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Model: ramankrishna10/npc-reason
Source: Original Platform

README.md

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+---
+license: mit
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+tags:
+  - math
+  - reasoning
+  - verifiable
+  - rlvr
+  - gguf
+pipeline_tag: text-generation
+---
+
+# NPC Reason 1.5B
+
+A math-reasoning model whose every load-bearing arithmetic step emits a mechanically-checkable
+assertion in the form `<<EXPR = RESULT>>`. Specialized from DeepSeek-R1-Distill-Qwen-1.5B (MIT).
+The point is not just a final answer. It is that a pure-code checker can re-execute every step and
+confirm the chain, so "verifiable-rate" is not the model's opinion. Anyone can run the checker.
+
+## Results (frozen held-out eval, n=500, GSM8K + MATH-500, greedy, format prompt)
+
+| metric                 | base R1-Distill | SFT (V4 distill) | NPC Reason (RL) |
+|------------------------|----------------:|-----------------:|----------------:|
+| verifiable-rate        |           0.0%  |          76.8%   |        76.2%    |
+| accuracy               |          61.6%  |          65.8%   |        66.6%    |
+| verified-and-correct   |           0.0%  |          58.0%   |        59.6%    |
+
+verified-and-correct (both axes) is the headline. The full arc is shown on purpose, not just the
+best column.
+
+## What actually happened (plain language, no overclaiming)
+
+- **The base model produces zero mechanically-verifiable chains, even when asked for the format.**
+  Only 1 of 500 base outputs even contained a `<<` marker.
+- **The SFT distillation did the heavy lifting: 0 to 76.8% verifiable.** Training on a corpus of
+  DeepSeek-V4 chains that the frozen verifier confirmed (verifiable AND correct, 7,546 kept of
+  13,245 generated) transferred the grounding. Accuracy rose (61.6 to 65.8), it was not bought by
+  sacrificing correctness.
+- **RLVR/GRPO against the frozen verifier was a stable refinement, not a decisive gain.** It moved
+  verified-and-correct +1.6pp (58.0 to 59.6) and accuracy +0.8pp, with verifiable flat (-0.6pp).
+  On n=500 that is roughly 8 problems. The RL model and the SFT model are statistically about even.
+- **The shipped model is the RL checkpoint** (marginally best on the headline). **The SFT model is
+  statistically equivalent and available** as a fallback. Either is a defensible "NPC Reason".
+- **The pre-registered 90% verifiable bar was NOT met (stuck near 77%).** It was deliberately not
+  chased into instability. This is the open limitation and the next frontier.
+- Accuracy includes the greedy no-answer floor. The same greedy decoding is used for base and tuned
+  models, so the comparisons are apples-to-apples.
+
+## The verifier (the methodological core)
+
+A pure-code Python/SymPy checker, frozen at sha256 `d5d146cf...`, used as BOTH the evaluation
+metric AND the RL reward (byte-identical both times). A chain is VERIFIABLE iff every load-bearing
+`<<EXPR=RESULT>>` assertion re-executes correctly AND the final answer composes from the last step.
+Correctness (final == gold) is a separate, independent axis. The verifier is shipped with the model
+(`verifier/step_verifier.py`); users run it on the model's own outputs.
+
+## Methods finding worth keeping
+
+GRPO with this hard, frozen, pure-code verifier reward trained STABLY: KL stayed flat (~0.0002),
+no length runaway, no mode collapse, no early-stop trip. This is notable because prior RL attempts
+in related work were unstable. RLVR with a clean verifier reward is a regime where a small model
+trains without collapsing. The lift was small here, but the stability is the keepable result.
+
+## Intended use and limits
+
+- Use: math problems where checkable, grounded reasoning steps matter (arithmetic and
+  arithmetic-reducible word problems). Prompt for the `<<EXPR = RESULT>>` format (see USAGE.md).
+- Math-first. Logic, proofs, and general chain-of-thought are NOT claimed and are future work.
+- Not a general chat model. The 1.5B reasoning ceiling applies. ~23% of format-prompt chains are
+  still not fully verifiable, the unverified tail.
+- Simulation/research artifact. Verify outputs with the included checker before relying on them.
+
+## Lineage and license
+
+- Base: DeepSeek-R1-Distill-Qwen-1.5B (MIT).
+- Training chains distilled from DeepSeek V4 (distillation permitted; output rights assigned to the
+  user). Released under MIT to match the base.
+- Attribution: Rama Krishna Bachu, Bottensor (Independent Research). ORCID 0009-0000-1298-0681.
+
+## Reproducibility
+
+The pre-registration was frozen BEFORE any training and an honest-null clause was in force.
+Frozen references:
+- Verifier: `VERIFIER.lock` sha256 `d5d146cf...`
+- Eval set: `EVAL.lock` sha256 `e1573cab...`
+- Pre-registration: `PREREG.lock` sha256 `b5a49437...`
+
+GGUF quantizations are provided with a per-quant decision-fidelity check vs the bf16 model
+(see `gguf_fidelity.md`); pick the recommended quant, do not choose on file size alone.