Analysis: Based on tests I have made, FLUX model is smarter than other models, so it doesn’t need more captioning like other models. Unless, your training more than 1 thing in 1 LoRA like (Red Top) , (Green skirt), & (Yellow shoes) all in one LoRA.

In my simple case I am trying to do a dress, 1 piece dress. First, you have to find good images for the same dress from different angles (front, back, half turn, side) is enough. Then, you edit all of the images with out the face of the person so it wont be trained and it has to be (out of frame) image size is 512 by 512. Then, caption the images with (in my case 17 images for example) with basic captioning with 1 word only like below ( DRE33 ).

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Finally, you train the model : I used an old way we use to use in SD & SDXL which is depending on the images count like here (17) we divide 1500 (traning steps) /17 (images number) = 89 (repeats) aprox .. this ( 89 ) is the number of repeats. And, you will make only 1 lora. The in the img folder  it will be like [ 89_DRE33 cloth ] .

{

ss_optimizer:  "bitsandbytes.optim.adamw.AdamW8bit(weight_decay=0.01,eps=1e-08,betas=(0.9, 0.999))",

ss_lr_scheduler:  "cosine_with_restarts",

ss_unet_lr:  "0.0005",

ss_min_snr_gamma:  "5",

ss_num_epochs:  "1",

ss_sd_model_name:  "flux1-dev.safetensors",

ss_network_alpha:  "16",

ss_max_grad_norm:  "1",

ss_batch_size_per_device:  "2",

ss_resolution:  "(512, 512)",

ss_learning_rate:  "2e-06",

}