--- library_name: pytorch license: apache-2.0 tags: - polymers - molecular-optimization - transformer - polyedit --- # PolyEdit Molecular Optimization Transformer (polymer-retrained) This checkpoint adapts MolecularAI's released Molecular Optimization Transformer to two-anchor PSMILES and the eight PolyEdit DFT properties. It is not directly comparable to the authors' original LogD/Solubility/Clint model without this adaptation. The original transformer body is retained: 6 encoder/decoder layers, hidden size 256, 8 heads, and feed-forward size 2,048. All 258 shape-compatible upstream tensors were loaded. Four vocabulary-dependent embedding/generator tensors were initialized for a new vocabulary in which padding and the `*` polymer anchor have distinct IDs. Training used 152,036 component-held-out examples; the best validation checkpoint was epoch 7 of 10. On the balanced 8,176-request test set, the checkpoint obtains 99.217% RDKit+TDC validity, 99.168% two-anchor polymer validity, 99.083% changed outputs, 8.892% strict MIPS-retrained full-edit hits, and 10.127% strict DFT full-edit hits at 95.034% DFT coverage. Only 383 unique raw outputs were generated, so the strong validity comes with substantial mode collapse and must not be reported without the diversity result. Upstream code: Upstream checkpoint: PolyEdit implementation and record-level evaluation: