metadata

language:
  - fr
widget:
  - text: je commence à me sentir déprimé
  - text: je me sentirais honoré et béni
  - text: je réalise que jai des amis je suis surpris
  - text: quand jai failli me faire tabasser par le frère de ma copine
pipeline_tag: text-classification
tags:
  - CamemBERT
  - emotion
  - text-classification
  - pytorch
  - latest
datasets:
  - botdevringring/FR_emotion_classification
  - dair-ai/emotion
metrics:
  - Accuracy, F1 Score
model-index:
  - name: botdevringring/fr-naxai-ai-emotion-classification-081808122023
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          config: default
          split: test
        metrics:
          - type: accuracy
            value: 0.896
            name: Accuracy
            verified: true
          - type: precision
            value: 0.897
            name: Precision Macro
            verified: true
          - type: precision
            value: 0.896
            name: Precision Micro
            verified: true
          - type: precision
            value: 0.897
            name: Precision Weighted
            verified: true
          - type: recall
            value: 0.896
            name: Recall Macro
            verified: true
          - type: recall
            value: 0.896
            name: Recall Micro
            verified: true
          - type: recall
            value: 0.896
            name: Recall Weighted
            verified: true
          - type: f1
            value: 0.896
            name: F1 Macro
            verified: true
          - type: f1
            value: 0.895
            name: F1 Micro
            verified: true
          - type: f1
            value: 0.895
            name: F1 Weighted
            verified: true

botdevringring/fr-naxai-ai-emotion-classification-081808122023(latest)

The model is trained on the emotion classification task in the French language. It uses 6 labels:

LABEL 0 : sadness
LABEL 1 : joy
LABEL 2 : love
LABEL 3 : anger
LABEL 4 : fear
LABEL 5 : surprise

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

Model Details

Language: fr
Problem type: Multi-class Classification
Model Architecture: CamemBERT
Model Name: fr-naxai-ai-emotion-classification-081808122023
Creation date:

Classification Report:

Label	Precision	Recall	f1-Score	Support
anger	0.91	0.91	0.91	2824
fear	0.89	0.87	0.88	2824
joy	0.91	0.82	0.87	2824
love	0.88	0.92	0.90	2824
sadness	0.93	0.90	0.91	2823
surprise	0.89	0.98	0.93	2824

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-emotion-classification-081808122023',
    tokenizer='botdevringring/fr-naxai-ai-emotion-classification-081808122023'
)
result = analyzer(
    "je commence à me sentir déprimé"
)

result

[
  {
    'label': 'sadness',
    'score': 0.999739944934845
  }
]

Or you can use cURL:

curl https://api-inference.huggingface.co/models/botdevringring/fr-naxai-ai-emotion-classification-081808122023 \
    -X POST \
    -d '{"inputs": "je commence à me sentir déprimé"}' \
    -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