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What is (2022 Model Capacity) Scaling Laws Vs Model Architectures - How Does Inductive Bias Influence Scaling about?

This paper investigates the impact of inductive bias and model architecture on the scaling laws of language models, particularly focusing on Transformer models. Through extensive experiments with ten diverse architectures, the authors find that architecture significantly influences scaling behavior, with varying performance across different scales. The study highlights the complexities of scaling models and suggests that the best-performing architecture can differ based on the compute region.

Author

m13829992306

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EN