SparseOpt is a new optimizer that counters batch normalization's gradient skew in dynamic sparse training, yielding faster convergence and better accuracy on ResNet models for CIFAR-100 and ImageNet.
Preconditioned Stochastic Gradient Descent , volume=
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Muon optimizer with weight decay and update scaling achieves ~2x efficiency over AdamW for large LLMs, shown via the Moonlight 3B/16B MoE model trained on 5.7T tokens.
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Muon is Scalable for LLM Training
Muon optimizer with weight decay and update scaling achieves ~2x efficiency over AdamW for large LLMs, shown via the Moonlight 3B/16B MoE model trained on 5.7T tokens.