2023-08-04 13:28:41 +00:00
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[wandb]
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2023-12-07 17:12:09 +00:00
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mode = "offline"
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2023-08-04 13:28:41 +00:00
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entity = "acme"
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project = "test-ldm-training"
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[models]
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lda = {checkpoint="/path/to/stable-diffusion-1-5/lda.safetensors", train=false}
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text_encoder = {checkpoint="/path/to/stable-diffusion-1-5/text_encoder.safetensors", train=true}
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unet = {checkpoint="/path/to/stable-diffusion-1-5/unet.safetensors", train=true}
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[latent_diffusion]
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unconditional_sampling_probability = 0.2
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offset_noise = 0.1
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[training]
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duration = "1:epoch"
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seed = 0
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gpu_index = 0
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num_epochs = 1
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batch_size = 1
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gradient_accumulation = "1:step"
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clip_grad_norm = 2.0
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clip_grad_value = 1.0
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evaluation_interval = "1:epoch"
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evaluation_seed = 0
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[optimizer]
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optimizer = "AdamW" # "AdamW", "AdamW8bit", "Lion8bit", "Prodigy", "SGD", "Adam"
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learning_rate = 1e-5
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betas = [0.9, 0.999]
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eps = 1e-8
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weight_decay = 1e-2
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[scheduler]
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[dropout]
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dropout_probability = 0.2
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[dataset]
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hf_repo = "acme/images"
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revision = "main"
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[checkpointing]
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# save_folder = "/path/to/ckpts"
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save_interval = "1:epoch"
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[test_diffusion]
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prompts = [
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"A cute cat",
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]
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