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Tactic: Early Stopping in Training
Tactic sort:
Awesome Tactic
Type: Architectural Tactic
Category: resource-adaptation
Title
Early Stopping in Training
Description
Setting early stopping criteria including representative performance metric and minimum improvement threshold, consumers can prevent the unnecessary use of computational resources on training runs that provide minimal additional improvements in model performance.
Participant
Cloud Platform Providers. Machine Learning Practitioners.
Related software artifact
Public Cloud Platforms.
Context
Machine Learning Systems Energy Use. Green AI.
Software feature
Stop Training Early.
Tactic intent
Increased Energy Efficiency.
Target quality attribute
Energy Efficiency.
Other related quality attributes
Cost Optimization.
Measured impact
< unknown >
Source
Green AI in the Cloud: Energy-Efficient Architectural Tactics for ML-Enabled Systems on Public Platforms by Jingzhi Zhang (Eloise)Graphical representation
