A zoo script desk keeps adding labeled exhibit notes and wonders when training from scratch might catch a transferred model. How should they find out?
Select an answer to reveal the explanation.
Short Explanation
When might from-scratch catch the transferred model? Run a data-size sweep that keeps the split honest and look for a crossover. Do not assume fifty rows, throw out transfer on the first new label, or count rows with a kernel.
Full Explanation
Labeled-data volume is a factor in a transfer experiment, not a folklore threshold. A sweep that grows the in-domain set while holding the split honest can show whether a from-scratch run ever catches the transferred model. That crossover is measured, not assumed. Arbitrary cutoffs, discarding transfer on the first new label, and counting kernels do not answer the question.