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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: 0.934169279 |
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- name: NER Recall |
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type: recall |
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value: 0.9445324881 |
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- name: NER F Score |
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type: f_score |
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value: 0.939322301 |
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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** | `>=3.4.1,<3.5.0` | |
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| **Default Pipeline** | `tok2vec`, `ner` | |
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| **Components** | `tok2vec`, `ner` | |
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| **Vectors** | 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 (20 labels for 1 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `APPLICATIONS`, `COLLEGE`, `COMMENT`, `CURRENCY`, `FIGURE`, `FURNITURE`, `GADGET`, `GPE`, `INSTITUITIONS`, `LOCATION`, `ORG`, `PEOPLE`, `PERIOD`, `PERSON`, `PROGRAM`, `SHELTER`, `SKILL`, `TIME`, `WEATHER CONDITION`, `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` | 93.93 | |
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| `ENTS_P` | 93.42 | |
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| `ENTS_R` | 94.45 | |
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| `TOK2VEC_LOSS` | 25728.50 | |
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| `NER_LOSS` | 421749.70 | |
