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Adaptive Moment Estimation - Mini

Adam-mini

2 papers tagged archive 2025-07-28

Introduced by Yushun Zhang et al. in Adam-mini: Use Fewer Learning Rates To Gain More

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Adam-mini is a memory-efficient Adam variant that achieves on-par or better performance than AdamW with 45% to 50% less memory footprint. Adam-mini reduces the memory footprint by cutting down the learning rate resources in Adam (i.e., 1/√(v)). The authors find that ≥ 90% of these learning rates in $ v $ could be harmlessly removed if they (1) carefully partition the parameters into blocks following their proposed principle on Hessian structure; (2) assign a single but good learning rate to each parameter block. They further find that, for each of these parameter blocks, there exists a single high-quality learning rate that can outperform Adam, provided that sufficient resources are available to search it out.

PaperSourceSee Code · zyushun/Adam-mini

Papers archive 2025-07-28

2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Language Modeling1
Language Modelling1
Large Language Model1

Usage over time archive 2025-07-28

Papers per year tagged with Adam-mini: 2024 to 2025, peak 1 1 0 2024: 1 paper 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (2 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

OptimizationStochastic Optimization

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