Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/ByT5 XXL

ByT5 XXL

Reported on 9 benchmarks across 4 tasks · 1 paper · 8 SOTA

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

Natural Language Processing9 results

Question AnsweringonXQuAD
EM· 2021-05-28
63.6
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Question AnsweringonXQuAD
F1· 2021-05-28
79.7
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Question AnsweringonTyDiQA-GoldP
F1· 2021-05-28
75.3
best: 88.5 (U-PaLM 62B (fine-tuned))
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Question AnsweringonMLQA
EM· 2021-05-28
54.9
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Question AnsweringonMLQA
F1· 2021-05-28
71.6
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Natural Language InferenceonXNLI
Accuracy· 2021-05-28
83.7
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Cross-LingualonWikiAnn NER
F1· 2021-05-28
67.7
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Cross-Lingual TransferonWikiAnn NER
F1· 2021-05-28
67.7
SOTA
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626
Question AnsweringonTyDiQA-GoldP
EM· 2021-05-28
60
best: 81.9 (ByT5 (fine-tuned))
ByT5: Towards a token-free future with pre-trained byte-to-byte models arXiv:2105.13626