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  1. 2b/diffusion_pytorch_model.safetensors +1 -1
  2. samples/2b_192x384_0.jpg +2 -2
  3. samples/2b_256x384_0.jpg +2 -2
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  11. samples/unet_320x384_0.jpg +0 -3
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  15. samples/unet_384x320_0.jpg +0 -3
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  20. samples/unet_576x320_0.jpg +0 -3
  21. samples/unet_576x384_0.jpg +0 -3
  22. samples/unet_576x448_0.jpg +0 -3
  23. samples/unet_576x512_0.jpg +0 -3
  24. samples/unet_576x576_0.jpg +0 -3
  25. train.py +5 -5
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train.py CHANGED
@@ -30,9 +30,9 @@ project = "2b"
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  batch_size = 32
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  base_learning_rate = 8e-5
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  min_learning_rate = 4e-5
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- num_epochs = 3
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  # samples/save per epoch
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- sample_interval_share = 10
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  use_wandb = True
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  save_model = True
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  use_decay = True
@@ -52,9 +52,9 @@ save_barrier = 1.03
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  dispersive_temperature=0.5
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  dispersive_weight= 0.05
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  percentile_clipping = 95 # 8bit optim
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- betta2 = 0.99 #0.97
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- eps = 1e-6 #1e-5
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- clip_grad_norm = 1. #.5
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  steps_offset = 1 # Scheduler
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  limit = 0
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  checkpoints_folder = ""
 
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  batch_size = 32
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  base_learning_rate = 8e-5
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  min_learning_rate = 4e-5
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+ num_epochs = 27
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  # samples/save per epoch
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+ sample_interval_share = 5
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  use_wandb = True
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  save_model = True
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  use_decay = True
 
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  dispersive_temperature=0.5
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  dispersive_weight= 0.05
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  percentile_clipping = 95 # 8bit optim
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+ betta2 = 0.97
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+ eps = 1e-5
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+ clip_grad_norm = .75
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  steps_offset = 1 # Scheduler
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  limit = 0
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  checkpoints_folder = ""