# AutoTrain Dataset for project: triageinfojuri

## Dataset Description

This dataset has been automatically processed by AutoTrain for project triageinfojuri.

### Languages

The BCP-47 code for the dataset's language is fr.

## Dataset Structure

### Data Instances

A sample from this dataset looks as follows:

```json
[
  {
    "target": 11,
    "text": "Je suis intervenant psychosociale depuis 2007 au Regroupement des familles monoparentales et recompos\u00e9es de Laval (RFMRL), organisme sans but lucratif. L\u2019organisme n\u2019offre aucune compensation pour les 14 premiers jours.  Je suis en Arr\u00eat de travail du 28 novembre au 12 d\u00e9cembre 2022 inclusivement pour \u00e9puisement professionnel pour raison m\u00e9dicale.   J\u2019aimerais savoir comment ca fonctionne ?  - M\u2019inscrire tout de suite \u00e0 l\u2019AE (15 semaines avant le 18 d\u00e9cembre ou 26 si apr\u00e8s le 18). Je peux attendre ?  - M\u2019inscrire pour indemnit\u00e9 de la CNESST en m\u00eame temps ?  - On m\u2019a sugg\u00e9r\u00e9 de prendre des vacances."
  },
  {
    "target": 8,
    "text": "J'ai achet\u00e9 une voiture dans un encan, je l'ai fait r\u00e9par\u00e9e chez un garagiste \u00e0 Trois Rivi\u00e8res (Andr\u00e9 Simon Inc.) et la derni\u00e8re estim\u00e9e \u00e9tais de 3500 et la facture finale pr\u00e8s de 10,000 tentative de ne n\u00e9gociation nulle,mercci"
  }
]
```

### Dataset Fields

The dataset has the following fields (also called "features"):

```json
{
  "target": "ClassLabel(names=['ADMINISTRATIF', 'AIN\u00c9S', 'ASSURANCES', 'AUTEUR', 'CONSOMMATION', 'CONSOMMMATION', 'CORPORATIF', 'CRIMINALIT\u00c9', 'CR\u00c9ANCES', 'DIVORCE', 'DPJ', 'EMPLOI', 'FAILLITE', 'FAMILLE', 'FISCALIT\u00c9', 'FRAUDE', 'INAPTITUDE', 'INTERNATIONAL', 'JEUNESSE', 'LOGEMENT', 'LOUAGE', 'L\u00c9SION', 'MUNICIPAL', 'MUNICPAL', 'PERSONNALIT\u00c9', 'PLUMITIFS', 'PROC\u00c9DURES ', 'PROFESSION', 'PROPRI\u00c9T\u00c9', 'Proc\u00e9dures ', 'RENSEIGNEMENTS', 'RESPONSABILIT\u00c9', 'SERVICE', 'SOINS', 'VENTE'], id=None)",
  "text": "Value(dtype='string', id=None)"
}
```

### Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

| Split name   | Num samples         |
| ------------ | ------------------- |
| train        | 619 |
| valid        | 174 |

task_categories:text-classification language:fr region:us
{"language": ["fr"], "task_categories": ["text-classification"]}
TAGS
#task_categories-text-classification #language-French #region-us 

AutoTrain Dataset for project: triageinfojuri
=============================================


Dataset Description
-------------------


This dataset has been automatically processed by AutoTrain for project triageinfojuri.


### Languages


The BCP-47 code for the dataset's language is fr.


Dataset Structure
-----------------


### Data Instances


A sample from this dataset looks as follows:


### Dataset Fields


The dataset has the following fields (also called "features"):


### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:




### Languages


The BCP-47 code for the dataset's language is fr.


Dataset Structure
----------------- ### Data Instances


A sample from this dataset looks as follows: ### Dataset Fields


The dataset has the following fields (also called "features"): ### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:
TAGS
#task_categories-text-classification #language-French #region-us 
 ### Languages


The BCP-47 code for the dataset's language is fr.


Dataset Structure
----------------- ### Data Instances


A sample from this dataset looks as follows: ### Dataset Fields


The dataset has the following fields (also called "features"): ### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:
passage: TAGS
#task_categories-text-classification #language-French #region-us 
### Languages


The BCP-47 code for the dataset's language is fr.


Dataset Structure
-----------------### Data Instances


A sample from this dataset looks as follows:### Dataset Fields


The dataset has the following fields (also called "features"):### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow: