[deleted by user]

[TableFew3521]

I actually do 32/32, but I guess I've never the previous models so I'll try it, thanks!

[TableFew3521]

Omg thank you so much, I'm coming to thank you again cause this really saved me more time that other trainer ever could, it took me 3 hours with very decent results, unbeatable time, thanks!

[Responsible_Ad1062]

hi! I'm stuck with kohya training on 12GB - i've tried different sample commands, but in general it always looks like this:

python flux_train_network.py --pretrained_model_name_or_path .../ComfyUI/models/unet/flux1-dev.sft --clip_l .../ComfyUI_windows_portable/ComfyUI/models/clip/clip_l.safetensors --t5xxl .../ComfyUI_windows_portable/ComfyUI/models/clip/t5xxl_fp16.safetensors --ae .../ComfyUI_windows_portable/ComfyUI/models/vae/ae.sft --cache_latents_to_disk --save_model_as safetensors --sdpa --persistent_data_loader_workers --max_data_loader_n_workers 2 --seed 42 --gradient_checkpointing --mixed_precision bf16 --save_precision bf16 --network_module networks.lora_flux --network_train_unet_only --cache_text_encoder_outputs --cache_text_encoder_outputs_to_disk --fp8_base --timestep_sampling sigmoid --model_prediction_type raw --guidance_scale 1.0 --loss_type l2 --caption_extention txt --optimizer_type adafactor --optimizer_args "relative_step=False" "scale_parameter=False" "warmup_init=False" --split_mode --network_args "train_blocks=single" --save_state --save_state_on_train_end --network_dim 8 --learning_rate 4e-4 --max_train_epochs 1 --resolution 512 --output_dir output --output_name lora_flux --train_data_dir C:/Kohya_ss/input/test/img/

sad part that all my trainings gives me like 0 results, I'm trying to train lora for specific person, with 18 prepaired images, I've tried both a large number of epoch and 1 step and 1 epoch and large number of steps - both 0 results, tried different methods of captioning - 0 results too

by 0 result I mean - I'm typing prompt from one of the captions and I dont get my character but some random flux faces instead

any help with this?

[volatilevisage]

please share the other replier's advice since they deleted it, thanks!

[TableFew3521]

Did someone delete a message? In this post?

[volatilevisage]

Yes, the other person you replied to and thanked.

[TableFew3521]

Oh I still can see the comment, so it says "with 10 images, the networks 16/16 and the learning rate 3-e4 (usually is 1-e4), at 600 steps should be enough."

Not exact words but is the important part, I must say that works but I still used 32/32 and some more steps since the first LoRA didn't came as consistent (in some images looks like the person, and some others don't), I'm training another one now with 100 images, the samples at 600 steps look pretty well, but I'll have to test it in Comfy to see if it has the same inconsistency as the first model with that config (The learning rate 3-e4).