---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_nerry_rel_trf_sentBert
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.9259259259
    - name: NER Recall
      type: recall
      value: 1.0
    - name: NER F Score
      type: f_score
      value: 0.9615384615
---
RE with transformer (sentence bert)

| Feature | Description |
| --- | --- |
| **Name** | `en_nerry_rel_trf_sentBert` |
| **Version** | `2.1.0` |
| **spaCy** | `>=3.6.1,<3.7.0` |
| **Default Pipeline** | `transformer`, `ner`, `relation_extractor` |
| **Components** | `transformer`, `ner`, `relation_extractor` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [HjAnthony]() |

### Label Scheme

<details>

<summary>View label scheme (4 labels for 2 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `CRIME`, `PERSON`, `PROCECUTION` |
| **`relation_extractor`** | `INVOVLED_IN` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 96.15 |
| `ENTS_P` | 92.59 |
| `ENTS_R` | 100.00 |
| `REL_MICRO_P` | 88.24 |
| `REL_MICRO_R` | 100.00 |
| `REL_MICRO_F` | 93.75 |
| `TRANSFORMER_LOSS` | 0.00 |
| `RELATION_EXTRACTOR_LOSS` | 366.91 |