Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
Open paper
Benchmark
Model
Rank
Results
natural-language-inference-on-snli
4096D BiLSTM with max-pooling
#54
% Test Accuracy: 84.5
% Train Accuracy: 85.6
Parameters: 40m
semantic-textual-similarity-on-mrpc
InferSent
#30
Accuracy: 76.2%
F1: 83.1%
Rank counts only results with a code link.