This is a roBERTa model for Named Entity Recognition, fine-tuned on OntoNotes v5 using Spacy in coNLL-2003 format and BIO tagged. For more details: https://github.com/nicoladisabato/ner-with-transformers

Feature Description
Name en_roberta_fine_tuned_ner
Version 0.0.0
spaCy >=3.5.0,<3.6.0
Default Pipeline transformer, ner
Components transformer, ner
Vectors 0 keys, 0 unique vectors (0 dimensions)
Sources n/a
License n/a
Author Nicola Disabato

Label Scheme

View label scheme (18 labels for 1 components)
Component Labels
ner CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART

Accuracy

Type Score
ENTS_F 89.44
ENTS_P 89.37
ENTS_R 89.50
TRANSFORMER_LOSS 294822.05
NER_LOSS 316133.78
Downloads last month
0
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Evaluation results