metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9175338189
- name: NER Recall
type: recall
value: 0.9087863953
- name: NER F Score
type: f_score
value: 0.9131391586
This model was trained with spaCy (distilbert-base-uncased transformer) to perform NER on resumes.
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.2,<3.8.0 |
| 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 (4 labels for 1 components)
| Component | Labels |
|---|---|
ner |
COMPANY, DIPLOMA, JOB_TITLE, SKILL |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
91.31 |
ENTS_P |
91.75 |
ENTS_R |
90.88 |