jiosephlee/intern-s1-mini-context-conditioned-molecule-transfer-v9-0-2-tdc-v2-skin-reaction-best

Intern-S1-mini molecule transfer V9.0.2 TDC V2 — Skin Reaction

Validation-selected checkpoint trained on the Skin Reaction V9.0.2 TDC V2 combined dataset. The training data combines 13,536 TDC and 85,321 Starling direct records with deterministic 1:1 indirect augmentation.

Provenance

• —Base model: jiosephlee/Intern-S1-mini-lm
• —Base model revision: fcb667c380ae01f57693a45b4b5c2d331052a107
• —Training dataset: jiosephlee/context-conditioned-molecule-transfer-v9.0.2-tdc-v2-skin-reaction-mixed-continuous-intern
• —Dataset revision: 4d97c745c735aa8d6dc07b81305e93f4e3bea496
• —Training configuration: 10 scheduled epochs, seed 42, 4 GPUs, device batch size 2, gradient accumulation 16, effective batch size 128, and ranking validation every 20 optimizer steps
• —Selection metric: validation KNN binary macro F1@5 (higher is better)
• —Selected optimizer step: 80
• —Selected validation F1@5: 0.7500
• —The run was deliberately stopped at step 222; this repository contains its complete best-observed checkpoint.
• —Training run
• —Held-out model/Morgan comparison

Held-out test comparison

The combined model was selected over the indirect-only model because its primary test F1@5 was 0.6192 versus 0.5732, and it beats both Morgan variants on F1@5. The top-1 and F1@3 results are included to make the tradeoff explicit.

The repository contains the full Transformers checkpoint and tokenizer files. metric.json is the complete validation-selection record stored with the checkpoint. Loading requires trust_remote_code=True for the custom tokenizer.