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learn-deeply t1_ixew0do wrote

tl;dr a thinly disguised ad comparing a zero-shot model with a fine-tuned model, of course the fine tuned model is going to be better. the lack of intellectual honesty really encourages me to try snorkel

also, /u/bradenjh good job pretending that you have no affiliation with the company

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bradenjh OP t1_ixeyajh wrote

Ha! If I was trying to pretend no affiliation, u/learn-deeply/ I probably wouldn't have a username literally matching the author string of the post?

You may also want to give it another read—the GPT-3 models are fine-tuned, that's the point! (The GPT-3 zero-shot baseline that I assume you're referencing is mentioned once as a curiosity but not compared to beyond that). You can even look at the full cross-product of fine-tuning RoBERTa vs GPT-3 on GT labels vs weak labels. With the larger training sets—the distilled and combined set of ~60k—they score essentially identically (within 0.1 point). i.e. you simply don't need all that GPT-3 capacity; all you need is the relevant information that it has for your problem.

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Acceptable-Cress-374 t1_ixg7d43 wrote

TBF, the article is pretty SEO-y and heavily uses bolded words that repeat throughout the article.

The research part is top-notch, tho, and opens up a lot of avenues for further training based on the (unusable at the amateur level) LLMs available now. Great work and thanks for sharing!

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