Summary

In this chapter, we went through some advanced theories. The principle of compositionality is not an intuitive concept. The principle of compositionality means that the transformer model must understand every part of the sentence to understand the whole sentence. This involves logical form rules that will provide links between the sentence segments.

The theoretical difficulty of sentiment analysis requires a large amount of transformer model training, powerful machines, and human resources. Although many transformer models are trained for many tasks, they often require more training for specific tasks.

We tested RoBERTa-large, DistilBERT, MiniLM-L12-H384-uncased, and the excellent BERT-base multilingual model. We found that some provided interesting answers but required more training to solve the SST sample we ran on several models.

Sentiment analysis requires a deep understanding of a sentence and extraordinarily complex sequences. So, it made sense to try RoBERTa...