Equation 4 · Part 10 · How a Model Actually Gets Small Enough to Run on a Phone

subscript

\sigma(z)_i = \frac{\exp(z_i / T)}{\sum_j \exp(z_j / T)}

subscript

What this part means

The lower label selects a particular version, component, or indexed member of the quantity. For example, x₀ and xₜ can be values at different positions.

Its job in the formula

A subscript distinguishes a version, component, step, or member of a quantity. It does not automatically mean multiplication.

Full expressionsubscriptArticle meaning

The passage around this formula

Distillation recovers it by training the small “student” network against the large “teacher” network’s full output distribution rather than against the label alone. Write the teacher’s and student’s pre-softmax outputs for a given input as $z_t$ and $z_s$ . A softmax with a temperature T is $\sigma(z)_i = \frac{\exp(z_i / T)}{\sum_j \exp(z_j / T)}$ . At T=1 this is the ordinary softmax used for prediction. Raising T flattens the distribution, pulling the small probabilities assigned to wrong classes up toward visibility, which is exactly the dark knowledge the method wants to expose. The training objective blends two terms: ordinary cross-entropy against the true label, and a match between the student’s and teacher’s…

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Learn the underlying idea

A subscript is a label attached below a symbol. It often selects a time step, component, category, or member of a sequence.

Open the illustrated subscripts: which member of a family? guide →

Sources cited in the article section

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