Sensitivity Analysis on Transferred Neural Architectures of BERT and GPT-2 for Financial Sentiment Analysis. (arXiv:2207.03037v1 [cs.CL])

The explosion in novel NLP word embedding and deep learning techniques has
induced significant endeavors into potential applications. One of these
directions is in the financial sector. Although there is a lot of work done in
state-of-the-art models like GPT and BERT, there are relatively few works on
how well these methods perform through fine-tuning after being pre-trained, as
well as info on how sensitive their parameters are. We investigate the
performance and sensitivity of transferred neural architectures from
pre-trained …

analysis arxiv bert financial gpt gpt-2 neural architectures sentiment sentiment analysis