v9

v9 (scale 1.00)

This is a standalone, merged BF16 checkpoint derived from tojointhecommunity/affine-5efg6cm3yl-king. It applies a scaled selective-fallback LoRA trained on preserved positive turns and sanitized, task-specific alternatives for high-confidence negative turns. It does not require a runtime router, custom Python code, or a PEFT adapter.

Training summary

• Exact parent revision: 7c1c94cd0572475d4b3e3fde5258b0e79563d54f
• Adapter scale at merge: 1.00
• LoRA: r16, alpha64, dropout0.0, all-linear
• Objective: DPO, beta0.2, learning rate 1.0e-07, 2.0 epoch
• Context during training: 8192 tokens
• Training GPUs: 2 x NVIDIA H200
• Selected target mix before context filtering: 100% preserve / 0% fallback

Held-out preference proxy

The table compares the scaled adapter with the untouched pinned parent. These small held-out metrics selected the merge strength; they are not a substitute for the exact full Affine duel on the dedicated evaluator.

Qualification status

Experimental candidate. Before submission, run exact stock-vLLM Affine duels, the exploit-pattern audit, repository preflight, and the official submission client check. selective_fallback_provenance.json contains the machine-readable training and merge record.