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A followup to original post (pasted shortened below), with major changes; release v1.1:
keras
+ tensorflow.keras
)keras
+ tensorflow.keras
)For a complete list of changes, see release notes. Optimizers here.
The latest Lookahead optimizer paper, co-authored by Geoffrey Hinton, used AdamW as its base optimizer, and noted it performing superior to plain Adam.
NadamW and SGDW included, along their WR (Warm Restart) counterparts – with cosine annealing learning rate schedule, and per layer learning rate multipliers (useful for pretraining). All optimizers are well-tested, and for me have yielded 3-4% F1-score improvements in already-tuned models for seizure classification.
submitted by /u/OverLordGoldDragon
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