metadata
language: fr
datasets:
- news_commentary
widget:
- text: Ne laisse aucun résidu. Ne nécessite pas de nettoyage après l'application.
example_title: Fluent example 1
- text: Nous n'avons pas d'argent et aucune relation.
example_title: Fluent example 2
- text: C'est marrant comme tout le monde oublie ça, hein ?
example_title: Fluent example 3
- text: Il estaaaaaaaaaaad impr2éviswwible, oui,i,v.1 danfaagereux.
example_title: Disfluent example 1
- text: L'hépssasdati@!@@!te, oui, une pleaaane indemnisation.
example_title: Disfluent example 2
- text: Après une\s hééésiéétation,!!! j'ai fait signe que oui.
example_title: Disfluent example 3
license: other
This model was trained for evaluating linguistic acceptability and grammaticality. The finetuning was carried out based off the camembert-base model.
To use the model:
from transformers import pipeline
classifier = pipeline("text-classification", model = 'EIStakovskii/camembert_base_fluency')
print(classifier("Il estaaaaaaaaaaad impr2éviswwible, oui,i,v.1 danfaagereux."))
Label_1 means ACCEPTABLE - the sentence is perfectly understandable by native speakers and has no serious grammatic and syntactic flaws.
Label_0 means NOT ACCEPTABLE - the sentence is flawed both orthographically and grammatically.
The model was trained on 50 thousand French sentences from the news_commentary dataset. Out of 50 thousand 25 thousand sentences were algorithmically corrupted using the open source Python library. The library was originally developed by aylliote, but it was slightly adapted for the purposes of this model.