Chemprop Issue with Custom Model in Reinvent_TLRL.ipynb

[kong0706]

I trained a chemoprop model (version 1.7.1) using my own data, and the model performed well. I embedded it into REINVENT and it ran smoothly on Reinvent_TLRL.ipynb. However, when I used the chemoprop model to predict the generated molecules, I found that the predicted values were significantly different from the ChemProp(raw) in stage_2.csv. I speculate that this may be a problem with the chemoprop model, because when I used the model.pt provided in Reinvent_TLRL.ipynb, the predicted values of the generated molecules were consistent with the ChemProp(raw) in stage_2.csv. I don't know how to solve this problem. Can you provide some constructive suggestions? Thank you.

[kong0706]

The chemprop scoring component in the toml file is written like this. Since my training set scores are all between 0-1, I did not add a score conversion function. Additionally, I uploaded my model.pt file. model.zip

[[stage.scoring.component]]
[stage.scoring.component.ChemProp]
[[stage.scoring.component.ChemProp.endpoint]]
name = "ChemProp"
weight = 0.6
params.checkpoint_dir = "/tmp/R4_notebooks_output/chemprop"
params.rdkit_2d_normalized = true
params.target_column = "score"

[halx]

I can't really add much to this. I had a similar experience with the TNKS2 model you are referring to. The model has been trained with ChemProp 1.5.2. Predictions with version 1.6, however, produced significantly different results. I do not know what the origin of that is.

[kong0706]

Thank you for your reply. I can only try using ChemProp 1.5.2 and observe the results.