I have trained a model to predict my blood sugar (Part 2) [P]

Excerpt

This is related to my previous post where I shared an encoder-only transformer model trained on ohiot1dm + shanghait1dm + azt1d datasets. This time I trained the model on the outputs of my T1DM patient simulator and then measured its zero-shot performance on my real-world blood glucose traces. The above model has 31,251 parameters (16 layers, 1 attention head per layer, and a hidden dimension size of 16). Training took my app for light fine-tuning on my actual CGM traces, but the figures & table