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The expression computes one minus the ratio of the later window mean to the earlier window mean, then converts to percent. With the supplied means it gives about 46.52465%. This is a reduction in the selected average gradient norm, not a percentage gain in capability or a replicated effect across training runs.
Terms & definitions
| Term | Meaning in this source |
|---|---|
| percent | Relative reduction of the stated window means |
How it works
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Original context
Read the surrounding source passage
Appendix B. Selected calculations and numerical checks The adjacent-window calculation is The largest evaluation-loss decrease is The full recorded evaluation-loss reduction is
Exact original notation
100\left(1-\frac{15.343834018707275}{28.693284511566162}\right)=46.52465104675545%.Related builds
Sources & provenance
100\left(1-\frac{15.343834018707275}{28.693284511566162}\right)=46.52465104675545%.
100\left(1-\frac{15.343834018707275}{28.693284511566162}\right)=46.52465104675545%.