---
language:
- en
inference: false
datasets:
- conll2003
- wnut_17
- jnlpba
- conll2012
- BTC
tags:
- PyTorch
---

# BERT base uncased model pre-trained on 5 NER datasets

Model was trained by [SberIDP](https://github.com)
* 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.