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StevenMup2004/lab22-dpo-vn
lab22-dpo-vn is a machine learning model from StevenMup2004. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
This repository contains the DPO LoRA adapter trained for Lab 22 DPO/ORPO Alignment. The run was executed on Kaggle T4 using Qwen2.5-3B as the base model.
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From the Hugging Face model README
This repository contains the DPO LoRA adapter trained for Lab 22 DPO/ORPO Alignment. The run was executed on Kaggle T4 using Qwen2.5-3B as the base model.
unsloth/Qwen2.5-3B-bnb-4bitThe model was trained in two stages:
SFT-mini adapter
5CD-AI/Vietnamese-alpaca-gpt4-gg-translated2e-4adapters/sft-miniDPO adapter
argilla/ultrafeedback-binarized-preferences-cleaned0.15e-7adapters/dpo16320.0unsloth8 fixed prompts were evaluated across helpfulness and safety.
| Category | SFT-only | SFT+DPO | Tie |
|---|---|---|---|
| Overall | 1/8 | 1/8 | 6/8 |
| Helpfulness | 0/4 | 1/4 | 3/4 |
| Safety | 1/4 | 0/4 | 3/4 |
Judge output showed that DPO improved one helpfulness case, while SFT-only won one safety case. Most prompts were ties, suggesting the DPO adapter made limited but measurable behavioral changes in this short T4 run.
Small benchmark slices were used for the lab smoke evaluation.
| Benchmark | SFT-only | SFT+DPO | Delta |
|---|---|---|---|
| IFEval | 0.000 | 0.000 | +0.000 |
| GSM8K | 1.000 | 1.000 | +0.000 |
| MMLU | 0.667 | 0.667 | +0.000 |
| AlpacaEval-lite | 0.500 | 0.500 | +0.000 |
The benchmark scores were flat in this run, which is expected for a small DPO experiment with limited preference data and sampled evaluation sets.
The merged SFT+DPO model was exported to GGUF for local serving.
Qwen2.5-3B.Q4_K_M.ggufThis adapter is a course lab artifact for studying preference learning and alignment behavior. It is suitable for demonstration, qualitative comparison, and small-scale experimentation.