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---
tags:
- spacy
- token-classification
language:
- es
license: gpl-3.0
model-index:
- name: es_cantemist_ner_trf
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8487622923
- name: NER Recall
type: recall
value: 0.8416274378
- name: NER F Score
type: f_score
value: 0.8451798075
widget:
- text: "JUICIO DIAGNÓSTICO Encefalitis límbica y polineuropatía sensitiva paraneoplásicas secundarias a carcinoma microcítico de pulmón cTxN2 M0 (enfermedad limitada) ."
---
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](https://temu.bsc.es/cantemist/). Visit our [GitHub repository](https://github.com/PlanTL-GOB-ES/lm-biomedical-clinical-es). 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_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.](https://huggingface.co/PlanTL-GOB-ES) |
| **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
<details>
<summary>View label scheme (1 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `MORFOLOGIA_NEOPLASIA` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 84.52 |
| `ENTS_P` | 84.88 |
| `ENTS_R` | 84.16 |
| `TRANSFORMER_LOSS` | 25646.78 |
| `NER_LOSS` | 9622.84 |