AIWORKX-KR-KG-Reasoner-0.5B-v0.10
Overview
AIWORKX-KR-KG-Reasoner-0.5B-v0.10 is a small Korean-specialized language model fine-tuned from Qwen/Qwen2.5-0.5B-Instruct.
This model was created as a local MVP for K-AI leaderboard submission experiments. The training pipeline uses copyright-safe structured factual triples, converts them into a local knowledge graph, and generates Korean supervised fine-tuning data through deterministic rule-based templates.
Base Model
- Base model:
Qwen/Qwen2.5-0.5B-Instruct
- Fine-tuning method: QLoRA supervised fine-tuning
- Adapter merge: LoRA adapter merged into the base model
Training Data
The training data was generated from local structured factual triples.
Pipeline:
- Local factual triples
- Knowledge graph nodes, edges, and evidence units
- Rule-based Korean QA generation
- SFT JSONL conversion
- QLoRA fine-tuning
No OpenAI API, paid API, live external API, or web crawling was used in this MVP.
Data Policy
The dataset uses structured factual triples rather than copied prose. The project is designed around copyright-safe factual data and knowledge-graph-based training.
Intended Use
- Korean factual QA
- Knowledge-graph-grounded QA
- Triple-to-text generation
- Evidence-based relation extraction
- Small-scale K-AI leaderboard submission experiment
Limitations
This is a small experimental model trained on a very small dataset. It may overfit to the rule-based format and may not perform well on broad open-domain tasks. It should not be used for high-stakes decisions.
Version
- Version: 0.10
- Project motto: Copyright-safe factual data + Knowledge Graph + Local QLoRA
