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DaCy_small_ner_fine_grained

DaCy is a Danish language processing framework with state-of-the-art pipelines as well as functionality for analyzing Danish pipelines. At the time of publishing this model, also included in DaCy encorporates the only models for fine-grained NER using DANSK dataset - a dataset containing 18 annotation types in the same format as Ontonotes. Moreover, DaCy's largest pipeline has achieved State-of-the-Art performance on Named entity recognition, part-of-speech tagging and dependency parsing for Danish on the DaNE dataset. Check out the DaCy repository for material on how to use DaCy and reproduce the results. DaCy also contains guides on usage of the package as well as behavioural test for biases and robustness of Danish NLP pipelines.

For information about the use of this model as well as guides to its use, please refer to DaCys documentation.

Feature Description
Name da_dacy_small_ner_fine_grained
Version 0.1.0
spaCy >=3.5.0,<3.6.0
Default Pipeline transformer, ner
Components transformer, ner
Vectors 0 keys, 0 unique vectors (0 dimensions)
Sources DANSK - Danish Annotations for NLP Specific TasKs (chcaa)
jonfd/electra-small-nordic (Jón Daðason)
License apache-2.0
Author Centre for Humanities Computing Aarhus

Label Scheme

View label scheme (18 labels for 1 components)
Component Labels
ner CARDINAL, DATE, EVENT, FACILITY, GPE, LANGUAGE, LAW, LOCATION, MONEY, NORP, ORDINAL, ORGANIZATION, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK OF ART

Accuracy

Type Score
ENTS_F 77.56
ENTS_P 78.12
ENTS_R 77.02
TRANSFORMER_LOSS 90762.74
NER_LOSS 99794.90

For progression in loss and performance on the dev set during training, please refer to the Weights and Biases run, HERE

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Dataset used to train chcaa/da_dacy_small_ner_fine_grained

Evaluation results