Codette Newton Star Hard

--- license: llama3.1 base_model: Raiff1982/codette-llama-3.1-8b-merged library_name: peft tags: [codette, star, lora, negative-result, research-artifact] --- # newton-star-hard — ⚠️ Research Artifact: Below-Baseline Result Second arm of a controlled STaR study. Trained on **350 keep-correct reasoning chains from difficulty-matched MMLU-Pro STEM** (61% keep yield — the data genuinely challenged the model). Scored **28.0% on GPQA-main** vs the untrained baseline's 34.0%: harder data *attenuated* the degradation seen with easy data (25.0%) but did not eliminate it. Notable provenance: trained free on a Kaggle T4 after working through six documented environment issues (all fixes committed to the repo), and one literal household power failure. Where there's a will. ## The STaR Study (GPQA-main, reason mode, n=100 per arm) | Adapter | Training data | GPQA | Verdict | |---|---|---|---| | newton (untrained baseline) | — | **34.0%** | reproduced to the decimal, 4 days apart | | newton-star-r | 350 keep-correct + 180 rationalized | *benchmark in progress* | complete STaR method | | newton-star-hard | 350 MMLU-Pro STEM keep-correct | **28.0%** | attenuated the harm, below baseline | | newton-star | 500 easy-science keep-correct | **25.0%** | regressed to chance | **Finding:** keep-correct self-taught reasoning *consolidates existing ability rather than extending it* — training data difficulty orders the outcome perfectly, but no keep-correct arm matched the untrained baseline. Full methodology, controls, and changelogs: [Codette-Reasoning](https://github.com/Raiff1982/Codette-Reasoning) (see `docs/CHANGELOG_2026-07-09.md`, `docs/CHANGELOG_2026-07-11.md`). Created by Jonathan Harrison (Raiff1982) · Raiff's Bits LLC

--- base_model: Raiff1982/codette-llama-3.1-8b-merged library_name: peft pipeline_tag: text-generation tags: - base_model:adapter:Raiff1982/codette-llama-3.1-8b-merged - lora - sft - transformers - trl --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or addit...

Source context: 0 downloads · 0 likes · Pipeline text-generation · Library peft · Repo Raiff1982/codette-newton-star-hard