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speedrun.sh: switch to Run 7 recipe (d22 + MuonClip + warmdown=0.85)

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gio 2026-04-26 21:36:37 -05:00
parent 889e588883
commit f8e217e6dd
1 changed files with 5 additions and 2 deletions
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7
runs/speedrun.sh
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@ -69,8 +69,11 @@ python -m scripts.tok_eval
echo "Waiting for dataset download to complete..."
wait $DATASET_DOWNLOAD_PID
# d24 model (slightly undertrained to beat GPT-2 => decrease data:params ratio from compute optimal 10.5 (default) to 8)
torchrun --standalone --nproc_per_node=8 -m scripts.base_train -- --depth=24 --target-param-data-ratio=8 --device-batch-size=16 --fp8 --run=$WANDB_RUN
# d22 model (slightly overtrained to beat GPT-2 => increase data:params ratio from compute optimal 10.5 (default) to 12).
# Mirror of Run 6's d24+ratio=8 strategy from the other side of compute-optimal — d22 is below GPT-2 capability,
# so we overtrain rather than undertrain. Combined with --warmdown-ratio=0.85 (longer low-LR tail) and
# --muon-qk-clip-tau=100 (Kimi K2 §A QK-Clip) the recipe crosses GPT-2 CORE in 3.3% less wall-clock than Run 6.
torchrun --standalone --nproc_per_node=8 -m scripts.base_train -- --depth=22 --target-param-data-ratio=12 --total-batch-size=1048576 --device-batch-size=16 --warmdown-ratio=0.85 --muon-qk-clip-tau=100 --fp8 --run=$WANDB_RUN
# evaluate the model: CORE metric, BPB on train/val, and draw samples
torchrun --standalone --nproc_per_node=8 -m scripts.base_eval -- --device-batch-size=16