YamenRM/sarcasm_model

DistilBERT for Sarcasm Detection 🎭

This is a fine-tuned DistilBERT model on the News Headlines Dataset for Sarcasm Detection.

📊 Dataset

• —Source: News Headlines Dataset for Sarcasm Detection
• —Task: Binary classification (0 = Not Sarcastic, 1 = Sarcastic)
• —Size: ~28,000 headlines

🧠 Model Training

• —Framework: Hugging Face Transformers
• —Tokenizer: distilbert-base-uncased
• —Training epochs: 3
• —Optimizer: AdamW
• —Batch size: 16

📈 Performance

🚀 Usage

from transformers import pipeline

# Load the model from HF Hub
classifier = pipeline("text-classification", model="YamenRM/sarcasm_model")

# Example
text = "Oh great, another Monday morning meeting!"
print(classifier(text))

Output:

[{'label': 'SARCASTIC', 'score': 0.93}]

✨ Author

Trained and uploaded by YamenRM .