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forwarder1121/
twotower-yelp-baseline

Name: twotower-yelp-baseline
Availability: InStock

Yelp/yelp_review_full

mit

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Two-Tower Recommendation Model (Yelp Baseline)

This repository contains a baseline Two-Tower recommendation model trained on the Yelp Dataset.

📘 Model Summary

Architecture: Two-Tower (User Tower + Item Tower)
User Tower: Embedding table trained end-to-end
Item Tower: MLP taking pretrained POI embeddings (772-dim)
Loss: Binary cross entropy with negative sampling
Negative Samples per interaction: 10
Training Epochs: 3 (CPU-based)

The model was trained as a foundational retrieval baseline to validate end-to-end recommendation pipeline feasibility.

📂 Included Files

twotower_model.pt — Trained model weights
.gitattributes — Git LFS tracking file

⚠ Limitations

This is a baseline model and achieves low performance due to:

user_id-only embeddings (no behavioral or text features)
CPU-only training (limited epochs)
sparse interactions across many users

🚀 Future Improvements

Add user textual embeddings (LLM-based persona summaries)
Add sequence-based behavioral embeddings
Apply hard negative sampling & better contrastive losses
Train on GPU for larger batch sizes & deeper models

📄 Usage Example (Python)

python

import torch
from model import TwoTowerModel  # Your model class

model = TwoTowerModel(num_users=851921, emb_dim=128)
model.load_state_dict(torch.load("twotower_model.pt"))
model.eval()

forwarder1121/twotower-yelp-baseline