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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_t2_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: 0.9840809754
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- name: NER Recall
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type: recall
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value: 0.9802474794
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- name: NER F Score
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type: f_score
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value: 0.9821604867
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---
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| Feature | Description |
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| --- | --- |
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| **Name** | `en_t2_pipeline` |
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| **Version** | `0.0.0` |
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| **spaCy** | `>=3.7.2,<3.8.0` |
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| **Default Pipeline** | `tok2vec`, `ner` |
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| **Components** | `tok2vec`, `ner` |
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| **Vectors** | 0 keys, 0 unique vectors (0 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 (5 labels for 1 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`ner`** | `Other`, `allergy_name`, `cancer`, `chronic_disease`, `treatment` |
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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` | 98.22 |
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| `ENTS_P` | 98.41 |
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| `ENTS_R` | 98.02 |
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| `TOK2VEC_LOSS` | 747277.39 |
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| `NER_LOSS` | 462952.49 | |
