25 lines
1.3 KiB
Markdown
25 lines
1.3 KiB
Markdown
---
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license: apache-2.0
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base_model: Qwen/Qwen3-4B
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pipeline_tag: text-generation
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tags:
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- deepshopper
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- recommendation
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- fashion
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- outfit
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---
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# DeepShopper Mapper (Qwen3-4B)
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Stage 1 of the **DeepShopper** 2-step recommender brain (Mapper → retrieval → Reducer).
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The **Mapper** maps a user need → a structured, catalog-agnostic query plan:
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`{num_items, reasoning, outfit:[{role, query}]}` — it defines *what to look for*.
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- **Base:** Qwen/Qwen3-4B, full SFT (3 epochs, lr 2e-5, eff-batch 8, max-len 2048).
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- **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).
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- **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%.
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- **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").
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- **Caveat:** men's-side outputs can show a 2-item bias / role-label slips under free generation (AMZ-male source data).
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Code: https://github.com/clijo/reco-rl (branch outfit_bundle).
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