F-ALBERT: A Distilled Model from a Two-Time Distillation System for Reduced Computational Complexity in ALBERT Model
Kyeong-Hwan Kim,
Chang-Sung Jeong
Abstract:Recently, language models based on the Transformer architecture have been predominantly used in AI natural language processing. These models, which have been proven to perform better with more parameters, have led to a significant increase in model size and computational load. ALBERT solves this problem by significantly reducing the number of parameters it retains by repeatedly reusing parameters. Although ALBERT significantly reduces the parameters it maintains, it requires a computational load similar to the… Show more
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