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PlanTL-GOB-ES/es_pharmaconer_ner_trf
es_pharmaconer_ner_trf is a token classification model from PlanTL-GOB-ES. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as mit.
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, Pharmaconer, a NER dataset annotated with substances, compounds and protein…
Downloads · 30 days
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From the Hugging Face model README
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, Pharmaconer, a NER dataset annotated with substances, compounds and proteins 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
| Feature | Description |
|---|---|
| Name | es_pharmaconer_ner_trf |
| Version | 3.4.1 |
| spaCy | >=3.4.1,<3.5.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | mit |
| 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 |
| Component | Labels |
|---|---|
ner | NORMALIZABLES, NO_NORMALIZABLES, PROTEINAS, UNCLEAR |
| Type | Score |
|---|---|
ENTS_F | 91.09 |
ENTS_P | 90.67 |
ENTS_R | 91.53 |
TRANSFORMER_LOSS | 15719.51 |
NER_LOSS | 22469.88 |