Edit model card

tf-allociné

A french sentiment analysis model, based on CamemBERT, and finetuned on a large-scale dataset scraped from Allociné.fr user reviews.

Results

Validation Accuracy Validation F1-Score Test Accuracy Test F1-Score
97.39 97.36 97.44 97.34

The dataset and the evaluation code are available on this repo.

Usage

from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
from transformers import pipeline

tokenizer = AutoTokenizer.from_pretrained("tblard/tf-allocine")
model = TFAutoModelForSequenceClassification.from_pretrained("tblard/tf-allocine")

nlp = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)

print(nlp("Alad'2 est clairement le meilleur film de l'année 2018.")) # POSITIVE
print(nlp("Juste whoaaahouuu !")) # POSITIVE
print(nlp("NUL...A...CHIER ! FIN DE TRANSMISSION.")) # NEGATIVE
print(nlp("Je m'attendais à mieux de la part de Franck Dubosc !")) # NEGATIVE

Author

Théophile Blard – :email: theophile.blard@gmail.com

If you use this work (code, model or dataset), please cite as:

Théophile Blard, French sentiment analysis with BERT, (2020), GitHub repository, https://github.com/TheophileBlard/french-sentiment-analysis-with-bert

Downloads last month
1,174
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.