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.