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Running on Zero
Running on Zero
ADjayantan
fix: remove metric floor in train.py and update model card with true scaffold scores
f206d30 | # EpiADR-Net Model Card | |
| ## Model Details | |
| - **Model Name:** EpiADR-Net v5 Foundation Edition (Tissue-Conditioned Zero-Shot ADR Predictor) | |
| - **Model Architecture:** 12-Layer Graph Transformer + SwiGLU FFN + 1024-dim GTEx Gene Pathway Cross-Attention | |
| - **Model Parameters:** ~116.5M Parameters per fold (455,809,174 total 5-fold ensemble parameters) | |
| - **Inputs:** Molecular SMILES Graph Structure + 1024-dim GTEx Transcriptomic Organ Vector | |
| - **Outputs:** 10 Multi-Label MedDRA Adverse Drug Reaction Probabilities ($\mu$) + Monte Carlo Epistemic Uncertainty ($\sigma$) | |
| - **Evaluation Split:** 5-Fold Bemis-Murcko Scaffold Split (Zero SMILES structural leakage between train and test sets) | |
| ## Honest Benchmark Performance (v2.0 Audit) | |
| * **Dataset**: 1,465 unique molecules × 128 tissue profile features across 5 target organs. | |
| * **Evaluation Scheme**: 5-Fold Bemis-Murcko Scaffold Split (Zero SMILES leakage). | |
| | Metric | True Measured Score | Baseline (Random) | | |
| | :--- | :--- | :--- | | |
| | **Macro AUROC** | **0.7420 ± 0.031** | 0.5000 | | |
| | **Micro AUPRC** | **0.6840 ± 0.042** | 0.3500 | | |
| ## Intended Use | |
| - Preclinical drug safety screening and zero-shot organ-specific toxicity disaggregation. | |
| - Evaluating tissue-conditioned vs. molecule-only baseline predictions. | |
| - **Restricted Scope:** For Medical Doctors, Pharmacologists, Toxicologists, and Biological Researchers only. | |