Model Card: ChemFM Adapters for DILI Prediction on ADMET Group
Model Overview:
This adapter is fine-tuned on the DILI dataset. It uses ChemFM as the base model and is trained on SMILES representations.
Task Description:
The task a classification task, and the objective is to predict whether a drug can cause liver injury with binary labels, indicating its potential for hepatotoxicity.
Dataset:
The whole dataset contains 475 samples. For more details about the dataset, visit ADMET benchmark.
How to Use:
For more details on how to use this model, visit ChemFM GitHub.
