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qwen35

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  1. samples/unet_1024x1280_0.jpg +3 -0
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  21. samples/unet_960x1280_0.jpg +3 -0
  22. train.py +4 -4
  23. unet/diffusion_pytorch_model.safetensors +1 -1
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train.py CHANGED
@@ -30,14 +30,14 @@ from collections import deque
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  from transformers import CLIPTokenizer, CLIPTextModel, Qwen3_5Tokenizer, Qwen3_5ForConditionalGeneration
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  # --------------------------- Параметры ---------------------------
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- ds_path = "/workspace/sdxs-1b/datasets/ds1_1280"
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  project = "unet"
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  ## total batch (split // num `GPU)
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  batch_size = 12
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  base_learning_rate = 3e-5
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  min_learning_rate = 3e-6
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  num_epochs = 4
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- sample_interval_share = 25
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  cfg_dropout = 0.10
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  max_length = 248
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  use_wandb = False
@@ -49,8 +49,8 @@ optimizer_type = "adam8bit"
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  torch_compile = False
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  unet_gradient = True
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  loss_normalize = False
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- fixed_seed = False
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- shuffle = False
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  comet_ml_api_key = "Agctp26mbqnoYrrlvQuKSTk6r"
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  comet_ml_workspace = "recoilme"
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  torch.backends.cuda.matmul.allow_tf32 = True
 
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  from transformers import CLIPTokenizer, CLIPTextModel, Qwen3_5Tokenizer, Qwen3_5ForConditionalGeneration
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  # --------------------------- Параметры ---------------------------
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+ ds_path = "/workspace/sdxs-1b/datasets/ds1234_1280"
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  project = "unet"
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  ## total batch (split // num `GPU)
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  batch_size = 12
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  base_learning_rate = 3e-5
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  min_learning_rate = 3e-6
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  num_epochs = 4
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+ sample_interval_share = 20
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  cfg_dropout = 0.10
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  max_length = 248
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  use_wandb = False
 
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  torch_compile = False
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  unet_gradient = True
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  loss_normalize = False
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+ fixed_seed = True
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+ shuffle = True
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  comet_ml_api_key = "Agctp26mbqnoYrrlvQuKSTk6r"
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  comet_ml_workspace = "recoilme"
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  torch.backends.cuda.matmul.allow_tf32 = True
unet/diffusion_pytorch_model.safetensors CHANGED
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  size 5960474736
 
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  size 5960474736