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AI / Machine Learning
TEKNOFEST 2026 - DualCore
A three-class query-product relevance system developed by Team DualCore for the TEKNOFEST 2026 E-Commerce Competition. The pipeline combines fine-tuned language models, a decision layer, and explainability tools within the competition runtime constraints.
Tech Stack
Gemma 4LoRAHistGradientBoostingvLLMDockerSHAP
Key Features
- Fine-tuned Gemma-4-12B with LoRA and built supervised hard-negative data using Gemma-4-31B as a teacher model
- Combined two LoRA adapters with a HistGradientBoosting decision layer
- Built a modular, deterministic vLLM and Docker inference pipeline
- Added SHAP, field-occlusion, attention, and what-if explainability
- Recorded the second-highest F1 score among finalists
- Reached 0.9452 Macro-F1 in query-disjoint cross-validation