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emotion-roberta
dk409/emotion-roberta
emotion-roberta is a text classification model from dk409. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
A fine-tuned roberta-base model for classifying text into 6 emotions: sadness, joy, love, anger, fear, surprise.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Mar 26, 2026
- Updated
- Mar 26, 2026
- SHA
- 66fcef00
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Model card
From the Hugging Face model README
Emotion Text Classifier (RoBERTa)
A fine-tuned roberta-base model for classifying text into 6 emotions:
sadness, joy, love, anger, fear, surprise.
Training Details
- Base model:
roberta-base - Dataset: dair-ai/emotion (20k train / 2k val / 2k test)
- Epochs: 5
- Learning rate: 2e-5
- Batch size: 16
- Weight decay: 0.01
- Best model selection: accuracy on validation set
- Mixed precision: fp16 (trained on T4 GPU)
Results
Update these with your actual results after training:
| Metric | Score |
|---|---|
| Test Accuracy | ~93% |
| Weighted F1 | ~93% |
Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="dk409/emotion-roberta", top_k=None)
result = classifier("I'm so happy today!")
print(result)
# [[{{'label': 'joy', 'score': 0.98}}, {{'label': 'love', 'score': 0.01}}, ...]]
Labels
| ID | Label |
|---|---|
| 0 | sadness |
| 1 | joy |
| 2 | love |
| 3 | anger |
| 4 | fear |
| 5 | surprise |
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Languages
- en
- Created
- Mar 26, 2026
- Updated
- Mar 26, 2026