diff --git "a/flowsdvae_50kx512_lgn1p0/log.txt" "b/flowsdvae_50kx512_lgn1p0/log.txt" new file mode 100644--- /dev/null +++ "b/flowsdvae_50kx512_lgn1p0/log.txt" @@ -0,0 +1,1273 @@ +[2025-02-26 18:56:03] Model: DistributedDataParallel( + (module): FlowAE( + (flow): FlowDecoder( + (conv_in): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (mid): Module( + (block_1): ResnetBlock( + (norm1): RMSNorm() + (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (temb_proj): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1)) + (norm2): RMSNorm() + (dropout): Dropout(p=0.0, inplace=False) + (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + (attn_1): AttnBlock( + (norm): RMSNorm() + (q): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1)) + (k): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1)) + (v): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1)) + (proj_out): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1)) + ) + (block_2): ResnetBlock( + (norm1): RMSNorm() + (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (temb_proj): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1)) + (norm2): RMSNorm() + (dropout): Dropout(p=0.0, inplace=False) + (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + ) + (up): ModuleList( + (0): Module( + (block): ModuleList( + (0): ResnetBlock( + (norm1): RMSNorm() + (conv1): Conv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (temb_proj): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1)) + (norm2): RMSNorm() + (dropout): Dropout(p=0.0, inplace=False) + (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (nin_shortcut): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) + ) + (1-2): 2 x ResnetBlock( + (norm1): RMSNorm() + (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (temb_proj): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1)) + (norm2): RMSNorm() + (dropout): Dropout(p=0.0, inplace=False) + (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + ) + (attn): ModuleList() + ) + (1): Module( + (block): ModuleList( + (0): ResnetBlock( + (norm1): RMSNorm() + (conv1): Conv2d(512, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (temb_proj): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1)) + (norm2): RMSNorm() + (dropout): Dropout(p=0.0, inplace=False) + (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (nin_shortcut): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1)) + ) + (1-2): 2 x ResnetBlock( + (norm1): RMSNorm() + (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (temb_proj): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1)) + (norm2): RMSNorm() + (dropout): Dropout(p=0.0, inplace=False) + (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + ) + (attn): ModuleList() + (upsample): Upsample( + (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + ) + (2-3): 2 x Module( + (block): ModuleList( + (0-2): 3 x ResnetBlock( + (norm1): RMSNorm() + (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + (temb_proj): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1)) + (norm2): RMSNorm() + (dropout): Dropout(p=0.0, inplace=False) + (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + ) + (attn): ModuleList() + (upsample): Upsample( + (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + ) + ) + (norm_out): RMSNorm() + (conv_out): Conv2d(128, 3, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) + ) + (t_embedder): TimestepEmbedder( + (mlp): Sequential( + (0): Linear(in_features=256, out_features=512, bias=True) + (1): SiLU() + (2): Linear(in_features=512, out_features=512, bias=True) + ) + ) + (y_embedder): Conv2d(4, 512, kernel_size=(1, 1), stride=(1, 1)) + (x_embedder): PatchEmbed( + (proj): Conv2d(3, 512, kernel_size=(8, 8), stride=(8, 8)) + (norm): Identity() + ) + ) +) +[2025-02-26 18:56:03] FlowVAE Parameters: 55.53M +[2025-02-26 18:56:03] FlowVAE Trainable Parameters: 55.01M +[2025-02-26 18:56:03] Optimizer: AdamW, lr=0.0002, beta2=0.95 +[2025-02-26 18:56:03] module.pos_embed.requires_grad : False +[2025-02-26 18:56:03] module.flow.conv_in.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.conv_in.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_1.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.norm.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.q.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.q.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.k.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.k.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.v.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.v.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.proj_out.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.attn_1.proj_out.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.mid.block_2.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.nin_shortcut.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.0.nin_shortcut.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.1.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.0.block.2.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.nin_shortcut.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.0.nin_shortcut.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.1.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.block.2.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.upsample.conv.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.1.upsample.conv.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.0.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.1.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.block.2.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.upsample.conv.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.2.upsample.conv.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.0.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.1.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.norm1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.conv1.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.conv1.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.temb_proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.temb_proj.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.norm2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.conv2.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.block.2.conv2.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.upsample.conv.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.up.3.upsample.conv.bias.requires_grad : True +[2025-02-26 18:56:03] module.flow.norm_out.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.conv_out.weight.requires_grad : True +[2025-02-26 18:56:03] module.flow.conv_out.bias.requires_grad : True +[2025-02-26 18:56:03] module.t_embedder.mlp.0.weight.requires_grad : True +[2025-02-26 18:56:03] module.t_embedder.mlp.0.bias.requires_grad : True +[2025-02-26 18:56:03] module.t_embedder.mlp.2.weight.requires_grad : True +[2025-02-26 18:56:03] module.t_embedder.mlp.2.bias.requires_grad : True +[2025-02-26 18:56:03] module.y_embedder.weight.requires_grad : True +[2025-02-26 18:56:03] module.y_embedder.bias.requires_grad : True +[2025-02-26 18:56:03] module.x_embedder.proj.weight.requires_grad : True +[2025-02-26 18:56:03] module.x_embedder.proj.bias.requires_grad : True +[2025-02-26 18:56:03] Dataset contains 1,281,168 images /data/checkpoints/LanguageBind/offline_feature/offline_sdvae_256_path/imagenet_train_256 +[2025-02-26 18:56:03] Batch size 64 per gpu, with 512 global batch size +[2025-02-26 18:56:03] Train config: {'ckpt_path': '/data/logs/flow/flowsdvae_50kx512_lgn1p0/checkpoints/0050000.pt', 'data': {'raw_data_dir': '/data/OpenDataLab___ImageNet-1K/raw/ImageNet-1K/train', 'raw_val_data_dir': '/data/OpenDataLab___ImageNet-1K/raw/ImageNet-1K/val', 'data_path': '/data/checkpoints/LanguageBind/offline_feature/offline_sdvae_256_path/imagenet_train_256', 'fid_reference_file': '/data/checkpoints/VIRTUAL_imagenet256_labeled.npz', 'image_size': 256, 'num_classes': 1000, 'num_workers': 16, 'latent_norm': False, 'latent_multiplier': 0.18215}, 'vae': {'vae_type': 'FlowSDVAE', 'model_path': '/data/checkpoints/stabilityai/sd-vae-ft-ema/vae-ft-ema-560000-ema-pruned.safetensors', 'downsample_ratio': 8, 'multi_latent': False, 'add_y_to_x': False, 'norm_type': 'rmsnorm'}, 'model': {'model_type': 'DiT-S/2', 'use_qknorm': True, 'use_swiglu': True, 'use_rope': True, 'use_rmsnorm': True, 'in_chans': 4, 'use_checkpoint': False}, 'train': {'max_steps': 50000, 'global_batch_size': 512, 'global_seed': 0, 'output_dir': '../logs/flow/flowsdvae_50kx512_lgn1p0', 'ckpt': None, 'log_every': 50, 'ckpt_every': 10000, 'eval_every': 10000, 'wandb': True, 'seed': 1234, 'precision': 'bf16', 'resume': False}, 'optimizer': {'lr': 0.0002, 'beta2': 0.95}, 'wandb': {'proj_name': 'flow', 'log_name': 'flowsdvae_50kx512_lgn1p0', 'key': '953e958793b218efb850fa194e85843e2c3bd88b'}, 'scheduler': {'diffusion': False, 'transport': True}, 'diffusion': {'learn_sigma': True, 'diffusion_steps': 1000}, 'transport': {'path_type': 'Linear', 'prediction': 'velocity', 'loss_weight': None, 'sample_eps': None, 'train_eps': None, 'use_cosine_loss': True, 'use_lognorm': True}, 'sample': {'mode': 'ODE', 'sampling_method': 'euler', 'atol': 1e-06, 'rtol': 0.001, 'reverse': False, 'likelihood': False, 'num_sampling_steps': 250, 'cfg_scale': 1.0, 'per_proc_batch_size': 64, 'fid_num': 50000, 'cfg_interval_start': 0.0, 'timestep_shift': 0.0}, 'flowvae_transport': {'path_type': 'Linear', 'prediction': 'velocity', 'loss_weight': None, 'sample_eps': None, 'train_eps': None, 'use_cosine_loss': False, 'use_lognorm': True, 'l2_loss': True, 'shift_lg': True, 'shifted_mu': 1.0, 'timestep_sampling': 'lognorm', 'beta_alpha': None, 'beta_beta': None, 'pareto_alpha': None}, 'flowvae_sample': {'mode': 'ODE', 'sampling_method': 'euler', 'atol': 1e-06, 'rtol': 0.001, 'reverse': False, 'likelihood': False, 'num_sampling_steps': 25, 'cfg_scale': 1.0, 'per_proc_batch_size': 64, 'fid_num': 50000, 'cfg_interval_start': 0.0, 'timestep_shift': 0.0}} +[2025-02-26 18:57:32] (step=0000050) Train Loss: 1.1528, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.57, Grad Norm: 3.1602 +[2025-02-26 18:58:30] (step=0000100) Train Loss: 1.0665, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9747 +[2025-02-26 18:59:28] (step=0000150) Train Loss: 1.0443, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6227 +[2025-02-26 19:00:27] (step=0000200) Train Loss: 1.0340, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4362 +[2025-02-26 19:01:25] (step=0000250) Train Loss: 1.0298, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3764 +[2025-02-26 19:02:23] (step=0000300) Train Loss: 1.0266, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3108 +[2025-02-26 19:03:22] (step=0000350) Train Loss: 1.0242, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3233 +[2025-02-26 19:04:20] (step=0000400) Train Loss: 1.0204, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3552 +[2025-02-26 19:05:19] (step=0000450) Train Loss: 1.0128, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3819 +[2025-02-26 19:06:17] (step=0000500) Train Loss: 1.0028, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3737 +[2025-02-26 19:07:16] (step=0000550) Train Loss: 0.9848, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4632 +[2025-02-26 19:08:14] (step=0000600) Train Loss: 0.9571, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5208 +[2025-02-26 19:09:12] (step=0000650) Train Loss: 0.9229, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8045 +[2025-02-26 19:10:11] (step=0000700) Train Loss: 0.8717, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8509 +[2025-02-26 19:11:09] (step=0000750) Train Loss: 0.8098, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8964 +[2025-02-26 19:12:07] (step=0000800) Train Loss: 0.7588, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0461 +[2025-02-26 19:13:06] (step=0000850) Train Loss: 0.7089, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2273 +[2025-02-26 19:14:04] (step=0000900) Train Loss: 0.6498, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2019 +[2025-02-26 19:15:03] (step=0000950) Train Loss: 0.6022, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2769 +[2025-02-26 19:16:01] (step=0001000) Train Loss: 0.5640, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.4122 +[2025-02-26 19:16:59] (step=0001050) Train Loss: 0.5294, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2919 +[2025-02-26 19:17:58] (step=0001100) Train Loss: 0.5074, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.4113 +[2025-02-26 19:18:56] (step=0001150) Train Loss: 0.4694, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.3211 +[2025-02-26 19:19:55] (step=0001200) Train Loss: 0.4377, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.4645 +[2025-02-26 19:20:53] (step=0001250) Train Loss: 0.4089, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.5410 +[2025-02-26 19:21:51] (step=0001300) Train Loss: 0.3784, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.5120 +[2025-02-26 19:22:50] (step=0001350) Train Loss: 0.3633, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.5713 +[2025-02-26 19:23:48] (step=0001400) Train Loss: 0.3427, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.4785 +[2025-02-26 19:24:47] (step=0001450) Train Loss: 0.3314, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.5288 +[2025-02-26 19:25:45] (step=0001500) Train Loss: 0.3211, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.6132 +[2025-02-26 19:26:43] (step=0001550) Train Loss: 0.3242, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.3708 +[2025-02-26 19:27:42] (step=0001600) Train Loss: 0.3090, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.4670 +[2025-02-26 19:28:40] (step=0001650) Train Loss: 0.3046, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.3512 +[2025-02-26 19:29:39] (step=0001700) Train Loss: 0.2973, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2884 +[2025-02-26 19:30:37] (step=0001750) Train Loss: 0.2942, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.4125 +[2025-02-26 19:31:35] (step=0001800) Train Loss: 0.2918, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.4099 +[2025-02-26 19:32:34] (step=0001850) Train Loss: 0.2849, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2827 +[2025-02-26 19:33:32] (step=0001900) Train Loss: 0.2804, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.3341 +[2025-02-26 19:34:30] (step=0001950) Train Loss: 0.2773, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.3312 +[2025-02-26 19:35:29] (step=0002000) Train Loss: 0.2785, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2944 +[2025-02-26 19:36:27] (step=0002050) Train Loss: 0.2713, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2096 +[2025-02-26 19:37:26] (step=0002100) Train Loss: 0.2695, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1666 +[2025-02-26 19:38:24] (step=0002150) Train Loss: 0.2678, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2524 +[2025-02-26 19:39:23] (step=0002200) Train Loss: 0.2629, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2436 +[2025-02-26 19:40:21] (step=0002250) Train Loss: 0.2618, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2011 +[2025-02-26 19:41:19] (step=0002300) Train Loss: 0.2575, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1803 +[2025-02-26 19:42:18] (step=0002350) Train Loss: 0.2575, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.3269 +[2025-02-26 19:43:16] (step=0002400) Train Loss: 0.2542, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0669 +[2025-02-26 19:44:15] (step=0002450) Train Loss: 0.2491, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0826 +[2025-02-26 19:45:13] (step=0002500) Train Loss: 0.2489, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2383 +[2025-02-26 19:46:14] (step=0002550) Train Loss: 0.2504, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 1.1273 +[2025-02-26 19:47:12] (step=0002600) Train Loss: 0.2475, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0556 +[2025-02-26 19:48:10] (step=0002650) Train Loss: 0.2448, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2097 +[2025-02-26 19:49:09] (step=0002700) Train Loss: 0.2466, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2152 +[2025-02-26 19:50:07] (step=0002750) Train Loss: 0.2387, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0832 +[2025-02-26 19:51:05] (step=0002800) Train Loss: 0.2387, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1446 +[2025-02-26 19:52:04] (step=0002850) Train Loss: 0.2369, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1696 +[2025-02-26 19:53:02] (step=0002900) Train Loss: 0.2361, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0723 +[2025-02-26 19:54:01] (step=0002950) Train Loss: 0.2338, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1150 +[2025-02-26 19:54:59] (step=0003000) Train Loss: 0.2345, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1212 +[2025-02-26 19:55:57] (step=0003050) Train Loss: 0.2328, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0067 +[2025-02-26 19:56:56] (step=0003100) Train Loss: 0.2302, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1036 +[2025-02-26 19:57:54] (step=0003150) Train Loss: 0.2265, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1012 +[2025-02-26 19:58:53] (step=0003200) Train Loss: 0.2274, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1112 +[2025-02-26 19:59:51] (step=0003250) Train Loss: 0.2286, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0776 +[2025-02-26 20:00:49] (step=0003300) Train Loss: 0.2245, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0657 +[2025-02-26 20:01:48] (step=0003350) Train Loss: 0.2257, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0281 +[2025-02-26 20:02:46] (step=0003400) Train Loss: 0.2277, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2017 +[2025-02-26 20:03:45] (step=0003450) Train Loss: 0.2181, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0703 +[2025-02-26 20:04:43] (step=0003500) Train Loss: 0.2190, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1055 +[2025-02-26 20:05:41] (step=0003550) Train Loss: 0.2174, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1354 +[2025-02-26 20:06:40] (step=0003600) Train Loss: 0.2137, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0348 +[2025-02-26 20:07:38] (step=0003650) Train Loss: 0.2140, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0687 +[2025-02-26 20:08:37] (step=0003700) Train Loss: 0.2109, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0213 +[2025-02-26 20:09:35] (step=0003750) Train Loss: 0.2143, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.2470 +[2025-02-26 20:10:33] (step=0003800) Train Loss: 0.2104, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0172 +[2025-02-26 20:11:32] (step=0003850) Train Loss: 0.2096, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0458 +[2025-02-26 20:12:30] (step=0003900) Train Loss: 0.2056, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0735 +[2025-02-26 20:13:29] (step=0003950) Train Loss: 0.2023, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0342 +[2025-02-26 20:14:27] (step=0004000) Train Loss: 0.2010, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0990 +[2025-02-26 20:15:25] (step=0004050) Train Loss: 0.1984, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0501 +[2025-02-26 20:16:24] (step=0004100) Train Loss: 0.1948, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9990 +[2025-02-26 20:17:22] (step=0004150) Train Loss: 0.1927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9854 +[2025-02-26 20:18:20] (step=0004200) Train Loss: 0.1919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0239 +[2025-02-26 20:19:19] (step=0004250) Train Loss: 0.1887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0078 +[2025-02-26 20:20:17] (step=0004300) Train Loss: 0.1882, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0447 +[2025-02-26 20:21:16] (step=0004350) Train Loss: 0.1884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.1117 +[2025-02-26 20:22:14] (step=0004400) Train Loss: 0.1835, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9304 +[2025-02-26 20:23:12] (step=0004450) Train Loss: 0.1821, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0635 +[2025-02-26 20:24:11] (step=0004500) Train Loss: 0.1786, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9264 +[2025-02-26 20:25:09] (step=0004550) Train Loss: 0.1777, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 1.0120 +[2025-02-26 20:26:08] (step=0004600) Train Loss: 0.1763, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9955 +[2025-02-26 20:27:06] (step=0004650) Train Loss: 0.1753, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9444 +[2025-02-26 20:28:04] (step=0004700) Train Loss: 0.1739, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9744 +[2025-02-26 20:29:03] (step=0004750) Train Loss: 0.1724, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9219 +[2025-02-26 20:30:01] (step=0004800) Train Loss: 0.1708, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9860 +[2025-02-26 20:31:00] (step=0004850) Train Loss: 0.1707, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9275 +[2025-02-26 20:31:58] (step=0004900) Train Loss: 0.1715, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9558 +[2025-02-26 20:32:56] (step=0004950) Train Loss: 0.1695, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9724 +[2025-02-26 20:33:55] (step=0005000) Train Loss: 0.1688, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9331 +[2025-02-26 20:34:55] (step=0005050) Train Loss: 0.1682, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 1.0095 +[2025-02-26 20:35:54] (step=0005100) Train Loss: 0.1671, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8872 +[2025-02-26 20:36:52] (step=0005150) Train Loss: 0.1658, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9590 +[2025-02-26 20:37:50] (step=0005200) Train Loss: 0.1654, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8866 +[2025-02-26 20:38:49] (step=0005250) Train Loss: 0.1639, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8946 +[2025-02-26 20:39:47] (step=0005300) Train Loss: 0.1635, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9765 +[2025-02-26 20:40:46] (step=0005350) Train Loss: 0.1629, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8621 +[2025-02-26 20:41:44] (step=0005400) Train Loss: 0.1621, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8625 +[2025-02-26 20:42:42] (step=0005450) Train Loss: 0.1612, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9317 +[2025-02-26 20:43:41] (step=0005500) Train Loss: 0.1630, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9704 +[2025-02-26 20:44:39] (step=0005550) Train Loss: 0.1565, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8700 +[2025-02-26 20:45:38] (step=0005600) Train Loss: 0.1552, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8940 +[2025-02-26 20:46:36] (step=0005650) Train Loss: 0.1540, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8441 +[2025-02-26 20:47:34] (step=0005700) Train Loss: 0.1506, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8656 +[2025-02-26 20:48:33] (step=0005750) Train Loss: 0.1471, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8728 +[2025-02-26 20:49:31] (step=0005800) Train Loss: 0.1465, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8468 +[2025-02-26 20:50:30] (step=0005850) Train Loss: 0.1445, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8602 +[2025-02-26 20:51:28] (step=0005900) Train Loss: 0.1413, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8311 +[2025-02-26 20:52:26] (step=0005950) Train Loss: 0.1378, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9253 +[2025-02-26 20:53:25] (step=0006000) Train Loss: 0.1368, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8857 +[2025-02-26 20:54:23] (step=0006050) Train Loss: 0.1352, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8890 +[2025-02-26 20:55:21] (step=0006100) Train Loss: 0.1326, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9130 +[2025-02-26 20:56:20] (step=0006150) Train Loss: 0.1308, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.9022 +[2025-02-26 20:57:18] (step=0006200) Train Loss: 0.1293, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8861 +[2025-02-26 20:58:17] (step=0006250) Train Loss: 0.1281, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8690 +[2025-02-26 20:59:15] (step=0006300) Train Loss: 0.1282, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8622 +[2025-02-26 21:00:13] (step=0006350) Train Loss: 0.1277, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8956 +[2025-02-26 21:01:12] (step=0006400) Train Loss: 0.1268, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8576 +[2025-02-26 21:02:10] (step=0006450) Train Loss: 0.1247, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8603 +[2025-02-26 21:03:09] (step=0006500) Train Loss: 0.1237, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8380 +[2025-02-26 21:04:07] (step=0006550) Train Loss: 0.1255, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8377 +[2025-02-26 21:05:05] (step=0006600) Train Loss: 0.1239, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8511 +[2025-02-26 21:06:04] (step=0006650) Train Loss: 0.1219, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8514 +[2025-02-26 21:07:02] (step=0006700) Train Loss: 0.1208, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8305 +[2025-02-26 21:08:01] (step=0006750) Train Loss: 0.1217, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8475 +[2025-02-26 21:08:59] (step=0006800) Train Loss: 0.1197, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8556 +[2025-02-26 21:09:57] (step=0006850) Train Loss: 0.1197, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8309 +[2025-02-26 21:10:56] (step=0006900) Train Loss: 0.1189, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8061 +[2025-02-26 21:11:54] (step=0006950) Train Loss: 0.1194, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8260 +[2025-02-26 21:12:53] (step=0007000) Train Loss: 0.1181, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8284 +[2025-02-26 21:13:51] (step=0007050) Train Loss: 0.1183, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7745 +[2025-02-26 21:14:49] (step=0007100) Train Loss: 0.1175, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8052 +[2025-02-26 21:15:48] (step=0007150) Train Loss: 0.1184, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8314 +[2025-02-26 21:16:46] (step=0007200) Train Loss: 0.1163, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8171 +[2025-02-26 21:17:45] (step=0007250) Train Loss: 0.1172, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8119 +[2025-02-26 21:18:43] (step=0007300) Train Loss: 0.1162, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7668 +[2025-02-26 21:19:41] (step=0007350) Train Loss: 0.1164, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7688 +[2025-02-26 21:20:40] (step=0007400) Train Loss: 0.1156, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8028 +[2025-02-26 21:21:38] (step=0007450) Train Loss: 0.1147, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7868 +[2025-02-26 21:22:37] (step=0007500) Train Loss: 0.1144, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7962 +[2025-02-26 21:23:37] (step=0007550) Train Loss: 0.1137, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 0.8004 +[2025-02-26 21:24:35] (step=0007600) Train Loss: 0.1152, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7729 +[2025-02-26 21:25:34] (step=0007650) Train Loss: 0.1128, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7854 +[2025-02-26 21:26:32] (step=0007700) Train Loss: 0.1128, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7765 +[2025-02-26 21:27:31] (step=0007750) Train Loss: 0.1125, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8064 +[2025-02-26 21:28:29] (step=0007800) Train Loss: 0.1114, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7762 +[2025-02-26 21:29:27] (step=0007850) Train Loss: 0.1125, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7631 +[2025-02-26 21:30:26] (step=0007900) Train Loss: 0.1121, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7672 +[2025-02-26 21:31:24] (step=0007950) Train Loss: 0.1114, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7769 +[2025-02-26 21:32:23] (step=0008000) Train Loss: 0.1111, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8070 +[2025-02-26 21:33:21] (step=0008050) Train Loss: 0.1103, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7344 +[2025-02-26 21:34:19] (step=0008100) Train Loss: 0.1109, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7605 +[2025-02-26 21:35:18] (step=0008150) Train Loss: 0.1111, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7753 +[2025-02-26 21:36:16] (step=0008200) Train Loss: 0.1106, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7914 +[2025-02-26 21:37:14] (step=0008250) Train Loss: 0.1111, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7604 +[2025-02-26 21:38:13] (step=0008300) Train Loss: 0.1092, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7809 +[2025-02-26 21:39:11] (step=0008350) Train Loss: 0.1098, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7304 +[2025-02-26 21:40:10] (step=0008400) Train Loss: 0.1094, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7915 +[2025-02-26 21:41:08] (step=0008450) Train Loss: 0.1095, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7362 +[2025-02-26 21:42:06] (step=0008500) Train Loss: 0.1086, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7562 +[2025-02-26 21:43:05] (step=0008550) Train Loss: 0.1089, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7319 +[2025-02-26 21:44:03] (step=0008600) Train Loss: 0.1093, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.8119 +[2025-02-26 21:45:02] (step=0008650) Train Loss: 0.1083, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7298 +[2025-02-26 21:46:00] (step=0008700) Train Loss: 0.1079, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7192 +[2025-02-26 21:46:58] (step=0008750) Train Loss: 0.1091, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7548 +[2025-02-26 21:47:57] (step=0008800) Train Loss: 0.1076, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7412 +[2025-02-26 21:48:55] (step=0008850) Train Loss: 0.1061, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7632 +[2025-02-26 21:49:54] (step=0008900) Train Loss: 0.1071, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7477 +[2025-02-26 21:50:52] (step=0008950) Train Loss: 0.1076, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7112 +[2025-02-26 21:51:50] (step=0009000) Train Loss: 0.1068, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7400 +[2025-02-26 21:52:49] (step=0009050) Train Loss: 0.1076, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7630 +[2025-02-26 21:53:47] (step=0009100) Train Loss: 0.1076, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7210 +[2025-02-26 21:54:45] (step=0009150) Train Loss: 0.1060, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7163 +[2025-02-26 21:55:44] (step=0009200) Train Loss: 0.1056, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7541 +[2025-02-26 21:56:42] (step=0009250) Train Loss: 0.1053, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7229 +[2025-02-26 21:57:41] (step=0009300) Train Loss: 0.1049, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7334 +[2025-02-26 21:58:39] (step=0009350) Train Loss: 0.1075, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7209 +[2025-02-26 21:59:37] (step=0009400) Train Loss: 0.1064, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7370 +[2025-02-26 22:00:36] (step=0009450) Train Loss: 0.1050, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7199 +[2025-02-26 22:01:34] (step=0009500) Train Loss: 0.1036, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7319 +[2025-02-26 22:02:33] (step=0009550) Train Loss: 0.1063, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7181 +[2025-02-26 22:03:31] (step=0009600) Train Loss: 0.1048, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7505 +[2025-02-26 22:04:29] (step=0009650) Train Loss: 0.1051, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6916 +[2025-02-26 22:05:28] (step=0009700) Train Loss: 0.1042, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7066 +[2025-02-26 22:06:26] (step=0009750) Train Loss: 0.1055, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6852 +[2025-02-26 22:07:25] (step=0009800) Train Loss: 0.1051, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7097 +[2025-02-26 22:08:23] (step=0009850) Train Loss: 0.1051, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6700 +[2025-02-26 22:09:21] (step=0009900) Train Loss: 0.1045, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7216 +[2025-02-26 22:10:20] (step=0009950) Train Loss: 0.1048, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6826 +[2025-02-26 22:11:18] (step=0010000) Train Loss: 0.1058, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7268 +[2025-02-26 22:11:20] Saved checkpoint to ../logs/flow/flowsdvae_50kx512_lgn1p0/checkpoints/0010000.pt +[2025-02-26 22:32:44] (step=0010000), Fid=117.78706739754062, PSNR=10.772548054766656, LPIPS=0.74609375, SSIM=0.04179586097598076 +[2025-02-26 22:33:44] (step=0010050) Train Loss: 0.1045, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.04, Grad Norm: 0.6732 +[2025-02-26 22:34:43] (step=0010100) Train Loss: 0.1047, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6736 +[2025-02-26 22:35:41] (step=0010150) Train Loss: 0.1032, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7355 +[2025-02-26 22:36:39] (step=0010200) Train Loss: 0.1038, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6870 +[2025-02-26 22:37:37] (step=0010250) Train Loss: 0.1032, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6739 +[2025-02-26 22:38:35] (step=0010300) Train Loss: 0.1037, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7143 +[2025-02-26 22:39:33] (step=0010350) Train Loss: 0.1020, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6442 +[2025-02-26 22:40:31] (step=0010400) Train Loss: 0.1042, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7072 +[2025-02-26 22:41:29] (step=0010450) Train Loss: 0.1017, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7102 +[2025-02-26 22:42:27] (step=0010500) Train Loss: 0.1024, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6915 +[2025-02-26 22:43:26] (step=0010550) Train Loss: 0.1030, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7092 +[2025-02-26 22:44:24] (step=0010600) Train Loss: 0.1025, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6668 +[2025-02-26 22:45:22] (step=0010650) Train Loss: 0.1016, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6611 +[2025-02-26 22:46:21] (step=0010700) Train Loss: 0.1029, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6789 +[2025-02-26 22:47:19] (step=0010750) Train Loss: 0.1027, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7060 +[2025-02-26 22:48:18] (step=0010800) Train Loss: 0.1029, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6137 +[2025-02-26 22:49:16] (step=0010850) Train Loss: 0.1022, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.7168 +[2025-02-26 22:50:15] (step=0010900) Train Loss: 0.1032, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6501 +[2025-02-26 22:51:13] (step=0010950) Train Loss: 0.1024, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6455 +[2025-02-26 22:52:12] (step=0011000) Train Loss: 0.1017, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6659 +[2025-02-26 22:53:10] (step=0011050) Train Loss: 0.1021, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6404 +[2025-02-26 22:54:09] (step=0011100) Train Loss: 0.1014, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6760 +[2025-02-26 22:55:07] (step=0011150) Train Loss: 0.1012, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6856 +[2025-02-26 22:56:06] (step=0011200) Train Loss: 0.1022, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6427 +[2025-02-26 22:57:04] (step=0011250) Train Loss: 0.1016, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6717 +[2025-02-26 22:58:03] (step=0011300) Train Loss: 0.1010, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6712 +[2025-02-26 22:59:01] (step=0011350) Train Loss: 0.1011, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6624 +[2025-02-26 23:00:00] (step=0011400) Train Loss: 0.1017, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6861 +[2025-02-26 23:00:58] (step=0011450) Train Loss: 0.0999, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6542 +[2025-02-26 23:01:57] (step=0011500) Train Loss: 0.1012, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6860 +[2025-02-26 23:02:55] (step=0011550) Train Loss: 0.1006, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6345 +[2025-02-26 23:03:54] (step=0011600) Train Loss: 0.1009, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6538 +[2025-02-26 23:04:52] (step=0011650) Train Loss: 0.1010, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6843 +[2025-02-26 23:05:51] (step=0011700) Train Loss: 0.1010, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6551 +[2025-02-26 23:06:49] (step=0011750) Train Loss: 0.1008, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6218 +[2025-02-26 23:07:47] (step=0011800) Train Loss: 0.1002, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6712 +[2025-02-26 23:08:46] (step=0011850) Train Loss: 0.1007, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6436 +[2025-02-26 23:09:44] (step=0011900) Train Loss: 0.1003, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6777 +[2025-02-26 23:10:43] (step=0011950) Train Loss: 0.1001, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6286 +[2025-02-26 23:11:41] (step=0012000) Train Loss: 0.1002, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6551 +[2025-02-26 23:12:40] (step=0012050) Train Loss: 0.0996, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6281 +[2025-02-26 23:13:38] (step=0012100) Train Loss: 0.1001, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6375 +[2025-02-26 23:14:37] (step=0012150) Train Loss: 0.1014, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6335 +[2025-02-26 23:15:35] (step=0012200) Train Loss: 0.0989, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6351 +[2025-02-26 23:16:34] (step=0012250) Train Loss: 0.0994, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6387 +[2025-02-26 23:17:32] (step=0012300) Train Loss: 0.0989, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6425 +[2025-02-26 23:18:31] (step=0012350) Train Loss: 0.0997, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6297 +[2025-02-26 23:19:29] (step=0012400) Train Loss: 0.0998, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6112 +[2025-02-26 23:20:28] (step=0012450) Train Loss: 0.0999, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6556 +[2025-02-26 23:21:26] (step=0012500) Train Loss: 0.0993, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6205 +[2025-02-26 23:22:27] (step=0012550) Train Loss: 0.0991, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 0.6215 +[2025-02-26 23:23:25] (step=0012600) Train Loss: 0.0996, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6556 +[2025-02-26 23:24:24] (step=0012650) Train Loss: 0.0984, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5981 +[2025-02-26 23:25:22] (step=0012700) Train Loss: 0.0999, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6263 +[2025-02-26 23:26:21] (step=0012750) Train Loss: 0.0997, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6248 +[2025-02-26 23:27:19] (step=0012800) Train Loss: 0.1005, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6131 +[2025-02-26 23:28:18] (step=0012850) Train Loss: 0.1000, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5948 +[2025-02-26 23:29:16] (step=0012900) Train Loss: 0.0983, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6128 +[2025-02-26 23:30:15] (step=0012950) Train Loss: 0.0996, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6709 +[2025-02-26 23:31:13] (step=0013000) Train Loss: 0.0989, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6150 +[2025-02-26 23:32:12] (step=0013050) Train Loss: 0.0991, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5981 +[2025-02-26 23:33:10] (step=0013100) Train Loss: 0.0987, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5968 +[2025-02-26 23:34:09] (step=0013150) Train Loss: 0.1001, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6331 +[2025-02-26 23:35:07] (step=0013200) Train Loss: 0.0984, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6072 +[2025-02-26 23:36:05] (step=0013250) Train Loss: 0.0978, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6020 +[2025-02-26 23:37:04] (step=0013300) Train Loss: 0.0980, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6176 +[2025-02-26 23:38:02] (step=0013350) Train Loss: 0.0990, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5832 +[2025-02-26 23:39:01] (step=0013400) Train Loss: 0.0989, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6222 +[2025-02-26 23:39:59] (step=0013450) Train Loss: 0.0987, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5700 +[2025-02-26 23:40:58] (step=0013500) Train Loss: 0.0975, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6008 +[2025-02-26 23:41:56] (step=0013550) Train Loss: 0.0974, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6484 +[2025-02-26 23:42:55] (step=0013600) Train Loss: 0.0984, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5880 +[2025-02-26 23:43:53] (step=0013650) Train Loss: 0.0983, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5821 +[2025-02-26 23:44:52] (step=0013700) Train Loss: 0.0992, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5996 +[2025-02-26 23:45:50] (step=0013750) Train Loss: 0.0987, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6343 +[2025-02-26 23:46:49] (step=0013800) Train Loss: 0.0981, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5533 +[2025-02-26 23:47:47] (step=0013850) Train Loss: 0.0981, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6028 +[2025-02-26 23:48:46] (step=0013900) Train Loss: 0.0976, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6103 +[2025-02-26 23:49:44] (step=0013950) Train Loss: 0.0985, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5735 +[2025-02-26 23:50:42] (step=0014000) Train Loss: 0.0972, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5814 +[2025-02-26 23:51:41] (step=0014050) Train Loss: 0.0978, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6184 +[2025-02-26 23:52:39] (step=0014100) Train Loss: 0.0985, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5760 +[2025-02-26 23:53:38] (step=0014150) Train Loss: 0.0977, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5497 +[2025-02-26 23:54:36] (step=0014200) Train Loss: 0.0982, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6082 +[2025-02-26 23:55:35] (step=0014250) Train Loss: 0.0965, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5976 +[2025-02-26 23:56:33] (step=0014300) Train Loss: 0.0979, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5766 +[2025-02-26 23:57:32] (step=0014350) Train Loss: 0.0978, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6255 +[2025-02-26 23:58:30] (step=0014400) Train Loss: 0.0963, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5474 +[2025-02-26 23:59:29] (step=0014450) Train Loss: 0.0984, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.6112 +[2025-02-27 00:00:27] (step=0014500) Train Loss: 0.0977, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5781 +[2025-02-27 00:01:26] (step=0014550) Train Loss: 0.0970, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5629 +[2025-02-27 00:02:24] (step=0014600) Train Loss: 0.0979, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5933 +[2025-02-27 00:03:23] (step=0014650) Train Loss: 0.0977, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5657 +[2025-02-27 00:04:21] (step=0014700) Train Loss: 0.0968, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5598 +[2025-02-27 00:05:19] (step=0014750) Train Loss: 0.0982, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5818 +[2025-02-27 00:06:18] (step=0014800) Train Loss: 0.0973, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5746 +[2025-02-27 00:07:16] (step=0014850) Train Loss: 0.0978, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5706 +[2025-02-27 00:08:15] (step=0014900) Train Loss: 0.0966, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5422 +[2025-02-27 00:09:13] (step=0014950) Train Loss: 0.0975, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5881 +[2025-02-27 00:10:12] (step=0015000) Train Loss: 0.0964, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5573 +[2025-02-27 00:11:12] (step=0015050) Train Loss: 0.0975, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 0.6189 +[2025-02-27 00:12:11] (step=0015100) Train Loss: 0.0963, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5415 +[2025-02-27 00:13:09] (step=0015150) Train Loss: 0.0966, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5655 +[2025-02-27 00:14:08] (step=0015200) Train Loss: 0.0978, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6145 +[2025-02-27 00:15:06] (step=0015250) Train Loss: 0.0970, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5270 +[2025-02-27 00:16:05] (step=0015300) Train Loss: 0.0973, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5866 +[2025-02-27 00:17:03] (step=0015350) Train Loss: 0.0969, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5607 +[2025-02-27 00:18:02] (step=0015400) Train Loss: 0.0957, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5081 +[2025-02-27 00:19:01] (step=0015450) Train Loss: 0.0967, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5438 +[2025-02-27 00:19:59] (step=0015500) Train Loss: 0.0961, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5926 +[2025-02-27 00:20:58] (step=0015550) Train Loss: 0.0977, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5804 +[2025-02-27 00:21:56] (step=0015600) Train Loss: 0.0970, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5723 +[2025-02-27 00:22:55] (step=0015650) Train Loss: 0.0962, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5706 +[2025-02-27 00:23:53] (step=0015700) Train Loss: 0.0961, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5150 +[2025-02-27 00:24:52] (step=0015750) Train Loss: 0.0968, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5341 +[2025-02-27 00:25:50] (step=0015800) Train Loss: 0.0979, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.6096 +[2025-02-27 00:26:49] (step=0015850) Train Loss: 0.0969, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5514 +[2025-02-27 00:27:47] (step=0015900) Train Loss: 0.0962, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5331 +[2025-02-27 00:28:46] (step=0015950) Train Loss: 0.0966, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5588 +[2025-02-27 00:29:44] (step=0016000) Train Loss: 0.0973, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5192 +[2025-02-27 00:30:43] (step=0016050) Train Loss: 0.0958, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5501 +[2025-02-27 00:31:41] (step=0016100) Train Loss: 0.0972, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5782 +[2025-02-27 00:32:40] (step=0016150) Train Loss: 0.0963, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5005 +[2025-02-27 00:33:38] (step=0016200) Train Loss: 0.0974, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5851 +[2025-02-27 00:34:37] (step=0016250) Train Loss: 0.0950, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5172 +[2025-02-27 00:35:35] (step=0016300) Train Loss: 0.0962, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5581 +[2025-02-27 00:36:34] (step=0016350) Train Loss: 0.0967, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5449 +[2025-02-27 00:37:32] (step=0016400) Train Loss: 0.0951, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5329 +[2025-02-27 00:38:31] (step=0016450) Train Loss: 0.0960, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5495 +[2025-02-27 00:39:29] (step=0016500) Train Loss: 0.0965, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5587 +[2025-02-27 00:40:28] (step=0016550) Train Loss: 0.0959, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5344 +[2025-02-27 00:41:26] (step=0016600) Train Loss: 0.0968, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5320 +[2025-02-27 00:42:25] (step=0016650) Train Loss: 0.0970, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5662 +[2025-02-27 00:43:23] (step=0016700) Train Loss: 0.0963, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5190 +[2025-02-27 00:44:22] (step=0016750) Train Loss: 0.0951, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5456 +[2025-02-27 00:45:20] (step=0016800) Train Loss: 0.0959, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5375 +[2025-02-27 00:46:19] (step=0016850) Train Loss: 0.0969, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5489 +[2025-02-27 00:47:17] (step=0016900) Train Loss: 0.0957, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5319 +[2025-02-27 00:48:16] (step=0016950) Train Loss: 0.0961, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5396 +[2025-02-27 00:49:15] (step=0017000) Train Loss: 0.0957, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5080 +[2025-02-27 00:50:13] (step=0017050) Train Loss: 0.0959, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5274 +[2025-02-27 00:51:12] (step=0017100) Train Loss: 0.0963, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5430 +[2025-02-27 00:52:10] (step=0017150) Train Loss: 0.0953, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5467 +[2025-02-27 00:53:09] (step=0017200) Train Loss: 0.0962, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5193 +[2025-02-27 00:54:07] (step=0017250) Train Loss: 0.0956, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5572 +[2025-02-27 00:55:06] (step=0017300) Train Loss: 0.0955, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5330 +[2025-02-27 00:56:04] (step=0017350) Train Loss: 0.0946, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5148 +[2025-02-27 00:57:03] (step=0017400) Train Loss: 0.0961, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5378 +[2025-02-27 00:58:01] (step=0017450) Train Loss: 0.0958, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5329 +[2025-02-27 00:59:00] (step=0017500) Train Loss: 0.0952, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5159 +[2025-02-27 01:00:00] (step=0017550) Train Loss: 0.0952, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.82, Grad Norm: 0.5495 +[2025-02-27 01:00:59] (step=0017600) Train Loss: 0.0949, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5223 +[2025-02-27 01:01:57] (step=0017650) Train Loss: 0.0958, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5331 +[2025-02-27 01:02:56] (step=0017700) Train Loss: 0.0948, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5268 +[2025-02-27 01:03:54] (step=0017750) Train Loss: 0.0958, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5092 +[2025-02-27 01:04:53] (step=0017800) Train Loss: 0.0954, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5077 +[2025-02-27 01:05:51] (step=0017850) Train Loss: 0.0956, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4969 +[2025-02-27 01:06:50] (step=0017900) Train Loss: 0.0959, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5435 +[2025-02-27 01:07:48] (step=0017950) Train Loss: 0.0959, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4925 +[2025-02-27 01:08:47] (step=0018000) Train Loss: 0.0961, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5590 +[2025-02-27 01:09:45] (step=0018050) Train Loss: 0.0960, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5420 +[2025-02-27 01:10:44] (step=0018100) Train Loss: 0.0949, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5134 +[2025-02-27 01:11:42] (step=0018150) Train Loss: 0.0964, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5214 +[2025-02-27 01:12:41] (step=0018200) Train Loss: 0.0953, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4997 +[2025-02-27 01:13:39] (step=0018250) Train Loss: 0.0952, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5008 +[2025-02-27 01:14:38] (step=0018300) Train Loss: 0.0956, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5200 +[2025-02-27 01:15:36] (step=0018350) Train Loss: 0.0960, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5257 +[2025-02-27 01:16:35] (step=0018400) Train Loss: 0.0943, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5125 +[2025-02-27 01:17:33] (step=0018450) Train Loss: 0.0959, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5140 +[2025-02-27 01:18:32] (step=0018500) Train Loss: 0.0950, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5196 +[2025-02-27 01:19:30] (step=0018550) Train Loss: 0.0948, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5274 +[2025-02-27 01:20:29] (step=0018600) Train Loss: 0.0954, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4867 +[2025-02-27 01:21:27] (step=0018650) Train Loss: 0.0943, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5024 +[2025-02-27 01:22:26] (step=0018700) Train Loss: 0.0940, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5170 +[2025-02-27 01:23:24] (step=0018750) Train Loss: 0.0945, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4920 +[2025-02-27 01:24:23] (step=0018800) Train Loss: 0.0943, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5068 +[2025-02-27 01:25:21] (step=0018850) Train Loss: 0.0952, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5196 +[2025-02-27 01:26:20] (step=0018900) Train Loss: 0.0942, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4819 +[2025-02-27 01:27:18] (step=0018950) Train Loss: 0.0957, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4848 +[2025-02-27 01:28:17] (step=0019000) Train Loss: 0.0956, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5262 +[2025-02-27 01:29:15] (step=0019050) Train Loss: 0.0948, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4951 +[2025-02-27 01:30:14] (step=0019100) Train Loss: 0.0947, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5441 +[2025-02-27 01:31:12] (step=0019150) Train Loss: 0.0952, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4827 +[2025-02-27 01:32:11] (step=0019200) Train Loss: 0.0946, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5186 +[2025-02-27 01:33:09] (step=0019250) Train Loss: 0.0940, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4801 +[2025-02-27 01:34:08] (step=0019300) Train Loss: 0.0948, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4786 +[2025-02-27 01:35:06] (step=0019350) Train Loss: 0.0946, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4940 +[2025-02-27 01:36:05] (step=0019400) Train Loss: 0.0947, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5001 +[2025-02-27 01:37:03] (step=0019450) Train Loss: 0.0948, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5121 +[2025-02-27 01:38:02] (step=0019500) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4742 +[2025-02-27 01:39:00] (step=0019550) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5057 +[2025-02-27 01:39:59] (step=0019600) Train Loss: 0.0939, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4904 +[2025-02-27 01:40:57] (step=0019650) Train Loss: 0.0937, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5432 +[2025-02-27 01:41:56] (step=0019700) Train Loss: 0.0945, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4528 +[2025-02-27 01:42:54] (step=0019750) Train Loss: 0.0929, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.5217 +[2025-02-27 01:43:53] (step=0019800) Train Loss: 0.0939, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4985 +[2025-02-27 01:44:51] (step=0019850) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4908 +[2025-02-27 01:45:50] (step=0019900) Train Loss: 0.0938, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4694 +[2025-02-27 01:46:48] (step=0019950) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4945 +[2025-02-27 01:47:47] (step=0020000) Train Loss: 0.0950, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4820 +[2025-02-27 01:47:48] Saved checkpoint to ../logs/flow/flowsdvae_50kx512_lgn1p0/checkpoints/0020000.pt +[2025-02-27 02:06:13] (step=0020000), Fid=25.4391401601751, PSNR=18.11237196903229, LPIPS=0.51171875, SSIM=0.2148485779762268 +[2025-02-27 02:07:14] (step=0020050) Train Loss: 0.0940, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.04, Grad Norm: 0.4969 +[2025-02-27 02:08:12] (step=0020100) Train Loss: 0.0948, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4982 +[2025-02-27 02:09:11] (step=0020150) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4898 +[2025-02-27 02:10:09] (step=0020200) Train Loss: 0.0932, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4789 +[2025-02-27 02:11:07] (step=0020250) Train Loss: 0.0934, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5048 +[2025-02-27 02:12:05] (step=0020300) Train Loss: 0.0944, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4703 +[2025-02-27 02:13:03] (step=0020350) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4916 +[2025-02-27 02:14:02] (step=0020400) Train Loss: 0.0944, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5105 +[2025-02-27 02:15:00] (step=0020450) Train Loss: 0.0940, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4753 +[2025-02-27 02:15:58] (step=0020500) Train Loss: 0.0940, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4748 +[2025-02-27 02:16:56] (step=0020550) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4773 +[2025-02-27 02:17:54] (step=0020600) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4556 +[2025-02-27 02:18:53] (step=0020650) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5370 +[2025-02-27 02:19:51] (step=0020700) Train Loss: 0.0934, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4655 +[2025-02-27 02:20:49] (step=0020750) Train Loss: 0.0926, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4916 +[2025-02-27 02:21:47] (step=0020800) Train Loss: 0.0936, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4696 +[2025-02-27 02:22:45] (step=0020850) Train Loss: 0.0938, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5117 +[2025-02-27 02:23:43] (step=0020900) Train Loss: 0.0939, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4794 +[2025-02-27 02:24:42] (step=0020950) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4650 +[2025-02-27 02:25:40] (step=0021000) Train Loss: 0.0946, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4898 +[2025-02-27 02:26:38] (step=0021050) Train Loss: 0.0935, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4690 +[2025-02-27 02:27:36] (step=0021100) Train Loss: 0.0943, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4503 +[2025-02-27 02:28:34] (step=0021150) Train Loss: 0.0942, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4747 +[2025-02-27 02:29:33] (step=0021200) Train Loss: 0.0933, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4738 +[2025-02-27 02:30:31] (step=0021250) Train Loss: 0.0939, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4976 +[2025-02-27 02:31:29] (step=0021300) Train Loss: 0.0926, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5003 +[2025-02-27 02:32:27] (step=0021350) Train Loss: 0.0943, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4904 +[2025-02-27 02:33:25] (step=0021400) Train Loss: 0.0937, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4452 +[2025-02-27 02:34:23] (step=0021450) Train Loss: 0.0939, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4837 +[2025-02-27 02:35:22] (step=0021500) Train Loss: 0.0934, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4721 +[2025-02-27 02:36:20] (step=0021550) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4714 +[2025-02-27 02:37:18] (step=0021600) Train Loss: 0.0936, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5143 +[2025-02-27 02:38:16] (step=0021650) Train Loss: 0.0940, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4493 +[2025-02-27 02:39:14] (step=0021700) Train Loss: 0.0929, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4569 +[2025-02-27 02:40:12] (step=0021750) Train Loss: 0.0952, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4796 +[2025-02-27 02:41:11] (step=0021800) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4690 +[2025-02-27 02:42:09] (step=0021850) Train Loss: 0.0936, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4884 +[2025-02-27 02:43:07] (step=0021900) Train Loss: 0.0934, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4343 +[2025-02-27 02:44:05] (step=0021950) Train Loss: 0.0938, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4979 +[2025-02-27 02:45:03] (step=0022000) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4719 +[2025-02-27 02:46:02] (step=0022050) Train Loss: 0.0935, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4445 +[2025-02-27 02:47:00] (step=0022100) Train Loss: 0.0929, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4553 +[2025-02-27 02:47:58] (step=0022150) Train Loss: 0.0936, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4735 +[2025-02-27 02:48:56] (step=0022200) Train Loss: 0.0933, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4435 +[2025-02-27 02:49:54] (step=0022250) Train Loss: 0.0932, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4698 +[2025-02-27 02:50:52] (step=0022300) Train Loss: 0.0934, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4667 +[2025-02-27 02:51:51] (step=0022350) Train Loss: 0.0936, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4974 +[2025-02-27 02:52:49] (step=0022400) Train Loss: 0.0936, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4261 +[2025-02-27 02:53:47] (step=0022450) Train Loss: 0.0940, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4823 +[2025-02-27 02:54:45] (step=0022500) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4698 +[2025-02-27 02:55:46] (step=0022550) Train Loss: 0.0930, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 0.4691 +[2025-02-27 02:56:44] (step=0022600) Train Loss: 0.0920, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4925 +[2025-02-27 02:57:42] (step=0022650) Train Loss: 0.0933, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4159 +[2025-02-27 02:58:40] (step=0022700) Train Loss: 0.0937, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4752 +[2025-02-27 02:59:39] (step=0022750) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4400 +[2025-02-27 03:00:37] (step=0022800) Train Loss: 0.0926, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4395 +[2025-02-27 03:01:35] (step=0022850) Train Loss: 0.0935, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4605 +[2025-02-27 03:02:33] (step=0022900) Train Loss: 0.0934, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4552 +[2025-02-27 03:03:31] (step=0022950) Train Loss: 0.0937, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.5020 +[2025-02-27 03:04:30] (step=0023000) Train Loss: 0.0930, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4343 +[2025-02-27 03:05:28] (step=0023050) Train Loss: 0.0935, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4389 +[2025-02-27 03:06:26] (step=0023100) Train Loss: 0.0941, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4814 +[2025-02-27 03:07:24] (step=0023150) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4275 +[2025-02-27 03:08:22] (step=0023200) Train Loss: 0.0936, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4425 +[2025-02-27 03:09:21] (step=0023250) Train Loss: 0.0939, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4634 +[2025-02-27 03:10:19] (step=0023300) Train Loss: 0.0942, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4746 +[2025-02-27 03:11:17] (step=0023350) Train Loss: 0.0934, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4446 +[2025-02-27 03:12:15] (step=0023400) Train Loss: 0.0921, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4634 +[2025-02-27 03:13:13] (step=0023450) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4650 +[2025-02-27 03:14:11] (step=0023500) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4802 +[2025-02-27 03:15:10] (step=0023550) Train Loss: 0.0932, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4699 +[2025-02-27 03:16:08] (step=0023600) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4460 +[2025-02-27 03:17:06] (step=0023650) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4419 +[2025-02-27 03:18:04] (step=0023700) Train Loss: 0.0930, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4655 +[2025-02-27 03:19:02] (step=0023750) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4781 +[2025-02-27 03:20:01] (step=0023800) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4166 +[2025-02-27 03:20:59] (step=0023850) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4726 +[2025-02-27 03:21:57] (step=0023900) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4201 +[2025-02-27 03:22:55] (step=0023950) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4738 +[2025-02-27 03:23:53] (step=0024000) Train Loss: 0.0925, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4639 +[2025-02-27 03:24:51] (step=0024050) Train Loss: 0.0923, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4162 +[2025-02-27 03:25:50] (step=0024100) Train Loss: 0.0930, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4527 +[2025-02-27 03:26:48] (step=0024150) Train Loss: 0.0932, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4317 +[2025-02-27 03:27:46] (step=0024200) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4658 +[2025-02-27 03:28:44] (step=0024250) Train Loss: 0.0932, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4273 +[2025-02-27 03:29:42] (step=0024300) Train Loss: 0.0930, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4455 +[2025-02-27 03:30:41] (step=0024350) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4732 +[2025-02-27 03:31:39] (step=0024400) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4262 +[2025-02-27 03:32:37] (step=0024450) Train Loss: 0.0930, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4124 +[2025-02-27 03:33:35] (step=0024500) Train Loss: 0.0937, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4665 +[2025-02-27 03:34:33] (step=0024550) Train Loss: 0.0933, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4472 +[2025-02-27 03:35:32] (step=0024600) Train Loss: 0.0929, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4516 +[2025-02-27 03:36:30] (step=0024650) Train Loss: 0.0921, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3968 +[2025-02-27 03:37:28] (step=0024700) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4516 +[2025-02-27 03:38:26] (step=0024750) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4620 +[2025-02-27 03:39:24] (step=0024800) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4370 +[2025-02-27 03:40:22] (step=0024850) Train Loss: 0.0918, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4232 +[2025-02-27 03:41:21] (step=0024900) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4356 +[2025-02-27 03:42:19] (step=0024950) Train Loss: 0.0935, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4562 +[2025-02-27 03:43:17] (step=0025000) Train Loss: 0.0925, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4386 +[2025-02-27 03:44:18] (step=0025050) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 0.4294 +[2025-02-27 03:45:16] (step=0025100) Train Loss: 0.0916, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4363 +[2025-02-27 03:46:14] (step=0025150) Train Loss: 0.0929, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4347 +[2025-02-27 03:47:12] (step=0025200) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4275 +[2025-02-27 03:48:11] (step=0025250) Train Loss: 0.0916, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4345 +[2025-02-27 03:49:09] (step=0025300) Train Loss: 0.0916, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4434 +[2025-02-27 03:50:07] (step=0025350) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4395 +[2025-02-27 03:51:05] (step=0025400) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4675 +[2025-02-27 03:52:03] (step=0025450) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4431 +[2025-02-27 03:53:02] (step=0025500) Train Loss: 0.0926, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4334 +[2025-02-27 03:54:00] (step=0025550) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4390 +[2025-02-27 03:54:58] (step=0025600) Train Loss: 0.0926, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3931 +[2025-02-27 03:55:56] (step=0025650) Train Loss: 0.0932, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4452 +[2025-02-27 03:56:54] (step=0025700) Train Loss: 0.0931, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4500 +[2025-02-27 03:57:53] (step=0025750) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4234 +[2025-02-27 03:58:51] (step=0025800) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4428 +[2025-02-27 03:59:49] (step=0025850) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4264 +[2025-02-27 04:00:47] (step=0025900) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4248 +[2025-02-27 04:01:45] (step=0025950) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4493 +[2025-02-27 04:02:44] (step=0026000) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4409 +[2025-02-27 04:03:42] (step=0026050) Train Loss: 0.0929, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3996 +[2025-02-27 04:04:40] (step=0026100) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4501 +[2025-02-27 04:05:38] (step=0026150) Train Loss: 0.0915, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4227 +[2025-02-27 04:06:36] (step=0026200) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4365 +[2025-02-27 04:07:34] (step=0026250) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4360 +[2025-02-27 04:08:33] (step=0026300) Train Loss: 0.0930, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4119 +[2025-02-27 04:09:31] (step=0026350) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4540 +[2025-02-27 04:10:29] (step=0026400) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4426 +[2025-02-27 04:11:27] (step=0026450) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3956 +[2025-02-27 04:12:25] (step=0026500) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4538 +[2025-02-27 04:13:24] (step=0026550) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4358 +[2025-02-27 04:14:22] (step=0026600) Train Loss: 0.0918, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3861 +[2025-02-27 04:15:20] (step=0026650) Train Loss: 0.0926, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4515 +[2025-02-27 04:16:18] (step=0026700) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4153 +[2025-02-27 04:17:16] (step=0026750) Train Loss: 0.0923, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4231 +[2025-02-27 04:18:14] (step=0026800) Train Loss: 0.0929, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4067 +[2025-02-27 04:19:13] (step=0026850) Train Loss: 0.0911, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4126 +[2025-02-27 04:20:11] (step=0026900) Train Loss: 0.0918, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4239 +[2025-02-27 04:21:09] (step=0026950) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4010 +[2025-02-27 04:22:07] (step=0027000) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4490 +[2025-02-27 04:23:05] (step=0027050) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4420 +[2025-02-27 04:24:04] (step=0027100) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4270 +[2025-02-27 04:25:02] (step=0027150) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4287 +[2025-02-27 04:26:00] (step=0027200) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4291 +[2025-02-27 04:26:58] (step=0027250) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4364 +[2025-02-27 04:27:56] (step=0027300) Train Loss: 0.0915, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4467 +[2025-02-27 04:28:55] (step=0027350) Train Loss: 0.0921, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4241 +[2025-02-27 04:29:53] (step=0027400) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4282 +[2025-02-27 04:30:51] (step=0027450) Train Loss: 0.0918, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3688 +[2025-02-27 04:31:49] (step=0027500) Train Loss: 0.0921, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4360 +[2025-02-27 04:32:49] (step=0027550) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 0.4507 +[2025-02-27 04:33:48] (step=0027600) Train Loss: 0.0921, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4479 +[2025-02-27 04:34:46] (step=0027650) Train Loss: 0.0915, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4008 +[2025-02-27 04:35:44] (step=0027700) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4173 +[2025-02-27 04:36:42] (step=0027750) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4027 +[2025-02-27 04:37:40] (step=0027800) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4261 +[2025-02-27 04:38:39] (step=0027850) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4128 +[2025-02-27 04:39:37] (step=0027900) Train Loss: 0.0922, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4186 +[2025-02-27 04:40:35] (step=0027950) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4134 +[2025-02-27 04:41:33] (step=0028000) Train Loss: 0.0908, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4147 +[2025-02-27 04:42:31] (step=0028050) Train Loss: 0.0925, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4474 +[2025-02-27 04:43:30] (step=0028100) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4612 +[2025-02-27 04:44:28] (step=0028150) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3908 +[2025-02-27 04:45:26] (step=0028200) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4428 +[2025-02-27 04:46:24] (step=0028250) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4004 +[2025-02-27 04:47:22] (step=0028300) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4035 +[2025-02-27 04:48:21] (step=0028350) Train Loss: 0.0925, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4262 +[2025-02-27 04:49:19] (step=0028400) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3833 +[2025-02-27 04:50:17] (step=0028450) Train Loss: 0.0927, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4586 +[2025-02-27 04:51:15] (step=0028500) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3721 +[2025-02-27 04:52:13] (step=0028550) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4369 +[2025-02-27 04:53:12] (step=0028600) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4096 +[2025-02-27 04:54:10] (step=0028650) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4253 +[2025-02-27 04:55:08] (step=0028700) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4110 +[2025-02-27 04:56:06] (step=0028750) Train Loss: 0.0916, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3753 +[2025-02-27 04:57:04] (step=0028800) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4246 +[2025-02-27 04:58:02] (step=0028850) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4147 +[2025-02-27 04:59:01] (step=0028900) Train Loss: 0.0918, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3850 +[2025-02-27 04:59:59] (step=0028950) Train Loss: 0.0925, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4579 +[2025-02-27 05:00:57] (step=0029000) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4000 +[2025-02-27 05:01:55] (step=0029050) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3943 +[2025-02-27 05:02:53] (step=0029100) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4061 +[2025-02-27 05:03:52] (step=0029150) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4003 +[2025-02-27 05:04:50] (step=0029200) Train Loss: 0.0911, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4141 +[2025-02-27 05:05:48] (step=0029250) Train Loss: 0.0919, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4353 +[2025-02-27 05:06:46] (step=0029300) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4365 +[2025-02-27 05:07:44] (step=0029350) Train Loss: 0.0920, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3890 +[2025-02-27 05:08:42] (step=0029400) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4370 +[2025-02-27 05:09:41] (step=0029450) Train Loss: 0.0904, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4183 +[2025-02-27 05:10:39] (step=0029500) Train Loss: 0.0916, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3861 +[2025-02-27 05:11:37] (step=0029550) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4215 +[2025-02-27 05:12:35] (step=0029600) Train Loss: 0.0928, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4183 +[2025-02-27 05:13:33] (step=0029650) Train Loss: 0.0911, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3989 +[2025-02-27 05:14:32] (step=0029700) Train Loss: 0.0915, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3992 +[2025-02-27 05:15:30] (step=0029750) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3848 +[2025-02-27 05:16:28] (step=0029800) Train Loss: 0.0915, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4299 +[2025-02-27 05:17:26] (step=0029850) Train Loss: 0.0920, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4346 +[2025-02-27 05:18:24] (step=0029900) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4000 +[2025-02-27 05:19:23] (step=0029950) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3789 +[2025-02-27 05:20:21] (step=0030000) Train Loss: 0.0920, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4523 +[2025-02-27 05:20:23] Saved checkpoint to ../logs/flow/flowsdvae_50kx512_lgn1p0/checkpoints/0030000.pt +[2025-02-27 05:38:52] (step=0030000), Fid=9.563512706973938, PSNR=22.56198896906376, LPIPS=0.34375, SSIM=0.49755585193634033 +[2025-02-27 05:39:53] (step=0030050) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.04, Grad Norm: 0.3711 +[2025-02-27 05:40:51] (step=0030100) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4231 +[2025-02-27 05:41:50] (step=0030150) Train Loss: 0.0920, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3847 +[2025-02-27 05:42:48] (step=0030200) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4286 +[2025-02-27 05:43:47] (step=0030250) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3957 +[2025-02-27 05:44:45] (step=0030300) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3699 +[2025-02-27 05:45:44] (step=0030350) Train Loss: 0.0918, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3931 +[2025-02-27 05:46:42] (step=0030400) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4157 +[2025-02-27 05:47:41] (step=0030450) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4070 +[2025-02-27 05:48:39] (step=0030500) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3842 +[2025-02-27 05:49:38] (step=0030550) Train Loss: 0.0915, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3886 +[2025-02-27 05:50:36] (step=0030600) Train Loss: 0.0921, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4070 +[2025-02-27 05:51:35] (step=0030650) Train Loss: 0.0908, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3826 +[2025-02-27 05:52:33] (step=0030700) Train Loss: 0.0924, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4164 +[2025-02-27 05:53:32] (step=0030750) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3943 +[2025-02-27 05:54:30] (step=0030800) Train Loss: 0.0911, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4161 +[2025-02-27 05:55:29] (step=0030850) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4136 +[2025-02-27 05:56:27] (step=0030900) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4007 +[2025-02-27 05:57:26] (step=0030950) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4032 +[2025-02-27 05:58:24] (step=0031000) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4152 +[2025-02-27 05:59:23] (step=0031050) Train Loss: 0.0911, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4042 +[2025-02-27 06:00:21] (step=0031100) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3866 +[2025-02-27 06:01:20] (step=0031150) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4066 +[2025-02-27 06:02:18] (step=0031200) Train Loss: 0.0916, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4306 +[2025-02-27 06:03:17] (step=0031250) Train Loss: 0.0913, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3822 +[2025-02-27 06:04:15] (step=0031300) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3873 +[2025-02-27 06:05:14] (step=0031350) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4044 +[2025-02-27 06:06:12] (step=0031400) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3870 +[2025-02-27 06:07:11] (step=0031450) Train Loss: 0.0911, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4186 +[2025-02-27 06:08:09] (step=0031500) Train Loss: 0.0915, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3877 +[2025-02-27 06:09:08] (step=0031550) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3822 +[2025-02-27 06:10:06] (step=0031600) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4357 +[2025-02-27 06:11:05] (step=0031650) Train Loss: 0.0908, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3640 +[2025-02-27 06:12:03] (step=0031700) Train Loss: 0.0901, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4226 +[2025-02-27 06:13:02] (step=0031750) Train Loss: 0.0904, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3708 +[2025-02-27 06:14:00] (step=0031800) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4406 +[2025-02-27 06:14:59] (step=0031850) Train Loss: 0.0916, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3865 +[2025-02-27 06:15:57] (step=0031900) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4274 +[2025-02-27 06:16:56] (step=0031950) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3721 +[2025-02-27 06:17:54] (step=0032000) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3776 +[2025-02-27 06:18:52] (step=0032050) Train Loss: 0.0920, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4283 +[2025-02-27 06:19:51] (step=0032100) Train Loss: 0.0908, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3944 +[2025-02-27 06:20:49] (step=0032150) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3965 +[2025-02-27 06:21:48] (step=0032200) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3955 +[2025-02-27 06:22:46] (step=0032250) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3988 +[2025-02-27 06:23:45] (step=0032300) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3979 +[2025-02-27 06:24:43] (step=0032350) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4086 +[2025-02-27 06:25:42] (step=0032400) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3847 +[2025-02-27 06:26:40] (step=0032450) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4091 +[2025-02-27 06:27:39] (step=0032500) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3974 +[2025-02-27 06:28:40] (step=0032550) Train Loss: 0.0904, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.82, Grad Norm: 0.4000 +[2025-02-27 06:29:38] (step=0032600) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3932 +[2025-02-27 06:30:37] (step=0032650) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3846 +[2025-02-27 06:31:35] (step=0032700) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4042 +[2025-02-27 06:32:34] (step=0032750) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3803 +[2025-02-27 06:33:32] (step=0032800) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4121 +[2025-02-27 06:34:31] (step=0032850) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3835 +[2025-02-27 06:35:29] (step=0032900) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3851 +[2025-02-27 06:36:28] (step=0032950) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3700 +[2025-02-27 06:37:26] (step=0033000) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4206 +[2025-02-27 06:38:25] (step=0033050) Train Loss: 0.0914, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3990 +[2025-02-27 06:39:23] (step=0033100) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3994 +[2025-02-27 06:40:22] (step=0033150) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3947 +[2025-02-27 06:41:20] (step=0033200) Train Loss: 0.0904, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3353 +[2025-02-27 06:42:19] (step=0033250) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4140 +[2025-02-27 06:43:17] (step=0033300) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3721 +[2025-02-27 06:44:16] (step=0033350) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3886 +[2025-02-27 06:45:14] (step=0033400) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3779 +[2025-02-27 06:46:13] (step=0033450) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3903 +[2025-02-27 06:47:11] (step=0033500) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4020 +[2025-02-27 06:48:10] (step=0033550) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3888 +[2025-02-27 06:49:08] (step=0033600) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3748 +[2025-02-27 06:50:07] (step=0033650) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4155 +[2025-02-27 06:51:05] (step=0033700) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3837 +[2025-02-27 06:52:04] (step=0033750) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3775 +[2025-02-27 06:53:02] (step=0033800) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3717 +[2025-02-27 06:54:01] (step=0033850) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4064 +[2025-02-27 06:54:59] (step=0033900) Train Loss: 0.0901, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3910 +[2025-02-27 06:55:58] (step=0033950) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3688 +[2025-02-27 06:56:56] (step=0034000) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3958 +[2025-02-27 06:57:55] (step=0034050) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3953 +[2025-02-27 06:58:53] (step=0034100) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3793 +[2025-02-27 06:59:52] (step=0034150) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3573 +[2025-02-27 07:00:50] (step=0034200) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3982 +[2025-02-27 07:01:49] (step=0034250) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3631 +[2025-02-27 07:02:47] (step=0034300) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3960 +[2025-02-27 07:03:46] (step=0034350) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4080 +[2025-02-27 07:04:44] (step=0034400) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3689 +[2025-02-27 07:05:42] (step=0034450) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3847 +[2025-02-27 07:06:41] (step=0034500) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3778 +[2025-02-27 07:07:39] (step=0034550) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3838 +[2025-02-27 07:08:38] (step=0034600) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3773 +[2025-02-27 07:09:36] (step=0034650) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3975 +[2025-02-27 07:10:35] (step=0034700) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3726 +[2025-02-27 07:11:33] (step=0034750) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4014 +[2025-02-27 07:12:32] (step=0034800) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3744 +[2025-02-27 07:13:30] (step=0034850) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3900 +[2025-02-27 07:14:29] (step=0034900) Train Loss: 0.0901, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3870 +[2025-02-27 07:15:27] (step=0034950) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3952 +[2025-02-27 07:16:26] (step=0035000) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3582 +[2025-02-27 07:17:27] (step=0035050) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.82, Grad Norm: 0.3909 +[2025-02-27 07:18:25] (step=0035100) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3919 +[2025-02-27 07:19:24] (step=0035150) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3794 +[2025-02-27 07:20:22] (step=0035200) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3676 +[2025-02-27 07:21:21] (step=0035250) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4157 +[2025-02-27 07:22:19] (step=0035300) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3583 +[2025-02-27 07:23:18] (step=0035350) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3791 +[2025-02-27 07:24:16] (step=0035400) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4114 +[2025-02-27 07:25:15] (step=0035450) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3510 +[2025-02-27 07:26:13] (step=0035500) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3838 +[2025-02-27 07:27:12] (step=0035550) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3753 +[2025-02-27 07:28:10] (step=0035600) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3757 +[2025-02-27 07:29:09] (step=0035650) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3730 +[2025-02-27 07:30:07] (step=0035700) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3896 +[2025-02-27 07:31:06] (step=0035750) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3595 +[2025-02-27 07:32:04] (step=0035800) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4049 +[2025-02-27 07:33:03] (step=0035850) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3661 +[2025-02-27 07:34:01] (step=0035900) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3828 +[2025-02-27 07:34:59] (step=0035950) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3655 +[2025-02-27 07:35:57] (step=0036000) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3861 +[2025-02-27 07:36:55] (step=0036050) Train Loss: 0.0904, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3716 +[2025-02-27 07:37:54] (step=0036100) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3878 +[2025-02-27 07:38:52] (step=0036150) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3760 +[2025-02-27 07:39:50] (step=0036200) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3785 +[2025-02-27 07:40:48] (step=0036250) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3740 +[2025-02-27 07:41:46] (step=0036300) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3784 +[2025-02-27 07:42:45] (step=0036350) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3794 +[2025-02-27 07:43:43] (step=0036400) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3660 +[2025-02-27 07:44:41] (step=0036450) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3805 +[2025-02-27 07:45:39] (step=0036500) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3716 +[2025-02-27 07:46:37] (step=0036550) Train Loss: 0.0909, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3949 +[2025-02-27 07:47:36] (step=0036600) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3849 +[2025-02-27 07:48:34] (step=0036650) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3557 +[2025-02-27 07:49:32] (step=0036700) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4011 +[2025-02-27 07:50:30] (step=0036750) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3723 +[2025-02-27 07:51:28] (step=0036800) Train Loss: 0.0910, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3607 +[2025-02-27 07:52:27] (step=0036850) Train Loss: 0.0911, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3821 +[2025-02-27 07:53:25] (step=0036900) Train Loss: 0.0904, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3513 +[2025-02-27 07:54:23] (step=0036950) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3616 +[2025-02-27 07:55:21] (step=0037000) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3826 +[2025-02-27 07:56:19] (step=0037050) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3779 +[2025-02-27 07:57:17] (step=0037100) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3751 +[2025-02-27 07:58:16] (step=0037150) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3903 +[2025-02-27 07:59:14] (step=0037200) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.4008 +[2025-02-27 08:00:12] (step=0037250) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3635 +[2025-02-27 08:01:10] (step=0037300) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3892 +[2025-02-27 08:02:08] (step=0037350) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3606 +[2025-02-27 08:03:07] (step=0037400) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3405 +[2025-02-27 08:04:05] (step=0037450) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3757 +[2025-02-27 08:05:03] (step=0037500) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.86, Grad Norm: 0.3992 +[2025-02-27 08:06:03] (step=0037550) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.83, Grad Norm: 0.3809 +[2025-02-27 08:07:02] (step=0037600) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3938 +[2025-02-27 08:08:00] (step=0037650) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3586 +[2025-02-27 08:08:59] (step=0037700) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3367 +[2025-02-27 08:09:57] (step=0037750) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3697 +[2025-02-27 08:10:56] (step=0037800) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3750 +[2025-02-27 08:11:54] (step=0037850) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3832 +[2025-02-27 08:12:53] (step=0037900) Train Loss: 0.0906, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4004 +[2025-02-27 08:13:51] (step=0037950) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3389 +[2025-02-27 08:14:50] (step=0038000) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3452 +[2025-02-27 08:15:48] (step=0038050) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3948 +[2025-02-27 08:16:47] (step=0038100) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3385 +[2025-02-27 08:17:45] (step=0038150) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3754 +[2025-02-27 08:18:44] (step=0038200) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3664 +[2025-02-27 08:19:42] (step=0038250) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3850 +[2025-02-27 08:20:41] (step=0038300) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3638 +[2025-02-27 08:21:39] (step=0038350) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3581 +[2025-02-27 08:22:38] (step=0038400) Train Loss: 0.0901, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3561 +[2025-02-27 08:23:36] (step=0038450) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4001 +[2025-02-27 08:24:35] (step=0038500) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3390 +[2025-02-27 08:25:33] (step=0038550) Train Loss: 0.0912, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3794 +[2025-02-27 08:26:32] (step=0038600) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3503 +[2025-02-27 08:27:30] (step=0038650) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3618 +[2025-02-27 08:28:29] (step=0038700) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3510 +[2025-02-27 08:29:27] (step=0038750) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3765 +[2025-02-27 08:30:26] (step=0038800) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3769 +[2025-02-27 08:31:24] (step=0038850) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3506 +[2025-02-27 08:32:23] (step=0038900) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3584 +[2025-02-27 08:33:21] (step=0038950) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3810 +[2025-02-27 08:34:20] (step=0039000) Train Loss: 0.0907, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3814 +[2025-02-27 08:35:18] (step=0039050) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3493 +[2025-02-27 08:36:17] (step=0039100) Train Loss: 0.0917, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3883 +[2025-02-27 08:37:15] (step=0039150) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3490 +[2025-02-27 08:38:14] (step=0039200) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3979 +[2025-02-27 08:39:12] (step=0039250) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3514 +[2025-02-27 08:40:11] (step=0039300) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3839 +[2025-02-27 08:41:09] (step=0039350) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3399 +[2025-02-27 08:42:08] (step=0039400) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3831 +[2025-02-27 08:43:06] (step=0039450) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3546 +[2025-02-27 08:44:05] (step=0039500) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3740 +[2025-02-27 08:45:03] (step=0039550) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3315 +[2025-02-27 08:46:02] (step=0039600) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.4140 +[2025-02-27 08:47:00] (step=0039650) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3375 +[2025-02-27 08:47:59] (step=0039700) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3611 +[2025-02-27 08:48:57] (step=0039750) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3709 +[2025-02-27 08:49:56] (step=0039800) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3790 +[2025-02-27 08:50:54] (step=0039850) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3448 +[2025-02-27 08:51:53] (step=0039900) Train Loss: 0.0877, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3724 +[2025-02-27 08:52:51] (step=0039950) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3713 +[2025-02-27 08:53:50] (step=0040000) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3680 +[2025-02-27 08:53:52] Saved checkpoint to ../logs/flow/flowsdvae_50kx512_lgn1p0/checkpoints/0040000.pt +[2025-02-27 09:12:53] (step=0040000), Fid=5.2692476984086625, PSNR=24.01686583752632, LPIPS=0.259765625, SSIM=0.6080275177955627 +[2025-02-27 09:13:53] (step=0040050) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.04, Grad Norm: 0.3741 +[2025-02-27 09:14:52] (step=0040100) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3656 +[2025-02-27 09:15:50] (step=0040150) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3476 +[2025-02-27 09:16:49] (step=0040200) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3505 +[2025-02-27 09:17:47] (step=0040250) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3570 +[2025-02-27 09:18:46] (step=0040300) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3521 +[2025-02-27 09:19:44] (step=0040350) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3628 +[2025-02-27 09:20:43] (step=0040400) Train Loss: 0.0901, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3569 +[2025-02-27 09:21:41] (step=0040450) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3598 +[2025-02-27 09:22:40] (step=0040500) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3616 +[2025-02-27 09:23:38] (step=0040550) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3581 +[2025-02-27 09:24:37] (step=0040600) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3433 +[2025-02-27 09:25:35] (step=0040650) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3496 +[2025-02-27 09:26:34] (step=0040700) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3826 +[2025-02-27 09:27:32] (step=0040750) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3641 +[2025-02-27 09:28:31] (step=0040800) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3480 +[2025-02-27 09:29:29] (step=0040850) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3550 +[2025-02-27 09:30:28] (step=0040900) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3790 +[2025-02-27 09:31:26] (step=0040950) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3581 +[2025-02-27 09:32:25] (step=0041000) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3595 +[2025-02-27 09:33:23] (step=0041050) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3221 +[2025-02-27 09:34:22] (step=0041100) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3936 +[2025-02-27 09:35:20] (step=0041150) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3158 +[2025-02-27 09:36:19] (step=0041200) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3728 +[2025-02-27 09:37:17] (step=0041250) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3384 +[2025-02-27 09:38:16] (step=0041300) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3561 +[2025-02-27 09:39:14] (step=0041350) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3618 +[2025-02-27 09:40:13] (step=0041400) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3650 +[2025-02-27 09:41:12] (step=0041450) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3681 +[2025-02-27 09:42:10] (step=0041500) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3560 +[2025-02-27 09:43:09] (step=0041550) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3495 +[2025-02-27 09:44:07] (step=0041600) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3383 +[2025-02-27 09:45:06] (step=0041650) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3586 +[2025-02-27 09:46:04] (step=0041700) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3612 +[2025-02-27 09:47:03] (step=0041750) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3687 +[2025-02-27 09:48:01] (step=0041800) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3495 +[2025-02-27 09:49:00] (step=0041850) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3453 +[2025-02-27 09:49:58] (step=0041900) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3441 +[2025-02-27 09:50:57] (step=0041950) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3390 +[2025-02-27 09:51:55] (step=0042000) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3779 +[2025-02-27 09:52:54] (step=0042050) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3548 +[2025-02-27 09:53:52] (step=0042100) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3484 +[2025-02-27 09:54:51] (step=0042150) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3277 +[2025-02-27 09:55:49] (step=0042200) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3411 +[2025-02-27 09:56:48] (step=0042250) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3539 +[2025-02-27 09:57:46] (step=0042300) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3442 +[2025-02-27 09:58:45] (step=0042350) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3529 +[2025-02-27 09:59:43] (step=0042400) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3422 +[2025-02-27 10:00:42] (step=0042450) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3524 +[2025-02-27 10:01:40] (step=0042500) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3477 +[2025-02-27 10:02:41] (step=0042550) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.82, Grad Norm: 0.3446 +[2025-02-27 10:03:39] (step=0042600) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3575 +[2025-02-27 10:04:38] (step=0042650) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3437 +[2025-02-27 10:05:36] (step=0042700) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3388 +[2025-02-27 10:06:35] (step=0042750) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3497 +[2025-02-27 10:07:33] (step=0042800) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3807 +[2025-02-27 10:08:32] (step=0042850) Train Loss: 0.0885, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3548 +[2025-02-27 10:09:30] (step=0042900) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3418 +[2025-02-27 10:10:29] (step=0042950) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3522 +[2025-02-27 10:11:27] (step=0043000) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3703 +[2025-02-27 10:12:26] (step=0043050) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3187 +[2025-02-27 10:13:24] (step=0043100) Train Loss: 0.0882, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3626 +[2025-02-27 10:14:23] (step=0043150) Train Loss: 0.0899, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3592 +[2025-02-27 10:15:22] (step=0043200) Train Loss: 0.0901, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3338 +[2025-02-27 10:16:20] (step=0043250) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3674 +[2025-02-27 10:17:19] (step=0043300) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3420 +[2025-02-27 10:18:17] (step=0043350) Train Loss: 0.0878, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3388 +[2025-02-27 10:19:16] (step=0043400) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3432 +[2025-02-27 10:20:14] (step=0043450) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3733 +[2025-02-27 10:21:13] (step=0043500) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3265 +[2025-02-27 10:22:11] (step=0043550) Train Loss: 0.0900, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3493 +[2025-02-27 10:23:10] (step=0043600) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3598 +[2025-02-27 10:24:08] (step=0043650) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3407 +[2025-02-27 10:25:07] (step=0043700) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3584 +[2025-02-27 10:26:05] (step=0043750) Train Loss: 0.0881, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3499 +[2025-02-27 10:27:04] (step=0043800) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3315 +[2025-02-27 10:28:02] (step=0043850) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3530 +[2025-02-27 10:29:01] (step=0043900) Train Loss: 0.0878, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3484 +[2025-02-27 10:29:59] (step=0043950) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3488 +[2025-02-27 10:30:58] (step=0044000) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3369 +[2025-02-27 10:31:56] (step=0044050) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3745 +[2025-02-27 10:32:55] (step=0044100) Train Loss: 0.0885, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3241 +[2025-02-27 10:33:53] (step=0044150) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3370 +[2025-02-27 10:34:52] (step=0044200) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3805 +[2025-02-27 10:35:50] (step=0044250) Train Loss: 0.0883, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.2707 +[2025-02-27 10:36:49] (step=0044300) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3740 +[2025-02-27 10:37:47] (step=0044350) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3568 +[2025-02-27 10:38:46] (step=0044400) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3296 +[2025-02-27 10:39:44] (step=0044450) Train Loss: 0.0905, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3740 +[2025-02-27 10:40:43] (step=0044500) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3546 +[2025-02-27 10:41:41] (step=0044550) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3314 +[2025-02-27 10:42:40] (step=0044600) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3484 +[2025-02-27 10:43:38] (step=0044650) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3342 +[2025-02-27 10:44:37] (step=0044700) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3609 +[2025-02-27 10:45:35] (step=0044750) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3770 +[2025-02-27 10:46:34] (step=0044800) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3190 +[2025-02-27 10:47:32] (step=0044850) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3396 +[2025-02-27 10:48:31] (step=0044900) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3460 +[2025-02-27 10:49:29] (step=0044950) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3565 +[2025-02-27 10:50:28] (step=0045000) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3334 +[2025-02-27 10:51:29] (step=0045050) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.82, Grad Norm: 0.3521 +[2025-02-27 10:52:27] (step=0045100) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3552 +[2025-02-27 10:53:26] (step=0045150) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3541 +[2025-02-27 10:54:24] (step=0045200) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3215 +[2025-02-27 10:55:23] (step=0045250) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3640 +[2025-02-27 10:56:21] (step=0045300) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3319 +[2025-02-27 10:57:20] (step=0045350) Train Loss: 0.0881, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3441 +[2025-02-27 10:58:18] (step=0045400) Train Loss: 0.0902, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3530 +[2025-02-27 10:59:17] (step=0045450) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3283 +[2025-02-27 11:00:15] (step=0045500) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3597 +[2025-02-27 11:01:14] (step=0045550) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3536 +[2025-02-27 11:02:12] (step=0045600) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3386 +[2025-02-27 11:03:11] (step=0045650) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3636 +[2025-02-27 11:04:09] (step=0045700) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3019 +[2025-02-27 11:05:08] (step=0045750) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3642 +[2025-02-27 11:06:06] (step=0045800) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3331 +[2025-02-27 11:07:05] (step=0045850) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3576 +[2025-02-27 11:08:03] (step=0045900) Train Loss: 0.0897, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3132 +[2025-02-27 11:09:02] (step=0045950) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3358 +[2025-02-27 11:10:00] (step=0046000) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3619 +[2025-02-27 11:10:59] (step=0046050) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3489 +[2025-02-27 11:11:57] (step=0046100) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3296 +[2025-02-27 11:12:56] (step=0046150) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3173 +[2025-02-27 11:13:54] (step=0046200) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3456 +[2025-02-27 11:14:53] (step=0046250) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3286 +[2025-02-27 11:15:51] (step=0046300) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3619 +[2025-02-27 11:16:50] (step=0046350) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3214 +[2025-02-27 11:17:48] (step=0046400) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3545 +[2025-02-27 11:18:47] (step=0046450) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3101 +[2025-02-27 11:19:45] (step=0046500) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3567 +[2025-02-27 11:20:44] (step=0046550) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3190 +[2025-02-27 11:21:42] (step=0046600) Train Loss: 0.0885, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3491 +[2025-02-27 11:22:41] (step=0046650) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3281 +[2025-02-27 11:23:40] (step=0046700) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3607 +[2025-02-27 11:24:38] (step=0046750) Train Loss: 0.0882, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3263 +[2025-02-27 11:25:37] (step=0046800) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3185 +[2025-02-27 11:26:35] (step=0046850) Train Loss: 0.0881, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3536 +[2025-02-27 11:27:34] (step=0046900) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3492 +[2025-02-27 11:28:32] (step=0046950) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3462 +[2025-02-27 11:29:31] (step=0047000) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3392 +[2025-02-27 11:30:29] (step=0047050) Train Loss: 0.0891, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3352 +[2025-02-27 11:31:28] (step=0047100) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3397 +[2025-02-27 11:32:26] (step=0047150) Train Loss: 0.0903, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3605 +[2025-02-27 11:33:25] (step=0047200) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3450 +[2025-02-27 11:34:23] (step=0047250) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3178 +[2025-02-27 11:35:22] (step=0047300) Train Loss: 0.0882, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3541 +[2025-02-27 11:36:20] (step=0047350) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3229 +[2025-02-27 11:37:19] (step=0047400) Train Loss: 0.0883, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3582 +[2025-02-27 11:38:17] (step=0047450) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3525 +[2025-02-27 11:39:16] (step=0047500) Train Loss: 0.0880, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3231 +[2025-02-27 11:40:16] (step=0047550) Train Loss: 0.0881, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.82, Grad Norm: 0.3271 +[2025-02-27 11:41:15] (step=0047600) Train Loss: 0.0895, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3364 +[2025-02-27 11:42:13] (step=0047650) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3304 +[2025-02-27 11:43:12] (step=0047700) Train Loss: 0.0871, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3505 +[2025-02-27 11:44:10] (step=0047750) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3122 +[2025-02-27 11:45:09] (step=0047800) Train Loss: 0.0885, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3307 +[2025-02-27 11:46:08] (step=0047850) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3330 +[2025-02-27 11:47:06] (step=0047900) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3345 +[2025-02-27 11:48:05] (step=0047950) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3343 +[2025-02-27 11:49:03] (step=0048000) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3233 +[2025-02-27 11:50:02] (step=0048050) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3352 +[2025-02-27 11:51:00] (step=0048100) Train Loss: 0.0898, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3368 +[2025-02-27 11:51:59] (step=0048150) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3092 +[2025-02-27 11:52:57] (step=0048200) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3203 +[2025-02-27 11:53:56] (step=0048250) Train Loss: 0.0894, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3412 +[2025-02-27 11:54:54] (step=0048300) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3544 +[2025-02-27 11:55:53] (step=0048350) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3082 +[2025-02-27 11:56:51] (step=0048400) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3565 +[2025-02-27 11:57:50] (step=0048450) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3194 +[2025-02-27 11:58:48] (step=0048500) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3308 +[2025-02-27 11:59:47] (step=0048550) Train Loss: 0.0893, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3413 +[2025-02-27 12:00:45] (step=0048600) Train Loss: 0.0882, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3301 +[2025-02-27 12:01:44] (step=0048650) Train Loss: 0.0888, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3397 +[2025-02-27 12:02:43] (step=0048700) Train Loss: 0.0883, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3384 +[2025-02-27 12:03:41] (step=0048750) Train Loss: 0.0880, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3463 +[2025-02-27 12:04:40] (step=0048800) Train Loss: 0.0881, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3256 +[2025-02-27 12:05:38] (step=0048850) Train Loss: 0.0880, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3092 +[2025-02-27 12:06:37] (step=0048900) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3374 +[2025-02-27 12:07:35] (step=0048950) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3321 +[2025-02-27 12:08:34] (step=0049000) Train Loss: 0.0876, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3207 +[2025-02-27 12:09:32] (step=0049050) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3317 +[2025-02-27 12:10:31] (step=0049100) Train Loss: 0.0892, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3189 +[2025-02-27 12:11:29] (step=0049150) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3173 +[2025-02-27 12:12:28] (step=0049200) Train Loss: 0.0896, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3109 +[2025-02-27 12:13:26] (step=0049250) Train Loss: 0.0883, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3278 +[2025-02-27 12:14:25] (step=0049300) Train Loss: 0.0877, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3305 +[2025-02-27 12:15:23] (step=0049350) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3220 +[2025-02-27 12:16:22] (step=0049400) Train Loss: 0.0886, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3239 +[2025-02-27 12:17:20] (step=0049450) Train Loss: 0.0889, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3283 +[2025-02-27 12:18:19] (step=0049500) Train Loss: 0.0872, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3138 +[2025-02-27 12:19:17] (step=0049550) Train Loss: 0.0880, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3518 +[2025-02-27 12:20:16] (step=0049600) Train Loss: 0.0885, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3191 +[2025-02-27 12:21:14] (step=0049650) Train Loss: 0.0885, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3486 +[2025-02-27 12:22:13] (step=0049700) Train Loss: 0.0885, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3318 +[2025-02-27 12:23:11] (step=0049750) Train Loss: 0.0876, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3111 +[2025-02-27 12:24:10] (step=0049800) Train Loss: 0.0880, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3064 +[2025-02-27 12:25:08] (step=0049850) Train Loss: 0.0883, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3490 +[2025-02-27 12:26:07] (step=0049900) Train Loss: 0.0890, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3099 +[2025-02-27 12:27:05] (step=0049950) Train Loss: 0.0884, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3266 +[2025-02-27 12:28:04] (step=0050000) Train Loss: 0.0887, Perceptual Loss: 0.0000, Cos Loss: 0.0000, Train Steps/Sec: 0.85, Grad Norm: 0.3331 +[2025-02-27 12:28:07] Saved checkpoint to ../logs/flow/flowsdvae_50kx512_lgn1p0/checkpoints/0050000.pt +[2025-02-27 12:48:02] (step=0050000), Fid=4.089798184892516, PSNR=24.499341709566117, LPIPS=0.224609375, SSIM=0.6338350772857666 +[2025-02-27 12:48:03] Done!