metadata
tags:
- spacy
- token-classification
language:
- es
model-index:
- name: es_metaextract_umsa_v1
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8582004936
- name: NER Recall
type: recall
value: 0.9470778743
- name: NER F Score
type: f_score
value: 0.9004513804
| Feature | Description |
|---|---|
| Name | es_metaextract_umsa_v1 |
| Version | 1.0 |
| spaCy | >=3.7.2,<3.8.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (6 labels for 1 components)
| Component | Labels |
|---|---|
ner |
ADVISOR, AUTHOR, DEPARTMENT, FACULTY, TITLE, YEAR |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
90.05 |
ENTS_P |
85.82 |
ENTS_R |
94.71 |
TOK2VEC_LOSS |
52012.59 |
NER_LOSS |
228767.42 |