
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: ***anger***, ***fear***, ***joy*** ***love***, ***sadness***, ***surprise***.

This model is finetuned from [distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base).
A distillation version of the [CamemBERT](https://huggingface.co/camembert-base) 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:

```python
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](https://www.linkedin.com/in/eduardobrigham/) for [Naxai](https://www.naxai.com/) powered by [The Ring Ring Company](https://www.ringring.be/)
{"language": ["fr"], "tags": ["CamemBERT", "emotion", "text-classification", "pytorch", "latest"], "datasets": ["botdevringring/FR_emotion_classification", "dair-ai/emotion"], "metrics": ["Accuracy, F1 Score"], "widget": [{"text": "je commence \u00e0 me sentir d\u00e9prim\u00e9"}, {"text": "je me sentirais honor\u00e9 et b\u00e9ni"}, {"text": "je r\u00e9alise que jai des amis je suis surpris"}, {"text": "quand jai failli me faire tabasser par le fr\u00e8re de ma copine"}], "pipeline_tag": "text-classification", "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}]}]}]}
transformers safetensors camembert text-classification CamemBERT emotion pytorch latest fr dataset:botdevringring/FR_emotion_classification dataset:dair-ai/emotion model-index autotrain_compatible endpoints_compatible region:us