README.md

metadata

license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-3B-Instruct
library_name: peft
tags:
  - competitive-programming
  - codeforces
  - qlora
datasets:
  - open-r1/codeforces-cots

Ladder-3B (unevaluated)

A QLoRA adapter for Qwen2.5-Coder-3B-Instruct, trained on verified Codeforces reasoning traces with Ladder.

This model has not been evaluated. There is no pass@1 for it, and none is claimed. It is stored here so the weights are not stranded on a temporary disk, and so any GPU can pick it up and score it. The repository stays private until there are measured numbers to publish with it.

Training

Base	unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit
Method	QLoRA, 4-bit, rank 32, loss on the assistant turn only
Data	2,271 traces, each verified by executing its solution against the problem's own tests
Steps	150, effective batch 16, context 8,192
Hardware	Tesla T4, 5.05 h, 594.9 tok/s, peak VRAM 6.78 GB

Evaluating it

git clone https://github.com/NiLabs-Models/ladder
ladder eval --config configs/ladder-3b-kaggle.yaml                  # base
ladder eval --config configs/ladder-3b-kaggle.yaml --adapter <this> # tuned

Scoring runs generated programs against real Codeforces test cases. No model-as-judge, no similarity metric.

Known limitations

• Python only; most competitive programming is C++.
• Trained on the 30% of the corpus short enough to fit 8,192 tokens. The median trace is ~13,770 tokens, so the hardest problems are disproportionately absent.
• Codeforces checker and interactive problems are excluded from evaluation.