---
tags:
- spacy
- token-classification
language:
- en
license: mit
model-index:
- name: en_healthsea
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.0
    - name: NER Recall
      type: recall
      value: 0.0
    - name: NER F Score
      type: f_score
      value: 0.0
  - task:
      name: SENTER
      type: token-classification
    metrics:
    - name: SENTER Precision
      type: precision
      value: 1.0
    - name: SENTER Recall
      type: recall
      value: 1.0
    - name: SENTER F Score
      type: f_score
      value: 1.0
---
Healthsea pipeline for analyzing reviews to supplement products

| Feature | Description |
| --- | --- |
| **Name** | `en_healthsea` |
| **Version** | `0.0.1` |
| **spaCy** | `>=3.2.0,<3.3.0` |
| **Default Pipeline** | `sentencizer`, `tok2vec`, `ner`, `benepar`, `segmentation`, `clausecat`, `aggregation` |
| **Components** | `sentencizer`, `tok2vec`, `ner`, `benepar`, `segmentation`, `clausecat`, `aggregation` |
| **Vectors** | 684830 keys, 684830 unique vectors (300 dimensions) |
| **Sources** | n/a |
| **License** | `MIT` |
| **Author** | [Explosion](explosion.ai) |

### Label Scheme

<details>

<summary>View label scheme (6 labels for 2 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `BENEFIT`, `CONDITION` |
| **`clausecat`** | `POSITIVE`, `NEUTRAL`, `NEGATIVE`, `ANAMNESIS` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `SENTS_F` | 100.00 |
| `SENTS_P` | 100.00 |
| `SENTS_R` | 100.00 |
| `ENTS_F` | 0.00 |
| `ENTS_P` | 0.00 |
| `ENTS_R` | 0.00 |
| `ENTS_PER_TYPE` | 0.00 |
| `CATS_SCORE` | 74.87 |
| `CATS_MICRO_P` | 82.39 |
| `CATS_MICRO_R` | 80.93 |
| `CATS_MICRO_F` | 81.66 |
| `CATS_MACRO_P` | 78.43 |
| `CATS_MACRO_R` | 72.16 |
| `CATS_MACRO_F` | 74.87 |
| `CATS_MACRO_AUC` | 92.78 |
| `CATS_MACRO_AUC_PER_TYPE` | 0.00 |
| `CLAUSECAT_LOSS` | 339.11 |