| --- |
| 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](https://github.com/NiLabs-Models/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 |
|
|
| ```bash |
| 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. |
|
|
