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language: en
tags: [autoscientist, adaption-labs, qlora, mathcode, dpo]
base_model: Qwen/Qwen2.5-0.5B-Instruct
datasets: [Rishidar/autoscientist-mathcode-dataset]
---
# AutoScientist Competition — Mathcode Model
Qwen2.5-0.5B-Instruct adapted for **mathcode** via Adaption Labs AutoScientist v5:
4-bit QLoRA SFT (r=32, alpha=64) then DPO (beta=0.1) on chosen/rejected pairs.
- DPO reward accuracy: 0.8181818181818182
- DPO reward margin: 8.761996030807495
Dataset: [Rishidar/autoscientist-mathcode-dataset](https://huggingface.co/datasets/Rishidar/autoscientist-mathcode-dataset).
Also mirrored on Kaggle: rishidard/autoscientist-mathcode-qlora.
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