metadata
tags:
- spacy
- token-classification
language:
- da
model-index:
- name: da_multi_dupli_onto_xlm_roberta_large
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.7785234899
- name: NER Recall
type: recall
value: 0.8226950355
- name: NER F Score
type: f_score
value: 0.8
| Feature | Description |
|---|---|
| Name | da_multi_dupli_onto_xlm_roberta_large |
| Version | 0.0.0 |
| spaCy | >=3.5.0,<3.6.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (16 labels for 1 components)
| Component | Labels |
|---|---|
ner |
CARDINAL, DATE, EVENT, FACILITY, GPE, LAW, LOCATION, MONEY, NORP, ORDINAL, ORGANIZATION, PERSON, PRODUCT, QUANTITY, TIME, WORK OF ART |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
80.00 |
ENTS_P |
77.85 |
ENTS_R |
82.27 |
TRANSFORMER_LOSS |
17711.38 |
NER_LOSS |
289765.47 |