
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
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gets general size and proportions right, and finally picked up on the two metal spires atop the building
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interior geometry is consistent, size (of room) is acceptable too
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I don't think I will train any more versions, but if i do, i would address
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reduce film grain/analogue film effect
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pods are slightly fuzzy (i think because some of the training images had them with demolition netting over)
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interiors always tend to generate hardwood floors
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sky tends to be overexposed (will have to photoshop dataset or find new images)
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switching to Ostris' ai-toolkit
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network rank (and alpha) increased to 32
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4000 steps
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LR 1e-4 (default for flux preset)
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explicit triggerword set
nctower
v4 - interior better, exterior worse
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It's kind of bad at replicating the exterior, but it is getting some of the interior geometries right
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network rank seems to be max 16 with my current simpletuner setup, i can't seem to make it any higher
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LR reset to default
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changed to CosineAnnealingWarmRestarts scheduler, 4 restarts
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max steps reverted to 2000
v3 something went horribly wrong
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Garbage output, maybe doubling LR wasn't the best idea?
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Dataset updated (more variety, particularly added more that depicted people, more detailed captions)
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all settings reset to default (same as V1), except:
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max steps reduced to 1800
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learning rate doubled to 10e4
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network rank doubled to 32somehow the setting didn't change?
v2 LoRA is okay
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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,
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it is starting to understand the qualities of the interior rooms.
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it is not overtrained or "burned"; it can render other types of towers just fine in the same prompt
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I think it needs a higher network rank to fully understand both interior and exterior qualities.
v1 LoRA is undertrained
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using sinmpletuner
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default learning rate, 2000 steps × batch size 1
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exterior appearance: it understands the individual pods but rarely arranges them in the same type of quasi-random geometry
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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