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abidlabs
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Model Details
Model Provider
abidlabs
Model Tree
Qwen/Qwen3-0.6B-Base
Input Modalities
Output Modalities
Supported Functionality
q_proj,k_proj,v_proj,o_proj,gate_proj,up_proj,down_projprompt + suffix_i + letter_i, loss read at the single answer-letter
position, restricted CE over the candidate option-letter tokens of the frozen LM head
(never materialising full-vocab logits)pngwn/typed-decisions-v2 @ 74a8ed2d0d28955351805f7829d7149961172f88
(train 31,109 states / 45,932 decisions)a100-large (torch 2.14.0+cu130, transformers 5.17.0, peft 0.21.0)Final calibration-split eval (n=640 decisions, quick_eval health metric): acc 0.6234, NLL 1.2755 (eval acc climbed 0.473 @ step 200 → 0.623 @ end; train loss 1.33 → ~0.4).
Note: this is the in-training quick-eval on a cal subsample, not the report's matched 5,214-decision test harness with temperature scaling — the report's full-eval numbers for arm B (accuracy 0.7518 on test, ECE 0.0154 after temperature scaling) were produced by a separate evaluation pipeline not re-run here.
Load Qwen/Qwen3-0.6B-Base + these adapters, prefill a typed-decision prompt once, then read the
next-token distribution restricted to the candidate option letters (" A".." Z" are single tokens
in the Qwen tokenizer) — one shared KV cache, one branch per decision.