New architectural features:
- Smear: mix previous token embedding into current position via learned
gate, providing cheap bigram-like info (works in training + KV cache)
- Backout: subtract learned fraction of mid-layer residual before logit
projection to remove low-level features
Hyperparameter tuning:
- Muon momentum warmdown 0.97→0.90 during LR warmdown phase
- Non-uniform per-layer init: resid_lambdas 1.15→1.05, x0_lambdas 0.20→0.05
- c_fc init scale 0.4x, QK norm scale 1.2, sliding window seq_len/4
- Speedrun data:params ratio reduced to 8
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
