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--- |
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tags: |
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- multilabel-classification |
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- emotion-detection |
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- text-classification |
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- transformers |
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- deberta |
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- huggingface |
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license: apache-2.0 |
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datasets: |
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- custom |
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language: |
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- en |
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--- |
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# DeBERTa-v3-Large for Multilabel Emotion Classification |
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This model is a fine-tuned version of [`microsoft/deberta-v3-large`](https://huggingface.co/microsoft/deberta-v3-large) for multilabel emotion classification. |
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It was trained on a custom dataset where each text sample may contain multiple emotions. |
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## 📌 Model Card |
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- **Model**: `FurqonAryadana/deberta-emotion-multilabel-0.5007` |
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- **Base**: DeBERTa-v3-Large |
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- **Task**: Multilabel Emotion Classification |
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- **License**: Apache 2.0 |
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- **Language**: English |
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- **Threshold Tuning**: Applied per-label |
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## 📊 Evaluation (Validation Set) |
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**Detailed Classification Report (Threshold Tuned)**: |
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| Emotion | Precision | Recall | F1-score | Support | |
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|----------------|-----------|--------|----------|---------| |
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| amusement | 0.61 | 0.72 | 0.66 | 851 | |
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| anger | 0.43 | 0.58 | 0.49 | 999 | |
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| annoyance | 0.34 | 0.70 | 0.46 | 1609 | |
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| caring | 0.41 | 0.57 | 0.48 | 594 | |
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| confusion | 0.49 | 0.71 | 0.58 | 800 | |
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| disappointment | 0.30 | 0.47 | 0.37 | 990 | |
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| disgust | 0.27 | 0.49 | 0.35 | 584 | |
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| embarrassment | 0.33 | 0.32 | 0.33 | 308 | |
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| excitement | 0.45 | 0.47 | 0.46 | 632 | |
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| fear | 0.49 | 0.54 | 0.52 | 321 | |
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| gratitude | 0.83 | 0.73 | 0.78 | 955 | |
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| joy | 0.43 | 0.58 | 0.50 | 876 | |
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| love | 0.64 | 0.79 | 0.71 | 701 | |
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| sadness | 0.40 | 0.57 | 0.47 | 714 | |
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- **F1 Micro**: `0.5101` |
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- **F1 Macro**: `0.5107` |
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## 🧠 Emotions (Label Order) |
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```python |
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[ |
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'amusement', 'anger', 'annoyance', 'caring', 'confusion', 'disappointment', |
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'disgust', 'embarrassment', 'excitement', 'fear', 'gratitude', 'joy', |
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'love', 'sadness' |
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] |
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