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ResearchFormerly WizWand

Regression on MoleculeNet BACE (test)

1.047RMSEMolFormer
0.998761.324381.651.97562Sep 5, 2022Apr 17, 2023Nov 27, 2023Jul 9, 2024Feb 18, 2025Sep 30, 2025May 13, 2026
Updated 5mo ago

Evaluation results

MethodLinks
MolFormerFine-tuned=true2022.111.047
SPMMPre-training=true, Fine-tuned=true2022.111.096
Chem-GMNetPre-training strategy=MLM, Pre-training size=10M2026.051.103
RFEvaluation Protocol=Fine-tuned2022.091.3178
N-GramRFFine-tuned=true2022.111.318
Random ForestPre-training strategy=None2026.051.318
Chem-GMNetPre-training strategy=scratch, k=82026.051.35
ChemBERTa-2Pre-training Task=MTR, Pre-training Dataset Size=77M, Evaluation Protocol=Fine-tuned2022.091.363
ChemBERTa-2Pre-training strategy=MTR, Pre-training size=77M2026.051.363
ChemBERTa-2Pre-training Task=MTR, Pre-training Dataset Size=10M, Evaluation Protocol=Fine-tuned2022.091.417
ChemBERTa-2Pre-training strategy=MTR, Pre-training size=10M2026.051.417
ChemBERTa-2Pre-training Task=MLM, Pre-training Dataset Size=5M, Evaluation Protocol=Fine-tuned2022.091.451
ChemBERTa-2Pre-training strategy=MLM, Pre-training size=5M2026.051.451
ChemBERTa-2Pre-training Task=MTR, Pre-training Dataset Size=5M, Evaluation Protocol=Fine-tuned2022.091.477
ChemBERTa-2Pre-training strategy=MTR, Pre-training size=5M2026.051.477
ChemBERTa-2Pre-training Task=MLM, Pre-training Dataset Size=77M, Evaluation Protocol=Fine-tuned2022.091.509
ChemBERTa-2Pre-training strategy=MLM, Pre-training size=77M2026.051.509
ChemBERTa-2Pre-training Task=MLM, Pre-training Dataset Size=10M, Evaluation Protocol=Fine-tuned2022.091.611
ChemBERTa-2Pre-training strategy=MLM, Pre-training size=10M2026.051.611
GCNEvaluation Protocol=Fine-tuned2022.091.645
GCNPre-training strategy=None2026.051.645
SPMM (w/o pre-train)Pre-training=false, Fine-tuned=true2022.111.675
D-MPNNEvaluation Protocol=Fine-tuned2022.092.253
D-MPNNFine-tuned=true2022.112.253
D-MPNN (Chemprop)Pre-training strategy=None2026.052.253