OmniOpt: Unified Analysis Framework and Benchmark for Large-Scale Model Training Optimizers
opendatalab · hf · 2026-07-07
OmniOpt proposes a unified framework for optimizer selection in large-scale model training, combining meta-pipeline transformations, norm-constrained linear minimization oracles, and cross-domain benchmarks to systematically analyze trade-offs across optimizer families under different training objectives and model sizes. This work provides researchers with a systematic tool for optimizer comparison and selection across various model scale scenarios.
Related event: OmniOpt Unifies Optimizer Taxonomy and Benchmarking(2 posts)→
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