I’m trying to build a multi-label classifier with TabularModel and TabularLearner. There are 206 targets I need to predict. However, 402 additional (auxiliary) targets are also provided (which I don’t need to predict).
The idea:
Train a model for the 402 auxiliary targets first.
Use the above as a pre-trained model & apply transfer learning to then train the final model (206 targets).
The input features for both models are exactly the same.
Strategy:
Create new architecture with same body & new head.
Load the ‘body weights’ of pre-trained model
How do I do this? In particular, how do I load just the body weights?