Nakagin Capsule Tower (Flux/F1D)版本v4 (ID: 808190)

Nakagin Capsule Tower (Flux/F1D)版本v4 (ID: 808190)

base F1.d doesn't know this building at all, so this is a training experiment for me to better understand how to train F1D LoRA models for non-people/non-characters.

I'm pretty satisfied with v5, I don't think I will be training any more versions unless I find out something revolutionary.

My training notes

v5 - excellent, i am satisfy

v5 works with onsite generator but isn't as consistent as local generation

  • gets general size and proportions right, and finally picked up on the two metal spires atop the building

  • interior geometry is consistent, size (of room) is acceptable too

  • I don't think I will train any more versions, but if i do, i would address

    • reduce film grain/analogue film effect

    • pods are slightly fuzzy (i think because some of the training images had them with demolition netting over)

    • interiors always tend to generate hardwood floors

    • sky tends to be overexposed (will have to photoshop dataset or find new images)

  • switching to Ostris' ai-toolkit

  • network rank (and alpha) increased to 32

  • 4000 steps

  • LR 1e-4 (default for flux preset)

  • explicit triggerword set nctower

v4 - interior better, exterior worse

  • It's kind of bad at replicating the exterior, but it is getting some of the interior geometries right

  • network rank seems to be max 16 with my current simpletuner setup, i can't seem to make it any higher

  • LR reset to default

  • changed to CosineAnnealingWarmRestarts scheduler, 4 restarts

  • max steps reverted to 2000

v3 something went horribly wrong

  • Garbage output, maybe doubling LR wasn't the best idea?

  • Dataset updated (more variety, particularly added more that depicted people, more detailed captions)

  • all settings reset to default (same as V1), except:

  • max steps reduced to 1800

  • learning rate doubled to 10e4

  • network rank doubled to 32 somehow the setting didn't change?

v2 LoRA is okay

  • I increased the batch size 4x, and as a result it was trained for much longer
    (2000 steps × batch size 4, I cut it off at 1500 as it was taking way too long on my rented hourly rate GPU)

  • it gets the exterior appearance consistent,

  • it is starting to understand the qualities of the interior rooms.

  • it is not overtrained or "burned"; it can render other types of towers just fine in the same prompt

  • I think it needs a higher network rank to fully understand both interior and exterior qualities.

v1 LoRA is undertrained

  • using sinmpletuner

  • default learning rate, 2000 steps × batch size 1

  • exterior appearance: it understands the individual pods but rarely arranges them in the same type of quasi-random geometry

  • interior: it understands the narrow room with single round window, but not much else

描述:

训练词语: Nakagin Capsule Tower

名称: ts_f1d_nakagincapsuletower_v4_2000.safetensors

大小 (KB): 36530

类型: Model

Pickle 扫描结果: Success

Pickle 扫描信息: No Pickle imports

病毒扫描结果: Success

名称: ts_f1d_nakagincapsuletower_v4_moreepochs.zip

大小 (KB): 115700

类型: Model

Pickle 扫描结果: Success

Pickle 扫描信息: No Pickle imports

病毒扫描结果: Success

名称: ts_nakagincapsuletower_v4.zip

大小 (KB): 34388

类型: Training Data

Pickle 扫描结果: Success

Pickle 扫描信息: No Pickle imports

病毒扫描结果: Success

Nakagin Capsule Tower (Flux/F1D)

Nakagin Capsule Tower (Flux/F1D)

Nakagin Capsule Tower (Flux/F1D)

Nakagin Capsule Tower (Flux/F1D)

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