BERT base uncased model pre-trained on 5 NER datasets

Model was trained by SberIDP . The pretraining process and technical details are described in this article .

• Task: Named Entity Recognition
• Base model: bert-base-uncased
• Training Data is 5 datasets: CoNLL-2003 , WNUT17 , JNLPBA , CoNLL-2012 (OntoNotes) , BTC
• Testing was made in Few-Shot scenario on Few-NERD dataset using the model as a backbone for StructShot

The model is pretrained for NER task using Reptile and can be finetuned for new entities with only a small amount of samples.