Segment 52
This sub-session focused on diagnosing why the DFlash drafter for Qwen3.6-27B was plateauing at much lower acceptance than expected. First, the user built a comprehensive evaluation harness on CT129 that extracted hidden states from fresh coding prompts and ran drafter inference side-by-side with the z-lab reference model, revealing a 4x gap (τ≈3.0 vs τ≈12.4). Tracing the root cause led to an architectural mismatch: the fc projection used only 4 of 5 target layers, omitting layer 61 which carries the richest next-token information. A deeper investigation into training logs and code comparison against the official speculators repository uncovered three critical bugs: noise was corrupting the target logits by being applied to the combined hidden state tensor before extracting the last layer; the fc included the target layer, creating a shortcut where the same information appeared in both conditioning and loss target; and the loss function used soft KL divergence with streak weighting instead of the paper's hard cross-entropy, diluting gradients. The user abandoned the current run, implemented all three fixes (split hidden states so noise only applies to fc input, revert fc to 4-layer input matching official architecture, switch loss to pure hard CE with gamma=7.0), and launched v5 training run which is now running with early metrics showing comparable accuracy.
Chunks
- The Evaluation That Changed Everything: Building Infrastructure to Uncover Three Critical Bugs in DFlash Drafter Training
- The Three-Bug Diagnosis: How Systematic Code Comparison Uncovered Critical Flaws in DFlash Drafter Training
- The Three-Bug Exorcism: How a 4x Performance Gap Was Traced, Diagnosed, and Fixed in DFlash Drafter Training