The current state-of-the-art on SST-2 Binary classification is T5-11B. See a full comparison of 87 papers with code.

It was parsed with the Stanford parser and includes a total of 215,154 unique phrases from those parse trees, each annotated by 3 human judges.

Repo for AI Model Share Tutorials. Contribute to AIModelShare/aimodelshare_tutorials development by creating an account on GitHub.

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 ...

Supported Tasks and Leaderboards The leaderboard for the GLUE benchmark can be found at this address. It comprises the following tasks: ax A manually-curated ...

This model is a fine-tuned version of bert-large-uncased originally released in BERT: Pre-training of Deep Bidirectional Transformers for Language ...

Textual similarity results on SST2 dataset in glue benchmark. Left: 125M, Right: 345M. The green line indicates the performance without pruning.

Stanford Dataset for predicting Sentiment from longer Movie Reviews.

AdvGLUE is the Adversarial GLUE Benchmark. ... The Stanford Sentiment Treebank (SST-2). Statistics. Word Sentence ...

Powering AWS purpose-built machine learning chips. Blazing fast and cost effective, natively integrated into PyTorch and TensorFlow and integrated with your ...