I'm following the tabnet tutorial RStudio AI Blog: torch, tidymodels, and high-energy physics
The author has shown how easy it is to tune the hyperparameter with the tidymodels framework but did not finalize the model with the best tuned parameters. I encountered error message when I finalize the workflow
best <- res %>% select_best(metric = "rmse") final_wf <- wf %>% finalize_workflow(best) Error in update.default(object = list(args = list(epochs = ~10, penalty = ~1e-06, : need an object with call component
Is it possible to update tabnet model with workflow or am I missing something here?