Specify a learning-rate schedule and compare repeated updates from two starting points.
Name the expected effect, metric and what would count against the hypothesis.
Record fixtures, source, version, parameters, units, controls and how cases are split.
| Case and split | Baseline result | Changed result | Interpretation |
|---|---|---|---|
At learning rate 1, this quadratic oscillates without improvement; above 1, the distance from the minimum grows.
Record your new case and rerun the original cases after redesign.
Explain the mechanism, one exact result and what would overturn your conclusion.
This convex quadratic is a controlled teaching case, not a neural training benchmark.
Next test: _ . Project filename: _ . Work that is mine and tools I used: ____ .
Use fictional data. Download a resumable project before changing devices. On a shared device, turn remembering off and clear your work when finished.