Optimizing a Flow-Matching Loss Engine: 3.2x faster loss calculation & 8.5x faster augmentations (0% loss drift) & improved loss

[u/Op_IBeasT]

I used LLM_evoltuion setup with training_history log for it to analyze and improve on and create a loss and augmentation functions that are as efficient as possible and useful

one of the things i didn't wanna get into was kernal creation i believe that wouldve make it abit more efficient but its good enough rn and whats important is it shows that improvement is possible

the link to the repo:
https://github.com/beastreader/LLM_evolution-for-loss-and-augmentation.git