# dispatch-fullrank-sftbase-e2e-step1000

Full-rank (1x, **no compression**) dispatch codec, e2e-trained on the SFT base
model. This is the **lossless sanity codec**: it proves the dispatch codec
recipe / objective / pipeline is clean, so any downstream gap at 2x is genuinely
a rank/capacity effect, not a pipeline bug.

## What it is

- **compression** `dispatch`, `compression_ratio: 1` (per-layer bottleneck = full
  hidden dim 2048), `init: identity_truncated`, `stale_stride: 12`.
- **base model** `models/sft-base-qwen3-30b-a3b` (fullft-qwen3base-bf16 step-4000
  backbone-hf). Do **not** load against Qwen3-30B-A3B-Instruct-2507.
- **training** e2e, frozen backbone, objective `lm0.25 + recon(KL) + router-KL`,
  bs 64, lr 1e-5, seed 42, DP4 (world_size 16), **step-1000**.

## Eval (lm-eval-harness, same protocol as the 2x codecs)

| task | metric | full-rank (this) | no-codec target |
|---|---|---|---|
| gsm8k | exact_match strict | 86.8 | 86.9 |
| mmlu | acc | 81.3 | 80.7 |
| hellaswag | acc_norm | 82.1 | 82.5 |
| arc_easy | acc_norm | 89.5 | 89.3 |
| arc_challenge | acc_norm | 68.9 | 69.1 |
| **AVG** | | **81.7** | **81.6** |

Lossless within noise (gap ~0). Contrast the best 2x dispatch codec
(`trained-codecs/dispatch-2x-sftbase-e2e-step7000`, avg 78.6, gap -3.0).

## Files

- `compression.pt` — codec state dict (load as init directly, no transform).
- `meta.json` — training provenance (git commit, base model, compression config).