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 |
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Evaluation results
- NER Precisionself-reported0.918
- NER Recallself-reported0.909
- NER F Scoreself-reported0.913