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During early training iterations, gradient moments (m_t and v_t) in adaptive optimizers are uncalibrated and noisy. A linear warmup gradually ramps the learning rate from zero to the target maximum, preventing large chaotic updates that destabilize initial weight manifolds.

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Ultron09
Aug 27, 2026
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