Iloriayomide/Symptom_Prediction

🏥 SymbiPredict: ClinicalBERT Symptom-to-Disease Classifier

This model is a fine-tuned version of Bio_ClinicalBERT, optimized to predict diseases based on natural language descriptions of symptoms.

It has been trained on a massive merged dataset of over 96,000 patient cases covering 115+ unique medical conditions.

📊 Model Performance

Epoch	Training Loss	Validation Loss
1	0.4108	0.3452
2	0.3092	0.2852
3	0.2526	0.2577

The model achieves a final validation loss of 0.2577, demonstrating high confidence and generalization capabilities across 115 disease classes.

🚀 How to Use (Python)

You can use this model directly with the Hugging Face pipeline.

from transformers import pipeline

# Load the pipeline
classifier = pipeline("text-classification", model="Iloriayomide/Symptom_Prediction", top_k=3)

# Test with symptoms
symptoms = "I have a severe headache, sensitivity to light, and I feel nauseous."
prediction = classifier(symptoms)

print(prediction)