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Models/PSQ (Chen et al., 2020)

PSQ (Chen et al., 2020)

Reported on 7 benchmarks across 4 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 Processing7 results

Natural Language InferenceonQNLI
Accuracy· 2020-10-27
94.5
SOTA
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks arXiv:2010.14298
Natural Language InferenceonRTE
Accuracy· 2020-10-27
86.8
SOTA
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks arXiv:2010.14298
Semantic Textual SimilarityonMRPC
Accuracy· 2020-10-27
90.4
SOTA
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks arXiv:2010.14298
Linguistic AcceptabilityonCoLA
Accuracy· 2020-10-27
67.5
best: 82.7 (LTG-BERT-base 98M)
SOTA
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks arXiv:2010.14298
Natural Language InferenceonMultiNLI
Matched· 2020-10-27
89.9
best: 92.6 (Turing NLR v5 XXL 5.4B (fine-tuned))
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks arXiv:2010.14298
Semantic Textual SimilarityonSTS Benchmark
Pearson Correlation· 2020-10-27
0.919
best: 0.929 (MT-DNN-SMART)
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks arXiv:2010.14298
Sentiment AnalysisonSST-2 Binary classification
Accuracy· 2020-10-27
96.2
best: 97.5 (T5-11B)
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks arXiv:2010.14298