---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_Resume_Matching_Keywords
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.6844809866
    - name: NER Recall
      type: recall
      value: 0.7717265353
    - name: NER F Score
      type: f_score
      value: 0.7254901961
---
| 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** | [n/a]() |

### Label Scheme

<details>

<summary>View label scheme (10 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `CERTIFICATIONS`, `CGPA`, `EMAIL`, `EXPERIENCE`, `LOCATION`, `NAME`, `PHONE`, `QUALIFICATION`, `SCORES`, `SKILLS` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 72.55 |
| `ENTS_P` | 68.45 |
| `ENTS_R` | 77.17 |
| `TRANSFORMER_LOSS` | 116555.35 |
| `NER_LOSS` | 109447.17 |