Subhra-123/distilbert-base-emotion

🧠 DistilBERT Emotion Classification (by Subhra Sikha Sahoo)

This model is a fine-tuned version of distilbert-base-uncased for emotion classification.
It predicts the emotion expressed in a given text such as joy, sadness, anger, fear, love, surprise, etc.

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📘 Model Details

• Base Model: distilbert-base-uncased
• Trained By: Subhra Sikha Sahoo
• Task: Multi-label Emotion Classification
• Language: English
• Dataset Size: 20,000 samples

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🚀 Usage Example

from transformers import pipeline

pipe = pipeline("text-classification", model="Subhra-123/distilbert-base-emotion", return_all_scores=True)
text = "I love my friends!"
pred = pipe(text)[0]
emotion = max(pred, key=lambda x: x['score'])
print(f"{text} → {emotion['label']} ({emotion['score']:.2f})")