🎭 Polish Twitter Emotion Classifier

This model predicts emotions and sentiment in Polish text using a fine-tuned PKOBP/polish-roberta-8k model.

Detected labels:

• Emotions: 😊 radość (joy), 🤢 wstręt (disgust), 😠 gniew (anger), 🤔 przeczuwanie (anticipation)
• Sentiment: 👍 pozytywny (positive), 👎 negatywny (negative), 😐 neutralny (neutral)
• Special: 😏 sarkazm (sarcasm)

The model uses multi-label classification - text can have multiple emotions/sentiments simultaneously.

Example Input

Model Performance

How to Use

1. Enter Polish text: Paste a tweet, social media post, or any Polish text
2. Select mode:
   • Calibrated (recommended): Uses temperature scaling and optimal thresholds per label
   • Default: Uses a single threshold for all labels
3. Adjust settings: Toggle mention anonymization, adjust threshold (Default mode)
4. Click Analyze: Get emotion and sentiment predictions with confidence scores

Prediction Modes

• Calibrated Mode (Recommended): Uses temperature scaling and label-specific optimal thresholds for better accuracy and calibration. This mode is recommended for most use cases.
• Default Mode: Uses sigmoid activation with a single threshold across all labels. Useful for quick predictions or when you want uniform threshold control.

Limitations

• Model is trained on Polish Twitter data and works best with informal social media text
• May not generalize well to formal Polish text (news, academic writing)
• Optimal for tweet-length texts (not very long documents)
• Multi-label nature means texts can have seemingly contradictory labels (e.g., sarkazm + pozytywny)

Citation

If you use this model, please cite:

@model{yazoniak2025twitteremotionpl,
  author = {yazoniak},
  title = {Polish Twitter Emotion Classifier},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/yazoniak/twitter-emotion-pl-classifier}
}

📄 License

GPL-3.0 License