PlanTL-GOB-ES/es_cantemist_ner_trf

Model

Basic Spacy BioNER pipeline, with a RoBERTa-based model [bsc-bio-ehr-es] (https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) and a dataset, CANTEMIST, annotated with tumour morphology entities. For further information, check the official website. Visit our GitHub repository. This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL

12 commits

2 linked in READMEs

updated Nov 17, 2022

See the code

README

Feature	Description
Name	`es_cantemist_ner_trf`
Version	`3.4.0`
spaCy	`>=3.4.0,<3.5.0`
Default Pipeline	`transformer`, `ner`
Components	`transformer`, `ner`
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	https://huggingface.co/datasets/PlanTL-GOB-ES/cantemist-ner
License	`[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)`
Author	The Text Mining Unit from Barcelona Supercomputing Center.
Copyright	Copyright by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) (2022)
Funding	This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL

Label Scheme

View label scheme (1 labels for 1 components)

Component	Labels
`ner`	`MORFOLOGIA_NEOPLASIA`

Accuracy

Type	Score
`ENTS_F`	84.52
`ENTS_P`	84.88
`ENTS_R`	84.16
`TRANSFORMER_LOSS`	25646.78
`NER_LOSS`	9622.84

model-index

spacy

token-classification

Contributors

joanllop

11 commits

crodri

1 commits

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12 commits

2 linked in READMEs

updated Nov 17, 2022

See the code

README

Feature	Description
Name	`es_cantemist_ner_trf`
Version	`3.4.0`
spaCy	`>=3.4.0,<3.5.0`
Default Pipeline	`transformer`, `ner`
Components	`transformer`, `ner`
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	https://huggingface.co/datasets/PlanTL-GOB-ES/cantemist-ner
License	`[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)`
Author	The Text Mining Unit from Barcelona Supercomputing Center.
Copyright	Copyright by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) (2022)
Funding	This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL