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Probe READMEs: decay is 1-sqrt (as in the trainer's WSD), not linear
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# probe_s12B_420k — decay probe of `s12B_arcmix_edu/` at step 420,000
**Why it exists:** a short side run that measures what the arm would score if training stopped here. The arm (ARC-MIX + FineWeb-Edu pool, building pair 1 arm B) trains at a constant learning rate, and constant-LR checkpoints are not comparable with decayed models. This probe copies the arm's step-420,000 checkpoint and runs only the decay phase: the learning rate decays from 3e-4 to 6e-5 over 4,000 steps with a 1−sqrt schedule (as in the trainer's WSD decay) (420,000 → 424,000), on the same data and with the same optimizer state. The arm itself is not affected and keeps training.
- **Use:** compared with the flagship and with the decay probe of arm A (`probe_s12A_420k/`) on the held-out selection sets, it shows how the two arms would compare after decay at this point.
- **Status:** research checkpoint, **not a leaderboard submission**.
- **Format:** PyTorch checkpoint dict with `model`, `opt`, `step`, `config`; `train_gpt_ref.py` in the repository root rebuilds the model from `config`.
- **Data:** as in `s12B_arcmix_edu/`; see the root card of this repository.