fr-naxai-ai-sentiment-classification-234220122023

The model is trained on the sentiment classification task in the French language. It uses 3 labels: -1, 0 and 1. These labels represent negative, neutral and positive sentiments.

This model is finetuned from Distilcamember. A distillation version of the CamemBERT model, a RoBERTa French model version.

Model Details

• Language: fr
• Problem type: Multi-class Classification
• Model Architecture: distilcamembert
• Model Name: fr-naxai-ai-sentiment-classification-234220122023
• Creation date: 23:42h 20/12/2023

Classification Report:

Label	Precision	Recall	f1-Score	Support
-1	0.98	0.98	0.98	4117
0	0.84	0.82	0.83	631
1	0.96	0.97	0.97	2184
accuracy			0.96	6932
macro avg	0.93	0.92	0.03	6932
weighted avg	0.96	0.96	0.96	6932

How to use this model

---

You can use Python to access this model:

from transformers import pipeline

analyzer = pipeline(
    task='text-classification',
    model=“botdevringring/fr-naxai-ai-sentiment-classification-234220122023”,
    tokenizer="botdevringring/fr-naxai-ai-sentiment-classification-234220122023"
)
result = analyzer(
    "J'aime me promener en forêt même si ça me donne mal aux pieds."
)

result

[
  {
    'label': '0',
    'score': 0.515792965888977
  }
]

Or you can use cURL:

curl https://api-inference.huggingface.co/models/botdevringring/fr-naxai-ai-sentiment-classification-234220122023 \
    -X POST \
    -d '{"inputs": "J'aime me promener en forêt même si ça me donne mal aux pieds."}' \
    -H 'Content-Type: application/json' \
    -H "Authorization: Bearer <Your HF API token>"

Acknowledgements

Model trained by Eduardo Brigham for Naxai powered by The Ring Ring Company