Empirical power-law scaling governs language model loss versus model size, data size, and compute, enabling optimal allocation of training compute.
18 [GRK17] Scott Gray, Alec Radford, and Diederik P Kingma
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Scaling Laws for Neural Language Models
Empirical power-law scaling governs language model loss versus model size, data size, and compute, enabling optimal allocation of training compute.