# Description

This model is designed to be used in conjunction with the [he-ref-ner](https://huggingface.co/Sefaria/he_ref_ner) model. See the README there for how to integrate them.

The model takes citations as input and tags the parts of the citation as entities. This is very useful for parsing the citation.

# Technical details

| Feature | Description |
| --- | --- |
| **Name** | `he_subref_ner` |
| **Version** | `1.0.0` |
| **spaCy** | `>=3.4.1,<3.5.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 394654 keys, 394654 unique vectors (50 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [n/a]() |

### Label Scheme

<details>

<summary>View label scheme (7 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `דה`, `כותרת`, `לא-רציף`, `לקמן-להלן`, `מספר`, `סימן-טווח`, `שם` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 96.32 |
| `ENTS_P` | 96.12 |
| `ENTS_R` | 96.51 |
| `TOK2VEC_LOSS` | 11226.82 |
| `NER_LOSS` | 2452.62 |
{"language": ["he"], "tags": ["spacy", "token-classification"]}
spacy token-classification he model-index region:us