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Models/T5-Base

T5-Base

Reported on 11 benchmarks across 6 tasks · 2 papers · 4 SOTA

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

Natural Language Processing9 results

Data-to-Text GenerationonWebNLG
BLEU· 2020-05-21
64.7
best: 67.32 (Control Prefixes (A1, T5-large))
SOTA
Text-to-Text Pre-Training for Data-to-Text Tasks arXiv:2005.10433
Data-to-Text GenerationonMULTIWOZ 2.1
BLEU· 2020-05-21
35.1
SOTA
Text-to-Text Pre-Training for Data-to-Text Tasks arXiv:2005.10433
Question AnsweringonSQuAD1.1 dev
EM· uses extra data· 2019-10-23
85.44
best: 90.06 (T5-11B)
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683
Question AnsweringonSQuAD1.1 dev
F1· uses extra data· 2019-10-23
92.08
best: 95.77 (XLNet+DSC)
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683
Natural Language InferenceonMultiNLI
Matched· 2019-10-23
87.1
best: 92.6 (Turing NLR v5 XXL 5.4B (fine-tuned))
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683
Natural Language InferenceonMultiNLI
Mismatched· 2019-10-23
86.2
best: 92.4 (Turing NLR v5 XXL 5.4B (fine-tuned))
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683
Semantic Textual SimilarityonMRPC
F1· 2019-10-23
90.7
best: 92.5 (T5-3B)
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683
Semantic Textual SimilarityonSTS Benchmark
Pearson Correlation· 2019-10-23
0.894
best: 0.929 (MT-DNN-SMART)
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683
Sentiment AnalysisonSST-2 Binary classification
Accuracy· 2019-10-23
95.2
best: 97.5 (T5-11B)
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683

Adversarial2 results

Text GenerationonWebNLG
BLEU· 2020-05-21
64.7
best: 67.32 (Control Prefixes (A1, T5-large))
SOTA
Text-to-Text Pre-Training for Data-to-Text Tasks arXiv:2005.10433
Text GenerationonMULTIWOZ 2.1
BLEU· 2020-05-21
35.1
SOTA
Text-to-Text Pre-Training for Data-to-Text Tasks arXiv:2005.10433