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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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- fr |
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model-index: |
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- name: fr_pipeline |
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results: [] |
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--- |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `fr_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`, `tagger`, `national`, `thematic`, `sentiments`, `ner` | |
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| **Components** | `tok2vec`, `tagger`, `national`, `thematic`, `sentiments`, `ner` | |
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| **Vectors** | -1 keys, 50000 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 (71 labels for 5 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`tagger`** | `1`, `10`, `100`, `125`, `13`, `14`, `15`, `17`, `19`, `190`, `2`, `25`, `3`, `46`, `5`, `50`, `500`, `6`, `7`, `80`, `800`, `ADJ`, `ADP`, `ADV`, `AUX`, `CCONJ`, `CONJ`, `DET`, `INTJ`, `NOUN`, `NUM`, `PRON`, `PROPN`, `PUNCT`, `SCONJ`, `SYM`, `VERB`, `X` | |
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| **`national`** | `International`, `National` | |
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| **`thematic`** | `Coopération/Diplomatie`, `Culture`, `Economie`, `Education`, `Election`, `Environnement`, `Gouvernement`, `Insolite`, `Justice`, `Nécrologie`, `People`, `Politique`, `Réligion`, `Santé`, `Sexualité/Vie couple`, `Société`, `Sport`, `Sécurité`, `Sécurité routière`, `Technologie` | |
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| **`sentiments`** | `Negatif`, `Neutre`, `Positif` | |
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| **`ner`** | `DATE`, `EVENT`, `LOC`, `MISC`, `MONEY`, `ORG`, `PER`, `PER-T` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| --- | --- | |
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| `CATS_SCORE` | 90.37 | |
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| `CATS_MICRO_P` | 96.04 | |
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| `CATS_MICRO_R` | 96.04 | |
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| `CATS_MICRO_F` | 96.04 | |
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| `CATS_MACRO_P` | 92.01 | |
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| `CATS_MACRO_R` | 88.90 | |
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| `CATS_MACRO_F` | 90.37 | |
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| `CATS_MACRO_AUC` | 97.36 | |
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| `CATS_MACRO_AUC_PER_TYPE` | 0.00 | |
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| `TOK2VEC_LOSS` | 0.00 | |
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| `TEXTCAT_LOSS` | 478.59 | |
