Viewing enriched Twitter post
Adam is similar to many algorithms, but cannot be effectively replaced by any simpler variant in LMs. The community is starting to get the recipe right, but what is the secret sauce? @gowerrobert and I found that it has to do with the beta parameters and variational inference.… https://t.co/CuPj9owJjS
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"text": "🧐Nice work and thanks for the pointer! If I understand it correctly (correct me if wrong): you suggest using (1) beta1= beta2 and (2) both betas need to be large. This actually lies in our theoretical \"good region\" as shown below in our early theory paper on Adam. I believe our theory can support your findings https://t.co/cNc1mkZjOR\n\nBut in our paper, we only know (1) and (2) would work, but we did not know (1) and (2) are actually near-optimal. This seems interesting if holds true for general LLMs.",
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"full_text": "@orvieto_antonio @gowerrobert 🧐Nice work and thanks for the pointer! If I understand it correctly (correct me if wrong): you suggest using (1) beta1= beta2 and (2) both betas need to be large. This actually lies in our theoretical \"good region\" as shown below in our early theory paper on Adam. I believe… https://t.co/mc0pxHHp3A",
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"full_text": "@orvieto_antonio @gowerrobert Interesting paper! FYI I think there's a small typo in eqn (4): in Apx C.3, (4) is minimized but with λ -> 1/λ, so the β=1/(1+λ) result holds when the KL term is weighted by 1/λ, not λ. This is more intuitive to me, since then large KL weight => large β => slowly varying m, σ²",
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