sst
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All datasets matching “sst”sst2
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Dataset Summary
The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the
compositional effects of sentiment in language. The corpus is based on the dataset introduced by Pang and Lee (2005)
and consists of 11,855 single sentences extracted from movie reviews. It was parsed with the Stanford parser and
includes a total of 215,154 unique phrases from those parse trees, each… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/sst2.sst5
Stanford Sentiment Treebank - Fine-Grained
Stanford Sentiment Treebank with 5 labels: very positive, positive, neutral, negative, very negative
Splits are from:
https://github.com/AcademiaSinicaNLPLab/sentiment_dataset/tree/master/data
Training data is on sentence level, not on phrase level!
sst2
Stanford Sentiment Treebank - Binary
Stanford Sentiment Treebank with 2 labels: negative, positive
Splits are from:
https://github.com/AcademiaSinicaNLPLab/sentiment_dataset/tree/master/data
Training data is on sentence level, not on phrase level!
rendered-sst2
Rendered SST-2
The Rendered SST-2 Dataset from Open AI.
Rendered SST2 is an image classification dataset used to evaluate the models capability on optical character recognition. This dataset was generated by rendering sentences in the Standford Sentiment Treebank v2 dataset.
This dataset contains two classes (positive and negative) and is divided in three splits: a train split containing 6920 images (3610 positive and 3310 negative), a validation split containing 872 images (444… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/rendered-sst2.sstThe Stanford Sentiment Treebank, the first corpus with fully labeled parse trees that allows for a
complete analysis of the compositional effects of sentiment in language.MICO-SST2
MICO SST-2 challenge dataset
Mico Argentatus (Silvery Marmoset) - William Warby/Flickr
For the accompanying code, visit the GitHub repository of the competition: https://github.com/microsoft/MICO/.
Getting Started
The starting kit notebook for this task is available at: https://github.com/microsoft/MICO/tree/main/starting-kit.
In the starting kit notebook you will find a walk-through of how to load the data and make your first submission.
We also provide a library… See the full description on the dataset page: https://huggingface.co/datasets/szanella/MICO-SST2.