Mental Health Emotion Detection - Logistic Regression

This model performs multi-label emotion classification for mental health applications, detecting 28 different emotions from text input.

Model Description

Model Type: Logistic Regression (Multi-Output Classifier)
Framework: scikit-learn
Task: Multi-label emotion classification
Dataset: GoEmotions (balanced subset)
Languages: English

Performance

Metric	Score
F1-Score	0.298
Precision	0.219
Recall	0.508
Accuracy	90.1%

Emotions Detected

The model can detect 28 emotions: admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise, neutral.

Usage

import pickle
import requests

# Using HuggingFace Inference API
API_URL = "https://api-inference.huggingface.co/models/YOUR_USERNAME/mental-health-logistic-regression"
headers = {"Authorization": "Bearer YOUR_HF_TOKEN"}

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

# Example usage
result = query({"inputs": "I'm feeling really anxious about tomorrow"})
print(result)

Training Details

Training Data: Balanced GoEmotions dataset (~15,000 samples)
Features: TF-IDF vectorization
Preprocessing: Contraction expansion, lowercase normalization
Class Balancing: Advanced sampling techniques for rare emotions

Intended Use

This model is designed for mental health applications, chatbots, and emotion-aware systems. It provides high recall for detecting emotional states that might require support or intervention.

Limitations

Trained primarily on English text
Performance may vary with informal language or slang
Should not be used as sole diagnostic tool for mental health

Citation

If you use this model, please cite:

@misc{mental-health-emotion-logistic,
  title={Mental Health Emotion Detection - Logistic Regression},
  author={Your Name},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/YOUR_USERNAME/mental-health-logistic-regression}
}

Downloads last month: 7