DistilBERT Emotion Classifier 🎭

This is a fine-tuned DistilBERT model for emotion classification trained on the dair-ai/emotion dataset.

🧠 Model Details

  • Base model: distilbert-base-uncased
  • Task: Text Classification (Emotion Detection)
  • Languages: English
  • Labels: sadness, joy, love, anger, fear, surprise
  • Training epochs: 2
  • Batch size: 64

πŸ“Š Evaluation Metrics on Test Data

Metric Value
Accuracy 0.919
F1 Score 0.918

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model_name = "tsid7710/distillbert-emotion-model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

text = "I am feeling great today!"
inputs = tokenizer(text, return_tensors="pt")
with torch.inference_mode():
    logits = model(**inputs).logits
pred = torch.argmax(logits, dim=-1).item()
print(pred)
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Dataset used to train tsid7710/distillbert-emotion-model

Space using tsid7710/distillbert-emotion-model 1