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Add layerwise SGDM learning rates for stock GPT-2 - #174
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Adds the next stock GPT-2 SGDM experiment: per-transformer-block learning-rate multipliers, separate embedding/other rates, 700-step warmup, cosine decay to a 0.10 floor, per-group LR logging, and immutable resumable full checkpoints every 2,000 updates. WeightWatcher/validation tracking remains intact. Also repairs the stale SGD regression test for the 19,560-step schedule. Multipliers are conservative and based on the previous run's layerwise alpha imbalance; this is an experimental schedule, not claimed as a published optimum.