MT-DNN-SMARTLARGEv0

Reported on 4 benchmarks across 1 task · 1 paper · 3 SOTA

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

Natural Language Processing4 results

Natural Language InferenceonSciTail
% Dev Accuracy· 2019-11-08
96.6
SOTA
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Natural Language InferenceonSciTail
% Test Accuracy· 2019-11-08
95.2
SOTA
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Natural Language InferenceonSNLI
% Dev Accuracy· 2019-11-08
92.6
SOTA
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Natural Language InferenceonSNLI
% Test Accuracy· 2019-11-08
91.7
best: 94.7 (UnitedSynT5 (3B))
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437