metadata
tags:
- spacy
- token-classification
- named-entity-recognition
language:
- en
model-index:
- name: en_Medical_Custom_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9538461538
- name: NER Recall
type: recall
value: 0.9763779528
- name: NER F Score
type: f_score
value: 0.9649805447
library_name: spacy
pipeline_tag: token-classification
| Feature | Description |
|---|---|
| Name | en_Medical_Custom_ner |
| 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 (3 labels for 1 components)
| Component | Labels |
|---|---|
ner |
MEDICALCONDITION, MEDICINE, PATHOGEN |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
96.50 |
ENTS_P |
95.38 |
ENTS_R |
97.64 |
TOK2VEC_LOSS |
8886.35 |
NER_LOSS |
41564.56 |