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---
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 | |