---
tags:
- spacy
- token-classification
language:
- fr
model-index:
- name: fr_pipeline
  results: []
---
| Feature | Description |
| --- | --- |
| **Name** | `fr_pipeline` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.4.1,<3.5.0` |
| **Default Pipeline** | `tok2vec`, `tagger`, `national`, `thematic`, `sentiments`, `ner` |
| **Components** | `tok2vec`, `tagger`, `national`, `thematic`, `sentiments`, `ner` |
| **Vectors** | -1 keys, 50000 unique vectors (300 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [n/a]() |

### Label Scheme

<details>

<summary>View label scheme (71 labels for 5 components)</summary>

| Component | Labels |
| --- | --- |
| **`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` |
| **`national`** | `International`, `National` |
| **`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` |
| **`sentiments`** | `Negatif`, `Neutre`, `Positif` |
| **`ner`** | `DATE`, `EVENT`, `LOC`, `MISC`, `MONEY`, `ORG`, `PER`, `PER-T` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `CATS_SCORE` | 90.37 |
| `CATS_MICRO_P` | 96.04 |
| `CATS_MICRO_R` | 96.04 |
| `CATS_MICRO_F` | 96.04 |
| `CATS_MACRO_P` | 92.01 |
| `CATS_MACRO_R` | 88.90 |
| `CATS_MACRO_F` | 90.37 |
| `CATS_MACRO_AUC` | 97.36 |
| `CATS_MACRO_AUC_PER_TYPE` | 0.00 |
| `TOK2VEC_LOSS` | 0.00 |
| `TEXTCAT_LOSS` | 478.59 |