The SST-5, also known as the Stanford Sentiment Treebank with 5 labels, is a dataset used for sentiment analysis. The SST-5 dataset consists of 11,855 single sentences extracted from movie reviews¹. It includes a total of 215,154 unique phrases from parse trees, each annotated by 3 human judges¹. Each phrase is labeled as either negative, somewhat negative, neutral, somewhat positive, or positive. This is why it's referred to as SST-5 or SST fine-grained.
Variants: SST-5 Fine-grained classification, SST-5
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Few-Shot Text Classification | SetFit + OCD | OCD: Learning to Overfit with … | 2022-10-02 |
Recent papers with results on this dataset: