deberta-emotion-classifier

DeBERTa Emotion Classifier

This model classifies text into 5 emotions:

• 😠 Anger
• 😨 Fear
• 😊 Joy
• 😢 Sadness
• 😲 Surprise

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model_name = "Somya26/deberta-emotion-classifier"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

text = "I am so happy today!"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
probs = torch.sigmoid(outputs.logits).squeeze()

emotions = ['anger', 'fear', 'joy', 'sadness', 'surprise']
for emotion, prob in zip(emotions, probs):
    print(f"{emotion}: {prob:.2%}")

Training

Trained on emotion classification dataset using DeBERTa-v3-base.