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Any time I've trained a transformer from scratch on webtext, the loss curve looks like this. The first drop makes sense, but why the second one? Gemini is telling me nonsense. Architecture same as gpt2 except swiglu, rope, untied embeddings training: muon + adam linear warmup (up til 500 steps) My best thought is the induction head formation meme, but my understanding is this happens quite late, like after several thousand training steps or like a billion tokens or sth, and i have 100k tokens per batch. Any transformer training people know why this happens?

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