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Medicanite – Fine-Tuned Medical Language Model (Granite-3.3-2B-Instruct)

Model Summary

Medicanite is a fine-tuned, 2.53-billion parameter instruction-following model specialized for medical and healthcare-related tasks. Built on top of Granite-3.3-2B-Instruct, Medicanite is optimized for factuality and QA performance in clinical domains.

It was trained on the MedQUAD corpus (pre-cleaned) using 15,586 curated QA pairs for training and 821 for validation, with a low learning rate and LoRA (r=4, Ξ±=16) adaptation strategy. Despite its compact size, Medicanite outperforms both its base model and other leading open medical models in its class.


πŸ”¬ Benchmark Performance

Task Medicanite Granite-3.3-2B JSL-MedPhi2-2.7B
MedMCQA 40.90% 40.50% 38.90%
MedQA 43.80% 42.50% 38.41%
MMLU Anatomy 53.30% 51.90% 48.89%
MMLU Clinical Knowledge 57.70% 60.80% 63.02%
MMLU College Biology 59.00% 59.00% 62.50%
MMLU College Medicine 53.80% 54.30% 58.38%
MMLU Medical Genetics 67.00% 62.00% 62.00%
MMLU Professional Medicine 54.00% 51.80% 44.12%
PubMedQA 72.80% 71.00% 73.00%
Average 55.82% 54.86% 54.36%

πŸ› οΈ Training Details

  • Base model: ibm-granite/granite-3.3-2b-instruct
  • Training corpus: MedQUAD (cleaned)
  • # Training examples: 15,586
  • # Validation examples: 821
  • LoRA rank (r): 4
  • Alpha: 16
  • Learning rate: 7e-6
  • Precision: bfloat16

🩺 Intended Use

This model is optimized for:

  • Medical question answering
  • Clinical knowledge tasks
  • Instruction-following in health-related domains
  • Educational use in biomedical fields
  • Local/offline deployment for low-resource settings

⚠️ Limitations

  • Not a diagnostic tool. Medicanite is intended for research and educational purposes only.
  • May hallucinate facts or give outdated/incomplete medical advice.
  • Always consult a licensed medical professional for clinical decisions.

πŸ“œ License

Apache 2.0 β€” same as the base Granite model.


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