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--- |
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tags: |
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- spacy |
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- token-classification |
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language: |
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- he |
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model-index: |
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- name: he_subref_ner |
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results: |
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- task: |
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name: NER |
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type: token-classification |
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metrics: |
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- name: NER Precision |
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type: precision |
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value: 0.9611848825 |
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- name: NER Recall |
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type: recall |
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value: 0.9651282051 |
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- name: NER F Score |
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type: f_score |
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value: 0.9631525077 |
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--- |
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# Description |
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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. |
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The model takes citations as input and tags the parts of the citation as entities. This is very useful for parsing the citation. |
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# Technical details |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `he_subref_ner` | |
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| **Version** | `1.0.0` | |
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| **spaCy** | `>=3.4.1,<3.5.0` | |
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| **Default Pipeline** | `tok2vec`, `ner` | |
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| **Components** | `tok2vec`, `ner` | |
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| **Vectors** | 394654 keys, 394654 unique vectors (50 dimensions) | |
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| **Sources** | n/a | |
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| **License** | n/a | |
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| **Author** | [n/a]() | |
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### Label Scheme |
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<details> |
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<summary>View label scheme (7 labels for 1 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `讚讛`, `讻讜转专转`, `诇讗-专爪讬祝`, `诇拽诪谉-诇讛诇谉`, `诪住驻专`, `住讬诪谉-讟讜讜讞`, `砖诐` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| --- | --- | |
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| `ENTS_F` | 96.32 | |
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| `ENTS_P` | 96.12 | |
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| `ENTS_R` | 96.51 | |
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| `TOK2VEC_LOSS` | 11226.82 | |
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| `NER_LOSS` | 2452.62 | |
