|
--- |
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annotations_creators: |
|
- found |
|
language_creators: |
|
- found |
|
language: |
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- af |
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- ar |
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- bg |
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- bn |
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- de |
|
- el |
|
- en |
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- es |
|
- et |
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- eu |
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- fa |
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- fi |
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- fr |
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- he |
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- hi |
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- hu |
|
- id |
|
- it |
|
- ja |
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- jv |
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- ka |
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- kk |
|
- ko |
|
- ml |
|
- mr |
|
- ms |
|
- my |
|
- nl |
|
- pt |
|
- ru |
|
- sw |
|
- ta |
|
- te |
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- th |
|
- tl |
|
- tr |
|
- ur |
|
- vi |
|
- yo |
|
- zh |
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language_bcp47: |
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- fa-IR |
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license: |
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- apache-2.0 |
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- cc-by-4.0 |
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- cc-by-2.0 |
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- cc-by-sa-4.0 |
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- other |
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- cc-by-nc-4.0 |
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license_details: Licence Universal Dependencies v2.5 |
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multilinguality: |
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- multilingual |
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- translation |
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pretty_name: XTREME |
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size_categories: |
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- n<1K |
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- 1K<n<10K |
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- 10K<n<100K |
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- 100K<n<1M |
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source_datasets: |
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- extended|xnli |
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- extended|paws-x |
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- extended|wikiann |
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- extended|xquad |
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- extended|mlqa |
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- extended|tydiqa |
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- extended|tatoeba |
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- extended|squad |
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task_categories: |
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- multiple-choice |
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- question-answering |
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- token-classification |
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- text-classification |
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- text-retrieval |
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- token-classification |
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task_ids: |
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- multiple-choice-qa |
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- extractive-qa |
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- open-domain-qa |
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- natural-language-inference |
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- named-entity-recognition |
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- part-of-speech |
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paperswithcode_id: xtreme |
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configs: |
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- MLQA.ar.ar |
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- MLQA.ar.de |
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- MLQA.ar.en |
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- MLQA.ar.es |
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- MLQA.ar.hi |
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- MLQA.ar.vi |
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- MLQA.ar.zh |
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- MLQA.de.ar |
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- MLQA.de.de |
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- MLQA.de.en |
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- MLQA.de.es |
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- MLQA.de.hi |
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- MLQA.de.vi |
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- MLQA.de.zh |
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- MLQA.en.ar |
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- MLQA.en.de |
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- MLQA.en.en |
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- MLQA.en.es |
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- MLQA.en.hi |
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- MLQA.en.vi |
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- MLQA.en.zh |
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- MLQA.es.ar |
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- MLQA.es.de |
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- MLQA.es.en |
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- MLQA.es.es |
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- MLQA.es.hi |
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- MLQA.es.vi |
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- MLQA.es.zh |
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- MLQA.hi.ar |
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- MLQA.hi.de |
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- MLQA.hi.en |
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- MLQA.hi.es |
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- MLQA.hi.hi |
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- MLQA.hi.vi |
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- MLQA.hi.zh |
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- MLQA.vi.ar |
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- MLQA.vi.de |
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- MLQA.vi.en |
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- MLQA.vi.es |
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- MLQA.vi.hi |
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- MLQA.vi.vi |
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- MLQA.vi.zh |
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- MLQA.zh.ar |
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- MLQA.zh.de |
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- MLQA.zh.en |
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- MLQA.zh.es |
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- MLQA.zh.hi |
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- MLQA.zh.vi |
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- MLQA.zh.zh |
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- PAN-X.af |
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- PAN-X.ar |
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- PAN-X.bg |
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- PAN-X.bn |
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- PAN-X.de |
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- PAN-X.el |
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- PAN-X.en |
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- PAN-X.es |
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- PAN-X.et |
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- PAN-X.eu |
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- PAN-X.fa |
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- PAN-X.fi |
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- PAN-X.fr |
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- PAN-X.he |
|
- PAN-X.hi |
|
- PAN-X.hu |
|
- PAN-X.id |
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- PAN-X.it |
|
- PAN-X.ja |
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- PAN-X.jv |
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- PAN-X.ka |
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- PAN-X.kk |
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- PAN-X.ko |
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- PAN-X.ml |
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- PAN-X.mr |
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- PAN-X.ms |
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- PAN-X.my |
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- PAN-X.nl |
|
- PAN-X.pt |
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- PAN-X.ru |
|
- PAN-X.sw |
|
- PAN-X.ta |
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- PAN-X.te |
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- PAN-X.th |
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- PAN-X.tl |
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- PAN-X.tr |
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- PAN-X.ur |
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- PAN-X.vi |
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- PAN-X.yo |
|
- PAN-X.zh |
|
- PAWS-X.de |
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- PAWS-X.en |
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- PAWS-X.es |
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- PAWS-X.fr |
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- PAWS-X.ja |
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- PAWS-X.ko |
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- PAWS-X.zh |
|
- SQuAD |
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- XNLI |
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- XQuAD |
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- bucc18.de |
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- bucc18.fr |
|
- bucc18.ru |
|
- bucc18.zh |
|
- tatoeba.afr |
|
- tatoeba.ara |
|
- tatoeba.ben |
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- tatoeba.bul |
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- tatoeba.cmn |
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- tatoeba.deu |
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- tatoeba.ell |
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- tatoeba.est |
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- tatoeba.eus |
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- tatoeba.fin |
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- tatoeba.fra |
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- tatoeba.heb |
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- tatoeba.hin |
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- tatoeba.hun |
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- tatoeba.ind |
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- tatoeba.ita |
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- tatoeba.jav |
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- tatoeba.jpn |
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- tatoeba.kat |
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- tatoeba.kaz |
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- tatoeba.kor |
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- tatoeba.mal |
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- tatoeba.mar |
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- tatoeba.nld |
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- tatoeba.pes |
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- tatoeba.por |
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- tatoeba.rus |
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- tatoeba.spa |
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- tatoeba.swh |
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- tatoeba.tam |
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- tatoeba.tel |
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- tatoeba.tgl |
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- tatoeba.tha |
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- tatoeba.tur |
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- tatoeba.urd |
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- tatoeba.vie |
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- tydiqa |
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- udpos.Afrikans |
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- udpos.Arabic |
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- udpos.Basque |
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- udpos.Bulgarian |
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- udpos.Chinese |
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- udpos.Dutch |
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- udpos.English |
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- udpos.Estonian |
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- udpos.Finnish |
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- udpos.French |
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- udpos.German |
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- udpos.Greek |
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- udpos.Hebrew |
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- udpos.Hindi |
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- udpos.Hungarian |
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- udpos.Indonesian |
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- udpos.Italian |
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- udpos.Japanese |
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- udpos.Kazakh |
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- udpos.Korean |
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- udpos.Marathi |
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- udpos.Persian |
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- udpos.Portuguese |
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- udpos.Russian |
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- udpos.Spanish |
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- udpos.Tagalog |
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- udpos.Tamil |
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- udpos.Telugu |
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- udpos.Thai |
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- udpos.Turkish |
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- udpos.Urdu |
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- udpos.Vietnamese |
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- udpos.Yoruba |
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tags: |
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- parallel-sentence-retrieval |
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- paraphrase-identification |
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dataset_info: |
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- config_name: XNLI |
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features: |
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- name: language |
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dtype: string |
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- name: sentence1 |
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dtype: string |
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- name: sentence2 |
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dtype: string |
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- name: gold_label |
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dtype: string |
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splits: |
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- name: test |
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num_bytes: 20359500 |
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num_examples: 75150 |
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- name: validation |
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num_bytes: 10049303 |
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num_examples: 37350 |
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download_size: 17865352 |
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dataset_size: 30408803 |
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- config_name: tydiqa |
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features: |
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- name: id |
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dtype: string |
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- name: title |
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dtype: string |
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- name: context |
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dtype: string |
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- name: question |
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dtype: string |
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- name: answers |
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sequence: |
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- name: answer_start |
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dtype: int32 |
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- name: text |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 52948607 |
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num_examples: 49881 |
|
- name: validation |
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num_bytes: 5006461 |
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num_examples: 5077 |
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download_size: 63621485 |
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dataset_size: 57955068 |
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- config_name: SQuAD |
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features: |
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- name: id |
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dtype: string |
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- name: title |
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dtype: string |
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- name: context |
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dtype: string |
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- name: question |
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dtype: string |
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- name: answers |
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sequence: |
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- name: answer_start |
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dtype: int32 |
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- name: text |
|
dtype: string |
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splits: |
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- name: train |
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num_bytes: 79317110 |
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num_examples: 87599 |
|
- name: validation |
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num_bytes: 10472653 |
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num_examples: 10570 |
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download_size: 35142551 |
|
dataset_size: 89789763 |
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- config_name: PAN-X.af |
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features: |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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sequence: |
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class_label: |
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names: |
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0: O |
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1: B-PER |
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2: I-PER |
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3: B-ORG |
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4: I-ORG |
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5: B-LOC |
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6: I-LOC |
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- name: langs |
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sequence: string |
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splits: |
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num_bytes: 259709 |
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num_examples: 1000 |
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num_bytes: 257204 |
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num_examples: 1000 |
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- name: train |
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num_bytes: 1321396 |
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num_examples: 5000 |
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download_size: 234008884 |
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dataset_size: 1838309 |
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- config_name: PAN-X.ar |
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features: |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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sequence: |
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class_label: |
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names: |
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1: B-PER |
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6: I-LOC |
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- name: langs |
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sequence: string |
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splits: |
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num_bytes: 1808303 |
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num_examples: 10000 |
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num_examples: 10000 |
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- name: train |
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num_bytes: 3634136 |
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num_examples: 20000 |
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download_size: 234008884 |
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dataset_size: 7254422 |
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- config_name: PAN-X.bg |
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features: |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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sequence: |
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class_label: |
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names: |
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num_bytes: 4600773 |
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num_examples: 20000 |
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download_size: 234008884 |
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dataset_size: 9217245 |
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- config_name: PAN-X.bn |
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features: |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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sequence: |
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class_label: |
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names: |
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1: B-PER |
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sequence: string |
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splits: |
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num_examples: 1000 |
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num_examples: 1000 |
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- name: train |
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num_bytes: 1568845 |
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num_examples: 10000 |
|
download_size: 234008884 |
|
dataset_size: 1887215 |
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- config_name: PAN-X.de |
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features: |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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sequence: |
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class_label: |
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num_examples: 20000 |
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download_size: 234008884 |
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dataset_size: 9521556 |
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- config_name: PAN-X.el |
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features: |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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sequence: |
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class_label: |
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download_size: 234008884 |
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dataset_size: 10144576 |
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- config_name: PAN-X.en |
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features: |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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class_label: |
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num_examples: 20000 |
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download_size: 234008884 |
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dataset_size: 7659763 |
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- config_name: PAN-X.es |
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features: |
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- name: tokens |
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- name: ner_tags |
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class_label: |
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features: |
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- name: ner_tags |
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download_size: 234008884 |
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- config_name: PAN-X.eu |
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- config_name: PAN-X.fa |
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- name: ner_tags |
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download_size: 234008884 |
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- config_name: PAN-X.fi |
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features: |
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- name: ner_tags |
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- config_name: PAN-X.fr |
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- config_name: PAN-X.he |
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features: |
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- name: tokens |
|
sequence: string |
|
- name: ner_tags |
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class_label: |
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--- |
|
|
|
# Dataset Card for "xtreme" |
|
|
|
## Table of Contents |
|
- [Dataset Description](#dataset-description) |
|
- [Dataset Summary](#dataset-summary) |
|
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
|
- [Languages](#languages) |
|
- [Dataset Structure](#dataset-structure) |
|
- [Data Instances](#data-instances) |
|
- [Data Fields](#data-fields) |
|
- [Data Splits](#data-splits) |
|
- [Dataset Creation](#dataset-creation) |
|
- [Curation Rationale](#curation-rationale) |
|
- [Source Data](#source-data) |
|
- [Annotations](#annotations) |
|
- [Personal and Sensitive Information](#personal-and-sensitive-information) |
|
- [Considerations for Using the Data](#considerations-for-using-the-data) |
|
- [Social Impact of Dataset](#social-impact-of-dataset) |
|
- [Discussion of Biases](#discussion-of-biases) |
|
- [Other Known Limitations](#other-known-limitations) |
|
- [Additional Information](#additional-information) |
|
- [Dataset Curators](#dataset-curators) |
|
- [Licensing Information](#licensing-information) |
|
- [Citation Information](#citation-information) |
|
- [Contributions](#contributions) |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** [https://github.com/google-research/xtreme](https://github.com/google-research/xtreme) |
|
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
- **Size of downloaded dataset files:** 15143.21 MB |
|
- **Size of the generated dataset:** 1027.42 MB |
|
- **Total amount of disk used:** 16170.64 MB |
|
|
|
### Dataset Summary |
|
|
|
The Cross-lingual Natural Language Inference (XNLI) corpus is a crowd-sourced collection of 5,000 test and |
|
2,500 dev pairs for the MultiNLI corpus. The pairs are annotated with textual entailment and translated into |
|
14 languages: French, Spanish, German, Greek, Bulgarian, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, |
|
Hindi, Swahili and Urdu. This results in 112.5k annotated pairs. Each premise can be associated with the |
|
corresponding hypothesis in the 15 languages, summing up to more than 1.5M combinations. The corpus is made to |
|
evaluate how to perform inference in any language (including low-resources ones like Swahili or Urdu) when only |
|
English NLI data is available at training time. One solution is cross-lingual sentence encoding, for which XNLI |
|
is an evaluation benchmark. |
|
The Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of |
|
the cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages |
|
(spanning 12 language families) and includes nine tasks that collectively require reasoning about different levels of |
|
syntax and semantics. The languages in XTREME are selected to maximize language diversity, coverage in existing tasks, |
|
and availability of training data. Among these are many under-studied languages, such as the Dravidian languages Tamil |
|
(spoken in southern India, Sri Lanka, and Singapore), Telugu and Malayalam (spoken mainly in southern India), and the |
|
Niger-Congo languages Swahili and Yoruba, spoken in Africa. |
|
|
|
### Supported Tasks and Leaderboards |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Languages |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
## Dataset Structure |
|
|
|
### Data Instances |
|
|
|
#### MLQA.ar.ar |
|
|
|
- **Size of downloaded dataset files:** 72.21 MB |
|
- **Size of the generated dataset:** 8.77 MB |
|
- **Total amount of disk used:** 80.98 MB |
|
|
|
An example of 'validation' looks as follows. |
|
``` |
|
|
|
``` |
|
|
|
#### MLQA.ar.de |
|
|
|
- **Size of downloaded dataset files:** 72.21 MB |
|
- **Size of the generated dataset:** 2.43 MB |
|
- **Total amount of disk used:** 74.64 MB |
|
|
|
An example of 'validation' looks as follows. |
|
``` |
|
|
|
``` |
|
|
|
#### MLQA.ar.en |
|
|
|
- **Size of downloaded dataset files:** 72.21 MB |
|
- **Size of the generated dataset:** 8.62 MB |
|
- **Total amount of disk used:** 80.83 MB |
|
|
|
An example of 'validation' looks as follows. |
|
``` |
|
|
|
``` |
|
|
|
#### MLQA.ar.es |
|
|
|
- **Size of downloaded dataset files:** 72.21 MB |
|
- **Size of the generated dataset:** 3.12 MB |
|
- **Total amount of disk used:** 75.33 MB |
|
|
|
An example of 'validation' looks as follows. |
|
``` |
|
|
|
``` |
|
|
|
#### MLQA.ar.hi |
|
|
|
- **Size of downloaded dataset files:** 72.21 MB |
|
- **Size of the generated dataset:** 3.17 MB |
|
- **Total amount of disk used:** 75.38 MB |
|
|
|
An example of 'validation' looks as follows. |
|
``` |
|
|
|
``` |
|
|
|
### Data Fields |
|
|
|
The data fields are the same among all splits. |
|
|
|
#### MLQA.ar.ar |
|
- `id`: a `string` feature. |
|
- `title`: a `string` feature. |
|
- `context`: a `string` feature. |
|
- `question`: a `string` feature. |
|
- `answers`: a dictionary feature containing: |
|
- `answer_start`: a `int32` feature. |
|
- `text`: a `string` feature. |
|
|
|
#### MLQA.ar.de |
|
- `id`: a `string` feature. |
|
- `title`: a `string` feature. |
|
- `context`: a `string` feature. |
|
- `question`: a `string` feature. |
|
- `answers`: a dictionary feature containing: |
|
- `answer_start`: a `int32` feature. |
|
- `text`: a `string` feature. |
|
|
|
#### MLQA.ar.en |
|
- `id`: a `string` feature. |
|
- `title`: a `string` feature. |
|
- `context`: a `string` feature. |
|
- `question`: a `string` feature. |
|
- `answers`: a dictionary feature containing: |
|
- `answer_start`: a `int32` feature. |
|
- `text`: a `string` feature. |
|
|
|
#### MLQA.ar.es |
|
- `id`: a `string` feature. |
|
- `title`: a `string` feature. |
|
- `context`: a `string` feature. |
|
- `question`: a `string` feature. |
|
- `answers`: a dictionary feature containing: |
|
- `answer_start`: a `int32` feature. |
|
- `text`: a `string` feature. |
|
|
|
#### MLQA.ar.hi |
|
- `id`: a `string` feature. |
|
- `title`: a `string` feature. |
|
- `context`: a `string` feature. |
|
- `question`: a `string` feature. |
|
- `answers`: a dictionary feature containing: |
|
- `answer_start`: a `int32` feature. |
|
- `text`: a `string` feature. |
|
|
|
### Data Splits |
|
|
|
| name |validation|test| |
|
|----------|---------:|---:| |
|
|MLQA.ar.ar| 517|5335| |
|
|MLQA.ar.de| 207|1649| |
|
|MLQA.ar.en| 517|5335| |
|
|MLQA.ar.es| 161|1978| |
|
|MLQA.ar.hi| 186|1831| |
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Source Data |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
#### Who are the source language producers? |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Annotations |
|
|
|
#### Annotation process |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
#### Who are the annotators? |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Personal and Sensitive Information |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Discussion of Biases |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Other Known Limitations |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Licensing Information |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
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### Citation Information |
|
|
|
``` |
|
@InProceedings{conneau2018xnli, |
|
author = {Conneau, Alexis |
|
and Rinott, Ruty |
|
and Lample, Guillaume |
|
and Williams, Adina |
|
and Bowman, Samuel R. |
|
and Schwenk, Holger |
|
and Stoyanov, Veselin}, |
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title = {XNLI: Evaluating Cross-lingual Sentence Representations}, |
|
booktitle = {Proceedings of the 2018 Conference on Empirical Methods |
|
in Natural Language Processing}, |
|
year = {2018}, |
|
publisher = {Association for Computational Linguistics}, |
|
location = {Brussels, Belgium}, |
|
} |
|
@article{hu2020xtreme, |
|
author = {Junjie Hu and Sebastian Ruder and Aditya Siddhant and Graham Neubig and Orhan Firat and Melvin Johnson}, |
|
title = {XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization}, |
|
journal = {CoRR}, |
|
volume = {abs/2003.11080}, |
|
year = {2020}, |
|
archivePrefix = {arXiv}, |
|
eprint = {2003.11080} |
|
} |
|
|
|
``` |
|
|
|
|
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### Contributions |
|
|
|
Thanks to [@thomwolf](https://github.com/thomwolf), [@jplu](https://github.com/jplu), [@lewtun](https://github.com/lewtun), [@lvwerra](https://github.com/lvwerra), [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten), [@mariamabarham](https://github.com/mariamabarham) for adding this dataset. |
