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Polaris-ASAP-OpenADMET2025
apalania/Polaris-ASAP-OpenADMET2025
Polaris-ASAP-OpenADMET2025 is a machine learning model from apalania. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-sa-4.0.
- LogDAugmented55Descrandomsplit1.pth - LogDPolaris25Descrandomsplit6.pth - LogDPolaris55Descrandomsplit6.pth
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Updated Sep 3, 2026
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At a glance
- License
- cc-by-sa-4.0
- Access
- Public
- Created
- Jan 9, 2026
- Updated
- Sep 3, 2026
- SHA
- 880188df
Model card
From the Hugging Face model README
Models from experiments with the ASAP-Polaris-OpenADMET Antiviral Challenge 2025
ADME models:
1. LogD ensemble:
- LogD_Augmented_55Desc_random_split1.pth
- LogD_Polaris_25Desc_random_split6.pth
- LogD_Polaris_55Desc_random_split6.pth
2. KSOL: single best model
- KSOL_Polaris_55Desc_scaffold_split6.pth
- KSOL_Polaris_55_scaffold_model_6_retrained.pth
The model before retraining as well as after retraining is provided
3. HLM ensemble:
- HLM_Augmented_25Desc_random_split8.pth
- HLM_Augmented_55Desc_random_split4.pth
- HLM_Polaris_55Desc_random_split5.pth
4. MLM ensemble:
- MLM_Augmented_55Desc_scaffold_split2.pth
- MLM_Polaris_25Desc_random_split9.pth
- MLM_Polaris_55Desc_random_split1.pth
5. MDR1-MDCKII: single best model
- MDR1-MDCK2_Polaris_25Desc_random_split1.pth
- MDR1-MDCK2_Polaris_25_scaffold_model_1_retrained.pth
Both the scaffold and random split for the same model configuration are provided.
Potency models:
1. Base ChEMBL-UniProt model:
- Potency_Base-model_EnhancedFeats.pt
- Potency_BaseModel_tokenizer_enhanced-features.pkl
- Potency_BaseModel_vocab_enhanced-features.pkl
2. Finetuned models:
- Potency_BaseModel_GPFT-Polaris_target-strats_random_p1-10-best.pt
- Potency_BaseModel_GPFT-Polaris_target-strats_scaffold_p1-5-best.pt
3. Domain-specific model GraphML trained from scratch:
- Potency_AttFPGNN-Transformer_Polaris-only_target-strats_random.pt
- Potency_AttFPGNN-Transformer_Polaris-only_target-strats_scaffold.pt
- Potency_AttFPGNN-Transformer_Polaris-only_tokenizer_enhanced_scaffold.pkl
- Potency_AttFPGNN-Transformer_Polaris-only_vocab_enhanced_scaffold.pkl
4. XGBoost models (enhanced with docking scores):
- Potency_xgb_25D_wDock_target-strat_random-split.json
- Potency_xgb_25D_wDock_target-strat_random-split.pkl
5. Stacking meta-learner (overall best):
- Potency_Stacking_overall-best_Polaris-only_random-split.pth
Inference codes:
- adme_inference.py
- potency_inference.py
References
- License
- cc-by-sa-4.0
- Created
- Jan 9, 2026
- Updated
- Sep 3, 2026