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--- |
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tags: |
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- spacy |
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- token-classification |
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- named-entity-recognition |
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language: |
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- en |
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model-index: |
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- name: en_Medical_Custom_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: 0.9538461538 |
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- name: NER Recall |
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type: recall |
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value: 0.9763779528 |
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- name: NER F Score |
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type: f_score |
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value: 0.9649805447 |
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library_name: spacy |
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pipeline_tag: token-classification |
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--- |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `en_Medical_Custom_ner` | |
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| **Version** | `0.0.0` | |
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| **spaCy** | `>=3.6.1,<3.7.0` | |
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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 (3 labels for 1 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `MEDICALCONDITION`, `MEDICINE`, `PATHOGEN` | |
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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` | 96.50 | |
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| `ENTS_P` | 95.38 | |
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| `ENTS_R` | 97.64 | |
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| `TOK2VEC_LOSS` | 8886.35 | |
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| `NER_LOSS` | 41564.56 | |
