--- tags: - spacy - token-classification - ner - resume matching language: - en model-index: - name: en_Resume_Matching_Keywords results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.6585136406 - name: NER Recall type: recall value: 0.799086758 - name: NER F Score type: f_score value: 0.7220216606 license: mit --- | Feature | Description | | --- | --- | | **Name** | `en_Resume_Matching_Keywords` | | **Version** | `0.0.0` | | **spaCy** | `>=3.7.4,<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** | [Priyanka Balivada]() | ### Label Scheme
View label scheme (10 labels for 1 components) | Component | Labels | | --- | --- | | **`ner`** | `CERTIFICATIONS`, `CGPA`, `EMAIL`, `EXPERIENCE`, `LOCATION`, `NAME`, `PHONE`, `QUALIFICATION`, `SCORES`, `SKILLS` |
### Accuracy | Type | Score | | --- | --- | | `ENTS_F` | 72.20 | | `ENTS_P` | 65.85 | | `ENTS_R` | 79.91 | | `TRANSFORMER_LOSS` | 12326.97 | | `NER_LOSS` | 19483.22 |