The Model Was Never the Bottleneck: What Shipping a Text Classifier Into a Government Office Taught
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The Model Was Never the Bottleneck: What Shipping a Text Classifier Into a Government Office Taught
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This story was originally published on HackerNoon at: https://hackernoon.com/the-model-was-never-the-bottleneck-what-shipping-a-text-classifier-into-a-government-office-taught.
We shipped a Word2Vec+LSTM over a more accurate BERT, then load testing showed the model was 0.3% of the wall-clock time. The queue was five human reviewers.
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We built a classifier that sorts incoming citizen appeals into complaints, applications and proposals, and routes them to the right department. BERT was the most accurate model we tested. We shipped a smaller Word2Vec+LSTM instead. Then load testing showed that neither choice mattered much, because the queue was never in the GPU. It was in the five people doing review.