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TheLastBen / fast-stable-diffusion

fast-stable-diffusion + DreamBooth
MIT License
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when I resume a session, it suggest some weights of the model checkpoint were not used #555

Open yasmineyxz opened 1 year ago

yasmineyxz commented 1 year ago

when I resume a session, it suggest this: (the session name and the pics are the same,I just want to add more steps, so it is "initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical" and is not expected? am I misunderstanding something?how can I fix it?） —————————————————————————————————————— Session found, loading the trained model ... Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.encoder.layers.15.self_attn.k_proj.bias', 'vision_model.encoder.layers.12.self_attn.k_proj.bias', 'vision_model.encoder.layers.9.self_attn.v_proj.bias', 'vision_model.encoder.layers.21.self_attn.q_proj.bias', 'vision_model.encoder.layers.15.self_attn.out_proj.bias', 'vision_model.encoder.layers.13.mlp.fc1.weight', 'vision_model.encoder.layers.7.layer_norm1.bias', 'vision_model.encoder.layers.19.layer_norm1.weight', 'vision_model.encoder.layers.22.mlp.fc1.bias', 'vision_model.encoder.layers.2.self_attn.out_proj.bias', 'vision_model.encoder.layers.0.self_attn.q_proj.weight', 'vision_model.encoder.layers.10.mlp.fc2.bias', 'vision_model.encoder.layers.11.self_attn.k_proj.weight', 'vision_model.encoder.layers.2.mlp.fc2.weight', 'vision_model.encoder.layers.18.self_attn.q_proj.bias', 'vision_model.encoder.layers.12.layer_norm1.weight', 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TheLastBen commented 1 year ago

it's a normal message, ignore it

yasmineyxz commented 1 year ago

thank you so much.Ben. I 've trained the first character(30 pics,6000steps,50% text_encoder), it's great, and now want to add new characters and resume training, should I keep the pics of the former character , or should I just remove it? If keep, how should I set the text encoder steps?( if 50%, would it affect the effect of the former character?)

TheLastBen commented 1 year ago

if the character is from a different gender, remove, the instance images, if not, keep them, you should know that training two characters from the same gender will result in merging them.

yasmineyxz commented 1 year ago

thx. if I training two characters from the same gender at one time, will it still merging? is there any way to alleviate the problem?

TheLastBen commented 1 year ago

Nothing much from the training side

yasmineyxz commented 1 year ago

Nothing much from the training side

thx for you reply: ) now I've trained 7 person in a session, each 10 imgs, totally 14000 steps，text encoder 40%。 The result is ok ,but not as good as the former one(one person , 30 imgs, 6000steps, textenc50%),not the merge person problem I think. I prepare to add 20 imgs each person and resume, should I delete the former 10 imgs? If I delete them, would the training effect now I've got be affected?(the former 10 imgs is the selected best 10) If I keep them, would the former imgs be over-trained?

TheLastBen commented 1 year ago

Keep all the images if the subjects are from the same class (people)