---
license: apache-2.0
base_model: Qwen/Qwen3-4B
pipeline_tag: text-generation
tags:
- deepshopper
- recommendation
- fashion
- outfit
---

# DeepShopper Mapper (Qwen3-4B)

Stage 1 of the **DeepShopper** 2-step recommender brain (Mapper → retrieval → Reducer).
The **Mapper** maps a user need → a structured, catalog-agnostic query plan:
`{num_items, reasoning, outfit:[{role, query}]}` — it defines *what to look for*.

- **Base:** Qwen/Qwen3-4B, full SFT (3 epochs, lr 2e-5, eff-batch 8, max-len 2048).
- **Data:** [`flavianv/fashionrec-amz-mapper-50-50-sft`](https://huggingface.co/datasets/flavianv/fashionrec-amz-mapper-50-50-sft) — 10k gender-balanced rows; reasoning + per-slot queries generated in a single Qwen3-32B call per outfit (replaces an earlier procedural template).
- **Eval (k=1 plan→retrieval→reward harness):** mean reward **0.099 vs 0.021** zero-shot; pass@1>0.10 **17%→55%**, >0.15 3%→24%.
- **Usage:** system prompt = "DeepShopper Mapper… return JSON {num_items, reasoning, outfit:[{role, query}]}"; control item count via the need (e.g. "as a 4-item set" / "including top, bottom, footwear").
- **Caveat:** men's-side outputs can show a 2-item bias / role-label slips under free generation (AMZ-male source data).

Code: https://github.com/clijo/reco-rl (branch outfit_bundle).