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m1_ind_layers_ref_cmbert_io_level_1

Introduction

This model is a model that was fine-tuned from Jean-Baptiste/camembert-ner for nested NER task on a nested NER Paris trade directories dataset.

Dataset

Abbreviation Entity group (level) Description
O 1 & 2 Outside of a named entity
PER 1 Person or company name
ACT 1 & 2 Person or company professional activity
TITREH 2 Military or civil distinction
DESC 1 Entry full description
TITREP 2 Professionnal reward
SPAT 1 Address
LOC 2 Street name
CARDINAL 2 Street number
FT 2 Geographical feature

Experiment parameter

Load model from the Hugging Face

**Warning 1 ** : this model only recognises level-1 entities of dataset. It has to be used with m1_ind_layers_ref_cmbert_io_level_2 to recognise nested entities level-2.

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("nlpso/m1_ind_layers_ref_cmbert_io_level_1")
model = AutoModelForTokenClassification.from_pretrained("nlpso/m1_ind_layers_ref_cmbert_io_level_1")
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Dataset used to train nlpso/m1_ind_layers_ref_cmbert_io_level_1