Question: In a concise analytical response, explain what beta = 1/40 changes in the training objective and why the dev set still matters when choosing beta.

Sample answer: Beta controls the contribution of a supplemental collection of 160,000 examples in the loss. In an objective that also uses 4,000 core examples, setting beta = 1/40 gives the supplemental collection the same total weight as the core collection, because 160,000 × 1/40 = 4,000. That is only one possible setting; beta should still be treated as a tunable hyperparameter and chosen using dev-set performance.

Key points:

• Beta scales the contribution of the supplemental data.
• The example compares 4,000 core examples with 160,000 supplemental examples.
• Beta = 1/40 makes the two collections equal in total influence.
• Beta is still selected by checking which value works best on the dev set.

Rubric: A strong response identifies what beta weights, explains why 1/40 equalizes the total contribution in this example, and states that beta should be tuned on the dev set rather than assumed to be fixed.