metadata
tags:
- spacy
- token-classification
language:
- fr
model-index:
- name: fr_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9011406844
- name: NER Recall
type: recall
value: 0.92578125
- name: NER F Score
type: f_score
value: 0.9132947977
| Feature | Description |
|---|---|
| Name | fr_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.2.1,<3.3.0 |
| 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 (4 labels for 1 components)
| Component | Labels |
|---|---|
ner |
FOOD PRODUCT, INGREDIENT, MEASURE, QUANTITY |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
91.33 |
ENTS_P |
90.11 |
ENTS_R |
92.58 |
TOK2VEC_LOSS |
8670.94 |
NER_LOSS |
4165.31 |