Comment by tonymet

For those curious about how the model was trained, and examples of positive/negative sentiment, here's a "nutritional label" of sorts.

- SST-2 (stanford sentiment test) example dataset from IMDB reviews https://huggingface.co/datasets/stanfordnlp/sst2/viewer

- BERT https://aclanthology.org/N19-1423/

- DistilBert -- the optimized model OP was using https://arxiv.org/pdf/1910.01108

SST-2 may have been used to train or qualify BERT -- read the papers to get the full story. I did a quick perusal.

It would be nice to have a nutritional label shared with Abstracts, showing the training data, with examples, and the base models.