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---
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: 0.5910614525
- name: NER Recall
type: recall
value: 0.6136890951
- name: NER F Score
type: f_score
value: 0.6021627775
---
| Feature | Description |
| --- | --- |
| **Name** | `en_pipeline` |
| **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 (11 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `College Name`, `Companies worked at`, `Degree`, `Designation`, `Email Address`, `Graduation Year`, `Location`, `Name`, `Skills`, `UNKNOWN`, `Years of Experience` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 60.22 |
| `ENTS_P` | 59.11 |
| `ENTS_R` | 61.37 |
| `TRANSFORMER_LOSS` | 26200.68 |
| `NER_LOSS` | 290652.50 | |