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aa530cdad58123ebfb79ab85d996c4641cfc6c90
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3 Commits

Author SHA1 Message Date
Andrej Karpathy aa530cdad5 Add learnable lambdas that gate the residual connection and a skip connection to the input embeddings, solid bump to val_bpb 2026-01-11 18:47:35 +00:00
Andrej Karpathy 2c4473dd1b Big Muon optimizer changes inspired by latest of modded-nanogpt. Added Polar Express, Adafactor-style variance reduction, cautious weight decay, schedule weight decay linearly to ramp down to zero. Tuned optimum weight decay for multiple model sizes d8, d12, d16, d20 and found a scaling law with optimum wd \propto 1/channels^2, including it as default into code. --weight_decay of base_train is now default on and configured optimally according to all of these experiments. Solid bump to val_bpb observed as a result of these changes. 2026-01-11 16:56:59 +00:00
Andrej Karpathy 061f83c152 delete grad_clip. appears to not be necessary at all. not only was it buggy because the clipping happened per gpu before grad synchronization, but it costs ~2% MFU, and it also doesn't even help. I tried deleting it a while ago and back then it did help. So I'm guessing that some hyperparameter tuning obviated the reason for it since then 2026-01-08 02:16:50 +00:00
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