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4e70e827ff |
@@ -302,7 +302,7 @@ Sequence length & 2,048 tokens \\
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\centering
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\centering
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\includegraphics[width=0.50\linewidth]{data/loss_compare.png}
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\includegraphics[width=0.50\linewidth]{data/loss_compare.png}
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\caption{Training loss curves: GPT-2 residual scaling vs.~Kaiming
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\caption{Training loss curves: GPT-2 residual scaling vs.~Kaiming
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initialization over $\sim$20B tokens.}
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initialization over $\sim$5B tokens.}
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\label{fig:loss}
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\label{fig:loss}
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\end{figure}
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\end{figure}
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@@ -547,17 +547,6 @@ spread.}
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\label{fig:ckpt_weight_density}
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\label{fig:ckpt_weight_density}
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\end{figure}
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\end{figure}
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\begin{figure}[H]
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\centering
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\includegraphics[width=0.95\linewidth]{data/ckpt_weight_density_per_run.png}
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\caption{Per-checkpoint weight density breakdowns. The three checkpoints
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are \texttt{norm-15bt} (AdamW, Normal init, 15B tokens), \texttt{kami-15bt}
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(AdamW, GPT-2 residual scaling, 15B tokens), and \texttt{muon-25bt}
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(Muon, 25B tokens). Note: the iteration labels inside the figure reflect
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legacy script metadata and should be ignored in favour of the token
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budgets stated here.}
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\label{fig:ckpt_weight_density_per_run}
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\end{figure}
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% ======================================================================
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% ======================================================================
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\section{Conclusion}
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\section{Conclusion}
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