PEARL Benchmark -- Top-5 Models per Dataset
Parameter-Efficient Adaptation with Retrieval-Augmented Learning for Molecular Property Prediction. Each dataset folder below holds its top-5 best-performing methods, ranked by the dataset's primary metric.
Code: https://github.com/raghvendra5688/PEARL
BACE (classification, ranked by MCC)
| Rank | Method | MCC | Configuration | Path |
|---|---|---|---|---|
| 1 | E2E LoRA -- Uni-Mol | 0.6234 | Weighted Loss | BACE/rank1_e2e-lora-uni-mol |
| 2 | E2E LoRA -- HF | 0.5660 | ibm__MoLFormer__XL__both__10pct, fl | BACE/rank2_e2e-lora-hf |
| 3 | FT Embed | 0.5570 | MolFormer_Finetuned_FL | BACE/rank3_ft-embed |
| 4 | RAFE | 0.5570 | MolFormer_Finetuned_FL | BACE/rank4_rafe |
| 5 | FT Embed+PC | 0.5500 | Molformer_Finetuned_WL_embeddings | BACE/rank5_ft-embed-pc |
BBBP (classification, ranked by MCC)
| Rank | Method | MCC | Configuration | Path |
|---|---|---|---|---|
| 1 | RAFE | 0.7980 | MolFormer_Finetuned_FL | BBBP/rank1_rafe |
| 2 | FT Embed+PC | 0.7890 | MolFormer_Finetuned_FL_embeddings | BBBP/rank2_ft-embed-pc |
| 3 | FT Embed | 0.7870 | MolFormer_Finetuned_FL | BBBP/rank3_ft-embed |
| 4 | E2E LoRA -- Uni-Mol | 0.7740 | Weighted Loss | BBBP/rank4_e2e-lora-uni-mol |
| 5 | E2E LoRA -- HF | 0.7670 | ibm__MoLFormer__XL__both__10pct, fl | BBBP/rank5_e2e-lora-hf |
FLAVOR (classification, ranked by MCC)
| Rank | Method | MCC | Configuration | Path |
|---|---|---|---|---|
| 1 | Chemprop | 0.8090 | D-MPNN | FLAVOR/rank1_chemprop |
| 2 | PC-only | 0.8080 | XGBoost | FLAVOR/rank2_pc-only |
| 3 | E2E LoRA -- HF | 0.8020 | DeepChem__ChemBERTa__77M__MTR, wl | FLAVOR/rank3_e2e-lora-hf |
| 4 | FT Embed+PC | 0.8010 | Molformer_Finetuned_WL_embeddings | FLAVOR/rank4_ft-embed-pc |
| 5 | RAFE | 0.8000 | ChemBERTa_77M_MTR_FL | FLAVOR/rank5_rafe |
HERG (classification, ranked by MCC)
| Rank | Method | MCC | Configuration | Path |
|---|---|---|---|---|
| 1 | E2E LoRA -- Uni-Mol | 0.6093 | Weighted Loss | HERG/rank1_e2e-lora-uni-mol |
| 2 | PC-only | 0.6040 | XGBoost | HERG/rank2_pc-only |
| 3 | FT Embed+PC | 0.6015 | UniMol_FL | HERG/rank3_ft-embed-pc |
| 4 | RAFE | 0.5889 | UniMol_FL | HERG/rank4_rafe |
| 5 | FT Embed | 0.5798 | UniMol_FL | HERG/rank5_ft-embed |
DILI (classification, ranked by MCC)
| Rank | Method | MCC | Configuration | Path |
|---|---|---|---|---|
| 1 | RAFE | 0.7897 | UniMol_FL | DILI/rank1_rafe |
| 2 | E2E LoRA -- HF | 0.7704 | DeepChem__ChemBERTa__77M__MTR, wl | DILI/rank2_e2e-lora-hf |
| 3 | PC-only | 0.7650 | CatBoost | DILI/rank3_pc-only |
| 4 | GCN | 0.7280 | GINConv | DILI/rank4_gcn |
| 5 | E2E LoRA -- Uni-Mol | 0.7079 | Focal Loss | DILI/rank5_e2e-lora-uni-mol |
CACO2 (regression, ranked by Spearman)
| Rank | Method | Spearman | Configuration | Path |
|---|---|---|---|---|
| 1 | PC-only | 0.8534 | CatBoost | CACO2/rank1_pc-only |
| 2 | RAFE | 0.8347 | ChemBERTa_77M_MTR_Huber | CACO2/rank2_rafe |
| 3 | FT Embed+PC | 0.8271 | ChemBERTa_77M_MTR_Huber | CACO2/rank3_ft-embed-pc |
| 4 | FT Embed | 0.8211 | ChemBERTa_77M_MTR_Huber | CACO2/rank4_ft-embed |
| 5 | Chemprop | 0.8022 | D-MPNN | CACO2/rank5_chemprop |
HALF_LIFE (regression, ranked by Spearman)
| Rank | Method | Spearman | Configuration | Path |
|---|---|---|---|---|
| 1 | FT Embed | 0.6226 | MolFormer_Finetuned_Huber | HALF_LIFE/rank1_ft-embed |
| 2 | FT Embed+PC | 0.5927 | MolFormer_Finetuned_Huber | HALF_LIFE/rank2_ft-embed-pc |
| 3 | RAFE | 0.5684 | MolFormer_Finetuned_Huber | HALF_LIFE/rank3_rafe |
| 4 | E2E LoRA -- HF | 0.5406 | DeepChem__ChemBERTa__77M__MTR, huber | HALF_LIFE/rank4_e2e-lora-hf |
| 5 | PC-only | 0.5211 | CatBoost | HALF_LIFE/rank5_pc-only |
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support