GenSen

Reported on 6 benchmarks across 3 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing6 results

Natural Language InferenceonMultiNLI
Matched· 2018-03-30
71.4
best: 92.6 (Turing NLR v5 XXL 5.4B (fine-tuned))
SOTA
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning arXiv:1804.00079
Natural Language InferenceonMultiNLI
Mismatched· 2018-03-30
71.3
best: 92.4 (Turing NLR v5 XXL 5.4B (fine-tuned))
SOTA
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning arXiv:1804.00079
Semantic Textual SimilarityonSentEval
SICK-E· 2018-03-30
87.8
SOTA
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning arXiv:1804.00079
Semantic Textual SimilarityonSentEval
SICK-R· 2018-03-30
0.888
SOTA
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning arXiv:1804.00079
Semantic Textual SimilarityonQuora Question Pairs
Accuracy· 2018-03-30
87.01
best: 92.4 (data2vec)
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning arXiv:1804.00079
Paraphrase IdentificationonQuora Question Pairs
Accuracy· 2018-03-30
87.01
best: 92.4 (data2vec)
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning arXiv:1804.00079