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Models/SMART-BERT

SMART-BERT

Reported on 9 benchmarks across 4 tasks · 1 paper · 2 SOTA

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

Natural Language Processing9 results

Semantic Textual SimilarityonQuora Question Pairs
Dev F1· 2019-11-08
88.5
SOTA
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Paraphrase IdentificationonQuora Question Pairs
Dev F1· 2019-11-08
88.5
SOTA
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Natural Language InferenceonMultiNLI
Dev Matched· 2019-11-08
85.6
best: 91.1 (SMARTRoBERTa)
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Natural Language InferenceonMultiNLI
Dev Mismatched· 2019-11-08
86
best: 91.3 (SMARTRoBERTa)
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Semantic Textual SimilarityonSTS Benchmark
Dev Pearson Correlation· 2019-11-08
90
best: 92.8 (SMARTRoBERTa)
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Semantic Textual SimilarityonSTS Benchmark
Dev Spearman Correlation· 2019-11-08
89.4
best: 92.6 (SMARTRoBERTa)
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Semantic Textual SimilarityonQuora Question Pairs
Dev Accuracy· 2019-11-08
91.5
best: 92.6 (FreeLB)
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Sentiment AnalysisonSST-2 Binary classification
Dev Accuracy· 2019-11-08
93
best: 96.9 (SMARTRoBERTa)
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437
Paraphrase IdentificationonQuora Question Pairs
Dev Accuracy· 2019-11-08
91.5
best: 92.6 (FreeLB)
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization arXiv:1911.03437