From bf1a66855f9d96d1ca9717026f674e6fb5c19186 Mon Sep 17 00:00:00 2001 From: Micah Villmow <4211002+mvillmow@users.noreply.github.com> Date: Mon, 24 Aug 2026 17:15:18 +0000 Subject: [PATCH] docs: add Qwen3.5 graft report 13 results --- .../benchmarking/qwen35-grafting-report-13.md | 83 +++++++++++++++++++ 1 file changed, 83 insertions(+) create mode 100644 docs/benchmarking/qwen35-grafting-report-13.md diff --git a/docs/benchmarking/qwen35-grafting-report-13.md b/docs/benchmarking/qwen35-grafting-report-13.md new file mode 100644 index 000000000000..1231dd436386 --- /dev/null +++ b/docs/benchmarking/qwen35-grafting-report-13.md @@ -0,0 +1,83 @@ +# Qwen3.5 graft Report 13: causal cross-attention fusion + +## Summary + +Report 13 evaluated a causal cross-attention graft from Qwen3.5-27B into the +complete Qwen3.5-9B host. The graft improved the combined MMLU-Pro and BBH score +at 100M continuation tokens, but the improvement did not persist through the +250M checkpoint. + +The best checkpoint was 100M: + +- MMLU-Pro: `0.514628` (`+0.000582` versus the 9B baseline) +- BBH: `0.623503` (`+0.005207` versus the 9B baseline) +- Combined: `1.138131` (`+0.005789` versus the 9B baseline) + +The 250M checkpoint fell to a combined score of `1.122947`, which is +`-0.009395` below baseline. The result supports checkpoint selection and early +stopping; it does not support treating longer continuation as monotonically +beneficial. + +## Configuration + +The experiment kept the complete Qwen3.5-9B host and inserted frozen donor +layers 31--33 from Qwen3.5-27B after host layer 15. The donor layers executed on +every forward pass. A trainable 512-wide, eight-head causal cross-attention +module fused donor information into the host stream, with a maximum residual +scale of `0.05`. + +The host and original donor parameters remained frozen. Training was restricted +to the input/output projections and report-specific graft parameters. Each +checkpoint used the same protocol identity: +`b82fc1daf569d506e0a1ff24d1e96674879315248311badd10966164a685e111`. + +Evaluation covered the complete deterministic task sets: + +- MMLU-Pro: 12,032 samples +- BBH: 5,761 samples + +The baseline and baseline-repeat evaluations were identical. + +## Results + +| Checkpoint | MMLU-Pro | BBH | Combined | Combined delta vs. baseline | +|---:|---:|---:|---:|---:| +| 9B baseline | 0.514046 | 0.618295 | 1.132341 | -- | +| 1M | 0.512799 | 0.617428 | 1.130227 | -0.002115 | +| 50M | 0.512716 | 0.616039 | 1.128755 | -0.003586 | +| **100M** | **0.514628** | **0.623503** | **1.138131** | **+0.005789** | +| 150M | 0.509475 | 0.616560 | 1.126034 | -0.006307 | +| 200M | 0.514295 | 0.618990 | 1.133285 | +0.000944 | +| 250M | 0.508644 | 0.614303 | 1.122947 | -0.009395 | + +## Interpretation + +The cross-attention graft can outperform the frozen host at a selected +checkpoint, driven mostly by BBH. The trajectory is unstable: the 100M gain +disappears at 150M, partially returns at 200M, and reverses at 250M. This makes +the 100M result evidence for a useful intermediate state, not evidence that the +architecture reliably improves with additional continuation. + +Follow-up work should evaluate the sealed 100M checkpoint on the campaign's +held-out tasks and compare multiple seeds before making a broader capability +claim. Promotion rules should select on a fixed validation protocol and retain +the selected checkpoint rather than automatically using the final checkpoint. + +## Artifact evidence + +The local campaign artifacts are not committed to this repository. The hashes +below bind this report to their immutable completion receipts. + +| Checkpoint | Training completion SHA-256 | Evaluation completion SHA-256 | +|---:|---|---| +| 1M | `880dbbef7173c3356a9b42ed50946f7856ea7dcfa8b752726a98d97b13be002b` | `d6c1b16825dac97fcd42e62cf9bc61ec84b13b05f850fe6488a29cc79e11dcf4` | +| 50M | `dc23d8d18c4179dc96e68729ff66538c8599fac47344875a15cd157d922800dd` | `bacd0deeb4aaf986b6cbb5338af0bac3d0709b0f00eab469da7af542a5ce21ba` | +| 100M | `ea07790362318cb0e59b7c6804d1d5ccf9bd33062d3516872fc299318f7a7c32` | `414b5821cddcefe0ae9766ce811b41040dfda4bbe27648c6443f834227edee60` | +| 150M | `f5c4f3f64cc971524064e9ac55a4e8ba10947f7a97aba0a569c85e0d19f6a6fb` | `f69f219eef484681e92949f59b9c4a24e52c765efb0f36492f8cc4c408c7d1b5` | +| 200M | `07da1faeeeacd8304d3292abc3c1bc85fdd4d22078958ada53ffd383b4b5d73b` | `9a4a96ef9f6fd7f8f9ffb6d8b9e79234b17208f3f67a0a5be5f279058a4cc2f7` | +| 250M | `1f408110f1680e234a426a0ade31c113cd311b3384096ecaeff3433de5eb933b` | `a4c0f9cda514bafe31dcf9128e80e27914875b9c9ddec2e112c0af765a48851c` | + +The runtime receipt binds runner SHA-256 +`e727e864c0703be6003a0e707983660e05d24cb1e2d64e56a7dcc2cbd9eaa950` +and core SHA-256 +`a3cdcd11273b87ed6edbaf48990e304a915767a9de1c9cce7ec8d11fd6364b8a`.