license: cc-by-4.0
pretty_name: cascade held-out eval pool (24h-lagged reveal)
tags:
- time-series
- forecasting
- benchmark
cascade eval pool — lagged public reveal
Daily snapshots of the held-out evaluation pool used by the cascade subnet, built from the tsbench-forge live catalog of real public time series across the 7 GIFT-Eval domains.
Each snapshot is revealed 24h AFTER it was used for scoring (as_of is a
closed UTC day). Because the pool rotates daily, a released snapshot is always
for a round that is already scored — it lets anyone reproduce the leaderboard
without exposing the round currently in play.
Layout
snapshots/<YYYY-MM-DD>/ one folder per revealed day (as_of)
<series_id>.npy float32, freshest context_length + horizon points
metadata.json {series_id: {freq, seasonal_period, domain, source}}
provenance.json build config (context_length, horizon, builder_version)
Scoring is identity-agnostic: MASE uses seasonal_period, CRPS/WQL use the
values + a model's quantiles, and the KOTH cluster-bootstrap groups windows by
source. Re-cut windows of context_length + horizon, forecast the horizon,
and the metrics reproduce byte-for-byte.
Latest snapshot — 2026-08-01
- series: 3504
- domains: transport=2545, energy=367, healthcare=227, nature=193, econ_fin=74, sales=66, web_cloudops=32
- cadences: min=2566, D=337, 30min=258, 15min=134, 5min=122, H=53, 10min=15, 6min=10, 240S=6, 15S=1, 10S=1, 1S=1
This is an evaluation set, not training data. Publishing it to train on would contaminate the benchmark it exists to measure.