mdeff/fma resource
FMA: A Dataset For Music Analysis observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3561
- days_rel: n/a
- days_push: 1336
- n_releases_24m: 0
Adoption not part of the score
2653 stars · 458 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
FMA is an open dataset of 106,574 Creative Commons-licensed music tracks (917 GiB, 343 days of audio) with metadata, pre-computed features, and a 161-genre hierarchy, plus smaller subsets for benchmarking. It ships with Jupyter notebooks and code for reproducible music information retrieval research, notably genre recognition baselines.
Use cases
- train a music genre classification model
- benchmark deep learning models on audio
- find a large open music dataset for research
- compare against GTZAN-style genre recognition baselines
- analyze music metadata and tags with pandas
- evaluate music information retrieval algorithms
When to choose
- you need large-scale, openly licensed full-length audio for MIR or deep learning research
- you want pre-computed features and metadata alongside raw audio
- you need a reproducible benchmark with train/validation/test splits
When to avoid
- you need commercial or top-40 music
- you only need small labeled clips and GTZAN suffices
- you need streaming-quality audio without large downloads
Facets
dataset · maturity stable
machine-learning data-science audio-processing nlp machine-learning data-science deep-learning python cross-platform music-information-retrieval audio-dataset genre-classification creative-commons open-data benchmark audio
6 sources
- readme: https://github.com/mdeff/fma · fetched 2026-08-28 · 3d8646626c52
- homepage: https://arxiv.org/abs/1612.01840 · fetched 2026-08-29 · 4a6a8ec2965a
- site_page: https://info.arxiv.org/about/donate.html · fetched 2026-08-29 · cca9c3a11c56
- site_page: https://info.arxiv.org/about/ourmembers.html · fetched 2026-08-29 · 47cbc55ff1de
- site_page: https://info.arxiv.org/about · fetched 2026-08-29 · a1f16f915a9a
- site_page: https://info.arxiv.org/labs/index.html · fetched 2026-08-29 · b14a8d05a0ec
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| mdeff/fma | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem