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---
tags:
- spacy
- token-classification
- ner
- TensorFlow
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
---
| 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
<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` | 72.20 |
| `ENTS_P` | 65.85 |
| `ENTS_R` | 79.91 |
| `TRANSFORMER_LOSS` | 12326.97 |
| `NER_LOSS` | 19483.22 | |