A Comprehensive Comparison of Pre-training Language Models
Abstract: Recently, the development of pre-trained LLMs has brought NLP tasks to the new state-of-the-art. In this paper we explore the efficiency of various pre-trained LLMs. We pre-train a list of transformer-based models with the same amount of text and the same training steps. The experimental results shows that the most improvement upon the origin BERT is adding the RNN-layer to capture more contextual information for short text understanding. But the conclusion is: There are no remarkable improvement for short text understanding for similar BERT structures. Data-centric method[12] can achieve better performance.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.