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OLMo3-32B reportedly dropped to 0% on an arithmetic diagnostic, then rebounded

The poster calls the swing “mode-hopping” and says validation loss decreased smoothly throughout.

2 Sources, 3h ago, first seen 3h ago

TLDR

A post says OLMo3-32B’s arithmetic diagnostic accuracy reached 81% at 2.17 trillion pre-training tokens, fell to 0% at 2.19 trillion, then rose to 81.7% at 2.21 trillion. The poster calls it “mode-hopping” and says validation loss decreased smoothly throughout.

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2 Sources, first seen 3h ago

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Combined views

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2 Sources, first seen 3h ago

— likes— comments— saves— reposts

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2 Sources

Grigory Sapunov@che_shr_cat1/ During OLMo3-32B pre-training, accuracy on an arithmetic diagnostic hits 81% at 2.17T tokens, collapses to 0% at 2.19T, and jumps back to 81.7% at 2.21T. All while validation loss decreases smoothly. The phenomenon: mode-hopping. 🧵3h
Jiaxin Wen@jiaxinwen22RT @che_shr_cat: 1/ During OLMo3-32B pre-training, accuracy on an arithmetic diagnostic hits 81% at 2.17T tokens, collapses to 0% at 2.19T,…1h
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    2 Sources

    Grigory Sapunov@che_shr_cat1/ During OLMo3-32B pre-training, accuracy on an arithmetic diagnostic hits 81% at 2.17T tokens, collapses to 0% at 2.19T, and jumps back to 81.7% at 2.21T. All while validation loss decreases smoothly. The phenomenon: mode-hopping. 🧵3h
    Jiaxin Wen@jiaxinwen22RT @che_shr_cat: 1/ During OLMo3-32B pre-training, accuracy on an arithmetic diagnostic hits 81% at 2.17T tokens, collapses to 0% at 2.19T,…1h
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