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Hynek Kydlíček
@HKydlicek
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MLE @huggingface 🤗 Prague, CZ 🇪🇺 eu/acc
Czech Republic
Joined December 2021
This is @karpathy 🐐 grade content on distributed training!
New Picotron video on distributed training is out ! This time you will learn how Distributed Data Parallel from Pytorch works in theory and how to implement it yourself ! Link of the video below 🧵
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@420_gunna @vwxyzjn @natolambert @hamishivi EM == string Exact match, usually it's rather quasy exact match tho
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@ryanmart3n @NeginRaoof_ We haven't uploaded re-extracted answers yet and yes we re-extracted the numina1.5
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@vwxyzjn @natolambert @hamishivi 🤗 When I switched from EM to math-verify we hoped by about 15% on most models
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There is pretty much nothing new in 0.5.2, compared to 0.5.1😅, so that won't help. I am not sure what you sourced your question/answers from, but at least for Numina I noticed that a lot of ground-truths are in very malformed latex, so one way to increased the recall is to re-extract the answers with LLM. We have done that but haven't run the final ablation yet.
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@vwxyzjn @natolambert @hamishivi You should switch to math-verify especially because of em on gsm8k sucks
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RT @anton_lozhkov: LLM Reasoning labs will be eating good today🍔 We commandeered the HF cluster for a few days and generated 1.2M reasonin…
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@Teknium1 I don't mind to review it, but won't do it myself. Should be literally two lines of code tho
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RT @LoubnaBenAllal1: We just published the second OpenR1 update with OpenR1-220k-Math, our new large-scale dataset for mathematical reasoni…
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@Noahpinion Not true at all; the biggest moat is the inherent byproduct that you need to obtain during the creation of LLM: infrastructure and data.
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