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arXiv · 2110.10828

AdamD: Improved bias-correction in Adam

John St John
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Abstract

Here I present a small update to the bias-correction term in the Adam optimizer that has the advantage of making smaller gradient updates in the first several steps of training. With the default bias-correction, Adam may actually make larger than requested gradient updates early in training. By only including the well-justified bias-correction of the second moment gradient estimate, $v_t$, and excluding the bias-correction on the first-order estimate, $m_t$, we attain these more desirable gradient update properties in the first series of steps. The default implementation of Adam may be as sensitive as it is to the hyperparameters $\beta_1, \beta_2$ partially due to the originally proposed bias correction procedure, and its behavior in early steps.

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John St John. 2021-10-20. AdamD: Improved bias-correction in Adam. https://arxiv.org/abs/2110.10828

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