roberta large ner english: model fine tuned from roberta large for NER task Introduction [roberta large ner english] is an english NER model that was fine tuned from roberta large on conll2003 dataset. Model was validated on emails/chat data and outperformed other models on this type of data specifically. In particular the model seems to work better on entity that don't start with an upper case. Training data Training data was classified as follow: Abbreviation Description O Outside of a named entity MISC Miscellaneous entity PER Person’s name ORG Organization LOC Location In order to simplify, the prefix B or I from original conll2003 was removed. I used the train and test dataset from original conll2003 for training and the "validation" dataset for validation. This resulted in a dataset of size: Train Validation 17494 3250 How to use roberta large ner english with HuggingFace Load roberta large ner english and its sub word tokenizer : Model performances Model performances computed on conll2003 validation dataset (computed on the tokens predictions) entity precision recall f1 PER 0.9914 0.9927 0.9920 ORG 0.9627 0.9661 0.9644 LOC 0.9795 0.9862 0.9828 MISC 0.9292 0.9262 0.9277 Overa…
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