metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_Task3_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.883527267
- name: NER Recall
type: recall
value: 0.9118275574
- name: NER F Score
type: f_score
value: 0.8974543626
| Feature | Description |
|---|---|
| Name | en_Task3_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.6.1,<3.7.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 514157 keys, 514157 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (4 labels for 1 components)
| Component | Labels |
|---|---|
ner |
Allergy, Cancer, Chronic Disease, Treatment |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
89.75 |
ENTS_P |
88.35 |
ENTS_R |
91.18 |
TOK2VEC_LOSS |
42393.86 |
NER_LOSS |
790020.07 |