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bert-base-NER-reptile-5-datasets

Token Classification

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ai-forever commited on Feb 3, 2022

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@@ -16,9 +16,9 @@ tags:
 Model was trained by SberIDP.
 * Task: `NER`
-* Training Data is 5 datasets: CoNLL-2003, WNUT17, JNLPBA, CoNLL-2012 (OntoNotes), BTC
-The model is described [in this article](https://habr.com/ru/company/sberbank/blog/).
 It is pretrained for NER task using [Reptile](https://openai.com/blog/reptile/) and can be finetuned for new entities with only a small amount of samples.

 Model was trained by SberIDP.
 * Task: `NER`
+* Training Data is 5 datasets: [CoNLL-2003](https://aclanthology.org/W03-0419.pdf), [WNUT17](http://noisy-text.github.io/2017/emerging-rare-entities.html), [JNLPBA](http://www.geniaproject.org/shared-tasks/bionlp-jnlpba-shared-task-2004), [CoNLL-2012 (OntoNotes)](https://aclanthology.org/W12-4501.pdf), [BTC](https://www.derczynski.com/papers/btc.pdf)
+The pretraining process and technical details are described [in this article](https://habr.com/ru/company/sberbank/blog/).
 It is pretrained for NER task using [Reptile](https://openai.com/blog/reptile/) and can be finetuned for new entities with only a small amount of samples.