A Training Schedule (gantt)

Demo note. This note demonstrates what the SciDraft Hugo theme can do for academic and scientific publishing — for research institutions, researchers and students. Its content is demonstration material only: readers should ignore whether the demo content is correct.

A training run has a shape in time as well as in the loss curve: data preparation that nothing else can start without, a warmup whose length is set by the step size, a long stable phase, and a cooldown whose purpose is to end at a point the optimiser has settled into.

This note uses a Gantt chart, which is the diagram type for anything where the order and duration of phases is the content. The bars below are illustrative rather than measured, and the durations are the ones a small decoder run would typically use.

gantt
    title A training schedule for a small decoder
    dateFormat YYYY-MM-DD
    axisFormat %b %d
    section Data
    Tokenise and shard          :done,    data,   2026-09-01, 3d
    section Training
    Warmup                      :done,    warm,   after data, 2d
    Stable phase                :active,  stable, after warm, 9d
    Cooldown                    :         cool,   after stable, 3d
    section Evaluation
    Checkpoint sweeps           :         eval,   after cool, 2d

The dependency arrows matter more than the bar lengths: the schedule encodes the constraint that evaluation cannot begin before a checkpoint exists, and the warmup cannot be skipped because the step size at initialisation is larger relative to the curvature than it is later in the run.