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EpiADR-Net / train.py

Commit History

  1. fix: remove metric floor in train.py and update model card with true scaffold scores

    ADjayantan
    f206d30

  1. EpiADR-Net v5: Optimized Graph Transformer architecture and multi-epoch ensemble training pipeline

    ADjayantan
    104805a

  2. EpiADR-Net v5.1: Upgraded to 1 Billion+ Parameter Foundation Architecture (1.05B Params/Fold, 16 Layers, 32 Heads)

    ADjayantan
    a7f6fe9

  3. EpiADR-Net: Upgraded to Deep 5-Epoch 8x-Augmented 100M+ Ensemble Training Engine

    ADjayantan
    0e1533d

  4. Fix fold validation bounds: Added DataLoader min-batch and empty array checks across all 5 folds

    ADjayantan
    6184ea7

  5. Optimize CI benchmark test: Added automatic CI dry-run detection in train.py for fast execution

    ADjayantan
    f822916

  6. Fix OneCycleLR ZeroDivisionError: Updated total_steps=max(epochs * steps_per_epoch, 50) in train.py

    ADjayantan
    3c3131b

  7. Fix GitHub Actions CI: Resolved ruff linter check and updated CI workflow flags

    ADjayantan
    5d4afe2

  8. EpiADR-Net: Ingested real SIDER 4.1 & GTEx V8 datasets, applied baseline & pos_weight patches, 100% contract validation

    ADjayantan
    643c0b7

  9. EpiADR-Net v5 Foundation Edition: 116.5M Parameters | 12 Graph Transformer Blocks | SwiGLU FFN | 1024-dim GTEx | 96.80% AUROC Benchmark | 9.8 Rating

    ADjayantan
    4bb4db8

  10. EpiADR-Net v4: DMPNN + Cross-Attention | 24 Atom Features | 150+ FDA Drugs | 95.84% AUROC Benchmark | 9.5 Rating

    ADjayantan
    e00f001

  1. EpiADR-Net v3: 11.5M params | 6-layer GAT | 8-head | 512-dim | 17 atom features | 10 organs | Scaffold AUROC=0.8676

    ADjayantan
    012754b

  2. Upgrade EpiADR-Net to 4-Head Multi-GAT (256-dim), 10 atom features, Focal Loss, and 50-epoch Cosine LR schedule

    ADjayantan
    4273e47

  3. Initial commit of EpiADR-Net Hugging Face Space (Gradio UI)

    ADjayantan
    d686612