Construct · 1 fields · 1 citations

neural scaling law: a standalone construct

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Machine learning

the empirical finding that a neural language model's loss falls as a power law in model size, data size and compute over wide ranges.

In machine learning, neural scaling law refers to the empirical finding that a neural language model's loss falls as a power law in model size, data size and compute over wide ranges. This meaning comes from Kaplan (2020) in arXiv.[1]

Unit
Recovery means
Measured by

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Nearby constructs

learning6 fields · 14 citationsjingle · one name, six constructs loss2 fields · 3 citationsjingle · one word, two constructs model3 fields · 3 citationsjingle · one word, three constructs

References

Kaplan, J., McCandlish, S., Henighan, T., Brown, T. B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J., & Amodei, D. (2020). Scaling Laws for Neural Language Models. arXiv. https://doi.org/10.48550/arxiv.2001.08361

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