SST-5
Introduced by Socher et al. in Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
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.
Benchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
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SST-5 Fine-grained classification
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Heinsen Routing + RoBERTa Large
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SST-5
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SetFit + OCD
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SST-5
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GCN
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Papers
| Paper | Code | Results | Date | Stars |
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