README.md

metadata

title: Loopback Two-Tower Music Recommender
emoji: 🎧
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false
license: apache-2.0
short_description: Two-tower music recommender trained on Last.fm 1K

loopback

Open-source two-tower neural recommender trained on Last.fm 1K (15.3M listening events, 1.5M tracks).

• Code: https://github.com/DanielRegaladoUMiami/loopback
• Dataset: https://huggingface.co/datasets/DanielRegaladoCardoso/lastfm-1k-twotower
• Model: https://huggingface.co/DanielRegaladoCardoso/loopback-twotower

Architecture

User tower:  user_id  ──► Embedding ──► MLP ──► L2-norm
Track tower: track_id ──► Embedding ┐
             artist_id ─► Embedding ┴► MLP ──► L2-norm
                                      score = u·t · exp(temp)

Trained with symmetric InfoNCE + in-batch negatives (CLIP-style) and a learnable temperature.

Results

Metric	Value
Recall@10	0.0708
Recall@50	0.2172
Recall@100	0.3140

Evaluated on 847 held-out users against the full 1.5M-track catalog with seen-track filtering.