1 files changed, 89 insertions, 0 deletions
diff --git a/docs/campaign/FW135M_BP_BASELINE.md b/docs/campaign/FW135M_BP_BASELINE.md
new file mode 100644
index 0000000..3f81ba8
--- /dev/null
+++ b/docs/campaign/FW135M_BP_BASELINE.md
@@ -0,0 +1,89 @@
+# FW135M BP Twin Run Sheet
+
+Source of truth: `docs/BASELINE_SPEC.md`.
+
+Status: commands configured on branch `xiang`; no training has started.
+
+## First width-only rung
+
+- Shape: `L12/C768/H12/T256`
+- Head dimension: `64`
+- Exact local parameter count: `135,303,936`
+- Data: existing FineWeb-Edu 32k bins
+- Batch: `B24`
+- Target: `20N = 2,706,078,720` tokens
+- Complete-batch exposure: `2,706,081,792` tokens
+- Trainer argument: `--steps 440442` (440,443 inclusive updates)
+
+## What changes from 72M
+
+- Width: `512 -> 768`
+- Heads: `8 -> 12`
+- Parameters: `72.11M -> 135.30M`
+- Run length: increases to preserve approximately 20 tokens/parameter
+
+## What stays identical
+
+- L12 depth and 64-dimensional heads
+- T256 and B24
+- FineWeb-Edu data and 32k tokenizer
+- OLMo2-style model implementation
+- Muon hybrid optimizer and cosine schedule
+- Weight decay 0.1 and BF16 autocast
+- Seed list and validation cadence
+- Existing `casc_bp_train.py` code path
+
+## LR sweep
+
+At this smallest new rung only:
+
+- `7e-4`
+- `1e-3`
+- `1.4e-3`
+
+Only Adam-side LR changes. Carry the winner to larger rungs.
+
+No result may be quoted with fewer than two seeds. Record best validation CE, final-step CE, and tail median. Save every 5,000 steps and log validation every 100 steps.
+
+## Dry-run launcher
+
+From `ep_run/`:
+
+```bash
+python -m py_compile fw135m_baseline.py
+python fw135m_baseline.py --mode smoke
+python fw135m_baseline.py --mode sweep
+python fw135m_baseline.py --mode full
+```
+
+Commands print by default. Add `--execute` only when ready.
+
+Smoke:
+
+```bash
+python fw135m_baseline.py --mode smoke --execute
+```
+
+LR sweep:
+
+```bash
+python fw135m_baseline.py --mode sweep --execute
+```
+
+Selected full run:
+
+```bash
+python fw135m_baseline.py --mode full --lr <selected-lr> --seed 1 --execute
+python fw135m_baseline.py --mode full --lr <selected-lr> --seed 2 --execute
+```
+
+W&B remains off until configured. Later:
+
+```bash
+python fw135m_baseline.py --mode full --lr <selected-lr> \
+  --wandb_project <project> --execute
+```
+
+## Final EP/BP comparison
+
+The EP arm must use the same shape, data, B/T, steps, optimizer family, selected shared settings, seeds, and evaluation cadence. Only the training rule and EP-specific `β` controls differ.