octo-models / octo

Octo is a transformer-based robot policy trained on a diverse mix of 800k robot trajectories.
https://octo-models.github.io/
MIT License
754 stars 146 forks source link

MSE loss in logs #33

Open lyshuga opened 8 months ago

lyshuga commented 8 months ago

Hi,

After doing fine-tuning, I have checked MSE plots in two tabs: " offline_metrics_red_cube/text_conditioned" and "training", and they were quite different.

image

I was wondering if it is the same function used in both of evaluations?

kpertsch commented 8 months ago

The training "MSE" for the diffusion head we are using is actually the MSE between predicted and actual noise, not actions. In contrast, the evaluation MSE is the mse between predicted and actual actions, so they are not comparable. See training MSE computation here.

This is a bit confusing, maybe we should proper action MSE computation to training or remove the training MSE for diffusion head alltogether.

lyshuga commented 8 months ago

Thanks for your reply, clear now.

Indeed, it would be great at least to add action MSE to the train logs, and detail the names. Should be easy to understand after that :)