How to interpret reconstruction loss increase but elbo loss decrease on trained scvi and scanvi models

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Hi, I am trying to use lung cancer single cell atlas (https://luca.icbi.at/) to annotate a Xenium experiment. Given Xenium is gene-panel based (~400 genes), I retrained atlas by subsetting features to 400, first training scvi model to integrate, then using semi-supervised scanvi model with cell type as label key. For both model, I trained 300 epochs. However, when examining the model metrics, I noticed elbo loss decrease but reconstruction loss increase. Here are the plots

luca_ref_404var_lungOnly.model_metrics
luca_ref_404var_lungOnly.model_metrics1500×1000 97.6 KB

I am wondering:

  1. Is my planned workflow (subset features - reference scvi training- reference scanvi training - query-reference mapping) valid?
  2. how do we interpret “reconstruction loss increase”? I am a little suspicious that the features from Xenium gene panel are not good to represent cell type. I am wondering whether this can be the reason.
  3. With this quality of training, can i use the model to do reference mapping for Xenium data?

Thank you!!!