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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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- en
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model-index:
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- name: en_pipeline
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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: 0.9848121503
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- name: NER Recall
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type: recall
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value: 0.9828480255
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- name: NER F Score
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type: f_score
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value: 0.9838291076
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---
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| Feature | Description |
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| --- | --- |
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| **Name** | `en_pipeline` |
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| **Version** | `0.0.0` |
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| **spaCy** | `>=3.7.5,<3.8.0` |
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| **Default Pipeline** | `tok2vec`, `ner` |
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| **Components** | `tok2vec`, `ner` |
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| **Vectors** | 514157 keys, 514157 unique vectors (300 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 (26 labels for 1 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`ner`** | `ANGLE`, `CHEMICAL TERM`, `COUNTABLE`, `DECIMAL`, `EQU`, `EQUATION CITATION`, `FIGURE CITATION`, `FRACTION`, `GREEK VARIABLE`, `LEADING ZERO`, `NAMEDATE REF. CITATION`, `NUMBER`, `OPERATOR`, `ORDINAL`, `ORIENTATION`, `PERCENTAGE`, `RANGE`, `RATIO`, `ROMAN NUMBER`, `SI UNIT`, `SI UNIT `, `TABLE CITATION`, `THOUSANDS OPERATOR`, `THOUSANDS SEPARATOR`, `TIME UNIT`, `YEAR` |
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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` | 98.38 |
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| `ENTS_P` | 98.48 |
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| `ENTS_R` | 98.28 |
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| `TOK2VEC_LOSS` | 34785.41 |
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| `NER_LOSS` | 84008.34 | |
