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Model card - tox21_grover_classifier
Model details
- Model name: Grover Tox21 Baseline
- Developer: Tencent AI Lab (trained by JKU Linz)
- Paper URL: https://arxiv.org/pdf/2007.02835
- Model type / architecture:
- Grover implemented using the code accompanying the paper.
- The pretrained grover_base model is used as provided.
- A multitask network is finetuned for all Tox21 targets.
- Inference: Access via FastAPI endpoint. Upon a Tox21 prediction request, the model generates and returns predictions for all Tox21 targets simultaneously.
- Model version: v0
- Model date: 10.12.2025
- Reproducibility: Code for full training is available and enables refitting of TabPFN from scratch.
- Reproducibility: Code for full training is available and enables retraining of the model from scratch.
Intended use
This model serves as a baseline benchmark for evaluating and comparing toxicity prediction methods across the 12 pathway assays of the Tox21 dataset. It is not intended for clinical decision-making without experimental validation.
Metric
Each Tox21 task is evaluated using the area under the receiver operating characteristic curve (AUC). Overall performance is reported as the mean AUC across all individual tasks.
Training data
Tox21 training and validation sets.
Evaluation data
Tox21 test set.