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Amazing work on your Amouranth LoRA for Wan2.1 T2V 14B! I saw you achieved great results

I'd love to learn from your experience as I'm training a similar LoRA on my RTX 4090 (24GB) using Diffusion-Pipe.

Could you possibly share some specifics of your training config? I'm trying to figure out the optimal settings, especially:

What resolution did you train at?

What LoRA rank did you use (to get the ~300MB size)?

What optimizer (e.g., AdamW8bitKahan?), lr, and LR scheduler settings worked well?

Roughly how many epochs did you train for?

What did you set for gradient_accumulation_steps and num_repeats in the dataset config?

Did you need to use blocks_to_swap, and if so, how many? Was activation_checkpointing enabled?

For captions, did you use detailed descriptions or just a trigger word?

Understanding these key parameters would be a massive help. Thanks for considering!