaging multiple fine-tuned checkpoints of the same base model to improve accuracy and reduce variance.
Overview
Wortsman et al. (2022) showed that averaging weights of models fine-tuned with different hyperparameters (a 'model soup') outperforms any individual soup ingredient. Uniform soup averages all; greedy soup greedily adds models that improve held-out accuracy. Low-overhead ensemble method requiring only weight averaging.
Reference details
| Topic | training |
|---|---|
| Last reviewed | 2026-06-24 |
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Frequently asked questions
What is Model Soup?
Weight-averaging multiple fine-tuned checkpoints of the same base model to improve accuracy and reduce variance.
What concepts are related to Model Soup?
Closely related concepts include model merging, knowledge distillation, continual learning.