diff --git "a/DRIP_4x_16_ViT_5_7/out.log" "b/DRIP_4x_16_ViT_5_7/out.log" new file mode 100644--- /dev/null +++ "b/DRIP_4x_16_ViT_5_7/out.log" @@ -0,0 +1,8047 @@ +2025-09-10,23:21:13 | INFO | Running with a single process. Device cuda. +2025-09-10,23:21:13 | INFO | Loaded ViT-B-16 model config. +2025-09-10,23:21:14 | INFO | Model: +2025-09-10,23:21:14 | INFO | CLIP( + (visual): DTPViT( + (patch_embed): PatchEmbedding( + (proj): Conv2d(3, 768, kernel_size=(16, 16), stride=(16, 16)) + ) + (dropout): Dropout(p=0.0, inplace=False) + (pre_blocks): ModuleList( + (0-4): 5 x TransformerEncoderLayer( + (self_attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (linear1): Linear(in_features=768, out_features=3072, bias=True) + (dropout): Dropout(p=0.0, inplace=False) + (linear2): Linear(in_features=3072, out_features=768, bias=True) + (norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (dropout1): Dropout(p=0.0, inplace=False) + (dropout2): Dropout(p=0.0, inplace=False) + ) + ) + (short_blocks): ModuleList( + (0-6): 7 x TransformerEncoderLayer( + (self_attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (linear1): Linear(in_features=768, out_features=3072, bias=True) + (dropout): Dropout(p=0.0, inplace=False) + (linear2): Linear(in_features=3072, out_features=768, bias=True) + (norm1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (norm2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (dropout1): Dropout(p=0.0, inplace=False) + (dropout2): Dropout(p=0.0, inplace=False) + ) + ) + (boundary_predictor): BoundaryPredictor( + (boundary_predictor): Sequential( + (0): Linear(in_features=768, out_features=3072, bias=True) + (1): GELU(approximate='none') + (2): Linear(in_features=3072, out_features=1, bias=True) + ) + (loss): BCEWithLogitsLoss() + ) + (down_ln): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (head): Linear(in_features=768, out_features=512, bias=True) + ) + (transformer): Transformer( + (resblocks): ModuleList( + (0-11): 12 x ResidualAttentionBlock( + (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=512, out_features=2048, bias=True) + (gelu): GELU(approximate='none') + (c_proj): Linear(in_features=2048, out_features=512, bias=True) + ) + (ls_2): Identity() + ) + ) + ) + (token_embedding): Embedding(49408, 512) + (ln_final): LayerNorm((512,), eps=1e-05, elementwise_affine=True) +) +2025-09-10,23:21:14 | INFO | Params: +2025-09-10,23:21:14 | INFO | DTP: True +2025-09-10,23:21:14 | INFO | accum_freq: 1 +2025-09-10,23:21:14 | INFO | aug_cfg: {} +2025-09-10,23:21:14 | INFO | batch_size: 512 +2025-09-10,23:21:14 | INFO | beta1: 0.9 +2025-09-10,23:21:14 | INFO | beta2: 0.98 +2025-09-10,23:21:14 | INFO | cache_dir: None +2025-09-10,23:21:14 | INFO | checkpoint_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_09_10-23_21_13-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/checkpoints +2025-09-10,23:21:14 | INFO | coca_caption_loss_weight: 2.0 +2025-09-10,23:21:14 | INFO | coca_contrastive_loss_weight: 1.0 +2025-09-10,23:21:14 | INFO | copy_codebase: False +2025-09-10,23:21:14 | INFO | csv_caption_key: title +2025-09-10,23:21:14 | INFO | csv_img_key: filepath +2025-09-10,23:21:14 | INFO | csv_separator: +2025-09-10,23:21:14 | INFO | dataset_resampled: False +2025-09-10,23:21:14 | INFO | dataset_type: webdataset +2025-09-10,23:21:14 | INFO | ddp_static_graph: False +2025-09-10,23:21:14 | INFO | debug: False +2025-09-10,23:21:14 | INFO | delete_previous_checkpoint: False +2025-09-10,23:21:14 | INFO | device: cuda +2025-09-10,23:21:14 | INFO | dist_backend: None +2025-09-10,23:21:14 | INFO | dist_url: None +2025-09-10,23:21:14 | INFO | distill: False +2025-09-10,23:21:14 | INFO | distill_model: None +2025-09-10,23:21:14 | INFO | distill_pretrained: None +2025-09-10,23:21:14 | INFO | distributed: False +2025-09-10,23:21:14 | INFO | epochs: 15 +2025-09-10,23:21:14 | INFO | epochs_cooldown: None +2025-09-10,23:21:14 | INFO | eps: 1e-06 +2025-09-10,23:21:14 | INFO | force_custom_text: False +2025-09-10,23:21:14 | INFO | force_image_size: None +2025-09-10,23:21:14 | INFO | force_patch_dropout: None +2025-09-10,23:21:14 | INFO | force_quick_gelu: False +2025-09-10,23:21:14 | INFO | gather_with_grad: False +2025-09-10,23:21:14 | INFO | grad_checkpointing: False +2025-09-10,23:21:14 | INFO | grad_clip_norm: None +2025-09-10,23:21:14 | INFO | horovod: False +2025-09-10,23:21:14 | INFO | image_interpolation: None +2025-09-10,23:21:14 | INFO | image_mean: None +2025-09-10,23:21:14 | INFO | image_resize_mode: None +2025-09-10,23:21:14 | INFO | image_std: None +2025-09-10,23:21:14 | INFO | imagenet_v2: None +2025-09-10,23:21:14 | INFO | imagenet_val: /fs/scratch/PAS2836/yusenpeng_dataset/val +2025-09-10,23:21:14 | INFO | local_loss: False +2025-09-10,23:21:14 | INFO | local_rank: 0 +2025-09-10,23:21:14 | INFO | lock_image: False +2025-09-10,23:21:14 | INFO | lock_image_freeze_bn_stats: False +2025-09-10,23:21:14 | INFO | lock_image_unlocked_groups: 0 +2025-09-10,23:21:14 | INFO | lock_text: False +2025-09-10,23:21:14 | INFO | lock_text_freeze_layer_norm: False +2025-09-10,23:21:14 | INFO | lock_text_unlocked_layers: 0 +2025-09-10,23:21:14 | INFO | log_every_n_steps: 100 +2025-09-10,23:21:14 | INFO | log_level: 20 +2025-09-10,23:21:14 | INFO | log_local: False +2025-09-10,23:21:14 | INFO | log_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_09_10-23_21_13-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/out.log +2025-09-10,23:21:14 | INFO | logs: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/ +2025-09-10,23:21:14 | INFO | loss_dist_impl: None +2025-09-10,23:21:14 | INFO | lr: 5e-05 +2025-09-10,23:21:14 | INFO | lr_cooldown_end: 0.0 +2025-09-10,23:21:14 | INFO | lr_cooldown_power: 1.0 +2025-09-10,23:21:14 | INFO | lr_scheduler: cosine +2025-09-10,23:21:14 | INFO | model: ViT-B-16 +2025-09-10,23:21:14 | INFO | momentum: None +2025-09-10,23:21:14 | INFO | name: 2025_09_10-23_21_13-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp +2025-09-10,23:21:14 | INFO | no_set_device_rank: False +2025-09-10,23:21:14 | INFO | opt: adamw +2025-09-10,23:21:14 | INFO | precision: amp +2025-09-10,23:21:14 | INFO | pretrained: +2025-09-10,23:21:14 | INFO | pretrained_image: False +2025-09-10,23:21:14 | INFO | rank: 0 +2025-09-10,23:21:14 | INFO | remote_sync: None +2025-09-10,23:21:14 | INFO | remote_sync_frequency: 300 +2025-09-10,23:21:14 | INFO | remote_sync_protocol: s3 +2025-09-10,23:21:14 | INFO | report_to: tensorboard +2025-09-10,23:21:14 | INFO | resume: None +2025-09-10,23:21:14 | INFO | save_frequency: 1 +2025-09-10,23:21:14 | INFO | save_most_recent: False +2025-09-10,23:21:14 | INFO | seed: 0 +2025-09-10,23:21:14 | INFO | siglip: False +2025-09-10,23:21:14 | INFO | skip_scheduler: False +2025-09-10,23:21:14 | INFO | tensorboard: True +2025-09-10,23:21:14 | INFO | tensorboard_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_09_10-23_21_13-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/tensorboard +2025-09-10,23:21:14 | INFO | torchcompile: False +2025-09-10,23:21:14 | INFO | torchscript: False +2025-09-10,23:21:14 | INFO | trace: False +2025-09-10,23:21:14 | INFO | train_data: 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+2025-09-10,23:21:14 | INFO | train_data_upsampling_factors: None +2025-09-10,23:21:14 | INFO | train_num_samples: 26365716 +2025-09-10,23:21:14 | INFO | use_bn_sync: False +2025-09-10,23:21:14 | INFO | use_bnb_linear: None +2025-09-10,23:21:14 | INFO | val_data: None +2025-09-10,23:21:14 | INFO | val_frequency: 1 +2025-09-10,23:21:14 | INFO | val_num_samples: None +2025-09-10,23:21:14 | INFO | wandb: False +2025-09-10,23:21:14 | INFO | wandb_notes: +2025-09-10,23:21:14 | INFO | wandb_project_name: open-clip +2025-09-10,23:21:14 | INFO | warmup: 50 +2025-09-10,23:21:14 | INFO | wd: 0.1 +2025-09-10,23:21:14 | INFO | workers: 8 +2025-09-10,23:21:14 | INFO | world_size: 1 +2025-09-10,23:21:14 | INFO | zeroshot_frequency: 1 +2025-09-10,23:21:14 | INFO | Created AdamW (adamw) optimizer: lr: 5e-05, betas: (0.9, 0.98), eps: 1e-06, weight_decay: 0.1, amsgrad: False, maximize: False, foreach: None, capturable: False, differentiable: False, fused: None, decoupled_weight_decay: True +2025-09-10,23:21:15 | INFO | Start epoch 0 +2025-09-10,23:21:24 | INFO | Train Epoch: 0 [ 512/26365952 (0%)] Avg Boundaries (per batch): 85.078 Boundary Ratio: 0.434 Contrastive_loss: 6.3153 (6.3153) Boundary_loss: 0.098450 (0.098450) Loss: 6.4137 (6.4137) +2025-09-10,23:22:35 | INFO | Train Epoch: 0 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 50.457 Boundary Ratio: 0.257 Contrastive_loss: 6.1600 (6.2376) Boundary_loss: 0.016663 (0.057556) Loss: 6.1767 (6.2952) +2025-09-10,23:23:44 | INFO | Train Epoch: 0 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 49.955 Boundary Ratio: 0.255 Contrastive_loss: 5.9581 (6.1445) Boundary_loss: 0.016930 (0.044014) Loss: 5.9750 (6.1885) +2025-09-10,23:24:54 | INFO | Train Epoch: 0 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.590 Boundary Ratio: 0.253 Contrastive_loss: 5.7429 (6.0441) Boundary_loss: 0.016614 (0.037164) Loss: 5.7595 (6.0812) +2025-09-10,23:26:03 | INFO | Train Epoch: 0 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.008 Boundary Ratio: 0.245 Contrastive_loss: 5.5450 (5.9442) Boundary_loss: 0.016631 (0.033058) Loss: 5.5616 (5.9773) +2025-09-10,23:27:12 | INFO | Train Epoch: 0 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 49.189 Boundary Ratio: 0.251 Contrastive_loss: 5.4805 (5.8670) Boundary_loss: 0.016516 (0.030301) Loss: 5.4970 (5.8973) +2025-09-10,23:28:22 | INFO | Train Epoch: 0 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 49.471 Boundary Ratio: 0.252 Contrastive_loss: 5.3338 (5.7908) Boundary_loss: 0.016449 (0.028322) Loss: 5.3503 (5.8191) +2025-09-10,23:29:31 | INFO | Train Epoch: 0 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 50.082 Boundary Ratio: 0.256 Contrastive_loss: 5.3877 (5.7404) Boundary_loss: 0.016829 (0.026885) Loss: 5.4045 (5.7673) +2025-09-10,23:30:40 | INFO | Train Epoch: 0 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 47.781 Boundary Ratio: 0.244 Contrastive_loss: 5.2211 (5.6827) Boundary_loss: 0.016669 (0.025750) Loss: 5.2377 (5.7085) +2025-09-10,23:31:49 | INFO | Train Epoch: 0 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.215 Boundary Ratio: 0.246 Contrastive_loss: 5.2476 (5.6392) Boundary_loss: 0.016342 (0.024809) Loss: 5.2639 (5.6640) +2025-09-10,23:32:59 | INFO | Train Epoch: 0 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 50.824 Boundary Ratio: 0.259 Contrastive_loss: 5.1403 (5.5938) Boundary_loss: 0.016809 (0.024082) Loss: 5.1571 (5.6179) +2025-09-10,23:34:08 | INFO | Train Epoch: 0 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 49.844 Boundary Ratio: 0.254 Contrastive_loss: 5.0087 (5.5451) Boundary_loss: 0.016535 (0.023453) Loss: 5.0253 (5.5685) +2025-09-10,23:35:18 | INFO | Train Epoch: 0 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 4.8890 (5.4946) Boundary_loss: 0.016552 (0.022922) Loss: 4.9056 (5.5175) +2025-09-10,23:36:27 | INFO | Train Epoch: 0 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 4.8826 (5.4509) Boundary_loss: 0.016410 (0.022457) Loss: 4.8990 (5.4734) +2025-09-10,23:37:36 | INFO | Train Epoch: 0 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.336 Boundary Ratio: 0.247 Contrastive_loss: 4.8980 (5.4140) Boundary_loss: 0.016210 (0.022041) Loss: 4.9142 (5.4361) +2025-09-10,23:38:45 | INFO | Train Epoch: 0 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.166 Boundary Ratio: 0.246 Contrastive_loss: 4.7658 (5.3735) Boundary_loss: 0.016761 (0.021711) Loss: 4.7826 (5.3952) +2025-09-10,23:39:55 | INFO | Train Epoch: 0 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 50.242 Boundary Ratio: 0.256 Contrastive_loss: 4.8727 (5.3441) Boundary_loss: 0.016440 (0.021401) Loss: 4.8892 (5.3655) +2025-09-10,23:41:04 | INFO | Train Epoch: 0 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 4.6866 (5.3075) Boundary_loss: 0.016333 (0.021119) Loss: 4.7030 (5.3287) +2025-09-10,23:42:13 | INFO | Train Epoch: 0 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 4.7814 (5.2799) Boundary_loss: 0.016228 (0.020862) Loss: 4.7976 (5.3007) +2025-09-10,23:43:23 | INFO | Train Epoch: 0 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 4.6633 (5.2490) Boundary_loss: 0.016311 (0.020634) Loss: 4.6796 (5.2697) +2025-09-10,23:44:32 | INFO | Train Epoch: 0 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 4.7003 (5.2229) Boundary_loss: 0.016205 (0.020423) Loss: 4.7165 (5.2433) +2025-09-10,23:45:41 | INFO | Train Epoch: 0 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 49.668 Boundary Ratio: 0.253 Contrastive_loss: 4.6134 (5.1952) Boundary_loss: 0.016193 (0.020231) Loss: 4.6296 (5.2154) +2025-09-10,23:46:50 | INFO | Train Epoch: 0 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 4.4968 (5.1648) Boundary_loss: 0.016131 (0.020053) Loss: 4.5129 (5.1849) +2025-09-10,23:48:00 | INFO | Train Epoch: 0 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 50.195 Boundary Ratio: 0.256 Contrastive_loss: 4.4905 (5.1367) Boundary_loss: 0.016303 (0.019897) Loss: 4.5069 (5.1566) +2025-09-10,23:49:09 | INFO | Train Epoch: 0 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 47.465 Boundary Ratio: 0.242 Contrastive_loss: 4.5603 (5.1137) Boundary_loss: 0.016171 (0.019747) Loss: 4.5765 (5.1334) +2025-09-10,23:50:18 | INFO | Train Epoch: 0 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 4.4455 (5.0880) Boundary_loss: 0.016172 (0.019610) Loss: 4.4617 (5.1076) +2025-09-10,23:51:27 | INFO | Train Epoch: 0 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.312 Boundary Ratio: 0.246 Contrastive_loss: 4.3592 (5.0610) Boundary_loss: 0.016242 (0.019485) Loss: 4.3754 (5.0805) +2025-09-10,23:52:36 | INFO | Train Epoch: 0 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 47.557 Boundary Ratio: 0.243 Contrastive_loss: 4.4795 (5.0402) Boundary_loss: 0.016050 (0.019363) Loss: 4.4956 (5.0596) +2025-09-10,23:53:45 | INFO | Train Epoch: 0 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 46.855 Boundary Ratio: 0.239 Contrastive_loss: 4.4766 (5.0208) Boundary_loss: 0.016689 (0.019270) Loss: 4.4933 (5.0401) +2025-09-10,23:54:54 | INFO | Train Epoch: 0 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 49.395 Boundary Ratio: 0.252 Contrastive_loss: 4.3149 (4.9973) Boundary_loss: 0.016361 (0.019173) Loss: 4.3312 (5.0164) +2025-09-10,23:56:03 | INFO | Train Epoch: 0 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.801 Boundary Ratio: 0.254 Contrastive_loss: 4.3144 (4.9752) Boundary_loss: 0.016338 (0.019082) Loss: 4.3307 (4.9943) +2025-09-10,23:57:13 | INFO | Train Epoch: 0 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 4.3100 (4.9544) Boundary_loss: 0.015846 (0.018981) Loss: 4.3258 (4.9734) +2025-09-10,23:58:22 | INFO | Train Epoch: 0 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 4.2342 (4.9326) Boundary_loss: 0.016161 (0.018895) Loss: 4.2504 (4.9515) +2025-09-10,23:59:31 | INFO | Train Epoch: 0 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.207 Boundary Ratio: 0.246 Contrastive_loss: 4.2740 (4.9132) Boundary_loss: 0.016161 (0.018815) Loss: 4.2901 (4.9321) +2025-09-11,00:00:40 | INFO | Train Epoch: 0 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 4.3289 (4.8965) Boundary_loss: 0.016075 (0.018737) Loss: 4.3450 (4.9153) +2025-09-11,00:01:49 | INFO | Train Epoch: 0 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 47.816 Boundary Ratio: 0.244 Contrastive_loss: 4.0837 (4.8740) Boundary_loss: 0.015980 (0.018660) Loss: 4.0997 (4.8926) +2025-09-11,00:02:58 | INFO | Train Epoch: 0 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 49.805 Boundary Ratio: 0.254 Contrastive_loss: 4.0177 (4.8508) Boundary_loss: 0.015897 (0.018585) Loss: 4.0336 (4.8694) +2025-09-11,00:04:07 | INFO | Train Epoch: 0 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 4.2191 (4.8342) Boundary_loss: 0.016094 (0.018520) Loss: 4.2352 (4.8527) +2025-09-11,00:05:16 | INFO | Train Epoch: 0 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 50.086 Boundary Ratio: 0.256 Contrastive_loss: 4.0037 (4.8129) Boundary_loss: 0.016223 (0.018461) Loss: 4.0199 (4.8314) +2025-09-11,00:06:25 | INFO | Train Epoch: 0 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 4.0520 (4.7939) Boundary_loss: 0.015931 (0.018398) Loss: 4.0679 (4.8123) +2025-09-11,00:07:34 | INFO | Train Epoch: 0 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 3.9199 (4.7726) Boundary_loss: 0.015964 (0.018338) Loss: 3.9358 (4.7909) +2025-09-11,00:08:43 | INFO | Train Epoch: 0 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 3.8141 (4.7497) Boundary_loss: 0.015760 (0.018277) Loss: 3.8299 (4.7680) +2025-09-11,00:09:52 | INFO | Train Epoch: 0 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 50.365 Boundary Ratio: 0.257 Contrastive_loss: 4.0954 (4.7345) Boundary_loss: 0.016051 (0.018225) Loss: 4.1115 (4.7528) +2025-09-11,00:11:01 | INFO | Train Epoch: 0 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 3.9684 (4.7171) Boundary_loss: 0.016020 (0.018175) Loss: 3.9845 (4.7353) +2025-09-11,00:12:10 | INFO | Train Epoch: 0 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 3.9558 (4.7002) Boundary_loss: 0.015961 (0.018126) Loss: 3.9718 (4.7183) +2025-09-11,00:13:19 | INFO | Train Epoch: 0 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 3.9187 (4.6832) Boundary_loss: 0.015891 (0.018077) Loss: 3.9346 (4.7013) +2025-09-11,00:14:28 | INFO | Train Epoch: 0 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 49.742 Boundary Ratio: 0.254 Contrastive_loss: 3.9854 (4.6684) Boundary_loss: 0.015924 (0.018031) Loss: 4.0013 (4.6864) +2025-09-11,00:15:37 | INFO | Train Epoch: 0 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 49.785 Boundary Ratio: 0.254 Contrastive_loss: 3.8370 (4.6510) Boundary_loss: 0.015803 (0.017985) Loss: 3.8528 (4.6690) +2025-09-11,00:16:46 | INFO | Train Epoch: 0 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 49.697 Boundary Ratio: 0.254 Contrastive_loss: 3.6953 (4.6315) Boundary_loss: 0.015898 (0.017942) Loss: 3.7112 (4.6495) +2025-09-11,00:17:55 | INFO | Train Epoch: 0 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 3.8826 (4.6166) Boundary_loss: 0.015945 (0.017902) Loss: 3.8986 (4.6345) +2025-09-11,00:19:04 | INFO | Train Epoch: 0 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 3.7121 (4.5988) Boundary_loss: 0.015924 (0.017864) Loss: 3.7280 (4.6167) +2025-09-11,00:20:12 | INFO | Train Epoch: 0 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 3.8404 (4.5842) Boundary_loss: 0.015873 (0.017825) Loss: 3.8562 (4.6021) +2025-09-11,00:21:21 | INFO | Train Epoch: 0 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 3.7998 (4.5694) Boundary_loss: 0.015714 (0.017786) Loss: 3.8155 (4.5872) +2025-09-11,00:22:30 | INFO | Train Epoch: 0 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.098 Boundary Ratio: 0.245 Contrastive_loss: 3.7958 (4.5551) Boundary_loss: 0.016013 (0.017753) Loss: 3.8118 (4.5729) +2025-09-11,00:23:39 | INFO | Train Epoch: 0 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 3.8175 (4.5417) Boundary_loss: 0.015863 (0.017718) Loss: 3.8334 (4.5594) +2025-09-11,00:24:48 | INFO | Train Epoch: 0 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 3.7465 (4.5275) Boundary_loss: 0.015687 (0.017682) Loss: 3.7622 (4.5452) +2025-09-11,00:25:57 | INFO | Train Epoch: 0 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 47.910 Boundary Ratio: 0.244 Contrastive_loss: 3.8041 (4.5148) Boundary_loss: 0.015942 (0.017652) Loss: 3.8200 (4.5325) +2025-09-11,00:27:06 | INFO | Train Epoch: 0 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 47.805 Boundary Ratio: 0.244 Contrastive_loss: 3.6839 (4.5005) Boundary_loss: 0.016005 (0.017623) Loss: 3.6999 (4.5181) +2025-09-11,00:28:15 | INFO | Train Epoch: 0 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 50.746 Boundary Ratio: 0.259 Contrastive_loss: 3.5718 (4.4847) Boundary_loss: 0.016208 (0.017599) Loss: 3.5881 (4.5023) +2025-09-11,00:29:24 | INFO | Train Epoch: 0 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.779 Boundary Ratio: 0.254 Contrastive_loss: 3.6519 (4.4709) Boundary_loss: 0.015856 (0.017570) Loss: 3.6677 (4.4884) +2025-09-11,00:30:33 | INFO | Train Epoch: 0 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 3.5347 (4.4555) Boundary_loss: 0.015836 (0.017542) Loss: 3.5505 (4.4731) +2025-09-11,00:31:42 | INFO | Train Epoch: 0 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 47.887 Boundary Ratio: 0.244 Contrastive_loss: 3.7258 (4.4437) Boundary_loss: 0.015879 (0.017515) Loss: 3.7417 (4.4613) +2025-09-11,00:32:50 | INFO | Train Epoch: 0 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 3.6653 (4.4314) Boundary_loss: 0.015821 (0.017488) Loss: 3.6811 (4.4489) +2025-09-11,00:33:59 | INFO | Train Epoch: 0 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 3.6673 (4.4195) Boundary_loss: 0.015991 (0.017465) Loss: 3.6833 (4.4369) +2025-09-11,00:35:08 | INFO | Train Epoch: 0 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 50.105 Boundary Ratio: 0.256 Contrastive_loss: 3.7565 (4.4093) Boundary_loss: 0.015863 (0.017440) Loss: 3.7724 (4.4267) +2025-09-11,00:36:17 | INFO | Train Epoch: 0 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 3.6866 (4.3983) Boundary_loss: 0.015871 (0.017416) Loss: 3.7024 (4.4157) +2025-09-11,00:37:26 | INFO | Train Epoch: 0 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 3.4302 (4.3839) Boundary_loss: 0.015915 (0.017394) Loss: 3.4461 (4.4012) +2025-09-11,00:38:34 | INFO | Train Epoch: 0 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 50.855 Boundary Ratio: 0.259 Contrastive_loss: 3.5683 (4.3719) Boundary_loss: 0.016050 (0.017374) Loss: 3.5844 (4.3892) +2025-09-11,00:39:43 | INFO | Train Epoch: 0 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 3.5499 (4.3599) Boundary_loss: 0.015774 (0.017351) Loss: 3.5657 (4.3773) +2025-09-11,00:40:52 | INFO | Train Epoch: 0 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 3.4857 (4.3475) Boundary_loss: 0.015909 (0.017330) Loss: 3.5016 (4.3648) +2025-09-11,00:42:01 | INFO | Train Epoch: 0 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 3.6028 (4.3370) Boundary_loss: 0.015780 (0.017308) Loss: 3.6186 (4.3543) +2025-09-11,00:43:10 | INFO | Train Epoch: 0 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 47.697 Boundary Ratio: 0.243 Contrastive_loss: 3.6242 (4.3271) Boundary_loss: 0.015787 (0.017287) Loss: 3.6400 (4.3444) +2025-09-11,00:44:19 | INFO | Train Epoch: 0 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 49.660 Boundary Ratio: 0.253 Contrastive_loss: 3.5326 (4.3162) Boundary_loss: 0.015697 (0.017265) Loss: 3.5483 (4.3335) +2025-09-11,00:45:28 | INFO | Train Epoch: 0 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 47.342 Boundary Ratio: 0.242 Contrastive_loss: 3.4790 (4.3049) Boundary_loss: 0.016086 (0.017250) Loss: 3.4951 (4.3221) +2025-09-11,00:46:37 | INFO | Train Epoch: 0 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.516 Boundary Ratio: 0.248 Contrastive_loss: 3.5404 (4.2947) Boundary_loss: 0.015422 (0.017225) Loss: 3.5558 (4.3119) +2025-09-11,00:47:46 | INFO | Train Epoch: 0 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.762 Boundary Ratio: 0.254 Contrastive_loss: 3.3910 (4.2828) Boundary_loss: 0.015839 (0.017207) Loss: 3.4068 (4.3000) +2025-09-11,00:48:54 | INFO | Train Epoch: 0 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 3.3655 (4.2709) Boundary_loss: 0.015730 (0.017188) Loss: 3.3812 (4.2881) +2025-09-11,00:50:03 | INFO | Train Epoch: 0 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 3.4560 (4.2604) Boundary_loss: 0.015662 (0.017168) Loss: 3.4717 (4.2776) +2025-09-11,00:51:12 | INFO | Train Epoch: 0 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 3.3452 (4.2488) Boundary_loss: 0.015729 (0.017150) Loss: 3.3609 (4.2660) +2025-09-11,00:52:21 | INFO | Train Epoch: 0 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 3.4136 (4.2384) Boundary_loss: 0.015753 (0.017133) Loss: 3.4294 (4.2555) +2025-09-11,00:53:30 | INFO | Train Epoch: 0 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 3.4088 (4.2282) Boundary_loss: 0.015904 (0.017117) Loss: 3.4247 (4.2453) +2025-09-11,00:54:39 | INFO | Train Epoch: 0 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 3.2361 (4.2161) Boundary_loss: 0.015829 (0.017102) Loss: 3.2519 (4.2332) +2025-09-11,00:55:48 | INFO | Train Epoch: 0 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 49.527 Boundary Ratio: 0.253 Contrastive_loss: 3.3177 (4.2052) Boundary_loss: 0.015748 (0.017085) Loss: 3.3335 (4.2223) +2025-09-11,00:56:57 | INFO | Train Epoch: 0 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 3.4905 (4.1967) Boundary_loss: 0.015831 (0.017070) Loss: 3.5063 (4.2138) +2025-09-11,00:58:06 | INFO | Train Epoch: 0 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 49.436 Boundary Ratio: 0.252 Contrastive_loss: 3.3986 (4.1873) Boundary_loss: 0.015612 (0.017053) Loss: 3.4142 (4.2044) +2025-09-11,00:59:14 | INFO | Train Epoch: 0 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 3.2817 (4.1768) Boundary_loss: 0.015666 (0.017037) Loss: 3.2974 (4.1939) +2025-09-11,01:00:23 | INFO | Train Epoch: 0 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 3.3188 (4.1670) Boundary_loss: 0.015643 (0.017021) Loss: 3.3344 (4.1840) +2025-09-11,01:01:32 | INFO | Train Epoch: 0 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 49.887 Boundary Ratio: 0.255 Contrastive_loss: 3.2661 (4.1567) Boundary_loss: 0.015687 (0.017006) Loss: 3.2818 (4.1737) +2025-09-11,01:02:41 | INFO | Train Epoch: 0 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 47.158 Boundary Ratio: 0.241 Contrastive_loss: 3.1952 (4.1459) Boundary_loss: 0.015735 (0.016992) Loss: 3.2109 (4.1629) +2025-09-11,01:03:50 | INFO | Train Epoch: 0 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 3.3954 (4.1376) Boundary_loss: 0.015689 (0.016977) Loss: 3.4111 (4.1545) +2025-09-11,01:04:59 | INFO | Train Epoch: 0 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 3.0837 (4.1260) Boundary_loss: 0.015647 (0.016963) Loss: 3.0994 (4.1430) +2025-09-11,01:06:07 | INFO | Train Epoch: 0 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 3.1397 (4.1153) Boundary_loss: 0.015704 (0.016949) Loss: 3.1554 (4.1322) +2025-09-11,01:07:16 | INFO | Train Epoch: 0 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 47.660 Boundary Ratio: 0.243 Contrastive_loss: 3.1927 (4.1054) Boundary_loss: 0.015650 (0.016935) Loss: 3.2083 (4.1223) +2025-09-11,01:08:25 | INFO | Train Epoch: 0 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 3.2452 (4.0962) Boundary_loss: 0.015616 (0.016921) Loss: 3.2608 (4.1131) +2025-09-11,01:09:34 | INFO | Train Epoch: 0 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.107 Boundary Ratio: 0.245 Contrastive_loss: 3.2169 (4.0869) Boundary_loss: 0.015690 (0.016908) Loss: 3.2325 (4.1039) +2025-09-11,01:10:43 | INFO | Train Epoch: 0 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 47.820 Boundary Ratio: 0.244 Contrastive_loss: 3.2346 (4.0781) Boundary_loss: 0.016053 (0.016899) Loss: 3.2507 (4.0950) +2025-09-11,01:11:52 | INFO | Train Epoch: 0 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 49.342 Boundary Ratio: 0.252 Contrastive_loss: 3.0756 (4.0677) Boundary_loss: 0.015792 (0.016888) Loss: 3.0914 (4.0846) +2025-09-11,01:13:01 | INFO | Train Epoch: 0 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 49.723 Boundary Ratio: 0.254 Contrastive_loss: 3.1628 (4.0585) Boundary_loss: 0.015678 (0.016875) Loss: 3.1784 (4.0754) +2025-09-11,01:14:10 | INFO | Train Epoch: 0 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 3.0860 (4.0487) Boundary_loss: 0.015702 (0.016863) Loss: 3.1017 (4.0655) +2025-09-11,01:15:18 | INFO | Train Epoch: 0 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 49.758 Boundary Ratio: 0.254 Contrastive_loss: 3.2425 (4.0406) Boundary_loss: 0.015852 (0.016853) Loss: 3.2584 (4.0575) +2025-09-11,01:16:27 | INFO | Train Epoch: 0 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 49.502 Boundary Ratio: 0.253 Contrastive_loss: 2.9082 (4.0294) Boundary_loss: 0.015861 (0.016843) Loss: 2.9241 (4.0462) +2025-09-11,01:17:36 | INFO | Train Epoch: 0 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 47.010 Boundary Ratio: 0.240 Contrastive_loss: 3.0986 (4.0203) Boundary_loss: 0.015847 (0.016834) Loss: 3.1145 (4.0371) +2025-09-11,01:18:45 | INFO | Train Epoch: 0 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 47.984 Boundary Ratio: 0.245 Contrastive_loss: 3.2406 (4.0127) Boundary_loss: 0.015664 (0.016822) Loss: 3.2563 (4.0295) +2025-09-11,01:19:53 | INFO | Train Epoch: 0 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.043 Boundary Ratio: 0.245 Contrastive_loss: 2.9715 (4.0027) Boundary_loss: 0.015514 (0.016810) Loss: 2.9870 (4.0195) +2025-09-11,01:21:02 | INFO | Train Epoch: 0 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 3.1781 (3.9948) Boundary_loss: 0.015704 (0.016799) Loss: 3.1938 (4.0116) +2025-09-11,01:22:11 | INFO | Train Epoch: 0 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 3.0756 (3.9862) Boundary_loss: 0.015762 (0.016789) Loss: 3.0914 (4.0030) +2025-09-11,01:23:20 | INFO | Train Epoch: 0 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 3.0622 (3.9775) Boundary_loss: 0.015634 (0.016779) Loss: 3.0779 (3.9943) +2025-09-11,01:24:29 | INFO | Train Epoch: 0 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 2.9168 (3.9677) Boundary_loss: 0.015797 (0.016770) Loss: 2.9326 (3.9845) +2025-09-11,01:25:38 | INFO | Train Epoch: 0 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 47.842 Boundary Ratio: 0.244 Contrastive_loss: 3.2532 (3.9612) Boundary_loss: 0.015739 (0.016760) Loss: 3.2690 (3.9779) +2025-09-11,01:26:46 | INFO | Train Epoch: 0 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 50.529 Boundary Ratio: 0.258 Contrastive_loss: 3.1057 (3.9534) Boundary_loss: 0.016010 (0.016753) Loss: 3.1218 (3.9701) +2025-09-11,01:27:55 | INFO | Train Epoch: 0 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 3.0000 (3.9448) Boundary_loss: 0.015657 (0.016743) Loss: 3.0157 (3.9615) +2025-09-11,01:29:04 | INFO | Train Epoch: 0 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.264 Boundary Ratio: 0.251 Contrastive_loss: 2.9548 (3.9360) Boundary_loss: 0.015619 (0.016733) Loss: 2.9704 (3.9527) +2025-09-11,01:30:13 | INFO | Train Epoch: 0 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 2.9045 (3.9268) Boundary_loss: 0.015690 (0.016724) Loss: 2.9202 (3.9435) +2025-09-11,01:31:22 | INFO | Train Epoch: 0 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 2.7673 (3.9167) Boundary_loss: 0.015662 (0.016715) Loss: 2.7830 (3.9334) +2025-09-11,01:32:31 | INFO | Train Epoch: 0 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.156 Boundary Ratio: 0.246 Contrastive_loss: 2.7510 (3.9065) Boundary_loss: 0.015672 (0.016706) Loss: 2.7667 (3.9232) +2025-09-11,01:33:40 | INFO | Train Epoch: 0 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.242 Boundary Ratio: 0.246 Contrastive_loss: 2.9369 (3.8982) Boundary_loss: 0.015683 (0.016697) Loss: 2.9525 (3.9149) +2025-09-11,01:34:48 | INFO | Train Epoch: 0 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 2.8714 (3.8894) Boundary_loss: 0.015610 (0.016688) Loss: 2.8870 (3.9061) +2025-09-11,01:35:57 | INFO | Train Epoch: 0 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 2.9478 (3.8814) Boundary_loss: 0.015719 (0.016679) Loss: 2.9635 (3.8981) +2025-09-11,01:37:06 | INFO | Train Epoch: 0 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 2.7738 (3.8721) Boundary_loss: 0.015600 (0.016670) Loss: 2.7894 (3.8888) +2025-09-11,01:38:15 | INFO | Train Epoch: 0 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 3.0143 (3.8649) Boundary_loss: 0.015579 (0.016661) Loss: 3.0299 (3.8816) +2025-09-11,01:39:23 | INFO | Train Epoch: 0 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 2.8466 (3.8565) Boundary_loss: 0.015624 (0.016653) Loss: 2.8622 (3.8732) +2025-09-11,01:40:32 | INFO | Train Epoch: 0 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.080 Boundary Ratio: 0.245 Contrastive_loss: 2.9704 (3.8493) Boundary_loss: 0.015588 (0.016644) Loss: 2.9860 (3.8659) +2025-09-11,01:41:41 | INFO | Train Epoch: 0 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 47.514 Boundary Ratio: 0.242 Contrastive_loss: 2.9937 (3.8423) Boundary_loss: 0.015697 (0.016636) Loss: 3.0094 (3.8589) +2025-09-11,01:42:50 | INFO | Train Epoch: 0 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 47.678 Boundary Ratio: 0.243 Contrastive_loss: 2.9413 (3.8350) Boundary_loss: 0.015842 (0.016630) Loss: 2.9571 (3.8517) +2025-09-11,01:43:59 | INFO | Train Epoch: 0 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 49.467 Boundary Ratio: 0.252 Contrastive_loss: 2.9327 (3.8278) Boundary_loss: 0.015475 (0.016621) Loss: 2.9482 (3.8444) +2025-09-11,01:45:08 | INFO | Train Epoch: 0 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 50.086 Boundary Ratio: 0.256 Contrastive_loss: 2.9039 (3.8205) Boundary_loss: 0.015798 (0.016614) Loss: 2.9197 (3.8371) +2025-09-11,01:46:16 | INFO | Train Epoch: 0 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 2.8401 (3.8128) Boundary_loss: 0.015495 (0.016605) Loss: 2.8556 (3.8294) +2025-09-11,01:47:25 | INFO | Train Epoch: 0 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 2.7511 (3.8045) Boundary_loss: 0.015374 (0.016596) Loss: 2.7665 (3.8211) +2025-09-11,01:48:34 | INFO | Train Epoch: 0 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 49.764 Boundary Ratio: 0.254 Contrastive_loss: 2.9401 (3.7978) Boundary_loss: 0.015782 (0.016589) Loss: 2.9558 (3.8144) +2025-09-11,01:49:42 | INFO | Train Epoch: 0 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 50.166 Boundary Ratio: 0.256 Contrastive_loss: 2.8742 (3.7907) Boundary_loss: 0.015693 (0.016582) Loss: 2.8899 (3.8073) +2025-09-11,01:50:51 | INFO | Train Epoch: 0 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 47.859 Boundary Ratio: 0.244 Contrastive_loss: 2.8569 (3.7835) Boundary_loss: 0.015717 (0.016576) Loss: 2.8727 (3.8001) +2025-09-11,01:52:00 | INFO | Train Epoch: 0 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 2.7998 (3.7761) Boundary_loss: 0.015585 (0.016568) Loss: 2.8154 (3.7927) +2025-09-11,01:53:09 | INFO | Train Epoch: 0 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 2.6920 (3.7679) Boundary_loss: 0.015602 (0.016561) Loss: 2.7076 (3.7845) +2025-09-11,01:54:17 | INFO | Train Epoch: 0 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.527 Boundary Ratio: 0.253 Contrastive_loss: 2.9332 (3.7617) Boundary_loss: 0.015772 (0.016555) Loss: 2.9490 (3.7783) +2025-09-11,01:55:26 | INFO | Train Epoch: 0 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 49.301 Boundary Ratio: 0.252 Contrastive_loss: 2.7008 (3.7539) Boundary_loss: 0.015460 (0.016547) Loss: 2.7162 (3.7704) +2025-09-11,01:56:35 | INFO | Train Epoch: 0 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 2.6343 (3.7456) Boundary_loss: 0.015454 (0.016539) Loss: 2.6498 (3.7622) +2025-09-11,01:57:44 | INFO | Train Epoch: 0 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 47.875 Boundary Ratio: 0.244 Contrastive_loss: 2.7569 (3.7384) Boundary_loss: 0.015634 (0.016532) Loss: 2.7725 (3.7549) +2025-09-11,01:58:52 | INFO | Train Epoch: 0 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.777 Boundary Ratio: 0.254 Contrastive_loss: 2.6550 (3.7306) Boundary_loss: 0.015546 (0.016525) Loss: 2.6705 (3.7471) +2025-09-11,02:00:01 | INFO | Train Epoch: 0 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 47.123 Boundary Ratio: 0.240 Contrastive_loss: 2.6019 (3.7224) Boundary_loss: 0.015718 (0.016519) Loss: 2.6176 (3.7390) +2025-09-11,02:01:10 | INFO | Train Epoch: 0 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 47.504 Boundary Ratio: 0.242 Contrastive_loss: 2.8255 (3.7160) Boundary_loss: 0.015558 (0.016513) Loss: 2.8411 (3.7325) +2025-09-11,02:02:18 | INFO | Train Epoch: 0 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 2.6025 (3.7081) Boundary_loss: 0.015486 (0.016505) Loss: 2.6179 (3.7246) +2025-09-11,02:03:27 | INFO | Train Epoch: 0 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 49.779 Boundary Ratio: 0.254 Contrastive_loss: 2.7574 (3.7014) Boundary_loss: 0.015816 (0.016500) Loss: 2.7732 (3.7179) +2025-09-11,02:04:36 | INFO | Train Epoch: 0 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 47.344 Boundary Ratio: 0.242 Contrastive_loss: 2.8047 (3.6952) Boundary_loss: 0.015646 (0.016495) Loss: 2.8203 (3.7117) +2025-09-11,02:05:45 | INFO | Train Epoch: 0 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.404 Boundary Ratio: 0.252 Contrastive_loss: 2.5786 (3.6874) Boundary_loss: 0.015643 (0.016489) Loss: 2.5942 (3.7039) +2025-09-11,02:06:53 | INFO | Train Epoch: 0 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 2.6118 (3.6800) Boundary_loss: 0.015429 (0.016481) Loss: 2.6273 (3.6965) +2025-09-11,02:08:02 | INFO | Train Epoch: 0 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 47.008 Boundary Ratio: 0.240 Contrastive_loss: 2.8837 (3.6745) Boundary_loss: 0.015774 (0.016476) Loss: 2.8994 (3.6910) +2025-09-11,02:09:11 | INFO | Train Epoch: 0 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 47.416 Boundary Ratio: 0.242 Contrastive_loss: 2.7603 (3.6683) Boundary_loss: 0.015512 (0.016470) Loss: 2.7758 (3.6848) +2025-09-11,02:10:20 | INFO | Train Epoch: 0 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 2.7361 (3.6620) Boundary_loss: 0.015578 (0.016464) Loss: 2.7517 (3.6785) +2025-09-11,02:11:28 | INFO | Train Epoch: 0 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 2.5891 (3.6548) Boundary_loss: 0.015540 (0.016458) Loss: 2.6047 (3.6713) +2025-09-11,02:12:37 | INFO | Train Epoch: 0 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 2.6408 (3.6481) Boundary_loss: 0.015531 (0.016451) Loss: 2.6563 (3.6645) +2025-09-11,02:13:46 | INFO | Train Epoch: 0 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 2.6053 (3.6412) Boundary_loss: 0.015269 (0.016444) Loss: 2.6206 (3.6576) +2025-09-11,02:14:55 | INFO | Train Epoch: 0 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 2.5943 (3.6343) Boundary_loss: 0.015444 (0.016437) Loss: 2.6097 (3.6507) +2025-09-11,02:16:03 | INFO | Train Epoch: 0 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 2.6887 (3.6281) Boundary_loss: 0.015483 (0.016431) Loss: 2.7042 (3.6445) +2025-09-11,02:17:12 | INFO | Train Epoch: 0 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 2.8280 (3.6229) Boundary_loss: 0.015711 (0.016426) Loss: 2.8437 (3.6393) +2025-09-11,02:18:21 | INFO | Train Epoch: 0 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.074 Boundary Ratio: 0.245 Contrastive_loss: 2.6912 (3.6169) Boundary_loss: 0.015581 (0.016421) Loss: 2.7068 (3.6333) +2025-09-11,02:19:29 | INFO | Train Epoch: 0 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 2.8167 (3.6118) Boundary_loss: 0.015533 (0.016415) Loss: 2.8323 (3.6282) +2025-09-11,02:20:38 | INFO | Train Epoch: 0 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 46.613 Boundary Ratio: 0.238 Contrastive_loss: 2.7093 (3.6060) Boundary_loss: 0.015914 (0.016412) Loss: 2.7252 (3.6224) +2025-09-11,02:21:47 | INFO | Train Epoch: 0 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 2.5114 (3.5991) Boundary_loss: 0.015540 (0.016406) Loss: 2.5269 (3.6155) +2025-09-11,02:22:55 | INFO | Train Epoch: 0 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.439 Boundary Ratio: 0.252 Contrastive_loss: 2.6254 (3.5930) Boundary_loss: 0.015764 (0.016402) Loss: 2.6412 (3.6094) +2025-09-11,02:24:04 | INFO | Train Epoch: 0 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 2.6200 (3.5869) Boundary_loss: 0.015499 (0.016397) Loss: 2.6355 (3.6033) +2025-09-11,02:25:13 | INFO | Train Epoch: 0 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 47.459 Boundary Ratio: 0.242 Contrastive_loss: 2.5343 (3.5803) Boundary_loss: 0.015669 (0.016392) Loss: 2.5500 (3.5967) +2025-09-11,02:26:21 | INFO | Train Epoch: 0 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.521 Boundary Ratio: 0.253 Contrastive_loss: 2.4824 (3.5736) Boundary_loss: 0.015551 (0.016387) Loss: 2.4979 (3.5899) +2025-09-11,02:27:30 | INFO | Train Epoch: 0 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 2.5495 (3.5673) Boundary_loss: 0.015578 (0.016382) Loss: 2.5650 (3.5837) +2025-09-11,02:28:39 | INFO | Train Epoch: 0 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.342 Boundary Ratio: 0.247 Contrastive_loss: 2.4711 (3.5606) Boundary_loss: 0.015394 (0.016376) Loss: 2.4865 (3.5770) +2025-09-11,02:29:47 | INFO | Train Epoch: 0 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 2.5861 (3.5547) Boundary_loss: 0.015483 (0.016371) Loss: 2.6016 (3.5711) +2025-09-11,02:30:56 | INFO | Train Epoch: 0 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 2.4468 (3.5480) Boundary_loss: 0.015462 (0.016365) Loss: 2.4622 (3.5644) +2025-09-11,02:32:05 | INFO | Train Epoch: 0 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.031 Boundary Ratio: 0.245 Contrastive_loss: 2.5779 (3.5422) Boundary_loss: 0.015590 (0.016360) Loss: 2.5935 (3.5586) +2025-09-11,02:33:13 | INFO | Train Epoch: 0 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 51.477 Boundary Ratio: 0.263 Contrastive_loss: 2.7771 (3.5376) Boundary_loss: 0.015955 (0.016358) Loss: 2.7931 (3.5540) +2025-09-11,02:34:22 | INFO | Train Epoch: 0 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 50.328 Boundary Ratio: 0.257 Contrastive_loss: 2.4905 (3.5315) Boundary_loss: 0.015834 (0.016355) Loss: 2.5063 (3.5478) +2025-09-11,02:35:30 | INFO | Train Epoch: 0 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 47.525 Boundary Ratio: 0.242 Contrastive_loss: 2.6129 (3.5260) Boundary_loss: 0.015448 (0.016350) Loss: 2.6283 (3.5424) +2025-09-11,02:36:39 | INFO | Train Epoch: 0 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 2.5503 (3.5203) Boundary_loss: 0.015490 (0.016345) Loss: 2.5658 (3.5367) +2025-09-11,02:37:48 | INFO | Train Epoch: 0 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.279 Boundary Ratio: 0.251 Contrastive_loss: 2.5651 (3.5148) Boundary_loss: 0.015636 (0.016340) Loss: 2.5807 (3.5311) +2025-09-11,02:38:56 | INFO | Train Epoch: 0 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 2.6496 (3.5098) Boundary_loss: 0.015475 (0.016335) Loss: 2.6651 (3.5261) +2025-09-11,02:40:05 | INFO | Train Epoch: 0 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 2.4723 (3.5038) Boundary_loss: 0.015451 (0.016330) Loss: 2.4878 (3.5202) +2025-09-11,02:41:14 | INFO | Train Epoch: 0 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 50.055 Boundary Ratio: 0.255 Contrastive_loss: 2.5537 (3.4984) Boundary_loss: 0.015460 (0.016325) Loss: 2.5691 (3.5147) +2025-09-11,02:42:22 | INFO | Train Epoch: 0 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 2.5105 (3.4928) Boundary_loss: 0.015603 (0.016321) Loss: 2.5261 (3.5091) +2025-09-11,02:43:31 | INFO | Train Epoch: 0 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 2.5160 (3.4873) Boundary_loss: 0.015426 (0.016316) Loss: 2.5314 (3.5036) +2025-09-11,02:44:40 | INFO | Train Epoch: 0 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 2.5435 (3.4820) Boundary_loss: 0.015397 (0.016311) Loss: 2.5589 (3.4983) +2025-09-11,02:45:48 | INFO | Train Epoch: 0 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 49.307 Boundary Ratio: 0.252 Contrastive_loss: 2.4987 (3.4765) Boundary_loss: 0.015481 (0.016306) Loss: 2.5142 (3.4928) +2025-09-11,02:46:57 | INFO | Train Epoch: 0 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 2.6238 (3.4717) Boundary_loss: 0.015489 (0.016302) Loss: 2.6393 (3.4880) +2025-09-11,02:48:05 | INFO | Train Epoch: 0 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.033 Boundary Ratio: 0.245 Contrastive_loss: 2.4951 (3.4663) Boundary_loss: 0.015584 (0.016298) Loss: 2.5106 (3.4826) +2025-09-11,02:49:14 | INFO | Train Epoch: 0 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 2.6337 (3.4618) Boundary_loss: 0.015526 (0.016294) Loss: 2.6493 (3.4781) +2025-09-11,02:50:23 | INFO | Train Epoch: 0 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.102 Boundary Ratio: 0.245 Contrastive_loss: 2.3952 (3.4559) Boundary_loss: 0.015426 (0.016289) Loss: 2.4106 (3.4722) +2025-09-11,02:51:31 | INFO | Train Epoch: 0 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 50.115 Boundary Ratio: 0.256 Contrastive_loss: 2.4295 (3.4504) Boundary_loss: 0.015650 (0.016285) Loss: 2.4451 (3.4666) +2025-09-11,02:52:40 | INFO | Train Epoch: 0 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 49.373 Boundary Ratio: 0.252 Contrastive_loss: 2.5061 (3.4452) Boundary_loss: 0.015318 (0.016280) Loss: 2.5214 (3.4615) +2025-09-11,02:53:48 | INFO | Train Epoch: 0 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 2.3974 (3.4396) Boundary_loss: 0.015627 (0.016277) Loss: 2.4131 (3.4559) +2025-09-11,02:54:57 | INFO | Train Epoch: 0 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 49.936 Boundary Ratio: 0.255 Contrastive_loss: 2.3897 (3.4340) Boundary_loss: 0.015404 (0.016272) Loss: 2.4051 (3.4503) +2025-09-11,02:56:05 | INFO | Train Epoch: 0 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 2.4556 (3.4288) Boundary_loss: 0.015425 (0.016268) Loss: 2.4710 (3.4451) +2025-09-11,02:57:14 | INFO | Train Epoch: 0 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 2.3529 (3.4231) Boundary_loss: 0.015322 (0.016263) Loss: 2.3682 (3.4394) +2025-09-11,02:58:22 | INFO | Train Epoch: 0 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 2.6207 (3.4189) Boundary_loss: 0.015414 (0.016258) Loss: 2.6361 (3.4351) +2025-09-11,02:59:31 | INFO | Train Epoch: 0 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.848 Boundary Ratio: 0.254 Contrastive_loss: 2.4844 (3.4140) Boundary_loss: 0.015278 (0.016253) Loss: 2.4997 (3.4302) +2025-09-11,03:00:39 | INFO | Train Epoch: 0 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 2.4957 (3.4092) Boundary_loss: 0.015597 (0.016250) Loss: 2.5113 (3.4255) +2025-09-11,03:01:48 | INFO | Train Epoch: 0 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 47.357 Boundary Ratio: 0.242 Contrastive_loss: 2.4412 (3.4042) Boundary_loss: 0.015855 (0.016247) Loss: 2.4571 (3.4204) +2025-09-11,03:02:56 | INFO | Train Epoch: 0 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 2.1470 (3.3977) Boundary_loss: 0.015502 (0.016244) Loss: 2.1625 (3.4140) +2025-09-11,03:04:05 | INFO | Train Epoch: 0 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.650 Boundary Ratio: 0.253 Contrastive_loss: 2.3933 (3.3926) Boundary_loss: 0.015464 (0.016240) Loss: 2.4088 (3.4088) +2025-09-11,03:05:14 | INFO | Train Epoch: 0 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 49.719 Boundary Ratio: 0.254 Contrastive_loss: 2.5886 (3.3885) Boundary_loss: 0.015408 (0.016235) Loss: 2.6040 (3.4047) +2025-09-11,03:06:22 | INFO | Train Epoch: 0 [10035712/26365952 (38%)] Avg Boundaries (per batch): 50.648 Boundary Ratio: 0.258 Contrastive_loss: 2.3885 (3.3834) Boundary_loss: 0.015764 (0.016233) Loss: 2.4043 (3.3996) +2025-09-11,03:07:31 | INFO | Train Epoch: 0 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.365 Boundary Ratio: 0.252 Contrastive_loss: 2.3736 (3.3783) Boundary_loss: 0.015248 (0.016228) Loss: 2.3888 (3.3945) +2025-09-11,03:08:39 | INFO | Train Epoch: 0 [10138112/26365952 (38%)] Avg Boundaries (per batch): 47.457 Boundary Ratio: 0.242 Contrastive_loss: 2.3583 (3.3732) Boundary_loss: 0.015421 (0.016224) Loss: 2.3738 (3.3894) +2025-09-11,03:09:48 | INFO | Train Epoch: 0 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.104 Boundary Ratio: 0.245 Contrastive_loss: 2.3342 (3.3680) Boundary_loss: 0.015459 (0.016220) Loss: 2.3497 (3.3842) +2025-09-11,03:10:56 | INFO | Train Epoch: 0 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 2.3020 (3.3627) Boundary_loss: 0.015380 (0.016216) Loss: 2.3174 (3.3789) +2025-09-11,03:12:05 | INFO | Train Epoch: 0 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.457 Boundary Ratio: 0.247 Contrastive_loss: 2.4909 (3.3583) Boundary_loss: 0.015432 (0.016212) Loss: 2.5063 (3.3746) +2025-09-11,03:13:13 | INFO | Train Epoch: 0 [10342912/26365952 (39%)] Avg Boundaries (per batch): 47.594 Boundary Ratio: 0.243 Contrastive_loss: 2.4309 (3.3538) Boundary_loss: 0.015498 (0.016209) Loss: 2.4464 (3.3700) +2025-09-11,03:14:21 | INFO | Train Epoch: 0 [10394112/26365952 (39%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 2.3622 (3.3489) Boundary_loss: 0.015370 (0.016204) Loss: 2.3776 (3.3651) +2025-09-11,03:15:30 | INFO | Train Epoch: 0 [10445312/26365952 (40%)] Avg Boundaries (per batch): 50.424 Boundary Ratio: 0.257 Contrastive_loss: 2.2888 (3.3437) Boundary_loss: 0.015482 (0.016201) Loss: 2.3043 (3.3599) +2025-09-11,03:16:38 | INFO | Train Epoch: 0 [10496512/26365952 (40%)] Avg Boundaries (per batch): 49.572 Boundary Ratio: 0.253 Contrastive_loss: 2.3555 (3.3389) Boundary_loss: 0.015418 (0.016197) Loss: 2.3709 (3.3551) +2025-09-11,03:17:47 | INFO | Train Epoch: 0 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 2.2535 (3.3337) Boundary_loss: 0.015636 (0.016194) Loss: 2.2691 (3.3499) +2025-09-11,03:18:55 | INFO | Train Epoch: 0 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 2.2123 (3.3283) Boundary_loss: 0.015392 (0.016191) Loss: 2.2277 (3.3445) +2025-09-11,03:20:04 | INFO | Train Epoch: 0 [10650112/26365952 (40%)] Avg Boundaries (per batch): 49.328 Boundary Ratio: 0.252 Contrastive_loss: 2.3654 (3.3237) Boundary_loss: 0.015260 (0.016186) Loss: 2.3807 (3.3399) +2025-09-11,03:21:12 | INFO | Train Epoch: 0 [10701312/26365952 (41%)] Avg Boundaries (per batch): 49.822 Boundary Ratio: 0.254 Contrastive_loss: 2.3282 (3.3190) Boundary_loss: 0.015547 (0.016183) Loss: 2.3438 (3.3351) +2025-09-11,03:22:21 | INFO | Train Epoch: 0 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.180 Boundary Ratio: 0.246 Contrastive_loss: 2.2479 (3.3139) Boundary_loss: 0.015505 (0.016180) Loss: 2.2634 (3.3301) +2025-09-11,03:23:29 | INFO | Train Epoch: 0 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 2.3855 (3.3095) Boundary_loss: 0.015301 (0.016176) Loss: 2.4008 (3.3257) +2025-09-11,03:24:38 | INFO | Train Epoch: 0 [10854912/26365952 (41%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 2.2282 (3.3044) Boundary_loss: 0.015426 (0.016172) Loss: 2.2437 (3.3206) +2025-09-11,03:25:46 | INFO | Train Epoch: 0 [10906112/26365952 (41%)] Avg Boundaries (per batch): 47.043 Boundary Ratio: 0.240 Contrastive_loss: 2.3509 (3.3000) Boundary_loss: 0.015578 (0.016169) Loss: 2.3664 (3.3161) +2025-09-11,03:26:55 | INFO | Train Epoch: 0 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 2.5381 (3.2964) Boundary_loss: 0.015548 (0.016166) Loss: 2.5537 (3.3126) +2025-09-11,03:28:03 | INFO | Train Epoch: 0 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 2.1950 (3.2913) Boundary_loss: 0.015509 (0.016163) Loss: 2.2105 (3.3075) +2025-09-11,03:29:12 | INFO | Train Epoch: 0 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.553 Boundary Ratio: 0.253 Contrastive_loss: 2.1727 (3.2862) Boundary_loss: 0.015296 (0.016159) Loss: 2.1880 (3.3023) +2025-09-11,03:30:20 | INFO | Train Epoch: 0 [11110912/26365952 (42%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 2.4304 (3.2823) Boundary_loss: 0.015501 (0.016156) Loss: 2.4459 (3.2984) +2025-09-11,03:31:28 | INFO | Train Epoch: 0 [11162112/26365952 (42%)] Avg Boundaries (per batch): 49.883 Boundary Ratio: 0.255 Contrastive_loss: 2.4218 (3.2783) Boundary_loss: 0.015452 (0.016153) Loss: 2.4373 (3.2945) +2025-09-11,03:32:37 | INFO | Train Epoch: 0 [11213312/26365952 (43%)] Avg Boundaries (per batch): 47.971 Boundary Ratio: 0.245 Contrastive_loss: 2.2440 (3.2736) Boundary_loss: 0.015475 (0.016150) Loss: 2.2595 (3.2898) +2025-09-11,03:33:45 | INFO | Train Epoch: 0 [11264512/26365952 (43%)] Avg Boundaries (per batch): 50.344 Boundary Ratio: 0.257 Contrastive_loss: 2.3909 (3.2696) Boundary_loss: 0.015569 (0.016148) Loss: 2.4065 (3.2858) +2025-09-11,03:34:53 | INFO | Train Epoch: 0 [11315712/26365952 (43%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 2.2335 (3.2650) Boundary_loss: 0.015379 (0.016144) Loss: 2.2488 (3.2811) +2025-09-11,03:36:02 | INFO | Train Epoch: 0 [11366912/26365952 (43%)] Avg Boundaries (per batch): 47.809 Boundary Ratio: 0.244 Contrastive_loss: 2.1488 (3.2600) Boundary_loss: 0.015461 (0.016141) Loss: 2.1642 (3.2761) +2025-09-11,03:37:10 | INFO | Train Epoch: 0 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 2.2518 (3.2555) Boundary_loss: 0.015324 (0.016137) Loss: 2.2671 (3.2716) +2025-09-11,03:38:19 | INFO | Train Epoch: 0 [11469312/26365952 (44%)] Avg Boundaries (per batch): 49.553 Boundary Ratio: 0.253 Contrastive_loss: 2.2644 (3.2510) Boundary_loss: 0.015441 (0.016134) Loss: 2.2798 (3.2672) +2025-09-11,03:39:27 | INFO | Train Epoch: 0 [11520512/26365952 (44%)] Avg Boundaries (per batch): 49.637 Boundary Ratio: 0.253 Contrastive_loss: 2.2300 (3.2465) Boundary_loss: 0.015403 (0.016131) Loss: 2.2454 (3.2627) +2025-09-11,03:40:36 | INFO | Train Epoch: 0 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 2.3013 (3.2424) Boundary_loss: 0.015437 (0.016128) Loss: 2.3168 (3.2585) +2025-09-11,03:41:44 | INFO | Train Epoch: 0 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 2.1549 (3.2376) Boundary_loss: 0.015489 (0.016125) Loss: 2.1704 (3.2537) +2025-09-11,03:42:53 | INFO | Train Epoch: 0 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 2.3202 (3.2336) Boundary_loss: 0.015368 (0.016122) Loss: 2.3356 (3.2497) +2025-09-11,03:44:01 | INFO | Train Epoch: 0 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 2.1080 (3.2287) Boundary_loss: 0.015350 (0.016118) Loss: 2.1233 (3.2448) +2025-09-11,03:45:10 | INFO | Train Epoch: 0 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 2.0528 (3.2236) Boundary_loss: 0.015470 (0.016116) Loss: 2.0682 (3.2397) +2025-09-11,03:46:18 | INFO | Train Epoch: 0 [11827712/26365952 (45%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 2.3310 (3.2198) Boundary_loss: 0.015425 (0.016113) Loss: 2.3464 (3.2359) +2025-09-11,03:47:26 | INFO | Train Epoch: 0 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 2.2738 (3.2157) Boundary_loss: 0.015346 (0.016109) Loss: 2.2891 (3.2318) +2025-09-11,03:48:35 | INFO | Train Epoch: 0 [11930112/26365952 (45%)] Avg Boundaries (per batch): 50.664 Boundary Ratio: 0.258 Contrastive_loss: 2.3805 (3.2121) Boundary_loss: 0.015754 (0.016108) Loss: 2.3963 (3.2282) +2025-09-11,03:49:43 | INFO | Train Epoch: 0 [11981312/26365952 (45%)] Avg Boundaries (per batch): 50.008 Boundary Ratio: 0.255 Contrastive_loss: 1.9719 (3.2069) Boundary_loss: 0.015444 (0.016105) Loss: 1.9873 (3.2230) +2025-09-11,03:50:52 | INFO | Train Epoch: 0 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 2.1398 (3.2023) Boundary_loss: 0.015443 (0.016102) Loss: 2.1552 (3.2184) +2025-09-11,03:52:00 | INFO | Train Epoch: 0 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.033 Boundary Ratio: 0.245 Contrastive_loss: 2.1314 (3.1978) Boundary_loss: 0.015576 (0.016100) Loss: 2.1470 (3.2139) +2025-09-11,03:53:09 | INFO | Train Epoch: 0 [12134912/26365952 (46%)] Avg Boundaries (per batch): 49.416 Boundary Ratio: 0.252 Contrastive_loss: 2.2014 (3.1936) Boundary_loss: 0.015307 (0.016097) Loss: 2.2167 (3.2097) +2025-09-11,03:54:17 | INFO | Train Epoch: 0 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 2.2090 (3.1895) Boundary_loss: 0.015403 (0.016094) Loss: 2.2244 (3.2056) +2025-09-11,03:55:26 | INFO | Train Epoch: 0 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.582 Boundary Ratio: 0.253 Contrastive_loss: 2.1727 (3.1853) Boundary_loss: 0.015399 (0.016091) Loss: 2.1881 (3.2014) +2025-09-11,03:56:34 | INFO | Train Epoch: 0 [12288512/26365952 (47%)] Avg Boundaries (per batch): 49.566 Boundary Ratio: 0.253 Contrastive_loss: 2.1106 (3.1808) Boundary_loss: 0.015441 (0.016088) Loss: 2.1260 (3.1969) +2025-09-11,03:57:42 | INFO | Train Epoch: 0 [12339712/26365952 (47%)] Avg Boundaries (per batch): 49.525 Boundary Ratio: 0.253 Contrastive_loss: 2.1079 (3.1764) Boundary_loss: 0.015566 (0.016086) Loss: 2.1235 (3.1925) +2025-09-11,03:58:51 | INFO | Train Epoch: 0 [12390912/26365952 (47%)] Avg Boundaries (per batch): 50.049 Boundary Ratio: 0.255 Contrastive_loss: 2.1167 (3.1720) Boundary_loss: 0.015468 (0.016084) Loss: 2.1321 (3.1881) +2025-09-11,03:59:59 | INFO | Train Epoch: 0 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 2.2000 (3.1680) Boundary_loss: 0.015287 (0.016080) Loss: 2.2152 (3.1841) +2025-09-11,04:01:08 | INFO | Train Epoch: 0 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 2.0679 (3.1635) Boundary_loss: 0.015407 (0.016078) Loss: 2.0833 (3.1796) +2025-09-11,04:02:16 | INFO | Train Epoch: 0 [12544512/26365952 (48%)] Avg Boundaries (per batch): 49.754 Boundary Ratio: 0.254 Contrastive_loss: 2.0106 (3.1589) Boundary_loss: 0.015610 (0.016076) Loss: 2.0262 (3.1749) +2025-09-11,04:03:24 | INFO | Train Epoch: 0 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 2.2121 (3.1550) Boundary_loss: 0.015322 (0.016073) Loss: 2.2274 (3.1711) +2025-09-11,04:04:32 | INFO | Train Epoch: 0 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 2.1483 (3.1510) Boundary_loss: 0.015423 (0.016070) Loss: 2.1638 (3.1670) +2025-09-11,04:05:41 | INFO | Train Epoch: 0 [12698112/26365952 (48%)] Avg Boundaries (per batch): 47.596 Boundary Ratio: 0.243 Contrastive_loss: 2.1802 (3.1471) Boundary_loss: 0.015327 (0.016067) Loss: 2.1955 (3.1631) +2025-09-11,04:06:49 | INFO | Train Epoch: 0 [12749312/26365952 (48%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 2.1530 (3.1431) Boundary_loss: 0.015506 (0.016065) Loss: 2.1685 (3.1592) +2025-09-11,04:07:57 | INFO | Train Epoch: 0 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.354 Boundary Ratio: 0.247 Contrastive_loss: 2.1372 (3.1391) Boundary_loss: 0.015342 (0.016062) Loss: 2.1526 (3.1551) +2025-09-11,04:09:06 | INFO | Train Epoch: 0 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 2.1129 (3.1350) Boundary_loss: 0.015443 (0.016059) Loss: 2.1283 (3.1511) +2025-09-11,04:10:14 | INFO | Train Epoch: 0 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 1.9636 (3.1304) Boundary_loss: 0.015418 (0.016057) Loss: 1.9790 (3.1464) +2025-09-11,04:11:22 | INFO | Train Epoch: 0 [12954112/26365952 (49%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 2.2687 (3.1270) Boundary_loss: 0.015398 (0.016054) Loss: 2.2841 (3.1430) +2025-09-11,04:12:31 | INFO | Train Epoch: 0 [13005312/26365952 (49%)] Avg Boundaries (per batch): 49.867 Boundary Ratio: 0.254 Contrastive_loss: 2.2129 (3.1234) Boundary_loss: 0.015382 (0.016052) Loss: 2.2283 (3.1395) +2025-09-11,04:13:39 | INFO | Train Epoch: 0 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 2.1048 (3.1194) Boundary_loss: 0.015421 (0.016049) Loss: 2.1202 (3.1355) +2025-09-11,04:14:47 | INFO | Train Epoch: 0 [13107712/26365952 (50%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 2.1364 (3.1156) Boundary_loss: 0.015402 (0.016047) Loss: 2.1519 (3.1316) +2025-09-11,04:15:56 | INFO | Train Epoch: 0 [13158912/26365952 (50%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 2.2836 (3.1124) Boundary_loss: 0.015356 (0.016044) Loss: 2.2989 (3.1284) +2025-09-11,04:17:04 | INFO | Train Epoch: 0 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 2.0347 (3.1082) Boundary_loss: 0.015315 (0.016041) Loss: 2.0500 (3.1243) +2025-09-11,04:18:13 | INFO | Train Epoch: 0 [13261312/26365952 (50%)] Avg Boundaries (per batch): 47.908 Boundary Ratio: 0.244 Contrastive_loss: 1.9984 (3.1039) Boundary_loss: 0.015151 (0.016038) Loss: 2.0136 (3.1200) +2025-09-11,04:19:21 | INFO | Train Epoch: 0 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 2.1917 (3.1004) Boundary_loss: 0.015551 (0.016036) Loss: 2.2073 (3.1165) +2025-09-11,04:20:29 | INFO | Train Epoch: 0 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 2.1006 (3.0966) Boundary_loss: 0.015349 (0.016033) Loss: 2.1159 (3.1127) +2025-09-11,04:21:37 | INFO | Train Epoch: 0 [13414912/26365952 (51%)] Avg Boundaries (per batch): 47.977 Boundary Ratio: 0.245 Contrastive_loss: 2.0729 (3.0927) Boundary_loss: 0.015185 (0.016030) Loss: 2.0881 (3.1088) +2025-09-11,04:22:46 | INFO | Train Epoch: 0 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.053 Boundary Ratio: 0.245 Contrastive_loss: 1.8951 (3.0882) Boundary_loss: 0.015372 (0.016028) Loss: 1.9105 (3.1042) +2025-09-11,04:23:54 | INFO | Train Epoch: 0 [13517312/26365952 (51%)] Avg Boundaries (per batch): 49.697 Boundary Ratio: 0.254 Contrastive_loss: 2.2307 (3.0850) Boundary_loss: 0.015338 (0.016025) Loss: 2.2460 (3.1010) +2025-09-11,04:25:03 | INFO | Train Epoch: 0 [13568512/26365952 (51%)] Avg Boundaries (per batch): 50.439 Boundary Ratio: 0.257 Contrastive_loss: 2.0426 (3.0810) Boundary_loss: 0.015528 (0.016023) Loss: 2.0582 (3.0971) +2025-09-11,04:26:11 | INFO | Train Epoch: 0 [13619712/26365952 (52%)] Avg Boundaries (per batch): 49.965 Boundary Ratio: 0.255 Contrastive_loss: 1.9742 (3.0769) Boundary_loss: 0.015480 (0.016021) Loss: 1.9897 (3.0929) +2025-09-11,04:27:19 | INFO | Train Epoch: 0 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 2.0045 (3.0729) Boundary_loss: 0.015193 (0.016018) Loss: 2.0197 (3.0889) +2025-09-11,04:28:27 | INFO | Train Epoch: 0 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 2.1392 (3.0694) Boundary_loss: 0.015330 (0.016015) Loss: 2.1545 (3.0854) +2025-09-11,04:29:36 | INFO | Train Epoch: 0 [13773312/26365952 (52%)] Avg Boundaries (per batch): 49.635 Boundary Ratio: 0.253 Contrastive_loss: 2.0344 (3.0656) Boundary_loss: 0.015251 (0.016013) Loss: 2.0496 (3.0816) +2025-09-11,04:30:44 | INFO | Train Epoch: 0 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 2.0304 (3.0618) Boundary_loss: 0.015468 (0.016011) Loss: 2.0458 (3.0778) +2025-09-11,04:31:52 | INFO | Train Epoch: 0 [13875712/26365952 (53%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 2.0647 (3.0581) Boundary_loss: 0.015335 (0.016008) Loss: 2.0801 (3.0741) +2025-09-11,04:33:01 | INFO | Train Epoch: 0 [13926912/26365952 (53%)] Avg Boundaries (per batch): 47.428 Boundary Ratio: 0.242 Contrastive_loss: 2.0572 (3.0544) Boundary_loss: 0.015469 (0.016006) Loss: 2.0726 (3.0704) +2025-09-11,04:34:09 | INFO | Train Epoch: 0 [13978112/26365952 (53%)] Avg Boundaries (per batch): 49.297 Boundary Ratio: 0.252 Contrastive_loss: 2.1788 (3.0512) Boundary_loss: 0.015319 (0.016004) Loss: 2.1942 (3.0673) +2025-09-11,04:35:17 | INFO | Train Epoch: 0 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 1.9749 (3.0473) Boundary_loss: 0.015287 (0.016001) Loss: 1.9902 (3.0633) +2025-09-11,04:36:26 | INFO | Train Epoch: 0 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 2.0235 (3.0436) Boundary_loss: 0.015408 (0.015999) Loss: 2.0389 (3.0596) +2025-09-11,04:37:34 | INFO | Train Epoch: 0 [14131712/26365952 (54%)] Avg Boundaries (per batch): 50.434 Boundary Ratio: 0.257 Contrastive_loss: 2.0077 (3.0399) Boundary_loss: 0.015569 (0.015997) Loss: 2.0233 (3.0559) +2025-09-11,04:38:42 | INFO | Train Epoch: 0 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.9761 (3.0361) Boundary_loss: 0.015270 (0.015995) Loss: 1.9914 (3.0521) +2025-09-11,04:39:51 | INFO | Train Epoch: 0 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.768 Boundary Ratio: 0.254 Contrastive_loss: 1.8089 (3.0317) Boundary_loss: 0.015637 (0.015993) Loss: 1.8245 (3.0477) +2025-09-11,04:40:59 | INFO | Train Epoch: 0 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 1.9710 (3.0279) Boundary_loss: 0.015359 (0.015991) Loss: 1.9864 (3.0439) +2025-09-11,04:42:07 | INFO | Train Epoch: 0 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 1.9774 (3.0241) Boundary_loss: 0.015389 (0.015989) Loss: 1.9928 (3.0401) +2025-09-11,04:43:16 | INFO | Train Epoch: 0 [14387712/26365952 (55%)] Avg Boundaries (per batch): 47.826 Boundary Ratio: 0.244 Contrastive_loss: 2.0161 (3.0206) Boundary_loss: 0.015426 (0.015987) Loss: 2.0316 (3.0365) +2025-09-11,04:44:24 | INFO | Train Epoch: 0 [14438912/26365952 (55%)] Avg Boundaries (per batch): 50.107 Boundary Ratio: 0.256 Contrastive_loss: 2.0977 (3.0173) Boundary_loss: 0.015380 (0.015985) Loss: 2.1131 (3.0333) +2025-09-11,04:45:32 | INFO | Train Epoch: 0 [14490112/26365952 (55%)] Avg Boundaries (per batch): 49.758 Boundary Ratio: 0.254 Contrastive_loss: 1.7965 (3.0130) Boundary_loss: 0.015423 (0.015983) Loss: 1.8119 (3.0290) +2025-09-11,04:46:40 | INFO | Train Epoch: 0 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 1.9737 (3.0094) Boundary_loss: 0.015404 (0.015981) Loss: 1.9891 (3.0253) +2025-09-11,04:47:49 | INFO | Train Epoch: 0 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.9911 (3.0058) Boundary_loss: 0.015269 (0.015978) Loss: 2.0064 (3.0218) +2025-09-11,04:48:57 | INFO | Train Epoch: 0 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.904 Boundary Ratio: 0.255 Contrastive_loss: 1.8815 (3.0019) Boundary_loss: 0.015585 (0.015977) Loss: 1.8971 (3.0179) +2025-09-11,04:50:05 | INFO | Train Epoch: 0 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.246 Boundary Ratio: 0.246 Contrastive_loss: 2.1761 (2.9990) Boundary_loss: 0.015275 (0.015974) Loss: 2.1914 (3.0150) +2025-09-11,04:51:14 | INFO | Train Epoch: 0 [14746112/26365952 (56%)] Avg Boundaries (per batch): 49.486 Boundary Ratio: 0.252 Contrastive_loss: 2.0530 (2.9957) Boundary_loss: 0.015060 (0.015971) Loss: 2.0680 (3.0117) +2025-09-11,04:52:22 | INFO | Train Epoch: 0 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 1.9174 (2.9920) Boundary_loss: 0.015097 (0.015968) Loss: 1.9325 (3.0080) +2025-09-11,04:53:30 | INFO | Train Epoch: 0 [14848512/26365952 (56%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 2.1075 (2.9890) Boundary_loss: 0.015384 (0.015966) Loss: 2.1229 (3.0049) +2025-09-11,04:54:38 | INFO | Train Epoch: 0 [14899712/26365952 (57%)] Avg Boundaries (per batch): 49.828 Boundary Ratio: 0.254 Contrastive_loss: 2.0640 (2.9858) Boundary_loss: 0.015558 (0.015965) Loss: 2.0796 (3.0018) +2025-09-11,04:55:47 | INFO | Train Epoch: 0 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.170 Boundary Ratio: 0.246 Contrastive_loss: 1.9684 (2.9823) Boundary_loss: 0.015187 (0.015962) Loss: 1.9836 (2.9983) +2025-09-11,04:56:55 | INFO | Train Epoch: 0 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.215 Boundary Ratio: 0.246 Contrastive_loss: 2.0425 (2.9791) Boundary_loss: 0.015059 (0.015959) Loss: 2.0576 (2.9951) +2025-09-11,04:58:03 | INFO | Train Epoch: 0 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 2.0227 (2.9759) Boundary_loss: 0.015199 (0.015957) Loss: 2.0379 (2.9919) +2025-09-11,04:59:12 | INFO | Train Epoch: 0 [15104512/26365952 (57%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 1.9931 (2.9726) Boundary_loss: 0.015243 (0.015954) Loss: 2.0084 (2.9885) +2025-09-11,05:00:20 | INFO | Train Epoch: 0 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 2.1121 (2.9697) Boundary_loss: 0.015245 (0.015952) Loss: 2.1274 (2.9856) +2025-09-11,05:01:28 | INFO | Train Epoch: 0 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 1.9587 (2.9663) Boundary_loss: 0.015251 (0.015949) Loss: 1.9739 (2.9822) +2025-09-11,05:02:36 | INFO | Train Epoch: 0 [15258112/26365952 (58%)] Avg Boundaries (per batch): 47.938 Boundary Ratio: 0.245 Contrastive_loss: 1.9054 (2.9627) Boundary_loss: 0.015267 (0.015947) Loss: 1.9207 (2.9787) +2025-09-11,05:03:44 | INFO | Train Epoch: 0 [15309312/26365952 (58%)] Avg Boundaries (per batch): 50.119 Boundary Ratio: 0.256 Contrastive_loss: 1.8919 (2.9592) Boundary_loss: 0.015428 (0.015945) Loss: 1.9073 (2.9751) +2025-09-11,05:04:53 | INFO | Train Epoch: 0 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 1.9135 (2.9557) Boundary_loss: 0.015349 (0.015943) Loss: 1.9289 (2.9716) +2025-09-11,05:06:01 | INFO | Train Epoch: 0 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 2.0105 (2.9526) Boundary_loss: 0.015220 (0.015941) Loss: 2.0257 (2.9685) +2025-09-11,05:07:09 | INFO | Train Epoch: 0 [15462912/26365952 (59%)] Avg Boundaries (per batch): 49.762 Boundary Ratio: 0.254 Contrastive_loss: 2.0629 (2.9496) Boundary_loss: 0.015378 (0.015939) Loss: 2.0783 (2.9656) +2025-09-11,05:08:17 | INFO | Train Epoch: 0 [15514112/26365952 (59%)] Avg Boundaries (per batch): 47.541 Boundary Ratio: 0.243 Contrastive_loss: 1.8358 (2.9460) Boundary_loss: 0.015364 (0.015937) Loss: 1.8512 (2.9619) +2025-09-11,05:09:26 | INFO | Train Epoch: 0 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 2.0599 (2.9431) Boundary_loss: 0.015372 (0.015935) Loss: 2.0752 (2.9590) +2025-09-11,05:10:34 | INFO | Train Epoch: 0 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 1.9225 (2.9397) Boundary_loss: 0.015108 (0.015933) Loss: 1.9376 (2.9557) +2025-09-11,05:11:42 | INFO | Train Epoch: 0 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 1.7955 (2.9360) Boundary_loss: 0.015314 (0.015931) Loss: 1.8108 (2.9519) +2025-09-11,05:12:50 | INFO | Train Epoch: 0 [15718912/26365952 (60%)] Avg Boundaries (per batch): 49.566 Boundary Ratio: 0.253 Contrastive_loss: 1.7705 (2.9322) Boundary_loss: 0.015416 (0.015929) Loss: 1.7859 (2.9481) +2025-09-11,05:13:59 | INFO | Train Epoch: 0 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.021 Boundary Ratio: 0.245 Contrastive_loss: 2.0466 (2.9293) Boundary_loss: 0.015217 (0.015927) Loss: 2.0618 (2.9453) +2025-09-11,05:15:07 | INFO | Train Epoch: 0 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 1.9999 (2.9263) Boundary_loss: 0.015156 (0.015924) Loss: 2.0150 (2.9423) +2025-09-11,05:16:15 | INFO | Train Epoch: 0 [15872512/26365952 (60%)] Avg Boundaries (per batch): 49.775 Boundary Ratio: 0.254 Contrastive_loss: 2.0427 (2.9235) Boundary_loss: 0.015542 (0.015923) Loss: 2.0583 (2.9394) +2025-09-11,05:17:23 | INFO | Train Epoch: 0 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 1.9456 (2.9204) Boundary_loss: 0.015240 (0.015921) Loss: 1.9609 (2.9363) +2025-09-11,05:18:31 | INFO | Train Epoch: 0 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 1.9037 (2.9171) Boundary_loss: 0.015219 (0.015919) Loss: 1.9189 (2.9330) +2025-09-11,05:19:40 | INFO | Train Epoch: 0 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.338 Boundary Ratio: 0.247 Contrastive_loss: 1.8624 (2.9138) Boundary_loss: 0.015179 (0.015916) Loss: 1.8776 (2.9297) +2025-09-11,05:20:48 | INFO | Train Epoch: 0 [16077312/26365952 (61%)] Avg Boundaries (per batch): 47.549 Boundary Ratio: 0.243 Contrastive_loss: 2.0204 (2.9109) Boundary_loss: 0.015563 (0.015915) Loss: 2.0360 (2.9268) +2025-09-11,05:21:56 | INFO | Train Epoch: 0 [16128512/26365952 (61%)] Avg Boundaries (per batch): 50.336 Boundary Ratio: 0.257 Contrastive_loss: 1.9960 (2.9080) Boundary_loss: 0.015356 (0.015913) Loss: 2.0114 (2.9239) +2025-09-11,05:23:04 | INFO | Train Epoch: 0 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 1.8261 (2.9046) Boundary_loss: 0.015206 (0.015911) Loss: 1.8413 (2.9205) +2025-09-11,05:24:12 | INFO | Train Epoch: 0 [16230912/26365952 (62%)] Avg Boundaries (per batch): 47.812 Boundary Ratio: 0.244 Contrastive_loss: 2.0280 (2.9019) Boundary_loss: 0.015364 (0.015909) Loss: 2.0434 (2.9178) +2025-09-11,05:25:21 | INFO | Train Epoch: 0 [16282112/26365952 (62%)] Avg Boundaries (per batch): 49.539 Boundary Ratio: 0.253 Contrastive_loss: 1.7742 (2.8983) Boundary_loss: 0.015030 (0.015907) Loss: 1.7893 (2.9142) +2025-09-11,05:26:29 | INFO | Train Epoch: 0 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.8552 (2.8951) Boundary_loss: 0.015184 (0.015904) Loss: 1.8704 (2.9110) +2025-09-11,05:27:37 | INFO | Train Epoch: 0 [16384512/26365952 (62%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 1.9299 (2.8921) Boundary_loss: 0.015347 (0.015903) Loss: 1.9453 (2.9080) +2025-09-11,05:28:46 | INFO | Train Epoch: 0 [16435712/26365952 (62%)] Avg Boundaries (per batch): 49.932 Boundary Ratio: 0.255 Contrastive_loss: 2.0078 (2.8893) Boundary_loss: 0.015205 (0.015901) Loss: 2.0230 (2.9052) +2025-09-11,05:29:54 | INFO | Train Epoch: 0 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.555 Boundary Ratio: 0.253 Contrastive_loss: 2.0381 (2.8867) Boundary_loss: 0.015338 (0.015899) Loss: 2.0534 (2.9026) +2025-09-11,05:31:02 | INFO | Train Epoch: 0 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 1.6588 (2.8829) Boundary_loss: 0.015303 (0.015897) Loss: 1.6741 (2.8988) +2025-09-11,05:32:10 | INFO | Train Epoch: 0 [16589312/26365952 (63%)] Avg Boundaries (per batch): 49.473 Boundary Ratio: 0.252 Contrastive_loss: 1.9816 (2.8801) Boundary_loss: 0.015324 (0.015895) Loss: 1.9970 (2.8960) +2025-09-11,05:33:18 | INFO | Train Epoch: 0 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 1.8741 (2.8770) Boundary_loss: 0.015372 (0.015894) Loss: 1.8894 (2.8929) +2025-09-11,05:34:27 | INFO | Train Epoch: 0 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 1.8184 (2.8738) Boundary_loss: 0.015134 (0.015891) Loss: 1.8335 (2.8897) +2025-09-11,05:35:35 | INFO | Train Epoch: 0 [16742912/26365952 (64%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 1.8982 (2.8708) Boundary_loss: 0.015236 (0.015889) Loss: 1.9134 (2.8867) +2025-09-11,05:36:43 | INFO | Train Epoch: 0 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.027 Boundary Ratio: 0.245 Contrastive_loss: 1.9825 (2.8681) Boundary_loss: 0.015325 (0.015888) Loss: 1.9979 (2.8840) +2025-09-11,05:37:51 | INFO | Train Epoch: 0 [16845312/26365952 (64%)] Avg Boundaries (per batch): 49.660 Boundary Ratio: 0.253 Contrastive_loss: 1.8684 (2.8651) Boundary_loss: 0.015105 (0.015885) Loss: 1.8835 (2.8810) +2025-09-11,05:38:59 | INFO | Train Epoch: 0 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 1.9575 (2.8624) Boundary_loss: 0.015120 (0.015883) Loss: 1.9727 (2.8782) +2025-09-11,05:40:08 | INFO | Train Epoch: 0 [16947712/26365952 (64%)] Avg Boundaries (per batch): 49.732 Boundary Ratio: 0.254 Contrastive_loss: 1.9742 (2.8597) Boundary_loss: 0.015442 (0.015882) Loss: 1.9896 (2.8756) +2025-09-11,05:41:16 | INFO | Train Epoch: 0 [16998912/26365952 (64%)] Avg Boundaries (per batch): 50.396 Boundary Ratio: 0.257 Contrastive_loss: 1.8751 (2.8567) Boundary_loss: 0.015385 (0.015880) Loss: 1.8905 (2.8726) +2025-09-11,05:42:24 | INFO | Train Epoch: 0 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.324 Boundary Ratio: 0.247 Contrastive_loss: 1.9847 (2.8541) Boundary_loss: 0.015347 (0.015878) Loss: 2.0000 (2.8700) +2025-09-11,05:43:32 | INFO | Train Epoch: 0 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 1.8077 (2.8510) Boundary_loss: 0.015205 (0.015876) Loss: 1.8229 (2.8669) +2025-09-11,05:44:40 | INFO | Train Epoch: 0 [17152512/26365952 (65%)] Avg Boundaries (per batch): 49.717 Boundary Ratio: 0.254 Contrastive_loss: 1.9202 (2.8482) Boundary_loss: 0.015265 (0.015875) Loss: 1.9354 (2.8641) +2025-09-11,05:45:48 | INFO | Train Epoch: 0 [17203712/26365952 (65%)] Avg Boundaries (per batch): 50.318 Boundary Ratio: 0.257 Contrastive_loss: 1.6958 (2.8448) Boundary_loss: 0.015371 (0.015873) Loss: 1.7111 (2.8607) +2025-09-11,05:46:56 | INFO | Train Epoch: 0 [17254912/26365952 (65%)] Avg Boundaries (per batch): 49.260 Boundary Ratio: 0.251 Contrastive_loss: 1.7464 (2.8415) Boundary_loss: 0.015216 (0.015871) Loss: 1.7617 (2.8574) +2025-09-11,05:48:05 | INFO | Train Epoch: 0 [17306112/26365952 (66%)] Avg Boundaries (per batch): 46.996 Boundary Ratio: 0.240 Contrastive_loss: 1.8508 (2.8386) Boundary_loss: 0.015283 (0.015869) Loss: 1.8661 (2.8545) +2025-09-11,05:49:13 | INFO | Train Epoch: 0 [17357312/26365952 (66%)] Avg Boundaries (per batch): 49.609 Boundary Ratio: 0.253 Contrastive_loss: 1.7719 (2.8355) Boundary_loss: 0.015214 (0.015867) Loss: 1.7871 (2.8514) +2025-09-11,05:50:21 | INFO | Train Epoch: 0 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 1.8540 (2.8326) Boundary_loss: 0.015228 (0.015866) Loss: 1.8693 (2.8485) +2025-09-11,05:51:29 | INFO | Train Epoch: 0 [17459712/26365952 (66%)] Avg Boundaries (per batch): 47.764 Boundary Ratio: 0.244 Contrastive_loss: 1.7902 (2.8296) Boundary_loss: 0.015328 (0.015864) Loss: 1.8056 (2.8454) +2025-09-11,05:52:37 | INFO | Train Epoch: 0 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.316 Boundary Ratio: 0.247 Contrastive_loss: 1.8834 (2.8268) Boundary_loss: 0.015053 (0.015862) Loss: 1.8985 (2.8427) +2025-09-11,05:53:45 | INFO | Train Epoch: 0 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.820 Boundary Ratio: 0.254 Contrastive_loss: 1.8038 (2.8238) Boundary_loss: 0.015171 (0.015860) Loss: 1.8189 (2.8397) +2025-09-11,05:54:53 | INFO | Train Epoch: 0 [17613312/26365952 (67%)] Avg Boundaries (per batch): 47.535 Boundary Ratio: 0.243 Contrastive_loss: 1.8457 (2.8210) Boundary_loss: 0.015314 (0.015858) Loss: 1.8610 (2.8368) +2025-09-11,05:56:02 | INFO | Train Epoch: 0 [17664512/26365952 (67%)] Avg Boundaries (per batch): 47.949 Boundary Ratio: 0.245 Contrastive_loss: 1.7846 (2.8180) Boundary_loss: 0.015064 (0.015856) Loss: 1.7997 (2.8339) +2025-09-11,05:57:10 | INFO | Train Epoch: 0 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.723 Boundary Ratio: 0.254 Contrastive_loss: 1.7109 (2.8148) Boundary_loss: 0.015069 (0.015854) Loss: 1.7259 (2.8307) +2025-09-11,05:58:18 | INFO | Train Epoch: 0 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.045 Boundary Ratio: 0.245 Contrastive_loss: 1.8916 (2.8122) Boundary_loss: 0.015243 (0.015852) Loss: 1.9069 (2.8280) +2025-09-11,05:59:26 | INFO | Train Epoch: 0 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.311 Boundary Ratio: 0.252 Contrastive_loss: 1.9712 (2.8097) Boundary_loss: 0.015227 (0.015850) Loss: 1.9864 (2.8256) +2025-09-11,06:00:34 | INFO | Train Epoch: 0 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 1.9328 (2.8072) Boundary_loss: 0.015063 (0.015848) Loss: 1.9478 (2.8231) +2025-09-11,06:01:42 | INFO | Train Epoch: 0 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.027 Boundary Ratio: 0.245 Contrastive_loss: 1.8089 (2.8044) Boundary_loss: 0.015117 (0.015846) Loss: 1.8240 (2.8202) +2025-09-11,06:02:50 | INFO | Train Epoch: 0 [17971712/26365952 (68%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 1.7689 (2.8015) Boundary_loss: 0.015100 (0.015844) Loss: 1.7840 (2.8173) +2025-09-11,06:03:58 | INFO | Train Epoch: 0 [18022912/26365952 (68%)] Avg Boundaries (per batch): 47.986 Boundary Ratio: 0.245 Contrastive_loss: 1.8524 (2.7988) Boundary_loss: 0.015148 (0.015842) Loss: 1.8675 (2.8146) +2025-09-11,06:05:06 | INFO | Train Epoch: 0 [18074112/26365952 (69%)] Avg Boundaries (per batch): 47.645 Boundary Ratio: 0.243 Contrastive_loss: 1.7972 (2.7959) Boundary_loss: 0.015294 (0.015840) Loss: 1.8125 (2.8118) +2025-09-11,06:06:14 | INFO | Train Epoch: 0 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 1.6955 (2.7928) Boundary_loss: 0.015058 (0.015838) Loss: 1.7106 (2.8087) +2025-09-11,06:07:22 | INFO | Train Epoch: 0 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 1.7909 (2.7900) Boundary_loss: 0.015101 (0.015836) Loss: 1.8060 (2.8059) +2025-09-11,06:08:30 | INFO | Train Epoch: 0 [18227712/26365952 (69%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 1.7861 (2.7872) Boundary_loss: 0.015106 (0.015834) Loss: 1.8012 (2.8030) +2025-09-11,06:09:38 | INFO | Train Epoch: 0 [18278912/26365952 (69%)] Avg Boundaries (per batch): 49.562 Boundary Ratio: 0.253 Contrastive_loss: 1.7095 (2.7842) Boundary_loss: 0.015003 (0.015831) Loss: 1.7245 (2.8000) +2025-09-11,06:10:46 | INFO | Train Epoch: 0 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.293 Boundary Ratio: 0.251 Contrastive_loss: 1.7630 (2.7814) Boundary_loss: 0.015101 (0.015829) Loss: 1.7781 (2.7972) +2025-09-11,06:11:54 | INFO | Train Epoch: 0 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.7773 (2.7786) Boundary_loss: 0.014989 (0.015827) Loss: 1.7923 (2.7944) +2025-09-11,06:13:02 | INFO | Train Epoch: 0 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 1.8947 (2.7761) Boundary_loss: 0.015185 (0.015825) Loss: 1.9099 (2.7919) +2025-09-11,06:14:10 | INFO | Train Epoch: 0 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.322 Boundary Ratio: 0.247 Contrastive_loss: 1.6475 (2.7730) Boundary_loss: 0.015053 (0.015823) Loss: 1.6626 (2.7888) +2025-09-11,06:15:18 | INFO | Train Epoch: 0 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 2.0116 (2.7709) Boundary_loss: 0.015041 (0.015821) Loss: 2.0266 (2.7867) +2025-09-11,06:16:25 | INFO | Train Epoch: 0 [18586112/26365952 (70%)] Avg Boundaries (per batch): 46.729 Boundary Ratio: 0.238 Contrastive_loss: 1.9156 (2.7686) Boundary_loss: 0.015344 (0.015820) Loss: 1.9310 (2.7844) +2025-09-11,06:17:33 | INFO | Train Epoch: 0 [18637312/26365952 (71%)] Avg Boundaries (per batch): 47.486 Boundary Ratio: 0.242 Contrastive_loss: 1.8830 (2.7661) Boundary_loss: 0.015090 (0.015818) Loss: 1.8981 (2.7819) +2025-09-11,06:18:41 | INFO | Train Epoch: 0 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.8178 (2.7635) Boundary_loss: 0.015004 (0.015815) Loss: 1.8328 (2.7793) +2025-09-11,06:19:49 | INFO | Train Epoch: 0 [18739712/26365952 (71%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 1.8147 (2.7609) Boundary_loss: 0.015051 (0.015813) Loss: 1.8298 (2.7768) +2025-09-11,06:20:57 | INFO | Train Epoch: 0 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 1.8571 (2.7585) Boundary_loss: 0.014868 (0.015811) Loss: 1.8719 (2.7743) +2025-09-11,06:22:05 | INFO | Train Epoch: 0 [18842112/26365952 (71%)] Avg Boundaries (per batch): 49.521 Boundary Ratio: 0.253 Contrastive_loss: 1.8816 (2.7561) Boundary_loss: 0.014947 (0.015808) Loss: 1.8965 (2.7719) +2025-09-11,06:23:12 | INFO | Train Epoch: 0 [18893312/26365952 (72%)] Avg Boundaries (per batch): 47.949 Boundary Ratio: 0.245 Contrastive_loss: 1.8396 (2.7536) Boundary_loss: 0.015061 (0.015806) Loss: 1.8546 (2.7694) +2025-09-11,06:24:20 | INFO | Train Epoch: 0 [18944512/26365952 (72%)] Avg Boundaries (per batch): 47.795 Boundary Ratio: 0.244 Contrastive_loss: 1.9351 (2.7514) Boundary_loss: 0.014999 (0.015804) Loss: 1.9501 (2.7672) +2025-09-11,06:25:28 | INFO | Train Epoch: 0 [18995712/26365952 (72%)] Avg Boundaries (per batch): 49.604 Boundary Ratio: 0.253 Contrastive_loss: 1.8059 (2.7489) Boundary_loss: 0.014924 (0.015802) Loss: 1.8209 (2.7647) +2025-09-11,06:26:36 | INFO | Train Epoch: 0 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.912 Boundary Ratio: 0.255 Contrastive_loss: 1.9057 (2.7466) Boundary_loss: 0.014968 (0.015800) Loss: 1.9207 (2.7624) +2025-09-11,06:27:44 | INFO | Train Epoch: 0 [19098112/26365952 (72%)] Avg Boundaries (per batch): 50.266 Boundary Ratio: 0.256 Contrastive_loss: 1.7583 (2.7440) Boundary_loss: 0.015103 (0.015798) Loss: 1.7734 (2.7598) +2025-09-11,06:28:52 | INFO | Train Epoch: 0 [19149312/26365952 (73%)] Avg Boundaries (per batch): 49.471 Boundary Ratio: 0.252 Contrastive_loss: 1.9684 (2.7419) Boundary_loss: 0.014924 (0.015795) Loss: 1.9833 (2.7577) +2025-09-11,06:29:59 | INFO | Train Epoch: 0 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.7515 (2.7393) Boundary_loss: 0.014989 (0.015793) Loss: 1.7665 (2.7551) +2025-09-11,06:31:07 | INFO | Train Epoch: 0 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 1.9394 (2.7372) Boundary_loss: 0.015060 (0.015791) Loss: 1.9545 (2.7530) +2025-09-11,06:32:15 | INFO | Train Epoch: 0 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 1.8957 (2.7349) Boundary_loss: 0.014963 (0.015789) Loss: 1.9107 (2.7507) +2025-09-11,06:33:23 | INFO | Train Epoch: 0 [19354112/26365952 (73%)] Avg Boundaries (per batch): 47.672 Boundary Ratio: 0.243 Contrastive_loss: 1.7505 (2.7323) Boundary_loss: 0.014943 (0.015787) Loss: 1.7655 (2.7481) +2025-09-11,06:34:30 | INFO | Train Epoch: 0 [19405312/26365952 (74%)] Avg Boundaries (per batch): 47.695 Boundary Ratio: 0.243 Contrastive_loss: 1.6516 (2.7295) Boundary_loss: 0.014852 (0.015784) Loss: 1.6665 (2.7453) +2025-09-11,06:35:38 | INFO | Train Epoch: 0 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 1.8867 (2.7273) Boundary_loss: 0.014743 (0.015782) Loss: 1.9014 (2.7431) +2025-09-11,06:36:46 | INFO | Train Epoch: 0 [19507712/26365952 (74%)] Avg Boundaries (per batch): 50.773 Boundary Ratio: 0.259 Contrastive_loss: 1.7237 (2.7247) Boundary_loss: 0.015141 (0.015780) Loss: 1.7388 (2.7404) +2025-09-11,06:37:54 | INFO | Train Epoch: 0 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.8039 (2.7223) Boundary_loss: 0.014883 (0.015778) Loss: 1.8188 (2.7380) +2025-09-11,06:39:01 | INFO | Train Epoch: 0 [19610112/26365952 (74%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 1.9815 (2.7203) Boundary_loss: 0.015042 (0.015776) Loss: 1.9965 (2.7361) +2025-09-11,06:40:09 | INFO | Train Epoch: 0 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 1.7946 (2.7179) Boundary_loss: 0.014862 (0.015773) Loss: 1.8095 (2.7337) +2025-09-11,06:41:17 | INFO | Train Epoch: 0 [19712512/26365952 (75%)] Avg Boundaries (per batch): 51.309 Boundary Ratio: 0.262 Contrastive_loss: 1.6865 (2.7152) Boundary_loss: 0.015225 (0.015772) Loss: 1.7017 (2.7310) +2025-09-11,06:42:25 | INFO | Train Epoch: 0 [19763712/26365952 (75%)] Avg Boundaries (per batch): 49.492 Boundary Ratio: 0.253 Contrastive_loss: 1.5875 (2.7123) Boundary_loss: 0.014854 (0.015770) Loss: 1.6024 (2.7281) +2025-09-11,06:43:32 | INFO | Train Epoch: 0 [19814912/26365952 (75%)] Avg Boundaries (per batch): 47.480 Boundary Ratio: 0.242 Contrastive_loss: 1.8546 (2.7101) Boundary_loss: 0.014963 (0.015768) Loss: 1.8696 (2.7259) +2025-09-11,06:44:40 | INFO | Train Epoch: 0 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 1.6996 (2.7075) Boundary_loss: 0.014709 (0.015765) Loss: 1.7143 (2.7233) +2025-09-11,06:45:48 | INFO | Train Epoch: 0 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 1.7168 (2.7050) Boundary_loss: 0.014842 (0.015762) Loss: 1.7316 (2.7207) +2025-09-11,06:46:55 | INFO | Train Epoch: 0 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 1.7807 (2.7026) Boundary_loss: 0.014737 (0.015760) Loss: 1.7955 (2.7184) +2025-09-11,06:48:03 | INFO | Train Epoch: 0 [20019712/26365952 (76%)] Avg Boundaries (per batch): 47.791 Boundary Ratio: 0.244 Contrastive_loss: 1.7068 (2.7001) Boundary_loss: 0.014754 (0.015757) Loss: 1.7216 (2.7158) +2025-09-11,06:49:11 | INFO | Train Epoch: 0 [20070912/26365952 (76%)] Avg Boundaries (per batch): 49.945 Boundary Ratio: 0.255 Contrastive_loss: 1.7909 (2.6978) Boundary_loss: 0.014802 (0.015755) Loss: 1.8057 (2.7135) +2025-09-11,06:50:18 | INFO | Train Epoch: 0 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.162 Boundary Ratio: 0.246 Contrastive_loss: 1.9182 (2.6958) Boundary_loss: 0.014838 (0.015753) Loss: 1.9330 (2.7115) +2025-09-11,06:51:26 | INFO | Train Epoch: 0 [20173312/26365952 (77%)] Avg Boundaries (per batch): 47.674 Boundary Ratio: 0.243 Contrastive_loss: 1.8272 (2.6936) Boundary_loss: 0.014882 (0.015750) Loss: 1.8421 (2.7093) +2025-09-11,06:52:34 | INFO | Train Epoch: 0 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.8197 (2.6914) Boundary_loss: 0.014720 (0.015748) Loss: 1.8344 (2.7071) +2025-09-11,06:53:41 | INFO | Train Epoch: 0 [20275712/26365952 (77%)] Avg Boundaries (per batch): 49.736 Boundary Ratio: 0.254 Contrastive_loss: 1.8387 (2.6892) Boundary_loss: 0.014847 (0.015745) Loss: 1.8536 (2.7050) +2025-09-11,06:54:49 | INFO | Train Epoch: 0 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 1.7794 (2.6869) Boundary_loss: 0.014745 (0.015743) Loss: 1.7941 (2.7027) +2025-09-11,06:55:57 | INFO | Train Epoch: 0 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 1.8457 (2.6848) Boundary_loss: 0.014704 (0.015740) Loss: 1.8604 (2.7006) +2025-09-11,06:57:04 | INFO | Train Epoch: 0 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 1.8620 (2.6828) Boundary_loss: 0.014780 (0.015738) Loss: 1.8767 (2.6985) +2025-09-11,06:58:12 | INFO | Train Epoch: 0 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 1.7499 (2.6805) Boundary_loss: 0.014831 (0.015736) Loss: 1.7647 (2.6962) +2025-09-11,06:59:19 | INFO | Train Epoch: 0 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 1.7617 (2.6782) Boundary_loss: 0.014823 (0.015733) Loss: 1.7765 (2.6939) +2025-09-11,07:00:27 | INFO | Train Epoch: 0 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 1.8600 (2.6761) Boundary_loss: 0.014687 (0.015731) Loss: 1.8747 (2.6919) +2025-09-11,07:01:34 | INFO | Train Epoch: 0 [20634112/26365952 (78%)] Avg Boundaries (per batch): 50.246 Boundary Ratio: 0.256 Contrastive_loss: 1.6582 (2.6736) Boundary_loss: 0.014668 (0.015728) Loss: 1.6729 (2.6893) +2025-09-11,07:02:42 | INFO | Train Epoch: 0 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 1.9222 (2.6718) Boundary_loss: 0.014720 (0.015726) Loss: 1.9370 (2.6875) +2025-09-11,07:03:49 | INFO | Train Epoch: 0 [20736512/26365952 (79%)] Avg Boundaries (per batch): 47.799 Boundary Ratio: 0.244 Contrastive_loss: 1.6658 (2.6693) Boundary_loss: 0.014763 (0.015723) Loss: 1.6805 (2.6850) +2025-09-11,07:04:57 | INFO | Train Epoch: 0 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.342 Boundary Ratio: 0.252 Contrastive_loss: 1.7082 (2.6669) Boundary_loss: 0.014693 (0.015721) Loss: 1.7229 (2.6826) +2025-09-11,07:06:04 | INFO | Train Epoch: 0 [20838912/26365952 (79%)] Avg Boundaries (per batch): 47.336 Boundary Ratio: 0.242 Contrastive_loss: 1.7190 (2.6646) Boundary_loss: 0.014832 (0.015719) Loss: 1.7338 (2.6803) +2025-09-11,07:07:12 | INFO | Train Epoch: 0 [20890112/26365952 (79%)] Avg Boundaries (per batch): 49.953 Boundary Ratio: 0.255 Contrastive_loss: 1.7452 (2.6624) Boundary_loss: 0.014744 (0.015716) Loss: 1.7599 (2.6781) +2025-09-11,07:08:19 | INFO | Train Epoch: 0 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 1.6857 (2.6600) Boundary_loss: 0.014672 (0.015714) Loss: 1.7004 (2.6757) +2025-09-11,07:09:27 | INFO | Train Epoch: 0 [20992512/26365952 (80%)] Avg Boundaries (per batch): 49.244 Boundary Ratio: 0.251 Contrastive_loss: 1.5623 (2.6573) Boundary_loss: 0.014542 (0.015711) Loss: 1.5768 (2.6730) +2025-09-11,07:10:34 | INFO | Train Epoch: 0 [21043712/26365952 (80%)] Avg Boundaries (per batch): 47.941 Boundary Ratio: 0.245 Contrastive_loss: 1.8244 (2.6553) Boundary_loss: 0.014667 (0.015708) Loss: 1.8391 (2.6710) +2025-09-11,07:11:42 | INFO | Train Epoch: 0 [21094912/26365952 (80%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 1.7785 (2.6532) Boundary_loss: 0.014693 (0.015706) Loss: 1.7932 (2.6689) +2025-09-11,07:12:49 | INFO | Train Epoch: 0 [21146112/26365952 (80%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 1.7400 (2.6510) Boundary_loss: 0.014699 (0.015703) Loss: 1.7547 (2.6667) +2025-09-11,07:13:57 | INFO | Train Epoch: 0 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.354 Boundary Ratio: 0.247 Contrastive_loss: 1.7750 (2.6488) Boundary_loss: 0.014581 (0.015701) Loss: 1.7896 (2.6645) +2025-09-11,07:15:04 | INFO | Train Epoch: 0 [21248512/26365952 (81%)] Avg Boundaries (per batch): 49.959 Boundary Ratio: 0.255 Contrastive_loss: 1.6367 (2.6464) Boundary_loss: 0.014669 (0.015698) Loss: 1.6514 (2.6621) +2025-09-11,07:16:11 | INFO | Train Epoch: 0 [21299712/26365952 (81%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 1.6700 (2.6441) Boundary_loss: 0.014796 (0.015696) Loss: 1.6848 (2.6598) +2025-09-11,07:17:19 | INFO | Train Epoch: 0 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 1.7890 (2.6420) Boundary_loss: 0.014629 (0.015693) Loss: 1.8037 (2.6577) +2025-09-11,07:18:26 | INFO | Train Epoch: 0 [21402112/26365952 (81%)] Avg Boundaries (per batch): 49.803 Boundary Ratio: 0.254 Contrastive_loss: 1.7981 (2.6400) Boundary_loss: 0.014771 (0.015691) Loss: 1.8129 (2.6557) +2025-09-11,07:19:34 | INFO | Train Epoch: 0 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 1.7607 (2.6379) Boundary_loss: 0.014592 (0.015689) Loss: 1.7753 (2.6536) +2025-09-11,07:20:41 | INFO | Train Epoch: 0 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.7004 (2.6357) Boundary_loss: 0.014526 (0.015686) Loss: 1.7149 (2.6514) +2025-09-11,07:21:49 | INFO | Train Epoch: 0 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.254 Boundary Ratio: 0.246 Contrastive_loss: 1.5411 (2.6331) Boundary_loss: 0.014627 (0.015683) Loss: 1.5557 (2.6488) +2025-09-11,07:22:56 | INFO | Train Epoch: 0 [21606912/26365952 (82%)] Avg Boundaries (per batch): 49.375 Boundary Ratio: 0.252 Contrastive_loss: 1.7731 (2.6311) Boundary_loss: 0.014606 (0.015681) Loss: 1.7877 (2.6467) +2025-09-11,07:24:03 | INFO | Train Epoch: 0 [21658112/26365952 (82%)] Avg Boundaries (per batch): 49.469 Boundary Ratio: 0.252 Contrastive_loss: 1.6713 (2.6288) Boundary_loss: 0.014595 (0.015678) Loss: 1.6859 (2.6445) +2025-09-11,07:25:11 | INFO | Train Epoch: 0 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 1.7401 (2.6267) Boundary_loss: 0.014573 (0.015676) Loss: 1.7546 (2.6424) +2025-09-11,07:26:18 | INFO | Train Epoch: 0 [21760512/26365952 (83%)] Avg Boundaries (per batch): 47.287 Boundary Ratio: 0.241 Contrastive_loss: 1.7414 (2.6246) Boundary_loss: 0.014748 (0.015674) Loss: 1.7562 (2.6403) +2025-09-11,07:27:25 | INFO | Train Epoch: 0 [21811712/26365952 (83%)] Avg Boundaries (per batch): 49.182 Boundary Ratio: 0.251 Contrastive_loss: 1.6468 (2.6223) Boundary_loss: 0.014626 (0.015671) Loss: 1.6614 (2.6380) +2025-09-11,07:28:33 | INFO | Train Epoch: 0 [21862912/26365952 (83%)] Avg Boundaries (per batch): 50.127 Boundary Ratio: 0.256 Contrastive_loss: 1.6124 (2.6200) Boundary_loss: 0.014628 (0.015669) Loss: 1.6270 (2.6356) +2025-09-11,07:29:40 | INFO | Train Epoch: 0 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 1.6697 (2.6178) Boundary_loss: 0.014640 (0.015666) Loss: 1.6844 (2.6334) +2025-09-11,07:30:47 | INFO | Train Epoch: 0 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.201 Boundary Ratio: 0.246 Contrastive_loss: 1.8459 (2.6160) Boundary_loss: 0.014648 (0.015664) Loss: 1.8605 (2.6316) +2025-09-11,07:31:55 | INFO | Train Epoch: 0 [22016512/26365952 (84%)] Avg Boundaries (per batch): 49.570 Boundary Ratio: 0.253 Contrastive_loss: 1.7187 (2.6139) Boundary_loss: 0.014579 (0.015661) Loss: 1.7333 (2.6295) +2025-09-11,07:33:02 | INFO | Train Epoch: 0 [22067712/26365952 (84%)] Avg Boundaries (per batch): 49.469 Boundary Ratio: 0.252 Contrastive_loss: 1.7080 (2.6118) Boundary_loss: 0.014634 (0.015659) Loss: 1.7227 (2.6274) +2025-09-11,07:34:09 | INFO | Train Epoch: 0 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 1.6704 (2.6096) Boundary_loss: 0.014523 (0.015656) Loss: 1.6849 (2.6253) +2025-09-11,07:35:17 | INFO | Train Epoch: 0 [22170112/26365952 (84%)] Avg Boundaries (per batch): 49.500 Boundary Ratio: 0.253 Contrastive_loss: 1.6742 (2.6075) Boundary_loss: 0.014511 (0.015654) Loss: 1.6887 (2.6231) +2025-09-11,07:36:24 | INFO | Train Epoch: 0 [22221312/26365952 (84%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 1.6285 (2.6052) Boundary_loss: 0.014460 (0.015651) Loss: 1.6429 (2.6209) +2025-09-11,07:37:31 | INFO | Train Epoch: 0 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.801 Boundary Ratio: 0.254 Contrastive_loss: 1.4683 (2.6026) Boundary_loss: 0.014486 (0.015648) Loss: 1.4828 (2.6182) +2025-09-11,07:38:39 | INFO | Train Epoch: 0 [22323712/26365952 (85%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 1.7200 (2.6006) Boundary_loss: 0.014527 (0.015646) Loss: 1.7346 (2.6162) +2025-09-11,07:39:46 | INFO | Train Epoch: 0 [22374912/26365952 (85%)] Avg Boundaries (per batch): 51.010 Boundary Ratio: 0.260 Contrastive_loss: 1.6616 (2.5984) Boundary_loss: 0.014798 (0.015644) Loss: 1.6764 (2.6141) +2025-09-11,07:40:53 | INFO | Train Epoch: 0 [22426112/26365952 (85%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 1.6722 (2.5963) Boundary_loss: 0.014447 (0.015641) Loss: 1.6866 (2.6120) +2025-09-11,07:42:00 | INFO | Train Epoch: 0 [22477312/26365952 (85%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 1.6361 (2.5941) Boundary_loss: 0.014532 (0.015639) Loss: 1.6506 (2.6098) +2025-09-11,07:43:08 | INFO | Train Epoch: 0 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 1.7119 (2.5921) Boundary_loss: 0.014493 (0.015636) Loss: 1.7264 (2.6078) +2025-09-11,07:44:15 | INFO | Train Epoch: 0 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.236 Boundary Ratio: 0.246 Contrastive_loss: 1.6242 (2.5900) Boundary_loss: 0.014524 (0.015633) Loss: 1.6388 (2.6056) +2025-09-11,07:45:22 | INFO | Train Epoch: 0 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.617 Boundary Ratio: 0.253 Contrastive_loss: 1.6507 (2.5878) Boundary_loss: 0.014642 (0.015631) Loss: 1.6653 (2.6035) +2025-09-11,07:46:30 | INFO | Train Epoch: 0 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 1.7407 (2.5859) Boundary_loss: 0.014503 (0.015629) Loss: 1.7552 (2.6016) +2025-09-11,07:47:37 | INFO | Train Epoch: 0 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.588 Boundary Ratio: 0.253 Contrastive_loss: 1.6802 (2.5839) Boundary_loss: 0.014549 (0.015626) Loss: 1.6947 (2.5995) +2025-09-11,07:48:44 | INFO | Train Epoch: 0 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.482 Boundary Ratio: 0.247 Contrastive_loss: 1.6181 (2.5817) Boundary_loss: 0.014448 (0.015624) Loss: 1.6325 (2.5973) +2025-09-11,07:49:51 | INFO | Train Epoch: 0 [22835712/26365952 (87%)] Avg Boundaries (per batch): 47.768 Boundary Ratio: 0.244 Contrastive_loss: 1.6312 (2.5796) Boundary_loss: 0.014565 (0.015621) Loss: 1.6458 (2.5952) +2025-09-11,07:50:59 | INFO | Train Epoch: 0 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 1.7697 (2.5778) Boundary_loss: 0.014509 (0.015619) Loss: 1.7842 (2.5934) +2025-09-11,07:52:06 | INFO | Train Epoch: 0 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.158 Boundary Ratio: 0.246 Contrastive_loss: 1.7022 (2.5758) Boundary_loss: 0.014440 (0.015616) Loss: 1.7167 (2.5915) +2025-09-11,07:53:13 | INFO | Train Epoch: 0 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 1.4774 (2.5734) Boundary_loss: 0.014511 (0.015614) Loss: 1.4920 (2.5890) +2025-09-11,07:54:20 | INFO | Train Epoch: 0 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 1.7096 (2.5715) Boundary_loss: 0.014529 (0.015611) Loss: 1.7241 (2.5871) +2025-09-11,07:55:28 | INFO | Train Epoch: 0 [23091712/26365952 (88%)] Avg Boundaries (per batch): 49.432 Boundary Ratio: 0.252 Contrastive_loss: 1.7401 (2.5696) Boundary_loss: 0.014469 (0.015609) Loss: 1.7545 (2.5853) +2025-09-11,07:56:35 | INFO | Train Epoch: 0 [23142912/26365952 (88%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 1.7005 (2.5677) Boundary_loss: 0.014550 (0.015606) Loss: 1.7151 (2.5833) +2025-09-11,07:57:42 | INFO | Train Epoch: 0 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 1.6015 (2.5656) Boundary_loss: 0.014393 (0.015604) Loss: 1.6159 (2.5812) +2025-09-11,07:58:49 | INFO | Train Epoch: 0 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 1.5259 (2.5633) Boundary_loss: 0.014558 (0.015601) Loss: 1.5405 (2.5789) +2025-09-11,07:59:56 | INFO | Train Epoch: 0 [23296512/26365952 (88%)] Avg Boundaries (per batch): 49.281 Boundary Ratio: 0.251 Contrastive_loss: 1.6610 (2.5613) Boundary_loss: 0.014414 (0.015599) Loss: 1.6754 (2.5769) +2025-09-11,08:01:03 | INFO | Train Epoch: 0 [23347712/26365952 (89%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 1.6532 (2.5593) Boundary_loss: 0.014447 (0.015596) Loss: 1.6676 (2.5749) +2025-09-11,08:02:11 | INFO | Train Epoch: 0 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.268 Boundary Ratio: 0.246 Contrastive_loss: 1.4804 (2.5570) Boundary_loss: 0.014451 (0.015594) Loss: 1.4949 (2.5726) +2025-09-11,08:03:18 | INFO | Train Epoch: 0 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 1.7110 (2.5551) Boundary_loss: 0.014365 (0.015591) Loss: 1.7254 (2.5707) +2025-09-11,08:04:25 | INFO | Train Epoch: 0 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 1.7845 (2.5535) Boundary_loss: 0.014525 (0.015589) Loss: 1.7990 (2.5691) +2025-09-11,08:05:32 | INFO | Train Epoch: 0 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 1.6948 (2.5516) Boundary_loss: 0.014388 (0.015586) Loss: 1.7092 (2.5672) +2025-09-11,08:06:39 | INFO | Train Epoch: 0 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 1.5794 (2.5495) Boundary_loss: 0.014410 (0.015584) Loss: 1.5938 (2.5651) +2025-09-11,08:07:47 | INFO | Train Epoch: 0 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 1.4846 (2.5472) Boundary_loss: 0.014432 (0.015581) Loss: 1.4990 (2.5628) +2025-09-11,08:08:54 | INFO | Train Epoch: 0 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.096 Boundary Ratio: 0.245 Contrastive_loss: 1.5399 (2.5450) Boundary_loss: 0.014432 (0.015579) Loss: 1.5543 (2.5606) +2025-09-11,08:10:01 | INFO | Train Epoch: 0 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 1.6234 (2.5431) Boundary_loss: 0.014400 (0.015576) Loss: 1.6378 (2.5586) +2025-09-11,08:11:08 | INFO | Train Epoch: 0 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 1.7386 (2.5413) Boundary_loss: 0.014425 (0.015574) Loss: 1.7530 (2.5569) +2025-09-11,08:12:15 | INFO | Train Epoch: 0 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.5693 (2.5392) Boundary_loss: 0.014397 (0.015571) Loss: 1.5837 (2.5548) +2025-09-11,08:13:22 | INFO | Train Epoch: 0 [23910912/26365952 (91%)] Avg Boundaries (per batch): 47.570 Boundary Ratio: 0.243 Contrastive_loss: 1.7444 (2.5375) Boundary_loss: 0.014531 (0.015569) Loss: 1.7589 (2.5531) +2025-09-11,08:14:30 | INFO | Train Epoch: 0 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 1.5814 (2.5355) Boundary_loss: 0.014460 (0.015567) Loss: 1.5959 (2.5511) +2025-09-11,08:15:37 | INFO | Train Epoch: 0 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.283 Boundary Ratio: 0.251 Contrastive_loss: 1.7595 (2.5339) Boundary_loss: 0.014398 (0.015564) Loss: 1.7738 (2.5494) +2025-09-11,08:16:44 | INFO | Train Epoch: 0 [24064512/26365952 (91%)] Avg Boundaries (per batch): 47.828 Boundary Ratio: 0.244 Contrastive_loss: 1.5900 (2.5319) Boundary_loss: 0.014536 (0.015562) Loss: 1.6045 (2.5474) +2025-09-11,08:17:51 | INFO | Train Epoch: 0 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.385 Boundary Ratio: 0.247 Contrastive_loss: 1.6977 (2.5301) Boundary_loss: 0.014328 (0.015559) Loss: 1.7120 (2.5456) +2025-09-11,08:18:58 | INFO | Train Epoch: 0 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 1.4804 (2.5279) Boundary_loss: 0.014367 (0.015557) Loss: 1.4948 (2.5434) +2025-09-11,08:20:05 | INFO | Train Epoch: 0 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 1.8018 (2.5263) Boundary_loss: 0.014371 (0.015554) Loss: 1.8162 (2.5419) +2025-09-11,08:21:12 | INFO | Train Epoch: 0 [24269312/26365952 (92%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 1.4274 (2.5240) Boundary_loss: 0.014434 (0.015552) Loss: 1.4418 (2.5396) +2025-09-11,08:22:20 | INFO | Train Epoch: 0 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 1.7022 (2.5223) Boundary_loss: 0.014380 (0.015549) Loss: 1.7166 (2.5378) +2025-09-11,08:23:27 | INFO | Train Epoch: 0 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 1.6401 (2.5204) Boundary_loss: 0.014377 (0.015547) Loss: 1.6545 (2.5360) +2025-09-11,08:24:34 | INFO | Train Epoch: 0 [24422912/26365952 (93%)] Avg Boundaries (per batch): 49.871 Boundary Ratio: 0.254 Contrastive_loss: 1.4071 (2.5181) Boundary_loss: 0.014358 (0.015544) Loss: 1.4214 (2.5337) +2025-09-11,08:25:41 | INFO | Train Epoch: 0 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.184 Boundary Ratio: 0.246 Contrastive_loss: 1.6184 (2.5162) Boundary_loss: 0.014394 (0.015542) Loss: 1.6327 (2.5318) +2025-09-11,08:26:48 | INFO | Train Epoch: 0 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 1.6253 (2.5144) Boundary_loss: 0.014385 (0.015540) Loss: 1.6397 (2.5299) +2025-09-11,08:27:55 | INFO | Train Epoch: 0 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.7600 (2.5128) Boundary_loss: 0.014335 (0.015537) Loss: 1.7743 (2.5284) +2025-09-11,08:29:02 | INFO | Train Epoch: 0 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 1.6193 (2.5110) Boundary_loss: 0.014362 (0.015535) Loss: 1.6337 (2.5265) +2025-09-11,08:30:09 | INFO | Train Epoch: 0 [24678912/26365952 (94%)] Avg Boundaries (per batch): 47.900 Boundary Ratio: 0.244 Contrastive_loss: 1.8408 (2.5096) Boundary_loss: 0.014412 (0.015532) Loss: 1.8552 (2.5251) +2025-09-11,08:31:16 | INFO | Train Epoch: 0 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 1.7468 (2.5080) Boundary_loss: 0.014357 (0.015530) Loss: 1.7612 (2.5235) +2025-09-11,08:32:23 | INFO | Train Epoch: 0 [24781312/26365952 (94%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 1.5529 (2.5060) Boundary_loss: 0.014282 (0.015527) Loss: 1.5672 (2.5216) +2025-09-11,08:33:31 | INFO | Train Epoch: 0 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 1.4610 (2.5039) Boundary_loss: 0.014387 (0.015525) Loss: 1.4754 (2.5194) +2025-09-11,08:34:38 | INFO | Train Epoch: 0 [24883712/26365952 (94%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 1.7265 (2.5023) Boundary_loss: 0.014349 (0.015523) Loss: 1.7408 (2.5178) +2025-09-11,08:35:45 | INFO | Train Epoch: 0 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 1.5905 (2.5004) Boundary_loss: 0.014312 (0.015520) Loss: 1.6048 (2.5159) +2025-09-11,08:36:52 | INFO | Train Epoch: 0 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 1.6184 (2.4986) Boundary_loss: 0.014250 (0.015518) Loss: 1.6327 (2.5141) +2025-09-11,08:37:59 | INFO | Train Epoch: 0 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 1.5808 (2.4967) Boundary_loss: 0.014268 (0.015515) Loss: 1.5951 (2.5123) +2025-09-11,08:39:06 | INFO | Train Epoch: 0 [25088512/26365952 (95%)] Avg Boundaries (per batch): 47.449 Boundary Ratio: 0.242 Contrastive_loss: 1.7911 (2.4953) Boundary_loss: 0.014564 (0.015513) Loss: 1.8057 (2.5108) +2025-09-11,08:40:13 | INFO | Train Epoch: 0 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.061 Boundary Ratio: 0.245 Contrastive_loss: 1.6988 (2.4937) Boundary_loss: 0.014337 (0.015511) Loss: 1.7132 (2.5092) +2025-09-11,08:41:20 | INFO | Train Epoch: 0 [25190912/26365952 (96%)] Avg Boundaries (per batch): 47.912 Boundary Ratio: 0.244 Contrastive_loss: 1.5933 (2.4919) Boundary_loss: 0.014318 (0.015508) Loss: 1.6076 (2.5074) +2025-09-11,08:42:27 | INFO | Train Epoch: 0 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 1.5872 (2.4900) Boundary_loss: 0.014303 (0.015506) Loss: 1.6015 (2.5055) +2025-09-11,08:43:34 | INFO | Train Epoch: 0 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 1.7250 (2.4885) Boundary_loss: 0.014349 (0.015503) Loss: 1.7393 (2.5040) +2025-09-11,08:44:41 | INFO | Train Epoch: 0 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 1.3816 (2.4862) Boundary_loss: 0.014411 (0.015501) Loss: 1.3960 (2.5017) +2025-09-11,08:45:48 | INFO | Train Epoch: 0 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.086 Boundary Ratio: 0.245 Contrastive_loss: 1.4402 (2.4841) Boundary_loss: 0.014367 (0.015499) Loss: 1.4545 (2.4996) +2025-09-11,08:46:55 | INFO | Train Epoch: 0 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 1.4378 (2.4820) Boundary_loss: 0.014353 (0.015497) Loss: 1.4521 (2.4975) +2025-09-11,08:48:02 | INFO | Train Epoch: 0 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.273 Boundary Ratio: 0.246 Contrastive_loss: 1.6077 (2.4803) Boundary_loss: 0.014307 (0.015494) Loss: 1.6220 (2.4958) +2025-09-11,08:49:09 | INFO | Train Epoch: 0 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.5631 (2.4785) Boundary_loss: 0.014271 (0.015492) Loss: 1.5774 (2.4939) +2025-09-11,08:50:16 | INFO | Train Epoch: 0 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 1.5310 (2.4766) Boundary_loss: 0.014328 (0.015490) Loss: 1.5453 (2.4921) +2025-09-11,08:51:24 | INFO | Train Epoch: 0 [25651712/26365952 (97%)] Avg Boundaries (per batch): 50.156 Boundary Ratio: 0.256 Contrastive_loss: 1.6457 (2.4749) Boundary_loss: 0.014497 (0.015488) Loss: 1.6602 (2.4904) +2025-09-11,08:52:31 | INFO | Train Epoch: 0 [25702912/26365952 (97%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 1.6318 (2.4732) Boundary_loss: 0.014369 (0.015485) Loss: 1.6461 (2.4887) +2025-09-11,08:53:38 | INFO | Train Epoch: 0 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.5597 (2.4714) Boundary_loss: 0.014321 (0.015483) Loss: 1.5741 (2.4869) +2025-09-11,08:54:45 | INFO | Train Epoch: 0 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 1.4384 (2.4694) Boundary_loss: 0.014312 (0.015481) Loss: 1.4527 (2.4849) +2025-09-11,08:55:52 | INFO | Train Epoch: 0 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.5683 (2.4676) Boundary_loss: 0.014347 (0.015478) Loss: 1.5827 (2.4831) +2025-09-11,08:56:59 | INFO | Train Epoch: 0 [25907712/26365952 (98%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 1.6375 (2.4660) Boundary_loss: 0.014265 (0.015476) Loss: 1.6518 (2.4814) +2025-09-11,08:58:06 | INFO | Train Epoch: 0 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 1.5089 (2.4641) Boundary_loss: 0.014307 (0.015474) Loss: 1.5233 (2.4795) +2025-09-11,08:59:13 | INFO | Train Epoch: 0 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 1.4644 (2.4621) Boundary_loss: 0.014449 (0.015472) Loss: 1.4789 (2.4776) +2025-09-11,09:00:20 | INFO | Train Epoch: 0 [26061312/26365952 (99%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 1.4602 (2.4601) Boundary_loss: 0.014259 (0.015469) Loss: 1.4744 (2.4756) +2025-09-11,09:01:27 | INFO | Train Epoch: 0 [26112512/26365952 (99%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 1.7082 (2.4587) Boundary_loss: 0.014232 (0.015467) Loss: 1.7224 (2.4741) +2025-09-11,09:02:34 | INFO | Train Epoch: 0 [26163712/26365952 (99%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 1.7275 (2.4572) Boundary_loss: 0.014271 (0.015465) Loss: 1.7418 (2.4727) +2025-09-11,09:03:41 | INFO | Train Epoch: 0 [26214912/26365952 (99%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 1.5792 (2.4555) Boundary_loss: 0.014313 (0.015462) Loss: 1.5935 (2.4710) +2025-09-11,09:04:48 | INFO | Train Epoch: 0 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 1.5618 (2.4538) Boundary_loss: 0.014259 (0.015460) Loss: 1.5761 (2.4693) +2025-09-11,09:05:55 | INFO | Train Epoch: 0 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 1.5938 (2.4521) Boundary_loss: 0.014346 (0.015458) Loss: 1.6081 (2.4676) +2025-09-11,09:06:59 | INFO | Train Epoch: 0 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.273 Boundary Ratio: 0.246 Contrastive_loss: 1.5587 (2.4504) Boundary_loss: 0.014300 (0.015456) Loss: 1.5730 (2.4658) +2025-09-11,09:06:59 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-11,09:06:59 | INFO | [Epoch 0] Average Step Time: 0.699s | Average GPU Memory: 32.1 GB +2025-09-11,09:06:59 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-11,09:06:59 | INFO | Starting zero-shot imagenet. +2025-09-11,09:06:59 | INFO | Building zero-shot classifier +2025-09-11,09:07:08 | INFO | Using classifier +2025-09-11,09:07:57 | INFO | Finished zero-shot imagenet. +2025-09-11,09:07:57 | INFO | Eval Epoch: 1 imagenet-zeroshot-val-top1: 0.1293 imagenet-zeroshot-val-top5: 0.3012 +2025-09-11,09:07:58 | INFO | Start epoch 1 +2025-09-11,09:08:01 | INFO | Train Epoch: 1 [ 512/26365952 (0%)] Avg Boundaries (per batch): 47.953 Boundary Ratio: 0.245 Contrastive_loss: 1.5494 (1.5494) Boundary_loss: 0.014400 (0.014400) Loss: 1.5638 (1.5638) +2025-09-11,09:09:08 | INFO | Train Epoch: 1 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.143 Boundary Ratio: 0.246 Contrastive_loss: 1.5595 (1.5544) Boundary_loss: 0.014281 (0.014340) Loss: 1.5738 (1.5688) +2025-09-11,09:10:14 | INFO | Train Epoch: 1 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 1.3648 (1.4912) Boundary_loss: 0.014351 (0.014344) Loss: 1.3791 (1.5056) +2025-09-11,09:11:21 | INFO | Train Epoch: 1 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 1.5936 (1.5168) Boundary_loss: 0.014248 (0.014320) Loss: 1.6079 (1.5311) +2025-09-11,09:12:28 | INFO | Train Epoch: 1 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 1.6031 (1.5341) Boundary_loss: 0.014351 (0.014326) Loss: 1.6175 (1.5484) +2025-09-11,09:13:35 | INFO | Train Epoch: 1 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 49.324 Boundary Ratio: 0.252 Contrastive_loss: 1.4861 (1.5261) Boundary_loss: 0.014290 (0.014320) Loss: 1.5003 (1.5404) +2025-09-11,09:14:42 | INFO | Train Epoch: 1 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 49.346 Boundary Ratio: 0.252 Contrastive_loss: 1.5233 (1.5257) Boundary_loss: 0.014326 (0.014321) Loss: 1.5376 (1.5400) +2025-09-11,09:15:49 | INFO | Train Epoch: 1 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 1.5475 (1.5284) Boundary_loss: 0.014377 (0.014328) Loss: 1.5618 (1.5427) +2025-09-11,09:16:56 | INFO | Train Epoch: 1 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.4962 (1.5248) Boundary_loss: 0.014243 (0.014318) Loss: 1.5105 (1.5391) +2025-09-11,09:18:03 | INFO | Train Epoch: 1 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 49.830 Boundary Ratio: 0.254 Contrastive_loss: 1.5894 (1.5313) Boundary_loss: 0.014346 (0.014321) Loss: 1.6037 (1.5456) +2025-09-11,09:19:09 | INFO | Train Epoch: 1 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 47.875 Boundary Ratio: 0.244 Contrastive_loss: 1.5625 (1.5341) Boundary_loss: 0.014299 (0.014319) Loss: 1.5768 (1.5484) +2025-09-11,09:20:16 | INFO | Train Epoch: 1 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 1.4105 (1.5238) Boundary_loss: 0.014217 (0.014311) Loss: 1.4247 (1.5381) +2025-09-11,09:21:23 | INFO | Train Epoch: 1 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 49.711 Boundary Ratio: 0.254 Contrastive_loss: 1.4586 (1.5188) Boundary_loss: 0.014288 (0.014309) Loss: 1.4729 (1.5331) +2025-09-11,09:22:30 | INFO | Train Epoch: 1 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 1.4212 (1.5118) Boundary_loss: 0.014260 (0.014305) Loss: 1.4355 (1.5261) +2025-09-11,09:23:37 | INFO | Train Epoch: 1 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 1.6212 (1.5191) Boundary_loss: 0.014231 (0.014300) Loss: 1.6354 (1.5334) +2025-09-11,09:24:43 | INFO | Train Epoch: 1 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 1.3274 (1.5071) Boundary_loss: 0.014254 (0.014298) Loss: 1.3416 (1.5214) +2025-09-11,09:25:50 | INFO | Train Epoch: 1 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 1.4732 (1.5051) Boundary_loss: 0.014253 (0.014295) Loss: 1.4875 (1.5194) +2025-09-11,09:26:57 | INFO | Train Epoch: 1 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 1.5079 (1.5053) Boundary_loss: 0.014319 (0.014296) Loss: 1.5222 (1.5196) +2025-09-11,09:28:04 | INFO | Train Epoch: 1 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 1.4135 (1.5005) Boundary_loss: 0.014239 (0.014293) Loss: 1.4278 (1.5148) +2025-09-11,09:29:11 | INFO | Train Epoch: 1 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 1.3963 (1.4953) Boundary_loss: 0.014204 (0.014289) Loss: 1.4105 (1.5095) +2025-09-11,09:30:18 | INFO | Train Epoch: 1 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 1.5505 (1.4979) Boundary_loss: 0.014289 (0.014289) Loss: 1.5648 (1.5122) +2025-09-11,09:31:25 | INFO | Train Epoch: 1 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 1.5207 (1.4989) Boundary_loss: 0.014281 (0.014288) Loss: 1.5350 (1.5132) +2025-09-11,09:32:31 | INFO | Train Epoch: 1 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 47.662 Boundary Ratio: 0.243 Contrastive_loss: 1.4689 (1.4976) Boundary_loss: 0.014327 (0.014290) Loss: 1.4832 (1.5119) +2025-09-11,09:33:38 | INFO | Train Epoch: 1 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 49.803 Boundary Ratio: 0.254 Contrastive_loss: 1.5992 (1.5019) Boundary_loss: 0.014320 (0.014291) Loss: 1.6136 (1.5161) +2025-09-11,09:34:45 | INFO | Train Epoch: 1 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 1.6758 (1.5088) Boundary_loss: 0.014257 (0.014290) Loss: 1.6900 (1.5231) +2025-09-11,09:35:52 | INFO | Train Epoch: 1 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.145 Boundary Ratio: 0.246 Contrastive_loss: 1.5148 (1.5090) Boundary_loss: 0.014254 (0.014289) Loss: 1.5291 (1.5233) +2025-09-11,09:36:59 | INFO | Train Epoch: 1 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 49.225 Boundary Ratio: 0.251 Contrastive_loss: 1.4167 (1.5056) Boundary_loss: 0.014300 (0.014289) Loss: 1.4310 (1.5199) +2025-09-11,09:38:06 | INFO | Train Epoch: 1 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 49.605 Boundary Ratio: 0.253 Contrastive_loss: 1.4694 (1.5043) Boundary_loss: 0.014311 (0.014290) Loss: 1.4837 (1.5186) +2025-09-11,09:39:12 | INFO | Train Epoch: 1 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 47.779 Boundary Ratio: 0.244 Contrastive_loss: 1.5080 (1.5044) Boundary_loss: 0.014309 (0.014291) Loss: 1.5223 (1.5187) +2025-09-11,09:40:19 | INFO | Train Epoch: 1 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.5324 (1.5054) Boundary_loss: 0.014214 (0.014288) Loss: 1.5466 (1.5197) +2025-09-11,09:41:26 | INFO | Train Epoch: 1 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.740 Boundary Ratio: 0.254 Contrastive_loss: 1.3685 (1.5010) Boundary_loss: 0.014417 (0.014292) Loss: 1.3829 (1.5153) +2025-09-11,09:42:33 | INFO | Train Epoch: 1 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 47.904 Boundary Ratio: 0.244 Contrastive_loss: 1.5490 (1.5025) Boundary_loss: 0.014445 (0.014297) Loss: 1.5635 (1.5168) +2025-09-11,09:43:40 | INFO | Train Epoch: 1 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 47.559 Boundary Ratio: 0.243 Contrastive_loss: 1.7963 (1.5114) Boundary_loss: 0.014428 (0.014301) Loss: 1.8107 (1.5257) +2025-09-11,09:44:46 | INFO | Train Epoch: 1 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 1.5582 (1.5127) Boundary_loss: 0.014266 (0.014300) Loss: 1.5725 (1.5270) +2025-09-11,09:45:53 | INFO | Train Epoch: 1 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.4441 (1.5108) Boundary_loss: 0.014263 (0.014299) Loss: 1.4583 (1.5251) +2025-09-11,09:47:00 | INFO | Train Epoch: 1 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 49.389 Boundary Ratio: 0.252 Contrastive_loss: 1.4248 (1.5084) Boundary_loss: 0.014240 (0.014297) Loss: 1.4391 (1.5227) +2025-09-11,09:48:07 | INFO | Train Epoch: 1 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.148 Boundary Ratio: 0.246 Contrastive_loss: 1.5896 (1.5106) Boundary_loss: 0.014263 (0.014296) Loss: 1.6039 (1.5249) +2025-09-11,09:49:14 | INFO | Train Epoch: 1 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 1.5149 (1.5107) Boundary_loss: 0.014293 (0.014296) Loss: 1.5292 (1.5250) +2025-09-11,09:50:21 | INFO | Train Epoch: 1 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 1.6152 (1.5134) Boundary_loss: 0.014274 (0.014296) Loss: 1.6295 (1.5277) +2025-09-11,09:51:28 | INFO | Train Epoch: 1 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 1.5675 (1.5147) Boundary_loss: 0.014210 (0.014293) Loss: 1.5817 (1.5290) +2025-09-11,09:52:34 | INFO | Train Epoch: 1 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 50.293 Boundary Ratio: 0.257 Contrastive_loss: 1.4905 (1.5141) Boundary_loss: 0.014412 (0.014296) Loss: 1.5050 (1.5284) +2025-09-11,09:53:41 | INFO | Train Epoch: 1 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 1.3418 (1.5100) Boundary_loss: 0.014250 (0.014295) Loss: 1.3561 (1.5243) +2025-09-11,09:54:48 | INFO | Train Epoch: 1 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 1.4787 (1.5093) Boundary_loss: 0.014224 (0.014294) Loss: 1.4929 (1.5236) +2025-09-11,09:55:55 | INFO | Train Epoch: 1 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 1.4341 (1.5076) Boundary_loss: 0.014235 (0.014292) Loss: 1.4483 (1.5219) +2025-09-11,09:57:02 | INFO | Train Epoch: 1 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 1.4555 (1.5064) Boundary_loss: 0.014274 (0.014292) Loss: 1.4698 (1.5207) +2025-09-11,09:58:09 | INFO | Train Epoch: 1 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 49.281 Boundary Ratio: 0.251 Contrastive_loss: 1.5544 (1.5075) Boundary_loss: 0.014272 (0.014291) Loss: 1.5686 (1.5218) +2025-09-11,09:59:15 | INFO | Train Epoch: 1 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.107 Boundary Ratio: 0.245 Contrastive_loss: 1.5784 (1.5090) Boundary_loss: 0.014272 (0.014291) Loss: 1.5927 (1.5233) +2025-09-11,10:00:22 | INFO | Train Epoch: 1 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 1.4447 (1.5077) Boundary_loss: 0.014230 (0.014290) Loss: 1.4589 (1.5219) +2025-09-11,10:01:29 | INFO | Train Epoch: 1 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.264 Boundary Ratio: 0.246 Contrastive_loss: 1.4477 (1.5064) Boundary_loss: 0.014339 (0.014291) Loss: 1.4621 (1.5207) +2025-09-11,10:02:36 | INFO | Train Epoch: 1 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 1.5300 (1.5069) Boundary_loss: 0.014285 (0.014291) Loss: 1.5443 (1.5212) +2025-09-11,10:03:43 | INFO | Train Epoch: 1 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.035 Boundary Ratio: 0.245 Contrastive_loss: 1.5202 (1.5072) Boundary_loss: 0.014234 (0.014290) Loss: 1.5344 (1.5215) +2025-09-11,10:04:49 | INFO | Train Epoch: 1 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 49.482 Boundary Ratio: 0.252 Contrastive_loss: 1.5572 (1.5081) Boundary_loss: 0.014283 (0.014289) Loss: 1.5715 (1.5224) +2025-09-11,10:05:56 | INFO | Train Epoch: 1 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.4206 (1.5065) Boundary_loss: 0.014247 (0.014289) Loss: 1.4349 (1.5208) +2025-09-11,10:07:03 | INFO | Train Epoch: 1 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.236 Boundary Ratio: 0.246 Contrastive_loss: 1.5432 (1.5072) Boundary_loss: 0.014217 (0.014287) Loss: 1.5574 (1.5214) +2025-09-11,10:08:10 | INFO | Train Epoch: 1 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.170 Boundary Ratio: 0.246 Contrastive_loss: 1.5111 (1.5072) Boundary_loss: 0.014267 (0.014287) Loss: 1.5254 (1.5215) +2025-09-11,10:09:17 | INFO | Train Epoch: 1 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 1.4782 (1.5067) Boundary_loss: 0.014299 (0.014287) Loss: 1.4925 (1.5210) +2025-09-11,10:10:24 | INFO | Train Epoch: 1 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 1.4471 (1.5057) Boundary_loss: 0.014262 (0.014287) Loss: 1.4614 (1.5200) +2025-09-11,10:11:30 | INFO | Train Epoch: 1 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 1.6029 (1.5073) Boundary_loss: 0.014228 (0.014286) Loss: 1.6172 (1.5216) +2025-09-11,10:12:37 | INFO | Train Epoch: 1 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.4680 (1.5067) Boundary_loss: 0.014213 (0.014284) Loss: 1.4822 (1.5210) +2025-09-11,10:13:44 | INFO | Train Epoch: 1 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.4156 (1.5052) Boundary_loss: 0.014215 (0.014283) Loss: 1.4298 (1.5194) +2025-09-11,10:14:51 | INFO | Train Epoch: 1 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 1.4603 (1.5044) Boundary_loss: 0.014150 (0.014281) Loss: 1.4745 (1.5187) +2025-09-11,10:15:58 | INFO | Train Epoch: 1 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 1.4281 (1.5032) Boundary_loss: 0.014227 (0.014280) Loss: 1.4423 (1.5175) +2025-09-11,10:17:05 | INFO | Train Epoch: 1 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 1.4082 (1.5017) Boundary_loss: 0.014228 (0.014279) Loss: 1.4224 (1.5160) +2025-09-11,10:18:11 | INFO | Train Epoch: 1 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.3784 (1.4998) Boundary_loss: 0.014184 (0.014278) Loss: 1.3926 (1.5140) +2025-09-11,10:19:18 | INFO | Train Epoch: 1 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 1.5775 (1.5010) Boundary_loss: 0.014231 (0.014277) Loss: 1.5917 (1.5152) +2025-09-11,10:20:25 | INFO | Train Epoch: 1 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 1.4053 (1.4995) Boundary_loss: 0.014242 (0.014277) Loss: 1.4195 (1.5138) +2025-09-11,10:21:32 | INFO | Train Epoch: 1 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 1.3730 (1.4976) Boundary_loss: 0.014211 (0.014276) Loss: 1.3872 (1.5119) +2025-09-11,10:22:39 | INFO | Train Epoch: 1 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.133 Boundary Ratio: 0.246 Contrastive_loss: 1.3993 (1.4962) Boundary_loss: 0.014310 (0.014276) Loss: 1.4136 (1.5104) +2025-09-11,10:23:46 | INFO | Train Epoch: 1 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 49.568 Boundary Ratio: 0.253 Contrastive_loss: 1.4504 (1.4955) Boundary_loss: 0.014259 (0.014276) Loss: 1.4646 (1.5098) +2025-09-11,10:24:53 | INFO | Train Epoch: 1 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 1.3318 (1.4932) Boundary_loss: 0.014239 (0.014275) Loss: 1.3460 (1.5074) +2025-09-11,10:26:00 | INFO | Train Epoch: 1 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 1.4134 (1.4920) Boundary_loss: 0.014249 (0.014275) Loss: 1.4276 (1.5063) +2025-09-11,10:27:07 | INFO | Train Epoch: 1 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.498 Boundary Ratio: 0.253 Contrastive_loss: 1.3603 (1.4902) Boundary_loss: 0.014214 (0.014274) Loss: 1.3745 (1.5045) +2025-09-11,10:28:13 | INFO | Train Epoch: 1 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 1.4245 (1.4893) Boundary_loss: 0.014210 (0.014273) Loss: 1.4387 (1.5036) +2025-09-11,10:29:20 | INFO | Train Epoch: 1 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 1.3214 (1.4870) Boundary_loss: 0.014228 (0.014273) Loss: 1.3356 (1.5013) +2025-09-11,10:30:27 | INFO | Train Epoch: 1 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 1.5313 (1.4876) Boundary_loss: 0.014202 (0.014272) Loss: 1.5455 (1.5019) +2025-09-11,10:31:34 | INFO | Train Epoch: 1 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 1.5576 (1.4886) Boundary_loss: 0.014208 (0.014271) Loss: 1.5718 (1.5028) +2025-09-11,10:32:41 | INFO | Train Epoch: 1 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 1.4520 (1.4881) Boundary_loss: 0.014181 (0.014270) Loss: 1.4662 (1.5023) +2025-09-11,10:33:48 | INFO | Train Epoch: 1 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 1.3609 (1.4864) Boundary_loss: 0.014236 (0.014269) Loss: 1.3752 (1.5007) +2025-09-11,10:34:55 | INFO | Train Epoch: 1 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 1.3868 (1.4852) Boundary_loss: 0.014205 (0.014268) Loss: 1.4010 (1.4995) +2025-09-11,10:36:02 | INFO | Train Epoch: 1 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 1.3979 (1.4841) Boundary_loss: 0.014261 (0.014268) Loss: 1.4121 (1.4984) +2025-09-11,10:37:08 | INFO | Train Epoch: 1 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 1.4332 (1.4835) Boundary_loss: 0.014200 (0.014268) Loss: 1.4474 (1.4977) +2025-09-11,10:38:15 | INFO | Train Epoch: 1 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 1.4232 (1.4827) Boundary_loss: 0.014233 (0.014267) Loss: 1.4374 (1.4970) +2025-09-11,10:39:22 | INFO | Train Epoch: 1 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.254 Boundary Ratio: 0.246 Contrastive_loss: 1.2589 (1.4800) Boundary_loss: 0.014196 (0.014266) Loss: 1.2731 (1.4943) +2025-09-11,10:40:29 | INFO | Train Epoch: 1 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 49.777 Boundary Ratio: 0.254 Contrastive_loss: 1.4008 (1.4791) Boundary_loss: 0.014418 (0.014268) Loss: 1.4152 (1.4934) +2025-09-11,10:41:36 | INFO | Train Epoch: 1 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 1.2062 (1.4759) Boundary_loss: 0.014252 (0.014268) Loss: 1.2205 (1.4901) +2025-09-11,10:42:43 | INFO | Train Epoch: 1 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 49.324 Boundary Ratio: 0.252 Contrastive_loss: 1.3466 (1.4744) Boundary_loss: 0.014299 (0.014268) Loss: 1.3609 (1.4886) +2025-09-11,10:43:50 | INFO | Train Epoch: 1 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.953 Boundary Ratio: 0.255 Contrastive_loss: 1.3568 (1.4730) Boundary_loss: 0.014319 (0.014269) Loss: 1.3711 (1.4873) +2025-09-11,10:44:56 | INFO | Train Epoch: 1 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 1.3413 (1.4715) Boundary_loss: 0.014227 (0.014268) Loss: 1.3556 (1.4858) +2025-09-11,10:46:03 | INFO | Train Epoch: 1 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 1.4590 (1.4714) Boundary_loss: 0.014185 (0.014267) Loss: 1.4732 (1.4857) +2025-09-11,10:47:10 | INFO | Train Epoch: 1 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.3230 (1.4697) Boundary_loss: 0.014206 (0.014267) Loss: 1.3372 (1.4840) +2025-09-11,10:48:17 | INFO | Train Epoch: 1 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 1.3163 (1.4681) Boundary_loss: 0.014165 (0.014266) Loss: 1.3305 (1.4823) +2025-09-11,10:49:24 | INFO | Train Epoch: 1 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 1.2550 (1.4657) Boundary_loss: 0.014166 (0.014265) Loss: 1.2692 (1.4800) +2025-09-11,10:50:31 | INFO | Train Epoch: 1 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 1.4804 (1.4659) Boundary_loss: 0.014208 (0.014264) Loss: 1.4946 (1.4802) +2025-09-11,10:51:38 | INFO | Train Epoch: 1 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 1.1959 (1.4630) Boundary_loss: 0.014193 (0.014263) Loss: 1.2101 (1.4773) +2025-09-11,10:52:44 | INFO | Train Epoch: 1 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 1.4303 (1.4627) Boundary_loss: 0.014162 (0.014262) Loss: 1.4445 (1.4769) +2025-09-11,10:53:51 | INFO | Train Epoch: 1 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.3136 (1.4611) Boundary_loss: 0.014194 (0.014261) Loss: 1.3278 (1.4754) +2025-09-11,10:54:58 | INFO | Train Epoch: 1 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.3711 (1.4602) Boundary_loss: 0.014181 (0.014261) Loss: 1.3852 (1.4745) +2025-09-11,10:56:05 | INFO | Train Epoch: 1 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 1.2847 (1.4584) Boundary_loss: 0.014239 (0.014260) Loss: 1.2990 (1.4727) +2025-09-11,10:57:12 | INFO | Train Epoch: 1 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.150 Boundary Ratio: 0.246 Contrastive_loss: 1.3768 (1.4576) Boundary_loss: 0.014219 (0.014260) Loss: 1.3910 (1.4718) +2025-09-11,10:58:19 | INFO | Train Epoch: 1 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 1.3090 (1.4561) Boundary_loss: 0.014213 (0.014259) Loss: 1.3233 (1.4704) +2025-09-11,10:59:26 | INFO | Train Epoch: 1 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 1.3862 (1.4554) Boundary_loss: 0.014219 (0.014259) Loss: 1.4004 (1.4697) +2025-09-11,11:00:33 | INFO | Train Epoch: 1 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 49.438 Boundary Ratio: 0.252 Contrastive_loss: 1.3859 (1.4547) Boundary_loss: 0.014266 (0.014259) Loss: 1.4002 (1.4690) +2025-09-11,11:01:39 | INFO | Train Epoch: 1 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.277 Boundary Ratio: 0.246 Contrastive_loss: 1.3084 (1.4533) Boundary_loss: 0.014208 (0.014259) Loss: 1.3226 (1.4676) +2025-09-11,11:02:46 | INFO | Train Epoch: 1 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 1.3196 (1.4520) Boundary_loss: 0.014187 (0.014258) Loss: 1.3338 (1.4663) +2025-09-11,11:03:53 | INFO | Train Epoch: 1 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 47.855 Boundary Ratio: 0.244 Contrastive_loss: 1.2644 (1.4502) Boundary_loss: 0.014243 (0.014258) Loss: 1.2786 (1.4645) +2025-09-11,11:05:00 | INFO | Train Epoch: 1 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 1.5723 (1.4514) Boundary_loss: 0.014198 (0.014257) Loss: 1.5865 (1.4656) +2025-09-11,11:06:07 | INFO | Train Epoch: 1 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 47.846 Boundary Ratio: 0.244 Contrastive_loss: 1.3571 (1.4505) Boundary_loss: 0.014229 (0.014257) Loss: 1.3713 (1.4648) +2025-09-11,11:07:14 | INFO | Train Epoch: 1 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.3211 (1.4493) Boundary_loss: 0.014180 (0.014256) Loss: 1.3352 (1.4636) +2025-09-11,11:08:20 | INFO | Train Epoch: 1 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 1.3659 (1.4485) Boundary_loss: 0.014197 (0.014256) Loss: 1.3801 (1.4628) +2025-09-11,11:09:27 | INFO | Train Epoch: 1 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 49.320 Boundary Ratio: 0.252 Contrastive_loss: 1.3410 (1.4476) Boundary_loss: 0.014194 (0.014255) Loss: 1.3552 (1.4618) +2025-09-11,11:10:34 | INFO | Train Epoch: 1 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 1.4606 (1.4477) Boundary_loss: 0.014232 (0.014255) Loss: 1.4749 (1.4619) +2025-09-11,11:11:41 | INFO | Train Epoch: 1 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 1.3154 (1.4465) Boundary_loss: 0.014224 (0.014255) Loss: 1.3296 (1.4608) +2025-09-11,11:12:48 | INFO | Train Epoch: 1 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 1.3471 (1.4456) Boundary_loss: 0.014223 (0.014254) Loss: 1.3614 (1.4599) +2025-09-11,11:13:55 | INFO | Train Epoch: 1 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 47.334 Boundary Ratio: 0.241 Contrastive_loss: 1.4253 (1.4454) Boundary_loss: 0.014531 (0.014257) Loss: 1.4398 (1.4597) +2025-09-11,11:15:01 | INFO | Train Epoch: 1 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 1.2296 (1.4436) Boundary_loss: 0.014204 (0.014256) Loss: 1.2438 (1.4578) +2025-09-11,11:16:08 | INFO | Train Epoch: 1 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 1.4081 (1.4433) Boundary_loss: 0.014175 (0.014256) Loss: 1.4223 (1.4575) +2025-09-11,11:17:15 | INFO | Train Epoch: 1 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 1.4090 (1.4430) Boundary_loss: 0.014209 (0.014255) Loss: 1.4232 (1.4572) +2025-09-11,11:18:22 | INFO | Train Epoch: 1 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 1.3575 (1.4422) Boundary_loss: 0.014226 (0.014255) Loss: 1.3717 (1.4565) +2025-09-11,11:19:29 | INFO | Train Epoch: 1 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 1.3917 (1.4418) Boundary_loss: 0.014199 (0.014255) Loss: 1.4059 (1.4561) +2025-09-11,11:20:36 | INFO | Train Epoch: 1 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 1.3974 (1.4414) Boundary_loss: 0.014151 (0.014254) Loss: 1.4115 (1.4557) +2025-09-11,11:21:43 | INFO | Train Epoch: 1 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 1.4287 (1.4413) Boundary_loss: 0.014180 (0.014253) Loss: 1.4429 (1.4556) +2025-09-11,11:22:49 | INFO | Train Epoch: 1 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 49.178 Boundary Ratio: 0.251 Contrastive_loss: 1.3818 (1.4408) Boundary_loss: 0.014242 (0.014253) Loss: 1.3961 (1.4551) +2025-09-11,11:23:56 | INFO | Train Epoch: 1 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 47.686 Boundary Ratio: 0.243 Contrastive_loss: 1.3068 (1.4398) Boundary_loss: 0.014243 (0.014253) Loss: 1.3211 (1.4540) +2025-09-11,11:25:03 | INFO | Train Epoch: 1 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 1.3778 (1.4393) Boundary_loss: 0.014158 (0.014252) Loss: 1.3919 (1.4535) +2025-09-11,11:26:10 | INFO | Train Epoch: 1 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.160 Boundary Ratio: 0.246 Contrastive_loss: 1.3000 (1.4381) Boundary_loss: 0.014173 (0.014252) Loss: 1.3141 (1.4524) +2025-09-11,11:27:17 | INFO | Train Epoch: 1 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 1.3562 (1.4375) Boundary_loss: 0.014195 (0.014251) Loss: 1.3704 (1.4517) +2025-09-11,11:28:24 | INFO | Train Epoch: 1 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 1.4235 (1.4374) Boundary_loss: 0.014189 (0.014251) Loss: 1.4377 (1.4516) +2025-09-11,11:29:31 | INFO | Train Epoch: 1 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 1.1621 (1.4352) Boundary_loss: 0.014190 (0.014250) Loss: 1.1763 (1.4495) +2025-09-11,11:30:38 | INFO | Train Epoch: 1 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 1.2710 (1.4340) Boundary_loss: 0.014205 (0.014250) Loss: 1.2852 (1.4482) +2025-09-11,11:31:45 | INFO | Train Epoch: 1 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 1.4324 (1.4339) Boundary_loss: 0.014199 (0.014249) Loss: 1.4466 (1.4482) +2025-09-11,11:32:51 | INFO | Train Epoch: 1 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 47.596 Boundary Ratio: 0.243 Contrastive_loss: 1.3765 (1.4335) Boundary_loss: 0.014279 (0.014250) Loss: 1.3908 (1.4478) +2025-09-11,11:33:58 | INFO | Train Epoch: 1 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 1.4616 (1.4337) Boundary_loss: 0.014162 (0.014249) Loss: 1.4757 (1.4480) +2025-09-11,11:35:05 | INFO | Train Epoch: 1 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.4926 (1.4342) Boundary_loss: 0.014184 (0.014248) Loss: 1.5068 (1.4484) +2025-09-11,11:36:12 | INFO | Train Epoch: 1 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.441 Boundary Ratio: 0.252 Contrastive_loss: 1.4688 (1.4344) Boundary_loss: 0.014176 (0.014248) Loss: 1.4830 (1.4487) +2025-09-11,11:37:19 | INFO | Train Epoch: 1 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 1.5634 (1.4354) Boundary_loss: 0.014192 (0.014247) Loss: 1.5776 (1.4496) +2025-09-11,11:38:25 | INFO | Train Epoch: 1 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 1.3769 (1.4350) Boundary_loss: 0.014221 (0.014247) Loss: 1.3912 (1.4492) +2025-09-11,11:39:32 | INFO | Train Epoch: 1 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 1.4106 (1.4348) Boundary_loss: 0.014151 (0.014247) Loss: 1.4247 (1.4490) +2025-09-11,11:40:39 | INFO | Train Epoch: 1 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.611 Boundary Ratio: 0.253 Contrastive_loss: 1.4358 (1.4348) Boundary_loss: 0.014267 (0.014247) Loss: 1.4500 (1.4490) +2025-09-11,11:41:46 | INFO | Train Epoch: 1 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 1.4580 (1.4349) Boundary_loss: 0.014171 (0.014246) Loss: 1.4722 (1.4492) +2025-09-11,11:42:53 | INFO | Train Epoch: 1 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 1.3404 (1.4343) Boundary_loss: 0.014182 (0.014246) Loss: 1.3546 (1.4485) +2025-09-11,11:43:59 | INFO | Train Epoch: 1 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 1.3917 (1.4340) Boundary_loss: 0.014183 (0.014245) Loss: 1.4059 (1.4482) +2025-09-11,11:45:06 | INFO | Train Epoch: 1 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 1.2841 (1.4329) Boundary_loss: 0.014150 (0.014245) Loss: 1.2983 (1.4472) +2025-09-11,11:46:13 | INFO | Train Epoch: 1 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 1.3510 (1.4323) Boundary_loss: 0.014268 (0.014245) Loss: 1.3652 (1.4466) +2025-09-11,11:47:20 | INFO | Train Epoch: 1 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.4005 (1.4321) Boundary_loss: 0.014141 (0.014244) Loss: 1.4146 (1.4464) +2025-09-11,11:48:27 | INFO | Train Epoch: 1 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 1.3332 (1.4314) Boundary_loss: 0.014219 (0.014244) Loss: 1.3474 (1.4457) +2025-09-11,11:49:34 | INFO | Train Epoch: 1 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 1.4450 (1.4315) Boundary_loss: 0.014196 (0.014244) Loss: 1.4592 (1.4458) +2025-09-11,11:50:41 | INFO | Train Epoch: 1 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 1.3216 (1.4308) Boundary_loss: 0.014175 (0.014243) Loss: 1.3357 (1.4450) +2025-09-11,11:51:48 | INFO | Train Epoch: 1 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 1.3625 (1.4303) Boundary_loss: 0.014152 (0.014242) Loss: 1.3766 (1.4446) +2025-09-11,11:52:54 | INFO | Train Epoch: 1 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.408 Boundary Ratio: 0.252 Contrastive_loss: 1.3708 (1.4299) Boundary_loss: 0.014143 (0.014242) Loss: 1.3849 (1.4442) +2025-09-11,11:54:01 | INFO | Train Epoch: 1 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 1.1911 (1.4283) Boundary_loss: 0.014151 (0.014241) Loss: 1.2052 (1.4426) +2025-09-11,11:55:08 | INFO | Train Epoch: 1 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 1.2151 (1.4269) Boundary_loss: 0.014196 (0.014241) Loss: 1.2293 (1.4412) +2025-09-11,11:56:15 | INFO | Train Epoch: 1 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 1.2353 (1.4257) Boundary_loss: 0.014221 (0.014241) Loss: 1.2496 (1.4399) +2025-09-11,11:57:22 | INFO | Train Epoch: 1 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 1.3366 (1.4251) Boundary_loss: 0.014136 (0.014240) Loss: 1.3508 (1.4393) +2025-09-11,11:58:29 | INFO | Train Epoch: 1 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.074 Boundary Ratio: 0.245 Contrastive_loss: 1.5324 (1.4258) Boundary_loss: 0.014204 (0.014240) Loss: 1.5466 (1.4400) +2025-09-11,11:59:36 | INFO | Train Epoch: 1 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.3782 (1.4255) Boundary_loss: 0.014172 (0.014239) Loss: 1.3924 (1.4397) +2025-09-11,12:00:43 | INFO | Train Epoch: 1 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 49.168 Boundary Ratio: 0.251 Contrastive_loss: 1.3495 (1.4250) Boundary_loss: 0.014214 (0.014239) Loss: 1.3637 (1.4392) +2025-09-11,12:01:50 | INFO | Train Epoch: 1 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.2962 (1.4242) Boundary_loss: 0.014118 (0.014238) Loss: 1.3103 (1.4384) +2025-09-11,12:02:56 | INFO | Train Epoch: 1 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 1.3096 (1.4234) Boundary_loss: 0.014146 (0.014238) Loss: 1.3237 (1.4377) +2025-09-11,12:04:03 | INFO | Train Epoch: 1 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.467 Boundary Ratio: 0.252 Contrastive_loss: 1.3553 (1.4230) Boundary_loss: 0.014213 (0.014238) Loss: 1.3696 (1.4372) +2025-09-11,12:05:10 | INFO | Train Epoch: 1 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 1.2522 (1.4219) Boundary_loss: 0.014135 (0.014237) Loss: 1.2663 (1.4362) +2025-09-11,12:06:17 | INFO | Train Epoch: 1 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 1.3594 (1.4215) Boundary_loss: 0.014128 (0.014236) Loss: 1.3736 (1.4358) +2025-09-11,12:07:24 | INFO | Train Epoch: 1 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 1.1988 (1.4202) Boundary_loss: 0.014179 (0.014236) Loss: 1.2130 (1.4344) +2025-09-11,12:08:31 | INFO | Train Epoch: 1 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.3360 (1.4197) Boundary_loss: 0.014140 (0.014235) Loss: 1.3502 (1.4339) +2025-09-11,12:09:37 | INFO | Train Epoch: 1 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 1.3756 (1.4194) Boundary_loss: 0.014178 (0.014235) Loss: 1.3898 (1.4336) +2025-09-11,12:10:44 | INFO | Train Epoch: 1 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 49.363 Boundary Ratio: 0.252 Contrastive_loss: 1.2534 (1.4184) Boundary_loss: 0.014182 (0.014235) Loss: 1.2676 (1.4326) +2025-09-11,12:11:51 | INFO | Train Epoch: 1 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.404 Boundary Ratio: 0.252 Contrastive_loss: 1.2975 (1.4177) Boundary_loss: 0.014212 (0.014235) Loss: 1.3117 (1.4319) +2025-09-11,12:12:58 | INFO | Train Epoch: 1 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.391 Boundary Ratio: 0.247 Contrastive_loss: 1.5057 (1.4182) Boundary_loss: 0.014185 (0.014234) Loss: 1.5199 (1.4324) +2025-09-11,12:14:05 | INFO | Train Epoch: 1 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 1.2792 (1.4174) Boundary_loss: 0.014140 (0.014234) Loss: 1.2934 (1.4316) +2025-09-11,12:15:12 | INFO | Train Epoch: 1 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 49.377 Boundary Ratio: 0.252 Contrastive_loss: 1.3959 (1.4172) Boundary_loss: 0.014139 (0.014233) Loss: 1.4100 (1.4315) +2025-09-11,12:16:19 | INFO | Train Epoch: 1 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 1.3133 (1.4166) Boundary_loss: 0.014115 (0.014233) Loss: 1.3275 (1.4308) +2025-09-11,12:17:26 | INFO | Train Epoch: 1 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 1.3111 (1.4160) Boundary_loss: 0.014172 (0.014232) Loss: 1.3253 (1.4302) +2025-09-11,12:18:33 | INFO | Train Epoch: 1 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.617 Boundary Ratio: 0.253 Contrastive_loss: 1.2817 (1.4152) Boundary_loss: 0.014212 (0.014232) Loss: 1.2959 (1.4295) +2025-09-11,12:19:39 | INFO | Train Epoch: 1 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 1.3386 (1.4148) Boundary_loss: 0.014143 (0.014232) Loss: 1.3527 (1.4290) +2025-09-11,12:20:46 | INFO | Train Epoch: 1 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.3013 (1.4141) Boundary_loss: 0.014192 (0.014231) Loss: 1.3155 (1.4284) +2025-09-11,12:21:53 | INFO | Train Epoch: 1 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 1.2340 (1.4131) Boundary_loss: 0.014224 (0.014231) Loss: 1.2483 (1.4273) +2025-09-11,12:23:00 | INFO | Train Epoch: 1 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 1.3262 (1.4126) Boundary_loss: 0.014141 (0.014231) Loss: 1.3403 (1.4268) +2025-09-11,12:24:07 | INFO | Train Epoch: 1 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 47.793 Boundary Ratio: 0.244 Contrastive_loss: 1.2228 (1.4115) Boundary_loss: 0.014238 (0.014231) Loss: 1.2371 (1.4258) +2025-09-11,12:25:14 | INFO | Train Epoch: 1 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 1.3401 (1.4111) Boundary_loss: 0.014152 (0.014230) Loss: 1.3542 (1.4254) +2025-09-11,12:26:21 | INFO | Train Epoch: 1 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 47.594 Boundary Ratio: 0.243 Contrastive_loss: 1.3581 (1.4108) Boundary_loss: 0.014330 (0.014231) Loss: 1.3724 (1.4251) +2025-09-11,12:27:27 | INFO | Train Epoch: 1 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 1.3041 (1.4102) Boundary_loss: 0.014181 (0.014231) Loss: 1.3182 (1.4245) +2025-09-11,12:28:34 | INFO | Train Epoch: 1 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 1.1531 (1.4088) Boundary_loss: 0.014172 (0.014230) Loss: 1.1672 (1.4230) +2025-09-11,12:29:41 | INFO | Train Epoch: 1 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 1.2400 (1.4079) Boundary_loss: 0.014139 (0.014230) Loss: 1.2541 (1.4221) +2025-09-11,12:30:48 | INFO | Train Epoch: 1 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 47.758 Boundary Ratio: 0.244 Contrastive_loss: 1.2555 (1.4071) Boundary_loss: 0.014238 (0.014230) Loss: 1.2698 (1.4213) +2025-09-11,12:31:55 | INFO | Train Epoch: 1 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 1.2630 (1.4063) Boundary_loss: 0.014189 (0.014230) Loss: 1.2772 (1.4205) +2025-09-11,12:33:02 | INFO | Train Epoch: 1 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 1.4208 (1.4064) Boundary_loss: 0.014184 (0.014229) Loss: 1.4350 (1.4206) +2025-09-11,12:34:09 | INFO | Train Epoch: 1 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 1.2537 (1.4055) Boundary_loss: 0.014287 (0.014230) Loss: 1.2680 (1.4198) +2025-09-11,12:35:16 | INFO | Train Epoch: 1 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 1.2198 (1.4045) Boundary_loss: 0.014174 (0.014229) Loss: 1.2339 (1.4188) +2025-09-11,12:36:22 | INFO | Train Epoch: 1 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 1.3391 (1.4042) Boundary_loss: 0.014179 (0.014229) Loss: 1.3532 (1.4184) +2025-09-11,12:37:29 | INFO | Train Epoch: 1 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 1.3699 (1.4040) Boundary_loss: 0.014181 (0.014229) Loss: 1.3840 (1.4182) +2025-09-11,12:38:36 | INFO | Train Epoch: 1 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 1.1397 (1.4026) Boundary_loss: 0.014219 (0.014229) Loss: 1.1539 (1.4168) +2025-09-11,12:39:43 | INFO | Train Epoch: 1 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 1.3460 (1.4023) Boundary_loss: 0.014165 (0.014229) Loss: 1.3602 (1.4165) +2025-09-11,12:40:50 | INFO | Train Epoch: 1 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 1.3372 (1.4020) Boundary_loss: 0.014173 (0.014228) Loss: 1.3514 (1.4162) +2025-09-11,12:41:57 | INFO | Train Epoch: 1 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.307 Boundary Ratio: 0.246 Contrastive_loss: 1.2925 (1.4014) Boundary_loss: 0.014177 (0.014228) Loss: 1.3066 (1.4156) +2025-09-11,12:43:04 | INFO | Train Epoch: 1 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.547 Boundary Ratio: 0.253 Contrastive_loss: 1.3598 (1.4012) Boundary_loss: 0.014204 (0.014228) Loss: 1.3740 (1.4154) +2025-09-11,12:44:11 | INFO | Train Epoch: 1 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 1.1776 (1.4001) Boundary_loss: 0.014158 (0.014227) Loss: 1.1917 (1.4143) +2025-09-11,12:45:18 | INFO | Train Epoch: 1 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 1.4906 (1.4005) Boundary_loss: 0.014140 (0.014227) Loss: 1.5048 (1.4147) +2025-09-11,12:46:24 | INFO | Train Epoch: 1 [10035712/26365952 (38%)] Avg Boundaries (per batch): 49.283 Boundary Ratio: 0.251 Contrastive_loss: 1.2991 (1.4000) Boundary_loss: 0.014135 (0.014227) Loss: 1.3133 (1.4142) +2025-09-11,12:47:31 | INFO | Train Epoch: 1 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.184 Boundary Ratio: 0.246 Contrastive_loss: 1.1621 (1.3988) Boundary_loss: 0.014207 (0.014226) Loss: 1.1763 (1.4130) +2025-09-11,12:48:38 | INFO | Train Epoch: 1 [10138112/26365952 (38%)] Avg Boundaries (per batch): 49.410 Boundary Ratio: 0.252 Contrastive_loss: 1.2833 (1.3982) Boundary_loss: 0.014176 (0.014226) Loss: 1.2974 (1.4124) +2025-09-11,12:49:45 | INFO | Train Epoch: 1 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 1.4357 (1.3984) Boundary_loss: 0.014141 (0.014226) Loss: 1.4499 (1.4126) +2025-09-11,12:50:51 | INFO | Train Epoch: 1 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 1.3328 (1.3981) Boundary_loss: 0.014107 (0.014225) Loss: 1.3469 (1.4123) +2025-09-11,12:51:58 | INFO | Train Epoch: 1 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 1.3193 (1.3977) Boundary_loss: 0.014129 (0.014225) Loss: 1.3334 (1.4119) +2025-09-11,12:53:05 | INFO | Train Epoch: 1 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 1.3006 (1.3972) Boundary_loss: 0.014138 (0.014224) Loss: 1.3147 (1.4114) +2025-09-11,12:54:12 | INFO | Train Epoch: 1 [10394112/26365952 (39%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 1.3176 (1.3968) Boundary_loss: 0.014298 (0.014225) Loss: 1.3319 (1.4110) +2025-09-11,12:55:18 | INFO | Train Epoch: 1 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.3467 (1.3966) Boundary_loss: 0.014157 (0.014224) Loss: 1.3609 (1.4108) +2025-09-11,12:56:25 | INFO | Train Epoch: 1 [10496512/26365952 (40%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 1.2476 (1.3959) Boundary_loss: 0.014126 (0.014224) Loss: 1.2617 (1.4101) +2025-09-11,12:57:32 | INFO | Train Epoch: 1 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 1.2703 (1.3952) Boundary_loss: 0.014134 (0.014223) Loss: 1.2844 (1.4095) +2025-09-11,12:58:39 | INFO | Train Epoch: 1 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 1.2735 (1.3947) Boundary_loss: 0.014142 (0.014223) Loss: 1.2877 (1.4089) +2025-09-11,12:59:45 | INFO | Train Epoch: 1 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 1.1882 (1.3937) Boundary_loss: 0.014144 (0.014223) Loss: 1.2023 (1.4079) +2025-09-11,13:00:52 | INFO | Train Epoch: 1 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 1.4720 (1.3940) Boundary_loss: 0.014195 (0.014222) Loss: 1.4862 (1.4083) +2025-09-11,13:01:59 | INFO | Train Epoch: 1 [10752512/26365952 (41%)] Avg Boundaries (per batch): 47.961 Boundary Ratio: 0.245 Contrastive_loss: 1.2147 (1.3932) Boundary_loss: 0.014270 (0.014223) Loss: 1.2290 (1.4074) +2025-09-11,13:03:06 | INFO | Train Epoch: 1 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 1.2622 (1.3926) Boundary_loss: 0.014182 (0.014223) Loss: 1.2763 (1.4068) +2025-09-11,13:04:12 | INFO | Train Epoch: 1 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 1.3059 (1.3922) Boundary_loss: 0.014172 (0.014222) Loss: 1.3201 (1.4064) +2025-09-11,13:05:19 | INFO | Train Epoch: 1 [10906112/26365952 (41%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 1.1595 (1.3911) Boundary_loss: 0.014124 (0.014222) Loss: 1.1736 (1.4053) +2025-09-11,13:06:26 | INFO | Train Epoch: 1 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 1.3694 (1.3910) Boundary_loss: 0.014233 (0.014222) Loss: 1.3836 (1.4052) +2025-09-11,13:07:33 | INFO | Train Epoch: 1 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.963 Boundary Ratio: 0.255 Contrastive_loss: 1.3179 (1.3906) Boundary_loss: 0.014254 (0.014222) Loss: 1.3321 (1.4049) +2025-09-11,13:08:40 | INFO | Train Epoch: 1 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.451 Boundary Ratio: 0.252 Contrastive_loss: 1.1442 (1.3895) Boundary_loss: 0.014254 (0.014222) Loss: 1.1584 (1.4037) +2025-09-11,13:09:46 | INFO | Train Epoch: 1 [11110912/26365952 (42%)] Avg Boundaries (per batch): 47.768 Boundary Ratio: 0.244 Contrastive_loss: 1.2913 (1.3891) Boundary_loss: 0.014172 (0.014222) Loss: 1.3055 (1.4033) +2025-09-11,13:10:53 | INFO | Train Epoch: 1 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 1.1480 (1.3880) Boundary_loss: 0.014199 (0.014222) Loss: 1.1622 (1.4022) +2025-09-11,13:12:00 | INFO | Train Epoch: 1 [11213312/26365952 (43%)] Avg Boundaries (per batch): 49.713 Boundary Ratio: 0.254 Contrastive_loss: 1.1877 (1.3870) Boundary_loss: 0.014227 (0.014222) Loss: 1.2019 (1.4013) +2025-09-11,13:13:07 | INFO | Train Epoch: 1 [11264512/26365952 (43%)] Avg Boundaries (per batch): 49.303 Boundary Ratio: 0.252 Contrastive_loss: 1.1271 (1.3859) Boundary_loss: 0.014158 (0.014222) Loss: 1.1412 (1.4001) +2025-09-11,13:14:14 | INFO | Train Epoch: 1 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 1.3956 (1.3859) Boundary_loss: 0.014092 (0.014221) Loss: 1.4097 (1.4001) +2025-09-11,13:15:20 | INFO | Train Epoch: 1 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.033 Boundary Ratio: 0.245 Contrastive_loss: 1.2224 (1.3852) Boundary_loss: 0.014177 (0.014221) Loss: 1.2366 (1.3994) +2025-09-11,13:16:27 | INFO | Train Epoch: 1 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 1.3553 (1.3850) Boundary_loss: 0.014163 (0.014221) Loss: 1.3695 (1.3993) +2025-09-11,13:17:34 | INFO | Train Epoch: 1 [11469312/26365952 (44%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 1.2486 (1.3844) Boundary_loss: 0.014146 (0.014220) Loss: 1.2627 (1.3987) +2025-09-11,13:18:41 | INFO | Train Epoch: 1 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.3504 (1.3843) Boundary_loss: 0.014162 (0.014220) Loss: 1.3645 (1.3985) +2025-09-11,13:19:48 | INFO | Train Epoch: 1 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.275 Boundary Ratio: 0.246 Contrastive_loss: 1.1978 (1.3835) Boundary_loss: 0.014149 (0.014220) Loss: 1.2119 (1.3977) +2025-09-11,13:20:54 | INFO | Train Epoch: 1 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 1.3100 (1.3831) Boundary_loss: 0.014141 (0.014219) Loss: 1.3241 (1.3974) +2025-09-11,13:22:01 | INFO | Train Epoch: 1 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 1.3885 (1.3832) Boundary_loss: 0.014173 (0.014219) Loss: 1.4027 (1.3974) +2025-09-11,13:23:08 | INFO | Train Epoch: 1 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 1.3501 (1.3830) Boundary_loss: 0.014123 (0.014219) Loss: 1.3642 (1.3972) +2025-09-11,13:24:15 | INFO | Train Epoch: 1 [11776512/26365952 (45%)] Avg Boundaries (per batch): 49.551 Boundary Ratio: 0.253 Contrastive_loss: 1.1516 (1.3820) Boundary_loss: 0.014207 (0.014219) Loss: 1.1658 (1.3962) +2025-09-11,13:25:21 | INFO | Train Epoch: 1 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 1.2947 (1.3816) Boundary_loss: 0.014177 (0.014218) Loss: 1.3089 (1.3959) +2025-09-11,13:26:28 | INFO | Train Epoch: 1 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 1.3176 (1.3814) Boundary_loss: 0.014130 (0.014218) Loss: 1.3317 (1.3956) +2025-09-11,13:27:35 | INFO | Train Epoch: 1 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.178 Boundary Ratio: 0.246 Contrastive_loss: 1.2541 (1.3808) Boundary_loss: 0.014148 (0.014218) Loss: 1.2683 (1.3950) +2025-09-11,13:28:42 | INFO | Train Epoch: 1 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 1.3727 (1.3808) Boundary_loss: 0.014104 (0.014217) Loss: 1.3868 (1.3950) +2025-09-11,13:29:48 | INFO | Train Epoch: 1 [12032512/26365952 (46%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 1.2866 (1.3804) Boundary_loss: 0.014186 (0.014217) Loss: 1.3008 (1.3946) +2025-09-11,13:30:55 | INFO | Train Epoch: 1 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 1.1737 (1.3795) Boundary_loss: 0.014142 (0.014217) Loss: 1.1878 (1.3937) +2025-09-11,13:32:02 | INFO | Train Epoch: 1 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 1.3788 (1.3795) Boundary_loss: 0.014187 (0.014217) Loss: 1.3930 (1.3937) +2025-09-11,13:33:09 | INFO | Train Epoch: 1 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.080 Boundary Ratio: 0.245 Contrastive_loss: 1.2674 (1.3791) Boundary_loss: 0.014160 (0.014216) Loss: 1.2815 (1.3933) +2025-09-11,13:34:15 | INFO | Train Epoch: 1 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 1.2347 (1.3785) Boundary_loss: 0.014149 (0.014216) Loss: 1.2489 (1.3927) +2025-09-11,13:35:22 | INFO | Train Epoch: 1 [12288512/26365952 (47%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 1.2453 (1.3779) Boundary_loss: 0.014140 (0.014216) Loss: 1.2595 (1.3921) +2025-09-11,13:36:29 | INFO | Train Epoch: 1 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 1.2344 (1.3773) Boundary_loss: 0.014153 (0.014216) Loss: 1.2485 (1.3915) +2025-09-11,13:37:36 | INFO | Train Epoch: 1 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.314 Boundary Ratio: 0.247 Contrastive_loss: 1.1735 (1.3765) Boundary_loss: 0.014142 (0.014215) Loss: 1.1877 (1.3907) +2025-09-11,13:38:42 | INFO | Train Epoch: 1 [12442112/26365952 (47%)] Avg Boundaries (per batch): 49.547 Boundary Ratio: 0.253 Contrastive_loss: 1.3287 (1.3763) Boundary_loss: 0.014203 (0.014215) Loss: 1.3429 (1.3905) +2025-09-11,13:39:49 | INFO | Train Epoch: 1 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 1.2954 (1.3759) Boundary_loss: 0.014167 (0.014215) Loss: 1.3096 (1.3902) +2025-09-11,13:40:56 | INFO | Train Epoch: 1 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 1.2081 (1.3753) Boundary_loss: 0.014138 (0.014215) Loss: 1.2222 (1.3895) +2025-09-11,13:42:03 | INFO | Train Epoch: 1 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.2609 (1.3748) Boundary_loss: 0.014183 (0.014215) Loss: 1.2751 (1.3890) +2025-09-11,13:43:09 | INFO | Train Epoch: 1 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 1.2069 (1.3741) Boundary_loss: 0.014146 (0.014214) Loss: 1.2210 (1.3883) +2025-09-11,13:44:16 | INFO | Train Epoch: 1 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 1.2774 (1.3737) Boundary_loss: 0.014130 (0.014214) Loss: 1.2915 (1.3879) +2025-09-11,13:45:23 | INFO | Train Epoch: 1 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 1.3332 (1.3736) Boundary_loss: 0.014104 (0.014214) Loss: 1.3473 (1.3878) +2025-09-11,13:46:30 | INFO | Train Epoch: 1 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.119 Boundary Ratio: 0.246 Contrastive_loss: 1.3389 (1.3734) Boundary_loss: 0.014162 (0.014213) Loss: 1.3531 (1.3876) +2025-09-11,13:47:37 | INFO | Train Epoch: 1 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 1.2006 (1.3727) Boundary_loss: 0.014142 (0.014213) Loss: 1.2147 (1.3870) +2025-09-11,13:48:44 | INFO | Train Epoch: 1 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 1.3662 (1.3727) Boundary_loss: 0.014138 (0.014213) Loss: 1.3803 (1.3869) +2025-09-11,13:49:51 | INFO | Train Epoch: 1 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 1.2124 (1.3721) Boundary_loss: 0.014157 (0.014213) Loss: 1.2265 (1.3863) +2025-09-11,13:50:57 | INFO | Train Epoch: 1 [13005312/26365952 (49%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 1.2760 (1.3717) Boundary_loss: 0.014187 (0.014212) Loss: 1.2902 (1.3859) +2025-09-11,13:52:04 | INFO | Train Epoch: 1 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.2246 (1.3711) Boundary_loss: 0.014136 (0.014212) Loss: 1.2387 (1.3853) +2025-09-11,13:53:11 | INFO | Train Epoch: 1 [13107712/26365952 (50%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 1.1595 (1.3703) Boundary_loss: 0.014125 (0.014212) Loss: 1.1737 (1.3845) +2025-09-11,13:54:18 | INFO | Train Epoch: 1 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 1.2753 (1.3699) Boundary_loss: 0.014112 (0.014211) Loss: 1.2894 (1.3842) +2025-09-11,13:55:24 | INFO | Train Epoch: 1 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.375 Boundary Ratio: 0.247 Contrastive_loss: 1.2109 (1.3693) Boundary_loss: 0.014102 (0.014211) Loss: 1.2250 (1.3835) +2025-09-11,13:56:31 | INFO | Train Epoch: 1 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 1.1776 (1.3686) Boundary_loss: 0.014150 (0.014211) Loss: 1.1917 (1.3828) +2025-09-11,13:57:38 | INFO | Train Epoch: 1 [13312512/26365952 (50%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 1.4410 (1.3689) Boundary_loss: 0.014103 (0.014210) Loss: 1.4551 (1.3831) +2025-09-11,13:58:45 | INFO | Train Epoch: 1 [13363712/26365952 (51%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 1.2450 (1.3684) Boundary_loss: 0.014168 (0.014210) Loss: 1.2592 (1.3826) +2025-09-11,13:59:51 | INFO | Train Epoch: 1 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 1.2650 (1.3680) Boundary_loss: 0.014135 (0.014210) Loss: 1.2792 (1.3822) +2025-09-11,14:00:58 | INFO | Train Epoch: 1 [13466112/26365952 (51%)] Avg Boundaries (per batch): 49.336 Boundary Ratio: 0.252 Contrastive_loss: 1.2080 (1.3674) Boundary_loss: 0.014193 (0.014210) Loss: 1.2222 (1.3816) +2025-09-11,14:02:05 | INFO | Train Epoch: 1 [13517312/26365952 (51%)] Avg Boundaries (per batch): 47.754 Boundary Ratio: 0.244 Contrastive_loss: 1.1898 (1.3667) Boundary_loss: 0.014202 (0.014210) Loss: 1.2040 (1.3809) +2025-09-11,14:03:12 | INFO | Train Epoch: 1 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 1.3327 (1.3666) Boundary_loss: 0.014204 (0.014210) Loss: 1.3469 (1.3808) +2025-09-11,14:04:19 | INFO | Train Epoch: 1 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 1.2997 (1.3663) Boundary_loss: 0.014153 (0.014210) Loss: 1.3139 (1.3806) +2025-09-11,14:05:25 | INFO | Train Epoch: 1 [13670912/26365952 (52%)] Avg Boundaries (per batch): 49.428 Boundary Ratio: 0.252 Contrastive_loss: 1.2565 (1.3659) Boundary_loss: 0.014145 (0.014209) Loss: 1.2707 (1.3801) +2025-09-11,14:06:32 | INFO | Train Epoch: 1 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 1.2148 (1.3654) Boundary_loss: 0.014124 (0.014209) Loss: 1.2289 (1.3796) +2025-09-11,14:07:39 | INFO | Train Epoch: 1 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 1.2257 (1.3649) Boundary_loss: 0.014127 (0.014209) Loss: 1.2398 (1.3791) +2025-09-11,14:08:46 | INFO | Train Epoch: 1 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 1.4089 (1.3650) Boundary_loss: 0.014145 (0.014208) Loss: 1.4230 (1.3792) +2025-09-11,14:09:53 | INFO | Train Epoch: 1 [13875712/26365952 (53%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 1.3159 (1.3648) Boundary_loss: 0.014133 (0.014208) Loss: 1.3300 (1.3790) +2025-09-11,14:10:59 | INFO | Train Epoch: 1 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.152 Boundary Ratio: 0.246 Contrastive_loss: 1.2012 (1.3642) Boundary_loss: 0.014170 (0.014208) Loss: 1.2154 (1.3785) +2025-09-11,14:12:06 | INFO | Train Epoch: 1 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 1.2236 (1.3637) Boundary_loss: 0.014090 (0.014208) Loss: 1.2377 (1.3779) +2025-09-11,14:13:13 | INFO | Train Epoch: 1 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 1.2246 (1.3632) Boundary_loss: 0.014171 (0.014208) Loss: 1.2388 (1.3774) +2025-09-11,14:14:20 | INFO | Train Epoch: 1 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.275 Boundary Ratio: 0.246 Contrastive_loss: 1.2456 (1.3628) Boundary_loss: 0.014169 (0.014207) Loss: 1.2597 (1.3770) +2025-09-11,14:15:27 | INFO | Train Epoch: 1 [14131712/26365952 (54%)] Avg Boundaries (per batch): 49.693 Boundary Ratio: 0.254 Contrastive_loss: 1.1646 (1.3621) Boundary_loss: 0.014183 (0.014207) Loss: 1.1788 (1.3763) +2025-09-11,14:16:34 | INFO | Train Epoch: 1 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 1.3122 (1.3619) Boundary_loss: 0.014117 (0.014207) Loss: 1.3263 (1.3761) +2025-09-11,14:17:40 | INFO | Train Epoch: 1 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 1.2183 (1.3614) Boundary_loss: 0.014116 (0.014207) Loss: 1.2324 (1.3756) +2025-09-11,14:18:47 | INFO | Train Epoch: 1 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.324 Boundary Ratio: 0.247 Contrastive_loss: 1.2692 (1.3611) Boundary_loss: 0.014139 (0.014206) Loss: 1.2834 (1.3753) +2025-09-11,14:19:54 | INFO | Train Epoch: 1 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 1.3344 (1.3610) Boundary_loss: 0.014114 (0.014206) Loss: 1.3485 (1.3752) +2025-09-11,14:21:01 | INFO | Train Epoch: 1 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 1.1546 (1.3602) Boundary_loss: 0.014135 (0.014206) Loss: 1.1687 (1.3744) +2025-09-11,14:22:07 | INFO | Train Epoch: 1 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 1.2545 (1.3599) Boundary_loss: 0.014143 (0.014206) Loss: 1.2687 (1.3741) +2025-09-11,14:23:14 | INFO | Train Epoch: 1 [14490112/26365952 (55%)] Avg Boundaries (per batch): 49.580 Boundary Ratio: 0.253 Contrastive_loss: 1.2559 (1.3595) Boundary_loss: 0.014161 (0.014205) Loss: 1.2700 (1.3737) +2025-09-11,14:24:21 | INFO | Train Epoch: 1 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.131 Boundary Ratio: 0.246 Contrastive_loss: 1.2378 (1.3591) Boundary_loss: 0.014136 (0.014205) Loss: 1.2519 (1.3733) +2025-09-11,14:25:28 | INFO | Train Epoch: 1 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 1.3574 (1.3591) Boundary_loss: 0.014133 (0.014205) Loss: 1.3716 (1.3733) +2025-09-11,14:26:35 | INFO | Train Epoch: 1 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 1.0832 (1.3581) Boundary_loss: 0.014131 (0.014205) Loss: 1.0973 (1.3723) +2025-09-11,14:27:41 | INFO | Train Epoch: 1 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.1493 (1.3574) Boundary_loss: 0.014132 (0.014204) Loss: 1.1634 (1.3716) +2025-09-11,14:28:48 | INFO | Train Epoch: 1 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 1.1718 (1.3567) Boundary_loss: 0.014143 (0.014204) Loss: 1.1859 (1.3709) +2025-09-11,14:29:55 | INFO | Train Epoch: 1 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 1.1496 (1.3560) Boundary_loss: 0.014164 (0.014204) Loss: 1.1637 (1.3702) +2025-09-11,14:31:02 | INFO | Train Epoch: 1 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 1.1451 (1.3553) Boundary_loss: 0.014134 (0.014204) Loss: 1.1592 (1.3695) +2025-09-11,14:32:08 | INFO | Train Epoch: 1 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 1.1248 (1.3545) Boundary_loss: 0.014194 (0.014204) Loss: 1.1390 (1.3687) +2025-09-11,14:33:15 | INFO | Train Epoch: 1 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.3653 (1.3545) Boundary_loss: 0.014105 (0.014203) Loss: 1.3794 (1.3687) +2025-09-11,14:34:22 | INFO | Train Epoch: 1 [15002112/26365952 (57%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 1.1935 (1.3540) Boundary_loss: 0.014103 (0.014203) Loss: 1.2076 (1.3682) +2025-09-11,14:35:29 | INFO | Train Epoch: 1 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 1.1911 (1.3534) Boundary_loss: 0.014102 (0.014203) Loss: 1.2052 (1.3676) +2025-09-11,14:36:35 | INFO | Train Epoch: 1 [15104512/26365952 (57%)] Avg Boundaries (per batch): 49.850 Boundary Ratio: 0.254 Contrastive_loss: 1.1960 (1.3529) Boundary_loss: 0.014338 (0.014203) Loss: 1.2103 (1.3671) +2025-09-11,14:37:42 | INFO | Train Epoch: 1 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 1.3321 (1.3528) Boundary_loss: 0.014106 (0.014203) Loss: 1.3462 (1.3670) +2025-09-11,14:38:49 | INFO | Train Epoch: 1 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 1.2639 (1.3525) Boundary_loss: 0.014105 (0.014203) Loss: 1.2780 (1.3667) +2025-09-11,14:39:56 | INFO | Train Epoch: 1 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 1.4015 (1.3527) Boundary_loss: 0.014093 (0.014202) Loss: 1.4156 (1.3669) +2025-09-11,14:41:03 | INFO | Train Epoch: 1 [15309312/26365952 (58%)] Avg Boundaries (per batch): 49.805 Boundary Ratio: 0.254 Contrastive_loss: 1.1320 (1.3520) Boundary_loss: 0.014177 (0.014202) Loss: 1.1462 (1.3662) +2025-09-11,14:42:10 | INFO | Train Epoch: 1 [15360512/26365952 (58%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 1.2545 (1.3516) Boundary_loss: 0.014093 (0.014202) Loss: 1.2686 (1.3658) +2025-09-11,14:43:16 | INFO | Train Epoch: 1 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 1.1841 (1.3511) Boundary_loss: 0.014076 (0.014201) Loss: 1.1982 (1.3653) +2025-09-11,14:44:23 | INFO | Train Epoch: 1 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 1.2055 (1.3506) Boundary_loss: 0.014130 (0.014201) Loss: 1.2196 (1.3648) +2025-09-11,14:45:30 | INFO | Train Epoch: 1 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.459 Boundary Ratio: 0.252 Contrastive_loss: 1.2339 (1.3502) Boundary_loss: 0.014115 (0.014201) Loss: 1.2480 (1.3644) +2025-09-11,14:46:37 | INFO | Train Epoch: 1 [15565312/26365952 (59%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 1.2640 (1.3499) Boundary_loss: 0.014110 (0.014201) Loss: 1.2781 (1.3641) +2025-09-11,14:47:44 | INFO | Train Epoch: 1 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.1764 (1.3494) Boundary_loss: 0.014104 (0.014200) Loss: 1.1905 (1.3636) +2025-09-11,14:48:50 | INFO | Train Epoch: 1 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.059 Boundary Ratio: 0.245 Contrastive_loss: 1.1952 (1.3489) Boundary_loss: 0.014167 (0.014200) Loss: 1.2094 (1.3631) +2025-09-11,14:49:57 | INFO | Train Epoch: 1 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 1.1186 (1.3481) Boundary_loss: 0.014100 (0.014200) Loss: 1.1327 (1.3623) +2025-09-11,14:51:04 | INFO | Train Epoch: 1 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.1166 (1.3474) Boundary_loss: 0.014130 (0.014200) Loss: 1.1307 (1.3616) +2025-09-11,14:52:11 | INFO | Train Epoch: 1 [15821312/26365952 (60%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 1.0945 (1.3466) Boundary_loss: 0.014092 (0.014199) Loss: 1.1086 (1.3608) +2025-09-11,14:53:17 | INFO | Train Epoch: 1 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 1.1367 (1.3459) Boundary_loss: 0.014084 (0.014199) Loss: 1.1508 (1.3601) +2025-09-11,14:54:24 | INFO | Train Epoch: 1 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.221 Boundary Ratio: 0.246 Contrastive_loss: 1.1622 (1.3453) Boundary_loss: 0.014122 (0.014199) Loss: 1.1764 (1.3595) +2025-09-11,14:55:31 | INFO | Train Epoch: 1 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 1.3241 (1.3452) Boundary_loss: 0.014123 (0.014198) Loss: 1.3383 (1.3594) +2025-09-11,14:56:38 | INFO | Train Epoch: 1 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 1.2694 (1.3450) Boundary_loss: 0.014126 (0.014198) Loss: 1.2835 (1.3592) +2025-09-11,14:57:45 | INFO | Train Epoch: 1 [16077312/26365952 (61%)] Avg Boundaries (per batch): 49.199 Boundary Ratio: 0.251 Contrastive_loss: 1.2304 (1.3446) Boundary_loss: 0.014116 (0.014198) Loss: 1.2445 (1.3588) +2025-09-11,14:58:52 | INFO | Train Epoch: 1 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.104 Boundary Ratio: 0.245 Contrastive_loss: 1.2898 (1.3444) Boundary_loss: 0.014139 (0.014198) Loss: 1.3040 (1.3586) +2025-09-11,14:59:58 | INFO | Train Epoch: 1 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 1.1727 (1.3439) Boundary_loss: 0.014142 (0.014197) Loss: 1.1868 (1.3581) +2025-09-11,15:01:05 | INFO | Train Epoch: 1 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 1.1538 (1.3433) Boundary_loss: 0.014094 (0.014197) Loss: 1.1679 (1.3575) +2025-09-11,15:02:12 | INFO | Train Epoch: 1 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 1.1850 (1.3428) Boundary_loss: 0.014086 (0.014197) Loss: 1.1991 (1.3570) +2025-09-11,15:03:19 | INFO | Train Epoch: 1 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 1.0792 (1.3420) Boundary_loss: 0.014112 (0.014197) Loss: 1.0933 (1.3562) +2025-09-11,15:04:26 | INFO | Train Epoch: 1 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.361 Boundary Ratio: 0.247 Contrastive_loss: 1.2451 (1.3417) Boundary_loss: 0.014127 (0.014196) Loss: 1.2593 (1.3559) +2025-09-11,15:05:33 | INFO | Train Epoch: 1 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 1.2448 (1.3414) Boundary_loss: 0.014091 (0.014196) Loss: 1.2589 (1.3556) +2025-09-11,15:06:40 | INFO | Train Epoch: 1 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 1.1786 (1.3409) Boundary_loss: 0.014099 (0.014196) Loss: 1.1927 (1.3551) +2025-09-11,15:07:47 | INFO | Train Epoch: 1 [16538112/26365952 (63%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 1.2826 (1.3407) Boundary_loss: 0.014110 (0.014195) Loss: 1.2967 (1.3549) +2025-09-11,15:08:53 | INFO | Train Epoch: 1 [16589312/26365952 (63%)] Avg Boundaries (per batch): 49.264 Boundary Ratio: 0.251 Contrastive_loss: 1.1337 (1.3401) Boundary_loss: 0.014123 (0.014195) Loss: 1.1478 (1.3543) +2025-09-11,15:10:00 | INFO | Train Epoch: 1 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 1.2240 (1.3397) Boundary_loss: 0.014104 (0.014195) Loss: 1.2381 (1.3539) +2025-09-11,15:11:07 | INFO | Train Epoch: 1 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 1.1989 (1.3393) Boundary_loss: 0.014104 (0.014195) Loss: 1.2130 (1.3535) +2025-09-11,15:12:14 | INFO | Train Epoch: 1 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 1.1063 (1.3386) Boundary_loss: 0.014108 (0.014194) Loss: 1.1204 (1.3528) +2025-09-11,15:13:21 | INFO | Train Epoch: 1 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.285 Boundary Ratio: 0.246 Contrastive_loss: 1.1003 (1.3378) Boundary_loss: 0.014112 (0.014194) Loss: 1.1144 (1.3520) +2025-09-11,15:14:28 | INFO | Train Epoch: 1 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 1.1488 (1.3373) Boundary_loss: 0.014102 (0.014194) Loss: 1.1629 (1.3515) +2025-09-11,15:15:35 | INFO | Train Epoch: 1 [16896512/26365952 (64%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 1.0769 (1.3365) Boundary_loss: 0.014101 (0.014194) Loss: 1.0910 (1.3507) +2025-09-11,15:16:41 | INFO | Train Epoch: 1 [16947712/26365952 (64%)] Avg Boundaries (per batch): 49.359 Boundary Ratio: 0.252 Contrastive_loss: 1.2236 (1.3361) Boundary_loss: 0.014100 (0.014193) Loss: 1.2377 (1.3503) +2025-09-11,15:17:48 | INFO | Train Epoch: 1 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 1.1094 (1.3355) Boundary_loss: 0.014075 (0.014193) Loss: 1.1235 (1.3497) +2025-09-11,15:18:55 | INFO | Train Epoch: 1 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 1.1195 (1.3348) Boundary_loss: 0.014123 (0.014193) Loss: 1.1336 (1.3490) +2025-09-11,15:20:02 | INFO | Train Epoch: 1 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 1.2364 (1.3345) Boundary_loss: 0.014097 (0.014192) Loss: 1.2505 (1.3487) +2025-09-11,15:21:09 | INFO | Train Epoch: 1 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 1.2373 (1.3342) Boundary_loss: 0.014106 (0.014192) Loss: 1.2514 (1.3484) +2025-09-11,15:22:16 | INFO | Train Epoch: 1 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 1.1776 (1.3338) Boundary_loss: 0.014099 (0.014192) Loss: 1.1917 (1.3480) +2025-09-11,15:23:22 | INFO | Train Epoch: 1 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 1.1693 (1.3333) Boundary_loss: 0.014104 (0.014192) Loss: 1.1834 (1.3475) +2025-09-11,15:24:29 | INFO | Train Epoch: 1 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.1592 (1.3328) Boundary_loss: 0.014104 (0.014191) Loss: 1.1733 (1.3470) +2025-09-11,15:25:36 | INFO | Train Epoch: 1 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 1.2010 (1.3324) Boundary_loss: 0.014198 (0.014191) Loss: 1.2152 (1.3466) +2025-09-11,15:26:43 | INFO | Train Epoch: 1 [17408512/26365952 (66%)] Avg Boundaries (per batch): 47.930 Boundary Ratio: 0.245 Contrastive_loss: 1.1214 (1.3318) Boundary_loss: 0.014188 (0.014191) Loss: 1.1356 (1.3460) +2025-09-11,15:27:50 | INFO | Train Epoch: 1 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 1.0853 (1.3310) Boundary_loss: 0.014071 (0.014191) Loss: 1.0993 (1.3452) +2025-09-11,15:28:57 | INFO | Train Epoch: 1 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 1.1094 (1.3304) Boundary_loss: 0.014096 (0.014191) Loss: 1.1235 (1.3446) +2025-09-11,15:30:03 | INFO | Train Epoch: 1 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 1.2785 (1.3302) Boundary_loss: 0.014123 (0.014191) Loss: 1.2926 (1.3444) +2025-09-11,15:31:10 | INFO | Train Epoch: 1 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 1.1701 (1.3298) Boundary_loss: 0.014107 (0.014190) Loss: 1.1842 (1.3440) +2025-09-11,15:32:17 | INFO | Train Epoch: 1 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 1.1331 (1.3292) Boundary_loss: 0.014108 (0.014190) Loss: 1.1472 (1.3434) +2025-09-11,15:33:24 | INFO | Train Epoch: 1 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 1.1359 (1.3287) Boundary_loss: 0.014070 (0.014190) Loss: 1.1500 (1.3428) +2025-09-11,15:34:31 | INFO | Train Epoch: 1 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 1.0972 (1.3280) Boundary_loss: 0.014173 (0.014190) Loss: 1.1114 (1.3422) +2025-09-11,15:35:38 | INFO | Train Epoch: 1 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 1.1990 (1.3276) Boundary_loss: 0.014080 (0.014189) Loss: 1.2131 (1.3418) +2025-09-11,15:36:45 | INFO | Train Epoch: 1 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.232 Boundary Ratio: 0.246 Contrastive_loss: 1.2001 (1.3273) Boundary_loss: 0.014127 (0.014189) Loss: 1.2142 (1.3414) +2025-09-11,15:37:52 | INFO | Train Epoch: 1 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.2143 (1.3269) Boundary_loss: 0.014133 (0.014189) Loss: 1.2284 (1.3411) +2025-09-11,15:38:59 | INFO | Train Epoch: 1 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.1680 (1.3265) Boundary_loss: 0.014106 (0.014189) Loss: 1.1821 (1.3407) +2025-09-11,15:40:06 | INFO | Train Epoch: 1 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 1.1074 (1.3259) Boundary_loss: 0.014097 (0.014189) Loss: 1.1215 (1.3400) +2025-09-11,15:41:13 | INFO | Train Epoch: 1 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 1.1061 (1.3252) Boundary_loss: 0.014094 (0.014188) Loss: 1.1202 (1.3394) +2025-09-11,15:42:19 | INFO | Train Epoch: 1 [18125312/26365952 (69%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 1.2043 (1.3249) Boundary_loss: 0.014103 (0.014188) Loss: 1.2184 (1.3391) +2025-09-11,15:43:26 | INFO | Train Epoch: 1 [18176512/26365952 (69%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 1.1153 (1.3243) Boundary_loss: 0.014091 (0.014188) Loss: 1.1293 (1.3385) +2025-09-11,15:44:33 | INFO | Train Epoch: 1 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 1.0621 (1.3236) Boundary_loss: 0.014103 (0.014188) Loss: 1.0763 (1.3378) +2025-09-11,15:45:40 | INFO | Train Epoch: 1 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 1.0274 (1.3227) Boundary_loss: 0.014127 (0.014187) Loss: 1.0415 (1.3369) +2025-09-11,15:46:47 | INFO | Train Epoch: 1 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 1.2413 (1.3225) Boundary_loss: 0.014099 (0.014187) Loss: 1.2554 (1.3367) +2025-09-11,15:47:54 | INFO | Train Epoch: 1 [18381312/26365952 (70%)] Avg Boundaries (per batch): 49.393 Boundary Ratio: 0.252 Contrastive_loss: 1.1218 (1.3220) Boundary_loss: 0.014149 (0.014187) Loss: 1.1359 (1.3362) +2025-09-11,15:49:01 | INFO | Train Epoch: 1 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 1.2039 (1.3216) Boundary_loss: 0.014065 (0.014187) Loss: 1.2180 (1.3358) +2025-09-11,15:50:08 | INFO | Train Epoch: 1 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.301 Boundary Ratio: 0.246 Contrastive_loss: 1.0346 (1.3208) Boundary_loss: 0.014083 (0.014186) Loss: 1.0487 (1.3350) +2025-09-11,15:51:15 | INFO | Train Epoch: 1 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.018 Boundary Ratio: 0.245 Contrastive_loss: 1.2656 (1.3207) Boundary_loss: 0.014143 (0.014186) Loss: 1.2797 (1.3349) +2025-09-11,15:52:22 | INFO | Train Epoch: 1 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 1.1001 (1.3201) Boundary_loss: 0.014096 (0.014186) Loss: 1.1142 (1.3343) +2025-09-11,15:53:29 | INFO | Train Epoch: 1 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.398 Boundary Ratio: 0.247 Contrastive_loss: 1.1514 (1.3196) Boundary_loss: 0.014109 (0.014186) Loss: 1.1655 (1.3338) +2025-09-11,15:54:36 | INFO | Train Epoch: 1 [18688512/26365952 (71%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 1.1015 (1.3190) Boundary_loss: 0.014114 (0.014186) Loss: 1.1156 (1.3332) +2025-09-11,15:55:43 | INFO | Train Epoch: 1 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.291 Boundary Ratio: 0.246 Contrastive_loss: 1.1656 (1.3186) Boundary_loss: 0.014125 (0.014185) Loss: 1.1797 (1.3328) +2025-09-11,15:56:49 | INFO | Train Epoch: 1 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.3057 (1.3186) Boundary_loss: 0.014093 (0.014185) Loss: 1.3198 (1.3328) +2025-09-11,15:57:56 | INFO | Train Epoch: 1 [18842112/26365952 (71%)] Avg Boundaries (per batch): 50.014 Boundary Ratio: 0.255 Contrastive_loss: 1.1055 (1.3180) Boundary_loss: 0.014252 (0.014185) Loss: 1.1198 (1.3322) +2025-09-11,15:59:03 | INFO | Train Epoch: 1 [18893312/26365952 (72%)] Avg Boundaries (per batch): 49.512 Boundary Ratio: 0.253 Contrastive_loss: 1.0680 (1.3173) Boundary_loss: 0.014103 (0.014185) Loss: 1.0821 (1.3315) +2025-09-11,16:00:10 | INFO | Train Epoch: 1 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 1.2248 (1.3171) Boundary_loss: 0.014128 (0.014185) Loss: 1.2389 (1.3313) +2025-09-11,16:01:17 | INFO | Train Epoch: 1 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 1.1435 (1.3166) Boundary_loss: 0.014078 (0.014185) Loss: 1.1575 (1.3308) +2025-09-11,16:02:24 | INFO | Train Epoch: 1 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 1.1080 (1.3160) Boundary_loss: 0.014119 (0.014185) Loss: 1.1221 (1.3302) +2025-09-11,16:03:31 | INFO | Train Epoch: 1 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.354 Boundary Ratio: 0.247 Contrastive_loss: 1.2115 (1.3158) Boundary_loss: 0.014153 (0.014184) Loss: 1.2257 (1.3300) +2025-09-11,16:04:38 | INFO | Train Epoch: 1 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 1.1662 (1.3154) Boundary_loss: 0.014085 (0.014184) Loss: 1.1803 (1.3296) +2025-09-11,16:05:45 | INFO | Train Epoch: 1 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 1.0596 (1.3147) Boundary_loss: 0.014083 (0.014184) Loss: 1.0736 (1.3289) +2025-09-11,16:06:52 | INFO | Train Epoch: 1 [19251712/26365952 (73%)] Avg Boundaries (per batch): 49.178 Boundary Ratio: 0.251 Contrastive_loss: 1.1016 (1.3141) Boundary_loss: 0.014125 (0.014184) Loss: 1.1157 (1.3283) +2025-09-11,16:07:58 | INFO | Train Epoch: 1 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 1.1112 (1.3136) Boundary_loss: 0.014098 (0.014184) Loss: 1.1253 (1.3278) +2025-09-11,16:09:05 | INFO | Train Epoch: 1 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 1.0518 (1.3129) Boundary_loss: 0.014092 (0.014183) Loss: 1.0659 (1.3271) +2025-09-11,16:10:12 | INFO | Train Epoch: 1 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.281 Boundary Ratio: 0.246 Contrastive_loss: 1.0180 (1.3121) Boundary_loss: 0.014116 (0.014183) Loss: 1.0321 (1.3263) +2025-09-11,16:11:19 | INFO | Train Epoch: 1 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.350 Boundary Ratio: 0.252 Contrastive_loss: 0.99696 (1.3113) Boundary_loss: 0.014129 (0.014183) Loss: 1.0111 (1.3255) +2025-09-11,16:12:26 | INFO | Train Epoch: 1 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 1.2095 (1.3110) Boundary_loss: 0.014121 (0.014183) Loss: 1.2237 (1.3252) +2025-09-11,16:13:33 | INFO | Train Epoch: 1 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 1.0191 (1.3103) Boundary_loss: 0.014099 (0.014183) Loss: 1.0332 (1.3244) +2025-09-11,16:14:40 | INFO | Train Epoch: 1 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 1.0089 (1.3095) Boundary_loss: 0.014126 (0.014182) Loss: 1.0230 (1.3237) +2025-09-11,16:15:47 | INFO | Train Epoch: 1 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.1441 (1.3090) Boundary_loss: 0.014097 (0.014182) Loss: 1.1582 (1.3232) +2025-09-11,16:16:53 | INFO | Train Epoch: 1 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 1.0546 (1.3084) Boundary_loss: 0.014071 (0.014182) Loss: 1.0686 (1.3226) +2025-09-11,16:18:00 | INFO | Train Epoch: 1 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 1.0352 (1.3077) Boundary_loss: 0.014104 (0.014182) Loss: 1.0493 (1.3219) +2025-09-11,16:19:07 | INFO | Train Epoch: 1 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 1.1024 (1.3072) Boundary_loss: 0.014118 (0.014182) Loss: 1.1165 (1.3213) +2025-09-11,16:20:14 | INFO | Train Epoch: 1 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.291 Boundary Ratio: 0.246 Contrastive_loss: 1.0898 (1.3066) Boundary_loss: 0.014095 (0.014181) Loss: 1.1039 (1.3208) +2025-09-11,16:21:21 | INFO | Train Epoch: 1 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 1.1816 (1.3063) Boundary_loss: 0.014052 (0.014181) Loss: 1.1957 (1.3205) +2025-09-11,16:22:28 | INFO | Train Epoch: 1 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 1.1188 (1.3058) Boundary_loss: 0.014141 (0.014181) Loss: 1.1329 (1.3200) +2025-09-11,16:23:35 | INFO | Train Epoch: 1 [20019712/26365952 (76%)] Avg Boundaries (per batch): 49.307 Boundary Ratio: 0.252 Contrastive_loss: 1.1633 (1.3054) Boundary_loss: 0.014156 (0.014181) Loss: 1.1775 (1.3196) +2025-09-11,16:24:42 | INFO | Train Epoch: 1 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.1574 (1.3051) Boundary_loss: 0.014079 (0.014181) Loss: 1.1714 (1.3192) +2025-09-11,16:25:48 | INFO | Train Epoch: 1 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.342 Boundary Ratio: 0.247 Contrastive_loss: 1.0469 (1.3044) Boundary_loss: 0.014171 (0.014181) Loss: 1.0610 (1.3186) +2025-09-11,16:26:55 | INFO | Train Epoch: 1 [20173312/26365952 (77%)] Avg Boundaries (per batch): 49.361 Boundary Ratio: 0.252 Contrastive_loss: 1.0781 (1.3038) Boundary_loss: 0.014094 (0.014180) Loss: 1.0922 (1.3180) +2025-09-11,16:28:02 | INFO | Train Epoch: 1 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 1.3295 (1.3039) Boundary_loss: 0.014064 (0.014180) Loss: 1.3435 (1.3181) +2025-09-11,16:29:09 | INFO | Train Epoch: 1 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.1293 (1.3035) Boundary_loss: 0.014092 (0.014180) Loss: 1.1434 (1.3176) +2025-09-11,16:30:16 | INFO | Train Epoch: 1 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 1.0889 (1.3029) Boundary_loss: 0.014097 (0.014180) Loss: 1.1030 (1.3171) +2025-09-11,16:31:23 | INFO | Train Epoch: 1 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 1.2094 (1.3027) Boundary_loss: 0.014087 (0.014179) Loss: 1.2235 (1.3169) +2025-09-11,16:32:30 | INFO | Train Epoch: 1 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.1390 (1.3023) Boundary_loss: 0.014065 (0.014179) Loss: 1.1530 (1.3164) +2025-09-11,16:33:36 | INFO | Train Epoch: 1 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.086 Boundary Ratio: 0.245 Contrastive_loss: 1.1194 (1.3018) Boundary_loss: 0.014120 (0.014179) Loss: 1.1336 (1.3160) +2025-09-11,16:34:43 | INFO | Train Epoch: 1 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 1.0204 (1.3011) Boundary_loss: 0.014083 (0.014179) Loss: 1.0345 (1.3153) +2025-09-11,16:35:50 | INFO | Train Epoch: 1 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 1.0212 (1.3004) Boundary_loss: 0.014080 (0.014178) Loss: 1.0353 (1.3146) +2025-09-11,16:36:57 | INFO | Train Epoch: 1 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 1.0998 (1.2999) Boundary_loss: 0.014091 (0.014178) Loss: 1.1139 (1.3141) +2025-09-11,16:38:04 | INFO | Train Epoch: 1 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 1.1815 (1.2996) Boundary_loss: 0.014078 (0.014178) Loss: 1.1956 (1.3138) +2025-09-11,16:39:10 | INFO | Train Epoch: 1 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.377 Boundary Ratio: 0.247 Contrastive_loss: 1.0313 (1.2990) Boundary_loss: 0.014071 (0.014178) Loss: 1.0454 (1.3131) +2025-09-11,16:40:17 | INFO | Train Epoch: 1 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 1.1116 (1.2985) Boundary_loss: 0.014101 (0.014178) Loss: 1.1257 (1.3127) +2025-09-11,16:41:24 | INFO | Train Epoch: 1 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 1.1446 (1.2981) Boundary_loss: 0.014093 (0.014177) Loss: 1.1587 (1.3123) +2025-09-11,16:42:31 | INFO | Train Epoch: 1 [20890112/26365952 (79%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 1.2602 (1.2980) Boundary_loss: 0.014071 (0.014177) Loss: 1.2743 (1.3122) +2025-09-11,16:43:38 | INFO | Train Epoch: 1 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.93887 (1.2972) Boundary_loss: 0.014145 (0.014177) Loss: 0.95302 (1.3113) +2025-09-11,16:44:44 | INFO | Train Epoch: 1 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 1.1691 (1.2969) Boundary_loss: 0.014087 (0.014177) Loss: 1.1831 (1.3110) +2025-09-11,16:45:51 | INFO | Train Epoch: 1 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 1.2693 (1.2968) Boundary_loss: 0.014087 (0.014177) Loss: 1.2834 (1.3110) +2025-09-11,16:46:58 | INFO | Train Epoch: 1 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 1.2416 (1.2967) Boundary_loss: 0.014093 (0.014176) Loss: 1.2557 (1.3108) +2025-09-11,16:48:05 | INFO | Train Epoch: 1 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 1.0972 (1.2962) Boundary_loss: 0.014107 (0.014176) Loss: 1.1113 (1.3103) +2025-09-11,16:49:12 | INFO | Train Epoch: 1 [21197312/26365952 (80%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 1.1186 (1.2957) Boundary_loss: 0.014103 (0.014176) Loss: 1.1327 (1.3099) +2025-09-11,16:50:18 | INFO | Train Epoch: 1 [21248512/26365952 (81%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 1.1740 (1.2954) Boundary_loss: 0.014139 (0.014176) Loss: 1.1881 (1.3096) +2025-09-11,16:51:25 | INFO | Train Epoch: 1 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 1.0565 (1.2949) Boundary_loss: 0.014067 (0.014176) Loss: 1.0706 (1.3091) +2025-09-11,16:52:32 | INFO | Train Epoch: 1 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 1.1649 (1.2946) Boundary_loss: 0.014105 (0.014176) Loss: 1.1790 (1.3087) +2025-09-11,16:53:39 | INFO | Train Epoch: 1 [21402112/26365952 (81%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 1.2267 (1.2944) Boundary_loss: 0.014117 (0.014175) Loss: 1.2409 (1.3086) +2025-09-11,16:54:46 | INFO | Train Epoch: 1 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 1.1321 (1.2940) Boundary_loss: 0.014124 (0.014175) Loss: 1.1462 (1.3082) +2025-09-11,16:55:53 | INFO | Train Epoch: 1 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 1.0969 (1.2935) Boundary_loss: 0.014103 (0.014175) Loss: 1.1110 (1.3077) +2025-09-11,16:56:59 | INFO | Train Epoch: 1 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 1.1668 (1.2932) Boundary_loss: 0.014095 (0.014175) Loss: 1.1809 (1.3074) +2025-09-11,16:58:06 | INFO | Train Epoch: 1 [21606912/26365952 (82%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 1.2978 (1.2933) Boundary_loss: 0.014105 (0.014175) Loss: 1.3119 (1.3074) +2025-09-11,16:59:13 | INFO | Train Epoch: 1 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 1.0464 (1.2927) Boundary_loss: 0.014086 (0.014175) Loss: 1.0604 (1.3069) +2025-09-11,17:00:20 | INFO | Train Epoch: 1 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.457 Boundary Ratio: 0.247 Contrastive_loss: 1.1339 (1.2923) Boundary_loss: 0.014092 (0.014174) Loss: 1.1480 (1.3065) +2025-09-11,17:01:27 | INFO | Train Epoch: 1 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 1.2189 (1.2921) Boundary_loss: 0.014068 (0.014174) Loss: 1.2330 (1.3063) +2025-09-11,17:02:33 | INFO | Train Epoch: 1 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 1.1331 (1.2918) Boundary_loss: 0.014111 (0.014174) Loss: 1.1472 (1.3059) +2025-09-11,17:03:40 | INFO | Train Epoch: 1 [21862912/26365952 (83%)] Avg Boundaries (per batch): 47.975 Boundary Ratio: 0.245 Contrastive_loss: 0.93944 (1.2909) Boundary_loss: 0.014144 (0.014174) Loss: 0.95359 (1.3051) +2025-09-11,17:04:47 | INFO | Train Epoch: 1 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.125 Boundary Ratio: 0.246 Contrastive_loss: 1.0809 (1.2904) Boundary_loss: 0.014146 (0.014174) Loss: 1.0950 (1.3046) +2025-09-11,17:05:54 | INFO | Train Epoch: 1 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.1224 (1.2901) Boundary_loss: 0.014111 (0.014174) Loss: 1.1365 (1.3042) +2025-09-11,17:07:00 | INFO | Train Epoch: 1 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.096 Boundary Ratio: 0.245 Contrastive_loss: 1.2248 (1.2899) Boundary_loss: 0.014154 (0.014174) Loss: 1.2390 (1.3041) +2025-09-11,17:08:07 | INFO | Train Epoch: 1 [22067712/26365952 (84%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 1.1675 (1.2896) Boundary_loss: 0.014094 (0.014173) Loss: 1.1816 (1.3038) +2025-09-11,17:09:14 | INFO | Train Epoch: 1 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 1.1893 (1.2894) Boundary_loss: 0.014089 (0.014173) Loss: 1.2034 (1.3036) +2025-09-11,17:10:21 | INFO | Train Epoch: 1 [22170112/26365952 (84%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 1.0550 (1.2888) Boundary_loss: 0.014105 (0.014173) Loss: 1.0691 (1.3030) +2025-09-11,17:11:27 | INFO | Train Epoch: 1 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 1.2312 (1.2887) Boundary_loss: 0.014090 (0.014173) Loss: 1.2453 (1.3029) +2025-09-11,17:12:34 | INFO | Train Epoch: 1 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 1.2350 (1.2886) Boundary_loss: 0.014074 (0.014173) Loss: 1.2491 (1.3028) +2025-09-11,17:13:41 | INFO | Train Epoch: 1 [22323712/26365952 (85%)] Avg Boundaries (per batch): 49.391 Boundary Ratio: 0.252 Contrastive_loss: 1.0687 (1.2881) Boundary_loss: 0.014109 (0.014173) Loss: 1.0828 (1.3023) +2025-09-11,17:14:48 | INFO | Train Epoch: 1 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 1.0792 (1.2876) Boundary_loss: 0.014040 (0.014172) Loss: 1.0932 (1.3018) +2025-09-11,17:15:54 | INFO | Train Epoch: 1 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 1.2340 (1.2875) Boundary_loss: 0.014076 (0.014172) Loss: 1.2481 (1.3017) +2025-09-11,17:17:01 | INFO | Train Epoch: 1 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.205 Boundary Ratio: 0.246 Contrastive_loss: 0.98500 (1.2868) Boundary_loss: 0.014103 (0.014172) Loss: 0.99910 (1.3010) +2025-09-11,17:18:08 | INFO | Train Epoch: 1 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.99614 (1.2861) Boundary_loss: 0.014066 (0.014172) Loss: 1.0102 (1.3003) +2025-09-11,17:19:15 | INFO | Train Epoch: 1 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.184 Boundary Ratio: 0.246 Contrastive_loss: 1.0946 (1.2857) Boundary_loss: 0.014091 (0.014171) Loss: 1.1087 (1.2999) +2025-09-11,17:20:21 | INFO | Train Epoch: 1 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 1.0537 (1.2852) Boundary_loss: 0.014110 (0.014171) Loss: 1.0678 (1.2994) +2025-09-11,17:21:28 | INFO | Train Epoch: 1 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.361 Boundary Ratio: 0.247 Contrastive_loss: 1.0165 (1.2846) Boundary_loss: 0.014104 (0.014171) Loss: 1.0306 (1.2988) +2025-09-11,17:22:35 | INFO | Train Epoch: 1 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 1.2252 (1.2844) Boundary_loss: 0.014097 (0.014171) Loss: 1.2393 (1.2986) +2025-09-11,17:23:42 | INFO | Train Epoch: 1 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 1.0213 (1.2839) Boundary_loss: 0.014100 (0.014171) Loss: 1.0354 (1.2980) +2025-09-11,17:24:48 | INFO | Train Epoch: 1 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.160 Boundary Ratio: 0.246 Contrastive_loss: 1.2140 (1.2837) Boundary_loss: 0.014099 (0.014171) Loss: 1.2281 (1.2979) +2025-09-11,17:25:55 | INFO | Train Epoch: 1 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.211 Boundary Ratio: 0.246 Contrastive_loss: 1.0960 (1.2833) Boundary_loss: 0.014086 (0.014170) Loss: 1.1101 (1.2975) +2025-09-11,17:27:02 | INFO | Train Epoch: 1 [22938112/26365952 (87%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 1.0846 (1.2828) Boundary_loss: 0.014132 (0.014170) Loss: 1.0988 (1.2970) +2025-09-11,17:28:09 | INFO | Train Epoch: 1 [22989312/26365952 (87%)] Avg Boundaries (per batch): 49.244 Boundary Ratio: 0.251 Contrastive_loss: 1.0606 (1.2823) Boundary_loss: 0.014160 (0.014170) Loss: 1.0748 (1.2965) +2025-09-11,17:29:16 | INFO | Train Epoch: 1 [23040512/26365952 (87%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 1.1845 (1.2821) Boundary_loss: 0.014098 (0.014170) Loss: 1.1986 (1.2963) +2025-09-11,17:30:22 | INFO | Train Epoch: 1 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 1.0050 (1.2815) Boundary_loss: 0.014084 (0.014170) Loss: 1.0191 (1.2957) +2025-09-11,17:31:29 | INFO | Train Epoch: 1 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 1.1467 (1.2812) Boundary_loss: 0.014060 (0.014170) Loss: 1.1608 (1.2954) +2025-09-11,17:32:36 | INFO | Train Epoch: 1 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.99475 (1.2806) Boundary_loss: 0.014050 (0.014169) Loss: 1.0088 (1.2948) +2025-09-11,17:33:43 | INFO | Train Epoch: 1 [23245312/26365952 (88%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 1.0331 (1.2800) Boundary_loss: 0.014102 (0.014169) Loss: 1.0472 (1.2942) +2025-09-11,17:34:49 | INFO | Train Epoch: 1 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.0339 (1.2795) Boundary_loss: 0.014069 (0.014169) Loss: 1.0480 (1.2937) +2025-09-11,17:35:56 | INFO | Train Epoch: 1 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 1.1403 (1.2792) Boundary_loss: 0.014073 (0.014169) Loss: 1.1544 (1.2934) +2025-09-11,17:37:03 | INFO | Train Epoch: 1 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.064 Boundary Ratio: 0.245 Contrastive_loss: 1.1117 (1.2788) Boundary_loss: 0.014136 (0.014169) Loss: 1.1258 (1.2930) +2025-09-11,17:38:09 | INFO | Train Epoch: 1 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.289 Boundary Ratio: 0.246 Contrastive_loss: 1.0240 (1.2783) Boundary_loss: 0.014072 (0.014169) Loss: 1.0380 (1.2924) +2025-09-11,17:39:16 | INFO | Train Epoch: 1 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 1.1203 (1.2779) Boundary_loss: 0.014107 (0.014168) Loss: 1.1344 (1.2921) +2025-09-11,17:40:23 | INFO | Train Epoch: 1 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 1.0666 (1.2775) Boundary_loss: 0.014112 (0.014168) Loss: 1.0807 (1.2916) +2025-09-11,17:41:29 | INFO | Train Epoch: 1 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 1.1378 (1.2772) Boundary_loss: 0.014099 (0.014168) Loss: 1.1519 (1.2913) +2025-09-11,17:42:36 | INFO | Train Epoch: 1 [23654912/26365952 (90%)] Avg Boundaries (per batch): 49.553 Boundary Ratio: 0.253 Contrastive_loss: 1.1409 (1.2769) Boundary_loss: 0.014138 (0.014168) Loss: 1.1550 (1.2910) +2025-09-11,17:43:43 | INFO | Train Epoch: 1 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 1.0970 (1.2765) Boundary_loss: 0.014057 (0.014168) Loss: 1.1110 (1.2907) +2025-09-11,17:44:50 | INFO | Train Epoch: 1 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.97607 (1.2758) Boundary_loss: 0.014087 (0.014168) Loss: 0.99016 (1.2900) +2025-09-11,17:45:56 | INFO | Train Epoch: 1 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.99492 (1.2752) Boundary_loss: 0.014086 (0.014168) Loss: 1.0090 (1.2894) +2025-09-11,17:47:03 | INFO | Train Epoch: 1 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 1.0668 (1.2748) Boundary_loss: 0.014063 (0.014167) Loss: 1.0808 (1.2890) +2025-09-11,17:48:10 | INFO | Train Epoch: 1 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.2021 (1.2746) Boundary_loss: 0.014107 (0.014167) Loss: 1.2162 (1.2888) +2025-09-11,17:49:17 | INFO | Train Epoch: 1 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 1.0646 (1.2742) Boundary_loss: 0.014064 (0.014167) Loss: 1.0787 (1.2884) +2025-09-11,17:50:23 | INFO | Train Epoch: 1 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 1.1613 (1.2740) Boundary_loss: 0.014082 (0.014167) Loss: 1.1754 (1.2881) +2025-09-11,17:51:30 | INFO | Train Epoch: 1 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 1.0216 (1.2734) Boundary_loss: 0.014105 (0.014167) Loss: 1.0357 (1.2876) +2025-09-11,17:52:36 | INFO | Train Epoch: 1 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 1.0951 (1.2730) Boundary_loss: 0.014110 (0.014167) Loss: 1.1092 (1.2872) +2025-09-11,17:53:43 | INFO | Train Epoch: 1 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.94058 (1.2723) Boundary_loss: 0.014089 (0.014166) Loss: 0.95467 (1.2865) +2025-09-11,17:54:50 | INFO | Train Epoch: 1 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 1.0532 (1.2719) Boundary_loss: 0.014070 (0.014166) Loss: 1.0673 (1.2860) +2025-09-11,17:55:57 | INFO | Train Epoch: 1 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.0332 (1.2714) Boundary_loss: 0.014067 (0.014166) Loss: 1.0472 (1.2855) +2025-09-11,17:57:04 | INFO | Train Epoch: 1 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 1.1087 (1.2710) Boundary_loss: 0.014070 (0.014166) Loss: 1.1227 (1.2852) +2025-09-11,17:58:10 | INFO | Train Epoch: 1 [24371712/26365952 (92%)] Avg Boundaries (per batch): 49.561 Boundary Ratio: 0.253 Contrastive_loss: 1.0771 (1.2706) Boundary_loss: 0.014091 (0.014166) Loss: 1.0912 (1.2848) +2025-09-11,17:59:17 | INFO | Train Epoch: 1 [24422912/26365952 (93%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 1.1554 (1.2704) Boundary_loss: 0.014122 (0.014166) Loss: 1.1695 (1.2845) +2025-09-11,18:00:24 | INFO | Train Epoch: 1 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.97505 (1.2698) Boundary_loss: 0.014066 (0.014165) Loss: 0.98912 (1.2839) +2025-09-11,18:01:30 | INFO | Train Epoch: 1 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 1.0012 (1.2692) Boundary_loss: 0.014089 (0.014165) Loss: 1.0153 (1.2834) +2025-09-11,18:02:37 | INFO | Train Epoch: 1 [24576512/26365952 (93%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 1.1999 (1.2691) Boundary_loss: 0.014079 (0.014165) Loss: 1.2139 (1.2832) +2025-09-11,18:03:44 | INFO | Train Epoch: 1 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.97465 (1.2685) Boundary_loss: 0.014055 (0.014165) Loss: 0.98871 (1.2826) +2025-09-11,18:04:51 | INFO | Train Epoch: 1 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.99448 (1.2679) Boundary_loss: 0.014073 (0.014165) Loss: 1.0086 (1.2820) +2025-09-11,18:05:57 | INFO | Train Epoch: 1 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 1.1459 (1.2676) Boundary_loss: 0.014092 (0.014164) Loss: 1.1600 (1.2818) +2025-09-11,18:07:04 | INFO | Train Epoch: 1 [24781312/26365952 (94%)] Avg Boundaries (per batch): 49.293 Boundary Ratio: 0.251 Contrastive_loss: 1.0085 (1.2671) Boundary_loss: 0.014084 (0.014164) Loss: 1.0226 (1.2813) +2025-09-11,18:08:11 | INFO | Train Epoch: 1 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.99023 (1.2665) Boundary_loss: 0.014100 (0.014164) Loss: 1.0043 (1.2807) +2025-09-11,18:09:18 | INFO | Train Epoch: 1 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 1.0426 (1.2661) Boundary_loss: 0.014084 (0.014164) Loss: 1.0567 (1.2802) +2025-09-11,18:10:24 | INFO | Train Epoch: 1 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.0709 (1.2657) Boundary_loss: 0.014096 (0.014164) Loss: 1.0850 (1.2798) +2025-09-11,18:11:31 | INFO | Train Epoch: 1 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 1.0783 (1.2653) Boundary_loss: 0.014094 (0.014164) Loss: 1.0924 (1.2794) +2025-09-11,18:12:38 | INFO | Train Epoch: 1 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 1.1455 (1.2650) Boundary_loss: 0.014065 (0.014163) Loss: 1.1596 (1.2792) +2025-09-11,18:13:44 | INFO | Train Epoch: 1 [25088512/26365952 (95%)] Avg Boundaries (per batch): 49.705 Boundary Ratio: 0.254 Contrastive_loss: 0.95819 (1.2644) Boundary_loss: 0.014227 (0.014164) Loss: 0.97242 (1.2786) +2025-09-11,18:14:51 | INFO | Train Epoch: 1 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 1.0085 (1.2639) Boundary_loss: 0.014092 (0.014163) Loss: 1.0225 (1.2781) +2025-09-11,18:15:58 | INFO | Train Epoch: 1 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.0951 (1.2636) Boundary_loss: 0.014056 (0.014163) Loss: 1.1091 (1.2777) +2025-09-11,18:17:04 | INFO | Train Epoch: 1 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 1.0357 (1.2631) Boundary_loss: 0.014044 (0.014163) Loss: 1.0497 (1.2773) +2025-09-11,18:18:11 | INFO | Train Epoch: 1 [25293312/26365952 (96%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 1.1041 (1.2628) Boundary_loss: 0.014097 (0.014163) Loss: 1.1182 (1.2769) +2025-09-11,18:19:18 | INFO | Train Epoch: 1 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 1.0490 (1.2623) Boundary_loss: 0.014073 (0.014163) Loss: 1.0631 (1.2765) +2025-09-11,18:20:25 | INFO | Train Epoch: 1 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 1.1131 (1.2620) Boundary_loss: 0.014048 (0.014162) Loss: 1.1271 (1.2762) +2025-09-11,18:21:31 | INFO | Train Epoch: 1 [25446912/26365952 (97%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 1.1098 (1.2617) Boundary_loss: 0.014052 (0.014162) Loss: 1.1239 (1.2759) +2025-09-11,18:22:38 | INFO | Train Epoch: 1 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 1.0350 (1.2613) Boundary_loss: 0.014083 (0.014162) Loss: 1.0491 (1.2754) +2025-09-11,18:23:45 | INFO | Train Epoch: 1 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 1.2358 (1.2612) Boundary_loss: 0.014092 (0.014162) Loss: 1.2499 (1.2754) +2025-09-11,18:24:51 | INFO | Train Epoch: 1 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.97286 (1.2607) Boundary_loss: 0.014097 (0.014162) Loss: 0.98696 (1.2748) +2025-09-11,18:25:58 | INFO | Train Epoch: 1 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 1.2354 (1.2606) Boundary_loss: 0.014084 (0.014162) Loss: 1.2494 (1.2748) +2025-09-11,18:27:05 | INFO | Train Epoch: 1 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 1.0585 (1.2602) Boundary_loss: 0.014121 (0.014162) Loss: 1.0726 (1.2744) +2025-09-11,18:28:11 | INFO | Train Epoch: 1 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 1.0978 (1.2599) Boundary_loss: 0.014069 (0.014161) Loss: 1.1119 (1.2740) +2025-09-11,18:29:18 | INFO | Train Epoch: 1 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.2104 (1.2598) Boundary_loss: 0.014062 (0.014161) Loss: 1.2245 (1.2739) +2025-09-11,18:30:25 | INFO | Train Epoch: 1 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 1.0891 (1.2594) Boundary_loss: 0.014062 (0.014161) Loss: 1.1032 (1.2736) +2025-09-11,18:31:31 | INFO | Train Epoch: 1 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 1.1192 (1.2592) Boundary_loss: 0.014051 (0.014161) Loss: 1.1332 (1.2733) +2025-09-11,18:32:38 | INFO | Train Epoch: 1 [25958912/26365952 (98%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 1.1711 (1.2590) Boundary_loss: 0.014059 (0.014161) Loss: 1.1851 (1.2732) +2025-09-11,18:33:45 | INFO | Train Epoch: 1 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 1.0562 (1.2586) Boundary_loss: 0.014084 (0.014160) Loss: 1.0703 (1.2728) +2025-09-11,18:34:51 | INFO | Train Epoch: 1 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.98842 (1.2581) Boundary_loss: 0.014111 (0.014160) Loss: 1.0025 (1.2722) +2025-09-11,18:35:58 | INFO | Train Epoch: 1 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 1.0753 (1.2577) Boundary_loss: 0.014112 (0.014160) Loss: 1.0894 (1.2719) +2025-09-11,18:37:05 | INFO | Train Epoch: 1 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.0471 (1.2573) Boundary_loss: 0.014058 (0.014160) Loss: 1.0612 (1.2715) +2025-09-11,18:38:11 | INFO | Train Epoch: 1 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 1.0546 (1.2569) Boundary_loss: 0.014161 (0.014160) Loss: 1.0688 (1.2711) +2025-09-11,18:39:18 | INFO | Train Epoch: 1 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.0725 (1.2565) Boundary_loss: 0.014032 (0.014160) Loss: 1.0865 (1.2707) +2025-09-11,18:40:25 | INFO | Train Epoch: 1 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.291 Boundary Ratio: 0.246 Contrastive_loss: 1.0802 (1.2562) Boundary_loss: 0.014090 (0.014160) Loss: 1.0943 (1.2704) +2025-09-11,18:41:28 | INFO | Train Epoch: 1 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.87563 (1.2555) Boundary_loss: 0.014070 (0.014159) Loss: 0.88970 (1.2696) +2025-09-11,18:41:28 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-11,18:41:28 | INFO | [Epoch 1] Average Step Time: 0.672s | Average GPU Memory: 31.3 GB +2025-09-11,18:41:28 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-11,18:41:28 | INFO | Starting zero-shot imagenet. +2025-09-11,18:41:28 | INFO | Building zero-shot classifier +2025-09-11,18:41:38 | INFO | Using classifier +2025-09-11,18:42:24 | INFO | Finished zero-shot imagenet. +2025-09-11,18:42:24 | INFO | Eval Epoch: 2 imagenet-zeroshot-val-top1: 0.1780 imagenet-zeroshot-val-top5: 0.3880 +2025-09-11,18:42:25 | INFO | Start epoch 2 +2025-09-11,18:42:28 | INFO | Train Epoch: 2 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 1.0570 (1.0570) Boundary_loss: 0.014048 (0.014048) Loss: 1.0710 (1.0710) +2025-09-11,18:43:34 | INFO | Train Epoch: 2 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 1.0564 (1.0567) Boundary_loss: 0.014027 (0.014037) Loss: 1.0704 (1.0707) +2025-09-11,18:44:41 | INFO | Train Epoch: 2 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.0101 (1.0412) Boundary_loss: 0.014074 (0.014049) Loss: 1.0242 (1.0552) +2025-09-11,18:45:47 | INFO | Train Epoch: 2 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 1.1503 (1.0684) Boundary_loss: 0.014039 (0.014047) Loss: 1.1643 (1.0825) +2025-09-11,18:46:54 | INFO | Train Epoch: 2 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.057 Boundary Ratio: 0.245 Contrastive_loss: 1.0658 (1.0679) Boundary_loss: 0.014112 (0.014060) Loss: 1.0799 (1.0820) +2025-09-11,18:48:00 | INFO | Train Epoch: 2 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 1.0170 (1.0594) Boundary_loss: 0.014076 (0.014063) Loss: 1.0310 (1.0735) +2025-09-11,18:49:07 | INFO | Train Epoch: 2 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.94829 (1.0435) Boundary_loss: 0.014037 (0.014059) Loss: 0.96233 (1.0576) +2025-09-11,18:50:13 | INFO | Train Epoch: 2 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.533 Boundary Ratio: 0.253 Contrastive_loss: 0.85619 (1.0201) Boundary_loss: 0.014098 (0.014064) Loss: 0.87029 (1.0342) +2025-09-11,18:51:20 | INFO | Train Epoch: 2 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.94371 (1.0116) Boundary_loss: 0.014053 (0.014063) Loss: 0.95777 (1.0257) +2025-09-11,18:52:26 | INFO | Train Epoch: 2 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 0.93671 (1.0041) Boundary_loss: 0.014096 (0.014066) Loss: 0.95080 (1.0182) +2025-09-11,18:53:33 | INFO | Train Epoch: 2 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.0369 (1.0071) Boundary_loss: 0.014097 (0.014069) Loss: 1.0510 (1.0212) +2025-09-11,18:54:39 | INFO | Train Epoch: 2 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.95958 (1.0032) Boundary_loss: 0.014073 (0.014069) Loss: 0.97366 (1.0172) +2025-09-11,18:55:46 | INFO | Train Epoch: 2 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 49.363 Boundary Ratio: 0.252 Contrastive_loss: 0.91272 (0.99620) Boundary_loss: 0.014063 (0.014069) Loss: 0.92678 (1.0103) +2025-09-11,18:56:52 | INFO | Train Epoch: 2 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.83591 (0.98475) Boundary_loss: 0.014092 (0.014070) Loss: 0.85000 (0.99882) +2025-09-11,18:57:58 | INFO | Train Epoch: 2 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.96553 (0.98347) Boundary_loss: 0.014048 (0.014069) Loss: 0.97957 (0.99754) +2025-09-11,18:59:05 | INFO | Train Epoch: 2 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 1.0716 (0.98898) Boundary_loss: 0.014079 (0.014069) Loss: 1.0857 (1.0030) +2025-09-11,19:00:11 | INFO | Train Epoch: 2 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 0.92763 (0.98537) Boundary_loss: 0.014057 (0.014069) Loss: 0.94168 (0.99944) +2025-09-11,19:01:18 | INFO | Train Epoch: 2 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 1.0516 (0.98905) Boundary_loss: 0.014055 (0.014068) Loss: 1.0657 (1.0031) +2025-09-11,19:02:24 | INFO | Train Epoch: 2 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.97992 (0.98857) Boundary_loss: 0.014141 (0.014072) Loss: 0.99407 (1.0026) +2025-09-11,19:03:31 | INFO | Train Epoch: 2 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 1.0710 (0.99269) Boundary_loss: 0.014086 (0.014072) Loss: 1.0851 (1.0068) +2025-09-11,19:04:37 | INFO | Train Epoch: 2 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 0.95216 (0.99076) Boundary_loss: 0.014081 (0.014073) Loss: 0.96625 (1.0048) +2025-09-11,19:05:44 | INFO | Train Epoch: 2 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 1.0731 (0.99451) Boundary_loss: 0.014055 (0.014072) Loss: 1.0872 (1.0086) +2025-09-11,19:06:50 | INFO | Train Epoch: 2 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.83134 (0.98741) Boundary_loss: 0.014072 (0.014072) Loss: 0.84541 (1.0015) +2025-09-11,19:07:57 | INFO | Train Epoch: 2 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.346 Boundary Ratio: 0.247 Contrastive_loss: 0.93087 (0.98506) Boundary_loss: 0.014072 (0.014072) Loss: 0.94494 (0.99913) +2025-09-11,19:09:03 | INFO | Train Epoch: 2 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.0216 (0.98652) Boundary_loss: 0.014071 (0.014072) Loss: 1.0357 (1.0006) +2025-09-11,19:10:10 | INFO | Train Epoch: 2 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 1.0973 (0.99078) Boundary_loss: 0.014061 (0.014072) Loss: 1.1113 (1.0049) +2025-09-11,19:11:16 | INFO | Train Epoch: 2 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 1.0328 (0.99234) Boundary_loss: 0.014055 (0.014071) Loss: 1.0469 (1.0064) +2025-09-11,19:12:22 | INFO | Train Epoch: 2 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.83307 (0.98665) Boundary_loss: 0.014073 (0.014071) Loss: 0.84714 (1.0007) +2025-09-11,19:13:29 | INFO | Train Epoch: 2 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.104 Boundary Ratio: 0.245 Contrastive_loss: 0.99125 (0.98681) Boundary_loss: 0.014068 (0.014071) Loss: 1.0053 (1.0009) +2025-09-11,19:14:35 | INFO | Train Epoch: 2 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.97778 (0.98651) Boundary_loss: 0.014046 (0.014070) Loss: 0.99182 (1.0006) +2025-09-11,19:15:42 | INFO | Train Epoch: 2 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 0.96541 (0.98583) Boundary_loss: 0.014069 (0.014070) Loss: 0.97948 (0.99990) +2025-09-11,19:16:48 | INFO | Train Epoch: 2 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 1.0520 (0.98789) Boundary_loss: 0.014057 (0.014070) Loss: 1.0660 (1.0020) +2025-09-11,19:17:55 | INFO | Train Epoch: 2 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 1.0140 (0.98868) Boundary_loss: 0.014078 (0.014070) Loss: 1.0281 (1.0028) +2025-09-11,19:19:01 | INFO | Train Epoch: 2 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.0064 (0.98921) Boundary_loss: 0.014063 (0.014070) Loss: 1.0204 (1.0033) +2025-09-11,19:20:08 | INFO | Train Epoch: 2 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.180 Boundary Ratio: 0.246 Contrastive_loss: 0.91841 (0.98718) Boundary_loss: 0.014079 (0.014070) Loss: 0.93248 (1.0013) +2025-09-11,19:21:14 | INFO | Train Epoch: 2 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 1.0619 (0.98926) Boundary_loss: 0.014053 (0.014070) Loss: 1.0760 (1.0033) +2025-09-11,19:22:21 | INFO | Train Epoch: 2 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.98566 (0.98916) Boundary_loss: 0.014026 (0.014068) Loss: 0.99969 (1.0032) +2025-09-11,19:23:27 | INFO | Train Epoch: 2 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 47.986 Boundary Ratio: 0.245 Contrastive_loss: 0.92036 (0.98735) Boundary_loss: 0.014094 (0.014069) Loss: 0.93446 (1.0014) +2025-09-11,19:24:34 | INFO | Train Epoch: 2 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.92488 (0.98575) Boundary_loss: 0.014047 (0.014068) Loss: 0.93893 (0.99982) +2025-09-11,19:25:40 | INFO | Train Epoch: 2 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.94550 (0.98474) Boundary_loss: 0.014044 (0.014068) Loss: 0.95955 (0.99881) +2025-09-11,19:26:47 | INFO | Train Epoch: 2 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.95477 (0.98401) Boundary_loss: 0.014044 (0.014067) Loss: 0.96881 (0.99808) +2025-09-11,19:27:53 | INFO | Train Epoch: 2 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 1.0285 (0.98507) Boundary_loss: 0.014088 (0.014068) Loss: 1.0426 (0.99914) +2025-09-11,19:29:00 | INFO | Train Epoch: 2 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.89080 (0.98288) Boundary_loss: 0.014043 (0.014067) Loss: 0.90484 (0.99694) +2025-09-11,19:30:06 | INFO | Train Epoch: 2 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 1.0189 (0.98370) Boundary_loss: 0.014082 (0.014067) Loss: 1.0329 (0.99776) +2025-09-11,19:31:13 | INFO | Train Epoch: 2 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.301 Boundary Ratio: 0.246 Contrastive_loss: 0.95802 (0.98312) Boundary_loss: 0.014063 (0.014067) Loss: 0.97209 (0.99719) +2025-09-11,19:32:19 | INFO | Train Epoch: 2 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.97038 (0.98285) Boundary_loss: 0.014107 (0.014068) Loss: 0.98448 (0.99692) +2025-09-11,19:33:26 | INFO | Train Epoch: 2 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.94002 (0.98194) Boundary_loss: 0.014093 (0.014069) Loss: 0.95411 (0.99600) +2025-09-11,19:34:32 | INFO | Train Epoch: 2 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.85386 (0.97927) Boundary_loss: 0.014106 (0.014070) Loss: 0.86797 (0.99334) +2025-09-11,19:35:39 | INFO | Train Epoch: 2 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 1.0580 (0.98088) Boundary_loss: 0.014056 (0.014069) Loss: 1.0721 (0.99494) +2025-09-11,19:36:46 | INFO | Train Epoch: 2 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.88218 (0.97890) Boundary_loss: 0.014068 (0.014069) Loss: 0.89624 (0.99297) +2025-09-11,19:37:52 | INFO | Train Epoch: 2 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.98132 (0.97895) Boundary_loss: 0.014050 (0.014069) Loss: 0.99537 (0.99302) +2025-09-11,19:38:59 | INFO | Train Epoch: 2 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.0419 (0.98016) Boundary_loss: 0.014049 (0.014068) Loss: 1.0560 (0.99423) +2025-09-11,19:40:05 | INFO | Train Epoch: 2 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.94385 (0.97947) Boundary_loss: 0.014041 (0.014068) Loss: 0.95789 (0.99354) +2025-09-11,19:41:12 | INFO | Train Epoch: 2 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.338 Boundary Ratio: 0.247 Contrastive_loss: 1.0453 (0.98069) Boundary_loss: 0.014065 (0.014068) Loss: 1.0593 (0.99476) +2025-09-11,19:42:18 | INFO | Train Epoch: 2 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 1.0310 (0.98161) Boundary_loss: 0.014075 (0.014068) Loss: 1.0450 (0.99568) +2025-09-11,19:43:25 | INFO | Train Epoch: 2 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 49.365 Boundary Ratio: 0.252 Contrastive_loss: 0.93556 (0.98078) Boundary_loss: 0.014089 (0.014068) Loss: 0.94964 (0.99485) +2025-09-11,19:44:31 | INFO | Train Epoch: 2 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 49.383 Boundary Ratio: 0.252 Contrastive_loss: 0.91208 (0.97958) Boundary_loss: 0.014102 (0.014069) Loss: 0.92618 (0.99365) +2025-09-11,19:45:38 | INFO | Train Epoch: 2 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 49.584 Boundary Ratio: 0.253 Contrastive_loss: 1.0275 (0.98041) Boundary_loss: 0.014144 (0.014070) Loss: 1.0417 (0.99448) +2025-09-11,19:46:44 | INFO | Train Epoch: 2 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 0.92064 (0.97939) Boundary_loss: 0.014112 (0.014071) Loss: 0.93476 (0.99346) +2025-09-11,19:47:51 | INFO | Train Epoch: 2 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.91344 (0.97829) Boundary_loss: 0.014058 (0.014071) Loss: 0.92749 (0.99237) +2025-09-11,19:48:57 | INFO | Train Epoch: 2 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.98175 (0.97835) Boundary_loss: 0.014039 (0.014070) Loss: 0.99579 (0.99242) +2025-09-11,19:50:04 | INFO | Train Epoch: 2 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.82480 (0.97587) Boundary_loss: 0.014052 (0.014070) Loss: 0.83885 (0.98994) +2025-09-11,19:51:10 | INFO | Train Epoch: 2 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.1035 (0.97790) Boundary_loss: 0.014069 (0.014070) Loss: 1.1176 (0.99197) +2025-09-11,19:52:17 | INFO | Train Epoch: 2 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.93515 (0.97723) Boundary_loss: 0.014072 (0.014070) Loss: 0.94923 (0.99130) +2025-09-11,19:53:23 | INFO | Train Epoch: 2 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 1.0440 (0.97826) Boundary_loss: 0.014079 (0.014070) Loss: 1.0581 (0.99233) +2025-09-11,19:54:30 | INFO | Train Epoch: 2 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.92008 (0.97738) Boundary_loss: 0.014046 (0.014070) Loss: 0.93413 (0.99145) +2025-09-11,19:55:36 | INFO | Train Epoch: 2 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.90673 (0.97632) Boundary_loss: 0.014044 (0.014069) Loss: 0.92078 (0.99039) +2025-09-11,19:56:43 | INFO | Train Epoch: 2 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.92118 (0.97551) Boundary_loss: 0.014063 (0.014069) Loss: 0.93525 (0.98958) +2025-09-11,19:57:49 | INFO | Train Epoch: 2 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 1.1125 (0.97750) Boundary_loss: 0.014051 (0.014069) Loss: 1.1266 (0.99157) +2025-09-11,19:58:56 | INFO | Train Epoch: 2 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 0.90815 (0.97651) Boundary_loss: 0.014057 (0.014069) Loss: 0.92221 (0.99058) +2025-09-11,20:00:03 | INFO | Train Epoch: 2 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.96063 (0.97628) Boundary_loss: 0.014036 (0.014068) Loss: 0.97467 (0.99035) +2025-09-11,20:01:09 | INFO | Train Epoch: 2 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.91936 (0.97549) Boundary_loss: 0.014065 (0.014068) Loss: 0.93343 (0.98956) +2025-09-11,20:02:16 | INFO | Train Epoch: 2 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.92062 (0.97474) Boundary_loss: 0.014031 (0.014068) Loss: 0.93465 (0.98881) +2025-09-11,20:03:22 | INFO | Train Epoch: 2 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.99216 (0.97498) Boundary_loss: 0.014016 (0.014067) Loss: 1.0062 (0.98904) +2025-09-11,20:04:29 | INFO | Train Epoch: 2 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.389 Boundary Ratio: 0.247 Contrastive_loss: 0.91681 (0.97420) Boundary_loss: 0.014063 (0.014067) Loss: 0.93087 (0.98827) +2025-09-11,20:05:35 | INFO | Train Epoch: 2 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.95145 (0.97390) Boundary_loss: 0.014037 (0.014067) Loss: 0.96549 (0.98797) +2025-09-11,20:06:42 | INFO | Train Epoch: 2 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.86805 (0.97253) Boundary_loss: 0.014066 (0.014067) Loss: 0.88212 (0.98659) +2025-09-11,20:07:48 | INFO | Train Epoch: 2 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 0.94295 (0.97215) Boundary_loss: 0.014059 (0.014067) Loss: 0.95701 (0.98622) +2025-09-11,20:08:55 | INFO | Train Epoch: 2 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.109 Boundary Ratio: 0.251 Contrastive_loss: 0.97367 (0.97217) Boundary_loss: 0.014050 (0.014066) Loss: 0.98772 (0.98623) +2025-09-11,20:10:01 | INFO | Train Epoch: 2 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.90820 (0.97137) Boundary_loss: 0.014049 (0.014066) Loss: 0.92224 (0.98543) +2025-09-11,20:11:08 | INFO | Train Epoch: 2 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 49.391 Boundary Ratio: 0.252 Contrastive_loss: 0.88733 (0.97033) Boundary_loss: 0.014114 (0.014067) Loss: 0.90144 (0.98440) +2025-09-11,20:12:15 | INFO | Train Epoch: 2 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.79357 (0.96818) Boundary_loss: 0.014091 (0.014067) Loss: 0.80766 (0.98224) +2025-09-11,20:13:21 | INFO | Train Epoch: 2 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.98547 (0.96838) Boundary_loss: 0.014047 (0.014067) Loss: 0.99952 (0.98245) +2025-09-11,20:14:28 | INFO | Train Epoch: 2 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.92682 (0.96789) Boundary_loss: 0.014081 (0.014067) Loss: 0.94090 (0.98196) +2025-09-11,20:15:34 | INFO | Train Epoch: 2 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 1.1024 (0.96947) Boundary_loss: 0.014047 (0.014067) Loss: 1.1165 (0.98354) +2025-09-11,20:16:41 | INFO | Train Epoch: 2 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 1.0422 (0.97032) Boundary_loss: 0.014035 (0.014066) Loss: 1.0563 (0.98438) +2025-09-11,20:17:47 | INFO | Train Epoch: 2 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.91952 (0.96973) Boundary_loss: 0.014072 (0.014066) Loss: 0.93359 (0.98380) +2025-09-11,20:18:54 | INFO | Train Epoch: 2 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.96242 (0.96965) Boundary_loss: 0.014051 (0.014066) Loss: 0.97647 (0.98372) +2025-09-11,20:20:00 | INFO | Train Epoch: 2 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 1.0503 (0.97056) Boundary_loss: 0.014047 (0.014066) Loss: 1.0643 (0.98462) +2025-09-11,20:21:07 | INFO | Train Epoch: 2 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 1.0622 (0.97157) Boundary_loss: 0.014057 (0.014066) Loss: 1.0762 (0.98564) +2025-09-11,20:22:14 | INFO | Train Epoch: 2 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.94597 (0.97129) Boundary_loss: 0.014043 (0.014066) Loss: 0.96001 (0.98536) +2025-09-11,20:23:20 | INFO | Train Epoch: 2 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.95145 (0.97108) Boundary_loss: 0.014035 (0.014065) Loss: 0.96548 (0.98514) +2025-09-11,20:24:27 | INFO | Train Epoch: 2 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.88233 (0.97012) Boundary_loss: 0.014078 (0.014065) Loss: 0.89640 (0.98419) +2025-09-11,20:25:33 | INFO | Train Epoch: 2 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.91807 (0.96957) Boundary_loss: 0.014058 (0.014065) Loss: 0.93213 (0.98363) +2025-09-11,20:26:40 | INFO | Train Epoch: 2 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 1.0362 (0.97027) Boundary_loss: 0.014055 (0.014065) Loss: 1.0503 (0.98434) +2025-09-11,20:27:46 | INFO | Train Epoch: 2 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.99168 (0.97049) Boundary_loss: 0.014075 (0.014065) Loss: 1.0058 (0.98456) +2025-09-11,20:28:53 | INFO | Train Epoch: 2 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.97834 (0.97057) Boundary_loss: 0.014062 (0.014065) Loss: 0.99240 (0.98464) +2025-09-11,20:29:59 | INFO | Train Epoch: 2 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.98856 (0.97076) Boundary_loss: 0.014047 (0.014065) Loss: 1.0026 (0.98482) +2025-09-11,20:31:06 | INFO | Train Epoch: 2 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.85345 (0.96957) Boundary_loss: 0.014039 (0.014065) Loss: 0.86749 (0.98364) +2025-09-11,20:32:13 | INFO | Train Epoch: 2 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.82510 (0.96813) Boundary_loss: 0.014052 (0.014065) Loss: 0.83916 (0.98219) +2025-09-11,20:33:19 | INFO | Train Epoch: 2 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 1.0450 (0.96889) Boundary_loss: 0.014142 (0.014066) Loss: 1.0592 (0.98296) +2025-09-11,20:34:26 | INFO | Train Epoch: 2 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.94405 (0.96865) Boundary_loss: 0.014062 (0.014065) Loss: 0.95812 (0.98271) +2025-09-11,20:35:32 | INFO | Train Epoch: 2 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.96466 (0.96861) Boundary_loss: 0.014035 (0.014065) Loss: 0.97869 (0.98267) +2025-09-11,20:36:39 | INFO | Train Epoch: 2 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.81174 (0.96710) Boundary_loss: 0.014046 (0.014065) Loss: 0.82578 (0.98116) +2025-09-11,20:37:45 | INFO | Train Epoch: 2 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.90553 (0.96651) Boundary_loss: 0.014080 (0.014065) Loss: 0.91961 (0.98058) +2025-09-11,20:38:52 | INFO | Train Epoch: 2 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 0.93166 (0.96618) Boundary_loss: 0.014091 (0.014065) Loss: 0.94575 (0.98025) +2025-09-11,20:39:58 | INFO | Train Epoch: 2 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.90624 (0.96562) Boundary_loss: 0.014052 (0.014065) Loss: 0.92030 (0.97969) +2025-09-11,20:41:05 | INFO | Train Epoch: 2 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.86727 (0.96471) Boundary_loss: 0.014032 (0.014065) Loss: 0.88130 (0.97878) +2025-09-11,20:42:11 | INFO | Train Epoch: 2 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 1.0592 (0.96558) Boundary_loss: 0.014030 (0.014065) Loss: 1.0732 (0.97964) +2025-09-11,20:43:18 | INFO | Train Epoch: 2 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.92453 (0.96521) Boundary_loss: 0.014049 (0.014064) Loss: 0.93858 (0.97927) +2025-09-11,20:44:24 | INFO | Train Epoch: 2 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 1.0041 (0.96556) Boundary_loss: 0.014071 (0.014065) Loss: 1.0181 (0.97962) +2025-09-11,20:45:31 | INFO | Train Epoch: 2 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.87844 (0.96478) Boundary_loss: 0.014036 (0.014064) Loss: 0.89248 (0.97884) +2025-09-11,20:46:37 | INFO | Train Epoch: 2 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 1.0154 (0.96523) Boundary_loss: 0.014048 (0.014064) Loss: 1.0295 (0.97929) +2025-09-11,20:47:44 | INFO | Train Epoch: 2 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.99189 (0.96546) Boundary_loss: 0.014053 (0.014064) Loss: 1.0059 (0.97953) +2025-09-11,20:48:50 | INFO | Train Epoch: 2 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.98934 (0.96567) Boundary_loss: 0.014022 (0.014064) Loss: 1.0034 (0.97973) +2025-09-11,20:49:57 | INFO | Train Epoch: 2 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.93642 (0.96542) Boundary_loss: 0.014067 (0.014064) Loss: 0.95049 (0.97948) +2025-09-11,20:51:03 | INFO | Train Epoch: 2 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 0.99382 (0.96566) Boundary_loss: 0.014021 (0.014063) Loss: 1.0078 (0.97972) +2025-09-11,20:52:10 | INFO | Train Epoch: 2 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 1.0627 (0.96648) Boundary_loss: 0.014056 (0.014063) Loss: 1.0767 (0.98054) +2025-09-11,20:53:17 | INFO | Train Epoch: 2 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 1.0044 (0.96680) Boundary_loss: 0.014066 (0.014063) Loss: 1.0185 (0.98086) +2025-09-11,20:54:23 | INFO | Train Epoch: 2 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.92615 (0.96646) Boundary_loss: 0.014086 (0.014063) Loss: 0.94024 (0.98052) +2025-09-11,20:55:29 | INFO | Train Epoch: 2 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.94196 (0.96626) Boundary_loss: 0.014037 (0.014063) Loss: 0.95600 (0.98032) +2025-09-11,20:56:36 | INFO | Train Epoch: 2 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.93029 (0.96596) Boundary_loss: 0.014052 (0.014063) Loss: 0.94434 (0.98003) +2025-09-11,20:57:42 | INFO | Train Epoch: 2 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.95962 (0.96591) Boundary_loss: 0.014020 (0.014063) Loss: 0.97364 (0.97998) +2025-09-11,20:58:49 | INFO | Train Epoch: 2 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.98765 (0.96609) Boundary_loss: 0.014052 (0.014063) Loss: 1.0017 (0.98015) +2025-09-11,20:59:56 | INFO | Train Epoch: 2 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.88469 (0.96544) Boundary_loss: 0.014071 (0.014063) Loss: 0.89876 (0.97950) +2025-09-11,21:01:02 | INFO | Train Epoch: 2 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.86041 (0.96460) Boundary_loss: 0.014043 (0.014063) Loss: 0.87445 (0.97867) +2025-09-11,21:02:09 | INFO | Train Epoch: 2 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.97709 (0.96470) Boundary_loss: 0.014021 (0.014062) Loss: 0.99111 (0.97876) +2025-09-11,21:03:15 | INFO | Train Epoch: 2 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.96109 (0.96467) Boundary_loss: 0.014045 (0.014062) Loss: 0.97514 (0.97874) +2025-09-11,21:04:22 | INFO | Train Epoch: 2 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.89036 (0.96410) Boundary_loss: 0.014036 (0.014062) Loss: 0.90439 (0.97816) +2025-09-11,21:05:28 | INFO | Train Epoch: 2 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 1.0472 (0.96474) Boundary_loss: 0.014023 (0.014062) Loss: 1.0612 (0.97880) +2025-09-11,21:06:35 | INFO | Train Epoch: 2 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.88775 (0.96415) Boundary_loss: 0.014056 (0.014062) Loss: 0.90180 (0.97821) +2025-09-11,21:07:41 | INFO | Train Epoch: 2 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.94624 (0.96401) Boundary_loss: 0.014025 (0.014061) Loss: 0.96026 (0.97807) +2025-09-11,21:08:48 | INFO | Train Epoch: 2 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 1.0301 (0.96451) Boundary_loss: 0.014023 (0.014061) Loss: 1.0441 (0.97857) +2025-09-11,21:09:54 | INFO | Train Epoch: 2 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.92926 (0.96425) Boundary_loss: 0.014048 (0.014061) Loss: 0.94331 (0.97831) +2025-09-11,21:11:00 | INFO | Train Epoch: 2 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.95412 (0.96417) Boundary_loss: 0.014052 (0.014061) Loss: 0.96818 (0.97823) +2025-09-11,21:12:07 | INFO | Train Epoch: 2 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.98161 (0.96430) Boundary_loss: 0.014039 (0.014061) Loss: 0.99565 (0.97836) +2025-09-11,21:13:13 | INFO | Train Epoch: 2 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.94474 (0.96416) Boundary_loss: 0.014075 (0.014061) Loss: 0.95882 (0.97822) +2025-09-11,21:14:20 | INFO | Train Epoch: 2 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.85511 (0.96337) Boundary_loss: 0.014042 (0.014061) Loss: 0.86915 (0.97743) +2025-09-11,21:15:27 | INFO | Train Epoch: 2 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 1.0046 (0.96366) Boundary_loss: 0.014066 (0.014061) Loss: 1.0186 (0.97772) +2025-09-11,21:16:33 | INFO | Train Epoch: 2 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.86772 (0.96298) Boundary_loss: 0.014021 (0.014060) Loss: 0.88174 (0.97704) +2025-09-11,21:17:40 | INFO | Train Epoch: 2 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.95495 (0.96292) Boundary_loss: 0.014029 (0.014060) Loss: 0.96898 (0.97698) +2025-09-11,21:18:46 | INFO | Train Epoch: 2 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.307 Boundary Ratio: 0.246 Contrastive_loss: 0.88792 (0.96239) Boundary_loss: 0.014071 (0.014060) Loss: 0.90199 (0.97645) +2025-09-11,21:19:52 | INFO | Train Epoch: 2 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 1.0243 (0.96283) Boundary_loss: 0.014022 (0.014060) Loss: 1.0383 (0.97689) +2025-09-11,21:20:59 | INFO | Train Epoch: 2 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.93319 (0.96262) Boundary_loss: 0.014035 (0.014060) Loss: 0.94722 (0.97668) +2025-09-11,21:22:05 | INFO | Train Epoch: 2 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.94226 (0.96248) Boundary_loss: 0.014031 (0.014060) Loss: 0.95629 (0.97654) +2025-09-11,21:23:12 | INFO | Train Epoch: 2 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.87413 (0.96187) Boundary_loss: 0.014065 (0.014060) Loss: 0.88820 (0.97593) +2025-09-11,21:24:18 | INFO | Train Epoch: 2 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.83099 (0.96098) Boundary_loss: 0.014091 (0.014060) Loss: 0.84508 (0.97504) +2025-09-11,21:25:25 | INFO | Train Epoch: 2 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 1.0306 (0.96145) Boundary_loss: 0.014028 (0.014060) Loss: 1.0446 (0.97551) +2025-09-11,21:26:31 | INFO | Train Epoch: 2 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.73581 (0.95994) Boundary_loss: 0.014036 (0.014060) Loss: 0.74985 (0.97400) +2025-09-11,21:27:38 | INFO | Train Epoch: 2 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.78724 (0.95879) Boundary_loss: 0.014080 (0.014060) Loss: 0.80132 (0.97285) +2025-09-11,21:28:44 | INFO | Train Epoch: 2 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.91644 (0.95851) Boundary_loss: 0.014023 (0.014059) Loss: 0.93046 (0.97257) +2025-09-11,21:29:51 | INFO | Train Epoch: 2 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.90130 (0.95813) Boundary_loss: 0.014027 (0.014059) Loss: 0.91533 (0.97219) +2025-09-11,21:30:57 | INFO | Train Epoch: 2 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.227 Boundary Ratio: 0.246 Contrastive_loss: 0.91903 (0.95788) Boundary_loss: 0.014061 (0.014059) Loss: 0.93309 (0.97194) +2025-09-11,21:32:04 | INFO | Train Epoch: 2 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 1.0401 (0.95841) Boundary_loss: 0.014091 (0.014059) Loss: 1.0542 (0.97247) +2025-09-11,21:33:10 | INFO | Train Epoch: 2 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.97567 (0.95852) Boundary_loss: 0.014056 (0.014059) Loss: 0.98973 (0.97258) +2025-09-11,21:34:17 | INFO | Train Epoch: 2 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.94915 (0.95846) Boundary_loss: 0.014014 (0.014059) Loss: 0.96316 (0.97252) +2025-09-11,21:35:23 | INFO | Train Epoch: 2 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.88108 (0.95797) Boundary_loss: 0.014052 (0.014059) Loss: 0.89514 (0.97203) +2025-09-11,21:36:30 | INFO | Train Epoch: 2 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.90868 (0.95766) Boundary_loss: 0.014012 (0.014059) Loss: 0.92269 (0.97171) +2025-09-11,21:37:36 | INFO | Train Epoch: 2 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.148 Boundary Ratio: 0.251 Contrastive_loss: 0.93455 (0.95751) Boundary_loss: 0.014091 (0.014059) Loss: 0.94864 (0.97157) +2025-09-11,21:38:43 | INFO | Train Epoch: 2 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.95598 (0.95750) Boundary_loss: 0.014032 (0.014059) Loss: 0.97002 (0.97156) +2025-09-11,21:39:49 | INFO | Train Epoch: 2 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 49.258 Boundary Ratio: 0.251 Contrastive_loss: 1.0282 (0.95794) Boundary_loss: 0.014058 (0.014059) Loss: 1.0422 (0.97200) +2025-09-11,21:40:56 | INFO | Train Epoch: 2 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.95610 (0.95793) Boundary_loss: 0.014043 (0.014059) Loss: 0.97015 (0.97199) +2025-09-11,21:42:02 | INFO | Train Epoch: 2 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.82671 (0.95712) Boundary_loss: 0.014033 (0.014059) Loss: 0.84074 (0.97118) +2025-09-11,21:43:09 | INFO | Train Epoch: 2 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.93450 (0.95699) Boundary_loss: 0.014015 (0.014058) Loss: 0.94852 (0.97104) +2025-09-11,21:44:15 | INFO | Train Epoch: 2 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 49.412 Boundary Ratio: 0.252 Contrastive_loss: 0.79954 (0.95603) Boundary_loss: 0.014062 (0.014058) Loss: 0.81361 (0.97009) +2025-09-11,21:45:22 | INFO | Train Epoch: 2 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 1.0152 (0.95639) Boundary_loss: 0.014054 (0.014058) Loss: 1.0292 (0.97045) +2025-09-11,21:46:29 | INFO | Train Epoch: 2 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.93051 (0.95623) Boundary_loss: 0.014038 (0.014058) Loss: 0.94455 (0.97029) +2025-09-11,21:47:35 | INFO | Train Epoch: 2 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.90179 (0.95591) Boundary_loss: 0.014023 (0.014058) Loss: 0.91582 (0.96997) +2025-09-11,21:48:42 | INFO | Train Epoch: 2 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.95729 (0.95592) Boundary_loss: 0.014076 (0.014058) Loss: 0.97137 (0.96998) +2025-09-11,21:49:48 | INFO | Train Epoch: 2 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.99722 (0.95616) Boundary_loss: 0.014026 (0.014058) Loss: 1.0112 (0.97022) +2025-09-11,21:50:55 | INFO | Train Epoch: 2 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.94523 (0.95610) Boundary_loss: 0.014016 (0.014058) Loss: 0.95925 (0.97015) +2025-09-11,21:52:01 | INFO | Train Epoch: 2 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.81057 (0.95525) Boundary_loss: 0.014010 (0.014057) Loss: 0.82458 (0.96931) +2025-09-11,21:53:08 | INFO | Train Epoch: 2 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.97843 (0.95538) Boundary_loss: 0.014021 (0.014057) Loss: 0.99245 (0.96944) +2025-09-11,21:54:14 | INFO | Train Epoch: 2 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 49.211 Boundary Ratio: 0.251 Contrastive_loss: 0.91974 (0.95518) Boundary_loss: 0.014024 (0.014057) Loss: 0.93376 (0.96924) +2025-09-11,21:55:21 | INFO | Train Epoch: 2 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.90331 (0.95488) Boundary_loss: 0.014028 (0.014057) Loss: 0.91734 (0.96894) +2025-09-11,21:56:27 | INFO | Train Epoch: 2 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.88606 (0.95449) Boundary_loss: 0.014041 (0.014057) Loss: 0.90010 (0.96855) +2025-09-11,21:57:34 | INFO | Train Epoch: 2 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.80002 (0.95362) Boundary_loss: 0.014050 (0.014057) Loss: 0.81407 (0.96768) +2025-09-11,21:58:40 | INFO | Train Epoch: 2 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.85878 (0.95309) Boundary_loss: 0.014025 (0.014056) Loss: 0.87281 (0.96714) +2025-09-11,21:59:47 | INFO | Train Epoch: 2 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.0140 (0.95343) Boundary_loss: 0.014037 (0.014056) Loss: 1.0280 (0.96748) +2025-09-11,22:00:53 | INFO | Train Epoch: 2 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 1.0341 (0.95387) Boundary_loss: 0.014012 (0.014056) Loss: 1.0481 (0.96793) +2025-09-11,22:02:00 | INFO | Train Epoch: 2 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.94172 (0.95381) Boundary_loss: 0.014025 (0.014056) Loss: 0.95575 (0.96786) +2025-09-11,22:03:06 | INFO | Train Epoch: 2 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.81267 (0.95303) Boundary_loss: 0.014054 (0.014056) Loss: 0.82672 (0.96709) +2025-09-11,22:04:13 | INFO | Train Epoch: 2 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.84819 (0.95246) Boundary_loss: 0.014032 (0.014056) Loss: 0.86223 (0.96651) +2025-09-11,22:05:20 | INFO | Train Epoch: 2 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.97280 (0.95257) Boundary_loss: 0.014062 (0.014056) Loss: 0.98686 (0.96663) +2025-09-11,22:06:26 | INFO | Train Epoch: 2 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.96066 (0.95261) Boundary_loss: 0.014022 (0.014056) Loss: 0.97469 (0.96667) +2025-09-11,22:07:33 | INFO | Train Epoch: 2 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.94494 (0.95257) Boundary_loss: 0.013996 (0.014055) Loss: 0.95894 (0.96663) +2025-09-11,22:08:39 | INFO | Train Epoch: 2 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.81984 (0.95186) Boundary_loss: 0.014015 (0.014055) Loss: 0.83386 (0.96592) +2025-09-11,22:09:46 | INFO | Train Epoch: 2 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.67723 (0.95040) Boundary_loss: 0.014020 (0.014055) Loss: 0.69125 (0.96446) +2025-09-11,22:10:52 | INFO | Train Epoch: 2 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.91707 (0.95022) Boundary_loss: 0.014058 (0.014055) Loss: 0.93113 (0.96428) +2025-09-11,22:11:59 | INFO | Train Epoch: 2 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.83779 (0.94963) Boundary_loss: 0.014012 (0.014055) Loss: 0.85180 (0.96369) +2025-09-11,22:13:05 | INFO | Train Epoch: 2 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.76680 (0.94868) Boundary_loss: 0.014008 (0.014054) Loss: 0.78081 (0.96273) +2025-09-11,22:14:12 | INFO | Train Epoch: 2 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.84590 (0.94814) Boundary_loss: 0.014049 (0.014054) Loss: 0.85995 (0.96220) +2025-09-11,22:15:18 | INFO | Train Epoch: 2 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.80756 (0.94741) Boundary_loss: 0.014004 (0.014054) Loss: 0.82156 (0.96147) +2025-09-11,22:16:25 | INFO | Train Epoch: 2 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.85580 (0.94694) Boundary_loss: 0.014021 (0.014054) Loss: 0.86982 (0.96099) +2025-09-11,22:17:31 | INFO | Train Epoch: 2 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 0.86653 (0.94653) Boundary_loss: 0.014027 (0.014054) Loss: 0.88055 (0.96058) +2025-09-11,22:18:38 | INFO | Train Epoch: 2 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.93033 (0.94644) Boundary_loss: 0.013996 (0.014054) Loss: 0.94432 (0.96050) +2025-09-11,22:19:44 | INFO | Train Epoch: 2 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.76286 (0.94551) Boundary_loss: 0.014027 (0.014053) Loss: 0.77689 (0.95957) +2025-09-11,22:20:51 | INFO | Train Epoch: 2 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.83686 (0.94496) Boundary_loss: 0.014053 (0.014053) Loss: 0.85091 (0.95902) +2025-09-11,22:21:57 | INFO | Train Epoch: 2 [10138112/26365952 (38%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.79932 (0.94423) Boundary_loss: 0.014018 (0.014053) Loss: 0.81334 (0.95829) +2025-09-11,22:23:04 | INFO | Train Epoch: 2 [10189312/26365952 (39%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.92572 (0.94414) Boundary_loss: 0.014039 (0.014053) Loss: 0.93976 (0.95819) +2025-09-11,22:24:10 | INFO | Train Epoch: 2 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.92400 (0.94404) Boundary_loss: 0.014023 (0.014053) Loss: 0.93802 (0.95809) +2025-09-11,22:25:17 | INFO | Train Epoch: 2 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.92692 (0.94395) Boundary_loss: 0.014015 (0.014053) Loss: 0.94093 (0.95801) +2025-09-11,22:26:23 | INFO | Train Epoch: 2 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.357 Boundary Ratio: 0.252 Contrastive_loss: 0.97107 (0.94409) Boundary_loss: 0.014032 (0.014053) Loss: 0.98510 (0.95814) +2025-09-11,22:27:30 | INFO | Train Epoch: 2 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.82906 (0.94352) Boundary_loss: 0.014035 (0.014053) Loss: 0.84310 (0.95758) +2025-09-11,22:28:37 | INFO | Train Epoch: 2 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.74069 (0.94254) Boundary_loss: 0.014047 (0.014053) Loss: 0.75473 (0.95659) +2025-09-11,22:29:43 | INFO | Train Epoch: 2 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.89407 (0.94230) Boundary_loss: 0.014008 (0.014052) Loss: 0.90807 (0.95635) +2025-09-11,22:30:50 | INFO | Train Epoch: 2 [10547712/26365952 (40%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.88713 (0.94203) Boundary_loss: 0.014037 (0.014052) Loss: 0.90117 (0.95609) +2025-09-11,22:31:56 | INFO | Train Epoch: 2 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.87404 (0.94171) Boundary_loss: 0.014024 (0.014052) Loss: 0.88806 (0.95576) +2025-09-11,22:33:03 | INFO | Train Epoch: 2 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.94854 (0.94174) Boundary_loss: 0.014020 (0.014052) Loss: 0.96256 (0.95579) +2025-09-11,22:34:09 | INFO | Train Epoch: 2 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 1.0080 (0.94205) Boundary_loss: 0.014018 (0.014052) Loss: 1.0220 (0.95611) +2025-09-11,22:35:16 | INFO | Train Epoch: 2 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.209 Boundary Ratio: 0.251 Contrastive_loss: 0.84188 (0.94158) Boundary_loss: 0.014028 (0.014052) Loss: 0.85591 (0.95563) +2025-09-11,22:36:22 | INFO | Train Epoch: 2 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.88464 (0.94131) Boundary_loss: 0.014010 (0.014052) Loss: 0.89865 (0.95536) +2025-09-11,22:37:29 | INFO | Train Epoch: 2 [10854912/26365952 (41%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.89997 (0.94112) Boundary_loss: 0.014041 (0.014052) Loss: 0.91401 (0.95517) +2025-09-11,22:38:35 | INFO | Train Epoch: 2 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 1.0040 (0.94141) Boundary_loss: 0.014030 (0.014051) Loss: 1.0180 (0.95546) +2025-09-11,22:39:42 | INFO | Train Epoch: 2 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.88233 (0.94114) Boundary_loss: 0.014009 (0.014051) Loss: 0.89634 (0.95519) +2025-09-11,22:40:48 | INFO | Train Epoch: 2 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.76190 (0.94031) Boundary_loss: 0.014061 (0.014051) Loss: 0.77596 (0.95436) +2025-09-11,22:41:55 | INFO | Train Epoch: 2 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.365 Boundary Ratio: 0.247 Contrastive_loss: 0.99038 (0.94054) Boundary_loss: 0.014032 (0.014051) Loss: 1.0044 (0.95459) +2025-09-11,22:43:01 | INFO | Train Epoch: 2 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.94093 (0.94054) Boundary_loss: 0.014076 (0.014051) Loss: 0.95501 (0.95459) +2025-09-11,22:44:08 | INFO | Train Epoch: 2 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 0.92074 (0.94045) Boundary_loss: 0.014057 (0.014051) Loss: 0.93480 (0.95450) +2025-09-11,22:45:14 | INFO | Train Epoch: 2 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.80717 (0.93984) Boundary_loss: 0.014043 (0.014051) Loss: 0.82121 (0.95389) +2025-09-11,22:46:21 | INFO | Train Epoch: 2 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.95192 (0.93990) Boundary_loss: 0.014029 (0.014051) Loss: 0.96595 (0.95395) +2025-09-11,22:47:27 | INFO | Train Epoch: 2 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.92651 (0.93984) Boundary_loss: 0.014024 (0.014051) Loss: 0.94054 (0.95389) +2025-09-11,22:48:34 | INFO | Train Epoch: 2 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.87428 (0.93954) Boundary_loss: 0.014038 (0.014051) Loss: 0.88832 (0.95359) +2025-09-11,22:49:40 | INFO | Train Epoch: 2 [11418112/26365952 (43%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.85576 (0.93917) Boundary_loss: 0.014009 (0.014051) Loss: 0.86977 (0.95322) +2025-09-11,22:50:47 | INFO | Train Epoch: 2 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.87257 (0.93887) Boundary_loss: 0.014044 (0.014051) Loss: 0.88662 (0.95292) +2025-09-11,22:51:53 | INFO | Train Epoch: 2 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.89812 (0.93869) Boundary_loss: 0.014036 (0.014051) Loss: 0.91216 (0.95274) +2025-09-11,22:53:00 | INFO | Train Epoch: 2 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.81563 (0.93815) Boundary_loss: 0.014076 (0.014051) Loss: 0.82971 (0.95220) +2025-09-11,22:54:06 | INFO | Train Epoch: 2 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.82180 (0.93764) Boundary_loss: 0.014024 (0.014051) Loss: 0.83582 (0.95169) +2025-09-11,22:55:13 | INFO | Train Epoch: 2 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 0.85618 (0.93728) Boundary_loss: 0.014051 (0.014051) Loss: 0.87023 (0.95134) +2025-09-11,22:56:19 | INFO | Train Epoch: 2 [11725312/26365952 (44%)] Avg Boundaries (per batch): 49.148 Boundary Ratio: 0.251 Contrastive_loss: 0.88613 (0.93706) Boundary_loss: 0.014064 (0.014051) Loss: 0.90019 (0.95111) +2025-09-11,22:57:26 | INFO | Train Epoch: 2 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.88230 (0.93682) Boundary_loss: 0.014018 (0.014051) Loss: 0.89631 (0.95088) +2025-09-11,22:58:32 | INFO | Train Epoch: 2 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.85250 (0.93646) Boundary_loss: 0.013994 (0.014050) Loss: 0.86650 (0.95051) +2025-09-11,22:59:39 | INFO | Train Epoch: 2 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.79417 (0.93585) Boundary_loss: 0.014039 (0.014050) Loss: 0.80821 (0.94990) +2025-09-11,23:00:45 | INFO | Train Epoch: 2 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.90448 (0.93572) Boundary_loss: 0.014040 (0.014050) Loss: 0.91852 (0.94977) +2025-09-11,23:01:52 | INFO | Train Epoch: 2 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.94361 (0.93575) Boundary_loss: 0.014030 (0.014050) Loss: 0.95764 (0.94980) +2025-09-11,23:02:58 | INFO | Train Epoch: 2 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.86708 (0.93546) Boundary_loss: 0.014038 (0.014050) Loss: 0.88112 (0.94951) +2025-09-11,23:04:05 | INFO | Train Epoch: 2 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.89984 (0.93531) Boundary_loss: 0.014038 (0.014050) Loss: 0.91388 (0.94936) +2025-09-11,23:05:12 | INFO | Train Epoch: 2 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.96579 (0.93544) Boundary_loss: 0.014061 (0.014050) Loss: 0.97985 (0.94949) +2025-09-11,23:06:18 | INFO | Train Epoch: 2 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.79094 (0.93483) Boundary_loss: 0.014021 (0.014050) Loss: 0.80497 (0.94888) +2025-09-11,23:07:24 | INFO | Train Epoch: 2 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.86253 (0.93453) Boundary_loss: 0.014015 (0.014050) Loss: 0.87654 (0.94858) +2025-09-11,23:08:31 | INFO | Train Epoch: 2 [12288512/26365952 (47%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.76101 (0.93381) Boundary_loss: 0.014025 (0.014050) Loss: 0.77504 (0.94786) +2025-09-11,23:09:37 | INFO | Train Epoch: 2 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.72313 (0.93294) Boundary_loss: 0.014020 (0.014050) Loss: 0.73715 (0.94699) +2025-09-11,23:10:44 | INFO | Train Epoch: 2 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.94553 (0.93299) Boundary_loss: 0.014076 (0.014050) Loss: 0.95961 (0.94704) +2025-09-11,23:11:50 | INFO | Train Epoch: 2 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.78069 (0.93237) Boundary_loss: 0.014030 (0.014050) Loss: 0.79472 (0.94642) +2025-09-11,23:12:57 | INFO | Train Epoch: 2 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.89928 (0.93223) Boundary_loss: 0.013994 (0.014049) Loss: 0.91328 (0.94628) +2025-09-11,23:14:03 | INFO | Train Epoch: 2 [12544512/26365952 (48%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.85119 (0.93190) Boundary_loss: 0.014048 (0.014049) Loss: 0.86524 (0.94595) +2025-09-11,23:15:10 | INFO | Train Epoch: 2 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.83977 (0.93153) Boundary_loss: 0.014000 (0.014049) Loss: 0.85377 (0.94558) +2025-09-11,23:16:16 | INFO | Train Epoch: 2 [12646912/26365952 (48%)] Avg Boundaries (per batch): 49.289 Boundary Ratio: 0.251 Contrastive_loss: 0.84790 (0.93119) Boundary_loss: 0.014024 (0.014049) Loss: 0.86192 (0.94524) +2025-09-11,23:17:23 | INFO | Train Epoch: 2 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.88205 (0.93100) Boundary_loss: 0.014004 (0.014049) Loss: 0.89606 (0.94505) +2025-09-11,23:18:29 | INFO | Train Epoch: 2 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.98596 (0.93122) Boundary_loss: 0.014022 (0.014049) Loss: 0.99998 (0.94527) +2025-09-11,23:19:36 | INFO | Train Epoch: 2 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.88445 (0.93103) Boundary_loss: 0.014031 (0.014049) Loss: 0.89848 (0.94508) +2025-09-11,23:20:42 | INFO | Train Epoch: 2 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.88385 (0.93084) Boundary_loss: 0.014036 (0.014049) Loss: 0.89789 (0.94489) +2025-09-11,23:21:49 | INFO | Train Epoch: 2 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.79755 (0.93032) Boundary_loss: 0.014059 (0.014049) Loss: 0.81161 (0.94436) +2025-09-11,23:22:55 | INFO | Train Epoch: 2 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.88654 (0.93014) Boundary_loss: 0.014010 (0.014049) Loss: 0.90055 (0.94419) +2025-09-11,23:24:02 | INFO | Train Epoch: 2 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.88087 (0.92995) Boundary_loss: 0.014007 (0.014048) Loss: 0.89488 (0.94400) +2025-09-11,23:25:08 | INFO | Train Epoch: 2 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.93708 (0.92998) Boundary_loss: 0.014028 (0.014048) Loss: 0.95111 (0.94403) +2025-09-11,23:26:15 | INFO | Train Epoch: 2 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.91806 (0.92993) Boundary_loss: 0.014014 (0.014048) Loss: 0.93207 (0.94398) +2025-09-11,23:27:21 | INFO | Train Epoch: 2 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.90620 (0.92984) Boundary_loss: 0.014014 (0.014048) Loss: 0.92022 (0.94389) +2025-09-11,23:28:28 | INFO | Train Epoch: 2 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.87361 (0.92962) Boundary_loss: 0.014020 (0.014048) Loss: 0.88763 (0.94367) +2025-09-11,23:29:34 | INFO | Train Epoch: 2 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.94512 (0.92968) Boundary_loss: 0.014003 (0.014048) Loss: 0.95913 (0.94373) +2025-09-11,23:30:41 | INFO | Train Epoch: 2 [13312512/26365952 (50%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.82837 (0.92929) Boundary_loss: 0.014017 (0.014048) Loss: 0.84239 (0.94334) +2025-09-11,23:31:47 | INFO | Train Epoch: 2 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.84589 (0.92898) Boundary_loss: 0.014011 (0.014048) Loss: 0.85990 (0.94302) +2025-09-11,23:32:54 | INFO | Train Epoch: 2 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 1.0640 (0.92949) Boundary_loss: 0.014017 (0.014047) Loss: 1.0780 (0.94354) +2025-09-11,23:34:00 | INFO | Train Epoch: 2 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.80081 (0.92900) Boundary_loss: 0.013995 (0.014047) Loss: 0.81480 (0.94305) +2025-09-11,23:35:07 | INFO | Train Epoch: 2 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.96773 (0.92915) Boundary_loss: 0.013999 (0.014047) Loss: 0.98173 (0.94319) +2025-09-11,23:36:13 | INFO | Train Epoch: 2 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.82330 (0.92875) Boundary_loss: 0.014024 (0.014047) Loss: 0.83732 (0.94280) +2025-09-11,23:37:20 | INFO | Train Epoch: 2 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 0.81953 (0.92834) Boundary_loss: 0.014022 (0.014047) Loss: 0.83355 (0.94239) +2025-09-11,23:38:26 | INFO | Train Epoch: 2 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.83155 (0.92798) Boundary_loss: 0.014018 (0.014047) Loss: 0.84557 (0.94203) +2025-09-11,23:39:33 | INFO | Train Epoch: 2 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.87019 (0.92776) Boundary_loss: 0.014035 (0.014047) Loss: 0.88422 (0.94181) +2025-09-11,23:40:39 | INFO | Train Epoch: 2 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.80474 (0.92731) Boundary_loss: 0.014024 (0.014047) Loss: 0.81876 (0.94136) +2025-09-11,23:41:46 | INFO | Train Epoch: 2 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.82477 (0.92693) Boundary_loss: 0.014027 (0.014047) Loss: 0.83880 (0.94098) +2025-09-11,23:42:52 | INFO | Train Epoch: 2 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.90235 (0.92684) Boundary_loss: 0.013995 (0.014046) Loss: 0.91634 (0.94089) +2025-09-11,23:43:59 | INFO | Train Epoch: 2 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.77434 (0.92628) Boundary_loss: 0.014022 (0.014046) Loss: 0.78836 (0.94033) +2025-09-11,23:45:05 | INFO | Train Epoch: 2 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 1.0160 (0.92661) Boundary_loss: 0.014061 (0.014046) Loss: 1.0301 (0.94066) +2025-09-11,23:46:12 | INFO | Train Epoch: 2 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.84361 (0.92631) Boundary_loss: 0.014023 (0.014046) Loss: 0.85763 (0.94035) +2025-09-11,23:47:18 | INFO | Train Epoch: 2 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.81391 (0.92590) Boundary_loss: 0.014023 (0.014046) Loss: 0.82793 (0.93995) +2025-09-11,23:48:25 | INFO | Train Epoch: 2 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.85763 (0.92565) Boundary_loss: 0.014010 (0.014046) Loss: 0.87165 (0.93970) +2025-09-11,23:49:31 | INFO | Train Epoch: 2 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.88788 (0.92552) Boundary_loss: 0.014025 (0.014046) Loss: 0.90191 (0.93956) +2025-09-11,23:50:38 | INFO | Train Epoch: 2 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 0.90696 (0.92545) Boundary_loss: 0.014006 (0.014046) Loss: 0.92097 (0.93950) +2025-09-11,23:51:44 | INFO | Train Epoch: 2 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.66115 (0.92451) Boundary_loss: 0.014005 (0.014046) Loss: 0.67516 (0.93855) +2025-09-11,23:52:51 | INFO | Train Epoch: 2 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 0.82194 (0.92414) Boundary_loss: 0.014017 (0.014046) Loss: 0.83596 (0.93819) +2025-09-11,23:53:57 | INFO | Train Epoch: 2 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.87851 (0.92398) Boundary_loss: 0.013997 (0.014045) Loss: 0.89251 (0.93803) +2025-09-11,23:55:04 | INFO | Train Epoch: 2 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.81636 (0.92360) Boundary_loss: 0.014008 (0.014045) Loss: 0.83037 (0.93765) +2025-09-11,23:56:10 | INFO | Train Epoch: 2 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.84889 (0.92334) Boundary_loss: 0.014027 (0.014045) Loss: 0.86292 (0.93738) +2025-09-11,23:57:17 | INFO | Train Epoch: 2 [14541312/26365952 (55%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.84259 (0.92305) Boundary_loss: 0.014031 (0.014045) Loss: 0.85662 (0.93710) +2025-09-11,23:58:23 | INFO | Train Epoch: 2 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.80048 (0.92263) Boundary_loss: 0.014017 (0.014045) Loss: 0.81450 (0.93667) +2025-09-11,23:59:30 | INFO | Train Epoch: 2 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.81421 (0.92225) Boundary_loss: 0.014003 (0.014045) Loss: 0.82821 (0.93629) +2025-09-12,00:00:37 | INFO | Train Epoch: 2 [14694912/26365952 (56%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.90174 (0.92218) Boundary_loss: 0.014018 (0.014045) Loss: 0.91576 (0.93622) +2025-09-12,00:01:43 | INFO | Train Epoch: 2 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.91247 (0.92214) Boundary_loss: 0.014009 (0.014045) Loss: 0.92648 (0.93619) +2025-09-12,00:02:49 | INFO | Train Epoch: 2 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.77109 (0.92162) Boundary_loss: 0.013996 (0.014045) Loss: 0.78508 (0.93567) +2025-09-12,00:03:56 | INFO | Train Epoch: 2 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.332 Boundary Ratio: 0.247 Contrastive_loss: 0.88504 (0.92150) Boundary_loss: 0.014050 (0.014045) Loss: 0.89909 (0.93554) +2025-09-12,00:05:02 | INFO | Train Epoch: 2 [14899712/26365952 (57%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.87228 (0.92133) Boundary_loss: 0.014016 (0.014045) Loss: 0.88629 (0.93537) +2025-09-12,00:06:09 | INFO | Train Epoch: 2 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.89264 (0.92123) Boundary_loss: 0.014033 (0.014044) Loss: 0.90668 (0.93527) +2025-09-12,00:07:15 | INFO | Train Epoch: 2 [15002112/26365952 (57%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 0.87857 (0.92108) Boundary_loss: 0.014030 (0.014044) Loss: 0.89260 (0.93513) +2025-09-12,00:08:22 | INFO | Train Epoch: 2 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.78989 (0.92064) Boundary_loss: 0.014032 (0.014044) Loss: 0.80393 (0.93468) +2025-09-12,00:09:28 | INFO | Train Epoch: 2 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.87867 (0.92050) Boundary_loss: 0.013990 (0.014044) Loss: 0.89266 (0.93454) +2025-09-12,00:10:35 | INFO | Train Epoch: 2 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 0.84307 (0.92024) Boundary_loss: 0.014022 (0.014044) Loss: 0.85710 (0.93428) +2025-09-12,00:11:41 | INFO | Train Epoch: 2 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.95552 (0.92036) Boundary_loss: 0.014058 (0.014044) Loss: 0.96957 (0.93440) +2025-09-12,00:12:48 | INFO | Train Epoch: 2 [15258112/26365952 (58%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.75922 (0.91982) Boundary_loss: 0.014001 (0.014044) Loss: 0.77322 (0.93386) +2025-09-12,00:13:54 | INFO | Train Epoch: 2 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.90879 (0.91978) Boundary_loss: 0.014019 (0.014044) Loss: 0.92280 (0.93382) +2025-09-12,00:15:01 | INFO | Train Epoch: 2 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.83003 (0.91948) Boundary_loss: 0.014018 (0.014044) Loss: 0.84404 (0.93353) +2025-09-12,00:16:07 | INFO | Train Epoch: 2 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.89070 (0.91939) Boundary_loss: 0.014020 (0.014044) Loss: 0.90472 (0.93343) +2025-09-12,00:17:14 | INFO | Train Epoch: 2 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.82310 (0.91907) Boundary_loss: 0.014072 (0.014044) Loss: 0.83717 (0.93311) +2025-09-12,00:18:20 | INFO | Train Epoch: 2 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.94861 (0.91917) Boundary_loss: 0.014029 (0.014044) Loss: 0.96264 (0.93321) +2025-09-12,00:19:27 | INFO | Train Epoch: 2 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.84582 (0.91893) Boundary_loss: 0.014021 (0.014044) Loss: 0.85984 (0.93297) +2025-09-12,00:20:33 | INFO | Train Epoch: 2 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.90299 (0.91887) Boundary_loss: 0.014016 (0.014044) Loss: 0.91701 (0.93292) +2025-09-12,00:21:40 | INFO | Train Epoch: 2 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.82604 (0.91857) Boundary_loss: 0.014021 (0.014044) Loss: 0.84006 (0.93261) +2025-09-12,00:22:46 | INFO | Train Epoch: 2 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.85619 (0.91837) Boundary_loss: 0.014013 (0.014043) Loss: 0.87020 (0.93241) +2025-09-12,00:23:53 | INFO | Train Epoch: 2 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.73579 (0.91778) Boundary_loss: 0.014013 (0.014043) Loss: 0.74980 (0.93182) +2025-09-12,00:24:59 | INFO | Train Epoch: 2 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.89399 (0.91770) Boundary_loss: 0.014011 (0.014043) Loss: 0.90800 (0.93174) +2025-09-12,00:26:06 | INFO | Train Epoch: 2 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.92691 (0.91773) Boundary_loss: 0.014002 (0.014043) Loss: 0.94091 (0.93177) +2025-09-12,00:27:12 | INFO | Train Epoch: 2 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.91289 (0.91772) Boundary_loss: 0.014004 (0.014043) Loss: 0.92690 (0.93176) +2025-09-12,00:28:19 | INFO | Train Epoch: 2 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.93740 (0.91778) Boundary_loss: 0.014015 (0.014043) Loss: 0.95142 (0.93182) +2025-09-12,00:29:25 | INFO | Train Epoch: 2 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.88633 (0.91768) Boundary_loss: 0.014014 (0.014043) Loss: 0.90034 (0.93172) +2025-09-12,00:30:31 | INFO | Train Epoch: 2 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.89473 (0.91760) Boundary_loss: 0.014037 (0.014043) Loss: 0.90876 (0.93165) +2025-09-12,00:31:38 | INFO | Train Epoch: 2 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.85805 (0.91742) Boundary_loss: 0.013991 (0.014043) Loss: 0.87204 (0.93146) +2025-09-12,00:32:44 | INFO | Train Epoch: 2 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.92976 (0.91746) Boundary_loss: 0.014018 (0.014043) Loss: 0.94377 (0.93150) +2025-09-12,00:33:51 | INFO | Train Epoch: 2 [16230912/26365952 (62%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.82523 (0.91717) Boundary_loss: 0.014032 (0.014043) Loss: 0.83927 (0.93121) +2025-09-12,00:34:58 | INFO | Train Epoch: 2 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.93458 (0.91722) Boundary_loss: 0.013989 (0.014042) Loss: 0.94857 (0.93126) +2025-09-12,00:36:04 | INFO | Train Epoch: 2 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.77832 (0.91679) Boundary_loss: 0.014001 (0.014042) Loss: 0.79232 (0.93083) +2025-09-12,00:37:11 | INFO | Train Epoch: 2 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.78006 (0.91636) Boundary_loss: 0.014000 (0.014042) Loss: 0.79406 (0.93040) +2025-09-12,00:38:17 | INFO | Train Epoch: 2 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.89008 (0.91628) Boundary_loss: 0.014005 (0.014042) Loss: 0.90408 (0.93032) +2025-09-12,00:39:23 | INFO | Train Epoch: 2 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.0402 (0.91666) Boundary_loss: 0.014018 (0.014042) Loss: 1.0542 (0.93070) +2025-09-12,00:40:30 | INFO | Train Epoch: 2 [16538112/26365952 (63%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.80773 (0.91633) Boundary_loss: 0.013991 (0.014042) Loss: 0.82173 (0.93037) +2025-09-12,00:41:36 | INFO | Train Epoch: 2 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.87258 (0.91619) Boundary_loss: 0.014034 (0.014042) Loss: 0.88662 (0.93023) +2025-09-12,00:42:43 | INFO | Train Epoch: 2 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.80299 (0.91584) Boundary_loss: 0.014027 (0.014042) Loss: 0.81702 (0.92989) +2025-09-12,00:43:49 | INFO | Train Epoch: 2 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.86768 (0.91570) Boundary_loss: 0.014007 (0.014042) Loss: 0.88169 (0.92974) +2025-09-12,00:44:56 | INFO | Train Epoch: 2 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.97356 (0.91587) Boundary_loss: 0.014002 (0.014041) Loss: 0.98756 (0.92991) +2025-09-12,00:46:02 | INFO | Train Epoch: 2 [16794112/26365952 (64%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.88383 (0.91578) Boundary_loss: 0.014028 (0.014041) Loss: 0.89786 (0.92982) +2025-09-12,00:47:09 | INFO | Train Epoch: 2 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.89065 (0.91570) Boundary_loss: 0.014023 (0.014041) Loss: 0.90468 (0.92974) +2025-09-12,00:48:15 | INFO | Train Epoch: 2 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 0.80391 (0.91536) Boundary_loss: 0.014004 (0.014041) Loss: 0.81792 (0.92940) +2025-09-12,00:49:22 | INFO | Train Epoch: 2 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.86335 (0.91521) Boundary_loss: 0.014002 (0.014041) Loss: 0.87735 (0.92925) +2025-09-12,00:50:28 | INFO | Train Epoch: 2 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.79367 (0.91484) Boundary_loss: 0.013998 (0.014041) Loss: 0.80767 (0.92888) +2025-09-12,00:51:35 | INFO | Train Epoch: 2 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.84097 (0.91462) Boundary_loss: 0.013993 (0.014041) Loss: 0.85496 (0.92866) +2025-09-12,00:52:41 | INFO | Train Epoch: 2 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.87983 (0.91452) Boundary_loss: 0.013999 (0.014041) Loss: 0.89383 (0.92856) +2025-09-12,00:53:48 | INFO | Train Epoch: 2 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.78001 (0.91411) Boundary_loss: 0.013988 (0.014041) Loss: 0.79400 (0.92816) +2025-09-12,00:54:54 | INFO | Train Epoch: 2 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.88045 (0.91401) Boundary_loss: 0.013996 (0.014040) Loss: 0.89444 (0.92806) +2025-09-12,00:56:01 | INFO | Train Epoch: 2 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.91620 (0.91402) Boundary_loss: 0.014052 (0.014040) Loss: 0.93026 (0.92806) +2025-09-12,00:57:07 | INFO | Train Epoch: 2 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.78914 (0.91365) Boundary_loss: 0.014011 (0.014040) Loss: 0.80316 (0.92769) +2025-09-12,00:58:14 | INFO | Train Epoch: 2 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.86729 (0.91352) Boundary_loss: 0.014034 (0.014040) Loss: 0.88133 (0.92756) +2025-09-12,00:59:20 | INFO | Train Epoch: 2 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.73229 (0.91299) Boundary_loss: 0.014040 (0.014040) Loss: 0.74633 (0.92703) +2025-09-12,01:00:27 | INFO | Train Epoch: 2 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 1.0794 (0.91347) Boundary_loss: 0.014011 (0.014040) Loss: 1.0934 (0.92751) +2025-09-12,01:01:33 | INFO | Train Epoch: 2 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.80872 (0.91317) Boundary_loss: 0.013994 (0.014040) Loss: 0.82271 (0.92721) +2025-09-12,01:02:40 | INFO | Train Epoch: 2 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.76201 (0.91273) Boundary_loss: 0.014023 (0.014040) Loss: 0.77604 (0.92677) +2025-09-12,01:03:46 | INFO | Train Epoch: 2 [17613312/26365952 (67%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.82073 (0.91246) Boundary_loss: 0.013993 (0.014040) Loss: 0.83472 (0.92650) +2025-09-12,01:04:53 | INFO | Train Epoch: 2 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.92454 (0.91250) Boundary_loss: 0.014007 (0.014040) Loss: 0.93855 (0.92653) +2025-09-12,01:05:59 | INFO | Train Epoch: 2 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.88652 (0.91242) Boundary_loss: 0.013997 (0.014040) Loss: 0.90051 (0.92646) +2025-09-12,01:07:06 | INFO | Train Epoch: 2 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.75164 (0.91196) Boundary_loss: 0.014004 (0.014040) Loss: 0.76564 (0.92600) +2025-09-12,01:08:12 | INFO | Train Epoch: 2 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.80412 (0.91165) Boundary_loss: 0.013993 (0.014040) Loss: 0.81811 (0.92569) +2025-09-12,01:09:19 | INFO | Train Epoch: 2 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.88335 (0.91157) Boundary_loss: 0.014003 (0.014039) Loss: 0.89735 (0.92561) +2025-09-12,01:10:25 | INFO | Train Epoch: 2 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.76816 (0.91116) Boundary_loss: 0.014026 (0.014039) Loss: 0.78218 (0.92520) +2025-09-12,01:11:32 | INFO | Train Epoch: 2 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.75001 (0.91070) Boundary_loss: 0.014006 (0.014039) Loss: 0.76402 (0.92474) +2025-09-12,01:12:38 | INFO | Train Epoch: 2 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.93346 (0.91077) Boundary_loss: 0.014011 (0.014039) Loss: 0.94747 (0.92481) +2025-09-12,01:13:45 | INFO | Train Epoch: 2 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.79479 (0.91044) Boundary_loss: 0.013991 (0.014039) Loss: 0.80878 (0.92448) +2025-09-12,01:14:51 | INFO | Train Epoch: 2 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.74452 (0.90997) Boundary_loss: 0.014027 (0.014039) Loss: 0.75855 (0.92401) +2025-09-12,01:15:58 | INFO | Train Epoch: 2 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.84317 (0.90978) Boundary_loss: 0.014032 (0.014039) Loss: 0.85720 (0.92382) +2025-09-12,01:17:04 | INFO | Train Epoch: 2 [18227712/26365952 (69%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.87243 (0.90968) Boundary_loss: 0.014013 (0.014039) Loss: 0.88644 (0.92372) +2025-09-12,01:18:11 | INFO | Train Epoch: 2 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 0.82140 (0.90943) Boundary_loss: 0.014030 (0.014039) Loss: 0.83543 (0.92347) +2025-09-12,01:19:18 | INFO | Train Epoch: 2 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.81982 (0.90918) Boundary_loss: 0.014010 (0.014039) Loss: 0.83383 (0.92322) +2025-09-12,01:20:24 | INFO | Train Epoch: 2 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.84128 (0.90899) Boundary_loss: 0.013985 (0.014039) Loss: 0.85526 (0.92303) +2025-09-12,01:21:31 | INFO | Train Epoch: 2 [18432512/26365952 (70%)] Avg Boundaries (per batch): 49.182 Boundary Ratio: 0.251 Contrastive_loss: 0.81394 (0.90873) Boundary_loss: 0.014019 (0.014039) Loss: 0.82796 (0.92277) +2025-09-12,01:22:37 | INFO | Train Epoch: 2 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.86881 (0.90862) Boundary_loss: 0.014002 (0.014039) Loss: 0.88281 (0.92266) +2025-09-12,01:23:44 | INFO | Train Epoch: 2 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.91021 (0.90863) Boundary_loss: 0.013976 (0.014038) Loss: 0.92419 (0.92266) +2025-09-12,01:24:50 | INFO | Train Epoch: 2 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.84222 (0.90844) Boundary_loss: 0.014017 (0.014038) Loss: 0.85623 (0.92248) +2025-09-12,01:25:57 | INFO | Train Epoch: 2 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.78040 (0.90809) Boundary_loss: 0.013994 (0.014038) Loss: 0.79439 (0.92213) +2025-09-12,01:27:03 | INFO | Train Epoch: 2 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.68344 (0.90748) Boundary_loss: 0.013995 (0.014038) Loss: 0.69744 (0.92152) +2025-09-12,01:28:10 | INFO | Train Epoch: 2 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.82337 (0.90725) Boundary_loss: 0.014015 (0.014038) Loss: 0.83739 (0.92129) +2025-09-12,01:29:16 | INFO | Train Epoch: 2 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 0.77507 (0.90689) Boundary_loss: 0.014006 (0.014038) Loss: 0.78908 (0.92093) +2025-09-12,01:30:23 | INFO | Train Epoch: 2 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.83898 (0.90671) Boundary_loss: 0.014033 (0.014038) Loss: 0.85302 (0.92074) +2025-09-12,01:31:29 | INFO | Train Epoch: 2 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.391 Boundary Ratio: 0.247 Contrastive_loss: 0.84850 (0.90655) Boundary_loss: 0.014014 (0.014038) Loss: 0.86252 (0.92059) +2025-09-12,01:32:36 | INFO | Train Epoch: 2 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.73645 (0.90609) Boundary_loss: 0.013993 (0.014038) Loss: 0.75045 (0.92013) +2025-09-12,01:33:42 | INFO | Train Epoch: 2 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.89181 (0.90605) Boundary_loss: 0.013982 (0.014038) Loss: 0.90580 (0.92009) +2025-09-12,01:34:49 | INFO | Train Epoch: 2 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.89087 (0.90601) Boundary_loss: 0.013998 (0.014037) Loss: 0.90487 (0.92005) +2025-09-12,01:35:55 | INFO | Train Epoch: 2 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.89992 (0.90599) Boundary_loss: 0.014014 (0.014037) Loss: 0.91393 (0.92003) +2025-09-12,01:37:02 | INFO | Train Epoch: 2 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.88669 (0.90594) Boundary_loss: 0.014000 (0.014037) Loss: 0.90069 (0.91998) +2025-09-12,01:38:09 | INFO | Train Epoch: 2 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.86003 (0.90582) Boundary_loss: 0.013994 (0.014037) Loss: 0.87403 (0.91986) +2025-09-12,01:39:15 | INFO | Train Epoch: 2 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.86157 (0.90570) Boundary_loss: 0.013994 (0.014037) Loss: 0.87557 (0.91974) +2025-09-12,01:40:22 | INFO | Train Epoch: 2 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.84591 (0.90555) Boundary_loss: 0.014044 (0.014037) Loss: 0.85995 (0.91958) +2025-09-12,01:41:28 | INFO | Train Epoch: 2 [19354112/26365952 (73%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.82992 (0.90535) Boundary_loss: 0.014099 (0.014037) Loss: 0.84402 (0.91938) +2025-09-12,01:42:35 | INFO | Train Epoch: 2 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 0.76766 (0.90498) Boundary_loss: 0.014001 (0.014037) Loss: 0.78166 (0.91902) +2025-09-12,01:43:41 | INFO | Train Epoch: 2 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.80751 (0.90473) Boundary_loss: 0.014015 (0.014037) Loss: 0.82153 (0.91876) +2025-09-12,01:44:48 | INFO | Train Epoch: 2 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.75001 (0.90432) Boundary_loss: 0.013998 (0.014037) Loss: 0.76401 (0.91836) +2025-09-12,01:45:54 | INFO | Train Epoch: 2 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.89815 (0.90431) Boundary_loss: 0.013997 (0.014037) Loss: 0.91215 (0.91834) +2025-09-12,01:47:01 | INFO | Train Epoch: 2 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.85477 (0.90418) Boundary_loss: 0.014008 (0.014037) Loss: 0.86878 (0.91821) +2025-09-12,01:48:07 | INFO | Train Epoch: 2 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.90513 (0.90418) Boundary_loss: 0.013998 (0.014037) Loss: 0.91913 (0.91822) +2025-09-12,01:49:14 | INFO | Train Epoch: 2 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.90839 (0.90419) Boundary_loss: 0.013986 (0.014037) Loss: 0.92238 (0.91823) +2025-09-12,01:50:20 | INFO | Train Epoch: 2 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.90917 (0.90420) Boundary_loss: 0.014000 (0.014036) Loss: 0.92317 (0.91824) +2025-09-12,01:51:26 | INFO | Train Epoch: 2 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.244 Boundary Ratio: 0.246 Contrastive_loss: 0.85239 (0.90407) Boundary_loss: 0.014015 (0.014036) Loss: 0.86641 (0.91811) +2025-09-12,01:52:33 | INFO | Train Epoch: 2 [19866112/26365952 (75%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.84748 (0.90392) Boundary_loss: 0.014020 (0.014036) Loss: 0.86150 (0.91796) +2025-09-12,01:53:39 | INFO | Train Epoch: 2 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.81361 (0.90369) Boundary_loss: 0.013985 (0.014036) Loss: 0.82759 (0.91773) +2025-09-12,01:54:46 | INFO | Train Epoch: 2 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 0.86966 (0.90361) Boundary_loss: 0.014052 (0.014036) Loss: 0.88371 (0.91764) +2025-09-12,01:55:53 | INFO | Train Epoch: 2 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.80341 (0.90335) Boundary_loss: 0.013985 (0.014036) Loss: 0.81740 (0.91739) +2025-09-12,01:56:59 | INFO | Train Epoch: 2 [20070912/26365952 (76%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.95904 (0.90349) Boundary_loss: 0.013987 (0.014036) Loss: 0.97302 (0.91753) +2025-09-12,01:58:05 | INFO | Train Epoch: 2 [20122112/26365952 (76%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.84237 (0.90334) Boundary_loss: 0.014003 (0.014036) Loss: 0.85638 (0.91737) +2025-09-12,01:59:12 | INFO | Train Epoch: 2 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.88454 (0.90329) Boundary_loss: 0.013989 (0.014036) Loss: 0.89853 (0.91733) +2025-09-12,02:00:19 | INFO | Train Epoch: 2 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.95453 (0.90342) Boundary_loss: 0.013968 (0.014036) Loss: 0.96850 (0.91745) +2025-09-12,02:01:25 | INFO | Train Epoch: 2 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.80842 (0.90318) Boundary_loss: 0.013993 (0.014036) Loss: 0.82241 (0.91722) +2025-09-12,02:02:31 | INFO | Train Epoch: 2 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.99683 (0.90342) Boundary_loss: 0.013986 (0.014035) Loss: 1.0108 (0.91745) +2025-09-12,02:03:38 | INFO | Train Epoch: 2 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.80421 (0.90317) Boundary_loss: 0.014015 (0.014035) Loss: 0.81822 (0.91720) +2025-09-12,02:04:44 | INFO | Train Epoch: 2 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.90901 (0.90318) Boundary_loss: 0.014012 (0.014035) Loss: 0.92302 (0.91722) +2025-09-12,02:05:51 | INFO | Train Epoch: 2 [20480512/26365952 (78%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.91747 (0.90322) Boundary_loss: 0.014021 (0.014035) Loss: 0.93149 (0.91725) +2025-09-12,02:06:57 | INFO | Train Epoch: 2 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.78594 (0.90292) Boundary_loss: 0.014019 (0.014035) Loss: 0.79996 (0.91696) +2025-09-12,02:08:04 | INFO | Train Epoch: 2 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.82790 (0.90274) Boundary_loss: 0.014002 (0.014035) Loss: 0.84190 (0.91677) +2025-09-12,02:09:10 | INFO | Train Epoch: 2 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.78232 (0.90244) Boundary_loss: 0.013992 (0.014035) Loss: 0.79631 (0.91648) +2025-09-12,02:10:17 | INFO | Train Epoch: 2 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.85145 (0.90231) Boundary_loss: 0.014000 (0.014035) Loss: 0.86545 (0.91635) +2025-09-12,02:11:23 | INFO | Train Epoch: 2 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.84790 (0.90218) Boundary_loss: 0.013997 (0.014035) Loss: 0.86190 (0.91622) +2025-09-12,02:12:30 | INFO | Train Epoch: 2 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.93889 (0.90227) Boundary_loss: 0.013974 (0.014035) Loss: 0.95286 (0.91631) +2025-09-12,02:13:36 | INFO | Train Epoch: 2 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.94017 (0.90236) Boundary_loss: 0.014030 (0.014035) Loss: 0.95420 (0.91640) +2025-09-12,02:14:43 | INFO | Train Epoch: 2 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.76501 (0.90203) Boundary_loss: 0.014027 (0.014035) Loss: 0.77904 (0.91606) +2025-09-12,02:15:49 | INFO | Train Epoch: 2 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.81806 (0.90182) Boundary_loss: 0.013964 (0.014035) Loss: 0.83203 (0.91586) +2025-09-12,02:16:56 | INFO | Train Epoch: 2 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.73843 (0.90143) Boundary_loss: 0.013973 (0.014034) Loss: 0.75240 (0.91546) +2025-09-12,02:18:02 | INFO | Train Epoch: 2 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.81516 (0.90122) Boundary_loss: 0.013982 (0.014034) Loss: 0.82915 (0.91525) +2025-09-12,02:19:09 | INFO | Train Epoch: 2 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.75718 (0.90087) Boundary_loss: 0.014032 (0.014034) Loss: 0.77121 (0.91490) +2025-09-12,02:20:15 | INFO | Train Epoch: 2 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.79384 (0.90061) Boundary_loss: 0.013990 (0.014034) Loss: 0.80783 (0.91464) +2025-09-12,02:21:22 | INFO | Train Epoch: 2 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.76580 (0.90028) Boundary_loss: 0.013978 (0.014034) Loss: 0.77978 (0.91432) +2025-09-12,02:22:28 | INFO | Train Epoch: 2 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.242 Boundary Ratio: 0.246 Contrastive_loss: 0.80506 (0.90006) Boundary_loss: 0.014004 (0.014034) Loss: 0.81907 (0.91409) +2025-09-12,02:23:35 | INFO | Train Epoch: 2 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.80930 (0.89984) Boundary_loss: 0.013995 (0.014034) Loss: 0.82330 (0.91387) +2025-09-12,02:24:41 | INFO | Train Epoch: 2 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 0.80682 (0.89962) Boundary_loss: 0.014017 (0.014034) Loss: 0.82083 (0.91365) +2025-09-12,02:25:48 | INFO | Train Epoch: 2 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.88883 (0.89959) Boundary_loss: 0.014009 (0.014034) Loss: 0.90284 (0.91362) +2025-09-12,02:26:54 | INFO | Train Epoch: 2 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.77909 (0.89930) Boundary_loss: 0.013988 (0.014034) Loss: 0.79308 (0.91334) +2025-09-12,02:28:01 | INFO | Train Epoch: 2 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.75800 (0.89897) Boundary_loss: 0.013975 (0.014033) Loss: 0.77197 (0.91300) +2025-09-12,02:29:07 | INFO | Train Epoch: 2 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.80391 (0.89874) Boundary_loss: 0.014000 (0.014033) Loss: 0.81791 (0.91277) +2025-09-12,02:30:14 | INFO | Train Epoch: 2 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.84359 (0.89861) Boundary_loss: 0.013989 (0.014033) Loss: 0.85758 (0.91264) +2025-09-12,02:31:20 | INFO | Train Epoch: 2 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.71930 (0.89819) Boundary_loss: 0.013993 (0.014033) Loss: 0.73329 (0.91222) +2025-09-12,02:32:27 | INFO | Train Epoch: 2 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.80462 (0.89797) Boundary_loss: 0.013989 (0.014033) Loss: 0.81861 (0.91200) +2025-09-12,02:33:33 | INFO | Train Epoch: 2 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.83713 (0.89783) Boundary_loss: 0.013993 (0.014033) Loss: 0.85112 (0.91186) +2025-09-12,02:34:40 | INFO | Train Epoch: 2 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.92987 (0.89790) Boundary_loss: 0.013985 (0.014033) Loss: 0.94385 (0.91193) +2025-09-12,02:35:46 | INFO | Train Epoch: 2 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.71650 (0.89748) Boundary_loss: 0.013990 (0.014033) Loss: 0.73049 (0.91151) +2025-09-12,02:36:53 | INFO | Train Epoch: 2 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.84735 (0.89736) Boundary_loss: 0.014007 (0.014033) Loss: 0.86136 (0.91139) +2025-09-12,02:38:00 | INFO | Train Epoch: 2 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.71270 (0.89693) Boundary_loss: 0.014010 (0.014033) Loss: 0.72671 (0.91096) +2025-09-12,02:39:06 | INFO | Train Epoch: 2 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.88286 (0.89690) Boundary_loss: 0.013967 (0.014033) Loss: 0.89683 (0.91093) +2025-09-12,02:40:12 | INFO | Train Epoch: 2 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.83812 (0.89676) Boundary_loss: 0.013994 (0.014032) Loss: 0.85211 (0.91079) +2025-09-12,02:41:19 | INFO | Train Epoch: 2 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.83917 (0.89663) Boundary_loss: 0.014010 (0.014032) Loss: 0.85318 (0.91066) +2025-09-12,02:42:26 | INFO | Train Epoch: 2 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.81247 (0.89643) Boundary_loss: 0.014013 (0.014032) Loss: 0.82648 (0.91047) +2025-09-12,02:43:32 | INFO | Train Epoch: 2 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.90761 (0.89646) Boundary_loss: 0.013984 (0.014032) Loss: 0.92160 (0.91049) +2025-09-12,02:44:39 | INFO | Train Epoch: 2 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.74856 (0.89612) Boundary_loss: 0.014020 (0.014032) Loss: 0.76258 (0.91015) +2025-09-12,02:45:45 | INFO | Train Epoch: 2 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.77412 (0.89584) Boundary_loss: 0.013989 (0.014032) Loss: 0.78811 (0.90987) +2025-09-12,02:46:52 | INFO | Train Epoch: 2 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.73839 (0.89548) Boundary_loss: 0.013964 (0.014032) Loss: 0.75235 (0.90951) +2025-09-12,02:47:58 | INFO | Train Epoch: 2 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.80757 (0.89528) Boundary_loss: 0.014000 (0.014032) Loss: 0.82157 (0.90931) +2025-09-12,02:49:05 | INFO | Train Epoch: 2 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.87090 (0.89523) Boundary_loss: 0.013995 (0.014032) Loss: 0.88490 (0.90926) +2025-09-12,02:50:11 | INFO | Train Epoch: 2 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.77143 (0.89495) Boundary_loss: 0.013992 (0.014032) Loss: 0.78542 (0.90898) +2025-09-12,02:51:18 | INFO | Train Epoch: 2 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.84667 (0.89484) Boundary_loss: 0.014016 (0.014032) Loss: 0.86069 (0.90887) +2025-09-12,02:52:25 | INFO | Train Epoch: 2 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.78506 (0.89459) Boundary_loss: 0.013982 (0.014032) Loss: 0.79904 (0.90862) +2025-09-12,02:53:31 | INFO | Train Epoch: 2 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.86665 (0.89453) Boundary_loss: 0.013999 (0.014031) Loss: 0.88065 (0.90856) +2025-09-12,02:54:38 | INFO | Train Epoch: 2 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.82712 (0.89437) Boundary_loss: 0.014022 (0.014031) Loss: 0.84114 (0.90841) +2025-09-12,02:55:44 | INFO | Train Epoch: 2 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.80616 (0.89418) Boundary_loss: 0.014022 (0.014031) Loss: 0.82019 (0.90821) +2025-09-12,02:56:51 | INFO | Train Epoch: 2 [22835712/26365952 (87%)] Avg Boundaries (per batch): 49.109 Boundary Ratio: 0.251 Contrastive_loss: 0.75096 (0.89386) Boundary_loss: 0.014008 (0.014031) Loss: 0.76497 (0.90789) +2025-09-12,02:57:57 | INFO | Train Epoch: 2 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.86047 (0.89378) Boundary_loss: 0.014038 (0.014031) Loss: 0.87451 (0.90781) +2025-09-12,02:59:04 | INFO | Train Epoch: 2 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.81849 (0.89361) Boundary_loss: 0.013981 (0.014031) Loss: 0.83247 (0.90765) +2025-09-12,03:00:10 | INFO | Train Epoch: 2 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.80674 (0.89342) Boundary_loss: 0.013993 (0.014031) Loss: 0.82074 (0.90745) +2025-09-12,03:01:17 | INFO | Train Epoch: 2 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.70675 (0.89301) Boundary_loss: 0.013985 (0.014031) Loss: 0.72074 (0.90704) +2025-09-12,03:02:23 | INFO | Train Epoch: 2 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.81654 (0.89284) Boundary_loss: 0.013970 (0.014031) Loss: 0.83051 (0.90687) +2025-09-12,03:03:30 | INFO | Train Epoch: 2 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.68917 (0.89239) Boundary_loss: 0.013974 (0.014031) Loss: 0.70314 (0.90642) +2025-09-12,03:04:36 | INFO | Train Epoch: 2 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.84532 (0.89228) Boundary_loss: 0.014002 (0.014031) Loss: 0.85932 (0.90632) +2025-09-12,03:05:43 | INFO | Train Epoch: 2 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.78003 (0.89204) Boundary_loss: 0.013978 (0.014031) Loss: 0.79401 (0.90607) +2025-09-12,03:06:49 | INFO | Train Epoch: 2 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.77343 (0.89178) Boundary_loss: 0.013967 (0.014031) Loss: 0.78739 (0.90581) +2025-09-12,03:07:55 | INFO | Train Epoch: 2 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.74059 (0.89145) Boundary_loss: 0.013997 (0.014030) Loss: 0.75459 (0.90548) +2025-09-12,03:09:02 | INFO | Train Epoch: 2 [23398912/26365952 (89%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 0.78792 (0.89122) Boundary_loss: 0.013977 (0.014030) Loss: 0.80190 (0.90525) +2025-09-12,03:10:08 | INFO | Train Epoch: 2 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.80867 (0.89104) Boundary_loss: 0.014009 (0.014030) Loss: 0.82268 (0.90507) +2025-09-12,03:11:15 | INFO | Train Epoch: 2 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.86123 (0.89098) Boundary_loss: 0.013978 (0.014030) Loss: 0.87521 (0.90501) +2025-09-12,03:12:21 | INFO | Train Epoch: 2 [23552512/26365952 (89%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 0.88545 (0.89096) Boundary_loss: 0.013985 (0.014030) Loss: 0.89944 (0.90499) +2025-09-12,03:13:28 | INFO | Train Epoch: 2 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.92398 (0.89104) Boundary_loss: 0.014007 (0.014030) Loss: 0.93799 (0.90507) +2025-09-12,03:14:34 | INFO | Train Epoch: 2 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.82259 (0.89089) Boundary_loss: 0.013973 (0.014030) Loss: 0.83656 (0.90492) +2025-09-12,03:15:41 | INFO | Train Epoch: 2 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.68638 (0.89045) Boundary_loss: 0.013974 (0.014030) Loss: 0.70036 (0.90448) +2025-09-12,03:16:47 | INFO | Train Epoch: 2 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.84700 (0.89035) Boundary_loss: 0.014020 (0.014030) Loss: 0.86102 (0.90438) +2025-09-12,03:17:54 | INFO | Train Epoch: 2 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.73703 (0.89002) Boundary_loss: 0.014021 (0.014030) Loss: 0.75105 (0.90405) +2025-09-12,03:19:00 | INFO | Train Epoch: 2 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.76645 (0.88976) Boundary_loss: 0.013979 (0.014030) Loss: 0.78043 (0.90379) +2025-09-12,03:20:07 | INFO | Train Epoch: 2 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.71814 (0.88939) Boundary_loss: 0.014001 (0.014030) Loss: 0.73214 (0.90342) +2025-09-12,03:21:13 | INFO | Train Epoch: 2 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.76893 (0.88914) Boundary_loss: 0.013971 (0.014029) Loss: 0.78290 (0.90317) +2025-09-12,03:22:20 | INFO | Train Epoch: 2 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.82345 (0.88900) Boundary_loss: 0.013980 (0.014029) Loss: 0.83743 (0.90303) +2025-09-12,03:23:26 | INFO | Train Epoch: 2 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.83412 (0.88888) Boundary_loss: 0.014083 (0.014029) Loss: 0.84820 (0.90291) +2025-09-12,03:24:33 | INFO | Train Epoch: 2 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.70330 (0.88849) Boundary_loss: 0.013981 (0.014029) Loss: 0.71728 (0.90252) +2025-09-12,03:25:39 | INFO | Train Epoch: 2 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.78432 (0.88827) Boundary_loss: 0.014007 (0.014029) Loss: 0.79832 (0.90230) +2025-09-12,03:26:46 | INFO | Train Epoch: 2 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.80009 (0.88808) Boundary_loss: 0.013996 (0.014029) Loss: 0.81409 (0.90211) +2025-09-12,03:27:52 | INFO | Train Epoch: 2 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.67660 (0.88764) Boundary_loss: 0.014014 (0.014029) Loss: 0.69062 (0.90167) +2025-09-12,03:28:58 | INFO | Train Epoch: 2 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.73471 (0.88731) Boundary_loss: 0.013978 (0.014029) Loss: 0.74869 (0.90134) +2025-09-12,03:30:05 | INFO | Train Epoch: 2 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.94167 (0.88743) Boundary_loss: 0.013976 (0.014029) Loss: 0.95564 (0.90146) +2025-09-12,03:31:11 | INFO | Train Epoch: 2 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.79766 (0.88724) Boundary_loss: 0.013985 (0.014029) Loss: 0.81165 (0.90127) +2025-09-12,03:32:18 | INFO | Train Epoch: 2 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.89423 (0.88726) Boundary_loss: 0.013972 (0.014029) Loss: 0.90820 (0.90128) +2025-09-12,03:33:24 | INFO | Train Epoch: 2 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.87546 (0.88723) Boundary_loss: 0.013972 (0.014029) Loss: 0.88943 (0.90126) +2025-09-12,03:34:31 | INFO | Train Epoch: 2 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.81879 (0.88709) Boundary_loss: 0.013978 (0.014029) Loss: 0.83277 (0.90112) +2025-09-12,03:35:37 | INFO | Train Epoch: 2 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.85052 (0.88701) Boundary_loss: 0.013975 (0.014028) Loss: 0.86450 (0.90104) +2025-09-12,03:36:44 | INFO | Train Epoch: 2 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.78479 (0.88680) Boundary_loss: 0.013990 (0.014028) Loss: 0.79879 (0.90083) +2025-09-12,03:37:50 | INFO | Train Epoch: 2 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.71843 (0.88645) Boundary_loss: 0.013987 (0.014028) Loss: 0.73242 (0.90048) +2025-09-12,03:38:56 | INFO | Train Epoch: 2 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.82325 (0.88632) Boundary_loss: 0.013967 (0.014028) Loss: 0.83722 (0.90035) +2025-09-12,03:40:03 | INFO | Train Epoch: 2 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.74594 (0.88603) Boundary_loss: 0.013969 (0.014028) Loss: 0.75991 (0.90006) +2025-09-12,03:41:09 | INFO | Train Epoch: 2 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.81144 (0.88588) Boundary_loss: 0.013974 (0.014028) Loss: 0.82542 (0.89991) +2025-09-12,03:42:16 | INFO | Train Epoch: 2 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.82875 (0.88576) Boundary_loss: 0.013974 (0.014028) Loss: 0.84272 (0.89979) +2025-09-12,03:43:22 | INFO | Train Epoch: 2 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.72181 (0.88543) Boundary_loss: 0.013987 (0.014028) Loss: 0.73579 (0.89946) +2025-09-12,03:44:29 | INFO | Train Epoch: 2 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.93041 (0.88552) Boundary_loss: 0.013992 (0.014028) Loss: 0.94440 (0.89955) +2025-09-12,03:45:35 | INFO | Train Epoch: 2 [25088512/26365952 (95%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.82144 (0.88539) Boundary_loss: 0.013984 (0.014028) Loss: 0.83542 (0.89942) +2025-09-12,03:46:42 | INFO | Train Epoch: 2 [25139712/26365952 (95%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.83613 (0.88529) Boundary_loss: 0.013988 (0.014027) Loss: 0.85012 (0.89932) +2025-09-12,03:47:48 | INFO | Train Epoch: 2 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.83715 (0.88519) Boundary_loss: 0.013978 (0.014027) Loss: 0.85113 (0.89922) +2025-09-12,03:48:55 | INFO | Train Epoch: 2 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.85332 (0.88513) Boundary_loss: 0.013963 (0.014027) Loss: 0.86729 (0.89915) +2025-09-12,03:50:01 | INFO | Train Epoch: 2 [25293312/26365952 (96%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.74831 (0.88485) Boundary_loss: 0.013985 (0.014027) Loss: 0.76230 (0.89888) +2025-09-12,03:51:07 | INFO | Train Epoch: 2 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.80493 (0.88469) Boundary_loss: 0.013964 (0.014027) Loss: 0.81890 (0.89872) +2025-09-12,03:52:14 | INFO | Train Epoch: 2 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.71484 (0.88435) Boundary_loss: 0.013972 (0.014027) Loss: 0.72882 (0.89838) +2025-09-12,03:53:20 | INFO | Train Epoch: 2 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.82657 (0.88423) Boundary_loss: 0.014010 (0.014027) Loss: 0.84058 (0.89826) +2025-09-12,03:54:27 | INFO | Train Epoch: 2 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.81618 (0.88410) Boundary_loss: 0.014001 (0.014027) Loss: 0.83018 (0.89812) +2025-09-12,03:55:33 | INFO | Train Epoch: 2 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.86615 (0.88406) Boundary_loss: 0.013967 (0.014027) Loss: 0.88012 (0.89809) +2025-09-12,03:56:40 | INFO | Train Epoch: 2 [25600512/26365952 (97%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.85544 (0.88400) Boundary_loss: 0.013973 (0.014027) Loss: 0.86941 (0.89803) +2025-09-12,03:57:46 | INFO | Train Epoch: 2 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.68306 (0.88360) Boundary_loss: 0.013970 (0.014027) Loss: 0.69703 (0.89763) +2025-09-12,03:58:53 | INFO | Train Epoch: 2 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.91294 (0.88366) Boundary_loss: 0.013999 (0.014026) Loss: 0.92694 (0.89769) +2025-09-12,03:59:59 | INFO | Train Epoch: 2 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.84028 (0.88357) Boundary_loss: 0.013975 (0.014026) Loss: 0.85425 (0.89760) +2025-09-12,04:01:06 | INFO | Train Epoch: 2 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.70154 (0.88321) Boundary_loss: 0.013991 (0.014026) Loss: 0.71553 (0.89724) +2025-09-12,04:02:12 | INFO | Train Epoch: 2 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.87296 (0.88319) Boundary_loss: 0.013982 (0.014026) Loss: 0.88694 (0.89722) +2025-09-12,04:03:19 | INFO | Train Epoch: 2 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.72706 (0.88289) Boundary_loss: 0.013995 (0.014026) Loss: 0.74106 (0.89691) +2025-09-12,04:04:25 | INFO | Train Epoch: 2 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.71015 (0.88255) Boundary_loss: 0.013983 (0.014026) Loss: 0.72413 (0.89657) +2025-09-12,04:05:32 | INFO | Train Epoch: 2 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.75878 (0.88230) Boundary_loss: 0.013963 (0.014026) Loss: 0.77274 (0.89633) +2025-09-12,04:06:38 | INFO | Train Epoch: 2 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.74069 (0.88203) Boundary_loss: 0.013999 (0.014026) Loss: 0.75468 (0.89605) +2025-09-12,04:07:45 | INFO | Train Epoch: 2 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.81999 (0.88190) Boundary_loss: 0.013973 (0.014026) Loss: 0.83396 (0.89593) +2025-09-12,04:08:51 | INFO | Train Epoch: 2 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.79463 (0.88173) Boundary_loss: 0.013970 (0.014026) Loss: 0.80860 (0.89576) +2025-09-12,04:09:58 | INFO | Train Epoch: 2 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.61163 (0.88121) Boundary_loss: 0.013967 (0.014026) Loss: 0.62560 (0.89523) +2025-09-12,04:11:04 | INFO | Train Epoch: 2 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.77487 (0.88100) Boundary_loss: 0.013971 (0.014025) Loss: 0.78884 (0.89503) +2025-09-12,04:12:11 | INFO | Train Epoch: 2 [26317312/26365952 (100%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.81184 (0.88087) Boundary_loss: 0.013979 (0.014025) Loss: 0.82582 (0.89489) +2025-09-12,04:13:14 | INFO | Train Epoch: 2 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.85479 (0.88081) Boundary_loss: 0.013985 (0.014025) Loss: 0.86878 (0.89484) +2025-09-12,04:13:14 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,04:13:14 | INFO | [Epoch 2] Average Step Time: 0.669s | Average GPU Memory: 31.2 GB +2025-09-12,04:13:14 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,04:13:14 | INFO | Starting zero-shot imagenet. +2025-09-12,04:13:14 | INFO | Building zero-shot classifier +2025-09-12,04:13:23 | INFO | Using classifier +2025-09-12,04:14:12 | INFO | Finished zero-shot imagenet. +2025-09-12,04:14:12 | INFO | Eval Epoch: 3 imagenet-zeroshot-val-top1: 0.2130 imagenet-zeroshot-val-top5: 0.4345 +2025-09-12,04:14:13 | INFO | Start epoch 3 +2025-09-12,04:14:15 | INFO | Train Epoch: 3 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.68919 (0.68919) Boundary_loss: 0.013989 (0.013989) Loss: 0.70318 (0.70318) +2025-09-12,04:15:22 | INFO | Train Epoch: 3 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.76218 (0.72569) Boundary_loss: 0.013965 (0.013977) Loss: 0.77615 (0.73966) +2025-09-12,04:16:28 | INFO | Train Epoch: 3 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.65361 (0.70166) Boundary_loss: 0.013971 (0.013975) Loss: 0.66758 (0.71564) +2025-09-12,04:17:35 | INFO | Train Epoch: 3 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.85224 (0.73931) Boundary_loss: 0.013991 (0.013979) Loss: 0.86623 (0.75328) +2025-09-12,04:18:41 | INFO | Train Epoch: 3 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.69215 (0.72987) Boundary_loss: 0.014005 (0.013984) Loss: 0.70615 (0.74386) +2025-09-12,04:19:47 | INFO | Train Epoch: 3 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.61743 (0.71113) Boundary_loss: 0.013986 (0.013984) Loss: 0.63142 (0.72512) +2025-09-12,04:20:54 | INFO | Train Epoch: 3 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.85267 (0.73135) Boundary_loss: 0.013999 (0.013986) Loss: 0.86667 (0.74534) +2025-09-12,04:22:00 | INFO | Train Epoch: 3 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.74893 (0.73355) Boundary_loss: 0.013973 (0.013985) Loss: 0.76291 (0.74754) +2025-09-12,04:23:06 | INFO | Train Epoch: 3 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.77166 (0.73778) Boundary_loss: 0.013971 (0.013983) Loss: 0.78563 (0.75177) +2025-09-12,04:24:13 | INFO | Train Epoch: 3 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.82639 (0.74665) Boundary_loss: 0.013966 (0.013981) Loss: 0.84036 (0.76063) +2025-09-12,04:25:19 | INFO | Train Epoch: 3 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.332 Boundary Ratio: 0.247 Contrastive_loss: 0.81779 (0.75311) Boundary_loss: 0.014017 (0.013985) Loss: 0.83181 (0.76710) +2025-09-12,04:26:25 | INFO | Train Epoch: 3 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.70755 (0.74932) Boundary_loss: 0.013979 (0.013984) Loss: 0.72153 (0.76330) +2025-09-12,04:27:32 | INFO | Train Epoch: 3 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 49.436 Boundary Ratio: 0.252 Contrastive_loss: 0.79577 (0.75289) Boundary_loss: 0.014082 (0.013992) Loss: 0.80985 (0.76688) +2025-09-12,04:28:38 | INFO | Train Epoch: 3 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.71472 (0.75016) Boundary_loss: 0.013968 (0.013990) Loss: 0.72868 (0.76415) +2025-09-12,04:29:44 | INFO | Train Epoch: 3 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.78004 (0.75215) Boundary_loss: 0.013988 (0.013990) Loss: 0.79403 (0.76614) +2025-09-12,04:30:51 | INFO | Train Epoch: 3 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.79209 (0.75465) Boundary_loss: 0.013971 (0.013989) Loss: 0.80606 (0.76864) +2025-09-12,04:31:57 | INFO | Train Epoch: 3 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.482 Boundary Ratio: 0.247 Contrastive_loss: 0.87395 (0.76167) Boundary_loss: 0.014008 (0.013990) Loss: 0.88796 (0.77566) +2025-09-12,04:33:03 | INFO | Train Epoch: 3 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.74843 (0.76093) Boundary_loss: 0.013994 (0.013990) Loss: 0.76243 (0.77492) +2025-09-12,04:34:10 | INFO | Train Epoch: 3 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.80364 (0.76318) Boundary_loss: 0.013982 (0.013990) Loss: 0.81762 (0.77717) +2025-09-12,04:35:16 | INFO | Train Epoch: 3 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.61403 (0.75572) Boundary_loss: 0.013956 (0.013988) Loss: 0.62798 (0.76971) +2025-09-12,04:36:22 | INFO | Train Epoch: 3 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.83813 (0.75965) Boundary_loss: 0.013993 (0.013988) Loss: 0.85212 (0.77364) +2025-09-12,04:37:29 | INFO | Train Epoch: 3 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.72429 (0.75804) Boundary_loss: 0.013967 (0.013987) Loss: 0.73826 (0.77203) +2025-09-12,04:38:35 | INFO | Train Epoch: 3 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.77634 (0.75884) Boundary_loss: 0.014001 (0.013988) Loss: 0.79034 (0.77282) +2025-09-12,04:39:41 | INFO | Train Epoch: 3 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 0.70487 (0.75659) Boundary_loss: 0.013980 (0.013987) Loss: 0.71885 (0.77057) +2025-09-12,04:40:48 | INFO | Train Epoch: 3 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.73188 (0.75560) Boundary_loss: 0.013969 (0.013987) Loss: 0.74584 (0.76959) +2025-09-12,04:41:54 | INFO | Train Epoch: 3 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.83786 (0.75876) Boundary_loss: 0.013980 (0.013986) Loss: 0.85184 (0.77275) +2025-09-12,04:43:00 | INFO | Train Epoch: 3 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.78692 (0.75981) Boundary_loss: 0.013986 (0.013986) Loss: 0.80090 (0.77379) +2025-09-12,04:44:07 | INFO | Train Epoch: 3 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.66393 (0.75638) Boundary_loss: 0.013956 (0.013985) Loss: 0.67789 (0.77037) +2025-09-12,04:45:13 | INFO | Train Epoch: 3 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.70533 (0.75462) Boundary_loss: 0.013972 (0.013985) Loss: 0.71930 (0.76861) +2025-09-12,04:46:19 | INFO | Train Epoch: 3 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.66297 (0.75157) Boundary_loss: 0.013991 (0.013985) Loss: 0.67696 (0.76555) +2025-09-12,04:47:26 | INFO | Train Epoch: 3 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.65350 (0.74840) Boundary_loss: 0.013976 (0.013985) Loss: 0.66748 (0.76239) +2025-09-12,04:48:32 | INFO | Train Epoch: 3 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.80230 (0.75009) Boundary_loss: 0.013975 (0.013984) Loss: 0.81628 (0.76407) +2025-09-12,04:49:38 | INFO | Train Epoch: 3 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.66944 (0.74764) Boundary_loss: 0.013972 (0.013984) Loss: 0.68341 (0.76163) +2025-09-12,04:50:45 | INFO | Train Epoch: 3 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.80755 (0.74940) Boundary_loss: 0.013991 (0.013984) Loss: 0.82154 (0.76339) +2025-09-12,04:51:51 | INFO | Train Epoch: 3 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.70929 (0.74826) Boundary_loss: 0.013946 (0.013983) Loss: 0.72323 (0.76224) +2025-09-12,04:52:57 | INFO | Train Epoch: 3 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.70129 (0.74695) Boundary_loss: 0.013963 (0.013983) Loss: 0.71526 (0.76094) +2025-09-12,04:54:04 | INFO | Train Epoch: 3 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.66652 (0.74478) Boundary_loss: 0.014040 (0.013984) Loss: 0.68056 (0.75876) +2025-09-12,04:55:10 | INFO | Train Epoch: 3 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.71421 (0.74398) Boundary_loss: 0.013959 (0.013984) Loss: 0.72817 (0.75796) +2025-09-12,04:56:16 | INFO | Train Epoch: 3 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.75066 (0.74415) Boundary_loss: 0.013951 (0.013983) Loss: 0.76461 (0.75813) +2025-09-12,04:57:23 | INFO | Train Epoch: 3 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.67609 (0.74245) Boundary_loss: 0.013993 (0.013983) Loss: 0.69008 (0.75643) +2025-09-12,04:58:29 | INFO | Train Epoch: 3 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.67095 (0.74070) Boundary_loss: 0.013962 (0.013982) Loss: 0.68492 (0.75468) +2025-09-12,04:59:35 | INFO | Train Epoch: 3 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.76144 (0.74120) Boundary_loss: 0.013957 (0.013982) Loss: 0.77540 (0.75518) +2025-09-12,05:00:42 | INFO | Train Epoch: 3 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.85621 (0.74387) Boundary_loss: 0.013964 (0.013981) Loss: 0.87017 (0.75785) +2025-09-12,05:01:48 | INFO | Train Epoch: 3 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.71719 (0.74326) Boundary_loss: 0.013961 (0.013981) Loss: 0.73115 (0.75724) +2025-09-12,05:02:54 | INFO | Train Epoch: 3 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.72950 (0.74296) Boundary_loss: 0.013953 (0.013980) Loss: 0.74346 (0.75694) +2025-09-12,05:04:01 | INFO | Train Epoch: 3 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.60281 (0.73991) Boundary_loss: 0.013946 (0.013980) Loss: 0.61675 (0.75389) +2025-09-12,05:05:07 | INFO | Train Epoch: 3 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.68968 (0.73884) Boundary_loss: 0.013981 (0.013980) Loss: 0.70366 (0.75282) +2025-09-12,05:06:13 | INFO | Train Epoch: 3 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.72356 (0.73852) Boundary_loss: 0.014023 (0.013980) Loss: 0.73759 (0.75250) +2025-09-12,05:07:20 | INFO | Train Epoch: 3 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 0.70819 (0.73791) Boundary_loss: 0.013974 (0.013980) Loss: 0.72216 (0.75189) +2025-09-12,05:08:26 | INFO | Train Epoch: 3 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.81269 (0.73940) Boundary_loss: 0.013965 (0.013980) Loss: 0.82666 (0.75338) +2025-09-12,05:09:32 | INFO | Train Epoch: 3 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.66098 (0.73786) Boundary_loss: 0.013955 (0.013980) Loss: 0.67493 (0.75184) +2025-09-12,05:10:39 | INFO | Train Epoch: 3 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.84924 (0.74000) Boundary_loss: 0.013955 (0.013979) Loss: 0.86319 (0.75398) +2025-09-12,05:11:45 | INFO | Train Epoch: 3 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.69227 (0.73910) Boundary_loss: 0.013961 (0.013979) Loss: 0.70623 (0.75308) +2025-09-12,05:12:52 | INFO | Train Epoch: 3 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 0.70428 (0.73846) Boundary_loss: 0.013989 (0.013979) Loss: 0.71827 (0.75244) +2025-09-12,05:13:58 | INFO | Train Epoch: 3 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.64286 (0.73672) Boundary_loss: 0.013959 (0.013979) Loss: 0.65682 (0.75070) +2025-09-12,05:15:04 | INFO | Train Epoch: 3 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.74133 (0.73680) Boundary_loss: 0.014001 (0.013979) Loss: 0.75533 (0.75078) +2025-09-12,05:16:11 | INFO | Train Epoch: 3 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.71478 (0.73642) Boundary_loss: 0.013968 (0.013979) Loss: 0.72875 (0.75040) +2025-09-12,05:17:17 | INFO | Train Epoch: 3 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 0.85461 (0.73845) Boundary_loss: 0.014000 (0.013979) Loss: 0.86861 (0.75243) +2025-09-12,05:18:23 | INFO | Train Epoch: 3 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.62338 (0.73650) Boundary_loss: 0.013972 (0.013979) Loss: 0.63735 (0.75048) +2025-09-12,05:19:30 | INFO | Train Epoch: 3 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.75946 (0.73689) Boundary_loss: 0.013974 (0.013979) Loss: 0.77343 (0.75087) +2025-09-12,05:20:36 | INFO | Train Epoch: 3 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.69460 (0.73619) Boundary_loss: 0.013975 (0.013979) Loss: 0.70858 (0.75017) +2025-09-12,05:21:42 | INFO | Train Epoch: 3 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.68458 (0.73536) Boundary_loss: 0.013973 (0.013979) Loss: 0.69855 (0.74934) +2025-09-12,05:22:49 | INFO | Train Epoch: 3 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.73505 (0.73536) Boundary_loss: 0.013953 (0.013978) Loss: 0.74901 (0.74933) +2025-09-12,05:23:55 | INFO | Train Epoch: 3 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.75182 (0.73561) Boundary_loss: 0.013964 (0.013978) Loss: 0.76579 (0.74959) +2025-09-12,05:25:01 | INFO | Train Epoch: 3 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.64145 (0.73417) Boundary_loss: 0.013952 (0.013978) Loss: 0.65540 (0.74814) +2025-09-12,05:26:08 | INFO | Train Epoch: 3 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.64116 (0.73276) Boundary_loss: 0.013967 (0.013978) Loss: 0.65513 (0.74673) +2025-09-12,05:27:14 | INFO | Train Epoch: 3 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.69919 (0.73225) Boundary_loss: 0.013950 (0.013977) Loss: 0.71314 (0.74623) +2025-09-12,05:28:21 | INFO | Train Epoch: 3 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.66722 (0.73130) Boundary_loss: 0.013971 (0.013977) Loss: 0.68119 (0.74528) +2025-09-12,05:29:27 | INFO | Train Epoch: 3 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.73896 (0.73141) Boundary_loss: 0.013969 (0.013977) Loss: 0.75293 (0.74539) +2025-09-12,05:30:33 | INFO | Train Epoch: 3 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.71443 (0.73117) Boundary_loss: 0.013960 (0.013977) Loss: 0.72839 (0.74514) +2025-09-12,05:31:40 | INFO | Train Epoch: 3 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 0.60532 (0.72939) Boundary_loss: 0.013988 (0.013977) Loss: 0.61931 (0.74337) +2025-09-12,05:32:46 | INFO | Train Epoch: 3 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.66831 (0.72855) Boundary_loss: 0.013996 (0.013977) Loss: 0.68230 (0.74252) +2025-09-12,05:33:52 | INFO | Train Epoch: 3 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.69014 (0.72802) Boundary_loss: 0.013963 (0.013977) Loss: 0.70411 (0.74200) +2025-09-12,05:34:59 | INFO | Train Epoch: 3 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.70659 (0.72773) Boundary_loss: 0.013966 (0.013977) Loss: 0.72056 (0.74171) +2025-09-12,05:36:05 | INFO | Train Epoch: 3 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.81255 (0.72886) Boundary_loss: 0.013963 (0.013977) Loss: 0.82651 (0.74284) +2025-09-12,05:37:12 | INFO | Train Epoch: 3 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.76510 (0.72934) Boundary_loss: 0.013964 (0.013976) Loss: 0.77907 (0.74331) +2025-09-12,05:38:18 | INFO | Train Epoch: 3 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.71000 (0.72909) Boundary_loss: 0.013980 (0.013976) Loss: 0.72398 (0.74306) +2025-09-12,05:39:24 | INFO | Train Epoch: 3 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.72059 (0.72898) Boundary_loss: 0.013963 (0.013976) Loss: 0.73455 (0.74295) +2025-09-12,05:40:31 | INFO | Train Epoch: 3 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.66417 (0.72816) Boundary_loss: 0.013955 (0.013976) Loss: 0.67813 (0.74213) +2025-09-12,05:41:37 | INFO | Train Epoch: 3 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.69712 (0.72777) Boundary_loss: 0.013989 (0.013976) Loss: 0.71111 (0.74175) +2025-09-12,05:42:43 | INFO | Train Epoch: 3 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.62622 (0.72652) Boundary_loss: 0.013987 (0.013976) Loss: 0.64020 (0.74049) +2025-09-12,05:43:50 | INFO | Train Epoch: 3 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.65257 (0.72561) Boundary_loss: 0.013963 (0.013976) Loss: 0.66653 (0.73959) +2025-09-12,05:44:56 | INFO | Train Epoch: 3 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.74595 (0.72586) Boundary_loss: 0.013986 (0.013976) Loss: 0.75994 (0.73984) +2025-09-12,05:46:03 | INFO | Train Epoch: 3 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.74481 (0.72608) Boundary_loss: 0.013977 (0.013976) Loss: 0.75879 (0.74006) +2025-09-12,05:47:09 | INFO | Train Epoch: 3 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.72350 (0.72605) Boundary_loss: 0.013992 (0.013977) Loss: 0.73749 (0.74003) +2025-09-12,05:48:16 | INFO | Train Epoch: 3 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.61433 (0.72476) Boundary_loss: 0.013968 (0.013976) Loss: 0.62829 (0.73873) +2025-09-12,05:49:22 | INFO | Train Epoch: 3 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.62157 (0.72357) Boundary_loss: 0.013979 (0.013976) Loss: 0.63555 (0.73755) +2025-09-12,05:50:28 | INFO | Train Epoch: 3 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.61670 (0.72235) Boundary_loss: 0.013965 (0.013976) Loss: 0.63066 (0.73633) +2025-09-12,05:51:35 | INFO | Train Epoch: 3 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.65873 (0.72164) Boundary_loss: 0.013959 (0.013976) Loss: 0.67268 (0.73562) +2025-09-12,05:52:41 | INFO | Train Epoch: 3 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.71833 (0.72160) Boundary_loss: 0.013964 (0.013976) Loss: 0.73230 (0.73558) +2025-09-12,05:53:48 | INFO | Train Epoch: 3 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.74424 (0.72185) Boundary_loss: 0.013961 (0.013976) Loss: 0.75820 (0.73583) +2025-09-12,05:54:54 | INFO | Train Epoch: 3 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.67694 (0.72136) Boundary_loss: 0.013960 (0.013976) Loss: 0.69090 (0.73534) +2025-09-12,05:56:00 | INFO | Train Epoch: 3 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.83887 (0.72263) Boundary_loss: 0.014001 (0.013976) Loss: 0.85287 (0.73660) +2025-09-12,05:57:07 | INFO | Train Epoch: 3 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.76455 (0.72307) Boundary_loss: 0.013970 (0.013976) Loss: 0.77852 (0.73705) +2025-09-12,05:58:13 | INFO | Train Epoch: 3 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.65761 (0.72238) Boundary_loss: 0.013963 (0.013976) Loss: 0.67158 (0.73636) +2025-09-12,05:59:20 | INFO | Train Epoch: 3 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.71807 (0.72234) Boundary_loss: 0.013958 (0.013976) Loss: 0.73203 (0.73631) +2025-09-12,06:00:26 | INFO | Train Epoch: 3 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.68590 (0.72196) Boundary_loss: 0.013963 (0.013975) Loss: 0.69986 (0.73594) +2025-09-12,06:01:33 | INFO | Train Epoch: 3 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.77901 (0.72255) Boundary_loss: 0.013979 (0.013975) Loss: 0.79299 (0.73652) +2025-09-12,06:02:39 | INFO | Train Epoch: 3 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.54040 (0.72071) Boundary_loss: 0.013970 (0.013975) Loss: 0.55437 (0.73468) +2025-09-12,06:03:45 | INFO | Train Epoch: 3 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.63296 (0.71983) Boundary_loss: 0.013954 (0.013975) Loss: 0.64692 (0.73380) +2025-09-12,06:04:52 | INFO | Train Epoch: 3 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.68667 (0.71950) Boundary_loss: 0.013967 (0.013975) Loss: 0.70064 (0.73348) +2025-09-12,06:05:58 | INFO | Train Epoch: 3 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.66135 (0.71893) Boundary_loss: 0.013952 (0.013975) Loss: 0.67530 (0.73290) +2025-09-12,06:07:05 | INFO | Train Epoch: 3 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.63984 (0.71816) Boundary_loss: 0.013950 (0.013975) Loss: 0.65379 (0.73214) +2025-09-12,06:08:11 | INFO | Train Epoch: 3 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.68310 (0.71783) Boundary_loss: 0.013947 (0.013974) Loss: 0.69705 (0.73180) +2025-09-12,06:09:17 | INFO | Train Epoch: 3 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.342 Boundary Ratio: 0.247 Contrastive_loss: 0.60648 (0.71676) Boundary_loss: 0.013986 (0.013974) Loss: 0.62046 (0.73074) +2025-09-12,06:10:24 | INFO | Train Epoch: 3 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.72070 (0.71680) Boundary_loss: 0.013949 (0.013974) Loss: 0.73465 (0.73078) +2025-09-12,06:11:31 | INFO | Train Epoch: 3 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.72196 (0.71685) Boundary_loss: 0.013998 (0.013974) Loss: 0.73595 (0.73082) +2025-09-12,06:12:37 | INFO | Train Epoch: 3 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.71848 (0.71686) Boundary_loss: 0.013972 (0.013974) Loss: 0.73245 (0.73084) +2025-09-12,06:13:44 | INFO | Train Epoch: 3 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.68703 (0.71659) Boundary_loss: 0.013958 (0.013974) Loss: 0.70098 (0.73057) +2025-09-12,06:14:50 | INFO | Train Epoch: 3 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.66910 (0.71616) Boundary_loss: 0.013982 (0.013974) Loss: 0.68308 (0.73013) +2025-09-12,06:15:57 | INFO | Train Epoch: 3 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.66904 (0.71573) Boundary_loss: 0.013956 (0.013974) Loss: 0.68300 (0.72971) +2025-09-12,06:17:03 | INFO | Train Epoch: 3 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.57351 (0.71447) Boundary_loss: 0.013960 (0.013974) Loss: 0.58747 (0.72844) +2025-09-12,06:18:10 | INFO | Train Epoch: 3 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.70281 (0.71436) Boundary_loss: 0.013947 (0.013974) Loss: 0.71676 (0.72834) +2025-09-12,06:19:16 | INFO | Train Epoch: 3 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.82108 (0.71530) Boundary_loss: 0.013983 (0.013974) Loss: 0.83506 (0.72927) +2025-09-12,06:20:22 | INFO | Train Epoch: 3 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.63083 (0.71456) Boundary_loss: 0.013972 (0.013974) Loss: 0.64480 (0.72854) +2025-09-12,06:21:29 | INFO | Train Epoch: 3 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.68681 (0.71432) Boundary_loss: 0.013960 (0.013974) Loss: 0.70077 (0.72830) +2025-09-12,06:22:35 | INFO | Train Epoch: 3 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.74579 (0.71459) Boundary_loss: 0.013947 (0.013974) Loss: 0.75973 (0.72857) +2025-09-12,06:23:42 | INFO | Train Epoch: 3 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.75648 (0.71495) Boundary_loss: 0.013976 (0.013974) Loss: 0.77046 (0.72892) +2025-09-12,06:24:48 | INFO | Train Epoch: 3 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.61881 (0.71414) Boundary_loss: 0.013991 (0.013974) Loss: 0.63280 (0.72811) +2025-09-12,06:25:55 | INFO | Train Epoch: 3 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.70790 (0.71409) Boundary_loss: 0.013981 (0.013974) Loss: 0.72188 (0.72806) +2025-09-12,06:27:01 | INFO | Train Epoch: 3 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.66938 (0.71372) Boundary_loss: 0.013945 (0.013974) Loss: 0.68332 (0.72769) +2025-09-12,06:28:07 | INFO | Train Epoch: 3 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.72994 (0.71385) Boundary_loss: 0.013973 (0.013974) Loss: 0.74391 (0.72783) +2025-09-12,06:29:14 | INFO | Train Epoch: 3 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.88995 (0.71528) Boundary_loss: 0.013961 (0.013973) Loss: 0.90391 (0.72926) +2025-09-12,06:30:20 | INFO | Train Epoch: 3 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.68158 (0.71501) Boundary_loss: 0.013953 (0.013973) Loss: 0.69553 (0.72898) +2025-09-12,06:31:27 | INFO | Train Epoch: 3 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.66715 (0.71463) Boundary_loss: 0.013954 (0.013973) Loss: 0.68110 (0.72860) +2025-09-12,06:32:33 | INFO | Train Epoch: 3 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.75418 (0.71494) Boundary_loss: 0.014027 (0.013974) Loss: 0.76820 (0.72892) +2025-09-12,06:33:40 | INFO | Train Epoch: 3 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.71402 (0.71494) Boundary_loss: 0.013950 (0.013973) Loss: 0.72797 (0.72891) +2025-09-12,06:34:46 | INFO | Train Epoch: 3 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.69834 (0.71481) Boundary_loss: 0.013978 (0.013973) Loss: 0.71232 (0.72878) +2025-09-12,06:35:53 | INFO | Train Epoch: 3 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.74401 (0.71503) Boundary_loss: 0.013970 (0.013973) Loss: 0.75798 (0.72901) +2025-09-12,06:36:59 | INFO | Train Epoch: 3 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.70291 (0.71494) Boundary_loss: 0.013959 (0.013973) Loss: 0.71687 (0.72891) +2025-09-12,06:38:05 | INFO | Train Epoch: 3 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.68852 (0.71474) Boundary_loss: 0.013947 (0.013973) Loss: 0.70247 (0.72871) +2025-09-12,06:39:12 | INFO | Train Epoch: 3 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.78509 (0.71527) Boundary_loss: 0.013947 (0.013973) Loss: 0.79904 (0.72924) +2025-09-12,06:40:18 | INFO | Train Epoch: 3 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.79132 (0.71584) Boundary_loss: 0.013975 (0.013973) Loss: 0.80529 (0.72981) +2025-09-12,06:41:25 | INFO | Train Epoch: 3 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.62052 (0.71513) Boundary_loss: 0.013956 (0.013973) Loss: 0.63448 (0.72910) +2025-09-12,06:42:31 | INFO | Train Epoch: 3 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.62136 (0.71444) Boundary_loss: 0.013950 (0.013973) Loss: 0.63531 (0.72841) +2025-09-12,06:43:37 | INFO | Train Epoch: 3 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.85234 (0.71545) Boundary_loss: 0.013956 (0.013972) Loss: 0.86630 (0.72942) +2025-09-12,06:44:44 | INFO | Train Epoch: 3 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.77802 (0.71591) Boundary_loss: 0.013949 (0.013972) Loss: 0.79197 (0.72988) +2025-09-12,06:45:50 | INFO | Train Epoch: 3 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.457 Boundary Ratio: 0.247 Contrastive_loss: 0.60166 (0.71508) Boundary_loss: 0.013967 (0.013972) Loss: 0.61563 (0.72905) +2025-09-12,06:46:57 | INFO | Train Epoch: 3 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.74729 (0.71531) Boundary_loss: 0.013941 (0.013972) Loss: 0.76124 (0.72928) +2025-09-12,06:48:03 | INFO | Train Epoch: 3 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.69462 (0.71516) Boundary_loss: 0.013954 (0.013972) Loss: 0.70857 (0.72913) +2025-09-12,06:49:10 | INFO | Train Epoch: 3 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.74720 (0.71539) Boundary_loss: 0.013959 (0.013972) Loss: 0.76115 (0.72936) +2025-09-12,06:50:16 | INFO | Train Epoch: 3 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.61807 (0.71470) Boundary_loss: 0.013941 (0.013972) Loss: 0.63201 (0.72868) +2025-09-12,06:51:22 | INFO | Train Epoch: 3 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.74202 (0.71490) Boundary_loss: 0.013962 (0.013971) Loss: 0.75598 (0.72887) +2025-09-12,06:52:29 | INFO | Train Epoch: 3 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.59583 (0.71407) Boundary_loss: 0.013950 (0.013971) Loss: 0.60979 (0.72804) +2025-09-12,06:53:35 | INFO | Train Epoch: 3 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.75043 (0.71432) Boundary_loss: 0.013945 (0.013971) Loss: 0.76438 (0.72829) +2025-09-12,06:54:42 | INFO | Train Epoch: 3 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.79709 (0.71489) Boundary_loss: 0.013979 (0.013971) Loss: 0.81107 (0.72886) +2025-09-12,06:55:48 | INFO | Train Epoch: 3 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.72871 (0.71498) Boundary_loss: 0.013953 (0.013971) Loss: 0.74267 (0.72895) +2025-09-12,06:56:54 | INFO | Train Epoch: 3 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.68349 (0.71477) Boundary_loss: 0.013965 (0.013971) Loss: 0.69745 (0.72874) +2025-09-12,06:58:01 | INFO | Train Epoch: 3 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.80230 (0.71536) Boundary_loss: 0.013979 (0.013971) Loss: 0.81628 (0.72933) +2025-09-12,06:59:07 | INFO | Train Epoch: 3 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.62649 (0.71476) Boundary_loss: 0.013958 (0.013971) Loss: 0.64045 (0.72873) +2025-09-12,07:00:14 | INFO | Train Epoch: 3 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.70021 (0.71467) Boundary_loss: 0.013967 (0.013971) Loss: 0.71418 (0.72864) +2025-09-12,07:01:20 | INFO | Train Epoch: 3 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.53751 (0.71350) Boundary_loss: 0.013964 (0.013971) Loss: 0.55147 (0.72747) +2025-09-12,07:02:27 | INFO | Train Epoch: 3 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.73654 (0.71365) Boundary_loss: 0.013951 (0.013971) Loss: 0.75049 (0.72762) +2025-09-12,07:03:33 | INFO | Train Epoch: 3 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.64910 (0.71323) Boundary_loss: 0.013944 (0.013971) Loss: 0.66305 (0.72720) +2025-09-12,07:04:39 | INFO | Train Epoch: 3 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.79428 (0.71376) Boundary_loss: 0.013980 (0.013971) Loss: 0.80826 (0.72773) +2025-09-12,07:05:46 | INFO | Train Epoch: 3 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.66018 (0.71341) Boundary_loss: 0.013945 (0.013971) Loss: 0.67413 (0.72738) +2025-09-12,07:06:52 | INFO | Train Epoch: 3 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.66071 (0.71308) Boundary_loss: 0.013961 (0.013970) Loss: 0.67467 (0.72705) +2025-09-12,07:07:59 | INFO | Train Epoch: 3 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.60864 (0.71242) Boundary_loss: 0.013940 (0.013970) Loss: 0.62258 (0.72639) +2025-09-12,07:09:05 | INFO | Train Epoch: 3 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.56512 (0.71149) Boundary_loss: 0.013954 (0.013970) Loss: 0.57907 (0.72546) +2025-09-12,07:10:12 | INFO | Train Epoch: 3 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.61712 (0.71090) Boundary_loss: 0.013985 (0.013970) Loss: 0.63111 (0.72487) +2025-09-12,07:11:18 | INFO | Train Epoch: 3 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.71763 (0.71094) Boundary_loss: 0.013953 (0.013970) Loss: 0.73158 (0.72491) +2025-09-12,07:12:24 | INFO | Train Epoch: 3 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.55807 (0.71000) Boundary_loss: 0.013951 (0.013970) Loss: 0.57202 (0.72397) +2025-09-12,07:13:31 | INFO | Train Epoch: 3 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.69102 (0.70988) Boundary_loss: 0.013952 (0.013970) Loss: 0.70498 (0.72385) +2025-09-12,07:14:37 | INFO | Train Epoch: 3 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.69731 (0.70980) Boundary_loss: 0.013956 (0.013970) Loss: 0.71127 (0.72377) +2025-09-12,07:15:44 | INFO | Train Epoch: 3 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.77750 (0.71021) Boundary_loss: 0.013971 (0.013970) Loss: 0.79147 (0.72418) +2025-09-12,07:16:50 | INFO | Train Epoch: 3 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.65151 (0.70986) Boundary_loss: 0.013956 (0.013970) Loss: 0.66546 (0.72383) +2025-09-12,07:17:56 | INFO | Train Epoch: 3 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.60052 (0.70921) Boundary_loss: 0.013969 (0.013970) Loss: 0.61449 (0.72318) +2025-09-12,07:19:03 | INFO | Train Epoch: 3 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.76436 (0.70953) Boundary_loss: 0.013952 (0.013970) Loss: 0.77832 (0.72350) +2025-09-12,07:20:09 | INFO | Train Epoch: 3 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.74379 (0.70974) Boundary_loss: 0.013972 (0.013970) Loss: 0.75776 (0.72371) +2025-09-12,07:21:16 | INFO | Train Epoch: 3 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.63954 (0.70932) Boundary_loss: 0.013948 (0.013970) Loss: 0.65348 (0.72329) +2025-09-12,07:22:22 | INFO | Train Epoch: 3 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.62492 (0.70883) Boundary_loss: 0.013953 (0.013969) Loss: 0.63888 (0.72280) +2025-09-12,07:23:29 | INFO | Train Epoch: 3 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.79738 (0.70935) Boundary_loss: 0.013947 (0.013969) Loss: 0.81133 (0.72331) +2025-09-12,07:24:35 | INFO | Train Epoch: 3 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.67276 (0.70913) Boundary_loss: 0.013942 (0.013969) Loss: 0.68671 (0.72310) +2025-09-12,07:25:41 | INFO | Train Epoch: 3 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.81054 (0.70972) Boundary_loss: 0.013969 (0.013969) Loss: 0.82451 (0.72369) +2025-09-12,07:26:48 | INFO | Train Epoch: 3 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.64982 (0.70937) Boundary_loss: 0.013946 (0.013969) Loss: 0.66376 (0.72334) +2025-09-12,07:27:54 | INFO | Train Epoch: 3 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.55200 (0.70848) Boundary_loss: 0.013962 (0.013969) Loss: 0.56596 (0.72245) +2025-09-12,07:29:01 | INFO | Train Epoch: 3 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.60069 (0.70787) Boundary_loss: 0.013972 (0.013969) Loss: 0.61466 (0.72184) +2025-09-12,07:30:07 | INFO | Train Epoch: 3 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.77654 (0.70826) Boundary_loss: 0.013973 (0.013969) Loss: 0.79051 (0.72223) +2025-09-12,07:31:13 | INFO | Train Epoch: 3 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.221 Boundary Ratio: 0.246 Contrastive_loss: 0.64397 (0.70790) Boundary_loss: 0.013989 (0.013969) Loss: 0.65796 (0.72187) +2025-09-12,07:32:20 | INFO | Train Epoch: 3 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.59782 (0.70729) Boundary_loss: 0.013944 (0.013969) Loss: 0.61176 (0.72126) +2025-09-12,07:33:26 | INFO | Train Epoch: 3 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.61427 (0.70677) Boundary_loss: 0.013949 (0.013969) Loss: 0.62822 (0.72074) +2025-09-12,07:34:33 | INFO | Train Epoch: 3 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.78585 (0.70721) Boundary_loss: 0.013987 (0.013969) Loss: 0.79984 (0.72118) +2025-09-12,07:35:39 | INFO | Train Epoch: 3 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.56426 (0.70643) Boundary_loss: 0.013953 (0.013969) Loss: 0.57821 (0.72039) +2025-09-12,07:36:45 | INFO | Train Epoch: 3 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.67777 (0.70627) Boundary_loss: 0.013973 (0.013969) Loss: 0.69174 (0.72024) +2025-09-12,07:37:52 | INFO | Train Epoch: 3 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.67884 (0.70612) Boundary_loss: 0.013957 (0.013969) Loss: 0.69279 (0.72009) +2025-09-12,07:38:58 | INFO | Train Epoch: 3 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.61399 (0.70563) Boundary_loss: 0.013955 (0.013969) Loss: 0.62794 (0.71960) +2025-09-12,07:40:05 | INFO | Train Epoch: 3 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.60246 (0.70507) Boundary_loss: 0.013965 (0.013969) Loss: 0.61642 (0.71904) +2025-09-12,07:41:11 | INFO | Train Epoch: 3 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.64083 (0.70473) Boundary_loss: 0.013960 (0.013969) Loss: 0.65479 (0.71870) +2025-09-12,07:42:17 | INFO | Train Epoch: 3 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.64769 (0.70443) Boundary_loss: 0.013950 (0.013969) Loss: 0.66164 (0.71840) +2025-09-12,07:43:24 | INFO | Train Epoch: 3 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.58123 (0.70378) Boundary_loss: 0.013943 (0.013968) Loss: 0.59518 (0.71775) +2025-09-12,07:44:30 | INFO | Train Epoch: 3 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.58471 (0.70316) Boundary_loss: 0.013965 (0.013968) Loss: 0.59867 (0.71713) +2025-09-12,07:45:36 | INFO | Train Epoch: 3 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.67863 (0.70303) Boundary_loss: 0.013964 (0.013968) Loss: 0.69259 (0.71700) +2025-09-12,07:46:43 | INFO | Train Epoch: 3 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.60672 (0.70253) Boundary_loss: 0.013934 (0.013968) Loss: 0.62065 (0.71650) +2025-09-12,07:47:49 | INFO | Train Epoch: 3 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.71713 (0.70261) Boundary_loss: 0.013940 (0.013968) Loss: 0.73107 (0.71658) +2025-09-12,07:48:55 | INFO | Train Epoch: 3 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.68342 (0.70251) Boundary_loss: 0.013943 (0.013968) Loss: 0.69736 (0.71648) +2025-09-12,07:50:02 | INFO | Train Epoch: 3 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.66529 (0.70232) Boundary_loss: 0.013947 (0.013968) Loss: 0.67924 (0.71629) +2025-09-12,07:51:08 | INFO | Train Epoch: 3 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.79481 (0.70279) Boundary_loss: 0.013960 (0.013968) Loss: 0.80877 (0.71676) +2025-09-12,07:52:15 | INFO | Train Epoch: 3 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.84547 (0.70351) Boundary_loss: 0.013954 (0.013968) Loss: 0.85943 (0.71748) +2025-09-12,07:53:21 | INFO | Train Epoch: 3 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.62895 (0.70313) Boundary_loss: 0.013938 (0.013968) Loss: 0.64289 (0.71710) +2025-09-12,07:54:27 | INFO | Train Epoch: 3 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.72666 (0.70325) Boundary_loss: 0.013957 (0.013968) Loss: 0.74062 (0.71722) +2025-09-12,07:55:34 | INFO | Train Epoch: 3 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.62086 (0.70284) Boundary_loss: 0.013951 (0.013967) Loss: 0.63481 (0.71681) +2025-09-12,07:56:40 | INFO | Train Epoch: 3 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.69009 (0.70278) Boundary_loss: 0.013943 (0.013967) Loss: 0.70404 (0.71675) +2025-09-12,07:57:47 | INFO | Train Epoch: 3 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.63169 (0.70243) Boundary_loss: 0.013951 (0.013967) Loss: 0.64564 (0.71640) +2025-09-12,07:58:53 | INFO | Train Epoch: 3 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.68537 (0.70235) Boundary_loss: 0.013952 (0.013967) Loss: 0.69932 (0.71631) +2025-09-12,07:59:59 | INFO | Train Epoch: 3 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.55735 (0.70164) Boundary_loss: 0.013968 (0.013967) Loss: 0.57131 (0.71561) +2025-09-12,08:01:06 | INFO | Train Epoch: 3 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.72107 (0.70173) Boundary_loss: 0.013941 (0.013967) Loss: 0.73501 (0.71570) +2025-09-12,08:02:12 | INFO | Train Epoch: 3 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.68517 (0.70165) Boundary_loss: 0.013966 (0.013967) Loss: 0.69914 (0.71562) +2025-09-12,08:03:18 | INFO | Train Epoch: 3 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.68509 (0.70157) Boundary_loss: 0.013950 (0.013967) Loss: 0.69904 (0.71554) +2025-09-12,08:04:25 | INFO | Train Epoch: 3 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.66368 (0.70139) Boundary_loss: 0.013943 (0.013967) Loss: 0.67762 (0.71536) +2025-09-12,08:05:31 | INFO | Train Epoch: 3 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.73145 (0.70153) Boundary_loss: 0.013945 (0.013967) Loss: 0.74540 (0.71550) +2025-09-12,08:06:38 | INFO | Train Epoch: 3 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.73271 (0.70168) Boundary_loss: 0.013965 (0.013967) Loss: 0.74667 (0.71565) +2025-09-12,08:07:44 | INFO | Train Epoch: 3 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.78683 (0.70208) Boundary_loss: 0.013939 (0.013967) Loss: 0.80077 (0.71605) +2025-09-12,08:08:50 | INFO | Train Epoch: 3 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.60151 (0.70161) Boundary_loss: 0.013968 (0.013967) Loss: 0.61548 (0.71558) +2025-09-12,08:09:57 | INFO | Train Epoch: 3 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.63967 (0.70132) Boundary_loss: 0.013948 (0.013967) Loss: 0.65362 (0.71529) +2025-09-12,08:11:03 | INFO | Train Epoch: 3 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.72410 (0.70143) Boundary_loss: 0.013957 (0.013967) Loss: 0.73805 (0.71539) +2025-09-12,08:12:09 | INFO | Train Epoch: 3 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.68056 (0.70133) Boundary_loss: 0.013949 (0.013966) Loss: 0.69451 (0.71530) +2025-09-12,08:13:16 | INFO | Train Epoch: 3 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.56745 (0.70071) Boundary_loss: 0.013960 (0.013966) Loss: 0.58141 (0.71468) +2025-09-12,08:14:22 | INFO | Train Epoch: 3 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.69404 (0.70068) Boundary_loss: 0.013954 (0.013966) Loss: 0.70799 (0.71465) +2025-09-12,08:15:28 | INFO | Train Epoch: 3 [11162112/26365952 (42%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.66591 (0.70053) Boundary_loss: 0.013959 (0.013966) Loss: 0.67987 (0.71449) +2025-09-12,08:16:35 | INFO | Train Epoch: 3 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.80581 (0.70100) Boundary_loss: 0.013981 (0.013966) Loss: 0.81979 (0.71497) +2025-09-12,08:17:41 | INFO | Train Epoch: 3 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.65858 (0.70081) Boundary_loss: 0.013966 (0.013966) Loss: 0.67255 (0.71478) +2025-09-12,08:18:47 | INFO | Train Epoch: 3 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.67170 (0.70068) Boundary_loss: 0.013962 (0.013966) Loss: 0.68566 (0.71465) +2025-09-12,08:19:54 | INFO | Train Epoch: 3 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.70432 (0.70070) Boundary_loss: 0.014003 (0.013967) Loss: 0.71833 (0.71466) +2025-09-12,08:21:00 | INFO | Train Epoch: 3 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.68834 (0.70064) Boundary_loss: 0.013979 (0.013967) Loss: 0.70232 (0.71461) +2025-09-12,08:22:06 | INFO | Train Epoch: 3 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.63378 (0.70034) Boundary_loss: 0.013942 (0.013966) Loss: 0.64772 (0.71431) +2025-09-12,08:23:13 | INFO | Train Epoch: 3 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.74392 (0.70054) Boundary_loss: 0.013949 (0.013966) Loss: 0.75787 (0.71450) +2025-09-12,08:24:19 | INFO | Train Epoch: 3 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.66105 (0.70036) Boundary_loss: 0.013956 (0.013966) Loss: 0.67501 (0.71433) +2025-09-12,08:25:25 | INFO | Train Epoch: 3 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.71296 (0.70042) Boundary_loss: 0.013943 (0.013966) Loss: 0.72690 (0.71439) +2025-09-12,08:26:32 | INFO | Train Epoch: 3 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.67535 (0.70031) Boundary_loss: 0.013951 (0.013966) Loss: 0.68930 (0.71428) +2025-09-12,08:27:38 | INFO | Train Epoch: 3 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.65849 (0.70013) Boundary_loss: 0.013960 (0.013966) Loss: 0.67245 (0.71409) +2025-09-12,08:28:44 | INFO | Train Epoch: 3 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.65164 (0.69992) Boundary_loss: 0.013946 (0.013966) Loss: 0.66559 (0.71388) +2025-09-12,08:29:51 | INFO | Train Epoch: 3 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.62459 (0.69959) Boundary_loss: 0.013946 (0.013966) Loss: 0.63854 (0.71356) +2025-09-12,08:30:57 | INFO | Train Epoch: 3 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.64075 (0.69934) Boundary_loss: 0.013953 (0.013966) Loss: 0.65470 (0.71331) +2025-09-12,08:32:03 | INFO | Train Epoch: 3 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.73413 (0.69949) Boundary_loss: 0.013960 (0.013966) Loss: 0.74809 (0.71346) +2025-09-12,08:33:10 | INFO | Train Epoch: 3 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.69767 (0.69948) Boundary_loss: 0.013950 (0.013966) Loss: 0.71162 (0.71345) +2025-09-12,08:34:16 | INFO | Train Epoch: 3 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.60377 (0.69908) Boundary_loss: 0.013971 (0.013966) Loss: 0.61774 (0.71304) +2025-09-12,08:35:22 | INFO | Train Epoch: 3 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.65134 (0.69887) Boundary_loss: 0.013969 (0.013966) Loss: 0.66530 (0.71284) +2025-09-12,08:36:29 | INFO | Train Epoch: 3 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.67930 (0.69879) Boundary_loss: 0.013959 (0.013966) Loss: 0.69325 (0.71276) +2025-09-12,08:37:35 | INFO | Train Epoch: 3 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.59248 (0.69835) Boundary_loss: 0.013958 (0.013966) Loss: 0.60644 (0.71231) +2025-09-12,08:38:41 | INFO | Train Epoch: 3 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.69881 (0.69835) Boundary_loss: 0.013939 (0.013966) Loss: 0.71275 (0.71232) +2025-09-12,08:39:48 | INFO | Train Epoch: 3 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.67189 (0.69824) Boundary_loss: 0.013957 (0.013966) Loss: 0.68585 (0.71221) +2025-09-12,08:40:54 | INFO | Train Epoch: 3 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59451 (0.69781) Boundary_loss: 0.013948 (0.013966) Loss: 0.60845 (0.71178) +2025-09-12,08:42:00 | INFO | Train Epoch: 3 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.75107 (0.69803) Boundary_loss: 0.013947 (0.013965) Loss: 0.76501 (0.71200) +2025-09-12,08:43:07 | INFO | Train Epoch: 3 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.64991 (0.69783) Boundary_loss: 0.013960 (0.013965) Loss: 0.66387 (0.71180) +2025-09-12,08:44:13 | INFO | Train Epoch: 3 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.68481 (0.69778) Boundary_loss: 0.013946 (0.013965) Loss: 0.69875 (0.71175) +2025-09-12,08:45:19 | INFO | Train Epoch: 3 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.53811 (0.69713) Boundary_loss: 0.013945 (0.013965) Loss: 0.55206 (0.71110) +2025-09-12,08:46:26 | INFO | Train Epoch: 3 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.56589 (0.69660) Boundary_loss: 0.013952 (0.013965) Loss: 0.57984 (0.71056) +2025-09-12,08:47:32 | INFO | Train Epoch: 3 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.63271 (0.69634) Boundary_loss: 0.013965 (0.013965) Loss: 0.64667 (0.71031) +2025-09-12,08:48:38 | INFO | Train Epoch: 3 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.66045 (0.69620) Boundary_loss: 0.013977 (0.013965) Loss: 0.67443 (0.71016) +2025-09-12,08:49:44 | INFO | Train Epoch: 3 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.73530 (0.69635) Boundary_loss: 0.013953 (0.013965) Loss: 0.74926 (0.71032) +2025-09-12,08:50:51 | INFO | Train Epoch: 3 [12800512/26365952 (49%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.70968 (0.69641) Boundary_loss: 0.013950 (0.013965) Loss: 0.72364 (0.71037) +2025-09-12,08:51:57 | INFO | Train Epoch: 3 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.69816 (0.69641) Boundary_loss: 0.013958 (0.013965) Loss: 0.71212 (0.71038) +2025-09-12,08:53:03 | INFO | Train Epoch: 3 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.73191 (0.69655) Boundary_loss: 0.013944 (0.013965) Loss: 0.74586 (0.71052) +2025-09-12,08:54:10 | INFO | Train Epoch: 3 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.54746 (0.69597) Boundary_loss: 0.013961 (0.013965) Loss: 0.56142 (0.70993) +2025-09-12,08:55:16 | INFO | Train Epoch: 3 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.69276 (0.69595) Boundary_loss: 0.013948 (0.013965) Loss: 0.70671 (0.70992) +2025-09-12,08:56:22 | INFO | Train Epoch: 3 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.66685 (0.69584) Boundary_loss: 0.013957 (0.013965) Loss: 0.68081 (0.70981) +2025-09-12,08:57:29 | INFO | Train Epoch: 3 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.59689 (0.69546) Boundary_loss: 0.013955 (0.013965) Loss: 0.61084 (0.70942) +2025-09-12,08:58:35 | INFO | Train Epoch: 3 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.64189 (0.69525) Boundary_loss: 0.013954 (0.013965) Loss: 0.65585 (0.70921) +2025-09-12,08:59:41 | INFO | Train Epoch: 3 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.68427 (0.69521) Boundary_loss: 0.013941 (0.013965) Loss: 0.69821 (0.70917) +2025-09-12,09:00:48 | INFO | Train Epoch: 3 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.61126 (0.69488) Boundary_loss: 0.013946 (0.013965) Loss: 0.62520 (0.70885) +2025-09-12,09:01:54 | INFO | Train Epoch: 3 [13312512/26365952 (50%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.65547 (0.69473) Boundary_loss: 0.013950 (0.013965) Loss: 0.66942 (0.70870) +2025-09-12,09:03:00 | INFO | Train Epoch: 3 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.61744 (0.69444) Boundary_loss: 0.013943 (0.013965) Loss: 0.63139 (0.70840) +2025-09-12,09:04:07 | INFO | Train Epoch: 3 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.78913 (0.69480) Boundary_loss: 0.013952 (0.013965) Loss: 0.80308 (0.70876) +2025-09-12,09:05:13 | INFO | Train Epoch: 3 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.66648 (0.69469) Boundary_loss: 0.013973 (0.013965) Loss: 0.68045 (0.70865) +2025-09-12,09:06:19 | INFO | Train Epoch: 3 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.62900 (0.69444) Boundary_loss: 0.014000 (0.013965) Loss: 0.64300 (0.70841) +2025-09-12,09:07:26 | INFO | Train Epoch: 3 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.60377 (0.69410) Boundary_loss: 0.013954 (0.013965) Loss: 0.61772 (0.70807) +2025-09-12,09:08:32 | INFO | Train Epoch: 3 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.61221 (0.69379) Boundary_loss: 0.013960 (0.013965) Loss: 0.62617 (0.70776) +2025-09-12,09:09:38 | INFO | Train Epoch: 3 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.70255 (0.69383) Boundary_loss: 0.013956 (0.013965) Loss: 0.71650 (0.70779) +2025-09-12,09:10:45 | INFO | Train Epoch: 3 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.68202 (0.69378) Boundary_loss: 0.013959 (0.013965) Loss: 0.69598 (0.70775) +2025-09-12,09:11:51 | INFO | Train Epoch: 3 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.65640 (0.69364) Boundary_loss: 0.013949 (0.013965) Loss: 0.67035 (0.70761) +2025-09-12,09:12:57 | INFO | Train Epoch: 3 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.67884 (0.69359) Boundary_loss: 0.013954 (0.013964) Loss: 0.69279 (0.70755) +2025-09-12,09:14:04 | INFO | Train Epoch: 3 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.64935 (0.69343) Boundary_loss: 0.013948 (0.013964) Loss: 0.66329 (0.70739) +2025-09-12,09:15:10 | INFO | Train Epoch: 3 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.66211 (0.69331) Boundary_loss: 0.013956 (0.013964) Loss: 0.67607 (0.70728) +2025-09-12,09:16:16 | INFO | Train Epoch: 3 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.76080 (0.69356) Boundary_loss: 0.013957 (0.013964) Loss: 0.77476 (0.70752) +2025-09-12,09:17:23 | INFO | Train Epoch: 3 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.58941 (0.69318) Boundary_loss: 0.013942 (0.013964) Loss: 0.60335 (0.70714) +2025-09-12,09:18:29 | INFO | Train Epoch: 3 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.60414 (0.69286) Boundary_loss: 0.013954 (0.013964) Loss: 0.61809 (0.70682) +2025-09-12,09:19:35 | INFO | Train Epoch: 3 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.69801 (0.69288) Boundary_loss: 0.013950 (0.013964) Loss: 0.71196 (0.70684) +2025-09-12,09:20:42 | INFO | Train Epoch: 3 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.57872 (0.69247) Boundary_loss: 0.013952 (0.013964) Loss: 0.59267 (0.70643) +2025-09-12,09:21:48 | INFO | Train Epoch: 3 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 0.57709 (0.69205) Boundary_loss: 0.013965 (0.013964) Loss: 0.59105 (0.70602) +2025-09-12,09:22:54 | INFO | Train Epoch: 3 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.69724 (0.69207) Boundary_loss: 0.013958 (0.013964) Loss: 0.71119 (0.70603) +2025-09-12,09:24:01 | INFO | Train Epoch: 3 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.64058 (0.69189) Boundary_loss: 0.013941 (0.013964) Loss: 0.65452 (0.70585) +2025-09-12,09:25:07 | INFO | Train Epoch: 3 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.73807 (0.69205) Boundary_loss: 0.013953 (0.013964) Loss: 0.75202 (0.70602) +2025-09-12,09:26:13 | INFO | Train Epoch: 3 [14438912/26365952 (55%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.78353 (0.69237) Boundary_loss: 0.013943 (0.013964) Loss: 0.79747 (0.70634) +2025-09-12,09:27:20 | INFO | Train Epoch: 3 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.65378 (0.69224) Boundary_loss: 0.013944 (0.013964) Loss: 0.66772 (0.70620) +2025-09-12,09:28:26 | INFO | Train Epoch: 3 [14541312/26365952 (55%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.83130 (0.69273) Boundary_loss: 0.013984 (0.013964) Loss: 0.84528 (0.70669) +2025-09-12,09:29:32 | INFO | Train Epoch: 3 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.74586 (0.69291) Boundary_loss: 0.013946 (0.013964) Loss: 0.75980 (0.70688) +2025-09-12,09:30:39 | INFO | Train Epoch: 3 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.55382 (0.69243) Boundary_loss: 0.013937 (0.013964) Loss: 0.56776 (0.70639) +2025-09-12,09:31:45 | INFO | Train Epoch: 3 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.58138 (0.69204) Boundary_loss: 0.013952 (0.013964) Loss: 0.59533 (0.70601) +2025-09-12,09:32:51 | INFO | Train Epoch: 3 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.67047 (0.69197) Boundary_loss: 0.013950 (0.013964) Loss: 0.68442 (0.70593) +2025-09-12,09:33:58 | INFO | Train Epoch: 3 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.64414 (0.69180) Boundary_loss: 0.013973 (0.013964) Loss: 0.65812 (0.70577) +2025-09-12,09:35:04 | INFO | Train Epoch: 3 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.76824 (0.69207) Boundary_loss: 0.014007 (0.013964) Loss: 0.78225 (0.70603) +2025-09-12,09:36:10 | INFO | Train Epoch: 3 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.61440 (0.69180) Boundary_loss: 0.013953 (0.013964) Loss: 0.62835 (0.70576) +2025-09-12,09:37:17 | INFO | Train Epoch: 3 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.62516 (0.69157) Boundary_loss: 0.013941 (0.013964) Loss: 0.63910 (0.70554) +2025-09-12,09:38:23 | INFO | Train Epoch: 3 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.56285 (0.69113) Boundary_loss: 0.013976 (0.013964) Loss: 0.57683 (0.70510) +2025-09-12,09:39:30 | INFO | Train Epoch: 3 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.77535 (0.69142) Boundary_loss: 0.013940 (0.013964) Loss: 0.78929 (0.70538) +2025-09-12,09:40:36 | INFO | Train Epoch: 3 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.69650 (0.69144) Boundary_loss: 0.013948 (0.013964) Loss: 0.71045 (0.70540) +2025-09-12,09:41:42 | INFO | Train Epoch: 3 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.64074 (0.69127) Boundary_loss: 0.013964 (0.013964) Loss: 0.65470 (0.70523) +2025-09-12,09:42:49 | INFO | Train Epoch: 3 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.60178 (0.69097) Boundary_loss: 0.014002 (0.013964) Loss: 0.61578 (0.70493) +2025-09-12,09:43:55 | INFO | Train Epoch: 3 [15258112/26365952 (58%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.68443 (0.69094) Boundary_loss: 0.013949 (0.013964) Loss: 0.69838 (0.70491) +2025-09-12,09:45:01 | INFO | Train Epoch: 3 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.74989 (0.69114) Boundary_loss: 0.013950 (0.013964) Loss: 0.76384 (0.70510) +2025-09-12,09:46:08 | INFO | Train Epoch: 3 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.58113 (0.69077) Boundary_loss: 0.013952 (0.013964) Loss: 0.59508 (0.70474) +2025-09-12,09:47:14 | INFO | Train Epoch: 3 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.68578 (0.69076) Boundary_loss: 0.013957 (0.013964) Loss: 0.69973 (0.70472) +2025-09-12,09:48:20 | INFO | Train Epoch: 3 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.75008 (0.69095) Boundary_loss: 0.013941 (0.013964) Loss: 0.76402 (0.70492) +2025-09-12,09:49:27 | INFO | Train Epoch: 3 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.65476 (0.69083) Boundary_loss: 0.013973 (0.013964) Loss: 0.66874 (0.70480) +2025-09-12,09:50:33 | INFO | Train Epoch: 3 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.60359 (0.69055) Boundary_loss: 0.013945 (0.013964) Loss: 0.61753 (0.70451) +2025-09-12,09:51:39 | INFO | Train Epoch: 3 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.68358 (0.69053) Boundary_loss: 0.013950 (0.013963) Loss: 0.69753 (0.70449) +2025-09-12,09:52:45 | INFO | Train Epoch: 3 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.67242 (0.69047) Boundary_loss: 0.013934 (0.013963) Loss: 0.68636 (0.70443) +2025-09-12,09:53:52 | INFO | Train Epoch: 3 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.69952 (0.69050) Boundary_loss: 0.013952 (0.013963) Loss: 0.71347 (0.70446) +2025-09-12,09:54:58 | INFO | Train Epoch: 3 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.54015 (0.69001) Boundary_loss: 0.013955 (0.013963) Loss: 0.55411 (0.70397) +2025-09-12,09:56:04 | INFO | Train Epoch: 3 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.66075 (0.68992) Boundary_loss: 0.013952 (0.013963) Loss: 0.67470 (0.70388) +2025-09-12,09:57:11 | INFO | Train Epoch: 3 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.49747 (0.68930) Boundary_loss: 0.013930 (0.013963) Loss: 0.51140 (0.70326) +2025-09-12,09:58:17 | INFO | Train Epoch: 3 [15923712/26365952 (60%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.72134 (0.68940) Boundary_loss: 0.013956 (0.013963) Loss: 0.73529 (0.70336) +2025-09-12,09:59:23 | INFO | Train Epoch: 3 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.62867 (0.68921) Boundary_loss: 0.013941 (0.013963) Loss: 0.64261 (0.70317) +2025-09-12,10:00:30 | INFO | Train Epoch: 3 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.68374 (0.68919) Boundary_loss: 0.013925 (0.013963) Loss: 0.69767 (0.70315) +2025-09-12,10:01:36 | INFO | Train Epoch: 3 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.57661 (0.68883) Boundary_loss: 0.013950 (0.013963) Loss: 0.59056 (0.70279) +2025-09-12,10:02:42 | INFO | Train Epoch: 3 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.70801 (0.68889) Boundary_loss: 0.013951 (0.013963) Loss: 0.72196 (0.70285) +2025-09-12,10:03:48 | INFO | Train Epoch: 3 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.64681 (0.68876) Boundary_loss: 0.013933 (0.013963) Loss: 0.66075 (0.70272) +2025-09-12,10:04:55 | INFO | Train Epoch: 3 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.57394 (0.68840) Boundary_loss: 0.013969 (0.013963) Loss: 0.58791 (0.70236) +2025-09-12,10:06:01 | INFO | Train Epoch: 3 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.65966 (0.68831) Boundary_loss: 0.013958 (0.013963) Loss: 0.67362 (0.70227) +2025-09-12,10:07:07 | INFO | Train Epoch: 3 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.64400 (0.68817) Boundary_loss: 0.013965 (0.013963) Loss: 0.65796 (0.70213) +2025-09-12,10:08:14 | INFO | Train Epoch: 3 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.68042 (0.68814) Boundary_loss: 0.013947 (0.013963) Loss: 0.69436 (0.70211) +2025-09-12,10:09:20 | INFO | Train Epoch: 3 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.60965 (0.68790) Boundary_loss: 0.013957 (0.013963) Loss: 0.62360 (0.70186) +2025-09-12,10:10:26 | INFO | Train Epoch: 3 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.62231 (0.68770) Boundary_loss: 0.013952 (0.013963) Loss: 0.63626 (0.70166) +2025-09-12,10:11:33 | INFO | Train Epoch: 3 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.65941 (0.68761) Boundary_loss: 0.013946 (0.013963) Loss: 0.67335 (0.70157) +2025-09-12,10:12:39 | INFO | Train Epoch: 3 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.72127 (0.68771) Boundary_loss: 0.013946 (0.013963) Loss: 0.73522 (0.70168) +2025-09-12,10:13:45 | INFO | Train Epoch: 3 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.70458 (0.68777) Boundary_loss: 0.013956 (0.013963) Loss: 0.71853 (0.70173) +2025-09-12,10:14:52 | INFO | Train Epoch: 3 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.62466 (0.68757) Boundary_loss: 0.013946 (0.013963) Loss: 0.63860 (0.70154) +2025-09-12,10:15:58 | INFO | Train Epoch: 3 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.61418 (0.68735) Boundary_loss: 0.013954 (0.013963) Loss: 0.62814 (0.70131) +2025-09-12,10:17:04 | INFO | Train Epoch: 3 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.71459 (0.68743) Boundary_loss: 0.013937 (0.013962) Loss: 0.72853 (0.70139) +2025-09-12,10:18:10 | INFO | Train Epoch: 3 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.58060 (0.68711) Boundary_loss: 0.013973 (0.013962) Loss: 0.59457 (0.70107) +2025-09-12,10:19:17 | INFO | Train Epoch: 3 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.64403 (0.68698) Boundary_loss: 0.013941 (0.013962) Loss: 0.65797 (0.70094) +2025-09-12,10:20:23 | INFO | Train Epoch: 3 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.51294 (0.68645) Boundary_loss: 0.013951 (0.013962) Loss: 0.52689 (0.70042) +2025-09-12,10:21:29 | INFO | Train Epoch: 3 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.63042 (0.68629) Boundary_loss: 0.013937 (0.013962) Loss: 0.64436 (0.70025) +2025-09-12,10:22:36 | INFO | Train Epoch: 3 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.63046 (0.68612) Boundary_loss: 0.013952 (0.013962) Loss: 0.64441 (0.70008) +2025-09-12,10:23:42 | INFO | Train Epoch: 3 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.67276 (0.68608) Boundary_loss: 0.013949 (0.013962) Loss: 0.68670 (0.70004) +2025-09-12,10:24:48 | INFO | Train Epoch: 3 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.69000 (0.68609) Boundary_loss: 0.013943 (0.013962) Loss: 0.70394 (0.70005) +2025-09-12,10:25:55 | INFO | Train Epoch: 3 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.70351 (0.68614) Boundary_loss: 0.013941 (0.013962) Loss: 0.71745 (0.70010) +2025-09-12,10:27:01 | INFO | Train Epoch: 3 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.73097 (0.68627) Boundary_loss: 0.013941 (0.013962) Loss: 0.74492 (0.70024) +2025-09-12,10:28:07 | INFO | Train Epoch: 3 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.71625 (0.68636) Boundary_loss: 0.013947 (0.013962) Loss: 0.73020 (0.70032) +2025-09-12,10:29:14 | INFO | Train Epoch: 3 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.63382 (0.68621) Boundary_loss: 0.013938 (0.013962) Loss: 0.64775 (0.70017) +2025-09-12,10:30:20 | INFO | Train Epoch: 3 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.69993 (0.68625) Boundary_loss: 0.013954 (0.013962) Loss: 0.71389 (0.70021) +2025-09-12,10:31:26 | INFO | Train Epoch: 3 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.60028 (0.68600) Boundary_loss: 0.013938 (0.013962) Loss: 0.61422 (0.69996) +2025-09-12,10:32:33 | INFO | Train Epoch: 3 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.72208 (0.68610) Boundary_loss: 0.013937 (0.013962) Loss: 0.73601 (0.70006) +2025-09-12,10:33:39 | INFO | Train Epoch: 3 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.63482 (0.68595) Boundary_loss: 0.013934 (0.013962) Loss: 0.64875 (0.69992) +2025-09-12,10:34:45 | INFO | Train Epoch: 3 [17613312/26365952 (67%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.60280 (0.68571) Boundary_loss: 0.013956 (0.013962) Loss: 0.61675 (0.69967) +2025-09-12,10:35:52 | INFO | Train Epoch: 3 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.65777 (0.68563) Boundary_loss: 0.013941 (0.013962) Loss: 0.67171 (0.69959) +2025-09-12,10:36:58 | INFO | Train Epoch: 3 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.57853 (0.68532) Boundary_loss: 0.013941 (0.013962) Loss: 0.59247 (0.69928) +2025-09-12,10:38:04 | INFO | Train Epoch: 3 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.63253 (0.68517) Boundary_loss: 0.013949 (0.013961) Loss: 0.64648 (0.69913) +2025-09-12,10:39:11 | INFO | Train Epoch: 3 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.65133 (0.68507) Boundary_loss: 0.013940 (0.013961) Loss: 0.66527 (0.69904) +2025-09-12,10:40:17 | INFO | Train Epoch: 3 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.68111 (0.68506) Boundary_loss: 0.013958 (0.013961) Loss: 0.69507 (0.69902) +2025-09-12,10:41:23 | INFO | Train Epoch: 3 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.56726 (0.68473) Boundary_loss: 0.013946 (0.013961) Loss: 0.58121 (0.69869) +2025-09-12,10:42:30 | INFO | Train Epoch: 3 [17971712/26365952 (68%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.64837 (0.68462) Boundary_loss: 0.013940 (0.013961) Loss: 0.66231 (0.69859) +2025-09-12,10:43:36 | INFO | Train Epoch: 3 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.70984 (0.68470) Boundary_loss: 0.013946 (0.013961) Loss: 0.72379 (0.69866) +2025-09-12,10:44:43 | INFO | Train Epoch: 3 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.66234 (0.68463) Boundary_loss: 0.013945 (0.013961) Loss: 0.67629 (0.69859) +2025-09-12,10:45:49 | INFO | Train Epoch: 3 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.57580 (0.68433) Boundary_loss: 0.013932 (0.013961) Loss: 0.58973 (0.69829) +2025-09-12,10:46:55 | INFO | Train Epoch: 3 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.63304 (0.68418) Boundary_loss: 0.013953 (0.013961) Loss: 0.64699 (0.69814) +2025-09-12,10:48:02 | INFO | Train Epoch: 3 [18227712/26365952 (69%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.69759 (0.68422) Boundary_loss: 0.013944 (0.013961) Loss: 0.71154 (0.69818) +2025-09-12,10:49:08 | INFO | Train Epoch: 3 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.57710 (0.68392) Boundary_loss: 0.013943 (0.013961) Loss: 0.59105 (0.69788) +2025-09-12,10:50:14 | INFO | Train Epoch: 3 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.80509 (0.68426) Boundary_loss: 0.013960 (0.013961) Loss: 0.81905 (0.69822) +2025-09-12,10:51:21 | INFO | Train Epoch: 3 [18381312/26365952 (70%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.60996 (0.68405) Boundary_loss: 0.013964 (0.013961) Loss: 0.62393 (0.69801) +2025-09-12,10:52:27 | INFO | Train Epoch: 3 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 0.67322 (0.68402) Boundary_loss: 0.013948 (0.013961) Loss: 0.68717 (0.69798) +2025-09-12,10:53:33 | INFO | Train Epoch: 3 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.68394 (0.68402) Boundary_loss: 0.013975 (0.013961) Loss: 0.69791 (0.69798) +2025-09-12,10:54:40 | INFO | Train Epoch: 3 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.58364 (0.68374) Boundary_loss: 0.013949 (0.013961) Loss: 0.59759 (0.69771) +2025-09-12,10:55:46 | INFO | Train Epoch: 3 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.61127 (0.68355) Boundary_loss: 0.013959 (0.013961) Loss: 0.62522 (0.69751) +2025-09-12,10:56:52 | INFO | Train Epoch: 3 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.67100 (0.68351) Boundary_loss: 0.013943 (0.013961) Loss: 0.68494 (0.69747) +2025-09-12,10:57:59 | INFO | Train Epoch: 3 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.59439 (0.68327) Boundary_loss: 0.013943 (0.013961) Loss: 0.60833 (0.69723) +2025-09-12,10:59:05 | INFO | Train Epoch: 3 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.56409 (0.68294) Boundary_loss: 0.013940 (0.013961) Loss: 0.57803 (0.69690) +2025-09-12,11:00:11 | INFO | Train Epoch: 3 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.58171 (0.68267) Boundary_loss: 0.013951 (0.013961) Loss: 0.59567 (0.69663) +2025-09-12,11:01:18 | INFO | Train Epoch: 3 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.66258 (0.68261) Boundary_loss: 0.013955 (0.013961) Loss: 0.67654 (0.69657) +2025-09-12,11:02:24 | INFO | Train Epoch: 3 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.59351 (0.68237) Boundary_loss: 0.013937 (0.013961) Loss: 0.60745 (0.69633) +2025-09-12,11:03:30 | INFO | Train Epoch: 3 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.69119 (0.68240) Boundary_loss: 0.013961 (0.013961) Loss: 0.70515 (0.69636) +2025-09-12,11:04:37 | INFO | Train Epoch: 3 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.65235 (0.68232) Boundary_loss: 0.013943 (0.013961) Loss: 0.66629 (0.69628) +2025-09-12,11:05:43 | INFO | Train Epoch: 3 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.61763 (0.68214) Boundary_loss: 0.013941 (0.013961) Loss: 0.63157 (0.69610) +2025-09-12,11:06:49 | INFO | Train Epoch: 3 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.55702 (0.68181) Boundary_loss: 0.013937 (0.013961) Loss: 0.57096 (0.69577) +2025-09-12,11:07:56 | INFO | Train Epoch: 3 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.68481 (0.68182) Boundary_loss: 0.013939 (0.013961) Loss: 0.69875 (0.69578) +2025-09-12,11:09:02 | INFO | Train Epoch: 3 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.68469 (0.68182) Boundary_loss: 0.013961 (0.013961) Loss: 0.69865 (0.69578) +2025-09-12,11:10:09 | INFO | Train Epoch: 3 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.59249 (0.68159) Boundary_loss: 0.013927 (0.013960) Loss: 0.60642 (0.69555) +2025-09-12,11:11:15 | INFO | Train Epoch: 3 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.67765 (0.68158) Boundary_loss: 0.013963 (0.013960) Loss: 0.69161 (0.69554) +2025-09-12,11:12:21 | INFO | Train Epoch: 3 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.63709 (0.68146) Boundary_loss: 0.013953 (0.013960) Loss: 0.65104 (0.69542) +2025-09-12,11:13:28 | INFO | Train Epoch: 3 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.73037 (0.68159) Boundary_loss: 0.013928 (0.013960) Loss: 0.74430 (0.69555) +2025-09-12,11:14:34 | INFO | Train Epoch: 3 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.61745 (0.68142) Boundary_loss: 0.013945 (0.013960) Loss: 0.63140 (0.69538) +2025-09-12,11:15:41 | INFO | Train Epoch: 3 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.68647 (0.68143) Boundary_loss: 0.013941 (0.013960) Loss: 0.70041 (0.69539) +2025-09-12,11:16:47 | INFO | Train Epoch: 3 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.64771 (0.68134) Boundary_loss: 0.013972 (0.013960) Loss: 0.66169 (0.69530) +2025-09-12,11:17:53 | INFO | Train Epoch: 3 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.64352 (0.68125) Boundary_loss: 0.013960 (0.013960) Loss: 0.65748 (0.69521) +2025-09-12,11:19:00 | INFO | Train Epoch: 3 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.62939 (0.68111) Boundary_loss: 0.013957 (0.013960) Loss: 0.64335 (0.69507) +2025-09-12,11:20:06 | INFO | Train Epoch: 3 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.63824 (0.68100) Boundary_loss: 0.013947 (0.013960) Loss: 0.65219 (0.69496) +2025-09-12,11:21:13 | INFO | Train Epoch: 3 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.64417 (0.68090) Boundary_loss: 0.013956 (0.013960) Loss: 0.65812 (0.69486) +2025-09-12,11:22:19 | INFO | Train Epoch: 3 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.63409 (0.68078) Boundary_loss: 0.013938 (0.013960) Loss: 0.64803 (0.69474) +2025-09-12,11:23:25 | INFO | Train Epoch: 3 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.66112 (0.68073) Boundary_loss: 0.013940 (0.013960) Loss: 0.67506 (0.69469) +2025-09-12,11:24:32 | INFO | Train Epoch: 3 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.67440 (0.68072) Boundary_loss: 0.013941 (0.013960) Loss: 0.68834 (0.69468) +2025-09-12,11:25:38 | INFO | Train Epoch: 3 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.57063 (0.68044) Boundary_loss: 0.013970 (0.013960) Loss: 0.58460 (0.69440) +2025-09-12,11:26:45 | INFO | Train Epoch: 3 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.63598 (0.68032) Boundary_loss: 0.013957 (0.013960) Loss: 0.64993 (0.69428) +2025-09-12,11:27:51 | INFO | Train Epoch: 3 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.68576 (0.68034) Boundary_loss: 0.013937 (0.013960) Loss: 0.69970 (0.69430) +2025-09-12,11:28:57 | INFO | Train Epoch: 3 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.64582 (0.68025) Boundary_loss: 0.013963 (0.013960) Loss: 0.65979 (0.69421) +2025-09-12,11:30:04 | INFO | Train Epoch: 3 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.67191 (0.68023) Boundary_loss: 0.013946 (0.013960) Loss: 0.68586 (0.69419) +2025-09-12,11:31:10 | INFO | Train Epoch: 3 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.61632 (0.68007) Boundary_loss: 0.013949 (0.013960) Loss: 0.63027 (0.69403) +2025-09-12,11:32:17 | INFO | Train Epoch: 3 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.61472 (0.67990) Boundary_loss: 0.014003 (0.013960) Loss: 0.62872 (0.69386) +2025-09-12,11:33:23 | INFO | Train Epoch: 3 [20326912/26365952 (77%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.63132 (0.67978) Boundary_loss: 0.013962 (0.013960) Loss: 0.64528 (0.69374) +2025-09-12,11:34:29 | INFO | Train Epoch: 3 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.63378 (0.67966) Boundary_loss: 0.013939 (0.013960) Loss: 0.64772 (0.69362) +2025-09-12,11:35:36 | INFO | Train Epoch: 3 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.53943 (0.67931) Boundary_loss: 0.013930 (0.013960) Loss: 0.55336 (0.69327) +2025-09-12,11:36:42 | INFO | Train Epoch: 3 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.64381 (0.67922) Boundary_loss: 0.013947 (0.013960) Loss: 0.65775 (0.69318) +2025-09-12,11:37:49 | INFO | Train Epoch: 3 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.58434 (0.67899) Boundary_loss: 0.013954 (0.013960) Loss: 0.59829 (0.69295) +2025-09-12,11:38:55 | INFO | Train Epoch: 3 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.61894 (0.67884) Boundary_loss: 0.013941 (0.013960) Loss: 0.63288 (0.69280) +2025-09-12,11:40:01 | INFO | Train Epoch: 3 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.64180 (0.67875) Boundary_loss: 0.013951 (0.013960) Loss: 0.65575 (0.69271) +2025-09-12,11:41:08 | INFO | Train Epoch: 3 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.69872 (0.67880) Boundary_loss: 0.013949 (0.013960) Loss: 0.71267 (0.69276) +2025-09-12,11:42:14 | INFO | Train Epoch: 3 [20736512/26365952 (79%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 0.61796 (0.67865) Boundary_loss: 0.013970 (0.013960) Loss: 0.63193 (0.69261) +2025-09-12,11:43:21 | INFO | Train Epoch: 3 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.62738 (0.67852) Boundary_loss: 0.013960 (0.013960) Loss: 0.64134 (0.69248) +2025-09-12,11:44:27 | INFO | Train Epoch: 3 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.57158 (0.67826) Boundary_loss: 0.013944 (0.013960) Loss: 0.58552 (0.69222) +2025-09-12,11:45:34 | INFO | Train Epoch: 3 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.58154 (0.67802) Boundary_loss: 0.013935 (0.013960) Loss: 0.59547 (0.69198) +2025-09-12,11:46:40 | INFO | Train Epoch: 3 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.66920 (0.67800) Boundary_loss: 0.013941 (0.013960) Loss: 0.68314 (0.69196) +2025-09-12,11:47:46 | INFO | Train Epoch: 3 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.70561 (0.67807) Boundary_loss: 0.013939 (0.013960) Loss: 0.71955 (0.69203) +2025-09-12,11:48:53 | INFO | Train Epoch: 3 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.62297 (0.67793) Boundary_loss: 0.013976 (0.013960) Loss: 0.63694 (0.69189) +2025-09-12,11:49:59 | INFO | Train Epoch: 3 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.64229 (0.67785) Boundary_loss: 0.013937 (0.013960) Loss: 0.65622 (0.69181) +2025-09-12,11:51:05 | INFO | Train Epoch: 3 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.58791 (0.67763) Boundary_loss: 0.013948 (0.013960) Loss: 0.60186 (0.69159) +2025-09-12,11:52:12 | INFO | Train Epoch: 3 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.67385 (0.67762) Boundary_loss: 0.013940 (0.013960) Loss: 0.68779 (0.69158) +2025-09-12,11:53:18 | INFO | Train Epoch: 3 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.47680 (0.67714) Boundary_loss: 0.013944 (0.013960) Loss: 0.49075 (0.69110) +2025-09-12,11:54:25 | INFO | Train Epoch: 3 [21299712/26365952 (81%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.58407 (0.67692) Boundary_loss: 0.013943 (0.013959) Loss: 0.59802 (0.69088) +2025-09-12,11:55:31 | INFO | Train Epoch: 3 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.60453 (0.67674) Boundary_loss: 0.013960 (0.013959) Loss: 0.61849 (0.69070) +2025-09-12,11:56:37 | INFO | Train Epoch: 3 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.60403 (0.67657) Boundary_loss: 0.013945 (0.013959) Loss: 0.61797 (0.69053) +2025-09-12,11:57:44 | INFO | Train Epoch: 3 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.71671 (0.67667) Boundary_loss: 0.013961 (0.013959) Loss: 0.73067 (0.69062) +2025-09-12,11:58:50 | INFO | Train Epoch: 3 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.60625 (0.67650) Boundary_loss: 0.013944 (0.013959) Loss: 0.62020 (0.69046) +2025-09-12,11:59:56 | INFO | Train Epoch: 3 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.59908 (0.67631) Boundary_loss: 0.013991 (0.013959) Loss: 0.61307 (0.69027) +2025-09-12,12:01:03 | INFO | Train Epoch: 3 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.55504 (0.67603) Boundary_loss: 0.013931 (0.013959) Loss: 0.56897 (0.68999) +2025-09-12,12:02:09 | INFO | Train Epoch: 3 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.66717 (0.67601) Boundary_loss: 0.013949 (0.013959) Loss: 0.68112 (0.68997) +2025-09-12,12:03:16 | INFO | Train Epoch: 3 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.64853 (0.67594) Boundary_loss: 0.013933 (0.013959) Loss: 0.66246 (0.68990) +2025-09-12,12:04:22 | INFO | Train Epoch: 3 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.72301 (0.67605) Boundary_loss: 0.013955 (0.013959) Loss: 0.73696 (0.69001) +2025-09-12,12:05:28 | INFO | Train Epoch: 3 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.62723 (0.67594) Boundary_loss: 0.013937 (0.013959) Loss: 0.64117 (0.68990) +2025-09-12,12:06:35 | INFO | Train Epoch: 3 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.51549 (0.67556) Boundary_loss: 0.013931 (0.013959) Loss: 0.52942 (0.68952) +2025-09-12,12:07:41 | INFO | Train Epoch: 3 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.65198 (0.67551) Boundary_loss: 0.013953 (0.013959) Loss: 0.66593 (0.68947) +2025-09-12,12:08:47 | INFO | Train Epoch: 3 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.63078 (0.67540) Boundary_loss: 0.013935 (0.013959) Loss: 0.64472 (0.68936) +2025-09-12,12:09:54 | INFO | Train Epoch: 3 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.57549 (0.67517) Boundary_loss: 0.013928 (0.013959) Loss: 0.58941 (0.68913) +2025-09-12,12:11:00 | INFO | Train Epoch: 3 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.60984 (0.67502) Boundary_loss: 0.013930 (0.013959) Loss: 0.62377 (0.68898) +2025-09-12,12:12:06 | INFO | Train Epoch: 3 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.65859 (0.67498) Boundary_loss: 0.013940 (0.013959) Loss: 0.67253 (0.68894) +2025-09-12,12:13:13 | INFO | Train Epoch: 3 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.60465 (0.67482) Boundary_loss: 0.013954 (0.013959) Loss: 0.61860 (0.68878) +2025-09-12,12:14:19 | INFO | Train Epoch: 3 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.64904 (0.67476) Boundary_loss: 0.013925 (0.013959) Loss: 0.66297 (0.68872) +2025-09-12,12:15:25 | INFO | Train Epoch: 3 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.50799 (0.67438) Boundary_loss: 0.013954 (0.013959) Loss: 0.52195 (0.68834) +2025-09-12,12:16:32 | INFO | Train Epoch: 3 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.71665 (0.67448) Boundary_loss: 0.013941 (0.013959) Loss: 0.73059 (0.68844) +2025-09-12,12:17:38 | INFO | Train Epoch: 3 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.71161 (0.67456) Boundary_loss: 0.013956 (0.013959) Loss: 0.72557 (0.68852) +2025-09-12,12:18:44 | INFO | Train Epoch: 3 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.57409 (0.67433) Boundary_loss: 0.013940 (0.013959) Loss: 0.58803 (0.68829) +2025-09-12,12:19:51 | INFO | Train Epoch: 3 [22477312/26365952 (85%)] Avg Boundaries (per batch): 49.148 Boundary Ratio: 0.251 Contrastive_loss: 0.68247 (0.67435) Boundary_loss: 0.013956 (0.013959) Loss: 0.69642 (0.68831) +2025-09-12,12:20:57 | INFO | Train Epoch: 3 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.71550 (0.67444) Boundary_loss: 0.013939 (0.013959) Loss: 0.72943 (0.68840) +2025-09-12,12:22:03 | INFO | Train Epoch: 3 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.56727 (0.67420) Boundary_loss: 0.013949 (0.013959) Loss: 0.58122 (0.68816) +2025-09-12,12:23:10 | INFO | Train Epoch: 3 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.60654 (0.67405) Boundary_loss: 0.013930 (0.013959) Loss: 0.62047 (0.68801) +2025-09-12,12:24:16 | INFO | Train Epoch: 3 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.67742 (0.67406) Boundary_loss: 0.013923 (0.013959) Loss: 0.69135 (0.68801) +2025-09-12,12:25:22 | INFO | Train Epoch: 3 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.50826 (0.67368) Boundary_loss: 0.013944 (0.013959) Loss: 0.52221 (0.68764) +2025-09-12,12:26:29 | INFO | Train Epoch: 3 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.58560 (0.67349) Boundary_loss: 0.013934 (0.013958) Loss: 0.59954 (0.68744) +2025-09-12,12:27:35 | INFO | Train Epoch: 3 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.61435 (0.67335) Boundary_loss: 0.013946 (0.013958) Loss: 0.62829 (0.68731) +2025-09-12,12:28:42 | INFO | Train Epoch: 3 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.62630 (0.67325) Boundary_loss: 0.013938 (0.013958) Loss: 0.64024 (0.68721) +2025-09-12,12:29:48 | INFO | Train Epoch: 3 [22938112/26365952 (87%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.65153 (0.67320) Boundary_loss: 0.013950 (0.013958) Loss: 0.66548 (0.68716) +2025-09-12,12:30:54 | INFO | Train Epoch: 3 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.62505 (0.67309) Boundary_loss: 0.013946 (0.013958) Loss: 0.63900 (0.68705) +2025-09-12,12:32:01 | INFO | Train Epoch: 3 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.68816 (0.67313) Boundary_loss: 0.013941 (0.013958) Loss: 0.70210 (0.68709) +2025-09-12,12:33:07 | INFO | Train Epoch: 3 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.64320 (0.67306) Boundary_loss: 0.013929 (0.013958) Loss: 0.65713 (0.68702) +2025-09-12,12:34:14 | INFO | Train Epoch: 3 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.53280 (0.67275) Boundary_loss: 0.013945 (0.013958) Loss: 0.54674 (0.68671) +2025-09-12,12:35:20 | INFO | Train Epoch: 3 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.61374 (0.67262) Boundary_loss: 0.013954 (0.013958) Loss: 0.62770 (0.68658) +2025-09-12,12:36:27 | INFO | Train Epoch: 3 [23245312/26365952 (88%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.57207 (0.67240) Boundary_loss: 0.013944 (0.013958) Loss: 0.58601 (0.68636) +2025-09-12,12:37:33 | INFO | Train Epoch: 3 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.62413 (0.67229) Boundary_loss: 0.013955 (0.013958) Loss: 0.63809 (0.68625) +2025-09-12,12:38:39 | INFO | Train Epoch: 3 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.60537 (0.67215) Boundary_loss: 0.013955 (0.013958) Loss: 0.61932 (0.68611) +2025-09-12,12:39:46 | INFO | Train Epoch: 3 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.66022 (0.67212) Boundary_loss: 0.013943 (0.013958) Loss: 0.67416 (0.68608) +2025-09-12,12:40:52 | INFO | Train Epoch: 3 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.65763 (0.67209) Boundary_loss: 0.013932 (0.013958) Loss: 0.67156 (0.68605) +2025-09-12,12:41:59 | INFO | Train Epoch: 3 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.69139 (0.67213) Boundary_loss: 0.013952 (0.013958) Loss: 0.70535 (0.68609) +2025-09-12,12:43:05 | INFO | Train Epoch: 3 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.64497 (0.67207) Boundary_loss: 0.013955 (0.013958) Loss: 0.65892 (0.68603) +2025-09-12,12:44:11 | INFO | Train Epoch: 3 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.59204 (0.67190) Boundary_loss: 0.013944 (0.013958) Loss: 0.60599 (0.68586) +2025-09-12,12:45:18 | INFO | Train Epoch: 3 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.66165 (0.67188) Boundary_loss: 0.013931 (0.013958) Loss: 0.67558 (0.68584) +2025-09-12,12:46:24 | INFO | Train Epoch: 3 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.63164 (0.67179) Boundary_loss: 0.013935 (0.013958) Loss: 0.64558 (0.68575) +2025-09-12,12:47:31 | INFO | Train Epoch: 3 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.69964 (0.67185) Boundary_loss: 0.013932 (0.013958) Loss: 0.71358 (0.68581) +2025-09-12,12:48:37 | INFO | Train Epoch: 3 [23808512/26365952 (90%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.66732 (0.67184) Boundary_loss: 0.013965 (0.013958) Loss: 0.68128 (0.68580) +2025-09-12,12:49:43 | INFO | Train Epoch: 3 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.57127 (0.67163) Boundary_loss: 0.013944 (0.013958) Loss: 0.58522 (0.68558) +2025-09-12,12:50:50 | INFO | Train Epoch: 3 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.73287 (0.67176) Boundary_loss: 0.013939 (0.013958) Loss: 0.74681 (0.68571) +2025-09-12,12:51:56 | INFO | Train Epoch: 3 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.52668 (0.67145) Boundary_loss: 0.013961 (0.013958) Loss: 0.54064 (0.68541) +2025-09-12,12:53:03 | INFO | Train Epoch: 3 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.54614 (0.67118) Boundary_loss: 0.013940 (0.013958) Loss: 0.56008 (0.68514) +2025-09-12,12:54:09 | INFO | Train Epoch: 3 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.67410 (0.67119) Boundary_loss: 0.013937 (0.013958) Loss: 0.68803 (0.68514) +2025-09-12,12:55:15 | INFO | Train Epoch: 3 [24115712/26365952 (91%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 0.50347 (0.67083) Boundary_loss: 0.013955 (0.013958) Loss: 0.51743 (0.68479) +2025-09-12,12:56:22 | INFO | Train Epoch: 3 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.61456 (0.67071) Boundary_loss: 0.013934 (0.013958) Loss: 0.62849 (0.68467) +2025-09-12,12:57:28 | INFO | Train Epoch: 3 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.50241 (0.67036) Boundary_loss: 0.013936 (0.013958) Loss: 0.51635 (0.68432) +2025-09-12,12:58:34 | INFO | Train Epoch: 3 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.60897 (0.67023) Boundary_loss: 0.013935 (0.013958) Loss: 0.62291 (0.68419) +2025-09-12,12:59:41 | INFO | Train Epoch: 3 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.64573 (0.67018) Boundary_loss: 0.013945 (0.013958) Loss: 0.65968 (0.68413) +2025-09-12,13:00:47 | INFO | Train Epoch: 3 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.61149 (0.67005) Boundary_loss: 0.013936 (0.013957) Loss: 0.62543 (0.68401) +2025-09-12,13:01:54 | INFO | Train Epoch: 3 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.57246 (0.66985) Boundary_loss: 0.013945 (0.013957) Loss: 0.58640 (0.68381) +2025-09-12,13:03:00 | INFO | Train Epoch: 3 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.70087 (0.66991) Boundary_loss: 0.013946 (0.013957) Loss: 0.71481 (0.68387) +2025-09-12,13:04:06 | INFO | Train Epoch: 3 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.53645 (0.66964) Boundary_loss: 0.013944 (0.013957) Loss: 0.55040 (0.68359) +2025-09-12,13:05:13 | INFO | Train Epoch: 3 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.54708 (0.66938) Boundary_loss: 0.013926 (0.013957) Loss: 0.56101 (0.68334) +2025-09-12,13:06:19 | INFO | Train Epoch: 3 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.52077 (0.66907) Boundary_loss: 0.013927 (0.013957) Loss: 0.53469 (0.68303) +2025-09-12,13:07:26 | INFO | Train Epoch: 3 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.64628 (0.66903) Boundary_loss: 0.013935 (0.013957) Loss: 0.66021 (0.68298) +2025-09-12,13:08:32 | INFO | Train Epoch: 3 [24730112/26365952 (94%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.61788 (0.66892) Boundary_loss: 0.013967 (0.013957) Loss: 0.63184 (0.68288) +2025-09-12,13:09:39 | INFO | Train Epoch: 3 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.58254 (0.66874) Boundary_loss: 0.013928 (0.013957) Loss: 0.59647 (0.68270) +2025-09-12,13:10:45 | INFO | Train Epoch: 3 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.56806 (0.66854) Boundary_loss: 0.013941 (0.013957) Loss: 0.58200 (0.68249) +2025-09-12,13:11:51 | INFO | Train Epoch: 3 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.63244 (0.66846) Boundary_loss: 0.013977 (0.013957) Loss: 0.64641 (0.68242) +2025-09-12,13:12:58 | INFO | Train Epoch: 3 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.61009 (0.66834) Boundary_loss: 0.013932 (0.013957) Loss: 0.62402 (0.68230) +2025-09-12,13:14:04 | INFO | Train Epoch: 3 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.61855 (0.66824) Boundary_loss: 0.013937 (0.013957) Loss: 0.63249 (0.68220) +2025-09-12,13:15:11 | INFO | Train Epoch: 3 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.60947 (0.66812) Boundary_loss: 0.013935 (0.013957) Loss: 0.62341 (0.68208) +2025-09-12,13:16:17 | INFO | Train Epoch: 3 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.74590 (0.66828) Boundary_loss: 0.013948 (0.013957) Loss: 0.75985 (0.68224) +2025-09-12,13:17:23 | INFO | Train Epoch: 3 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.60208 (0.66814) Boundary_loss: 0.013932 (0.013957) Loss: 0.61601 (0.68210) +2025-09-12,13:18:30 | INFO | Train Epoch: 3 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.58733 (0.66798) Boundary_loss: 0.013946 (0.013957) Loss: 0.60128 (0.68194) +2025-09-12,13:19:36 | INFO | Train Epoch: 3 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.65985 (0.66796) Boundary_loss: 0.013937 (0.013957) Loss: 0.67379 (0.68192) +2025-09-12,13:20:43 | INFO | Train Epoch: 3 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.63589 (0.66790) Boundary_loss: 0.013939 (0.013957) Loss: 0.64983 (0.68186) +2025-09-12,13:21:49 | INFO | Train Epoch: 3 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.55559 (0.66767) Boundary_loss: 0.013943 (0.013957) Loss: 0.56953 (0.68163) +2025-09-12,13:22:55 | INFO | Train Epoch: 3 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.57511 (0.66749) Boundary_loss: 0.013947 (0.013957) Loss: 0.58906 (0.68144) +2025-09-12,13:24:02 | INFO | Train Epoch: 3 [25446912/26365952 (97%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.58799 (0.66733) Boundary_loss: 0.013937 (0.013957) Loss: 0.60193 (0.68128) +2025-09-12,13:25:08 | INFO | Train Epoch: 3 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.65627 (0.66730) Boundary_loss: 0.013938 (0.013957) Loss: 0.67021 (0.68126) +2025-09-12,13:26:15 | INFO | Train Epoch: 3 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.58232 (0.66713) Boundary_loss: 0.013945 (0.013957) Loss: 0.59627 (0.68109) +2025-09-12,13:27:21 | INFO | Train Epoch: 3 [25600512/26365952 (97%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.70832 (0.66722) Boundary_loss: 0.013988 (0.013957) Loss: 0.72231 (0.68117) +2025-09-12,13:28:27 | INFO | Train Epoch: 3 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.55992 (0.66700) Boundary_loss: 0.013932 (0.013957) Loss: 0.57385 (0.68096) +2025-09-12,13:29:34 | INFO | Train Epoch: 3 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.67487 (0.66702) Boundary_loss: 0.013949 (0.013957) Loss: 0.68882 (0.68097) +2025-09-12,13:30:40 | INFO | Train Epoch: 3 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.74399 (0.66717) Boundary_loss: 0.013933 (0.013957) Loss: 0.75793 (0.68113) +2025-09-12,13:31:46 | INFO | Train Epoch: 3 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.75762 (0.66735) Boundary_loss: 0.013951 (0.013957) Loss: 0.77157 (0.68131) +2025-09-12,13:32:53 | INFO | Train Epoch: 3 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.65384 (0.66732) Boundary_loss: 0.013950 (0.013957) Loss: 0.66779 (0.68128) +2025-09-12,13:33:59 | INFO | Train Epoch: 3 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.73441 (0.66746) Boundary_loss: 0.013929 (0.013957) Loss: 0.74834 (0.68141) +2025-09-12,13:35:05 | INFO | Train Epoch: 3 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.57072 (0.66727) Boundary_loss: 0.013940 (0.013957) Loss: 0.58466 (0.68122) +2025-09-12,13:36:12 | INFO | Train Epoch: 3 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.63458 (0.66720) Boundary_loss: 0.013943 (0.013957) Loss: 0.64852 (0.68116) +2025-09-12,13:37:18 | INFO | Train Epoch: 3 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.54632 (0.66696) Boundary_loss: 0.013931 (0.013957) Loss: 0.56025 (0.68092) +2025-09-12,13:38:24 | INFO | Train Epoch: 3 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.67897 (0.66699) Boundary_loss: 0.013952 (0.013957) Loss: 0.69292 (0.68094) +2025-09-12,13:39:31 | INFO | Train Epoch: 3 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.65065 (0.66696) Boundary_loss: 0.013936 (0.013956) Loss: 0.66458 (0.68091) +2025-09-12,13:40:37 | INFO | Train Epoch: 3 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.54782 (0.66672) Boundary_loss: 0.013933 (0.013956) Loss: 0.56175 (0.68068) +2025-09-12,13:41:43 | INFO | Train Epoch: 3 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.65012 (0.66669) Boundary_loss: 0.013938 (0.013956) Loss: 0.66406 (0.68065) +2025-09-12,13:42:50 | INFO | Train Epoch: 3 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.59060 (0.66654) Boundary_loss: 0.013930 (0.013956) Loss: 0.60453 (0.68050) +2025-09-12,13:43:53 | INFO | Train Epoch: 3 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.65384 (0.66652) Boundary_loss: 0.013920 (0.013956) Loss: 0.66776 (0.68047) +2025-09-12,13:43:53 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,13:43:53 | INFO | [Epoch 3] Average Step Time: 0.666s | Average GPU Memory: 31.1 GB +2025-09-12,13:43:53 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,13:43:53 | INFO | Starting zero-shot imagenet. +2025-09-12,13:43:53 | INFO | Building zero-shot classifier +2025-09-12,13:44:02 | INFO | Using classifier +2025-09-12,13:45:30 | INFO | Finished zero-shot imagenet. +2025-09-12,13:45:30 | INFO | Eval Epoch: 4 imagenet-zeroshot-val-top1: 0.2305 imagenet-zeroshot-val-top5: 0.4674 +2025-09-12,13:45:32 | INFO | Start epoch 4 +2025-09-12,13:45:34 | INFO | Train Epoch: 4 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.45638 (0.45638) Boundary_loss: 0.013924 (0.013924) Loss: 0.47030 (0.47030) +2025-09-12,13:46:40 | INFO | Train Epoch: 4 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.54290 (0.49964) Boundary_loss: 0.013947 (0.013935) Loss: 0.55685 (0.51358) +2025-09-12,13:47:46 | INFO | Train Epoch: 4 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.48834 (0.49587) Boundary_loss: 0.013952 (0.013941) Loss: 0.50229 (0.50981) +2025-09-12,13:48:52 | INFO | Train Epoch: 4 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.61669 (0.52608) Boundary_loss: 0.013933 (0.013939) Loss: 0.63062 (0.54002) +2025-09-12,13:49:58 | INFO | Train Epoch: 4 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.56130 (0.53312) Boundary_loss: 0.013934 (0.013938) Loss: 0.57523 (0.54706) +2025-09-12,13:51:05 | INFO | Train Epoch: 4 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.43536 (0.51683) Boundary_loss: 0.013934 (0.013937) Loss: 0.44930 (0.53076) +2025-09-12,13:52:11 | INFO | Train Epoch: 4 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.58274 (0.52624) Boundary_loss: 0.013937 (0.013937) Loss: 0.59667 (0.54018) +2025-09-12,13:53:17 | INFO | Train Epoch: 4 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.51835 (0.52526) Boundary_loss: 0.013934 (0.013937) Loss: 0.53229 (0.53919) +2025-09-12,13:54:23 | INFO | Train Epoch: 4 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.60156 (0.53374) Boundary_loss: 0.013940 (0.013937) Loss: 0.61550 (0.54767) +2025-09-12,13:55:29 | INFO | Train Epoch: 4 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.53630 (0.53399) Boundary_loss: 0.013935 (0.013937) Loss: 0.55024 (0.54793) +2025-09-12,13:56:35 | INFO | Train Epoch: 4 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.57915 (0.53810) Boundary_loss: 0.013957 (0.013939) Loss: 0.59311 (0.55204) +2025-09-12,13:57:41 | INFO | Train Epoch: 4 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.62940 (0.54571) Boundary_loss: 0.013939 (0.013939) Loss: 0.64334 (0.55965) +2025-09-12,13:58:47 | INFO | Train Epoch: 4 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.60599 (0.55034) Boundary_loss: 0.013923 (0.013938) Loss: 0.61992 (0.56428) +2025-09-12,13:59:54 | INFO | Train Epoch: 4 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.58246 (0.55264) Boundary_loss: 0.013923 (0.013937) Loss: 0.59638 (0.56657) +2025-09-12,14:01:00 | INFO | Train Epoch: 4 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.45158 (0.54590) Boundary_loss: 0.013938 (0.013937) Loss: 0.46551 (0.55984) +2025-09-12,14:02:06 | INFO | Train Epoch: 4 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.60122 (0.54936) Boundary_loss: 0.013940 (0.013937) Loss: 0.61516 (0.56329) +2025-09-12,14:03:12 | INFO | Train Epoch: 4 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.56869 (0.55050) Boundary_loss: 0.013947 (0.013937) Loss: 0.58264 (0.56443) +2025-09-12,14:04:18 | INFO | Train Epoch: 4 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.61396 (0.55402) Boundary_loss: 0.013937 (0.013937) Loss: 0.62790 (0.56796) +2025-09-12,14:05:24 | INFO | Train Epoch: 4 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.54952 (0.55378) Boundary_loss: 0.013929 (0.013937) Loss: 0.56345 (0.56772) +2025-09-12,14:06:30 | INFO | Train Epoch: 4 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.58922 (0.55556) Boundary_loss: 0.013953 (0.013938) Loss: 0.60317 (0.56949) +2025-09-12,14:07:37 | INFO | Train Epoch: 4 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.61418 (0.55835) Boundary_loss: 0.013949 (0.013938) Loss: 0.62813 (0.57229) +2025-09-12,14:08:43 | INFO | Train Epoch: 4 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.55629 (0.55825) Boundary_loss: 0.013960 (0.013939) Loss: 0.57025 (0.57219) +2025-09-12,14:09:49 | INFO | Train Epoch: 4 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.51928 (0.55656) Boundary_loss: 0.013933 (0.013939) Loss: 0.53321 (0.57050) +2025-09-12,14:10:55 | INFO | Train Epoch: 4 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.52684 (0.55532) Boundary_loss: 0.013952 (0.013940) Loss: 0.54079 (0.56926) +2025-09-12,14:12:01 | INFO | Train Epoch: 4 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.58630 (0.55656) Boundary_loss: 0.013953 (0.013940) Loss: 0.60026 (0.57050) +2025-09-12,14:13:07 | INFO | Train Epoch: 4 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.50728 (0.55467) Boundary_loss: 0.013961 (0.013941) Loss: 0.52124 (0.56861) +2025-09-12,14:14:14 | INFO | Train Epoch: 4 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.62018 (0.55709) Boundary_loss: 0.013929 (0.013940) Loss: 0.63411 (0.57103) +2025-09-12,14:15:20 | INFO | Train Epoch: 4 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.63020 (0.55970) Boundary_loss: 0.013952 (0.013941) Loss: 0.64415 (0.57364) +2025-09-12,14:16:26 | INFO | Train Epoch: 4 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.62216 (0.56186) Boundary_loss: 0.013944 (0.013941) Loss: 0.63611 (0.57580) +2025-09-12,14:17:32 | INFO | Train Epoch: 4 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.56258 (0.56188) Boundary_loss: 0.013926 (0.013940) Loss: 0.57651 (0.57582) +2025-09-12,14:18:38 | INFO | Train Epoch: 4 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.51716 (0.56044) Boundary_loss: 0.013929 (0.013940) Loss: 0.53109 (0.57438) +2025-09-12,14:19:44 | INFO | Train Epoch: 4 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.56152 (0.56047) Boundary_loss: 0.013941 (0.013940) Loss: 0.57546 (0.57441) +2025-09-12,14:20:51 | INFO | Train Epoch: 4 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.62457 (0.56241) Boundary_loss: 0.013949 (0.013940) Loss: 0.63852 (0.57635) +2025-09-12,14:21:57 | INFO | Train Epoch: 4 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.51595 (0.56105) Boundary_loss: 0.013938 (0.013940) Loss: 0.52989 (0.57499) +2025-09-12,14:23:03 | INFO | Train Epoch: 4 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.57076 (0.56133) Boundary_loss: 0.013933 (0.013940) Loss: 0.58470 (0.57527) +2025-09-12,14:24:09 | INFO | Train Epoch: 4 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.50508 (0.55976) Boundary_loss: 0.013941 (0.013940) Loss: 0.51902 (0.57370) +2025-09-12,14:25:15 | INFO | Train Epoch: 4 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.51446 (0.55854) Boundary_loss: 0.013943 (0.013940) Loss: 0.52841 (0.57248) +2025-09-12,14:26:21 | INFO | Train Epoch: 4 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.58936 (0.55935) Boundary_loss: 0.013938 (0.013940) Loss: 0.60330 (0.57329) +2025-09-12,14:27:27 | INFO | Train Epoch: 4 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.49576 (0.55772) Boundary_loss: 0.013932 (0.013940) Loss: 0.50969 (0.57166) +2025-09-12,14:28:34 | INFO | Train Epoch: 4 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.51182 (0.55657) Boundary_loss: 0.013967 (0.013941) Loss: 0.52579 (0.57051) +2025-09-12,14:29:40 | INFO | Train Epoch: 4 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.54299 (0.55624) Boundary_loss: 0.013932 (0.013940) Loss: 0.55692 (0.57018) +2025-09-12,14:30:46 | INFO | Train Epoch: 4 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.63020 (0.55800) Boundary_loss: 0.013925 (0.013940) Loss: 0.64412 (0.57194) +2025-09-12,14:31:52 | INFO | Train Epoch: 4 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.58913 (0.55873) Boundary_loss: 0.013926 (0.013940) Loss: 0.60305 (0.57266) +2025-09-12,14:32:58 | INFO | Train Epoch: 4 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.63593 (0.56048) Boundary_loss: 0.013945 (0.013940) Loss: 0.64988 (0.57442) +2025-09-12,14:34:05 | INFO | Train Epoch: 4 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.49640 (0.55906) Boundary_loss: 0.013936 (0.013940) Loss: 0.51034 (0.57300) +2025-09-12,14:35:11 | INFO | Train Epoch: 4 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.54194 (0.55868) Boundary_loss: 0.013928 (0.013939) Loss: 0.55587 (0.57262) +2025-09-12,14:36:17 | INFO | Train Epoch: 4 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.55420 (0.55859) Boundary_loss: 0.013948 (0.013940) Loss: 0.56815 (0.57253) +2025-09-12,14:37:23 | INFO | Train Epoch: 4 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.61767 (0.55982) Boundary_loss: 0.013924 (0.013939) Loss: 0.63160 (0.57376) +2025-09-12,14:38:29 | INFO | Train Epoch: 4 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.50395 (0.55868) Boundary_loss: 0.013944 (0.013939) Loss: 0.51789 (0.57262) +2025-09-12,14:39:35 | INFO | Train Epoch: 4 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.59131 (0.55933) Boundary_loss: 0.013944 (0.013940) Loss: 0.60525 (0.57327) +2025-09-12,14:40:42 | INFO | Train Epoch: 4 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.66493 (0.56140) Boundary_loss: 0.013936 (0.013939) Loss: 0.67887 (0.57534) +2025-09-12,14:41:48 | INFO | Train Epoch: 4 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.61336 (0.56240) Boundary_loss: 0.013930 (0.013939) Loss: 0.62729 (0.57634) +2025-09-12,14:42:54 | INFO | Train Epoch: 4 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.51869 (0.56158) Boundary_loss: 0.013941 (0.013939) Loss: 0.53263 (0.57552) +2025-09-12,14:44:00 | INFO | Train Epoch: 4 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.54492 (0.56127) Boundary_loss: 0.013928 (0.013939) Loss: 0.55885 (0.57521) +2025-09-12,14:45:07 | INFO | Train Epoch: 4 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.52393 (0.56059) Boundary_loss: 0.013944 (0.013939) Loss: 0.53788 (0.57453) +2025-09-12,14:46:13 | INFO | Train Epoch: 4 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.55357 (0.56046) Boundary_loss: 0.013930 (0.013939) Loss: 0.56750 (0.57440) +2025-09-12,14:47:19 | INFO | Train Epoch: 4 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.54763 (0.56024) Boundary_loss: 0.013943 (0.013939) Loss: 0.56157 (0.57418) +2025-09-12,14:48:25 | INFO | Train Epoch: 4 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.61387 (0.56116) Boundary_loss: 0.013925 (0.013939) Loss: 0.62780 (0.57510) +2025-09-12,14:49:31 | INFO | Train Epoch: 4 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.72191 (0.56389) Boundary_loss: 0.013940 (0.013939) Loss: 0.73585 (0.57783) +2025-09-12,14:50:38 | INFO | Train Epoch: 4 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.55330 (0.56371) Boundary_loss: 0.013930 (0.013939) Loss: 0.56723 (0.57765) +2025-09-12,14:51:44 | INFO | Train Epoch: 4 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.62228 (0.56467) Boundary_loss: 0.013936 (0.013939) Loss: 0.63621 (0.57861) +2025-09-12,14:52:50 | INFO | Train Epoch: 4 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.46905 (0.56313) Boundary_loss: 0.013935 (0.013939) Loss: 0.48299 (0.57707) +2025-09-12,14:53:56 | INFO | Train Epoch: 4 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.55512 (0.56300) Boundary_loss: 0.013929 (0.013938) Loss: 0.56905 (0.57694) +2025-09-12,14:55:03 | INFO | Train Epoch: 4 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.66558 (0.56461) Boundary_loss: 0.013927 (0.013938) Loss: 0.67951 (0.57854) +2025-09-12,14:56:09 | INFO | Train Epoch: 4 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.61273 (0.56535) Boundary_loss: 0.013967 (0.013939) Loss: 0.62670 (0.57928) +2025-09-12,14:57:15 | INFO | Train Epoch: 4 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.47796 (0.56402) Boundary_loss: 0.013932 (0.013939) Loss: 0.49189 (0.57796) +2025-09-12,14:58:21 | INFO | Train Epoch: 4 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.58126 (0.56428) Boundary_loss: 0.013932 (0.013939) Loss: 0.59519 (0.57822) +2025-09-12,14:59:27 | INFO | Train Epoch: 4 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.44503 (0.56253) Boundary_loss: 0.013950 (0.013939) Loss: 0.45898 (0.57646) +2025-09-12,15:00:34 | INFO | Train Epoch: 4 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.53861 (0.56218) Boundary_loss: 0.013931 (0.013939) Loss: 0.55254 (0.57612) +2025-09-12,15:01:40 | INFO | Train Epoch: 4 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.60061 (0.56273) Boundary_loss: 0.013956 (0.013939) Loss: 0.61456 (0.57667) +2025-09-12,15:02:46 | INFO | Train Epoch: 4 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.57039 (0.56284) Boundary_loss: 0.013934 (0.013939) Loss: 0.58432 (0.57677) +2025-09-12,15:03:53 | INFO | Train Epoch: 4 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.56496 (0.56287) Boundary_loss: 0.013945 (0.013939) Loss: 0.57891 (0.57680) +2025-09-12,15:04:59 | INFO | Train Epoch: 4 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.61095 (0.56352) Boundary_loss: 0.013961 (0.013939) Loss: 0.62491 (0.57746) +2025-09-12,15:06:05 | INFO | Train Epoch: 4 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.54843 (0.56332) Boundary_loss: 0.013922 (0.013939) Loss: 0.56235 (0.57726) +2025-09-12,15:07:11 | INFO | Train Epoch: 4 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.58784 (0.56365) Boundary_loss: 0.013935 (0.013939) Loss: 0.60177 (0.57759) +2025-09-12,15:08:17 | INFO | Train Epoch: 4 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.50765 (0.56291) Boundary_loss: 0.013938 (0.013939) Loss: 0.52159 (0.57685) +2025-09-12,15:09:24 | INFO | Train Epoch: 4 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.59655 (0.56335) Boundary_loss: 0.013947 (0.013939) Loss: 0.61050 (0.57729) +2025-09-12,15:10:30 | INFO | Train Epoch: 4 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.55461 (0.56323) Boundary_loss: 0.013953 (0.013939) Loss: 0.56856 (0.57717) +2025-09-12,15:11:36 | INFO | Train Epoch: 4 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.54103 (0.56295) Boundary_loss: 0.013923 (0.013939) Loss: 0.55496 (0.57689) +2025-09-12,15:12:42 | INFO | Train Epoch: 4 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.70085 (0.56468) Boundary_loss: 0.013926 (0.013939) Loss: 0.71478 (0.57862) +2025-09-12,15:13:49 | INFO | Train Epoch: 4 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.67532 (0.56604) Boundary_loss: 0.013933 (0.013939) Loss: 0.68925 (0.57998) +2025-09-12,15:14:55 | INFO | Train Epoch: 4 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.53957 (0.56572) Boundary_loss: 0.013944 (0.013939) Loss: 0.55352 (0.57966) +2025-09-12,15:16:01 | INFO | Train Epoch: 4 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.41045 (0.56385) Boundary_loss: 0.013960 (0.013939) Loss: 0.42441 (0.57779) +2025-09-12,15:17:07 | INFO | Train Epoch: 4 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.52763 (0.56342) Boundary_loss: 0.013960 (0.013939) Loss: 0.54159 (0.57736) +2025-09-12,15:18:14 | INFO | Train Epoch: 4 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.49812 (0.56265) Boundary_loss: 0.013927 (0.013939) Loss: 0.51205 (0.57659) +2025-09-12,15:19:20 | INFO | Train Epoch: 4 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.61870 (0.56330) Boundary_loss: 0.013926 (0.013939) Loss: 0.63263 (0.57724) +2025-09-12,15:20:26 | INFO | Train Epoch: 4 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.67799 (0.56462) Boundary_loss: 0.013945 (0.013939) Loss: 0.69193 (0.57856) +2025-09-12,15:21:32 | INFO | Train Epoch: 4 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 0.49924 (0.56388) Boundary_loss: 0.013935 (0.013939) Loss: 0.51318 (0.57782) +2025-09-12,15:22:39 | INFO | Train Epoch: 4 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.57507 (0.56400) Boundary_loss: 0.013926 (0.013939) Loss: 0.58899 (0.57794) +2025-09-12,15:23:45 | INFO | Train Epoch: 4 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.52065 (0.56352) Boundary_loss: 0.013936 (0.013939) Loss: 0.53459 (0.57746) +2025-09-12,15:24:51 | INFO | Train Epoch: 4 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.60770 (0.56401) Boundary_loss: 0.013930 (0.013939) Loss: 0.62163 (0.57795) +2025-09-12,15:25:57 | INFO | Train Epoch: 4 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.62329 (0.56465) Boundary_loss: 0.013929 (0.013939) Loss: 0.63721 (0.57859) +2025-09-12,15:27:04 | INFO | Train Epoch: 4 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.55876 (0.56459) Boundary_loss: 0.013925 (0.013938) Loss: 0.57269 (0.57853) +2025-09-12,15:28:10 | INFO | Train Epoch: 4 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.70147 (0.56604) Boundary_loss: 0.013927 (0.013938) Loss: 0.71540 (0.57998) +2025-09-12,15:29:16 | INFO | Train Epoch: 4 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.58166 (0.56621) Boundary_loss: 0.013919 (0.013938) Loss: 0.59558 (0.58015) +2025-09-12,15:30:22 | INFO | Train Epoch: 4 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.55268 (0.56607) Boundary_loss: 0.013931 (0.013938) Loss: 0.56661 (0.58001) +2025-09-12,15:31:28 | INFO | Train Epoch: 4 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.52044 (0.56560) Boundary_loss: 0.013931 (0.013938) Loss: 0.53437 (0.57954) +2025-09-12,15:32:35 | INFO | Train Epoch: 4 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.61112 (0.56606) Boundary_loss: 0.013922 (0.013938) Loss: 0.62504 (0.58000) +2025-09-12,15:33:41 | INFO | Train Epoch: 4 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.60397 (0.56644) Boundary_loss: 0.013943 (0.013938) Loss: 0.61792 (0.58038) +2025-09-12,15:34:47 | INFO | Train Epoch: 4 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.50616 (0.56584) Boundary_loss: 0.013926 (0.013938) Loss: 0.52008 (0.57978) +2025-09-12,15:35:53 | INFO | Train Epoch: 4 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.57648 (0.56595) Boundary_loss: 0.013946 (0.013938) Loss: 0.59042 (0.57989) +2025-09-12,15:36:59 | INFO | Train Epoch: 4 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.52209 (0.56552) Boundary_loss: 0.013966 (0.013938) Loss: 0.53606 (0.57946) +2025-09-12,15:38:06 | INFO | Train Epoch: 4 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.54729 (0.56534) Boundary_loss: 0.013937 (0.013938) Loss: 0.56123 (0.57928) +2025-09-12,15:39:12 | INFO | Train Epoch: 4 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.50275 (0.56474) Boundary_loss: 0.013917 (0.013938) Loss: 0.51667 (0.57868) +2025-09-12,15:40:18 | INFO | Train Epoch: 4 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.55194 (0.56462) Boundary_loss: 0.013924 (0.013938) Loss: 0.56587 (0.57855) +2025-09-12,15:41:24 | INFO | Train Epoch: 4 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.71887 (0.56607) Boundary_loss: 0.013943 (0.013938) Loss: 0.73281 (0.58001) +2025-09-12,15:42:30 | INFO | Train Epoch: 4 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.54664 (0.56589) Boundary_loss: 0.013923 (0.013938) Loss: 0.56057 (0.57983) +2025-09-12,15:43:37 | INFO | Train Epoch: 4 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.51404 (0.56541) Boundary_loss: 0.013931 (0.013938) Loss: 0.52797 (0.57935) +2025-09-12,15:44:43 | INFO | Train Epoch: 4 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.63232 (0.56602) Boundary_loss: 0.013935 (0.013938) Loss: 0.64626 (0.57996) +2025-09-12,15:45:49 | INFO | Train Epoch: 4 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.51515 (0.56556) Boundary_loss: 0.013924 (0.013937) Loss: 0.52907 (0.57950) +2025-09-12,15:46:55 | INFO | Train Epoch: 4 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.52513 (0.56520) Boundary_loss: 0.013956 (0.013938) Loss: 0.53909 (0.57914) +2025-09-12,15:48:02 | INFO | Train Epoch: 4 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.63900 (0.56586) Boundary_loss: 0.013936 (0.013938) Loss: 0.65294 (0.57979) +2025-09-12,15:49:08 | INFO | Train Epoch: 4 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.61367 (0.56628) Boundary_loss: 0.013934 (0.013938) Loss: 0.62760 (0.58022) +2025-09-12,15:50:14 | INFO | Train Epoch: 4 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.56576 (0.56627) Boundary_loss: 0.013955 (0.013938) Loss: 0.57971 (0.58021) +2025-09-12,15:51:20 | INFO | Train Epoch: 4 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.57481 (0.56635) Boundary_loss: 0.013925 (0.013938) Loss: 0.58874 (0.58029) +2025-09-12,15:52:27 | INFO | Train Epoch: 4 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.53671 (0.56609) Boundary_loss: 0.013958 (0.013938) Loss: 0.55067 (0.58003) +2025-09-12,15:53:33 | INFO | Train Epoch: 4 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.54502 (0.56591) Boundary_loss: 0.013945 (0.013938) Loss: 0.55896 (0.57985) +2025-09-12,15:54:39 | INFO | Train Epoch: 4 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.60247 (0.56622) Boundary_loss: 0.013931 (0.013938) Loss: 0.61641 (0.58016) +2025-09-12,15:55:45 | INFO | Train Epoch: 4 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.52958 (0.56592) Boundary_loss: 0.013922 (0.013938) Loss: 0.54350 (0.57985) +2025-09-12,15:56:52 | INFO | Train Epoch: 4 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.55275 (0.56581) Boundary_loss: 0.013931 (0.013938) Loss: 0.56668 (0.57974) +2025-09-12,15:57:58 | INFO | Train Epoch: 4 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.64636 (0.56647) Boundary_loss: 0.013949 (0.013938) Loss: 0.66031 (0.58041) +2025-09-12,15:59:04 | INFO | Train Epoch: 4 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.55912 (0.56641) Boundary_loss: 0.013932 (0.013938) Loss: 0.57305 (0.58035) +2025-09-12,16:00:10 | INFO | Train Epoch: 4 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.61522 (0.56681) Boundary_loss: 0.013921 (0.013938) Loss: 0.62914 (0.58075) +2025-09-12,16:01:17 | INFO | Train Epoch: 4 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.47852 (0.56610) Boundary_loss: 0.013934 (0.013938) Loss: 0.49245 (0.58003) +2025-09-12,16:02:23 | INFO | Train Epoch: 4 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.54795 (0.56595) Boundary_loss: 0.013956 (0.013938) Loss: 0.56190 (0.57989) +2025-09-12,16:03:29 | INFO | Train Epoch: 4 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.53505 (0.56571) Boundary_loss: 0.013941 (0.013938) Loss: 0.54899 (0.57964) +2025-09-12,16:04:35 | INFO | Train Epoch: 4 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.51693 (0.56532) Boundary_loss: 0.013927 (0.013938) Loss: 0.53086 (0.57926) +2025-09-12,16:05:42 | INFO | Train Epoch: 4 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.56828 (0.56534) Boundary_loss: 0.013942 (0.013938) Loss: 0.58222 (0.57928) +2025-09-12,16:06:48 | INFO | Train Epoch: 4 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.49614 (0.56481) Boundary_loss: 0.013932 (0.013938) Loss: 0.51007 (0.57875) +2025-09-12,16:07:54 | INFO | Train Epoch: 4 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.61912 (0.56523) Boundary_loss: 0.013931 (0.013938) Loss: 0.63305 (0.57916) +2025-09-12,16:09:00 | INFO | Train Epoch: 4 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.66633 (0.56600) Boundary_loss: 0.013938 (0.013938) Loss: 0.68027 (0.57994) +2025-09-12,16:10:07 | INFO | Train Epoch: 4 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.44904 (0.56511) Boundary_loss: 0.013946 (0.013938) Loss: 0.46298 (0.57905) +2025-09-12,16:11:13 | INFO | Train Epoch: 4 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.53327 (0.56487) Boundary_loss: 0.013926 (0.013938) Loss: 0.54719 (0.57881) +2025-09-12,16:12:19 | INFO | Train Epoch: 4 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.53987 (0.56469) Boundary_loss: 0.013929 (0.013937) Loss: 0.55380 (0.57862) +2025-09-12,16:13:25 | INFO | Train Epoch: 4 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.54628 (0.56455) Boundary_loss: 0.013946 (0.013938) Loss: 0.56022 (0.57849) +2025-09-12,16:14:32 | INFO | Train Epoch: 4 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.51576 (0.56419) Boundary_loss: 0.013932 (0.013937) Loss: 0.52969 (0.57813) +2025-09-12,16:15:38 | INFO | Train Epoch: 4 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.62611 (0.56464) Boundary_loss: 0.013958 (0.013938) Loss: 0.64007 (0.57858) +2025-09-12,16:16:44 | INFO | Train Epoch: 4 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.51578 (0.56429) Boundary_loss: 0.013935 (0.013938) Loss: 0.52971 (0.57823) +2025-09-12,16:17:50 | INFO | Train Epoch: 4 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.51357 (0.56392) Boundary_loss: 0.013934 (0.013938) Loss: 0.52751 (0.57786) +2025-09-12,16:18:57 | INFO | Train Epoch: 4 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.51365 (0.56356) Boundary_loss: 0.013942 (0.013938) Loss: 0.52759 (0.57750) +2025-09-12,16:20:03 | INFO | Train Epoch: 4 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.63801 (0.56409) Boundary_loss: 0.013941 (0.013938) Loss: 0.65195 (0.57803) +2025-09-12,16:21:09 | INFO | Train Epoch: 4 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.50705 (0.56369) Boundary_loss: 0.013932 (0.013938) Loss: 0.52099 (0.57763) +2025-09-12,16:22:15 | INFO | Train Epoch: 4 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.55564 (0.56363) Boundary_loss: 0.013955 (0.013938) Loss: 0.56959 (0.57757) +2025-09-12,16:23:22 | INFO | Train Epoch: 4 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.44778 (0.56283) Boundary_loss: 0.013928 (0.013938) Loss: 0.46170 (0.57677) +2025-09-12,16:24:28 | INFO | Train Epoch: 4 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.52999 (0.56260) Boundary_loss: 0.013930 (0.013938) Loss: 0.54393 (0.57654) +2025-09-12,16:25:34 | INFO | Train Epoch: 4 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.46945 (0.56197) Boundary_loss: 0.013941 (0.013938) Loss: 0.48339 (0.57590) +2025-09-12,16:26:41 | INFO | Train Epoch: 4 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.47119 (0.56135) Boundary_loss: 0.013937 (0.013938) Loss: 0.48513 (0.57529) +2025-09-12,16:27:47 | INFO | Train Epoch: 4 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.50038 (0.56094) Boundary_loss: 0.013931 (0.013938) Loss: 0.51431 (0.57487) +2025-09-12,16:28:53 | INFO | Train Epoch: 4 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.58626 (0.56111) Boundary_loss: 0.013930 (0.013938) Loss: 0.60019 (0.57504) +2025-09-12,16:29:59 | INFO | Train Epoch: 4 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.54190 (0.56098) Boundary_loss: 0.013926 (0.013937) Loss: 0.55582 (0.57492) +2025-09-12,16:31:05 | INFO | Train Epoch: 4 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.54583 (0.56088) Boundary_loss: 0.013936 (0.013937) Loss: 0.55977 (0.57482) +2025-09-12,16:32:12 | INFO | Train Epoch: 4 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.53735 (0.56072) Boundary_loss: 0.013934 (0.013937) Loss: 0.55128 (0.57466) +2025-09-12,16:33:18 | INFO | Train Epoch: 4 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.55346 (0.56068) Boundary_loss: 0.013934 (0.013937) Loss: 0.56739 (0.57461) +2025-09-12,16:34:24 | INFO | Train Epoch: 4 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.55637 (0.56065) Boundary_loss: 0.013935 (0.013937) Loss: 0.57030 (0.57458) +2025-09-12,16:35:30 | INFO | Train Epoch: 4 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.56400 (0.56067) Boundary_loss: 0.013935 (0.013937) Loss: 0.57793 (0.57461) +2025-09-12,16:36:37 | INFO | Train Epoch: 4 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.53278 (0.56049) Boundary_loss: 0.013926 (0.013937) Loss: 0.54670 (0.57443) +2025-09-12,16:37:43 | INFO | Train Epoch: 4 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.47685 (0.55996) Boundary_loss: 0.013930 (0.013937) Loss: 0.49078 (0.57389) +2025-09-12,16:38:49 | INFO | Train Epoch: 4 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.59715 (0.56019) Boundary_loss: 0.013926 (0.013937) Loss: 0.61108 (0.57413) +2025-09-12,16:39:55 | INFO | Train Epoch: 4 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.54226 (0.56008) Boundary_loss: 0.013924 (0.013937) Loss: 0.55619 (0.57402) +2025-09-12,16:41:01 | INFO | Train Epoch: 4 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.57119 (0.56015) Boundary_loss: 0.013946 (0.013937) Loss: 0.58514 (0.57409) +2025-09-12,16:42:08 | INFO | Train Epoch: 4 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.61314 (0.56048) Boundary_loss: 0.013928 (0.013937) Loss: 0.62706 (0.57442) +2025-09-12,16:43:14 | INFO | Train Epoch: 4 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.55776 (0.56046) Boundary_loss: 0.013922 (0.013937) Loss: 0.57168 (0.57440) +2025-09-12,16:44:20 | INFO | Train Epoch: 4 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.56171 (0.56047) Boundary_loss: 0.013936 (0.013937) Loss: 0.57565 (0.57441) +2025-09-12,16:45:27 | INFO | Train Epoch: 4 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.53114 (0.56029) Boundary_loss: 0.013951 (0.013937) Loss: 0.54509 (0.57423) +2025-09-12,16:46:33 | INFO | Train Epoch: 4 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.57470 (0.56038) Boundary_loss: 0.013927 (0.013937) Loss: 0.58863 (0.57431) +2025-09-12,16:47:39 | INFO | Train Epoch: 4 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.51979 (0.56013) Boundary_loss: 0.013947 (0.013937) Loss: 0.53374 (0.57407) +2025-09-12,16:48:46 | INFO | Train Epoch: 4 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.51860 (0.55988) Boundary_loss: 0.013935 (0.013937) Loss: 0.53254 (0.57382) +2025-09-12,16:49:52 | INFO | Train Epoch: 4 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.57555 (0.55998) Boundary_loss: 0.013935 (0.013937) Loss: 0.58949 (0.57392) +2025-09-12,16:50:58 | INFO | Train Epoch: 4 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.55706 (0.55996) Boundary_loss: 0.013927 (0.013937) Loss: 0.57099 (0.57390) +2025-09-12,16:52:05 | INFO | Train Epoch: 4 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.50651 (0.55965) Boundary_loss: 0.013930 (0.013937) Loss: 0.52044 (0.57358) +2025-09-12,16:53:11 | INFO | Train Epoch: 4 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.56695 (0.55969) Boundary_loss: 0.013931 (0.013937) Loss: 0.58088 (0.57363) +2025-09-12,16:54:17 | INFO | Train Epoch: 4 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.49397 (0.55931) Boundary_loss: 0.013956 (0.013937) Loss: 0.50793 (0.57324) +2025-09-12,16:55:24 | INFO | Train Epoch: 4 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.54725 (0.55924) Boundary_loss: 0.013932 (0.013937) Loss: 0.56118 (0.57317) +2025-09-12,16:56:30 | INFO | Train Epoch: 4 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.57620 (0.55933) Boundary_loss: 0.013934 (0.013937) Loss: 0.59013 (0.57327) +2025-09-12,16:57:36 | INFO | Train Epoch: 4 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.48210 (0.55889) Boundary_loss: 0.013944 (0.013937) Loss: 0.49605 (0.57283) +2025-09-12,16:58:43 | INFO | Train Epoch: 4 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.55328 (0.55886) Boundary_loss: 0.013931 (0.013937) Loss: 0.56721 (0.57280) +2025-09-12,16:59:49 | INFO | Train Epoch: 4 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.72236 (0.55979) Boundary_loss: 0.013939 (0.013937) Loss: 0.73630 (0.57372) +2025-09-12,17:00:55 | INFO | Train Epoch: 4 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.46987 (0.55928) Boundary_loss: 0.013954 (0.013937) Loss: 0.48382 (0.57322) +2025-09-12,17:02:02 | INFO | Train Epoch: 4 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.58759 (0.55944) Boundary_loss: 0.013935 (0.013937) Loss: 0.60153 (0.57338) +2025-09-12,17:03:08 | INFO | Train Epoch: 4 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.57028 (0.55950) Boundary_loss: 0.013928 (0.013937) Loss: 0.58421 (0.57344) +2025-09-12,17:04:14 | INFO | Train Epoch: 4 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.60994 (0.55978) Boundary_loss: 0.013921 (0.013937) Loss: 0.62386 (0.57371) +2025-09-12,17:05:20 | INFO | Train Epoch: 4 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.48040 (0.55934) Boundary_loss: 0.013922 (0.013937) Loss: 0.49433 (0.57328) +2025-09-12,17:06:27 | INFO | Train Epoch: 4 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.47553 (0.55888) Boundary_loss: 0.013925 (0.013937) Loss: 0.48945 (0.57282) +2025-09-12,17:07:33 | INFO | Train Epoch: 4 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.48571 (0.55849) Boundary_loss: 0.013941 (0.013937) Loss: 0.49965 (0.57242) +2025-09-12,17:08:39 | INFO | Train Epoch: 4 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.46621 (0.55799) Boundary_loss: 0.013925 (0.013937) Loss: 0.48013 (0.57192) +2025-09-12,17:09:46 | INFO | Train Epoch: 4 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.52207 (0.55779) Boundary_loss: 0.013958 (0.013937) Loss: 0.53602 (0.57173) +2025-09-12,17:10:52 | INFO | Train Epoch: 4 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.53535 (0.55767) Boundary_loss: 0.013917 (0.013937) Loss: 0.54927 (0.57161) +2025-09-12,17:11:59 | INFO | Train Epoch: 4 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.48317 (0.55728) Boundary_loss: 0.013942 (0.013937) Loss: 0.49711 (0.57121) +2025-09-12,17:13:05 | INFO | Train Epoch: 4 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.49088 (0.55693) Boundary_loss: 0.013942 (0.013937) Loss: 0.50482 (0.57086) +2025-09-12,17:14:11 | INFO | Train Epoch: 4 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.54880 (0.55688) Boundary_loss: 0.013925 (0.013937) Loss: 0.56273 (0.57082) +2025-09-12,17:15:18 | INFO | Train Epoch: 4 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.39866 (0.55605) Boundary_loss: 0.013915 (0.013937) Loss: 0.41258 (0.56999) +2025-09-12,17:16:24 | INFO | Train Epoch: 4 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.47706 (0.55564) Boundary_loss: 0.013930 (0.013937) Loss: 0.49099 (0.56958) +2025-09-12,17:17:30 | INFO | Train Epoch: 4 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.57876 (0.55576) Boundary_loss: 0.013934 (0.013937) Loss: 0.59270 (0.56970) +2025-09-12,17:18:36 | INFO | Train Epoch: 4 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.49738 (0.55546) Boundary_loss: 0.013927 (0.013937) Loss: 0.51130 (0.56940) +2025-09-12,17:19:43 | INFO | Train Epoch: 4 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.55228 (0.55545) Boundary_loss: 0.013924 (0.013936) Loss: 0.56620 (0.56938) +2025-09-12,17:20:49 | INFO | Train Epoch: 4 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.64455 (0.55590) Boundary_loss: 0.013936 (0.013936) Loss: 0.65848 (0.56984) +2025-09-12,17:21:55 | INFO | Train Epoch: 4 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.55618 (0.55590) Boundary_loss: 0.013922 (0.013936) Loss: 0.57010 (0.56984) +2025-09-12,17:23:02 | INFO | Train Epoch: 4 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.51274 (0.55568) Boundary_loss: 0.013932 (0.013936) Loss: 0.52667 (0.56962) +2025-09-12,17:24:08 | INFO | Train Epoch: 4 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.56326 (0.55572) Boundary_loss: 0.013931 (0.013936) Loss: 0.57719 (0.56966) +2025-09-12,17:25:14 | INFO | Train Epoch: 4 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.63975 (0.55614) Boundary_loss: 0.013940 (0.013936) Loss: 0.65369 (0.57008) +2025-09-12,17:26:21 | INFO | Train Epoch: 4 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.60116 (0.55637) Boundary_loss: 0.013925 (0.013936) Loss: 0.61508 (0.57030) +2025-09-12,17:27:27 | INFO | Train Epoch: 4 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.51449 (0.55616) Boundary_loss: 0.013931 (0.013936) Loss: 0.52842 (0.57009) +2025-09-12,17:28:33 | INFO | Train Epoch: 4 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.58609 (0.55631) Boundary_loss: 0.013923 (0.013936) Loss: 0.60001 (0.57024) +2025-09-12,17:29:40 | INFO | Train Epoch: 4 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.47291 (0.55590) Boundary_loss: 0.013938 (0.013936) Loss: 0.48685 (0.56983) +2025-09-12,17:30:46 | INFO | Train Epoch: 4 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.49305 (0.55559) Boundary_loss: 0.013935 (0.013936) Loss: 0.50699 (0.56953) +2025-09-12,17:31:52 | INFO | Train Epoch: 4 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.63366 (0.55597) Boundary_loss: 0.013924 (0.013936) Loss: 0.64759 (0.56991) +2025-09-12,17:32:58 | INFO | Train Epoch: 4 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.56236 (0.55600) Boundary_loss: 0.013937 (0.013936) Loss: 0.57629 (0.56994) +2025-09-12,17:34:05 | INFO | Train Epoch: 4 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.49795 (0.55572) Boundary_loss: 0.013932 (0.013936) Loss: 0.51188 (0.56966) +2025-09-12,17:35:11 | INFO | Train Epoch: 4 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.56412 (0.55576) Boundary_loss: 0.013934 (0.013936) Loss: 0.57806 (0.56970) +2025-09-12,17:36:17 | INFO | Train Epoch: 4 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.45245 (0.55527) Boundary_loss: 0.013931 (0.013936) Loss: 0.46638 (0.56921) +2025-09-12,17:37:24 | INFO | Train Epoch: 4 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.54593 (0.55523) Boundary_loss: 0.013934 (0.013936) Loss: 0.55986 (0.56916) +2025-09-12,17:38:30 | INFO | Train Epoch: 4 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.51301 (0.55503) Boundary_loss: 0.013925 (0.013936) Loss: 0.52694 (0.56896) +2025-09-12,17:39:36 | INFO | Train Epoch: 4 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.55208 (0.55501) Boundary_loss: 0.013919 (0.013936) Loss: 0.56599 (0.56895) +2025-09-12,17:40:43 | INFO | Train Epoch: 4 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.53643 (0.55493) Boundary_loss: 0.013928 (0.013936) Loss: 0.55036 (0.56886) +2025-09-12,17:41:49 | INFO | Train Epoch: 4 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.51763 (0.55475) Boundary_loss: 0.013926 (0.013936) Loss: 0.53155 (0.56869) +2025-09-12,17:42:55 | INFO | Train Epoch: 4 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.58353 (0.55489) Boundary_loss: 0.013927 (0.013936) Loss: 0.59746 (0.56882) +2025-09-12,17:44:02 | INFO | Train Epoch: 4 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.52414 (0.55474) Boundary_loss: 0.013937 (0.013936) Loss: 0.53807 (0.56868) +2025-09-12,17:45:08 | INFO | Train Epoch: 4 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.50829 (0.55453) Boundary_loss: 0.013919 (0.013936) Loss: 0.52221 (0.56847) +2025-09-12,17:46:14 | INFO | Train Epoch: 4 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.39325 (0.55379) Boundary_loss: 0.013954 (0.013936) Loss: 0.40721 (0.56773) +2025-09-12,17:47:21 | INFO | Train Epoch: 4 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.42234 (0.55320) Boundary_loss: 0.013939 (0.013936) Loss: 0.43628 (0.56713) +2025-09-12,17:48:27 | INFO | Train Epoch: 4 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.44997 (0.55273) Boundary_loss: 0.013933 (0.013936) Loss: 0.46390 (0.56667) +2025-09-12,17:49:33 | INFO | Train Epoch: 4 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.53476 (0.55265) Boundary_loss: 0.013923 (0.013936) Loss: 0.54869 (0.56658) +2025-09-12,17:50:40 | INFO | Train Epoch: 4 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.43342 (0.55211) Boundary_loss: 0.013924 (0.013936) Loss: 0.44735 (0.56605) +2025-09-12,17:51:46 | INFO | Train Epoch: 4 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.49630 (0.55186) Boundary_loss: 0.013925 (0.013936) Loss: 0.51022 (0.56580) +2025-09-12,17:52:52 | INFO | Train Epoch: 4 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.49510 (0.55161) Boundary_loss: 0.013923 (0.013936) Loss: 0.50903 (0.56555) +2025-09-12,17:53:59 | INFO | Train Epoch: 4 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.54470 (0.55158) Boundary_loss: 0.013937 (0.013936) Loss: 0.55863 (0.56552) +2025-09-12,17:55:05 | INFO | Train Epoch: 4 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.51898 (0.55144) Boundary_loss: 0.013931 (0.013936) Loss: 0.53291 (0.56537) +2025-09-12,17:56:11 | INFO | Train Epoch: 4 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.52959 (0.55134) Boundary_loss: 0.013925 (0.013936) Loss: 0.54351 (0.56528) +2025-09-12,17:57:18 | INFO | Train Epoch: 4 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.58638 (0.55150) Boundary_loss: 0.013929 (0.013936) Loss: 0.60031 (0.56543) +2025-09-12,17:58:24 | INFO | Train Epoch: 4 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.42093 (0.55093) Boundary_loss: 0.013931 (0.013936) Loss: 0.43486 (0.56486) +2025-09-12,17:59:30 | INFO | Train Epoch: 4 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.58355 (0.55107) Boundary_loss: 0.013934 (0.013936) Loss: 0.59748 (0.56500) +2025-09-12,18:00:37 | INFO | Train Epoch: 4 [11827712/26365952 (45%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.55403 (0.55108) Boundary_loss: 0.013934 (0.013936) Loss: 0.56796 (0.56502) +2025-09-12,18:01:43 | INFO | Train Epoch: 4 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.51381 (0.55092) Boundary_loss: 0.013929 (0.013936) Loss: 0.52774 (0.56486) +2025-09-12,18:02:49 | INFO | Train Epoch: 4 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.46843 (0.55057) Boundary_loss: 0.013931 (0.013935) Loss: 0.48236 (0.56450) +2025-09-12,18:03:56 | INFO | Train Epoch: 4 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.65644 (0.55102) Boundary_loss: 0.013929 (0.013935) Loss: 0.67037 (0.56496) +2025-09-12,18:05:02 | INFO | Train Epoch: 4 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.54242 (0.55098) Boundary_loss: 0.013926 (0.013935) Loss: 0.55635 (0.56492) +2025-09-12,18:06:08 | INFO | Train Epoch: 4 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.54101 (0.55094) Boundary_loss: 0.013924 (0.013935) Loss: 0.55493 (0.56488) +2025-09-12,18:07:15 | INFO | Train Epoch: 4 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.53971 (0.55089) Boundary_loss: 0.013929 (0.013935) Loss: 0.55364 (0.56483) +2025-09-12,18:08:21 | INFO | Train Epoch: 4 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.52831 (0.55080) Boundary_loss: 0.013932 (0.013935) Loss: 0.54225 (0.56473) +2025-09-12,18:09:27 | INFO | Train Epoch: 4 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.58633 (0.55095) Boundary_loss: 0.013930 (0.013935) Loss: 0.60026 (0.56488) +2025-09-12,18:10:33 | INFO | Train Epoch: 4 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.52239 (0.55083) Boundary_loss: 0.013925 (0.013935) Loss: 0.53631 (0.56476) +2025-09-12,18:11:40 | INFO | Train Epoch: 4 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.46523 (0.55048) Boundary_loss: 0.013928 (0.013935) Loss: 0.47916 (0.56441) +2025-09-12,18:12:46 | INFO | Train Epoch: 4 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.54126 (0.55044) Boundary_loss: 0.013927 (0.013935) Loss: 0.55519 (0.56437) +2025-09-12,18:13:53 | INFO | Train Epoch: 4 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.63412 (0.55078) Boundary_loss: 0.013935 (0.013935) Loss: 0.64806 (0.56472) +2025-09-12,18:14:59 | INFO | Train Epoch: 4 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.53431 (0.55071) Boundary_loss: 0.013925 (0.013935) Loss: 0.54824 (0.56465) +2025-09-12,18:16:05 | INFO | Train Epoch: 4 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46168 (0.55035) Boundary_loss: 0.013946 (0.013935) Loss: 0.47563 (0.56429) +2025-09-12,18:17:12 | INFO | Train Epoch: 4 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.55656 (0.55038) Boundary_loss: 0.013932 (0.013935) Loss: 0.57049 (0.56431) +2025-09-12,18:18:18 | INFO | Train Epoch: 4 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.57794 (0.55049) Boundary_loss: 0.013935 (0.013935) Loss: 0.59188 (0.56442) +2025-09-12,18:19:24 | INFO | Train Epoch: 4 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.52518 (0.55039) Boundary_loss: 0.013944 (0.013935) Loss: 0.53912 (0.56432) +2025-09-12,18:20:31 | INFO | Train Epoch: 4 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.49627 (0.55017) Boundary_loss: 0.013921 (0.013935) Loss: 0.51019 (0.56410) +2025-09-12,18:21:37 | INFO | Train Epoch: 4 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.50602 (0.54999) Boundary_loss: 0.013927 (0.013935) Loss: 0.51995 (0.56393) +2025-09-12,18:22:43 | INFO | Train Epoch: 4 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.52367 (0.54989) Boundary_loss: 0.013916 (0.013935) Loss: 0.53759 (0.56382) +2025-09-12,18:23:50 | INFO | Train Epoch: 4 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.50982 (0.54973) Boundary_loss: 0.013923 (0.013935) Loss: 0.52374 (0.56367) +2025-09-12,18:24:56 | INFO | Train Epoch: 4 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.54194 (0.54970) Boundary_loss: 0.013932 (0.013935) Loss: 0.55588 (0.56364) +2025-09-12,18:26:02 | INFO | Train Epoch: 4 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.50327 (0.54952) Boundary_loss: 0.013930 (0.013935) Loss: 0.51720 (0.56345) +2025-09-12,18:27:09 | INFO | Train Epoch: 4 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.50241 (0.54933) Boundary_loss: 0.013936 (0.013935) Loss: 0.51634 (0.56327) +2025-09-12,18:28:15 | INFO | Train Epoch: 4 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.57437 (0.54943) Boundary_loss: 0.013919 (0.013935) Loss: 0.58829 (0.56337) +2025-09-12,18:29:21 | INFO | Train Epoch: 4 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.56189 (0.54948) Boundary_loss: 0.013941 (0.013935) Loss: 0.57583 (0.56341) +2025-09-12,18:30:28 | INFO | Train Epoch: 4 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.50522 (0.54931) Boundary_loss: 0.013940 (0.013935) Loss: 0.51916 (0.56324) +2025-09-12,18:31:34 | INFO | Train Epoch: 4 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.55894 (0.54935) Boundary_loss: 0.013947 (0.013935) Loss: 0.57289 (0.56328) +2025-09-12,18:32:41 | INFO | Train Epoch: 4 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.49108 (0.54912) Boundary_loss: 0.013932 (0.013935) Loss: 0.50501 (0.56306) +2025-09-12,18:33:47 | INFO | Train Epoch: 4 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.53499 (0.54907) Boundary_loss: 0.013916 (0.013935) Loss: 0.54891 (0.56300) +2025-09-12,18:34:53 | INFO | Train Epoch: 4 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.41360 (0.54855) Boundary_loss: 0.013931 (0.013935) Loss: 0.42753 (0.56249) +2025-09-12,18:36:00 | INFO | Train Epoch: 4 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.58869 (0.54871) Boundary_loss: 0.013938 (0.013935) Loss: 0.60263 (0.56264) +2025-09-12,18:37:06 | INFO | Train Epoch: 4 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.53840 (0.54867) Boundary_loss: 0.013933 (0.013935) Loss: 0.55234 (0.56260) +2025-09-12,18:38:12 | INFO | Train Epoch: 4 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.48771 (0.54844) Boundary_loss: 0.013939 (0.013935) Loss: 0.50165 (0.56237) +2025-09-12,18:39:19 | INFO | Train Epoch: 4 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.49528 (0.54824) Boundary_loss: 0.013924 (0.013935) Loss: 0.50920 (0.56217) +2025-09-12,18:40:25 | INFO | Train Epoch: 4 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.55250 (0.54825) Boundary_loss: 0.013921 (0.013935) Loss: 0.56642 (0.56219) +2025-09-12,18:41:31 | INFO | Train Epoch: 4 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.53893 (0.54822) Boundary_loss: 0.013923 (0.013935) Loss: 0.55285 (0.56215) +2025-09-12,18:42:38 | INFO | Train Epoch: 4 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.52455 (0.54813) Boundary_loss: 0.013921 (0.013935) Loss: 0.53847 (0.56207) +2025-09-12,18:43:44 | INFO | Train Epoch: 4 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.43731 (0.54772) Boundary_loss: 0.013927 (0.013935) Loss: 0.45124 (0.56166) +2025-09-12,18:44:50 | INFO | Train Epoch: 4 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.49182 (0.54752) Boundary_loss: 0.013929 (0.013935) Loss: 0.50575 (0.56145) +2025-09-12,18:45:57 | INFO | Train Epoch: 4 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.50749 (0.54737) Boundary_loss: 0.013932 (0.013935) Loss: 0.52142 (0.56131) +2025-09-12,18:47:03 | INFO | Train Epoch: 4 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.49528 (0.54718) Boundary_loss: 0.013924 (0.013935) Loss: 0.50920 (0.56112) +2025-09-12,18:48:09 | INFO | Train Epoch: 4 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.58424 (0.54732) Boundary_loss: 0.013932 (0.013935) Loss: 0.59817 (0.56125) +2025-09-12,18:49:16 | INFO | Train Epoch: 4 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.52185 (0.54722) Boundary_loss: 0.013929 (0.013935) Loss: 0.53577 (0.56116) +2025-09-12,18:50:22 | INFO | Train Epoch: 4 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.54435 (0.54721) Boundary_loss: 0.013922 (0.013935) Loss: 0.55828 (0.56115) +2025-09-12,18:51:28 | INFO | Train Epoch: 4 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.51039 (0.54708) Boundary_loss: 0.013942 (0.013935) Loss: 0.52433 (0.56102) +2025-09-12,18:52:35 | INFO | Train Epoch: 4 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.50217 (0.54692) Boundary_loss: 0.013933 (0.013935) Loss: 0.51611 (0.56085) +2025-09-12,18:53:41 | INFO | Train Epoch: 4 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.55913 (0.54696) Boundary_loss: 0.013923 (0.013935) Loss: 0.57305 (0.56090) +2025-09-12,18:54:47 | INFO | Train Epoch: 4 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.49719 (0.54679) Boundary_loss: 0.013934 (0.013935) Loss: 0.51113 (0.56072) +2025-09-12,18:55:54 | INFO | Train Epoch: 4 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.49348 (0.54660) Boundary_loss: 0.013931 (0.013935) Loss: 0.50741 (0.56053) +2025-09-12,18:57:00 | INFO | Train Epoch: 4 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.58685 (0.54674) Boundary_loss: 0.013924 (0.013934) Loss: 0.60078 (0.56067) +2025-09-12,18:58:06 | INFO | Train Epoch: 4 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.50324 (0.54659) Boundary_loss: 0.013921 (0.013934) Loss: 0.51716 (0.56052) +2025-09-12,18:59:13 | INFO | Train Epoch: 4 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.47629 (0.54634) Boundary_loss: 0.013929 (0.013934) Loss: 0.49022 (0.56027) +2025-09-12,19:00:19 | INFO | Train Epoch: 4 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.52814 (0.54628) Boundary_loss: 0.013921 (0.013934) Loss: 0.54206 (0.56021) +2025-09-12,19:01:25 | INFO | Train Epoch: 4 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.46878 (0.54601) Boundary_loss: 0.013923 (0.013934) Loss: 0.48270 (0.55994) +2025-09-12,19:02:32 | INFO | Train Epoch: 4 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.52778 (0.54594) Boundary_loss: 0.013950 (0.013934) Loss: 0.54173 (0.55988) +2025-09-12,19:03:38 | INFO | Train Epoch: 4 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.52687 (0.54588) Boundary_loss: 0.013936 (0.013934) Loss: 0.54080 (0.55981) +2025-09-12,19:04:44 | INFO | Train Epoch: 4 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.51128 (0.54576) Boundary_loss: 0.013941 (0.013934) Loss: 0.52522 (0.55969) +2025-09-12,19:05:51 | INFO | Train Epoch: 4 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.48004 (0.54553) Boundary_loss: 0.013935 (0.013934) Loss: 0.49397 (0.55947) +2025-09-12,19:06:57 | INFO | Train Epoch: 4 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.63130 (0.54583) Boundary_loss: 0.013930 (0.013934) Loss: 0.64523 (0.55976) +2025-09-12,19:08:03 | INFO | Train Epoch: 4 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.50889 (0.54570) Boundary_loss: 0.013923 (0.013934) Loss: 0.52281 (0.55963) +2025-09-12,19:09:10 | INFO | Train Epoch: 4 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.48917 (0.54551) Boundary_loss: 0.013943 (0.013934) Loss: 0.50311 (0.55944) +2025-09-12,19:10:16 | INFO | Train Epoch: 4 [15053312/26365952 (57%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.56404 (0.54557) Boundary_loss: 0.013942 (0.013934) Loss: 0.57799 (0.55950) +2025-09-12,19:11:22 | INFO | Train Epoch: 4 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.43438 (0.54519) Boundary_loss: 0.013927 (0.013934) Loss: 0.44831 (0.55913) +2025-09-12,19:12:29 | INFO | Train Epoch: 4 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.34893 (0.54453) Boundary_loss: 0.013924 (0.013934) Loss: 0.36285 (0.55847) +2025-09-12,19:13:35 | INFO | Train Epoch: 4 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.53601 (0.54450) Boundary_loss: 0.013924 (0.013934) Loss: 0.54993 (0.55844) +2025-09-12,19:14:41 | INFO | Train Epoch: 4 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.63299 (0.54480) Boundary_loss: 0.013924 (0.013934) Loss: 0.64692 (0.55873) +2025-09-12,19:15:48 | INFO | Train Epoch: 4 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.54217 (0.54479) Boundary_loss: 0.013923 (0.013934) Loss: 0.55609 (0.55873) +2025-09-12,19:16:54 | INFO | Train Epoch: 4 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.50870 (0.54467) Boundary_loss: 0.013940 (0.013934) Loss: 0.52264 (0.55861) +2025-09-12,19:18:01 | INFO | Train Epoch: 4 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.49082 (0.54449) Boundary_loss: 0.013925 (0.013934) Loss: 0.50475 (0.55843) +2025-09-12,19:19:07 | INFO | Train Epoch: 4 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.42194 (0.54409) Boundary_loss: 0.013933 (0.013934) Loss: 0.43587 (0.55802) +2025-09-12,19:20:13 | INFO | Train Epoch: 4 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.56247 (0.54415) Boundary_loss: 0.013939 (0.013934) Loss: 0.57641 (0.55808) +2025-09-12,19:21:19 | INFO | Train Epoch: 4 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.46499 (0.54389) Boundary_loss: 0.013925 (0.013934) Loss: 0.47891 (0.55782) +2025-09-12,19:22:26 | INFO | Train Epoch: 4 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.51171 (0.54378) Boundary_loss: 0.013929 (0.013934) Loss: 0.52564 (0.55772) +2025-09-12,19:23:32 | INFO | Train Epoch: 4 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.56363 (0.54385) Boundary_loss: 0.013929 (0.013934) Loss: 0.57756 (0.55778) +2025-09-12,19:24:39 | INFO | Train Epoch: 4 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.46465 (0.54359) Boundary_loss: 0.013942 (0.013934) Loss: 0.47860 (0.55753) +2025-09-12,19:25:45 | INFO | Train Epoch: 4 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.48776 (0.54341) Boundary_loss: 0.013937 (0.013934) Loss: 0.50169 (0.55735) +2025-09-12,19:26:51 | INFO | Train Epoch: 4 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.55208 (0.54344) Boundary_loss: 0.013934 (0.013934) Loss: 0.56601 (0.55737) +2025-09-12,19:27:57 | INFO | Train Epoch: 4 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.59885 (0.54362) Boundary_loss: 0.013931 (0.013934) Loss: 0.61278 (0.55755) +2025-09-12,19:29:04 | INFO | Train Epoch: 4 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.55951 (0.54367) Boundary_loss: 0.013932 (0.013934) Loss: 0.57344 (0.55760) +2025-09-12,19:30:10 | INFO | Train Epoch: 4 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.52144 (0.54360) Boundary_loss: 0.013955 (0.013934) Loss: 0.53539 (0.55753) +2025-09-12,19:31:17 | INFO | Train Epoch: 4 [16026112/26365952 (61%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.45201 (0.54331) Boundary_loss: 0.013957 (0.013934) Loss: 0.46596 (0.55724) +2025-09-12,19:32:23 | INFO | Train Epoch: 4 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.59737 (0.54348) Boundary_loss: 0.013926 (0.013934) Loss: 0.61130 (0.55741) +2025-09-12,19:33:29 | INFO | Train Epoch: 4 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.52045 (0.54340) Boundary_loss: 0.013931 (0.013934) Loss: 0.53438 (0.55734) +2025-09-12,19:34:36 | INFO | Train Epoch: 4 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.51576 (0.54332) Boundary_loss: 0.013919 (0.013934) Loss: 0.52968 (0.55725) +2025-09-12,19:35:42 | INFO | Train Epoch: 4 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.49351 (0.54316) Boundary_loss: 0.013923 (0.013934) Loss: 0.50743 (0.55710) +2025-09-12,19:36:48 | INFO | Train Epoch: 4 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.48011 (0.54296) Boundary_loss: 0.013929 (0.013934) Loss: 0.49404 (0.55690) +2025-09-12,19:37:55 | INFO | Train Epoch: 4 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.50681 (0.54285) Boundary_loss: 0.013941 (0.013934) Loss: 0.52075 (0.55678) +2025-09-12,19:39:01 | INFO | Train Epoch: 4 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.53260 (0.54282) Boundary_loss: 0.013926 (0.013934) Loss: 0.54653 (0.55675) +2025-09-12,19:40:07 | INFO | Train Epoch: 4 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.53650 (0.54280) Boundary_loss: 0.013943 (0.013934) Loss: 0.55044 (0.55673) +2025-09-12,19:41:14 | INFO | Train Epoch: 4 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.52794 (0.54275) Boundary_loss: 0.013961 (0.013934) Loss: 0.54190 (0.55669) +2025-09-12,19:42:20 | INFO | Train Epoch: 4 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.61135 (0.54296) Boundary_loss: 0.013922 (0.013934) Loss: 0.62528 (0.55690) +2025-09-12,19:43:26 | INFO | Train Epoch: 4 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.53600 (0.54294) Boundary_loss: 0.013932 (0.013934) Loss: 0.54993 (0.55688) +2025-09-12,19:44:33 | INFO | Train Epoch: 4 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.51584 (0.54286) Boundary_loss: 0.013921 (0.013934) Loss: 0.52976 (0.55679) +2025-09-12,19:45:39 | INFO | Train Epoch: 4 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.63852 (0.54315) Boundary_loss: 0.013927 (0.013934) Loss: 0.65245 (0.55709) +2025-09-12,19:46:45 | INFO | Train Epoch: 4 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.54756 (0.54317) Boundary_loss: 0.013920 (0.013934) Loss: 0.56148 (0.55710) +2025-09-12,19:47:52 | INFO | Train Epoch: 4 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.55788 (0.54321) Boundary_loss: 0.013917 (0.013934) Loss: 0.57180 (0.55714) +2025-09-12,19:48:58 | INFO | Train Epoch: 4 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.51572 (0.54313) Boundary_loss: 0.013925 (0.013934) Loss: 0.52964 (0.55706) +2025-09-12,19:50:04 | INFO | Train Epoch: 4 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.63625 (0.54341) Boundary_loss: 0.013917 (0.013934) Loss: 0.65016 (0.55734) +2025-09-12,19:51:11 | INFO | Train Epoch: 4 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.53611 (0.54339) Boundary_loss: 0.013932 (0.013934) Loss: 0.55004 (0.55732) +2025-09-12,19:52:17 | INFO | Train Epoch: 4 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.57777 (0.54349) Boundary_loss: 0.013930 (0.013934) Loss: 0.59170 (0.55742) +2025-09-12,19:53:23 | INFO | Train Epoch: 4 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.57247 (0.54358) Boundary_loss: 0.013925 (0.013934) Loss: 0.58640 (0.55751) +2025-09-12,19:54:30 | INFO | Train Epoch: 4 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.54787 (0.54359) Boundary_loss: 0.013921 (0.013934) Loss: 0.56179 (0.55752) +2025-09-12,19:55:36 | INFO | Train Epoch: 4 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.47022 (0.54337) Boundary_loss: 0.013928 (0.013934) Loss: 0.48415 (0.55730) +2025-09-12,19:56:42 | INFO | Train Epoch: 4 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.54230 (0.54337) Boundary_loss: 0.013948 (0.013934) Loss: 0.55625 (0.55730) +2025-09-12,19:57:49 | INFO | Train Epoch: 4 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.51176 (0.54327) Boundary_loss: 0.013929 (0.013934) Loss: 0.52569 (0.55721) +2025-09-12,19:58:55 | INFO | Train Epoch: 4 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.56658 (0.54334) Boundary_loss: 0.013938 (0.013934) Loss: 0.58052 (0.55728) +2025-09-12,20:00:01 | INFO | Train Epoch: 4 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.55717 (0.54338) Boundary_loss: 0.013921 (0.013934) Loss: 0.57109 (0.55732) +2025-09-12,20:01:08 | INFO | Train Epoch: 4 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.52594 (0.54333) Boundary_loss: 0.013927 (0.013934) Loss: 0.53986 (0.55727) +2025-09-12,20:02:14 | INFO | Train Epoch: 4 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.54543 (0.54334) Boundary_loss: 0.013933 (0.013934) Loss: 0.55937 (0.55727) +2025-09-12,20:03:21 | INFO | Train Epoch: 4 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.55219 (0.54336) Boundary_loss: 0.013925 (0.013934) Loss: 0.56612 (0.55730) +2025-09-12,20:04:27 | INFO | Train Epoch: 4 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.51687 (0.54329) Boundary_loss: 0.013943 (0.013934) Loss: 0.53082 (0.55722) +2025-09-12,20:05:33 | INFO | Train Epoch: 4 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.52094 (0.54322) Boundary_loss: 0.013922 (0.013934) Loss: 0.53486 (0.55716) +2025-09-12,20:06:40 | INFO | Train Epoch: 4 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.56963 (0.54330) Boundary_loss: 0.013916 (0.013934) Loss: 0.58354 (0.55723) +2025-09-12,20:07:46 | INFO | Train Epoch: 4 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.54093 (0.54329) Boundary_loss: 0.013922 (0.013934) Loss: 0.55485 (0.55723) +2025-09-12,20:08:52 | INFO | Train Epoch: 4 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.53646 (0.54327) Boundary_loss: 0.013929 (0.013934) Loss: 0.55039 (0.55721) +2025-09-12,20:09:59 | INFO | Train Epoch: 4 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.56078 (0.54332) Boundary_loss: 0.013931 (0.013934) Loss: 0.57471 (0.55726) +2025-09-12,20:11:05 | INFO | Train Epoch: 4 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.51119 (0.54323) Boundary_loss: 0.013922 (0.013934) Loss: 0.52511 (0.55716) +2025-09-12,20:12:11 | INFO | Train Epoch: 4 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.54869 (0.54325) Boundary_loss: 0.013918 (0.013934) Loss: 0.56261 (0.55718) +2025-09-12,20:13:18 | INFO | Train Epoch: 4 [17971712/26365952 (68%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.49182 (0.54310) Boundary_loss: 0.013923 (0.013934) Loss: 0.50574 (0.55703) +2025-09-12,20:14:24 | INFO | Train Epoch: 4 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.48131 (0.54293) Boundary_loss: 0.013929 (0.013934) Loss: 0.49524 (0.55686) +2025-09-12,20:15:30 | INFO | Train Epoch: 4 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.59107 (0.54306) Boundary_loss: 0.013936 (0.013934) Loss: 0.60500 (0.55700) +2025-09-12,20:16:37 | INFO | Train Epoch: 4 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.42928 (0.54274) Boundary_loss: 0.013922 (0.013934) Loss: 0.44320 (0.55667) +2025-09-12,20:17:43 | INFO | Train Epoch: 4 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.48153 (0.54257) Boundary_loss: 0.013931 (0.013934) Loss: 0.49546 (0.55650) +2025-09-12,20:18:50 | INFO | Train Epoch: 4 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.55782 (0.54261) Boundary_loss: 0.013922 (0.013934) Loss: 0.57174 (0.55655) +2025-09-12,20:19:56 | INFO | Train Epoch: 4 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.51118 (0.54252) Boundary_loss: 0.013928 (0.013934) Loss: 0.52510 (0.55646) +2025-09-12,20:21:02 | INFO | Train Epoch: 4 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.40369 (0.54214) Boundary_loss: 0.013932 (0.013934) Loss: 0.41762 (0.55607) +2025-09-12,20:22:09 | INFO | Train Epoch: 4 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.57298 (0.54222) Boundary_loss: 0.013935 (0.013934) Loss: 0.58691 (0.55616) +2025-09-12,20:23:15 | INFO | Train Epoch: 4 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.56982 (0.54230) Boundary_loss: 0.013924 (0.013934) Loss: 0.58374 (0.55623) +2025-09-12,20:24:21 | INFO | Train Epoch: 4 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.50532 (0.54220) Boundary_loss: 0.013925 (0.013934) Loss: 0.51924 (0.55613) +2025-09-12,20:25:28 | INFO | Train Epoch: 4 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.47495 (0.54201) Boundary_loss: 0.013921 (0.013933) Loss: 0.48887 (0.55595) +2025-09-12,20:26:34 | INFO | Train Epoch: 4 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.54457 (0.54202) Boundary_loss: 0.013925 (0.013933) Loss: 0.55849 (0.55595) +2025-09-12,20:27:40 | INFO | Train Epoch: 4 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.50697 (0.54192) Boundary_loss: 0.013924 (0.013933) Loss: 0.52090 (0.55586) +2025-09-12,20:28:47 | INFO | Train Epoch: 4 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.47418 (0.54174) Boundary_loss: 0.013924 (0.013933) Loss: 0.48810 (0.55567) +2025-09-12,20:29:53 | INFO | Train Epoch: 4 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.52505 (0.54169) Boundary_loss: 0.013929 (0.013933) Loss: 0.53898 (0.55563) +2025-09-12,20:30:59 | INFO | Train Epoch: 4 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.47671 (0.54152) Boundary_loss: 0.013923 (0.013933) Loss: 0.49063 (0.55545) +2025-09-12,20:32:06 | INFO | Train Epoch: 4 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.51841 (0.54145) Boundary_loss: 0.013923 (0.013933) Loss: 0.53233 (0.55539) +2025-09-12,20:33:12 | INFO | Train Epoch: 4 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.50586 (0.54136) Boundary_loss: 0.013971 (0.013933) Loss: 0.51983 (0.55529) +2025-09-12,20:34:19 | INFO | Train Epoch: 4 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.46788 (0.54116) Boundary_loss: 0.013929 (0.013933) Loss: 0.48181 (0.55509) +2025-09-12,20:35:25 | INFO | Train Epoch: 4 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.51531 (0.54109) Boundary_loss: 0.013938 (0.013933) Loss: 0.52924 (0.55502) +2025-09-12,20:36:31 | INFO | Train Epoch: 4 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.56602 (0.54116) Boundary_loss: 0.013935 (0.013933) Loss: 0.57995 (0.55509) +2025-09-12,20:37:38 | INFO | Train Epoch: 4 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.49369 (0.54103) Boundary_loss: 0.013913 (0.013933) Loss: 0.50761 (0.55496) +2025-09-12,20:38:44 | INFO | Train Epoch: 4 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.54665 (0.54104) Boundary_loss: 0.013947 (0.013933) Loss: 0.56060 (0.55498) +2025-09-12,20:39:50 | INFO | Train Epoch: 4 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.42744 (0.54074) Boundary_loss: 0.013926 (0.013933) Loss: 0.44137 (0.55468) +2025-09-12,20:40:57 | INFO | Train Epoch: 4 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.60023 (0.54090) Boundary_loss: 0.013925 (0.013933) Loss: 0.61416 (0.55483) +2025-09-12,20:42:03 | INFO | Train Epoch: 4 [19302912/26365952 (73%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.59088 (0.54103) Boundary_loss: 0.013929 (0.013933) Loss: 0.60481 (0.55497) +2025-09-12,20:43:09 | INFO | Train Epoch: 4 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.46969 (0.54084) Boundary_loss: 0.013919 (0.013933) Loss: 0.48361 (0.55478) +2025-09-12,20:44:16 | INFO | Train Epoch: 4 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.42787 (0.54055) Boundary_loss: 0.013935 (0.013933) Loss: 0.44181 (0.55448) +2025-09-12,20:45:22 | INFO | Train Epoch: 4 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.56459 (0.54061) Boundary_loss: 0.013929 (0.013933) Loss: 0.57852 (0.55454) +2025-09-12,20:46:29 | INFO | Train Epoch: 4 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.51045 (0.54053) Boundary_loss: 0.013915 (0.013933) Loss: 0.52436 (0.55446) +2025-09-12,20:47:35 | INFO | Train Epoch: 4 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.46571 (0.54034) Boundary_loss: 0.013922 (0.013933) Loss: 0.47963 (0.55427) +2025-09-12,20:48:41 | INFO | Train Epoch: 4 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.61024 (0.54052) Boundary_loss: 0.013933 (0.013933) Loss: 0.62417 (0.55445) +2025-09-12,20:49:48 | INFO | Train Epoch: 4 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.48712 (0.54038) Boundary_loss: 0.013926 (0.013933) Loss: 0.50105 (0.55431) +2025-09-12,20:50:54 | INFO | Train Epoch: 4 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.57021 (0.54046) Boundary_loss: 0.013937 (0.013933) Loss: 0.58415 (0.55439) +2025-09-12,20:52:00 | INFO | Train Epoch: 4 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.53603 (0.54044) Boundary_loss: 0.013929 (0.013933) Loss: 0.54996 (0.55438) +2025-09-12,20:53:07 | INFO | Train Epoch: 4 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.51903 (0.54039) Boundary_loss: 0.013919 (0.013933) Loss: 0.53295 (0.55432) +2025-09-12,20:54:13 | INFO | Train Epoch: 4 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.57417 (0.54048) Boundary_loss: 0.013933 (0.013933) Loss: 0.58810 (0.55441) +2025-09-12,20:55:19 | INFO | Train Epoch: 4 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.50130 (0.54038) Boundary_loss: 0.013923 (0.013933) Loss: 0.51523 (0.55431) +2025-09-12,20:56:26 | INFO | Train Epoch: 4 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.49161 (0.54025) Boundary_loss: 0.013941 (0.013933) Loss: 0.50555 (0.55418) +2025-09-12,20:57:32 | INFO | Train Epoch: 4 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.44964 (0.54002) Boundary_loss: 0.013922 (0.013933) Loss: 0.46356 (0.55395) +2025-09-12,20:58:38 | INFO | Train Epoch: 4 [20070912/26365952 (76%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.49977 (0.53992) Boundary_loss: 0.013928 (0.013933) Loss: 0.51370 (0.55385) +2025-09-12,20:59:45 | INFO | Train Epoch: 4 [20122112/26365952 (76%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.56442 (0.53998) Boundary_loss: 0.013930 (0.013933) Loss: 0.57835 (0.55391) +2025-09-12,21:00:51 | INFO | Train Epoch: 4 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.54773 (0.54000) Boundary_loss: 0.013922 (0.013933) Loss: 0.56165 (0.55393) +2025-09-12,21:01:58 | INFO | Train Epoch: 4 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.45881 (0.53979) Boundary_loss: 0.013932 (0.013933) Loss: 0.47274 (0.55373) +2025-09-12,21:03:04 | INFO | Train Epoch: 4 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.45440 (0.53958) Boundary_loss: 0.013939 (0.013933) Loss: 0.46834 (0.55351) +2025-09-12,21:04:10 | INFO | Train Epoch: 4 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.41976 (0.53928) Boundary_loss: 0.013924 (0.013933) Loss: 0.43368 (0.55321) +2025-09-12,21:05:17 | INFO | Train Epoch: 4 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.57851 (0.53938) Boundary_loss: 0.013922 (0.013933) Loss: 0.59244 (0.55331) +2025-09-12,21:06:23 | INFO | Train Epoch: 4 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.48994 (0.53925) Boundary_loss: 0.013946 (0.013933) Loss: 0.50388 (0.55319) +2025-09-12,21:07:30 | INFO | Train Epoch: 4 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.52478 (0.53922) Boundary_loss: 0.013928 (0.013933) Loss: 0.53870 (0.55315) +2025-09-12,21:08:36 | INFO | Train Epoch: 4 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.47163 (0.53905) Boundary_loss: 0.013936 (0.013933) Loss: 0.48557 (0.55298) +2025-09-12,21:09:43 | INFO | Train Epoch: 4 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.50525 (0.53896) Boundary_loss: 0.013936 (0.013933) Loss: 0.51919 (0.55290) +2025-09-12,21:10:49 | INFO | Train Epoch: 4 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.48656 (0.53884) Boundary_loss: 0.013921 (0.013933) Loss: 0.50048 (0.55277) +2025-09-12,21:11:55 | INFO | Train Epoch: 4 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.51183 (0.53877) Boundary_loss: 0.013923 (0.013933) Loss: 0.52575 (0.55270) +2025-09-12,21:13:02 | INFO | Train Epoch: 4 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.63397 (0.53900) Boundary_loss: 0.013930 (0.013933) Loss: 0.64790 (0.55294) +2025-09-12,21:14:08 | INFO | Train Epoch: 4 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.56984 (0.53908) Boundary_loss: 0.013935 (0.013933) Loss: 0.58377 (0.55301) +2025-09-12,21:15:14 | INFO | Train Epoch: 4 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.48653 (0.53895) Boundary_loss: 0.013924 (0.013933) Loss: 0.50045 (0.55288) +2025-09-12,21:16:21 | INFO | Train Epoch: 4 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.40414 (0.53862) Boundary_loss: 0.013922 (0.013933) Loss: 0.41806 (0.55255) +2025-09-12,21:17:27 | INFO | Train Epoch: 4 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.41856 (0.53833) Boundary_loss: 0.013918 (0.013933) Loss: 0.43248 (0.55226) +2025-09-12,21:18:33 | INFO | Train Epoch: 4 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.53751 (0.53833) Boundary_loss: 0.013954 (0.013933) Loss: 0.55147 (0.55226) +2025-09-12,21:19:40 | INFO | Train Epoch: 4 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.46762 (0.53815) Boundary_loss: 0.013922 (0.013933) Loss: 0.48154 (0.55209) +2025-09-12,21:20:46 | INFO | Train Epoch: 4 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.52444 (0.53812) Boundary_loss: 0.013926 (0.013933) Loss: 0.53837 (0.55205) +2025-09-12,21:21:53 | INFO | Train Epoch: 4 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.49112 (0.53801) Boundary_loss: 0.013935 (0.013933) Loss: 0.50506 (0.55194) +2025-09-12,21:22:59 | INFO | Train Epoch: 4 [21197312/26365952 (80%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.49746 (0.53791) Boundary_loss: 0.013933 (0.013933) Loss: 0.51139 (0.55184) +2025-09-12,21:24:05 | INFO | Train Epoch: 4 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.48427 (0.53778) Boundary_loss: 0.013920 (0.013933) Loss: 0.49819 (0.55171) +2025-09-12,21:25:12 | INFO | Train Epoch: 4 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.53266 (0.53777) Boundary_loss: 0.013936 (0.013933) Loss: 0.54660 (0.55170) +2025-09-12,21:26:18 | INFO | Train Epoch: 4 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.47183 (0.53761) Boundary_loss: 0.013931 (0.013933) Loss: 0.48576 (0.55154) +2025-09-12,21:27:24 | INFO | Train Epoch: 4 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.46756 (0.53744) Boundary_loss: 0.013929 (0.013933) Loss: 0.48149 (0.55138) +2025-09-12,21:28:31 | INFO | Train Epoch: 4 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.53726 (0.53744) Boundary_loss: 0.013929 (0.013933) Loss: 0.55119 (0.55138) +2025-09-12,21:29:37 | INFO | Train Epoch: 4 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.59096 (0.53757) Boundary_loss: 0.013918 (0.013933) Loss: 0.60488 (0.55150) +2025-09-12,21:30:43 | INFO | Train Epoch: 4 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.64190 (0.53782) Boundary_loss: 0.013938 (0.013933) Loss: 0.65584 (0.55175) +2025-09-12,21:31:50 | INFO | Train Epoch: 4 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.54623 (0.53784) Boundary_loss: 0.013925 (0.013933) Loss: 0.56016 (0.55177) +2025-09-12,21:32:56 | INFO | Train Epoch: 4 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.45899 (0.53765) Boundary_loss: 0.013921 (0.013933) Loss: 0.47291 (0.55158) +2025-09-12,21:34:02 | INFO | Train Epoch: 4 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.53743 (0.53765) Boundary_loss: 0.013923 (0.013933) Loss: 0.55135 (0.55158) +2025-09-12,21:35:09 | INFO | Train Epoch: 4 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.43759 (0.53742) Boundary_loss: 0.013938 (0.013933) Loss: 0.45153 (0.55135) +2025-09-12,21:36:15 | INFO | Train Epoch: 4 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.56462 (0.53748) Boundary_loss: 0.013939 (0.013933) Loss: 0.57856 (0.55141) +2025-09-12,21:37:21 | INFO | Train Epoch: 4 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.49993 (0.53739) Boundary_loss: 0.013924 (0.013933) Loss: 0.51385 (0.55132) +2025-09-12,21:38:28 | INFO | Train Epoch: 4 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.42953 (0.53714) Boundary_loss: 0.013915 (0.013933) Loss: 0.44344 (0.55107) +2025-09-12,21:39:34 | INFO | Train Epoch: 4 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.57863 (0.53724) Boundary_loss: 0.013924 (0.013933) Loss: 0.59255 (0.55117) +2025-09-12,21:40:40 | INFO | Train Epoch: 4 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.55338 (0.53727) Boundary_loss: 0.013925 (0.013933) Loss: 0.56730 (0.55121) +2025-09-12,21:41:47 | INFO | Train Epoch: 4 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.45927 (0.53709) Boundary_loss: 0.013920 (0.013933) Loss: 0.47319 (0.55103) +2025-09-12,21:42:53 | INFO | Train Epoch: 4 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.59501 (0.53723) Boundary_loss: 0.013924 (0.013933) Loss: 0.60894 (0.55116) +2025-09-12,21:43:59 | INFO | Train Epoch: 4 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.42822 (0.53698) Boundary_loss: 0.013924 (0.013933) Loss: 0.44214 (0.55091) +2025-09-12,21:45:06 | INFO | Train Epoch: 4 [22221312/26365952 (84%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.43836 (0.53675) Boundary_loss: 0.013917 (0.013933) Loss: 0.45227 (0.55068) +2025-09-12,21:46:12 | INFO | Train Epoch: 4 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.50550 (0.53668) Boundary_loss: 0.013923 (0.013933) Loss: 0.51942 (0.55061) +2025-09-12,21:47:18 | INFO | Train Epoch: 4 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.53876 (0.53668) Boundary_loss: 0.013933 (0.013933) Loss: 0.55269 (0.55062) +2025-09-12,21:48:25 | INFO | Train Epoch: 4 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.51322 (0.53663) Boundary_loss: 0.013924 (0.013933) Loss: 0.52714 (0.55056) +2025-09-12,21:49:31 | INFO | Train Epoch: 4 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.51602 (0.53658) Boundary_loss: 0.013928 (0.013933) Loss: 0.52995 (0.55051) +2025-09-12,21:50:37 | INFO | Train Epoch: 4 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.51050 (0.53652) Boundary_loss: 0.013932 (0.013933) Loss: 0.52443 (0.55046) +2025-09-12,21:51:44 | INFO | Train Epoch: 4 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.47847 (0.53639) Boundary_loss: 0.013914 (0.013933) Loss: 0.49239 (0.55032) +2025-09-12,21:52:50 | INFO | Train Epoch: 4 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.45397 (0.53620) Boundary_loss: 0.013924 (0.013933) Loss: 0.46790 (0.55014) +2025-09-12,21:53:57 | INFO | Train Epoch: 4 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.45579 (0.53602) Boundary_loss: 0.013924 (0.013933) Loss: 0.46971 (0.54996) +2025-09-12,21:55:03 | INFO | Train Epoch: 4 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.48626 (0.53591) Boundary_loss: 0.013940 (0.013933) Loss: 0.50020 (0.54984) +2025-09-12,21:56:09 | INFO | Train Epoch: 4 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.50138 (0.53583) Boundary_loss: 0.013917 (0.013932) Loss: 0.51529 (0.54977) +2025-09-12,21:57:16 | INFO | Train Epoch: 4 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.58548 (0.53594) Boundary_loss: 0.013924 (0.013932) Loss: 0.59940 (0.54988) +2025-09-12,21:58:22 | INFO | Train Epoch: 4 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.52727 (0.53593) Boundary_loss: 0.013927 (0.013932) Loss: 0.54119 (0.54986) +2025-09-12,21:59:28 | INFO | Train Epoch: 4 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.51921 (0.53589) Boundary_loss: 0.013913 (0.013932) Loss: 0.53312 (0.54982) +2025-09-12,22:00:35 | INFO | Train Epoch: 4 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.45765 (0.53571) Boundary_loss: 0.013921 (0.013932) Loss: 0.47157 (0.54965) +2025-09-12,22:01:41 | INFO | Train Epoch: 4 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.50632 (0.53565) Boundary_loss: 0.013929 (0.013932) Loss: 0.52025 (0.54958) +2025-09-12,22:02:47 | INFO | Train Epoch: 4 [23040512/26365952 (87%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.52860 (0.53563) Boundary_loss: 0.013932 (0.013932) Loss: 0.54254 (0.54957) +2025-09-12,22:03:54 | INFO | Train Epoch: 4 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.60949 (0.53580) Boundary_loss: 0.013919 (0.013932) Loss: 0.62341 (0.54973) +2025-09-12,22:05:00 | INFO | Train Epoch: 4 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.56941 (0.53587) Boundary_loss: 0.013924 (0.013932) Loss: 0.58333 (0.54980) +2025-09-12,22:06:06 | INFO | Train Epoch: 4 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.45261 (0.53569) Boundary_loss: 0.013916 (0.013932) Loss: 0.46653 (0.54962) +2025-09-12,22:07:13 | INFO | Train Epoch: 4 [23245312/26365952 (88%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.53813 (0.53569) Boundary_loss: 0.013927 (0.013932) Loss: 0.55206 (0.54962) +2025-09-12,22:08:19 | INFO | Train Epoch: 4 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.43601 (0.53547) Boundary_loss: 0.013926 (0.013932) Loss: 0.44994 (0.54941) +2025-09-12,22:09:25 | INFO | Train Epoch: 4 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.60142 (0.53562) Boundary_loss: 0.013927 (0.013932) Loss: 0.61535 (0.54955) +2025-09-12,22:10:32 | INFO | Train Epoch: 4 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.52350 (0.53559) Boundary_loss: 0.013923 (0.013932) Loss: 0.53742 (0.54952) +2025-09-12,22:11:38 | INFO | Train Epoch: 4 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.48778 (0.53549) Boundary_loss: 0.013924 (0.013932) Loss: 0.50170 (0.54942) +2025-09-12,22:12:44 | INFO | Train Epoch: 4 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.52176 (0.53546) Boundary_loss: 0.013924 (0.013932) Loss: 0.53569 (0.54939) +2025-09-12,22:13:51 | INFO | Train Epoch: 4 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.52220 (0.53543) Boundary_loss: 0.013922 (0.013932) Loss: 0.53612 (0.54936) +2025-09-12,22:14:57 | INFO | Train Epoch: 4 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.53579 (0.53543) Boundary_loss: 0.013930 (0.013932) Loss: 0.54972 (0.54936) +2025-09-12,22:16:04 | INFO | Train Epoch: 4 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.53232 (0.53542) Boundary_loss: 0.013920 (0.013932) Loss: 0.54624 (0.54936) +2025-09-12,22:17:10 | INFO | Train Epoch: 4 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.54488 (0.53544) Boundary_loss: 0.013926 (0.013932) Loss: 0.55881 (0.54938) +2025-09-12,22:18:16 | INFO | Train Epoch: 4 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.56829 (0.53551) Boundary_loss: 0.013923 (0.013932) Loss: 0.58222 (0.54945) +2025-09-12,22:19:23 | INFO | Train Epoch: 4 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.57975 (0.53561) Boundary_loss: 0.013918 (0.013932) Loss: 0.59367 (0.54954) +2025-09-12,22:20:29 | INFO | Train Epoch: 4 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.51521 (0.53557) Boundary_loss: 0.013919 (0.013932) Loss: 0.52913 (0.54950) +2025-09-12,22:21:35 | INFO | Train Epoch: 4 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.54892 (0.53559) Boundary_loss: 0.013915 (0.013932) Loss: 0.56284 (0.54953) +2025-09-12,22:22:42 | INFO | Train Epoch: 4 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.41502 (0.53534) Boundary_loss: 0.013918 (0.013932) Loss: 0.42894 (0.54927) +2025-09-12,22:23:48 | INFO | Train Epoch: 4 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.57774 (0.53543) Boundary_loss: 0.013925 (0.013932) Loss: 0.59167 (0.54936) +2025-09-12,22:24:54 | INFO | Train Epoch: 4 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.54136 (0.53544) Boundary_loss: 0.013944 (0.013932) Loss: 0.55530 (0.54937) +2025-09-12,22:26:01 | INFO | Train Epoch: 4 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.52279 (0.53541) Boundary_loss: 0.013920 (0.013932) Loss: 0.53671 (0.54934) +2025-09-12,22:27:07 | INFO | Train Epoch: 4 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.49194 (0.53532) Boundary_loss: 0.013944 (0.013932) Loss: 0.50588 (0.54925) +2025-09-12,22:28:13 | INFO | Train Epoch: 4 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.55344 (0.53536) Boundary_loss: 0.013929 (0.013932) Loss: 0.56737 (0.54929) +2025-09-12,22:29:20 | INFO | Train Epoch: 4 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.57560 (0.53544) Boundary_loss: 0.013922 (0.013932) Loss: 0.58953 (0.54938) +2025-09-12,22:30:26 | INFO | Train Epoch: 4 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.50535 (0.53538) Boundary_loss: 0.013927 (0.013932) Loss: 0.51928 (0.54931) +2025-09-12,22:31:32 | INFO | Train Epoch: 4 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.45828 (0.53522) Boundary_loss: 0.013932 (0.013932) Loss: 0.47222 (0.54915) +2025-09-12,22:32:39 | INFO | Train Epoch: 4 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.48460 (0.53511) Boundary_loss: 0.013940 (0.013932) Loss: 0.49854 (0.54904) +2025-09-12,22:33:45 | INFO | Train Epoch: 4 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.44753 (0.53493) Boundary_loss: 0.013924 (0.013932) Loss: 0.46145 (0.54886) +2025-09-12,22:34:51 | INFO | Train Epoch: 4 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.45255 (0.53476) Boundary_loss: 0.013922 (0.013932) Loss: 0.46647 (0.54869) +2025-09-12,22:35:58 | INFO | Train Epoch: 4 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.48422 (0.53465) Boundary_loss: 0.013930 (0.013932) Loss: 0.49815 (0.54859) +2025-09-12,22:37:04 | INFO | Train Epoch: 4 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.49835 (0.53458) Boundary_loss: 0.013923 (0.013932) Loss: 0.51227 (0.54851) +2025-09-12,22:38:10 | INFO | Train Epoch: 4 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.59008 (0.53469) Boundary_loss: 0.013929 (0.013932) Loss: 0.60401 (0.54862) +2025-09-12,22:39:17 | INFO | Train Epoch: 4 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.41116 (0.53444) Boundary_loss: 0.013924 (0.013932) Loss: 0.42508 (0.54837) +2025-09-12,22:40:23 | INFO | Train Epoch: 4 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.59484 (0.53456) Boundary_loss: 0.013936 (0.013932) Loss: 0.60878 (0.54849) +2025-09-12,22:41:29 | INFO | Train Epoch: 4 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.59544 (0.53469) Boundary_loss: 0.013924 (0.013932) Loss: 0.60937 (0.54862) +2025-09-12,22:42:36 | INFO | Train Epoch: 4 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.60456 (0.53483) Boundary_loss: 0.013922 (0.013932) Loss: 0.61849 (0.54876) +2025-09-12,22:43:42 | INFO | Train Epoch: 4 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.42900 (0.53461) Boundary_loss: 0.013954 (0.013932) Loss: 0.44296 (0.54855) +2025-09-12,22:44:48 | INFO | Train Epoch: 4 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.46261 (0.53447) Boundary_loss: 0.013925 (0.013932) Loss: 0.47653 (0.54840) +2025-09-12,22:45:54 | INFO | Train Epoch: 4 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.60763 (0.53462) Boundary_loss: 0.013925 (0.013932) Loss: 0.62156 (0.54855) +2025-09-12,22:47:01 | INFO | Train Epoch: 4 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.56955 (0.53469) Boundary_loss: 0.013931 (0.013932) Loss: 0.58348 (0.54862) +2025-09-12,22:48:07 | INFO | Train Epoch: 4 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.43478 (0.53448) Boundary_loss: 0.013929 (0.013932) Loss: 0.44871 (0.54842) +2025-09-12,22:49:14 | INFO | Train Epoch: 4 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.48460 (0.53438) Boundary_loss: 0.013933 (0.013932) Loss: 0.49854 (0.54832) +2025-09-12,22:50:20 | INFO | Train Epoch: 4 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.55267 (0.53442) Boundary_loss: 0.013932 (0.013932) Loss: 0.56660 (0.54835) +2025-09-12,22:51:26 | INFO | Train Epoch: 4 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.52585 (0.53440) Boundary_loss: 0.013931 (0.013932) Loss: 0.53978 (0.54833) +2025-09-12,22:52:33 | INFO | Train Epoch: 4 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.51389 (0.53436) Boundary_loss: 0.013921 (0.013932) Loss: 0.52781 (0.54829) +2025-09-12,22:53:39 | INFO | Train Epoch: 4 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.49298 (0.53428) Boundary_loss: 0.013922 (0.013932) Loss: 0.50690 (0.54821) +2025-09-12,22:54:45 | INFO | Train Epoch: 4 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.52420 (0.53426) Boundary_loss: 0.013942 (0.013932) Loss: 0.53814 (0.54819) +2025-09-12,22:55:51 | INFO | Train Epoch: 4 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.50461 (0.53420) Boundary_loss: 0.013923 (0.013932) Loss: 0.51853 (0.54813) +2025-09-12,22:56:58 | INFO | Train Epoch: 4 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.54158 (0.53421) Boundary_loss: 0.013920 (0.013932) Loss: 0.55550 (0.54815) +2025-09-12,22:58:04 | INFO | Train Epoch: 4 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.54941 (0.53424) Boundary_loss: 0.013926 (0.013932) Loss: 0.56334 (0.54818) +2025-09-12,22:59:10 | INFO | Train Epoch: 4 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.49524 (0.53417) Boundary_loss: 0.013919 (0.013932) Loss: 0.50916 (0.54810) +2025-09-12,23:00:17 | INFO | Train Epoch: 4 [25702912/26365952 (97%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.51177 (0.53412) Boundary_loss: 0.013930 (0.013932) Loss: 0.52570 (0.54805) +2025-09-12,23:01:23 | INFO | Train Epoch: 4 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.45040 (0.53396) Boundary_loss: 0.013941 (0.013932) Loss: 0.46434 (0.54789) +2025-09-12,23:02:29 | INFO | Train Epoch: 4 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.48219 (0.53385) Boundary_loss: 0.013935 (0.013932) Loss: 0.49612 (0.54778) +2025-09-12,23:03:36 | INFO | Train Epoch: 4 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.46118 (0.53371) Boundary_loss: 0.013923 (0.013932) Loss: 0.47510 (0.54764) +2025-09-12,23:04:42 | INFO | Train Epoch: 4 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.45535 (0.53355) Boundary_loss: 0.013924 (0.013932) Loss: 0.46927 (0.54749) +2025-09-12,23:05:48 | INFO | Train Epoch: 4 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.42835 (0.53335) Boundary_loss: 0.013933 (0.013932) Loss: 0.44228 (0.54728) +2025-09-12,23:06:55 | INFO | Train Epoch: 4 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.46525 (0.53321) Boundary_loss: 0.013931 (0.013932) Loss: 0.47918 (0.54715) +2025-09-12,23:08:01 | INFO | Train Epoch: 4 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.51633 (0.53318) Boundary_loss: 0.013931 (0.013932) Loss: 0.53026 (0.54711) +2025-09-12,23:09:07 | INFO | Train Epoch: 4 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.57811 (0.53327) Boundary_loss: 0.013937 (0.013932) Loss: 0.59204 (0.54720) +2025-09-12,23:10:14 | INFO | Train Epoch: 4 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.43817 (0.53308) Boundary_loss: 0.013936 (0.013932) Loss: 0.45211 (0.54701) +2025-09-12,23:11:20 | INFO | Train Epoch: 4 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.54642 (0.53311) Boundary_loss: 0.013934 (0.013932) Loss: 0.56035 (0.54704) +2025-09-12,23:12:26 | INFO | Train Epoch: 4 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.56707 (0.53317) Boundary_loss: 0.013926 (0.013932) Loss: 0.58100 (0.54711) +2025-09-12,23:13:33 | INFO | Train Epoch: 4 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.49142 (0.53309) Boundary_loss: 0.013926 (0.013932) Loss: 0.50534 (0.54703) +2025-09-12,23:14:36 | INFO | Train Epoch: 4 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.49901 (0.53303) Boundary_loss: 0.013943 (0.013932) Loss: 0.51295 (0.54696) +2025-09-12,23:14:36 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,23:14:36 | INFO | [Epoch 4] Average Step Time: 0.666s | Average GPU Memory: 31.1 GB +2025-09-12,23:14:36 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,23:14:36 | INFO | Starting zero-shot imagenet. +2025-09-12,23:14:36 | INFO | Building zero-shot classifier +2025-09-12,23:14:45 | INFO | Using classifier +2025-09-12,23:16:19 | INFO | Finished zero-shot imagenet. +2025-09-12,23:16:19 | INFO | Eval Epoch: 5 imagenet-zeroshot-val-top1: 0.2484 imagenet-zeroshot-val-top5: 0.4940 +2025-09-12,23:16:20 | INFO | Start epoch 5 +2025-09-12,23:16:23 | INFO | Train Epoch: 5 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.48044 (0.48044) Boundary_loss: 0.013935 (0.013935) Loss: 0.49438 (0.49438) +2025-09-12,23:17:29 | INFO | Train Epoch: 5 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.45419 (0.46732) Boundary_loss: 0.013930 (0.013932) Loss: 0.46812 (0.48125) +2025-09-12,23:18:35 | INFO | Train Epoch: 5 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.45085 (0.46183) Boundary_loss: 0.013923 (0.013929) Loss: 0.46477 (0.47576) +2025-09-12,23:19:41 | INFO | Train Epoch: 5 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.50735 (0.47321) Boundary_loss: 0.013937 (0.013931) Loss: 0.52129 (0.48714) +2025-09-12,23:20:47 | INFO | Train Epoch: 5 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.37159 (0.45288) Boundary_loss: 0.013932 (0.013931) Loss: 0.38552 (0.46682) +2025-09-12,23:21:53 | INFO | Train Epoch: 5 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.48581 (0.45837) Boundary_loss: 0.013916 (0.013929) Loss: 0.49973 (0.47230) +2025-09-12,23:22:59 | INFO | Train Epoch: 5 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.42889 (0.45416) Boundary_loss: 0.013934 (0.013930) Loss: 0.44282 (0.46809) +2025-09-12,23:24:05 | INFO | Train Epoch: 5 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.59037 (0.47119) Boundary_loss: 0.013925 (0.013929) Loss: 0.60429 (0.48511) +2025-09-12,23:25:12 | INFO | Train Epoch: 5 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.43317 (0.46696) Boundary_loss: 0.013926 (0.013929) Loss: 0.44710 (0.48089) +2025-09-12,23:26:18 | INFO | Train Epoch: 5 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.48775 (0.46904) Boundary_loss: 0.013919 (0.013928) Loss: 0.50167 (0.48297) +2025-09-12,23:27:24 | INFO | Train Epoch: 5 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.52084 (0.47375) Boundary_loss: 0.013919 (0.013927) Loss: 0.53476 (0.48768) +2025-09-12,23:28:30 | INFO | Train Epoch: 5 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.50444 (0.47631) Boundary_loss: 0.013931 (0.013927) Loss: 0.51837 (0.49024) +2025-09-12,23:29:36 | INFO | Train Epoch: 5 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.40199 (0.47059) Boundary_loss: 0.013920 (0.013927) Loss: 0.41591 (0.48452) +2025-09-12,23:30:42 | INFO | Train Epoch: 5 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.47554 (0.47094) Boundary_loss: 0.013925 (0.013927) Loss: 0.48946 (0.48487) +2025-09-12,23:31:48 | INFO | Train Epoch: 5 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.49270 (0.47239) Boundary_loss: 0.013913 (0.013926) Loss: 0.50662 (0.48632) +2025-09-12,23:32:54 | INFO | Train Epoch: 5 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.49685 (0.47392) Boundary_loss: 0.013929 (0.013926) Loss: 0.51078 (0.48785) +2025-09-12,23:34:01 | INFO | Train Epoch: 5 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.43689 (0.47174) Boundary_loss: 0.013942 (0.013927) Loss: 0.45083 (0.48567) +2025-09-12,23:35:07 | INFO | Train Epoch: 5 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.37471 (0.46635) Boundary_loss: 0.013923 (0.013927) Loss: 0.38863 (0.48028) +2025-09-12,23:36:13 | INFO | Train Epoch: 5 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.45443 (0.46573) Boundary_loss: 0.013926 (0.013927) Loss: 0.46836 (0.47965) +2025-09-12,23:37:19 | INFO | Train Epoch: 5 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.45203 (0.46504) Boundary_loss: 0.013916 (0.013926) Loss: 0.46595 (0.47897) +2025-09-12,23:38:25 | INFO | Train Epoch: 5 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.38390 (0.46118) Boundary_loss: 0.013936 (0.013927) Loss: 0.39784 (0.47510) +2025-09-12,23:39:31 | INFO | Train Epoch: 5 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.40297 (0.45853) Boundary_loss: 0.013936 (0.013927) Loss: 0.41691 (0.47246) +2025-09-12,23:40:37 | INFO | Train Epoch: 5 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.48213 (0.45956) Boundary_loss: 0.013923 (0.013927) Loss: 0.49606 (0.47349) +2025-09-12,23:41:44 | INFO | Train Epoch: 5 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.44440 (0.45893) Boundary_loss: 0.013921 (0.013927) Loss: 0.45832 (0.47285) +2025-09-12,23:42:50 | INFO | Train Epoch: 5 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.41497 (0.45717) Boundary_loss: 0.013923 (0.013926) Loss: 0.42889 (0.47109) +2025-09-12,23:43:56 | INFO | Train Epoch: 5 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.42223 (0.45582) Boundary_loss: 0.013925 (0.013926) Loss: 0.43616 (0.46975) +2025-09-12,23:45:02 | INFO | Train Epoch: 5 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.43916 (0.45521) Boundary_loss: 0.013917 (0.013926) Loss: 0.45308 (0.46913) +2025-09-12,23:46:08 | INFO | Train Epoch: 5 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.39954 (0.45322) Boundary_loss: 0.013929 (0.013926) Loss: 0.41347 (0.46715) +2025-09-12,23:47:14 | INFO | Train Epoch: 5 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.47967 (0.45413) Boundary_loss: 0.013937 (0.013926) Loss: 0.49361 (0.46806) +2025-09-12,23:48:21 | INFO | Train Epoch: 5 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.50820 (0.45593) Boundary_loss: 0.013919 (0.013926) Loss: 0.52212 (0.46986) +2025-09-12,23:49:27 | INFO | Train Epoch: 5 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.49930 (0.45733) Boundary_loss: 0.013917 (0.013926) Loss: 0.51322 (0.47126) +2025-09-12,23:50:33 | INFO | Train Epoch: 5 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.49794 (0.45860) Boundary_loss: 0.013933 (0.013926) Loss: 0.51187 (0.47253) +2025-09-12,23:51:39 | INFO | Train Epoch: 5 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.45446 (0.45848) Boundary_loss: 0.013917 (0.013926) Loss: 0.46837 (0.47240) +2025-09-12,23:52:45 | INFO | Train Epoch: 5 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.51758 (0.46021) Boundary_loss: 0.013935 (0.013926) Loss: 0.53151 (0.47414) +2025-09-12,23:53:51 | INFO | Train Epoch: 5 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.47404 (0.46061) Boundary_loss: 0.013918 (0.013926) Loss: 0.48796 (0.47454) +2025-09-12,23:54:57 | INFO | Train Epoch: 5 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.53297 (0.46262) Boundary_loss: 0.013932 (0.013926) Loss: 0.54690 (0.47655) +2025-09-12,23:56:04 | INFO | Train Epoch: 5 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.52667 (0.46435) Boundary_loss: 0.013926 (0.013926) Loss: 0.54059 (0.47828) +2025-09-12,23:57:10 | INFO | Train Epoch: 5 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.41924 (0.46316) Boundary_loss: 0.013931 (0.013926) Loss: 0.43317 (0.47709) +2025-09-12,23:58:16 | INFO | Train Epoch: 5 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.55034 (0.46540) Boundary_loss: 0.013922 (0.013926) Loss: 0.56426 (0.47932) +2025-09-12,23:59:22 | INFO | Train Epoch: 5 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.45851 (0.46523) Boundary_loss: 0.013920 (0.013926) Loss: 0.47243 (0.47915) +2025-09-13,00:00:28 | INFO | Train Epoch: 5 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.33708 (0.46210) Boundary_loss: 0.013927 (0.013926) Loss: 0.35101 (0.47603) +2025-09-13,00:01:34 | INFO | Train Epoch: 5 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.40491 (0.46074) Boundary_loss: 0.013914 (0.013926) Loss: 0.41882 (0.47466) +2025-09-13,00:02:40 | INFO | Train Epoch: 5 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.39775 (0.45927) Boundary_loss: 0.013919 (0.013925) Loss: 0.41167 (0.47320) +2025-09-13,00:03:47 | INFO | Train Epoch: 5 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.60730 (0.46264) Boundary_loss: 0.013927 (0.013926) Loss: 0.62122 (0.47656) +2025-09-13,00:04:53 | INFO | Train Epoch: 5 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.41473 (0.46157) Boundary_loss: 0.013920 (0.013925) Loss: 0.42865 (0.47550) +2025-09-13,00:05:59 | INFO | Train Epoch: 5 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.45885 (0.46151) Boundary_loss: 0.013919 (0.013925) Loss: 0.47277 (0.47544) +2025-09-13,00:07:05 | INFO | Train Epoch: 5 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.51771 (0.46271) Boundary_loss: 0.013920 (0.013925) Loss: 0.53163 (0.47664) +2025-09-13,00:08:11 | INFO | Train Epoch: 5 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.37382 (0.46086) Boundary_loss: 0.013926 (0.013925) Loss: 0.38775 (0.47478) +2025-09-13,00:09:18 | INFO | Train Epoch: 5 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.56152 (0.46291) Boundary_loss: 0.013919 (0.013925) Loss: 0.57544 (0.47684) +2025-09-13,00:10:24 | INFO | Train Epoch: 5 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.46522 (0.46296) Boundary_loss: 0.013918 (0.013925) Loss: 0.47914 (0.47688) +2025-09-13,00:11:30 | INFO | Train Epoch: 5 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.46444 (0.46299) Boundary_loss: 0.013917 (0.013925) Loss: 0.47835 (0.47691) +2025-09-13,00:12:36 | INFO | Train Epoch: 5 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.45127 (0.46276) Boundary_loss: 0.013921 (0.013925) Loss: 0.46520 (0.47669) +2025-09-13,00:13:42 | INFO | Train Epoch: 5 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.49345 (0.46334) Boundary_loss: 0.013921 (0.013925) Loss: 0.50737 (0.47727) +2025-09-13,00:14:48 | INFO | Train Epoch: 5 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.44889 (0.46307) Boundary_loss: 0.013916 (0.013924) Loss: 0.46281 (0.47700) +2025-09-13,00:15:55 | INFO | Train Epoch: 5 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.37271 (0.46143) Boundary_loss: 0.013925 (0.013924) Loss: 0.38663 (0.47536) +2025-09-13,00:17:01 | INFO | Train Epoch: 5 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.39280 (0.46021) Boundary_loss: 0.013917 (0.013924) Loss: 0.40671 (0.47413) +2025-09-13,00:18:07 | INFO | Train Epoch: 5 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.52551 (0.46135) Boundary_loss: 0.013910 (0.013924) Loss: 0.53942 (0.47528) +2025-09-13,00:19:13 | INFO | Train Epoch: 5 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.58048 (0.46340) Boundary_loss: 0.013919 (0.013924) Loss: 0.59440 (0.47733) +2025-09-13,00:20:19 | INFO | Train Epoch: 5 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.46525 (0.46344) Boundary_loss: 0.013925 (0.013924) Loss: 0.47918 (0.47736) +2025-09-13,00:21:26 | INFO | Train Epoch: 5 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.44902 (0.46320) Boundary_loss: 0.013922 (0.013924) Loss: 0.46294 (0.47712) +2025-09-13,00:22:32 | INFO | Train Epoch: 5 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.45242 (0.46302) Boundary_loss: 0.013926 (0.013924) Loss: 0.46634 (0.47694) +2025-09-13,00:23:38 | INFO | Train Epoch: 5 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.42475 (0.46240) Boundary_loss: 0.013919 (0.013924) Loss: 0.43867 (0.47633) +2025-09-13,00:24:44 | INFO | Train Epoch: 5 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.49001 (0.46284) Boundary_loss: 0.013914 (0.013924) Loss: 0.50392 (0.47676) +2025-09-13,00:25:50 | INFO | Train Epoch: 5 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.53315 (0.46394) Boundary_loss: 0.013916 (0.013924) Loss: 0.54707 (0.47786) +2025-09-13,00:26:56 | INFO | Train Epoch: 5 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.41079 (0.46312) Boundary_loss: 0.013921 (0.013924) Loss: 0.42472 (0.47704) +2025-09-13,00:28:02 | INFO | Train Epoch: 5 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.46746 (0.46319) Boundary_loss: 0.013926 (0.013924) Loss: 0.48139 (0.47711) +2025-09-13,00:29:09 | INFO | Train Epoch: 5 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.36824 (0.46177) Boundary_loss: 0.013916 (0.013924) Loss: 0.38215 (0.47569) +2025-09-13,00:30:15 | INFO | Train Epoch: 5 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.47540 (0.46197) Boundary_loss: 0.013918 (0.013923) Loss: 0.48932 (0.47589) +2025-09-13,00:31:21 | INFO | Train Epoch: 5 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.47418 (0.46215) Boundary_loss: 0.013924 (0.013923) Loss: 0.48810 (0.47607) +2025-09-13,00:32:27 | INFO | Train Epoch: 5 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.46822 (0.46223) Boundary_loss: 0.013930 (0.013924) Loss: 0.48215 (0.47616) +2025-09-13,00:33:33 | INFO | Train Epoch: 5 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.43031 (0.46178) Boundary_loss: 0.013922 (0.013924) Loss: 0.44424 (0.47571) +2025-09-13,00:34:40 | INFO | Train Epoch: 5 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.39942 (0.46092) Boundary_loss: 0.013926 (0.013924) Loss: 0.41335 (0.47484) +2025-09-13,00:35:46 | INFO | Train Epoch: 5 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.42358 (0.46041) Boundary_loss: 0.013927 (0.013924) Loss: 0.43750 (0.47433) +2025-09-13,00:36:52 | INFO | Train Epoch: 5 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.38779 (0.45943) Boundary_loss: 0.013916 (0.013923) Loss: 0.40170 (0.47335) +2025-09-13,00:37:58 | INFO | Train Epoch: 5 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.39219 (0.45853) Boundary_loss: 0.013916 (0.013923) Loss: 0.40611 (0.47245) +2025-09-13,00:39:04 | INFO | Train Epoch: 5 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.39558 (0.45770) Boundary_loss: 0.013921 (0.013923) Loss: 0.40950 (0.47162) +2025-09-13,00:40:11 | INFO | Train Epoch: 5 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.43209 (0.45737) Boundary_loss: 0.013924 (0.013923) Loss: 0.44602 (0.47129) +2025-09-13,00:41:17 | INFO | Train Epoch: 5 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.55194 (0.45858) Boundary_loss: 0.013925 (0.013923) Loss: 0.56587 (0.47250) +2025-09-13,00:42:23 | INFO | Train Epoch: 5 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.51278 (0.45927) Boundary_loss: 0.013924 (0.013923) Loss: 0.52670 (0.47319) +2025-09-13,00:43:29 | INFO | Train Epoch: 5 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.45358 (0.45920) Boundary_loss: 0.013913 (0.013923) Loss: 0.46749 (0.47312) +2025-09-13,00:44:35 | INFO | Train Epoch: 5 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.50672 (0.45978) Boundary_loss: 0.013919 (0.013923) Loss: 0.52063 (0.47371) +2025-09-13,00:45:42 | INFO | Train Epoch: 5 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.47238 (0.45994) Boundary_loss: 0.013918 (0.013923) Loss: 0.48630 (0.47386) +2025-09-13,00:46:48 | INFO | Train Epoch: 5 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.36259 (0.45876) Boundary_loss: 0.013916 (0.013923) Loss: 0.37650 (0.47269) +2025-09-13,00:47:54 | INFO | Train Epoch: 5 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.40724 (0.45815) Boundary_loss: 0.013921 (0.013923) Loss: 0.42117 (0.47207) +2025-09-13,00:49:00 | INFO | Train Epoch: 5 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.47839 (0.45839) Boundary_loss: 0.013925 (0.013923) Loss: 0.49232 (0.47231) +2025-09-13,00:50:06 | INFO | Train Epoch: 5 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.52226 (0.45913) Boundary_loss: 0.013922 (0.013923) Loss: 0.53618 (0.47305) +2025-09-13,00:51:13 | INFO | Train Epoch: 5 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.42679 (0.45876) Boundary_loss: 0.013916 (0.013923) Loss: 0.44071 (0.47268) +2025-09-13,00:52:19 | INFO | Train Epoch: 5 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.34294 (0.45744) Boundary_loss: 0.013930 (0.013923) Loss: 0.35687 (0.47137) +2025-09-13,00:53:25 | INFO | Train Epoch: 5 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.43594 (0.45720) Boundary_loss: 0.013934 (0.013923) Loss: 0.44987 (0.47112) +2025-09-13,00:54:31 | INFO | Train Epoch: 5 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.42291 (0.45682) Boundary_loss: 0.013918 (0.013923) Loss: 0.43683 (0.47074) +2025-09-13,00:55:37 | INFO | Train Epoch: 5 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.45604 (0.45681) Boundary_loss: 0.013924 (0.013923) Loss: 0.46996 (0.47073) +2025-09-13,00:56:43 | INFO | Train Epoch: 5 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.47044 (0.45696) Boundary_loss: 0.013921 (0.013923) Loss: 0.48436 (0.47088) +2025-09-13,00:57:50 | INFO | Train Epoch: 5 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.49065 (0.45732) Boundary_loss: 0.013916 (0.013923) Loss: 0.50457 (0.47124) +2025-09-13,00:58:56 | INFO | Train Epoch: 5 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.50240 (0.45780) Boundary_loss: 0.013924 (0.013923) Loss: 0.51632 (0.47172) +2025-09-13,01:00:02 | INFO | Train Epoch: 5 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.37601 (0.45694) Boundary_loss: 0.013925 (0.013923) Loss: 0.38994 (0.47086) +2025-09-13,01:01:08 | INFO | Train Epoch: 5 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.39030 (0.45625) Boundary_loss: 0.013922 (0.013923) Loss: 0.40423 (0.47017) +2025-09-13,01:02:15 | INFO | Train Epoch: 5 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.37565 (0.45542) Boundary_loss: 0.013926 (0.013923) Loss: 0.38957 (0.46934) +2025-09-13,01:03:21 | INFO | Train Epoch: 5 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.48852 (0.45575) Boundary_loss: 0.013921 (0.013923) Loss: 0.50244 (0.46968) +2025-09-13,01:04:27 | INFO | Train Epoch: 5 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.48870 (0.45609) Boundary_loss: 0.013921 (0.013923) Loss: 0.50262 (0.47001) +2025-09-13,01:05:33 | INFO | Train Epoch: 5 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.57097 (0.45723) Boundary_loss: 0.013917 (0.013923) Loss: 0.58489 (0.47116) +2025-09-13,01:06:39 | INFO | Train Epoch: 5 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.47763 (0.45744) Boundary_loss: 0.013945 (0.013923) Loss: 0.49157 (0.47136) +2025-09-13,01:07:46 | INFO | Train Epoch: 5 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.41978 (0.45707) Boundary_loss: 0.013939 (0.013923) Loss: 0.43372 (0.47099) +2025-09-13,01:08:52 | INFO | Train Epoch: 5 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.42310 (0.45674) Boundary_loss: 0.013914 (0.013923) Loss: 0.43701 (0.47066) +2025-09-13,01:09:58 | INFO | Train Epoch: 5 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.50905 (0.45724) Boundary_loss: 0.013925 (0.013923) Loss: 0.52298 (0.47116) +2025-09-13,01:11:04 | INFO | Train Epoch: 5 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.47985 (0.45746) Boundary_loss: 0.013912 (0.013923) Loss: 0.49376 (0.47138) +2025-09-13,01:12:10 | INFO | Train Epoch: 5 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.35889 (0.45653) Boundary_loss: 0.013919 (0.013923) Loss: 0.37281 (0.47045) +2025-09-13,01:13:17 | INFO | Train Epoch: 5 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.41170 (0.45611) Boundary_loss: 0.013915 (0.013923) Loss: 0.42562 (0.47003) +2025-09-13,01:14:23 | INFO | Train Epoch: 5 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.36520 (0.45527) Boundary_loss: 0.013919 (0.013923) Loss: 0.37912 (0.46919) +2025-09-13,01:15:29 | INFO | Train Epoch: 5 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.45849 (0.45529) Boundary_loss: 0.013919 (0.013923) Loss: 0.47241 (0.46922) +2025-09-13,01:16:35 | INFO | Train Epoch: 5 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.55195 (0.45617) Boundary_loss: 0.013917 (0.013923) Loss: 0.56587 (0.47010) +2025-09-13,01:17:41 | INFO | Train Epoch: 5 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.40480 (0.45571) Boundary_loss: 0.013924 (0.013923) Loss: 0.41873 (0.46963) +2025-09-13,01:18:48 | INFO | Train Epoch: 5 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.53552 (0.45642) Boundary_loss: 0.013915 (0.013923) Loss: 0.54944 (0.47035) +2025-09-13,01:19:54 | INFO | Train Epoch: 5 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.37292 (0.45568) Boundary_loss: 0.013918 (0.013923) Loss: 0.38684 (0.46961) +2025-09-13,01:21:00 | INFO | Train Epoch: 5 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.47700 (0.45587) Boundary_loss: 0.013920 (0.013923) Loss: 0.49092 (0.46979) +2025-09-13,01:22:06 | INFO | Train Epoch: 5 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.50539 (0.45630) Boundary_loss: 0.013916 (0.013923) Loss: 0.51931 (0.47022) +2025-09-13,01:23:12 | INFO | Train Epoch: 5 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.45005 (0.45625) Boundary_loss: 0.013920 (0.013923) Loss: 0.46397 (0.47017) +2025-09-13,01:24:19 | INFO | Train Epoch: 5 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.45427 (0.45623) Boundary_loss: 0.013925 (0.013923) Loss: 0.46820 (0.47015) +2025-09-13,01:25:25 | INFO | Train Epoch: 5 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.40412 (0.45579) Boundary_loss: 0.013936 (0.013923) Loss: 0.41806 (0.46971) +2025-09-13,01:26:31 | INFO | Train Epoch: 5 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.43289 (0.45560) Boundary_loss: 0.013935 (0.013923) Loss: 0.44683 (0.46952) +2025-09-13,01:27:37 | INFO | Train Epoch: 5 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.43794 (0.45545) Boundary_loss: 0.013915 (0.013923) Loss: 0.45185 (0.46937) +2025-09-13,01:28:43 | INFO | Train Epoch: 5 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.43727 (0.45530) Boundary_loss: 0.013918 (0.013923) Loss: 0.45119 (0.46922) +2025-09-13,01:29:50 | INFO | Train Epoch: 5 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.48063 (0.45551) Boundary_loss: 0.013922 (0.013923) Loss: 0.49455 (0.46943) +2025-09-13,01:30:56 | INFO | Train Epoch: 5 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.43253 (0.45532) Boundary_loss: 0.013923 (0.013923) Loss: 0.44646 (0.46924) +2025-09-13,01:32:02 | INFO | Train Epoch: 5 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.49724 (0.45566) Boundary_loss: 0.013916 (0.013923) Loss: 0.51115 (0.46958) +2025-09-13,01:33:08 | INFO | Train Epoch: 5 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.48629 (0.45590) Boundary_loss: 0.013919 (0.013923) Loss: 0.50020 (0.46983) +2025-09-13,01:34:14 | INFO | Train Epoch: 5 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.39114 (0.45539) Boundary_loss: 0.013921 (0.013923) Loss: 0.40506 (0.46931) +2025-09-13,01:35:21 | INFO | Train Epoch: 5 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.51847 (0.45589) Boundary_loss: 0.013918 (0.013923) Loss: 0.53238 (0.46981) +2025-09-13,01:36:27 | INFO | Train Epoch: 5 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.50378 (0.45626) Boundary_loss: 0.013937 (0.013923) Loss: 0.51772 (0.47018) +2025-09-13,01:37:33 | INFO | Train Epoch: 5 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.52965 (0.45683) Boundary_loss: 0.013923 (0.013923) Loss: 0.54358 (0.47075) +2025-09-13,01:38:39 | INFO | Train Epoch: 5 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.50802 (0.45722) Boundary_loss: 0.013922 (0.013923) Loss: 0.52195 (0.47115) +2025-09-13,01:39:46 | INFO | Train Epoch: 5 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.44445 (0.45713) Boundary_loss: 0.013916 (0.013923) Loss: 0.45837 (0.47105) +2025-09-13,01:40:52 | INFO | Train Epoch: 5 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.45774 (0.45713) Boundary_loss: 0.013921 (0.013923) Loss: 0.47166 (0.47105) +2025-09-13,01:41:58 | INFO | Train Epoch: 5 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.41652 (0.45683) Boundary_loss: 0.013914 (0.013923) Loss: 0.43043 (0.47075) +2025-09-13,01:43:04 | INFO | Train Epoch: 5 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.48147 (0.45701) Boundary_loss: 0.013920 (0.013923) Loss: 0.49539 (0.47093) +2025-09-13,01:44:10 | INFO | Train Epoch: 5 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.46450 (0.45706) Boundary_loss: 0.013922 (0.013923) Loss: 0.47843 (0.47099) +2025-09-13,01:45:17 | INFO | Train Epoch: 5 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.43127 (0.45687) Boundary_loss: 0.013919 (0.013923) Loss: 0.44519 (0.47080) +2025-09-13,01:46:23 | INFO | Train Epoch: 5 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.42551 (0.45665) Boundary_loss: 0.013921 (0.013923) Loss: 0.43943 (0.47057) +2025-09-13,01:47:29 | INFO | Train Epoch: 5 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.43317 (0.45648) Boundary_loss: 0.013925 (0.013923) Loss: 0.44709 (0.47040) +2025-09-13,01:48:35 | INFO | Train Epoch: 5 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.41124 (0.45615) Boundary_loss: 0.013933 (0.013923) Loss: 0.42517 (0.47007) +2025-09-13,01:49:42 | INFO | Train Epoch: 5 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.47822 (0.45631) Boundary_loss: 0.013921 (0.013923) Loss: 0.49215 (0.47023) +2025-09-13,01:50:48 | INFO | Train Epoch: 5 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.45048 (0.45627) Boundary_loss: 0.013920 (0.013923) Loss: 0.46440 (0.47019) +2025-09-13,01:51:54 | INFO | Train Epoch: 5 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.42721 (0.45606) Boundary_loss: 0.013933 (0.013923) Loss: 0.44114 (0.46998) +2025-09-13,01:53:00 | INFO | Train Epoch: 5 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.39833 (0.45566) Boundary_loss: 0.013935 (0.013923) Loss: 0.41226 (0.46958) +2025-09-13,01:54:07 | INFO | Train Epoch: 5 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.34420 (0.45488) Boundary_loss: 0.013914 (0.013923) Loss: 0.35811 (0.46881) +2025-09-13,01:55:13 | INFO | Train Epoch: 5 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.45909 (0.45491) Boundary_loss: 0.013917 (0.013923) Loss: 0.47301 (0.46884) +2025-09-13,01:56:19 | INFO | Train Epoch: 5 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.35478 (0.45423) Boundary_loss: 0.013921 (0.013923) Loss: 0.36870 (0.46815) +2025-09-13,01:57:25 | INFO | Train Epoch: 5 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.37106 (0.45366) Boundary_loss: 0.013937 (0.013923) Loss: 0.38500 (0.46758) +2025-09-13,01:58:32 | INFO | Train Epoch: 5 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.49259 (0.45392) Boundary_loss: 0.013937 (0.013923) Loss: 0.50652 (0.46785) +2025-09-13,01:59:38 | INFO | Train Epoch: 5 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.47799 (0.45409) Boundary_loss: 0.013913 (0.013923) Loss: 0.49190 (0.46801) +2025-09-13,02:00:44 | INFO | Train Epoch: 5 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.38112 (0.45360) Boundary_loss: 0.013924 (0.013923) Loss: 0.39504 (0.46752) +2025-09-13,02:01:50 | INFO | Train Epoch: 5 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.46346 (0.45367) Boundary_loss: 0.013930 (0.013923) Loss: 0.47739 (0.46759) +2025-09-13,02:02:57 | INFO | Train Epoch: 5 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.39602 (0.45329) Boundary_loss: 0.013922 (0.013923) Loss: 0.40994 (0.46721) +2025-09-13,02:04:03 | INFO | Train Epoch: 5 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.51192 (0.45367) Boundary_loss: 0.013915 (0.013923) Loss: 0.52583 (0.46759) +2025-09-13,02:05:09 | INFO | Train Epoch: 5 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.49109 (0.45391) Boundary_loss: 0.013923 (0.013923) Loss: 0.50501 (0.46783) +2025-09-13,02:06:15 | INFO | Train Epoch: 5 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.64661 (0.45516) Boundary_loss: 0.013917 (0.013923) Loss: 0.66053 (0.46908) +2025-09-13,02:07:21 | INFO | Train Epoch: 5 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.39058 (0.45474) Boundary_loss: 0.013918 (0.013923) Loss: 0.40449 (0.46866) +2025-09-13,02:08:28 | INFO | Train Epoch: 5 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.44528 (0.45468) Boundary_loss: 0.013922 (0.013923) Loss: 0.45920 (0.46860) +2025-09-13,02:09:34 | INFO | Train Epoch: 5 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.43848 (0.45458) Boundary_loss: 0.013912 (0.013923) Loss: 0.45239 (0.46850) +2025-09-13,02:10:40 | INFO | Train Epoch: 5 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.39572 (0.45421) Boundary_loss: 0.013921 (0.013923) Loss: 0.40964 (0.46813) +2025-09-13,02:11:46 | INFO | Train Epoch: 5 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.55096 (0.45481) Boundary_loss: 0.013941 (0.013923) Loss: 0.56490 (0.46874) +2025-09-13,02:12:52 | INFO | Train Epoch: 5 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.41542 (0.45457) Boundary_loss: 0.013917 (0.013923) Loss: 0.42933 (0.46849) +2025-09-13,02:13:59 | INFO | Train Epoch: 5 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.42383 (0.45438) Boundary_loss: 0.013917 (0.013923) Loss: 0.43775 (0.46830) +2025-09-13,02:15:05 | INFO | Train Epoch: 5 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.45053 (0.45435) Boundary_loss: 0.013916 (0.013923) Loss: 0.46444 (0.46828) +2025-09-13,02:16:11 | INFO | Train Epoch: 5 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.50687 (0.45468) Boundary_loss: 0.013920 (0.013923) Loss: 0.52079 (0.46860) +2025-09-13,02:17:17 | INFO | Train Epoch: 5 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.45419 (0.45467) Boundary_loss: 0.013913 (0.013923) Loss: 0.46810 (0.46859) +2025-09-13,02:18:23 | INFO | Train Epoch: 5 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.41741 (0.45445) Boundary_loss: 0.013929 (0.013923) Loss: 0.43134 (0.46837) +2025-09-13,02:19:29 | INFO | Train Epoch: 5 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.41655 (0.45422) Boundary_loss: 0.013936 (0.013923) Loss: 0.43048 (0.46814) +2025-09-13,02:20:36 | INFO | Train Epoch: 5 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.44864 (0.45419) Boundary_loss: 0.013919 (0.013923) Loss: 0.46256 (0.46811) +2025-09-13,02:21:42 | INFO | Train Epoch: 5 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.43073 (0.45405) Boundary_loss: 0.013914 (0.013923) Loss: 0.44464 (0.46797) +2025-09-13,02:22:48 | INFO | Train Epoch: 5 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.38169 (0.45362) Boundary_loss: 0.013918 (0.013923) Loss: 0.39561 (0.46755) +2025-09-13,02:23:54 | INFO | Train Epoch: 5 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.40424 (0.45333) Boundary_loss: 0.013919 (0.013923) Loss: 0.41816 (0.46726) +2025-09-13,02:25:00 | INFO | Train Epoch: 5 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.46437 (0.45340) Boundary_loss: 0.013929 (0.013923) Loss: 0.47830 (0.46732) +2025-09-13,02:26:06 | INFO | Train Epoch: 5 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.43751 (0.45331) Boundary_loss: 0.013917 (0.013923) Loss: 0.45142 (0.46723) +2025-09-13,02:27:13 | INFO | Train Epoch: 5 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.43769 (0.45322) Boundary_loss: 0.013919 (0.013923) Loss: 0.45161 (0.46714) +2025-09-13,02:28:19 | INFO | Train Epoch: 5 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.49407 (0.45345) Boundary_loss: 0.013916 (0.013923) Loss: 0.50799 (0.46737) +2025-09-13,02:29:25 | INFO | Train Epoch: 5 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.50931 (0.45377) Boundary_loss: 0.013914 (0.013923) Loss: 0.52322 (0.46769) +2025-09-13,02:30:31 | INFO | Train Epoch: 5 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.45300 (0.45376) Boundary_loss: 0.013922 (0.013923) Loss: 0.46692 (0.46769) +2025-09-13,02:31:37 | INFO | Train Epoch: 5 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.46805 (0.45384) Boundary_loss: 0.013927 (0.013923) Loss: 0.48198 (0.46777) +2025-09-13,02:32:44 | INFO | Train Epoch: 5 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.45888 (0.45387) Boundary_loss: 0.013921 (0.013923) Loss: 0.47280 (0.46779) +2025-09-13,02:33:50 | INFO | Train Epoch: 5 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.45366 (0.45387) Boundary_loss: 0.013923 (0.013923) Loss: 0.46758 (0.46779) +2025-09-13,02:34:56 | INFO | Train Epoch: 5 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.45192 (0.45386) Boundary_loss: 0.013914 (0.013922) Loss: 0.46584 (0.46778) +2025-09-13,02:36:02 | INFO | Train Epoch: 5 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.38838 (0.45350) Boundary_loss: 0.013915 (0.013922) Loss: 0.40229 (0.46742) +2025-09-13,02:37:09 | INFO | Train Epoch: 5 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.40498 (0.45323) Boundary_loss: 0.013926 (0.013922) Loss: 0.41890 (0.46716) +2025-09-13,02:38:15 | INFO | Train Epoch: 5 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.46942 (0.45332) Boundary_loss: 0.013939 (0.013923) Loss: 0.48336 (0.46725) +2025-09-13,02:39:21 | INFO | Train Epoch: 5 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.51144 (0.45364) Boundary_loss: 0.013914 (0.013922) Loss: 0.52536 (0.46756) +2025-09-13,02:40:27 | INFO | Train Epoch: 5 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.52776 (0.45404) Boundary_loss: 0.013921 (0.013922) Loss: 0.54168 (0.46796) +2025-09-13,02:41:34 | INFO | Train Epoch: 5 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.46174 (0.45408) Boundary_loss: 0.013919 (0.013922) Loss: 0.47566 (0.46800) +2025-09-13,02:42:40 | INFO | Train Epoch: 5 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.37004 (0.45363) Boundary_loss: 0.013918 (0.013922) Loss: 0.38396 (0.46755) +2025-09-13,02:43:46 | INFO | Train Epoch: 5 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.52460 (0.45401) Boundary_loss: 0.013928 (0.013922) Loss: 0.53853 (0.46793) +2025-09-13,02:44:52 | INFO | Train Epoch: 5 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.43016 (0.45388) Boundary_loss: 0.013914 (0.013922) Loss: 0.44407 (0.46780) +2025-09-13,02:45:59 | INFO | Train Epoch: 5 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.36477 (0.45341) Boundary_loss: 0.013917 (0.013922) Loss: 0.37869 (0.46734) +2025-09-13,02:47:05 | INFO | Train Epoch: 5 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.50347 (0.45367) Boundary_loss: 0.013916 (0.013922) Loss: 0.51738 (0.46760) +2025-09-13,02:48:11 | INFO | Train Epoch: 5 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.43344 (0.45357) Boundary_loss: 0.013915 (0.013922) Loss: 0.44735 (0.46749) +2025-09-13,02:49:17 | INFO | Train Epoch: 5 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.48894 (0.45375) Boundary_loss: 0.013916 (0.013922) Loss: 0.50285 (0.46767) +2025-09-13,02:50:24 | INFO | Train Epoch: 5 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.50816 (0.45403) Boundary_loss: 0.013915 (0.013922) Loss: 0.52207 (0.46795) +2025-09-13,02:51:30 | INFO | Train Epoch: 5 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.48804 (0.45420) Boundary_loss: 0.013915 (0.013922) Loss: 0.50195 (0.46813) +2025-09-13,02:52:36 | INFO | Train Epoch: 5 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.50503 (0.45446) Boundary_loss: 0.013913 (0.013922) Loss: 0.51894 (0.46838) +2025-09-13,02:53:42 | INFO | Train Epoch: 5 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.45568 (0.45447) Boundary_loss: 0.013919 (0.013922) Loss: 0.46960 (0.46839) +2025-09-13,02:54:49 | INFO | Train Epoch: 5 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.45758 (0.45448) Boundary_loss: 0.013930 (0.013922) Loss: 0.47151 (0.46841) +2025-09-13,02:55:55 | INFO | Train Epoch: 5 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.44693 (0.45445) Boundary_loss: 0.013920 (0.013922) Loss: 0.46086 (0.46837) +2025-09-13,02:57:01 | INFO | Train Epoch: 5 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.45277 (0.45444) Boundary_loss: 0.013918 (0.013922) Loss: 0.46668 (0.46836) +2025-09-13,02:58:07 | INFO | Train Epoch: 5 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.53110 (0.45482) Boundary_loss: 0.013918 (0.013922) Loss: 0.54502 (0.46874) +2025-09-13,02:59:14 | INFO | Train Epoch: 5 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.40677 (0.45458) Boundary_loss: 0.013914 (0.013922) Loss: 0.42068 (0.46850) +2025-09-13,03:00:20 | INFO | Train Epoch: 5 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.42382 (0.45443) Boundary_loss: 0.013919 (0.013922) Loss: 0.43774 (0.46835) +2025-09-13,03:01:26 | INFO | Train Epoch: 5 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.41429 (0.45423) Boundary_loss: 0.013918 (0.013922) Loss: 0.42821 (0.46816) +2025-09-13,03:02:32 | INFO | Train Epoch: 5 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.42573 (0.45410) Boundary_loss: 0.013915 (0.013922) Loss: 0.43965 (0.46802) +2025-09-13,03:03:39 | INFO | Train Epoch: 5 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.48985 (0.45427) Boundary_loss: 0.013914 (0.013922) Loss: 0.50376 (0.46819) +2025-09-13,03:04:45 | INFO | Train Epoch: 5 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.40393 (0.45403) Boundary_loss: 0.013913 (0.013922) Loss: 0.41784 (0.46795) +2025-09-13,03:05:51 | INFO | Train Epoch: 5 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.47202 (0.45411) Boundary_loss: 0.013920 (0.013922) Loss: 0.48594 (0.46803) +2025-09-13,03:06:57 | INFO | Train Epoch: 5 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.46068 (0.45414) Boundary_loss: 0.013916 (0.013922) Loss: 0.47459 (0.46807) +2025-09-13,03:08:04 | INFO | Train Epoch: 5 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.48268 (0.45428) Boundary_loss: 0.013932 (0.013922) Loss: 0.49661 (0.46820) +2025-09-13,03:09:10 | INFO | Train Epoch: 5 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.47434 (0.45437) Boundary_loss: 0.013924 (0.013922) Loss: 0.48827 (0.46830) +2025-09-13,03:10:16 | INFO | Train Epoch: 5 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.36878 (0.45397) Boundary_loss: 0.013921 (0.013922) Loss: 0.38270 (0.46789) +2025-09-13,03:11:23 | INFO | Train Epoch: 5 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.39435 (0.45369) Boundary_loss: 0.013926 (0.013922) Loss: 0.40827 (0.46761) +2025-09-13,03:12:29 | INFO | Train Epoch: 5 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.45474 (0.45370) Boundary_loss: 0.013917 (0.013922) Loss: 0.46865 (0.46762) +2025-09-13,03:13:35 | INFO | Train Epoch: 5 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.41981 (0.45354) Boundary_loss: 0.013920 (0.013922) Loss: 0.43373 (0.46746) +2025-09-13,03:14:42 | INFO | Train Epoch: 5 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.44803 (0.45352) Boundary_loss: 0.013944 (0.013922) Loss: 0.46198 (0.46744) +2025-09-13,03:15:48 | INFO | Train Epoch: 5 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.52765 (0.45386) Boundary_loss: 0.013927 (0.013922) Loss: 0.54158 (0.46778) +2025-09-13,03:16:54 | INFO | Train Epoch: 5 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.43302 (0.45376) Boundary_loss: 0.013915 (0.013922) Loss: 0.44693 (0.46768) +2025-09-13,03:18:00 | INFO | Train Epoch: 5 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.43835 (0.45369) Boundary_loss: 0.013914 (0.013922) Loss: 0.45226 (0.46761) +2025-09-13,03:19:07 | INFO | Train Epoch: 5 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.44560 (0.45365) Boundary_loss: 0.013917 (0.013922) Loss: 0.45952 (0.46758) +2025-09-13,03:20:13 | INFO | Train Epoch: 5 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.44782 (0.45363) Boundary_loss: 0.013914 (0.013922) Loss: 0.46173 (0.46755) +2025-09-13,03:21:19 | INFO | Train Epoch: 5 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.44900 (0.45361) Boundary_loss: 0.013910 (0.013922) Loss: 0.46291 (0.46753) +2025-09-13,03:22:25 | INFO | Train Epoch: 5 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.43417 (0.45352) Boundary_loss: 0.013917 (0.013922) Loss: 0.44809 (0.46744) +2025-09-13,03:23:32 | INFO | Train Epoch: 5 [11469312/26365952 (44%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.53186 (0.45387) Boundary_loss: 0.013917 (0.013922) Loss: 0.54578 (0.46779) +2025-09-13,03:24:38 | INFO | Train Epoch: 5 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.43460 (0.45378) Boundary_loss: 0.013914 (0.013922) Loss: 0.44851 (0.46770) +2025-09-13,03:25:44 | INFO | Train Epoch: 5 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.52628 (0.45410) Boundary_loss: 0.013922 (0.013922) Loss: 0.54020 (0.46802) +2025-09-13,03:26:51 | INFO | Train Epoch: 5 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.49797 (0.45429) Boundary_loss: 0.013921 (0.013922) Loss: 0.51189 (0.46822) +2025-09-13,03:27:57 | INFO | Train Epoch: 5 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.50479 (0.45452) Boundary_loss: 0.013921 (0.013922) Loss: 0.51871 (0.46844) +2025-09-13,03:29:03 | INFO | Train Epoch: 5 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.46853 (0.45458) Boundary_loss: 0.013927 (0.013922) Loss: 0.48246 (0.46850) +2025-09-13,03:30:09 | INFO | Train Epoch: 5 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.41867 (0.45442) Boundary_loss: 0.013921 (0.013922) Loss: 0.43259 (0.46834) +2025-09-13,03:31:16 | INFO | Train Epoch: 5 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.41564 (0.45425) Boundary_loss: 0.013918 (0.013922) Loss: 0.42956 (0.46818) +2025-09-13,03:32:22 | INFO | Train Epoch: 5 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.39978 (0.45402) Boundary_loss: 0.013918 (0.013922) Loss: 0.41370 (0.46794) +2025-09-13,03:33:28 | INFO | Train Epoch: 5 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.45214 (0.45401) Boundary_loss: 0.013916 (0.013922) Loss: 0.46606 (0.46793) +2025-09-13,03:34:34 | INFO | Train Epoch: 5 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.42971 (0.45391) Boundary_loss: 0.013921 (0.013922) Loss: 0.44363 (0.46783) +2025-09-13,03:35:41 | INFO | Train Epoch: 5 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.41767 (0.45375) Boundary_loss: 0.013917 (0.013922) Loss: 0.43159 (0.46768) +2025-09-13,03:36:47 | INFO | Train Epoch: 5 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.40581 (0.45355) Boundary_loss: 0.013917 (0.013922) Loss: 0.41973 (0.46747) +2025-09-13,03:37:53 | INFO | Train Epoch: 5 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.44947 (0.45354) Boundary_loss: 0.013915 (0.013922) Loss: 0.46339 (0.46746) +2025-09-13,03:38:59 | INFO | Train Epoch: 5 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.49819 (0.45372) Boundary_loss: 0.013918 (0.013922) Loss: 0.51211 (0.46764) +2025-09-13,03:40:06 | INFO | Train Epoch: 5 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.44747 (0.45370) Boundary_loss: 0.013919 (0.013922) Loss: 0.46138 (0.46762) +2025-09-13,03:41:12 | INFO | Train Epoch: 5 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.58385 (0.45424) Boundary_loss: 0.013919 (0.013922) Loss: 0.59777 (0.46816) +2025-09-13,03:42:18 | INFO | Train Epoch: 5 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.41691 (0.45408) Boundary_loss: 0.013911 (0.013922) Loss: 0.43082 (0.46800) +2025-09-13,03:43:24 | INFO | Train Epoch: 5 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.56029 (0.45452) Boundary_loss: 0.013921 (0.013922) Loss: 0.57421 (0.46844) +2025-09-13,03:44:31 | INFO | Train Epoch: 5 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.47722 (0.45461) Boundary_loss: 0.013926 (0.013922) Loss: 0.49115 (0.46853) +2025-09-13,03:45:37 | INFO | Train Epoch: 5 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.36398 (0.45424) Boundary_loss: 0.013914 (0.013922) Loss: 0.37790 (0.46816) +2025-09-13,03:46:43 | INFO | Train Epoch: 5 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.40638 (0.45405) Boundary_loss: 0.013915 (0.013922) Loss: 0.42030 (0.46797) +2025-09-13,03:47:49 | INFO | Train Epoch: 5 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.46865 (0.45411) Boundary_loss: 0.013919 (0.013922) Loss: 0.48257 (0.46803) +2025-09-13,03:48:56 | INFO | Train Epoch: 5 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.44077 (0.45405) Boundary_loss: 0.013920 (0.013922) Loss: 0.45469 (0.46797) +2025-09-13,03:50:02 | INFO | Train Epoch: 5 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.45757 (0.45407) Boundary_loss: 0.013915 (0.013922) Loss: 0.47149 (0.46799) +2025-09-13,03:51:08 | INFO | Train Epoch: 5 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.32020 (0.45353) Boundary_loss: 0.013916 (0.013922) Loss: 0.33412 (0.46745) +2025-09-13,03:52:14 | INFO | Train Epoch: 5 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.42618 (0.45342) Boundary_loss: 0.013910 (0.013921) Loss: 0.44009 (0.46734) +2025-09-13,03:53:21 | INFO | Train Epoch: 5 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.38461 (0.45315) Boundary_loss: 0.013913 (0.013921) Loss: 0.39852 (0.46707) +2025-09-13,03:54:27 | INFO | Train Epoch: 5 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.41572 (0.45300) Boundary_loss: 0.013920 (0.013921) Loss: 0.42964 (0.46692) +2025-09-13,03:55:33 | INFO | Train Epoch: 5 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.41247 (0.45284) Boundary_loss: 0.013915 (0.013921) Loss: 0.42638 (0.46676) +2025-09-13,03:56:39 | INFO | Train Epoch: 5 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.39908 (0.45263) Boundary_loss: 0.013914 (0.013921) Loss: 0.41299 (0.46655) +2025-09-13,03:57:46 | INFO | Train Epoch: 5 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.47813 (0.45273) Boundary_loss: 0.013918 (0.013921) Loss: 0.49205 (0.46665) +2025-09-13,03:58:52 | INFO | Train Epoch: 5 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.35176 (0.45234) Boundary_loss: 0.013923 (0.013921) Loss: 0.36569 (0.46626) +2025-09-13,03:59:58 | INFO | Train Epoch: 5 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.46845 (0.45240) Boundary_loss: 0.013913 (0.013921) Loss: 0.48237 (0.46632) +2025-09-13,04:01:04 | INFO | Train Epoch: 5 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.44592 (0.45238) Boundary_loss: 0.013917 (0.013921) Loss: 0.45984 (0.46630) +2025-09-13,04:02:11 | INFO | Train Epoch: 5 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.43122 (0.45229) Boundary_loss: 0.013922 (0.013921) Loss: 0.44514 (0.46622) +2025-09-13,04:03:17 | INFO | Train Epoch: 5 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.39784 (0.45209) Boundary_loss: 0.013922 (0.013921) Loss: 0.41176 (0.46601) +2025-09-13,04:04:23 | INFO | Train Epoch: 5 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.48223 (0.45220) Boundary_loss: 0.013919 (0.013921) Loss: 0.49615 (0.46612) +2025-09-13,04:05:29 | INFO | Train Epoch: 5 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.44553 (0.45218) Boundary_loss: 0.013926 (0.013921) Loss: 0.45946 (0.46610) +2025-09-13,04:06:36 | INFO | Train Epoch: 5 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.50086 (0.45236) Boundary_loss: 0.013924 (0.013921) Loss: 0.51478 (0.46628) +2025-09-13,04:07:42 | INFO | Train Epoch: 5 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.48154 (0.45247) Boundary_loss: 0.013923 (0.013921) Loss: 0.49546 (0.46639) +2025-09-13,04:08:48 | INFO | Train Epoch: 5 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.46282 (0.45251) Boundary_loss: 0.013918 (0.013921) Loss: 0.47674 (0.46643) +2025-09-13,04:09:55 | INFO | Train Epoch: 5 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.46883 (0.45257) Boundary_loss: 0.013919 (0.013921) Loss: 0.48274 (0.46649) +2025-09-13,04:11:01 | INFO | Train Epoch: 5 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.34729 (0.45218) Boundary_loss: 0.013912 (0.013921) Loss: 0.36120 (0.46610) +2025-09-13,04:12:07 | INFO | Train Epoch: 5 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.39295 (0.45196) Boundary_loss: 0.013948 (0.013921) Loss: 0.40690 (0.46588) +2025-09-13,04:13:13 | INFO | Train Epoch: 5 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.37640 (0.45168) Boundary_loss: 0.013921 (0.013921) Loss: 0.39033 (0.46560) +2025-09-13,04:14:20 | INFO | Train Epoch: 5 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46623 (0.45173) Boundary_loss: 0.013921 (0.013921) Loss: 0.48015 (0.46565) +2025-09-13,04:15:26 | INFO | Train Epoch: 5 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.38679 (0.45149) Boundary_loss: 0.013930 (0.013921) Loss: 0.40072 (0.46541) +2025-09-13,04:16:32 | INFO | Train Epoch: 5 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.39507 (0.45129) Boundary_loss: 0.013923 (0.013921) Loss: 0.40900 (0.46521) +2025-09-13,04:17:39 | INFO | Train Epoch: 5 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.41351 (0.45115) Boundary_loss: 0.013919 (0.013921) Loss: 0.42743 (0.46507) +2025-09-13,04:18:45 | INFO | Train Epoch: 5 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.36151 (0.45082) Boundary_loss: 0.013912 (0.013921) Loss: 0.37543 (0.46474) +2025-09-13,04:19:51 | INFO | Train Epoch: 5 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.41253 (0.45068) Boundary_loss: 0.013926 (0.013921) Loss: 0.42645 (0.46460) +2025-09-13,04:20:57 | INFO | Train Epoch: 5 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.46660 (0.45074) Boundary_loss: 0.013914 (0.013921) Loss: 0.48052 (0.46466) +2025-09-13,04:22:04 | INFO | Train Epoch: 5 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.40967 (0.45059) Boundary_loss: 0.013922 (0.013921) Loss: 0.42359 (0.46451) +2025-09-13,04:23:10 | INFO | Train Epoch: 5 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.37067 (0.45031) Boundary_loss: 0.013912 (0.013921) Loss: 0.38458 (0.46423) +2025-09-13,04:24:16 | INFO | Train Epoch: 5 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.42955 (0.45023) Boundary_loss: 0.013920 (0.013921) Loss: 0.44347 (0.46415) +2025-09-13,04:25:23 | INFO | Train Epoch: 5 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.46546 (0.45029) Boundary_loss: 0.013927 (0.013921) Loss: 0.47939 (0.46421) +2025-09-13,04:26:29 | INFO | Train Epoch: 5 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.43090 (0.45022) Boundary_loss: 0.013918 (0.013921) Loss: 0.44482 (0.46414) +2025-09-13,04:27:35 | INFO | Train Epoch: 5 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.38854 (0.45000) Boundary_loss: 0.013919 (0.013921) Loss: 0.40246 (0.46392) +2025-09-13,04:28:41 | INFO | Train Epoch: 5 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.46306 (0.45005) Boundary_loss: 0.013920 (0.013921) Loss: 0.47698 (0.46397) +2025-09-13,04:29:48 | INFO | Train Epoch: 5 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.44624 (0.45003) Boundary_loss: 0.013914 (0.013921) Loss: 0.46015 (0.46395) +2025-09-13,04:30:54 | INFO | Train Epoch: 5 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.38368 (0.44980) Boundary_loss: 0.013920 (0.013921) Loss: 0.39760 (0.46372) +2025-09-13,04:32:00 | INFO | Train Epoch: 5 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.41276 (0.44967) Boundary_loss: 0.013917 (0.013921) Loss: 0.42667 (0.46359) +2025-09-13,04:33:06 | INFO | Train Epoch: 5 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.44282 (0.44965) Boundary_loss: 0.013917 (0.013921) Loss: 0.45674 (0.46357) +2025-09-13,04:34:13 | INFO | Train Epoch: 5 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.42715 (0.44957) Boundary_loss: 0.013917 (0.013921) Loss: 0.44107 (0.46349) +2025-09-13,04:35:19 | INFO | Train Epoch: 5 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.42795 (0.44949) Boundary_loss: 0.013946 (0.013921) Loss: 0.44190 (0.46342) +2025-09-13,04:36:25 | INFO | Train Epoch: 5 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.40022 (0.44933) Boundary_loss: 0.013919 (0.013921) Loss: 0.41414 (0.46325) +2025-09-13,04:37:32 | INFO | Train Epoch: 5 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.27116 (0.44872) Boundary_loss: 0.013909 (0.013921) Loss: 0.28507 (0.46264) +2025-09-13,04:38:38 | INFO | Train Epoch: 5 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.54994 (0.44906) Boundary_loss: 0.013921 (0.013921) Loss: 0.56386 (0.46298) +2025-09-13,04:39:44 | INFO | Train Epoch: 5 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.51531 (0.44929) Boundary_loss: 0.013921 (0.013921) Loss: 0.52923 (0.46321) +2025-09-13,04:40:50 | INFO | Train Epoch: 5 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.38323 (0.44906) Boundary_loss: 0.013920 (0.013921) Loss: 0.39715 (0.46298) +2025-09-13,04:41:57 | INFO | Train Epoch: 5 [15104512/26365952 (57%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.48004 (0.44917) Boundary_loss: 0.013934 (0.013921) Loss: 0.49397 (0.46309) +2025-09-13,04:43:03 | INFO | Train Epoch: 5 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.43184 (0.44911) Boundary_loss: 0.013913 (0.013921) Loss: 0.44575 (0.46303) +2025-09-13,04:44:09 | INFO | Train Epoch: 5 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.41981 (0.44901) Boundary_loss: 0.013915 (0.013921) Loss: 0.43373 (0.46293) +2025-09-13,04:45:15 | INFO | Train Epoch: 5 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.45474 (0.44903) Boundary_loss: 0.013922 (0.013921) Loss: 0.46866 (0.46295) +2025-09-13,04:46:22 | INFO | Train Epoch: 5 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.36250 (0.44874) Boundary_loss: 0.013913 (0.013921) Loss: 0.37641 (0.46266) +2025-09-13,04:47:28 | INFO | Train Epoch: 5 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.45514 (0.44876) Boundary_loss: 0.013923 (0.013921) Loss: 0.46906 (0.46268) +2025-09-13,04:48:34 | INFO | Train Epoch: 5 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.47791 (0.44886) Boundary_loss: 0.013913 (0.013921) Loss: 0.49182 (0.46278) +2025-09-13,04:49:40 | INFO | Train Epoch: 5 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.44065 (0.44883) Boundary_loss: 0.013913 (0.013921) Loss: 0.45456 (0.46275) +2025-09-13,04:50:47 | INFO | Train Epoch: 5 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.56339 (0.44921) Boundary_loss: 0.013926 (0.013921) Loss: 0.57731 (0.46313) +2025-09-13,04:51:53 | INFO | Train Epoch: 5 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.47766 (0.44930) Boundary_loss: 0.013918 (0.013921) Loss: 0.49158 (0.46322) +2025-09-13,04:52:59 | INFO | Train Epoch: 5 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.44325 (0.44928) Boundary_loss: 0.013931 (0.013921) Loss: 0.45719 (0.46320) +2025-09-13,04:54:06 | INFO | Train Epoch: 5 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.45241 (0.44929) Boundary_loss: 0.013917 (0.013921) Loss: 0.46633 (0.46321) +2025-09-13,04:55:12 | INFO | Train Epoch: 5 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.44286 (0.44927) Boundary_loss: 0.013914 (0.013921) Loss: 0.45677 (0.46319) +2025-09-13,04:56:18 | INFO | Train Epoch: 5 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.50310 (0.44945) Boundary_loss: 0.013915 (0.013921) Loss: 0.51701 (0.46337) +2025-09-13,04:57:24 | INFO | Train Epoch: 5 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.48199 (0.44955) Boundary_loss: 0.013913 (0.013921) Loss: 0.49590 (0.46347) +2025-09-13,04:58:31 | INFO | Train Epoch: 5 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.43036 (0.44949) Boundary_loss: 0.013917 (0.013921) Loss: 0.44428 (0.46341) +2025-09-13,04:59:37 | INFO | Train Epoch: 5 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.46047 (0.44952) Boundary_loss: 0.013917 (0.013921) Loss: 0.47438 (0.46344) +2025-09-13,05:00:43 | INFO | Train Epoch: 5 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.47637 (0.44961) Boundary_loss: 0.013918 (0.013921) Loss: 0.49029 (0.46353) +2025-09-13,05:01:49 | INFO | Train Epoch: 5 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.40281 (0.44946) Boundary_loss: 0.013916 (0.013921) Loss: 0.41673 (0.46338) +2025-09-13,05:02:56 | INFO | Train Epoch: 5 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.51706 (0.44968) Boundary_loss: 0.013915 (0.013921) Loss: 0.53098 (0.46360) +2025-09-13,05:04:02 | INFO | Train Epoch: 5 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.40831 (0.44954) Boundary_loss: 0.013911 (0.013921) Loss: 0.42222 (0.46347) +2025-09-13,05:05:08 | INFO | Train Epoch: 5 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.52843 (0.44979) Boundary_loss: 0.013910 (0.013921) Loss: 0.54234 (0.46371) +2025-09-13,05:06:14 | INFO | Train Epoch: 5 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.43370 (0.44974) Boundary_loss: 0.013920 (0.013921) Loss: 0.44762 (0.46366) +2025-09-13,05:07:21 | INFO | Train Epoch: 5 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.44331 (0.44972) Boundary_loss: 0.013925 (0.013921) Loss: 0.45724 (0.46364) +2025-09-13,05:08:27 | INFO | Train Epoch: 5 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.41293 (0.44961) Boundary_loss: 0.013923 (0.013921) Loss: 0.42685 (0.46353) +2025-09-13,05:09:33 | INFO | Train Epoch: 5 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.47968 (0.44970) Boundary_loss: 0.013922 (0.013921) Loss: 0.49360 (0.46362) +2025-09-13,05:10:40 | INFO | Train Epoch: 5 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.40932 (0.44958) Boundary_loss: 0.013915 (0.013921) Loss: 0.42323 (0.46350) +2025-09-13,05:11:46 | INFO | Train Epoch: 5 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.33669 (0.44923) Boundary_loss: 0.013916 (0.013921) Loss: 0.35060 (0.46315) +2025-09-13,05:12:52 | INFO | Train Epoch: 5 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.42946 (0.44917) Boundary_loss: 0.013915 (0.013921) Loss: 0.44337 (0.46309) +2025-09-13,05:13:58 | INFO | Train Epoch: 5 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.35084 (0.44886) Boundary_loss: 0.013918 (0.013921) Loss: 0.36476 (0.46278) +2025-09-13,05:15:05 | INFO | Train Epoch: 5 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.39826 (0.44871) Boundary_loss: 0.013914 (0.013921) Loss: 0.41217 (0.46263) +2025-09-13,05:16:11 | INFO | Train Epoch: 5 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42745 (0.44864) Boundary_loss: 0.013917 (0.013921) Loss: 0.44137 (0.46256) +2025-09-13,05:17:17 | INFO | Train Epoch: 5 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.48493 (0.44875) Boundary_loss: 0.013924 (0.013921) Loss: 0.49886 (0.46267) +2025-09-13,05:18:23 | INFO | Train Epoch: 5 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.41925 (0.44866) Boundary_loss: 0.013917 (0.013921) Loss: 0.43317 (0.46258) +2025-09-13,05:19:30 | INFO | Train Epoch: 5 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.39541 (0.44850) Boundary_loss: 0.013911 (0.013921) Loss: 0.40932 (0.46242) +2025-09-13,05:20:36 | INFO | Train Epoch: 5 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.43796 (0.44847) Boundary_loss: 0.013910 (0.013921) Loss: 0.45187 (0.46239) +2025-09-13,05:21:42 | INFO | Train Epoch: 5 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.40495 (0.44834) Boundary_loss: 0.013920 (0.013921) Loss: 0.41887 (0.46226) +2025-09-13,05:22:48 | INFO | Train Epoch: 5 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.45363 (0.44835) Boundary_loss: 0.013917 (0.013921) Loss: 0.46755 (0.46228) +2025-09-13,05:23:55 | INFO | Train Epoch: 5 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.44359 (0.44834) Boundary_loss: 0.013917 (0.013921) Loss: 0.45750 (0.46226) +2025-09-13,05:25:01 | INFO | Train Epoch: 5 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.45446 (0.44836) Boundary_loss: 0.013919 (0.013921) Loss: 0.46838 (0.46228) +2025-09-13,05:26:07 | INFO | Train Epoch: 5 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.41310 (0.44825) Boundary_loss: 0.013921 (0.013921) Loss: 0.42702 (0.46217) +2025-09-13,05:27:13 | INFO | Train Epoch: 5 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.37779 (0.44804) Boundary_loss: 0.013921 (0.013921) Loss: 0.39171 (0.46197) +2025-09-13,05:28:20 | INFO | Train Epoch: 5 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.32091 (0.44767) Boundary_loss: 0.013914 (0.013921) Loss: 0.33483 (0.46159) +2025-09-13,05:29:26 | INFO | Train Epoch: 5 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.42975 (0.44762) Boundary_loss: 0.013932 (0.013921) Loss: 0.44369 (0.46154) +2025-09-13,05:30:32 | INFO | Train Epoch: 5 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.38167 (0.44742) Boundary_loss: 0.013914 (0.013921) Loss: 0.39558 (0.46134) +2025-09-13,05:31:38 | INFO | Train Epoch: 5 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.43563 (0.44739) Boundary_loss: 0.013915 (0.013921) Loss: 0.44954 (0.46131) +2025-09-13,05:32:45 | INFO | Train Epoch: 5 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.49434 (0.44752) Boundary_loss: 0.013911 (0.013921) Loss: 0.50825 (0.46145) +2025-09-13,05:33:51 | INFO | Train Epoch: 5 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.42648 (0.44746) Boundary_loss: 0.013920 (0.013921) Loss: 0.44040 (0.46138) +2025-09-13,05:34:57 | INFO | Train Epoch: 5 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.47806 (0.44755) Boundary_loss: 0.013918 (0.013921) Loss: 0.49198 (0.46147) +2025-09-13,05:36:04 | INFO | Train Epoch: 5 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.41915 (0.44747) Boundary_loss: 0.013915 (0.013921) Loss: 0.43306 (0.46139) +2025-09-13,05:37:10 | INFO | Train Epoch: 5 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.41141 (0.44737) Boundary_loss: 0.013918 (0.013921) Loss: 0.42532 (0.46129) +2025-09-13,05:38:16 | INFO | Train Epoch: 5 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.41019 (0.44726) Boundary_loss: 0.013943 (0.013921) Loss: 0.42413 (0.46118) +2025-09-13,05:39:22 | INFO | Train Epoch: 5 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.44663 (0.44726) Boundary_loss: 0.013934 (0.013921) Loss: 0.46056 (0.46118) +2025-09-13,05:40:29 | INFO | Train Epoch: 5 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.40602 (0.44714) Boundary_loss: 0.013920 (0.013921) Loss: 0.41994 (0.46106) +2025-09-13,05:41:35 | INFO | Train Epoch: 5 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.50148 (0.44729) Boundary_loss: 0.013914 (0.013921) Loss: 0.51540 (0.46121) +2025-09-13,05:42:41 | INFO | Train Epoch: 5 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.47797 (0.44738) Boundary_loss: 0.013917 (0.013921) Loss: 0.49189 (0.46130) +2025-09-13,05:43:47 | INFO | Train Epoch: 5 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.46234 (0.44742) Boundary_loss: 0.013908 (0.013921) Loss: 0.47624 (0.46134) +2025-09-13,05:44:54 | INFO | Train Epoch: 5 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.38360 (0.44724) Boundary_loss: 0.013922 (0.013921) Loss: 0.39753 (0.46116) +2025-09-13,05:46:00 | INFO | Train Epoch: 5 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.45597 (0.44727) Boundary_loss: 0.013915 (0.013921) Loss: 0.46988 (0.46119) +2025-09-13,05:47:06 | INFO | Train Epoch: 5 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.37863 (0.44707) Boundary_loss: 0.013913 (0.013921) Loss: 0.39254 (0.46099) +2025-09-13,05:48:12 | INFO | Train Epoch: 5 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.45477 (0.44710) Boundary_loss: 0.013917 (0.013921) Loss: 0.46869 (0.46102) +2025-09-13,05:49:19 | INFO | Train Epoch: 5 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.50545 (0.44726) Boundary_loss: 0.013915 (0.013921) Loss: 0.51936 (0.46118) +2025-09-13,05:50:25 | INFO | Train Epoch: 5 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.38880 (0.44710) Boundary_loss: 0.013930 (0.013921) Loss: 0.40273 (0.46102) +2025-09-13,05:51:31 | INFO | Train Epoch: 5 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.47761 (0.44718) Boundary_loss: 0.013922 (0.013921) Loss: 0.49153 (0.46110) +2025-09-13,05:52:37 | INFO | Train Epoch: 5 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.44746 (0.44718) Boundary_loss: 0.013914 (0.013921) Loss: 0.46137 (0.46110) +2025-09-13,05:53:44 | INFO | Train Epoch: 5 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.45048 (0.44719) Boundary_loss: 0.013912 (0.013921) Loss: 0.46439 (0.46111) +2025-09-13,05:54:50 | INFO | Train Epoch: 5 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.44377 (0.44718) Boundary_loss: 0.013918 (0.013921) Loss: 0.45769 (0.46110) +2025-09-13,05:55:56 | INFO | Train Epoch: 5 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.48612 (0.44729) Boundary_loss: 0.013919 (0.013921) Loss: 0.50003 (0.46121) +2025-09-13,05:57:02 | INFO | Train Epoch: 5 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.37756 (0.44710) Boundary_loss: 0.013916 (0.013921) Loss: 0.39147 (0.46102) +2025-09-13,05:58:09 | INFO | Train Epoch: 5 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.37019 (0.44689) Boundary_loss: 0.013911 (0.013921) Loss: 0.38410 (0.46081) +2025-09-13,05:59:15 | INFO | Train Epoch: 5 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.44162 (0.44687) Boundary_loss: 0.013919 (0.013921) Loss: 0.45554 (0.46079) +2025-09-13,06:00:21 | INFO | Train Epoch: 5 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.44503 (0.44687) Boundary_loss: 0.013915 (0.013921) Loss: 0.45895 (0.46079) +2025-09-13,06:01:27 | INFO | Train Epoch: 5 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.40455 (0.44675) Boundary_loss: 0.013918 (0.013921) Loss: 0.41847 (0.46067) +2025-09-13,06:02:34 | INFO | Train Epoch: 5 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.39664 (0.44662) Boundary_loss: 0.013917 (0.013921) Loss: 0.41056 (0.46054) +2025-09-13,06:03:40 | INFO | Train Epoch: 5 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.42278 (0.44655) Boundary_loss: 0.013925 (0.013921) Loss: 0.43670 (0.46047) +2025-09-13,06:04:46 | INFO | Train Epoch: 5 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.42045 (0.44648) Boundary_loss: 0.013915 (0.013921) Loss: 0.43436 (0.46040) +2025-09-13,06:05:53 | INFO | Train Epoch: 5 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38062 (0.44630) Boundary_loss: 0.013914 (0.013921) Loss: 0.39453 (0.46022) +2025-09-13,06:06:59 | INFO | Train Epoch: 5 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.50898 (0.44647) Boundary_loss: 0.013910 (0.013921) Loss: 0.52289 (0.46039) +2025-09-13,06:08:05 | INFO | Train Epoch: 5 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.50153 (0.44662) Boundary_loss: 0.013913 (0.013921) Loss: 0.51544 (0.46054) +2025-09-13,06:09:11 | INFO | Train Epoch: 5 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.39088 (0.44647) Boundary_loss: 0.013912 (0.013921) Loss: 0.40480 (0.46039) +2025-09-13,06:10:18 | INFO | Train Epoch: 5 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.47031 (0.44653) Boundary_loss: 0.013911 (0.013920) Loss: 0.48422 (0.46045) +2025-09-13,06:11:24 | INFO | Train Epoch: 5 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.44702 (0.44654) Boundary_loss: 0.013914 (0.013920) Loss: 0.46093 (0.46046) +2025-09-13,06:12:30 | INFO | Train Epoch: 5 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.43460 (0.44650) Boundary_loss: 0.013916 (0.013920) Loss: 0.44852 (0.46042) +2025-09-13,06:13:37 | INFO | Train Epoch: 5 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.36662 (0.44629) Boundary_loss: 0.013927 (0.013920) Loss: 0.38054 (0.46021) +2025-09-13,06:14:43 | INFO | Train Epoch: 5 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.44303 (0.44628) Boundary_loss: 0.013927 (0.013921) Loss: 0.45695 (0.46021) +2025-09-13,06:15:49 | INFO | Train Epoch: 5 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.43613 (0.44626) Boundary_loss: 0.013923 (0.013921) Loss: 0.45005 (0.46018) +2025-09-13,06:16:56 | INFO | Train Epoch: 5 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.46788 (0.44631) Boundary_loss: 0.013916 (0.013920) Loss: 0.48180 (0.46024) +2025-09-13,06:18:02 | INFO | Train Epoch: 5 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.49911 (0.44645) Boundary_loss: 0.013916 (0.013920) Loss: 0.51303 (0.46037) +2025-09-13,06:19:08 | INFO | Train Epoch: 5 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.36750 (0.44625) Boundary_loss: 0.013926 (0.013920) Loss: 0.38143 (0.46017) +2025-09-13,06:20:15 | INFO | Train Epoch: 5 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.40479 (0.44614) Boundary_loss: 0.013914 (0.013920) Loss: 0.41870 (0.46006) +2025-09-13,06:21:21 | INFO | Train Epoch: 5 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.47024 (0.44620) Boundary_loss: 0.013916 (0.013920) Loss: 0.48415 (0.46012) +2025-09-13,06:22:27 | INFO | Train Epoch: 5 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.40995 (0.44611) Boundary_loss: 0.013917 (0.013920) Loss: 0.42387 (0.46003) +2025-09-13,06:23:34 | INFO | Train Epoch: 5 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.52241 (0.44630) Boundary_loss: 0.013918 (0.013920) Loss: 0.53632 (0.46023) +2025-09-13,06:24:40 | INFO | Train Epoch: 5 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.40341 (0.44619) Boundary_loss: 0.013913 (0.013920) Loss: 0.41732 (0.46011) +2025-09-13,06:25:46 | INFO | Train Epoch: 5 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.45711 (0.44622) Boundary_loss: 0.013907 (0.013920) Loss: 0.47101 (0.46014) +2025-09-13,06:26:52 | INFO | Train Epoch: 5 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.44524 (0.44622) Boundary_loss: 0.013925 (0.013920) Loss: 0.45917 (0.46014) +2025-09-13,06:27:59 | INFO | Train Epoch: 5 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.36342 (0.44601) Boundary_loss: 0.013919 (0.013920) Loss: 0.37734 (0.45993) +2025-09-13,06:29:05 | INFO | Train Epoch: 5 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.36499 (0.44580) Boundary_loss: 0.013915 (0.013920) Loss: 0.37890 (0.45972) +2025-09-13,06:30:11 | INFO | Train Epoch: 5 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.46505 (0.44585) Boundary_loss: 0.013917 (0.013920) Loss: 0.47897 (0.45977) +2025-09-13,06:31:18 | INFO | Train Epoch: 5 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.48690 (0.44596) Boundary_loss: 0.013930 (0.013920) Loss: 0.50083 (0.45988) +2025-09-13,06:32:24 | INFO | Train Epoch: 5 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.45850 (0.44599) Boundary_loss: 0.013914 (0.013920) Loss: 0.47241 (0.45991) +2025-09-13,06:33:30 | INFO | Train Epoch: 5 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.45149 (0.44600) Boundary_loss: 0.013916 (0.013920) Loss: 0.46541 (0.45992) +2025-09-13,06:34:36 | INFO | Train Epoch: 5 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.41854 (0.44593) Boundary_loss: 0.013918 (0.013920) Loss: 0.43246 (0.45985) +2025-09-13,06:35:43 | INFO | Train Epoch: 5 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.38055 (0.44577) Boundary_loss: 0.013908 (0.013920) Loss: 0.39446 (0.45969) +2025-09-13,06:36:49 | INFO | Train Epoch: 5 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.42385 (0.44571) Boundary_loss: 0.013919 (0.013920) Loss: 0.43777 (0.45963) +2025-09-13,06:37:55 | INFO | Train Epoch: 5 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.40013 (0.44560) Boundary_loss: 0.013911 (0.013920) Loss: 0.41404 (0.45952) +2025-09-13,06:39:01 | INFO | Train Epoch: 5 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.35433 (0.44537) Boundary_loss: 0.013929 (0.013920) Loss: 0.36825 (0.45929) +2025-09-13,06:40:08 | INFO | Train Epoch: 5 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.42447 (0.44532) Boundary_loss: 0.013913 (0.013920) Loss: 0.43838 (0.45924) +2025-09-13,06:41:14 | INFO | Train Epoch: 5 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.44757 (0.44533) Boundary_loss: 0.013917 (0.013920) Loss: 0.46149 (0.45925) +2025-09-13,06:42:20 | INFO | Train Epoch: 5 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.41262 (0.44525) Boundary_loss: 0.013911 (0.013920) Loss: 0.42654 (0.45917) +2025-09-13,06:43:27 | INFO | Train Epoch: 5 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.53110 (0.44546) Boundary_loss: 0.013915 (0.013920) Loss: 0.54501 (0.45938) +2025-09-13,06:44:33 | INFO | Train Epoch: 5 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.50885 (0.44561) Boundary_loss: 0.013907 (0.013920) Loss: 0.52276 (0.45953) +2025-09-13,06:45:39 | INFO | Train Epoch: 5 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.47437 (0.44568) Boundary_loss: 0.013915 (0.013920) Loss: 0.48829 (0.45960) +2025-09-13,06:46:46 | INFO | Train Epoch: 5 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.48293 (0.44577) Boundary_loss: 0.013912 (0.013920) Loss: 0.49684 (0.45969) +2025-09-13,06:47:52 | INFO | Train Epoch: 5 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.37594 (0.44560) Boundary_loss: 0.013916 (0.013920) Loss: 0.38986 (0.45952) +2025-09-13,06:48:58 | INFO | Train Epoch: 5 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.43635 (0.44558) Boundary_loss: 0.013919 (0.013920) Loss: 0.45027 (0.45950) +2025-09-13,06:50:04 | INFO | Train Epoch: 5 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42176 (0.44552) Boundary_loss: 0.013917 (0.013920) Loss: 0.43568 (0.45944) +2025-09-13,06:51:11 | INFO | Train Epoch: 5 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.43449 (0.44550) Boundary_loss: 0.013919 (0.013920) Loss: 0.44841 (0.45942) +2025-09-13,06:52:17 | INFO | Train Epoch: 5 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.33688 (0.44523) Boundary_loss: 0.013917 (0.013920) Loss: 0.35080 (0.45915) +2025-09-13,06:53:23 | INFO | Train Epoch: 5 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.39400 (0.44511) Boundary_loss: 0.013919 (0.013920) Loss: 0.40792 (0.45903) +2025-09-13,06:54:29 | INFO | Train Epoch: 5 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.38251 (0.44496) Boundary_loss: 0.013914 (0.013920) Loss: 0.39642 (0.45888) +2025-09-13,06:55:36 | INFO | Train Epoch: 5 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.33373 (0.44469) Boundary_loss: 0.013924 (0.013920) Loss: 0.34766 (0.45861) +2025-09-13,06:56:42 | INFO | Train Epoch: 5 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.47436 (0.44476) Boundary_loss: 0.013917 (0.013920) Loss: 0.48828 (0.45868) +2025-09-13,06:57:48 | INFO | Train Epoch: 5 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.43003 (0.44473) Boundary_loss: 0.013912 (0.013920) Loss: 0.44395 (0.45865) +2025-09-13,06:58:54 | INFO | Train Epoch: 5 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.44963 (0.44474) Boundary_loss: 0.013914 (0.013920) Loss: 0.46355 (0.45866) +2025-09-13,07:00:01 | INFO | Train Epoch: 5 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.42853 (0.44470) Boundary_loss: 0.013920 (0.013920) Loss: 0.44245 (0.45862) +2025-09-13,07:01:07 | INFO | Train Epoch: 5 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.44869 (0.44471) Boundary_loss: 0.013919 (0.013920) Loss: 0.46261 (0.45863) +2025-09-13,07:02:13 | INFO | Train Epoch: 5 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.40350 (0.44461) Boundary_loss: 0.013920 (0.013920) Loss: 0.41742 (0.45853) +2025-09-13,07:03:20 | INFO | Train Epoch: 5 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.38650 (0.44448) Boundary_loss: 0.013912 (0.013920) Loss: 0.40041 (0.45840) +2025-09-13,07:04:26 | INFO | Train Epoch: 5 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.46290 (0.44452) Boundary_loss: 0.013912 (0.013920) Loss: 0.47681 (0.45844) +2025-09-13,07:05:32 | INFO | Train Epoch: 5 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.45834 (0.44455) Boundary_loss: 0.013914 (0.013920) Loss: 0.47225 (0.45847) +2025-09-13,07:06:39 | INFO | Train Epoch: 5 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.46231 (0.44459) Boundary_loss: 0.013918 (0.013920) Loss: 0.47622 (0.45852) +2025-09-13,07:07:45 | INFO | Train Epoch: 5 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.42977 (0.44456) Boundary_loss: 0.013918 (0.013920) Loss: 0.44369 (0.45848) +2025-09-13,07:08:51 | INFO | Train Epoch: 5 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.48648 (0.44466) Boundary_loss: 0.013920 (0.013920) Loss: 0.50040 (0.45858) +2025-09-13,07:09:58 | INFO | Train Epoch: 5 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.38730 (0.44452) Boundary_loss: 0.013918 (0.013920) Loss: 0.40122 (0.45844) +2025-09-13,07:11:04 | INFO | Train Epoch: 5 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.51627 (0.44469) Boundary_loss: 0.013915 (0.013920) Loss: 0.53018 (0.45861) +2025-09-13,07:12:10 | INFO | Train Epoch: 5 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.38484 (0.44455) Boundary_loss: 0.013915 (0.013920) Loss: 0.39875 (0.45847) +2025-09-13,07:13:16 | INFO | Train Epoch: 5 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.39867 (0.44445) Boundary_loss: 0.013910 (0.013920) Loss: 0.41258 (0.45837) +2025-09-13,07:14:23 | INFO | Train Epoch: 5 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.53209 (0.44465) Boundary_loss: 0.013918 (0.013920) Loss: 0.54600 (0.45857) +2025-09-13,07:15:29 | INFO | Train Epoch: 5 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.47011 (0.44471) Boundary_loss: 0.013916 (0.013920) Loss: 0.48402 (0.45863) +2025-09-13,07:16:35 | INFO | Train Epoch: 5 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.36441 (0.44452) Boundary_loss: 0.013926 (0.013920) Loss: 0.37833 (0.45844) +2025-09-13,07:17:42 | INFO | Train Epoch: 5 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.47408 (0.44459) Boundary_loss: 0.013918 (0.013920) Loss: 0.48800 (0.45851) +2025-09-13,07:18:48 | INFO | Train Epoch: 5 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.43177 (0.44456) Boundary_loss: 0.013918 (0.013920) Loss: 0.44569 (0.45848) +2025-09-13,07:19:54 | INFO | Train Epoch: 5 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.47169 (0.44462) Boundary_loss: 0.013922 (0.013920) Loss: 0.48562 (0.45854) +2025-09-13,07:21:00 | INFO | Train Epoch: 5 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.56115 (0.44489) Boundary_loss: 0.013909 (0.013920) Loss: 0.57506 (0.45881) +2025-09-13,07:22:07 | INFO | Train Epoch: 5 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.47085 (0.44495) Boundary_loss: 0.013914 (0.013920) Loss: 0.48477 (0.45887) +2025-09-13,07:23:13 | INFO | Train Epoch: 5 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.44262 (0.44494) Boundary_loss: 0.013925 (0.013920) Loss: 0.45655 (0.45886) +2025-09-13,07:24:19 | INFO | Train Epoch: 5 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.46647 (0.44499) Boundary_loss: 0.013911 (0.013920) Loss: 0.48038 (0.45891) +2025-09-13,07:25:26 | INFO | Train Epoch: 5 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.35389 (0.44478) Boundary_loss: 0.013910 (0.013920) Loss: 0.36780 (0.45870) +2025-09-13,07:26:32 | INFO | Train Epoch: 5 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.49005 (0.44489) Boundary_loss: 0.013914 (0.013920) Loss: 0.50396 (0.45881) +2025-09-13,07:27:38 | INFO | Train Epoch: 5 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.40964 (0.44481) Boundary_loss: 0.013916 (0.013920) Loss: 0.42356 (0.45873) +2025-09-13,07:28:44 | INFO | Train Epoch: 5 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.47992 (0.44489) Boundary_loss: 0.013924 (0.013920) Loss: 0.49384 (0.45881) +2025-09-13,07:29:51 | INFO | Train Epoch: 5 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.45017 (0.44490) Boundary_loss: 0.013916 (0.013920) Loss: 0.46409 (0.45882) +2025-09-13,07:30:57 | INFO | Train Epoch: 5 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.48175 (0.44498) Boundary_loss: 0.013914 (0.013920) Loss: 0.49566 (0.45890) +2025-09-13,07:32:03 | INFO | Train Epoch: 5 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.38310 (0.44484) Boundary_loss: 0.013917 (0.013920) Loss: 0.39702 (0.45876) +2025-09-13,07:33:10 | INFO | Train Epoch: 5 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.36432 (0.44466) Boundary_loss: 0.013910 (0.013920) Loss: 0.37823 (0.45858) +2025-09-13,07:34:16 | INFO | Train Epoch: 5 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.46582 (0.44471) Boundary_loss: 0.013916 (0.013920) Loss: 0.47973 (0.45863) +2025-09-13,07:35:22 | INFO | Train Epoch: 5 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.41868 (0.44465) Boundary_loss: 0.013923 (0.013920) Loss: 0.43261 (0.45857) +2025-09-13,07:36:29 | INFO | Train Epoch: 5 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.46614 (0.44470) Boundary_loss: 0.013918 (0.013920) Loss: 0.48006 (0.45862) +2025-09-13,07:37:35 | INFO | Train Epoch: 5 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.49356 (0.44481) Boundary_loss: 0.013920 (0.013920) Loss: 0.50748 (0.45873) +2025-09-13,07:38:41 | INFO | Train Epoch: 5 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.39154 (0.44469) Boundary_loss: 0.013915 (0.013920) Loss: 0.40545 (0.45861) +2025-09-13,07:39:47 | INFO | Train Epoch: 5 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.53449 (0.44489) Boundary_loss: 0.013912 (0.013920) Loss: 0.54840 (0.45881) +2025-09-13,07:40:54 | INFO | Train Epoch: 5 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.40404 (0.44480) Boundary_loss: 0.013921 (0.013920) Loss: 0.41796 (0.45872) +2025-09-13,07:42:00 | INFO | Train Epoch: 5 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.48015 (0.44488) Boundary_loss: 0.013919 (0.013920) Loss: 0.49407 (0.45880) +2025-09-13,07:43:06 | INFO | Train Epoch: 5 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.45385 (0.44490) Boundary_loss: 0.013915 (0.013920) Loss: 0.46776 (0.45881) +2025-09-13,07:44:13 | INFO | Train Epoch: 5 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.42445 (0.44485) Boundary_loss: 0.013911 (0.013920) Loss: 0.43836 (0.45877) +2025-09-13,07:45:19 | INFO | Train Epoch: 5 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.36994 (0.44469) Boundary_loss: 0.013913 (0.013920) Loss: 0.38386 (0.45861) +2025-09-13,07:46:25 | INFO | Train Epoch: 5 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.44262 (0.44468) Boundary_loss: 0.013913 (0.013920) Loss: 0.45653 (0.45860) +2025-09-13,07:47:32 | INFO | Train Epoch: 5 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.44770 (0.44469) Boundary_loss: 0.013915 (0.013920) Loss: 0.46162 (0.45861) +2025-09-13,07:48:38 | INFO | Train Epoch: 5 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.37951 (0.44455) Boundary_loss: 0.013915 (0.013920) Loss: 0.39343 (0.45847) +2025-09-13,07:49:44 | INFO | Train Epoch: 5 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.34594 (0.44434) Boundary_loss: 0.013913 (0.013920) Loss: 0.35985 (0.45826) +2025-09-13,07:50:50 | INFO | Train Epoch: 5 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.44374 (0.44434) Boundary_loss: 0.013919 (0.013920) Loss: 0.45766 (0.45826) +2025-09-13,07:51:57 | INFO | Train Epoch: 5 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.41276 (0.44427) Boundary_loss: 0.013913 (0.013920) Loss: 0.42667 (0.45819) +2025-09-13,07:53:03 | INFO | Train Epoch: 5 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.55277 (0.44450) Boundary_loss: 0.013918 (0.013920) Loss: 0.56669 (0.45842) +2025-09-13,07:54:09 | INFO | Train Epoch: 5 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.35142 (0.44430) Boundary_loss: 0.013917 (0.013920) Loss: 0.36534 (0.45822) +2025-09-13,07:55:16 | INFO | Train Epoch: 5 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.49174 (0.44440) Boundary_loss: 0.013913 (0.013920) Loss: 0.50565 (0.45832) +2025-09-13,07:56:22 | INFO | Train Epoch: 5 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.39253 (0.44429) Boundary_loss: 0.013915 (0.013920) Loss: 0.40644 (0.45821) +2025-09-13,07:57:28 | INFO | Train Epoch: 5 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.46718 (0.44434) Boundary_loss: 0.013912 (0.013920) Loss: 0.48109 (0.45826) +2025-09-13,07:58:35 | INFO | Train Epoch: 5 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.44823 (0.44435) Boundary_loss: 0.013917 (0.013920) Loss: 0.46215 (0.45827) +2025-09-13,07:59:41 | INFO | Train Epoch: 5 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.39177 (0.44424) Boundary_loss: 0.013924 (0.013920) Loss: 0.40570 (0.45816) +2025-09-13,08:00:47 | INFO | Train Epoch: 5 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.50345 (0.44436) Boundary_loss: 0.013919 (0.013920) Loss: 0.51737 (0.45828) +2025-09-13,08:01:54 | INFO | Train Epoch: 5 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.40797 (0.44429) Boundary_loss: 0.013915 (0.013920) Loss: 0.42188 (0.45821) +2025-09-13,08:03:00 | INFO | Train Epoch: 5 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.49542 (0.44440) Boundary_loss: 0.013915 (0.013920) Loss: 0.50933 (0.45831) +2025-09-13,08:04:06 | INFO | Train Epoch: 5 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.42013 (0.44434) Boundary_loss: 0.013929 (0.013920) Loss: 0.43406 (0.45826) +2025-09-13,08:05:13 | INFO | Train Epoch: 5 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.42509 (0.44430) Boundary_loss: 0.013919 (0.013920) Loss: 0.43901 (0.45822) +2025-09-13,08:06:19 | INFO | Train Epoch: 5 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.52333 (0.44447) Boundary_loss: 0.013921 (0.013920) Loss: 0.53725 (0.45839) +2025-09-13,08:07:25 | INFO | Train Epoch: 5 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.49185 (0.44457) Boundary_loss: 0.013927 (0.013920) Loss: 0.50578 (0.45849) +2025-09-13,08:08:32 | INFO | Train Epoch: 5 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.47177 (0.44462) Boundary_loss: 0.013917 (0.013920) Loss: 0.48569 (0.45854) +2025-09-13,08:09:38 | INFO | Train Epoch: 5 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.41908 (0.44457) Boundary_loss: 0.013919 (0.013920) Loss: 0.43300 (0.45849) +2025-09-13,08:10:44 | INFO | Train Epoch: 5 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.44414 (0.44457) Boundary_loss: 0.013919 (0.013920) Loss: 0.45806 (0.45849) +2025-09-13,08:11:50 | INFO | Train Epoch: 5 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.42496 (0.44453) Boundary_loss: 0.013918 (0.013920) Loss: 0.43887 (0.45845) +2025-09-13,08:12:57 | INFO | Train Epoch: 5 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.41983 (0.44448) Boundary_loss: 0.013916 (0.013920) Loss: 0.43375 (0.45840) +2025-09-13,08:14:03 | INFO | Train Epoch: 5 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.48389 (0.44456) Boundary_loss: 0.013926 (0.013920) Loss: 0.49782 (0.45848) +2025-09-13,08:15:09 | INFO | Train Epoch: 5 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.42380 (0.44452) Boundary_loss: 0.013913 (0.013920) Loss: 0.43772 (0.45844) +2025-09-13,08:16:16 | INFO | Train Epoch: 5 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.43929 (0.44451) Boundary_loss: 0.013923 (0.013920) Loss: 0.45321 (0.45843) +2025-09-13,08:17:22 | INFO | Train Epoch: 5 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.39440 (0.44440) Boundary_loss: 0.013915 (0.013920) Loss: 0.40832 (0.45832) +2025-09-13,08:18:28 | INFO | Train Epoch: 5 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.44639 (0.44441) Boundary_loss: 0.013918 (0.013920) Loss: 0.46031 (0.45833) +2025-09-13,08:19:35 | INFO | Train Epoch: 5 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.46582 (0.44445) Boundary_loss: 0.013925 (0.013920) Loss: 0.47975 (0.45837) +2025-09-13,08:20:41 | INFO | Train Epoch: 5 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.40969 (0.44438) Boundary_loss: 0.013914 (0.013920) Loss: 0.42361 (0.45830) +2025-09-13,08:21:47 | INFO | Train Epoch: 5 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.43299 (0.44436) Boundary_loss: 0.013914 (0.013920) Loss: 0.44690 (0.45828) +2025-09-13,08:22:54 | INFO | Train Epoch: 5 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.48747 (0.44445) Boundary_loss: 0.013916 (0.013920) Loss: 0.50138 (0.45836) +2025-09-13,08:24:00 | INFO | Train Epoch: 5 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.46962 (0.44450) Boundary_loss: 0.013924 (0.013920) Loss: 0.48354 (0.45842) +2025-09-13,08:25:06 | INFO | Train Epoch: 5 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.37395 (0.44435) Boundary_loss: 0.013914 (0.013920) Loss: 0.38787 (0.45827) +2025-09-13,08:26:13 | INFO | Train Epoch: 5 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.38913 (0.44424) Boundary_loss: 0.013912 (0.013920) Loss: 0.40304 (0.45816) +2025-09-13,08:27:19 | INFO | Train Epoch: 5 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.40216 (0.44416) Boundary_loss: 0.013926 (0.013920) Loss: 0.41609 (0.45808) +2025-09-13,08:28:25 | INFO | Train Epoch: 5 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.53342 (0.44434) Boundary_loss: 0.013913 (0.013920) Loss: 0.54733 (0.45826) +2025-09-13,08:29:31 | INFO | Train Epoch: 5 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.45766 (0.44436) Boundary_loss: 0.013915 (0.013920) Loss: 0.47157 (0.45828) +2025-09-13,08:30:38 | INFO | Train Epoch: 5 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.43682 (0.44435) Boundary_loss: 0.013909 (0.013920) Loss: 0.45073 (0.45827) +2025-09-13,08:31:44 | INFO | Train Epoch: 5 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.43887 (0.44434) Boundary_loss: 0.013913 (0.013920) Loss: 0.45278 (0.45826) +2025-09-13,08:32:50 | INFO | Train Epoch: 5 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.47151 (0.44439) Boundary_loss: 0.013916 (0.013920) Loss: 0.48542 (0.45831) +2025-09-13,08:33:57 | INFO | Train Epoch: 5 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.39639 (0.44430) Boundary_loss: 0.013926 (0.013920) Loss: 0.41032 (0.45822) +2025-09-13,08:35:03 | INFO | Train Epoch: 5 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.42297 (0.44426) Boundary_loss: 0.013910 (0.013920) Loss: 0.43688 (0.45817) +2025-09-13,08:36:09 | INFO | Train Epoch: 5 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.46543 (0.44430) Boundary_loss: 0.013916 (0.013920) Loss: 0.47935 (0.45822) +2025-09-13,08:37:16 | INFO | Train Epoch: 5 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.52532 (0.44446) Boundary_loss: 0.013913 (0.013920) Loss: 0.53923 (0.45838) +2025-09-13,08:38:22 | INFO | Train Epoch: 5 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.40810 (0.44438) Boundary_loss: 0.013913 (0.013920) Loss: 0.42201 (0.45830) +2025-09-13,08:39:28 | INFO | Train Epoch: 5 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.48199 (0.44446) Boundary_loss: 0.013909 (0.013920) Loss: 0.49590 (0.45838) +2025-09-13,08:40:35 | INFO | Train Epoch: 5 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.37039 (0.44431) Boundary_loss: 0.013911 (0.013920) Loss: 0.38430 (0.45823) +2025-09-13,08:41:41 | INFO | Train Epoch: 5 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.46072 (0.44435) Boundary_loss: 0.013910 (0.013919) Loss: 0.47463 (0.45827) +2025-09-13,08:42:47 | INFO | Train Epoch: 5 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.40264 (0.44426) Boundary_loss: 0.013914 (0.013919) Loss: 0.41656 (0.45818) +2025-09-13,08:43:53 | INFO | Train Epoch: 5 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.46270 (0.44430) Boundary_loss: 0.013927 (0.013919) Loss: 0.47663 (0.45822) +2025-09-13,08:44:56 | INFO | Train Epoch: 5 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.46099 (0.44433) Boundary_loss: 0.013910 (0.013919) Loss: 0.47490 (0.45825) +2025-09-13,08:44:56 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,08:44:56 | INFO | [Epoch 5] Average Step Time: 0.666s | Average GPU Memory: 31.0 GB +2025-09-13,08:44:56 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,08:44:56 | INFO | Starting zero-shot imagenet. +2025-09-13,08:44:56 | INFO | Building zero-shot classifier +2025-09-13,08:45:06 | INFO | Using classifier +2025-09-13,08:46:41 | INFO | Finished zero-shot imagenet. +2025-09-13,08:46:41 | INFO | Eval Epoch: 6 imagenet-zeroshot-val-top1: 0.2583 imagenet-zeroshot-val-top5: 0.5093 +2025-09-13,08:46:46 | INFO | Start epoch 6 +2025-09-13,08:46:48 | INFO | Train Epoch: 6 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.34681 (0.34681) Boundary_loss: 0.013915 (0.013915) Loss: 0.36072 (0.36072) +2025-09-13,08:47:54 | INFO | Train Epoch: 6 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.32296 (0.33488) Boundary_loss: 0.013911 (0.013913) Loss: 0.33687 (0.34880) +2025-09-13,08:49:00 | INFO | Train Epoch: 6 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.37423 (0.34800) Boundary_loss: 0.013910 (0.013912) Loss: 0.38814 (0.36191) +2025-09-13,08:50:06 | INFO | Train Epoch: 6 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.44248 (0.37162) Boundary_loss: 0.013912 (0.013912) Loss: 0.45639 (0.38553) +2025-09-13,08:51:12 | INFO | Train Epoch: 6 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37073 (0.37144) Boundary_loss: 0.013923 (0.013914) Loss: 0.38465 (0.38536) +2025-09-13,08:52:18 | INFO | Train Epoch: 6 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.37304 (0.37171) Boundary_loss: 0.013916 (0.013915) Loss: 0.38695 (0.38562) +2025-09-13,08:53:24 | INFO | Train Epoch: 6 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.40385 (0.37630) Boundary_loss: 0.013911 (0.013914) Loss: 0.41777 (0.39021) +2025-09-13,08:54:30 | INFO | Train Epoch: 6 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.36625 (0.37504) Boundary_loss: 0.013912 (0.013914) Loss: 0.38016 (0.38896) +2025-09-13,08:55:36 | INFO | Train Epoch: 6 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.35377 (0.37268) Boundary_loss: 0.013904 (0.013913) Loss: 0.36767 (0.38659) +2025-09-13,08:56:42 | INFO | Train Epoch: 6 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.35690 (0.37110) Boundary_loss: 0.013909 (0.013912) Loss: 0.37081 (0.38501) +2025-09-13,08:57:48 | INFO | Train Epoch: 6 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.38680 (0.37253) Boundary_loss: 0.013911 (0.013912) Loss: 0.40071 (0.38644) +2025-09-13,08:58:54 | INFO | Train Epoch: 6 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.36998 (0.37232) Boundary_loss: 0.013913 (0.013912) Loss: 0.38389 (0.38623) +2025-09-13,09:00:00 | INFO | Train Epoch: 6 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.34219 (0.37000) Boundary_loss: 0.013915 (0.013913) Loss: 0.35611 (0.38391) +2025-09-13,09:01:06 | INFO | Train Epoch: 6 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.33127 (0.36723) Boundary_loss: 0.013911 (0.013912) Loss: 0.34518 (0.38115) +2025-09-13,09:02:12 | INFO | Train Epoch: 6 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.32600 (0.36448) Boundary_loss: 0.013915 (0.013913) Loss: 0.33992 (0.37840) +2025-09-13,09:03:18 | INFO | Train Epoch: 6 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42318 (0.36815) Boundary_loss: 0.013920 (0.013913) Loss: 0.43710 (0.38207) +2025-09-13,09:04:24 | INFO | Train Epoch: 6 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.41317 (0.37080) Boundary_loss: 0.013920 (0.013913) Loss: 0.42709 (0.38471) +2025-09-13,09:05:30 | INFO | Train Epoch: 6 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.34228 (0.36922) Boundary_loss: 0.013911 (0.013913) Loss: 0.35619 (0.38313) +2025-09-13,09:06:36 | INFO | Train Epoch: 6 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.42375 (0.37209) Boundary_loss: 0.013914 (0.013913) Loss: 0.43767 (0.38600) +2025-09-13,09:07:42 | INFO | Train Epoch: 6 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.35018 (0.37099) Boundary_loss: 0.013910 (0.013913) Loss: 0.36409 (0.38491) +2025-09-13,09:08:48 | INFO | Train Epoch: 6 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.36497 (0.37071) Boundary_loss: 0.013911 (0.013913) Loss: 0.37888 (0.38462) +2025-09-13,09:09:54 | INFO | Train Epoch: 6 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.34028 (0.36932) Boundary_loss: 0.013922 (0.013913) Loss: 0.35420 (0.38324) +2025-09-13,09:11:00 | INFO | Train Epoch: 6 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.46390 (0.37343) Boundary_loss: 0.013916 (0.013914) Loss: 0.47782 (0.38735) +2025-09-13,09:12:06 | INFO | Train Epoch: 6 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.34276 (0.37216) Boundary_loss: 0.013907 (0.013913) Loss: 0.35667 (0.38607) +2025-09-13,09:13:12 | INFO | Train Epoch: 6 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.41503 (0.37387) Boundary_loss: 0.013913 (0.013913) Loss: 0.42894 (0.38778) +2025-09-13,09:14:18 | INFO | Train Epoch: 6 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.37149 (0.37378) Boundary_loss: 0.013909 (0.013913) Loss: 0.38540 (0.38769) +2025-09-13,09:15:24 | INFO | Train Epoch: 6 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.48524 (0.37791) Boundary_loss: 0.013922 (0.013913) Loss: 0.49916 (0.39182) +2025-09-13,09:16:30 | INFO | Train Epoch: 6 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.38761 (0.37825) Boundary_loss: 0.013914 (0.013913) Loss: 0.40152 (0.39217) +2025-09-13,09:17:36 | INFO | Train Epoch: 6 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.40685 (0.37924) Boundary_loss: 0.013919 (0.013914) Loss: 0.42077 (0.39315) +2025-09-13,09:18:42 | INFO | Train Epoch: 6 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.33108 (0.37763) Boundary_loss: 0.013910 (0.013914) Loss: 0.34499 (0.39155) +2025-09-13,09:19:48 | INFO | Train Epoch: 6 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.30629 (0.37533) Boundary_loss: 0.013916 (0.013914) Loss: 0.32021 (0.38925) +2025-09-13,09:20:54 | INFO | Train Epoch: 6 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.40081 (0.37613) Boundary_loss: 0.013921 (0.013914) Loss: 0.41473 (0.39004) +2025-09-13,09:22:00 | INFO | Train Epoch: 6 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.35725 (0.37556) Boundary_loss: 0.013904 (0.013914) Loss: 0.37116 (0.38947) +2025-09-13,09:23:06 | INFO | Train Epoch: 6 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.38437 (0.37582) Boundary_loss: 0.013914 (0.013914) Loss: 0.39828 (0.38973) +2025-09-13,09:24:12 | INFO | Train Epoch: 6 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.35574 (0.37524) Boundary_loss: 0.013919 (0.013914) Loss: 0.36966 (0.38916) +2025-09-13,09:25:18 | INFO | Train Epoch: 6 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.31915 (0.37369) Boundary_loss: 0.013917 (0.013914) Loss: 0.33307 (0.38760) +2025-09-13,09:26:24 | INFO | Train Epoch: 6 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.34319 (0.37286) Boundary_loss: 0.013913 (0.013914) Loss: 0.35710 (0.38677) +2025-09-13,09:27:30 | INFO | Train Epoch: 6 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.38609 (0.37321) Boundary_loss: 0.013921 (0.013914) Loss: 0.40001 (0.38712) +2025-09-13,09:28:36 | INFO | Train Epoch: 6 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.32961 (0.37209) Boundary_loss: 0.013920 (0.013914) Loss: 0.34353 (0.38601) +2025-09-13,09:29:42 | INFO | Train Epoch: 6 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42124 (0.37332) Boundary_loss: 0.013920 (0.013914) Loss: 0.43516 (0.38723) +2025-09-13,09:30:49 | INFO | Train Epoch: 6 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.48081 (0.37594) Boundary_loss: 0.013917 (0.013914) Loss: 0.49472 (0.38986) +2025-09-13,09:31:54 | INFO | Train Epoch: 6 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36515 (0.37568) Boundary_loss: 0.013916 (0.013914) Loss: 0.37907 (0.38960) +2025-09-13,09:33:01 | INFO | Train Epoch: 6 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.33568 (0.37475) Boundary_loss: 0.013921 (0.013915) Loss: 0.34960 (0.38867) +2025-09-13,09:34:07 | INFO | Train Epoch: 6 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.36792 (0.37460) Boundary_loss: 0.013915 (0.013915) Loss: 0.38183 (0.38851) +2025-09-13,09:35:13 | INFO | Train Epoch: 6 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.42832 (0.37579) Boundary_loss: 0.013918 (0.013915) Loss: 0.44224 (0.38971) +2025-09-13,09:36:19 | INFO | Train Epoch: 6 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.31944 (0.37457) Boundary_loss: 0.013908 (0.013914) Loss: 0.33335 (0.38848) +2025-09-13,09:37:25 | INFO | Train Epoch: 6 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.30993 (0.37319) Boundary_loss: 0.013917 (0.013915) Loss: 0.32385 (0.38711) +2025-09-13,09:38:31 | INFO | Train Epoch: 6 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.32360 (0.37216) Boundary_loss: 0.013908 (0.013914) Loss: 0.33751 (0.38607) +2025-09-13,09:39:37 | INFO | Train Epoch: 6 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.49900 (0.37475) Boundary_loss: 0.013911 (0.013914) Loss: 0.51292 (0.38866) +2025-09-13,09:40:43 | INFO | Train Epoch: 6 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.32225 (0.37370) Boundary_loss: 0.013919 (0.013914) Loss: 0.33617 (0.38761) +2025-09-13,09:41:49 | INFO | Train Epoch: 6 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.35792 (0.37339) Boundary_loss: 0.013915 (0.013914) Loss: 0.37183 (0.38730) +2025-09-13,09:42:55 | INFO | Train Epoch: 6 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.32440 (0.37245) Boundary_loss: 0.013910 (0.013914) Loss: 0.33831 (0.38636) +2025-09-13,09:44:01 | INFO | Train Epoch: 6 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.28817 (0.37086) Boundary_loss: 0.013919 (0.013914) Loss: 0.30209 (0.38477) +2025-09-13,09:45:07 | INFO | Train Epoch: 6 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.33020 (0.37010) Boundary_loss: 0.013923 (0.013915) Loss: 0.34412 (0.38402) +2025-09-13,09:46:13 | INFO | Train Epoch: 6 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.34492 (0.36965) Boundary_loss: 0.013910 (0.013915) Loss: 0.35883 (0.38356) +2025-09-13,09:47:19 | INFO | Train Epoch: 6 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.33271 (0.36899) Boundary_loss: 0.013912 (0.013914) Loss: 0.34662 (0.38290) +2025-09-13,09:48:25 | INFO | Train Epoch: 6 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.37591 (0.36911) Boundary_loss: 0.013913 (0.013914) Loss: 0.38983 (0.38302) +2025-09-13,09:49:31 | INFO | Train Epoch: 6 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.43627 (0.37027) Boundary_loss: 0.013913 (0.013914) Loss: 0.45019 (0.38418) +2025-09-13,09:50:37 | INFO | Train Epoch: 6 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.43271 (0.37132) Boundary_loss: 0.013913 (0.013914) Loss: 0.44662 (0.38524) +2025-09-13,09:51:43 | INFO | Train Epoch: 6 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.37547 (0.37139) Boundary_loss: 0.013922 (0.013915) Loss: 0.38939 (0.38531) +2025-09-13,09:52:49 | INFO | Train Epoch: 6 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.37702 (0.37149) Boundary_loss: 0.013919 (0.013915) Loss: 0.39094 (0.38540) +2025-09-13,09:53:55 | INFO | Train Epoch: 6 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.40871 (0.37209) Boundary_loss: 0.013920 (0.013915) Loss: 0.42263 (0.38600) +2025-09-13,09:55:01 | INFO | Train Epoch: 6 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.43937 (0.37315) Boundary_loss: 0.013918 (0.013915) Loss: 0.45329 (0.38707) +2025-09-13,09:56:07 | INFO | Train Epoch: 6 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.35947 (0.37294) Boundary_loss: 0.013910 (0.013915) Loss: 0.37338 (0.38685) +2025-09-13,09:57:13 | INFO | Train Epoch: 6 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.30464 (0.37189) Boundary_loss: 0.013915 (0.013915) Loss: 0.31855 (0.38580) +2025-09-13,09:58:19 | INFO | Train Epoch: 6 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.40862 (0.37245) Boundary_loss: 0.013914 (0.013915) Loss: 0.42254 (0.38636) +2025-09-13,09:59:25 | INFO | Train Epoch: 6 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.30892 (0.37150) Boundary_loss: 0.013914 (0.013915) Loss: 0.32283 (0.38541) +2025-09-13,10:00:31 | INFO | Train Epoch: 6 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.37447 (0.37154) Boundary_loss: 0.013924 (0.013915) Loss: 0.38839 (0.38546) +2025-09-13,10:01:37 | INFO | Train Epoch: 6 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.43293 (0.37243) Boundary_loss: 0.013913 (0.013915) Loss: 0.44685 (0.38635) +2025-09-13,10:02:43 | INFO | Train Epoch: 6 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.42186 (0.37314) Boundary_loss: 0.013917 (0.013915) Loss: 0.43578 (0.38705) +2025-09-13,10:03:49 | INFO | Train Epoch: 6 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.29059 (0.37197) Boundary_loss: 0.013923 (0.013915) Loss: 0.30451 (0.38589) +2025-09-13,10:04:56 | INFO | Train Epoch: 6 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.47230 (0.37337) Boundary_loss: 0.013915 (0.013915) Loss: 0.48622 (0.38728) +2025-09-13,10:06:02 | INFO | Train Epoch: 6 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.34399 (0.37297) Boundary_loss: 0.013915 (0.013915) Loss: 0.35790 (0.38688) +2025-09-13,10:07:08 | INFO | Train Epoch: 6 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.28345 (0.37176) Boundary_loss: 0.013907 (0.013915) Loss: 0.29735 (0.38567) +2025-09-13,10:08:14 | INFO | Train Epoch: 6 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.49060 (0.37334) Boundary_loss: 0.013912 (0.013915) Loss: 0.50451 (0.38725) +2025-09-13,10:09:20 | INFO | Train Epoch: 6 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.32078 (0.37265) Boundary_loss: 0.013912 (0.013915) Loss: 0.33469 (0.38656) +2025-09-13,10:10:26 | INFO | Train Epoch: 6 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.38741 (0.37284) Boundary_loss: 0.013909 (0.013915) Loss: 0.40132 (0.38675) +2025-09-13,10:11:32 | INFO | Train Epoch: 6 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.41954 (0.37344) Boundary_loss: 0.013913 (0.013915) Loss: 0.43345 (0.38735) +2025-09-13,10:12:38 | INFO | Train Epoch: 6 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.34392 (0.37307) Boundary_loss: 0.013922 (0.013915) Loss: 0.35784 (0.38698) +2025-09-13,10:13:44 | INFO | Train Epoch: 6 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.29103 (0.37204) Boundary_loss: 0.013908 (0.013915) Loss: 0.30494 (0.38595) +2025-09-13,10:14:50 | INFO | Train Epoch: 6 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.35267 (0.37180) Boundary_loss: 0.013909 (0.013915) Loss: 0.36658 (0.38572) +2025-09-13,10:15:57 | INFO | Train Epoch: 6 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.44165 (0.37265) Boundary_loss: 0.013911 (0.013915) Loss: 0.45556 (0.38657) +2025-09-13,10:17:03 | INFO | Train Epoch: 6 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.39518 (0.37292) Boundary_loss: 0.013910 (0.013914) Loss: 0.40909 (0.38684) +2025-09-13,10:18:09 | INFO | Train Epoch: 6 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.34569 (0.37260) Boundary_loss: 0.013912 (0.013914) Loss: 0.35960 (0.38651) +2025-09-13,10:19:15 | INFO | Train Epoch: 6 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.36139 (0.37247) Boundary_loss: 0.013914 (0.013914) Loss: 0.37530 (0.38638) +2025-09-13,10:20:21 | INFO | Train Epoch: 6 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.30608 (0.37170) Boundary_loss: 0.013910 (0.013914) Loss: 0.31999 (0.38561) +2025-09-13,10:21:27 | INFO | Train Epoch: 6 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.34081 (0.37134) Boundary_loss: 0.013916 (0.013914) Loss: 0.35473 (0.38526) +2025-09-13,10:22:33 | INFO | Train Epoch: 6 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.34872 (0.37108) Boundary_loss: 0.013908 (0.013914) Loss: 0.36263 (0.38500) +2025-09-13,10:23:39 | INFO | Train Epoch: 6 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.34810 (0.37083) Boundary_loss: 0.013909 (0.013914) Loss: 0.36201 (0.38474) +2025-09-13,10:24:45 | INFO | Train Epoch: 6 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.43856 (0.37158) Boundary_loss: 0.013920 (0.013914) Loss: 0.45248 (0.38549) +2025-09-13,10:25:52 | INFO | Train Epoch: 6 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.37252 (0.37159) Boundary_loss: 0.013909 (0.013914) Loss: 0.38643 (0.38550) +2025-09-13,10:26:58 | INFO | Train Epoch: 6 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.37368 (0.37161) Boundary_loss: 0.013918 (0.013914) Loss: 0.38760 (0.38553) +2025-09-13,10:28:04 | INFO | Train Epoch: 6 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.34303 (0.37130) Boundary_loss: 0.013918 (0.013914) Loss: 0.35695 (0.38522) +2025-09-13,10:29:10 | INFO | Train Epoch: 6 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.41406 (0.37176) Boundary_loss: 0.013914 (0.013914) Loss: 0.42797 (0.38567) +2025-09-13,10:30:16 | INFO | Train Epoch: 6 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.43581 (0.37243) Boundary_loss: 0.013911 (0.013914) Loss: 0.44972 (0.38635) +2025-09-13,10:31:22 | INFO | Train Epoch: 6 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.44008 (0.37314) Boundary_loss: 0.013911 (0.013914) Loss: 0.45399 (0.38705) +2025-09-13,10:32:28 | INFO | Train Epoch: 6 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.32936 (0.37269) Boundary_loss: 0.013925 (0.013914) Loss: 0.34328 (0.38660) +2025-09-13,10:33:34 | INFO | Train Epoch: 6 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.39191 (0.37288) Boundary_loss: 0.013909 (0.013914) Loss: 0.40582 (0.38680) +2025-09-13,10:34:41 | INFO | Train Epoch: 6 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.34111 (0.37256) Boundary_loss: 0.013917 (0.013914) Loss: 0.35503 (0.38648) +2025-09-13,10:35:47 | INFO | Train Epoch: 6 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.40444 (0.37288) Boundary_loss: 0.013914 (0.013914) Loss: 0.41835 (0.38679) +2025-09-13,10:36:53 | INFO | Train Epoch: 6 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.34768 (0.37263) Boundary_loss: 0.013914 (0.013914) Loss: 0.36159 (0.38654) +2025-09-13,10:37:59 | INFO | Train Epoch: 6 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.51949 (0.37407) Boundary_loss: 0.013918 (0.013914) Loss: 0.53341 (0.38798) +2025-09-13,10:39:05 | INFO | Train Epoch: 6 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.41348 (0.37445) Boundary_loss: 0.013905 (0.013914) Loss: 0.42739 (0.38837) +2025-09-13,10:40:11 | INFO | Train Epoch: 6 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.36628 (0.37437) Boundary_loss: 0.013913 (0.013914) Loss: 0.38019 (0.38829) +2025-09-13,10:41:17 | INFO | Train Epoch: 6 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.37918 (0.37442) Boundary_loss: 0.013910 (0.013914) Loss: 0.39309 (0.38833) +2025-09-13,10:42:24 | INFO | Train Epoch: 6 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.39193 (0.37459) Boundary_loss: 0.013912 (0.013914) Loss: 0.40584 (0.38850) +2025-09-13,10:43:30 | INFO | Train Epoch: 6 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.41711 (0.37498) Boundary_loss: 0.013932 (0.013914) Loss: 0.43104 (0.38890) +2025-09-13,10:44:36 | INFO | Train Epoch: 6 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.39844 (0.37520) Boundary_loss: 0.013925 (0.013915) Loss: 0.41237 (0.38911) +2025-09-13,10:45:42 | INFO | Train Epoch: 6 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.40729 (0.37549) Boundary_loss: 0.013914 (0.013915) Loss: 0.42120 (0.38941) +2025-09-13,10:46:48 | INFO | Train Epoch: 6 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.35346 (0.37529) Boundary_loss: 0.013913 (0.013914) Loss: 0.36737 (0.38921) +2025-09-13,10:47:54 | INFO | Train Epoch: 6 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.34747 (0.37504) Boundary_loss: 0.013911 (0.013914) Loss: 0.36138 (0.38896) +2025-09-13,10:49:00 | INFO | Train Epoch: 6 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.33208 (0.37466) Boundary_loss: 0.013921 (0.013915) Loss: 0.34600 (0.38857) +2025-09-13,10:50:06 | INFO | Train Epoch: 6 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.40387 (0.37492) Boundary_loss: 0.013912 (0.013914) Loss: 0.41779 (0.38883) +2025-09-13,10:51:13 | INFO | Train Epoch: 6 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.40534 (0.37519) Boundary_loss: 0.013913 (0.013914) Loss: 0.41925 (0.38910) +2025-09-13,10:52:19 | INFO | Train Epoch: 6 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.39374 (0.37535) Boundary_loss: 0.013913 (0.013914) Loss: 0.40766 (0.38926) +2025-09-13,10:53:25 | INFO | Train Epoch: 6 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.36269 (0.37524) Boundary_loss: 0.013915 (0.013914) Loss: 0.37660 (0.38915) +2025-09-13,10:54:31 | INFO | Train Epoch: 6 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.42662 (0.37568) Boundary_loss: 0.013930 (0.013915) Loss: 0.44055 (0.38959) +2025-09-13,10:55:37 | INFO | Train Epoch: 6 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.32679 (0.37526) Boundary_loss: 0.013917 (0.013915) Loss: 0.34071 (0.38918) +2025-09-13,10:56:43 | INFO | Train Epoch: 6 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.33000 (0.37488) Boundary_loss: 0.013912 (0.013915) Loss: 0.34391 (0.38880) +2025-09-13,10:57:50 | INFO | Train Epoch: 6 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.39440 (0.37504) Boundary_loss: 0.013914 (0.013915) Loss: 0.40832 (0.38896) +2025-09-13,10:58:56 | INFO | Train Epoch: 6 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.30813 (0.37449) Boundary_loss: 0.013910 (0.013915) Loss: 0.32204 (0.38841) +2025-09-13,11:00:02 | INFO | Train Epoch: 6 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.44400 (0.37506) Boundary_loss: 0.013906 (0.013914) Loss: 0.45791 (0.38898) +2025-09-13,11:01:08 | INFO | Train Epoch: 6 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.32664 (0.37467) Boundary_loss: 0.013914 (0.013914) Loss: 0.34056 (0.38858) +2025-09-13,11:02:14 | INFO | Train Epoch: 6 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.43483 (0.37515) Boundary_loss: 0.013911 (0.013914) Loss: 0.44874 (0.38907) +2025-09-13,11:03:20 | INFO | Train Epoch: 6 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.36723 (0.37509) Boundary_loss: 0.013909 (0.013914) Loss: 0.38114 (0.38900) +2025-09-13,11:04:26 | INFO | Train Epoch: 6 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30907 (0.37457) Boundary_loss: 0.013916 (0.013914) Loss: 0.32298 (0.38848) +2025-09-13,11:05:32 | INFO | Train Epoch: 6 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.40403 (0.37480) Boundary_loss: 0.013906 (0.013914) Loss: 0.41794 (0.38871) +2025-09-13,11:06:39 | INFO | Train Epoch: 6 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.38536 (0.37488) Boundary_loss: 0.013923 (0.013914) Loss: 0.39928 (0.38879) +2025-09-13,11:07:45 | INFO | Train Epoch: 6 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.40899 (0.37514) Boundary_loss: 0.013914 (0.013914) Loss: 0.42291 (0.38906) +2025-09-13,11:08:51 | INFO | Train Epoch: 6 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.28180 (0.37443) Boundary_loss: 0.013915 (0.013914) Loss: 0.29571 (0.38834) +2025-09-13,11:09:57 | INFO | Train Epoch: 6 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.35995 (0.37432) Boundary_loss: 0.013911 (0.013914) Loss: 0.37386 (0.38823) +2025-09-13,11:11:03 | INFO | Train Epoch: 6 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.32674 (0.37396) Boundary_loss: 0.013940 (0.013915) Loss: 0.34068 (0.38787) +2025-09-13,11:12:09 | INFO | Train Epoch: 6 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.36125 (0.37386) Boundary_loss: 0.013907 (0.013915) Loss: 0.37516 (0.38777) +2025-09-13,11:13:16 | INFO | Train Epoch: 6 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.37292 (0.37385) Boundary_loss: 0.013917 (0.013915) Loss: 0.38683 (0.38777) +2025-09-13,11:14:22 | INFO | Train Epoch: 6 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.37633 (0.37387) Boundary_loss: 0.013909 (0.013914) Loss: 0.39024 (0.38779) +2025-09-13,11:15:28 | INFO | Train Epoch: 6 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.42814 (0.37427) Boundary_loss: 0.013921 (0.013915) Loss: 0.44206 (0.38819) +2025-09-13,11:16:34 | INFO | Train Epoch: 6 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.33708 (0.37400) Boundary_loss: 0.013921 (0.013915) Loss: 0.35100 (0.38791) +2025-09-13,11:17:40 | INFO | Train Epoch: 6 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.49030 (0.37484) Boundary_loss: 0.013917 (0.013915) Loss: 0.50421 (0.38876) +2025-09-13,11:18:46 | INFO | Train Epoch: 6 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.38434 (0.37491) Boundary_loss: 0.013917 (0.013915) Loss: 0.39825 (0.38882) +2025-09-13,11:19:53 | INFO | Train Epoch: 6 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.33071 (0.37459) Boundary_loss: 0.013914 (0.013915) Loss: 0.34462 (0.38851) +2025-09-13,11:20:59 | INFO | Train Epoch: 6 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.36744 (0.37454) Boundary_loss: 0.013903 (0.013915) Loss: 0.38134 (0.38846) +2025-09-13,11:22:05 | INFO | Train Epoch: 6 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.37048 (0.37451) Boundary_loss: 0.013909 (0.013914) Loss: 0.38439 (0.38843) +2025-09-13,11:23:11 | INFO | Train Epoch: 6 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.34876 (0.37433) Boundary_loss: 0.013910 (0.013914) Loss: 0.36267 (0.38825) +2025-09-13,11:24:17 | INFO | Train Epoch: 6 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.25690 (0.37352) Boundary_loss: 0.013916 (0.013914) Loss: 0.27081 (0.38743) +2025-09-13,11:25:24 | INFO | Train Epoch: 6 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.42681 (0.37389) Boundary_loss: 0.013911 (0.013914) Loss: 0.44072 (0.38780) +2025-09-13,11:26:30 | INFO | Train Epoch: 6 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.38397 (0.37396) Boundary_loss: 0.013914 (0.013914) Loss: 0.39789 (0.38787) +2025-09-13,11:27:36 | INFO | Train Epoch: 6 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.32075 (0.37359) Boundary_loss: 0.013905 (0.013914) Loss: 0.33465 (0.38751) +2025-09-13,11:28:42 | INFO | Train Epoch: 6 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.38316 (0.37366) Boundary_loss: 0.013923 (0.013914) Loss: 0.39709 (0.38757) +2025-09-13,11:29:48 | INFO | Train Epoch: 6 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.41414 (0.37393) Boundary_loss: 0.013907 (0.013914) Loss: 0.42805 (0.38784) +2025-09-13,11:30:55 | INFO | Train Epoch: 6 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.42143 (0.37425) Boundary_loss: 0.013914 (0.013914) Loss: 0.43535 (0.38816) +2025-09-13,11:32:01 | INFO | Train Epoch: 6 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.35049 (0.37409) Boundary_loss: 0.013917 (0.013914) Loss: 0.36441 (0.38800) +2025-09-13,11:33:07 | INFO | Train Epoch: 6 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.34115 (0.37387) Boundary_loss: 0.013912 (0.013914) Loss: 0.35506 (0.38779) +2025-09-13,11:34:13 | INFO | Train Epoch: 6 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.38960 (0.37398) Boundary_loss: 0.013912 (0.013914) Loss: 0.40352 (0.38789) +2025-09-13,11:35:19 | INFO | Train Epoch: 6 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.38951 (0.37408) Boundary_loss: 0.013917 (0.013914) Loss: 0.40343 (0.38799) +2025-09-13,11:36:26 | INFO | Train Epoch: 6 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.31664 (0.37371) Boundary_loss: 0.013910 (0.013914) Loss: 0.33055 (0.38762) +2025-09-13,11:37:32 | INFO | Train Epoch: 6 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.32202 (0.37337) Boundary_loss: 0.013911 (0.013914) Loss: 0.33593 (0.38729) +2025-09-13,11:38:38 | INFO | Train Epoch: 6 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.37983 (0.37342) Boundary_loss: 0.013913 (0.013914) Loss: 0.39374 (0.38733) +2025-09-13,11:39:44 | INFO | Train Epoch: 6 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.33162 (0.37315) Boundary_loss: 0.013918 (0.013914) Loss: 0.34554 (0.38707) +2025-09-13,11:40:50 | INFO | Train Epoch: 6 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.41367 (0.37341) Boundary_loss: 0.013916 (0.013914) Loss: 0.42759 (0.38732) +2025-09-13,11:41:56 | INFO | Train Epoch: 6 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.32135 (0.37308) Boundary_loss: 0.013925 (0.013914) Loss: 0.33528 (0.38700) +2025-09-13,11:43:03 | INFO | Train Epoch: 6 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.36266 (0.37302) Boundary_loss: 0.013916 (0.013914) Loss: 0.37658 (0.38693) +2025-09-13,11:44:09 | INFO | Train Epoch: 6 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.39800 (0.37317) Boundary_loss: 0.013906 (0.013914) Loss: 0.41191 (0.38708) +2025-09-13,11:45:15 | INFO | Train Epoch: 6 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.43350 (0.37354) Boundary_loss: 0.013913 (0.013914) Loss: 0.44742 (0.38745) +2025-09-13,11:46:21 | INFO | Train Epoch: 6 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.36690 (0.37350) Boundary_loss: 0.013917 (0.013914) Loss: 0.38081 (0.38741) +2025-09-13,11:47:27 | INFO | Train Epoch: 6 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.37352 (0.37350) Boundary_loss: 0.013903 (0.013914) Loss: 0.38742 (0.38741) +2025-09-13,11:48:34 | INFO | Train Epoch: 6 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.34646 (0.37334) Boundary_loss: 0.013920 (0.013914) Loss: 0.36038 (0.38725) +2025-09-13,11:49:40 | INFO | Train Epoch: 6 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.39134 (0.37344) Boundary_loss: 0.013911 (0.013914) Loss: 0.40525 (0.38736) +2025-09-13,11:50:46 | INFO | Train Epoch: 6 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.39645 (0.37358) Boundary_loss: 0.013906 (0.013914) Loss: 0.41036 (0.38750) +2025-09-13,11:51:52 | INFO | Train Epoch: 6 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.27311 (0.37299) Boundary_loss: 0.013912 (0.013914) Loss: 0.28702 (0.38690) +2025-09-13,11:52:58 | INFO | Train Epoch: 6 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.43355 (0.37334) Boundary_loss: 0.013915 (0.013914) Loss: 0.44747 (0.38726) +2025-09-13,11:54:04 | INFO | Train Epoch: 6 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.39526 (0.37347) Boundary_loss: 0.013911 (0.013914) Loss: 0.40917 (0.38739) +2025-09-13,11:55:10 | INFO | Train Epoch: 6 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.46810 (0.37402) Boundary_loss: 0.013908 (0.013914) Loss: 0.48201 (0.38794) +2025-09-13,11:56:17 | INFO | Train Epoch: 6 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.41730 (0.37427) Boundary_loss: 0.013913 (0.013914) Loss: 0.43121 (0.38819) +2025-09-13,11:57:23 | INFO | Train Epoch: 6 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.34019 (0.37408) Boundary_loss: 0.013907 (0.013914) Loss: 0.35410 (0.38799) +2025-09-13,11:58:29 | INFO | Train Epoch: 6 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.34789 (0.37393) Boundary_loss: 0.013912 (0.013914) Loss: 0.36180 (0.38784) +2025-09-13,11:59:35 | INFO | Train Epoch: 6 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.41032 (0.37413) Boundary_loss: 0.013909 (0.013914) Loss: 0.42423 (0.38805) +2025-09-13,12:00:41 | INFO | Train Epoch: 6 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.39252 (0.37424) Boundary_loss: 0.013904 (0.013914) Loss: 0.40642 (0.38815) +2025-09-13,12:01:47 | INFO | Train Epoch: 6 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25622 (0.37357) Boundary_loss: 0.013916 (0.013914) Loss: 0.27014 (0.38749) +2025-09-13,12:02:54 | INFO | Train Epoch: 6 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.38297 (0.37363) Boundary_loss: 0.013909 (0.013914) Loss: 0.39688 (0.38754) +2025-09-13,12:04:00 | INFO | Train Epoch: 6 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.32224 (0.37334) Boundary_loss: 0.013911 (0.013914) Loss: 0.33615 (0.38726) +2025-09-13,12:05:06 | INFO | Train Epoch: 6 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.38978 (0.37343) Boundary_loss: 0.013918 (0.013914) Loss: 0.40370 (0.38735) +2025-09-13,12:06:12 | INFO | Train Epoch: 6 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.38160 (0.37348) Boundary_loss: 0.013906 (0.013914) Loss: 0.39551 (0.38739) +2025-09-13,12:07:18 | INFO | Train Epoch: 6 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.36328 (0.37342) Boundary_loss: 0.013909 (0.013914) Loss: 0.37719 (0.38734) +2025-09-13,12:08:25 | INFO | Train Epoch: 6 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.36314 (0.37337) Boundary_loss: 0.013912 (0.013914) Loss: 0.37706 (0.38728) +2025-09-13,12:09:31 | INFO | Train Epoch: 6 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.42034 (0.37362) Boundary_loss: 0.013920 (0.013914) Loss: 0.43426 (0.38753) +2025-09-13,12:10:37 | INFO | Train Epoch: 6 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.31040 (0.37328) Boundary_loss: 0.013909 (0.013914) Loss: 0.32431 (0.38719) +2025-09-13,12:11:43 | INFO | Train Epoch: 6 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.32760 (0.37304) Boundary_loss: 0.013909 (0.013914) Loss: 0.34151 (0.38695) +2025-09-13,12:12:49 | INFO | Train Epoch: 6 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.37509 (0.37305) Boundary_loss: 0.013907 (0.013914) Loss: 0.38899 (0.38696) +2025-09-13,12:13:56 | INFO | Train Epoch: 6 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.32728 (0.37280) Boundary_loss: 0.013917 (0.013914) Loss: 0.34119 (0.38672) +2025-09-13,12:15:02 | INFO | Train Epoch: 6 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.36745 (0.37278) Boundary_loss: 0.013912 (0.013914) Loss: 0.38136 (0.38669) +2025-09-13,12:16:08 | INFO | Train Epoch: 6 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.36154 (0.37272) Boundary_loss: 0.013918 (0.013914) Loss: 0.37546 (0.38663) +2025-09-13,12:17:14 | INFO | Train Epoch: 6 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.46904 (0.37322) Boundary_loss: 0.013911 (0.013914) Loss: 0.48295 (0.38713) +2025-09-13,12:18:20 | INFO | Train Epoch: 6 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.38330 (0.37327) Boundary_loss: 0.013916 (0.013914) Loss: 0.39722 (0.38718) +2025-09-13,12:19:26 | INFO | Train Epoch: 6 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.42094 (0.37352) Boundary_loss: 0.013913 (0.013914) Loss: 0.43486 (0.38743) +2025-09-13,12:20:33 | INFO | Train Epoch: 6 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.33619 (0.37333) Boundary_loss: 0.013904 (0.013914) Loss: 0.35010 (0.38724) +2025-09-13,12:21:39 | INFO | Train Epoch: 6 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.33454 (0.37313) Boundary_loss: 0.013907 (0.013914) Loss: 0.34845 (0.38704) +2025-09-13,12:22:45 | INFO | Train Epoch: 6 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.32265 (0.37287) Boundary_loss: 0.013911 (0.013914) Loss: 0.33656 (0.38678) +2025-09-13,12:23:51 | INFO | Train Epoch: 6 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.32852 (0.37265) Boundary_loss: 0.013915 (0.013914) Loss: 0.34243 (0.38656) +2025-09-13,12:24:57 | INFO | Train Epoch: 6 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.34074 (0.37249) Boundary_loss: 0.013908 (0.013914) Loss: 0.35465 (0.38640) +2025-09-13,12:26:04 | INFO | Train Epoch: 6 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.41818 (0.37272) Boundary_loss: 0.013910 (0.013914) Loss: 0.43209 (0.38663) +2025-09-13,12:27:10 | INFO | Train Epoch: 6 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.39191 (0.37281) Boundary_loss: 0.013912 (0.013914) Loss: 0.40582 (0.38672) +2025-09-13,12:28:16 | INFO | Train Epoch: 6 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.42469 (0.37307) Boundary_loss: 0.013916 (0.013914) Loss: 0.43861 (0.38698) +2025-09-13,12:29:22 | INFO | Train Epoch: 6 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.33654 (0.37289) Boundary_loss: 0.013912 (0.013914) Loss: 0.35046 (0.38680) +2025-09-13,12:30:28 | INFO | Train Epoch: 6 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.40785 (0.37306) Boundary_loss: 0.013909 (0.013914) Loss: 0.42176 (0.38697) +2025-09-13,12:31:34 | INFO | Train Epoch: 6 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.37930 (0.37309) Boundary_loss: 0.013912 (0.013914) Loss: 0.39321 (0.38700) +2025-09-13,12:32:41 | INFO | Train Epoch: 6 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.47166 (0.37357) Boundary_loss: 0.013906 (0.013914) Loss: 0.48557 (0.38748) +2025-09-13,12:33:47 | INFO | Train Epoch: 6 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.39964 (0.37369) Boundary_loss: 0.013906 (0.013914) Loss: 0.41354 (0.38761) +2025-09-13,12:34:53 | INFO | Train Epoch: 6 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.30252 (0.37335) Boundary_loss: 0.013906 (0.013914) Loss: 0.31643 (0.38727) +2025-09-13,12:35:59 | INFO | Train Epoch: 6 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.39842 (0.37347) Boundary_loss: 0.013913 (0.013914) Loss: 0.41233 (0.38739) +2025-09-13,12:37:05 | INFO | Train Epoch: 6 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.33983 (0.37331) Boundary_loss: 0.013917 (0.013914) Loss: 0.35375 (0.38723) +2025-09-13,12:38:12 | INFO | Train Epoch: 6 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.33728 (0.37314) Boundary_loss: 0.013916 (0.013914) Loss: 0.35120 (0.38705) +2025-09-13,12:39:18 | INFO | Train Epoch: 6 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.34194 (0.37299) Boundary_loss: 0.013912 (0.013914) Loss: 0.35585 (0.38691) +2025-09-13,12:40:24 | INFO | Train Epoch: 6 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.33585 (0.37282) Boundary_loss: 0.013916 (0.013914) Loss: 0.34976 (0.38673) +2025-09-13,12:41:30 | INFO | Train Epoch: 6 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.36200 (0.37277) Boundary_loss: 0.013926 (0.013914) Loss: 0.37592 (0.38668) +2025-09-13,12:42:36 | INFO | Train Epoch: 6 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.33846 (0.37261) Boundary_loss: 0.013909 (0.013914) Loss: 0.35237 (0.38652) +2025-09-13,12:43:42 | INFO | Train Epoch: 6 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.35395 (0.37252) Boundary_loss: 0.013909 (0.013914) Loss: 0.36786 (0.38644) +2025-09-13,12:44:48 | INFO | Train Epoch: 6 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.36984 (0.37251) Boundary_loss: 0.013912 (0.013914) Loss: 0.38376 (0.38642) +2025-09-13,12:45:55 | INFO | Train Epoch: 6 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.31640 (0.37225) Boundary_loss: 0.013920 (0.013914) Loss: 0.33032 (0.38617) +2025-09-13,12:47:01 | INFO | Train Epoch: 6 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.35260 (0.37216) Boundary_loss: 0.013910 (0.013914) Loss: 0.36651 (0.38608) +2025-09-13,12:48:07 | INFO | Train Epoch: 6 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.40494 (0.37231) Boundary_loss: 0.013908 (0.013914) Loss: 0.41885 (0.38623) +2025-09-13,12:49:13 | INFO | Train Epoch: 6 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.35003 (0.37221) Boundary_loss: 0.013910 (0.013914) Loss: 0.36394 (0.38612) +2025-09-13,12:50:20 | INFO | Train Epoch: 6 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.40255 (0.37235) Boundary_loss: 0.013914 (0.013914) Loss: 0.41646 (0.38626) +2025-09-13,12:51:26 | INFO | Train Epoch: 6 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.35507 (0.37227) Boundary_loss: 0.013926 (0.013914) Loss: 0.36900 (0.38618) +2025-09-13,12:52:32 | INFO | Train Epoch: 6 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.35208 (0.37218) Boundary_loss: 0.013907 (0.013914) Loss: 0.36599 (0.38609) +2025-09-13,12:53:38 | INFO | Train Epoch: 6 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.37425 (0.37219) Boundary_loss: 0.013910 (0.013914) Loss: 0.38816 (0.38610) +2025-09-13,12:54:44 | INFO | Train Epoch: 6 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.43118 (0.37245) Boundary_loss: 0.013920 (0.013914) Loss: 0.44510 (0.38636) +2025-09-13,12:55:51 | INFO | Train Epoch: 6 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.34966 (0.37235) Boundary_loss: 0.013906 (0.013914) Loss: 0.36357 (0.38626) +2025-09-13,12:56:57 | INFO | Train Epoch: 6 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.35154 (0.37226) Boundary_loss: 0.013908 (0.013914) Loss: 0.36545 (0.38617) +2025-09-13,12:58:03 | INFO | Train Epoch: 6 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.31921 (0.37203) Boundary_loss: 0.013910 (0.013914) Loss: 0.33312 (0.38594) +2025-09-13,12:59:09 | INFO | Train Epoch: 6 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.31767 (0.37179) Boundary_loss: 0.013912 (0.013914) Loss: 0.33158 (0.38570) +2025-09-13,13:00:15 | INFO | Train Epoch: 6 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.38973 (0.37187) Boundary_loss: 0.013908 (0.013914) Loss: 0.40364 (0.38578) +2025-09-13,13:01:21 | INFO | Train Epoch: 6 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.41559 (0.37206) Boundary_loss: 0.013912 (0.013914) Loss: 0.42950 (0.38597) +2025-09-13,13:02:27 | INFO | Train Epoch: 6 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.31450 (0.37181) Boundary_loss: 0.013911 (0.013914) Loss: 0.32841 (0.38572) +2025-09-13,13:03:34 | INFO | Train Epoch: 6 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.36570 (0.37178) Boundary_loss: 0.013924 (0.013914) Loss: 0.37962 (0.38570) +2025-09-13,13:04:40 | INFO | Train Epoch: 6 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.30651 (0.37151) Boundary_loss: 0.013915 (0.013914) Loss: 0.32043 (0.38542) +2025-09-13,13:05:46 | INFO | Train Epoch: 6 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.42923 (0.37175) Boundary_loss: 0.013913 (0.013914) Loss: 0.44315 (0.38566) +2025-09-13,13:06:52 | INFO | Train Epoch: 6 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.35069 (0.37166) Boundary_loss: 0.013911 (0.013914) Loss: 0.36460 (0.38558) +2025-09-13,13:07:58 | INFO | Train Epoch: 6 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.35157 (0.37158) Boundary_loss: 0.013907 (0.013914) Loss: 0.36547 (0.38549) +2025-09-13,13:09:04 | INFO | Train Epoch: 6 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.33611 (0.37143) Boundary_loss: 0.013918 (0.013914) Loss: 0.35003 (0.38534) +2025-09-13,13:10:11 | INFO | Train Epoch: 6 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.42159 (0.37164) Boundary_loss: 0.013913 (0.013914) Loss: 0.43550 (0.38555) +2025-09-13,13:11:17 | INFO | Train Epoch: 6 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.32311 (0.37144) Boundary_loss: 0.013909 (0.013914) Loss: 0.33702 (0.38535) +2025-09-13,13:12:23 | INFO | Train Epoch: 6 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.43079 (0.37168) Boundary_loss: 0.013908 (0.013914) Loss: 0.44469 (0.38560) +2025-09-13,13:13:29 | INFO | Train Epoch: 6 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.36001 (0.37163) Boundary_loss: 0.013921 (0.013914) Loss: 0.37393 (0.38555) +2025-09-13,13:14:35 | INFO | Train Epoch: 6 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.37320 (0.37164) Boundary_loss: 0.013914 (0.013914) Loss: 0.38712 (0.38555) +2025-09-13,13:15:41 | INFO | Train Epoch: 6 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.35994 (0.37159) Boundary_loss: 0.013909 (0.013914) Loss: 0.37385 (0.38551) +2025-09-13,13:16:47 | INFO | Train Epoch: 6 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.44109 (0.37188) Boundary_loss: 0.013909 (0.013914) Loss: 0.45500 (0.38579) +2025-09-13,13:17:54 | INFO | Train Epoch: 6 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.37693 (0.37190) Boundary_loss: 0.013907 (0.013914) Loss: 0.39084 (0.38581) +2025-09-13,13:19:00 | INFO | Train Epoch: 6 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.37563 (0.37191) Boundary_loss: 0.013910 (0.013914) Loss: 0.38954 (0.38582) +2025-09-13,13:20:06 | INFO | Train Epoch: 6 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.32013 (0.37170) Boundary_loss: 0.013906 (0.013913) Loss: 0.33404 (0.38562) +2025-09-13,13:21:12 | INFO | Train Epoch: 6 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.35772 (0.37165) Boundary_loss: 0.013909 (0.013913) Loss: 0.37163 (0.38556) +2025-09-13,13:22:18 | INFO | Train Epoch: 6 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.32156 (0.37145) Boundary_loss: 0.013912 (0.013913) Loss: 0.33547 (0.38536) +2025-09-13,13:23:24 | INFO | Train Epoch: 6 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.37556 (0.37146) Boundary_loss: 0.013908 (0.013913) Loss: 0.38947 (0.38538) +2025-09-13,13:24:30 | INFO | Train Epoch: 6 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.37097 (0.37146) Boundary_loss: 0.013919 (0.013913) Loss: 0.38489 (0.38538) +2025-09-13,13:25:37 | INFO | Train Epoch: 6 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.30972 (0.37122) Boundary_loss: 0.013911 (0.013913) Loss: 0.32364 (0.38513) +2025-09-13,13:26:43 | INFO | Train Epoch: 6 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.35364 (0.37115) Boundary_loss: 0.013906 (0.013913) Loss: 0.36755 (0.38506) +2025-09-13,13:27:49 | INFO | Train Epoch: 6 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.32194 (0.37096) Boundary_loss: 0.013906 (0.013913) Loss: 0.33585 (0.38487) +2025-09-13,13:28:55 | INFO | Train Epoch: 6 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.31351 (0.37073) Boundary_loss: 0.013910 (0.013913) Loss: 0.32742 (0.38465) +2025-09-13,13:30:01 | INFO | Train Epoch: 6 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38094 (0.37077) Boundary_loss: 0.013920 (0.013913) Loss: 0.39486 (0.38469) +2025-09-13,13:31:08 | INFO | Train Epoch: 6 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.47096 (0.37116) Boundary_loss: 0.013908 (0.013913) Loss: 0.48487 (0.38507) +2025-09-13,13:32:14 | INFO | Train Epoch: 6 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37540 (0.37118) Boundary_loss: 0.013912 (0.013913) Loss: 0.38931 (0.38509) +2025-09-13,13:33:20 | INFO | Train Epoch: 6 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.38480 (0.37123) Boundary_loss: 0.013913 (0.013913) Loss: 0.39871 (0.38514) +2025-09-13,13:34:26 | INFO | Train Epoch: 6 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.37299 (0.37124) Boundary_loss: 0.013917 (0.013913) Loss: 0.38691 (0.38515) +2025-09-13,13:35:32 | INFO | Train Epoch: 6 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.37857 (0.37126) Boundary_loss: 0.013905 (0.013913) Loss: 0.39248 (0.38518) +2025-09-13,13:36:38 | INFO | Train Epoch: 6 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.43583 (0.37151) Boundary_loss: 0.013910 (0.013913) Loss: 0.44974 (0.38542) +2025-09-13,13:37:45 | INFO | Train Epoch: 6 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.41333 (0.37167) Boundary_loss: 0.013917 (0.013913) Loss: 0.42725 (0.38558) +2025-09-13,13:38:51 | INFO | Train Epoch: 6 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.33878 (0.37154) Boundary_loss: 0.013916 (0.013913) Loss: 0.35270 (0.38546) +2025-09-13,13:39:57 | INFO | Train Epoch: 6 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.32604 (0.37137) Boundary_loss: 0.013919 (0.013913) Loss: 0.33996 (0.38529) +2025-09-13,13:41:03 | INFO | Train Epoch: 6 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.30808 (0.37114) Boundary_loss: 0.013909 (0.013913) Loss: 0.32199 (0.38505) +2025-09-13,13:42:09 | INFO | Train Epoch: 6 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.33924 (0.37102) Boundary_loss: 0.013921 (0.013913) Loss: 0.35316 (0.38493) +2025-09-13,13:43:15 | INFO | Train Epoch: 6 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.32377 (0.37084) Boundary_loss: 0.013913 (0.013913) Loss: 0.33769 (0.38476) +2025-09-13,13:44:21 | INFO | Train Epoch: 6 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.31263 (0.37063) Boundary_loss: 0.013910 (0.013913) Loss: 0.32654 (0.38454) +2025-09-13,13:45:27 | INFO | Train Epoch: 6 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.41657 (0.37080) Boundary_loss: 0.013913 (0.013913) Loss: 0.43049 (0.38471) +2025-09-13,13:46:33 | INFO | Train Epoch: 6 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.40669 (0.37093) Boundary_loss: 0.013907 (0.013913) Loss: 0.42059 (0.38484) +2025-09-13,13:47:39 | INFO | Train Epoch: 6 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.40994 (0.37107) Boundary_loss: 0.013918 (0.013913) Loss: 0.42386 (0.38498) +2025-09-13,13:48:45 | INFO | Train Epoch: 6 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.37209 (0.37107) Boundary_loss: 0.013905 (0.013913) Loss: 0.38600 (0.38499) +2025-09-13,13:49:51 | INFO | Train Epoch: 6 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.33781 (0.37095) Boundary_loss: 0.013904 (0.013913) Loss: 0.35171 (0.38487) +2025-09-13,13:50:57 | INFO | Train Epoch: 6 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.38164 (0.37099) Boundary_loss: 0.013909 (0.013913) Loss: 0.39555 (0.38491) +2025-09-13,13:52:03 | INFO | Train Epoch: 6 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.36162 (0.37096) Boundary_loss: 0.013916 (0.013913) Loss: 0.37554 (0.38487) +2025-09-13,13:53:10 | INFO | Train Epoch: 6 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.32168 (0.37078) Boundary_loss: 0.013916 (0.013913) Loss: 0.33560 (0.38469) +2025-09-13,13:54:16 | INFO | Train Epoch: 6 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.44387 (0.37104) Boundary_loss: 0.013916 (0.013913) Loss: 0.45779 (0.38496) +2025-09-13,13:55:22 | INFO | Train Epoch: 6 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.43435 (0.37127) Boundary_loss: 0.013912 (0.013913) Loss: 0.44826 (0.38518) +2025-09-13,13:56:28 | INFO | Train Epoch: 6 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.34493 (0.37117) Boundary_loss: 0.013906 (0.013913) Loss: 0.35884 (0.38509) +2025-09-13,13:57:34 | INFO | Train Epoch: 6 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.43259 (0.37139) Boundary_loss: 0.013908 (0.013913) Loss: 0.44650 (0.38530) +2025-09-13,13:58:41 | INFO | Train Epoch: 6 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.32150 (0.37122) Boundary_loss: 0.013912 (0.013913) Loss: 0.33541 (0.38513) +2025-09-13,13:59:47 | INFO | Train Epoch: 6 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.36117 (0.37118) Boundary_loss: 0.013910 (0.013913) Loss: 0.37508 (0.38509) +2025-09-13,14:00:53 | INFO | Train Epoch: 6 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.32309 (0.37101) Boundary_loss: 0.013914 (0.013913) Loss: 0.33700 (0.38493) +2025-09-13,14:01:59 | INFO | Train Epoch: 6 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.39075 (0.37108) Boundary_loss: 0.013910 (0.013913) Loss: 0.40466 (0.38499) +2025-09-13,14:03:05 | INFO | Train Epoch: 6 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.28595 (0.37079) Boundary_loss: 0.013914 (0.013913) Loss: 0.29987 (0.38470) +2025-09-13,14:04:12 | INFO | Train Epoch: 6 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.38857 (0.37085) Boundary_loss: 0.013905 (0.013913) Loss: 0.40247 (0.38476) +2025-09-13,14:05:18 | INFO | Train Epoch: 6 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.41052 (0.37098) Boundary_loss: 0.013916 (0.013913) Loss: 0.42443 (0.38490) +2025-09-13,14:06:24 | INFO | Train Epoch: 6 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.40690 (0.37111) Boundary_loss: 0.013911 (0.013913) Loss: 0.42082 (0.38502) +2025-09-13,14:07:30 | INFO | Train Epoch: 6 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.34898 (0.37103) Boundary_loss: 0.013907 (0.013913) Loss: 0.36289 (0.38494) +2025-09-13,14:08:36 | INFO | Train Epoch: 6 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.42285 (0.37121) Boundary_loss: 0.013917 (0.013913) Loss: 0.43677 (0.38512) +2025-09-13,14:09:42 | INFO | Train Epoch: 6 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.43262 (0.37142) Boundary_loss: 0.013912 (0.013913) Loss: 0.44653 (0.38533) +2025-09-13,14:10:48 | INFO | Train Epoch: 6 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.34593 (0.37133) Boundary_loss: 0.013914 (0.013913) Loss: 0.35985 (0.38524) +2025-09-13,14:11:55 | INFO | Train Epoch: 6 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.36476 (0.37131) Boundary_loss: 0.013915 (0.013913) Loss: 0.37868 (0.38522) +2025-09-13,14:13:01 | INFO | Train Epoch: 6 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.39646 (0.37139) Boundary_loss: 0.013910 (0.013913) Loss: 0.41037 (0.38531) +2025-09-13,14:14:07 | INFO | Train Epoch: 6 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.33082 (0.37126) Boundary_loss: 0.013917 (0.013913) Loss: 0.34473 (0.38517) +2025-09-13,14:15:13 | INFO | Train Epoch: 6 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.38195 (0.37129) Boundary_loss: 0.013907 (0.013913) Loss: 0.39585 (0.38521) +2025-09-13,14:16:20 | INFO | Train Epoch: 6 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.38343 (0.37133) Boundary_loss: 0.013906 (0.013913) Loss: 0.39733 (0.38525) +2025-09-13,14:17:26 | INFO | Train Epoch: 6 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.35889 (0.37129) Boundary_loss: 0.013914 (0.013913) Loss: 0.37280 (0.38521) +2025-09-13,14:18:32 | INFO | Train Epoch: 6 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.38136 (0.37133) Boundary_loss: 0.013911 (0.013913) Loss: 0.39527 (0.38524) +2025-09-13,14:19:38 | INFO | Train Epoch: 6 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.43963 (0.37155) Boundary_loss: 0.013908 (0.013913) Loss: 0.45354 (0.38546) +2025-09-13,14:20:44 | INFO | Train Epoch: 6 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.43139 (0.37175) Boundary_loss: 0.013913 (0.013913) Loss: 0.44530 (0.38566) +2025-09-13,14:21:51 | INFO | Train Epoch: 6 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.28373 (0.37146) Boundary_loss: 0.013907 (0.013913) Loss: 0.29763 (0.38537) +2025-09-13,14:22:57 | INFO | Train Epoch: 6 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.30429 (0.37124) Boundary_loss: 0.013908 (0.013913) Loss: 0.31820 (0.38515) +2025-09-13,14:24:03 | INFO | Train Epoch: 6 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.32279 (0.37108) Boundary_loss: 0.013906 (0.013913) Loss: 0.33670 (0.38499) +2025-09-13,14:25:09 | INFO | Train Epoch: 6 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.28866 (0.37081) Boundary_loss: 0.013931 (0.013913) Loss: 0.30259 (0.38473) +2025-09-13,14:26:15 | INFO | Train Epoch: 6 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.32596 (0.37067) Boundary_loss: 0.013911 (0.013913) Loss: 0.33987 (0.38458) +2025-09-13,14:27:21 | INFO | Train Epoch: 6 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.40305 (0.37077) Boundary_loss: 0.013911 (0.013913) Loss: 0.41696 (0.38469) +2025-09-13,14:28:28 | INFO | Train Epoch: 6 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.28881 (0.37051) Boundary_loss: 0.013929 (0.013913) Loss: 0.30274 (0.38442) +2025-09-13,14:29:34 | INFO | Train Epoch: 6 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.38130 (0.37054) Boundary_loss: 0.013914 (0.013913) Loss: 0.39522 (0.38446) +2025-09-13,14:30:40 | INFO | Train Epoch: 6 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.36826 (0.37054) Boundary_loss: 0.013910 (0.013913) Loss: 0.38217 (0.38445) +2025-09-13,14:31:46 | INFO | Train Epoch: 6 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.38649 (0.37059) Boundary_loss: 0.013912 (0.013913) Loss: 0.40040 (0.38450) +2025-09-13,14:32:52 | INFO | Train Epoch: 6 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.29943 (0.37036) Boundary_loss: 0.013911 (0.013913) Loss: 0.31334 (0.38428) +2025-09-13,14:33:58 | INFO | Train Epoch: 6 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.34633 (0.37029) Boundary_loss: 0.013915 (0.013913) Loss: 0.36024 (0.38420) +2025-09-13,14:35:05 | INFO | Train Epoch: 6 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.38744 (0.37034) Boundary_loss: 0.013915 (0.013913) Loss: 0.40136 (0.38425) +2025-09-13,14:36:11 | INFO | Train Epoch: 6 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.35440 (0.37029) Boundary_loss: 0.013916 (0.013913) Loss: 0.36832 (0.38420) +2025-09-13,14:37:17 | INFO | Train Epoch: 6 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.31906 (0.37013) Boundary_loss: 0.013910 (0.013913) Loss: 0.33297 (0.38404) +2025-09-13,14:38:23 | INFO | Train Epoch: 6 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.39474 (0.37021) Boundary_loss: 0.013907 (0.013913) Loss: 0.40864 (0.38412) +2025-09-13,14:39:29 | INFO | Train Epoch: 6 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.34840 (0.37014) Boundary_loss: 0.013911 (0.013913) Loss: 0.36231 (0.38405) +2025-09-13,14:40:35 | INFO | Train Epoch: 6 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.30213 (0.36993) Boundary_loss: 0.013906 (0.013913) Loss: 0.31604 (0.38384) +2025-09-13,14:41:41 | INFO | Train Epoch: 6 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.44039 (0.37015) Boundary_loss: 0.013905 (0.013913) Loss: 0.45429 (0.38406) +2025-09-13,14:42:48 | INFO | Train Epoch: 6 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.44338 (0.37037) Boundary_loss: 0.013912 (0.013913) Loss: 0.45729 (0.38428) +2025-09-13,14:43:54 | INFO | Train Epoch: 6 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.35748 (0.37033) Boundary_loss: 0.013907 (0.013913) Loss: 0.37139 (0.38424) +2025-09-13,14:45:00 | INFO | Train Epoch: 6 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.39071 (0.37039) Boundary_loss: 0.013916 (0.013913) Loss: 0.40462 (0.38431) +2025-09-13,14:46:06 | INFO | Train Epoch: 6 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.36477 (0.37038) Boundary_loss: 0.013905 (0.013913) Loss: 0.37868 (0.38429) +2025-09-13,14:47:12 | INFO | Train Epoch: 6 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.27041 (0.37007) Boundary_loss: 0.013907 (0.013913) Loss: 0.28431 (0.38399) +2025-09-13,14:48:18 | INFO | Train Epoch: 6 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.31267 (0.36990) Boundary_loss: 0.013907 (0.013913) Loss: 0.32658 (0.38381) +2025-09-13,14:49:25 | INFO | Train Epoch: 6 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.31771 (0.36974) Boundary_loss: 0.013908 (0.013913) Loss: 0.33162 (0.38365) +2025-09-13,14:50:31 | INFO | Train Epoch: 6 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.33825 (0.36964) Boundary_loss: 0.013908 (0.013913) Loss: 0.35216 (0.38356) +2025-09-13,14:51:37 | INFO | Train Epoch: 6 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.30273 (0.36944) Boundary_loss: 0.013904 (0.013913) Loss: 0.31664 (0.38336) +2025-09-13,14:52:43 | INFO | Train Epoch: 6 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.34482 (0.36937) Boundary_loss: 0.013907 (0.013913) Loss: 0.35873 (0.38328) +2025-09-13,14:53:49 | INFO | Train Epoch: 6 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.34158 (0.36929) Boundary_loss: 0.013905 (0.013913) Loss: 0.35549 (0.38320) +2025-09-13,14:54:55 | INFO | Train Epoch: 6 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.47863 (0.36961) Boundary_loss: 0.013913 (0.013913) Loss: 0.49254 (0.38353) +2025-09-13,14:56:02 | INFO | Train Epoch: 6 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.30194 (0.36941) Boundary_loss: 0.013910 (0.013913) Loss: 0.31585 (0.38332) +2025-09-13,14:57:08 | INFO | Train Epoch: 6 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.34095 (0.36933) Boundary_loss: 0.013914 (0.013913) Loss: 0.35486 (0.38324) +2025-09-13,14:58:14 | INFO | Train Epoch: 6 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.33942 (0.36924) Boundary_loss: 0.013908 (0.013913) Loss: 0.35333 (0.38315) +2025-09-13,14:59:20 | INFO | Train Epoch: 6 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.30389 (0.36905) Boundary_loss: 0.013908 (0.013913) Loss: 0.31780 (0.38296) +2025-09-13,15:00:26 | INFO | Train Epoch: 6 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.44538 (0.36927) Boundary_loss: 0.013908 (0.013913) Loss: 0.45929 (0.38318) +2025-09-13,15:01:32 | INFO | Train Epoch: 6 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.40996 (0.36939) Boundary_loss: 0.013910 (0.013913) Loss: 0.42387 (0.38330) +2025-09-13,15:02:39 | INFO | Train Epoch: 6 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.29471 (0.36917) Boundary_loss: 0.013907 (0.013913) Loss: 0.30861 (0.38308) +2025-09-13,15:03:45 | INFO | Train Epoch: 6 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.29991 (0.36897) Boundary_loss: 0.013907 (0.013913) Loss: 0.31381 (0.38288) +2025-09-13,15:04:51 | INFO | Train Epoch: 6 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.38508 (0.36902) Boundary_loss: 0.013925 (0.013913) Loss: 0.39900 (0.38293) +2025-09-13,15:05:57 | INFO | Train Epoch: 6 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.40230 (0.36911) Boundary_loss: 0.013910 (0.013913) Loss: 0.41621 (0.38302) +2025-09-13,15:07:03 | INFO | Train Epoch: 6 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.34950 (0.36906) Boundary_loss: 0.013908 (0.013913) Loss: 0.36341 (0.38297) +2025-09-13,15:08:09 | INFO | Train Epoch: 6 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.30863 (0.36888) Boundary_loss: 0.013917 (0.013913) Loss: 0.32255 (0.38279) +2025-09-13,15:09:16 | INFO | Train Epoch: 6 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.31221 (0.36872) Boundary_loss: 0.013908 (0.013913) Loss: 0.32612 (0.38263) +2025-09-13,15:10:22 | INFO | Train Epoch: 6 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.44155 (0.36893) Boundary_loss: 0.013909 (0.013913) Loss: 0.45546 (0.38284) +2025-09-13,15:11:28 | INFO | Train Epoch: 6 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.40636 (0.36903) Boundary_loss: 0.013905 (0.013913) Loss: 0.42027 (0.38295) +2025-09-13,15:12:34 | INFO | Train Epoch: 6 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.40859 (0.36915) Boundary_loss: 0.013913 (0.013913) Loss: 0.42250 (0.38306) +2025-09-13,15:13:40 | INFO | Train Epoch: 6 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.33956 (0.36906) Boundary_loss: 0.013908 (0.013913) Loss: 0.35347 (0.38298) +2025-09-13,15:14:46 | INFO | Train Epoch: 6 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.45932 (0.36932) Boundary_loss: 0.013913 (0.013913) Loss: 0.47323 (0.38323) +2025-09-13,15:15:52 | INFO | Train Epoch: 6 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.43189 (0.36949) Boundary_loss: 0.013920 (0.013913) Loss: 0.44581 (0.38341) +2025-09-13,15:16:59 | INFO | Train Epoch: 6 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.32023 (0.36936) Boundary_loss: 0.013919 (0.013913) Loss: 0.33415 (0.38327) +2025-09-13,15:18:05 | INFO | Train Epoch: 6 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.41734 (0.36949) Boundary_loss: 0.013915 (0.013913) Loss: 0.43126 (0.38340) +2025-09-13,15:19:11 | INFO | Train Epoch: 6 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.43818 (0.36968) Boundary_loss: 0.013960 (0.013913) Loss: 0.45214 (0.38360) +2025-09-13,15:20:17 | INFO | Train Epoch: 6 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.39153 (0.36974) Boundary_loss: 0.013913 (0.013913) Loss: 0.40544 (0.38366) +2025-09-13,15:21:23 | INFO | Train Epoch: 6 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.34209 (0.36967) Boundary_loss: 0.013906 (0.013913) Loss: 0.35600 (0.38358) +2025-09-13,15:22:29 | INFO | Train Epoch: 6 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.36902 (0.36967) Boundary_loss: 0.013905 (0.013913) Loss: 0.38292 (0.38358) +2025-09-13,15:23:36 | INFO | Train Epoch: 6 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.36767 (0.36966) Boundary_loss: 0.013911 (0.013913) Loss: 0.38158 (0.38357) +2025-09-13,15:24:42 | INFO | Train Epoch: 6 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.44907 (0.36988) Boundary_loss: 0.013925 (0.013913) Loss: 0.46300 (0.38379) +2025-09-13,15:25:48 | INFO | Train Epoch: 6 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.40002 (0.36996) Boundary_loss: 0.013907 (0.013913) Loss: 0.41392 (0.38388) +2025-09-13,15:26:54 | INFO | Train Epoch: 6 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.37486 (0.36998) Boundary_loss: 0.013903 (0.013913) Loss: 0.38876 (0.38389) +2025-09-13,15:28:00 | INFO | Train Epoch: 6 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.35411 (0.36993) Boundary_loss: 0.013910 (0.013913) Loss: 0.36802 (0.38385) +2025-09-13,15:29:07 | INFO | Train Epoch: 6 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.37561 (0.36995) Boundary_loss: 0.013918 (0.013913) Loss: 0.38953 (0.38386) +2025-09-13,15:30:13 | INFO | Train Epoch: 6 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.39544 (0.37002) Boundary_loss: 0.013908 (0.013913) Loss: 0.40935 (0.38393) +2025-09-13,15:31:19 | INFO | Train Epoch: 6 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.37019 (0.37002) Boundary_loss: 0.013907 (0.013913) Loss: 0.38410 (0.38393) +2025-09-13,15:32:25 | INFO | Train Epoch: 6 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.38737 (0.37006) Boundary_loss: 0.013907 (0.013913) Loss: 0.40128 (0.38398) +2025-09-13,15:33:31 | INFO | Train Epoch: 6 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.33939 (0.36998) Boundary_loss: 0.013904 (0.013913) Loss: 0.35329 (0.38389) +2025-09-13,15:34:37 | INFO | Train Epoch: 6 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.32915 (0.36987) Boundary_loss: 0.013905 (0.013913) Loss: 0.34305 (0.38378) +2025-09-13,15:35:44 | INFO | Train Epoch: 6 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.34003 (0.36979) Boundary_loss: 0.013917 (0.013913) Loss: 0.35395 (0.38370) +2025-09-13,15:36:50 | INFO | Train Epoch: 6 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.30598 (0.36962) Boundary_loss: 0.013908 (0.013913) Loss: 0.31989 (0.38353) +2025-09-13,15:37:56 | INFO | Train Epoch: 6 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.32570 (0.36950) Boundary_loss: 0.013903 (0.013913) Loss: 0.33960 (0.38342) +2025-09-13,15:39:02 | INFO | Train Epoch: 6 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.37093 (0.36951) Boundary_loss: 0.013906 (0.013913) Loss: 0.38484 (0.38342) +2025-09-13,15:40:08 | INFO | Train Epoch: 6 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.35205 (0.36946) Boundary_loss: 0.013903 (0.013913) Loss: 0.36595 (0.38337) +2025-09-13,15:41:14 | INFO | Train Epoch: 6 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.35159 (0.36941) Boundary_loss: 0.013908 (0.013913) Loss: 0.36549 (0.38333) +2025-09-13,15:42:21 | INFO | Train Epoch: 6 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.40740 (0.36951) Boundary_loss: 0.013908 (0.013913) Loss: 0.42131 (0.38343) +2025-09-13,15:43:27 | INFO | Train Epoch: 6 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.35156 (0.36947) Boundary_loss: 0.013906 (0.013913) Loss: 0.36547 (0.38338) +2025-09-13,15:44:33 | INFO | Train Epoch: 6 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.38546 (0.36951) Boundary_loss: 0.013907 (0.013913) Loss: 0.39937 (0.38342) +2025-09-13,15:45:39 | INFO | Train Epoch: 6 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.40864 (0.36961) Boundary_loss: 0.013908 (0.013913) Loss: 0.42254 (0.38352) +2025-09-13,15:46:45 | INFO | Train Epoch: 6 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.34286 (0.36954) Boundary_loss: 0.013919 (0.013913) Loss: 0.35678 (0.38345) +2025-09-13,15:47:51 | INFO | Train Epoch: 6 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.29265 (0.36934) Boundary_loss: 0.013910 (0.013913) Loss: 0.30656 (0.38325) +2025-09-13,15:48:58 | INFO | Train Epoch: 6 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.35957 (0.36931) Boundary_loss: 0.013917 (0.013913) Loss: 0.37349 (0.38323) +2025-09-13,15:50:04 | INFO | Train Epoch: 6 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.35967 (0.36929) Boundary_loss: 0.013904 (0.013913) Loss: 0.37358 (0.38320) +2025-09-13,15:51:10 | INFO | Train Epoch: 6 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.38176 (0.36932) Boundary_loss: 0.013912 (0.013913) Loss: 0.39567 (0.38323) +2025-09-13,15:52:16 | INFO | Train Epoch: 6 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.34643 (0.36926) Boundary_loss: 0.013905 (0.013913) Loss: 0.36034 (0.38318) +2025-09-13,15:53:22 | INFO | Train Epoch: 6 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.32071 (0.36914) Boundary_loss: 0.013910 (0.013913) Loss: 0.33462 (0.38305) +2025-09-13,15:54:29 | INFO | Train Epoch: 6 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.25510 (0.36884) Boundary_loss: 0.013912 (0.013913) Loss: 0.26902 (0.38276) +2025-09-13,15:55:35 | INFO | Train Epoch: 6 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.28607 (0.36863) Boundary_loss: 0.013913 (0.013913) Loss: 0.29998 (0.38255) +2025-09-13,15:56:41 | INFO | Train Epoch: 6 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.33654 (0.36855) Boundary_loss: 0.013908 (0.013913) Loss: 0.35045 (0.38246) +2025-09-13,15:57:47 | INFO | Train Epoch: 6 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.39017 (0.36861) Boundary_loss: 0.013903 (0.013913) Loss: 0.40407 (0.38252) +2025-09-13,15:58:53 | INFO | Train Epoch: 6 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.35453 (0.36857) Boundary_loss: 0.013906 (0.013913) Loss: 0.36844 (0.38248) +2025-09-13,15:59:59 | INFO | Train Epoch: 6 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.29426 (0.36838) Boundary_loss: 0.013907 (0.013913) Loss: 0.30817 (0.38229) +2025-09-13,16:01:05 | INFO | Train Epoch: 6 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.36669 (0.36838) Boundary_loss: 0.013905 (0.013913) Loss: 0.38059 (0.38229) +2025-09-13,16:02:11 | INFO | Train Epoch: 6 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.43133 (0.36854) Boundary_loss: 0.013907 (0.013913) Loss: 0.44524 (0.38245) +2025-09-13,16:03:17 | INFO | Train Epoch: 6 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.31750 (0.36841) Boundary_loss: 0.013910 (0.013913) Loss: 0.33141 (0.38232) +2025-09-13,16:04:24 | INFO | Train Epoch: 6 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.38051 (0.36844) Boundary_loss: 0.013906 (0.013913) Loss: 0.39442 (0.38235) +2025-09-13,16:05:30 | INFO | Train Epoch: 6 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.40989 (0.36854) Boundary_loss: 0.013918 (0.013913) Loss: 0.42381 (0.38245) +2025-09-13,16:06:36 | INFO | Train Epoch: 6 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.37195 (0.36855) Boundary_loss: 0.013914 (0.013913) Loss: 0.38587 (0.38246) +2025-09-13,16:07:42 | INFO | Train Epoch: 6 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.39902 (0.36863) Boundary_loss: 0.013911 (0.013913) Loss: 0.41293 (0.38254) +2025-09-13,16:08:48 | INFO | Train Epoch: 6 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.40679 (0.36872) Boundary_loss: 0.013911 (0.013913) Loss: 0.42071 (0.38263) +2025-09-13,16:09:54 | INFO | Train Epoch: 6 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.29746 (0.36854) Boundary_loss: 0.013904 (0.013913) Loss: 0.31136 (0.38246) +2025-09-13,16:11:00 | INFO | Train Epoch: 6 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.42062 (0.36867) Boundary_loss: 0.013909 (0.013913) Loss: 0.43453 (0.38259) +2025-09-13,16:12:06 | INFO | Train Epoch: 6 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.35823 (0.36865) Boundary_loss: 0.013911 (0.013913) Loss: 0.37215 (0.38256) +2025-09-13,16:13:12 | INFO | Train Epoch: 6 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.32808 (0.36855) Boundary_loss: 0.013909 (0.013913) Loss: 0.34199 (0.38246) +2025-09-13,16:14:19 | INFO | Train Epoch: 6 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.38811 (0.36860) Boundary_loss: 0.013918 (0.013913) Loss: 0.40203 (0.38251) +2025-09-13,16:15:25 | INFO | Train Epoch: 6 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.39399 (0.36866) Boundary_loss: 0.013905 (0.013913) Loss: 0.40789 (0.38257) +2025-09-13,16:16:31 | INFO | Train Epoch: 6 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.34866 (0.36861) Boundary_loss: 0.013906 (0.013912) Loss: 0.36256 (0.38252) +2025-09-13,16:17:37 | INFO | Train Epoch: 6 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.39130 (0.36866) Boundary_loss: 0.013909 (0.013912) Loss: 0.40521 (0.38258) +2025-09-13,16:18:43 | INFO | Train Epoch: 6 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.38014 (0.36869) Boundary_loss: 0.013912 (0.013912) Loss: 0.39405 (0.38260) +2025-09-13,16:19:49 | INFO | Train Epoch: 6 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.32514 (0.36859) Boundary_loss: 0.013912 (0.013912) Loss: 0.33905 (0.38250) +2025-09-13,16:20:55 | INFO | Train Epoch: 6 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.24703 (0.36829) Boundary_loss: 0.013906 (0.013912) Loss: 0.26093 (0.38220) +2025-09-13,16:22:02 | INFO | Train Epoch: 6 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.31132 (0.36815) Boundary_loss: 0.013908 (0.013912) Loss: 0.32522 (0.38207) +2025-09-13,16:23:08 | INFO | Train Epoch: 6 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.44910 (0.36835) Boundary_loss: 0.013911 (0.013912) Loss: 0.46301 (0.38226) +2025-09-13,16:24:14 | INFO | Train Epoch: 6 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.46959 (0.36859) Boundary_loss: 0.013909 (0.013912) Loss: 0.48350 (0.38251) +2025-09-13,16:25:20 | INFO | Train Epoch: 6 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.37368 (0.36860) Boundary_loss: 0.013905 (0.013912) Loss: 0.38759 (0.38252) +2025-09-13,16:26:26 | INFO | Train Epoch: 6 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.42223 (0.36873) Boundary_loss: 0.013900 (0.013912) Loss: 0.43613 (0.38265) +2025-09-13,16:27:32 | INFO | Train Epoch: 6 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.43801 (0.36890) Boundary_loss: 0.013905 (0.013912) Loss: 0.45191 (0.38281) +2025-09-13,16:28:38 | INFO | Train Epoch: 6 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.40059 (0.36897) Boundary_loss: 0.013908 (0.013912) Loss: 0.41449 (0.38289) +2025-09-13,16:29:45 | INFO | Train Epoch: 6 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.38286 (0.36901) Boundary_loss: 0.013910 (0.013912) Loss: 0.39677 (0.38292) +2025-09-13,16:30:51 | INFO | Train Epoch: 6 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.33365 (0.36892) Boundary_loss: 0.013910 (0.013912) Loss: 0.34756 (0.38284) +2025-09-13,16:31:57 | INFO | Train Epoch: 6 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.38575 (0.36896) Boundary_loss: 0.013907 (0.013912) Loss: 0.39965 (0.38288) +2025-09-13,16:33:03 | INFO | Train Epoch: 6 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.28444 (0.36876) Boundary_loss: 0.013905 (0.013912) Loss: 0.29835 (0.38268) +2025-09-13,16:34:09 | INFO | Train Epoch: 6 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.27528 (0.36854) Boundary_loss: 0.013907 (0.013912) Loss: 0.28918 (0.38246) +2025-09-13,16:35:16 | INFO | Train Epoch: 6 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35774 (0.36852) Boundary_loss: 0.013923 (0.013912) Loss: 0.37166 (0.38243) +2025-09-13,16:36:22 | INFO | Train Epoch: 6 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.31579 (0.36839) Boundary_loss: 0.013906 (0.013912) Loss: 0.32969 (0.38231) +2025-09-13,16:37:28 | INFO | Train Epoch: 6 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.31625 (0.36827) Boundary_loss: 0.013909 (0.013912) Loss: 0.33016 (0.38219) +2025-09-13,16:38:34 | INFO | Train Epoch: 6 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.41097 (0.36837) Boundary_loss: 0.013909 (0.013912) Loss: 0.42488 (0.38228) +2025-09-13,16:39:40 | INFO | Train Epoch: 6 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.36165 (0.36836) Boundary_loss: 0.013908 (0.013912) Loss: 0.37556 (0.38227) +2025-09-13,16:40:47 | INFO | Train Epoch: 6 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.33562 (0.36828) Boundary_loss: 0.013912 (0.013912) Loss: 0.34953 (0.38219) +2025-09-13,16:41:53 | INFO | Train Epoch: 6 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.39138 (0.36833) Boundary_loss: 0.013905 (0.013912) Loss: 0.40529 (0.38225) +2025-09-13,16:42:59 | INFO | Train Epoch: 6 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.39940 (0.36841) Boundary_loss: 0.013908 (0.013912) Loss: 0.41331 (0.38232) +2025-09-13,16:44:05 | INFO | Train Epoch: 6 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.46604 (0.36863) Boundary_loss: 0.013911 (0.013912) Loss: 0.47995 (0.38254) +2025-09-13,16:45:11 | INFO | Train Epoch: 6 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.37699 (0.36865) Boundary_loss: 0.013903 (0.013912) Loss: 0.39089 (0.38256) +2025-09-13,16:46:18 | INFO | Train Epoch: 6 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.34889 (0.36861) Boundary_loss: 0.013913 (0.013912) Loss: 0.36281 (0.38252) +2025-09-13,16:47:24 | INFO | Train Epoch: 6 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.38124 (0.36863) Boundary_loss: 0.013909 (0.013912) Loss: 0.39515 (0.38255) +2025-09-13,16:48:30 | INFO | Train Epoch: 6 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.24979 (0.36836) Boundary_loss: 0.013911 (0.013912) Loss: 0.26370 (0.38227) +2025-09-13,16:49:36 | INFO | Train Epoch: 6 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.40241 (0.36844) Boundary_loss: 0.013913 (0.013912) Loss: 0.41632 (0.38235) +2025-09-13,16:50:42 | INFO | Train Epoch: 6 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.35494 (0.36841) Boundary_loss: 0.013911 (0.013912) Loss: 0.36886 (0.38232) +2025-09-13,16:51:49 | INFO | Train Epoch: 6 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.31220 (0.36828) Boundary_loss: 0.013913 (0.013912) Loss: 0.32611 (0.38219) +2025-09-13,16:52:55 | INFO | Train Epoch: 6 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.28521 (0.36809) Boundary_loss: 0.013910 (0.013912) Loss: 0.29912 (0.38201) +2025-09-13,16:54:01 | INFO | Train Epoch: 6 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.32702 (0.36800) Boundary_loss: 0.013910 (0.013912) Loss: 0.34094 (0.38191) +2025-09-13,16:55:07 | INFO | Train Epoch: 6 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.42600 (0.36813) Boundary_loss: 0.013911 (0.013912) Loss: 0.43991 (0.38204) +2025-09-13,16:56:14 | INFO | Train Epoch: 6 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.38053 (0.36816) Boundary_loss: 0.013906 (0.013912) Loss: 0.39443 (0.38207) +2025-09-13,16:57:20 | INFO | Train Epoch: 6 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.32301 (0.36806) Boundary_loss: 0.013911 (0.013912) Loss: 0.33692 (0.38197) +2025-09-13,16:58:26 | INFO | Train Epoch: 6 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.31054 (0.36793) Boundary_loss: 0.013908 (0.013912) Loss: 0.32445 (0.38184) +2025-09-13,16:59:32 | INFO | Train Epoch: 6 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.40572 (0.36801) Boundary_loss: 0.013915 (0.013912) Loss: 0.41963 (0.38193) +2025-09-13,17:00:38 | INFO | Train Epoch: 6 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.38928 (0.36806) Boundary_loss: 0.013907 (0.013912) Loss: 0.40318 (0.38197) +2025-09-13,17:01:44 | INFO | Train Epoch: 6 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.31438 (0.36794) Boundary_loss: 0.013909 (0.013912) Loss: 0.32829 (0.38185) +2025-09-13,17:02:51 | INFO | Train Epoch: 6 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.40593 (0.36803) Boundary_loss: 0.013905 (0.013912) Loss: 0.41983 (0.38194) +2025-09-13,17:03:57 | INFO | Train Epoch: 6 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.31674 (0.36791) Boundary_loss: 0.013909 (0.013912) Loss: 0.33065 (0.38183) +2025-09-13,17:05:03 | INFO | Train Epoch: 6 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.31987 (0.36781) Boundary_loss: 0.013905 (0.013912) Loss: 0.33378 (0.38172) +2025-09-13,17:06:09 | INFO | Train Epoch: 6 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.30419 (0.36767) Boundary_loss: 0.013906 (0.013912) Loss: 0.31809 (0.38158) +2025-09-13,17:07:15 | INFO | Train Epoch: 6 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.30604 (0.36753) Boundary_loss: 0.013906 (0.013912) Loss: 0.31995 (0.38144) +2025-09-13,17:08:22 | INFO | Train Epoch: 6 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.34780 (0.36749) Boundary_loss: 0.013906 (0.013912) Loss: 0.36171 (0.38140) +2025-09-13,17:09:28 | INFO | Train Epoch: 6 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.33004 (0.36741) Boundary_loss: 0.013910 (0.013912) Loss: 0.34395 (0.38132) +2025-09-13,17:10:34 | INFO | Train Epoch: 6 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.36667 (0.36740) Boundary_loss: 0.013911 (0.013912) Loss: 0.38058 (0.38132) +2025-09-13,17:11:40 | INFO | Train Epoch: 6 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.34528 (0.36736) Boundary_loss: 0.013911 (0.013912) Loss: 0.35919 (0.38127) +2025-09-13,17:12:46 | INFO | Train Epoch: 6 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.33701 (0.36729) Boundary_loss: 0.013906 (0.013912) Loss: 0.35092 (0.38120) +2025-09-13,17:13:53 | INFO | Train Epoch: 6 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.32682 (0.36720) Boundary_loss: 0.013908 (0.013912) Loss: 0.34073 (0.38111) +2025-09-13,17:14:59 | INFO | Train Epoch: 6 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.37899 (0.36723) Boundary_loss: 0.013903 (0.013912) Loss: 0.39289 (0.38114) +2025-09-13,17:16:05 | INFO | Train Epoch: 6 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.37242 (0.36724) Boundary_loss: 0.013907 (0.013912) Loss: 0.38633 (0.38115) +2025-09-13,17:17:11 | INFO | Train Epoch: 6 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.40305 (0.36732) Boundary_loss: 0.013905 (0.013912) Loss: 0.41695 (0.38123) +2025-09-13,17:18:17 | INFO | Train Epoch: 6 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.39136 (0.36737) Boundary_loss: 0.013911 (0.013912) Loss: 0.40527 (0.38128) +2025-09-13,17:19:24 | INFO | Train Epoch: 6 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.37416 (0.36738) Boundary_loss: 0.013912 (0.013912) Loss: 0.38807 (0.38129) +2025-09-13,17:20:30 | INFO | Train Epoch: 6 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.39253 (0.36744) Boundary_loss: 0.013909 (0.013912) Loss: 0.40644 (0.38135) +2025-09-13,17:21:36 | INFO | Train Epoch: 6 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.38932 (0.36748) Boundary_loss: 0.013912 (0.013912) Loss: 0.40324 (0.38140) +2025-09-13,17:22:42 | INFO | Train Epoch: 6 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.26424 (0.36726) Boundary_loss: 0.013909 (0.013912) Loss: 0.27815 (0.38118) +2025-09-13,17:23:48 | INFO | Train Epoch: 6 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.39444 (0.36732) Boundary_loss: 0.013903 (0.013912) Loss: 0.40834 (0.38123) +2025-09-13,17:24:54 | INFO | Train Epoch: 6 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.36384 (0.36731) Boundary_loss: 0.013908 (0.013912) Loss: 0.37775 (0.38123) +2025-09-13,17:26:00 | INFO | Train Epoch: 6 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.39680 (0.36738) Boundary_loss: 0.013908 (0.013912) Loss: 0.41071 (0.38129) +2025-09-13,17:27:07 | INFO | Train Epoch: 6 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.33298 (0.36730) Boundary_loss: 0.013905 (0.013912) Loss: 0.34689 (0.38122) +2025-09-13,17:28:13 | INFO | Train Epoch: 6 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.35522 (0.36728) Boundary_loss: 0.013911 (0.013912) Loss: 0.36913 (0.38119) +2025-09-13,17:29:19 | INFO | Train Epoch: 6 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.40688 (0.36736) Boundary_loss: 0.013906 (0.013912) Loss: 0.42078 (0.38127) +2025-09-13,17:30:25 | INFO | Train Epoch: 6 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.30760 (0.36724) Boundary_loss: 0.013904 (0.013912) Loss: 0.32151 (0.38115) +2025-09-13,17:31:31 | INFO | Train Epoch: 6 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.37547 (0.36725) Boundary_loss: 0.013907 (0.013912) Loss: 0.38938 (0.38117) +2025-09-13,17:32:37 | INFO | Train Epoch: 6 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.44043 (0.36741) Boundary_loss: 0.013910 (0.013912) Loss: 0.45434 (0.38132) +2025-09-13,17:33:44 | INFO | Train Epoch: 6 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.43415 (0.36755) Boundary_loss: 0.013915 (0.013912) Loss: 0.44806 (0.38146) +2025-09-13,17:34:50 | INFO | Train Epoch: 6 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.43418 (0.36768) Boundary_loss: 0.013910 (0.013912) Loss: 0.44809 (0.38160) +2025-09-13,17:35:56 | INFO | Train Epoch: 6 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28824 (0.36752) Boundary_loss: 0.013911 (0.013912) Loss: 0.30215 (0.38143) +2025-09-13,17:37:02 | INFO | Train Epoch: 6 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.39966 (0.36759) Boundary_loss: 0.013905 (0.013912) Loss: 0.41356 (0.38150) +2025-09-13,17:38:08 | INFO | Train Epoch: 6 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.35583 (0.36756) Boundary_loss: 0.013904 (0.013912) Loss: 0.36973 (0.38147) +2025-09-13,17:39:14 | INFO | Train Epoch: 6 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.34647 (0.36752) Boundary_loss: 0.013910 (0.013912) Loss: 0.36038 (0.38143) +2025-09-13,17:40:21 | INFO | Train Epoch: 6 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.29862 (0.36738) Boundary_loss: 0.013910 (0.013912) Loss: 0.31253 (0.38129) +2025-09-13,17:41:27 | INFO | Train Epoch: 6 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.32805 (0.36729) Boundary_loss: 0.013905 (0.013912) Loss: 0.34196 (0.38121) +2025-09-13,17:42:33 | INFO | Train Epoch: 6 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.35600 (0.36727) Boundary_loss: 0.013910 (0.013912) Loss: 0.36991 (0.38118) +2025-09-13,17:43:39 | INFO | Train Epoch: 6 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.39543 (0.36733) Boundary_loss: 0.013907 (0.013912) Loss: 0.40933 (0.38124) +2025-09-13,17:44:45 | INFO | Train Epoch: 6 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.34392 (0.36728) Boundary_loss: 0.013915 (0.013912) Loss: 0.35784 (0.38119) +2025-09-13,17:45:52 | INFO | Train Epoch: 6 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.38946 (0.36733) Boundary_loss: 0.013906 (0.013912) Loss: 0.40337 (0.38124) +2025-09-13,17:46:58 | INFO | Train Epoch: 6 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.36580 (0.36732) Boundary_loss: 0.013903 (0.013912) Loss: 0.37970 (0.38124) +2025-09-13,17:48:04 | INFO | Train Epoch: 6 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.34948 (0.36729) Boundary_loss: 0.013910 (0.013912) Loss: 0.36339 (0.38120) +2025-09-13,17:49:10 | INFO | Train Epoch: 6 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.29643 (0.36714) Boundary_loss: 0.013907 (0.013912) Loss: 0.31034 (0.38106) +2025-09-13,17:50:16 | INFO | Train Epoch: 6 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.27884 (0.36697) Boundary_loss: 0.013911 (0.013912) Loss: 0.29275 (0.38088) +2025-09-13,17:51:22 | INFO | Train Epoch: 6 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.36597 (0.36696) Boundary_loss: 0.013911 (0.013912) Loss: 0.37988 (0.38087) +2025-09-13,17:52:29 | INFO | Train Epoch: 6 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.34209 (0.36691) Boundary_loss: 0.013917 (0.013912) Loss: 0.35601 (0.38082) +2025-09-13,17:53:35 | INFO | Train Epoch: 6 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.33027 (0.36684) Boundary_loss: 0.013917 (0.013912) Loss: 0.34419 (0.38075) +2025-09-13,17:54:41 | INFO | Train Epoch: 6 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.42053 (0.36695) Boundary_loss: 0.013905 (0.013912) Loss: 0.43444 (0.38086) +2025-09-13,17:55:47 | INFO | Train Epoch: 6 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.35684 (0.36693) Boundary_loss: 0.013909 (0.013912) Loss: 0.37074 (0.38084) +2025-09-13,17:56:54 | INFO | Train Epoch: 6 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.33559 (0.36686) Boundary_loss: 0.013909 (0.013912) Loss: 0.34950 (0.38078) +2025-09-13,17:58:00 | INFO | Train Epoch: 6 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.30333 (0.36674) Boundary_loss: 0.013916 (0.013912) Loss: 0.31724 (0.38065) +2025-09-13,17:59:06 | INFO | Train Epoch: 6 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.38649 (0.36678) Boundary_loss: 0.013908 (0.013912) Loss: 0.40039 (0.38069) +2025-09-13,18:00:12 | INFO | Train Epoch: 6 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.46375 (0.36697) Boundary_loss: 0.013911 (0.013912) Loss: 0.47766 (0.38088) +2025-09-13,18:01:18 | INFO | Train Epoch: 6 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.37953 (0.36699) Boundary_loss: 0.013909 (0.013912) Loss: 0.39344 (0.38091) +2025-09-13,18:02:24 | INFO | Train Epoch: 6 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.35528 (0.36697) Boundary_loss: 0.013928 (0.013912) Loss: 0.36921 (0.38088) +2025-09-13,18:03:31 | INFO | Train Epoch: 6 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.29339 (0.36683) Boundary_loss: 0.013909 (0.013912) Loss: 0.30730 (0.38074) +2025-09-13,18:04:37 | INFO | Train Epoch: 6 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.29513 (0.36668) Boundary_loss: 0.013915 (0.013912) Loss: 0.30904 (0.38060) +2025-09-13,18:05:43 | INFO | Train Epoch: 6 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.39174 (0.36673) Boundary_loss: 0.013908 (0.013912) Loss: 0.40565 (0.38065) +2025-09-13,18:06:49 | INFO | Train Epoch: 6 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.42660 (0.36685) Boundary_loss: 0.013913 (0.013912) Loss: 0.44051 (0.38076) +2025-09-13,18:07:55 | INFO | Train Epoch: 6 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.32793 (0.36677) Boundary_loss: 0.013915 (0.013912) Loss: 0.34185 (0.38069) +2025-09-13,18:09:01 | INFO | Train Epoch: 6 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.37260 (0.36679) Boundary_loss: 0.013907 (0.013912) Loss: 0.38651 (0.38070) +2025-09-13,18:10:08 | INFO | Train Epoch: 6 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.35213 (0.36676) Boundary_loss: 0.013906 (0.013912) Loss: 0.36603 (0.38067) +2025-09-13,18:11:14 | INFO | Train Epoch: 6 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.35272 (0.36673) Boundary_loss: 0.013913 (0.013912) Loss: 0.36663 (0.38064) +2025-09-13,18:12:20 | INFO | Train Epoch: 6 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.34351 (0.36669) Boundary_loss: 0.013906 (0.013912) Loss: 0.35741 (0.38060) +2025-09-13,18:13:26 | INFO | Train Epoch: 6 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.32572 (0.36661) Boundary_loss: 0.013906 (0.013912) Loss: 0.33962 (0.38052) +2025-09-13,18:14:29 | INFO | Train Epoch: 6 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.35038 (0.36657) Boundary_loss: 0.013905 (0.013912) Loss: 0.36429 (0.38049) +2025-09-13,18:14:29 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,18:14:29 | INFO | [Epoch 6] Average Step Time: 0.664s | Average GPU Memory: 31.0 GB +2025-09-13,18:14:29 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,18:14:29 | INFO | Starting zero-shot imagenet. +2025-09-13,18:14:29 | INFO | Building zero-shot classifier +2025-09-13,18:14:39 | INFO | Using classifier +2025-09-13,18:16:10 | INFO | Finished zero-shot imagenet. +2025-09-13,18:16:10 | INFO | Eval Epoch: 7 imagenet-zeroshot-val-top1: 0.2760 imagenet-zeroshot-val-top5: 0.5331 +2025-09-13,18:16:11 | INFO | Start epoch 7 +2025-09-13,18:16:14 | INFO | Train Epoch: 7 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25581 (0.25581) Boundary_loss: 0.013904 (0.013904) Loss: 0.26972 (0.26972) +2025-09-13,18:17:19 | INFO | Train Epoch: 7 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.34739 (0.30160) Boundary_loss: 0.013916 (0.013910) Loss: 0.36131 (0.31551) +2025-09-13,18:18:25 | INFO | Train Epoch: 7 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.31428 (0.30583) Boundary_loss: 0.013912 (0.013911) Loss: 0.32819 (0.31974) +2025-09-13,18:19:31 | INFO | Train Epoch: 7 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.30849 (0.30649) Boundary_loss: 0.013910 (0.013910) Loss: 0.32240 (0.32040) +2025-09-13,18:20:37 | INFO | Train Epoch: 7 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.34371 (0.31394) Boundary_loss: 0.013910 (0.013910) Loss: 0.35762 (0.32785) +2025-09-13,18:21:43 | INFO | Train Epoch: 7 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.31779 (0.31458) Boundary_loss: 0.013907 (0.013910) Loss: 0.33170 (0.32849) +2025-09-13,18:22:49 | INFO | Train Epoch: 7 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.32803 (0.31650) Boundary_loss: 0.013905 (0.013909) Loss: 0.34193 (0.33041) +2025-09-13,18:23:54 | INFO | Train Epoch: 7 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.28337 (0.31236) Boundary_loss: 0.013906 (0.013909) Loss: 0.29728 (0.32627) +2025-09-13,18:25:00 | INFO | Train Epoch: 7 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.29450 (0.31037) Boundary_loss: 0.013912 (0.013909) Loss: 0.30841 (0.32428) +2025-09-13,18:26:06 | INFO | Train Epoch: 7 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.30352 (0.30969) Boundary_loss: 0.013909 (0.013909) Loss: 0.31743 (0.32360) +2025-09-13,18:27:12 | INFO | Train Epoch: 7 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.29363 (0.30823) Boundary_loss: 0.013918 (0.013910) Loss: 0.30755 (0.32214) +2025-09-13,18:28:18 | INFO | Train Epoch: 7 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.31232 (0.30857) Boundary_loss: 0.013909 (0.013910) Loss: 0.32623 (0.32248) +2025-09-13,18:29:24 | INFO | Train Epoch: 7 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.28390 (0.30667) Boundary_loss: 0.013905 (0.013909) Loss: 0.29780 (0.32058) +2025-09-13,18:30:30 | INFO | Train Epoch: 7 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.26007 (0.30334) Boundary_loss: 0.013911 (0.013910) Loss: 0.27398 (0.31725) +2025-09-13,18:31:36 | INFO | Train Epoch: 7 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.30327 (0.30334) Boundary_loss: 0.013909 (0.013909) Loss: 0.31718 (0.31725) +2025-09-13,18:32:42 | INFO | Train Epoch: 7 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.31154 (0.30385) Boundary_loss: 0.013909 (0.013909) Loss: 0.32545 (0.31776) +2025-09-13,18:33:47 | INFO | Train Epoch: 7 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.32341 (0.30500) Boundary_loss: 0.013910 (0.013909) Loss: 0.33732 (0.31891) +2025-09-13,18:34:53 | INFO | Train Epoch: 7 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.28471 (0.30387) Boundary_loss: 0.013907 (0.013909) Loss: 0.29861 (0.31778) +2025-09-13,18:35:59 | INFO | Train Epoch: 7 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.31165 (0.30428) Boundary_loss: 0.013916 (0.013910) Loss: 0.32556 (0.31819) +2025-09-13,18:37:05 | INFO | Train Epoch: 7 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.26924 (0.30253) Boundary_loss: 0.013904 (0.013909) Loss: 0.28314 (0.31644) +2025-09-13,18:38:11 | INFO | Train Epoch: 7 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.38801 (0.30660) Boundary_loss: 0.013909 (0.013909) Loss: 0.40192 (0.32051) +2025-09-13,18:39:17 | INFO | Train Epoch: 7 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.33738 (0.30800) Boundary_loss: 0.013906 (0.013909) Loss: 0.35129 (0.32191) +2025-09-13,18:40:23 | INFO | Train Epoch: 7 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.30178 (0.30773) Boundary_loss: 0.013919 (0.013910) Loss: 0.31570 (0.32164) +2025-09-13,18:41:29 | INFO | Train Epoch: 7 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.34911 (0.30945) Boundary_loss: 0.013904 (0.013909) Loss: 0.36301 (0.32336) +2025-09-13,18:42:34 | INFO | Train Epoch: 7 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32901 (0.31024) Boundary_loss: 0.013907 (0.013909) Loss: 0.34291 (0.32415) +2025-09-13,18:43:40 | INFO | Train Epoch: 7 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.37780 (0.31283) Boundary_loss: 0.013909 (0.013909) Loss: 0.39171 (0.32674) +2025-09-13,18:44:46 | INFO | Train Epoch: 7 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.27089 (0.31128) Boundary_loss: 0.013915 (0.013910) Loss: 0.28481 (0.32519) +2025-09-13,18:45:52 | INFO | Train Epoch: 7 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.25576 (0.30930) Boundary_loss: 0.013915 (0.013910) Loss: 0.26967 (0.32321) +2025-09-13,18:46:58 | INFO | Train Epoch: 7 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.38434 (0.31189) Boundary_loss: 0.013907 (0.013910) Loss: 0.39824 (0.32580) +2025-09-13,18:48:04 | INFO | Train Epoch: 7 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.34594 (0.31302) Boundary_loss: 0.013915 (0.013910) Loss: 0.35985 (0.32693) +2025-09-13,18:49:10 | INFO | Train Epoch: 7 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.33482 (0.31372) Boundary_loss: 0.013911 (0.013910) Loss: 0.34873 (0.32763) +2025-09-13,18:50:16 | INFO | Train Epoch: 7 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.31338 (0.31371) Boundary_loss: 0.013912 (0.013910) Loss: 0.32729 (0.32762) +2025-09-13,18:51:22 | INFO | Train Epoch: 7 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.42240 (0.31701) Boundary_loss: 0.013907 (0.013910) Loss: 0.43631 (0.33092) +2025-09-13,18:52:27 | INFO | Train Epoch: 7 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.34900 (0.31795) Boundary_loss: 0.013906 (0.013910) Loss: 0.36291 (0.33186) +2025-09-13,18:53:33 | INFO | Train Epoch: 7 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.28346 (0.31696) Boundary_loss: 0.013903 (0.013910) Loss: 0.29737 (0.33087) +2025-09-13,18:54:39 | INFO | Train Epoch: 7 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.34859 (0.31784) Boundary_loss: 0.013907 (0.013909) Loss: 0.36249 (0.33175) +2025-09-13,18:55:45 | INFO | Train Epoch: 7 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.37617 (0.31942) Boundary_loss: 0.013904 (0.013909) Loss: 0.39007 (0.33333) +2025-09-13,18:56:51 | INFO | Train Epoch: 7 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.27898 (0.31835) Boundary_loss: 0.013908 (0.013909) Loss: 0.29289 (0.33226) +2025-09-13,18:57:57 | INFO | Train Epoch: 7 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.34273 (0.31898) Boundary_loss: 0.013908 (0.013909) Loss: 0.35664 (0.33289) +2025-09-13,18:59:03 | INFO | Train Epoch: 7 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.27072 (0.31777) Boundary_loss: 0.013905 (0.013909) Loss: 0.28462 (0.33168) +2025-09-13,19:00:09 | INFO | Train Epoch: 7 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.27417 (0.31671) Boundary_loss: 0.013904 (0.013909) Loss: 0.28808 (0.33062) +2025-09-13,19:01:15 | INFO | Train Epoch: 7 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.32501 (0.31691) Boundary_loss: 0.013904 (0.013909) Loss: 0.33892 (0.33082) +2025-09-13,19:02:21 | INFO | Train Epoch: 7 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.34311 (0.31752) Boundary_loss: 0.013909 (0.013909) Loss: 0.35702 (0.33142) +2025-09-13,19:03:27 | INFO | Train Epoch: 7 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.37222 (0.31876) Boundary_loss: 0.013906 (0.013909) Loss: 0.38612 (0.33267) +2025-09-13,19:04:33 | INFO | Train Epoch: 7 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.33434 (0.31911) Boundary_loss: 0.013907 (0.013909) Loss: 0.34824 (0.33301) +2025-09-13,19:05:38 | INFO | Train Epoch: 7 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.26198 (0.31786) Boundary_loss: 0.013904 (0.013909) Loss: 0.27588 (0.33177) +2025-09-13,19:06:44 | INFO | Train Epoch: 7 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.32917 (0.31810) Boundary_loss: 0.013904 (0.013909) Loss: 0.34308 (0.33201) +2025-09-13,19:07:50 | INFO | Train Epoch: 7 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.28418 (0.31740) Boundary_loss: 0.013903 (0.013908) Loss: 0.29808 (0.33131) +2025-09-13,19:08:56 | INFO | Train Epoch: 7 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.27947 (0.31662) Boundary_loss: 0.013906 (0.013908) Loss: 0.29337 (0.33053) +2025-09-13,19:10:02 | INFO | Train Epoch: 7 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.34384 (0.31717) Boundary_loss: 0.013910 (0.013908) Loss: 0.35774 (0.33108) +2025-09-13,19:11:08 | INFO | Train Epoch: 7 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.35352 (0.31788) Boundary_loss: 0.013907 (0.013908) Loss: 0.36743 (0.33179) +2025-09-13,19:12:14 | INFO | Train Epoch: 7 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.31717 (0.31787) Boundary_loss: 0.013904 (0.013908) Loss: 0.33108 (0.33178) +2025-09-13,19:13:20 | INFO | Train Epoch: 7 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.31577 (0.31783) Boundary_loss: 0.013905 (0.013908) Loss: 0.32968 (0.33174) +2025-09-13,19:14:26 | INFO | Train Epoch: 7 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.33916 (0.31822) Boundary_loss: 0.013906 (0.013908) Loss: 0.35306 (0.33213) +2025-09-13,19:15:32 | INFO | Train Epoch: 7 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.24687 (0.31692) Boundary_loss: 0.013905 (0.013908) Loss: 0.26078 (0.33083) +2025-09-13,19:16:38 | INFO | Train Epoch: 7 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.27603 (0.31619) Boundary_loss: 0.013915 (0.013908) Loss: 0.28995 (0.33010) +2025-09-13,19:17:44 | INFO | Train Epoch: 7 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.32015 (0.31626) Boundary_loss: 0.013907 (0.013908) Loss: 0.33405 (0.33017) +2025-09-13,19:18:50 | INFO | Train Epoch: 7 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.30458 (0.31606) Boundary_loss: 0.013906 (0.013908) Loss: 0.31849 (0.32997) +2025-09-13,19:19:56 | INFO | Train Epoch: 7 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.35029 (0.31664) Boundary_loss: 0.013909 (0.013908) Loss: 0.36420 (0.33055) +2025-09-13,19:21:02 | INFO | Train Epoch: 7 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28873 (0.31618) Boundary_loss: 0.013906 (0.013908) Loss: 0.30264 (0.33009) +2025-09-13,19:22:07 | INFO | Train Epoch: 7 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.40047 (0.31756) Boundary_loss: 0.013901 (0.013908) Loss: 0.41437 (0.33147) +2025-09-13,19:23:13 | INFO | Train Epoch: 7 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.27630 (0.31689) Boundary_loss: 0.013907 (0.013908) Loss: 0.29021 (0.33080) +2025-09-13,19:24:19 | INFO | Train Epoch: 7 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.25461 (0.31591) Boundary_loss: 0.013920 (0.013908) Loss: 0.26852 (0.32981) +2025-09-13,19:25:25 | INFO | Train Epoch: 7 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.22942 (0.31455) Boundary_loss: 0.013909 (0.013908) Loss: 0.24333 (0.32846) +2025-09-13,19:26:31 | INFO | Train Epoch: 7 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.27709 (0.31398) Boundary_loss: 0.013902 (0.013908) Loss: 0.29100 (0.32789) +2025-09-13,19:27:37 | INFO | Train Epoch: 7 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.28778 (0.31358) Boundary_loss: 0.013907 (0.013908) Loss: 0.30169 (0.32749) +2025-09-13,19:28:43 | INFO | Train Epoch: 7 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.29217 (0.31326) Boundary_loss: 0.013903 (0.013908) Loss: 0.30608 (0.32717) +2025-09-13,19:29:49 | INFO | Train Epoch: 7 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.37359 (0.31415) Boundary_loss: 0.013906 (0.013908) Loss: 0.38750 (0.32806) +2025-09-13,19:30:55 | INFO | Train Epoch: 7 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.20927 (0.31263) Boundary_loss: 0.013912 (0.013908) Loss: 0.22318 (0.32654) +2025-09-13,19:32:01 | INFO | Train Epoch: 7 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.31032 (0.31260) Boundary_loss: 0.013905 (0.013908) Loss: 0.32422 (0.32650) +2025-09-13,19:33:07 | INFO | Train Epoch: 7 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.23724 (0.31153) Boundary_loss: 0.013909 (0.013908) Loss: 0.25115 (0.32544) +2025-09-13,19:34:13 | INFO | Train Epoch: 7 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.28510 (0.31117) Boundary_loss: 0.013908 (0.013908) Loss: 0.29901 (0.32508) +2025-09-13,19:35:19 | INFO | Train Epoch: 7 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.29659 (0.31097) Boundary_loss: 0.013921 (0.013908) Loss: 0.31051 (0.32488) +2025-09-13,19:36:25 | INFO | Train Epoch: 7 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.36028 (0.31163) Boundary_loss: 0.013901 (0.013908) Loss: 0.37418 (0.32554) +2025-09-13,19:37:31 | INFO | Train Epoch: 7 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.31083 (0.31162) Boundary_loss: 0.013913 (0.013908) Loss: 0.32475 (0.32553) +2025-09-13,19:38:37 | INFO | Train Epoch: 7 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.30888 (0.31159) Boundary_loss: 0.013912 (0.013908) Loss: 0.32279 (0.32550) +2025-09-13,19:39:43 | INFO | Train Epoch: 7 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.23264 (0.31056) Boundary_loss: 0.013911 (0.013908) Loss: 0.24655 (0.32447) +2025-09-13,19:40:49 | INFO | Train Epoch: 7 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.37411 (0.31138) Boundary_loss: 0.013905 (0.013908) Loss: 0.38801 (0.32528) +2025-09-13,19:41:55 | INFO | Train Epoch: 7 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.29333 (0.31115) Boundary_loss: 0.013909 (0.013908) Loss: 0.30723 (0.32506) +2025-09-13,19:43:01 | INFO | Train Epoch: 7 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.31277 (0.31117) Boundary_loss: 0.013909 (0.013908) Loss: 0.32668 (0.32508) +2025-09-13,19:44:07 | INFO | Train Epoch: 7 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.24074 (0.31030) Boundary_loss: 0.013906 (0.013908) Loss: 0.25465 (0.32421) +2025-09-13,19:45:13 | INFO | Train Epoch: 7 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.35483 (0.31084) Boundary_loss: 0.013903 (0.013908) Loss: 0.36873 (0.32475) +2025-09-13,19:46:18 | INFO | Train Epoch: 7 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.31548 (0.31090) Boundary_loss: 0.013907 (0.013908) Loss: 0.32939 (0.32481) +2025-09-13,19:47:24 | INFO | Train Epoch: 7 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.31988 (0.31100) Boundary_loss: 0.013910 (0.013908) Loss: 0.33379 (0.32491) +2025-09-13,19:48:30 | INFO | Train Epoch: 7 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.36323 (0.31162) Boundary_loss: 0.013902 (0.013908) Loss: 0.37714 (0.32553) +2025-09-13,19:49:36 | INFO | Train Epoch: 7 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.28976 (0.31136) Boundary_loss: 0.013908 (0.013908) Loss: 0.30367 (0.32527) +2025-09-13,19:50:42 | INFO | Train Epoch: 7 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.33386 (0.31162) Boundary_loss: 0.013912 (0.013908) Loss: 0.34777 (0.32553) +2025-09-13,19:51:48 | INFO | Train Epoch: 7 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.35811 (0.31215) Boundary_loss: 0.013903 (0.013908) Loss: 0.37201 (0.32606) +2025-09-13,19:52:54 | INFO | Train Epoch: 7 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.29629 (0.31197) Boundary_loss: 0.013903 (0.013908) Loss: 0.31019 (0.32588) +2025-09-13,19:54:00 | INFO | Train Epoch: 7 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.26274 (0.31143) Boundary_loss: 0.013908 (0.013908) Loss: 0.27665 (0.32533) +2025-09-13,19:55:06 | INFO | Train Epoch: 7 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.31604 (0.31148) Boundary_loss: 0.013914 (0.013908) Loss: 0.32996 (0.32539) +2025-09-13,19:56:12 | INFO | Train Epoch: 7 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.23030 (0.31059) Boundary_loss: 0.013907 (0.013908) Loss: 0.24421 (0.32450) +2025-09-13,19:57:18 | INFO | Train Epoch: 7 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.29580 (0.31044) Boundary_loss: 0.013914 (0.013908) Loss: 0.30971 (0.32434) +2025-09-13,19:58:24 | INFO | Train Epoch: 7 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.31006 (0.31043) Boundary_loss: 0.013912 (0.013908) Loss: 0.32397 (0.32434) +2025-09-13,19:59:30 | INFO | Train Epoch: 7 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.29196 (0.31024) Boundary_loss: 0.013913 (0.013908) Loss: 0.30588 (0.32415) +2025-09-13,20:00:36 | INFO | Train Epoch: 7 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.20055 (0.30909) Boundary_loss: 0.013909 (0.013908) Loss: 0.21446 (0.32300) +2025-09-13,20:01:42 | INFO | Train Epoch: 7 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.27575 (0.30875) Boundary_loss: 0.013909 (0.013908) Loss: 0.28966 (0.32266) +2025-09-13,20:02:48 | INFO | Train Epoch: 7 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.26461 (0.30830) Boundary_loss: 0.013903 (0.013908) Loss: 0.27851 (0.32221) +2025-09-13,20:03:54 | INFO | Train Epoch: 7 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.31234 (0.30834) Boundary_loss: 0.013904 (0.013908) Loss: 0.32625 (0.32225) +2025-09-13,20:05:00 | INFO | Train Epoch: 7 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.33810 (0.30864) Boundary_loss: 0.013909 (0.013908) Loss: 0.35201 (0.32255) +2025-09-13,20:06:06 | INFO | Train Epoch: 7 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.27755 (0.30833) Boundary_loss: 0.013907 (0.013908) Loss: 0.29146 (0.32224) +2025-09-13,20:07:12 | INFO | Train Epoch: 7 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25812 (0.30784) Boundary_loss: 0.013906 (0.013908) Loss: 0.27203 (0.32175) +2025-09-13,20:08:18 | INFO | Train Epoch: 7 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.32821 (0.30804) Boundary_loss: 0.013904 (0.013908) Loss: 0.34212 (0.32194) +2025-09-13,20:09:24 | INFO | Train Epoch: 7 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.29097 (0.30787) Boundary_loss: 0.013910 (0.013908) Loss: 0.30487 (0.32178) +2025-09-13,20:10:30 | INFO | Train Epoch: 7 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.32597 (0.30804) Boundary_loss: 0.013926 (0.013908) Loss: 0.33990 (0.32195) +2025-09-13,20:11:36 | INFO | Train Epoch: 7 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.31232 (0.30809) Boundary_loss: 0.013913 (0.013908) Loss: 0.32623 (0.32199) +2025-09-13,20:12:42 | INFO | Train Epoch: 7 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29948 (0.30800) Boundary_loss: 0.013907 (0.013908) Loss: 0.31339 (0.32191) +2025-09-13,20:13:48 | INFO | Train Epoch: 7 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.27892 (0.30774) Boundary_loss: 0.013904 (0.013908) Loss: 0.29282 (0.32164) +2025-09-13,20:14:54 | INFO | Train Epoch: 7 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.28082 (0.30749) Boundary_loss: 0.013913 (0.013908) Loss: 0.29474 (0.32140) +2025-09-13,20:16:00 | INFO | Train Epoch: 7 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.27117 (0.30716) Boundary_loss: 0.013907 (0.013908) Loss: 0.28507 (0.32107) +2025-09-13,20:17:06 | INFO | Train Epoch: 7 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.32102 (0.30728) Boundary_loss: 0.013905 (0.013908) Loss: 0.33493 (0.32119) +2025-09-13,20:18:12 | INFO | Train Epoch: 7 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.40199 (0.30813) Boundary_loss: 0.013902 (0.013908) Loss: 0.41589 (0.32204) +2025-09-13,20:19:18 | INFO | Train Epoch: 7 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.29360 (0.30800) Boundary_loss: 0.013906 (0.013908) Loss: 0.30750 (0.32191) +2025-09-13,20:20:24 | INFO | Train Epoch: 7 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.33764 (0.30826) Boundary_loss: 0.013906 (0.013908) Loss: 0.35154 (0.32217) +2025-09-13,20:21:30 | INFO | Train Epoch: 7 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.33062 (0.30845) Boundary_loss: 0.013911 (0.013908) Loss: 0.34453 (0.32236) +2025-09-13,20:22:36 | INFO | Train Epoch: 7 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.29983 (0.30838) Boundary_loss: 0.013902 (0.013908) Loss: 0.31374 (0.32229) +2025-09-13,20:23:42 | INFO | Train Epoch: 7 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.34048 (0.30865) Boundary_loss: 0.013906 (0.013908) Loss: 0.35439 (0.32256) +2025-09-13,20:24:48 | INFO | Train Epoch: 7 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.37528 (0.30922) Boundary_loss: 0.013904 (0.013908) Loss: 0.38918 (0.32313) +2025-09-13,20:25:54 | INFO | Train Epoch: 7 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.22462 (0.30851) Boundary_loss: 0.013906 (0.013908) Loss: 0.23852 (0.32242) +2025-09-13,20:27:00 | INFO | Train Epoch: 7 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.31749 (0.30858) Boundary_loss: 0.013905 (0.013908) Loss: 0.33139 (0.32249) +2025-09-13,20:28:06 | INFO | Train Epoch: 7 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.26418 (0.30822) Boundary_loss: 0.013907 (0.013908) Loss: 0.27808 (0.32212) +2025-09-13,20:29:12 | INFO | Train Epoch: 7 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.40375 (0.30900) Boundary_loss: 0.013903 (0.013908) Loss: 0.41765 (0.32291) +2025-09-13,20:30:18 | INFO | Train Epoch: 7 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.31419 (0.30904) Boundary_loss: 0.013903 (0.013908) Loss: 0.32810 (0.32295) +2025-09-13,20:31:24 | INFO | Train Epoch: 7 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.36442 (0.30949) Boundary_loss: 0.013905 (0.013908) Loss: 0.37832 (0.32340) +2025-09-13,20:32:30 | INFO | Train Epoch: 7 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.30246 (0.30943) Boundary_loss: 0.013907 (0.013908) Loss: 0.31637 (0.32334) +2025-09-13,20:33:36 | INFO | Train Epoch: 7 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.31713 (0.30949) Boundary_loss: 0.013905 (0.013908) Loss: 0.33103 (0.32340) +2025-09-13,20:34:42 | INFO | Train Epoch: 7 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.25731 (0.30908) Boundary_loss: 0.013908 (0.013908) Loss: 0.27122 (0.32299) +2025-09-13,20:35:48 | INFO | Train Epoch: 7 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.34423 (0.30936) Boundary_loss: 0.013903 (0.013908) Loss: 0.35813 (0.32326) +2025-09-13,20:36:55 | INFO | Train Epoch: 7 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.25902 (0.30897) Boundary_loss: 0.013909 (0.013908) Loss: 0.27293 (0.32287) +2025-09-13,20:38:01 | INFO | Train Epoch: 7 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.39548 (0.30963) Boundary_loss: 0.013910 (0.013908) Loss: 0.40939 (0.32354) +2025-09-13,20:39:07 | INFO | Train Epoch: 7 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.30961 (0.30963) Boundary_loss: 0.013910 (0.013908) Loss: 0.32352 (0.32354) +2025-09-13,20:40:13 | INFO | Train Epoch: 7 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.36900 (0.31008) Boundary_loss: 0.013907 (0.013908) Loss: 0.38290 (0.32399) +2025-09-13,20:41:19 | INFO | Train Epoch: 7 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.25972 (0.30970) Boundary_loss: 0.013910 (0.013908) Loss: 0.27363 (0.32361) +2025-09-13,20:42:25 | INFO | Train Epoch: 7 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.27806 (0.30947) Boundary_loss: 0.013906 (0.013908) Loss: 0.29197 (0.32337) +2025-09-13,20:43:31 | INFO | Train Epoch: 7 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.30076 (0.30940) Boundary_loss: 0.013916 (0.013908) Loss: 0.31468 (0.32331) +2025-09-13,20:44:37 | INFO | Train Epoch: 7 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.33702 (0.30961) Boundary_loss: 0.013913 (0.013908) Loss: 0.35093 (0.32351) +2025-09-13,20:45:43 | INFO | Train Epoch: 7 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.25989 (0.30924) Boundary_loss: 0.013909 (0.013908) Loss: 0.27380 (0.32315) +2025-09-13,20:46:49 | INFO | Train Epoch: 7 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.33100 (0.30940) Boundary_loss: 0.013903 (0.013908) Loss: 0.34490 (0.32331) +2025-09-13,20:47:55 | INFO | Train Epoch: 7 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.30399 (0.30936) Boundary_loss: 0.013909 (0.013908) Loss: 0.31790 (0.32327) +2025-09-13,20:49:01 | INFO | Train Epoch: 7 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.32052 (0.30944) Boundary_loss: 0.013905 (0.013908) Loss: 0.33443 (0.32335) +2025-09-13,20:50:07 | INFO | Train Epoch: 7 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.33095 (0.30959) Boundary_loss: 0.013903 (0.013908) Loss: 0.34485 (0.32350) +2025-09-13,20:51:13 | INFO | Train Epoch: 7 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.32957 (0.30973) Boundary_loss: 0.013905 (0.013908) Loss: 0.34348 (0.32364) +2025-09-13,20:52:19 | INFO | Train Epoch: 7 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.27952 (0.30952) Boundary_loss: 0.013902 (0.013908) Loss: 0.29342 (0.32343) +2025-09-13,20:53:25 | INFO | Train Epoch: 7 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.29377 (0.30941) Boundary_loss: 0.013902 (0.013908) Loss: 0.30767 (0.32332) +2025-09-13,20:54:31 | INFO | Train Epoch: 7 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.33651 (0.30960) Boundary_loss: 0.013910 (0.013908) Loss: 0.35042 (0.32351) +2025-09-13,20:55:37 | INFO | Train Epoch: 7 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.36931 (0.31001) Boundary_loss: 0.013908 (0.013908) Loss: 0.38322 (0.32392) +2025-09-13,20:56:43 | INFO | Train Epoch: 7 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.25761 (0.30965) Boundary_loss: 0.013906 (0.013908) Loss: 0.27152 (0.32356) +2025-09-13,20:57:49 | INFO | Train Epoch: 7 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.27146 (0.30939) Boundary_loss: 0.013908 (0.013908) Loss: 0.28537 (0.32330) +2025-09-13,20:58:55 | INFO | Train Epoch: 7 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.28290 (0.30922) Boundary_loss: 0.013906 (0.013908) Loss: 0.29680 (0.32312) +2025-09-13,21:00:01 | INFO | Train Epoch: 7 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.26865 (0.30895) Boundary_loss: 0.013904 (0.013908) Loss: 0.28255 (0.32285) +2025-09-13,21:01:07 | INFO | Train Epoch: 7 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.25103 (0.30856) Boundary_loss: 0.013902 (0.013908) Loss: 0.26493 (0.32247) +2025-09-13,21:02:13 | INFO | Train Epoch: 7 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.36627 (0.30894) Boundary_loss: 0.013909 (0.013908) Loss: 0.38018 (0.32285) +2025-09-13,21:03:19 | INFO | Train Epoch: 7 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.34524 (0.30918) Boundary_loss: 0.013904 (0.013908) Loss: 0.35915 (0.32309) +2025-09-13,21:04:25 | INFO | Train Epoch: 7 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.30346 (0.30914) Boundary_loss: 0.013904 (0.013908) Loss: 0.31736 (0.32305) +2025-09-13,21:05:31 | INFO | Train Epoch: 7 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.39979 (0.30973) Boundary_loss: 0.013910 (0.013908) Loss: 0.41370 (0.32364) +2025-09-13,21:06:37 | INFO | Train Epoch: 7 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.36593 (0.31009) Boundary_loss: 0.013908 (0.013908) Loss: 0.37983 (0.32400) +2025-09-13,21:07:43 | INFO | Train Epoch: 7 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.23542 (0.30961) Boundary_loss: 0.013909 (0.013908) Loss: 0.24933 (0.32352) +2025-09-13,21:08:49 | INFO | Train Epoch: 7 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.39500 (0.31015) Boundary_loss: 0.013909 (0.013908) Loss: 0.40891 (0.32406) +2025-09-13,21:09:55 | INFO | Train Epoch: 7 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.27030 (0.30990) Boundary_loss: 0.013908 (0.013908) Loss: 0.28421 (0.32381) +2025-09-13,21:11:01 | INFO | Train Epoch: 7 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.29601 (0.30982) Boundary_loss: 0.013906 (0.013908) Loss: 0.30992 (0.32372) +2025-09-13,21:12:07 | INFO | Train Epoch: 7 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.27106 (0.30957) Boundary_loss: 0.013910 (0.013908) Loss: 0.28497 (0.32348) +2025-09-13,21:13:13 | INFO | Train Epoch: 7 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.28112 (0.30940) Boundary_loss: 0.013905 (0.013908) Loss: 0.29503 (0.32331) +2025-09-13,21:14:19 | INFO | Train Epoch: 7 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.27477 (0.30919) Boundary_loss: 0.013905 (0.013908) Loss: 0.28868 (0.32309) +2025-09-13,21:15:25 | INFO | Train Epoch: 7 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.37054 (0.30956) Boundary_loss: 0.013904 (0.013908) Loss: 0.38445 (0.32347) +2025-09-13,21:16:31 | INFO | Train Epoch: 7 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.30934 (0.30956) Boundary_loss: 0.013906 (0.013908) Loss: 0.32325 (0.32347) +2025-09-13,21:17:37 | INFO | Train Epoch: 7 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.28735 (0.30943) Boundary_loss: 0.013908 (0.013908) Loss: 0.30126 (0.32333) +2025-09-13,21:18:43 | INFO | Train Epoch: 7 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.32501 (0.30952) Boundary_loss: 0.013906 (0.013908) Loss: 0.33892 (0.32343) +2025-09-13,21:19:49 | INFO | Train Epoch: 7 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.23505 (0.30908) Boundary_loss: 0.013905 (0.013908) Loss: 0.24895 (0.32298) +2025-09-13,21:20:55 | INFO | Train Epoch: 7 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.28585 (0.30894) Boundary_loss: 0.013911 (0.013908) Loss: 0.29977 (0.32285) +2025-09-13,21:22:01 | INFO | Train Epoch: 7 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.24446 (0.30856) Boundary_loss: 0.013906 (0.013908) Loss: 0.25837 (0.32247) +2025-09-13,21:23:07 | INFO | Train Epoch: 7 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.25919 (0.30827) Boundary_loss: 0.013907 (0.013908) Loss: 0.27310 (0.32218) +2025-09-13,21:24:13 | INFO | Train Epoch: 7 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.32435 (0.30836) Boundary_loss: 0.013907 (0.013908) Loss: 0.33825 (0.32227) +2025-09-13,21:25:19 | INFO | Train Epoch: 7 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.40824 (0.30894) Boundary_loss: 0.013904 (0.013908) Loss: 0.42214 (0.32285) +2025-09-13,21:26:25 | INFO | Train Epoch: 7 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.27112 (0.30872) Boundary_loss: 0.013908 (0.013908) Loss: 0.28503 (0.32263) +2025-09-13,21:27:31 | INFO | Train Epoch: 7 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.20833 (0.30815) Boundary_loss: 0.013914 (0.013908) Loss: 0.22225 (0.32206) +2025-09-13,21:28:37 | INFO | Train Epoch: 7 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.29289 (0.30806) Boundary_loss: 0.013912 (0.013908) Loss: 0.30680 (0.32197) +2025-09-13,21:29:43 | INFO | Train Epoch: 7 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.27860 (0.30790) Boundary_loss: 0.013918 (0.013908) Loss: 0.29251 (0.32180) +2025-09-13,21:30:49 | INFO | Train Epoch: 7 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.27754 (0.30773) Boundary_loss: 0.013909 (0.013908) Loss: 0.29145 (0.32163) +2025-09-13,21:31:55 | INFO | Train Epoch: 7 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.28360 (0.30759) Boundary_loss: 0.013920 (0.013908) Loss: 0.29752 (0.32150) +2025-09-13,21:33:01 | INFO | Train Epoch: 7 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.26557 (0.30736) Boundary_loss: 0.013903 (0.013908) Loss: 0.27948 (0.32127) +2025-09-13,21:34:07 | INFO | Train Epoch: 7 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.22582 (0.30691) Boundary_loss: 0.013902 (0.013908) Loss: 0.23972 (0.32082) +2025-09-13,21:35:13 | INFO | Train Epoch: 7 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.26299 (0.30667) Boundary_loss: 0.013911 (0.013908) Loss: 0.27690 (0.32057) +2025-09-13,21:36:19 | INFO | Train Epoch: 7 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.36336 (0.30698) Boundary_loss: 0.013904 (0.013908) Loss: 0.37726 (0.32088) +2025-09-13,21:37:25 | INFO | Train Epoch: 7 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.33734 (0.30714) Boundary_loss: 0.013904 (0.013908) Loss: 0.35125 (0.32105) +2025-09-13,21:38:31 | INFO | Train Epoch: 7 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.31442 (0.30718) Boundary_loss: 0.013909 (0.013908) Loss: 0.32833 (0.32109) +2025-09-13,21:39:37 | INFO | Train Epoch: 7 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.30475 (0.30717) Boundary_loss: 0.013911 (0.013908) Loss: 0.31866 (0.32107) +2025-09-13,21:40:43 | INFO | Train Epoch: 7 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.24239 (0.30682) Boundary_loss: 0.013907 (0.013908) Loss: 0.25629 (0.32073) +2025-09-13,21:41:49 | INFO | Train Epoch: 7 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.32288 (0.30691) Boundary_loss: 0.013907 (0.013908) Loss: 0.33678 (0.32081) +2025-09-13,21:42:55 | INFO | Train Epoch: 7 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.33954 (0.30708) Boundary_loss: 0.013901 (0.013908) Loss: 0.35344 (0.32099) +2025-09-13,21:44:01 | INFO | Train Epoch: 7 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20230 (0.30653) Boundary_loss: 0.013906 (0.013908) Loss: 0.21620 (0.32044) +2025-09-13,21:45:07 | INFO | Train Epoch: 7 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.34503 (0.30673) Boundary_loss: 0.013903 (0.013908) Loss: 0.35894 (0.32064) +2025-09-13,21:46:13 | INFO | Train Epoch: 7 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.32627 (0.30683) Boundary_loss: 0.013905 (0.013908) Loss: 0.34017 (0.32074) +2025-09-13,21:47:19 | INFO | Train Epoch: 7 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.37638 (0.30719) Boundary_loss: 0.013908 (0.013908) Loss: 0.39028 (0.32110) +2025-09-13,21:48:25 | INFO | Train Epoch: 7 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.36205 (0.30747) Boundary_loss: 0.013909 (0.013908) Loss: 0.37596 (0.32138) +2025-09-13,21:49:31 | INFO | Train Epoch: 7 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.31946 (0.30754) Boundary_loss: 0.013905 (0.013908) Loss: 0.33337 (0.32144) +2025-09-13,21:50:37 | INFO | Train Epoch: 7 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.33511 (0.30768) Boundary_loss: 0.013905 (0.013908) Loss: 0.34901 (0.32158) +2025-09-13,21:51:43 | INFO | Train Epoch: 7 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.30622 (0.30767) Boundary_loss: 0.013907 (0.013908) Loss: 0.32013 (0.32158) +2025-09-13,21:52:49 | INFO | Train Epoch: 7 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.30135 (0.30764) Boundary_loss: 0.013907 (0.013908) Loss: 0.31525 (0.32154) +2025-09-13,21:53:55 | INFO | Train Epoch: 7 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.27977 (0.30750) Boundary_loss: 0.013911 (0.013908) Loss: 0.29369 (0.32140) +2025-09-13,21:55:01 | INFO | Train Epoch: 7 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.38057 (0.30786) Boundary_loss: 0.013910 (0.013908) Loss: 0.39448 (0.32177) +2025-09-13,21:56:07 | INFO | Train Epoch: 7 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.23539 (0.30750) Boundary_loss: 0.013905 (0.013908) Loss: 0.24930 (0.32141) +2025-09-13,21:57:13 | INFO | Train Epoch: 7 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.29419 (0.30744) Boundary_loss: 0.013906 (0.013908) Loss: 0.30810 (0.32134) +2025-09-13,21:58:19 | INFO | Train Epoch: 7 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.30287 (0.30741) Boundary_loss: 0.013904 (0.013908) Loss: 0.31677 (0.32132) +2025-09-13,21:59:25 | INFO | Train Epoch: 7 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.38703 (0.30780) Boundary_loss: 0.013909 (0.013908) Loss: 0.40094 (0.32171) +2025-09-13,22:00:31 | INFO | Train Epoch: 7 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.38442 (0.30818) Boundary_loss: 0.013906 (0.013908) Loss: 0.39833 (0.32208) +2025-09-13,22:01:37 | INFO | Train Epoch: 7 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.34603 (0.30836) Boundary_loss: 0.013927 (0.013908) Loss: 0.35996 (0.32227) +2025-09-13,22:02:43 | INFO | Train Epoch: 7 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.28523 (0.30825) Boundary_loss: 0.013906 (0.013908) Loss: 0.29914 (0.32216) +2025-09-13,22:03:49 | INFO | Train Epoch: 7 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.26743 (0.30805) Boundary_loss: 0.013914 (0.013908) Loss: 0.28135 (0.32196) +2025-09-13,22:04:56 | INFO | Train Epoch: 7 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.31903 (0.30811) Boundary_loss: 0.013907 (0.013908) Loss: 0.33293 (0.32201) +2025-09-13,22:06:02 | INFO | Train Epoch: 7 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.32729 (0.30820) Boundary_loss: 0.013903 (0.013908) Loss: 0.34119 (0.32210) +2025-09-13,22:07:08 | INFO | Train Epoch: 7 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.26071 (0.30797) Boundary_loss: 0.013915 (0.013908) Loss: 0.27463 (0.32188) +2025-09-13,22:08:14 | INFO | Train Epoch: 7 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25810 (0.30774) Boundary_loss: 0.013905 (0.013908) Loss: 0.27200 (0.32164) +2025-09-13,22:09:20 | INFO | Train Epoch: 7 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.32032 (0.30780) Boundary_loss: 0.013906 (0.013908) Loss: 0.33423 (0.32170) +2025-09-13,22:10:26 | INFO | Train Epoch: 7 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.34522 (0.30797) Boundary_loss: 0.013904 (0.013908) Loss: 0.35912 (0.32188) +2025-09-13,22:11:32 | INFO | Train Epoch: 7 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.29786 (0.30792) Boundary_loss: 0.013906 (0.013908) Loss: 0.31176 (0.32183) +2025-09-13,22:12:38 | INFO | Train Epoch: 7 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.27759 (0.30778) Boundary_loss: 0.013903 (0.013908) Loss: 0.29149 (0.32169) +2025-09-13,22:13:44 | INFO | Train Epoch: 7 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.30533 (0.30777) Boundary_loss: 0.013904 (0.013908) Loss: 0.31923 (0.32168) +2025-09-13,22:14:50 | INFO | Train Epoch: 7 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.33735 (0.30791) Boundary_loss: 0.013905 (0.013908) Loss: 0.35125 (0.32181) +2025-09-13,22:15:56 | INFO | Train Epoch: 7 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.26716 (0.30772) Boundary_loss: 0.013904 (0.013908) Loss: 0.28106 (0.32163) +2025-09-13,22:17:02 | INFO | Train Epoch: 7 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.30676 (0.30772) Boundary_loss: 0.013913 (0.013908) Loss: 0.32067 (0.32162) +2025-09-13,22:18:08 | INFO | Train Epoch: 7 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.23013 (0.30737) Boundary_loss: 0.013902 (0.013908) Loss: 0.24403 (0.32127) +2025-09-13,22:19:14 | INFO | Train Epoch: 7 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.30316 (0.30735) Boundary_loss: 0.013903 (0.013908) Loss: 0.31707 (0.32125) +2025-09-13,22:20:20 | INFO | Train Epoch: 7 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.34597 (0.30752) Boundary_loss: 0.013916 (0.013908) Loss: 0.35989 (0.32143) +2025-09-13,22:21:26 | INFO | Train Epoch: 7 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.27063 (0.30736) Boundary_loss: 0.013908 (0.013908) Loss: 0.28454 (0.32126) +2025-09-13,22:22:32 | INFO | Train Epoch: 7 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.34884 (0.30754) Boundary_loss: 0.013903 (0.013908) Loss: 0.36275 (0.32145) +2025-09-13,22:23:38 | INFO | Train Epoch: 7 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.34344 (0.30770) Boundary_loss: 0.013900 (0.013908) Loss: 0.35734 (0.32161) +2025-09-13,22:24:44 | INFO | Train Epoch: 7 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.37083 (0.30798) Boundary_loss: 0.013905 (0.013908) Loss: 0.38473 (0.32188) +2025-09-13,22:25:50 | INFO | Train Epoch: 7 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.32237 (0.30804) Boundary_loss: 0.013903 (0.013908) Loss: 0.33627 (0.32195) +2025-09-13,22:26:56 | INFO | Train Epoch: 7 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21028 (0.30761) Boundary_loss: 0.013905 (0.013908) Loss: 0.22419 (0.32152) +2025-09-13,22:28:02 | INFO | Train Epoch: 7 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.27142 (0.30746) Boundary_loss: 0.013913 (0.013908) Loss: 0.28534 (0.32136) +2025-09-13,22:29:08 | INFO | Train Epoch: 7 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.27781 (0.30733) Boundary_loss: 0.013911 (0.013908) Loss: 0.29172 (0.32123) +2025-09-13,22:30:14 | INFO | Train Epoch: 7 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.30178 (0.30730) Boundary_loss: 0.013907 (0.013908) Loss: 0.31569 (0.32121) +2025-09-13,22:31:20 | INFO | Train Epoch: 7 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.29594 (0.30725) Boundary_loss: 0.013902 (0.013908) Loss: 0.30984 (0.32116) +2025-09-13,22:32:26 | INFO | Train Epoch: 7 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.24604 (0.30699) Boundary_loss: 0.013907 (0.013908) Loss: 0.25995 (0.32090) +2025-09-13,22:33:32 | INFO | Train Epoch: 7 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.33321 (0.30710) Boundary_loss: 0.013907 (0.013908) Loss: 0.34711 (0.32101) +2025-09-13,22:34:38 | INFO | Train Epoch: 7 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.28999 (0.30703) Boundary_loss: 0.013905 (0.013908) Loss: 0.30390 (0.32094) +2025-09-13,22:35:44 | INFO | Train Epoch: 7 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.29912 (0.30700) Boundary_loss: 0.013903 (0.013908) Loss: 0.31302 (0.32091) +2025-09-13,22:36:50 | INFO | Train Epoch: 7 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.30870 (0.30701) Boundary_loss: 0.013909 (0.013908) Loss: 0.32261 (0.32091) +2025-09-13,22:37:56 | INFO | Train Epoch: 7 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.27774 (0.30688) Boundary_loss: 0.013935 (0.013908) Loss: 0.29167 (0.32079) +2025-09-13,22:39:02 | INFO | Train Epoch: 7 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29350 (0.30683) Boundary_loss: 0.013909 (0.013908) Loss: 0.30741 (0.32074) +2025-09-13,22:40:08 | INFO | Train Epoch: 7 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.26564 (0.30666) Boundary_loss: 0.013904 (0.013908) Loss: 0.27954 (0.32056) +2025-09-13,22:41:14 | INFO | Train Epoch: 7 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.35093 (0.30684) Boundary_loss: 0.013903 (0.013908) Loss: 0.36483 (0.32075) +2025-09-13,22:42:20 | INFO | Train Epoch: 7 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.26793 (0.30668) Boundary_loss: 0.013907 (0.013908) Loss: 0.28184 (0.32059) +2025-09-13,22:43:26 | INFO | Train Epoch: 7 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.35551 (0.30688) Boundary_loss: 0.013906 (0.013908) Loss: 0.36941 (0.32079) +2025-09-13,22:44:32 | INFO | Train Epoch: 7 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.32757 (0.30696) Boundary_loss: 0.013908 (0.013908) Loss: 0.34148 (0.32087) +2025-09-13,22:45:38 | INFO | Train Epoch: 7 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.38854 (0.30730) Boundary_loss: 0.013903 (0.013908) Loss: 0.40244 (0.32120) +2025-09-13,22:46:44 | INFO | Train Epoch: 7 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.32259 (0.30736) Boundary_loss: 0.013901 (0.013908) Loss: 0.33650 (0.32127) +2025-09-13,22:47:50 | INFO | Train Epoch: 7 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.28232 (0.30726) Boundary_loss: 0.013904 (0.013908) Loss: 0.29622 (0.32116) +2025-09-13,22:48:56 | INFO | Train Epoch: 7 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.27950 (0.30715) Boundary_loss: 0.013905 (0.013908) Loss: 0.29341 (0.32105) +2025-09-13,22:50:02 | INFO | Train Epoch: 7 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.31110 (0.30716) Boundary_loss: 0.013904 (0.013908) Loss: 0.32500 (0.32107) +2025-09-13,22:51:08 | INFO | Train Epoch: 7 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.24763 (0.30692) Boundary_loss: 0.013903 (0.013908) Loss: 0.26153 (0.32083) +2025-09-13,22:52:14 | INFO | Train Epoch: 7 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21275 (0.30655) Boundary_loss: 0.013904 (0.013908) Loss: 0.22665 (0.32046) +2025-09-13,22:53:20 | INFO | Train Epoch: 7 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.29419 (0.30650) Boundary_loss: 0.013904 (0.013908) Loss: 0.30809 (0.32041) +2025-09-13,22:54:26 | INFO | Train Epoch: 7 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.26834 (0.30635) Boundary_loss: 0.013914 (0.013908) Loss: 0.28226 (0.32026) +2025-09-13,22:55:32 | INFO | Train Epoch: 7 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.25389 (0.30615) Boundary_loss: 0.013923 (0.013908) Loss: 0.26782 (0.32005) +2025-09-13,22:56:38 | INFO | Train Epoch: 7 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.20676 (0.30576) Boundary_loss: 0.013903 (0.013908) Loss: 0.22067 (0.31966) +2025-09-13,22:57:44 | INFO | Train Epoch: 7 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.30856 (0.30577) Boundary_loss: 0.013908 (0.013908) Loss: 0.32247 (0.31968) +2025-09-13,22:58:50 | INFO | Train Epoch: 7 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.26851 (0.30562) Boundary_loss: 0.013905 (0.013908) Loss: 0.28242 (0.31953) +2025-09-13,22:59:57 | INFO | Train Epoch: 7 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.31783 (0.30567) Boundary_loss: 0.013905 (0.013908) Loss: 0.33174 (0.31958) +2025-09-13,23:01:02 | INFO | Train Epoch: 7 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.25734 (0.30548) Boundary_loss: 0.013905 (0.013908) Loss: 0.27125 (0.31939) +2025-09-13,23:02:08 | INFO | Train Epoch: 7 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.26644 (0.30534) Boundary_loss: 0.013904 (0.013908) Loss: 0.28035 (0.31924) +2025-09-13,23:03:15 | INFO | Train Epoch: 7 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.26394 (0.30518) Boundary_loss: 0.013913 (0.013908) Loss: 0.27786 (0.31908) +2025-09-13,23:04:21 | INFO | Train Epoch: 7 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.34044 (0.30531) Boundary_loss: 0.013906 (0.013908) Loss: 0.35434 (0.31922) +2025-09-13,23:05:27 | INFO | Train Epoch: 7 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.30334 (0.30530) Boundary_loss: 0.013900 (0.013908) Loss: 0.31724 (0.31921) +2025-09-13,23:06:33 | INFO | Train Epoch: 7 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.31677 (0.30535) Boundary_loss: 0.013910 (0.013908) Loss: 0.33068 (0.31925) +2025-09-13,23:07:39 | INFO | Train Epoch: 7 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.36428 (0.30557) Boundary_loss: 0.013904 (0.013908) Loss: 0.37819 (0.31948) +2025-09-13,23:08:45 | INFO | Train Epoch: 7 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.29853 (0.30554) Boundary_loss: 0.013905 (0.013908) Loss: 0.31244 (0.31945) +2025-09-13,23:09:51 | INFO | Train Epoch: 7 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.26926 (0.30541) Boundary_loss: 0.013903 (0.013907) Loss: 0.28316 (0.31931) +2025-09-13,23:10:57 | INFO | Train Epoch: 7 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.34028 (0.30554) Boundary_loss: 0.013906 (0.013907) Loss: 0.35419 (0.31944) +2025-09-13,23:12:03 | INFO | Train Epoch: 7 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.22479 (0.30524) Boundary_loss: 0.013902 (0.013907) Loss: 0.23869 (0.31915) +2025-09-13,23:13:09 | INFO | Train Epoch: 7 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.35829 (0.30543) Boundary_loss: 0.013911 (0.013907) Loss: 0.37220 (0.31934) +2025-09-13,23:14:15 | INFO | Train Epoch: 7 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.23737 (0.30518) Boundary_loss: 0.013904 (0.013907) Loss: 0.25128 (0.31909) +2025-09-13,23:15:21 | INFO | Train Epoch: 7 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.25862 (0.30501) Boundary_loss: 0.013907 (0.013907) Loss: 0.27252 (0.31892) +2025-09-13,23:16:28 | INFO | Train Epoch: 7 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.28546 (0.30494) Boundary_loss: 0.013908 (0.013907) Loss: 0.29937 (0.31885) +2025-09-13,23:17:34 | INFO | Train Epoch: 7 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.33612 (0.30505) Boundary_loss: 0.013901 (0.013907) Loss: 0.35002 (0.31896) +2025-09-13,23:18:40 | INFO | Train Epoch: 7 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.22583 (0.30477) Boundary_loss: 0.013907 (0.013907) Loss: 0.23974 (0.31867) +2025-09-13,23:19:46 | INFO | Train Epoch: 7 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.26380 (0.30462) Boundary_loss: 0.013909 (0.013907) Loss: 0.27771 (0.31853) +2025-09-13,23:20:52 | INFO | Train Epoch: 7 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.26323 (0.30447) Boundary_loss: 0.013908 (0.013907) Loss: 0.27714 (0.31838) +2025-09-13,23:21:58 | INFO | Train Epoch: 7 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.31210 (0.30450) Boundary_loss: 0.013905 (0.013907) Loss: 0.32601 (0.31841) +2025-09-13,23:23:04 | INFO | Train Epoch: 7 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.29103 (0.30445) Boundary_loss: 0.013899 (0.013907) Loss: 0.30493 (0.31836) +2025-09-13,23:24:10 | INFO | Train Epoch: 7 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.29754 (0.30443) Boundary_loss: 0.013912 (0.013907) Loss: 0.31146 (0.31833) +2025-09-13,23:25:16 | INFO | Train Epoch: 7 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.34419 (0.30457) Boundary_loss: 0.013904 (0.013907) Loss: 0.35809 (0.31847) +2025-09-13,23:26:22 | INFO | Train Epoch: 7 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.21186 (0.30424) Boundary_loss: 0.013920 (0.013907) Loss: 0.22578 (0.31815) +2025-09-13,23:27:28 | INFO | Train Epoch: 7 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.40472 (0.30459) Boundary_loss: 0.013904 (0.013907) Loss: 0.41862 (0.31850) +2025-09-13,23:28:34 | INFO | Train Epoch: 7 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.29823 (0.30457) Boundary_loss: 0.013907 (0.013907) Loss: 0.31214 (0.31848) +2025-09-13,23:29:40 | INFO | Train Epoch: 7 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.30804 (0.30458) Boundary_loss: 0.013910 (0.013907) Loss: 0.32195 (0.31849) +2025-09-13,23:30:46 | INFO | Train Epoch: 7 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.35298 (0.30475) Boundary_loss: 0.013910 (0.013907) Loss: 0.36689 (0.31866) +2025-09-13,23:31:53 | INFO | Train Epoch: 7 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.32322 (0.30482) Boundary_loss: 0.013907 (0.013907) Loss: 0.33713 (0.31872) +2025-09-13,23:32:59 | INFO | Train Epoch: 7 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.27823 (0.30472) Boundary_loss: 0.013908 (0.013907) Loss: 0.29214 (0.31863) +2025-09-13,23:34:05 | INFO | Train Epoch: 7 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.34631 (0.30487) Boundary_loss: 0.013902 (0.013907) Loss: 0.36021 (0.31877) +2025-09-13,23:35:11 | INFO | Train Epoch: 7 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.26066 (0.30471) Boundary_loss: 0.013910 (0.013907) Loss: 0.27457 (0.31862) +2025-09-13,23:36:17 | INFO | Train Epoch: 7 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24859 (0.30452) Boundary_loss: 0.013907 (0.013907) Loss: 0.26250 (0.31843) +2025-09-13,23:37:23 | INFO | Train Epoch: 7 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.25599 (0.30436) Boundary_loss: 0.013914 (0.013907) Loss: 0.26990 (0.31826) +2025-09-13,23:38:29 | INFO | Train Epoch: 7 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.27505 (0.30426) Boundary_loss: 0.013905 (0.013907) Loss: 0.28895 (0.31816) +2025-09-13,23:39:35 | INFO | Train Epoch: 7 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.26464 (0.30412) Boundary_loss: 0.013920 (0.013908) Loss: 0.27856 (0.31803) +2025-09-13,23:40:41 | INFO | Train Epoch: 7 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.25291 (0.30395) Boundary_loss: 0.013907 (0.013908) Loss: 0.26681 (0.31786) +2025-09-13,23:41:47 | INFO | Train Epoch: 7 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.34935 (0.30410) Boundary_loss: 0.013906 (0.013908) Loss: 0.36326 (0.31801) +2025-09-13,23:42:53 | INFO | Train Epoch: 7 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.34542 (0.30424) Boundary_loss: 0.013902 (0.013907) Loss: 0.35932 (0.31815) +2025-09-13,23:43:59 | INFO | Train Epoch: 7 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.35500 (0.30441) Boundary_loss: 0.013910 (0.013907) Loss: 0.36891 (0.31832) +2025-09-13,23:45:05 | INFO | Train Epoch: 7 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.41119 (0.30477) Boundary_loss: 0.013902 (0.013907) Loss: 0.42509 (0.31867) +2025-09-13,23:46:11 | INFO | Train Epoch: 7 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.32035 (0.30482) Boundary_loss: 0.013901 (0.013907) Loss: 0.33425 (0.31873) +2025-09-13,23:47:17 | INFO | Train Epoch: 7 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.28080 (0.30474) Boundary_loss: 0.013904 (0.013907) Loss: 0.29470 (0.31865) +2025-09-13,23:48:23 | INFO | Train Epoch: 7 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.29214 (0.30470) Boundary_loss: 0.013902 (0.013907) Loss: 0.30604 (0.31861) +2025-09-13,23:49:29 | INFO | Train Epoch: 7 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.24409 (0.30450) Boundary_loss: 0.013903 (0.013907) Loss: 0.25799 (0.31841) +2025-09-13,23:50:35 | INFO | Train Epoch: 7 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.34568 (0.30463) Boundary_loss: 0.013912 (0.013907) Loss: 0.35960 (0.31854) +2025-09-13,23:51:41 | INFO | Train Epoch: 7 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.29588 (0.30460) Boundary_loss: 0.013910 (0.013907) Loss: 0.30979 (0.31851) +2025-09-13,23:52:47 | INFO | Train Epoch: 7 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.25425 (0.30444) Boundary_loss: 0.013912 (0.013907) Loss: 0.26817 (0.31835) +2025-09-13,23:53:53 | INFO | Train Epoch: 7 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.29529 (0.30441) Boundary_loss: 0.013907 (0.013907) Loss: 0.30920 (0.31832) +2025-09-13,23:54:59 | INFO | Train Epoch: 7 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.38819 (0.30468) Boundary_loss: 0.013904 (0.013907) Loss: 0.40209 (0.31859) +2025-09-13,23:56:05 | INFO | Train Epoch: 7 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.28084 (0.30461) Boundary_loss: 0.013905 (0.013907) Loss: 0.29475 (0.31851) +2025-09-13,23:57:12 | INFO | Train Epoch: 7 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.35732 (0.30477) Boundary_loss: 0.013906 (0.013907) Loss: 0.37122 (0.31868) +2025-09-13,23:58:17 | INFO | Train Epoch: 7 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.32824 (0.30485) Boundary_loss: 0.013906 (0.013907) Loss: 0.34214 (0.31876) +2025-09-13,23:59:24 | INFO | Train Epoch: 7 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.29115 (0.30481) Boundary_loss: 0.013911 (0.013907) Loss: 0.30506 (0.31871) +2025-09-14,00:00:30 | INFO | Train Epoch: 7 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.30291 (0.30480) Boundary_loss: 0.013907 (0.013907) Loss: 0.31681 (0.31871) +2025-09-14,00:01:36 | INFO | Train Epoch: 7 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.34473 (0.30493) Boundary_loss: 0.013914 (0.013907) Loss: 0.35865 (0.31883) +2025-09-14,00:02:42 | INFO | Train Epoch: 7 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.22177 (0.30466) Boundary_loss: 0.013906 (0.013907) Loss: 0.23568 (0.31857) +2025-09-14,00:03:48 | INFO | Train Epoch: 7 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.25829 (0.30452) Boundary_loss: 0.013903 (0.013907) Loss: 0.27219 (0.31842) +2025-09-14,00:04:54 | INFO | Train Epoch: 7 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.33425 (0.30461) Boundary_loss: 0.013906 (0.013907) Loss: 0.34816 (0.31852) +2025-09-14,00:06:00 | INFO | Train Epoch: 7 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24314 (0.30442) Boundary_loss: 0.013905 (0.013907) Loss: 0.25705 (0.31833) +2025-09-14,00:07:06 | INFO | Train Epoch: 7 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.35044 (0.30456) Boundary_loss: 0.013902 (0.013907) Loss: 0.36434 (0.31847) +2025-09-14,00:08:12 | INFO | Train Epoch: 7 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.35316 (0.30471) Boundary_loss: 0.013909 (0.013907) Loss: 0.36707 (0.31862) +2025-09-14,00:09:18 | INFO | Train Epoch: 7 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.35039 (0.30486) Boundary_loss: 0.013917 (0.013907) Loss: 0.36430 (0.31876) +2025-09-14,00:10:24 | INFO | Train Epoch: 7 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.32331 (0.30491) Boundary_loss: 0.013904 (0.013907) Loss: 0.33722 (0.31882) +2025-09-14,00:11:30 | INFO | Train Epoch: 7 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.28822 (0.30486) Boundary_loss: 0.013913 (0.013907) Loss: 0.30214 (0.31877) +2025-09-14,00:12:36 | INFO | Train Epoch: 7 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.27665 (0.30477) Boundary_loss: 0.013905 (0.013907) Loss: 0.29056 (0.31868) +2025-09-14,00:13:42 | INFO | Train Epoch: 7 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.29544 (0.30475) Boundary_loss: 0.013908 (0.013907) Loss: 0.30935 (0.31865) +2025-09-14,00:14:48 | INFO | Train Epoch: 7 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.21497 (0.30447) Boundary_loss: 0.013910 (0.013907) Loss: 0.22888 (0.31838) +2025-09-14,00:15:54 | INFO | Train Epoch: 7 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.36058 (0.30464) Boundary_loss: 0.013907 (0.013907) Loss: 0.37449 (0.31855) +2025-09-14,00:17:00 | INFO | Train Epoch: 7 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.39334 (0.30491) Boundary_loss: 0.013902 (0.013907) Loss: 0.40724 (0.31882) +2025-09-14,00:18:06 | INFO | Train Epoch: 7 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.30263 (0.30490) Boundary_loss: 0.013909 (0.013907) Loss: 0.31654 (0.31881) +2025-09-14,00:19:12 | INFO | Train Epoch: 7 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.27108 (0.30480) Boundary_loss: 0.013901 (0.013907) Loss: 0.28498 (0.31871) +2025-09-14,00:20:17 | INFO | Train Epoch: 7 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.27276 (0.30471) Boundary_loss: 0.013906 (0.013907) Loss: 0.28666 (0.31861) +2025-09-14,00:21:23 | INFO | Train Epoch: 7 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.32214 (0.30476) Boundary_loss: 0.013907 (0.013907) Loss: 0.33605 (0.31867) +2025-09-14,00:22:29 | INFO | Train Epoch: 7 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.26623 (0.30464) Boundary_loss: 0.013904 (0.013907) Loss: 0.28013 (0.31855) +2025-09-14,00:23:35 | INFO | Train Epoch: 7 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.29868 (0.30463) Boundary_loss: 0.013905 (0.013907) Loss: 0.31258 (0.31853) +2025-09-14,00:24:41 | INFO | Train Epoch: 7 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.32113 (0.30467) Boundary_loss: 0.013912 (0.013907) Loss: 0.33504 (0.31858) +2025-09-14,00:25:47 | INFO | Train Epoch: 7 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.34024 (0.30478) Boundary_loss: 0.013907 (0.013907) Loss: 0.35414 (0.31869) +2025-09-14,00:26:53 | INFO | Train Epoch: 7 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.27454 (0.30469) Boundary_loss: 0.013906 (0.013907) Loss: 0.28845 (0.31860) +2025-09-14,00:27:59 | INFO | Train Epoch: 7 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.31553 (0.30472) Boundary_loss: 0.013907 (0.013907) Loss: 0.32943 (0.31863) +2025-09-14,00:29:04 | INFO | Train Epoch: 7 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.22323 (0.30448) Boundary_loss: 0.013905 (0.013907) Loss: 0.23714 (0.31839) +2025-09-14,00:30:10 | INFO | Train Epoch: 7 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.30500 (0.30448) Boundary_loss: 0.013910 (0.013907) Loss: 0.31891 (0.31839) +2025-09-14,00:31:16 | INFO | Train Epoch: 7 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.34894 (0.30461) Boundary_loss: 0.013902 (0.013907) Loss: 0.36284 (0.31852) +2025-09-14,00:32:22 | INFO | Train Epoch: 7 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.31351 (0.30464) Boundary_loss: 0.013913 (0.013907) Loss: 0.32743 (0.31855) +2025-09-14,00:33:28 | INFO | Train Epoch: 7 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.26425 (0.30452) Boundary_loss: 0.013902 (0.013907) Loss: 0.27815 (0.31843) +2025-09-14,00:34:34 | INFO | Train Epoch: 7 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.28605 (0.30447) Boundary_loss: 0.013905 (0.013907) Loss: 0.29996 (0.31838) +2025-09-14,00:35:40 | INFO | Train Epoch: 7 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.31956 (0.30451) Boundary_loss: 0.013909 (0.013907) Loss: 0.33346 (0.31842) +2025-09-14,00:36:46 | INFO | Train Epoch: 7 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.32395 (0.30457) Boundary_loss: 0.013905 (0.013907) Loss: 0.33785 (0.31848) +2025-09-14,00:37:52 | INFO | Train Epoch: 7 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.30873 (0.30458) Boundary_loss: 0.013903 (0.013907) Loss: 0.32264 (0.31849) +2025-09-14,00:38:58 | INFO | Train Epoch: 7 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.28057 (0.30451) Boundary_loss: 0.013908 (0.013907) Loss: 0.29448 (0.31842) +2025-09-14,00:40:04 | INFO | Train Epoch: 7 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.35114 (0.30465) Boundary_loss: 0.013903 (0.013907) Loss: 0.36504 (0.31855) +2025-09-14,00:41:11 | INFO | Train Epoch: 7 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.33699 (0.30474) Boundary_loss: 0.013905 (0.013907) Loss: 0.35089 (0.31864) +2025-09-14,00:42:17 | INFO | Train Epoch: 7 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.39115 (0.30498) Boundary_loss: 0.013902 (0.013907) Loss: 0.40506 (0.31889) +2025-09-14,00:43:23 | INFO | Train Epoch: 7 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.37275 (0.30517) Boundary_loss: 0.013909 (0.013907) Loss: 0.38666 (0.31908) +2025-09-14,00:44:29 | INFO | Train Epoch: 7 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.33521 (0.30526) Boundary_loss: 0.013906 (0.013907) Loss: 0.34912 (0.31917) +2025-09-14,00:45:35 | INFO | Train Epoch: 7 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.35131 (0.30539) Boundary_loss: 0.013905 (0.013907) Loss: 0.36521 (0.31930) +2025-09-14,00:46:41 | INFO | Train Epoch: 7 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.32904 (0.30546) Boundary_loss: 0.013904 (0.013907) Loss: 0.34294 (0.31936) +2025-09-14,00:47:47 | INFO | Train Epoch: 7 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.29494 (0.30543) Boundary_loss: 0.013906 (0.013907) Loss: 0.30885 (0.31933) +2025-09-14,00:48:53 | INFO | Train Epoch: 7 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.29878 (0.30541) Boundary_loss: 0.013905 (0.013907) Loss: 0.31269 (0.31932) +2025-09-14,00:49:59 | INFO | Train Epoch: 7 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.32306 (0.30546) Boundary_loss: 0.013910 (0.013907) Loss: 0.33697 (0.31936) +2025-09-14,00:51:05 | INFO | Train Epoch: 7 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.24572 (0.30529) Boundary_loss: 0.013901 (0.013907) Loss: 0.25962 (0.31920) +2025-09-14,00:52:11 | INFO | Train Epoch: 7 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.29837 (0.30527) Boundary_loss: 0.013904 (0.013907) Loss: 0.31227 (0.31918) +2025-09-14,00:53:17 | INFO | Train Epoch: 7 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.26742 (0.30517) Boundary_loss: 0.013902 (0.013907) Loss: 0.28132 (0.31907) +2025-09-14,00:54:23 | INFO | Train Epoch: 7 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.33532 (0.30525) Boundary_loss: 0.013904 (0.013907) Loss: 0.34922 (0.31916) +2025-09-14,00:55:29 | INFO | Train Epoch: 7 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.27126 (0.30516) Boundary_loss: 0.013906 (0.013907) Loss: 0.28517 (0.31906) +2025-09-14,00:56:35 | INFO | Train Epoch: 7 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.27423 (0.30507) Boundary_loss: 0.013909 (0.013907) Loss: 0.28814 (0.31898) +2025-09-14,00:57:41 | INFO | Train Epoch: 7 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.24854 (0.30492) Boundary_loss: 0.013904 (0.013907) Loss: 0.26245 (0.31883) +2025-09-14,00:58:47 | INFO | Train Epoch: 7 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.32543 (0.30497) Boundary_loss: 0.013910 (0.013907) Loss: 0.33935 (0.31888) +2025-09-14,00:59:53 | INFO | Train Epoch: 7 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.31665 (0.30501) Boundary_loss: 0.013901 (0.013907) Loss: 0.33056 (0.31891) +2025-09-14,01:00:59 | INFO | Train Epoch: 7 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.27036 (0.30491) Boundary_loss: 0.013904 (0.013907) Loss: 0.28426 (0.31882) +2025-09-14,01:02:05 | INFO | Train Epoch: 7 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.34487 (0.30502) Boundary_loss: 0.013905 (0.013907) Loss: 0.35877 (0.31893) +2025-09-14,01:03:11 | INFO | Train Epoch: 7 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.28395 (0.30496) Boundary_loss: 0.013903 (0.013907) Loss: 0.29785 (0.31887) +2025-09-14,01:04:17 | INFO | Train Epoch: 7 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.28227 (0.30490) Boundary_loss: 0.013906 (0.013907) Loss: 0.29618 (0.31881) +2025-09-14,01:05:23 | INFO | Train Epoch: 7 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.33833 (0.30499) Boundary_loss: 0.013905 (0.013907) Loss: 0.35223 (0.31890) +2025-09-14,01:06:29 | INFO | Train Epoch: 7 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.31984 (0.30503) Boundary_loss: 0.013929 (0.013907) Loss: 0.33377 (0.31894) +2025-09-14,01:07:35 | INFO | Train Epoch: 7 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.34014 (0.30512) Boundary_loss: 0.013903 (0.013907) Loss: 0.35404 (0.31903) +2025-09-14,01:08:41 | INFO | Train Epoch: 7 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.25768 (0.30500) Boundary_loss: 0.013906 (0.013907) Loss: 0.27158 (0.31891) +2025-09-14,01:09:47 | INFO | Train Epoch: 7 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.33642 (0.30508) Boundary_loss: 0.013901 (0.013907) Loss: 0.35032 (0.31899) +2025-09-14,01:10:53 | INFO | Train Epoch: 7 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.26806 (0.30498) Boundary_loss: 0.013904 (0.013907) Loss: 0.28197 (0.31889) +2025-09-14,01:12:00 | INFO | Train Epoch: 7 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.28093 (0.30492) Boundary_loss: 0.013899 (0.013907) Loss: 0.29482 (0.31883) +2025-09-14,01:13:06 | INFO | Train Epoch: 7 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.32445 (0.30497) Boundary_loss: 0.013902 (0.013907) Loss: 0.33835 (0.31888) +2025-09-14,01:14:12 | INFO | Train Epoch: 7 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.34507 (0.30508) Boundary_loss: 0.013903 (0.013907) Loss: 0.35898 (0.31898) +2025-09-14,01:15:18 | INFO | Train Epoch: 7 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.22643 (0.30487) Boundary_loss: 0.013902 (0.013907) Loss: 0.24034 (0.31878) +2025-09-14,01:16:24 | INFO | Train Epoch: 7 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.34306 (0.30497) Boundary_loss: 0.013908 (0.013907) Loss: 0.35697 (0.31888) +2025-09-14,01:17:30 | INFO | Train Epoch: 7 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.23817 (0.30480) Boundary_loss: 0.013904 (0.013907) Loss: 0.25207 (0.31870) +2025-09-14,01:18:36 | INFO | Train Epoch: 7 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.33756 (0.30488) Boundary_loss: 0.013912 (0.013907) Loss: 0.35147 (0.31879) +2025-09-14,01:19:42 | INFO | Train Epoch: 7 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.36422 (0.30504) Boundary_loss: 0.013905 (0.013907) Loss: 0.37813 (0.31894) +2025-09-14,01:20:48 | INFO | Train Epoch: 7 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.29678 (0.30501) Boundary_loss: 0.013906 (0.013907) Loss: 0.31069 (0.31892) +2025-09-14,01:21:54 | INFO | Train Epoch: 7 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.30221 (0.30501) Boundary_loss: 0.013906 (0.013907) Loss: 0.31612 (0.31891) +2025-09-14,01:23:00 | INFO | Train Epoch: 7 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.24721 (0.30486) Boundary_loss: 0.013902 (0.013907) Loss: 0.26112 (0.31877) +2025-09-14,01:24:06 | INFO | Train Epoch: 7 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.31219 (0.30488) Boundary_loss: 0.013907 (0.013907) Loss: 0.32609 (0.31878) +2025-09-14,01:25:12 | INFO | Train Epoch: 7 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.33317 (0.30495) Boundary_loss: 0.013902 (0.013907) Loss: 0.34707 (0.31886) +2025-09-14,01:26:18 | INFO | Train Epoch: 7 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.26756 (0.30485) Boundary_loss: 0.013903 (0.013907) Loss: 0.28146 (0.31876) +2025-09-14,01:27:24 | INFO | Train Epoch: 7 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.26403 (0.30475) Boundary_loss: 0.013913 (0.013907) Loss: 0.27794 (0.31866) +2025-09-14,01:28:30 | INFO | Train Epoch: 7 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31892 (0.30479) Boundary_loss: 0.013904 (0.013907) Loss: 0.33283 (0.31869) +2025-09-14,01:29:36 | INFO | Train Epoch: 7 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.30089 (0.30478) Boundary_loss: 0.013903 (0.013907) Loss: 0.31479 (0.31868) +2025-09-14,01:30:42 | INFO | Train Epoch: 7 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.29226 (0.30475) Boundary_loss: 0.013908 (0.013907) Loss: 0.30617 (0.31865) +2025-09-14,01:31:49 | INFO | Train Epoch: 7 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.27452 (0.30467) Boundary_loss: 0.013907 (0.013907) Loss: 0.28842 (0.31858) +2025-09-14,01:32:55 | INFO | Train Epoch: 7 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.35762 (0.30480) Boundary_loss: 0.013902 (0.013907) Loss: 0.37153 (0.31871) +2025-09-14,01:34:01 | INFO | Train Epoch: 7 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.32550 (0.30485) Boundary_loss: 0.013903 (0.013907) Loss: 0.33940 (0.31876) +2025-09-14,01:35:07 | INFO | Train Epoch: 7 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.28778 (0.30481) Boundary_loss: 0.013900 (0.013907) Loss: 0.30168 (0.31872) +2025-09-14,01:36:13 | INFO | Train Epoch: 7 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.34259 (0.30491) Boundary_loss: 0.013910 (0.013907) Loss: 0.35650 (0.31881) +2025-09-14,01:37:19 | INFO | Train Epoch: 7 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.34425 (0.30500) Boundary_loss: 0.013902 (0.013907) Loss: 0.35815 (0.31891) +2025-09-14,01:38:25 | INFO | Train Epoch: 7 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.26876 (0.30491) Boundary_loss: 0.013902 (0.013907) Loss: 0.28267 (0.31882) +2025-09-14,01:39:31 | INFO | Train Epoch: 7 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.27695 (0.30484) Boundary_loss: 0.013901 (0.013907) Loss: 0.29085 (0.31875) +2025-09-14,01:40:37 | INFO | Train Epoch: 7 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.29079 (0.30481) Boundary_loss: 0.013905 (0.013907) Loss: 0.30470 (0.31872) +2025-09-14,01:41:43 | INFO | Train Epoch: 7 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.23398 (0.30463) Boundary_loss: 0.013904 (0.013907) Loss: 0.24788 (0.31854) +2025-09-14,01:42:50 | INFO | Train Epoch: 7 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.38828 (0.30484) Boundary_loss: 0.013906 (0.013907) Loss: 0.40218 (0.31875) +2025-09-14,01:43:56 | INFO | Train Epoch: 7 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.27857 (0.30478) Boundary_loss: 0.013915 (0.013907) Loss: 0.29249 (0.31868) +2025-09-14,01:45:02 | INFO | Train Epoch: 7 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.23923 (0.30462) Boundary_loss: 0.013904 (0.013907) Loss: 0.25313 (0.31852) +2025-09-14,01:46:08 | INFO | Train Epoch: 7 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.28813 (0.30458) Boundary_loss: 0.013903 (0.013907) Loss: 0.30203 (0.31848) +2025-09-14,01:47:14 | INFO | Train Epoch: 7 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.28258 (0.30452) Boundary_loss: 0.013911 (0.013907) Loss: 0.29649 (0.31843) +2025-09-14,01:48:20 | INFO | Train Epoch: 7 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.32145 (0.30456) Boundary_loss: 0.013902 (0.013907) Loss: 0.33535 (0.31847) +2025-09-14,01:49:26 | INFO | Train Epoch: 7 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.32219 (0.30461) Boundary_loss: 0.013908 (0.013907) Loss: 0.33610 (0.31851) +2025-09-14,01:50:33 | INFO | Train Epoch: 7 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.32692 (0.30466) Boundary_loss: 0.013907 (0.013907) Loss: 0.34082 (0.31857) +2025-09-14,01:51:39 | INFO | Train Epoch: 7 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.29471 (0.30464) Boundary_loss: 0.013910 (0.013907) Loss: 0.30862 (0.31854) +2025-09-14,01:52:45 | INFO | Train Epoch: 7 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.31891 (0.30467) Boundary_loss: 0.013904 (0.013907) Loss: 0.33281 (0.31858) +2025-09-14,01:53:51 | INFO | Train Epoch: 7 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.25935 (0.30456) Boundary_loss: 0.013903 (0.013907) Loss: 0.27325 (0.31847) +2025-09-14,01:54:57 | INFO | Train Epoch: 7 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.33171 (0.30463) Boundary_loss: 0.013904 (0.013907) Loss: 0.34561 (0.31853) +2025-09-14,01:56:03 | INFO | Train Epoch: 7 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.34551 (0.30472) Boundary_loss: 0.013904 (0.013907) Loss: 0.35941 (0.31863) +2025-09-14,01:57:10 | INFO | Train Epoch: 7 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.30347 (0.30472) Boundary_loss: 0.013901 (0.013907) Loss: 0.31737 (0.31863) +2025-09-14,01:58:16 | INFO | Train Epoch: 7 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.41545 (0.30498) Boundary_loss: 0.013911 (0.013907) Loss: 0.42936 (0.31889) +2025-09-14,01:59:22 | INFO | Train Epoch: 7 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.33325 (0.30505) Boundary_loss: 0.013907 (0.013907) Loss: 0.34716 (0.31896) +2025-09-14,02:00:28 | INFO | Train Epoch: 7 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.27268 (0.30497) Boundary_loss: 0.013902 (0.013907) Loss: 0.28658 (0.31888) +2025-09-14,02:01:34 | INFO | Train Epoch: 7 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.27909 (0.30491) Boundary_loss: 0.013901 (0.013907) Loss: 0.29299 (0.31882) +2025-09-14,02:02:40 | INFO | Train Epoch: 7 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.31885 (0.30495) Boundary_loss: 0.013910 (0.013907) Loss: 0.33276 (0.31885) +2025-09-14,02:03:46 | INFO | Train Epoch: 7 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.32276 (0.30499) Boundary_loss: 0.013909 (0.013907) Loss: 0.33667 (0.31889) +2025-09-14,02:04:52 | INFO | Train Epoch: 7 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.27889 (0.30493) Boundary_loss: 0.013907 (0.013907) Loss: 0.29279 (0.31883) +2025-09-14,02:05:58 | INFO | Train Epoch: 7 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.41008 (0.30517) Boundary_loss: 0.013909 (0.013907) Loss: 0.42399 (0.31908) +2025-09-14,02:07:04 | INFO | Train Epoch: 7 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.29108 (0.30514) Boundary_loss: 0.013904 (0.013907) Loss: 0.30499 (0.31905) +2025-09-14,02:08:10 | INFO | Train Epoch: 7 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.26578 (0.30505) Boundary_loss: 0.013912 (0.013907) Loss: 0.27969 (0.31896) +2025-09-14,02:09:16 | INFO | Train Epoch: 7 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.26975 (0.30497) Boundary_loss: 0.013906 (0.013907) Loss: 0.28365 (0.31887) +2025-09-14,02:10:23 | INFO | Train Epoch: 7 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.24292 (0.30482) Boundary_loss: 0.013908 (0.013907) Loss: 0.25683 (0.31873) +2025-09-14,02:11:29 | INFO | Train Epoch: 7 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.33209 (0.30489) Boundary_loss: 0.013904 (0.013907) Loss: 0.34600 (0.31879) +2025-09-14,02:12:35 | INFO | Train Epoch: 7 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.29642 (0.30487) Boundary_loss: 0.013901 (0.013907) Loss: 0.31032 (0.31877) +2025-09-14,02:13:41 | INFO | Train Epoch: 7 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29824 (0.30485) Boundary_loss: 0.013903 (0.013907) Loss: 0.31214 (0.31876) +2025-09-14,02:14:47 | INFO | Train Epoch: 7 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.29174 (0.30482) Boundary_loss: 0.013905 (0.013907) Loss: 0.30565 (0.31873) +2025-09-14,02:15:53 | INFO | Train Epoch: 7 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.29733 (0.30480) Boundary_loss: 0.013906 (0.013907) Loss: 0.31123 (0.31871) +2025-09-14,02:16:59 | INFO | Train Epoch: 7 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.29096 (0.30477) Boundary_loss: 0.013906 (0.013907) Loss: 0.30487 (0.31868) +2025-09-14,02:18:05 | INFO | Train Epoch: 7 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.28451 (0.30473) Boundary_loss: 0.013904 (0.013907) Loss: 0.29841 (0.31863) +2025-09-14,02:19:11 | INFO | Train Epoch: 7 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.26789 (0.30464) Boundary_loss: 0.013906 (0.013907) Loss: 0.28180 (0.31855) +2025-09-14,02:20:17 | INFO | Train Epoch: 7 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36411 (0.30478) Boundary_loss: 0.013902 (0.013907) Loss: 0.37801 (0.31868) +2025-09-14,02:21:23 | INFO | Train Epoch: 7 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.33352 (0.30484) Boundary_loss: 0.013904 (0.013907) Loss: 0.34742 (0.31875) +2025-09-14,02:22:29 | INFO | Train Epoch: 7 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.31107 (0.30486) Boundary_loss: 0.013903 (0.013907) Loss: 0.32497 (0.31876) +2025-09-14,02:23:35 | INFO | Train Epoch: 7 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.33378 (0.30492) Boundary_loss: 0.013901 (0.013907) Loss: 0.34768 (0.31883) +2025-09-14,02:24:42 | INFO | Train Epoch: 7 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.25863 (0.30482) Boundary_loss: 0.013903 (0.013907) Loss: 0.27253 (0.31872) +2025-09-14,02:25:48 | INFO | Train Epoch: 7 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.28998 (0.30478) Boundary_loss: 0.013905 (0.013907) Loss: 0.30388 (0.31869) +2025-09-14,02:26:54 | INFO | Train Epoch: 7 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.30319 (0.30478) Boundary_loss: 0.013902 (0.013907) Loss: 0.31709 (0.31869) +2025-09-14,02:28:00 | INFO | Train Epoch: 7 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.25180 (0.30466) Boundary_loss: 0.013899 (0.013907) Loss: 0.26570 (0.31857) +2025-09-14,02:29:06 | INFO | Train Epoch: 7 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.25720 (0.30456) Boundary_loss: 0.013903 (0.013907) Loss: 0.27110 (0.31846) +2025-09-14,02:30:12 | INFO | Train Epoch: 7 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.34008 (0.30464) Boundary_loss: 0.013901 (0.013907) Loss: 0.35398 (0.31854) +2025-09-14,02:31:18 | INFO | Train Epoch: 7 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.21721 (0.30444) Boundary_loss: 0.013909 (0.013907) Loss: 0.23112 (0.31835) +2025-09-14,02:32:24 | INFO | Train Epoch: 7 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.32836 (0.30449) Boundary_loss: 0.013905 (0.013907) Loss: 0.34226 (0.31840) +2025-09-14,02:33:30 | INFO | Train Epoch: 7 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.26051 (0.30440) Boundary_loss: 0.013907 (0.013907) Loss: 0.27442 (0.31830) +2025-09-14,02:34:37 | INFO | Train Epoch: 7 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.31121 (0.30441) Boundary_loss: 0.013903 (0.013907) Loss: 0.32512 (0.31832) +2025-09-14,02:35:43 | INFO | Train Epoch: 7 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.29096 (0.30438) Boundary_loss: 0.013901 (0.013907) Loss: 0.30486 (0.31829) +2025-09-14,02:36:49 | INFO | Train Epoch: 7 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.22145 (0.30420) Boundary_loss: 0.013907 (0.013907) Loss: 0.23536 (0.31811) +2025-09-14,02:37:55 | INFO | Train Epoch: 7 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.29098 (0.30417) Boundary_loss: 0.013910 (0.013907) Loss: 0.30489 (0.31808) +2025-09-14,02:39:01 | INFO | Train Epoch: 7 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.30173 (0.30417) Boundary_loss: 0.013900 (0.013907) Loss: 0.31563 (0.31807) +2025-09-14,02:40:07 | INFO | Train Epoch: 7 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.34509 (0.30426) Boundary_loss: 0.013913 (0.013907) Loss: 0.35900 (0.31816) +2025-09-14,02:41:13 | INFO | Train Epoch: 7 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.31094 (0.30427) Boundary_loss: 0.013901 (0.013907) Loss: 0.32484 (0.31818) +2025-09-14,02:42:19 | INFO | Train Epoch: 7 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.32571 (0.30432) Boundary_loss: 0.013905 (0.013907) Loss: 0.33961 (0.31822) +2025-09-14,02:43:25 | INFO | Train Epoch: 7 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.24574 (0.30419) Boundary_loss: 0.013904 (0.013907) Loss: 0.25964 (0.31810) +2025-09-14,02:44:32 | INFO | Train Epoch: 7 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.24995 (0.30407) Boundary_loss: 0.013905 (0.013907) Loss: 0.26385 (0.31798) +2025-09-14,02:45:38 | INFO | Train Epoch: 7 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.26371 (0.30399) Boundary_loss: 0.013905 (0.013907) Loss: 0.27762 (0.31789) +2025-09-14,02:46:44 | INFO | Train Epoch: 7 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.32318 (0.30403) Boundary_loss: 0.013909 (0.013907) Loss: 0.33709 (0.31793) +2025-09-14,02:47:50 | INFO | Train Epoch: 7 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.30430 (0.30403) Boundary_loss: 0.013903 (0.013907) Loss: 0.31821 (0.31793) +2025-09-14,02:48:56 | INFO | Train Epoch: 7 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.31313 (0.30405) Boundary_loss: 0.013904 (0.013907) Loss: 0.32703 (0.31795) +2025-09-14,02:50:02 | INFO | Train Epoch: 7 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.32690 (0.30410) Boundary_loss: 0.013906 (0.013907) Loss: 0.34080 (0.31800) +2025-09-14,02:51:08 | INFO | Train Epoch: 7 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.28769 (0.30406) Boundary_loss: 0.013900 (0.013907) Loss: 0.30159 (0.31797) +2025-09-14,02:52:14 | INFO | Train Epoch: 7 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.31517 (0.30408) Boundary_loss: 0.013904 (0.013907) Loss: 0.32907 (0.31799) +2025-09-14,02:53:20 | INFO | Train Epoch: 7 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.31572 (0.30411) Boundary_loss: 0.013907 (0.013907) Loss: 0.32963 (0.31802) +2025-09-14,02:54:26 | INFO | Train Epoch: 7 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.32241 (0.30415) Boundary_loss: 0.013907 (0.013907) Loss: 0.33632 (0.31806) +2025-09-14,02:55:33 | INFO | Train Epoch: 7 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.28323 (0.30410) Boundary_loss: 0.013908 (0.013907) Loss: 0.29714 (0.31801) +2025-09-14,02:56:39 | INFO | Train Epoch: 7 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.33347 (0.30417) Boundary_loss: 0.013907 (0.013907) Loss: 0.34738 (0.31807) +2025-09-14,02:57:45 | INFO | Train Epoch: 7 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.30112 (0.30416) Boundary_loss: 0.013906 (0.013907) Loss: 0.31502 (0.31807) +2025-09-14,02:58:51 | INFO | Train Epoch: 7 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.37932 (0.30432) Boundary_loss: 0.013906 (0.013907) Loss: 0.39322 (0.31822) +2025-09-14,02:59:57 | INFO | Train Epoch: 7 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.27991 (0.30427) Boundary_loss: 0.013904 (0.013907) Loss: 0.29381 (0.31817) +2025-09-14,03:01:03 | INFO | Train Epoch: 7 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.24858 (0.30415) Boundary_loss: 0.013903 (0.013907) Loss: 0.26249 (0.31806) +2025-09-14,03:02:09 | INFO | Train Epoch: 7 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.31567 (0.30417) Boundary_loss: 0.013919 (0.013907) Loss: 0.32959 (0.31808) +2025-09-14,03:03:16 | INFO | Train Epoch: 7 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.39637 (0.30437) Boundary_loss: 0.013907 (0.013907) Loss: 0.41028 (0.31827) +2025-09-14,03:04:22 | INFO | Train Epoch: 7 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.26404 (0.30428) Boundary_loss: 0.013902 (0.013907) Loss: 0.27794 (0.31819) +2025-09-14,03:05:28 | INFO | Train Epoch: 7 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.27188 (0.30421) Boundary_loss: 0.013905 (0.013907) Loss: 0.28579 (0.31812) +2025-09-14,03:06:34 | INFO | Train Epoch: 7 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.29709 (0.30420) Boundary_loss: 0.013908 (0.013907) Loss: 0.31099 (0.31811) +2025-09-14,03:07:40 | INFO | Train Epoch: 7 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.31526 (0.30422) Boundary_loss: 0.013900 (0.013907) Loss: 0.32916 (0.31813) +2025-09-14,03:08:46 | INFO | Train Epoch: 7 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.27592 (0.30416) Boundary_loss: 0.013905 (0.013907) Loss: 0.28982 (0.31807) +2025-09-14,03:09:52 | INFO | Train Epoch: 7 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.31115 (0.30418) Boundary_loss: 0.013904 (0.013907) Loss: 0.32506 (0.31809) +2025-09-14,03:10:58 | INFO | Train Epoch: 7 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.33108 (0.30423) Boundary_loss: 0.013904 (0.013907) Loss: 0.34499 (0.31814) +2025-09-14,03:12:04 | INFO | Train Epoch: 7 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.31252 (0.30425) Boundary_loss: 0.013910 (0.013907) Loss: 0.32643 (0.31816) +2025-09-14,03:13:10 | INFO | Train Epoch: 7 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.36809 (0.30438) Boundary_loss: 0.013904 (0.013907) Loss: 0.38199 (0.31829) +2025-09-14,03:14:17 | INFO | Train Epoch: 7 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.31561 (0.30440) Boundary_loss: 0.013903 (0.013907) Loss: 0.32952 (0.31831) +2025-09-14,03:15:23 | INFO | Train Epoch: 7 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.27875 (0.30435) Boundary_loss: 0.013903 (0.013907) Loss: 0.29265 (0.31826) +2025-09-14,03:16:29 | INFO | Train Epoch: 7 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.29133 (0.30433) Boundary_loss: 0.013904 (0.013907) Loss: 0.30523 (0.31823) +2025-09-14,03:17:35 | INFO | Train Epoch: 7 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.29230 (0.30430) Boundary_loss: 0.013904 (0.013907) Loss: 0.30620 (0.31821) +2025-09-14,03:18:41 | INFO | Train Epoch: 7 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.32484 (0.30434) Boundary_loss: 0.013910 (0.013907) Loss: 0.33875 (0.31825) +2025-09-14,03:19:47 | INFO | Train Epoch: 7 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.34125 (0.30442) Boundary_loss: 0.013902 (0.013907) Loss: 0.35515 (0.31832) +2025-09-14,03:20:53 | INFO | Train Epoch: 7 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.24491 (0.30430) Boundary_loss: 0.013902 (0.013907) Loss: 0.25881 (0.31820) +2025-09-14,03:21:59 | INFO | Train Epoch: 7 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.25554 (0.30420) Boundary_loss: 0.013907 (0.013907) Loss: 0.26944 (0.31811) +2025-09-14,03:23:05 | INFO | Train Epoch: 7 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.28108 (0.30415) Boundary_loss: 0.013909 (0.013907) Loss: 0.29499 (0.31806) +2025-09-14,03:24:12 | INFO | Train Epoch: 7 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.30509 (0.30416) Boundary_loss: 0.013905 (0.013907) Loss: 0.31899 (0.31806) +2025-09-14,03:25:18 | INFO | Train Epoch: 7 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.25054 (0.30405) Boundary_loss: 0.013903 (0.013907) Loss: 0.26445 (0.31795) +2025-09-14,03:26:24 | INFO | Train Epoch: 7 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.24378 (0.30393) Boundary_loss: 0.013907 (0.013907) Loss: 0.25769 (0.31783) +2025-09-14,03:27:30 | INFO | Train Epoch: 7 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.23481 (0.30379) Boundary_loss: 0.013902 (0.013907) Loss: 0.24872 (0.31770) +2025-09-14,03:28:36 | INFO | Train Epoch: 7 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.29375 (0.30377) Boundary_loss: 0.013904 (0.013907) Loss: 0.30765 (0.31768) +2025-09-14,03:29:42 | INFO | Train Epoch: 7 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.27151 (0.30371) Boundary_loss: 0.013903 (0.013907) Loss: 0.28541 (0.31761) +2025-09-14,03:30:48 | INFO | Train Epoch: 7 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.32615 (0.30375) Boundary_loss: 0.013901 (0.013907) Loss: 0.34005 (0.31766) +2025-09-14,03:31:54 | INFO | Train Epoch: 7 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.26179 (0.30367) Boundary_loss: 0.013905 (0.013907) Loss: 0.27570 (0.31757) +2025-09-14,03:33:00 | INFO | Train Epoch: 7 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.33755 (0.30373) Boundary_loss: 0.013909 (0.013907) Loss: 0.35146 (0.31764) +2025-09-14,03:34:06 | INFO | Train Epoch: 7 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.28572 (0.30370) Boundary_loss: 0.013902 (0.013907) Loss: 0.29962 (0.31761) +2025-09-14,03:35:13 | INFO | Train Epoch: 7 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.29287 (0.30368) Boundary_loss: 0.013901 (0.013907) Loss: 0.30677 (0.31758) +2025-09-14,03:36:19 | INFO | Train Epoch: 7 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.29016 (0.30365) Boundary_loss: 0.013908 (0.013907) Loss: 0.30406 (0.31756) +2025-09-14,03:37:25 | INFO | Train Epoch: 7 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.35087 (0.30374) Boundary_loss: 0.013902 (0.013907) Loss: 0.36477 (0.31765) +2025-09-14,03:38:31 | INFO | Train Epoch: 7 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.30343 (0.30374) Boundary_loss: 0.013907 (0.013907) Loss: 0.31734 (0.31765) +2025-09-14,03:39:37 | INFO | Train Epoch: 7 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.30681 (0.30375) Boundary_loss: 0.013905 (0.013907) Loss: 0.32071 (0.31766) +2025-09-14,03:40:43 | INFO | Train Epoch: 7 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.29168 (0.30373) Boundary_loss: 0.013906 (0.013907) Loss: 0.30559 (0.31763) +2025-09-14,03:41:49 | INFO | Train Epoch: 7 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.26465 (0.30365) Boundary_loss: 0.013901 (0.013907) Loss: 0.27855 (0.31756) +2025-09-14,03:42:52 | INFO | Train Epoch: 7 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.34827 (0.30374) Boundary_loss: 0.013901 (0.013907) Loss: 0.36217 (0.31764) +2025-09-14,03:42:52 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,03:42:52 | INFO | [Epoch 7] Average Step Time: 0.663s | Average GPU Memory: 30.9 GB +2025-09-14,03:42:52 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,03:42:52 | INFO | Starting zero-shot imagenet. +2025-09-14,03:42:52 | INFO | Building zero-shot classifier +2025-09-14,03:43:02 | INFO | Using classifier +2025-09-14,03:43:53 | INFO | Finished zero-shot imagenet. +2025-09-14,03:43:53 | INFO | Eval Epoch: 8 imagenet-zeroshot-val-top1: 0.2849 imagenet-zeroshot-val-top5: 0.5429 +2025-09-14,03:43:54 | INFO | Start epoch 8 +2025-09-14,03:43:57 | INFO | Train Epoch: 8 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.26398 (0.26398) Boundary_loss: 0.013902 (0.013902) Loss: 0.27788 (0.27788) +2025-09-14,03:45:02 | INFO | Train Epoch: 8 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.27335 (0.26866) Boundary_loss: 0.013902 (0.013902) Loss: 0.28725 (0.28257) +2025-09-14,03:46:08 | INFO | Train Epoch: 8 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.27617 (0.27117) Boundary_loss: 0.013909 (0.013904) Loss: 0.29008 (0.28507) +2025-09-14,03:47:14 | INFO | Train Epoch: 8 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.32443 (0.28448) Boundary_loss: 0.013901 (0.013904) Loss: 0.33833 (0.29839) +2025-09-14,03:48:20 | INFO | Train Epoch: 8 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.29028 (0.28564) Boundary_loss: 0.013907 (0.013904) Loss: 0.30419 (0.29955) +2025-09-14,03:49:26 | INFO | Train Epoch: 8 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.16961 (0.26630) Boundary_loss: 0.013903 (0.013904) Loss: 0.18351 (0.28021) +2025-09-14,03:50:31 | INFO | Train Epoch: 8 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.30161 (0.27135) Boundary_loss: 0.013906 (0.013904) Loss: 0.31552 (0.28525) +2025-09-14,03:51:37 | INFO | Train Epoch: 8 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.30166 (0.27514) Boundary_loss: 0.013903 (0.013904) Loss: 0.31556 (0.28904) +2025-09-14,03:52:43 | INFO | Train Epoch: 8 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.19486 (0.26622) Boundary_loss: 0.013905 (0.013904) Loss: 0.20877 (0.28012) +2025-09-14,03:53:49 | INFO | Train Epoch: 8 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.27269 (0.26686) Boundary_loss: 0.013903 (0.013904) Loss: 0.28660 (0.28077) +2025-09-14,03:54:55 | INFO | Train Epoch: 8 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.18838 (0.25973) Boundary_loss: 0.013906 (0.013904) Loss: 0.20228 (0.27363) +2025-09-14,03:56:01 | INFO | Train Epoch: 8 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.25545 (0.25937) Boundary_loss: 0.013905 (0.013904) Loss: 0.26936 (0.27328) +2025-09-14,03:57:06 | INFO | Train Epoch: 8 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.23927 (0.25783) Boundary_loss: 0.013906 (0.013905) Loss: 0.25318 (0.27173) +2025-09-14,03:58:12 | INFO | Train Epoch: 8 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.20713 (0.25421) Boundary_loss: 0.013902 (0.013904) Loss: 0.22103 (0.26811) +2025-09-14,03:59:18 | INFO | Train Epoch: 8 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.26542 (0.25495) Boundary_loss: 0.013902 (0.013904) Loss: 0.27932 (0.26886) +2025-09-14,04:00:24 | INFO | Train Epoch: 8 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.23691 (0.25383) Boundary_loss: 0.013902 (0.013904) Loss: 0.25081 (0.26773) +2025-09-14,04:01:30 | INFO | Train Epoch: 8 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.27018 (0.25479) Boundary_loss: 0.013907 (0.013904) Loss: 0.28409 (0.26869) +2025-09-14,04:02:36 | INFO | Train Epoch: 8 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.29368 (0.25695) Boundary_loss: 0.013901 (0.013904) Loss: 0.30758 (0.27085) +2025-09-14,04:03:41 | INFO | Train Epoch: 8 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.23983 (0.25605) Boundary_loss: 0.013902 (0.013904) Loss: 0.25373 (0.26995) +2025-09-14,04:04:47 | INFO | Train Epoch: 8 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.29032 (0.25776) Boundary_loss: 0.013907 (0.013904) Loss: 0.30422 (0.27167) +2025-09-14,04:05:53 | INFO | Train Epoch: 8 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22882 (0.25638) Boundary_loss: 0.013905 (0.013904) Loss: 0.24273 (0.27029) +2025-09-14,04:06:59 | INFO | Train Epoch: 8 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.22220 (0.25483) Boundary_loss: 0.013903 (0.013904) Loss: 0.23611 (0.26873) +2025-09-14,04:08:05 | INFO | Train Epoch: 8 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.22047 (0.25334) Boundary_loss: 0.013902 (0.013904) Loss: 0.23437 (0.26724) +2025-09-14,04:09:11 | INFO | Train Epoch: 8 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.32937 (0.25650) Boundary_loss: 0.013907 (0.013904) Loss: 0.34327 (0.27041) +2025-09-14,04:10:16 | INFO | Train Epoch: 8 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16341 (0.25278) Boundary_loss: 0.013905 (0.013904) Loss: 0.17732 (0.26668) +2025-09-14,04:11:22 | INFO | Train Epoch: 8 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.33060 (0.25577) Boundary_loss: 0.013905 (0.013904) Loss: 0.34451 (0.26968) +2025-09-14,04:12:28 | INFO | Train Epoch: 8 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25713 (0.25582) Boundary_loss: 0.013900 (0.013904) Loss: 0.27103 (0.26973) +2025-09-14,04:13:34 | INFO | Train Epoch: 8 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.24798 (0.25554) Boundary_loss: 0.013904 (0.013904) Loss: 0.26188 (0.26945) +2025-09-14,04:14:40 | INFO | Train Epoch: 8 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.21306 (0.25408) Boundary_loss: 0.013909 (0.013904) Loss: 0.22697 (0.26798) +2025-09-14,04:15:46 | INFO | Train Epoch: 8 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.23936 (0.25359) Boundary_loss: 0.013904 (0.013904) Loss: 0.25326 (0.26749) +2025-09-14,04:16:52 | INFO | Train Epoch: 8 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.28237 (0.25452) Boundary_loss: 0.013902 (0.013904) Loss: 0.29627 (0.26842) +2025-09-14,04:17:57 | INFO | Train Epoch: 8 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.21444 (0.25326) Boundary_loss: 0.013905 (0.013904) Loss: 0.22834 (0.26717) +2025-09-14,04:19:03 | INFO | Train Epoch: 8 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.21697 (0.25216) Boundary_loss: 0.013904 (0.013904) Loss: 0.23088 (0.26607) +2025-09-14,04:20:09 | INFO | Train Epoch: 8 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.27196 (0.25275) Boundary_loss: 0.013903 (0.013904) Loss: 0.28587 (0.26665) +2025-09-14,04:21:15 | INFO | Train Epoch: 8 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.25328 (0.25276) Boundary_loss: 0.013909 (0.013904) Loss: 0.26719 (0.26667) +2025-09-14,04:22:21 | INFO | Train Epoch: 8 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.27811 (0.25347) Boundary_loss: 0.013904 (0.013904) Loss: 0.29201 (0.26737) +2025-09-14,04:23:27 | INFO | Train Epoch: 8 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.22593 (0.25272) Boundary_loss: 0.013902 (0.013904) Loss: 0.23983 (0.26663) +2025-09-14,04:24:33 | INFO | Train Epoch: 8 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.26327 (0.25300) Boundary_loss: 0.013906 (0.013904) Loss: 0.27718 (0.26690) +2025-09-14,04:25:38 | INFO | Train Epoch: 8 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.30567 (0.25435) Boundary_loss: 0.013907 (0.013904) Loss: 0.31958 (0.26825) +2025-09-14,04:26:44 | INFO | Train Epoch: 8 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.21657 (0.25340) Boundary_loss: 0.013907 (0.013904) Loss: 0.23048 (0.26731) +2025-09-14,04:27:50 | INFO | Train Epoch: 8 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.29016 (0.25430) Boundary_loss: 0.013906 (0.013904) Loss: 0.30407 (0.26821) +2025-09-14,04:28:56 | INFO | Train Epoch: 8 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.23765 (0.25390) Boundary_loss: 0.013908 (0.013905) Loss: 0.25156 (0.26781) +2025-09-14,04:30:02 | INFO | Train Epoch: 8 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.25214 (0.25386) Boundary_loss: 0.013905 (0.013905) Loss: 0.26605 (0.26777) +2025-09-14,04:31:08 | INFO | Train Epoch: 8 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.25695 (0.25393) Boundary_loss: 0.013905 (0.013905) Loss: 0.27086 (0.26784) +2025-09-14,04:32:14 | INFO | Train Epoch: 8 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.26159 (0.25410) Boundary_loss: 0.013906 (0.013905) Loss: 0.27549 (0.26801) +2025-09-14,04:33:20 | INFO | Train Epoch: 8 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.26931 (0.25443) Boundary_loss: 0.013911 (0.013905) Loss: 0.28322 (0.26834) +2025-09-14,04:34:26 | INFO | Train Epoch: 8 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.28285 (0.25504) Boundary_loss: 0.013906 (0.013905) Loss: 0.29675 (0.26894) +2025-09-14,04:35:32 | INFO | Train Epoch: 8 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27828 (0.25552) Boundary_loss: 0.013901 (0.013905) Loss: 0.29219 (0.26943) +2025-09-14,04:36:38 | INFO | Train Epoch: 8 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30592 (0.25655) Boundary_loss: 0.013906 (0.013905) Loss: 0.31982 (0.27046) +2025-09-14,04:37:44 | INFO | Train Epoch: 8 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21317 (0.25568) Boundary_loss: 0.013906 (0.013905) Loss: 0.22707 (0.26959) +2025-09-14,04:38:49 | INFO | Train Epoch: 8 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.28671 (0.25629) Boundary_loss: 0.013904 (0.013905) Loss: 0.30061 (0.27020) +2025-09-14,04:39:55 | INFO | Train Epoch: 8 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.22442 (0.25568) Boundary_loss: 0.013914 (0.013905) Loss: 0.23833 (0.26958) +2025-09-14,04:41:01 | INFO | Train Epoch: 8 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.22666 (0.25513) Boundary_loss: 0.013905 (0.013905) Loss: 0.24057 (0.26904) +2025-09-14,04:42:07 | INFO | Train Epoch: 8 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.31948 (0.25632) Boundary_loss: 0.013908 (0.013905) Loss: 0.33338 (0.27023) +2025-09-14,04:43:13 | INFO | Train Epoch: 8 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.24364 (0.25609) Boundary_loss: 0.013906 (0.013905) Loss: 0.25754 (0.27000) +2025-09-14,04:44:19 | INFO | Train Epoch: 8 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.22608 (0.25556) Boundary_loss: 0.013904 (0.013905) Loss: 0.23998 (0.26946) +2025-09-14,04:45:25 | INFO | Train Epoch: 8 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.24792 (0.25542) Boundary_loss: 0.013903 (0.013905) Loss: 0.26182 (0.26933) +2025-09-14,04:46:31 | INFO | Train Epoch: 8 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.25581 (0.25543) Boundary_loss: 0.013904 (0.013905) Loss: 0.26971 (0.26933) +2025-09-14,04:47:37 | INFO | Train Epoch: 8 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.17964 (0.25414) Boundary_loss: 0.013903 (0.013905) Loss: 0.19354 (0.26805) +2025-09-14,04:48:43 | INFO | Train Epoch: 8 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.27414 (0.25448) Boundary_loss: 0.013901 (0.013905) Loss: 0.28804 (0.26838) +2025-09-14,04:49:48 | INFO | Train Epoch: 8 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.28333 (0.25495) Boundary_loss: 0.013901 (0.013905) Loss: 0.29723 (0.26886) +2025-09-14,04:50:54 | INFO | Train Epoch: 8 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.20454 (0.25414) Boundary_loss: 0.013901 (0.013905) Loss: 0.21845 (0.26804) +2025-09-14,04:52:00 | INFO | Train Epoch: 8 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.31977 (0.25518) Boundary_loss: 0.013902 (0.013905) Loss: 0.33368 (0.26908) +2025-09-14,04:53:06 | INFO | Train Epoch: 8 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.22663 (0.25473) Boundary_loss: 0.013901 (0.013905) Loss: 0.24053 (0.26864) +2025-09-14,04:54:12 | INFO | Train Epoch: 8 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.23912 (0.25449) Boundary_loss: 0.013910 (0.013905) Loss: 0.25303 (0.26840) +2025-09-14,04:55:18 | INFO | Train Epoch: 8 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.23030 (0.25413) Boundary_loss: 0.013903 (0.013905) Loss: 0.24421 (0.26803) +2025-09-14,04:56:24 | INFO | Train Epoch: 8 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.21514 (0.25355) Boundary_loss: 0.013909 (0.013905) Loss: 0.22904 (0.26745) +2025-09-14,04:57:30 | INFO | Train Epoch: 8 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.29235 (0.25412) Boundary_loss: 0.013902 (0.013905) Loss: 0.30625 (0.26802) +2025-09-14,04:58:36 | INFO | Train Epoch: 8 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.26802 (0.25432) Boundary_loss: 0.013907 (0.013905) Loss: 0.28193 (0.26822) +2025-09-14,04:59:42 | INFO | Train Epoch: 8 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.25073 (0.25427) Boundary_loss: 0.013903 (0.013905) Loss: 0.26463 (0.26817) +2025-09-14,05:00:48 | INFO | Train Epoch: 8 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.26575 (0.25443) Boundary_loss: 0.013903 (0.013905) Loss: 0.27965 (0.26833) +2025-09-14,05:01:53 | INFO | Train Epoch: 8 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.29631 (0.25501) Boundary_loss: 0.013907 (0.013905) Loss: 0.31021 (0.26891) +2025-09-14,05:02:59 | INFO | Train Epoch: 8 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.27388 (0.25527) Boundary_loss: 0.013907 (0.013905) Loss: 0.28778 (0.26917) +2025-09-14,05:04:05 | INFO | Train Epoch: 8 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.23881 (0.25505) Boundary_loss: 0.013901 (0.013905) Loss: 0.25271 (0.26895) +2025-09-14,05:05:11 | INFO | Train Epoch: 8 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.24700 (0.25494) Boundary_loss: 0.013903 (0.013905) Loss: 0.26090 (0.26884) +2025-09-14,05:06:17 | INFO | Train Epoch: 8 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.21987 (0.25448) Boundary_loss: 0.013909 (0.013905) Loss: 0.23378 (0.26838) +2025-09-14,05:07:23 | INFO | Train Epoch: 8 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.23656 (0.25424) Boundary_loss: 0.013902 (0.013905) Loss: 0.25046 (0.26815) +2025-09-14,05:08:29 | INFO | Train Epoch: 8 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.27853 (0.25456) Boundary_loss: 0.013898 (0.013905) Loss: 0.29243 (0.26846) +2025-09-14,05:09:35 | INFO | Train Epoch: 8 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.20553 (0.25393) Boundary_loss: 0.013904 (0.013905) Loss: 0.21944 (0.26784) +2025-09-14,05:10:41 | INFO | Train Epoch: 8 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.22863 (0.25362) Boundary_loss: 0.013903 (0.013904) Loss: 0.24254 (0.26752) +2025-09-14,05:11:47 | INFO | Train Epoch: 8 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.21762 (0.25317) Boundary_loss: 0.013903 (0.013904) Loss: 0.23152 (0.26708) +2025-09-14,05:12:52 | INFO | Train Epoch: 8 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.23135 (0.25291) Boundary_loss: 0.013908 (0.013905) Loss: 0.24525 (0.26681) +2025-09-14,05:13:58 | INFO | Train Epoch: 8 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23136 (0.25265) Boundary_loss: 0.013902 (0.013904) Loss: 0.24526 (0.26655) +2025-09-14,05:15:04 | INFO | Train Epoch: 8 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.30966 (0.25333) Boundary_loss: 0.013907 (0.013905) Loss: 0.32357 (0.26723) +2025-09-14,05:16:10 | INFO | Train Epoch: 8 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.30385 (0.25392) Boundary_loss: 0.013904 (0.013905) Loss: 0.31775 (0.26783) +2025-09-14,05:17:16 | INFO | Train Epoch: 8 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26101 (0.25400) Boundary_loss: 0.013899 (0.013904) Loss: 0.27491 (0.26791) +2025-09-14,05:18:22 | INFO | Train Epoch: 8 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.26428 (0.25412) Boundary_loss: 0.013905 (0.013904) Loss: 0.27818 (0.26803) +2025-09-14,05:19:28 | INFO | Train Epoch: 8 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.28255 (0.25444) Boundary_loss: 0.013910 (0.013905) Loss: 0.29646 (0.26835) +2025-09-14,05:20:34 | INFO | Train Epoch: 8 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.18750 (0.25369) Boundary_loss: 0.013904 (0.013905) Loss: 0.20141 (0.26760) +2025-09-14,05:21:40 | INFO | Train Epoch: 8 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.23004 (0.25343) Boundary_loss: 0.013904 (0.013905) Loss: 0.24394 (0.26733) +2025-09-14,05:22:46 | INFO | Train Epoch: 8 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.26235 (0.25353) Boundary_loss: 0.013908 (0.013905) Loss: 0.27626 (0.26743) +2025-09-14,05:23:52 | INFO | Train Epoch: 8 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.26039 (0.25360) Boundary_loss: 0.013904 (0.013905) Loss: 0.27430 (0.26751) +2025-09-14,05:24:58 | INFO | Train Epoch: 8 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.31455 (0.25426) Boundary_loss: 0.013902 (0.013905) Loss: 0.32845 (0.26816) +2025-09-14,05:26:04 | INFO | Train Epoch: 8 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.20504 (0.25373) Boundary_loss: 0.013911 (0.013905) Loss: 0.21895 (0.26764) +2025-09-14,05:27:10 | INFO | Train Epoch: 8 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.27624 (0.25397) Boundary_loss: 0.013900 (0.013905) Loss: 0.29014 (0.26788) +2025-09-14,05:28:16 | INFO | Train Epoch: 8 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.30818 (0.25454) Boundary_loss: 0.013910 (0.013905) Loss: 0.32209 (0.26844) +2025-09-14,05:29:22 | INFO | Train Epoch: 8 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.26823 (0.25468) Boundary_loss: 0.013900 (0.013905) Loss: 0.28213 (0.26858) +2025-09-14,05:30:27 | INFO | Train Epoch: 8 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.21540 (0.25428) Boundary_loss: 0.013907 (0.013905) Loss: 0.22931 (0.26818) +2025-09-14,05:31:33 | INFO | Train Epoch: 8 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.22148 (0.25395) Boundary_loss: 0.013902 (0.013905) Loss: 0.23538 (0.26785) +2025-09-14,05:32:39 | INFO | Train Epoch: 8 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.28035 (0.25421) Boundary_loss: 0.013905 (0.013905) Loss: 0.29425 (0.26811) +2025-09-14,05:33:45 | INFO | Train Epoch: 8 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.20597 (0.25373) Boundary_loss: 0.013902 (0.013905) Loss: 0.21987 (0.26764) +2025-09-14,05:34:51 | INFO | Train Epoch: 8 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.31004 (0.25428) Boundary_loss: 0.013904 (0.013905) Loss: 0.32395 (0.26819) +2025-09-14,05:35:57 | INFO | Train Epoch: 8 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.28359 (0.25457) Boundary_loss: 0.013905 (0.013905) Loss: 0.29749 (0.26847) +2025-09-14,05:37:03 | INFO | Train Epoch: 8 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.22329 (0.25427) Boundary_loss: 0.013902 (0.013905) Loss: 0.23719 (0.26817) +2025-09-14,05:38:09 | INFO | Train Epoch: 8 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.27016 (0.25442) Boundary_loss: 0.013912 (0.013905) Loss: 0.28408 (0.26832) +2025-09-14,05:39:15 | INFO | Train Epoch: 8 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.25562 (0.25443) Boundary_loss: 0.013902 (0.013905) Loss: 0.26952 (0.26833) +2025-09-14,05:40:21 | INFO | Train Epoch: 8 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.23804 (0.25428) Boundary_loss: 0.013901 (0.013905) Loss: 0.25194 (0.26818) +2025-09-14,05:41:27 | INFO | Train Epoch: 8 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.22339 (0.25399) Boundary_loss: 0.013911 (0.013905) Loss: 0.23730 (0.26790) +2025-09-14,05:42:33 | INFO | Train Epoch: 8 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.18749 (0.25338) Boundary_loss: 0.013903 (0.013905) Loss: 0.20139 (0.26729) +2025-09-14,05:43:39 | INFO | Train Epoch: 8 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.28002 (0.25362) Boundary_loss: 0.013905 (0.013905) Loss: 0.29393 (0.26753) +2025-09-14,05:44:45 | INFO | Train Epoch: 8 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.33121 (0.25432) Boundary_loss: 0.013904 (0.013905) Loss: 0.34511 (0.26823) +2025-09-14,05:45:51 | INFO | Train Epoch: 8 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.26122 (0.25438) Boundary_loss: 0.013900 (0.013905) Loss: 0.27512 (0.26829) +2025-09-14,05:46:57 | INFO | Train Epoch: 8 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.22881 (0.25416) Boundary_loss: 0.013900 (0.013904) Loss: 0.24271 (0.26806) +2025-09-14,05:48:03 | INFO | Train Epoch: 8 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.25661 (0.25418) Boundary_loss: 0.013900 (0.013904) Loss: 0.27051 (0.26808) +2025-09-14,05:49:09 | INFO | Train Epoch: 8 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.27259 (0.25434) Boundary_loss: 0.013903 (0.013904) Loss: 0.28649 (0.26824) +2025-09-14,05:50:14 | INFO | Train Epoch: 8 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.22569 (0.25409) Boundary_loss: 0.013903 (0.013904) Loss: 0.23960 (0.26800) +2025-09-14,05:51:20 | INFO | Train Epoch: 8 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.18892 (0.25353) Boundary_loss: 0.013901 (0.013904) Loss: 0.20283 (0.26744) +2025-09-14,05:52:26 | INFO | Train Epoch: 8 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.29393 (0.25388) Boundary_loss: 0.013902 (0.013904) Loss: 0.30784 (0.26778) +2025-09-14,05:53:32 | INFO | Train Epoch: 8 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.23167 (0.25369) Boundary_loss: 0.013902 (0.013904) Loss: 0.24557 (0.26759) +2025-09-14,05:54:38 | INFO | Train Epoch: 8 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.22549 (0.25346) Boundary_loss: 0.013909 (0.013904) Loss: 0.23940 (0.26736) +2025-09-14,05:55:44 | INFO | Train Epoch: 8 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.29529 (0.25380) Boundary_loss: 0.013900 (0.013904) Loss: 0.30919 (0.26771) +2025-09-14,05:56:50 | INFO | Train Epoch: 8 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.22243 (0.25354) Boundary_loss: 0.013903 (0.013904) Loss: 0.23633 (0.26745) +2025-09-14,05:57:56 | INFO | Train Epoch: 8 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.19693 (0.25308) Boundary_loss: 0.013902 (0.013904) Loss: 0.21083 (0.26699) +2025-09-14,05:59:02 | INFO | Train Epoch: 8 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.22630 (0.25287) Boundary_loss: 0.013902 (0.013904) Loss: 0.24020 (0.26677) +2025-09-14,06:00:08 | INFO | Train Epoch: 8 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.30174 (0.25326) Boundary_loss: 0.013901 (0.013904) Loss: 0.31564 (0.26716) +2025-09-14,06:01:14 | INFO | Train Epoch: 8 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.26003 (0.25331) Boundary_loss: 0.013901 (0.013904) Loss: 0.27393 (0.26722) +2025-09-14,06:02:20 | INFO | Train Epoch: 8 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.27464 (0.25348) Boundary_loss: 0.013904 (0.013904) Loss: 0.28854 (0.26738) +2025-09-14,06:03:25 | INFO | Train Epoch: 8 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.28762 (0.25375) Boundary_loss: 0.013905 (0.013904) Loss: 0.30153 (0.26765) +2025-09-14,06:04:31 | INFO | Train Epoch: 8 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.30043 (0.25411) Boundary_loss: 0.013902 (0.013904) Loss: 0.31434 (0.26801) +2025-09-14,06:05:37 | INFO | Train Epoch: 8 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.23853 (0.25399) Boundary_loss: 0.013904 (0.013904) Loss: 0.25243 (0.26789) +2025-09-14,06:06:43 | INFO | Train Epoch: 8 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.19232 (0.25352) Boundary_loss: 0.013902 (0.013904) Loss: 0.20623 (0.26742) +2025-09-14,06:07:49 | INFO | Train Epoch: 8 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.23953 (0.25341) Boundary_loss: 0.013906 (0.013904) Loss: 0.25344 (0.26732) +2025-09-14,06:08:55 | INFO | Train Epoch: 8 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.33326 (0.25401) Boundary_loss: 0.013906 (0.013904) Loss: 0.34717 (0.26792) +2025-09-14,06:10:01 | INFO | Train Epoch: 8 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24508 (0.25395) Boundary_loss: 0.013908 (0.013904) Loss: 0.25899 (0.26785) +2025-09-14,06:11:07 | INFO | Train Epoch: 8 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.23707 (0.25382) Boundary_loss: 0.013903 (0.013904) Loss: 0.25097 (0.26773) +2025-09-14,06:12:13 | INFO | Train Epoch: 8 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.25177 (0.25381) Boundary_loss: 0.013902 (0.013904) Loss: 0.26567 (0.26771) +2025-09-14,06:13:19 | INFO | Train Epoch: 8 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.21827 (0.25355) Boundary_loss: 0.013902 (0.013904) Loss: 0.23217 (0.26745) +2025-09-14,06:14:25 | INFO | Train Epoch: 8 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.25272 (0.25354) Boundary_loss: 0.013904 (0.013904) Loss: 0.26662 (0.26745) +2025-09-14,06:15:31 | INFO | Train Epoch: 8 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.24353 (0.25347) Boundary_loss: 0.013904 (0.013904) Loss: 0.25744 (0.26737) +2025-09-14,06:16:37 | INFO | Train Epoch: 8 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.22725 (0.25328) Boundary_loss: 0.013908 (0.013904) Loss: 0.24115 (0.26719) +2025-09-14,06:17:43 | INFO | Train Epoch: 8 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.25430 (0.25329) Boundary_loss: 0.013904 (0.013904) Loss: 0.26820 (0.26719) +2025-09-14,06:18:49 | INFO | Train Epoch: 8 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.24123 (0.25320) Boundary_loss: 0.013901 (0.013904) Loss: 0.25513 (0.26711) +2025-09-14,06:19:55 | INFO | Train Epoch: 8 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.28194 (0.25340) Boundary_loss: 0.013901 (0.013904) Loss: 0.29584 (0.26731) +2025-09-14,06:21:01 | INFO | Train Epoch: 8 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.23228 (0.25326) Boundary_loss: 0.013902 (0.013904) Loss: 0.24618 (0.26716) +2025-09-14,06:22:07 | INFO | Train Epoch: 8 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.20211 (0.25291) Boundary_loss: 0.013904 (0.013904) Loss: 0.21602 (0.26681) +2025-09-14,06:23:13 | INFO | Train Epoch: 8 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.26985 (0.25302) Boundary_loss: 0.013900 (0.013904) Loss: 0.28375 (0.26693) +2025-09-14,06:24:19 | INFO | Train Epoch: 8 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.22645 (0.25284) Boundary_loss: 0.013904 (0.013904) Loss: 0.24036 (0.26674) +2025-09-14,06:25:25 | INFO | Train Epoch: 8 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.23315 (0.25271) Boundary_loss: 0.013906 (0.013904) Loss: 0.24706 (0.26661) +2025-09-14,06:26:31 | INFO | Train Epoch: 8 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.23787 (0.25261) Boundary_loss: 0.013902 (0.013904) Loss: 0.25177 (0.26651) +2025-09-14,06:27:37 | INFO | Train Epoch: 8 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.29556 (0.25289) Boundary_loss: 0.013902 (0.013904) Loss: 0.30946 (0.26680) +2025-09-14,06:28:43 | INFO | Train Epoch: 8 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.31432 (0.25330) Boundary_loss: 0.013904 (0.013904) Loss: 0.32822 (0.26721) +2025-09-14,06:29:49 | INFO | Train Epoch: 8 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.20333 (0.25297) Boundary_loss: 0.013902 (0.013904) Loss: 0.21723 (0.26688) +2025-09-14,06:30:55 | INFO | Train Epoch: 8 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25415 (0.25298) Boundary_loss: 0.013902 (0.013904) Loss: 0.26805 (0.26688) +2025-09-14,06:32:01 | INFO | Train Epoch: 8 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.25127 (0.25297) Boundary_loss: 0.013903 (0.013904) Loss: 0.26517 (0.26687) +2025-09-14,06:33:07 | INFO | Train Epoch: 8 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20717 (0.25267) Boundary_loss: 0.013907 (0.013904) Loss: 0.22108 (0.26658) +2025-09-14,06:34:13 | INFO | Train Epoch: 8 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.26841 (0.25277) Boundary_loss: 0.013901 (0.013904) Loss: 0.28231 (0.26668) +2025-09-14,06:35:19 | INFO | Train Epoch: 8 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.23182 (0.25264) Boundary_loss: 0.013899 (0.013904) Loss: 0.24572 (0.26654) +2025-09-14,06:36:25 | INFO | Train Epoch: 8 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.32974 (0.25313) Boundary_loss: 0.013902 (0.013904) Loss: 0.34364 (0.26703) +2025-09-14,06:37:31 | INFO | Train Epoch: 8 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.26316 (0.25319) Boundary_loss: 0.013902 (0.013904) Loss: 0.27706 (0.26710) +2025-09-14,06:38:37 | INFO | Train Epoch: 8 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.28661 (0.25340) Boundary_loss: 0.013903 (0.013904) Loss: 0.30052 (0.26730) +2025-09-14,06:39:43 | INFO | Train Epoch: 8 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.29078 (0.25363) Boundary_loss: 0.013903 (0.013904) Loss: 0.30469 (0.26754) +2025-09-14,06:40:49 | INFO | Train Epoch: 8 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.25481 (0.25364) Boundary_loss: 0.013902 (0.013904) Loss: 0.26871 (0.26754) +2025-09-14,06:41:55 | INFO | Train Epoch: 8 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.19292 (0.25327) Boundary_loss: 0.013901 (0.013904) Loss: 0.20682 (0.26717) +2025-09-14,06:43:01 | INFO | Train Epoch: 8 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.20797 (0.25299) Boundary_loss: 0.013900 (0.013904) Loss: 0.22187 (0.26690) +2025-09-14,06:44:07 | INFO | Train Epoch: 8 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.25876 (0.25303) Boundary_loss: 0.013904 (0.013904) Loss: 0.27266 (0.26693) +2025-09-14,06:45:13 | INFO | Train Epoch: 8 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.25035 (0.25301) Boundary_loss: 0.013903 (0.013904) Loss: 0.26426 (0.26691) +2025-09-14,06:46:19 | INFO | Train Epoch: 8 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.28470 (0.25320) Boundary_loss: 0.013910 (0.013904) Loss: 0.29861 (0.26710) +2025-09-14,06:47:25 | INFO | Train Epoch: 8 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.26021 (0.25324) Boundary_loss: 0.013902 (0.013904) Loss: 0.27411 (0.26715) +2025-09-14,06:48:31 | INFO | Train Epoch: 8 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.24127 (0.25317) Boundary_loss: 0.013904 (0.013904) Loss: 0.25518 (0.26707) +2025-09-14,06:49:37 | INFO | Train Epoch: 8 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.21571 (0.25295) Boundary_loss: 0.013904 (0.013904) Loss: 0.22962 (0.26685) +2025-09-14,06:50:43 | INFO | Train Epoch: 8 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.28087 (0.25311) Boundary_loss: 0.013904 (0.013904) Loss: 0.29477 (0.26702) +2025-09-14,06:51:49 | INFO | Train Epoch: 8 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.27696 (0.25325) Boundary_loss: 0.013899 (0.013904) Loss: 0.29086 (0.26716) +2025-09-14,06:52:55 | INFO | Train Epoch: 8 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.25204 (0.25325) Boundary_loss: 0.013914 (0.013904) Loss: 0.26596 (0.26715) +2025-09-14,06:54:01 | INFO | Train Epoch: 8 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.24444 (0.25319) Boundary_loss: 0.013904 (0.013904) Loss: 0.25834 (0.26710) +2025-09-14,06:55:07 | INFO | Train Epoch: 8 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26943 (0.25329) Boundary_loss: 0.013906 (0.013904) Loss: 0.28333 (0.26719) +2025-09-14,06:56:13 | INFO | Train Epoch: 8 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.23921 (0.25321) Boundary_loss: 0.013904 (0.013904) Loss: 0.25312 (0.26711) +2025-09-14,06:57:20 | INFO | Train Epoch: 8 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.25040 (0.25319) Boundary_loss: 0.013908 (0.013904) Loss: 0.26430 (0.26710) +2025-09-14,06:58:26 | INFO | Train Epoch: 8 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.25558 (0.25321) Boundary_loss: 0.013901 (0.013904) Loss: 0.26948 (0.26711) +2025-09-14,06:59:32 | INFO | Train Epoch: 8 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.23111 (0.25308) Boundary_loss: 0.013911 (0.013904) Loss: 0.24502 (0.26699) +2025-09-14,07:00:38 | INFO | Train Epoch: 8 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.26671 (0.25316) Boundary_loss: 0.013902 (0.013904) Loss: 0.28061 (0.26706) +2025-09-14,07:01:44 | INFO | Train Epoch: 8 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18611 (0.25279) Boundary_loss: 0.013903 (0.013904) Loss: 0.20001 (0.26669) +2025-09-14,07:02:50 | INFO | Train Epoch: 8 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.30871 (0.25309) Boundary_loss: 0.013900 (0.013904) Loss: 0.32261 (0.26700) +2025-09-14,07:03:56 | INFO | Train Epoch: 8 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.26546 (0.25316) Boundary_loss: 0.013903 (0.013904) Loss: 0.27936 (0.26707) +2025-09-14,07:05:02 | INFO | Train Epoch: 8 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.27548 (0.25328) Boundary_loss: 0.013905 (0.013904) Loss: 0.28939 (0.26719) +2025-09-14,07:06:08 | INFO | Train Epoch: 8 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.26164 (0.25333) Boundary_loss: 0.013903 (0.013904) Loss: 0.27555 (0.26723) +2025-09-14,07:07:14 | INFO | Train Epoch: 8 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.22210 (0.25316) Boundary_loss: 0.013907 (0.013904) Loss: 0.23601 (0.26706) +2025-09-14,07:08:20 | INFO | Train Epoch: 8 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.25000 (0.25314) Boundary_loss: 0.013900 (0.013904) Loss: 0.26390 (0.26705) +2025-09-14,07:09:26 | INFO | Train Epoch: 8 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.29593 (0.25337) Boundary_loss: 0.013905 (0.013904) Loss: 0.30984 (0.26728) +2025-09-14,07:10:32 | INFO | Train Epoch: 8 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.25069 (0.25336) Boundary_loss: 0.013898 (0.013904) Loss: 0.26459 (0.26726) +2025-09-14,07:11:38 | INFO | Train Epoch: 8 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.21989 (0.25318) Boundary_loss: 0.013899 (0.013904) Loss: 0.23379 (0.26708) +2025-09-14,07:12:44 | INFO | Train Epoch: 8 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.27181 (0.25328) Boundary_loss: 0.013904 (0.013904) Loss: 0.28572 (0.26718) +2025-09-14,07:13:50 | INFO | Train Epoch: 8 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.25202 (0.25327) Boundary_loss: 0.013901 (0.013904) Loss: 0.26592 (0.26718) +2025-09-14,07:14:56 | INFO | Train Epoch: 8 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.20570 (0.25303) Boundary_loss: 0.013909 (0.013904) Loss: 0.21961 (0.26693) +2025-09-14,07:16:02 | INFO | Train Epoch: 8 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.20767 (0.25279) Boundary_loss: 0.013910 (0.013904) Loss: 0.22158 (0.26670) +2025-09-14,07:17:08 | INFO | Train Epoch: 8 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.25367 (0.25280) Boundary_loss: 0.013902 (0.013904) Loss: 0.26757 (0.26670) +2025-09-14,07:18:14 | INFO | Train Epoch: 8 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.24193 (0.25274) Boundary_loss: 0.013902 (0.013904) Loss: 0.25584 (0.26664) +2025-09-14,07:19:20 | INFO | Train Epoch: 8 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.21700 (0.25256) Boundary_loss: 0.013902 (0.013904) Loss: 0.23090 (0.26646) +2025-09-14,07:20:26 | INFO | Train Epoch: 8 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.28807 (0.25274) Boundary_loss: 0.013904 (0.013904) Loss: 0.30198 (0.26664) +2025-09-14,07:21:32 | INFO | Train Epoch: 8 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.23652 (0.25266) Boundary_loss: 0.013902 (0.013904) Loss: 0.25042 (0.26656) +2025-09-14,07:22:38 | INFO | Train Epoch: 8 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17337 (0.25226) Boundary_loss: 0.013900 (0.013904) Loss: 0.18727 (0.26616) +2025-09-14,07:23:44 | INFO | Train Epoch: 8 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.21707 (0.25209) Boundary_loss: 0.013901 (0.013904) Loss: 0.23097 (0.26599) +2025-09-14,07:24:50 | INFO | Train Epoch: 8 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.28152 (0.25223) Boundary_loss: 0.013905 (0.013904) Loss: 0.29543 (0.26614) +2025-09-14,07:25:56 | INFO | Train Epoch: 8 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.19105 (0.25193) Boundary_loss: 0.013901 (0.013904) Loss: 0.20495 (0.26583) +2025-09-14,07:27:02 | INFO | Train Epoch: 8 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.24358 (0.25189) Boundary_loss: 0.013903 (0.013904) Loss: 0.25748 (0.26579) +2025-09-14,07:28:08 | INFO | Train Epoch: 8 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.27460 (0.25200) Boundary_loss: 0.013909 (0.013904) Loss: 0.28851 (0.26590) +2025-09-14,07:29:14 | INFO | Train Epoch: 8 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.20167 (0.25176) Boundary_loss: 0.013912 (0.013904) Loss: 0.21558 (0.26566) +2025-09-14,07:30:21 | INFO | Train Epoch: 8 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.24882 (0.25174) Boundary_loss: 0.013909 (0.013904) Loss: 0.26273 (0.26565) +2025-09-14,07:31:27 | INFO | Train Epoch: 8 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.16164 (0.25131) Boundary_loss: 0.013906 (0.013904) Loss: 0.17554 (0.26521) +2025-09-14,07:32:33 | INFO | Train Epoch: 8 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.25462 (0.25132) Boundary_loss: 0.013900 (0.013904) Loss: 0.26851 (0.26523) +2025-09-14,07:33:39 | INFO | Train Epoch: 8 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19384 (0.25105) Boundary_loss: 0.013903 (0.013904) Loss: 0.20775 (0.26495) +2025-09-14,07:34:45 | INFO | Train Epoch: 8 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.25155 (0.25105) Boundary_loss: 0.013906 (0.013904) Loss: 0.26546 (0.26496) +2025-09-14,07:35:51 | INFO | Train Epoch: 8 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.26603 (0.25112) Boundary_loss: 0.013901 (0.013904) Loss: 0.27993 (0.26503) +2025-09-14,07:36:57 | INFO | Train Epoch: 8 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.24397 (0.25109) Boundary_loss: 0.013905 (0.013904) Loss: 0.25787 (0.26499) +2025-09-14,07:38:03 | INFO | Train Epoch: 8 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.25000 (0.25108) Boundary_loss: 0.013903 (0.013904) Loss: 0.26391 (0.26499) +2025-09-14,07:39:09 | INFO | Train Epoch: 8 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.23059 (0.25099) Boundary_loss: 0.013906 (0.013904) Loss: 0.24450 (0.26489) +2025-09-14,07:40:15 | INFO | Train Epoch: 8 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.26229 (0.25104) Boundary_loss: 0.013899 (0.013904) Loss: 0.27619 (0.26495) +2025-09-14,07:41:21 | INFO | Train Epoch: 8 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.21224 (0.25086) Boundary_loss: 0.013899 (0.013904) Loss: 0.22614 (0.26477) +2025-09-14,07:42:27 | INFO | Train Epoch: 8 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.26196 (0.25091) Boundary_loss: 0.013906 (0.013904) Loss: 0.27587 (0.26482) +2025-09-14,07:43:33 | INFO | Train Epoch: 8 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.21463 (0.25075) Boundary_loss: 0.013904 (0.013904) Loss: 0.22853 (0.26465) +2025-09-14,07:44:39 | INFO | Train Epoch: 8 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.18331 (0.25044) Boundary_loss: 0.013906 (0.013904) Loss: 0.19722 (0.26435) +2025-09-14,07:45:45 | INFO | Train Epoch: 8 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.21718 (0.25029) Boundary_loss: 0.013906 (0.013904) Loss: 0.23109 (0.26419) +2025-09-14,07:46:51 | INFO | Train Epoch: 8 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.24999 (0.25029) Boundary_loss: 0.013900 (0.013904) Loss: 0.26389 (0.26419) +2025-09-14,07:47:57 | INFO | Train Epoch: 8 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.22153 (0.25016) Boundary_loss: 0.013901 (0.013904) Loss: 0.23543 (0.26406) +2025-09-14,07:49:03 | INFO | Train Epoch: 8 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.24138 (0.25012) Boundary_loss: 0.013901 (0.013904) Loss: 0.25528 (0.26403) +2025-09-14,07:50:09 | INFO | Train Epoch: 8 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.31330 (0.25040) Boundary_loss: 0.013908 (0.013904) Loss: 0.32721 (0.26431) +2025-09-14,07:51:16 | INFO | Train Epoch: 8 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.18932 (0.25013) Boundary_loss: 0.013904 (0.013904) Loss: 0.20322 (0.26404) +2025-09-14,07:52:22 | INFO | Train Epoch: 8 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.22151 (0.25001) Boundary_loss: 0.013900 (0.013904) Loss: 0.23541 (0.26391) +2025-09-14,07:53:28 | INFO | Train Epoch: 8 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.20163 (0.24979) Boundary_loss: 0.013901 (0.013904) Loss: 0.21553 (0.26370) +2025-09-14,07:54:34 | INFO | Train Epoch: 8 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.30167 (0.25002) Boundary_loss: 0.013900 (0.013904) Loss: 0.31557 (0.26392) +2025-09-14,07:55:40 | INFO | Train Epoch: 8 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.23276 (0.24995) Boundary_loss: 0.013902 (0.013904) Loss: 0.24667 (0.26385) +2025-09-14,07:56:46 | INFO | Train Epoch: 8 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.23790 (0.24989) Boundary_loss: 0.013905 (0.013904) Loss: 0.25181 (0.26380) +2025-09-14,07:57:52 | INFO | Train Epoch: 8 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.27725 (0.25001) Boundary_loss: 0.013899 (0.013904) Loss: 0.29115 (0.26391) +2025-09-14,07:58:58 | INFO | Train Epoch: 8 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.25026 (0.25001) Boundary_loss: 0.013904 (0.013904) Loss: 0.26416 (0.26392) +2025-09-14,08:00:04 | INFO | Train Epoch: 8 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.26512 (0.25008) Boundary_loss: 0.013903 (0.013904) Loss: 0.27902 (0.26398) +2025-09-14,08:01:10 | INFO | Train Epoch: 8 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.23376 (0.25001) Boundary_loss: 0.013903 (0.013904) Loss: 0.24766 (0.26391) +2025-09-14,08:02:16 | INFO | Train Epoch: 8 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.27561 (0.25012) Boundary_loss: 0.013905 (0.013904) Loss: 0.28952 (0.26402) +2025-09-14,08:03:22 | INFO | Train Epoch: 8 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.21788 (0.24998) Boundary_loss: 0.013904 (0.013904) Loss: 0.23179 (0.26388) +2025-09-14,08:04:28 | INFO | Train Epoch: 8 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.24002 (0.24994) Boundary_loss: 0.013904 (0.013904) Loss: 0.25393 (0.26384) +2025-09-14,08:05:34 | INFO | Train Epoch: 8 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.30170 (0.25015) Boundary_loss: 0.013901 (0.013904) Loss: 0.31560 (0.26406) +2025-09-14,08:06:40 | INFO | Train Epoch: 8 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.20139 (0.24995) Boundary_loss: 0.013902 (0.013904) Loss: 0.21529 (0.26386) +2025-09-14,08:07:46 | INFO | Train Epoch: 8 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.23750 (0.24990) Boundary_loss: 0.013901 (0.013904) Loss: 0.25140 (0.26380) +2025-09-14,08:08:52 | INFO | Train Epoch: 8 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.20894 (0.24973) Boundary_loss: 0.013901 (0.013904) Loss: 0.22284 (0.26363) +2025-09-14,08:09:58 | INFO | Train Epoch: 8 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.25136 (0.24974) Boundary_loss: 0.013904 (0.013904) Loss: 0.26527 (0.26364) +2025-09-14,08:11:05 | INFO | Train Epoch: 8 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28561 (0.24988) Boundary_loss: 0.013904 (0.013904) Loss: 0.29951 (0.26379) +2025-09-14,08:12:11 | INFO | Train Epoch: 8 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.24390 (0.24986) Boundary_loss: 0.013902 (0.013904) Loss: 0.25781 (0.26376) +2025-09-14,08:13:17 | INFO | Train Epoch: 8 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.28720 (0.25001) Boundary_loss: 0.013903 (0.013904) Loss: 0.30110 (0.26392) +2025-09-14,08:14:23 | INFO | Train Epoch: 8 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.25103 (0.25002) Boundary_loss: 0.013900 (0.013904) Loss: 0.26493 (0.26392) +2025-09-14,08:15:29 | INFO | Train Epoch: 8 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.22463 (0.24991) Boundary_loss: 0.013910 (0.013904) Loss: 0.23854 (0.26382) +2025-09-14,08:16:35 | INFO | Train Epoch: 8 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.23308 (0.24985) Boundary_loss: 0.013907 (0.013904) Loss: 0.24699 (0.26375) +2025-09-14,08:17:41 | INFO | Train Epoch: 8 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.23580 (0.24979) Boundary_loss: 0.013904 (0.013904) Loss: 0.24970 (0.26369) +2025-09-14,08:18:47 | INFO | Train Epoch: 8 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.15710 (0.24942) Boundary_loss: 0.013905 (0.013904) Loss: 0.17100 (0.26332) +2025-09-14,08:19:53 | INFO | Train Epoch: 8 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.36811 (0.24989) Boundary_loss: 0.013902 (0.013904) Loss: 0.38201 (0.26379) +2025-09-14,08:20:59 | INFO | Train Epoch: 8 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.18986 (0.24965) Boundary_loss: 0.013901 (0.013904) Loss: 0.20376 (0.26356) +2025-09-14,08:22:05 | INFO | Train Epoch: 8 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.19859 (0.24945) Boundary_loss: 0.013899 (0.013904) Loss: 0.21249 (0.26336) +2025-09-14,08:23:11 | INFO | Train Epoch: 8 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.22857 (0.24937) Boundary_loss: 0.013916 (0.013904) Loss: 0.24248 (0.26327) +2025-09-14,08:24:17 | INFO | Train Epoch: 8 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.25573 (0.24940) Boundary_loss: 0.013904 (0.013904) Loss: 0.26964 (0.26330) +2025-09-14,08:25:23 | INFO | Train Epoch: 8 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15205 (0.24902) Boundary_loss: 0.013901 (0.013904) Loss: 0.16595 (0.26292) +2025-09-14,08:26:29 | INFO | Train Epoch: 8 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.23834 (0.24898) Boundary_loss: 0.013904 (0.013904) Loss: 0.25224 (0.26288) +2025-09-14,08:27:35 | INFO | Train Epoch: 8 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.18281 (0.24872) Boundary_loss: 0.013900 (0.013904) Loss: 0.19671 (0.26262) +2025-09-14,08:28:41 | INFO | Train Epoch: 8 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.23079 (0.24865) Boundary_loss: 0.013903 (0.013904) Loss: 0.24469 (0.26255) +2025-09-14,08:29:47 | INFO | Train Epoch: 8 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.22991 (0.24858) Boundary_loss: 0.013900 (0.013904) Loss: 0.24381 (0.26248) +2025-09-14,08:30:53 | INFO | Train Epoch: 8 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.27716 (0.24869) Boundary_loss: 0.013899 (0.013904) Loss: 0.29106 (0.26259) +2025-09-14,08:32:00 | INFO | Train Epoch: 8 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.22675 (0.24860) Boundary_loss: 0.013911 (0.013904) Loss: 0.24066 (0.26251) +2025-09-14,08:33:06 | INFO | Train Epoch: 8 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.22094 (0.24850) Boundary_loss: 0.013908 (0.013904) Loss: 0.23485 (0.26240) +2025-09-14,08:34:12 | INFO | Train Epoch: 8 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.20282 (0.24833) Boundary_loss: 0.013902 (0.013904) Loss: 0.21672 (0.26223) +2025-09-14,08:35:18 | INFO | Train Epoch: 8 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.20681 (0.24817) Boundary_loss: 0.013899 (0.013904) Loss: 0.22071 (0.26208) +2025-09-14,08:36:24 | INFO | Train Epoch: 8 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.28658 (0.24832) Boundary_loss: 0.013900 (0.013904) Loss: 0.30048 (0.26222) +2025-09-14,08:37:30 | INFO | Train Epoch: 8 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.22700 (0.24824) Boundary_loss: 0.013903 (0.013904) Loss: 0.24090 (0.26214) +2025-09-14,08:38:36 | INFO | Train Epoch: 8 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.26298 (0.24829) Boundary_loss: 0.013912 (0.013904) Loss: 0.27689 (0.26219) +2025-09-14,08:39:42 | INFO | Train Epoch: 8 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.27850 (0.24840) Boundary_loss: 0.013901 (0.013904) Loss: 0.29240 (0.26231) +2025-09-14,08:40:48 | INFO | Train Epoch: 8 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.37314 (0.24886) Boundary_loss: 0.013912 (0.013904) Loss: 0.38706 (0.26277) +2025-09-14,08:41:54 | INFO | Train Epoch: 8 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.21271 (0.24873) Boundary_loss: 0.013903 (0.013904) Loss: 0.22661 (0.26263) +2025-09-14,08:43:00 | INFO | Train Epoch: 8 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.27351 (0.24882) Boundary_loss: 0.013903 (0.013904) Loss: 0.28741 (0.26272) +2025-09-14,08:44:06 | INFO | Train Epoch: 8 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.24188 (0.24880) Boundary_loss: 0.013904 (0.013904) Loss: 0.25578 (0.26270) +2025-09-14,08:45:13 | INFO | Train Epoch: 8 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.26128 (0.24884) Boundary_loss: 0.013902 (0.013904) Loss: 0.27519 (0.26274) +2025-09-14,08:46:19 | INFO | Train Epoch: 8 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27575 (0.24894) Boundary_loss: 0.013905 (0.013904) Loss: 0.28965 (0.26284) +2025-09-14,08:47:25 | INFO | Train Epoch: 8 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.19956 (0.24876) Boundary_loss: 0.013903 (0.013904) Loss: 0.21346 (0.26266) +2025-09-14,08:48:31 | INFO | Train Epoch: 8 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.23374 (0.24871) Boundary_loss: 0.013901 (0.013904) Loss: 0.24764 (0.26261) +2025-09-14,08:49:37 | INFO | Train Epoch: 8 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.32916 (0.24899) Boundary_loss: 0.013901 (0.013904) Loss: 0.34306 (0.26290) +2025-09-14,08:50:43 | INFO | Train Epoch: 8 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.36362 (0.24940) Boundary_loss: 0.013905 (0.013904) Loss: 0.37752 (0.26331) +2025-09-14,08:51:49 | INFO | Train Epoch: 8 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22413 (0.24931) Boundary_loss: 0.013904 (0.013904) Loss: 0.23804 (0.26322) +2025-09-14,08:52:55 | INFO | Train Epoch: 8 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.25363 (0.24933) Boundary_loss: 0.013901 (0.013904) Loss: 0.26753 (0.26323) +2025-09-14,08:54:01 | INFO | Train Epoch: 8 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22634 (0.24925) Boundary_loss: 0.013902 (0.013904) Loss: 0.24024 (0.26315) +2025-09-14,08:55:07 | INFO | Train Epoch: 8 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.30634 (0.24945) Boundary_loss: 0.013903 (0.013904) Loss: 0.32025 (0.26335) +2025-09-14,08:56:13 | INFO | Train Epoch: 8 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.19576 (0.24926) Boundary_loss: 0.013902 (0.013904) Loss: 0.20966 (0.26316) +2025-09-14,08:57:19 | INFO | Train Epoch: 8 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.27886 (0.24936) Boundary_loss: 0.013899 (0.013904) Loss: 0.29275 (0.26327) +2025-09-14,08:58:25 | INFO | Train Epoch: 8 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.26150 (0.24941) Boundary_loss: 0.013901 (0.013904) Loss: 0.27540 (0.26331) +2025-09-14,08:59:31 | INFO | Train Epoch: 8 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.24098 (0.24938) Boundary_loss: 0.013903 (0.013904) Loss: 0.25488 (0.26328) +2025-09-14,09:00:38 | INFO | Train Epoch: 8 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.21592 (0.24926) Boundary_loss: 0.013904 (0.013904) Loss: 0.22983 (0.26317) +2025-09-14,09:01:44 | INFO | Train Epoch: 8 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.27901 (0.24936) Boundary_loss: 0.013902 (0.013904) Loss: 0.29291 (0.26327) +2025-09-14,09:02:50 | INFO | Train Epoch: 8 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.25456 (0.24938) Boundary_loss: 0.013900 (0.013904) Loss: 0.26846 (0.26329) +2025-09-14,09:03:56 | INFO | Train Epoch: 8 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.23393 (0.24933) Boundary_loss: 0.013901 (0.013904) Loss: 0.24784 (0.26323) +2025-09-14,09:05:02 | INFO | Train Epoch: 8 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.25064 (0.24933) Boundary_loss: 0.013899 (0.013904) Loss: 0.26454 (0.26324) +2025-09-14,09:06:08 | INFO | Train Epoch: 8 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.23996 (0.24930) Boundary_loss: 0.013904 (0.013904) Loss: 0.25387 (0.26321) +2025-09-14,09:07:14 | INFO | Train Epoch: 8 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.25370 (0.24932) Boundary_loss: 0.013903 (0.013904) Loss: 0.26760 (0.26322) +2025-09-14,09:08:20 | INFO | Train Epoch: 8 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.18037 (0.24908) Boundary_loss: 0.013902 (0.013904) Loss: 0.19427 (0.26299) +2025-09-14,09:09:26 | INFO | Train Epoch: 8 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.27842 (0.24918) Boundary_loss: 0.013901 (0.013904) Loss: 0.29232 (0.26309) +2025-09-14,09:10:32 | INFO | Train Epoch: 8 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22891 (0.24911) Boundary_loss: 0.013901 (0.013904) Loss: 0.24281 (0.26302) +2025-09-14,09:11:38 | INFO | Train Epoch: 8 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.28362 (0.24923) Boundary_loss: 0.013900 (0.013904) Loss: 0.29752 (0.26313) +2025-09-14,09:12:44 | INFO | Train Epoch: 8 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.24542 (0.24922) Boundary_loss: 0.013901 (0.013904) Loss: 0.25932 (0.26312) +2025-09-14,09:13:50 | INFO | Train Epoch: 8 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.29040 (0.24935) Boundary_loss: 0.013901 (0.013904) Loss: 0.30430 (0.26326) +2025-09-14,09:14:57 | INFO | Train Epoch: 8 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.25039 (0.24936) Boundary_loss: 0.013897 (0.013904) Loss: 0.26429 (0.26326) +2025-09-14,09:16:03 | INFO | Train Epoch: 8 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.32442 (0.24960) Boundary_loss: 0.013898 (0.013904) Loss: 0.33831 (0.26351) +2025-09-14,09:17:09 | INFO | Train Epoch: 8 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.19064 (0.24941) Boundary_loss: 0.013901 (0.013904) Loss: 0.20454 (0.26331) +2025-09-14,09:18:15 | INFO | Train Epoch: 8 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.22289 (0.24932) Boundary_loss: 0.013902 (0.013904) Loss: 0.23679 (0.26323) +2025-09-14,09:19:21 | INFO | Train Epoch: 8 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.21174 (0.24920) Boundary_loss: 0.013902 (0.013904) Loss: 0.22564 (0.26310) +2025-09-14,09:20:27 | INFO | Train Epoch: 8 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.28549 (0.24932) Boundary_loss: 0.013899 (0.013904) Loss: 0.29939 (0.26322) +2025-09-14,09:21:33 | INFO | Train Epoch: 8 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.19294 (0.24914) Boundary_loss: 0.013909 (0.013904) Loss: 0.20685 (0.26304) +2025-09-14,09:22:39 | INFO | Train Epoch: 8 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.23554 (0.24909) Boundary_loss: 0.013900 (0.013904) Loss: 0.24944 (0.26300) +2025-09-14,09:23:45 | INFO | Train Epoch: 8 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.17997 (0.24887) Boundary_loss: 0.013904 (0.013904) Loss: 0.19387 (0.26277) +2025-09-14,09:24:51 | INFO | Train Epoch: 8 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17614 (0.24864) Boundary_loss: 0.013902 (0.013904) Loss: 0.19005 (0.26254) +2025-09-14,09:25:57 | INFO | Train Epoch: 8 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.28333 (0.24875) Boundary_loss: 0.013909 (0.013904) Loss: 0.29724 (0.26265) +2025-09-14,09:27:03 | INFO | Train Epoch: 8 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.20024 (0.24859) Boundary_loss: 0.013903 (0.013904) Loss: 0.21415 (0.26250) +2025-09-14,09:28:09 | INFO | Train Epoch: 8 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.23134 (0.24854) Boundary_loss: 0.013902 (0.013904) Loss: 0.24524 (0.26244) +2025-09-14,09:29:15 | INFO | Train Epoch: 8 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.26581 (0.24859) Boundary_loss: 0.013905 (0.013904) Loss: 0.27972 (0.26250) +2025-09-14,09:30:21 | INFO | Train Epoch: 8 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.24994 (0.24860) Boundary_loss: 0.013905 (0.013904) Loss: 0.26384 (0.26250) +2025-09-14,09:31:28 | INFO | Train Epoch: 8 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.22558 (0.24852) Boundary_loss: 0.013900 (0.013904) Loss: 0.23948 (0.26243) +2025-09-14,09:32:34 | INFO | Train Epoch: 8 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.26820 (0.24859) Boundary_loss: 0.013899 (0.013904) Loss: 0.28209 (0.26249) +2025-09-14,09:33:40 | INFO | Train Epoch: 8 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20304 (0.24844) Boundary_loss: 0.013901 (0.013904) Loss: 0.21695 (0.26235) +2025-09-14,09:34:46 | INFO | Train Epoch: 8 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19981 (0.24829) Boundary_loss: 0.013901 (0.013904) Loss: 0.21371 (0.26219) +2025-09-14,09:35:52 | INFO | Train Epoch: 8 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.20763 (0.24816) Boundary_loss: 0.013900 (0.013904) Loss: 0.22153 (0.26207) +2025-09-14,09:36:58 | INFO | Train Epoch: 8 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.25328 (0.24818) Boundary_loss: 0.013902 (0.013904) Loss: 0.26718 (0.26208) +2025-09-14,09:38:04 | INFO | Train Epoch: 8 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.23194 (0.24813) Boundary_loss: 0.013903 (0.013904) Loss: 0.24584 (0.26203) +2025-09-14,09:39:10 | INFO | Train Epoch: 8 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.19650 (0.24797) Boundary_loss: 0.013902 (0.013904) Loss: 0.21040 (0.26187) +2025-09-14,09:40:16 | INFO | Train Epoch: 8 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.17969 (0.24776) Boundary_loss: 0.013903 (0.013904) Loss: 0.19359 (0.26166) +2025-09-14,09:41:22 | INFO | Train Epoch: 8 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.21685 (0.24767) Boundary_loss: 0.013899 (0.013904) Loss: 0.23075 (0.26157) +2025-09-14,09:42:28 | INFO | Train Epoch: 8 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.26370 (0.24771) Boundary_loss: 0.013903 (0.013904) Loss: 0.27760 (0.26162) +2025-09-14,09:43:34 | INFO | Train Epoch: 8 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30134 (0.24788) Boundary_loss: 0.013900 (0.013904) Loss: 0.31524 (0.26178) +2025-09-14,09:44:40 | INFO | Train Epoch: 8 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.25240 (0.24789) Boundary_loss: 0.013903 (0.013904) Loss: 0.26630 (0.26179) +2025-09-14,09:45:46 | INFO | Train Epoch: 8 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.23658 (0.24786) Boundary_loss: 0.013902 (0.013904) Loss: 0.25048 (0.26176) +2025-09-14,09:46:52 | INFO | Train Epoch: 8 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.26572 (0.24791) Boundary_loss: 0.013903 (0.013904) Loss: 0.27963 (0.26181) +2025-09-14,09:47:58 | INFO | Train Epoch: 8 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.26015 (0.24795) Boundary_loss: 0.013907 (0.013904) Loss: 0.27406 (0.26185) +2025-09-14,09:49:05 | INFO | Train Epoch: 8 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.24326 (0.24793) Boundary_loss: 0.013902 (0.013904) Loss: 0.25716 (0.26184) +2025-09-14,09:50:11 | INFO | Train Epoch: 8 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.21782 (0.24784) Boundary_loss: 0.013907 (0.013904) Loss: 0.23173 (0.26175) +2025-09-14,09:51:17 | INFO | Train Epoch: 8 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.35407 (0.24816) Boundary_loss: 0.013901 (0.013904) Loss: 0.36797 (0.26206) +2025-09-14,09:52:23 | INFO | Train Epoch: 8 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.22604 (0.24809) Boundary_loss: 0.013902 (0.013904) Loss: 0.23994 (0.26200) +2025-09-14,09:53:29 | INFO | Train Epoch: 8 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.24216 (0.24808) Boundary_loss: 0.013902 (0.013904) Loss: 0.25606 (0.26198) +2025-09-14,09:54:35 | INFO | Train Epoch: 8 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.22306 (0.24800) Boundary_loss: 0.013901 (0.013904) Loss: 0.23697 (0.26191) +2025-09-14,09:55:41 | INFO | Train Epoch: 8 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.24890 (0.24801) Boundary_loss: 0.013898 (0.013904) Loss: 0.26279 (0.26191) +2025-09-14,09:56:47 | INFO | Train Epoch: 8 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.19319 (0.24784) Boundary_loss: 0.013900 (0.013903) Loss: 0.20709 (0.26175) +2025-09-14,09:57:53 | INFO | Train Epoch: 8 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.25741 (0.24787) Boundary_loss: 0.013900 (0.013903) Loss: 0.27131 (0.26178) +2025-09-14,09:58:59 | INFO | Train Epoch: 8 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.23764 (0.24784) Boundary_loss: 0.013905 (0.013903) Loss: 0.25154 (0.26175) +2025-09-14,10:00:05 | INFO | Train Epoch: 8 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.20429 (0.24772) Boundary_loss: 0.013904 (0.013903) Loss: 0.21819 (0.26162) +2025-09-14,10:01:12 | INFO | Train Epoch: 8 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.24286 (0.24770) Boundary_loss: 0.013902 (0.013903) Loss: 0.25676 (0.26161) +2025-09-14,10:02:18 | INFO | Train Epoch: 8 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.19441 (0.24755) Boundary_loss: 0.013900 (0.013903) Loss: 0.20831 (0.26145) +2025-09-14,10:03:24 | INFO | Train Epoch: 8 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.29714 (0.24769) Boundary_loss: 0.013900 (0.013903) Loss: 0.31104 (0.26159) +2025-09-14,10:04:30 | INFO | Train Epoch: 8 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.25501 (0.24771) Boundary_loss: 0.013906 (0.013903) Loss: 0.26892 (0.26162) +2025-09-14,10:05:36 | INFO | Train Epoch: 8 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.26043 (0.24775) Boundary_loss: 0.013904 (0.013903) Loss: 0.27433 (0.26165) +2025-09-14,10:06:42 | INFO | Train Epoch: 8 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.18562 (0.24757) Boundary_loss: 0.013900 (0.013903) Loss: 0.19952 (0.26147) +2025-09-14,10:07:48 | INFO | Train Epoch: 8 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.19191 (0.24741) Boundary_loss: 0.013902 (0.013903) Loss: 0.20581 (0.26131) +2025-09-14,10:08:54 | INFO | Train Epoch: 8 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.24885 (0.24742) Boundary_loss: 0.013902 (0.013903) Loss: 0.26275 (0.26132) +2025-09-14,10:10:00 | INFO | Train Epoch: 8 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.25952 (0.24745) Boundary_loss: 0.013898 (0.013903) Loss: 0.27342 (0.26135) +2025-09-14,10:11:06 | INFO | Train Epoch: 8 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.19254 (0.24729) Boundary_loss: 0.013900 (0.013903) Loss: 0.20644 (0.26120) +2025-09-14,10:12:12 | INFO | Train Epoch: 8 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.22017 (0.24722) Boundary_loss: 0.013903 (0.013903) Loss: 0.23407 (0.26112) +2025-09-14,10:13:19 | INFO | Train Epoch: 8 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.27475 (0.24730) Boundary_loss: 0.013902 (0.013903) Loss: 0.28865 (0.26120) +2025-09-14,10:14:25 | INFO | Train Epoch: 8 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.23399 (0.24726) Boundary_loss: 0.013902 (0.013903) Loss: 0.24790 (0.26116) +2025-09-14,10:15:31 | INFO | Train Epoch: 8 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.22942 (0.24721) Boundary_loss: 0.013900 (0.013903) Loss: 0.24332 (0.26111) +2025-09-14,10:16:37 | INFO | Train Epoch: 8 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.24585 (0.24720) Boundary_loss: 0.013901 (0.013903) Loss: 0.25975 (0.26111) +2025-09-14,10:17:43 | INFO | Train Epoch: 8 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.22913 (0.24715) Boundary_loss: 0.013901 (0.013903) Loss: 0.24303 (0.26106) +2025-09-14,10:18:49 | INFO | Train Epoch: 8 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.31776 (0.24735) Boundary_loss: 0.013904 (0.013903) Loss: 0.33167 (0.26125) +2025-09-14,10:19:55 | INFO | Train Epoch: 8 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.25008 (0.24736) Boundary_loss: 0.013903 (0.013903) Loss: 0.26398 (0.26126) +2025-09-14,10:21:01 | INFO | Train Epoch: 8 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23510 (0.24732) Boundary_loss: 0.013901 (0.013903) Loss: 0.24900 (0.26123) +2025-09-14,10:22:07 | INFO | Train Epoch: 8 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.26854 (0.24738) Boundary_loss: 0.013900 (0.013903) Loss: 0.28244 (0.26129) +2025-09-14,10:23:13 | INFO | Train Epoch: 8 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.20921 (0.24728) Boundary_loss: 0.013899 (0.013903) Loss: 0.22311 (0.26118) +2025-09-14,10:24:19 | INFO | Train Epoch: 8 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.23241 (0.24724) Boundary_loss: 0.013901 (0.013903) Loss: 0.24631 (0.26114) +2025-09-14,10:25:25 | INFO | Train Epoch: 8 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.26269 (0.24728) Boundary_loss: 0.013906 (0.013903) Loss: 0.27660 (0.26118) +2025-09-14,10:26:31 | INFO | Train Epoch: 8 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.26560 (0.24733) Boundary_loss: 0.013904 (0.013903) Loss: 0.27951 (0.26123) +2025-09-14,10:27:37 | INFO | Train Epoch: 8 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.28737 (0.24744) Boundary_loss: 0.013907 (0.013903) Loss: 0.30128 (0.26134) +2025-09-14,10:28:43 | INFO | Train Epoch: 8 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.34138 (0.24769) Boundary_loss: 0.013902 (0.013903) Loss: 0.35528 (0.26160) +2025-09-14,10:29:49 | INFO | Train Epoch: 8 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26639 (0.24774) Boundary_loss: 0.013900 (0.013903) Loss: 0.28029 (0.26165) +2025-09-14,10:30:55 | INFO | Train Epoch: 8 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.21851 (0.24766) Boundary_loss: 0.013903 (0.013903) Loss: 0.23241 (0.26157) +2025-09-14,10:32:02 | INFO | Train Epoch: 8 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.22595 (0.24761) Boundary_loss: 0.013904 (0.013903) Loss: 0.23985 (0.26151) +2025-09-14,10:33:08 | INFO | Train Epoch: 8 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.24657 (0.24760) Boundary_loss: 0.013903 (0.013903) Loss: 0.26047 (0.26151) +2025-09-14,10:34:14 | INFO | Train Epoch: 8 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.29207 (0.24772) Boundary_loss: 0.013904 (0.013903) Loss: 0.30597 (0.26162) +2025-09-14,10:35:20 | INFO | Train Epoch: 8 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.25782 (0.24775) Boundary_loss: 0.013902 (0.013903) Loss: 0.27172 (0.26165) +2025-09-14,10:36:26 | INFO | Train Epoch: 8 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.20850 (0.24764) Boundary_loss: 0.013901 (0.013903) Loss: 0.22240 (0.26155) +2025-09-14,10:37:32 | INFO | Train Epoch: 8 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.22917 (0.24759) Boundary_loss: 0.013901 (0.013903) Loss: 0.24307 (0.26150) +2025-09-14,10:38:38 | INFO | Train Epoch: 8 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.18009 (0.24742) Boundary_loss: 0.013899 (0.013903) Loss: 0.19399 (0.26132) +2025-09-14,10:39:44 | INFO | Train Epoch: 8 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.27588 (0.24749) Boundary_loss: 0.013903 (0.013903) Loss: 0.28979 (0.26139) +2025-09-14,10:40:51 | INFO | Train Epoch: 8 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.20875 (0.24739) Boundary_loss: 0.013902 (0.013903) Loss: 0.22265 (0.26129) +2025-09-14,10:41:57 | INFO | Train Epoch: 8 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.25110 (0.24740) Boundary_loss: 0.013903 (0.013903) Loss: 0.26500 (0.26130) +2025-09-14,10:43:03 | INFO | Train Epoch: 8 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.22786 (0.24735) Boundary_loss: 0.013902 (0.013903) Loss: 0.24176 (0.26125) +2025-09-14,10:44:09 | INFO | Train Epoch: 8 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.22294 (0.24728) Boundary_loss: 0.013906 (0.013903) Loss: 0.23685 (0.26119) +2025-09-14,10:45:15 | INFO | Train Epoch: 8 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.21892 (0.24721) Boundary_loss: 0.013904 (0.013903) Loss: 0.23283 (0.26111) +2025-09-14,10:46:21 | INFO | Train Epoch: 8 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.21436 (0.24713) Boundary_loss: 0.013900 (0.013903) Loss: 0.22826 (0.26103) +2025-09-14,10:47:27 | INFO | Train Epoch: 8 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.33183 (0.24734) Boundary_loss: 0.013900 (0.013903) Loss: 0.34573 (0.26125) +2025-09-14,10:48:33 | INFO | Train Epoch: 8 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.23335 (0.24731) Boundary_loss: 0.013902 (0.013903) Loss: 0.24725 (0.26121) +2025-09-14,10:49:39 | INFO | Train Epoch: 8 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.22680 (0.24726) Boundary_loss: 0.013900 (0.013903) Loss: 0.24070 (0.26116) +2025-09-14,10:50:45 | INFO | Train Epoch: 8 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.23607 (0.24723) Boundary_loss: 0.013900 (0.013903) Loss: 0.24997 (0.26113) +2025-09-14,10:51:51 | INFO | Train Epoch: 8 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.27339 (0.24729) Boundary_loss: 0.013900 (0.013903) Loss: 0.28729 (0.26120) +2025-09-14,10:52:58 | INFO | Train Epoch: 8 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.19858 (0.24717) Boundary_loss: 0.013908 (0.013903) Loss: 0.21249 (0.26107) +2025-09-14,10:54:04 | INFO | Train Epoch: 8 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.22360 (0.24711) Boundary_loss: 0.013903 (0.013903) Loss: 0.23750 (0.26101) +2025-09-14,10:55:10 | INFO | Train Epoch: 8 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.30806 (0.24726) Boundary_loss: 0.013901 (0.013903) Loss: 0.32196 (0.26117) +2025-09-14,10:56:16 | INFO | Train Epoch: 8 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.34717 (0.24752) Boundary_loss: 0.013902 (0.013903) Loss: 0.36107 (0.26142) +2025-09-14,10:57:22 | INFO | Train Epoch: 8 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.25029 (0.24752) Boundary_loss: 0.013899 (0.013903) Loss: 0.26418 (0.26143) +2025-09-14,10:58:28 | INFO | Train Epoch: 8 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.26304 (0.24756) Boundary_loss: 0.013900 (0.013903) Loss: 0.27694 (0.26147) +2025-09-14,10:59:34 | INFO | Train Epoch: 8 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.24464 (0.24756) Boundary_loss: 0.013904 (0.013903) Loss: 0.25855 (0.26146) +2025-09-14,11:00:40 | INFO | Train Epoch: 8 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.23528 (0.24753) Boundary_loss: 0.013901 (0.013903) Loss: 0.24918 (0.26143) +2025-09-14,11:01:46 | INFO | Train Epoch: 8 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.24045 (0.24751) Boundary_loss: 0.013902 (0.013903) Loss: 0.25435 (0.26141) +2025-09-14,11:02:52 | INFO | Train Epoch: 8 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.26863 (0.24756) Boundary_loss: 0.013902 (0.013903) Loss: 0.28253 (0.26146) +2025-09-14,11:03:59 | INFO | Train Epoch: 8 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20023 (0.24744) Boundary_loss: 0.013906 (0.013903) Loss: 0.21414 (0.26135) +2025-09-14,11:05:05 | INFO | Train Epoch: 8 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.27037 (0.24750) Boundary_loss: 0.013906 (0.013903) Loss: 0.28427 (0.26140) +2025-09-14,11:06:11 | INFO | Train Epoch: 8 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.25899 (0.24753) Boundary_loss: 0.013900 (0.013903) Loss: 0.27289 (0.26143) +2025-09-14,11:07:17 | INFO | Train Epoch: 8 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.29849 (0.24765) Boundary_loss: 0.013903 (0.013903) Loss: 0.31239 (0.26156) +2025-09-14,11:08:23 | INFO | Train Epoch: 8 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.26127 (0.24769) Boundary_loss: 0.013902 (0.013903) Loss: 0.27517 (0.26159) +2025-09-14,11:09:29 | INFO | Train Epoch: 8 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.24231 (0.24767) Boundary_loss: 0.013900 (0.013903) Loss: 0.25621 (0.26158) +2025-09-14,11:10:35 | INFO | Train Epoch: 8 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.33680 (0.24789) Boundary_loss: 0.013901 (0.013903) Loss: 0.35070 (0.26180) +2025-09-14,11:11:41 | INFO | Train Epoch: 8 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.23027 (0.24785) Boundary_loss: 0.013900 (0.013903) Loss: 0.24417 (0.26175) +2025-09-14,11:12:47 | INFO | Train Epoch: 8 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.23016 (0.24781) Boundary_loss: 0.013901 (0.013903) Loss: 0.24406 (0.26171) +2025-09-14,11:13:53 | INFO | Train Epoch: 8 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.21579 (0.24773) Boundary_loss: 0.013902 (0.013903) Loss: 0.22969 (0.26163) +2025-09-14,11:14:59 | INFO | Train Epoch: 8 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.14926 (0.24749) Boundary_loss: 0.013900 (0.013903) Loss: 0.16316 (0.26139) +2025-09-14,11:16:05 | INFO | Train Epoch: 8 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.29249 (0.24760) Boundary_loss: 0.013905 (0.013903) Loss: 0.30639 (0.26150) +2025-09-14,11:17:11 | INFO | Train Epoch: 8 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.22763 (0.24755) Boundary_loss: 0.013904 (0.013903) Loss: 0.24153 (0.26145) +2025-09-14,11:18:17 | INFO | Train Epoch: 8 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.23433 (0.24752) Boundary_loss: 0.013903 (0.013903) Loss: 0.24823 (0.26142) +2025-09-14,11:19:23 | INFO | Train Epoch: 8 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.25887 (0.24755) Boundary_loss: 0.013906 (0.013903) Loss: 0.27278 (0.26145) +2025-09-14,11:20:29 | INFO | Train Epoch: 8 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.24502 (0.24754) Boundary_loss: 0.013900 (0.013903) Loss: 0.25892 (0.26144) +2025-09-14,11:21:35 | INFO | Train Epoch: 8 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.26206 (0.24757) Boundary_loss: 0.013905 (0.013903) Loss: 0.27597 (0.26148) +2025-09-14,11:22:41 | INFO | Train Epoch: 8 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.22531 (0.24752) Boundary_loss: 0.013899 (0.013903) Loss: 0.23921 (0.26142) +2025-09-14,11:23:47 | INFO | Train Epoch: 8 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.27016 (0.24758) Boundary_loss: 0.013898 (0.013903) Loss: 0.28406 (0.26148) +2025-09-14,11:24:54 | INFO | Train Epoch: 8 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.23595 (0.24755) Boundary_loss: 0.013899 (0.013903) Loss: 0.24985 (0.26145) +2025-09-14,11:26:00 | INFO | Train Epoch: 8 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.28891 (0.24765) Boundary_loss: 0.013899 (0.013903) Loss: 0.30281 (0.26155) +2025-09-14,11:27:06 | INFO | Train Epoch: 8 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.20333 (0.24754) Boundary_loss: 0.013903 (0.013903) Loss: 0.21723 (0.26144) +2025-09-14,11:28:12 | INFO | Train Epoch: 8 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.27352 (0.24760) Boundary_loss: 0.013910 (0.013903) Loss: 0.28743 (0.26151) +2025-09-14,11:29:18 | INFO | Train Epoch: 8 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.20844 (0.24751) Boundary_loss: 0.013906 (0.013903) Loss: 0.22235 (0.26141) +2025-09-14,11:30:24 | INFO | Train Epoch: 8 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18910 (0.24737) Boundary_loss: 0.013902 (0.013903) Loss: 0.20300 (0.26128) +2025-09-14,11:31:30 | INFO | Train Epoch: 8 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.28596 (0.24746) Boundary_loss: 0.013903 (0.013903) Loss: 0.29986 (0.26137) +2025-09-14,11:32:36 | INFO | Train Epoch: 8 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.25331 (0.24748) Boundary_loss: 0.013904 (0.013903) Loss: 0.26721 (0.26138) +2025-09-14,11:33:42 | INFO | Train Epoch: 8 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.24567 (0.24747) Boundary_loss: 0.013901 (0.013903) Loss: 0.25957 (0.26138) +2025-09-14,11:34:48 | INFO | Train Epoch: 8 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.21571 (0.24740) Boundary_loss: 0.013901 (0.013903) Loss: 0.22961 (0.26130) +2025-09-14,11:35:54 | INFO | Train Epoch: 8 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.21271 (0.24732) Boundary_loss: 0.013902 (0.013903) Loss: 0.22661 (0.26122) +2025-09-14,11:37:00 | INFO | Train Epoch: 8 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.26527 (0.24736) Boundary_loss: 0.013904 (0.013903) Loss: 0.27918 (0.26126) +2025-09-14,11:38:06 | INFO | Train Epoch: 8 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.25186 (0.24737) Boundary_loss: 0.013903 (0.013903) Loss: 0.26576 (0.26127) +2025-09-14,11:39:12 | INFO | Train Epoch: 8 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.19470 (0.24725) Boundary_loss: 0.013902 (0.013903) Loss: 0.20861 (0.26115) +2025-09-14,11:40:18 | INFO | Train Epoch: 8 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24830 (0.24725) Boundary_loss: 0.013902 (0.013903) Loss: 0.26220 (0.26115) +2025-09-14,11:41:24 | INFO | Train Epoch: 8 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.26965 (0.24730) Boundary_loss: 0.013901 (0.013903) Loss: 0.28355 (0.26121) +2025-09-14,11:42:30 | INFO | Train Epoch: 8 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.25792 (0.24733) Boundary_loss: 0.013901 (0.013903) Loss: 0.27182 (0.26123) +2025-09-14,11:43:36 | INFO | Train Epoch: 8 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.28193 (0.24741) Boundary_loss: 0.013903 (0.013903) Loss: 0.29584 (0.26131) +2025-09-14,11:44:42 | INFO | Train Epoch: 8 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.25077 (0.24741) Boundary_loss: 0.013901 (0.013903) Loss: 0.26467 (0.26132) +2025-09-14,11:45:48 | INFO | Train Epoch: 8 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24554 (0.24741) Boundary_loss: 0.013901 (0.013903) Loss: 0.25944 (0.26131) +2025-09-14,11:46:54 | INFO | Train Epoch: 8 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.29905 (0.24753) Boundary_loss: 0.013901 (0.013903) Loss: 0.31295 (0.26143) +2025-09-14,11:48:00 | INFO | Train Epoch: 8 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.25260 (0.24754) Boundary_loss: 0.013904 (0.013903) Loss: 0.26651 (0.26144) +2025-09-14,11:49:06 | INFO | Train Epoch: 8 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.27169 (0.24759) Boundary_loss: 0.013900 (0.013903) Loss: 0.28559 (0.26150) +2025-09-14,11:50:12 | INFO | Train Epoch: 8 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.24320 (0.24758) Boundary_loss: 0.013899 (0.013903) Loss: 0.25710 (0.26149) +2025-09-14,11:51:18 | INFO | Train Epoch: 8 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.22581 (0.24753) Boundary_loss: 0.013901 (0.013903) Loss: 0.23971 (0.26144) +2025-09-14,11:52:24 | INFO | Train Epoch: 8 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.25955 (0.24756) Boundary_loss: 0.013902 (0.013903) Loss: 0.27345 (0.26146) +2025-09-14,11:53:30 | INFO | Train Epoch: 8 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.27824 (0.24763) Boundary_loss: 0.013899 (0.013903) Loss: 0.29214 (0.26153) +2025-09-14,11:54:36 | INFO | Train Epoch: 8 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.28393 (0.24771) Boundary_loss: 0.013906 (0.013903) Loss: 0.29783 (0.26161) +2025-09-14,11:55:42 | INFO | Train Epoch: 8 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.26041 (0.24774) Boundary_loss: 0.013901 (0.013903) Loss: 0.27431 (0.26164) +2025-09-14,11:56:48 | INFO | Train Epoch: 8 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.28425 (0.24782) Boundary_loss: 0.013900 (0.013903) Loss: 0.29815 (0.26172) +2025-09-14,11:57:54 | INFO | Train Epoch: 8 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.18506 (0.24768) Boundary_loss: 0.013901 (0.013903) Loss: 0.19896 (0.26158) +2025-09-14,11:59:00 | INFO | Train Epoch: 8 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.26897 (0.24773) Boundary_loss: 0.013903 (0.013903) Loss: 0.28287 (0.26163) +2025-09-14,12:00:06 | INFO | Train Epoch: 8 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.27487 (0.24779) Boundary_loss: 0.013899 (0.013903) Loss: 0.28877 (0.26169) +2025-09-14,12:01:12 | INFO | Train Epoch: 8 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.18219 (0.24764) Boundary_loss: 0.013901 (0.013903) Loss: 0.19609 (0.26155) +2025-09-14,12:02:18 | INFO | Train Epoch: 8 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.25968 (0.24767) Boundary_loss: 0.013902 (0.013903) Loss: 0.27358 (0.26157) +2025-09-14,12:03:24 | INFO | Train Epoch: 8 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.22001 (0.24761) Boundary_loss: 0.013904 (0.013903) Loss: 0.23391 (0.26151) +2025-09-14,12:04:30 | INFO | Train Epoch: 8 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26742 (0.24765) Boundary_loss: 0.013901 (0.013903) Loss: 0.28132 (0.26156) +2025-09-14,12:05:36 | INFO | Train Epoch: 8 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.16954 (0.24748) Boundary_loss: 0.013901 (0.013903) Loss: 0.18344 (0.26138) +2025-09-14,12:06:42 | INFO | Train Epoch: 8 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.18358 (0.24734) Boundary_loss: 0.013904 (0.013903) Loss: 0.19748 (0.26125) +2025-09-14,12:07:48 | INFO | Train Epoch: 8 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.23238 (0.24731) Boundary_loss: 0.013907 (0.013903) Loss: 0.24629 (0.26121) +2025-09-14,12:08:54 | INFO | Train Epoch: 8 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.27783 (0.24738) Boundary_loss: 0.013903 (0.013903) Loss: 0.29174 (0.26128) +2025-09-14,12:10:00 | INFO | Train Epoch: 8 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.29787 (0.24749) Boundary_loss: 0.013904 (0.013903) Loss: 0.31177 (0.26139) +2025-09-14,12:11:06 | INFO | Train Epoch: 8 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.19961 (0.24738) Boundary_loss: 0.013897 (0.013903) Loss: 0.21351 (0.26128) +2025-09-14,12:12:12 | INFO | Train Epoch: 8 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.27107 (0.24743) Boundary_loss: 0.013901 (0.013903) Loss: 0.28497 (0.26134) +2025-09-14,12:13:18 | INFO | Train Epoch: 8 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.23477 (0.24741) Boundary_loss: 0.013902 (0.013903) Loss: 0.24867 (0.26131) +2025-09-14,12:14:24 | INFO | Train Epoch: 8 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.21937 (0.24735) Boundary_loss: 0.013897 (0.013903) Loss: 0.23327 (0.26125) +2025-09-14,12:15:30 | INFO | Train Epoch: 8 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.25656 (0.24737) Boundary_loss: 0.013902 (0.013903) Loss: 0.27046 (0.26127) +2025-09-14,12:16:36 | INFO | Train Epoch: 8 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.30154 (0.24748) Boundary_loss: 0.013905 (0.013903) Loss: 0.31545 (0.26138) +2025-09-14,12:17:42 | INFO | Train Epoch: 8 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.24556 (0.24748) Boundary_loss: 0.013900 (0.013903) Loss: 0.25946 (0.26138) +2025-09-14,12:18:48 | INFO | Train Epoch: 8 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.22162 (0.24742) Boundary_loss: 0.013898 (0.013903) Loss: 0.23552 (0.26132) +2025-09-14,12:19:54 | INFO | Train Epoch: 8 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.27401 (0.24748) Boundary_loss: 0.013899 (0.013903) Loss: 0.28791 (0.26138) +2025-09-14,12:21:00 | INFO | Train Epoch: 8 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.23965 (0.24746) Boundary_loss: 0.013899 (0.013903) Loss: 0.25355 (0.26136) +2025-09-14,12:22:06 | INFO | Train Epoch: 8 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25781 (0.24748) Boundary_loss: 0.013902 (0.013903) Loss: 0.27171 (0.26139) +2025-09-14,12:23:12 | INFO | Train Epoch: 8 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.26228 (0.24752) Boundary_loss: 0.013900 (0.013903) Loss: 0.27618 (0.26142) +2025-09-14,12:24:18 | INFO | Train Epoch: 8 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.24425 (0.24751) Boundary_loss: 0.013900 (0.013903) Loss: 0.25815 (0.26141) +2025-09-14,12:25:24 | INFO | Train Epoch: 8 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.26781 (0.24755) Boundary_loss: 0.013901 (0.013903) Loss: 0.28171 (0.26145) +2025-09-14,12:26:30 | INFO | Train Epoch: 8 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.25480 (0.24757) Boundary_loss: 0.013909 (0.013903) Loss: 0.26871 (0.26147) +2025-09-14,12:27:36 | INFO | Train Epoch: 8 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.22546 (0.24752) Boundary_loss: 0.013899 (0.013903) Loss: 0.23936 (0.26142) +2025-09-14,12:28:42 | INFO | Train Epoch: 8 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.22356 (0.24747) Boundary_loss: 0.013900 (0.013903) Loss: 0.23745 (0.26137) +2025-09-14,12:29:48 | INFO | Train Epoch: 8 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.21750 (0.24741) Boundary_loss: 0.013901 (0.013903) Loss: 0.23140 (0.26131) +2025-09-14,12:30:54 | INFO | Train Epoch: 8 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.22691 (0.24736) Boundary_loss: 0.013903 (0.013903) Loss: 0.24081 (0.26127) +2025-09-14,12:32:00 | INFO | Train Epoch: 8 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.23701 (0.24734) Boundary_loss: 0.013904 (0.013903) Loss: 0.25092 (0.26125) +2025-09-14,12:33:06 | INFO | Train Epoch: 8 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.25097 (0.24735) Boundary_loss: 0.013903 (0.013903) Loss: 0.26488 (0.26125) +2025-09-14,12:34:11 | INFO | Train Epoch: 8 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.25649 (0.24737) Boundary_loss: 0.013901 (0.013903) Loss: 0.27039 (0.26127) +2025-09-14,12:35:17 | INFO | Train Epoch: 8 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.27021 (0.24742) Boundary_loss: 0.013900 (0.013903) Loss: 0.28411 (0.26132) +2025-09-14,12:36:23 | INFO | Train Epoch: 8 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.23198 (0.24738) Boundary_loss: 0.013900 (0.013903) Loss: 0.24588 (0.26129) +2025-09-14,12:37:29 | INFO | Train Epoch: 8 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.28527 (0.24746) Boundary_loss: 0.013902 (0.013903) Loss: 0.29917 (0.26137) +2025-09-14,12:38:35 | INFO | Train Epoch: 8 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27500 (0.24752) Boundary_loss: 0.013904 (0.013903) Loss: 0.28890 (0.26142) +2025-09-14,12:39:41 | INFO | Train Epoch: 8 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24442 (0.24751) Boundary_loss: 0.013903 (0.013903) Loss: 0.25832 (0.26142) +2025-09-14,12:40:47 | INFO | Train Epoch: 8 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.18651 (0.24739) Boundary_loss: 0.013899 (0.013903) Loss: 0.20041 (0.26129) +2025-09-14,12:41:53 | INFO | Train Epoch: 8 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.29479 (0.24748) Boundary_loss: 0.013899 (0.013903) Loss: 0.30869 (0.26139) +2025-09-14,12:42:59 | INFO | Train Epoch: 8 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.30241 (0.24760) Boundary_loss: 0.013901 (0.013903) Loss: 0.31631 (0.26150) +2025-09-14,12:44:05 | INFO | Train Epoch: 8 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.30295 (0.24771) Boundary_loss: 0.013900 (0.013903) Loss: 0.31685 (0.26161) +2025-09-14,12:45:11 | INFO | Train Epoch: 8 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.21927 (0.24765) Boundary_loss: 0.013899 (0.013903) Loss: 0.23317 (0.26155) +2025-09-14,12:46:17 | INFO | Train Epoch: 8 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.20564 (0.24757) Boundary_loss: 0.013902 (0.013903) Loss: 0.21954 (0.26147) +2025-09-14,12:47:23 | INFO | Train Epoch: 8 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.22369 (0.24752) Boundary_loss: 0.013904 (0.013903) Loss: 0.23760 (0.26142) +2025-09-14,12:48:29 | INFO | Train Epoch: 8 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.26336 (0.24755) Boundary_loss: 0.013903 (0.013903) Loss: 0.27726 (0.26145) +2025-09-14,12:49:36 | INFO | Train Epoch: 8 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25568 (0.24757) Boundary_loss: 0.013903 (0.013903) Loss: 0.26959 (0.26147) +2025-09-14,12:50:41 | INFO | Train Epoch: 8 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.23281 (0.24754) Boundary_loss: 0.013899 (0.013903) Loss: 0.24671 (0.26144) +2025-09-14,12:51:47 | INFO | Train Epoch: 8 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.29160 (0.24763) Boundary_loss: 0.013900 (0.013903) Loss: 0.30550 (0.26153) +2025-09-14,12:52:53 | INFO | Train Epoch: 8 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.23191 (0.24759) Boundary_loss: 0.013904 (0.013903) Loss: 0.24582 (0.26150) +2025-09-14,12:53:59 | INFO | Train Epoch: 8 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23007 (0.24756) Boundary_loss: 0.013902 (0.013903) Loss: 0.24397 (0.26146) +2025-09-14,12:55:05 | INFO | Train Epoch: 8 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.22006 (0.24750) Boundary_loss: 0.013903 (0.013903) Loss: 0.23396 (0.26141) +2025-09-14,12:56:11 | INFO | Train Epoch: 8 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.16054 (0.24733) Boundary_loss: 0.013899 (0.013903) Loss: 0.17444 (0.26123) +2025-09-14,12:57:17 | INFO | Train Epoch: 8 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.22193 (0.24728) Boundary_loss: 0.013903 (0.013903) Loss: 0.23584 (0.26118) +2025-09-14,12:58:23 | INFO | Train Epoch: 8 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.28404 (0.24735) Boundary_loss: 0.013902 (0.013903) Loss: 0.29794 (0.26126) +2025-09-14,12:59:29 | INFO | Train Epoch: 8 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.25198 (0.24736) Boundary_loss: 0.013901 (0.013903) Loss: 0.26588 (0.26127) +2025-09-14,13:00:35 | INFO | Train Epoch: 8 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.28934 (0.24745) Boundary_loss: 0.013901 (0.013903) Loss: 0.30324 (0.26135) +2025-09-14,13:01:41 | INFO | Train Epoch: 8 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.24766 (0.24745) Boundary_loss: 0.013900 (0.013903) Loss: 0.26156 (0.26135) +2025-09-14,13:02:47 | INFO | Train Epoch: 8 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.26323 (0.24748) Boundary_loss: 0.013914 (0.013903) Loss: 0.27714 (0.26138) +2025-09-14,13:03:53 | INFO | Train Epoch: 8 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.22003 (0.24742) Boundary_loss: 0.013901 (0.013903) Loss: 0.23393 (0.26133) +2025-09-14,13:04:59 | INFO | Train Epoch: 8 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.22781 (0.24738) Boundary_loss: 0.013901 (0.013903) Loss: 0.24171 (0.26129) +2025-09-14,13:06:05 | INFO | Train Epoch: 8 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.19225 (0.24728) Boundary_loss: 0.013904 (0.013903) Loss: 0.20616 (0.26118) +2025-09-14,13:07:11 | INFO | Train Epoch: 8 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.25177 (0.24729) Boundary_loss: 0.013899 (0.013903) Loss: 0.26567 (0.26119) +2025-09-14,13:08:17 | INFO | Train Epoch: 8 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.22904 (0.24725) Boundary_loss: 0.013899 (0.013903) Loss: 0.24294 (0.26115) +2025-09-14,13:09:23 | INFO | Train Epoch: 8 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.22793 (0.24721) Boundary_loss: 0.013900 (0.013903) Loss: 0.24183 (0.26112) +2025-09-14,13:10:26 | INFO | Train Epoch: 8 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.21239 (0.24715) Boundary_loss: 0.013906 (0.013903) Loss: 0.22629 (0.26105) +2025-09-14,13:10:26 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,13:10:26 | INFO | [Epoch 8] Average Step Time: 0.663s | Average GPU Memory: 30.9 GB +2025-09-14,13:10:26 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,13:10:26 | INFO | Starting zero-shot imagenet. +2025-09-14,13:10:26 | INFO | Building zero-shot classifier +2025-09-14,13:10:36 | INFO | Using classifier +2025-09-14,13:11:18 | INFO | Finished zero-shot imagenet. +2025-09-14,13:11:18 | INFO | Eval Epoch: 9 imagenet-zeroshot-val-top1: 0.2932 imagenet-zeroshot-val-top5: 0.5575 +2025-09-14,13:11:19 | INFO | Start epoch 9 +2025-09-14,13:11:22 | INFO | Train Epoch: 9 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17091 (0.17091) Boundary_loss: 0.013901 (0.013901) Loss: 0.18481 (0.18481) +2025-09-14,13:12:27 | INFO | Train Epoch: 9 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.21011 (0.19051) Boundary_loss: 0.013903 (0.013902) Loss: 0.22401 (0.20441) +2025-09-14,13:13:33 | INFO | Train Epoch: 9 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.22884 (0.20329) Boundary_loss: 0.013899 (0.013901) Loss: 0.24273 (0.21719) +2025-09-14,13:14:39 | INFO | Train Epoch: 9 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.22792 (0.20944) Boundary_loss: 0.013901 (0.013901) Loss: 0.24182 (0.22335) +2025-09-14,13:15:45 | INFO | Train Epoch: 9 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18809 (0.20517) Boundary_loss: 0.013900 (0.013901) Loss: 0.20199 (0.21907) +2025-09-14,13:16:51 | INFO | Train Epoch: 9 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.26132 (0.21453) Boundary_loss: 0.013900 (0.013900) Loss: 0.27522 (0.22843) +2025-09-14,13:17:56 | INFO | Train Epoch: 9 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16259 (0.20711) Boundary_loss: 0.013900 (0.013900) Loss: 0.17649 (0.22101) +2025-09-14,13:19:02 | INFO | Train Epoch: 9 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.19184 (0.20520) Boundary_loss: 0.013902 (0.013901) Loss: 0.20574 (0.21910) +2025-09-14,13:20:08 | INFO | Train Epoch: 9 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22368 (0.20726) Boundary_loss: 0.013902 (0.013901) Loss: 0.23758 (0.22116) +2025-09-14,13:21:13 | INFO | Train Epoch: 9 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.18398 (0.20493) Boundary_loss: 0.013902 (0.013901) Loss: 0.19788 (0.21883) +2025-09-14,13:22:19 | INFO | Train Epoch: 9 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.19218 (0.20377) Boundary_loss: 0.013901 (0.013901) Loss: 0.20608 (0.21767) +2025-09-14,13:23:25 | INFO | Train Epoch: 9 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.25245 (0.20783) Boundary_loss: 0.013907 (0.013901) Loss: 0.26636 (0.22173) +2025-09-14,13:24:31 | INFO | Train Epoch: 9 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21108 (0.20808) Boundary_loss: 0.013902 (0.013901) Loss: 0.22498 (0.22198) +2025-09-14,13:25:37 | INFO | Train Epoch: 9 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.16982 (0.20534) Boundary_loss: 0.013904 (0.013902) Loss: 0.18372 (0.21924) +2025-09-14,13:26:42 | INFO | Train Epoch: 9 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.20659 (0.20543) Boundary_loss: 0.013899 (0.013901) Loss: 0.22048 (0.21933) +2025-09-14,13:27:48 | INFO | Train Epoch: 9 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17624 (0.20360) Boundary_loss: 0.013901 (0.013901) Loss: 0.19014 (0.21750) +2025-09-14,13:28:54 | INFO | Train Epoch: 9 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.16796 (0.20150) Boundary_loss: 0.013900 (0.013901) Loss: 0.18186 (0.21541) +2025-09-14,13:30:00 | INFO | Train Epoch: 9 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.23151 (0.20317) Boundary_loss: 0.013903 (0.013901) Loss: 0.24541 (0.21707) +2025-09-14,13:31:05 | INFO | Train Epoch: 9 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.21934 (0.20402) Boundary_loss: 0.013903 (0.013902) Loss: 0.23325 (0.21792) +2025-09-14,13:32:11 | INFO | Train Epoch: 9 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19162 (0.20340) Boundary_loss: 0.013904 (0.013902) Loss: 0.20552 (0.21730) +2025-09-14,13:33:17 | INFO | Train Epoch: 9 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.19525 (0.20301) Boundary_loss: 0.013900 (0.013902) Loss: 0.20915 (0.21692) +2025-09-14,13:34:23 | INFO | Train Epoch: 9 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.18568 (0.20223) Boundary_loss: 0.013899 (0.013901) Loss: 0.19958 (0.21613) +2025-09-14,13:35:29 | INFO | Train Epoch: 9 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.16019 (0.20040) Boundary_loss: 0.013899 (0.013901) Loss: 0.17409 (0.21430) +2025-09-14,13:36:34 | INFO | Train Epoch: 9 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.18139 (0.19961) Boundary_loss: 0.013907 (0.013902) Loss: 0.19529 (0.21351) +2025-09-14,13:37:40 | INFO | Train Epoch: 9 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.21725 (0.20031) Boundary_loss: 0.013902 (0.013902) Loss: 0.23115 (0.21421) +2025-09-14,13:38:46 | INFO | Train Epoch: 9 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.19071 (0.19994) Boundary_loss: 0.013900 (0.013902) Loss: 0.20461 (0.21385) +2025-09-14,13:39:52 | INFO | Train Epoch: 9 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.18322 (0.19932) Boundary_loss: 0.013900 (0.013901) Loss: 0.19712 (0.21323) +2025-09-14,13:40:57 | INFO | Train Epoch: 9 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.25651 (0.20137) Boundary_loss: 0.013902 (0.013902) Loss: 0.27041 (0.21527) +2025-09-14,13:42:03 | INFO | Train Epoch: 9 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.19480 (0.20114) Boundary_loss: 0.013901 (0.013901) Loss: 0.20870 (0.21504) +2025-09-14,13:43:09 | INFO | Train Epoch: 9 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.21292 (0.20153) Boundary_loss: 0.013900 (0.013901) Loss: 0.22682 (0.21543) +2025-09-14,13:44:15 | INFO | Train Epoch: 9 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.18601 (0.20103) Boundary_loss: 0.013903 (0.013901) Loss: 0.19991 (0.21493) +2025-09-14,13:45:21 | INFO | Train Epoch: 9 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.17467 (0.20021) Boundary_loss: 0.013904 (0.013902) Loss: 0.18857 (0.21411) +2025-09-14,13:46:26 | INFO | Train Epoch: 9 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.21747 (0.20073) Boundary_loss: 0.013900 (0.013902) Loss: 0.23137 (0.21463) +2025-09-14,13:47:32 | INFO | Train Epoch: 9 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16756 (0.19976) Boundary_loss: 0.013899 (0.013901) Loss: 0.18146 (0.21366) +2025-09-14,13:48:38 | INFO | Train Epoch: 9 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.20885 (0.20002) Boundary_loss: 0.013902 (0.013901) Loss: 0.22275 (0.21392) +2025-09-14,13:49:44 | INFO | Train Epoch: 9 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.17622 (0.19935) Boundary_loss: 0.013900 (0.013901) Loss: 0.19012 (0.21326) +2025-09-14,13:50:50 | INFO | Train Epoch: 9 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.17409 (0.19867) Boundary_loss: 0.013904 (0.013901) Loss: 0.18799 (0.21257) +2025-09-14,13:51:55 | INFO | Train Epoch: 9 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.22325 (0.19932) Boundary_loss: 0.013905 (0.013902) Loss: 0.23715 (0.21322) +2025-09-14,13:53:01 | INFO | Train Epoch: 9 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.21417 (0.19970) Boundary_loss: 0.013902 (0.013902) Loss: 0.22807 (0.21360) +2025-09-14,13:54:07 | INFO | Train Epoch: 9 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.17751 (0.19914) Boundary_loss: 0.013899 (0.013902) Loss: 0.19141 (0.21305) +2025-09-14,13:55:13 | INFO | Train Epoch: 9 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.19032 (0.19893) Boundary_loss: 0.013911 (0.013902) Loss: 0.20424 (0.21283) +2025-09-14,13:56:19 | INFO | Train Epoch: 9 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.20365 (0.19904) Boundary_loss: 0.013901 (0.013902) Loss: 0.21755 (0.21294) +2025-09-14,13:57:25 | INFO | Train Epoch: 9 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.20031 (0.19907) Boundary_loss: 0.013904 (0.013902) Loss: 0.21421 (0.21297) +2025-09-14,13:58:30 | INFO | Train Epoch: 9 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.23172 (0.19981) Boundary_loss: 0.013899 (0.013902) Loss: 0.24562 (0.21371) +2025-09-14,13:59:36 | INFO | Train Epoch: 9 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.22019 (0.20027) Boundary_loss: 0.013901 (0.013902) Loss: 0.23410 (0.21417) +2025-09-14,14:00:42 | INFO | Train Epoch: 9 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.18641 (0.19996) Boundary_loss: 0.013899 (0.013902) Loss: 0.20031 (0.21387) +2025-09-14,14:01:48 | INFO | Train Epoch: 9 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16879 (0.19930) Boundary_loss: 0.013902 (0.013902) Loss: 0.18270 (0.21320) +2025-09-14,14:02:53 | INFO | Train Epoch: 9 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.19706 (0.19925) Boundary_loss: 0.013911 (0.013902) Loss: 0.21097 (0.21316) +2025-09-14,14:03:59 | INFO | Train Epoch: 9 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.16960 (0.19865) Boundary_loss: 0.013898 (0.013902) Loss: 0.18350 (0.21255) +2025-09-14,14:05:05 | INFO | Train Epoch: 9 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.16966 (0.19807) Boundary_loss: 0.013900 (0.013902) Loss: 0.18356 (0.21197) +2025-09-14,14:06:11 | INFO | Train Epoch: 9 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.23037 (0.19870) Boundary_loss: 0.013902 (0.013902) Loss: 0.24427 (0.21260) +2025-09-14,14:07:17 | INFO | Train Epoch: 9 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.22236 (0.19916) Boundary_loss: 0.013897 (0.013902) Loss: 0.23625 (0.21306) +2025-09-14,14:08:23 | INFO | Train Epoch: 9 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.27029 (0.20050) Boundary_loss: 0.013898 (0.013902) Loss: 0.28419 (0.21440) +2025-09-14,14:09:28 | INFO | Train Epoch: 9 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.14716 (0.19951) Boundary_loss: 0.013900 (0.013902) Loss: 0.16106 (0.21341) +2025-09-14,14:10:34 | INFO | Train Epoch: 9 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18998 (0.19934) Boundary_loss: 0.013900 (0.013902) Loss: 0.20388 (0.21324) +2025-09-14,14:11:40 | INFO | Train Epoch: 9 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.18229 (0.19903) Boundary_loss: 0.013901 (0.013902) Loss: 0.19619 (0.21294) +2025-09-14,14:12:46 | INFO | Train Epoch: 9 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.24176 (0.19978) Boundary_loss: 0.013900 (0.013901) Loss: 0.25566 (0.21369) +2025-09-14,14:13:52 | INFO | Train Epoch: 9 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.17715 (0.19939) Boundary_loss: 0.013898 (0.013901) Loss: 0.19105 (0.21330) +2025-09-14,14:14:57 | INFO | Train Epoch: 9 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.19784 (0.19937) Boundary_loss: 0.013902 (0.013901) Loss: 0.21174 (0.21327) +2025-09-14,14:16:03 | INFO | Train Epoch: 9 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.21120 (0.19956) Boundary_loss: 0.013902 (0.013901) Loss: 0.22510 (0.21347) +2025-09-14,14:17:09 | INFO | Train Epoch: 9 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19469 (0.19948) Boundary_loss: 0.013898 (0.013901) Loss: 0.20859 (0.21339) +2025-09-14,14:18:15 | INFO | Train Epoch: 9 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.28817 (0.20092) Boundary_loss: 0.013899 (0.013901) Loss: 0.30207 (0.21482) +2025-09-14,14:19:21 | INFO | Train Epoch: 9 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.14993 (0.20011) Boundary_loss: 0.013900 (0.013901) Loss: 0.16383 (0.21401) +2025-09-14,14:20:26 | INFO | Train Epoch: 9 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19617 (0.20004) Boundary_loss: 0.013899 (0.013901) Loss: 0.21007 (0.21395) +2025-09-14,14:21:32 | INFO | Train Epoch: 9 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.20415 (0.20011) Boundary_loss: 0.013903 (0.013901) Loss: 0.21805 (0.21401) +2025-09-14,14:22:38 | INFO | Train Epoch: 9 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.19024 (0.19996) Boundary_loss: 0.013899 (0.013901) Loss: 0.20414 (0.21386) +2025-09-14,14:23:44 | INFO | Train Epoch: 9 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.20971 (0.20010) Boundary_loss: 0.013902 (0.013901) Loss: 0.22361 (0.21401) +2025-09-14,14:24:50 | INFO | Train Epoch: 9 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13576 (0.19916) Boundary_loss: 0.013902 (0.013901) Loss: 0.14966 (0.21306) +2025-09-14,14:25:56 | INFO | Train Epoch: 9 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.21111 (0.19933) Boundary_loss: 0.013899 (0.013901) Loss: 0.22501 (0.21323) +2025-09-14,14:27:02 | INFO | Train Epoch: 9 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.18855 (0.19918) Boundary_loss: 0.013902 (0.013901) Loss: 0.20245 (0.21308) +2025-09-14,14:28:07 | INFO | Train Epoch: 9 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.24382 (0.19981) Boundary_loss: 0.013900 (0.013901) Loss: 0.25772 (0.21371) +2025-09-14,14:29:13 | INFO | Train Epoch: 9 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.21557 (0.20002) Boundary_loss: 0.013902 (0.013901) Loss: 0.22947 (0.21393) +2025-09-14,14:30:19 | INFO | Train Epoch: 9 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17382 (0.19967) Boundary_loss: 0.013901 (0.013901) Loss: 0.18772 (0.21357) +2025-09-14,14:31:25 | INFO | Train Epoch: 9 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.20476 (0.19973) Boundary_loss: 0.013900 (0.013901) Loss: 0.21866 (0.21364) +2025-09-14,14:32:31 | INFO | Train Epoch: 9 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.15785 (0.19918) Boundary_loss: 0.013902 (0.013901) Loss: 0.17175 (0.21308) +2025-09-14,14:33:37 | INFO | Train Epoch: 9 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.18436 (0.19898) Boundary_loss: 0.013901 (0.013901) Loss: 0.19826 (0.21288) +2025-09-14,14:34:42 | INFO | Train Epoch: 9 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.17819 (0.19871) Boundary_loss: 0.013900 (0.013901) Loss: 0.19209 (0.21261) +2025-09-14,14:35:48 | INFO | Train Epoch: 9 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.23436 (0.19917) Boundary_loss: 0.013905 (0.013901) Loss: 0.24826 (0.21307) +2025-09-14,14:36:54 | INFO | Train Epoch: 9 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.20746 (0.19927) Boundary_loss: 0.013904 (0.013901) Loss: 0.22136 (0.21317) +2025-09-14,14:38:00 | INFO | Train Epoch: 9 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.19591 (0.19923) Boundary_loss: 0.013900 (0.013901) Loss: 0.20981 (0.21313) +2025-09-14,14:39:06 | INFO | Train Epoch: 9 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25717 (0.19995) Boundary_loss: 0.013902 (0.013901) Loss: 0.27107 (0.21385) +2025-09-14,14:40:12 | INFO | Train Epoch: 9 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.20019 (0.19995) Boundary_loss: 0.013901 (0.013901) Loss: 0.21409 (0.21385) +2025-09-14,14:41:17 | INFO | Train Epoch: 9 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.20074 (0.19996) Boundary_loss: 0.013898 (0.013901) Loss: 0.21464 (0.21386) +2025-09-14,14:42:23 | INFO | Train Epoch: 9 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.20277 (0.19999) Boundary_loss: 0.013901 (0.013901) Loss: 0.21667 (0.21389) +2025-09-14,14:43:29 | INFO | Train Epoch: 9 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.17391 (0.19969) Boundary_loss: 0.013898 (0.013901) Loss: 0.18781 (0.21359) +2025-09-14,14:44:35 | INFO | Train Epoch: 9 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16354 (0.19927) Boundary_loss: 0.013902 (0.013901) Loss: 0.17744 (0.21317) +2025-09-14,14:45:41 | INFO | Train Epoch: 9 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.20129 (0.19929) Boundary_loss: 0.013901 (0.013901) Loss: 0.21519 (0.21319) +2025-09-14,14:46:47 | INFO | Train Epoch: 9 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.16478 (0.19890) Boundary_loss: 0.013903 (0.013901) Loss: 0.17868 (0.21280) +2025-09-14,14:47:52 | INFO | Train Epoch: 9 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.26115 (0.19960) Boundary_loss: 0.013902 (0.013901) Loss: 0.27506 (0.21350) +2025-09-14,14:48:58 | INFO | Train Epoch: 9 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.26328 (0.20030) Boundary_loss: 0.013902 (0.013901) Loss: 0.27718 (0.21420) +2025-09-14,14:50:04 | INFO | Train Epoch: 9 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18583 (0.20014) Boundary_loss: 0.013901 (0.013901) Loss: 0.19974 (0.21405) +2025-09-14,14:51:10 | INFO | Train Epoch: 9 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.22354 (0.20040) Boundary_loss: 0.013900 (0.013901) Loss: 0.23744 (0.21430) +2025-09-14,14:52:16 | INFO | Train Epoch: 9 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.18381 (0.20022) Boundary_loss: 0.013900 (0.013901) Loss: 0.19771 (0.21412) +2025-09-14,14:53:22 | INFO | Train Epoch: 9 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.18620 (0.20007) Boundary_loss: 0.013904 (0.013901) Loss: 0.20010 (0.21397) +2025-09-14,14:54:27 | INFO | Train Epoch: 9 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.16226 (0.19967) Boundary_loss: 0.013897 (0.013901) Loss: 0.17616 (0.21357) +2025-09-14,14:55:33 | INFO | Train Epoch: 9 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.14283 (0.19908) Boundary_loss: 0.013900 (0.013901) Loss: 0.15673 (0.21298) +2025-09-14,14:56:39 | INFO | Train Epoch: 9 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.22111 (0.19931) Boundary_loss: 0.013901 (0.013901) Loss: 0.23501 (0.21321) +2025-09-14,14:57:45 | INFO | Train Epoch: 9 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.17636 (0.19907) Boundary_loss: 0.013899 (0.013901) Loss: 0.19026 (0.21297) +2025-09-14,14:58:51 | INFO | Train Epoch: 9 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.22386 (0.19932) Boundary_loss: 0.013901 (0.013901) Loss: 0.23776 (0.21323) +2025-09-14,14:59:57 | INFO | Train Epoch: 9 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.24241 (0.19975) Boundary_loss: 0.013903 (0.013901) Loss: 0.25631 (0.21366) +2025-09-14,15:01:02 | INFO | Train Epoch: 9 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.18116 (0.19957) Boundary_loss: 0.013904 (0.013901) Loss: 0.19507 (0.21347) +2025-09-14,15:02:08 | INFO | Train Epoch: 9 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.25994 (0.20016) Boundary_loss: 0.013903 (0.013901) Loss: 0.27384 (0.21406) +2025-09-14,15:03:14 | INFO | Train Epoch: 9 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.17076 (0.19988) Boundary_loss: 0.013900 (0.013901) Loss: 0.18466 (0.21378) +2025-09-14,15:04:20 | INFO | Train Epoch: 9 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.21237 (0.20000) Boundary_loss: 0.013904 (0.013901) Loss: 0.22627 (0.21390) +2025-09-14,15:05:26 | INFO | Train Epoch: 9 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.20965 (0.20009) Boundary_loss: 0.013900 (0.013901) Loss: 0.22355 (0.21399) +2025-09-14,15:06:32 | INFO | Train Epoch: 9 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.15703 (0.19968) Boundary_loss: 0.013899 (0.013901) Loss: 0.17093 (0.21358) +2025-09-14,15:07:38 | INFO | Train Epoch: 9 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.14891 (0.19921) Boundary_loss: 0.013900 (0.013901) Loss: 0.16281 (0.21311) +2025-09-14,15:08:44 | INFO | Train Epoch: 9 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.17220 (0.19896) Boundary_loss: 0.013901 (0.013901) Loss: 0.18610 (0.21286) +2025-09-14,15:09:49 | INFO | Train Epoch: 9 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.13914 (0.19841) Boundary_loss: 0.013901 (0.013901) Loss: 0.15304 (0.21231) +2025-09-14,15:10:55 | INFO | Train Epoch: 9 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.20981 (0.19851) Boundary_loss: 0.013899 (0.013901) Loss: 0.22371 (0.21241) +2025-09-14,15:12:01 | INFO | Train Epoch: 9 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.11867 (0.19779) Boundary_loss: 0.013901 (0.013901) Loss: 0.13257 (0.21170) +2025-09-14,15:13:07 | INFO | Train Epoch: 9 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.21206 (0.19792) Boundary_loss: 0.013900 (0.013901) Loss: 0.22596 (0.21182) +2025-09-14,15:14:13 | INFO | Train Epoch: 9 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.20340 (0.19797) Boundary_loss: 0.013902 (0.013901) Loss: 0.21730 (0.21187) +2025-09-14,15:15:19 | INFO | Train Epoch: 9 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.15708 (0.19761) Boundary_loss: 0.013901 (0.013901) Loss: 0.17098 (0.21151) +2025-09-14,15:16:25 | INFO | Train Epoch: 9 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.15188 (0.19721) Boundary_loss: 0.013904 (0.013901) Loss: 0.16579 (0.21111) +2025-09-14,15:17:31 | INFO | Train Epoch: 9 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.22163 (0.19742) Boundary_loss: 0.013901 (0.013901) Loss: 0.23554 (0.21133) +2025-09-14,15:18:36 | INFO | Train Epoch: 9 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.27021 (0.19805) Boundary_loss: 0.013899 (0.013901) Loss: 0.28411 (0.21195) +2025-09-14,15:19:42 | INFO | Train Epoch: 9 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.24275 (0.19843) Boundary_loss: 0.013899 (0.013901) Loss: 0.25665 (0.21233) +2025-09-14,15:20:48 | INFO | Train Epoch: 9 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12938 (0.19784) Boundary_loss: 0.013905 (0.013901) Loss: 0.14328 (0.21175) +2025-09-14,15:21:54 | INFO | Train Epoch: 9 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.22774 (0.19809) Boundary_loss: 0.013908 (0.013901) Loss: 0.24165 (0.21200) +2025-09-14,15:23:00 | INFO | Train Epoch: 9 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.14593 (0.19766) Boundary_loss: 0.013905 (0.013901) Loss: 0.15983 (0.21156) +2025-09-14,15:24:06 | INFO | Train Epoch: 9 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.24709 (0.19807) Boundary_loss: 0.013900 (0.013901) Loss: 0.26099 (0.21197) +2025-09-14,15:25:12 | INFO | Train Epoch: 9 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.23954 (0.19841) Boundary_loss: 0.013901 (0.013901) Loss: 0.25345 (0.21231) +2025-09-14,15:26:18 | INFO | Train Epoch: 9 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16243 (0.19812) Boundary_loss: 0.013899 (0.013901) Loss: 0.17633 (0.21202) +2025-09-14,15:27:23 | INFO | Train Epoch: 9 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.20175 (0.19814) Boundary_loss: 0.013902 (0.013901) Loss: 0.21565 (0.21205) +2025-09-14,15:28:29 | INFO | Train Epoch: 9 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.16138 (0.19785) Boundary_loss: 0.013901 (0.013901) Loss: 0.17529 (0.21175) +2025-09-14,15:29:35 | INFO | Train Epoch: 9 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.13447 (0.19735) Boundary_loss: 0.013901 (0.013901) Loss: 0.14837 (0.21125) +2025-09-14,15:30:41 | INFO | Train Epoch: 9 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.22043 (0.19753) Boundary_loss: 0.013899 (0.013901) Loss: 0.23433 (0.21143) +2025-09-14,15:31:47 | INFO | Train Epoch: 9 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.16932 (0.19731) Boundary_loss: 0.013898 (0.013901) Loss: 0.18322 (0.21122) +2025-09-14,15:32:53 | INFO | Train Epoch: 9 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.17377 (0.19713) Boundary_loss: 0.013901 (0.013901) Loss: 0.18767 (0.21104) +2025-09-14,15:33:59 | INFO | Train Epoch: 9 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.23416 (0.19742) Boundary_loss: 0.013898 (0.013901) Loss: 0.24806 (0.21132) +2025-09-14,15:35:05 | INFO | Train Epoch: 9 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.23371 (0.19769) Boundary_loss: 0.013910 (0.013901) Loss: 0.24762 (0.21159) +2025-09-14,15:36:11 | INFO | Train Epoch: 9 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.18495 (0.19760) Boundary_loss: 0.013898 (0.013901) Loss: 0.19885 (0.21150) +2025-09-14,15:37:17 | INFO | Train Epoch: 9 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.25709 (0.19804) Boundary_loss: 0.013898 (0.013901) Loss: 0.27099 (0.21194) +2025-09-14,15:38:22 | INFO | Train Epoch: 9 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24255 (0.19837) Boundary_loss: 0.013903 (0.013901) Loss: 0.25645 (0.21227) +2025-09-14,15:39:28 | INFO | Train Epoch: 9 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.26767 (0.19888) Boundary_loss: 0.013898 (0.013901) Loss: 0.28157 (0.21278) +2025-09-14,15:40:34 | INFO | Train Epoch: 9 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26438 (0.19936) Boundary_loss: 0.013901 (0.013901) Loss: 0.27828 (0.21326) +2025-09-14,15:41:40 | INFO | Train Epoch: 9 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.20293 (0.19938) Boundary_loss: 0.013899 (0.013901) Loss: 0.21683 (0.21328) +2025-09-14,15:42:46 | INFO | Train Epoch: 9 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19872 (0.19938) Boundary_loss: 0.013899 (0.013901) Loss: 0.21262 (0.21328) +2025-09-14,15:43:52 | INFO | Train Epoch: 9 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.16592 (0.19914) Boundary_loss: 0.013903 (0.013901) Loss: 0.17982 (0.21304) +2025-09-14,15:44:58 | INFO | Train Epoch: 9 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.20972 (0.19921) Boundary_loss: 0.013905 (0.013901) Loss: 0.22362 (0.21312) +2025-09-14,15:46:04 | INFO | Train Epoch: 9 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.20207 (0.19923) Boundary_loss: 0.013899 (0.013901) Loss: 0.21597 (0.21314) +2025-09-14,15:47:10 | INFO | Train Epoch: 9 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.22508 (0.19941) Boundary_loss: 0.013901 (0.013901) Loss: 0.23898 (0.21332) +2025-09-14,15:48:16 | INFO | Train Epoch: 9 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.21542 (0.19953) Boundary_loss: 0.013899 (0.013901) Loss: 0.22932 (0.21343) +2025-09-14,15:49:22 | INFO | Train Epoch: 9 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17518 (0.19936) Boundary_loss: 0.013898 (0.013901) Loss: 0.18907 (0.21326) +2025-09-14,15:50:28 | INFO | Train Epoch: 9 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.19282 (0.19931) Boundary_loss: 0.013901 (0.013901) Loss: 0.20672 (0.21321) +2025-09-14,15:51:34 | INFO | Train Epoch: 9 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.23383 (0.19955) Boundary_loss: 0.013901 (0.013901) Loss: 0.24773 (0.21345) +2025-09-14,15:52:39 | INFO | Train Epoch: 9 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18591 (0.19946) Boundary_loss: 0.013900 (0.013901) Loss: 0.19981 (0.21336) +2025-09-14,15:53:45 | INFO | Train Epoch: 9 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.18854 (0.19938) Boundary_loss: 0.013900 (0.013901) Loss: 0.20244 (0.21328) +2025-09-14,15:54:51 | INFO | Train Epoch: 9 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.18883 (0.19931) Boundary_loss: 0.013899 (0.013901) Loss: 0.20273 (0.21321) +2025-09-14,15:55:57 | INFO | Train Epoch: 9 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19044 (0.19925) Boundary_loss: 0.013902 (0.013901) Loss: 0.20435 (0.21315) +2025-09-14,15:57:03 | INFO | Train Epoch: 9 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18956 (0.19919) Boundary_loss: 0.013905 (0.013901) Loss: 0.20346 (0.21309) +2025-09-14,15:58:09 | INFO | Train Epoch: 9 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.20103 (0.19920) Boundary_loss: 0.013899 (0.013901) Loss: 0.21493 (0.21310) +2025-09-14,15:59:15 | INFO | Train Epoch: 9 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.22187 (0.19935) Boundary_loss: 0.013902 (0.013901) Loss: 0.23578 (0.21325) +2025-09-14,16:00:21 | INFO | Train Epoch: 9 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.14590 (0.19900) Boundary_loss: 0.013899 (0.013901) Loss: 0.15980 (0.21291) +2025-09-14,16:01:27 | INFO | Train Epoch: 9 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.21604 (0.19911) Boundary_loss: 0.013901 (0.013901) Loss: 0.22994 (0.21301) +2025-09-14,16:02:33 | INFO | Train Epoch: 9 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17933 (0.19899) Boundary_loss: 0.013898 (0.013901) Loss: 0.19323 (0.21289) +2025-09-14,16:03:39 | INFO | Train Epoch: 9 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.15708 (0.19872) Boundary_loss: 0.013901 (0.013901) Loss: 0.17098 (0.21262) +2025-09-14,16:04:45 | INFO | Train Epoch: 9 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.16306 (0.19850) Boundary_loss: 0.013900 (0.013901) Loss: 0.17696 (0.21240) +2025-09-14,16:05:51 | INFO | Train Epoch: 9 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.18003 (0.19838) Boundary_loss: 0.013900 (0.013901) Loss: 0.19393 (0.21228) +2025-09-14,16:06:57 | INFO | Train Epoch: 9 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17135 (0.19821) Boundary_loss: 0.013899 (0.013901) Loss: 0.18525 (0.21212) +2025-09-14,16:08:03 | INFO | Train Epoch: 9 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.24937 (0.19853) Boundary_loss: 0.013899 (0.013901) Loss: 0.26327 (0.21243) +2025-09-14,16:09:08 | INFO | Train Epoch: 9 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.18534 (0.19845) Boundary_loss: 0.013897 (0.013901) Loss: 0.19923 (0.21235) +2025-09-14,16:10:14 | INFO | Train Epoch: 9 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20828 (0.19851) Boundary_loss: 0.013904 (0.013901) Loss: 0.22218 (0.21241) +2025-09-14,16:11:20 | INFO | Train Epoch: 9 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.20790 (0.19857) Boundary_loss: 0.013903 (0.013901) Loss: 0.22180 (0.21247) +2025-09-14,16:12:26 | INFO | Train Epoch: 9 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.16371 (0.19836) Boundary_loss: 0.013904 (0.013901) Loss: 0.17762 (0.21226) +2025-09-14,16:13:32 | INFO | Train Epoch: 9 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.22217 (0.19850) Boundary_loss: 0.013899 (0.013901) Loss: 0.23607 (0.21240) +2025-09-14,16:14:38 | INFO | Train Epoch: 9 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.21745 (0.19861) Boundary_loss: 0.013899 (0.013901) Loss: 0.23135 (0.21251) +2025-09-14,16:15:44 | INFO | Train Epoch: 9 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.24794 (0.19890) Boundary_loss: 0.013900 (0.013901) Loss: 0.26184 (0.21280) +2025-09-14,16:16:50 | INFO | Train Epoch: 9 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.20665 (0.19895) Boundary_loss: 0.013899 (0.013901) Loss: 0.22055 (0.21285) +2025-09-14,16:17:56 | INFO | Train Epoch: 9 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17777 (0.19883) Boundary_loss: 0.013900 (0.013901) Loss: 0.19167 (0.21273) +2025-09-14,16:19:02 | INFO | Train Epoch: 9 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.18015 (0.19872) Boundary_loss: 0.013897 (0.013901) Loss: 0.19405 (0.21262) +2025-09-14,16:20:08 | INFO | Train Epoch: 9 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.22086 (0.19884) Boundary_loss: 0.013899 (0.013901) Loss: 0.23476 (0.21275) +2025-09-14,16:21:14 | INFO | Train Epoch: 9 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.22277 (0.19898) Boundary_loss: 0.013901 (0.013901) Loss: 0.23667 (0.21288) +2025-09-14,16:22:20 | INFO | Train Epoch: 9 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.23129 (0.19917) Boundary_loss: 0.013898 (0.013901) Loss: 0.24519 (0.21307) +2025-09-14,16:23:26 | INFO | Train Epoch: 9 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.22612 (0.19932) Boundary_loss: 0.013901 (0.013901) Loss: 0.24002 (0.21322) +2025-09-14,16:24:32 | INFO | Train Epoch: 9 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12973 (0.19893) Boundary_loss: 0.013899 (0.013901) Loss: 0.14363 (0.21283) +2025-09-14,16:25:38 | INFO | Train Epoch: 9 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.23893 (0.19915) Boundary_loss: 0.013902 (0.013901) Loss: 0.25284 (0.21305) +2025-09-14,16:26:44 | INFO | Train Epoch: 9 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.17244 (0.19900) Boundary_loss: 0.013902 (0.013901) Loss: 0.18635 (0.21290) +2025-09-14,16:27:50 | INFO | Train Epoch: 9 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.26395 (0.19936) Boundary_loss: 0.013900 (0.013901) Loss: 0.27785 (0.21326) +2025-09-14,16:28:56 | INFO | Train Epoch: 9 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.20501 (0.19939) Boundary_loss: 0.013899 (0.013901) Loss: 0.21891 (0.21330) +2025-09-14,16:30:02 | INFO | Train Epoch: 9 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17726 (0.19927) Boundary_loss: 0.013899 (0.013901) Loss: 0.19116 (0.21317) +2025-09-14,16:31:08 | INFO | Train Epoch: 9 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.23433 (0.19946) Boundary_loss: 0.013900 (0.013901) Loss: 0.24823 (0.21337) +2025-09-14,16:32:14 | INFO | Train Epoch: 9 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.20995 (0.19952) Boundary_loss: 0.013899 (0.013901) Loss: 0.22385 (0.21342) +2025-09-14,16:33:20 | INFO | Train Epoch: 9 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.17440 (0.19939) Boundary_loss: 0.013900 (0.013901) Loss: 0.18830 (0.21329) +2025-09-14,16:34:26 | INFO | Train Epoch: 9 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.22895 (0.19954) Boundary_loss: 0.013899 (0.013901) Loss: 0.24285 (0.21345) +2025-09-14,16:35:32 | INFO | Train Epoch: 9 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.21492 (0.19963) Boundary_loss: 0.013902 (0.013901) Loss: 0.22883 (0.21353) +2025-09-14,16:36:38 | INFO | Train Epoch: 9 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.15494 (0.19939) Boundary_loss: 0.013900 (0.013901) Loss: 0.16884 (0.21329) +2025-09-14,16:37:44 | INFO | Train Epoch: 9 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.20001 (0.19939) Boundary_loss: 0.013900 (0.013901) Loss: 0.21391 (0.21329) +2025-09-14,16:38:50 | INFO | Train Epoch: 9 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.13530 (0.19906) Boundary_loss: 0.013900 (0.013901) Loss: 0.14920 (0.21296) +2025-09-14,16:39:56 | INFO | Train Epoch: 9 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.17612 (0.19894) Boundary_loss: 0.013899 (0.013901) Loss: 0.19002 (0.21284) +2025-09-14,16:41:02 | INFO | Train Epoch: 9 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22233 (0.19906) Boundary_loss: 0.013898 (0.013901) Loss: 0.23623 (0.21296) +2025-09-14,16:42:08 | INFO | Train Epoch: 9 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.21657 (0.19915) Boundary_loss: 0.013900 (0.013901) Loss: 0.23047 (0.21305) +2025-09-14,16:43:14 | INFO | Train Epoch: 9 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.15393 (0.19891) Boundary_loss: 0.013906 (0.013901) Loss: 0.16783 (0.21282) +2025-09-14,16:44:20 | INFO | Train Epoch: 9 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.17850 (0.19881) Boundary_loss: 0.013902 (0.013901) Loss: 0.19240 (0.21271) +2025-09-14,16:45:26 | INFO | Train Epoch: 9 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.19341 (0.19878) Boundary_loss: 0.013900 (0.013901) Loss: 0.20731 (0.21268) +2025-09-14,16:46:32 | INFO | Train Epoch: 9 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.19627 (0.19877) Boundary_loss: 0.013905 (0.013901) Loss: 0.21018 (0.21267) +2025-09-14,16:47:38 | INFO | Train Epoch: 9 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.24815 (0.19902) Boundary_loss: 0.013899 (0.013901) Loss: 0.26205 (0.21292) +2025-09-14,16:48:44 | INFO | Train Epoch: 9 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.19721 (0.19901) Boundary_loss: 0.013902 (0.013901) Loss: 0.21111 (0.21291) +2025-09-14,16:49:50 | INFO | Train Epoch: 9 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.20362 (0.19903) Boundary_loss: 0.013902 (0.013901) Loss: 0.21753 (0.21293) +2025-09-14,16:50:56 | INFO | Train Epoch: 9 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.24080 (0.19924) Boundary_loss: 0.013902 (0.013901) Loss: 0.25470 (0.21314) +2025-09-14,16:52:02 | INFO | Train Epoch: 9 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.18273 (0.19916) Boundary_loss: 0.013898 (0.013901) Loss: 0.19662 (0.21306) +2025-09-14,16:53:08 | INFO | Train Epoch: 9 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.23801 (0.19935) Boundary_loss: 0.013899 (0.013901) Loss: 0.25191 (0.21325) +2025-09-14,16:54:13 | INFO | Train Epoch: 9 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.14436 (0.19908) Boundary_loss: 0.013899 (0.013901) Loss: 0.15826 (0.21298) +2025-09-14,16:55:19 | INFO | Train Epoch: 9 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.17841 (0.19898) Boundary_loss: 0.013899 (0.013901) Loss: 0.19231 (0.21288) +2025-09-14,16:56:25 | INFO | Train Epoch: 9 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.24592 (0.19921) Boundary_loss: 0.013899 (0.013901) Loss: 0.25982 (0.21311) +2025-09-14,16:57:31 | INFO | Train Epoch: 9 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.23931 (0.19940) Boundary_loss: 0.013899 (0.013901) Loss: 0.25321 (0.21330) +2025-09-14,16:58:37 | INFO | Train Epoch: 9 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.21551 (0.19948) Boundary_loss: 0.013903 (0.013901) Loss: 0.22941 (0.21338) +2025-09-14,16:59:43 | INFO | Train Epoch: 9 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.20932 (0.19953) Boundary_loss: 0.013901 (0.013901) Loss: 0.22322 (0.21343) +2025-09-14,17:00:49 | INFO | Train Epoch: 9 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.25011 (0.19977) Boundary_loss: 0.013899 (0.013901) Loss: 0.26401 (0.21367) +2025-09-14,17:01:55 | INFO | Train Epoch: 9 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.18254 (0.19969) Boundary_loss: 0.013900 (0.013901) Loss: 0.19644 (0.21359) +2025-09-14,17:03:01 | INFO | Train Epoch: 9 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21614 (0.19976) Boundary_loss: 0.013903 (0.013901) Loss: 0.23004 (0.21366) +2025-09-14,17:04:07 | INFO | Train Epoch: 9 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.21554 (0.19984) Boundary_loss: 0.013898 (0.013901) Loss: 0.22943 (0.21374) +2025-09-14,17:05:13 | INFO | Train Epoch: 9 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.27300 (0.20018) Boundary_loss: 0.013898 (0.013901) Loss: 0.28690 (0.21408) +2025-09-14,17:06:19 | INFO | Train Epoch: 9 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24717 (0.20040) Boundary_loss: 0.013901 (0.013901) Loss: 0.26107 (0.21430) +2025-09-14,17:07:25 | INFO | Train Epoch: 9 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.19414 (0.20037) Boundary_loss: 0.013901 (0.013901) Loss: 0.20804 (0.21427) +2025-09-14,17:08:31 | INFO | Train Epoch: 9 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.23188 (0.20051) Boundary_loss: 0.013903 (0.013901) Loss: 0.24578 (0.21441) +2025-09-14,17:09:37 | INFO | Train Epoch: 9 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.20912 (0.20055) Boundary_loss: 0.013899 (0.013901) Loss: 0.22302 (0.21445) +2025-09-14,17:10:43 | INFO | Train Epoch: 9 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.14210 (0.20029) Boundary_loss: 0.013904 (0.013901) Loss: 0.15600 (0.21419) +2025-09-14,17:11:49 | INFO | Train Epoch: 9 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.17330 (0.20016) Boundary_loss: 0.013899 (0.013901) Loss: 0.18720 (0.21406) +2025-09-14,17:12:55 | INFO | Train Epoch: 9 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.21988 (0.20025) Boundary_loss: 0.013902 (0.013901) Loss: 0.23379 (0.21415) +2025-09-14,17:14:01 | INFO | Train Epoch: 9 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.20319 (0.20027) Boundary_loss: 0.013899 (0.013901) Loss: 0.21709 (0.21417) +2025-09-14,17:15:07 | INFO | Train Epoch: 9 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.20887 (0.20030) Boundary_loss: 0.013900 (0.013901) Loss: 0.22277 (0.21421) +2025-09-14,17:16:13 | INFO | Train Epoch: 9 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.16741 (0.20016) Boundary_loss: 0.013901 (0.013901) Loss: 0.18131 (0.21406) +2025-09-14,17:17:19 | INFO | Train Epoch: 9 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17383 (0.20004) Boundary_loss: 0.013898 (0.013901) Loss: 0.18773 (0.21394) +2025-09-14,17:18:25 | INFO | Train Epoch: 9 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.18723 (0.19998) Boundary_loss: 0.013902 (0.013901) Loss: 0.20113 (0.21388) +2025-09-14,17:19:31 | INFO | Train Epoch: 9 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.17705 (0.19988) Boundary_loss: 0.013900 (0.013901) Loss: 0.19095 (0.21378) +2025-09-14,17:20:37 | INFO | Train Epoch: 9 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.19792 (0.19987) Boundary_loss: 0.013900 (0.013901) Loss: 0.21182 (0.21378) +2025-09-14,17:21:43 | INFO | Train Epoch: 9 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19712 (0.19986) Boundary_loss: 0.013902 (0.013901) Loss: 0.21102 (0.21376) +2025-09-14,17:22:49 | INFO | Train Epoch: 9 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.20930 (0.19990) Boundary_loss: 0.013901 (0.013901) Loss: 0.22320 (0.21380) +2025-09-14,17:23:55 | INFO | Train Epoch: 9 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.19779 (0.19989) Boundary_loss: 0.013899 (0.013901) Loss: 0.21169 (0.21380) +2025-09-14,17:25:01 | INFO | Train Epoch: 9 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.18634 (0.19984) Boundary_loss: 0.013899 (0.013901) Loss: 0.20024 (0.21374) +2025-09-14,17:26:07 | INFO | Train Epoch: 9 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17301 (0.19972) Boundary_loss: 0.013900 (0.013901) Loss: 0.18691 (0.21362) +2025-09-14,17:27:13 | INFO | Train Epoch: 9 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.16730 (0.19958) Boundary_loss: 0.013900 (0.013901) Loss: 0.18120 (0.21348) +2025-09-14,17:28:19 | INFO | Train Epoch: 9 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.21614 (0.19965) Boundary_loss: 0.013901 (0.013901) Loss: 0.23004 (0.21355) +2025-09-14,17:29:25 | INFO | Train Epoch: 9 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.19504 (0.19963) Boundary_loss: 0.013898 (0.013901) Loss: 0.20893 (0.21353) +2025-09-14,17:30:30 | INFO | Train Epoch: 9 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.19765 (0.19962) Boundary_loss: 0.013902 (0.013901) Loss: 0.21155 (0.21353) +2025-09-14,17:31:36 | INFO | Train Epoch: 9 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.18849 (0.19958) Boundary_loss: 0.013897 (0.013901) Loss: 0.20239 (0.21348) +2025-09-14,17:32:42 | INFO | Train Epoch: 9 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.21404 (0.19964) Boundary_loss: 0.013898 (0.013901) Loss: 0.22794 (0.21354) +2025-09-14,17:33:48 | INFO | Train Epoch: 9 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.24627 (0.19983) Boundary_loss: 0.013908 (0.013901) Loss: 0.26017 (0.21373) +2025-09-14,17:34:54 | INFO | Train Epoch: 9 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15825 (0.19966) Boundary_loss: 0.013897 (0.013901) Loss: 0.17215 (0.21356) +2025-09-14,17:36:00 | INFO | Train Epoch: 9 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.13399 (0.19939) Boundary_loss: 0.013900 (0.013901) Loss: 0.14789 (0.21329) +2025-09-14,17:37:06 | INFO | Train Epoch: 9 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15799 (0.19922) Boundary_loss: 0.013901 (0.013901) Loss: 0.17189 (0.21312) +2025-09-14,17:38:12 | INFO | Train Epoch: 9 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19478 (0.19920) Boundary_loss: 0.013898 (0.013901) Loss: 0.20868 (0.21310) +2025-09-14,17:39:18 | INFO | Train Epoch: 9 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.24616 (0.19939) Boundary_loss: 0.013901 (0.013901) Loss: 0.26006 (0.21329) +2025-09-14,17:40:24 | INFO | Train Epoch: 9 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.15851 (0.19923) Boundary_loss: 0.013898 (0.013901) Loss: 0.17241 (0.21313) +2025-09-14,17:41:30 | INFO | Train Epoch: 9 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.19174 (0.19920) Boundary_loss: 0.013900 (0.013901) Loss: 0.20564 (0.21310) +2025-09-14,17:42:36 | INFO | Train Epoch: 9 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.18878 (0.19915) Boundary_loss: 0.013900 (0.013901) Loss: 0.20268 (0.21305) +2025-09-14,17:43:42 | INFO | Train Epoch: 9 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.16442 (0.19901) Boundary_loss: 0.013899 (0.013901) Loss: 0.17832 (0.21291) +2025-09-14,17:44:48 | INFO | Train Epoch: 9 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.16174 (0.19886) Boundary_loss: 0.013899 (0.013901) Loss: 0.17564 (0.21277) +2025-09-14,17:45:54 | INFO | Train Epoch: 9 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.18732 (0.19882) Boundary_loss: 0.013898 (0.013901) Loss: 0.20122 (0.21272) +2025-09-14,17:47:00 | INFO | Train Epoch: 9 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.18507 (0.19876) Boundary_loss: 0.013898 (0.013901) Loss: 0.19896 (0.21267) +2025-09-14,17:48:06 | INFO | Train Epoch: 9 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.27915 (0.19908) Boundary_loss: 0.013901 (0.013901) Loss: 0.29305 (0.21298) +2025-09-14,17:49:12 | INFO | Train Epoch: 9 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.21571 (0.19915) Boundary_loss: 0.013902 (0.013901) Loss: 0.22961 (0.21305) +2025-09-14,17:50:18 | INFO | Train Epoch: 9 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.20505 (0.19917) Boundary_loss: 0.013896 (0.013901) Loss: 0.21894 (0.21307) +2025-09-14,17:51:24 | INFO | Train Epoch: 9 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.20901 (0.19921) Boundary_loss: 0.013899 (0.013901) Loss: 0.22291 (0.21311) +2025-09-14,17:52:30 | INFO | Train Epoch: 9 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.17351 (0.19911) Boundary_loss: 0.013899 (0.013901) Loss: 0.18741 (0.21301) +2025-09-14,17:53:36 | INFO | Train Epoch: 9 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.27672 (0.19941) Boundary_loss: 0.013911 (0.013901) Loss: 0.29063 (0.21331) +2025-09-14,17:54:42 | INFO | Train Epoch: 9 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.19526 (0.19939) Boundary_loss: 0.013899 (0.013901) Loss: 0.20915 (0.21329) +2025-09-14,17:55:48 | INFO | Train Epoch: 9 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.23141 (0.19952) Boundary_loss: 0.013901 (0.013901) Loss: 0.24531 (0.21342) +2025-09-14,17:56:54 | INFO | Train Epoch: 9 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17906 (0.19944) Boundary_loss: 0.013899 (0.013901) Loss: 0.19296 (0.21334) +2025-09-14,17:58:00 | INFO | Train Epoch: 9 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.22778 (0.19955) Boundary_loss: 0.013900 (0.013901) Loss: 0.24168 (0.21345) +2025-09-14,17:59:06 | INFO | Train Epoch: 9 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.23303 (0.19967) Boundary_loss: 0.013899 (0.013901) Loss: 0.24692 (0.21357) +2025-09-14,18:00:12 | INFO | Train Epoch: 9 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.20129 (0.19968) Boundary_loss: 0.013899 (0.013901) Loss: 0.21519 (0.21358) +2025-09-14,18:01:18 | INFO | Train Epoch: 9 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.17346 (0.19958) Boundary_loss: 0.013898 (0.013901) Loss: 0.18735 (0.21348) +2025-09-14,18:02:24 | INFO | Train Epoch: 9 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15116 (0.19940) Boundary_loss: 0.013898 (0.013901) Loss: 0.16506 (0.21330) +2025-09-14,18:03:30 | INFO | Train Epoch: 9 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23727 (0.19954) Boundary_loss: 0.013897 (0.013901) Loss: 0.25116 (0.21344) +2025-09-14,18:04:36 | INFO | Train Epoch: 9 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.20573 (0.19956) Boundary_loss: 0.013903 (0.013901) Loss: 0.21963 (0.21346) +2025-09-14,18:05:42 | INFO | Train Epoch: 9 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.21864 (0.19964) Boundary_loss: 0.013898 (0.013901) Loss: 0.23253 (0.21354) +2025-09-14,18:06:48 | INFO | Train Epoch: 9 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.18201 (0.19957) Boundary_loss: 0.013897 (0.013901) Loss: 0.19590 (0.21347) +2025-09-14,18:07:54 | INFO | Train Epoch: 9 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.20715 (0.19960) Boundary_loss: 0.013900 (0.013901) Loss: 0.22105 (0.21350) +2025-09-14,18:09:00 | INFO | Train Epoch: 9 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.21781 (0.19966) Boundary_loss: 0.013902 (0.013901) Loss: 0.23171 (0.21357) +2025-09-14,18:10:06 | INFO | Train Epoch: 9 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.17314 (0.19957) Boundary_loss: 0.013902 (0.013901) Loss: 0.18704 (0.21347) +2025-09-14,18:11:12 | INFO | Train Epoch: 9 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.22709 (0.19967) Boundary_loss: 0.013908 (0.013901) Loss: 0.24100 (0.21357) +2025-09-14,18:12:17 | INFO | Train Epoch: 9 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.20928 (0.19970) Boundary_loss: 0.013899 (0.013901) Loss: 0.22318 (0.21360) +2025-09-14,18:13:23 | INFO | Train Epoch: 9 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.17879 (0.19963) Boundary_loss: 0.013898 (0.013901) Loss: 0.19269 (0.21353) +2025-09-14,18:14:29 | INFO | Train Epoch: 9 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.19710 (0.19962) Boundary_loss: 0.013899 (0.013901) Loss: 0.21100 (0.21352) +2025-09-14,18:15:35 | INFO | Train Epoch: 9 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.26361 (0.19985) Boundary_loss: 0.013904 (0.013901) Loss: 0.27751 (0.21375) +2025-09-14,18:16:41 | INFO | Train Epoch: 9 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.19114 (0.19982) Boundary_loss: 0.013900 (0.013901) Loss: 0.20504 (0.21372) +2025-09-14,18:17:47 | INFO | Train Epoch: 9 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.20411 (0.19983) Boundary_loss: 0.013899 (0.013901) Loss: 0.21801 (0.21373) +2025-09-14,18:18:53 | INFO | Train Epoch: 9 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23415 (0.19995) Boundary_loss: 0.013900 (0.013901) Loss: 0.24805 (0.21386) +2025-09-14,18:19:59 | INFO | Train Epoch: 9 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.20601 (0.19998) Boundary_loss: 0.013904 (0.013901) Loss: 0.21991 (0.21388) +2025-09-14,18:21:05 | INFO | Train Epoch: 9 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.21156 (0.20002) Boundary_loss: 0.013898 (0.013901) Loss: 0.22546 (0.21392) +2025-09-14,18:22:11 | INFO | Train Epoch: 9 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.20788 (0.20004) Boundary_loss: 0.013898 (0.013901) Loss: 0.22178 (0.21395) +2025-09-14,18:23:17 | INFO | Train Epoch: 9 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21005 (0.20008) Boundary_loss: 0.013897 (0.013901) Loss: 0.22395 (0.21398) +2025-09-14,18:24:23 | INFO | Train Epoch: 9 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.17627 (0.20000) Boundary_loss: 0.013898 (0.013901) Loss: 0.19017 (0.21390) +2025-09-14,18:25:29 | INFO | Train Epoch: 9 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.18244 (0.19994) Boundary_loss: 0.013901 (0.013901) Loss: 0.19634 (0.21384) +2025-09-14,18:26:35 | INFO | Train Epoch: 9 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.18422 (0.19988) Boundary_loss: 0.013901 (0.013901) Loss: 0.19812 (0.21378) +2025-09-14,18:27:41 | INFO | Train Epoch: 9 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.21172 (0.19992) Boundary_loss: 0.013900 (0.013901) Loss: 0.22562 (0.21382) +2025-09-14,18:28:47 | INFO | Train Epoch: 9 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.21736 (0.19998) Boundary_loss: 0.013900 (0.013901) Loss: 0.23126 (0.21388) +2025-09-14,18:29:53 | INFO | Train Epoch: 9 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.26587 (0.20021) Boundary_loss: 0.013901 (0.013901) Loss: 0.27978 (0.21411) +2025-09-14,18:30:59 | INFO | Train Epoch: 9 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15029 (0.20004) Boundary_loss: 0.013900 (0.013901) Loss: 0.16419 (0.21394) +2025-09-14,18:32:05 | INFO | Train Epoch: 9 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.20032 (0.20004) Boundary_loss: 0.013900 (0.013901) Loss: 0.21422 (0.21394) +2025-09-14,18:33:11 | INFO | Train Epoch: 9 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16868 (0.19993) Boundary_loss: 0.013899 (0.013901) Loss: 0.18258 (0.21383) +2025-09-14,18:34:17 | INFO | Train Epoch: 9 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.17713 (0.19985) Boundary_loss: 0.013901 (0.013901) Loss: 0.19103 (0.21375) +2025-09-14,18:35:23 | INFO | Train Epoch: 9 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.18930 (0.19982) Boundary_loss: 0.013898 (0.013901) Loss: 0.20320 (0.21372) +2025-09-14,18:36:29 | INFO | Train Epoch: 9 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.23944 (0.19995) Boundary_loss: 0.013900 (0.013901) Loss: 0.25334 (0.21385) +2025-09-14,18:37:35 | INFO | Train Epoch: 9 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21064 (0.19999) Boundary_loss: 0.013898 (0.013901) Loss: 0.22454 (0.21389) +2025-09-14,18:38:41 | INFO | Train Epoch: 9 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.19217 (0.19996) Boundary_loss: 0.013904 (0.013901) Loss: 0.20607 (0.21386) +2025-09-14,18:39:47 | INFO | Train Epoch: 9 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.22023 (0.20003) Boundary_loss: 0.013898 (0.013901) Loss: 0.23413 (0.21393) +2025-09-14,18:40:53 | INFO | Train Epoch: 9 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19745 (0.20002) Boundary_loss: 0.013899 (0.013901) Loss: 0.21135 (0.21392) +2025-09-14,18:41:59 | INFO | Train Epoch: 9 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.18974 (0.19999) Boundary_loss: 0.013900 (0.013901) Loss: 0.20364 (0.21389) +2025-09-14,18:43:05 | INFO | Train Epoch: 9 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.14987 (0.19982) Boundary_loss: 0.013898 (0.013901) Loss: 0.16377 (0.21372) +2025-09-14,18:44:11 | INFO | Train Epoch: 9 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.14247 (0.19963) Boundary_loss: 0.013902 (0.013901) Loss: 0.15637 (0.21353) +2025-09-14,18:45:17 | INFO | Train Epoch: 9 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21488 (0.19968) Boundary_loss: 0.013896 (0.013901) Loss: 0.22877 (0.21358) +2025-09-14,18:46:23 | INFO | Train Epoch: 9 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17752 (0.19961) Boundary_loss: 0.013900 (0.013901) Loss: 0.19142 (0.21351) +2025-09-14,18:47:29 | INFO | Train Epoch: 9 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15172 (0.19945) Boundary_loss: 0.013899 (0.013901) Loss: 0.16562 (0.21335) +2025-09-14,18:48:35 | INFO | Train Epoch: 9 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.21252 (0.19950) Boundary_loss: 0.013899 (0.013901) Loss: 0.22642 (0.21340) +2025-09-14,18:49:41 | INFO | Train Epoch: 9 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.25658 (0.19968) Boundary_loss: 0.013898 (0.013901) Loss: 0.27047 (0.21358) +2025-09-14,18:50:46 | INFO | Train Epoch: 9 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.17528 (0.19960) Boundary_loss: 0.013897 (0.013901) Loss: 0.18918 (0.21350) +2025-09-14,18:51:52 | INFO | Train Epoch: 9 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18244 (0.19955) Boundary_loss: 0.013899 (0.013901) Loss: 0.19633 (0.21345) +2025-09-14,18:52:58 | INFO | Train Epoch: 9 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17288 (0.19946) Boundary_loss: 0.013899 (0.013901) Loss: 0.18678 (0.21336) +2025-09-14,18:54:04 | INFO | Train Epoch: 9 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.22905 (0.19956) Boundary_loss: 0.013900 (0.013901) Loss: 0.24295 (0.21346) +2025-09-14,18:55:10 | INFO | Train Epoch: 9 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.14549 (0.19938) Boundary_loss: 0.013898 (0.013901) Loss: 0.15939 (0.21328) +2025-09-14,18:56:16 | INFO | Train Epoch: 9 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.16570 (0.19928) Boundary_loss: 0.013904 (0.013901) Loss: 0.17960 (0.21318) +2025-09-14,18:57:22 | INFO | Train Epoch: 9 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.21753 (0.19934) Boundary_loss: 0.013900 (0.013901) Loss: 0.23143 (0.21324) +2025-09-14,18:58:28 | INFO | Train Epoch: 9 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17157 (0.19925) Boundary_loss: 0.013897 (0.013901) Loss: 0.18547 (0.21315) +2025-09-14,18:59:34 | INFO | Train Epoch: 9 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.22031 (0.19931) Boundary_loss: 0.013898 (0.013901) Loss: 0.23420 (0.21321) +2025-09-14,19:00:40 | INFO | Train Epoch: 9 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.14082 (0.19913) Boundary_loss: 0.013898 (0.013901) Loss: 0.15472 (0.21303) +2025-09-14,19:01:46 | INFO | Train Epoch: 9 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.17120 (0.19904) Boundary_loss: 0.013902 (0.013901) Loss: 0.18510 (0.21294) +2025-09-14,19:02:52 | INFO | Train Epoch: 9 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.27317 (0.19927) Boundary_loss: 0.013904 (0.013901) Loss: 0.28708 (0.21317) +2025-09-14,19:03:58 | INFO | Train Epoch: 9 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20567 (0.19929) Boundary_loss: 0.013900 (0.013901) Loss: 0.21957 (0.21319) +2025-09-14,19:05:04 | INFO | Train Epoch: 9 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.16535 (0.19919) Boundary_loss: 0.013896 (0.013901) Loss: 0.17924 (0.21309) +2025-09-14,19:06:10 | INFO | Train Epoch: 9 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.16929 (0.19910) Boundary_loss: 0.013902 (0.013901) Loss: 0.18319 (0.21300) +2025-09-14,19:07:16 | INFO | Train Epoch: 9 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.20806 (0.19912) Boundary_loss: 0.013899 (0.013901) Loss: 0.22196 (0.21302) +2025-09-14,19:08:22 | INFO | Train Epoch: 9 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.14814 (0.19897) Boundary_loss: 0.013899 (0.013901) Loss: 0.16204 (0.21287) +2025-09-14,19:09:28 | INFO | Train Epoch: 9 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.18735 (0.19893) Boundary_loss: 0.013898 (0.013901) Loss: 0.20125 (0.21283) +2025-09-14,19:10:34 | INFO | Train Epoch: 9 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.15955 (0.19881) Boundary_loss: 0.013900 (0.013901) Loss: 0.17345 (0.21271) +2025-09-14,19:11:40 | INFO | Train Epoch: 9 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17873 (0.19875) Boundary_loss: 0.013899 (0.013901) Loss: 0.19263 (0.21265) +2025-09-14,19:12:46 | INFO | Train Epoch: 9 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.27702 (0.19899) Boundary_loss: 0.013897 (0.013901) Loss: 0.29091 (0.21289) +2025-09-14,19:13:51 | INFO | Train Epoch: 9 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.17796 (0.19892) Boundary_loss: 0.013899 (0.013901) Loss: 0.19186 (0.21283) +2025-09-14,19:14:57 | INFO | Train Epoch: 9 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.18917 (0.19890) Boundary_loss: 0.013899 (0.013901) Loss: 0.20307 (0.21280) +2025-09-14,19:16:03 | INFO | Train Epoch: 9 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.21320 (0.19894) Boundary_loss: 0.013898 (0.013901) Loss: 0.22710 (0.21284) +2025-09-14,19:17:09 | INFO | Train Epoch: 9 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.20895 (0.19897) Boundary_loss: 0.013898 (0.013900) Loss: 0.22285 (0.21287) +2025-09-14,19:18:15 | INFO | Train Epoch: 9 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.19547 (0.19896) Boundary_loss: 0.013900 (0.013900) Loss: 0.20937 (0.21286) +2025-09-14,19:19:21 | INFO | Train Epoch: 9 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.14736 (0.19880) Boundary_loss: 0.013901 (0.013900) Loss: 0.16126 (0.21270) +2025-09-14,19:20:27 | INFO | Train Epoch: 9 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.21366 (0.19885) Boundary_loss: 0.013895 (0.013900) Loss: 0.22755 (0.21275) +2025-09-14,19:21:33 | INFO | Train Epoch: 9 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18454 (0.19881) Boundary_loss: 0.013898 (0.013900) Loss: 0.19844 (0.21271) +2025-09-14,19:22:39 | INFO | Train Epoch: 9 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13734 (0.19862) Boundary_loss: 0.013899 (0.013900) Loss: 0.15124 (0.21253) +2025-09-14,19:23:45 | INFO | Train Epoch: 9 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.27402 (0.19885) Boundary_loss: 0.013900 (0.013900) Loss: 0.28792 (0.21275) +2025-09-14,19:24:51 | INFO | Train Epoch: 9 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.25392 (0.19901) Boundary_loss: 0.013899 (0.013900) Loss: 0.26782 (0.21291) +2025-09-14,19:25:57 | INFO | Train Epoch: 9 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.15654 (0.19888) Boundary_loss: 0.013901 (0.013900) Loss: 0.17044 (0.21278) +2025-09-14,19:27:03 | INFO | Train Epoch: 9 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16198 (0.19878) Boundary_loss: 0.013899 (0.013900) Loss: 0.17588 (0.21268) +2025-09-14,19:28:09 | INFO | Train Epoch: 9 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.24801 (0.19892) Boundary_loss: 0.013901 (0.013900) Loss: 0.26191 (0.21282) +2025-09-14,19:29:15 | INFO | Train Epoch: 9 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.19658 (0.19891) Boundary_loss: 0.013897 (0.013900) Loss: 0.21048 (0.21281) +2025-09-14,19:30:21 | INFO | Train Epoch: 9 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.15737 (0.19879) Boundary_loss: 0.013899 (0.013900) Loss: 0.17127 (0.21269) +2025-09-14,19:31:27 | INFO | Train Epoch: 9 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.21157 (0.19883) Boundary_loss: 0.013899 (0.013900) Loss: 0.22546 (0.21273) +2025-09-14,19:32:33 | INFO | Train Epoch: 9 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15254 (0.19870) Boundary_loss: 0.013899 (0.013900) Loss: 0.16644 (0.21260) +2025-09-14,19:33:39 | INFO | Train Epoch: 9 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.18419 (0.19865) Boundary_loss: 0.013898 (0.013900) Loss: 0.19809 (0.21256) +2025-09-14,19:34:45 | INFO | Train Epoch: 9 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.21109 (0.19869) Boundary_loss: 0.013898 (0.013900) Loss: 0.22499 (0.21259) +2025-09-14,19:35:51 | INFO | Train Epoch: 9 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16824 (0.19860) Boundary_loss: 0.013900 (0.013900) Loss: 0.18213 (0.21250) +2025-09-14,19:36:57 | INFO | Train Epoch: 9 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.19434 (0.19859) Boundary_loss: 0.013899 (0.013900) Loss: 0.20824 (0.21249) +2025-09-14,19:38:03 | INFO | Train Epoch: 9 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.21610 (0.19864) Boundary_loss: 0.013898 (0.013900) Loss: 0.23000 (0.21254) +2025-09-14,19:39:09 | INFO | Train Epoch: 9 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.23059 (0.19873) Boundary_loss: 0.013899 (0.013900) Loss: 0.24449 (0.21263) +2025-09-14,19:40:15 | INFO | Train Epoch: 9 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.21030 (0.19876) Boundary_loss: 0.013901 (0.013900) Loss: 0.22421 (0.21266) +2025-09-14,19:41:21 | INFO | Train Epoch: 9 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.19172 (0.19874) Boundary_loss: 0.013898 (0.013900) Loss: 0.20562 (0.21264) +2025-09-14,19:42:27 | INFO | Train Epoch: 9 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.18412 (0.19870) Boundary_loss: 0.013901 (0.013900) Loss: 0.19802 (0.21260) +2025-09-14,19:43:33 | INFO | Train Epoch: 9 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.17784 (0.19864) Boundary_loss: 0.013897 (0.013900) Loss: 0.19174 (0.21255) +2025-09-14,19:44:39 | INFO | Train Epoch: 9 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.24458 (0.19877) Boundary_loss: 0.013901 (0.013900) Loss: 0.25848 (0.21267) +2025-09-14,19:45:45 | INFO | Train Epoch: 9 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.15712 (0.19866) Boundary_loss: 0.013904 (0.013900) Loss: 0.17102 (0.21256) +2025-09-14,19:46:51 | INFO | Train Epoch: 9 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.17874 (0.19860) Boundary_loss: 0.013900 (0.013900) Loss: 0.19264 (0.21250) +2025-09-14,19:47:57 | INFO | Train Epoch: 9 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.14872 (0.19846) Boundary_loss: 0.013903 (0.013900) Loss: 0.16262 (0.21236) +2025-09-14,19:49:03 | INFO | Train Epoch: 9 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.20139 (0.19847) Boundary_loss: 0.013901 (0.013900) Loss: 0.21529 (0.21237) +2025-09-14,19:50:09 | INFO | Train Epoch: 9 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19940 (0.19847) Boundary_loss: 0.013899 (0.013900) Loss: 0.21330 (0.21238) +2025-09-14,19:51:15 | INFO | Train Epoch: 9 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.19444 (0.19846) Boundary_loss: 0.013901 (0.013900) Loss: 0.20835 (0.21236) +2025-09-14,19:52:21 | INFO | Train Epoch: 9 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.18694 (0.19843) Boundary_loss: 0.013899 (0.013900) Loss: 0.20084 (0.21233) +2025-09-14,19:53:27 | INFO | Train Epoch: 9 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.16725 (0.19835) Boundary_loss: 0.013898 (0.013900) Loss: 0.18115 (0.21225) +2025-09-14,19:54:33 | INFO | Train Epoch: 9 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20778 (0.19837) Boundary_loss: 0.013898 (0.013900) Loss: 0.22168 (0.21227) +2025-09-14,19:55:39 | INFO | Train Epoch: 9 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.18451 (0.19834) Boundary_loss: 0.013901 (0.013900) Loss: 0.19841 (0.21224) +2025-09-14,19:56:45 | INFO | Train Epoch: 9 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.19399 (0.19832) Boundary_loss: 0.013900 (0.013900) Loss: 0.20789 (0.21222) +2025-09-14,19:57:51 | INFO | Train Epoch: 9 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15051 (0.19819) Boundary_loss: 0.013900 (0.013900) Loss: 0.16441 (0.21210) +2025-09-14,19:58:57 | INFO | Train Epoch: 9 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.19302 (0.19818) Boundary_loss: 0.013899 (0.013900) Loss: 0.20691 (0.21208) +2025-09-14,20:00:03 | INFO | Train Epoch: 9 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20805 (0.19821) Boundary_loss: 0.013899 (0.013900) Loss: 0.22194 (0.21211) +2025-09-14,20:01:09 | INFO | Train Epoch: 9 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.20211 (0.19822) Boundary_loss: 0.013897 (0.013900) Loss: 0.21601 (0.21212) +2025-09-14,20:02:15 | INFO | Train Epoch: 9 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.18484 (0.19818) Boundary_loss: 0.013900 (0.013900) Loss: 0.19874 (0.21208) +2025-09-14,20:03:21 | INFO | Train Epoch: 9 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19481 (0.19817) Boundary_loss: 0.013900 (0.013900) Loss: 0.20871 (0.21207) +2025-09-14,20:04:27 | INFO | Train Epoch: 9 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.13051 (0.19799) Boundary_loss: 0.013904 (0.013900) Loss: 0.14441 (0.21189) +2025-09-14,20:05:33 | INFO | Train Epoch: 9 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.19256 (0.19798) Boundary_loss: 0.013900 (0.013900) Loss: 0.20646 (0.21188) +2025-09-14,20:06:39 | INFO | Train Epoch: 9 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16808 (0.19790) Boundary_loss: 0.013897 (0.013900) Loss: 0.18198 (0.21180) +2025-09-14,20:07:45 | INFO | Train Epoch: 9 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14382 (0.19776) Boundary_loss: 0.013899 (0.013900) Loss: 0.15772 (0.21166) +2025-09-14,20:08:51 | INFO | Train Epoch: 9 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15620 (0.19765) Boundary_loss: 0.013896 (0.013900) Loss: 0.17010 (0.21155) +2025-09-14,20:09:57 | INFO | Train Epoch: 9 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.15761 (0.19754) Boundary_loss: 0.013899 (0.013900) Loss: 0.17151 (0.21144) +2025-09-14,20:11:03 | INFO | Train Epoch: 9 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.20698 (0.19757) Boundary_loss: 0.013899 (0.013900) Loss: 0.22088 (0.21147) +2025-09-14,20:12:09 | INFO | Train Epoch: 9 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.19344 (0.19756) Boundary_loss: 0.013900 (0.013900) Loss: 0.20734 (0.21146) +2025-09-14,20:13:15 | INFO | Train Epoch: 9 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.23844 (0.19766) Boundary_loss: 0.013900 (0.013900) Loss: 0.25234 (0.21156) +2025-09-14,20:14:21 | INFO | Train Epoch: 9 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.17390 (0.19760) Boundary_loss: 0.013899 (0.013900) Loss: 0.18780 (0.21150) +2025-09-14,20:15:27 | INFO | Train Epoch: 9 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.20625 (0.19762) Boundary_loss: 0.013900 (0.013900) Loss: 0.22015 (0.21153) +2025-09-14,20:16:33 | INFO | Train Epoch: 9 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21565 (0.19767) Boundary_loss: 0.013899 (0.013900) Loss: 0.22954 (0.21157) +2025-09-14,20:17:39 | INFO | Train Epoch: 9 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20947 (0.19770) Boundary_loss: 0.013899 (0.013900) Loss: 0.22337 (0.21160) +2025-09-14,20:18:45 | INFO | Train Epoch: 9 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22884 (0.19778) Boundary_loss: 0.013902 (0.013900) Loss: 0.24274 (0.21168) +2025-09-14,20:19:51 | INFO | Train Epoch: 9 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.18148 (0.19774) Boundary_loss: 0.013900 (0.013900) Loss: 0.19538 (0.21164) +2025-09-14,20:20:57 | INFO | Train Epoch: 9 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.16262 (0.19765) Boundary_loss: 0.013901 (0.013900) Loss: 0.17652 (0.21155) +2025-09-14,20:22:03 | INFO | Train Epoch: 9 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16050 (0.19756) Boundary_loss: 0.013898 (0.013900) Loss: 0.17439 (0.21146) +2025-09-14,20:23:09 | INFO | Train Epoch: 9 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.19474 (0.19755) Boundary_loss: 0.013899 (0.013900) Loss: 0.20864 (0.21145) +2025-09-14,20:24:15 | INFO | Train Epoch: 9 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.20713 (0.19757) Boundary_loss: 0.013898 (0.013900) Loss: 0.22103 (0.21147) +2025-09-14,20:25:21 | INFO | Train Epoch: 9 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.20798 (0.19760) Boundary_loss: 0.013897 (0.013900) Loss: 0.22188 (0.21150) +2025-09-14,20:26:27 | INFO | Train Epoch: 9 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.17559 (0.19754) Boundary_loss: 0.013908 (0.013900) Loss: 0.18949 (0.21144) +2025-09-14,20:27:33 | INFO | Train Epoch: 9 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.18047 (0.19750) Boundary_loss: 0.013899 (0.013900) Loss: 0.19437 (0.21140) +2025-09-14,20:28:39 | INFO | Train Epoch: 9 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19167 (0.19749) Boundary_loss: 0.013898 (0.013900) Loss: 0.20557 (0.21139) +2025-09-14,20:29:45 | INFO | Train Epoch: 9 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.17577 (0.19743) Boundary_loss: 0.013900 (0.013900) Loss: 0.18967 (0.21133) +2025-09-14,20:30:51 | INFO | Train Epoch: 9 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.19663 (0.19743) Boundary_loss: 0.013902 (0.013900) Loss: 0.21053 (0.21133) +2025-09-14,20:31:57 | INFO | Train Epoch: 9 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19292 (0.19742) Boundary_loss: 0.013900 (0.013900) Loss: 0.20682 (0.21132) +2025-09-14,20:33:03 | INFO | Train Epoch: 9 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.16878 (0.19735) Boundary_loss: 0.013900 (0.013900) Loss: 0.18268 (0.21125) +2025-09-14,20:34:09 | INFO | Train Epoch: 9 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21365 (0.19739) Boundary_loss: 0.013899 (0.013900) Loss: 0.22755 (0.21129) +2025-09-14,20:35:15 | INFO | Train Epoch: 9 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.12588 (0.19721) Boundary_loss: 0.013900 (0.013900) Loss: 0.13978 (0.21111) +2025-09-14,20:36:22 | INFO | Train Epoch: 9 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.26841 (0.19739) Boundary_loss: 0.013897 (0.013900) Loss: 0.28231 (0.21129) +2025-09-14,20:37:28 | INFO | Train Epoch: 9 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.18569 (0.19736) Boundary_loss: 0.013899 (0.013900) Loss: 0.19959 (0.21126) +2025-09-14,20:38:34 | INFO | Train Epoch: 9 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.20715 (0.19738) Boundary_loss: 0.013898 (0.013900) Loss: 0.22105 (0.21128) +2025-09-14,20:39:40 | INFO | Train Epoch: 9 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.18608 (0.19735) Boundary_loss: 0.013902 (0.013900) Loss: 0.19998 (0.21125) +2025-09-14,20:40:46 | INFO | Train Epoch: 9 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.14446 (0.19723) Boundary_loss: 0.013900 (0.013900) Loss: 0.15836 (0.21113) +2025-09-14,20:41:52 | INFO | Train Epoch: 9 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.19663 (0.19722) Boundary_loss: 0.013899 (0.013900) Loss: 0.21053 (0.21112) +2025-09-14,20:42:58 | INFO | Train Epoch: 9 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17259 (0.19716) Boundary_loss: 0.013900 (0.013900) Loss: 0.18649 (0.21106) +2025-09-14,20:44:04 | INFO | Train Epoch: 9 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13964 (0.19702) Boundary_loss: 0.013898 (0.013900) Loss: 0.15354 (0.21093) +2025-09-14,20:45:10 | INFO | Train Epoch: 9 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.17215 (0.19696) Boundary_loss: 0.013903 (0.013900) Loss: 0.18605 (0.21087) +2025-09-14,20:46:16 | INFO | Train Epoch: 9 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.19347 (0.19696) Boundary_loss: 0.013898 (0.013900) Loss: 0.20737 (0.21086) +2025-09-14,20:47:22 | INFO | Train Epoch: 9 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.16182 (0.19687) Boundary_loss: 0.013899 (0.013900) Loss: 0.17572 (0.21077) +2025-09-14,20:48:28 | INFO | Train Epoch: 9 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.17019 (0.19681) Boundary_loss: 0.013899 (0.013900) Loss: 0.18409 (0.21071) +2025-09-14,20:49:34 | INFO | Train Epoch: 9 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20461 (0.19683) Boundary_loss: 0.013899 (0.013900) Loss: 0.21850 (0.21073) +2025-09-14,20:50:40 | INFO | Train Epoch: 9 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.15099 (0.19672) Boundary_loss: 0.013905 (0.013900) Loss: 0.16489 (0.21062) +2025-09-14,20:51:46 | INFO | Train Epoch: 9 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.15937 (0.19663) Boundary_loss: 0.013899 (0.013900) Loss: 0.17327 (0.21053) +2025-09-14,20:52:52 | INFO | Train Epoch: 9 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.18121 (0.19659) Boundary_loss: 0.013899 (0.013900) Loss: 0.19511 (0.21049) +2025-09-14,20:53:58 | INFO | Train Epoch: 9 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.21408 (0.19663) Boundary_loss: 0.013899 (0.013900) Loss: 0.22798 (0.21053) +2025-09-14,20:55:04 | INFO | Train Epoch: 9 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.20205 (0.19665) Boundary_loss: 0.013898 (0.013900) Loss: 0.21595 (0.21055) +2025-09-14,20:56:10 | INFO | Train Epoch: 9 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17123 (0.19659) Boundary_loss: 0.013902 (0.013900) Loss: 0.18513 (0.21049) +2025-09-14,20:57:16 | INFO | Train Epoch: 9 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.13568 (0.19644) Boundary_loss: 0.013901 (0.013900) Loss: 0.14958 (0.21034) +2025-09-14,20:58:22 | INFO | Train Epoch: 9 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.18281 (0.19641) Boundary_loss: 0.013898 (0.013900) Loss: 0.19671 (0.21031) +2025-09-14,20:59:28 | INFO | Train Epoch: 9 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19529 (0.19641) Boundary_loss: 0.013898 (0.013900) Loss: 0.20919 (0.21031) +2025-09-14,21:00:34 | INFO | Train Epoch: 9 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16943 (0.19634) Boundary_loss: 0.013900 (0.013900) Loss: 0.18333 (0.21025) +2025-09-14,21:01:40 | INFO | Train Epoch: 9 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.24662 (0.19646) Boundary_loss: 0.013903 (0.013900) Loss: 0.26052 (0.21036) +2025-09-14,21:02:46 | INFO | Train Epoch: 9 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.13556 (0.19632) Boundary_loss: 0.013902 (0.013900) Loss: 0.14946 (0.21022) +2025-09-14,21:03:52 | INFO | Train Epoch: 9 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18239 (0.19629) Boundary_loss: 0.013899 (0.013900) Loss: 0.19629 (0.21019) +2025-09-14,21:04:58 | INFO | Train Epoch: 9 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.15623 (0.19620) Boundary_loss: 0.013900 (0.013900) Loss: 0.17013 (0.21010) +2025-09-14,21:06:04 | INFO | Train Epoch: 9 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.20344 (0.19621) Boundary_loss: 0.013899 (0.013900) Loss: 0.21734 (0.21011) +2025-09-14,21:07:10 | INFO | Train Epoch: 9 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15679 (0.19612) Boundary_loss: 0.013899 (0.013900) Loss: 0.17069 (0.21002) +2025-09-14,21:08:16 | INFO | Train Epoch: 9 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17380 (0.19607) Boundary_loss: 0.013897 (0.013900) Loss: 0.18770 (0.20997) +2025-09-14,21:09:22 | INFO | Train Epoch: 9 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.19267 (0.19606) Boundary_loss: 0.013899 (0.013900) Loss: 0.20656 (0.20996) +2025-09-14,21:10:28 | INFO | Train Epoch: 9 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.19986 (0.19607) Boundary_loss: 0.013900 (0.013900) Loss: 0.21376 (0.20997) +2025-09-14,21:11:34 | INFO | Train Epoch: 9 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.24424 (0.19618) Boundary_loss: 0.013901 (0.013900) Loss: 0.25814 (0.21008) +2025-09-14,21:12:40 | INFO | Train Epoch: 9 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.17585 (0.19613) Boundary_loss: 0.013898 (0.013900) Loss: 0.18975 (0.21003) +2025-09-14,21:13:46 | INFO | Train Epoch: 9 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.22800 (0.19621) Boundary_loss: 0.013899 (0.013900) Loss: 0.24190 (0.21011) +2025-09-14,21:14:52 | INFO | Train Epoch: 9 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.14698 (0.19610) Boundary_loss: 0.013898 (0.013900) Loss: 0.16088 (0.21000) +2025-09-14,21:15:58 | INFO | Train Epoch: 9 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.22706 (0.19617) Boundary_loss: 0.013902 (0.013900) Loss: 0.24096 (0.21007) +2025-09-14,21:17:04 | INFO | Train Epoch: 9 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.19796 (0.19617) Boundary_loss: 0.013896 (0.013900) Loss: 0.21186 (0.21007) +2025-09-14,21:18:10 | INFO | Train Epoch: 9 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.21983 (0.19622) Boundary_loss: 0.013898 (0.013900) Loss: 0.23373 (0.21012) +2025-09-14,21:19:16 | INFO | Train Epoch: 9 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.18692 (0.19620) Boundary_loss: 0.013901 (0.013900) Loss: 0.20082 (0.21010) +2025-09-14,21:20:22 | INFO | Train Epoch: 9 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.20838 (0.19623) Boundary_loss: 0.013899 (0.013900) Loss: 0.22228 (0.21013) +2025-09-14,21:21:28 | INFO | Train Epoch: 9 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.21287 (0.19627) Boundary_loss: 0.013900 (0.013900) Loss: 0.22677 (0.21017) +2025-09-14,21:22:34 | INFO | Train Epoch: 9 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.19339 (0.19626) Boundary_loss: 0.013899 (0.013900) Loss: 0.20729 (0.21016) +2025-09-14,21:23:40 | INFO | Train Epoch: 9 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.21881 (0.19631) Boundary_loss: 0.013900 (0.013900) Loss: 0.23270 (0.21021) +2025-09-14,21:24:46 | INFO | Train Epoch: 9 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16343 (0.19624) Boundary_loss: 0.013897 (0.013900) Loss: 0.17733 (0.21014) +2025-09-14,21:25:52 | INFO | Train Epoch: 9 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.21701 (0.19628) Boundary_loss: 0.013898 (0.013900) Loss: 0.23090 (0.21018) +2025-09-14,21:26:58 | INFO | Train Epoch: 9 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.17406 (0.19623) Boundary_loss: 0.013899 (0.013900) Loss: 0.18795 (0.21013) +2025-09-14,21:28:04 | INFO | Train Epoch: 9 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.18811 (0.19622) Boundary_loss: 0.013898 (0.013900) Loss: 0.20201 (0.21012) +2025-09-14,21:29:10 | INFO | Train Epoch: 9 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.21015 (0.19625) Boundary_loss: 0.013898 (0.013900) Loss: 0.22405 (0.21015) +2025-09-14,21:30:17 | INFO | Train Epoch: 9 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.20221 (0.19626) Boundary_loss: 0.013899 (0.013900) Loss: 0.21610 (0.21016) +2025-09-14,21:31:23 | INFO | Train Epoch: 9 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.17247 (0.19621) Boundary_loss: 0.013898 (0.013900) Loss: 0.18637 (0.21011) +2025-09-14,21:32:29 | INFO | Train Epoch: 9 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14100 (0.19609) Boundary_loss: 0.013899 (0.013900) Loss: 0.15490 (0.20999) +2025-09-14,21:33:35 | INFO | Train Epoch: 9 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19117 (0.19608) Boundary_loss: 0.013900 (0.013900) Loss: 0.20507 (0.20998) +2025-09-14,21:34:41 | INFO | Train Epoch: 9 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.20191 (0.19609) Boundary_loss: 0.013901 (0.013900) Loss: 0.21581 (0.20999) +2025-09-14,21:35:47 | INFO | Train Epoch: 9 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.19282 (0.19608) Boundary_loss: 0.013898 (0.013900) Loss: 0.20672 (0.20998) +2025-09-14,21:36:53 | INFO | Train Epoch: 9 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.16300 (0.19601) Boundary_loss: 0.013901 (0.013900) Loss: 0.17690 (0.20991) +2025-09-14,21:37:59 | INFO | Train Epoch: 9 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17704 (0.19597) Boundary_loss: 0.013900 (0.013900) Loss: 0.19094 (0.20987) +2025-09-14,21:39:05 | INFO | Train Epoch: 9 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15088 (0.19587) Boundary_loss: 0.013900 (0.013900) Loss: 0.16478 (0.20977) +2025-09-14,21:40:11 | INFO | Train Epoch: 9 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.14922 (0.19577) Boundary_loss: 0.013900 (0.013900) Loss: 0.16312 (0.20967) +2025-09-14,21:41:17 | INFO | Train Epoch: 9 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17231 (0.19572) Boundary_loss: 0.013899 (0.013900) Loss: 0.18621 (0.20962) +2025-09-14,21:42:23 | INFO | Train Epoch: 9 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.18638 (0.19570) Boundary_loss: 0.013899 (0.013900) Loss: 0.20028 (0.20960) +2025-09-14,21:43:29 | INFO | Train Epoch: 9 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.17786 (0.19566) Boundary_loss: 0.013898 (0.013900) Loss: 0.19176 (0.20956) +2025-09-14,21:44:35 | INFO | Train Epoch: 9 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.21149 (0.19570) Boundary_loss: 0.013898 (0.013900) Loss: 0.22539 (0.20960) +2025-09-14,21:45:41 | INFO | Train Epoch: 9 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18419 (0.19567) Boundary_loss: 0.013899 (0.013900) Loss: 0.19809 (0.20957) +2025-09-14,21:46:47 | INFO | Train Epoch: 9 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.13636 (0.19555) Boundary_loss: 0.013900 (0.013900) Loss: 0.15026 (0.20945) +2025-09-14,21:47:53 | INFO | Train Epoch: 9 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.28216 (0.19573) Boundary_loss: 0.013902 (0.013900) Loss: 0.29606 (0.20963) +2025-09-14,21:48:59 | INFO | Train Epoch: 9 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19960 (0.19574) Boundary_loss: 0.013899 (0.013900) Loss: 0.21350 (0.20964) +2025-09-14,21:50:05 | INFO | Train Epoch: 9 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.17022 (0.19568) Boundary_loss: 0.013898 (0.013900) Loss: 0.18412 (0.20958) +2025-09-14,21:51:11 | INFO | Train Epoch: 9 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.22902 (0.19575) Boundary_loss: 0.013902 (0.013900) Loss: 0.24292 (0.20965) +2025-09-14,21:52:17 | INFO | Train Epoch: 9 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20011 (0.19576) Boundary_loss: 0.013898 (0.013900) Loss: 0.21401 (0.20966) +2025-09-14,21:53:24 | INFO | Train Epoch: 9 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.19187 (0.19575) Boundary_loss: 0.013899 (0.013900) Loss: 0.20577 (0.20966) +2025-09-14,21:54:30 | INFO | Train Epoch: 9 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.18911 (0.19574) Boundary_loss: 0.013899 (0.013900) Loss: 0.20301 (0.20964) +2025-09-14,21:55:36 | INFO | Train Epoch: 9 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.20578 (0.19576) Boundary_loss: 0.013898 (0.013900) Loss: 0.21968 (0.20966) +2025-09-14,21:56:42 | INFO | Train Epoch: 9 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.17073 (0.19571) Boundary_loss: 0.013898 (0.013900) Loss: 0.18463 (0.20961) +2025-09-14,21:57:48 | INFO | Train Epoch: 9 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.20010 (0.19572) Boundary_loss: 0.013902 (0.013900) Loss: 0.21401 (0.20962) +2025-09-14,21:58:54 | INFO | Train Epoch: 9 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.18455 (0.19570) Boundary_loss: 0.013899 (0.013900) Loss: 0.19845 (0.20960) +2025-09-14,22:00:00 | INFO | Train Epoch: 9 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.19168 (0.19569) Boundary_loss: 0.013898 (0.013900) Loss: 0.20558 (0.20959) +2025-09-14,22:01:06 | INFO | Train Epoch: 9 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.24970 (0.19580) Boundary_loss: 0.013901 (0.013900) Loss: 0.26360 (0.20970) +2025-09-14,22:02:12 | INFO | Train Epoch: 9 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.25253 (0.19592) Boundary_loss: 0.013900 (0.013900) Loss: 0.26643 (0.20982) +2025-09-14,22:03:18 | INFO | Train Epoch: 9 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.18039 (0.19588) Boundary_loss: 0.013901 (0.013900) Loss: 0.19429 (0.20978) +2025-09-14,22:04:24 | INFO | Train Epoch: 9 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.17548 (0.19584) Boundary_loss: 0.013899 (0.013900) Loss: 0.18938 (0.20974) +2025-09-14,22:05:30 | INFO | Train Epoch: 9 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20371 (0.19586) Boundary_loss: 0.013898 (0.013900) Loss: 0.21761 (0.20976) +2025-09-14,22:06:36 | INFO | Train Epoch: 9 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17521 (0.19582) Boundary_loss: 0.013898 (0.013900) Loss: 0.18911 (0.20972) +2025-09-14,22:07:42 | INFO | Train Epoch: 9 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.19634 (0.19582) Boundary_loss: 0.013898 (0.013900) Loss: 0.21023 (0.20972) +2025-09-14,22:08:48 | INFO | Train Epoch: 9 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.19115 (0.19581) Boundary_loss: 0.013901 (0.013900) Loss: 0.20505 (0.20971) +2025-09-14,22:09:54 | INFO | Train Epoch: 9 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.17506 (0.19577) Boundary_loss: 0.013901 (0.013900) Loss: 0.18896 (0.20967) +2025-09-14,22:11:00 | INFO | Train Epoch: 9 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.15525 (0.19568) Boundary_loss: 0.013900 (0.013900) Loss: 0.16915 (0.20958) +2025-09-14,22:12:06 | INFO | Train Epoch: 9 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.20260 (0.19570) Boundary_loss: 0.013899 (0.013900) Loss: 0.21650 (0.20960) +2025-09-14,22:13:12 | INFO | Train Epoch: 9 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.21339 (0.19573) Boundary_loss: 0.013898 (0.013900) Loss: 0.22729 (0.20963) +2025-09-14,22:14:18 | INFO | Train Epoch: 9 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.18308 (0.19571) Boundary_loss: 0.013899 (0.013900) Loss: 0.19698 (0.20961) +2025-09-14,22:15:24 | INFO | Train Epoch: 9 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23200 (0.19578) Boundary_loss: 0.013896 (0.013900) Loss: 0.24590 (0.20968) +2025-09-14,22:16:30 | INFO | Train Epoch: 9 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.21012 (0.19581) Boundary_loss: 0.013900 (0.013900) Loss: 0.22402 (0.20971) +2025-09-14,22:17:36 | INFO | Train Epoch: 9 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.18586 (0.19579) Boundary_loss: 0.013900 (0.013900) Loss: 0.19976 (0.20969) +2025-09-14,22:18:42 | INFO | Train Epoch: 9 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20301 (0.19580) Boundary_loss: 0.013897 (0.013900) Loss: 0.21691 (0.20970) +2025-09-14,22:19:49 | INFO | Train Epoch: 9 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.17669 (0.19577) Boundary_loss: 0.013900 (0.013900) Loss: 0.19059 (0.20967) +2025-09-14,22:20:55 | INFO | Train Epoch: 9 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.22604 (0.19583) Boundary_loss: 0.013901 (0.013900) Loss: 0.23994 (0.20973) +2025-09-14,22:22:01 | INFO | Train Epoch: 9 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17094 (0.19578) Boundary_loss: 0.013898 (0.013900) Loss: 0.18484 (0.20968) +2025-09-14,22:23:07 | INFO | Train Epoch: 9 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.13714 (0.19566) Boundary_loss: 0.013900 (0.013900) Loss: 0.15104 (0.20956) +2025-09-14,22:24:13 | INFO | Train Epoch: 9 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18105 (0.19563) Boundary_loss: 0.013900 (0.013900) Loss: 0.19495 (0.20953) +2025-09-14,22:25:19 | INFO | Train Epoch: 9 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.20876 (0.19566) Boundary_loss: 0.013899 (0.013900) Loss: 0.22265 (0.20956) +2025-09-14,22:26:25 | INFO | Train Epoch: 9 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.22701 (0.19572) Boundary_loss: 0.013899 (0.013900) Loss: 0.24091 (0.20962) +2025-09-14,22:27:31 | INFO | Train Epoch: 9 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.11086 (0.19555) Boundary_loss: 0.013901 (0.013900) Loss: 0.12476 (0.20945) +2025-09-14,22:28:37 | INFO | Train Epoch: 9 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.16851 (0.19550) Boundary_loss: 0.013898 (0.013900) Loss: 0.18240 (0.20940) +2025-09-14,22:29:43 | INFO | Train Epoch: 9 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19879 (0.19550) Boundary_loss: 0.013897 (0.013900) Loss: 0.21269 (0.20940) +2025-09-14,22:30:49 | INFO | Train Epoch: 9 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.22554 (0.19556) Boundary_loss: 0.013898 (0.013900) Loss: 0.23944 (0.20946) +2025-09-14,22:31:55 | INFO | Train Epoch: 9 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.20043 (0.19557) Boundary_loss: 0.013898 (0.013900) Loss: 0.21433 (0.20947) +2025-09-14,22:33:01 | INFO | Train Epoch: 9 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.14295 (0.19547) Boundary_loss: 0.013899 (0.013900) Loss: 0.15685 (0.20937) +2025-09-14,22:34:07 | INFO | Train Epoch: 9 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.17957 (0.19544) Boundary_loss: 0.013897 (0.013900) Loss: 0.19346 (0.20934) +2025-09-14,22:35:13 | INFO | Train Epoch: 9 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.18725 (0.19542) Boundary_loss: 0.013901 (0.013900) Loss: 0.20115 (0.20932) +2025-09-14,22:36:19 | INFO | Train Epoch: 9 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23909 (0.19551) Boundary_loss: 0.013898 (0.013900) Loss: 0.25298 (0.20941) +2025-09-14,22:37:22 | INFO | Train Epoch: 9 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20380 (0.19552) Boundary_loss: 0.013898 (0.013900) Loss: 0.21770 (0.20942) +2025-09-14,22:37:22 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,22:37:22 | INFO | [Epoch 9] Average Step Time: 0.662s | Average GPU Memory: 30.9 GB +2025-09-14,22:37:22 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,22:37:22 | INFO | Starting zero-shot imagenet. +2025-09-14,22:37:22 | INFO | Building zero-shot classifier +2025-09-14,22:37:31 | INFO | Using classifier +2025-09-14,22:38:13 | INFO | Finished zero-shot imagenet. +2025-09-14,22:38:13 | INFO | Eval Epoch: 10 imagenet-zeroshot-val-top1: 0.3071 imagenet-zeroshot-val-top5: 0.5723 +2025-09-14,22:38:14 | INFO | Start epoch 10 +2025-09-14,22:38:17 | INFO | Train Epoch: 10 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.12640 (0.12640) Boundary_loss: 0.013899 (0.013899) Loss: 0.14030 (0.14030) +2025-09-14,22:39:22 | INFO | Train Epoch: 10 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11874 (0.12257) Boundary_loss: 0.013897 (0.013898) Loss: 0.13264 (0.13647) +2025-09-14,22:40:28 | INFO | Train Epoch: 10 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.18848 (0.14454) Boundary_loss: 0.013900 (0.013899) Loss: 0.20238 (0.15844) +2025-09-14,22:41:34 | INFO | Train Epoch: 10 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.14518 (0.14470) Boundary_loss: 0.013902 (0.013899) Loss: 0.15908 (0.15860) +2025-09-14,22:42:40 | INFO | Train Epoch: 10 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16738 (0.14924) Boundary_loss: 0.013898 (0.013899) Loss: 0.18128 (0.16313) +2025-09-14,22:43:45 | INFO | Train Epoch: 10 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.13751 (0.14728) Boundary_loss: 0.013899 (0.013899) Loss: 0.15141 (0.16118) +2025-09-14,22:44:51 | INFO | Train Epoch: 10 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16687 (0.15008) Boundary_loss: 0.013899 (0.013899) Loss: 0.18077 (0.16398) +2025-09-14,22:45:57 | INFO | Train Epoch: 10 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13294 (0.14794) Boundary_loss: 0.013898 (0.013899) Loss: 0.14684 (0.16184) +2025-09-14,22:47:03 | INFO | Train Epoch: 10 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.15637 (0.14887) Boundary_loss: 0.013905 (0.013900) Loss: 0.17027 (0.16277) +2025-09-14,22:48:08 | INFO | Train Epoch: 10 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15234 (0.14922) Boundary_loss: 0.013899 (0.013900) Loss: 0.16624 (0.16312) +2025-09-14,22:49:14 | INFO | Train Epoch: 10 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14645 (0.14897) Boundary_loss: 0.013900 (0.013900) Loss: 0.16035 (0.16287) +2025-09-14,22:50:20 | INFO | Train Epoch: 10 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.15841 (0.14976) Boundary_loss: 0.013901 (0.013900) Loss: 0.17231 (0.16366) +2025-09-14,22:51:26 | INFO | Train Epoch: 10 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18475 (0.15245) Boundary_loss: 0.013900 (0.013900) Loss: 0.19865 (0.16635) +2025-09-14,22:52:31 | INFO | Train Epoch: 10 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.17042 (0.15373) Boundary_loss: 0.013898 (0.013900) Loss: 0.18432 (0.16763) +2025-09-14,22:53:37 | INFO | Train Epoch: 10 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20662 (0.15726) Boundary_loss: 0.013897 (0.013900) Loss: 0.22052 (0.17116) +2025-09-14,22:54:43 | INFO | Train Epoch: 10 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.13408 (0.15581) Boundary_loss: 0.013899 (0.013899) Loss: 0.14798 (0.16971) +2025-09-14,22:55:49 | INFO | Train Epoch: 10 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.19362 (0.15803) Boundary_loss: 0.013897 (0.013899) Loss: 0.20752 (0.17193) +2025-09-14,22:56:54 | INFO | Train Epoch: 10 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.12613 (0.15626) Boundary_loss: 0.013898 (0.013899) Loss: 0.14003 (0.17016) +2025-09-14,22:58:00 | INFO | Train Epoch: 10 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16039 (0.15648) Boundary_loss: 0.013898 (0.013899) Loss: 0.17429 (0.17038) +2025-09-14,22:59:06 | INFO | Train Epoch: 10 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.14093 (0.15570) Boundary_loss: 0.013898 (0.013899) Loss: 0.15483 (0.16960) +2025-09-14,23:00:12 | INFO | Train Epoch: 10 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.17483 (0.15661) Boundary_loss: 0.013898 (0.013899) Loss: 0.18873 (0.17051) +2025-09-14,23:01:18 | INFO | Train Epoch: 10 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.21826 (0.15941) Boundary_loss: 0.013901 (0.013899) Loss: 0.23217 (0.17331) +2025-09-14,23:02:23 | INFO | Train Epoch: 10 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.14715 (0.15888) Boundary_loss: 0.013900 (0.013899) Loss: 0.16105 (0.17278) +2025-09-14,23:03:29 | INFO | Train Epoch: 10 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14018 (0.15810) Boundary_loss: 0.013898 (0.013899) Loss: 0.15408 (0.17200) +2025-09-14,23:04:35 | INFO | Train Epoch: 10 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12114 (0.15662) Boundary_loss: 0.013897 (0.013899) Loss: 0.13503 (0.17052) +2025-09-14,23:05:41 | INFO | Train Epoch: 10 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.13508 (0.15579) Boundary_loss: 0.013899 (0.013899) Loss: 0.14898 (0.16969) +2025-09-14,23:06:46 | INFO | Train Epoch: 10 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.14262 (0.15531) Boundary_loss: 0.013899 (0.013899) Loss: 0.15652 (0.16921) +2025-09-14,23:07:52 | INFO | Train Epoch: 10 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.17998 (0.15619) Boundary_loss: 0.013898 (0.013899) Loss: 0.19388 (0.17009) +2025-09-14,23:08:58 | INFO | Train Epoch: 10 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18434 (0.15716) Boundary_loss: 0.013898 (0.013899) Loss: 0.19824 (0.17106) +2025-09-14,23:10:04 | INFO | Train Epoch: 10 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11099 (0.15562) Boundary_loss: 0.013902 (0.013899) Loss: 0.12489 (0.16952) +2025-09-14,23:11:10 | INFO | Train Epoch: 10 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.12687 (0.15469) Boundary_loss: 0.013900 (0.013899) Loss: 0.14077 (0.16859) +2025-09-14,23:12:15 | INFO | Train Epoch: 10 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17179 (0.15523) Boundary_loss: 0.013899 (0.013899) Loss: 0.18569 (0.16913) +2025-09-14,23:13:21 | INFO | Train Epoch: 10 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.23180 (0.15755) Boundary_loss: 0.013900 (0.013899) Loss: 0.24570 (0.17145) +2025-09-14,23:14:27 | INFO | Train Epoch: 10 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.17177 (0.15796) Boundary_loss: 0.013897 (0.013899) Loss: 0.18567 (0.17186) +2025-09-14,23:15:33 | INFO | Train Epoch: 10 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.17602 (0.15848) Boundary_loss: 0.013902 (0.013899) Loss: 0.18992 (0.17238) +2025-09-14,23:16:39 | INFO | Train Epoch: 10 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.15980 (0.15852) Boundary_loss: 0.013899 (0.013899) Loss: 0.17369 (0.17242) +2025-09-14,23:17:44 | INFO | Train Epoch: 10 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.20068 (0.15966) Boundary_loss: 0.013900 (0.013899) Loss: 0.21458 (0.17356) +2025-09-14,23:18:50 | INFO | Train Epoch: 10 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.15161 (0.15944) Boundary_loss: 0.013901 (0.013899) Loss: 0.16551 (0.17334) +2025-09-14,23:19:56 | INFO | Train Epoch: 10 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.23803 (0.16146) Boundary_loss: 0.013902 (0.013899) Loss: 0.25193 (0.17536) +2025-09-14,23:21:02 | INFO | Train Epoch: 10 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14961 (0.16116) Boundary_loss: 0.013898 (0.013899) Loss: 0.16351 (0.17506) +2025-09-14,23:22:08 | INFO | Train Epoch: 10 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.19631 (0.16202) Boundary_loss: 0.013901 (0.013899) Loss: 0.21022 (0.17592) +2025-09-14,23:23:13 | INFO | Train Epoch: 10 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.18733 (0.16262) Boundary_loss: 0.013897 (0.013899) Loss: 0.20122 (0.17652) +2025-09-14,23:24:19 | INFO | Train Epoch: 10 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.15290 (0.16240) Boundary_loss: 0.013898 (0.013899) Loss: 0.16680 (0.17630) +2025-09-14,23:25:25 | INFO | Train Epoch: 10 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15153 (0.16215) Boundary_loss: 0.013899 (0.013899) Loss: 0.16543 (0.17605) +2025-09-14,23:26:31 | INFO | Train Epoch: 10 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18054 (0.16256) Boundary_loss: 0.013897 (0.013899) Loss: 0.19443 (0.17646) +2025-09-14,23:27:37 | INFO | Train Epoch: 10 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14852 (0.16225) Boundary_loss: 0.013898 (0.013899) Loss: 0.16242 (0.17615) +2025-09-14,23:28:42 | INFO | Train Epoch: 10 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.17500 (0.16252) Boundary_loss: 0.013897 (0.013899) Loss: 0.18890 (0.17642) +2025-09-14,23:29:48 | INFO | Train Epoch: 10 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.14683 (0.16220) Boundary_loss: 0.013898 (0.013899) Loss: 0.16073 (0.17610) +2025-09-14,23:30:54 | INFO | Train Epoch: 10 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15506 (0.16205) Boundary_loss: 0.013900 (0.013899) Loss: 0.16896 (0.17595) +2025-09-14,23:32:00 | INFO | Train Epoch: 10 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11548 (0.16112) Boundary_loss: 0.013899 (0.013899) Loss: 0.12938 (0.17502) +2025-09-14,23:33:06 | INFO | Train Epoch: 10 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.17655 (0.16142) Boundary_loss: 0.013898 (0.013899) Loss: 0.19045 (0.17532) +2025-09-14,23:34:12 | INFO | Train Epoch: 10 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17244 (0.16164) Boundary_loss: 0.013898 (0.013899) Loss: 0.18634 (0.17553) +2025-09-14,23:35:17 | INFO | Train Epoch: 10 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12430 (0.16093) Boundary_loss: 0.013898 (0.013899) Loss: 0.13820 (0.17483) +2025-09-14,23:36:23 | INFO | Train Epoch: 10 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18070 (0.16130) Boundary_loss: 0.013900 (0.013899) Loss: 0.19460 (0.17520) +2025-09-14,23:37:29 | INFO | Train Epoch: 10 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.11819 (0.16051) Boundary_loss: 0.013900 (0.013899) Loss: 0.13209 (0.17441) +2025-09-14,23:38:35 | INFO | Train Epoch: 10 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.16870 (0.16066) Boundary_loss: 0.013901 (0.013899) Loss: 0.18260 (0.17456) +2025-09-14,23:39:41 | INFO | Train Epoch: 10 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.13745 (0.16025) Boundary_loss: 0.013898 (0.013899) Loss: 0.15135 (0.17415) +2025-09-14,23:40:47 | INFO | Train Epoch: 10 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.12296 (0.15961) Boundary_loss: 0.013900 (0.013899) Loss: 0.13686 (0.17351) +2025-09-14,23:41:52 | INFO | Train Epoch: 10 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.12930 (0.15910) Boundary_loss: 0.013902 (0.013899) Loss: 0.14320 (0.17299) +2025-09-14,23:42:58 | INFO | Train Epoch: 10 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15338 (0.15900) Boundary_loss: 0.013898 (0.013899) Loss: 0.16728 (0.17290) +2025-09-14,23:44:04 | INFO | Train Epoch: 10 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15620 (0.15895) Boundary_loss: 0.013900 (0.013899) Loss: 0.17010 (0.17285) +2025-09-14,23:45:10 | INFO | Train Epoch: 10 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.18432 (0.15936) Boundary_loss: 0.013898 (0.013899) Loss: 0.19822 (0.17326) +2025-09-14,23:46:16 | INFO | Train Epoch: 10 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17170 (0.15956) Boundary_loss: 0.013897 (0.013899) Loss: 0.18560 (0.17346) +2025-09-14,23:47:22 | INFO | Train Epoch: 10 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12302 (0.15899) Boundary_loss: 0.013899 (0.013899) Loss: 0.13692 (0.17289) +2025-09-14,23:48:27 | INFO | Train Epoch: 10 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15103 (0.15887) Boundary_loss: 0.013897 (0.013899) Loss: 0.16493 (0.17277) +2025-09-14,23:49:33 | INFO | Train Epoch: 10 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.16627 (0.15898) Boundary_loss: 0.013897 (0.013899) Loss: 0.18017 (0.17288) +2025-09-14,23:50:39 | INFO | Train Epoch: 10 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.18948 (0.15943) Boundary_loss: 0.013901 (0.013899) Loss: 0.20338 (0.17333) +2025-09-14,23:51:45 | INFO | Train Epoch: 10 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.16377 (0.15950) Boundary_loss: 0.013898 (0.013899) Loss: 0.17767 (0.17340) +2025-09-14,23:52:51 | INFO | Train Epoch: 10 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.16242 (0.15954) Boundary_loss: 0.013896 (0.013899) Loss: 0.17632 (0.17344) +2025-09-14,23:53:57 | INFO | Train Epoch: 10 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.12708 (0.15908) Boundary_loss: 0.013905 (0.013899) Loss: 0.14099 (0.17298) +2025-09-14,23:55:02 | INFO | Train Epoch: 10 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16137 (0.15911) Boundary_loss: 0.013899 (0.013899) Loss: 0.17527 (0.17301) +2025-09-14,23:56:08 | INFO | Train Epoch: 10 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11883 (0.15855) Boundary_loss: 0.013898 (0.013899) Loss: 0.13273 (0.17245) +2025-09-14,23:57:14 | INFO | Train Epoch: 10 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.15514 (0.15850) Boundary_loss: 0.013901 (0.013899) Loss: 0.16904 (0.17240) +2025-09-14,23:58:20 | INFO | Train Epoch: 10 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.16555 (0.15860) Boundary_loss: 0.013898 (0.013899) Loss: 0.17945 (0.17250) +2025-09-14,23:59:26 | INFO | Train Epoch: 10 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.16632 (0.15870) Boundary_loss: 0.013900 (0.013899) Loss: 0.18021 (0.17260) +2025-09-15,00:00:32 | INFO | Train Epoch: 10 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.15694 (0.15868) Boundary_loss: 0.013897 (0.013899) Loss: 0.17084 (0.17258) +2025-09-15,00:01:38 | INFO | Train Epoch: 10 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.19531 (0.15915) Boundary_loss: 0.013901 (0.013899) Loss: 0.20921 (0.17305) +2025-09-15,00:02:43 | INFO | Train Epoch: 10 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.16647 (0.15925) Boundary_loss: 0.013899 (0.013899) Loss: 0.18037 (0.17315) +2025-09-15,00:03:49 | INFO | Train Epoch: 10 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.20067 (0.15977) Boundary_loss: 0.013897 (0.013899) Loss: 0.21457 (0.17367) +2025-09-15,00:04:55 | INFO | Train Epoch: 10 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.15576 (0.15972) Boundary_loss: 0.013901 (0.013899) Loss: 0.16966 (0.17362) +2025-09-15,00:06:01 | INFO | Train Epoch: 10 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.20435 (0.16027) Boundary_loss: 0.013898 (0.013899) Loss: 0.21824 (0.17417) +2025-09-15,00:07:07 | INFO | Train Epoch: 10 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.13296 (0.15994) Boundary_loss: 0.013898 (0.013899) Loss: 0.14686 (0.17384) +2025-09-15,00:08:13 | INFO | Train Epoch: 10 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.18034 (0.16018) Boundary_loss: 0.013899 (0.013899) Loss: 0.19424 (0.17408) +2025-09-15,00:09:18 | INFO | Train Epoch: 10 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14996 (0.16006) Boundary_loss: 0.013899 (0.013899) Loss: 0.16386 (0.17396) +2025-09-15,00:10:24 | INFO | Train Epoch: 10 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.14617 (0.15990) Boundary_loss: 0.013899 (0.013899) Loss: 0.16007 (0.17380) +2025-09-15,00:11:30 | INFO | Train Epoch: 10 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.14828 (0.15976) Boundary_loss: 0.013902 (0.013899) Loss: 0.16218 (0.17366) +2025-09-15,00:12:36 | INFO | Train Epoch: 10 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17063 (0.15989) Boundary_loss: 0.013899 (0.013899) Loss: 0.18453 (0.17379) +2025-09-15,00:13:42 | INFO | Train Epoch: 10 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17373 (0.16005) Boundary_loss: 0.013898 (0.013899) Loss: 0.18763 (0.17395) +2025-09-15,00:14:48 | INFO | Train Epoch: 10 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.17661 (0.16023) Boundary_loss: 0.013900 (0.013899) Loss: 0.19051 (0.17413) +2025-09-15,00:15:54 | INFO | Train Epoch: 10 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12616 (0.15985) Boundary_loss: 0.013897 (0.013899) Loss: 0.14005 (0.17375) +2025-09-15,00:16:59 | INFO | Train Epoch: 10 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14592 (0.15970) Boundary_loss: 0.013900 (0.013899) Loss: 0.15982 (0.17360) +2025-09-15,00:18:05 | INFO | Train Epoch: 10 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.14082 (0.15950) Boundary_loss: 0.013897 (0.013899) Loss: 0.15471 (0.17339) +2025-09-15,00:19:11 | INFO | Train Epoch: 10 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.16302 (0.15953) Boundary_loss: 0.013899 (0.013899) Loss: 0.17692 (0.17343) +2025-09-15,00:20:17 | INFO | Train Epoch: 10 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.15422 (0.15948) Boundary_loss: 0.013900 (0.013899) Loss: 0.16812 (0.17338) +2025-09-15,00:21:23 | INFO | Train Epoch: 10 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.19441 (0.15984) Boundary_loss: 0.013898 (0.013899) Loss: 0.20831 (0.17374) +2025-09-15,00:22:29 | INFO | Train Epoch: 10 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.13526 (0.15959) Boundary_loss: 0.013900 (0.013899) Loss: 0.14916 (0.17349) +2025-09-15,00:23:35 | INFO | Train Epoch: 10 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18117 (0.15981) Boundary_loss: 0.013898 (0.013899) Loss: 0.19507 (0.17371) +2025-09-15,00:24:41 | INFO | Train Epoch: 10 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.19304 (0.16015) Boundary_loss: 0.013899 (0.013899) Loss: 0.20694 (0.17405) +2025-09-15,00:25:47 | INFO | Train Epoch: 10 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.12465 (0.15979) Boundary_loss: 0.013898 (0.013899) Loss: 0.13855 (0.17369) +2025-09-15,00:26:52 | INFO | Train Epoch: 10 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13219 (0.15952) Boundary_loss: 0.013897 (0.013899) Loss: 0.14609 (0.17341) +2025-09-15,00:27:58 | INFO | Train Epoch: 10 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15241 (0.15945) Boundary_loss: 0.013900 (0.013899) Loss: 0.16631 (0.17334) +2025-09-15,00:29:04 | INFO | Train Epoch: 10 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.14847 (0.15934) Boundary_loss: 0.013900 (0.013899) Loss: 0.16237 (0.17324) +2025-09-15,00:30:10 | INFO | Train Epoch: 10 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.12668 (0.15902) Boundary_loss: 0.013902 (0.013899) Loss: 0.14058 (0.17292) +2025-09-15,00:31:16 | INFO | Train Epoch: 10 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.13466 (0.15879) Boundary_loss: 0.013897 (0.013899) Loss: 0.14856 (0.17269) +2025-09-15,00:32:22 | INFO | Train Epoch: 10 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15030 (0.15871) Boundary_loss: 0.013897 (0.013899) Loss: 0.16419 (0.17260) +2025-09-15,00:33:27 | INFO | Train Epoch: 10 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.16071 (0.15872) Boundary_loss: 0.013898 (0.013899) Loss: 0.17461 (0.17262) +2025-09-15,00:34:33 | INFO | Train Epoch: 10 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19555 (0.15907) Boundary_loss: 0.013898 (0.013899) Loss: 0.20945 (0.17297) +2025-09-15,00:35:39 | INFO | Train Epoch: 10 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13266 (0.15882) Boundary_loss: 0.013897 (0.013899) Loss: 0.14656 (0.17272) +2025-09-15,00:36:45 | INFO | Train Epoch: 10 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.14068 (0.15866) Boundary_loss: 0.013898 (0.013899) Loss: 0.15458 (0.17256) +2025-09-15,00:37:51 | INFO | Train Epoch: 10 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12732 (0.15837) Boundary_loss: 0.013898 (0.013899) Loss: 0.14121 (0.17227) +2025-09-15,00:38:57 | INFO | Train Epoch: 10 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13219 (0.15814) Boundary_loss: 0.013898 (0.013899) Loss: 0.14609 (0.17204) +2025-09-15,00:40:03 | INFO | Train Epoch: 10 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.16159 (0.15817) Boundary_loss: 0.013900 (0.013899) Loss: 0.17549 (0.17207) +2025-09-15,00:41:09 | INFO | Train Epoch: 10 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13062 (0.15792) Boundary_loss: 0.013896 (0.013899) Loss: 0.14452 (0.17182) +2025-09-15,00:42:14 | INFO | Train Epoch: 10 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.17051 (0.15803) Boundary_loss: 0.013900 (0.013899) Loss: 0.18441 (0.17193) +2025-09-15,00:43:20 | INFO | Train Epoch: 10 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.18518 (0.15827) Boundary_loss: 0.013897 (0.013899) Loss: 0.19907 (0.17217) +2025-09-15,00:44:26 | INFO | Train Epoch: 10 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.14088 (0.15812) Boundary_loss: 0.013900 (0.013899) Loss: 0.15478 (0.17202) +2025-09-15,00:45:32 | INFO | Train Epoch: 10 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15489 (0.15809) Boundary_loss: 0.013898 (0.013899) Loss: 0.16878 (0.17199) +2025-09-15,00:46:38 | INFO | Train Epoch: 10 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13109 (0.15786) Boundary_loss: 0.013897 (0.013899) Loss: 0.14499 (0.17176) +2025-09-15,00:47:44 | INFO | Train Epoch: 10 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.18809 (0.15812) Boundary_loss: 0.013897 (0.013899) Loss: 0.20199 (0.17202) +2025-09-15,00:48:50 | INFO | Train Epoch: 10 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.15049 (0.15805) Boundary_loss: 0.013899 (0.013899) Loss: 0.16439 (0.17195) +2025-09-15,00:49:56 | INFO | Train Epoch: 10 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.15801 (0.15805) Boundary_loss: 0.013899 (0.013899) Loss: 0.17191 (0.17195) +2025-09-15,00:51:01 | INFO | Train Epoch: 10 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16152 (0.15808) Boundary_loss: 0.013900 (0.013899) Loss: 0.17542 (0.17198) +2025-09-15,00:52:07 | INFO | Train Epoch: 10 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.20228 (0.15844) Boundary_loss: 0.013900 (0.013899) Loss: 0.21618 (0.17234) +2025-09-15,00:53:13 | INFO | Train Epoch: 10 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16985 (0.15853) Boundary_loss: 0.013898 (0.013899) Loss: 0.18374 (0.17243) +2025-09-15,00:54:19 | INFO | Train Epoch: 10 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.13425 (0.15834) Boundary_loss: 0.013899 (0.013899) Loss: 0.14815 (0.17224) +2025-09-15,00:55:25 | INFO | Train Epoch: 10 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.14612 (0.15824) Boundary_loss: 0.013898 (0.013899) Loss: 0.16002 (0.17214) +2025-09-15,00:56:31 | INFO | Train Epoch: 10 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14484 (0.15814) Boundary_loss: 0.013898 (0.013899) Loss: 0.15873 (0.17204) +2025-09-15,00:57:36 | INFO | Train Epoch: 10 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16083 (0.15816) Boundary_loss: 0.013898 (0.013899) Loss: 0.17473 (0.17206) +2025-09-15,00:58:42 | INFO | Train Epoch: 10 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14600 (0.15806) Boundary_loss: 0.013901 (0.013899) Loss: 0.15990 (0.17196) +2025-09-15,00:59:48 | INFO | Train Epoch: 10 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.15670 (0.15805) Boundary_loss: 0.013898 (0.013899) Loss: 0.17060 (0.17195) +2025-09-15,01:00:54 | INFO | Train Epoch: 10 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15505 (0.15803) Boundary_loss: 0.013899 (0.013899) Loss: 0.16895 (0.17193) +2025-09-15,01:02:00 | INFO | Train Epoch: 10 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13539 (0.15786) Boundary_loss: 0.013897 (0.013899) Loss: 0.14929 (0.17176) +2025-09-15,01:03:06 | INFO | Train Epoch: 10 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14992 (0.15780) Boundary_loss: 0.013901 (0.013899) Loss: 0.16382 (0.17170) +2025-09-15,01:04:12 | INFO | Train Epoch: 10 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16225 (0.15783) Boundary_loss: 0.013900 (0.013899) Loss: 0.17615 (0.17173) +2025-09-15,01:05:17 | INFO | Train Epoch: 10 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.16629 (0.15790) Boundary_loss: 0.013898 (0.013899) Loss: 0.18018 (0.17179) +2025-09-15,01:06:23 | INFO | Train Epoch: 10 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.15179 (0.15785) Boundary_loss: 0.013898 (0.013899) Loss: 0.16569 (0.17175) +2025-09-15,01:07:29 | INFO | Train Epoch: 10 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13474 (0.15768) Boundary_loss: 0.013896 (0.013899) Loss: 0.14864 (0.17158) +2025-09-15,01:08:35 | INFO | Train Epoch: 10 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15817 (0.15769) Boundary_loss: 0.013897 (0.013899) Loss: 0.17206 (0.17158) +2025-09-15,01:09:41 | INFO | Train Epoch: 10 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16069 (0.15771) Boundary_loss: 0.013900 (0.013899) Loss: 0.17459 (0.17161) +2025-09-15,01:10:47 | INFO | Train Epoch: 10 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18010 (0.15787) Boundary_loss: 0.013897 (0.013899) Loss: 0.19399 (0.17177) +2025-09-15,01:11:53 | INFO | Train Epoch: 10 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11585 (0.15757) Boundary_loss: 0.013896 (0.013899) Loss: 0.12975 (0.17147) +2025-09-15,01:12:58 | INFO | Train Epoch: 10 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.17582 (0.15770) Boundary_loss: 0.013900 (0.013899) Loss: 0.18972 (0.17160) +2025-09-15,01:14:04 | INFO | Train Epoch: 10 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.15519 (0.15768) Boundary_loss: 0.013901 (0.013899) Loss: 0.16909 (0.17158) +2025-09-15,01:15:10 | INFO | Train Epoch: 10 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.20000 (0.15797) Boundary_loss: 0.013898 (0.013899) Loss: 0.21390 (0.17187) +2025-09-15,01:16:16 | INFO | Train Epoch: 10 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14256 (0.15787) Boundary_loss: 0.013896 (0.013899) Loss: 0.15646 (0.17177) +2025-09-15,01:17:22 | INFO | Train Epoch: 10 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19929 (0.15815) Boundary_loss: 0.013900 (0.013899) Loss: 0.21319 (0.17205) +2025-09-15,01:18:28 | INFO | Train Epoch: 10 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.11952 (0.15789) Boundary_loss: 0.013899 (0.013899) Loss: 0.13342 (0.17179) +2025-09-15,01:19:34 | INFO | Train Epoch: 10 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.14448 (0.15780) Boundary_loss: 0.013898 (0.013899) Loss: 0.15838 (0.17170) +2025-09-15,01:20:39 | INFO | Train Epoch: 10 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.19191 (0.15803) Boundary_loss: 0.013902 (0.013899) Loss: 0.20581 (0.17193) +2025-09-15,01:21:45 | INFO | Train Epoch: 10 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.12639 (0.15782) Boundary_loss: 0.013898 (0.013899) Loss: 0.14029 (0.17171) +2025-09-15,01:22:51 | INFO | Train Epoch: 10 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.14917 (0.15776) Boundary_loss: 0.013898 (0.013899) Loss: 0.16307 (0.17166) +2025-09-15,01:23:57 | INFO | Train Epoch: 10 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.12292 (0.15753) Boundary_loss: 0.013897 (0.013899) Loss: 0.13682 (0.17143) +2025-09-15,01:25:03 | INFO | Train Epoch: 10 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.14340 (0.15744) Boundary_loss: 0.013901 (0.013899) Loss: 0.15730 (0.17134) +2025-09-15,01:26:09 | INFO | Train Epoch: 10 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10877 (0.15712) Boundary_loss: 0.013899 (0.013899) Loss: 0.12267 (0.17102) +2025-09-15,01:27:15 | INFO | Train Epoch: 10 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.14179 (0.15702) Boundary_loss: 0.013901 (0.013899) Loss: 0.15569 (0.17092) +2025-09-15,01:28:20 | INFO | Train Epoch: 10 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16616 (0.15708) Boundary_loss: 0.013897 (0.013899) Loss: 0.18005 (0.17098) +2025-09-15,01:29:26 | INFO | Train Epoch: 10 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17896 (0.15722) Boundary_loss: 0.013898 (0.013899) Loss: 0.19286 (0.17112) +2025-09-15,01:30:32 | INFO | Train Epoch: 10 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.16886 (0.15729) Boundary_loss: 0.013897 (0.013899) Loss: 0.18276 (0.17119) +2025-09-15,01:31:38 | INFO | Train Epoch: 10 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.13634 (0.15716) Boundary_loss: 0.013898 (0.013899) Loss: 0.15024 (0.17106) +2025-09-15,01:32:44 | INFO | Train Epoch: 10 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14682 (0.15710) Boundary_loss: 0.013897 (0.013899) Loss: 0.16072 (0.17100) +2025-09-15,01:33:50 | INFO | Train Epoch: 10 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.10495 (0.15677) Boundary_loss: 0.013898 (0.013899) Loss: 0.11885 (0.17067) +2025-09-15,01:34:56 | INFO | Train Epoch: 10 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.15060 (0.15674) Boundary_loss: 0.013902 (0.013899) Loss: 0.16450 (0.17063) +2025-09-15,01:36:01 | INFO | Train Epoch: 10 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15309 (0.15671) Boundary_loss: 0.013897 (0.013899) Loss: 0.16698 (0.17061) +2025-09-15,01:37:07 | INFO | Train Epoch: 10 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14318 (0.15663) Boundary_loss: 0.013897 (0.013899) Loss: 0.15708 (0.17053) +2025-09-15,01:38:13 | INFO | Train Epoch: 10 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14928 (0.15659) Boundary_loss: 0.013897 (0.013899) Loss: 0.16318 (0.17048) +2025-09-15,01:39:19 | INFO | Train Epoch: 10 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.10663 (0.15628) Boundary_loss: 0.013907 (0.013899) Loss: 0.12053 (0.17018) +2025-09-15,01:40:25 | INFO | Train Epoch: 10 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.16823 (0.15636) Boundary_loss: 0.013900 (0.013899) Loss: 0.18213 (0.17026) +2025-09-15,01:41:31 | INFO | Train Epoch: 10 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.15280 (0.15634) Boundary_loss: 0.013899 (0.013899) Loss: 0.16670 (0.17023) +2025-09-15,01:42:37 | INFO | Train Epoch: 10 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.10756 (0.15605) Boundary_loss: 0.013899 (0.013899) Loss: 0.12145 (0.16995) +2025-09-15,01:43:43 | INFO | Train Epoch: 10 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.13552 (0.15593) Boundary_loss: 0.013899 (0.013899) Loss: 0.14942 (0.16982) +2025-09-15,01:44:49 | INFO | Train Epoch: 10 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.11451 (0.15568) Boundary_loss: 0.013901 (0.013899) Loss: 0.12841 (0.16958) +2025-09-15,01:45:54 | INFO | Train Epoch: 10 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11827 (0.15547) Boundary_loss: 0.013896 (0.013899) Loss: 0.13217 (0.16936) +2025-09-15,01:47:00 | INFO | Train Epoch: 10 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11331 (0.15522) Boundary_loss: 0.013900 (0.013899) Loss: 0.12721 (0.16912) +2025-09-15,01:48:06 | INFO | Train Epoch: 10 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.085578 (0.15482) Boundary_loss: 0.013904 (0.013899) Loss: 0.099482 (0.16872) +2025-09-15,01:49:12 | INFO | Train Epoch: 10 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.18832 (0.15501) Boundary_loss: 0.013899 (0.013899) Loss: 0.20222 (0.16891) +2025-09-15,01:50:18 | INFO | Train Epoch: 10 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14971 (0.15498) Boundary_loss: 0.013897 (0.013899) Loss: 0.16361 (0.16888) +2025-09-15,01:51:24 | INFO | Train Epoch: 10 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14544 (0.15493) Boundary_loss: 0.013901 (0.013899) Loss: 0.15934 (0.16883) +2025-09-15,01:52:30 | INFO | Train Epoch: 10 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.14775 (0.15489) Boundary_loss: 0.013898 (0.013899) Loss: 0.16165 (0.16879) +2025-09-15,01:53:36 | INFO | Train Epoch: 10 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16324 (0.15494) Boundary_loss: 0.013899 (0.013899) Loss: 0.17714 (0.16883) +2025-09-15,01:54:42 | INFO | Train Epoch: 10 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.22777 (0.15534) Boundary_loss: 0.013898 (0.013899) Loss: 0.24167 (0.16924) +2025-09-15,01:55:48 | INFO | Train Epoch: 10 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.16333 (0.15538) Boundary_loss: 0.013900 (0.013899) Loss: 0.17723 (0.16928) +2025-09-15,01:56:54 | INFO | Train Epoch: 10 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.13049 (0.15525) Boundary_loss: 0.013897 (0.013899) Loss: 0.14439 (0.16915) +2025-09-15,01:58:00 | INFO | Train Epoch: 10 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13796 (0.15515) Boundary_loss: 0.013897 (0.013899) Loss: 0.15186 (0.16905) +2025-09-15,01:59:05 | INFO | Train Epoch: 10 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.10819 (0.15490) Boundary_loss: 0.013897 (0.013899) Loss: 0.12208 (0.16880) +2025-09-15,02:00:11 | INFO | Train Epoch: 10 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15651 (0.15491) Boundary_loss: 0.013899 (0.013899) Loss: 0.17041 (0.16881) +2025-09-15,02:01:17 | INFO | Train Epoch: 10 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.11639 (0.15470) Boundary_loss: 0.013901 (0.013899) Loss: 0.13029 (0.16860) +2025-09-15,02:02:23 | INFO | Train Epoch: 10 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.14455 (0.15465) Boundary_loss: 0.013900 (0.013899) Loss: 0.15845 (0.16854) +2025-09-15,02:03:29 | INFO | Train Epoch: 10 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13715 (0.15455) Boundary_loss: 0.013899 (0.013899) Loss: 0.15105 (0.16845) +2025-09-15,02:04:35 | INFO | Train Epoch: 10 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.19778 (0.15478) Boundary_loss: 0.013898 (0.013899) Loss: 0.21167 (0.16868) +2025-09-15,02:05:41 | INFO | Train Epoch: 10 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16953 (0.15486) Boundary_loss: 0.013898 (0.013899) Loss: 0.18343 (0.16876) +2025-09-15,02:06:47 | INFO | Train Epoch: 10 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11604 (0.15466) Boundary_loss: 0.013896 (0.013899) Loss: 0.12994 (0.16855) +2025-09-15,02:07:53 | INFO | Train Epoch: 10 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14761 (0.15462) Boundary_loss: 0.013898 (0.013899) Loss: 0.16151 (0.16852) +2025-09-15,02:08:59 | INFO | Train Epoch: 10 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15201 (0.15461) Boundary_loss: 0.013898 (0.013899) Loss: 0.16590 (0.16850) +2025-09-15,02:10:05 | INFO | Train Epoch: 10 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.19098 (0.15479) Boundary_loss: 0.013900 (0.013899) Loss: 0.20488 (0.16869) +2025-09-15,02:11:11 | INFO | Train Epoch: 10 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16382 (0.15484) Boundary_loss: 0.013899 (0.013899) Loss: 0.17772 (0.16874) +2025-09-15,02:12:16 | INFO | Train Epoch: 10 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16638 (0.15490) Boundary_loss: 0.013896 (0.013899) Loss: 0.18028 (0.16880) +2025-09-15,02:13:22 | INFO | Train Epoch: 10 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.19038 (0.15508) Boundary_loss: 0.013898 (0.013899) Loss: 0.20428 (0.16898) +2025-09-15,02:14:28 | INFO | Train Epoch: 10 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.15377 (0.15507) Boundary_loss: 0.013898 (0.013899) Loss: 0.16767 (0.16897) +2025-09-15,02:15:34 | INFO | Train Epoch: 10 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.14479 (0.15502) Boundary_loss: 0.013898 (0.013899) Loss: 0.15868 (0.16892) +2025-09-15,02:16:40 | INFO | Train Epoch: 10 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.11930 (0.15484) Boundary_loss: 0.013897 (0.013899) Loss: 0.13320 (0.16874) +2025-09-15,02:17:46 | INFO | Train Epoch: 10 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19137 (0.15502) Boundary_loss: 0.013899 (0.013899) Loss: 0.20527 (0.16892) +2025-09-15,02:18:52 | INFO | Train Epoch: 10 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14252 (0.15496) Boundary_loss: 0.013898 (0.013899) Loss: 0.15642 (0.16886) +2025-09-15,02:19:58 | INFO | Train Epoch: 10 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14470 (0.15491) Boundary_loss: 0.013898 (0.013899) Loss: 0.15860 (0.16881) +2025-09-15,02:21:04 | INFO | Train Epoch: 10 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12935 (0.15479) Boundary_loss: 0.013899 (0.013899) Loss: 0.14325 (0.16868) +2025-09-15,02:22:10 | INFO | Train Epoch: 10 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15928 (0.15481) Boundary_loss: 0.013897 (0.013899) Loss: 0.17318 (0.16871) +2025-09-15,02:23:16 | INFO | Train Epoch: 10 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.16738 (0.15487) Boundary_loss: 0.013901 (0.013899) Loss: 0.18128 (0.16877) +2025-09-15,02:24:21 | INFO | Train Epoch: 10 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.20591 (0.15511) Boundary_loss: 0.013899 (0.013899) Loss: 0.21981 (0.16901) +2025-09-15,02:25:27 | INFO | Train Epoch: 10 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.18878 (0.15528) Boundary_loss: 0.013901 (0.013899) Loss: 0.20268 (0.16918) +2025-09-15,02:26:33 | INFO | Train Epoch: 10 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14578 (0.15523) Boundary_loss: 0.013897 (0.013899) Loss: 0.15968 (0.16913) +2025-09-15,02:27:39 | INFO | Train Epoch: 10 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17029 (0.15530) Boundary_loss: 0.013899 (0.013899) Loss: 0.18419 (0.16920) +2025-09-15,02:28:45 | INFO | Train Epoch: 10 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14705 (0.15526) Boundary_loss: 0.013900 (0.013899) Loss: 0.16095 (0.16916) +2025-09-15,02:29:51 | INFO | Train Epoch: 10 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.20282 (0.15549) Boundary_loss: 0.013895 (0.013899) Loss: 0.21671 (0.16939) +2025-09-15,02:30:57 | INFO | Train Epoch: 10 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13183 (0.15538) Boundary_loss: 0.013898 (0.013899) Loss: 0.14573 (0.16928) +2025-09-15,02:32:03 | INFO | Train Epoch: 10 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14034 (0.15531) Boundary_loss: 0.013895 (0.013899) Loss: 0.15423 (0.16921) +2025-09-15,02:33:09 | INFO | Train Epoch: 10 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.14118 (0.15524) Boundary_loss: 0.013897 (0.013899) Loss: 0.15508 (0.16914) +2025-09-15,02:34:15 | INFO | Train Epoch: 10 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10995 (0.15503) Boundary_loss: 0.013899 (0.013899) Loss: 0.12385 (0.16893) +2025-09-15,02:35:21 | INFO | Train Epoch: 10 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16980 (0.15510) Boundary_loss: 0.013898 (0.013899) Loss: 0.18369 (0.16900) +2025-09-15,02:36:27 | INFO | Train Epoch: 10 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15282 (0.15509) Boundary_loss: 0.013897 (0.013899) Loss: 0.16672 (0.16899) +2025-09-15,02:37:32 | INFO | Train Epoch: 10 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.16217 (0.15512) Boundary_loss: 0.013899 (0.013899) Loss: 0.17607 (0.16902) +2025-09-15,02:38:38 | INFO | Train Epoch: 10 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10010 (0.15487) Boundary_loss: 0.013897 (0.013899) Loss: 0.11400 (0.16877) +2025-09-15,02:39:44 | INFO | Train Epoch: 10 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16388 (0.15491) Boundary_loss: 0.013897 (0.013899) Loss: 0.17778 (0.16881) +2025-09-15,02:40:50 | INFO | Train Epoch: 10 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.17471 (0.15500) Boundary_loss: 0.013898 (0.013899) Loss: 0.18861 (0.16890) +2025-09-15,02:41:56 | INFO | Train Epoch: 10 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16068 (0.15503) Boundary_loss: 0.013898 (0.013899) Loss: 0.17457 (0.16893) +2025-09-15,02:43:02 | INFO | Train Epoch: 10 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14345 (0.15497) Boundary_loss: 0.013898 (0.013899) Loss: 0.15734 (0.16887) +2025-09-15,02:44:08 | INFO | Train Epoch: 10 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.14000 (0.15491) Boundary_loss: 0.013897 (0.013899) Loss: 0.15390 (0.16881) +2025-09-15,02:45:14 | INFO | Train Epoch: 10 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19930 (0.15510) Boundary_loss: 0.013898 (0.013899) Loss: 0.21320 (0.16900) +2025-09-15,02:46:20 | INFO | Train Epoch: 10 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.15077 (0.15509) Boundary_loss: 0.013898 (0.013899) Loss: 0.16466 (0.16898) +2025-09-15,02:47:26 | INFO | Train Epoch: 10 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17163 (0.15516) Boundary_loss: 0.013898 (0.013899) Loss: 0.18553 (0.16906) +2025-09-15,02:48:32 | INFO | Train Epoch: 10 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12456 (0.15502) Boundary_loss: 0.013902 (0.013899) Loss: 0.13846 (0.16892) +2025-09-15,02:49:38 | INFO | Train Epoch: 10 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.18777 (0.15517) Boundary_loss: 0.013898 (0.013899) Loss: 0.20167 (0.16907) +2025-09-15,02:50:43 | INFO | Train Epoch: 10 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.18376 (0.15529) Boundary_loss: 0.013897 (0.013899) Loss: 0.19766 (0.16919) +2025-09-15,02:51:49 | INFO | Train Epoch: 10 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.16075 (0.15531) Boundary_loss: 0.013901 (0.013899) Loss: 0.17465 (0.16921) +2025-09-15,02:52:55 | INFO | Train Epoch: 10 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15125 (0.15530) Boundary_loss: 0.013897 (0.013899) Loss: 0.16515 (0.16920) +2025-09-15,02:54:01 | INFO | Train Epoch: 10 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11383 (0.15512) Boundary_loss: 0.013897 (0.013899) Loss: 0.12773 (0.16902) +2025-09-15,02:55:07 | INFO | Train Epoch: 10 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13845 (0.15505) Boundary_loss: 0.013896 (0.013899) Loss: 0.15234 (0.16895) +2025-09-15,02:56:13 | INFO | Train Epoch: 10 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18053 (0.15516) Boundary_loss: 0.013897 (0.013899) Loss: 0.19442 (0.16906) +2025-09-15,02:57:19 | INFO | Train Epoch: 10 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.14848 (0.15513) Boundary_loss: 0.013900 (0.013899) Loss: 0.16238 (0.16903) +2025-09-15,02:58:25 | INFO | Train Epoch: 10 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.13745 (0.15505) Boundary_loss: 0.013899 (0.013899) Loss: 0.15135 (0.16895) +2025-09-15,02:59:31 | INFO | Train Epoch: 10 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16550 (0.15510) Boundary_loss: 0.013896 (0.013899) Loss: 0.17940 (0.16900) +2025-09-15,03:00:37 | INFO | Train Epoch: 10 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.13073 (0.15500) Boundary_loss: 0.013899 (0.013899) Loss: 0.14463 (0.16890) +2025-09-15,03:01:43 | INFO | Train Epoch: 10 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.17332 (0.15507) Boundary_loss: 0.013898 (0.013899) Loss: 0.18722 (0.16897) +2025-09-15,03:02:49 | INFO | Train Epoch: 10 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.18416 (0.15519) Boundary_loss: 0.013896 (0.013899) Loss: 0.19806 (0.16909) +2025-09-15,03:03:55 | INFO | Train Epoch: 10 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12189 (0.15506) Boundary_loss: 0.013897 (0.013899) Loss: 0.13578 (0.16895) +2025-09-15,03:05:00 | INFO | Train Epoch: 10 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.13908 (0.15499) Boundary_loss: 0.013898 (0.013899) Loss: 0.15297 (0.16889) +2025-09-15,03:06:06 | INFO | Train Epoch: 10 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.16253 (0.15502) Boundary_loss: 0.013897 (0.013899) Loss: 0.17643 (0.16892) +2025-09-15,03:07:12 | INFO | Train Epoch: 10 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13168 (0.15493) Boundary_loss: 0.013896 (0.013899) Loss: 0.14558 (0.16882) +2025-09-15,03:08:18 | INFO | Train Epoch: 10 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.19490 (0.15509) Boundary_loss: 0.013896 (0.013899) Loss: 0.20879 (0.16899) +2025-09-15,03:09:24 | INFO | Train Epoch: 10 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.17664 (0.15517) Boundary_loss: 0.013898 (0.013899) Loss: 0.19053 (0.16907) +2025-09-15,03:10:30 | INFO | Train Epoch: 10 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.18394 (0.15529) Boundary_loss: 0.013896 (0.013899) Loss: 0.19784 (0.16919) +2025-09-15,03:11:36 | INFO | Train Epoch: 10 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.13498 (0.15521) Boundary_loss: 0.013896 (0.013899) Loss: 0.14888 (0.16911) +2025-09-15,03:12:42 | INFO | Train Epoch: 10 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.13511 (0.15513) Boundary_loss: 0.013897 (0.013899) Loss: 0.14901 (0.16903) +2025-09-15,03:13:48 | INFO | Train Epoch: 10 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.18583 (0.15525) Boundary_loss: 0.013898 (0.013899) Loss: 0.19973 (0.16915) +2025-09-15,03:14:54 | INFO | Train Epoch: 10 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16016 (0.15527) Boundary_loss: 0.013897 (0.013899) Loss: 0.17406 (0.16917) +2025-09-15,03:16:00 | INFO | Train Epoch: 10 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.16172 (0.15530) Boundary_loss: 0.013898 (0.013899) Loss: 0.17562 (0.16919) +2025-09-15,03:17:06 | INFO | Train Epoch: 10 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.11144 (0.15512) Boundary_loss: 0.013898 (0.013899) Loss: 0.12534 (0.16902) +2025-09-15,03:18:12 | INFO | Train Epoch: 10 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.16662 (0.15517) Boundary_loss: 0.013899 (0.013899) Loss: 0.18052 (0.16907) +2025-09-15,03:19:17 | INFO | Train Epoch: 10 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16084 (0.15519) Boundary_loss: 0.013897 (0.013899) Loss: 0.17474 (0.16909) +2025-09-15,03:20:23 | INFO | Train Epoch: 10 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16184 (0.15522) Boundary_loss: 0.013897 (0.013899) Loss: 0.17574 (0.16912) +2025-09-15,03:21:29 | INFO | Train Epoch: 10 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11355 (0.15506) Boundary_loss: 0.013900 (0.013899) Loss: 0.12745 (0.16895) +2025-09-15,03:22:35 | INFO | Train Epoch: 10 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.13106 (0.15496) Boundary_loss: 0.013900 (0.013899) Loss: 0.14496 (0.16886) +2025-09-15,03:23:41 | INFO | Train Epoch: 10 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.16321 (0.15499) Boundary_loss: 0.013896 (0.013899) Loss: 0.17711 (0.16889) +2025-09-15,03:24:47 | INFO | Train Epoch: 10 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14620 (0.15496) Boundary_loss: 0.013898 (0.013899) Loss: 0.16009 (0.16886) +2025-09-15,03:25:53 | INFO | Train Epoch: 10 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14909 (0.15494) Boundary_loss: 0.013900 (0.013899) Loss: 0.16299 (0.16884) +2025-09-15,03:26:59 | INFO | Train Epoch: 10 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15007 (0.15492) Boundary_loss: 0.013898 (0.013899) Loss: 0.16397 (0.16882) +2025-09-15,03:28:05 | INFO | Train Epoch: 10 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.19686 (0.15508) Boundary_loss: 0.013899 (0.013899) Loss: 0.21076 (0.16898) +2025-09-15,03:29:11 | INFO | Train Epoch: 10 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.17043 (0.15514) Boundary_loss: 0.013896 (0.013899) Loss: 0.18432 (0.16904) +2025-09-15,03:30:16 | INFO | Train Epoch: 10 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13980 (0.15508) Boundary_loss: 0.013899 (0.013899) Loss: 0.15370 (0.16898) +2025-09-15,03:31:22 | INFO | Train Epoch: 10 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.093601 (0.15485) Boundary_loss: 0.013898 (0.013899) Loss: 0.10750 (0.16875) +2025-09-15,03:32:28 | INFO | Train Epoch: 10 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.14206 (0.15480) Boundary_loss: 0.013897 (0.013899) Loss: 0.15596 (0.16870) +2025-09-15,03:33:34 | INFO | Train Epoch: 10 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.13526 (0.15473) Boundary_loss: 0.013899 (0.013899) Loss: 0.14915 (0.16863) +2025-09-15,03:34:40 | INFO | Train Epoch: 10 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10410 (0.15454) Boundary_loss: 0.013899 (0.013899) Loss: 0.11800 (0.16844) +2025-09-15,03:35:46 | INFO | Train Epoch: 10 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.15400 (0.15454) Boundary_loss: 0.013898 (0.013899) Loss: 0.16790 (0.16844) +2025-09-15,03:36:52 | INFO | Train Epoch: 10 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.16607 (0.15458) Boundary_loss: 0.013898 (0.013899) Loss: 0.17997 (0.16848) +2025-09-15,03:37:58 | INFO | Train Epoch: 10 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15280 (0.15458) Boundary_loss: 0.013899 (0.013899) Loss: 0.16670 (0.16848) +2025-09-15,03:39:04 | INFO | Train Epoch: 10 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.11918 (0.15445) Boundary_loss: 0.013900 (0.013899) Loss: 0.13308 (0.16835) +2025-09-15,03:40:10 | INFO | Train Epoch: 10 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.15490 (0.15445) Boundary_loss: 0.013898 (0.013899) Loss: 0.16880 (0.16835) +2025-09-15,03:41:16 | INFO | Train Epoch: 10 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.17585 (0.15453) Boundary_loss: 0.013897 (0.013899) Loss: 0.18975 (0.16843) +2025-09-15,03:42:22 | INFO | Train Epoch: 10 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.14989 (0.15451) Boundary_loss: 0.013899 (0.013899) Loss: 0.16379 (0.16841) +2025-09-15,03:43:28 | INFO | Train Epoch: 10 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.16917 (0.15456) Boundary_loss: 0.013897 (0.013899) Loss: 0.18307 (0.16846) +2025-09-15,03:44:34 | INFO | Train Epoch: 10 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11456 (0.15442) Boundary_loss: 0.013898 (0.013899) Loss: 0.12845 (0.16832) +2025-09-15,03:45:40 | INFO | Train Epoch: 10 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18366 (0.15452) Boundary_loss: 0.013896 (0.013899) Loss: 0.19756 (0.16842) +2025-09-15,03:46:46 | INFO | Train Epoch: 10 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.15623 (0.15453) Boundary_loss: 0.013898 (0.013899) Loss: 0.17013 (0.16843) +2025-09-15,03:47:52 | INFO | Train Epoch: 10 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.18654 (0.15464) Boundary_loss: 0.013898 (0.013899) Loss: 0.20043 (0.16854) +2025-09-15,03:48:58 | INFO | Train Epoch: 10 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15282 (0.15464) Boundary_loss: 0.013896 (0.013899) Loss: 0.16671 (0.16854) +2025-09-15,03:50:04 | INFO | Train Epoch: 10 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.12951 (0.15455) Boundary_loss: 0.013898 (0.013899) Loss: 0.14341 (0.16845) +2025-09-15,03:51:09 | INFO | Train Epoch: 10 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12710 (0.15445) Boundary_loss: 0.013899 (0.013899) Loss: 0.14100 (0.16835) +2025-09-15,03:52:15 | INFO | Train Epoch: 10 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.10992 (0.15430) Boundary_loss: 0.013901 (0.013899) Loss: 0.12382 (0.16820) +2025-09-15,03:53:21 | INFO | Train Epoch: 10 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.16230 (0.15433) Boundary_loss: 0.013897 (0.013899) Loss: 0.17620 (0.16822) +2025-09-15,03:54:27 | INFO | Train Epoch: 10 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14406 (0.15429) Boundary_loss: 0.013899 (0.013899) Loss: 0.15796 (0.16819) +2025-09-15,03:55:33 | INFO | Train Epoch: 10 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10480 (0.15412) Boundary_loss: 0.013898 (0.013899) Loss: 0.11870 (0.16802) +2025-09-15,03:56:39 | INFO | Train Epoch: 10 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.14705 (0.15409) Boundary_loss: 0.013899 (0.013899) Loss: 0.16095 (0.16799) +2025-09-15,03:57:45 | INFO | Train Epoch: 10 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.19099 (0.15422) Boundary_loss: 0.013897 (0.013899) Loss: 0.20489 (0.16812) +2025-09-15,03:58:51 | INFO | Train Epoch: 10 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15654 (0.15423) Boundary_loss: 0.013896 (0.013899) Loss: 0.17044 (0.16813) +2025-09-15,03:59:57 | INFO | Train Epoch: 10 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12664 (0.15414) Boundary_loss: 0.013898 (0.013899) Loss: 0.14054 (0.16803) +2025-09-15,04:01:03 | INFO | Train Epoch: 10 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.15699 (0.15414) Boundary_loss: 0.013899 (0.013899) Loss: 0.17089 (0.16804) +2025-09-15,04:02:09 | INFO | Train Epoch: 10 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13955 (0.15410) Boundary_loss: 0.013899 (0.013899) Loss: 0.15345 (0.16799) +2025-09-15,04:03:15 | INFO | Train Epoch: 10 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.12851 (0.15401) Boundary_loss: 0.013899 (0.013899) Loss: 0.14241 (0.16791) +2025-09-15,04:04:21 | INFO | Train Epoch: 10 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17978 (0.15410) Boundary_loss: 0.013900 (0.013899) Loss: 0.19368 (0.16799) +2025-09-15,04:05:27 | INFO | Train Epoch: 10 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.20981 (0.15428) Boundary_loss: 0.013899 (0.013899) Loss: 0.22371 (0.16818) +2025-09-15,04:06:33 | INFO | Train Epoch: 10 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13316 (0.15421) Boundary_loss: 0.013899 (0.013899) Loss: 0.14706 (0.16811) +2025-09-15,04:07:39 | INFO | Train Epoch: 10 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14864 (0.15419) Boundary_loss: 0.013896 (0.013899) Loss: 0.16254 (0.16809) +2025-09-15,04:08:45 | INFO | Train Epoch: 10 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.20575 (0.15436) Boundary_loss: 0.013897 (0.013899) Loss: 0.21965 (0.16826) +2025-09-15,04:09:51 | INFO | Train Epoch: 10 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16394 (0.15440) Boundary_loss: 0.013896 (0.013899) Loss: 0.17784 (0.16829) +2025-09-15,04:10:56 | INFO | Train Epoch: 10 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.21258 (0.15459) Boundary_loss: 0.013897 (0.013899) Loss: 0.22648 (0.16849) +2025-09-15,04:12:02 | INFO | Train Epoch: 10 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14983 (0.15457) Boundary_loss: 0.013896 (0.013899) Loss: 0.16373 (0.16847) +2025-09-15,04:13:08 | INFO | Train Epoch: 10 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13472 (0.15451) Boundary_loss: 0.013900 (0.013899) Loss: 0.14862 (0.16841) +2025-09-15,04:14:14 | INFO | Train Epoch: 10 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.16380 (0.15454) Boundary_loss: 0.013899 (0.013899) Loss: 0.17770 (0.16844) +2025-09-15,04:15:20 | INFO | Train Epoch: 10 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12902 (0.15445) Boundary_loss: 0.013898 (0.013899) Loss: 0.14292 (0.16835) +2025-09-15,04:16:26 | INFO | Train Epoch: 10 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13478 (0.15439) Boundary_loss: 0.013898 (0.013899) Loss: 0.14868 (0.16829) +2025-09-15,04:17:32 | INFO | Train Epoch: 10 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.15641 (0.15440) Boundary_loss: 0.013900 (0.013899) Loss: 0.17031 (0.16830) +2025-09-15,04:18:38 | INFO | Train Epoch: 10 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.15858 (0.15441) Boundary_loss: 0.013899 (0.013899) Loss: 0.17248 (0.16831) +2025-09-15,04:19:44 | INFO | Train Epoch: 10 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15235 (0.15440) Boundary_loss: 0.013897 (0.013899) Loss: 0.16625 (0.16830) +2025-09-15,04:20:50 | INFO | Train Epoch: 10 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15898 (0.15442) Boundary_loss: 0.013897 (0.013899) Loss: 0.17288 (0.16832) +2025-09-15,04:21:56 | INFO | Train Epoch: 10 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.15024 (0.15441) Boundary_loss: 0.013897 (0.013898) Loss: 0.16414 (0.16830) +2025-09-15,04:23:02 | INFO | Train Epoch: 10 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13242 (0.15434) Boundary_loss: 0.013896 (0.013898) Loss: 0.14632 (0.16823) +2025-09-15,04:24:08 | INFO | Train Epoch: 10 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.16348 (0.15436) Boundary_loss: 0.013899 (0.013898) Loss: 0.17738 (0.16826) +2025-09-15,04:25:14 | INFO | Train Epoch: 10 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.12639 (0.15428) Boundary_loss: 0.013898 (0.013898) Loss: 0.14029 (0.16817) +2025-09-15,04:26:20 | INFO | Train Epoch: 10 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.15550 (0.15428) Boundary_loss: 0.013898 (0.013898) Loss: 0.16940 (0.16818) +2025-09-15,04:27:25 | INFO | Train Epoch: 10 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.11965 (0.15417) Boundary_loss: 0.013898 (0.013898) Loss: 0.13354 (0.16807) +2025-09-15,04:28:31 | INFO | Train Epoch: 10 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.12792 (0.15409) Boundary_loss: 0.013901 (0.013898) Loss: 0.14182 (0.16799) +2025-09-15,04:29:37 | INFO | Train Epoch: 10 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11122 (0.15396) Boundary_loss: 0.013899 (0.013898) Loss: 0.12512 (0.16785) +2025-09-15,04:30:43 | INFO | Train Epoch: 10 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14139 (0.15392) Boundary_loss: 0.013896 (0.013898) Loss: 0.15529 (0.16782) +2025-09-15,04:31:49 | INFO | Train Epoch: 10 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.13849 (0.15387) Boundary_loss: 0.013899 (0.013898) Loss: 0.15239 (0.16777) +2025-09-15,04:32:55 | INFO | Train Epoch: 10 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.15239 (0.15386) Boundary_loss: 0.013897 (0.013898) Loss: 0.16629 (0.16776) +2025-09-15,04:34:01 | INFO | Train Epoch: 10 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11608 (0.15375) Boundary_loss: 0.013897 (0.013898) Loss: 0.12998 (0.16765) +2025-09-15,04:35:07 | INFO | Train Epoch: 10 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13115 (0.15368) Boundary_loss: 0.013897 (0.013898) Loss: 0.14504 (0.16758) +2025-09-15,04:36:13 | INFO | Train Epoch: 10 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.15632 (0.15369) Boundary_loss: 0.013898 (0.013898) Loss: 0.17022 (0.16759) +2025-09-15,04:37:19 | INFO | Train Epoch: 10 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18788 (0.15379) Boundary_loss: 0.013897 (0.013898) Loss: 0.20178 (0.16769) +2025-09-15,04:38:25 | INFO | Train Epoch: 10 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.13999 (0.15375) Boundary_loss: 0.013897 (0.013898) Loss: 0.15389 (0.16765) +2025-09-15,04:39:31 | INFO | Train Epoch: 10 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.17762 (0.15382) Boundary_loss: 0.013897 (0.013898) Loss: 0.19152 (0.16772) +2025-09-15,04:40:37 | INFO | Train Epoch: 10 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.17871 (0.15390) Boundary_loss: 0.013900 (0.013898) Loss: 0.19261 (0.16780) +2025-09-15,04:41:43 | INFO | Train Epoch: 10 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.18473 (0.15399) Boundary_loss: 0.013901 (0.013898) Loss: 0.19863 (0.16789) +2025-09-15,04:42:49 | INFO | Train Epoch: 10 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.16998 (0.15404) Boundary_loss: 0.013899 (0.013898) Loss: 0.18388 (0.16794) +2025-09-15,04:43:55 | INFO | Train Epoch: 10 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15732 (0.15405) Boundary_loss: 0.013899 (0.013898) Loss: 0.17122 (0.16795) +2025-09-15,04:45:01 | INFO | Train Epoch: 10 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13898 (0.15400) Boundary_loss: 0.013898 (0.013898) Loss: 0.15287 (0.16790) +2025-09-15,04:46:07 | INFO | Train Epoch: 10 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13409 (0.15394) Boundary_loss: 0.013899 (0.013898) Loss: 0.14799 (0.16784) +2025-09-15,04:47:13 | INFO | Train Epoch: 10 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.16142 (0.15397) Boundary_loss: 0.013897 (0.013898) Loss: 0.17532 (0.16786) +2025-09-15,04:48:19 | INFO | Train Epoch: 10 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14776 (0.15395) Boundary_loss: 0.013898 (0.013898) Loss: 0.16165 (0.16785) +2025-09-15,04:49:24 | INFO | Train Epoch: 10 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.16412 (0.15398) Boundary_loss: 0.013899 (0.013898) Loss: 0.17802 (0.16788) +2025-09-15,04:50:30 | INFO | Train Epoch: 10 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.13215 (0.15391) Boundary_loss: 0.013899 (0.013898) Loss: 0.14605 (0.16781) +2025-09-15,04:51:36 | INFO | Train Epoch: 10 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14740 (0.15389) Boundary_loss: 0.013896 (0.013898) Loss: 0.16130 (0.16779) +2025-09-15,04:52:42 | INFO | Train Epoch: 10 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15706 (0.15390) Boundary_loss: 0.013898 (0.013898) Loss: 0.17096 (0.16780) +2025-09-15,04:53:48 | INFO | Train Epoch: 10 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15455 (0.15390) Boundary_loss: 0.013899 (0.013898) Loss: 0.16845 (0.16780) +2025-09-15,04:54:54 | INFO | Train Epoch: 10 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.14464 (0.15388) Boundary_loss: 0.013899 (0.013898) Loss: 0.15854 (0.16778) +2025-09-15,04:56:00 | INFO | Train Epoch: 10 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.13697 (0.15383) Boundary_loss: 0.013898 (0.013898) Loss: 0.15087 (0.16773) +2025-09-15,04:57:06 | INFO | Train Epoch: 10 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.13197 (0.15377) Boundary_loss: 0.013897 (0.013898) Loss: 0.14587 (0.16766) +2025-09-15,04:58:12 | INFO | Train Epoch: 10 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.15492 (0.15377) Boundary_loss: 0.013896 (0.013898) Loss: 0.16882 (0.16767) +2025-09-15,04:59:18 | INFO | Train Epoch: 10 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13484 (0.15371) Boundary_loss: 0.013898 (0.013898) Loss: 0.14874 (0.16761) +2025-09-15,05:00:24 | INFO | Train Epoch: 10 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.20345 (0.15386) Boundary_loss: 0.013896 (0.013898) Loss: 0.21735 (0.16776) +2025-09-15,05:01:30 | INFO | Train Epoch: 10 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16433 (0.15389) Boundary_loss: 0.013896 (0.013898) Loss: 0.17822 (0.16779) +2025-09-15,05:02:36 | INFO | Train Epoch: 10 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15712 (0.15390) Boundary_loss: 0.013897 (0.013898) Loss: 0.17101 (0.16779) +2025-09-15,05:03:42 | INFO | Train Epoch: 10 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12908 (0.15383) Boundary_loss: 0.013896 (0.013898) Loss: 0.14297 (0.16772) +2025-09-15,05:04:48 | INFO | Train Epoch: 10 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13627 (0.15378) Boundary_loss: 0.013896 (0.013898) Loss: 0.15017 (0.16767) +2025-09-15,05:05:54 | INFO | Train Epoch: 10 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.12352 (0.15369) Boundary_loss: 0.013898 (0.013898) Loss: 0.13741 (0.16759) +2025-09-15,05:07:00 | INFO | Train Epoch: 10 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11019 (0.15357) Boundary_loss: 0.013897 (0.013898) Loss: 0.12409 (0.16747) +2025-09-15,05:08:06 | INFO | Train Epoch: 10 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.15087 (0.15356) Boundary_loss: 0.013900 (0.013898) Loss: 0.16477 (0.16746) +2025-09-15,05:09:12 | INFO | Train Epoch: 10 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.23643 (0.15379) Boundary_loss: 0.013896 (0.013898) Loss: 0.25032 (0.16769) +2025-09-15,05:10:17 | INFO | Train Epoch: 10 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.15243 (0.15379) Boundary_loss: 0.013899 (0.013898) Loss: 0.16632 (0.16769) +2025-09-15,05:11:23 | INFO | Train Epoch: 10 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.13906 (0.15375) Boundary_loss: 0.013899 (0.013898) Loss: 0.15296 (0.16765) +2025-09-15,05:12:29 | INFO | Train Epoch: 10 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.11269 (0.15363) Boundary_loss: 0.013903 (0.013898) Loss: 0.12659 (0.16753) +2025-09-15,05:13:35 | INFO | Train Epoch: 10 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.17331 (0.15369) Boundary_loss: 0.013895 (0.013898) Loss: 0.18720 (0.16759) +2025-09-15,05:14:41 | INFO | Train Epoch: 10 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.13883 (0.15365) Boundary_loss: 0.013898 (0.013898) Loss: 0.15273 (0.16755) +2025-09-15,05:15:47 | INFO | Train Epoch: 10 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13565 (0.15360) Boundary_loss: 0.013897 (0.013898) Loss: 0.14955 (0.16750) +2025-09-15,05:16:53 | INFO | Train Epoch: 10 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.20160 (0.15373) Boundary_loss: 0.013898 (0.013898) Loss: 0.21550 (0.16763) +2025-09-15,05:17:59 | INFO | Train Epoch: 10 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13025 (0.15367) Boundary_loss: 0.013897 (0.013898) Loss: 0.14415 (0.16756) +2025-09-15,05:19:05 | INFO | Train Epoch: 10 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15407 (0.15367) Boundary_loss: 0.013896 (0.013898) Loss: 0.16797 (0.16756) +2025-09-15,05:20:11 | INFO | Train Epoch: 10 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13455 (0.15361) Boundary_loss: 0.013898 (0.013898) Loss: 0.14845 (0.16751) +2025-09-15,05:21:17 | INFO | Train Epoch: 10 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14870 (0.15360) Boundary_loss: 0.013897 (0.013898) Loss: 0.16260 (0.16750) +2025-09-15,05:22:23 | INFO | Train Epoch: 10 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.17468 (0.15366) Boundary_loss: 0.013897 (0.013898) Loss: 0.18858 (0.16756) +2025-09-15,05:23:29 | INFO | Train Epoch: 10 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.14031 (0.15362) Boundary_loss: 0.013899 (0.013898) Loss: 0.15421 (0.16752) +2025-09-15,05:24:35 | INFO | Train Epoch: 10 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.16461 (0.15365) Boundary_loss: 0.013896 (0.013898) Loss: 0.17851 (0.16755) +2025-09-15,05:25:41 | INFO | Train Epoch: 10 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14853 (0.15364) Boundary_loss: 0.013898 (0.013898) Loss: 0.16242 (0.16754) +2025-09-15,05:26:47 | INFO | Train Epoch: 10 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.12412 (0.15356) Boundary_loss: 0.013898 (0.013898) Loss: 0.13802 (0.16746) +2025-09-15,05:27:53 | INFO | Train Epoch: 10 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12924 (0.15349) Boundary_loss: 0.013897 (0.013898) Loss: 0.14313 (0.16739) +2025-09-15,05:28:59 | INFO | Train Epoch: 10 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12743 (0.15342) Boundary_loss: 0.013898 (0.013898) Loss: 0.14132 (0.16732) +2025-09-15,05:30:05 | INFO | Train Epoch: 10 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.14136 (0.15339) Boundary_loss: 0.013897 (0.013898) Loss: 0.15526 (0.16729) +2025-09-15,05:31:11 | INFO | Train Epoch: 10 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.14414 (0.15337) Boundary_loss: 0.013898 (0.013898) Loss: 0.15804 (0.16727) +2025-09-15,05:32:17 | INFO | Train Epoch: 10 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.10666 (0.15324) Boundary_loss: 0.013898 (0.013898) Loss: 0.12055 (0.16714) +2025-09-15,05:33:23 | INFO | Train Epoch: 10 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13478 (0.15320) Boundary_loss: 0.013896 (0.013898) Loss: 0.14868 (0.16709) +2025-09-15,05:34:28 | INFO | Train Epoch: 10 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13053 (0.15314) Boundary_loss: 0.013897 (0.013898) Loss: 0.14443 (0.16703) +2025-09-15,05:35:34 | INFO | Train Epoch: 10 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.14623 (0.15312) Boundary_loss: 0.013898 (0.013898) Loss: 0.16013 (0.16702) +2025-09-15,05:36:40 | INFO | Train Epoch: 10 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12985 (0.15306) Boundary_loss: 0.013897 (0.013898) Loss: 0.14375 (0.16695) +2025-09-15,05:37:46 | INFO | Train Epoch: 10 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16858 (0.15310) Boundary_loss: 0.013898 (0.013898) Loss: 0.18248 (0.16700) +2025-09-15,05:38:52 | INFO | Train Epoch: 10 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15372 (0.15310) Boundary_loss: 0.013897 (0.013898) Loss: 0.16761 (0.16700) +2025-09-15,05:39:58 | INFO | Train Epoch: 10 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.14653 (0.15308) Boundary_loss: 0.013897 (0.013898) Loss: 0.16043 (0.16698) +2025-09-15,05:41:04 | INFO | Train Epoch: 10 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17829 (0.15315) Boundary_loss: 0.013899 (0.013898) Loss: 0.19219 (0.16705) +2025-09-15,05:42:10 | INFO | Train Epoch: 10 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.17312 (0.15320) Boundary_loss: 0.013902 (0.013898) Loss: 0.18703 (0.16710) +2025-09-15,05:43:16 | INFO | Train Epoch: 10 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10973 (0.15309) Boundary_loss: 0.013898 (0.013898) Loss: 0.12362 (0.16698) +2025-09-15,05:44:22 | INFO | Train Epoch: 10 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11489 (0.15299) Boundary_loss: 0.013898 (0.013898) Loss: 0.12879 (0.16689) +2025-09-15,05:45:28 | INFO | Train Epoch: 10 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10227 (0.15286) Boundary_loss: 0.013896 (0.013898) Loss: 0.11616 (0.16676) +2025-09-15,05:46:34 | INFO | Train Epoch: 10 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16057 (0.15288) Boundary_loss: 0.013898 (0.013898) Loss: 0.17447 (0.16678) +2025-09-15,05:47:39 | INFO | Train Epoch: 10 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16471 (0.15291) Boundary_loss: 0.013897 (0.013898) Loss: 0.17860 (0.16681) +2025-09-15,05:48:45 | INFO | Train Epoch: 10 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.16709 (0.15294) Boundary_loss: 0.013896 (0.013898) Loss: 0.18098 (0.16684) +2025-09-15,05:49:51 | INFO | Train Epoch: 10 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17275 (0.15299) Boundary_loss: 0.013897 (0.013898) Loss: 0.18664 (0.16689) +2025-09-15,05:50:57 | INFO | Train Epoch: 10 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.14898 (0.15298) Boundary_loss: 0.013896 (0.013898) Loss: 0.16288 (0.16688) +2025-09-15,05:52:03 | INFO | Train Epoch: 10 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.12401 (0.15291) Boundary_loss: 0.013896 (0.013898) Loss: 0.13791 (0.16681) +2025-09-15,05:53:09 | INFO | Train Epoch: 10 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.11639 (0.15282) Boundary_loss: 0.013899 (0.013898) Loss: 0.13029 (0.16672) +2025-09-15,05:54:15 | INFO | Train Epoch: 10 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12577 (0.15275) Boundary_loss: 0.013896 (0.013898) Loss: 0.13966 (0.16665) +2025-09-15,05:55:21 | INFO | Train Epoch: 10 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.14402 (0.15273) Boundary_loss: 0.013899 (0.013898) Loss: 0.15792 (0.16663) +2025-09-15,05:56:27 | INFO | Train Epoch: 10 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.16657 (0.15276) Boundary_loss: 0.013898 (0.013898) Loss: 0.18047 (0.16666) +2025-09-15,05:57:33 | INFO | Train Epoch: 10 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.13440 (0.15272) Boundary_loss: 0.013897 (0.013898) Loss: 0.14829 (0.16662) +2025-09-15,05:58:39 | INFO | Train Epoch: 10 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.12566 (0.15265) Boundary_loss: 0.013899 (0.013898) Loss: 0.13956 (0.16655) +2025-09-15,05:59:45 | INFO | Train Epoch: 10 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15876 (0.15267) Boundary_loss: 0.013897 (0.013898) Loss: 0.17265 (0.16656) +2025-09-15,06:00:51 | INFO | Train Epoch: 10 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13893 (0.15263) Boundary_loss: 0.013897 (0.013898) Loss: 0.15282 (0.16653) +2025-09-15,06:01:57 | INFO | Train Epoch: 10 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12388 (0.15256) Boundary_loss: 0.013897 (0.013898) Loss: 0.13778 (0.16646) +2025-09-15,06:03:02 | INFO | Train Epoch: 10 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.14531 (0.15254) Boundary_loss: 0.013898 (0.013898) Loss: 0.15921 (0.16644) +2025-09-15,06:04:08 | INFO | Train Epoch: 10 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.092529 (0.15240) Boundary_loss: 0.013897 (0.013898) Loss: 0.10643 (0.16629) +2025-09-15,06:05:14 | INFO | Train Epoch: 10 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.12865 (0.15234) Boundary_loss: 0.013897 (0.013898) Loss: 0.14254 (0.16624) +2025-09-15,06:06:20 | INFO | Train Epoch: 10 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12041 (0.15226) Boundary_loss: 0.013897 (0.013898) Loss: 0.13430 (0.16616) +2025-09-15,06:07:26 | INFO | Train Epoch: 10 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13309 (0.15221) Boundary_loss: 0.013896 (0.013898) Loss: 0.14698 (0.16611) +2025-09-15,06:08:32 | INFO | Train Epoch: 10 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15457 (0.15222) Boundary_loss: 0.013896 (0.013898) Loss: 0.16846 (0.16612) +2025-09-15,06:09:38 | INFO | Train Epoch: 10 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.096443 (0.15208) Boundary_loss: 0.013900 (0.013898) Loss: 0.11034 (0.16598) +2025-09-15,06:10:44 | INFO | Train Epoch: 10 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.13257 (0.15204) Boundary_loss: 0.013899 (0.013898) Loss: 0.14647 (0.16593) +2025-09-15,06:11:50 | INFO | Train Epoch: 10 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16148 (0.15206) Boundary_loss: 0.013897 (0.013898) Loss: 0.17538 (0.16596) +2025-09-15,06:12:56 | INFO | Train Epoch: 10 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.13866 (0.15203) Boundary_loss: 0.013896 (0.013898) Loss: 0.15256 (0.16592) +2025-09-15,06:14:02 | INFO | Train Epoch: 10 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.16462 (0.15206) Boundary_loss: 0.013897 (0.013898) Loss: 0.17851 (0.16595) +2025-09-15,06:15:08 | INFO | Train Epoch: 10 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.15882 (0.15207) Boundary_loss: 0.013899 (0.013898) Loss: 0.17272 (0.16597) +2025-09-15,06:16:14 | INFO | Train Epoch: 10 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14420 (0.15205) Boundary_loss: 0.013898 (0.013898) Loss: 0.15810 (0.16595) +2025-09-15,06:17:19 | INFO | Train Epoch: 10 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.14807 (0.15204) Boundary_loss: 0.013901 (0.013898) Loss: 0.16197 (0.16594) +2025-09-15,06:18:25 | INFO | Train Epoch: 10 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14222 (0.15202) Boundary_loss: 0.013897 (0.013898) Loss: 0.15611 (0.16592) +2025-09-15,06:19:31 | INFO | Train Epoch: 10 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15589 (0.15203) Boundary_loss: 0.013896 (0.013898) Loss: 0.16979 (0.16593) +2025-09-15,06:20:37 | INFO | Train Epoch: 10 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11393 (0.15194) Boundary_loss: 0.013897 (0.013898) Loss: 0.12783 (0.16584) +2025-09-15,06:21:43 | INFO | Train Epoch: 10 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17119 (0.15199) Boundary_loss: 0.013896 (0.013898) Loss: 0.18509 (0.16588) +2025-09-15,06:22:49 | INFO | Train Epoch: 10 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.14970 (0.15198) Boundary_loss: 0.013898 (0.013898) Loss: 0.16360 (0.16588) +2025-09-15,06:23:55 | INFO | Train Epoch: 10 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10090 (0.15186) Boundary_loss: 0.013896 (0.013898) Loss: 0.11480 (0.16576) +2025-09-15,06:25:01 | INFO | Train Epoch: 10 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15845 (0.15188) Boundary_loss: 0.013896 (0.013898) Loss: 0.17234 (0.16577) +2025-09-15,06:26:07 | INFO | Train Epoch: 10 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.11935 (0.15180) Boundary_loss: 0.013898 (0.013898) Loss: 0.13325 (0.16570) +2025-09-15,06:27:12 | INFO | Train Epoch: 10 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.17121 (0.15184) Boundary_loss: 0.013898 (0.013898) Loss: 0.18511 (0.16574) +2025-09-15,06:28:19 | INFO | Train Epoch: 10 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12280 (0.15178) Boundary_loss: 0.013898 (0.013898) Loss: 0.13670 (0.16567) +2025-09-15,06:29:25 | INFO | Train Epoch: 10 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12645 (0.15172) Boundary_loss: 0.013900 (0.013898) Loss: 0.14034 (0.16562) +2025-09-15,06:30:30 | INFO | Train Epoch: 10 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15375 (0.15172) Boundary_loss: 0.013898 (0.013898) Loss: 0.16765 (0.16562) +2025-09-15,06:31:36 | INFO | Train Epoch: 10 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.17493 (0.15178) Boundary_loss: 0.013897 (0.013898) Loss: 0.18883 (0.16567) +2025-09-15,06:32:42 | INFO | Train Epoch: 10 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19184 (0.15187) Boundary_loss: 0.013897 (0.013898) Loss: 0.20574 (0.16577) +2025-09-15,06:33:48 | INFO | Train Epoch: 10 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.12357 (0.15180) Boundary_loss: 0.013899 (0.013898) Loss: 0.13747 (0.16570) +2025-09-15,06:34:54 | INFO | Train Epoch: 10 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.11710 (0.15172) Boundary_loss: 0.013900 (0.013898) Loss: 0.13100 (0.16562) +2025-09-15,06:36:00 | INFO | Train Epoch: 10 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13157 (0.15168) Boundary_loss: 0.013899 (0.013898) Loss: 0.14547 (0.16558) +2025-09-15,06:37:06 | INFO | Train Epoch: 10 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10834 (0.15158) Boundary_loss: 0.013897 (0.013898) Loss: 0.12224 (0.16548) +2025-09-15,06:38:12 | INFO | Train Epoch: 10 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14371 (0.15156) Boundary_loss: 0.013898 (0.013898) Loss: 0.15761 (0.16546) +2025-09-15,06:39:18 | INFO | Train Epoch: 10 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13208 (0.15152) Boundary_loss: 0.013899 (0.013898) Loss: 0.14598 (0.16541) +2025-09-15,06:40:24 | INFO | Train Epoch: 10 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10574 (0.15141) Boundary_loss: 0.013899 (0.013898) Loss: 0.11964 (0.16531) +2025-09-15,06:41:30 | INFO | Train Epoch: 10 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13314 (0.15137) Boundary_loss: 0.013897 (0.013898) Loss: 0.14704 (0.16527) +2025-09-15,06:42:36 | INFO | Train Epoch: 10 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.14408 (0.15135) Boundary_loss: 0.013898 (0.013898) Loss: 0.15798 (0.16525) +2025-09-15,06:43:41 | INFO | Train Epoch: 10 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.18177 (0.15142) Boundary_loss: 0.013898 (0.013898) Loss: 0.19567 (0.16532) +2025-09-15,06:44:47 | INFO | Train Epoch: 10 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.17142 (0.15147) Boundary_loss: 0.013897 (0.013898) Loss: 0.18531 (0.16537) +2025-09-15,06:45:53 | INFO | Train Epoch: 10 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14473 (0.15145) Boundary_loss: 0.013897 (0.013898) Loss: 0.15862 (0.16535) +2025-09-15,06:46:59 | INFO | Train Epoch: 10 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12720 (0.15140) Boundary_loss: 0.013898 (0.013898) Loss: 0.14110 (0.16530) +2025-09-15,06:48:05 | INFO | Train Epoch: 10 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.14791 (0.15139) Boundary_loss: 0.013897 (0.013898) Loss: 0.16181 (0.16529) +2025-09-15,06:49:11 | INFO | Train Epoch: 10 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.18662 (0.15147) Boundary_loss: 0.013898 (0.013898) Loss: 0.20052 (0.16537) +2025-09-15,06:50:17 | INFO | Train Epoch: 10 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13205 (0.15143) Boundary_loss: 0.013897 (0.013898) Loss: 0.14594 (0.16532) +2025-09-15,06:51:23 | INFO | Train Epoch: 10 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.17866 (0.15149) Boundary_loss: 0.013899 (0.013898) Loss: 0.19256 (0.16538) +2025-09-15,06:52:29 | INFO | Train Epoch: 10 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11753 (0.15141) Boundary_loss: 0.013899 (0.013898) Loss: 0.13142 (0.16531) +2025-09-15,06:53:35 | INFO | Train Epoch: 10 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12986 (0.15136) Boundary_loss: 0.013897 (0.013898) Loss: 0.14376 (0.16526) +2025-09-15,06:54:41 | INFO | Train Epoch: 10 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.19166 (0.15145) Boundary_loss: 0.013900 (0.013898) Loss: 0.20556 (0.16535) +2025-09-15,06:55:47 | INFO | Train Epoch: 10 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13479 (0.15142) Boundary_loss: 0.013898 (0.013898) Loss: 0.14869 (0.16531) +2025-09-15,06:56:52 | INFO | Train Epoch: 10 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.20413 (0.15153) Boundary_loss: 0.013896 (0.013898) Loss: 0.21803 (0.16543) +2025-09-15,06:57:58 | INFO | Train Epoch: 10 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.18778 (0.15161) Boundary_loss: 0.013896 (0.013898) Loss: 0.20167 (0.16551) +2025-09-15,06:59:04 | INFO | Train Epoch: 10 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.22130 (0.15176) Boundary_loss: 0.013900 (0.013898) Loss: 0.23520 (0.16566) +2025-09-15,07:00:10 | INFO | Train Epoch: 10 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14567 (0.15175) Boundary_loss: 0.013898 (0.013898) Loss: 0.15957 (0.16565) +2025-09-15,07:01:16 | INFO | Train Epoch: 10 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.16266 (0.15177) Boundary_loss: 0.013896 (0.013898) Loss: 0.17655 (0.16567) +2025-09-15,07:02:22 | INFO | Train Epoch: 10 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.17659 (0.15183) Boundary_loss: 0.013898 (0.013898) Loss: 0.19049 (0.16573) +2025-09-15,07:03:28 | INFO | Train Epoch: 10 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.17633 (0.15188) Boundary_loss: 0.013899 (0.013898) Loss: 0.19023 (0.16578) +2025-09-15,07:04:34 | INFO | Train Epoch: 10 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16320 (0.15191) Boundary_loss: 0.013896 (0.013898) Loss: 0.17709 (0.16580) +2025-09-15,07:05:40 | INFO | Train Epoch: 10 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.13158 (0.15186) Boundary_loss: 0.013897 (0.013898) Loss: 0.14548 (0.16576) +2025-09-15,07:06:46 | INFO | Train Epoch: 10 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.14456 (0.15185) Boundary_loss: 0.013898 (0.013898) Loss: 0.15846 (0.16574) +2025-09-15,07:07:52 | INFO | Train Epoch: 10 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16105 (0.15187) Boundary_loss: 0.013896 (0.013898) Loss: 0.17494 (0.16576) +2025-09-15,07:08:58 | INFO | Train Epoch: 10 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.15329 (0.15187) Boundary_loss: 0.013897 (0.013898) Loss: 0.16719 (0.16577) +2025-09-15,07:10:04 | INFO | Train Epoch: 10 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11837 (0.15180) Boundary_loss: 0.013898 (0.013898) Loss: 0.13226 (0.16570) +2025-09-15,07:11:10 | INFO | Train Epoch: 10 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.13692 (0.15177) Boundary_loss: 0.013896 (0.013898) Loss: 0.15081 (0.16566) +2025-09-15,07:12:16 | INFO | Train Epoch: 10 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.14099 (0.15174) Boundary_loss: 0.013896 (0.013898) Loss: 0.15489 (0.16564) +2025-09-15,07:13:22 | INFO | Train Epoch: 10 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13828 (0.15171) Boundary_loss: 0.013898 (0.013898) Loss: 0.15218 (0.16561) +2025-09-15,07:14:28 | INFO | Train Epoch: 10 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15619 (0.15172) Boundary_loss: 0.013896 (0.013898) Loss: 0.17008 (0.16562) +2025-09-15,07:15:34 | INFO | Train Epoch: 10 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11240 (0.15164) Boundary_loss: 0.013896 (0.013898) Loss: 0.12629 (0.16554) +2025-09-15,07:16:40 | INFO | Train Epoch: 10 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.18288 (0.15171) Boundary_loss: 0.013898 (0.013898) Loss: 0.19678 (0.16560) +2025-09-15,07:17:45 | INFO | Train Epoch: 10 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14597 (0.15169) Boundary_loss: 0.013896 (0.013898) Loss: 0.15986 (0.16559) +2025-09-15,07:18:51 | INFO | Train Epoch: 10 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.17777 (0.15175) Boundary_loss: 0.013898 (0.013898) Loss: 0.19167 (0.16565) +2025-09-15,07:19:57 | INFO | Train Epoch: 10 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15216 (0.15175) Boundary_loss: 0.013899 (0.013898) Loss: 0.16606 (0.16565) +2025-09-15,07:21:03 | INFO | Train Epoch: 10 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16761 (0.15178) Boundary_loss: 0.013898 (0.013898) Loss: 0.18151 (0.16568) +2025-09-15,07:22:09 | INFO | Train Epoch: 10 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.14356 (0.15177) Boundary_loss: 0.013898 (0.013898) Loss: 0.15746 (0.16566) +2025-09-15,07:23:15 | INFO | Train Epoch: 10 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14191 (0.15174) Boundary_loss: 0.013896 (0.013898) Loss: 0.15581 (0.16564) +2025-09-15,07:24:21 | INFO | Train Epoch: 10 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.14370 (0.15173) Boundary_loss: 0.013900 (0.013898) Loss: 0.15760 (0.16563) +2025-09-15,07:25:27 | INFO | Train Epoch: 10 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.16113 (0.15175) Boundary_loss: 0.013898 (0.013898) Loss: 0.17503 (0.16565) +2025-09-15,07:26:33 | INFO | Train Epoch: 10 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14860 (0.15174) Boundary_loss: 0.013899 (0.013898) Loss: 0.16249 (0.16564) +2025-09-15,07:27:39 | INFO | Train Epoch: 10 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17428 (0.15179) Boundary_loss: 0.013897 (0.013898) Loss: 0.18817 (0.16569) +2025-09-15,07:28:45 | INFO | Train Epoch: 10 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.094872 (0.15167) Boundary_loss: 0.013896 (0.013898) Loss: 0.10877 (0.16557) +2025-09-15,07:29:51 | INFO | Train Epoch: 10 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.091994 (0.15155) Boundary_loss: 0.013896 (0.013898) Loss: 0.10589 (0.16545) +2025-09-15,07:30:57 | INFO | Train Epoch: 10 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11343 (0.15147) Boundary_loss: 0.013897 (0.013898) Loss: 0.12733 (0.16537) +2025-09-15,07:32:03 | INFO | Train Epoch: 10 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15751 (0.15148) Boundary_loss: 0.013897 (0.013898) Loss: 0.17141 (0.16538) +2025-09-15,07:33:09 | INFO | Train Epoch: 10 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13235 (0.15144) Boundary_loss: 0.013896 (0.013898) Loss: 0.14625 (0.16534) +2025-09-15,07:34:14 | INFO | Train Epoch: 10 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14755 (0.15143) Boundary_loss: 0.013896 (0.013898) Loss: 0.16145 (0.16533) +2025-09-15,07:35:20 | INFO | Train Epoch: 10 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12979 (0.15139) Boundary_loss: 0.013898 (0.013898) Loss: 0.14368 (0.16529) +2025-09-15,07:36:26 | INFO | Train Epoch: 10 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.11517 (0.15132) Boundary_loss: 0.013901 (0.013898) Loss: 0.12907 (0.16521) +2025-09-15,07:37:32 | INFO | Train Epoch: 10 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15552 (0.15132) Boundary_loss: 0.013898 (0.013898) Loss: 0.16942 (0.16522) +2025-09-15,07:38:38 | INFO | Train Epoch: 10 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10093 (0.15122) Boundary_loss: 0.013896 (0.013898) Loss: 0.11482 (0.16512) +2025-09-15,07:39:44 | INFO | Train Epoch: 10 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15648 (0.15123) Boundary_loss: 0.013896 (0.013898) Loss: 0.17038 (0.16513) +2025-09-15,07:40:50 | INFO | Train Epoch: 10 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11800 (0.15117) Boundary_loss: 0.013896 (0.013898) Loss: 0.13189 (0.16506) +2025-09-15,07:41:56 | INFO | Train Epoch: 10 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.15209 (0.15117) Boundary_loss: 0.013898 (0.013898) Loss: 0.16599 (0.16507) +2025-09-15,07:43:02 | INFO | Train Epoch: 10 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.13321 (0.15113) Boundary_loss: 0.013898 (0.013898) Loss: 0.14710 (0.16503) +2025-09-15,07:44:08 | INFO | Train Epoch: 10 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16035 (0.15115) Boundary_loss: 0.013897 (0.013898) Loss: 0.17425 (0.16505) +2025-09-15,07:45:14 | INFO | Train Epoch: 10 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.14546 (0.15114) Boundary_loss: 0.013898 (0.013898) Loss: 0.15936 (0.16504) +2025-09-15,07:46:20 | INFO | Train Epoch: 10 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.088751 (0.15101) Boundary_loss: 0.013898 (0.013898) Loss: 0.10265 (0.16491) +2025-09-15,07:47:26 | INFO | Train Epoch: 10 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.14798 (0.15101) Boundary_loss: 0.013898 (0.013898) Loss: 0.16187 (0.16491) +2025-09-15,07:48:32 | INFO | Train Epoch: 10 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15300 (0.15101) Boundary_loss: 0.013896 (0.013898) Loss: 0.16690 (0.16491) +2025-09-15,07:49:38 | INFO | Train Epoch: 10 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13743 (0.15098) Boundary_loss: 0.013895 (0.013898) Loss: 0.15132 (0.16488) +2025-09-15,07:50:44 | INFO | Train Epoch: 10 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.079640 (0.15084) Boundary_loss: 0.013897 (0.013898) Loss: 0.093537 (0.16474) +2025-09-15,07:51:50 | INFO | Train Epoch: 10 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11545 (0.15077) Boundary_loss: 0.013898 (0.013898) Loss: 0.12934 (0.16467) +2025-09-15,07:52:55 | INFO | Train Epoch: 10 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.095244 (0.15066) Boundary_loss: 0.013896 (0.013898) Loss: 0.10914 (0.16456) +2025-09-15,07:54:01 | INFO | Train Epoch: 10 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.12315 (0.15061) Boundary_loss: 0.013897 (0.013898) Loss: 0.13705 (0.16451) +2025-09-15,07:55:07 | INFO | Train Epoch: 10 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.11391 (0.15054) Boundary_loss: 0.013899 (0.013898) Loss: 0.12781 (0.16444) +2025-09-15,07:56:13 | INFO | Train Epoch: 10 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14005 (0.15052) Boundary_loss: 0.013896 (0.013898) Loss: 0.15394 (0.16441) +2025-09-15,07:57:19 | INFO | Train Epoch: 10 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19390 (0.15060) Boundary_loss: 0.013896 (0.013898) Loss: 0.20780 (0.16450) +2025-09-15,07:58:25 | INFO | Train Epoch: 10 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14485 (0.15059) Boundary_loss: 0.013896 (0.013898) Loss: 0.15875 (0.16449) +2025-09-15,07:59:31 | INFO | Train Epoch: 10 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14886 (0.15059) Boundary_loss: 0.013896 (0.013898) Loss: 0.16275 (0.16448) +2025-09-15,08:00:37 | INFO | Train Epoch: 10 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.18837 (0.15066) Boundary_loss: 0.013897 (0.013898) Loss: 0.20227 (0.16456) +2025-09-15,08:01:43 | INFO | Train Epoch: 10 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13953 (0.15064) Boundary_loss: 0.013898 (0.013898) Loss: 0.15343 (0.16454) +2025-09-15,08:02:49 | INFO | Train Epoch: 10 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.18163 (0.15070) Boundary_loss: 0.013897 (0.013898) Loss: 0.19553 (0.16460) +2025-09-15,08:03:52 | INFO | Train Epoch: 10 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.16247 (0.15072) Boundary_loss: 0.013899 (0.013898) Loss: 0.17637 (0.16462) +2025-09-15,08:03:52 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-15,08:03:52 | INFO | [Epoch 10] Average Step Time: 0.662s | Average GPU Memory: 30.9 GB +2025-09-15,08:03:52 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-15,08:03:52 | INFO | Starting zero-shot imagenet. +2025-09-15,08:03:52 | INFO | Building zero-shot classifier +2025-09-15,08:04:01 | INFO | Using classifier +2025-09-15,08:04:43 | INFO | Finished zero-shot imagenet. +2025-09-15,08:04:43 | INFO | Eval Epoch: 11 imagenet-zeroshot-val-top1: 0.3146 imagenet-zeroshot-val-top5: 0.5870 +2025-09-15,08:04:44 | INFO | Start epoch 11 +2025-09-15,08:04:47 | INFO | Train Epoch: 11 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.099256 (0.099256) Boundary_loss: 0.013898 (0.013898) Loss: 0.11315 (0.11315) +2025-09-15,08:05:52 | INFO | Train Epoch: 11 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16375 (0.13150) Boundary_loss: 0.013897 (0.013897) Loss: 0.17765 (0.14540) +2025-09-15,08:06:58 | INFO | Train Epoch: 11 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.12861 (0.13054) Boundary_loss: 0.013901 (0.013899) Loss: 0.14251 (0.14444) +2025-09-15,08:08:04 | INFO | Train Epoch: 11 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.11443 (0.12651) Boundary_loss: 0.013898 (0.013898) Loss: 0.12833 (0.14041) +2025-09-15,08:09:09 | INFO | Train Epoch: 11 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10558 (0.12232) Boundary_loss: 0.013898 (0.013898) Loss: 0.11948 (0.13622) +2025-09-15,08:10:15 | INFO | Train Epoch: 11 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16909 (0.13012) Boundary_loss: 0.013896 (0.013898) Loss: 0.18299 (0.14402) +2025-09-15,08:11:20 | INFO | Train Epoch: 11 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19115 (0.13884) Boundary_loss: 0.013896 (0.013898) Loss: 0.20504 (0.15274) +2025-09-15,08:12:26 | INFO | Train Epoch: 11 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.093700 (0.13320) Boundary_loss: 0.013898 (0.013898) Loss: 0.10760 (0.14709) +2025-09-15,08:13:32 | INFO | Train Epoch: 11 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.12939 (0.13277) Boundary_loss: 0.013897 (0.013898) Loss: 0.14329 (0.14667) +2025-09-15,08:14:37 | INFO | Train Epoch: 11 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18163 (0.13766) Boundary_loss: 0.013898 (0.013898) Loss: 0.19553 (0.15156) +2025-09-15,08:15:43 | INFO | Train Epoch: 11 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10590 (0.13477) Boundary_loss: 0.013896 (0.013898) Loss: 0.11979 (0.14867) +2025-09-15,08:16:48 | INFO | Train Epoch: 11 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.094448 (0.13141) Boundary_loss: 0.013898 (0.013898) Loss: 0.10835 (0.14531) +2025-09-15,08:17:54 | INFO | Train Epoch: 11 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11890 (0.13045) Boundary_loss: 0.013897 (0.013897) Loss: 0.13279 (0.14435) +2025-09-15,08:19:00 | INFO | Train Epoch: 11 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.11697 (0.12949) Boundary_loss: 0.013899 (0.013898) Loss: 0.13087 (0.14338) +2025-09-15,08:20:05 | INFO | Train Epoch: 11 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.089519 (0.12682) Boundary_loss: 0.013896 (0.013897) Loss: 0.10341 (0.14072) +2025-09-15,08:21:11 | INFO | Train Epoch: 11 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.15271 (0.12844) Boundary_loss: 0.013899 (0.013898) Loss: 0.16661 (0.14234) +2025-09-15,08:22:17 | INFO | Train Epoch: 11 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.12298 (0.12812) Boundary_loss: 0.013897 (0.013898) Loss: 0.13688 (0.14202) +2025-09-15,08:23:22 | INFO | Train Epoch: 11 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.098169 (0.12645) Boundary_loss: 0.013897 (0.013897) Loss: 0.11207 (0.14035) +2025-09-15,08:24:28 | INFO | Train Epoch: 11 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11178 (0.12568) Boundary_loss: 0.013896 (0.013897) Loss: 0.12568 (0.13958) +2025-09-15,08:25:33 | INFO | Train Epoch: 11 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10061 (0.12443) Boundary_loss: 0.013897 (0.013897) Loss: 0.11451 (0.13833) +2025-09-15,08:26:39 | INFO | Train Epoch: 11 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.12301 (0.12436) Boundary_loss: 0.013900 (0.013898) Loss: 0.13691 (0.13826) +2025-09-15,08:27:45 | INFO | Train Epoch: 11 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.11595 (0.12398) Boundary_loss: 0.013901 (0.013898) Loss: 0.12985 (0.13788) +2025-09-15,08:28:50 | INFO | Train Epoch: 11 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.11079 (0.12341) Boundary_loss: 0.013899 (0.013898) Loss: 0.12469 (0.13730) +2025-09-15,08:29:56 | INFO | Train Epoch: 11 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.086111 (0.12185) Boundary_loss: 0.013897 (0.013898) Loss: 0.10001 (0.13575) +2025-09-15,08:31:01 | INFO | Train Epoch: 11 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.11013 (0.12138) Boundary_loss: 0.013897 (0.013898) Loss: 0.12403 (0.13528) +2025-09-15,08:32:07 | INFO | Train Epoch: 11 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.12761 (0.12162) Boundary_loss: 0.013899 (0.013898) Loss: 0.14151 (0.13552) +2025-09-15,08:33:13 | INFO | Train Epoch: 11 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.096851 (0.12071) Boundary_loss: 0.013898 (0.013898) Loss: 0.11075 (0.13460) +2025-09-15,08:34:18 | INFO | Train Epoch: 11 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.12681 (0.12092) Boundary_loss: 0.013898 (0.013898) Loss: 0.14071 (0.13482) +2025-09-15,08:35:24 | INFO | Train Epoch: 11 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.11175 (0.12061) Boundary_loss: 0.013898 (0.013898) Loss: 0.12565 (0.13450) +2025-09-15,08:36:30 | INFO | Train Epoch: 11 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13539 (0.12110) Boundary_loss: 0.013899 (0.013898) Loss: 0.14929 (0.13500) +2025-09-15,08:37:35 | INFO | Train Epoch: 11 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.14575 (0.12189) Boundary_loss: 0.013897 (0.013898) Loss: 0.15965 (0.13579) +2025-09-15,08:38:41 | INFO | Train Epoch: 11 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.097315 (0.12113) Boundary_loss: 0.013898 (0.013898) Loss: 0.11121 (0.13502) +2025-09-15,08:39:46 | INFO | Train Epoch: 11 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.097607 (0.12041) Boundary_loss: 0.013896 (0.013898) Loss: 0.11150 (0.13431) +2025-09-15,08:40:52 | INFO | Train Epoch: 11 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.14994 (0.12128) Boundary_loss: 0.013898 (0.013898) Loss: 0.16383 (0.13518) +2025-09-15,08:41:57 | INFO | Train Epoch: 11 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13129 (0.12157) Boundary_loss: 0.013896 (0.013898) Loss: 0.14519 (0.13547) +2025-09-15,08:43:03 | INFO | Train Epoch: 11 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12448 (0.12165) Boundary_loss: 0.013897 (0.013898) Loss: 0.13837 (0.13555) +2025-09-15,08:44:09 | INFO | Train Epoch: 11 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.098582 (0.12103) Boundary_loss: 0.013897 (0.013898) Loss: 0.11248 (0.13492) +2025-09-15,08:45:14 | INFO | Train Epoch: 11 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.17120 (0.12235) Boundary_loss: 0.013897 (0.013898) Loss: 0.18510 (0.13624) +2025-09-15,08:46:20 | INFO | Train Epoch: 11 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13969 (0.12279) Boundary_loss: 0.013897 (0.013898) Loss: 0.15359 (0.13669) +2025-09-15,08:47:26 | INFO | Train Epoch: 11 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12435 (0.12283) Boundary_loss: 0.013897 (0.013898) Loss: 0.13825 (0.13673) +2025-09-15,08:48:31 | INFO | Train Epoch: 11 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.12959 (0.12299) Boundary_loss: 0.013897 (0.013898) Loss: 0.14349 (0.13689) +2025-09-15,08:49:37 | INFO | Train Epoch: 11 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.097563 (0.12239) Boundary_loss: 0.013898 (0.013898) Loss: 0.11146 (0.13629) +2025-09-15,08:50:42 | INFO | Train Epoch: 11 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.16647 (0.12341) Boundary_loss: 0.013897 (0.013898) Loss: 0.18037 (0.13731) +2025-09-15,08:51:48 | INFO | Train Epoch: 11 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11492 (0.12322) Boundary_loss: 0.013897 (0.013898) Loss: 0.12882 (0.13712) +2025-09-15,08:52:54 | INFO | Train Epoch: 11 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13501 (0.12348) Boundary_loss: 0.013899 (0.013898) Loss: 0.14891 (0.13738) +2025-09-15,08:53:59 | INFO | Train Epoch: 11 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.12293 (0.12347) Boundary_loss: 0.013897 (0.013898) Loss: 0.13683 (0.13737) +2025-09-15,08:55:05 | INFO | Train Epoch: 11 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11939 (0.12338) Boundary_loss: 0.013898 (0.013898) Loss: 0.13329 (0.13728) +2025-09-15,08:56:11 | INFO | Train Epoch: 11 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13915 (0.12371) Boundary_loss: 0.013898 (0.013898) Loss: 0.15305 (0.13761) +2025-09-15,08:57:16 | INFO | Train Epoch: 11 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14503 (0.12415) Boundary_loss: 0.013898 (0.013898) Loss: 0.15893 (0.13805) +2025-09-15,08:58:22 | INFO | Train Epoch: 11 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.099588 (0.12366) Boundary_loss: 0.013897 (0.013898) Loss: 0.11349 (0.13755) +2025-09-15,08:59:28 | INFO | Train Epoch: 11 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12279 (0.12364) Boundary_loss: 0.013897 (0.013898) Loss: 0.13669 (0.13754) +2025-09-15,09:00:33 | INFO | Train Epoch: 11 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.088075 (0.12296) Boundary_loss: 0.013899 (0.013898) Loss: 0.10197 (0.13685) +2025-09-15,09:01:39 | INFO | Train Epoch: 11 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12256 (0.12295) Boundary_loss: 0.013897 (0.013898) Loss: 0.13646 (0.13685) +2025-09-15,09:02:45 | INFO | Train Epoch: 11 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.14250 (0.12331) Boundary_loss: 0.013897 (0.013898) Loss: 0.15640 (0.13721) +2025-09-15,09:03:50 | INFO | Train Epoch: 11 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.084920 (0.12261) Boundary_loss: 0.013898 (0.013898) Loss: 0.098818 (0.13651) +2025-09-15,09:04:56 | INFO | Train Epoch: 11 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10971 (0.12238) Boundary_loss: 0.013896 (0.013898) Loss: 0.12360 (0.13628) +2025-09-15,09:06:02 | INFO | Train Epoch: 11 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.10263 (0.12204) Boundary_loss: 0.013898 (0.013898) Loss: 0.11652 (0.13593) +2025-09-15,09:07:07 | INFO | Train Epoch: 11 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.10251 (0.12170) Boundary_loss: 0.013898 (0.013898) Loss: 0.11641 (0.13560) +2025-09-15,09:08:13 | INFO | Train Epoch: 11 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.11603 (0.12160) Boundary_loss: 0.013898 (0.013898) Loss: 0.12993 (0.13550) +2025-09-15,09:09:19 | INFO | Train Epoch: 11 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.15376 (0.12214) Boundary_loss: 0.013897 (0.013898) Loss: 0.16765 (0.13604) +2025-09-15,09:10:24 | INFO | Train Epoch: 11 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12402 (0.12217) Boundary_loss: 0.013896 (0.013898) Loss: 0.13791 (0.13607) +2025-09-15,09:11:30 | INFO | Train Epoch: 11 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14260 (0.12250) Boundary_loss: 0.013897 (0.013898) Loss: 0.15650 (0.13640) +2025-09-15,09:12:36 | INFO | Train Epoch: 11 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.12913 (0.12260) Boundary_loss: 0.013900 (0.013898) Loss: 0.14303 (0.13650) +2025-09-15,09:13:41 | INFO | Train Epoch: 11 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.092634 (0.12214) Boundary_loss: 0.013899 (0.013898) Loss: 0.10653 (0.13603) +2025-09-15,09:14:47 | INFO | Train Epoch: 11 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11474 (0.12202) Boundary_loss: 0.013900 (0.013898) Loss: 0.12864 (0.13592) +2025-09-15,09:15:53 | INFO | Train Epoch: 11 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.088996 (0.12152) Boundary_loss: 0.013897 (0.013898) Loss: 0.10289 (0.13542) +2025-09-15,09:16:58 | INFO | Train Epoch: 11 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11497 (0.12142) Boundary_loss: 0.013896 (0.013898) Loss: 0.12886 (0.13532) +2025-09-15,09:18:04 | INFO | Train Epoch: 11 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.12056 (0.12141) Boundary_loss: 0.013898 (0.013898) Loss: 0.13446 (0.13531) +2025-09-15,09:19:10 | INFO | Train Epoch: 11 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.10240 (0.12114) Boundary_loss: 0.013897 (0.013898) Loss: 0.11630 (0.13503) +2025-09-15,09:20:15 | INFO | Train Epoch: 11 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.11213 (0.12101) Boundary_loss: 0.013898 (0.013898) Loss: 0.12603 (0.13490) +2025-09-15,09:21:21 | INFO | Train Epoch: 11 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13957 (0.12127) Boundary_loss: 0.013897 (0.013898) Loss: 0.15347 (0.13517) +2025-09-15,09:22:27 | INFO | Train Epoch: 11 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.11510 (0.12118) Boundary_loss: 0.013900 (0.013898) Loss: 0.12900 (0.13508) +2025-09-15,09:23:32 | INFO | Train Epoch: 11 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.13325 (0.12135) Boundary_loss: 0.013897 (0.013898) Loss: 0.14715 (0.13525) +2025-09-15,09:24:38 | INFO | Train Epoch: 11 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10432 (0.12112) Boundary_loss: 0.013897 (0.013898) Loss: 0.11822 (0.13502) +2025-09-15,09:25:44 | INFO | Train Epoch: 11 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10272 (0.12087) Boundary_loss: 0.013895 (0.013898) Loss: 0.11662 (0.13477) +2025-09-15,09:26:49 | INFO | Train Epoch: 11 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10824 (0.12071) Boundary_loss: 0.013896 (0.013898) Loss: 0.12214 (0.13460) +2025-09-15,09:27:55 | INFO | Train Epoch: 11 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.071135 (0.12006) Boundary_loss: 0.013896 (0.013898) Loss: 0.085031 (0.13396) +2025-09-15,09:29:01 | INFO | Train Epoch: 11 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.12123 (0.12008) Boundary_loss: 0.013896 (0.013898) Loss: 0.13513 (0.13398) +2025-09-15,09:30:06 | INFO | Train Epoch: 11 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14612 (0.12041) Boundary_loss: 0.013898 (0.013898) Loss: 0.16002 (0.13431) +2025-09-15,09:31:12 | INFO | Train Epoch: 11 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.10128 (0.12017) Boundary_loss: 0.013897 (0.013898) Loss: 0.11518 (0.13407) +2025-09-15,09:32:18 | INFO | Train Epoch: 11 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11168 (0.12006) Boundary_loss: 0.013896 (0.013898) Loss: 0.12558 (0.13396) +2025-09-15,09:33:23 | INFO | Train Epoch: 11 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.081759 (0.11960) Boundary_loss: 0.013898 (0.013898) Loss: 0.095657 (0.13349) +2025-09-15,09:34:29 | INFO | Train Epoch: 11 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10121 (0.11938) Boundary_loss: 0.013897 (0.013898) Loss: 0.11511 (0.13327) +2025-09-15,09:35:35 | INFO | Train Epoch: 11 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13343 (0.11954) Boundary_loss: 0.013896 (0.013898) Loss: 0.14733 (0.13344) +2025-09-15,09:36:40 | INFO | Train Epoch: 11 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11671 (0.11951) Boundary_loss: 0.013898 (0.013898) Loss: 0.13060 (0.13341) +2025-09-15,09:37:46 | INFO | Train Epoch: 11 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13832 (0.11973) Boundary_loss: 0.013896 (0.013898) Loss: 0.15221 (0.13363) +2025-09-15,09:38:52 | INFO | Train Epoch: 11 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11735 (0.11970) Boundary_loss: 0.013897 (0.013898) Loss: 0.13125 (0.13360) +2025-09-15,09:39:57 | INFO | Train Epoch: 11 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14839 (0.12003) Boundary_loss: 0.013896 (0.013897) Loss: 0.16229 (0.13392) +2025-09-15,09:41:03 | INFO | Train Epoch: 11 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12199 (0.12005) Boundary_loss: 0.013896 (0.013897) Loss: 0.13589 (0.13395) +2025-09-15,09:42:09 | INFO | Train Epoch: 11 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.092118 (0.11974) Boundary_loss: 0.013896 (0.013897) Loss: 0.10601 (0.13364) +2025-09-15,09:43:14 | INFO | Train Epoch: 11 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.13380 (0.11989) Boundary_loss: 0.013897 (0.013897) Loss: 0.14769 (0.13379) +2025-09-15,09:44:20 | INFO | Train Epoch: 11 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14122 (0.12012) Boundary_loss: 0.013896 (0.013897) Loss: 0.15511 (0.13402) +2025-09-15,09:45:26 | INFO | Train Epoch: 11 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11973 (0.12012) Boundary_loss: 0.013896 (0.013897) Loss: 0.13362 (0.13402) +2025-09-15,09:46:32 | INFO | Train Epoch: 11 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17338 (0.12069) Boundary_loss: 0.013899 (0.013897) Loss: 0.18728 (0.13458) +2025-09-15,09:47:37 | INFO | Train Epoch: 11 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13278 (0.12081) Boundary_loss: 0.013898 (0.013897) Loss: 0.14668 (0.13471) +2025-09-15,09:48:43 | INFO | Train Epoch: 11 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15801 (0.12120) Boundary_loss: 0.013897 (0.013897) Loss: 0.17190 (0.13510) +2025-09-15,09:49:49 | INFO | Train Epoch: 11 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.14803 (0.12148) Boundary_loss: 0.013898 (0.013897) Loss: 0.16193 (0.13538) +2025-09-15,09:50:55 | INFO | Train Epoch: 11 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.13087 (0.12157) Boundary_loss: 0.013897 (0.013897) Loss: 0.14477 (0.13547) +2025-09-15,09:52:00 | INFO | Train Epoch: 11 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14205 (0.12178) Boundary_loss: 0.013898 (0.013897) Loss: 0.15595 (0.13568) +2025-09-15,09:53:06 | INFO | Train Epoch: 11 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10291 (0.12159) Boundary_loss: 0.013897 (0.013897) Loss: 0.11681 (0.13549) +2025-09-15,09:54:12 | INFO | Train Epoch: 11 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.077555 (0.12116) Boundary_loss: 0.013898 (0.013897) Loss: 0.091454 (0.13505) +2025-09-15,09:55:17 | INFO | Train Epoch: 11 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15701 (0.12151) Boundary_loss: 0.013898 (0.013897) Loss: 0.17091 (0.13540) +2025-09-15,09:56:23 | INFO | Train Epoch: 11 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11398 (0.12143) Boundary_loss: 0.013898 (0.013897) Loss: 0.12788 (0.13533) +2025-09-15,09:57:29 | INFO | Train Epoch: 11 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.14185 (0.12163) Boundary_loss: 0.013896 (0.013897) Loss: 0.15574 (0.13553) +2025-09-15,09:58:34 | INFO | Train Epoch: 11 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11203 (0.12154) Boundary_loss: 0.013899 (0.013897) Loss: 0.12593 (0.13544) +2025-09-15,09:59:40 | INFO | Train Epoch: 11 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.092766 (0.12127) Boundary_loss: 0.013896 (0.013897) Loss: 0.10666 (0.13517) +2025-09-15,10:00:46 | INFO | Train Epoch: 11 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14720 (0.12151) Boundary_loss: 0.013897 (0.013897) Loss: 0.16110 (0.13541) +2025-09-15,10:01:52 | INFO | Train Epoch: 11 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13642 (0.12165) Boundary_loss: 0.013898 (0.013897) Loss: 0.15032 (0.13555) +2025-09-15,10:02:57 | INFO | Train Epoch: 11 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.088172 (0.12134) Boundary_loss: 0.013896 (0.013897) Loss: 0.10207 (0.13524) +2025-09-15,10:04:03 | INFO | Train Epoch: 11 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.075858 (0.12093) Boundary_loss: 0.013898 (0.013897) Loss: 0.089755 (0.13483) +2025-09-15,10:05:09 | INFO | Train Epoch: 11 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12407 (0.12096) Boundary_loss: 0.013897 (0.013897) Loss: 0.13796 (0.13485) +2025-09-15,10:06:15 | INFO | Train Epoch: 11 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11397 (0.12089) Boundary_loss: 0.013898 (0.013897) Loss: 0.12787 (0.13479) +2025-09-15,10:07:20 | INFO | Train Epoch: 11 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.14654 (0.12112) Boundary_loss: 0.013895 (0.013897) Loss: 0.16043 (0.13502) +2025-09-15,10:08:26 | INFO | Train Epoch: 11 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.11569 (0.12107) Boundary_loss: 0.013897 (0.013897) Loss: 0.12959 (0.13497) +2025-09-15,10:09:32 | INFO | Train Epoch: 11 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11015 (0.12098) Boundary_loss: 0.013899 (0.013897) Loss: 0.12405 (0.13488) +2025-09-15,10:10:38 | INFO | Train Epoch: 11 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11851 (0.12096) Boundary_loss: 0.013896 (0.013897) Loss: 0.13241 (0.13485) +2025-09-15,10:11:43 | INFO | Train Epoch: 11 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.095376 (0.12074) Boundary_loss: 0.013896 (0.013897) Loss: 0.10927 (0.13464) +2025-09-15,10:12:49 | INFO | Train Epoch: 11 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15846 (0.12106) Boundary_loss: 0.013897 (0.013897) Loss: 0.17235 (0.13496) +2025-09-15,10:13:55 | INFO | Train Epoch: 11 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11251 (0.12099) Boundary_loss: 0.013896 (0.013897) Loss: 0.12641 (0.13488) +2025-09-15,10:15:00 | INFO | Train Epoch: 11 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11638 (0.12095) Boundary_loss: 0.013897 (0.013897) Loss: 0.13028 (0.13484) +2025-09-15,10:16:06 | INFO | Train Epoch: 11 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.15935 (0.12126) Boundary_loss: 0.013899 (0.013897) Loss: 0.17325 (0.13516) +2025-09-15,10:17:12 | INFO | Train Epoch: 11 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.097827 (0.12107) Boundary_loss: 0.013896 (0.013897) Loss: 0.11172 (0.13497) +2025-09-15,10:18:18 | INFO | Train Epoch: 11 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11771 (0.12105) Boundary_loss: 0.013897 (0.013897) Loss: 0.13161 (0.13494) +2025-09-15,10:19:24 | INFO | Train Epoch: 11 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.14158 (0.12121) Boundary_loss: 0.013899 (0.013897) Loss: 0.15547 (0.13511) +2025-09-15,10:20:29 | INFO | Train Epoch: 11 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13235 (0.12130) Boundary_loss: 0.013896 (0.013897) Loss: 0.14625 (0.13520) +2025-09-15,10:21:35 | INFO | Train Epoch: 11 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12420 (0.12132) Boundary_loss: 0.013896 (0.013897) Loss: 0.13810 (0.13522) +2025-09-15,10:22:41 | INFO | Train Epoch: 11 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12766 (0.12137) Boundary_loss: 0.013896 (0.013897) Loss: 0.14155 (0.13527) +2025-09-15,10:23:47 | INFO | Train Epoch: 11 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12943 (0.12144) Boundary_loss: 0.013898 (0.013897) Loss: 0.14333 (0.13533) +2025-09-15,10:24:52 | INFO | Train Epoch: 11 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10366 (0.12130) Boundary_loss: 0.013897 (0.013897) Loss: 0.11756 (0.13520) +2025-09-15,10:25:58 | INFO | Train Epoch: 11 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.091828 (0.12107) Boundary_loss: 0.013899 (0.013897) Loss: 0.10573 (0.13497) +2025-09-15,10:27:04 | INFO | Train Epoch: 11 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16146 (0.12138) Boundary_loss: 0.013899 (0.013897) Loss: 0.17536 (0.13528) +2025-09-15,10:28:10 | INFO | Train Epoch: 11 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.11203 (0.12131) Boundary_loss: 0.013898 (0.013897) Loss: 0.12593 (0.13521) +2025-09-15,10:29:15 | INFO | Train Epoch: 11 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12857 (0.12136) Boundary_loss: 0.013897 (0.013897) Loss: 0.14247 (0.13526) +2025-09-15,10:30:21 | INFO | Train Epoch: 11 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.13523 (0.12147) Boundary_loss: 0.013895 (0.013897) Loss: 0.14913 (0.13536) +2025-09-15,10:31:27 | INFO | Train Epoch: 11 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12453 (0.12149) Boundary_loss: 0.013897 (0.013897) Loss: 0.13843 (0.13539) +2025-09-15,10:32:33 | INFO | Train Epoch: 11 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.11984 (0.12148) Boundary_loss: 0.013899 (0.013897) Loss: 0.13374 (0.13538) +2025-09-15,10:33:38 | INFO | Train Epoch: 11 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13557 (0.12158) Boundary_loss: 0.013897 (0.013897) Loss: 0.14947 (0.13548) +2025-09-15,10:34:44 | INFO | Train Epoch: 11 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11753 (0.12155) Boundary_loss: 0.013895 (0.013897) Loss: 0.13142 (0.13545) +2025-09-15,10:35:50 | INFO | Train Epoch: 11 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10986 (0.12147) Boundary_loss: 0.013896 (0.013897) Loss: 0.12375 (0.13536) +2025-09-15,10:36:56 | INFO | Train Epoch: 11 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10781 (0.12137) Boundary_loss: 0.013895 (0.013897) Loss: 0.12170 (0.13527) +2025-09-15,10:38:01 | INFO | Train Epoch: 11 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.14008 (0.12150) Boundary_loss: 0.013898 (0.013897) Loss: 0.15398 (0.13540) +2025-09-15,10:39:07 | INFO | Train Epoch: 11 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.076235 (0.12118) Boundary_loss: 0.013897 (0.013897) Loss: 0.090132 (0.13508) +2025-09-15,10:40:13 | INFO | Train Epoch: 11 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18408 (0.12162) Boundary_loss: 0.013896 (0.013897) Loss: 0.19798 (0.13552) +2025-09-15,10:41:19 | INFO | Train Epoch: 11 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13812 (0.12174) Boundary_loss: 0.013896 (0.013897) Loss: 0.15202 (0.13564) +2025-09-15,10:42:25 | INFO | Train Epoch: 11 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.15376 (0.12196) Boundary_loss: 0.013899 (0.013897) Loss: 0.16766 (0.13586) +2025-09-15,10:43:30 | INFO | Train Epoch: 11 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10273 (0.12183) Boundary_loss: 0.013896 (0.013897) Loss: 0.11663 (0.13572) +2025-09-15,10:44:36 | INFO | Train Epoch: 11 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18999 (0.12229) Boundary_loss: 0.013898 (0.013897) Loss: 0.20389 (0.13619) +2025-09-15,10:45:42 | INFO | Train Epoch: 11 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.12198 (0.12229) Boundary_loss: 0.013898 (0.013897) Loss: 0.13588 (0.13619) +2025-09-15,10:46:48 | INFO | Train Epoch: 11 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11318 (0.12223) Boundary_loss: 0.013898 (0.013897) Loss: 0.12708 (0.13612) +2025-09-15,10:47:53 | INFO | Train Epoch: 11 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11066 (0.12215) Boundary_loss: 0.013896 (0.013897) Loss: 0.12455 (0.13605) +2025-09-15,10:48:59 | INFO | Train Epoch: 11 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.14602 (0.12231) Boundary_loss: 0.013896 (0.013897) Loss: 0.15992 (0.13621) +2025-09-15,10:50:05 | INFO | Train Epoch: 11 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.092840 (0.12211) Boundary_loss: 0.013897 (0.013897) Loss: 0.10674 (0.13601) +2025-09-15,10:51:11 | INFO | Train Epoch: 11 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.11579 (0.12207) Boundary_loss: 0.013896 (0.013897) Loss: 0.12969 (0.13597) +2025-09-15,10:52:16 | INFO | Train Epoch: 11 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11469 (0.12203) Boundary_loss: 0.013896 (0.013897) Loss: 0.12859 (0.13592) +2025-09-15,10:53:22 | INFO | Train Epoch: 11 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.13123 (0.12208) Boundary_loss: 0.013896 (0.013897) Loss: 0.14513 (0.13598) +2025-09-15,10:54:28 | INFO | Train Epoch: 11 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17037 (0.12239) Boundary_loss: 0.013898 (0.013897) Loss: 0.18427 (0.13629) +2025-09-15,10:55:34 | INFO | Train Epoch: 11 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.094401 (0.12222) Boundary_loss: 0.013897 (0.013897) Loss: 0.10830 (0.13611) +2025-09-15,10:56:39 | INFO | Train Epoch: 11 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12159 (0.12221) Boundary_loss: 0.013897 (0.013897) Loss: 0.13548 (0.13611) +2025-09-15,10:57:45 | INFO | Train Epoch: 11 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.089286 (0.12200) Boundary_loss: 0.013897 (0.013897) Loss: 0.10318 (0.13590) +2025-09-15,10:58:51 | INFO | Train Epoch: 11 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11992 (0.12199) Boundary_loss: 0.013896 (0.013897) Loss: 0.13381 (0.13589) +2025-09-15,10:59:57 | INFO | Train Epoch: 11 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13247 (0.12206) Boundary_loss: 0.013897 (0.013897) Loss: 0.14637 (0.13595) +2025-09-15,11:01:02 | INFO | Train Epoch: 11 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10182 (0.12193) Boundary_loss: 0.013901 (0.013897) Loss: 0.11572 (0.13583) +2025-09-15,11:02:08 | INFO | Train Epoch: 11 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13865 (0.12203) Boundary_loss: 0.013898 (0.013897) Loss: 0.15255 (0.13593) +2025-09-15,11:03:14 | INFO | Train Epoch: 11 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.12145 (0.12203) Boundary_loss: 0.013896 (0.013897) Loss: 0.13535 (0.13593) +2025-09-15,11:04:20 | INFO | Train Epoch: 11 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.092055 (0.12185) Boundary_loss: 0.013896 (0.013897) Loss: 0.10595 (0.13575) +2025-09-15,11:05:26 | INFO | Train Epoch: 11 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11650 (0.12182) Boundary_loss: 0.013899 (0.013897) Loss: 0.13040 (0.13571) +2025-09-15,11:06:32 | INFO | Train Epoch: 11 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.13193 (0.12188) Boundary_loss: 0.013896 (0.013897) Loss: 0.14582 (0.13578) +2025-09-15,11:07:38 | INFO | Train Epoch: 11 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.10491 (0.12178) Boundary_loss: 0.013897 (0.013897) Loss: 0.11880 (0.13567) +2025-09-15,11:08:43 | INFO | Train Epoch: 11 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.064067 (0.12144) Boundary_loss: 0.013897 (0.013897) Loss: 0.077964 (0.13533) +2025-09-15,11:09:49 | INFO | Train Epoch: 11 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.099452 (0.12131) Boundary_loss: 0.013897 (0.013897) Loss: 0.11335 (0.13520) +2025-09-15,11:10:55 | INFO | Train Epoch: 11 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.13042 (0.12136) Boundary_loss: 0.013898 (0.013897) Loss: 0.14432 (0.13526) +2025-09-15,11:12:01 | INFO | Train Epoch: 11 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.11500 (0.12132) Boundary_loss: 0.013899 (0.013897) Loss: 0.12890 (0.13522) +2025-09-15,11:13:07 | INFO | Train Epoch: 11 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.12770 (0.12136) Boundary_loss: 0.013897 (0.013897) Loss: 0.14160 (0.13526) +2025-09-15,11:14:13 | INFO | Train Epoch: 11 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.094382 (0.12120) Boundary_loss: 0.013897 (0.013897) Loss: 0.10828 (0.13510) +2025-09-15,11:15:18 | INFO | Train Epoch: 11 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.095997 (0.12106) Boundary_loss: 0.013897 (0.013897) Loss: 0.10989 (0.13496) +2025-09-15,11:16:24 | INFO | Train Epoch: 11 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11184 (0.12101) Boundary_loss: 0.013897 (0.013897) Loss: 0.12573 (0.13490) +2025-09-15,11:17:30 | INFO | Train Epoch: 11 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11331 (0.12096) Boundary_loss: 0.013897 (0.013897) Loss: 0.12720 (0.13486) +2025-09-15,11:18:36 | INFO | Train Epoch: 11 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16755 (0.12123) Boundary_loss: 0.013896 (0.013897) Loss: 0.18145 (0.13512) +2025-09-15,11:19:42 | INFO | Train Epoch: 11 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13554 (0.12131) Boundary_loss: 0.013896 (0.013897) Loss: 0.14944 (0.13520) +2025-09-15,11:20:48 | INFO | Train Epoch: 11 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12606 (0.12133) Boundary_loss: 0.013897 (0.013897) Loss: 0.13996 (0.13523) +2025-09-15,11:21:54 | INFO | Train Epoch: 11 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.099496 (0.12121) Boundary_loss: 0.013897 (0.013897) Loss: 0.11339 (0.13511) +2025-09-15,11:22:59 | INFO | Train Epoch: 11 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12025 (0.12121) Boundary_loss: 0.013898 (0.013897) Loss: 0.13414 (0.13510) +2025-09-15,11:24:05 | INFO | Train Epoch: 11 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.11740 (0.12119) Boundary_loss: 0.013898 (0.013897) Loss: 0.13130 (0.13508) +2025-09-15,11:25:11 | INFO | Train Epoch: 11 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.11582 (0.12116) Boundary_loss: 0.013898 (0.013897) Loss: 0.12971 (0.13505) +2025-09-15,11:26:17 | INFO | Train Epoch: 11 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.11525 (0.12112) Boundary_loss: 0.013897 (0.013897) Loss: 0.12915 (0.13502) +2025-09-15,11:27:23 | INFO | Train Epoch: 11 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10799 (0.12105) Boundary_loss: 0.013897 (0.013897) Loss: 0.12189 (0.13495) +2025-09-15,11:28:29 | INFO | Train Epoch: 11 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12054 (0.12105) Boundary_loss: 0.013897 (0.013897) Loss: 0.13444 (0.13495) +2025-09-15,11:29:35 | INFO | Train Epoch: 11 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11221 (0.12100) Boundary_loss: 0.013896 (0.013897) Loss: 0.12611 (0.13490) +2025-09-15,11:30:41 | INFO | Train Epoch: 11 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.086389 (0.12082) Boundary_loss: 0.013896 (0.013897) Loss: 0.10028 (0.13472) +2025-09-15,11:31:46 | INFO | Train Epoch: 11 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.10847 (0.12076) Boundary_loss: 0.013897 (0.013897) Loss: 0.12237 (0.13465) +2025-09-15,11:32:52 | INFO | Train Epoch: 11 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.089736 (0.12059) Boundary_loss: 0.013898 (0.013897) Loss: 0.10363 (0.13449) +2025-09-15,11:33:58 | INFO | Train Epoch: 11 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11822 (0.12058) Boundary_loss: 0.013897 (0.013897) Loss: 0.13212 (0.13448) +2025-09-15,11:35:04 | INFO | Train Epoch: 11 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.076848 (0.12035) Boundary_loss: 0.013896 (0.013897) Loss: 0.090744 (0.13425) +2025-09-15,11:36:10 | INFO | Train Epoch: 11 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.11499 (0.12033) Boundary_loss: 0.013897 (0.013897) Loss: 0.12889 (0.13422) +2025-09-15,11:37:16 | INFO | Train Epoch: 11 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.097805 (0.12021) Boundary_loss: 0.013896 (0.013897) Loss: 0.11170 (0.13411) +2025-09-15,11:38:21 | INFO | Train Epoch: 11 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.11114 (0.12017) Boundary_loss: 0.013897 (0.013897) Loss: 0.12504 (0.13406) +2025-09-15,11:39:27 | INFO | Train Epoch: 11 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12397 (0.12018) Boundary_loss: 0.013896 (0.013897) Loss: 0.13787 (0.13408) +2025-09-15,11:40:33 | INFO | Train Epoch: 11 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11447 (0.12016) Boundary_loss: 0.013895 (0.013897) Loss: 0.12837 (0.13405) +2025-09-15,11:41:39 | INFO | Train Epoch: 11 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.079124 (0.11995) Boundary_loss: 0.013896 (0.013897) Loss: 0.093020 (0.13385) +2025-09-15,11:42:45 | INFO | Train Epoch: 11 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.097480 (0.11984) Boundary_loss: 0.013897 (0.013897) Loss: 0.11138 (0.13373) +2025-09-15,11:43:51 | INFO | Train Epoch: 11 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.14691 (0.11997) Boundary_loss: 0.013898 (0.013897) Loss: 0.16081 (0.13387) +2025-09-15,11:44:57 | INFO | Train Epoch: 11 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13674 (0.12005) Boundary_loss: 0.013896 (0.013897) Loss: 0.15064 (0.13395) +2025-09-15,11:46:02 | INFO | Train Epoch: 11 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.11152 (0.12001) Boundary_loss: 0.013897 (0.013897) Loss: 0.12542 (0.13391) +2025-09-15,11:47:08 | INFO | Train Epoch: 11 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.11381 (0.11998) Boundary_loss: 0.013898 (0.013897) Loss: 0.12771 (0.13388) +2025-09-15,11:48:14 | INFO | Train Epoch: 11 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11188 (0.11994) Boundary_loss: 0.013896 (0.013897) Loss: 0.12578 (0.13384) +2025-09-15,11:49:20 | INFO | Train Epoch: 11 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10772 (0.11988) Boundary_loss: 0.013895 (0.013897) Loss: 0.12162 (0.13378) +2025-09-15,11:50:26 | INFO | Train Epoch: 11 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11555 (0.11986) Boundary_loss: 0.013898 (0.013897) Loss: 0.12945 (0.13376) +2025-09-15,11:51:32 | INFO | Train Epoch: 11 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12126 (0.11987) Boundary_loss: 0.013896 (0.013897) Loss: 0.13516 (0.13377) +2025-09-15,11:52:38 | INFO | Train Epoch: 11 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.094395 (0.11975) Boundary_loss: 0.013896 (0.013897) Loss: 0.10829 (0.13364) +2025-09-15,11:53:44 | INFO | Train Epoch: 11 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12178 (0.11976) Boundary_loss: 0.013897 (0.013897) Loss: 0.13568 (0.13365) +2025-09-15,11:54:50 | INFO | Train Epoch: 11 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11064 (0.11971) Boundary_loss: 0.013897 (0.013897) Loss: 0.12454 (0.13361) +2025-09-15,11:55:55 | INFO | Train Epoch: 11 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.14282 (0.11982) Boundary_loss: 0.013897 (0.013897) Loss: 0.15672 (0.13372) +2025-09-15,11:57:01 | INFO | Train Epoch: 11 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.099253 (0.11973) Boundary_loss: 0.013896 (0.013897) Loss: 0.11315 (0.13362) +2025-09-15,11:58:07 | INFO | Train Epoch: 11 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.083370 (0.11956) Boundary_loss: 0.013896 (0.013897) Loss: 0.097266 (0.13345) +2025-09-15,11:59:13 | INFO | Train Epoch: 11 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.099614 (0.11946) Boundary_loss: 0.013897 (0.013897) Loss: 0.11351 (0.13336) +2025-09-15,12:00:19 | INFO | Train Epoch: 11 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10794 (0.11941) Boundary_loss: 0.013897 (0.013897) Loss: 0.12183 (0.13331) +2025-09-15,12:01:25 | INFO | Train Epoch: 11 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11591 (0.11939) Boundary_loss: 0.013898 (0.013897) Loss: 0.12981 (0.13329) +2025-09-15,12:02:31 | INFO | Train Epoch: 11 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.11158 (0.11936) Boundary_loss: 0.013898 (0.013897) Loss: 0.12547 (0.13326) +2025-09-15,12:03:37 | INFO | Train Epoch: 11 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12349 (0.11938) Boundary_loss: 0.013896 (0.013897) Loss: 0.13738 (0.13327) +2025-09-15,12:04:42 | INFO | Train Epoch: 11 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.077635 (0.11919) Boundary_loss: 0.013897 (0.013897) Loss: 0.091533 (0.13308) +2025-09-15,12:05:48 | INFO | Train Epoch: 11 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.088860 (0.11905) Boundary_loss: 0.013899 (0.013897) Loss: 0.10276 (0.13295) +2025-09-15,12:06:54 | INFO | Train Epoch: 11 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.092826 (0.11893) Boundary_loss: 0.013898 (0.013897) Loss: 0.10672 (0.13283) +2025-09-15,12:08:00 | INFO | Train Epoch: 11 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10090 (0.11885) Boundary_loss: 0.013896 (0.013897) Loss: 0.11480 (0.13275) +2025-09-15,12:09:06 | INFO | Train Epoch: 11 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10784 (0.11880) Boundary_loss: 0.013896 (0.013897) Loss: 0.12174 (0.13270) +2025-09-15,12:10:12 | INFO | Train Epoch: 11 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.10832 (0.11876) Boundary_loss: 0.013898 (0.013897) Loss: 0.12222 (0.13265) +2025-09-15,12:11:17 | INFO | Train Epoch: 11 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12095 (0.11877) Boundary_loss: 0.013898 (0.013897) Loss: 0.13484 (0.13266) +2025-09-15,12:12:23 | INFO | Train Epoch: 11 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10816 (0.11872) Boundary_loss: 0.013895 (0.013897) Loss: 0.12206 (0.13262) +2025-09-15,12:13:29 | INFO | Train Epoch: 11 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.079815 (0.11855) Boundary_loss: 0.013896 (0.013897) Loss: 0.093710 (0.13245) +2025-09-15,12:14:35 | INFO | Train Epoch: 11 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.10651 (0.11850) Boundary_loss: 0.013899 (0.013897) Loss: 0.12041 (0.13239) +2025-09-15,12:15:41 | INFO | Train Epoch: 11 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.097801 (0.11841) Boundary_loss: 0.013898 (0.013897) Loss: 0.11170 (0.13230) +2025-09-15,12:16:47 | INFO | Train Epoch: 11 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.12449 (0.11843) Boundary_loss: 0.013898 (0.013897) Loss: 0.13839 (0.13233) +2025-09-15,12:17:53 | INFO | Train Epoch: 11 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10551 (0.11838) Boundary_loss: 0.013896 (0.013897) Loss: 0.11940 (0.13227) +2025-09-15,12:18:58 | INFO | Train Epoch: 11 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14149 (0.11848) Boundary_loss: 0.013896 (0.013897) Loss: 0.15538 (0.13237) +2025-09-15,12:20:04 | INFO | Train Epoch: 11 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.078696 (0.11831) Boundary_loss: 0.013897 (0.013897) Loss: 0.092592 (0.13220) +2025-09-15,12:21:10 | INFO | Train Epoch: 11 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.10951 (0.11827) Boundary_loss: 0.013898 (0.013897) Loss: 0.12341 (0.13216) +2025-09-15,12:22:16 | INFO | Train Epoch: 11 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10387 (0.11821) Boundary_loss: 0.013895 (0.013897) Loss: 0.11776 (0.13210) +2025-09-15,12:23:22 | INFO | Train Epoch: 11 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.11266 (0.11818) Boundary_loss: 0.013898 (0.013897) Loss: 0.12656 (0.13208) +2025-09-15,12:24:28 | INFO | Train Epoch: 11 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.11535 (0.11817) Boundary_loss: 0.013897 (0.013897) Loss: 0.12924 (0.13207) +2025-09-15,12:25:34 | INFO | Train Epoch: 11 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10151 (0.11810) Boundary_loss: 0.013897 (0.013897) Loss: 0.11540 (0.13200) +2025-09-15,12:26:39 | INFO | Train Epoch: 11 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11148 (0.11807) Boundary_loss: 0.013898 (0.013897) Loss: 0.12538 (0.13197) +2025-09-15,12:27:45 | INFO | Train Epoch: 11 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11805 (0.11807) Boundary_loss: 0.013897 (0.013897) Loss: 0.13195 (0.13197) +2025-09-15,12:28:51 | INFO | Train Epoch: 11 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.096951 (0.11799) Boundary_loss: 0.013897 (0.013897) Loss: 0.11085 (0.13188) +2025-09-15,12:29:57 | INFO | Train Epoch: 11 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.076213 (0.11781) Boundary_loss: 0.013897 (0.013897) Loss: 0.090110 (0.13171) +2025-09-15,12:31:03 | INFO | Train Epoch: 11 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13104 (0.11787) Boundary_loss: 0.013897 (0.013897) Loss: 0.14494 (0.13177) +2025-09-15,12:32:09 | INFO | Train Epoch: 11 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.13636 (0.11794) Boundary_loss: 0.013896 (0.013897) Loss: 0.15025 (0.13184) +2025-09-15,12:33:14 | INFO | Train Epoch: 11 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.073562 (0.11776) Boundary_loss: 0.013896 (0.013897) Loss: 0.087458 (0.13166) +2025-09-15,12:34:20 | INFO | Train Epoch: 11 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11638 (0.11776) Boundary_loss: 0.013896 (0.013897) Loss: 0.13028 (0.13166) +2025-09-15,12:35:26 | INFO | Train Epoch: 11 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.15477 (0.11791) Boundary_loss: 0.013897 (0.013897) Loss: 0.16867 (0.13180) +2025-09-15,12:36:32 | INFO | Train Epoch: 11 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.10319 (0.11785) Boundary_loss: 0.013897 (0.013897) Loss: 0.11708 (0.13175) +2025-09-15,12:37:38 | INFO | Train Epoch: 11 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.093221 (0.11775) Boundary_loss: 0.013899 (0.013897) Loss: 0.10712 (0.13165) +2025-09-15,12:38:44 | INFO | Train Epoch: 11 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.078256 (0.11759) Boundary_loss: 0.013898 (0.013897) Loss: 0.092154 (0.13149) +2025-09-15,12:39:50 | INFO | Train Epoch: 11 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.10866 (0.11756) Boundary_loss: 0.013897 (0.013897) Loss: 0.12256 (0.13145) +2025-09-15,12:40:55 | INFO | Train Epoch: 11 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.094570 (0.11747) Boundary_loss: 0.013897 (0.013897) Loss: 0.10847 (0.13136) +2025-09-15,12:42:01 | INFO | Train Epoch: 11 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11654 (0.11746) Boundary_loss: 0.013896 (0.013897) Loss: 0.13043 (0.13136) +2025-09-15,12:43:07 | INFO | Train Epoch: 11 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10390 (0.11741) Boundary_loss: 0.013896 (0.013897) Loss: 0.11780 (0.13131) +2025-09-15,12:44:13 | INFO | Train Epoch: 11 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10672 (0.11737) Boundary_loss: 0.013896 (0.013897) Loss: 0.12061 (0.13126) +2025-09-15,12:45:19 | INFO | Train Epoch: 11 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.084120 (0.11724) Boundary_loss: 0.013899 (0.013897) Loss: 0.098019 (0.13114) +2025-09-15,12:46:25 | INFO | Train Epoch: 11 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.089651 (0.11713) Boundary_loss: 0.013895 (0.013897) Loss: 0.10355 (0.13103) +2025-09-15,12:47:30 | INFO | Train Epoch: 11 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11303 (0.11712) Boundary_loss: 0.013896 (0.013897) Loss: 0.12693 (0.13101) +2025-09-15,12:48:36 | INFO | Train Epoch: 11 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.10983 (0.11709) Boundary_loss: 0.013897 (0.013897) Loss: 0.12373 (0.13098) +2025-09-15,12:49:42 | INFO | Train Epoch: 11 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11509 (0.11708) Boundary_loss: 0.013896 (0.013897) Loss: 0.12899 (0.13098) +2025-09-15,12:50:48 | INFO | Train Epoch: 11 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.085063 (0.11696) Boundary_loss: 0.013897 (0.013897) Loss: 0.098959 (0.13085) +2025-09-15,12:51:54 | INFO | Train Epoch: 11 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10511 (0.11691) Boundary_loss: 0.013898 (0.013897) Loss: 0.11901 (0.13081) +2025-09-15,12:53:00 | INFO | Train Epoch: 11 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13014 (0.11696) Boundary_loss: 0.013897 (0.013897) Loss: 0.14404 (0.13086) +2025-09-15,12:54:06 | INFO | Train Epoch: 11 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.087544 (0.11685) Boundary_loss: 0.013897 (0.013897) Loss: 0.10144 (0.13075) +2025-09-15,12:55:11 | INFO | Train Epoch: 11 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.12950 (0.11690) Boundary_loss: 0.013897 (0.013897) Loss: 0.14340 (0.13080) +2025-09-15,12:56:17 | INFO | Train Epoch: 11 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.092629 (0.11681) Boundary_loss: 0.013897 (0.013897) Loss: 0.10653 (0.13071) +2025-09-15,12:57:23 | INFO | Train Epoch: 11 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.10175 (0.11675) Boundary_loss: 0.013897 (0.013897) Loss: 0.11565 (0.13065) +2025-09-15,12:58:29 | INFO | Train Epoch: 11 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.12426 (0.11678) Boundary_loss: 0.013897 (0.013897) Loss: 0.13816 (0.13068) +2025-09-15,12:59:35 | INFO | Train Epoch: 11 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13653 (0.11685) Boundary_loss: 0.013899 (0.013897) Loss: 0.15043 (0.13075) +2025-09-15,13:00:41 | INFO | Train Epoch: 11 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.086525 (0.11674) Boundary_loss: 0.013898 (0.013897) Loss: 0.10042 (0.13064) +2025-09-15,13:01:46 | INFO | Train Epoch: 11 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.10739 (0.11671) Boundary_loss: 0.013898 (0.013897) Loss: 0.12129 (0.13060) +2025-09-15,13:02:52 | INFO | Train Epoch: 11 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.13265 (0.11677) Boundary_loss: 0.013896 (0.013897) Loss: 0.14655 (0.13066) +2025-09-15,13:03:58 | INFO | Train Epoch: 11 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12519 (0.11680) Boundary_loss: 0.013899 (0.013897) Loss: 0.13909 (0.13069) +2025-09-15,13:05:04 | INFO | Train Epoch: 11 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12452 (0.11682) Boundary_loss: 0.013897 (0.013897) Loss: 0.13841 (0.13072) +2025-09-15,13:06:10 | INFO | Train Epoch: 11 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10392 (0.11678) Boundary_loss: 0.013896 (0.013897) Loss: 0.11782 (0.13067) +2025-09-15,13:07:16 | INFO | Train Epoch: 11 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11666 (0.11678) Boundary_loss: 0.013895 (0.013897) Loss: 0.13055 (0.13067) +2025-09-15,13:08:22 | INFO | Train Epoch: 11 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.14191 (0.11687) Boundary_loss: 0.013898 (0.013897) Loss: 0.15581 (0.13076) +2025-09-15,13:09:28 | INFO | Train Epoch: 11 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.099344 (0.11680) Boundary_loss: 0.013898 (0.013897) Loss: 0.11324 (0.13070) +2025-09-15,13:10:33 | INFO | Train Epoch: 11 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.056075 (0.11659) Boundary_loss: 0.013897 (0.013897) Loss: 0.069973 (0.13049) +2025-09-15,13:11:39 | INFO | Train Epoch: 11 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.087755 (0.11649) Boundary_loss: 0.013896 (0.013897) Loss: 0.10165 (0.13038) +2025-09-15,13:12:45 | INFO | Train Epoch: 11 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11129 (0.11647) Boundary_loss: 0.013897 (0.013897) Loss: 0.12518 (0.13036) +2025-09-15,13:13:51 | INFO | Train Epoch: 11 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.088416 (0.11637) Boundary_loss: 0.013896 (0.013897) Loss: 0.10231 (0.13026) +2025-09-15,13:14:57 | INFO | Train Epoch: 11 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11116 (0.11635) Boundary_loss: 0.013898 (0.013897) Loss: 0.12506 (0.13025) +2025-09-15,13:16:03 | INFO | Train Epoch: 11 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.13352 (0.11641) Boundary_loss: 0.013898 (0.013897) Loss: 0.14741 (0.13031) +2025-09-15,13:17:09 | INFO | Train Epoch: 11 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.14452 (0.11651) Boundary_loss: 0.013896 (0.013897) Loss: 0.15841 (0.13041) +2025-09-15,13:18:15 | INFO | Train Epoch: 11 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.097013 (0.11644) Boundary_loss: 0.013896 (0.013897) Loss: 0.11091 (0.13034) +2025-09-15,13:19:21 | INFO | Train Epoch: 11 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11630 (0.11644) Boundary_loss: 0.013897 (0.013897) Loss: 0.13019 (0.13034) +2025-09-15,13:20:26 | INFO | Train Epoch: 11 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12081 (0.11645) Boundary_loss: 0.013896 (0.013897) Loss: 0.13470 (0.13035) +2025-09-15,13:21:32 | INFO | Train Epoch: 11 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11282 (0.11644) Boundary_loss: 0.013896 (0.013897) Loss: 0.12672 (0.13034) +2025-09-15,13:22:38 | INFO | Train Epoch: 11 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13882 (0.11652) Boundary_loss: 0.013896 (0.013897) Loss: 0.15272 (0.13042) +2025-09-15,13:23:44 | INFO | Train Epoch: 11 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10402 (0.11648) Boundary_loss: 0.013895 (0.013897) Loss: 0.11791 (0.13037) +2025-09-15,13:24:50 | INFO | Train Epoch: 11 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13180 (0.11653) Boundary_loss: 0.013896 (0.013897) Loss: 0.14569 (0.13043) +2025-09-15,13:25:56 | INFO | Train Epoch: 11 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.085692 (0.11642) Boundary_loss: 0.013896 (0.013897) Loss: 0.099588 (0.13032) +2025-09-15,13:27:02 | INFO | Train Epoch: 11 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.099789 (0.11637) Boundary_loss: 0.013897 (0.013897) Loss: 0.11369 (0.13026) +2025-09-15,13:28:08 | INFO | Train Epoch: 11 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12707 (0.11640) Boundary_loss: 0.013897 (0.013897) Loss: 0.14096 (0.13030) +2025-09-15,13:29:14 | INFO | Train Epoch: 11 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.10644 (0.11637) Boundary_loss: 0.013895 (0.013897) Loss: 0.12033 (0.13027) +2025-09-15,13:30:20 | INFO | Train Epoch: 11 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.087752 (0.11627) Boundary_loss: 0.013897 (0.013897) Loss: 0.10165 (0.13017) +2025-09-15,13:31:26 | INFO | Train Epoch: 11 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12544 (0.11630) Boundary_loss: 0.013897 (0.013897) Loss: 0.13933 (0.13020) +2025-09-15,13:32:32 | INFO | Train Epoch: 11 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.14919 (0.11641) Boundary_loss: 0.013897 (0.013897) Loss: 0.16309 (0.13031) +2025-09-15,13:33:38 | INFO | Train Epoch: 11 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.090727 (0.11633) Boundary_loss: 0.013897 (0.013897) Loss: 0.10462 (0.13023) +2025-09-15,13:34:43 | INFO | Train Epoch: 11 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12286 (0.11635) Boundary_loss: 0.013898 (0.013897) Loss: 0.13676 (0.13025) +2025-09-15,13:35:49 | INFO | Train Epoch: 11 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.056552 (0.11615) Boundary_loss: 0.013896 (0.013897) Loss: 0.070448 (0.13005) +2025-09-15,13:36:55 | INFO | Train Epoch: 11 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10008 (0.11610) Boundary_loss: 0.013896 (0.013897) Loss: 0.11398 (0.13000) +2025-09-15,13:38:01 | INFO | Train Epoch: 11 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.087084 (0.11600) Boundary_loss: 0.013895 (0.013897) Loss: 0.10098 (0.12990) +2025-09-15,13:39:07 | INFO | Train Epoch: 11 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.098470 (0.11595) Boundary_loss: 0.013897 (0.013897) Loss: 0.11237 (0.12984) +2025-09-15,13:40:13 | INFO | Train Epoch: 11 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.087240 (0.11585) Boundary_loss: 0.013898 (0.013897) Loss: 0.10114 (0.12975) +2025-09-15,13:41:19 | INFO | Train Epoch: 11 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12801 (0.11589) Boundary_loss: 0.013898 (0.013897) Loss: 0.14191 (0.12979) +2025-09-15,13:42:25 | INFO | Train Epoch: 11 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11876 (0.11590) Boundary_loss: 0.013897 (0.013897) Loss: 0.13266 (0.12980) +2025-09-15,13:43:31 | INFO | Train Epoch: 11 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.097512 (0.11584) Boundary_loss: 0.013897 (0.013897) Loss: 0.11141 (0.12974) +2025-09-15,13:44:37 | INFO | Train Epoch: 11 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.096361 (0.11578) Boundary_loss: 0.013899 (0.013897) Loss: 0.11026 (0.12968) +2025-09-15,13:45:43 | INFO | Train Epoch: 11 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12294 (0.11580) Boundary_loss: 0.013896 (0.013897) Loss: 0.13684 (0.12970) +2025-09-15,13:46:49 | INFO | Train Epoch: 11 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10207 (0.11576) Boundary_loss: 0.013897 (0.013897) Loss: 0.11596 (0.12966) +2025-09-15,13:47:54 | INFO | Train Epoch: 11 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.076752 (0.11564) Boundary_loss: 0.013896 (0.013897) Loss: 0.090648 (0.12953) +2025-09-15,13:49:00 | INFO | Train Epoch: 11 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10272 (0.11559) Boundary_loss: 0.013897 (0.013897) Loss: 0.11662 (0.12949) +2025-09-15,13:50:06 | INFO | Train Epoch: 11 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.067333 (0.11544) Boundary_loss: 0.013896 (0.013897) Loss: 0.081229 (0.12934) +2025-09-15,13:51:12 | INFO | Train Epoch: 11 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.11663 (0.11545) Boundary_loss: 0.013898 (0.013897) Loss: 0.13053 (0.12934) +2025-09-15,13:52:18 | INFO | Train Epoch: 11 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.090221 (0.11537) Boundary_loss: 0.013900 (0.013897) Loss: 0.10412 (0.12926) +2025-09-15,13:53:24 | INFO | Train Epoch: 11 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.093483 (0.11530) Boundary_loss: 0.013897 (0.013897) Loss: 0.10738 (0.12919) +2025-09-15,13:54:30 | INFO | Train Epoch: 11 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10014 (0.11525) Boundary_loss: 0.013896 (0.013897) Loss: 0.11404 (0.12915) +2025-09-15,13:55:36 | INFO | Train Epoch: 11 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.11683 (0.11526) Boundary_loss: 0.013897 (0.013897) Loss: 0.13072 (0.12915) +2025-09-15,13:56:42 | INFO | Train Epoch: 11 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.12466 (0.11528) Boundary_loss: 0.013896 (0.013897) Loss: 0.13856 (0.12918) +2025-09-15,13:57:48 | INFO | Train Epoch: 11 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.097740 (0.11523) Boundary_loss: 0.013897 (0.013897) Loss: 0.11164 (0.12913) +2025-09-15,13:58:54 | INFO | Train Epoch: 11 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11018 (0.11521) Boundary_loss: 0.013896 (0.013897) Loss: 0.12408 (0.12911) +2025-09-15,14:00:00 | INFO | Train Epoch: 11 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.083448 (0.11512) Boundary_loss: 0.013897 (0.013897) Loss: 0.097345 (0.12901) +2025-09-15,14:01:06 | INFO | Train Epoch: 11 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.086582 (0.11503) Boundary_loss: 0.013897 (0.013897) Loss: 0.10048 (0.12893) +2025-09-15,14:02:12 | INFO | Train Epoch: 11 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10561 (0.11500) Boundary_loss: 0.013896 (0.013897) Loss: 0.11950 (0.12890) +2025-09-15,14:03:18 | INFO | Train Epoch: 11 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.096882 (0.11495) Boundary_loss: 0.013896 (0.013897) Loss: 0.11078 (0.12884) +2025-09-15,14:04:23 | INFO | Train Epoch: 11 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.087738 (0.11486) Boundary_loss: 0.013897 (0.013897) Loss: 0.10163 (0.12876) +2025-09-15,14:05:29 | INFO | Train Epoch: 11 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10188 (0.11482) Boundary_loss: 0.013897 (0.013897) Loss: 0.11578 (0.12872) +2025-09-15,14:06:35 | INFO | Train Epoch: 11 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13239 (0.11488) Boundary_loss: 0.013898 (0.013897) Loss: 0.14629 (0.12877) +2025-09-15,14:07:41 | INFO | Train Epoch: 11 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.083090 (0.11478) Boundary_loss: 0.013898 (0.013897) Loss: 0.096987 (0.12868) +2025-09-15,14:08:47 | INFO | Train Epoch: 11 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11368 (0.11478) Boundary_loss: 0.013896 (0.013897) Loss: 0.12757 (0.12867) +2025-09-15,14:09:53 | INFO | Train Epoch: 11 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.13922 (0.11485) Boundary_loss: 0.013897 (0.013897) Loss: 0.15312 (0.12875) +2025-09-15,14:10:59 | INFO | Train Epoch: 11 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.074752 (0.11473) Boundary_loss: 0.013898 (0.013897) Loss: 0.088650 (0.12863) +2025-09-15,14:12:05 | INFO | Train Epoch: 11 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11641 (0.11474) Boundary_loss: 0.013895 (0.013897) Loss: 0.13030 (0.12863) +2025-09-15,14:13:11 | INFO | Train Epoch: 11 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12233 (0.11476) Boundary_loss: 0.013895 (0.013897) Loss: 0.13623 (0.12866) +2025-09-15,14:14:17 | INFO | Train Epoch: 11 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13153 (0.11481) Boundary_loss: 0.013898 (0.013897) Loss: 0.14543 (0.12871) +2025-09-15,14:15:23 | INFO | Train Epoch: 11 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13023 (0.11485) Boundary_loss: 0.013896 (0.013897) Loss: 0.14413 (0.12875) +2025-09-15,14:16:29 | INFO | Train Epoch: 11 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.098268 (0.11480) Boundary_loss: 0.013896 (0.013897) Loss: 0.11216 (0.12870) +2025-09-15,14:17:35 | INFO | Train Epoch: 11 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10978 (0.11479) Boundary_loss: 0.013895 (0.013897) Loss: 0.12367 (0.12869) +2025-09-15,14:18:41 | INFO | Train Epoch: 11 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.099237 (0.11474) Boundary_loss: 0.013897 (0.013897) Loss: 0.11313 (0.12864) +2025-09-15,14:19:47 | INFO | Train Epoch: 11 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.087005 (0.11466) Boundary_loss: 0.013895 (0.013897) Loss: 0.10090 (0.12856) +2025-09-15,14:20:53 | INFO | Train Epoch: 11 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10039 (0.11462) Boundary_loss: 0.013897 (0.013897) Loss: 0.11429 (0.12852) +2025-09-15,14:21:58 | INFO | Train Epoch: 11 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11477 (0.11462) Boundary_loss: 0.013895 (0.013897) Loss: 0.12866 (0.12852) +2025-09-15,14:23:04 | INFO | Train Epoch: 11 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13009 (0.11467) Boundary_loss: 0.013897 (0.013897) Loss: 0.14399 (0.12856) +2025-09-15,14:24:10 | INFO | Train Epoch: 11 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10678 (0.11464) Boundary_loss: 0.013897 (0.013897) Loss: 0.12068 (0.12854) +2025-09-15,14:25:16 | INFO | Train Epoch: 11 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11483 (0.11465) Boundary_loss: 0.013897 (0.013897) Loss: 0.12873 (0.12854) +2025-09-15,14:26:22 | INFO | Train Epoch: 11 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.094004 (0.11459) Boundary_loss: 0.013897 (0.013897) Loss: 0.10790 (0.12848) +2025-09-15,14:27:28 | INFO | Train Epoch: 11 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.084519 (0.11450) Boundary_loss: 0.013896 (0.013897) Loss: 0.098415 (0.12840) +2025-09-15,14:28:34 | INFO | Train Epoch: 11 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11388 (0.11450) Boundary_loss: 0.013896 (0.013897) Loss: 0.12778 (0.12840) +2025-09-15,14:29:40 | INFO | Train Epoch: 11 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12846 (0.11454) Boundary_loss: 0.013896 (0.013897) Loss: 0.14235 (0.12843) +2025-09-15,14:30:46 | INFO | Train Epoch: 11 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.16506 (0.11468) Boundary_loss: 0.013897 (0.013897) Loss: 0.17896 (0.12858) +2025-09-15,14:31:52 | INFO | Train Epoch: 11 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14515 (0.11477) Boundary_loss: 0.013898 (0.013897) Loss: 0.15905 (0.12866) +2025-09-15,14:32:58 | INFO | Train Epoch: 11 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.11189 (0.11476) Boundary_loss: 0.013898 (0.013897) Loss: 0.12579 (0.12866) +2025-09-15,14:34:04 | INFO | Train Epoch: 11 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.092893 (0.11470) Boundary_loss: 0.013895 (0.013897) Loss: 0.10679 (0.12859) +2025-09-15,14:35:10 | INFO | Train Epoch: 11 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.11534 (0.11470) Boundary_loss: 0.013897 (0.013897) Loss: 0.12923 (0.12860) +2025-09-15,14:36:16 | INFO | Train Epoch: 11 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.17380 (0.11486) Boundary_loss: 0.013897 (0.013897) Loss: 0.18770 (0.12876) +2025-09-15,14:37:22 | INFO | Train Epoch: 11 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13037 (0.11491) Boundary_loss: 0.013897 (0.013897) Loss: 0.14427 (0.12880) +2025-09-15,14:38:28 | INFO | Train Epoch: 11 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.097352 (0.11486) Boundary_loss: 0.013897 (0.013897) Loss: 0.11125 (0.12876) +2025-09-15,14:39:34 | INFO | Train Epoch: 11 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.080089 (0.11476) Boundary_loss: 0.013896 (0.013897) Loss: 0.093985 (0.12866) +2025-09-15,14:40:40 | INFO | Train Epoch: 11 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11199 (0.11475) Boundary_loss: 0.013898 (0.013897) Loss: 0.12589 (0.12865) +2025-09-15,14:41:45 | INFO | Train Epoch: 11 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.093622 (0.11470) Boundary_loss: 0.013897 (0.013897) Loss: 0.10752 (0.12859) +2025-09-15,14:42:51 | INFO | Train Epoch: 11 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13155 (0.11474) Boundary_loss: 0.013897 (0.013897) Loss: 0.14544 (0.12864) +2025-09-15,14:43:57 | INFO | Train Epoch: 11 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10787 (0.11472) Boundary_loss: 0.013898 (0.013897) Loss: 0.12177 (0.12862) +2025-09-15,14:45:03 | INFO | Train Epoch: 11 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11234 (0.11472) Boundary_loss: 0.013899 (0.013897) Loss: 0.12624 (0.12861) +2025-09-15,14:46:09 | INFO | Train Epoch: 11 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.086586 (0.11464) Boundary_loss: 0.013897 (0.013897) Loss: 0.10048 (0.12854) +2025-09-15,14:47:15 | INFO | Train Epoch: 11 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10551 (0.11462) Boundary_loss: 0.013896 (0.013897) Loss: 0.11940 (0.12851) +2025-09-15,14:48:21 | INFO | Train Epoch: 11 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11146 (0.11461) Boundary_loss: 0.013895 (0.013897) Loss: 0.12535 (0.12850) +2025-09-15,14:49:27 | INFO | Train Epoch: 11 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.094011 (0.11455) Boundary_loss: 0.013896 (0.013897) Loss: 0.10791 (0.12845) +2025-09-15,14:50:33 | INFO | Train Epoch: 11 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.12015 (0.11457) Boundary_loss: 0.013897 (0.013897) Loss: 0.13404 (0.12846) +2025-09-15,14:51:39 | INFO | Train Epoch: 11 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.094370 (0.11451) Boundary_loss: 0.013896 (0.013897) Loss: 0.10827 (0.12841) +2025-09-15,14:52:45 | INFO | Train Epoch: 11 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.11426 (0.11451) Boundary_loss: 0.013895 (0.013897) Loss: 0.12815 (0.12841) +2025-09-15,14:53:51 | INFO | Train Epoch: 11 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11529 (0.11451) Boundary_loss: 0.013897 (0.013897) Loss: 0.12918 (0.12841) +2025-09-15,14:54:57 | INFO | Train Epoch: 11 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11992 (0.11453) Boundary_loss: 0.013896 (0.013897) Loss: 0.13382 (0.12843) +2025-09-15,14:56:03 | INFO | Train Epoch: 11 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12268 (0.11455) Boundary_loss: 0.013898 (0.013897) Loss: 0.13658 (0.12845) +2025-09-15,14:57:09 | INFO | Train Epoch: 11 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10421 (0.11452) Boundary_loss: 0.013896 (0.013897) Loss: 0.11811 (0.12842) +2025-09-15,14:58:15 | INFO | Train Epoch: 11 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11303 (0.11452) Boundary_loss: 0.013897 (0.013897) Loss: 0.12693 (0.12842) +2025-09-15,14:59:21 | INFO | Train Epoch: 11 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.075834 (0.11442) Boundary_loss: 0.013896 (0.013897) Loss: 0.089730 (0.12831) +2025-09-15,15:00:27 | INFO | Train Epoch: 11 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.12130 (0.11443) Boundary_loss: 0.013897 (0.013897) Loss: 0.13520 (0.12833) +2025-09-15,15:01:33 | INFO | Train Epoch: 11 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11752 (0.11444) Boundary_loss: 0.013899 (0.013897) Loss: 0.13142 (0.12834) +2025-09-15,15:02:39 | INFO | Train Epoch: 11 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14334 (0.11452) Boundary_loss: 0.013897 (0.013897) Loss: 0.15723 (0.12842) +2025-09-15,15:03:44 | INFO | Train Epoch: 11 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.15058 (0.11461) Boundary_loss: 0.013898 (0.013897) Loss: 0.16448 (0.12851) +2025-09-15,15:04:50 | INFO | Train Epoch: 11 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14305 (0.11469) Boundary_loss: 0.013897 (0.013897) Loss: 0.15694 (0.12858) +2025-09-15,15:05:56 | INFO | Train Epoch: 11 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.11499 (0.11469) Boundary_loss: 0.013901 (0.013897) Loss: 0.12889 (0.12858) +2025-09-15,15:07:02 | INFO | Train Epoch: 11 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11445 (0.11469) Boundary_loss: 0.013895 (0.013897) Loss: 0.12834 (0.12858) +2025-09-15,15:08:08 | INFO | Train Epoch: 11 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.061293 (0.11455) Boundary_loss: 0.013896 (0.013897) Loss: 0.075189 (0.12845) +2025-09-15,15:09:14 | INFO | Train Epoch: 11 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.074182 (0.11444) Boundary_loss: 0.013898 (0.013897) Loss: 0.088080 (0.12834) +2025-09-15,15:10:20 | INFO | Train Epoch: 11 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12975 (0.11448) Boundary_loss: 0.013898 (0.013897) Loss: 0.14365 (0.12838) +2025-09-15,15:11:26 | INFO | Train Epoch: 11 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11748 (0.11449) Boundary_loss: 0.013898 (0.013897) Loss: 0.13137 (0.12839) +2025-09-15,15:12:32 | INFO | Train Epoch: 11 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13415 (0.11454) Boundary_loss: 0.013896 (0.013897) Loss: 0.14805 (0.12844) +2025-09-15,15:13:38 | INFO | Train Epoch: 11 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.093676 (0.11449) Boundary_loss: 0.013895 (0.013897) Loss: 0.10757 (0.12839) +2025-09-15,15:14:44 | INFO | Train Epoch: 11 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10239 (0.11446) Boundary_loss: 0.013896 (0.013897) Loss: 0.11629 (0.12836) +2025-09-15,15:15:50 | INFO | Train Epoch: 11 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13522 (0.11451) Boundary_loss: 0.013896 (0.013897) Loss: 0.14911 (0.12841) +2025-09-15,15:16:56 | INFO | Train Epoch: 11 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10026 (0.11447) Boundary_loss: 0.013896 (0.013897) Loss: 0.11415 (0.12837) +2025-09-15,15:18:02 | INFO | Train Epoch: 11 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.082008 (0.11439) Boundary_loss: 0.013895 (0.013897) Loss: 0.095903 (0.12829) +2025-09-15,15:19:08 | INFO | Train Epoch: 11 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.088987 (0.11433) Boundary_loss: 0.013897 (0.013897) Loss: 0.10288 (0.12823) +2025-09-15,15:20:14 | INFO | Train Epoch: 11 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12722 (0.11436) Boundary_loss: 0.013897 (0.013897) Loss: 0.14112 (0.12826) +2025-09-15,15:21:20 | INFO | Train Epoch: 11 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.097882 (0.11432) Boundary_loss: 0.013897 (0.013897) Loss: 0.11178 (0.12822) +2025-09-15,15:22:26 | INFO | Train Epoch: 11 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11875 (0.11433) Boundary_loss: 0.013898 (0.013897) Loss: 0.13264 (0.12823) +2025-09-15,15:23:32 | INFO | Train Epoch: 11 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.17334 (0.11448) Boundary_loss: 0.013896 (0.013897) Loss: 0.18723 (0.12838) +2025-09-15,15:24:38 | INFO | Train Epoch: 11 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.11933 (0.11449) Boundary_loss: 0.013896 (0.013897) Loss: 0.13323 (0.12839) +2025-09-15,15:25:44 | INFO | Train Epoch: 11 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.13284 (0.11454) Boundary_loss: 0.013899 (0.013897) Loss: 0.14674 (0.12843) +2025-09-15,15:26:50 | INFO | Train Epoch: 11 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11980 (0.11455) Boundary_loss: 0.013897 (0.013897) Loss: 0.13370 (0.12845) +2025-09-15,15:27:56 | INFO | Train Epoch: 11 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15037 (0.11464) Boundary_loss: 0.013896 (0.013897) Loss: 0.16427 (0.12853) +2025-09-15,15:29:01 | INFO | Train Epoch: 11 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14541 (0.11471) Boundary_loss: 0.013898 (0.013897) Loss: 0.15931 (0.12861) +2025-09-15,15:30:07 | INFO | Train Epoch: 11 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.098180 (0.11467) Boundary_loss: 0.013896 (0.013897) Loss: 0.11208 (0.12857) +2025-09-15,15:31:13 | INFO | Train Epoch: 11 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10251 (0.11464) Boundary_loss: 0.013896 (0.013897) Loss: 0.11641 (0.12854) +2025-09-15,15:32:19 | INFO | Train Epoch: 11 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11020 (0.11463) Boundary_loss: 0.013897 (0.013897) Loss: 0.12409 (0.12853) +2025-09-15,15:33:25 | INFO | Train Epoch: 11 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.11202 (0.11463) Boundary_loss: 0.013897 (0.013897) Loss: 0.12591 (0.12852) +2025-09-15,15:34:31 | INFO | Train Epoch: 11 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.060701 (0.11449) Boundary_loss: 0.013896 (0.013897) Loss: 0.074597 (0.12839) +2025-09-15,15:35:37 | INFO | Train Epoch: 11 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.080254 (0.11441) Boundary_loss: 0.013895 (0.013897) Loss: 0.094148 (0.12831) +2025-09-15,15:36:43 | INFO | Train Epoch: 11 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11835 (0.11442) Boundary_loss: 0.013897 (0.013897) Loss: 0.13225 (0.12832) +2025-09-15,15:37:49 | INFO | Train Epoch: 11 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.094550 (0.11437) Boundary_loss: 0.013897 (0.013897) Loss: 0.10845 (0.12827) +2025-09-15,15:38:55 | INFO | Train Epoch: 11 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.10869 (0.11436) Boundary_loss: 0.013897 (0.013897) Loss: 0.12258 (0.12826) +2025-09-15,15:40:01 | INFO | Train Epoch: 11 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.14561 (0.11443) Boundary_loss: 0.013899 (0.013897) Loss: 0.15951 (0.12833) +2025-09-15,15:41:07 | INFO | Train Epoch: 11 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.063362 (0.11431) Boundary_loss: 0.013898 (0.013897) Loss: 0.077260 (0.12821) +2025-09-15,15:42:13 | INFO | Train Epoch: 11 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10072 (0.11428) Boundary_loss: 0.013896 (0.013897) Loss: 0.11461 (0.12818) +2025-09-15,15:43:19 | INFO | Train Epoch: 11 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10214 (0.11425) Boundary_loss: 0.013897 (0.013897) Loss: 0.11604 (0.12815) +2025-09-15,15:44:25 | INFO | Train Epoch: 11 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10345 (0.11422) Boundary_loss: 0.013896 (0.013897) Loss: 0.11734 (0.12812) +2025-09-15,15:45:31 | INFO | Train Epoch: 11 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11087 (0.11422) Boundary_loss: 0.013896 (0.013897) Loss: 0.12477 (0.12811) +2025-09-15,15:46:37 | INFO | Train Epoch: 11 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.12608 (0.11424) Boundary_loss: 0.013895 (0.013897) Loss: 0.13998 (0.12814) +2025-09-15,15:47:43 | INFO | Train Epoch: 11 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.082328 (0.11417) Boundary_loss: 0.013897 (0.013897) Loss: 0.096225 (0.12807) +2025-09-15,15:48:49 | INFO | Train Epoch: 11 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.062919 (0.11405) Boundary_loss: 0.013897 (0.013897) Loss: 0.076816 (0.12795) +2025-09-15,15:49:54 | INFO | Train Epoch: 11 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12677 (0.11408) Boundary_loss: 0.013896 (0.013897) Loss: 0.14067 (0.12798) +2025-09-15,15:51:00 | INFO | Train Epoch: 11 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14993 (0.11416) Boundary_loss: 0.013897 (0.013897) Loss: 0.16383 (0.12806) +2025-09-15,15:52:06 | INFO | Train Epoch: 11 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.099988 (0.11413) Boundary_loss: 0.013896 (0.013897) Loss: 0.11388 (0.12803) +2025-09-15,15:53:12 | INFO | Train Epoch: 11 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.099689 (0.11410) Boundary_loss: 0.013898 (0.013897) Loss: 0.11359 (0.12799) +2025-09-15,15:54:18 | INFO | Train Epoch: 11 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.094399 (0.11405) Boundary_loss: 0.013896 (0.013897) Loss: 0.10830 (0.12795) +2025-09-15,15:55:24 | INFO | Train Epoch: 11 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11322 (0.11405) Boundary_loss: 0.013897 (0.013897) Loss: 0.12711 (0.12794) +2025-09-15,15:56:30 | INFO | Train Epoch: 11 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11238 (0.11404) Boundary_loss: 0.013898 (0.013897) Loss: 0.12627 (0.12794) +2025-09-15,15:57:36 | INFO | Train Epoch: 11 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.12039 (0.11406) Boundary_loss: 0.013897 (0.013897) Loss: 0.13429 (0.12796) +2025-09-15,15:58:42 | INFO | Train Epoch: 11 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10106 (0.11403) Boundary_loss: 0.013898 (0.013897) Loss: 0.11496 (0.12793) +2025-09-15,15:59:48 | INFO | Train Epoch: 11 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11079 (0.11402) Boundary_loss: 0.013897 (0.013897) Loss: 0.12469 (0.12792) +2025-09-15,16:00:54 | INFO | Train Epoch: 11 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.10702 (0.11400) Boundary_loss: 0.013897 (0.013897) Loss: 0.12092 (0.12790) +2025-09-15,16:02:00 | INFO | Train Epoch: 11 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14408 (0.11407) Boundary_loss: 0.013897 (0.013897) Loss: 0.15798 (0.12797) +2025-09-15,16:03:06 | INFO | Train Epoch: 11 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.080340 (0.11400) Boundary_loss: 0.013896 (0.013897) Loss: 0.094236 (0.12789) +2025-09-15,16:04:12 | INFO | Train Epoch: 11 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.13139 (0.11404) Boundary_loss: 0.013897 (0.013897) Loss: 0.14529 (0.12793) +2025-09-15,16:05:18 | INFO | Train Epoch: 11 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12050 (0.11405) Boundary_loss: 0.013895 (0.013897) Loss: 0.13440 (0.12795) +2025-09-15,16:06:24 | INFO | Train Epoch: 11 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12098 (0.11407) Boundary_loss: 0.013896 (0.013897) Loss: 0.13488 (0.12796) +2025-09-15,16:07:30 | INFO | Train Epoch: 11 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10769 (0.11405) Boundary_loss: 0.013896 (0.013897) Loss: 0.12159 (0.12795) +2025-09-15,16:08:36 | INFO | Train Epoch: 11 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10668 (0.11404) Boundary_loss: 0.013896 (0.013897) Loss: 0.12057 (0.12793) +2025-09-15,16:09:42 | INFO | Train Epoch: 11 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.088277 (0.11398) Boundary_loss: 0.013896 (0.013897) Loss: 0.10217 (0.12787) +2025-09-15,16:10:48 | INFO | Train Epoch: 11 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.081239 (0.11390) Boundary_loss: 0.013897 (0.013897) Loss: 0.095137 (0.12780) +2025-09-15,16:11:54 | INFO | Train Epoch: 11 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.079407 (0.11383) Boundary_loss: 0.013897 (0.013897) Loss: 0.093303 (0.12772) +2025-09-15,16:12:59 | INFO | Train Epoch: 11 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10518 (0.11381) Boundary_loss: 0.013896 (0.013897) Loss: 0.11908 (0.12770) +2025-09-15,16:14:05 | INFO | Train Epoch: 11 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.088919 (0.11375) Boundary_loss: 0.013897 (0.013897) Loss: 0.10282 (0.12765) +2025-09-15,16:15:11 | INFO | Train Epoch: 11 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.14450 (0.11382) Boundary_loss: 0.013898 (0.013897) Loss: 0.15840 (0.12772) +2025-09-15,16:16:17 | INFO | Train Epoch: 11 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11384 (0.11382) Boundary_loss: 0.013895 (0.013897) Loss: 0.12773 (0.12772) +2025-09-15,16:17:23 | INFO | Train Epoch: 11 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10769 (0.11381) Boundary_loss: 0.013896 (0.013897) Loss: 0.12159 (0.12770) +2025-09-15,16:18:29 | INFO | Train Epoch: 11 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.13638 (0.11386) Boundary_loss: 0.013897 (0.013897) Loss: 0.15028 (0.12775) +2025-09-15,16:19:35 | INFO | Train Epoch: 11 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.091529 (0.11381) Boundary_loss: 0.013896 (0.013897) Loss: 0.10543 (0.12770) +2025-09-15,16:20:41 | INFO | Train Epoch: 11 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12941 (0.11384) Boundary_loss: 0.013897 (0.013897) Loss: 0.14330 (0.12774) +2025-09-15,16:21:47 | INFO | Train Epoch: 11 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13210 (0.11388) Boundary_loss: 0.013895 (0.013897) Loss: 0.14599 (0.12778) +2025-09-15,16:22:53 | INFO | Train Epoch: 11 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.10537 (0.11386) Boundary_loss: 0.013898 (0.013897) Loss: 0.11927 (0.12776) +2025-09-15,16:23:59 | INFO | Train Epoch: 11 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.079821 (0.11379) Boundary_loss: 0.013897 (0.013897) Loss: 0.093717 (0.12769) +2025-09-15,16:25:05 | INFO | Train Epoch: 11 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11680 (0.11379) Boundary_loss: 0.013896 (0.013897) Loss: 0.13070 (0.12769) +2025-09-15,16:26:11 | INFO | Train Epoch: 11 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.084695 (0.11373) Boundary_loss: 0.013896 (0.013897) Loss: 0.098591 (0.12763) +2025-09-15,16:27:17 | INFO | Train Epoch: 11 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.088470 (0.11368) Boundary_loss: 0.013896 (0.013897) Loss: 0.10237 (0.12757) +2025-09-15,16:28:23 | INFO | Train Epoch: 11 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.081687 (0.11361) Boundary_loss: 0.013899 (0.013897) Loss: 0.095587 (0.12750) +2025-09-15,16:29:29 | INFO | Train Epoch: 11 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.099938 (0.11358) Boundary_loss: 0.013897 (0.013897) Loss: 0.11383 (0.12747) +2025-09-15,16:30:35 | INFO | Train Epoch: 11 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11190 (0.11357) Boundary_loss: 0.013897 (0.013897) Loss: 0.12580 (0.12747) +2025-09-15,16:31:41 | INFO | Train Epoch: 11 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15131 (0.11365) Boundary_loss: 0.013897 (0.013897) Loss: 0.16521 (0.12755) +2025-09-15,16:32:47 | INFO | Train Epoch: 11 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.10072 (0.11363) Boundary_loss: 0.013899 (0.013897) Loss: 0.11462 (0.12752) +2025-09-15,16:33:52 | INFO | Train Epoch: 11 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.17222 (0.11375) Boundary_loss: 0.013896 (0.013897) Loss: 0.18612 (0.12765) +2025-09-15,16:34:58 | INFO | Train Epoch: 11 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13164 (0.11379) Boundary_loss: 0.013898 (0.013897) Loss: 0.14553 (0.12769) +2025-09-15,16:36:04 | INFO | Train Epoch: 11 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10310 (0.11377) Boundary_loss: 0.013898 (0.013897) Loss: 0.11699 (0.12767) +2025-09-15,16:37:10 | INFO | Train Epoch: 11 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11982 (0.11378) Boundary_loss: 0.013896 (0.013897) Loss: 0.13372 (0.12768) +2025-09-15,16:38:16 | INFO | Train Epoch: 11 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13182 (0.11382) Boundary_loss: 0.013896 (0.013897) Loss: 0.14571 (0.12772) +2025-09-15,16:39:22 | INFO | Train Epoch: 11 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.093875 (0.11378) Boundary_loss: 0.013896 (0.013897) Loss: 0.10777 (0.12767) +2025-09-15,16:40:28 | INFO | Train Epoch: 11 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.096750 (0.11374) Boundary_loss: 0.013896 (0.013897) Loss: 0.11065 (0.12764) +2025-09-15,16:41:34 | INFO | Train Epoch: 11 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.094658 (0.11370) Boundary_loss: 0.013898 (0.013897) Loss: 0.10856 (0.12760) +2025-09-15,16:42:40 | INFO | Train Epoch: 11 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.072031 (0.11361) Boundary_loss: 0.013896 (0.013897) Loss: 0.085928 (0.12751) +2025-09-15,16:43:46 | INFO | Train Epoch: 11 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.092709 (0.11357) Boundary_loss: 0.013895 (0.013897) Loss: 0.10660 (0.12747) +2025-09-15,16:44:51 | INFO | Train Epoch: 11 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.078571 (0.11349) Boundary_loss: 0.013898 (0.013897) Loss: 0.092469 (0.12739) +2025-09-15,16:45:57 | INFO | Train Epoch: 11 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12859 (0.11353) Boundary_loss: 0.013897 (0.013897) Loss: 0.14249 (0.12742) +2025-09-15,16:47:03 | INFO | Train Epoch: 11 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11038 (0.11352) Boundary_loss: 0.013898 (0.013897) Loss: 0.12427 (0.12742) +2025-09-15,16:48:09 | INFO | Train Epoch: 11 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15487 (0.11361) Boundary_loss: 0.013895 (0.013897) Loss: 0.16876 (0.12750) +2025-09-15,16:49:15 | INFO | Train Epoch: 11 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.099148 (0.11358) Boundary_loss: 0.013897 (0.013897) Loss: 0.11305 (0.12747) +2025-09-15,16:50:21 | INFO | Train Epoch: 11 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.091017 (0.11353) Boundary_loss: 0.013899 (0.013897) Loss: 0.10492 (0.12743) +2025-09-15,16:51:27 | INFO | Train Epoch: 11 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11159 (0.11353) Boundary_loss: 0.013897 (0.013897) Loss: 0.12549 (0.12742) +2025-09-15,16:52:33 | INFO | Train Epoch: 11 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12254 (0.11354) Boundary_loss: 0.013897 (0.013897) Loss: 0.13644 (0.12744) +2025-09-15,16:53:39 | INFO | Train Epoch: 11 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.079176 (0.11347) Boundary_loss: 0.013896 (0.013897) Loss: 0.093073 (0.12737) +2025-09-15,16:54:45 | INFO | Train Epoch: 11 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10351 (0.11345) Boundary_loss: 0.013896 (0.013897) Loss: 0.11740 (0.12735) +2025-09-15,16:55:51 | INFO | Train Epoch: 11 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.092109 (0.11341) Boundary_loss: 0.013894 (0.013897) Loss: 0.10600 (0.12731) +2025-09-15,16:56:56 | INFO | Train Epoch: 11 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13233 (0.11345) Boundary_loss: 0.013897 (0.013897) Loss: 0.14623 (0.12734) +2025-09-15,16:58:02 | INFO | Train Epoch: 11 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.12341 (0.11347) Boundary_loss: 0.013897 (0.013897) Loss: 0.13731 (0.12736) +2025-09-15,16:59:08 | INFO | Train Epoch: 11 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.10435 (0.11345) Boundary_loss: 0.013898 (0.013897) Loss: 0.11825 (0.12735) +2025-09-15,17:00:14 | INFO | Train Epoch: 11 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12750 (0.11348) Boundary_loss: 0.013896 (0.013897) Loss: 0.14139 (0.12737) +2025-09-15,17:01:20 | INFO | Train Epoch: 11 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13414 (0.11352) Boundary_loss: 0.013896 (0.013897) Loss: 0.14803 (0.12742) +2025-09-15,17:02:26 | INFO | Train Epoch: 11 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11547 (0.11352) Boundary_loss: 0.013898 (0.013897) Loss: 0.12937 (0.12742) +2025-09-15,17:03:32 | INFO | Train Epoch: 11 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11161 (0.11352) Boundary_loss: 0.013897 (0.013897) Loss: 0.12550 (0.12742) +2025-09-15,17:04:38 | INFO | Train Epoch: 11 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11571 (0.11352) Boundary_loss: 0.013896 (0.013897) Loss: 0.12961 (0.12742) +2025-09-15,17:05:44 | INFO | Train Epoch: 11 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10911 (0.11352) Boundary_loss: 0.013896 (0.013897) Loss: 0.12301 (0.12741) +2025-09-15,17:06:50 | INFO | Train Epoch: 11 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12012 (0.11353) Boundary_loss: 0.013896 (0.013897) Loss: 0.13401 (0.12743) +2025-09-15,17:07:56 | INFO | Train Epoch: 11 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.084435 (0.11347) Boundary_loss: 0.013896 (0.013897) Loss: 0.098330 (0.12737) +2025-09-15,17:09:02 | INFO | Train Epoch: 11 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13730 (0.11352) Boundary_loss: 0.013897 (0.013897) Loss: 0.15120 (0.12742) +2025-09-15,17:10:08 | INFO | Train Epoch: 11 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10396 (0.11350) Boundary_loss: 0.013896 (0.013897) Loss: 0.11785 (0.12740) +2025-09-15,17:11:14 | INFO | Train Epoch: 11 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.070773 (0.11341) Boundary_loss: 0.013897 (0.013897) Loss: 0.084670 (0.12731) +2025-09-15,17:12:20 | INFO | Train Epoch: 11 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.14936 (0.11349) Boundary_loss: 0.013897 (0.013897) Loss: 0.16325 (0.12738) +2025-09-15,17:13:25 | INFO | Train Epoch: 11 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14397 (0.11355) Boundary_loss: 0.013896 (0.013897) Loss: 0.15787 (0.12744) +2025-09-15,17:14:31 | INFO | Train Epoch: 11 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10730 (0.11353) Boundary_loss: 0.013896 (0.013897) Loss: 0.12120 (0.12743) +2025-09-15,17:15:37 | INFO | Train Epoch: 11 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.099153 (0.11351) Boundary_loss: 0.013897 (0.013897) Loss: 0.11305 (0.12740) +2025-09-15,17:16:43 | INFO | Train Epoch: 11 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11518 (0.11351) Boundary_loss: 0.013897 (0.013897) Loss: 0.12908 (0.12741) +2025-09-15,17:17:49 | INFO | Train Epoch: 11 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10215 (0.11349) Boundary_loss: 0.013896 (0.013897) Loss: 0.11604 (0.12738) +2025-09-15,17:18:55 | INFO | Train Epoch: 11 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.099825 (0.11346) Boundary_loss: 0.013896 (0.013897) Loss: 0.11372 (0.12736) +2025-09-15,17:20:01 | INFO | Train Epoch: 11 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.15578 (0.11354) Boundary_loss: 0.013897 (0.013897) Loss: 0.16968 (0.12744) +2025-09-15,17:21:07 | INFO | Train Epoch: 11 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.14212 (0.11360) Boundary_loss: 0.013896 (0.013897) Loss: 0.15601 (0.12750) +2025-09-15,17:22:13 | INFO | Train Epoch: 11 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.12472 (0.11362) Boundary_loss: 0.013897 (0.013897) Loss: 0.13862 (0.12752) +2025-09-15,17:23:19 | INFO | Train Epoch: 11 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.083859 (0.11356) Boundary_loss: 0.013897 (0.013897) Loss: 0.097756 (0.12746) +2025-09-15,17:24:25 | INFO | Train Epoch: 11 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.074412 (0.11349) Boundary_loss: 0.013898 (0.013897) Loss: 0.088309 (0.12738) +2025-09-15,17:25:31 | INFO | Train Epoch: 11 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.085334 (0.11343) Boundary_loss: 0.013898 (0.013897) Loss: 0.099232 (0.12733) +2025-09-15,17:26:37 | INFO | Train Epoch: 11 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.095628 (0.11340) Boundary_loss: 0.013896 (0.013897) Loss: 0.10952 (0.12729) +2025-09-15,17:27:43 | INFO | Train Epoch: 11 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.095931 (0.11336) Boundary_loss: 0.013897 (0.013897) Loss: 0.10983 (0.12726) +2025-09-15,17:28:49 | INFO | Train Epoch: 11 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13109 (0.11340) Boundary_loss: 0.013898 (0.013897) Loss: 0.14499 (0.12729) +2025-09-15,17:29:51 | INFO | Train Epoch: 11 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10320 (0.11338) Boundary_loss: 0.013895 (0.013897) Loss: 0.11710 (0.12727) +2025-09-15,17:29:51 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-15,17:29:51 | INFO | [Epoch 11] Average Step Time: 0.661s | Average GPU Memory: 30.8 GB +2025-09-15,17:29:51 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-15,17:29:51 | INFO | Starting zero-shot imagenet. +2025-09-15,17:29:51 | INFO | Building zero-shot classifier +2025-09-15,17:30:01 | INFO | Using classifier +2025-09-15,17:30:49 | INFO | Finished zero-shot imagenet. +2025-09-15,17:30:49 | INFO | Eval Epoch: 12 imagenet-zeroshot-val-top1: 0.3216 imagenet-zeroshot-val-top5: 0.5966 +2025-09-15,17:30:50 | INFO | Start epoch 12 +2025-09-15,17:30:52 | INFO | Train Epoch: 12 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.069225 (0.069225) Boundary_loss: 0.013895 (0.013895) Loss: 0.083120 (0.083120) +2025-09-15,17:31:58 | INFO | Train Epoch: 12 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.096655 (0.082940) Boundary_loss: 0.013897 (0.013896) Loss: 0.11055 (0.096836) +2025-09-15,17:33:04 | INFO | Train Epoch: 12 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11850 (0.094792) Boundary_loss: 0.013895 (0.013896) Loss: 0.13239 (0.10869) +2025-09-15,17:34:09 | INFO | Train Epoch: 12 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.065984 (0.087590) Boundary_loss: 0.013898 (0.013896) Loss: 0.079882 (0.10149) +2025-09-15,17:35:15 | INFO | Train Epoch: 12 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.089650 (0.088002) Boundary_loss: 0.013895 (0.013896) Loss: 0.10354 (0.10190) +2025-09-15,17:36:21 | INFO | Train Epoch: 12 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.087593 (0.087934) Boundary_loss: 0.013896 (0.013896) Loss: 0.10149 (0.10183) +2025-09-15,17:37:26 | INFO | Train Epoch: 12 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.063385 (0.084427) Boundary_loss: 0.013897 (0.013896) Loss: 0.077281 (0.098323) +2025-09-15,17:38:32 | INFO | Train Epoch: 12 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.073905 (0.083112) Boundary_loss: 0.013897 (0.013896) Loss: 0.087802 (0.097008) +2025-09-15,17:39:38 | INFO | Train Epoch: 12 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.087962 (0.083651) Boundary_loss: 0.013896 (0.013896) Loss: 0.10186 (0.097547) +2025-09-15,17:40:43 | INFO | Train Epoch: 12 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11863 (0.087148) Boundary_loss: 0.013896 (0.013896) Loss: 0.13252 (0.10104) +2025-09-15,17:41:49 | INFO | Train Epoch: 12 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.081761 (0.086659) Boundary_loss: 0.013896 (0.013896) Loss: 0.095658 (0.10055) +2025-09-15,17:42:55 | INFO | Train Epoch: 12 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.085604 (0.086571) Boundary_loss: 0.013896 (0.013896) Loss: 0.099500 (0.10047) +2025-09-15,17:44:00 | INFO | Train Epoch: 12 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.094593 (0.087188) Boundary_loss: 0.013897 (0.013896) Loss: 0.10849 (0.10108) +2025-09-15,17:45:06 | INFO | Train Epoch: 12 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13276 (0.090443) Boundary_loss: 0.013896 (0.013896) Loss: 0.14666 (0.10434) +2025-09-15,17:46:12 | INFO | Train Epoch: 12 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.080893 (0.089806) Boundary_loss: 0.013896 (0.013896) Loss: 0.094789 (0.10370) +2025-09-15,17:47:17 | INFO | Train Epoch: 12 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.075896 (0.088937) Boundary_loss: 0.013898 (0.013896) Loss: 0.089794 (0.10283) +2025-09-15,17:48:23 | INFO | Train Epoch: 12 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10109 (0.089652) Boundary_loss: 0.013897 (0.013896) Loss: 0.11499 (0.10355) +2025-09-15,17:49:29 | INFO | Train Epoch: 12 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.11147 (0.090864) Boundary_loss: 0.013897 (0.013896) Loss: 0.12536 (0.10476) +2025-09-15,17:50:34 | INFO | Train Epoch: 12 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.060950 (0.089289) Boundary_loss: 0.013896 (0.013896) Loss: 0.074846 (0.10319) +2025-09-15,17:51:40 | INFO | Train Epoch: 12 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.094764 (0.089563) Boundary_loss: 0.013897 (0.013896) Loss: 0.10866 (0.10346) +2025-09-15,17:52:46 | INFO | Train Epoch: 12 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11363 (0.090709) Boundary_loss: 0.013895 (0.013896) Loss: 0.12753 (0.10461) +2025-09-15,17:53:51 | INFO | Train Epoch: 12 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11703 (0.091906) Boundary_loss: 0.013896 (0.013896) Loss: 0.13093 (0.10580) +2025-09-15,17:54:57 | INFO | Train Epoch: 12 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11915 (0.093090) Boundary_loss: 0.013896 (0.013896) Loss: 0.13305 (0.10699) +2025-09-15,17:56:03 | INFO | Train Epoch: 12 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.093590 (0.093111) Boundary_loss: 0.013896 (0.013896) Loss: 0.10749 (0.10701) +2025-09-15,17:57:09 | INFO | Train Epoch: 12 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.052220 (0.091475) Boundary_loss: 0.013895 (0.013896) Loss: 0.066116 (0.10537) +2025-09-15,17:58:14 | INFO | Train Epoch: 12 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.094354 (0.091586) Boundary_loss: 0.013897 (0.013896) Loss: 0.10825 (0.10548) +2025-09-15,17:59:20 | INFO | Train Epoch: 12 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.089561 (0.091511) Boundary_loss: 0.013896 (0.013896) Loss: 0.10346 (0.10541) +2025-09-15,18:00:26 | INFO | Train Epoch: 12 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.074964 (0.090920) Boundary_loss: 0.013897 (0.013896) Loss: 0.088861 (0.10482) +2025-09-15,18:01:31 | INFO | Train Epoch: 12 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10933 (0.091555) Boundary_loss: 0.013896 (0.013896) Loss: 0.12323 (0.10545) +2025-09-15,18:02:37 | INFO | Train Epoch: 12 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.088341 (0.091448) Boundary_loss: 0.013898 (0.013896) Loss: 0.10224 (0.10534) +2025-09-15,18:03:43 | INFO | Train Epoch: 12 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12735 (0.092606) Boundary_loss: 0.013897 (0.013896) Loss: 0.14124 (0.10650) +2025-09-15,18:04:48 | INFO | Train Epoch: 12 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.085074 (0.092371) Boundary_loss: 0.013895 (0.013896) Loss: 0.098969 (0.10627) +2025-09-15,18:05:54 | INFO | Train Epoch: 12 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.092379 (0.092371) Boundary_loss: 0.013896 (0.013896) Loss: 0.10627 (0.10627) +2025-09-15,18:07:00 | INFO | Train Epoch: 12 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.069569 (0.091700) Boundary_loss: 0.013897 (0.013896) Loss: 0.083466 (0.10560) +2025-09-15,18:08:05 | INFO | Train Epoch: 12 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.099654 (0.091927) Boundary_loss: 0.013896 (0.013896) Loss: 0.11355 (0.10582) +2025-09-15,18:09:11 | INFO | Train Epoch: 12 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.070362 (0.091328) Boundary_loss: 0.013895 (0.013896) Loss: 0.084258 (0.10522) +2025-09-15,18:10:17 | INFO | Train Epoch: 12 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.087044 (0.091213) Boundary_loss: 0.013898 (0.013896) Loss: 0.10094 (0.10511) +2025-09-15,18:11:23 | INFO | Train Epoch: 12 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.095460 (0.091324) Boundary_loss: 0.013897 (0.013896) Loss: 0.10936 (0.10522) +2025-09-15,18:12:28 | INFO | Train Epoch: 12 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.085869 (0.091185) Boundary_loss: 0.013897 (0.013896) Loss: 0.099766 (0.10508) +2025-09-15,18:13:34 | INFO | Train Epoch: 12 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.095504 (0.091293) Boundary_loss: 0.013897 (0.013896) Loss: 0.10940 (0.10519) +2025-09-15,18:14:40 | INFO | Train Epoch: 12 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.082899 (0.091088) Boundary_loss: 0.013898 (0.013896) Loss: 0.096796 (0.10498) +2025-09-15,18:15:45 | INFO | Train Epoch: 12 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.086172 (0.090971) Boundary_loss: 0.013896 (0.013896) Loss: 0.10007 (0.10487) +2025-09-15,18:16:51 | INFO | Train Epoch: 12 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.084648 (0.090824) Boundary_loss: 0.013895 (0.013896) Loss: 0.098543 (0.10472) +2025-09-15,18:17:57 | INFO | Train Epoch: 12 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.073218 (0.090424) Boundary_loss: 0.013897 (0.013896) Loss: 0.087115 (0.10432) +2025-09-15,18:19:03 | INFO | Train Epoch: 12 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.089403 (0.090401) Boundary_loss: 0.013897 (0.013896) Loss: 0.10330 (0.10430) +2025-09-15,18:20:08 | INFO | Train Epoch: 12 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10198 (0.090653) Boundary_loss: 0.013897 (0.013896) Loss: 0.11588 (0.10455) +2025-09-15,18:21:14 | INFO | Train Epoch: 12 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.074157 (0.090302) Boundary_loss: 0.013896 (0.013896) Loss: 0.088053 (0.10420) +2025-09-15,18:22:20 | INFO | Train Epoch: 12 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.095991 (0.090420) Boundary_loss: 0.013896 (0.013896) Loss: 0.10989 (0.10432) +2025-09-15,18:23:25 | INFO | Train Epoch: 12 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10954 (0.090810) Boundary_loss: 0.013896 (0.013896) Loss: 0.12343 (0.10471) +2025-09-15,18:24:31 | INFO | Train Epoch: 12 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.080065 (0.090595) Boundary_loss: 0.013895 (0.013896) Loss: 0.093961 (0.10449) +2025-09-15,18:25:37 | INFO | Train Epoch: 12 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.063466 (0.090064) Boundary_loss: 0.013897 (0.013896) Loss: 0.077363 (0.10396) +2025-09-15,18:26:42 | INFO | Train Epoch: 12 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.077418 (0.089820) Boundary_loss: 0.013896 (0.013896) Loss: 0.091314 (0.10372) +2025-09-15,18:27:48 | INFO | Train Epoch: 12 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10615 (0.090128) Boundary_loss: 0.013895 (0.013896) Loss: 0.12005 (0.10402) +2025-09-15,18:28:54 | INFO | Train Epoch: 12 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.075910 (0.089865) Boundary_loss: 0.013896 (0.013896) Loss: 0.089807 (0.10376) +2025-09-15,18:30:00 | INFO | Train Epoch: 12 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.096043 (0.089977) Boundary_loss: 0.013896 (0.013896) Loss: 0.10994 (0.10387) +2025-09-15,18:31:05 | INFO | Train Epoch: 12 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10530 (0.090251) Boundary_loss: 0.013895 (0.013896) Loss: 0.11919 (0.10415) +2025-09-15,18:32:11 | INFO | Train Epoch: 12 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.094721 (0.090329) Boundary_loss: 0.013896 (0.013896) Loss: 0.10862 (0.10423) +2025-09-15,18:33:17 | INFO | Train Epoch: 12 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.088362 (0.090296) Boundary_loss: 0.013896 (0.013896) Loss: 0.10226 (0.10419) +2025-09-15,18:34:22 | INFO | Train Epoch: 12 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.075995 (0.090053) Boundary_loss: 0.013897 (0.013896) Loss: 0.089892 (0.10395) +2025-09-15,18:35:28 | INFO | Train Epoch: 12 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10674 (0.090331) Boundary_loss: 0.013896 (0.013896) Loss: 0.12063 (0.10423) +2025-09-15,18:36:34 | INFO | Train Epoch: 12 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10635 (0.090594) Boundary_loss: 0.013897 (0.013896) Loss: 0.12025 (0.10449) +2025-09-15,18:37:39 | INFO | Train Epoch: 12 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.097142 (0.090700) Boundary_loss: 0.013896 (0.013896) Loss: 0.11104 (0.10460) +2025-09-15,18:38:45 | INFO | Train Epoch: 12 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.097724 (0.090811) Boundary_loss: 0.013895 (0.013896) Loss: 0.11162 (0.10471) +2025-09-15,18:39:51 | INFO | Train Epoch: 12 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.12170 (0.091294) Boundary_loss: 0.013898 (0.013896) Loss: 0.13560 (0.10519) +2025-09-15,18:40:57 | INFO | Train Epoch: 12 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.096913 (0.091380) Boundary_loss: 0.013897 (0.013896) Loss: 0.11081 (0.10528) +2025-09-15,18:42:02 | INFO | Train Epoch: 12 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.067552 (0.091019) Boundary_loss: 0.013898 (0.013896) Loss: 0.081450 (0.10492) +2025-09-15,18:43:08 | INFO | Train Epoch: 12 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.084348 (0.090920) Boundary_loss: 0.013897 (0.013896) Loss: 0.098245 (0.10482) +2025-09-15,18:44:14 | INFO | Train Epoch: 12 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.099659 (0.091048) Boundary_loss: 0.013896 (0.013896) Loss: 0.11355 (0.10494) +2025-09-15,18:45:19 | INFO | Train Epoch: 12 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.083963 (0.090945) Boundary_loss: 0.013896 (0.013896) Loss: 0.097859 (0.10484) +2025-09-15,18:46:25 | INFO | Train Epoch: 12 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.074842 (0.090715) Boundary_loss: 0.013897 (0.013896) Loss: 0.088739 (0.10461) +2025-09-15,18:47:31 | INFO | Train Epoch: 12 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.089746 (0.090702) Boundary_loss: 0.013896 (0.013896) Loss: 0.10364 (0.10460) +2025-09-15,18:48:36 | INFO | Train Epoch: 12 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.071903 (0.090441) Boundary_loss: 0.013896 (0.013896) Loss: 0.085800 (0.10434) +2025-09-15,18:49:42 | INFO | Train Epoch: 12 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.081171 (0.090314) Boundary_loss: 0.013896 (0.013896) Loss: 0.095067 (0.10421) +2025-09-15,18:50:48 | INFO | Train Epoch: 12 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.089785 (0.090307) Boundary_loss: 0.013896 (0.013896) Loss: 0.10368 (0.10420) +2025-09-15,18:51:54 | INFO | Train Epoch: 12 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.084292 (0.090226) Boundary_loss: 0.013896 (0.013896) Loss: 0.098188 (0.10412) +2025-09-15,18:52:59 | INFO | Train Epoch: 12 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.076522 (0.090046) Boundary_loss: 0.013897 (0.013896) Loss: 0.090420 (0.10394) +2025-09-15,18:54:05 | INFO | Train Epoch: 12 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.056154 (0.089606) Boundary_loss: 0.013897 (0.013896) Loss: 0.070050 (0.10350) +2025-09-15,18:55:11 | INFO | Train Epoch: 12 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12845 (0.090104) Boundary_loss: 0.013897 (0.013896) Loss: 0.14235 (0.10400) +2025-09-15,18:56:17 | INFO | Train Epoch: 12 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.095010 (0.090166) Boundary_loss: 0.013896 (0.013896) Loss: 0.10891 (0.10406) +2025-09-15,18:57:22 | INFO | Train Epoch: 12 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.081080 (0.090052) Boundary_loss: 0.013897 (0.013896) Loss: 0.094978 (0.10395) +2025-09-15,18:58:28 | INFO | Train Epoch: 12 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10980 (0.090296) Boundary_loss: 0.013896 (0.013896) Loss: 0.12370 (0.10419) +2025-09-15,18:59:34 | INFO | Train Epoch: 12 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.099814 (0.090412) Boundary_loss: 0.013897 (0.013896) Loss: 0.11371 (0.10431) +2025-09-15,19:00:40 | INFO | Train Epoch: 12 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.064242 (0.090097) Boundary_loss: 0.013895 (0.013896) Loss: 0.078137 (0.10399) +2025-09-15,19:01:45 | INFO | Train Epoch: 12 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.096547 (0.090174) Boundary_loss: 0.013896 (0.013896) Loss: 0.11044 (0.10407) +2025-09-15,19:02:51 | INFO | Train Epoch: 12 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.078426 (0.090036) Boundary_loss: 0.013896 (0.013896) Loss: 0.092322 (0.10393) +2025-09-15,19:03:57 | INFO | Train Epoch: 12 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.12063 (0.090391) Boundary_loss: 0.013897 (0.013896) Loss: 0.13453 (0.10429) +2025-09-15,19:05:02 | INFO | Train Epoch: 12 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.082711 (0.090303) Boundary_loss: 0.013896 (0.013896) Loss: 0.096607 (0.10420) +2025-09-15,19:06:08 | INFO | Train Epoch: 12 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13584 (0.090821) Boundary_loss: 0.013895 (0.013896) Loss: 0.14974 (0.10472) +2025-09-15,19:07:14 | INFO | Train Epoch: 12 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.055587 (0.090425) Boundary_loss: 0.013896 (0.013896) Loss: 0.069483 (0.10432) +2025-09-15,19:08:20 | INFO | Train Epoch: 12 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.081508 (0.090326) Boundary_loss: 0.013896 (0.013896) Loss: 0.095404 (0.10422) +2025-09-15,19:09:25 | INFO | Train Epoch: 12 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.096257 (0.090391) Boundary_loss: 0.013897 (0.013896) Loss: 0.11015 (0.10429) +2025-09-15,19:10:31 | INFO | Train Epoch: 12 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.10795 (0.090582) Boundary_loss: 0.013897 (0.013896) Loss: 0.12184 (0.10448) +2025-09-15,19:11:37 | INFO | Train Epoch: 12 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13174 (0.091024) Boundary_loss: 0.013895 (0.013896) Loss: 0.14563 (0.10492) +2025-09-15,19:12:43 | INFO | Train Epoch: 12 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11504 (0.091280) Boundary_loss: 0.013895 (0.013896) Loss: 0.12894 (0.10518) +2025-09-15,19:13:48 | INFO | Train Epoch: 12 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.075046 (0.091109) Boundary_loss: 0.013897 (0.013896) Loss: 0.088943 (0.10501) +2025-09-15,19:14:54 | INFO | Train Epoch: 12 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.071219 (0.090902) Boundary_loss: 0.013895 (0.013896) Loss: 0.085114 (0.10480) +2025-09-15,19:16:00 | INFO | Train Epoch: 12 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.068812 (0.090674) Boundary_loss: 0.013897 (0.013896) Loss: 0.082709 (0.10457) +2025-09-15,19:17:06 | INFO | Train Epoch: 12 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.062264 (0.090384) Boundary_loss: 0.013896 (0.013896) Loss: 0.076161 (0.10428) +2025-09-15,19:18:11 | INFO | Train Epoch: 12 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.071924 (0.090197) Boundary_loss: 0.013896 (0.013896) Loss: 0.085820 (0.10409) +2025-09-15,19:19:17 | INFO | Train Epoch: 12 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.082190 (0.090117) Boundary_loss: 0.013897 (0.013896) Loss: 0.096087 (0.10401) +2025-09-15,19:20:23 | INFO | Train Epoch: 12 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.083289 (0.090050) Boundary_loss: 0.013896 (0.013896) Loss: 0.097185 (0.10395) +2025-09-15,19:21:29 | INFO | Train Epoch: 12 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.085004 (0.090000) Boundary_loss: 0.013897 (0.013896) Loss: 0.098901 (0.10390) +2025-09-15,19:22:35 | INFO | Train Epoch: 12 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.080865 (0.089912) Boundary_loss: 0.013895 (0.013896) Loss: 0.094760 (0.10381) +2025-09-15,19:23:40 | INFO | Train Epoch: 12 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.086214 (0.089876) Boundary_loss: 0.013897 (0.013896) Loss: 0.10011 (0.10377) +2025-09-15,19:24:46 | INFO | Train Epoch: 12 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.087734 (0.089856) Boundary_loss: 0.013895 (0.013896) Loss: 0.10163 (0.10375) +2025-09-15,19:25:52 | INFO | Train Epoch: 12 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.045631 (0.089438) Boundary_loss: 0.013897 (0.013896) Loss: 0.059528 (0.10333) +2025-09-15,19:26:58 | INFO | Train Epoch: 12 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.073136 (0.089286) Boundary_loss: 0.013896 (0.013896) Loss: 0.087032 (0.10318) +2025-09-15,19:28:03 | INFO | Train Epoch: 12 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10184 (0.089402) Boundary_loss: 0.013896 (0.013896) Loss: 0.11573 (0.10330) +2025-09-15,19:29:09 | INFO | Train Epoch: 12 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.074037 (0.089261) Boundary_loss: 0.013897 (0.013896) Loss: 0.087934 (0.10316) +2025-09-15,19:30:15 | INFO | Train Epoch: 12 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.084666 (0.089220) Boundary_loss: 0.013895 (0.013896) Loss: 0.098561 (0.10312) +2025-09-15,19:31:21 | INFO | Train Epoch: 12 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.084450 (0.089177) Boundary_loss: 0.013896 (0.013896) Loss: 0.098346 (0.10307) +2025-09-15,19:32:26 | INFO | Train Epoch: 12 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11095 (0.089371) Boundary_loss: 0.013897 (0.013896) Loss: 0.12484 (0.10327) +2025-09-15,19:33:32 | INFO | Train Epoch: 12 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.084568 (0.089328) Boundary_loss: 0.013896 (0.013896) Loss: 0.098464 (0.10322) +2025-09-15,19:34:38 | INFO | Train Epoch: 12 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.085095 (0.089291) Boundary_loss: 0.013896 (0.013896) Loss: 0.098991 (0.10319) +2025-09-15,19:35:44 | INFO | Train Epoch: 12 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.064004 (0.089071) Boundary_loss: 0.013896 (0.013896) Loss: 0.077900 (0.10297) +2025-09-15,19:36:50 | INFO | Train Epoch: 12 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.090824 (0.089087) Boundary_loss: 0.013897 (0.013896) Loss: 0.10472 (0.10298) +2025-09-15,19:37:55 | INFO | Train Epoch: 12 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.089051 (0.089086) Boundary_loss: 0.013896 (0.013896) Loss: 0.10295 (0.10298) +2025-09-15,19:39:01 | INFO | Train Epoch: 12 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10108 (0.089188) Boundary_loss: 0.013896 (0.013896) Loss: 0.11498 (0.10308) +2025-09-15,19:40:07 | INFO | Train Epoch: 12 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.084946 (0.089152) Boundary_loss: 0.013896 (0.013896) Loss: 0.098842 (0.10305) +2025-09-15,19:41:13 | INFO | Train Epoch: 12 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.070325 (0.088995) Boundary_loss: 0.013896 (0.013896) Loss: 0.084222 (0.10289) +2025-09-15,19:42:18 | INFO | Train Epoch: 12 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10042 (0.089090) Boundary_loss: 0.013897 (0.013896) Loss: 0.11431 (0.10299) +2025-09-15,19:43:24 | INFO | Train Epoch: 12 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.10876 (0.089251) Boundary_loss: 0.013899 (0.013896) Loss: 0.12266 (0.10315) +2025-09-15,19:44:30 | INFO | Train Epoch: 12 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.099840 (0.089337) Boundary_loss: 0.013897 (0.013896) Loss: 0.11374 (0.10323) +2025-09-15,19:45:36 | INFO | Train Epoch: 12 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12261 (0.089605) Boundary_loss: 0.013897 (0.013896) Loss: 0.13651 (0.10350) +2025-09-15,19:46:42 | INFO | Train Epoch: 12 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10557 (0.089733) Boundary_loss: 0.013898 (0.013896) Loss: 0.11947 (0.10363) +2025-09-15,19:47:47 | INFO | Train Epoch: 12 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.097197 (0.089792) Boundary_loss: 0.013895 (0.013896) Loss: 0.11109 (0.10369) +2025-09-15,19:48:53 | INFO | Train Epoch: 12 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11808 (0.090015) Boundary_loss: 0.013896 (0.013896) Loss: 0.13198 (0.10391) +2025-09-15,19:49:59 | INFO | Train Epoch: 12 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.070341 (0.089861) Boundary_loss: 0.013896 (0.013896) Loss: 0.084237 (0.10376) +2025-09-15,19:51:05 | INFO | Train Epoch: 12 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.076186 (0.089755) Boundary_loss: 0.013897 (0.013896) Loss: 0.090084 (0.10365) +2025-09-15,19:52:10 | INFO | Train Epoch: 12 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.089109 (0.089750) Boundary_loss: 0.013896 (0.013896) Loss: 0.10301 (0.10365) +2025-09-15,19:53:16 | INFO | Train Epoch: 12 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.089427 (0.089748) Boundary_loss: 0.013896 (0.013896) Loss: 0.10332 (0.10364) +2025-09-15,19:54:22 | INFO | Train Epoch: 12 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.081480 (0.089685) Boundary_loss: 0.013897 (0.013896) Loss: 0.095377 (0.10358) +2025-09-15,19:55:28 | INFO | Train Epoch: 12 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.078071 (0.089598) Boundary_loss: 0.013897 (0.013896) Loss: 0.091968 (0.10349) +2025-09-15,19:56:34 | INFO | Train Epoch: 12 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.077237 (0.089506) Boundary_loss: 0.013899 (0.013896) Loss: 0.091136 (0.10340) +2025-09-15,19:57:40 | INFO | Train Epoch: 12 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11376 (0.089685) Boundary_loss: 0.013897 (0.013896) Loss: 0.12766 (0.10358) +2025-09-15,19:58:45 | INFO | Train Epoch: 12 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.078140 (0.089601) Boundary_loss: 0.013895 (0.013896) Loss: 0.092036 (0.10350) +2025-09-15,19:59:51 | INFO | Train Epoch: 12 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.093972 (0.089632) Boundary_loss: 0.013897 (0.013896) Loss: 0.10787 (0.10353) +2025-09-15,20:00:57 | INFO | Train Epoch: 12 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.087552 (0.089617) Boundary_loss: 0.013898 (0.013896) Loss: 0.10145 (0.10351) +2025-09-15,20:02:03 | INFO | Train Epoch: 12 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.055750 (0.089374) Boundary_loss: 0.013896 (0.013896) Loss: 0.069646 (0.10327) +2025-09-15,20:03:08 | INFO | Train Epoch: 12 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.084843 (0.089341) Boundary_loss: 0.013895 (0.013896) Loss: 0.098738 (0.10324) +2025-09-15,20:04:14 | INFO | Train Epoch: 12 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.094921 (0.089381) Boundary_loss: 0.013895 (0.013896) Loss: 0.10882 (0.10328) +2025-09-15,20:05:20 | INFO | Train Epoch: 12 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.075823 (0.089285) Boundary_loss: 0.013895 (0.013896) Loss: 0.089718 (0.10318) +2025-09-15,20:06:26 | INFO | Train Epoch: 12 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11428 (0.089460) Boundary_loss: 0.013895 (0.013896) Loss: 0.12817 (0.10336) +2025-09-15,20:07:32 | INFO | Train Epoch: 12 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.076209 (0.089368) Boundary_loss: 0.013896 (0.013896) Loss: 0.090105 (0.10326) +2025-09-15,20:08:37 | INFO | Train Epoch: 12 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12448 (0.089610) Boundary_loss: 0.013895 (0.013896) Loss: 0.13838 (0.10351) +2025-09-15,20:09:43 | INFO | Train Epoch: 12 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.14823 (0.090012) Boundary_loss: 0.013896 (0.013896) Loss: 0.16213 (0.10391) +2025-09-15,20:10:49 | INFO | Train Epoch: 12 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.066090 (0.089849) Boundary_loss: 0.013896 (0.013896) Loss: 0.079986 (0.10375) +2025-09-15,20:11:54 | INFO | Train Epoch: 12 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.058275 (0.089636) Boundary_loss: 0.013896 (0.013896) Loss: 0.072170 (0.10353) +2025-09-15,20:13:00 | INFO | Train Epoch: 12 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.079966 (0.089571) Boundary_loss: 0.013896 (0.013896) Loss: 0.093862 (0.10347) +2025-09-15,20:14:06 | INFO | Train Epoch: 12 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12481 (0.089806) Boundary_loss: 0.013895 (0.013896) Loss: 0.13870 (0.10370) +2025-09-15,20:15:12 | INFO | Train Epoch: 12 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10332 (0.089895) Boundary_loss: 0.013896 (0.013896) Loss: 0.11722 (0.10379) +2025-09-15,20:16:18 | INFO | Train Epoch: 12 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11071 (0.090032) Boundary_loss: 0.013896 (0.013896) Loss: 0.12461 (0.10393) +2025-09-15,20:17:23 | INFO | Train Epoch: 12 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.094920 (0.090064) Boundary_loss: 0.013896 (0.013896) Loss: 0.10882 (0.10396) +2025-09-15,20:18:29 | INFO | Train Epoch: 12 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10240 (0.090144) Boundary_loss: 0.013896 (0.013896) Loss: 0.11630 (0.10404) +2025-09-15,20:19:35 | INFO | Train Epoch: 12 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.057682 (0.089935) Boundary_loss: 0.013897 (0.013896) Loss: 0.071579 (0.10383) +2025-09-15,20:20:40 | INFO | Train Epoch: 12 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10978 (0.090062) Boundary_loss: 0.013895 (0.013896) Loss: 0.12368 (0.10396) +2025-09-15,20:21:46 | INFO | Train Epoch: 12 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.086330 (0.090038) Boundary_loss: 0.013895 (0.013896) Loss: 0.10023 (0.10393) +2025-09-15,20:22:52 | INFO | Train Epoch: 12 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.082222 (0.089989) Boundary_loss: 0.013897 (0.013896) Loss: 0.096118 (0.10389) +2025-09-15,20:23:58 | INFO | Train Epoch: 12 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.071693 (0.089874) Boundary_loss: 0.013896 (0.013896) Loss: 0.085589 (0.10377) +2025-09-15,20:25:03 | INFO | Train Epoch: 12 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.075064 (0.089781) Boundary_loss: 0.013896 (0.013896) Loss: 0.088960 (0.10368) +2025-09-15,20:26:09 | INFO | Train Epoch: 12 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12904 (0.090025) Boundary_loss: 0.013898 (0.013896) Loss: 0.14294 (0.10392) +2025-09-15,20:27:15 | INFO | Train Epoch: 12 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.090460 (0.090028) Boundary_loss: 0.013897 (0.013896) Loss: 0.10436 (0.10392) +2025-09-15,20:28:21 | INFO | Train Epoch: 12 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.069657 (0.089903) Boundary_loss: 0.013895 (0.013896) Loss: 0.083552 (0.10380) +2025-09-15,20:29:26 | INFO | Train Epoch: 12 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.077036 (0.089824) Boundary_loss: 0.013896 (0.013896) Loss: 0.090932 (0.10372) +2025-09-15,20:30:32 | INFO | Train Epoch: 12 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.056526 (0.089623) Boundary_loss: 0.013898 (0.013896) Loss: 0.070424 (0.10352) +2025-09-15,20:31:38 | INFO | Train Epoch: 12 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.080105 (0.089565) Boundary_loss: 0.013897 (0.013896) Loss: 0.094002 (0.10346) +2025-09-15,20:32:44 | INFO | Train Epoch: 12 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.097451 (0.089612) Boundary_loss: 0.013895 (0.013896) Loss: 0.11135 (0.10351) +2025-09-15,20:33:49 | INFO | Train Epoch: 12 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.066594 (0.089475) Boundary_loss: 0.013896 (0.013896) Loss: 0.080490 (0.10337) +2025-09-15,20:34:55 | INFO | Train Epoch: 12 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10554 (0.089571) Boundary_loss: 0.013896 (0.013896) Loss: 0.11943 (0.10347) +2025-09-15,20:36:01 | INFO | Train Epoch: 12 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.086380 (0.089552) Boundary_loss: 0.013895 (0.013896) Loss: 0.10028 (0.10345) +2025-09-15,20:37:07 | INFO | Train Epoch: 12 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.075127 (0.089467) Boundary_loss: 0.013895 (0.013896) Loss: 0.089022 (0.10336) +2025-09-15,20:38:13 | INFO | Train Epoch: 12 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.088595 (0.089462) Boundary_loss: 0.013897 (0.013896) Loss: 0.10249 (0.10336) +2025-09-15,20:39:19 | INFO | Train Epoch: 12 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.075894 (0.089384) Boundary_loss: 0.013894 (0.013896) Loss: 0.089789 (0.10328) +2025-09-15,20:40:25 | INFO | Train Epoch: 12 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.069038 (0.089267) Boundary_loss: 0.013897 (0.013896) Loss: 0.082935 (0.10316) +2025-09-15,20:41:30 | INFO | Train Epoch: 12 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11828 (0.089433) Boundary_loss: 0.013896 (0.013896) Loss: 0.13217 (0.10333) +2025-09-15,20:42:36 | INFO | Train Epoch: 12 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10281 (0.089509) Boundary_loss: 0.013897 (0.013896) Loss: 0.11671 (0.10341) +2025-09-15,20:43:42 | INFO | Train Epoch: 12 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.066557 (0.089379) Boundary_loss: 0.013896 (0.013896) Loss: 0.080453 (0.10328) +2025-09-15,20:44:48 | INFO | Train Epoch: 12 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.035670 (0.089077) Boundary_loss: 0.013896 (0.013896) Loss: 0.049566 (0.10297) +2025-09-15,20:45:54 | INFO | Train Epoch: 12 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.063006 (0.088932) Boundary_loss: 0.013897 (0.013896) Loss: 0.076902 (0.10283) +2025-09-15,20:47:00 | INFO | Train Epoch: 12 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.083606 (0.088902) Boundary_loss: 0.013897 (0.013896) Loss: 0.097503 (0.10280) +2025-09-15,20:48:06 | INFO | Train Epoch: 12 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.077202 (0.088837) Boundary_loss: 0.013897 (0.013896) Loss: 0.091099 (0.10273) +2025-09-15,20:49:11 | INFO | Train Epoch: 12 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.091159 (0.088850) Boundary_loss: 0.013898 (0.013896) Loss: 0.10506 (0.10275) +2025-09-15,20:50:17 | INFO | Train Epoch: 12 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.072029 (0.088758) Boundary_loss: 0.013897 (0.013896) Loss: 0.085926 (0.10265) +2025-09-15,20:51:23 | INFO | Train Epoch: 12 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10892 (0.088868) Boundary_loss: 0.013897 (0.013896) Loss: 0.12282 (0.10276) +2025-09-15,20:52:29 | INFO | Train Epoch: 12 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10360 (0.088948) Boundary_loss: 0.013896 (0.013896) Loss: 0.11750 (0.10284) +2025-09-15,20:53:35 | INFO | Train Epoch: 12 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10197 (0.089018) Boundary_loss: 0.013897 (0.013896) Loss: 0.11586 (0.10291) +2025-09-15,20:54:41 | INFO | Train Epoch: 12 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.071469 (0.088924) Boundary_loss: 0.013896 (0.013896) Loss: 0.085364 (0.10282) +2025-09-15,20:55:46 | INFO | Train Epoch: 12 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.087273 (0.088915) Boundary_loss: 0.013896 (0.013896) Loss: 0.10117 (0.10281) +2025-09-15,20:56:52 | INFO | Train Epoch: 12 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.10983 (0.089026) Boundary_loss: 0.013897 (0.013896) Loss: 0.12372 (0.10292) +2025-09-15,20:57:58 | INFO | Train Epoch: 12 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.068089 (0.088915) Boundary_loss: 0.013898 (0.013896) Loss: 0.081986 (0.10281) +2025-09-15,20:59:04 | INFO | Train Epoch: 12 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10486 (0.088999) Boundary_loss: 0.013896 (0.013896) Loss: 0.11876 (0.10290) +2025-09-15,21:00:10 | INFO | Train Epoch: 12 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.082594 (0.088965) Boundary_loss: 0.013896 (0.013896) Loss: 0.096489 (0.10286) +2025-09-15,21:01:16 | INFO | Train Epoch: 12 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.11617 (0.089106) Boundary_loss: 0.013897 (0.013896) Loss: 0.13007 (0.10300) +2025-09-15,21:02:22 | INFO | Train Epoch: 12 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.069709 (0.089006) Boundary_loss: 0.013897 (0.013896) Loss: 0.083606 (0.10290) +2025-09-15,21:03:27 | INFO | Train Epoch: 12 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.059242 (0.088854) Boundary_loss: 0.013896 (0.013896) Loss: 0.073138 (0.10275) +2025-09-15,21:04:33 | INFO | Train Epoch: 12 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.085680 (0.088838) Boundary_loss: 0.013896 (0.013896) Loss: 0.099576 (0.10273) +2025-09-15,21:05:39 | INFO | Train Epoch: 12 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.096673 (0.088877) Boundary_loss: 0.013896 (0.013896) Loss: 0.11057 (0.10277) +2025-09-15,21:06:45 | INFO | Train Epoch: 12 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.066082 (0.088762) Boundary_loss: 0.013896 (0.013896) Loss: 0.079978 (0.10266) +2025-09-15,21:07:51 | INFO | Train Epoch: 12 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13010 (0.088970) Boundary_loss: 0.013896 (0.013896) Loss: 0.14400 (0.10287) +2025-09-15,21:08:57 | INFO | Train Epoch: 12 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.066658 (0.088858) Boundary_loss: 0.013897 (0.013896) Loss: 0.080554 (0.10275) +2025-09-15,21:10:02 | INFO | Train Epoch: 12 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.074495 (0.088787) Boundary_loss: 0.013896 (0.013896) Loss: 0.088391 (0.10268) +2025-09-15,21:11:08 | INFO | Train Epoch: 12 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.060891 (0.088649) Boundary_loss: 0.013896 (0.013896) Loss: 0.074787 (0.10255) +2025-09-15,21:12:14 | INFO | Train Epoch: 12 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.073062 (0.088572) Boundary_loss: 0.013896 (0.013896) Loss: 0.086957 (0.10247) +2025-09-15,21:13:20 | INFO | Train Epoch: 12 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.097556 (0.088616) Boundary_loss: 0.013895 (0.013896) Loss: 0.11145 (0.10251) +2025-09-15,21:14:26 | INFO | Train Epoch: 12 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.076198 (0.088556) Boundary_loss: 0.013896 (0.013896) Loss: 0.090095 (0.10245) +2025-09-15,21:15:32 | INFO | Train Epoch: 12 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.082039 (0.088524) Boundary_loss: 0.013896 (0.013896) Loss: 0.095935 (0.10242) +2025-09-15,21:16:37 | INFO | Train Epoch: 12 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.078842 (0.088477) Boundary_loss: 0.013896 (0.013896) Loss: 0.092738 (0.10237) +2025-09-15,21:17:43 | INFO | Train Epoch: 12 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.067791 (0.088378) Boundary_loss: 0.013897 (0.013896) Loss: 0.081688 (0.10227) +2025-09-15,21:18:49 | INFO | Train Epoch: 12 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.088328 (0.088377) Boundary_loss: 0.013897 (0.013896) Loss: 0.10223 (0.10227) +2025-09-15,21:19:55 | INFO | Train Epoch: 12 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.099718 (0.088431) Boundary_loss: 0.013895 (0.013896) Loss: 0.11361 (0.10233) +2025-09-15,21:21:01 | INFO | Train Epoch: 12 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.047026 (0.088235) Boundary_loss: 0.013895 (0.013896) Loss: 0.060921 (0.10213) +2025-09-15,21:22:06 | INFO | Train Epoch: 12 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.082580 (0.088209) Boundary_loss: 0.013896 (0.013896) Loss: 0.096476 (0.10210) +2025-09-15,21:23:12 | INFO | Train Epoch: 12 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.073600 (0.088140) Boundary_loss: 0.013898 (0.013896) Loss: 0.087498 (0.10204) +2025-09-15,21:24:18 | INFO | Train Epoch: 12 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.062749 (0.088021) Boundary_loss: 0.013896 (0.013896) Loss: 0.076645 (0.10192) +2025-09-15,21:25:24 | INFO | Train Epoch: 12 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.084860 (0.088007) Boundary_loss: 0.013895 (0.013896) Loss: 0.098755 (0.10190) +2025-09-15,21:26:30 | INFO | Train Epoch: 12 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.12464 (0.088176) Boundary_loss: 0.013897 (0.013896) Loss: 0.13854 (0.10207) +2025-09-15,21:27:36 | INFO | Train Epoch: 12 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.053129 (0.088015) Boundary_loss: 0.013897 (0.013896) Loss: 0.067026 (0.10191) +2025-09-15,21:28:41 | INFO | Train Epoch: 12 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.097111 (0.088056) Boundary_loss: 0.013896 (0.013896) Loss: 0.11101 (0.10195) +2025-09-15,21:29:47 | INFO | Train Epoch: 12 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.085020 (0.088043) Boundary_loss: 0.013897 (0.013896) Loss: 0.098917 (0.10194) +2025-09-15,21:30:53 | INFO | Train Epoch: 12 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.095289 (0.088076) Boundary_loss: 0.013897 (0.013896) Loss: 0.10919 (0.10197) +2025-09-15,21:31:59 | INFO | Train Epoch: 12 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.079275 (0.088036) Boundary_loss: 0.013896 (0.013896) Loss: 0.093171 (0.10193) +2025-09-15,21:33:05 | INFO | Train Epoch: 12 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14073 (0.088273) Boundary_loss: 0.013895 (0.013896) Loss: 0.15463 (0.10217) +2025-09-15,21:34:11 | INFO | Train Epoch: 12 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.082937 (0.088249) Boundary_loss: 0.013898 (0.013896) Loss: 0.096835 (0.10215) +2025-09-15,21:35:16 | INFO | Train Epoch: 12 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10331 (0.088316) Boundary_loss: 0.013896 (0.013896) Loss: 0.11720 (0.10221) +2025-09-15,21:36:22 | INFO | Train Epoch: 12 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.078222 (0.088271) Boundary_loss: 0.013896 (0.013896) Loss: 0.092117 (0.10217) +2025-09-15,21:37:28 | INFO | Train Epoch: 12 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.042641 (0.088070) Boundary_loss: 0.013896 (0.013896) Loss: 0.056537 (0.10197) +2025-09-15,21:38:34 | INFO | Train Epoch: 12 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.095740 (0.088103) Boundary_loss: 0.013895 (0.013896) Loss: 0.10964 (0.10200) +2025-09-15,21:39:40 | INFO | Train Epoch: 12 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.080404 (0.088070) Boundary_loss: 0.013897 (0.013896) Loss: 0.094300 (0.10197) +2025-09-15,21:40:45 | INFO | Train Epoch: 12 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.070183 (0.087991) Boundary_loss: 0.013896 (0.013896) Loss: 0.084078 (0.10189) +2025-09-15,21:41:51 | INFO | Train Epoch: 12 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.075370 (0.087937) Boundary_loss: 0.013896 (0.013896) Loss: 0.089266 (0.10183) +2025-09-15,21:42:57 | INFO | Train Epoch: 12 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.077573 (0.087892) Boundary_loss: 0.013897 (0.013896) Loss: 0.091469 (0.10179) +2025-09-15,21:44:03 | INFO | Train Epoch: 12 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.059873 (0.087771) Boundary_loss: 0.013895 (0.013896) Loss: 0.073768 (0.10167) +2025-09-15,21:45:09 | INFO | Train Epoch: 12 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.080686 (0.087741) Boundary_loss: 0.013897 (0.013896) Loss: 0.094582 (0.10164) +2025-09-15,21:46:14 | INFO | Train Epoch: 12 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.11106 (0.087840) Boundary_loss: 0.013896 (0.013896) Loss: 0.12496 (0.10174) +2025-09-15,21:47:20 | INFO | Train Epoch: 12 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.084067 (0.087824) Boundary_loss: 0.013896 (0.013896) Loss: 0.097963 (0.10172) +2025-09-15,21:48:26 | INFO | Train Epoch: 12 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.085401 (0.087814) Boundary_loss: 0.013895 (0.013896) Loss: 0.099296 (0.10171) +2025-09-15,21:49:32 | INFO | Train Epoch: 12 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.081255 (0.087786) Boundary_loss: 0.013897 (0.013896) Loss: 0.095151 (0.10168) +2025-09-15,21:50:37 | INFO | Train Epoch: 12 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11421 (0.087897) Boundary_loss: 0.013895 (0.013896) Loss: 0.12810 (0.10179) +2025-09-15,21:51:43 | INFO | Train Epoch: 12 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.085905 (0.087889) Boundary_loss: 0.013896 (0.013896) Loss: 0.099802 (0.10179) +2025-09-15,21:52:49 | INFO | Train Epoch: 12 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.091718 (0.087905) Boundary_loss: 0.013896 (0.013896) Loss: 0.10561 (0.10180) +2025-09-15,21:53:55 | INFO | Train Epoch: 12 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.095639 (0.087937) Boundary_loss: 0.013895 (0.013896) Loss: 0.10953 (0.10183) +2025-09-15,21:55:00 | INFO | Train Epoch: 12 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.056965 (0.087809) Boundary_loss: 0.013896 (0.013896) Loss: 0.070861 (0.10171) +2025-09-15,21:56:06 | INFO | Train Epoch: 12 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10815 (0.087893) Boundary_loss: 0.013896 (0.013896) Loss: 0.12204 (0.10179) +2025-09-15,21:57:12 | INFO | Train Epoch: 12 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10308 (0.087955) Boundary_loss: 0.013896 (0.013896) Loss: 0.11697 (0.10185) +2025-09-15,21:58:18 | INFO | Train Epoch: 12 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.098893 (0.088000) Boundary_loss: 0.013897 (0.013896) Loss: 0.11279 (0.10190) +2025-09-15,21:59:23 | INFO | Train Epoch: 12 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.066042 (0.087910) Boundary_loss: 0.013896 (0.013896) Loss: 0.079938 (0.10181) +2025-09-15,22:00:29 | INFO | Train Epoch: 12 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.073599 (0.087852) Boundary_loss: 0.013897 (0.013896) Loss: 0.087495 (0.10175) +2025-09-15,22:01:35 | INFO | Train Epoch: 12 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.069623 (0.087779) Boundary_loss: 0.013897 (0.013896) Loss: 0.083520 (0.10168) +2025-09-15,22:02:41 | INFO | Train Epoch: 12 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.085845 (0.087771) Boundary_loss: 0.013895 (0.013896) Loss: 0.099740 (0.10167) +2025-09-15,22:03:47 | INFO | Train Epoch: 12 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.077352 (0.087729) Boundary_loss: 0.013896 (0.013896) Loss: 0.091248 (0.10163) +2025-09-15,22:04:52 | INFO | Train Epoch: 12 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10978 (0.087817) Boundary_loss: 0.013896 (0.013896) Loss: 0.12367 (0.10171) +2025-09-15,22:05:58 | INFO | Train Epoch: 12 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.077481 (0.087776) Boundary_loss: 0.013895 (0.013896) Loss: 0.091375 (0.10167) +2025-09-15,22:07:04 | INFO | Train Epoch: 12 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.080829 (0.087749) Boundary_loss: 0.013896 (0.013896) Loss: 0.094725 (0.10165) +2025-09-15,22:08:10 | INFO | Train Epoch: 12 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.063655 (0.087654) Boundary_loss: 0.013896 (0.013896) Loss: 0.077551 (0.10155) +2025-09-15,22:09:16 | INFO | Train Epoch: 12 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10793 (0.087733) Boundary_loss: 0.013895 (0.013896) Loss: 0.12183 (0.10163) +2025-09-15,22:10:21 | INFO | Train Epoch: 12 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.093391 (0.087756) Boundary_loss: 0.013896 (0.013896) Loss: 0.10729 (0.10165) +2025-09-15,22:11:27 | INFO | Train Epoch: 12 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.079691 (0.087724) Boundary_loss: 0.013895 (0.013896) Loss: 0.093586 (0.10162) +2025-09-15,22:12:33 | INFO | Train Epoch: 12 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.090020 (0.087733) Boundary_loss: 0.013894 (0.013896) Loss: 0.10391 (0.10163) +2025-09-15,22:13:39 | INFO | Train Epoch: 12 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.064998 (0.087645) Boundary_loss: 0.013897 (0.013896) Loss: 0.078895 (0.10154) +2025-09-15,22:14:45 | INFO | Train Epoch: 12 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.093876 (0.087669) Boundary_loss: 0.013896 (0.013896) Loss: 0.10777 (0.10157) +2025-09-15,22:15:50 | INFO | Train Epoch: 12 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.098995 (0.087713) Boundary_loss: 0.013897 (0.013896) Loss: 0.11289 (0.10161) +2025-09-15,22:16:56 | INFO | Train Epoch: 12 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.082011 (0.087691) Boundary_loss: 0.013895 (0.013896) Loss: 0.095905 (0.10159) +2025-09-15,22:18:02 | INFO | Train Epoch: 12 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.081365 (0.087667) Boundary_loss: 0.013895 (0.013896) Loss: 0.095260 (0.10156) +2025-09-15,22:19:08 | INFO | Train Epoch: 12 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.052747 (0.087535) Boundary_loss: 0.013896 (0.013896) Loss: 0.066643 (0.10143) +2025-09-15,22:20:14 | INFO | Train Epoch: 12 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.087901 (0.087536) Boundary_loss: 0.013896 (0.013896) Loss: 0.10180 (0.10143) +2025-09-15,22:21:19 | INFO | Train Epoch: 12 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.092627 (0.087555) Boundary_loss: 0.013896 (0.013896) Loss: 0.10652 (0.10145) +2025-09-15,22:22:25 | INFO | Train Epoch: 12 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.095776 (0.087586) Boundary_loss: 0.013896 (0.013896) Loss: 0.10967 (0.10148) +2025-09-15,22:23:31 | INFO | Train Epoch: 12 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11626 (0.087693) Boundary_loss: 0.013896 (0.013896) Loss: 0.13015 (0.10159) +2025-09-15,22:24:37 | INFO | Train Epoch: 12 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10161 (0.087745) Boundary_loss: 0.013895 (0.013896) Loss: 0.11551 (0.10164) +2025-09-15,22:25:43 | INFO | Train Epoch: 12 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.076711 (0.087704) Boundary_loss: 0.013895 (0.013896) Loss: 0.090606 (0.10160) +2025-09-15,22:26:48 | INFO | Train Epoch: 12 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.066947 (0.087627) Boundary_loss: 0.013896 (0.013896) Loss: 0.080843 (0.10152) +2025-09-15,22:27:54 | INFO | Train Epoch: 12 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.092300 (0.087644) Boundary_loss: 0.013896 (0.013896) Loss: 0.10620 (0.10154) +2025-09-15,22:29:00 | INFO | Train Epoch: 12 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.086547 (0.087640) Boundary_loss: 0.013897 (0.013896) Loss: 0.10044 (0.10154) +2025-09-15,22:30:06 | INFO | Train Epoch: 12 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.059388 (0.087537) Boundary_loss: 0.013896 (0.013896) Loss: 0.073284 (0.10143) +2025-09-15,22:31:11 | INFO | Train Epoch: 12 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.090214 (0.087547) Boundary_loss: 0.013895 (0.013896) Loss: 0.10411 (0.10144) +2025-09-15,22:32:17 | INFO | Train Epoch: 12 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10084 (0.087595) Boundary_loss: 0.013895 (0.013896) Loss: 0.11473 (0.10149) +2025-09-15,22:33:23 | INFO | Train Epoch: 12 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.082667 (0.087577) Boundary_loss: 0.013898 (0.013896) Loss: 0.096565 (0.10147) +2025-09-15,22:34:29 | INFO | Train Epoch: 12 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.052446 (0.087451) Boundary_loss: 0.013896 (0.013896) Loss: 0.066342 (0.10135) +2025-09-15,22:35:35 | INFO | Train Epoch: 12 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.076567 (0.087412) Boundary_loss: 0.013896 (0.013896) Loss: 0.090463 (0.10131) +2025-09-15,22:36:41 | INFO | Train Epoch: 12 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.096102 (0.087443) Boundary_loss: 0.013895 (0.013896) Loss: 0.11000 (0.10134) +2025-09-15,22:37:46 | INFO | Train Epoch: 12 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.068476 (0.087375) Boundary_loss: 0.013898 (0.013896) Loss: 0.082374 (0.10127) +2025-09-15,22:38:52 | INFO | Train Epoch: 12 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.10464 (0.087437) Boundary_loss: 0.013896 (0.013896) Loss: 0.11854 (0.10133) +2025-09-15,22:39:58 | INFO | Train Epoch: 12 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.088399 (0.087440) Boundary_loss: 0.013896 (0.013896) Loss: 0.10229 (0.10134) +2025-09-15,22:41:04 | INFO | Train Epoch: 12 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.072984 (0.087389) Boundary_loss: 0.013895 (0.013896) Loss: 0.086879 (0.10129) +2025-09-15,22:42:10 | INFO | Train Epoch: 12 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.074422 (0.087344) Boundary_loss: 0.013896 (0.013896) Loss: 0.088318 (0.10124) +2025-09-15,22:43:15 | INFO | Train Epoch: 12 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.084487 (0.087334) Boundary_loss: 0.013897 (0.013896) Loss: 0.098384 (0.10123) +2025-09-15,22:44:21 | INFO | Train Epoch: 12 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.051724 (0.087210) Boundary_loss: 0.013896 (0.013896) Loss: 0.065619 (0.10111) +2025-09-15,22:45:27 | INFO | Train Epoch: 12 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.065924 (0.087136) Boundary_loss: 0.013898 (0.013896) Loss: 0.079822 (0.10103) +2025-09-15,22:46:33 | INFO | Train Epoch: 12 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.062169 (0.087049) Boundary_loss: 0.013896 (0.013896) Loss: 0.076065 (0.10095) +2025-09-15,22:47:39 | INFO | Train Epoch: 12 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.089760 (0.087059) Boundary_loss: 0.013897 (0.013896) Loss: 0.10366 (0.10095) +2025-09-15,22:48:44 | INFO | Train Epoch: 12 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.056391 (0.086953) Boundary_loss: 0.013897 (0.013896) Loss: 0.070288 (0.10085) +2025-09-15,22:49:50 | INFO | Train Epoch: 12 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.094772 (0.086980) Boundary_loss: 0.013897 (0.013896) Loss: 0.10867 (0.10088) +2025-09-15,22:50:56 | INFO | Train Epoch: 12 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.050320 (0.086855) Boundary_loss: 0.013896 (0.013896) Loss: 0.064216 (0.10075) +2025-09-15,22:52:02 | INFO | Train Epoch: 12 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.065197 (0.086781) Boundary_loss: 0.013896 (0.013896) Loss: 0.079093 (0.10068) +2025-09-15,22:53:08 | INFO | Train Epoch: 12 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.082152 (0.086766) Boundary_loss: 0.013896 (0.013896) Loss: 0.096048 (0.10066) +2025-09-15,22:54:13 | INFO | Train Epoch: 12 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.075769 (0.086728) Boundary_loss: 0.013895 (0.013896) Loss: 0.089664 (0.10062) +2025-09-15,22:55:19 | INFO | Train Epoch: 12 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.091540 (0.086745) Boundary_loss: 0.013896 (0.013896) Loss: 0.10544 (0.10064) +2025-09-15,22:56:25 | INFO | Train Epoch: 12 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.097759 (0.086782) Boundary_loss: 0.013896 (0.013896) Loss: 0.11165 (0.10068) +2025-09-15,22:57:31 | INFO | Train Epoch: 12 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10893 (0.086856) Boundary_loss: 0.013896 (0.013896) Loss: 0.12282 (0.10075) +2025-09-15,22:58:37 | INFO | Train Epoch: 12 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.088326 (0.086861) Boundary_loss: 0.013896 (0.013896) Loss: 0.10222 (0.10076) +2025-09-15,22:59:43 | INFO | Train Epoch: 12 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.056208 (0.086759) Boundary_loss: 0.013894 (0.013896) Loss: 0.070102 (0.10065) +2025-09-15,23:00:48 | INFO | Train Epoch: 12 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.090423 (0.086771) Boundary_loss: 0.013896 (0.013896) Loss: 0.10432 (0.10067) +2025-09-15,23:01:54 | INFO | Train Epoch: 12 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.060254 (0.086683) Boundary_loss: 0.013897 (0.013896) Loss: 0.074151 (0.10058) +2025-09-15,23:03:00 | INFO | Train Epoch: 12 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.064335 (0.086610) Boundary_loss: 0.013897 (0.013896) Loss: 0.078232 (0.10051) +2025-09-15,23:04:06 | INFO | Train Epoch: 12 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.074093 (0.086569) Boundary_loss: 0.013895 (0.013896) Loss: 0.087988 (0.10046) +2025-09-15,23:05:12 | INFO | Train Epoch: 12 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11314 (0.086656) Boundary_loss: 0.013895 (0.013896) Loss: 0.12703 (0.10055) +2025-09-15,23:06:17 | INFO | Train Epoch: 12 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.091053 (0.086670) Boundary_loss: 0.013895 (0.013896) Loss: 0.10495 (0.10057) +2025-09-15,23:07:23 | INFO | Train Epoch: 12 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.080224 (0.086649) Boundary_loss: 0.013895 (0.013896) Loss: 0.094118 (0.10055) +2025-09-15,23:08:29 | INFO | Train Epoch: 12 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.062073 (0.086569) Boundary_loss: 0.013897 (0.013896) Loss: 0.075969 (0.10047) +2025-09-15,23:09:35 | INFO | Train Epoch: 12 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.098926 (0.086609) Boundary_loss: 0.013896 (0.013896) Loss: 0.11282 (0.10051) +2025-09-15,23:10:41 | INFO | Train Epoch: 12 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.079272 (0.086586) Boundary_loss: 0.013897 (0.013896) Loss: 0.093170 (0.10048) +2025-09-15,23:11:46 | INFO | Train Epoch: 12 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.11479 (0.086676) Boundary_loss: 0.013897 (0.013896) Loss: 0.12869 (0.10057) +2025-09-15,23:12:52 | INFO | Train Epoch: 12 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11066 (0.086753) Boundary_loss: 0.013895 (0.013896) Loss: 0.12455 (0.10065) +2025-09-15,23:13:58 | INFO | Train Epoch: 12 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.084486 (0.086746) Boundary_loss: 0.013895 (0.013896) Loss: 0.098382 (0.10064) +2025-09-15,23:15:04 | INFO | Train Epoch: 12 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11135 (0.086824) Boundary_loss: 0.013895 (0.013896) Loss: 0.12524 (0.10072) +2025-09-15,23:16:10 | INFO | Train Epoch: 12 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.069402 (0.086768) Boundary_loss: 0.013896 (0.013896) Loss: 0.083298 (0.10066) +2025-09-15,23:17:15 | INFO | Train Epoch: 12 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.073545 (0.086727) Boundary_loss: 0.013896 (0.013896) Loss: 0.087441 (0.10062) +2025-09-15,23:18:21 | INFO | Train Epoch: 12 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.078378 (0.086701) Boundary_loss: 0.013896 (0.013896) Loss: 0.092275 (0.10060) +2025-09-15,23:19:27 | INFO | Train Epoch: 12 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10991 (0.086773) Boundary_loss: 0.013896 (0.013896) Loss: 0.12381 (0.10067) +2025-09-15,23:20:33 | INFO | Train Epoch: 12 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.082713 (0.086761) Boundary_loss: 0.013898 (0.013896) Loss: 0.096611 (0.10066) +2025-09-15,23:21:39 | INFO | Train Epoch: 12 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.079247 (0.086737) Boundary_loss: 0.013897 (0.013896) Loss: 0.093144 (0.10063) +2025-09-15,23:22:45 | INFO | Train Epoch: 12 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12560 (0.086858) Boundary_loss: 0.013897 (0.013896) Loss: 0.13950 (0.10075) +2025-09-15,23:23:50 | INFO | Train Epoch: 12 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.083808 (0.086848) Boundary_loss: 0.013895 (0.013896) Loss: 0.097703 (0.10074) +2025-09-15,23:24:56 | INFO | Train Epoch: 12 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10806 (0.086914) Boundary_loss: 0.013896 (0.013896) Loss: 0.12195 (0.10081) +2025-09-15,23:26:02 | INFO | Train Epoch: 12 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.083818 (0.086904) Boundary_loss: 0.013897 (0.013896) Loss: 0.097715 (0.10080) +2025-09-15,23:27:08 | INFO | Train Epoch: 12 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.10124 (0.086948) Boundary_loss: 0.013896 (0.013896) Loss: 0.11514 (0.10084) +2025-09-15,23:28:14 | INFO | Train Epoch: 12 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.085026 (0.086942) Boundary_loss: 0.013896 (0.013896) Loss: 0.098923 (0.10084) +2025-09-15,23:29:20 | INFO | Train Epoch: 12 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.074003 (0.086903) Boundary_loss: 0.013896 (0.013896) Loss: 0.087899 (0.10080) +2025-09-15,23:30:25 | INFO | Train Epoch: 12 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.078169 (0.086876) Boundary_loss: 0.013895 (0.013896) Loss: 0.092065 (0.10077) +2025-09-15,23:31:31 | INFO | Train Epoch: 12 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.098865 (0.086913) Boundary_loss: 0.013896 (0.013896) Loss: 0.11276 (0.10081) +2025-09-15,23:32:37 | INFO | Train Epoch: 12 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.081245 (0.086896) Boundary_loss: 0.013896 (0.013896) Loss: 0.095141 (0.10079) +2025-09-15,23:33:43 | INFO | Train Epoch: 12 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.096100 (0.086923) Boundary_loss: 0.013895 (0.013896) Loss: 0.10999 (0.10082) +2025-09-15,23:34:49 | INFO | Train Epoch: 12 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10149 (0.086967) Boundary_loss: 0.013896 (0.013896) Loss: 0.11538 (0.10086) +2025-09-15,23:35:55 | INFO | Train Epoch: 12 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.077710 (0.086939) Boundary_loss: 0.013895 (0.013896) Loss: 0.091605 (0.10084) +2025-09-15,23:37:00 | INFO | Train Epoch: 12 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.094370 (0.086962) Boundary_loss: 0.013896 (0.013896) Loss: 0.10827 (0.10086) +2025-09-15,23:38:06 | INFO | Train Epoch: 12 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.078347 (0.086936) Boundary_loss: 0.013897 (0.013896) Loss: 0.092244 (0.10083) +2025-09-15,23:39:12 | INFO | Train Epoch: 12 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11095 (0.087007) Boundary_loss: 0.013896 (0.013896) Loss: 0.12485 (0.10090) +2025-09-15,23:40:18 | INFO | Train Epoch: 12 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.062126 (0.086934) Boundary_loss: 0.013896 (0.013896) Loss: 0.076022 (0.10083) +2025-09-15,23:41:24 | INFO | Train Epoch: 12 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.073522 (0.086894) Boundary_loss: 0.013897 (0.013896) Loss: 0.087420 (0.10079) +2025-09-15,23:42:30 | INFO | Train Epoch: 12 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.070350 (0.086845) Boundary_loss: 0.013896 (0.013896) Loss: 0.084246 (0.10074) +2025-09-15,23:43:35 | INFO | Train Epoch: 12 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.089229 (0.086852) Boundary_loss: 0.013897 (0.013896) Loss: 0.10313 (0.10075) +2025-09-15,23:44:41 | INFO | Train Epoch: 12 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.089198 (0.086859) Boundary_loss: 0.013896 (0.013896) Loss: 0.10309 (0.10076) +2025-09-15,23:45:47 | INFO | Train Epoch: 12 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.082060 (0.086845) Boundary_loss: 0.013896 (0.013896) Loss: 0.095956 (0.10074) +2025-09-15,23:46:53 | INFO | Train Epoch: 12 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.072626 (0.086804) Boundary_loss: 0.013896 (0.013896) Loss: 0.086522 (0.10070) +2025-09-15,23:47:59 | INFO | Train Epoch: 12 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.088858 (0.086810) Boundary_loss: 0.013895 (0.013896) Loss: 0.10275 (0.10071) +2025-09-15,23:49:05 | INFO | Train Epoch: 12 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.063712 (0.086743) Boundary_loss: 0.013894 (0.013896) Loss: 0.077606 (0.10064) +2025-09-15,23:50:11 | INFO | Train Epoch: 12 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.088988 (0.086750) Boundary_loss: 0.013896 (0.013896) Loss: 0.10288 (0.10065) +2025-09-15,23:51:16 | INFO | Train Epoch: 12 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.088056 (0.086753) Boundary_loss: 0.013896 (0.013896) Loss: 0.10195 (0.10065) +2025-09-15,23:52:22 | INFO | Train Epoch: 12 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.053037 (0.086657) Boundary_loss: 0.013896 (0.013896) Loss: 0.066933 (0.10055) +2025-09-15,23:53:28 | INFO | Train Epoch: 12 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.089444 (0.086665) Boundary_loss: 0.013896 (0.013896) Loss: 0.10334 (0.10056) +2025-09-15,23:54:34 | INFO | Train Epoch: 12 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.081084 (0.086649) Boundary_loss: 0.013896 (0.013896) Loss: 0.094981 (0.10055) +2025-09-15,23:55:40 | INFO | Train Epoch: 12 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.073919 (0.086613) Boundary_loss: 0.013895 (0.013896) Loss: 0.087814 (0.10051) +2025-09-15,23:56:46 | INFO | Train Epoch: 12 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.075891 (0.086582) Boundary_loss: 0.013897 (0.013896) Loss: 0.089788 (0.10048) +2025-09-15,23:57:52 | INFO | Train Epoch: 12 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.065508 (0.086523) Boundary_loss: 0.013896 (0.013896) Loss: 0.079403 (0.10042) +2025-09-15,23:58:57 | INFO | Train Epoch: 12 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.092278 (0.086539) Boundary_loss: 0.013897 (0.013896) Loss: 0.10617 (0.10044) +2025-09-16,00:00:03 | INFO | Train Epoch: 12 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.065875 (0.086481) Boundary_loss: 0.013895 (0.013896) Loss: 0.079770 (0.10038) +2025-09-16,00:01:09 | INFO | Train Epoch: 12 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.094150 (0.086502) Boundary_loss: 0.013896 (0.013896) Loss: 0.10805 (0.10040) +2025-09-16,00:02:15 | INFO | Train Epoch: 12 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.070241 (0.086457) Boundary_loss: 0.013896 (0.013896) Loss: 0.084137 (0.10035) +2025-09-16,00:03:21 | INFO | Train Epoch: 12 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14987 (0.086634) Boundary_loss: 0.013896 (0.013896) Loss: 0.16377 (0.10053) +2025-09-16,00:04:27 | INFO | Train Epoch: 12 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.081737 (0.086620) Boundary_loss: 0.013899 (0.013896) Loss: 0.095635 (0.10052) +2025-09-16,00:05:33 | INFO | Train Epoch: 12 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.085687 (0.086617) Boundary_loss: 0.013896 (0.013896) Loss: 0.099583 (0.10051) +2025-09-16,00:06:38 | INFO | Train Epoch: 12 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11264 (0.086689) Boundary_loss: 0.013896 (0.013896) Loss: 0.12654 (0.10059) +2025-09-16,00:07:44 | INFO | Train Epoch: 12 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.076043 (0.086660) Boundary_loss: 0.013896 (0.013896) Loss: 0.089939 (0.10056) +2025-09-16,00:08:50 | INFO | Train Epoch: 12 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.077597 (0.086635) Boundary_loss: 0.013896 (0.013896) Loss: 0.091493 (0.10053) +2025-09-16,00:09:56 | INFO | Train Epoch: 12 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.093376 (0.086654) Boundary_loss: 0.013896 (0.013896) Loss: 0.10727 (0.10055) +2025-09-16,00:11:02 | INFO | Train Epoch: 12 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11790 (0.086739) Boundary_loss: 0.013895 (0.013896) Loss: 0.13179 (0.10064) +2025-09-16,00:12:08 | INFO | Train Epoch: 12 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.083240 (0.086729) Boundary_loss: 0.013897 (0.013896) Loss: 0.097137 (0.10063) +2025-09-16,00:13:14 | INFO | Train Epoch: 12 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.081608 (0.086715) Boundary_loss: 0.013895 (0.013896) Loss: 0.095503 (0.10061) +2025-09-16,00:14:20 | INFO | Train Epoch: 12 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.098476 (0.086747) Boundary_loss: 0.013895 (0.013896) Loss: 0.11237 (0.10064) +2025-09-16,00:15:25 | INFO | Train Epoch: 12 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10912 (0.086808) Boundary_loss: 0.013894 (0.013896) Loss: 0.12301 (0.10070) +2025-09-16,00:16:31 | INFO | Train Epoch: 12 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.073470 (0.086772) Boundary_loss: 0.013897 (0.013896) Loss: 0.087367 (0.10067) +2025-09-16,00:17:37 | INFO | Train Epoch: 12 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.099283 (0.086806) Boundary_loss: 0.013897 (0.013896) Loss: 0.11318 (0.10070) +2025-09-16,00:18:43 | INFO | Train Epoch: 12 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.073771 (0.086771) Boundary_loss: 0.013896 (0.013896) Loss: 0.087667 (0.10067) +2025-09-16,00:19:49 | INFO | Train Epoch: 12 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.070879 (0.086728) Boundary_loss: 0.013897 (0.013896) Loss: 0.084775 (0.10062) +2025-09-16,00:20:55 | INFO | Train Epoch: 12 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11573 (0.086805) Boundary_loss: 0.013898 (0.013896) Loss: 0.12962 (0.10070) +2025-09-16,00:22:00 | INFO | Train Epoch: 12 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.088527 (0.086810) Boundary_loss: 0.013895 (0.013896) Loss: 0.10242 (0.10071) +2025-09-16,00:23:06 | INFO | Train Epoch: 12 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.076822 (0.086783) Boundary_loss: 0.013895 (0.013896) Loss: 0.090717 (0.10068) +2025-09-16,00:24:12 | INFO | Train Epoch: 12 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.061419 (0.086716) Boundary_loss: 0.013896 (0.013896) Loss: 0.075315 (0.10061) +2025-09-16,00:25:18 | INFO | Train Epoch: 12 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.093590 (0.086735) Boundary_loss: 0.013895 (0.013896) Loss: 0.10749 (0.10063) +2025-09-16,00:26:24 | INFO | Train Epoch: 12 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.066995 (0.086683) Boundary_loss: 0.013897 (0.013896) Loss: 0.080892 (0.10058) +2025-09-16,00:27:30 | INFO | Train Epoch: 12 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.088041 (0.086686) Boundary_loss: 0.013896 (0.013896) Loss: 0.10194 (0.10058) +2025-09-16,00:28:36 | INFO | Train Epoch: 12 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10422 (0.086732) Boundary_loss: 0.013895 (0.013896) Loss: 0.11812 (0.10063) +2025-09-16,00:29:41 | INFO | Train Epoch: 12 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.078708 (0.086711) Boundary_loss: 0.013896 (0.013896) Loss: 0.092605 (0.10061) +2025-09-16,00:30:47 | INFO | Train Epoch: 12 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.070718 (0.086669) Boundary_loss: 0.013897 (0.013896) Loss: 0.084615 (0.10057) +2025-09-16,00:31:53 | INFO | Train Epoch: 12 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.083382 (0.086661) Boundary_loss: 0.013896 (0.013896) Loss: 0.097278 (0.10056) +2025-09-16,00:32:59 | INFO | Train Epoch: 12 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10596 (0.086711) Boundary_loss: 0.013896 (0.013896) Loss: 0.11986 (0.10061) +2025-09-16,00:34:05 | INFO | Train Epoch: 12 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10471 (0.086757) Boundary_loss: 0.013895 (0.013896) Loss: 0.11861 (0.10065) +2025-09-16,00:35:11 | INFO | Train Epoch: 12 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.056358 (0.086679) Boundary_loss: 0.013896 (0.013896) Loss: 0.070254 (0.10058) +2025-09-16,00:36:17 | INFO | Train Epoch: 12 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.088843 (0.086685) Boundary_loss: 0.013897 (0.013896) Loss: 0.10274 (0.10058) +2025-09-16,00:37:23 | INFO | Train Epoch: 12 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.085024 (0.086680) Boundary_loss: 0.013896 (0.013896) Loss: 0.098920 (0.10058) +2025-09-16,00:38:28 | INFO | Train Epoch: 12 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.052801 (0.086594) Boundary_loss: 0.013896 (0.013896) Loss: 0.066696 (0.10049) +2025-09-16,00:39:34 | INFO | Train Epoch: 12 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.10353 (0.086637) Boundary_loss: 0.013896 (0.013896) Loss: 0.11743 (0.10053) +2025-09-16,00:40:40 | INFO | Train Epoch: 12 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.078973 (0.086617) Boundary_loss: 0.013896 (0.013896) Loss: 0.092869 (0.10051) +2025-09-16,00:41:46 | INFO | Train Epoch: 12 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.075497 (0.086589) Boundary_loss: 0.013896 (0.013896) Loss: 0.089393 (0.10049) +2025-09-16,00:42:52 | INFO | Train Epoch: 12 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.081443 (0.086576) Boundary_loss: 0.013895 (0.013896) Loss: 0.095338 (0.10047) +2025-09-16,00:43:58 | INFO | Train Epoch: 12 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.065716 (0.086524) Boundary_loss: 0.013898 (0.013896) Loss: 0.079614 (0.10042) +2025-09-16,00:45:04 | INFO | Train Epoch: 12 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.097202 (0.086550) Boundary_loss: 0.013897 (0.013896) Loss: 0.11110 (0.10045) +2025-09-16,00:46:10 | INFO | Train Epoch: 12 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.073915 (0.086519) Boundary_loss: 0.013895 (0.013896) Loss: 0.087810 (0.10041) +2025-09-16,00:47:16 | INFO | Train Epoch: 12 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.069737 (0.086477) Boundary_loss: 0.013895 (0.013896) Loss: 0.083632 (0.10037) +2025-09-16,00:48:21 | INFO | Train Epoch: 12 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.071212 (0.086438) Boundary_loss: 0.013896 (0.013896) Loss: 0.085108 (0.10033) +2025-09-16,00:49:27 | INFO | Train Epoch: 12 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.098276 (0.086468) Boundary_loss: 0.013895 (0.013896) Loss: 0.11217 (0.10036) +2025-09-16,00:50:33 | INFO | Train Epoch: 12 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.089591 (0.086476) Boundary_loss: 0.013897 (0.013896) Loss: 0.10349 (0.10037) +2025-09-16,00:51:39 | INFO | Train Epoch: 12 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10420 (0.086520) Boundary_loss: 0.013895 (0.013896) Loss: 0.11810 (0.10042) +2025-09-16,00:52:45 | INFO | Train Epoch: 12 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10591 (0.086568) Boundary_loss: 0.013895 (0.013896) Loss: 0.11981 (0.10046) +2025-09-16,00:53:51 | INFO | Train Epoch: 12 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12475 (0.086662) Boundary_loss: 0.013895 (0.013896) Loss: 0.13865 (0.10056) +2025-09-16,00:54:57 | INFO | Train Epoch: 12 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.071315 (0.086624) Boundary_loss: 0.013896 (0.013896) Loss: 0.085211 (0.10052) +2025-09-16,00:56:03 | INFO | Train Epoch: 12 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.079317 (0.086606) Boundary_loss: 0.013895 (0.013896) Loss: 0.093212 (0.10050) +2025-09-16,00:57:08 | INFO | Train Epoch: 12 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.097067 (0.086632) Boundary_loss: 0.013895 (0.013896) Loss: 0.11096 (0.10053) +2025-09-16,00:58:14 | INFO | Train Epoch: 12 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12454 (0.086725) Boundary_loss: 0.013897 (0.013896) Loss: 0.13844 (0.10062) +2025-09-16,00:59:20 | INFO | Train Epoch: 12 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.083796 (0.086717) Boundary_loss: 0.013897 (0.013896) Loss: 0.097693 (0.10061) +2025-09-16,01:00:26 | INFO | Train Epoch: 12 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.072867 (0.086684) Boundary_loss: 0.013895 (0.013896) Loss: 0.086763 (0.10058) +2025-09-16,01:01:32 | INFO | Train Epoch: 12 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.059988 (0.086619) Boundary_loss: 0.013895 (0.013896) Loss: 0.073883 (0.10052) +2025-09-16,01:02:38 | INFO | Train Epoch: 12 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.094229 (0.086637) Boundary_loss: 0.013896 (0.013896) Loss: 0.10813 (0.10053) +2025-09-16,01:03:44 | INFO | Train Epoch: 12 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.052552 (0.086555) Boundary_loss: 0.013898 (0.013896) Loss: 0.066450 (0.10045) +2025-09-16,01:04:50 | INFO | Train Epoch: 12 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.067984 (0.086510) Boundary_loss: 0.013895 (0.013896) Loss: 0.081879 (0.10041) +2025-09-16,01:05:55 | INFO | Train Epoch: 12 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.095367 (0.086532) Boundary_loss: 0.013895 (0.013896) Loss: 0.10926 (0.10043) +2025-09-16,01:07:01 | INFO | Train Epoch: 12 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.073171 (0.086500) Boundary_loss: 0.013897 (0.013896) Loss: 0.087068 (0.10040) +2025-09-16,01:08:07 | INFO | Train Epoch: 12 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10282 (0.086539) Boundary_loss: 0.013897 (0.013896) Loss: 0.11672 (0.10043) +2025-09-16,01:09:13 | INFO | Train Epoch: 12 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.091458 (0.086550) Boundary_loss: 0.013897 (0.013896) Loss: 0.10535 (0.10045) +2025-09-16,01:10:19 | INFO | Train Epoch: 12 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.065659 (0.086501) Boundary_loss: 0.013896 (0.013896) Loss: 0.079555 (0.10040) +2025-09-16,01:11:25 | INFO | Train Epoch: 12 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.074699 (0.086473) Boundary_loss: 0.013896 (0.013896) Loss: 0.088596 (0.10037) +2025-09-16,01:12:31 | INFO | Train Epoch: 12 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.074067 (0.086443) Boundary_loss: 0.013895 (0.013896) Loss: 0.087962 (0.10034) +2025-09-16,01:13:36 | INFO | Train Epoch: 12 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.078515 (0.086424) Boundary_loss: 0.013897 (0.013896) Loss: 0.092412 (0.10032) +2025-09-16,01:14:42 | INFO | Train Epoch: 12 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.074347 (0.086396) Boundary_loss: 0.013895 (0.013896) Loss: 0.088242 (0.10029) +2025-09-16,01:15:48 | INFO | Train Epoch: 12 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.098963 (0.086426) Boundary_loss: 0.013895 (0.013896) Loss: 0.11286 (0.10032) +2025-09-16,01:16:54 | INFO | Train Epoch: 12 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.12214 (0.086509) Boundary_loss: 0.013895 (0.013896) Loss: 0.13604 (0.10041) +2025-09-16,01:18:00 | INFO | Train Epoch: 12 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.099528 (0.086540) Boundary_loss: 0.013895 (0.013896) Loss: 0.11342 (0.10044) +2025-09-16,01:19:06 | INFO | Train Epoch: 12 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.070077 (0.086501) Boundary_loss: 0.013895 (0.013896) Loss: 0.083972 (0.10040) +2025-09-16,01:20:12 | INFO | Train Epoch: 12 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12731 (0.086597) Boundary_loss: 0.013896 (0.013896) Loss: 0.14121 (0.10049) +2025-09-16,01:21:17 | INFO | Train Epoch: 12 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10226 (0.086633) Boundary_loss: 0.013895 (0.013896) Loss: 0.11615 (0.10053) +2025-09-16,01:22:23 | INFO | Train Epoch: 12 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.073815 (0.086603) Boundary_loss: 0.013897 (0.013896) Loss: 0.087712 (0.10050) +2025-09-16,01:23:29 | INFO | Train Epoch: 12 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10328 (0.086642) Boundary_loss: 0.013895 (0.013896) Loss: 0.11718 (0.10054) +2025-09-16,01:24:35 | INFO | Train Epoch: 12 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.079595 (0.086626) Boundary_loss: 0.013896 (0.013896) Loss: 0.093491 (0.10052) +2025-09-16,01:25:41 | INFO | Train Epoch: 12 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.066547 (0.086579) Boundary_loss: 0.013895 (0.013896) Loss: 0.080442 (0.10048) +2025-09-16,01:26:47 | INFO | Train Epoch: 12 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10018 (0.086611) Boundary_loss: 0.013895 (0.013896) Loss: 0.11407 (0.10051) +2025-09-16,01:27:52 | INFO | Train Epoch: 12 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.073007 (0.086579) Boundary_loss: 0.013896 (0.013896) Loss: 0.086903 (0.10048) +2025-09-16,01:28:58 | INFO | Train Epoch: 12 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.082029 (0.086569) Boundary_loss: 0.013897 (0.013896) Loss: 0.095926 (0.10047) +2025-09-16,01:30:04 | INFO | Train Epoch: 12 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.088904 (0.086574) Boundary_loss: 0.013898 (0.013896) Loss: 0.10280 (0.10047) +2025-09-16,01:31:10 | INFO | Train Epoch: 12 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.064448 (0.086524) Boundary_loss: 0.013896 (0.013896) Loss: 0.078344 (0.10042) +2025-09-16,01:32:16 | INFO | Train Epoch: 12 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.069624 (0.086485) Boundary_loss: 0.013897 (0.013896) Loss: 0.083521 (0.10038) +2025-09-16,01:33:22 | INFO | Train Epoch: 12 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.074812 (0.086459) Boundary_loss: 0.013897 (0.013896) Loss: 0.088709 (0.10036) +2025-09-16,01:34:28 | INFO | Train Epoch: 12 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.095659 (0.086480) Boundary_loss: 0.013897 (0.013896) Loss: 0.10956 (0.10038) +2025-09-16,01:35:33 | INFO | Train Epoch: 12 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.088384 (0.086484) Boundary_loss: 0.013896 (0.013896) Loss: 0.10228 (0.10038) +2025-09-16,01:36:39 | INFO | Train Epoch: 12 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.072285 (0.086452) Boundary_loss: 0.013895 (0.013896) Loss: 0.086180 (0.10035) +2025-09-16,01:37:45 | INFO | Train Epoch: 12 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.092387 (0.086465) Boundary_loss: 0.013896 (0.013896) Loss: 0.10628 (0.10036) +2025-09-16,01:38:51 | INFO | Train Epoch: 12 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.057247 (0.086400) Boundary_loss: 0.013896 (0.013896) Loss: 0.071143 (0.10030) +2025-09-16,01:39:57 | INFO | Train Epoch: 12 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.098265 (0.086426) Boundary_loss: 0.013896 (0.013896) Loss: 0.11216 (0.10032) +2025-09-16,01:41:03 | INFO | Train Epoch: 12 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.066577 (0.086382) Boundary_loss: 0.013896 (0.013896) Loss: 0.080473 (0.10028) +2025-09-16,01:42:09 | INFO | Train Epoch: 12 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12038 (0.086458) Boundary_loss: 0.013896 (0.013896) Loss: 0.13428 (0.10035) +2025-09-16,01:43:15 | INFO | Train Epoch: 12 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.071093 (0.086424) Boundary_loss: 0.013896 (0.013896) Loss: 0.084989 (0.10032) +2025-09-16,01:44:20 | INFO | Train Epoch: 12 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.055422 (0.086355) Boundary_loss: 0.013896 (0.013896) Loss: 0.069319 (0.10025) +2025-09-16,01:45:26 | INFO | Train Epoch: 12 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12180 (0.086433) Boundary_loss: 0.013896 (0.013896) Loss: 0.13570 (0.10033) +2025-09-16,01:46:32 | INFO | Train Epoch: 12 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.064870 (0.086386) Boundary_loss: 0.013896 (0.013896) Loss: 0.078766 (0.10028) +2025-09-16,01:47:38 | INFO | Train Epoch: 12 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.059278 (0.086326) Boundary_loss: 0.013896 (0.013896) Loss: 0.073174 (0.10022) +2025-09-16,01:48:44 | INFO | Train Epoch: 12 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.058320 (0.086265) Boundary_loss: 0.013896 (0.013896) Loss: 0.072216 (0.10016) +2025-09-16,01:49:50 | INFO | Train Epoch: 12 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.064459 (0.086217) Boundary_loss: 0.013896 (0.013896) Loss: 0.078355 (0.10011) +2025-09-16,01:50:56 | INFO | Train Epoch: 12 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10660 (0.086261) Boundary_loss: 0.013897 (0.013896) Loss: 0.12050 (0.10016) +2025-09-16,01:52:02 | INFO | Train Epoch: 12 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.089169 (0.086268) Boundary_loss: 0.013897 (0.013896) Loss: 0.10307 (0.10016) +2025-09-16,01:53:08 | INFO | Train Epoch: 12 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.074035 (0.086241) Boundary_loss: 0.013896 (0.013896) Loss: 0.087930 (0.10014) +2025-09-16,01:54:14 | INFO | Train Epoch: 12 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.091538 (0.086253) Boundary_loss: 0.013896 (0.013896) Loss: 0.10543 (0.10015) +2025-09-16,01:55:19 | INFO | Train Epoch: 12 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.039891 (0.086152) Boundary_loss: 0.013896 (0.013896) Loss: 0.053787 (0.10005) +2025-09-16,01:56:25 | INFO | Train Epoch: 12 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.089485 (0.086159) Boundary_loss: 0.013895 (0.013896) Loss: 0.10338 (0.10006) +2025-09-16,01:57:31 | INFO | Train Epoch: 12 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.075427 (0.086136) Boundary_loss: 0.013895 (0.013896) Loss: 0.089322 (0.10003) +2025-09-16,01:58:37 | INFO | Train Epoch: 12 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10109 (0.086168) Boundary_loss: 0.013896 (0.013896) Loss: 0.11499 (0.10006) +2025-09-16,01:59:43 | INFO | Train Epoch: 12 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.070286 (0.086134) Boundary_loss: 0.013896 (0.013896) Loss: 0.084183 (0.10003) +2025-09-16,02:00:49 | INFO | Train Epoch: 12 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.065679 (0.086090) Boundary_loss: 0.013896 (0.013896) Loss: 0.079575 (0.099986) +2025-09-16,02:01:55 | INFO | Train Epoch: 12 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.080283 (0.086078) Boundary_loss: 0.013896 (0.013896) Loss: 0.094178 (0.099974) +2025-09-16,02:03:01 | INFO | Train Epoch: 12 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.072418 (0.086049) Boundary_loss: 0.013896 (0.013896) Loss: 0.086314 (0.099945) +2025-09-16,02:04:07 | INFO | Train Epoch: 12 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.067466 (0.086009) Boundary_loss: 0.013897 (0.013896) Loss: 0.081364 (0.099905) +2025-09-16,02:05:12 | INFO | Train Epoch: 12 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.058615 (0.085951) Boundary_loss: 0.013896 (0.013896) Loss: 0.072511 (0.099847) +2025-09-16,02:06:18 | INFO | Train Epoch: 12 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10141 (0.085983) Boundary_loss: 0.013896 (0.013896) Loss: 0.11531 (0.099880) +2025-09-16,02:07:24 | INFO | Train Epoch: 12 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.071984 (0.085954) Boundary_loss: 0.013894 (0.013896) Loss: 0.085878 (0.099850) +2025-09-16,02:08:30 | INFO | Train Epoch: 12 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.082363 (0.085946) Boundary_loss: 0.013897 (0.013896) Loss: 0.096259 (0.099842) +2025-09-16,02:09:36 | INFO | Train Epoch: 12 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.074680 (0.085922) Boundary_loss: 0.013896 (0.013896) Loss: 0.088576 (0.099819) +2025-09-16,02:10:42 | INFO | Train Epoch: 12 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.073095 (0.085895) Boundary_loss: 0.013897 (0.013896) Loss: 0.086992 (0.099792) +2025-09-16,02:11:48 | INFO | Train Epoch: 12 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.049529 (0.085819) Boundary_loss: 0.013895 (0.013896) Loss: 0.063424 (0.099715) +2025-09-16,02:12:54 | INFO | Train Epoch: 12 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.086103 (0.085820) Boundary_loss: 0.013896 (0.013896) Loss: 0.099999 (0.099716) +2025-09-16,02:14:00 | INFO | Train Epoch: 12 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.051760 (0.085748) Boundary_loss: 0.013897 (0.013896) Loss: 0.065657 (0.099645) +2025-09-16,02:15:06 | INFO | Train Epoch: 12 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.068314 (0.085712) Boundary_loss: 0.013895 (0.013896) Loss: 0.082209 (0.099608) +2025-09-16,02:16:12 | INFO | Train Epoch: 12 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.069716 (0.085679) Boundary_loss: 0.013894 (0.013896) Loss: 0.083611 (0.099575) +2025-09-16,02:17:17 | INFO | Train Epoch: 12 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.071885 (0.085650) Boundary_loss: 0.013897 (0.013896) Loss: 0.085782 (0.099546) +2025-09-16,02:18:23 | INFO | Train Epoch: 12 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.050100 (0.085576) Boundary_loss: 0.013895 (0.013896) Loss: 0.063995 (0.099472) +2025-09-16,02:19:29 | INFO | Train Epoch: 12 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.078704 (0.085562) Boundary_loss: 0.013896 (0.013896) Loss: 0.092600 (0.099458) +2025-09-16,02:20:35 | INFO | Train Epoch: 12 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.079065 (0.085549) Boundary_loss: 0.013895 (0.013896) Loss: 0.092960 (0.099445) +2025-09-16,02:21:41 | INFO | Train Epoch: 12 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.077030 (0.085531) Boundary_loss: 0.013896 (0.013896) Loss: 0.090926 (0.099427) +2025-09-16,02:22:47 | INFO | Train Epoch: 12 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.084621 (0.085529) Boundary_loss: 0.013896 (0.013896) Loss: 0.098516 (0.099425) +2025-09-16,02:23:53 | INFO | Train Epoch: 12 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.080884 (0.085520) Boundary_loss: 0.013895 (0.013896) Loss: 0.094779 (0.099416) +2025-09-16,02:24:59 | INFO | Train Epoch: 12 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.071006 (0.085490) Boundary_loss: 0.013898 (0.013896) Loss: 0.084903 (0.099386) +2025-09-16,02:26:05 | INFO | Train Epoch: 12 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.088175 (0.085495) Boundary_loss: 0.013896 (0.013896) Loss: 0.10207 (0.099391) +2025-09-16,02:27:10 | INFO | Train Epoch: 12 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.072875 (0.085470) Boundary_loss: 0.013896 (0.013896) Loss: 0.086770 (0.099366) +2025-09-16,02:28:16 | INFO | Train Epoch: 12 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.078415 (0.085455) Boundary_loss: 0.013896 (0.013896) Loss: 0.092311 (0.099351) +2025-09-16,02:29:22 | INFO | Train Epoch: 12 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.097078 (0.085479) Boundary_loss: 0.013895 (0.013896) Loss: 0.11097 (0.099375) +2025-09-16,02:30:28 | INFO | Train Epoch: 12 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.070189 (0.085448) Boundary_loss: 0.013895 (0.013896) Loss: 0.084084 (0.099344) +2025-09-16,02:31:34 | INFO | Train Epoch: 12 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.098376 (0.085474) Boundary_loss: 0.013895 (0.013896) Loss: 0.11227 (0.099370) +2025-09-16,02:32:40 | INFO | Train Epoch: 12 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.074795 (0.085452) Boundary_loss: 0.013897 (0.013896) Loss: 0.088692 (0.099349) +2025-09-16,02:33:46 | INFO | Train Epoch: 12 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.069968 (0.085421) Boundary_loss: 0.013895 (0.013896) Loss: 0.083864 (0.099317) +2025-09-16,02:34:52 | INFO | Train Epoch: 12 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.070561 (0.085391) Boundary_loss: 0.013894 (0.013896) Loss: 0.084455 (0.099287) +2025-09-16,02:35:57 | INFO | Train Epoch: 12 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.089268 (0.085399) Boundary_loss: 0.013895 (0.013896) Loss: 0.10316 (0.099295) +2025-09-16,02:37:03 | INFO | Train Epoch: 12 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.096915 (0.085422) Boundary_loss: 0.013895 (0.013896) Loss: 0.11081 (0.099318) +2025-09-16,02:38:09 | INFO | Train Epoch: 12 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.082533 (0.085416) Boundary_loss: 0.013896 (0.013896) Loss: 0.096429 (0.099313) +2025-09-16,02:39:15 | INFO | Train Epoch: 12 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.088856 (0.085423) Boundary_loss: 0.013897 (0.013896) Loss: 0.10275 (0.099319) +2025-09-16,02:40:21 | INFO | Train Epoch: 12 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.066528 (0.085386) Boundary_loss: 0.013895 (0.013896) Loss: 0.080423 (0.099282) +2025-09-16,02:41:27 | INFO | Train Epoch: 12 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.082203 (0.085379) Boundary_loss: 0.013896 (0.013896) Loss: 0.096099 (0.099275) +2025-09-16,02:42:33 | INFO | Train Epoch: 12 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10283 (0.085414) Boundary_loss: 0.013896 (0.013896) Loss: 0.11672 (0.099310) +2025-09-16,02:43:39 | INFO | Train Epoch: 12 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10489 (0.085453) Boundary_loss: 0.013896 (0.013896) Loss: 0.11878 (0.099349) +2025-09-16,02:44:44 | INFO | Train Epoch: 12 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.099766 (0.085481) Boundary_loss: 0.013896 (0.013896) Loss: 0.11366 (0.099377) +2025-09-16,02:45:50 | INFO | Train Epoch: 12 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.055451 (0.085422) Boundary_loss: 0.013896 (0.013896) Loss: 0.069347 (0.099318) +2025-09-16,02:46:56 | INFO | Train Epoch: 12 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.076376 (0.085404) Boundary_loss: 0.013894 (0.013896) Loss: 0.090270 (0.099300) +2025-09-16,02:48:02 | INFO | Train Epoch: 12 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.089709 (0.085412) Boundary_loss: 0.013895 (0.013896) Loss: 0.10360 (0.099308) +2025-09-16,02:49:08 | INFO | Train Epoch: 12 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.074954 (0.085392) Boundary_loss: 0.013896 (0.013896) Loss: 0.088850 (0.099288) +2025-09-16,02:50:14 | INFO | Train Epoch: 12 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.062107 (0.085346) Boundary_loss: 0.013896 (0.013896) Loss: 0.076003 (0.099242) +2025-09-16,02:51:20 | INFO | Train Epoch: 12 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.076804 (0.085329) Boundary_loss: 0.013896 (0.013896) Loss: 0.090700 (0.099226) +2025-09-16,02:52:26 | INFO | Train Epoch: 12 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10262 (0.085363) Boundary_loss: 0.013896 (0.013896) Loss: 0.11652 (0.099259) +2025-09-16,02:53:31 | INFO | Train Epoch: 12 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.061735 (0.085317) Boundary_loss: 0.013896 (0.013896) Loss: 0.075631 (0.099213) +2025-09-16,02:54:37 | INFO | Train Epoch: 12 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.072333 (0.085292) Boundary_loss: 0.013896 (0.013896) Loss: 0.086229 (0.099188) +2025-09-16,02:55:40 | INFO | Train Epoch: 12 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.091116 (0.085303) Boundary_loss: 0.013896 (0.013896) Loss: 0.10501 (0.099199) +2025-09-16,02:55:40 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-16,02:55:40 | INFO | [Epoch 12] Average Step Time: 0.662s | Average GPU Memory: 30.8 GB +2025-09-16,02:55:40 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-16,02:55:40 | INFO | Starting zero-shot imagenet. +2025-09-16,02:55:40 | INFO | Building zero-shot classifier +2025-09-16,02:55:49 | INFO | Using classifier +2025-09-16,02:56:33 | INFO | Finished zero-shot imagenet. +2025-09-16,02:56:33 | INFO | Eval Epoch: 13 imagenet-zeroshot-val-top1: 0.3308 imagenet-zeroshot-val-top5: 0.6068 +2025-09-16,02:56:34 | INFO | Start epoch 13 +2025-09-16,02:56:36 | INFO | Train Epoch: 13 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.073718 (0.073718) Boundary_loss: 0.013896 (0.013896) Loss: 0.087613 (0.087613) +2025-09-16,02:57:42 | INFO | Train Epoch: 13 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.046463 (0.060090) Boundary_loss: 0.013895 (0.013896) Loss: 0.060358 (0.073986) +2025-09-16,02:58:48 | INFO | Train Epoch: 13 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.072706 (0.064295) Boundary_loss: 0.013897 (0.013896) Loss: 0.086602 (0.078191) +2025-09-16,02:59:53 | INFO | Train Epoch: 13 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.071492 (0.066095) Boundary_loss: 0.013896 (0.013896) Loss: 0.085389 (0.079991) +2025-09-16,03:00:59 | INFO | Train Epoch: 13 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.081044 (0.069085) Boundary_loss: 0.013898 (0.013896) Loss: 0.094942 (0.082981) +2025-09-16,03:02:04 | INFO | Train Epoch: 13 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.071760 (0.069530) Boundary_loss: 0.013896 (0.013896) Loss: 0.085656 (0.083427) +2025-09-16,03:03:10 | INFO | Train Epoch: 13 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.078949 (0.070876) Boundary_loss: 0.013896 (0.013896) Loss: 0.092845 (0.084772) +2025-09-16,03:04:15 | INFO | Train Epoch: 13 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.050330 (0.068308) Boundary_loss: 0.013895 (0.013896) Loss: 0.064225 (0.082204) +2025-09-16,03:05:21 | INFO | Train Epoch: 13 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.049093 (0.066173) Boundary_loss: 0.013896 (0.013896) Loss: 0.062990 (0.080069) +2025-09-16,03:06:26 | INFO | Train Epoch: 13 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.068009 (0.066356) Boundary_loss: 0.013896 (0.013896) Loss: 0.081905 (0.080252) +2025-09-16,03:07:32 | INFO | Train Epoch: 13 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.048993 (0.064778) Boundary_loss: 0.013895 (0.013896) Loss: 0.062889 (0.078674) +2025-09-16,03:08:37 | INFO | Train Epoch: 13 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.071843 (0.065367) Boundary_loss: 0.013897 (0.013896) Loss: 0.085741 (0.079263) +2025-09-16,03:09:43 | INFO | Train Epoch: 13 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.079278 (0.066437) Boundary_loss: 0.013896 (0.013896) Loss: 0.093174 (0.080333) +2025-09-16,03:10:48 | INFO | Train Epoch: 13 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.072133 (0.066844) Boundary_loss: 0.013896 (0.013896) Loss: 0.086029 (0.080740) +2025-09-16,03:11:54 | INFO | Train Epoch: 13 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.067081 (0.066860) Boundary_loss: 0.013896 (0.013896) Loss: 0.080977 (0.080756) +2025-09-16,03:12:59 | INFO | Train Epoch: 13 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.069456 (0.067022) Boundary_loss: 0.013895 (0.013896) Loss: 0.083351 (0.080918) +2025-09-16,03:14:05 | INFO | Train Epoch: 13 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.054720 (0.066298) Boundary_loss: 0.013894 (0.013896) Loss: 0.068615 (0.080194) +2025-09-16,03:15:10 | INFO | Train Epoch: 13 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.093055 (0.067785) Boundary_loss: 0.013896 (0.013896) Loss: 0.10695 (0.081681) +2025-09-16,03:16:16 | INFO | Train Epoch: 13 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.074698 (0.068149) Boundary_loss: 0.013895 (0.013896) Loss: 0.088593 (0.082044) +2025-09-16,03:17:21 | INFO | Train Epoch: 13 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.094334 (0.069458) Boundary_loss: 0.013895 (0.013896) Loss: 0.10823 (0.083354) +2025-09-16,03:18:27 | INFO | Train Epoch: 13 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.062202 (0.069112) Boundary_loss: 0.013897 (0.013896) Loss: 0.076099 (0.083008) +2025-09-16,03:19:32 | INFO | Train Epoch: 13 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.047872 (0.068147) Boundary_loss: 0.013897 (0.013896) Loss: 0.061769 (0.082043) +2025-09-16,03:20:38 | INFO | Train Epoch: 13 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.092006 (0.069184) Boundary_loss: 0.013895 (0.013896) Loss: 0.10590 (0.083080) +2025-09-16,03:21:44 | INFO | Train Epoch: 13 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.085486 (0.069863) Boundary_loss: 0.013897 (0.013896) Loss: 0.099383 (0.083759) +2025-09-16,03:22:49 | INFO | Train Epoch: 13 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.055821 (0.069302) Boundary_loss: 0.013895 (0.013896) Loss: 0.069716 (0.083198) +2025-09-16,03:23:55 | INFO | Train Epoch: 13 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.049028 (0.068522) Boundary_loss: 0.013896 (0.013896) Loss: 0.062924 (0.082418) +2025-09-16,03:25:00 | INFO | Train Epoch: 13 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.061829 (0.068274) Boundary_loss: 0.013895 (0.013896) Loss: 0.075724 (0.082170) +2025-09-16,03:26:06 | INFO | Train Epoch: 13 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.064161 (0.068127) Boundary_loss: 0.013896 (0.013896) Loss: 0.078057 (0.082023) +2025-09-16,03:27:11 | INFO | Train Epoch: 13 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.069467 (0.068173) Boundary_loss: 0.013896 (0.013896) Loss: 0.083363 (0.082069) +2025-09-16,03:28:17 | INFO | Train Epoch: 13 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.090523 (0.068918) Boundary_loss: 0.013895 (0.013896) Loss: 0.10442 (0.082814) +2025-09-16,03:29:22 | INFO | Train Epoch: 13 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.058688 (0.068588) Boundary_loss: 0.013896 (0.013896) Loss: 0.072584 (0.082484) +2025-09-16,03:30:28 | INFO | Train Epoch: 13 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.061703 (0.068373) Boundary_loss: 0.013895 (0.013896) Loss: 0.075598 (0.082269) +2025-09-16,03:31:34 | INFO | Train Epoch: 13 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.077690 (0.068655) Boundary_loss: 0.013895 (0.013896) Loss: 0.091585 (0.082551) +2025-09-16,03:32:39 | INFO | Train Epoch: 13 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.088158 (0.069229) Boundary_loss: 0.013897 (0.013896) Loss: 0.10206 (0.083125) +2025-09-16,03:33:45 | INFO | Train Epoch: 13 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.078688 (0.069499) Boundary_loss: 0.013897 (0.013896) Loss: 0.092585 (0.083395) +2025-09-16,03:34:50 | INFO | Train Epoch: 13 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.088035 (0.070014) Boundary_loss: 0.013896 (0.013896) Loss: 0.10193 (0.083910) +2025-09-16,03:35:56 | INFO | Train Epoch: 13 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.032809 (0.069009) Boundary_loss: 0.013896 (0.013896) Loss: 0.046705 (0.082905) +2025-09-16,03:37:02 | INFO | Train Epoch: 13 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.065857 (0.068926) Boundary_loss: 0.013896 (0.013896) Loss: 0.079753 (0.082822) +2025-09-16,03:38:07 | INFO | Train Epoch: 13 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.094046 (0.069570) Boundary_loss: 0.013896 (0.013896) Loss: 0.10794 (0.083466) +2025-09-16,03:39:13 | INFO | Train Epoch: 13 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.054015 (0.069181) Boundary_loss: 0.013895 (0.013896) Loss: 0.067911 (0.083077) +2025-09-16,03:40:18 | INFO | Train Epoch: 13 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10401 (0.070030) Boundary_loss: 0.013896 (0.013896) Loss: 0.11790 (0.083926) +2025-09-16,03:41:24 | INFO | Train Epoch: 13 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.080365 (0.070276) Boundary_loss: 0.013895 (0.013896) Loss: 0.094260 (0.084172) +2025-09-16,03:42:30 | INFO | Train Epoch: 13 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.047359 (0.069744) Boundary_loss: 0.013895 (0.013896) Loss: 0.061255 (0.083639) +2025-09-16,03:43:35 | INFO | Train Epoch: 13 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.091555 (0.070239) Boundary_loss: 0.013896 (0.013896) Loss: 0.10545 (0.084135) +2025-09-16,03:44:41 | INFO | Train Epoch: 13 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.096502 (0.070823) Boundary_loss: 0.013895 (0.013896) Loss: 0.11040 (0.084719) +2025-09-16,03:45:47 | INFO | Train Epoch: 13 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10369 (0.071537) Boundary_loss: 0.013896 (0.013896) Loss: 0.11758 (0.085433) +2025-09-16,03:46:52 | INFO | Train Epoch: 13 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.062961 (0.071355) Boundary_loss: 0.013895 (0.013896) Loss: 0.076856 (0.085251) +2025-09-16,03:47:58 | INFO | Train Epoch: 13 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.059988 (0.071118) Boundary_loss: 0.013896 (0.013896) Loss: 0.073883 (0.085014) +2025-09-16,03:49:03 | INFO | Train Epoch: 13 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.043776 (0.070560) Boundary_loss: 0.013897 (0.013896) Loss: 0.057673 (0.084456) +2025-09-16,03:50:09 | INFO | Train Epoch: 13 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.055973 (0.070268) Boundary_loss: 0.013896 (0.013896) Loss: 0.069869 (0.084164) +2025-09-16,03:51:15 | INFO | Train Epoch: 13 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.056273 (0.069994) Boundary_loss: 0.013895 (0.013896) Loss: 0.070168 (0.083890) +2025-09-16,03:52:20 | INFO | Train Epoch: 13 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.049322 (0.069596) Boundary_loss: 0.013897 (0.013896) Loss: 0.063219 (0.083492) +2025-09-16,03:53:26 | INFO | Train Epoch: 13 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.053655 (0.069296) Boundary_loss: 0.013898 (0.013896) Loss: 0.067553 (0.083191) +2025-09-16,03:54:32 | INFO | Train Epoch: 13 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.067950 (0.069271) Boundary_loss: 0.013896 (0.013896) Loss: 0.081845 (0.083166) +2025-09-16,03:55:37 | INFO | Train Epoch: 13 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.059949 (0.069101) Boundary_loss: 0.013895 (0.013896) Loss: 0.073844 (0.082997) +2025-09-16,03:56:43 | INFO | Train Epoch: 13 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.080860 (0.069311) Boundary_loss: 0.013895 (0.013896) Loss: 0.094754 (0.083207) +2025-09-16,03:57:48 | INFO | Train Epoch: 13 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.063226 (0.069204) Boundary_loss: 0.013896 (0.013896) Loss: 0.077122 (0.083100) +2025-09-16,03:58:54 | INFO | Train Epoch: 13 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.060025 (0.069046) Boundary_loss: 0.013897 (0.013896) Loss: 0.073922 (0.082942) +2025-09-16,04:00:00 | INFO | Train Epoch: 13 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.064852 (0.068975) Boundary_loss: 0.013895 (0.013896) Loss: 0.078746 (0.082871) +2025-09-16,04:01:05 | INFO | Train Epoch: 13 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.061538 (0.068851) Boundary_loss: 0.013896 (0.013896) Loss: 0.075434 (0.082747) +2025-09-16,04:02:11 | INFO | Train Epoch: 13 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.083260 (0.069087) Boundary_loss: 0.013896 (0.013896) Loss: 0.097156 (0.082983) +2025-09-16,04:03:17 | INFO | Train Epoch: 13 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.044039 (0.068683) Boundary_loss: 0.013895 (0.013896) Loss: 0.057934 (0.082579) +2025-09-16,04:04:22 | INFO | Train Epoch: 13 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.046486 (0.068331) Boundary_loss: 0.013897 (0.013896) Loss: 0.060383 (0.082227) +2025-09-16,04:05:28 | INFO | Train Epoch: 13 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.064388 (0.068269) Boundary_loss: 0.013896 (0.013896) Loss: 0.078284 (0.082165) +2025-09-16,04:06:34 | INFO | Train Epoch: 13 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.067715 (0.068261) Boundary_loss: 0.013896 (0.013896) Loss: 0.081611 (0.082157) +2025-09-16,04:07:39 | INFO | Train Epoch: 13 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.065201 (0.068214) Boundary_loss: 0.013897 (0.013896) Loss: 0.079098 (0.082110) +2025-09-16,04:08:45 | INFO | Train Epoch: 13 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.083979 (0.068450) Boundary_loss: 0.013897 (0.013896) Loss: 0.097876 (0.082346) +2025-09-16,04:09:51 | INFO | Train Epoch: 13 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.070881 (0.068485) Boundary_loss: 0.013897 (0.013896) Loss: 0.084778 (0.082381) +2025-09-16,04:10:56 | INFO | Train Epoch: 13 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.045659 (0.068155) Boundary_loss: 0.013897 (0.013896) Loss: 0.059556 (0.082051) +2025-09-16,04:12:02 | INFO | Train Epoch: 13 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.066245 (0.068127) Boundary_loss: 0.013896 (0.013896) Loss: 0.080141 (0.082023) +2025-09-16,04:13:08 | INFO | Train Epoch: 13 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.054807 (0.067940) Boundary_loss: 0.013896 (0.013896) Loss: 0.068702 (0.081836) +2025-09-16,04:14:13 | INFO | Train Epoch: 13 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.081124 (0.068123) Boundary_loss: 0.013895 (0.013896) Loss: 0.095019 (0.082019) +2025-09-16,04:15:19 | INFO | Train Epoch: 13 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.089417 (0.068415) Boundary_loss: 0.013897 (0.013896) Loss: 0.10331 (0.082310) +2025-09-16,04:16:25 | INFO | Train Epoch: 13 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.052753 (0.068203) Boundary_loss: 0.013895 (0.013896) Loss: 0.066648 (0.082099) +2025-09-16,04:17:30 | INFO | Train Epoch: 13 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.073154 (0.068269) Boundary_loss: 0.013896 (0.013896) Loss: 0.087051 (0.082165) +2025-09-16,04:18:36 | INFO | Train Epoch: 13 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10863 (0.068800) Boundary_loss: 0.013894 (0.013896) Loss: 0.12253 (0.082696) +2025-09-16,04:19:42 | INFO | Train Epoch: 13 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.058272 (0.068663) Boundary_loss: 0.013898 (0.013896) Loss: 0.072171 (0.082559) +2025-09-16,04:20:48 | INFO | Train Epoch: 13 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.058204 (0.068529) Boundary_loss: 0.013896 (0.013896) Loss: 0.072100 (0.082425) +2025-09-16,04:21:53 | INFO | Train Epoch: 13 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.081467 (0.068693) Boundary_loss: 0.013896 (0.013896) Loss: 0.095363 (0.082589) +2025-09-16,04:22:59 | INFO | Train Epoch: 13 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.067338 (0.068676) Boundary_loss: 0.013896 (0.013896) Loss: 0.081234 (0.082572) +2025-09-16,04:24:05 | INFO | Train Epoch: 13 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.086741 (0.068899) Boundary_loss: 0.013896 (0.013896) Loss: 0.10064 (0.082795) +2025-09-16,04:25:10 | INFO | Train Epoch: 13 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10007 (0.069279) Boundary_loss: 0.013896 (0.013896) Loss: 0.11397 (0.083175) +2025-09-16,04:26:16 | INFO | Train Epoch: 13 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.054038 (0.069096) Boundary_loss: 0.013897 (0.013896) Loss: 0.067935 (0.082991) +2025-09-16,04:27:22 | INFO | Train Epoch: 13 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.057997 (0.068963) Boundary_loss: 0.013894 (0.013896) Loss: 0.071891 (0.082859) +2025-09-16,04:28:28 | INFO | Train Epoch: 13 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.073781 (0.069020) Boundary_loss: 0.013896 (0.013896) Loss: 0.087678 (0.082916) +2025-09-16,04:29:33 | INFO | Train Epoch: 13 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10997 (0.069496) Boundary_loss: 0.013897 (0.013896) Loss: 0.12387 (0.083392) +2025-09-16,04:30:39 | INFO | Train Epoch: 13 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.063835 (0.069431) Boundary_loss: 0.013895 (0.013896) Loss: 0.077730 (0.083327) +2025-09-16,04:31:45 | INFO | Train Epoch: 13 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.065297 (0.069384) Boundary_loss: 0.013896 (0.013896) Loss: 0.079194 (0.083280) +2025-09-16,04:32:51 | INFO | Train Epoch: 13 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.061143 (0.069292) Boundary_loss: 0.013896 (0.013896) Loss: 0.075039 (0.083188) +2025-09-16,04:33:56 | INFO | Train Epoch: 13 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.091152 (0.069535) Boundary_loss: 0.013897 (0.013896) Loss: 0.10505 (0.083430) +2025-09-16,04:35:02 | INFO | Train Epoch: 13 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.050911 (0.069330) Boundary_loss: 0.013897 (0.013896) Loss: 0.064808 (0.083226) +2025-09-16,04:36:08 | INFO | Train Epoch: 13 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.051624 (0.069137) Boundary_loss: 0.013896 (0.013896) Loss: 0.065520 (0.083033) +2025-09-16,04:37:14 | INFO | Train Epoch: 13 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.067989 (0.069125) Boundary_loss: 0.013897 (0.013896) Loss: 0.081886 (0.083021) +2025-09-16,04:38:19 | INFO | Train Epoch: 13 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.073015 (0.069166) Boundary_loss: 0.013897 (0.013896) Loss: 0.086912 (0.083062) +2025-09-16,04:39:25 | INFO | Train Epoch: 13 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.076642 (0.069245) Boundary_loss: 0.013896 (0.013896) Loss: 0.090539 (0.083141) +2025-09-16,04:40:31 | INFO | Train Epoch: 13 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.064662 (0.069197) Boundary_loss: 0.013897 (0.013896) Loss: 0.078559 (0.083093) +2025-09-16,04:41:37 | INFO | Train Epoch: 13 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.053909 (0.069040) Boundary_loss: 0.013895 (0.013896) Loss: 0.067804 (0.082936) +2025-09-16,04:42:42 | INFO | Train Epoch: 13 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.11170 (0.069475) Boundary_loss: 0.013896 (0.013896) Loss: 0.12559 (0.083371) +2025-09-16,04:43:48 | INFO | Train Epoch: 13 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.081309 (0.069595) Boundary_loss: 0.013895 (0.013896) Loss: 0.095204 (0.083491) +2025-09-16,04:44:54 | INFO | Train Epoch: 13 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.046915 (0.069368) Boundary_loss: 0.013896 (0.013896) Loss: 0.060812 (0.083264) +2025-09-16,04:46:00 | INFO | Train Epoch: 13 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.067421 (0.069349) Boundary_loss: 0.013895 (0.013896) Loss: 0.081315 (0.083244) +2025-09-16,04:47:05 | INFO | Train Epoch: 13 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.057844 (0.069236) Boundary_loss: 0.013896 (0.013896) Loss: 0.071740 (0.083132) +2025-09-16,04:48:11 | INFO | Train Epoch: 13 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.050976 (0.069058) Boundary_loss: 0.013895 (0.013896) Loss: 0.064871 (0.082954) +2025-09-16,04:49:17 | INFO | Train Epoch: 13 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.054614 (0.068920) Boundary_loss: 0.013896 (0.013896) Loss: 0.068509 (0.082815) +2025-09-16,04:50:23 | INFO | Train Epoch: 13 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.064689 (0.068879) Boundary_loss: 0.013897 (0.013896) Loss: 0.078586 (0.082775) +2025-09-16,04:51:28 | INFO | Train Epoch: 13 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.077135 (0.068957) Boundary_loss: 0.013896 (0.013896) Loss: 0.091031 (0.082853) +2025-09-16,04:52:34 | INFO | Train Epoch: 13 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.064142 (0.068912) Boundary_loss: 0.013896 (0.013896) Loss: 0.078038 (0.082808) +2025-09-16,04:53:40 | INFO | Train Epoch: 13 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.049794 (0.068735) Boundary_loss: 0.013897 (0.013896) Loss: 0.063691 (0.082631) +2025-09-16,04:54:45 | INFO | Train Epoch: 13 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10320 (0.069051) Boundary_loss: 0.013895 (0.013896) Loss: 0.11710 (0.082947) +2025-09-16,04:55:51 | INFO | Train Epoch: 13 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.070988 (0.069069) Boundary_loss: 0.013896 (0.013896) Loss: 0.084884 (0.082965) +2025-09-16,04:56:57 | INFO | Train Epoch: 13 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.080901 (0.069176) Boundary_loss: 0.013895 (0.013896) Loss: 0.094797 (0.083071) +2025-09-16,04:58:03 | INFO | Train Epoch: 13 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.068942 (0.069173) Boundary_loss: 0.013896 (0.013896) Loss: 0.082838 (0.083069) +2025-09-16,04:59:09 | INFO | Train Epoch: 13 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.072038 (0.069199) Boundary_loss: 0.013896 (0.013896) Loss: 0.085934 (0.083095) +2025-09-16,05:00:14 | INFO | Train Epoch: 13 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.075075 (0.069250) Boundary_loss: 0.013896 (0.013896) Loss: 0.088971 (0.083146) +2025-09-16,05:01:20 | INFO | Train Epoch: 13 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.055777 (0.069133) Boundary_loss: 0.013897 (0.013896) Loss: 0.069674 (0.083029) +2025-09-16,05:02:26 | INFO | Train Epoch: 13 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.087326 (0.069290) Boundary_loss: 0.013895 (0.013896) Loss: 0.10122 (0.083186) +2025-09-16,05:03:32 | INFO | Train Epoch: 13 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.062131 (0.069229) Boundary_loss: 0.013894 (0.013896) Loss: 0.076025 (0.083125) +2025-09-16,05:04:37 | INFO | Train Epoch: 13 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.076925 (0.069294) Boundary_loss: 0.013896 (0.013896) Loss: 0.090821 (0.083190) +2025-09-16,05:05:43 | INFO | Train Epoch: 13 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.069860 (0.069299) Boundary_loss: 0.013897 (0.013896) Loss: 0.083758 (0.083195) +2025-09-16,05:06:49 | INFO | Train Epoch: 13 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.088171 (0.069456) Boundary_loss: 0.013895 (0.013896) Loss: 0.10207 (0.083352) +2025-09-16,05:07:55 | INFO | Train Epoch: 13 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.060118 (0.069379) Boundary_loss: 0.013896 (0.013896) Loss: 0.074015 (0.083275) +2025-09-16,05:09:00 | INFO | Train Epoch: 13 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.064642 (0.069340) Boundary_loss: 0.013895 (0.013896) Loss: 0.078537 (0.083236) +2025-09-16,05:10:06 | INFO | Train Epoch: 13 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.090669 (0.069513) Boundary_loss: 0.013897 (0.013896) Loss: 0.10457 (0.083409) +2025-09-16,05:11:12 | INFO | Train Epoch: 13 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.066415 (0.069488) Boundary_loss: 0.013896 (0.013896) Loss: 0.080311 (0.083384) +2025-09-16,05:12:18 | INFO | Train Epoch: 13 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.067021 (0.069469) Boundary_loss: 0.013896 (0.013896) Loss: 0.080917 (0.083365) +2025-09-16,05:13:23 | INFO | Train Epoch: 13 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.075275 (0.069515) Boundary_loss: 0.013896 (0.013896) Loss: 0.089171 (0.083411) +2025-09-16,05:14:29 | INFO | Train Epoch: 13 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.097123 (0.069732) Boundary_loss: 0.013895 (0.013896) Loss: 0.11102 (0.083628) +2025-09-16,05:15:35 | INFO | Train Epoch: 13 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.072206 (0.069752) Boundary_loss: 0.013895 (0.013896) Loss: 0.086100 (0.083647) +2025-09-16,05:16:41 | INFO | Train Epoch: 13 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.076773 (0.069806) Boundary_loss: 0.013896 (0.013896) Loss: 0.090670 (0.083702) +2025-09-16,05:17:47 | INFO | Train Epoch: 13 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.063439 (0.069757) Boundary_loss: 0.013895 (0.013896) Loss: 0.077334 (0.083653) +2025-09-16,05:18:52 | INFO | Train Epoch: 13 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.063926 (0.069712) Boundary_loss: 0.013896 (0.013896) Loss: 0.077822 (0.083608) +2025-09-16,05:19:58 | INFO | Train Epoch: 13 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.057754 (0.069622) Boundary_loss: 0.013896 (0.013896) Loss: 0.071650 (0.083518) +2025-09-16,05:21:04 | INFO | Train Epoch: 13 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.079959 (0.069700) Boundary_loss: 0.013895 (0.013896) Loss: 0.093854 (0.083596) +2025-09-16,05:22:10 | INFO | Train Epoch: 13 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.091040 (0.069859) Boundary_loss: 0.013895 (0.013896) Loss: 0.10494 (0.083755) +2025-09-16,05:23:15 | INFO | Train Epoch: 13 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.057494 (0.069767) Boundary_loss: 0.013896 (0.013896) Loss: 0.071391 (0.083663) +2025-09-16,05:24:21 | INFO | Train Epoch: 13 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.047771 (0.069606) Boundary_loss: 0.013896 (0.013896) Loss: 0.061667 (0.083501) +2025-09-16,05:25:27 | INFO | Train Epoch: 13 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.068367 (0.069597) Boundary_loss: 0.013897 (0.013896) Loss: 0.082264 (0.083492) +2025-09-16,05:26:33 | INFO | Train Epoch: 13 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.060138 (0.069528) Boundary_loss: 0.013897 (0.013896) Loss: 0.074035 (0.083424) +2025-09-16,05:27:38 | INFO | Train Epoch: 13 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.067845 (0.069516) Boundary_loss: 0.013895 (0.013896) Loss: 0.081740 (0.083412) +2025-09-16,05:28:44 | INFO | Train Epoch: 13 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.067586 (0.069502) Boundary_loss: 0.013895 (0.013896) Loss: 0.081480 (0.083398) +2025-09-16,05:29:50 | INFO | Train Epoch: 13 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.047002 (0.069343) Boundary_loss: 0.013896 (0.013896) Loss: 0.060898 (0.083238) +2025-09-16,05:30:56 | INFO | Train Epoch: 13 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.056769 (0.069254) Boundary_loss: 0.013896 (0.013896) Loss: 0.070666 (0.083150) +2025-09-16,05:32:01 | INFO | Train Epoch: 13 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.071950 (0.069273) Boundary_loss: 0.013896 (0.013896) Loss: 0.085846 (0.083169) +2025-09-16,05:33:07 | INFO | Train Epoch: 13 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.074625 (0.069310) Boundary_loss: 0.013896 (0.013896) Loss: 0.088521 (0.083206) +2025-09-16,05:34:13 | INFO | Train Epoch: 13 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.072116 (0.069329) Boundary_loss: 0.013896 (0.013896) Loss: 0.086011 (0.083225) +2025-09-16,05:35:19 | INFO | Train Epoch: 13 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.072867 (0.069354) Boundary_loss: 0.013895 (0.013896) Loss: 0.086762 (0.083249) +2025-09-16,05:36:24 | INFO | Train Epoch: 13 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.062847 (0.069309) Boundary_loss: 0.013895 (0.013896) Loss: 0.076742 (0.083205) +2025-09-16,05:37:30 | INFO | Train Epoch: 13 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.059074 (0.069240) Boundary_loss: 0.013897 (0.013896) Loss: 0.072971 (0.083136) +2025-09-16,05:38:36 | INFO | Train Epoch: 13 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.045882 (0.069083) Boundary_loss: 0.013897 (0.013896) Loss: 0.059779 (0.082979) +2025-09-16,05:39:42 | INFO | Train Epoch: 13 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.083774 (0.069181) Boundary_loss: 0.013896 (0.013896) Loss: 0.097670 (0.083077) +2025-09-16,05:40:47 | INFO | Train Epoch: 13 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.058844 (0.069113) Boundary_loss: 0.013895 (0.013896) Loss: 0.072739 (0.083009) +2025-09-16,05:41:53 | INFO | Train Epoch: 13 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.099457 (0.069312) Boundary_loss: 0.013896 (0.013896) Loss: 0.11335 (0.083208) +2025-09-16,05:42:59 | INFO | Train Epoch: 13 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.087803 (0.069433) Boundary_loss: 0.013896 (0.013896) Loss: 0.10170 (0.083329) +2025-09-16,05:44:05 | INFO | Train Epoch: 13 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.093003 (0.069586) Boundary_loss: 0.013897 (0.013896) Loss: 0.10690 (0.083482) +2025-09-16,05:45:10 | INFO | Train Epoch: 13 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.060764 (0.069529) Boundary_loss: 0.013895 (0.013896) Loss: 0.074658 (0.083425) +2025-09-16,05:46:16 | INFO | Train Epoch: 13 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.094425 (0.069689) Boundary_loss: 0.013896 (0.013896) Loss: 0.10832 (0.083585) +2025-09-16,05:47:22 | INFO | Train Epoch: 13 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.084499 (0.069783) Boundary_loss: 0.013896 (0.013896) Loss: 0.098394 (0.083679) +2025-09-16,05:48:28 | INFO | Train Epoch: 13 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.046078 (0.069633) Boundary_loss: 0.013895 (0.013896) Loss: 0.059973 (0.083529) +2025-09-16,05:49:33 | INFO | Train Epoch: 13 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.059717 (0.069571) Boundary_loss: 0.013896 (0.013896) Loss: 0.073613 (0.083467) +2025-09-16,05:50:39 | INFO | Train Epoch: 13 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.083001 (0.069655) Boundary_loss: 0.013895 (0.013896) Loss: 0.096897 (0.083551) +2025-09-16,05:51:45 | INFO | Train Epoch: 13 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.078500 (0.069710) Boundary_loss: 0.013895 (0.013896) Loss: 0.092395 (0.083606) +2025-09-16,05:52:51 | INFO | Train Epoch: 13 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10311 (0.069916) Boundary_loss: 0.013895 (0.013896) Loss: 0.11701 (0.083812) +2025-09-16,05:53:56 | INFO | Train Epoch: 13 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.054331 (0.069820) Boundary_loss: 0.013896 (0.013896) Loss: 0.068227 (0.083716) +2025-09-16,05:55:02 | INFO | Train Epoch: 13 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.048525 (0.069691) Boundary_loss: 0.013897 (0.013896) Loss: 0.062421 (0.083586) +2025-09-16,05:56:08 | INFO | Train Epoch: 13 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.067399 (0.069677) Boundary_loss: 0.013896 (0.013896) Loss: 0.081294 (0.083573) +2025-09-16,05:57:14 | INFO | Train Epoch: 13 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.051398 (0.069567) Boundary_loss: 0.013895 (0.013896) Loss: 0.065293 (0.083462) +2025-09-16,05:58:19 | INFO | Train Epoch: 13 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.053879 (0.069473) Boundary_loss: 0.013895 (0.013896) Loss: 0.067774 (0.083369) +2025-09-16,05:59:25 | INFO | Train Epoch: 13 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.060514 (0.069419) Boundary_loss: 0.013897 (0.013896) Loss: 0.074411 (0.083315) +2025-09-16,06:00:31 | INFO | Train Epoch: 13 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.054154 (0.069329) Boundary_loss: 0.013897 (0.013896) Loss: 0.068050 (0.083225) +2025-09-16,06:01:37 | INFO | Train Epoch: 13 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.074391 (0.069359) Boundary_loss: 0.013896 (0.013896) Loss: 0.088287 (0.083255) +2025-09-16,06:02:42 | INFO | Train Epoch: 13 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.060167 (0.069305) Boundary_loss: 0.013897 (0.013896) Loss: 0.074064 (0.083201) +2025-09-16,06:03:48 | INFO | Train Epoch: 13 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.038945 (0.069128) Boundary_loss: 0.013896 (0.013896) Loss: 0.052841 (0.083024) +2025-09-16,06:04:54 | INFO | Train Epoch: 13 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.041455 (0.068969) Boundary_loss: 0.013896 (0.013896) Loss: 0.055352 (0.082864) +2025-09-16,06:06:00 | INFO | Train Epoch: 13 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.079051 (0.069026) Boundary_loss: 0.013895 (0.013896) Loss: 0.092946 (0.082922) +2025-09-16,06:07:06 | INFO | Train Epoch: 13 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.070287 (0.069034) Boundary_loss: 0.013895 (0.013896) Loss: 0.084182 (0.082930) +2025-09-16,06:08:11 | INFO | Train Epoch: 13 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.067412 (0.069024) Boundary_loss: 0.013897 (0.013896) Loss: 0.081310 (0.082920) +2025-09-16,06:09:17 | INFO | Train Epoch: 13 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.068243 (0.069020) Boundary_loss: 0.013895 (0.013896) Loss: 0.082138 (0.082916) +2025-09-16,06:10:23 | INFO | Train Epoch: 13 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.059992 (0.068969) Boundary_loss: 0.013896 (0.013896) Loss: 0.073888 (0.082865) +2025-09-16,06:11:29 | INFO | Train Epoch: 13 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.070737 (0.068979) Boundary_loss: 0.013895 (0.013896) Loss: 0.084632 (0.082875) +2025-09-16,06:12:34 | INFO | Train Epoch: 13 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.083186 (0.069058) Boundary_loss: 0.013894 (0.013896) Loss: 0.097080 (0.082954) +2025-09-16,06:13:40 | INFO | Train Epoch: 13 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.084718 (0.069145) Boundary_loss: 0.013896 (0.013896) Loss: 0.098614 (0.083041) +2025-09-16,06:14:46 | INFO | Train Epoch: 13 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10721 (0.069354) Boundary_loss: 0.013895 (0.013896) Loss: 0.12111 (0.083250) +2025-09-16,06:15:52 | INFO | Train Epoch: 13 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.074130 (0.069380) Boundary_loss: 0.013894 (0.013896) Loss: 0.088024 (0.083276) +2025-09-16,06:16:57 | INFO | Train Epoch: 13 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.065625 (0.069359) Boundary_loss: 0.013896 (0.013896) Loss: 0.079521 (0.083255) +2025-09-16,06:18:03 | INFO | Train Epoch: 13 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.073048 (0.069379) Boundary_loss: 0.013896 (0.013896) Loss: 0.086944 (0.083275) +2025-09-16,06:19:09 | INFO | Train Epoch: 13 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.079328 (0.069433) Boundary_loss: 0.013895 (0.013896) Loss: 0.093223 (0.083329) +2025-09-16,06:20:15 | INFO | Train Epoch: 13 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.074324 (0.069459) Boundary_loss: 0.013895 (0.013896) Loss: 0.088219 (0.083355) +2025-09-16,06:21:20 | INFO | Train Epoch: 13 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.067718 (0.069450) Boundary_loss: 0.013895 (0.013896) Loss: 0.081613 (0.083346) +2025-09-16,06:22:26 | INFO | Train Epoch: 13 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.052278 (0.069359) Boundary_loss: 0.013895 (0.013896) Loss: 0.066173 (0.083255) +2025-09-16,06:23:32 | INFO | Train Epoch: 13 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.080259 (0.069416) Boundary_loss: 0.013895 (0.013896) Loss: 0.094154 (0.083312) +2025-09-16,06:24:38 | INFO | Train Epoch: 13 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.052153 (0.069326) Boundary_loss: 0.013896 (0.013896) Loss: 0.066049 (0.083222) +2025-09-16,06:25:43 | INFO | Train Epoch: 13 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.033913 (0.069142) Boundary_loss: 0.013895 (0.013896) Loss: 0.047807 (0.083037) +2025-09-16,06:26:49 | INFO | Train Epoch: 13 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.070888 (0.069151) Boundary_loss: 0.013895 (0.013896) Loss: 0.084782 (0.083046) +2025-09-16,06:27:55 | INFO | Train Epoch: 13 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.045911 (0.069031) Boundary_loss: 0.013895 (0.013896) Loss: 0.059806 (0.082927) +2025-09-16,06:29:01 | INFO | Train Epoch: 13 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.058640 (0.068977) Boundary_loss: 0.013895 (0.013896) Loss: 0.072536 (0.082873) +2025-09-16,06:30:06 | INFO | Train Epoch: 13 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.071061 (0.068988) Boundary_loss: 0.013896 (0.013896) Loss: 0.084957 (0.082884) +2025-09-16,06:31:12 | INFO | Train Epoch: 13 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.050050 (0.068892) Boundary_loss: 0.013896 (0.013896) Loss: 0.063945 (0.082788) +2025-09-16,06:32:18 | INFO | Train Epoch: 13 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.061802 (0.068856) Boundary_loss: 0.013896 (0.013896) Loss: 0.075698 (0.082752) +2025-09-16,06:33:24 | INFO | Train Epoch: 13 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.081792 (0.068921) Boundary_loss: 0.013896 (0.013896) Loss: 0.095689 (0.082817) +2025-09-16,06:34:29 | INFO | Train Epoch: 13 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.073917 (0.068946) Boundary_loss: 0.013895 (0.013896) Loss: 0.087812 (0.082842) +2025-09-16,06:35:35 | INFO | Train Epoch: 13 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.076114 (0.068982) Boundary_loss: 0.013897 (0.013896) Loss: 0.090011 (0.082878) +2025-09-16,06:36:41 | INFO | Train Epoch: 13 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.071675 (0.068995) Boundary_loss: 0.013895 (0.013896) Loss: 0.085571 (0.082891) +2025-09-16,06:37:47 | INFO | Train Epoch: 13 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.078581 (0.069042) Boundary_loss: 0.013895 (0.013896) Loss: 0.092476 (0.082938) +2025-09-16,06:38:53 | INFO | Train Epoch: 13 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.045012 (0.068925) Boundary_loss: 0.013895 (0.013896) Loss: 0.058907 (0.082820) +2025-09-16,06:39:58 | INFO | Train Epoch: 13 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.069029 (0.068925) Boundary_loss: 0.013897 (0.013896) Loss: 0.082925 (0.082821) +2025-09-16,06:41:04 | INFO | Train Epoch: 13 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.079018 (0.068974) Boundary_loss: 0.013897 (0.013896) Loss: 0.092916 (0.082870) +2025-09-16,06:42:10 | INFO | Train Epoch: 13 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.063063 (0.068946) Boundary_loss: 0.013896 (0.013896) Loss: 0.076959 (0.082841) +2025-09-16,06:43:16 | INFO | Train Epoch: 13 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.076244 (0.068981) Boundary_loss: 0.013896 (0.013896) Loss: 0.090140 (0.082876) +2025-09-16,06:44:21 | INFO | Train Epoch: 13 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.074434 (0.069007) Boundary_loss: 0.013896 (0.013896) Loss: 0.088331 (0.082903) +2025-09-16,06:45:27 | INFO | Train Epoch: 13 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.083998 (0.069078) Boundary_loss: 0.013894 (0.013896) Loss: 0.097892 (0.082974) +2025-09-16,06:46:33 | INFO | Train Epoch: 13 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.089440 (0.069175) Boundary_loss: 0.013894 (0.013896) Loss: 0.10333 (0.083070) +2025-09-16,06:47:39 | INFO | Train Epoch: 13 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.051031 (0.069089) Boundary_loss: 0.013896 (0.013896) Loss: 0.064927 (0.082985) +2025-09-16,06:48:45 | INFO | Train Epoch: 13 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.053499 (0.069016) Boundary_loss: 0.013896 (0.013896) Loss: 0.067396 (0.082912) +2025-09-16,06:49:50 | INFO | Train Epoch: 13 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.087465 (0.069102) Boundary_loss: 0.013896 (0.013896) Loss: 0.10136 (0.082998) +2025-09-16,06:50:56 | INFO | Train Epoch: 13 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.065153 (0.069084) Boundary_loss: 0.013895 (0.013896) Loss: 0.079048 (0.082979) +2025-09-16,06:52:02 | INFO | Train Epoch: 13 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.082246 (0.069145) Boundary_loss: 0.013896 (0.013896) Loss: 0.096143 (0.083040) +2025-09-16,06:53:08 | INFO | Train Epoch: 13 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.063938 (0.069121) Boundary_loss: 0.013894 (0.013896) Loss: 0.077833 (0.083016) +2025-09-16,06:54:13 | INFO | Train Epoch: 13 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.026374 (0.068925) Boundary_loss: 0.013896 (0.013896) Loss: 0.040269 (0.082820) +2025-09-16,06:55:19 | INFO | Train Epoch: 13 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.069740 (0.068928) Boundary_loss: 0.013896 (0.013896) Loss: 0.083635 (0.082824) +2025-09-16,06:56:25 | INFO | Train Epoch: 13 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.083421 (0.068994) Boundary_loss: 0.013896 (0.013896) Loss: 0.097317 (0.082890) +2025-09-16,06:57:31 | INFO | Train Epoch: 13 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.071467 (0.069005) Boundary_loss: 0.013896 (0.013896) Loss: 0.085364 (0.082901) +2025-09-16,06:58:37 | INFO | Train Epoch: 13 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.061729 (0.068973) Boundary_loss: 0.013897 (0.013896) Loss: 0.075625 (0.082868) +2025-09-16,06:59:42 | INFO | Train Epoch: 13 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.063818 (0.068949) Boundary_loss: 0.013895 (0.013896) Loss: 0.077714 (0.082845) +2025-09-16,07:00:48 | INFO | Train Epoch: 13 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.072314 (0.068964) Boundary_loss: 0.013895 (0.013896) Loss: 0.086210 (0.082860) +2025-09-16,07:01:54 | INFO | Train Epoch: 13 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.078602 (0.069007) Boundary_loss: 0.013896 (0.013896) Loss: 0.092497 (0.082903) +2025-09-16,07:03:00 | INFO | Train Epoch: 13 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10313 (0.069158) Boundary_loss: 0.013896 (0.013896) Loss: 0.11703 (0.083054) +2025-09-16,07:04:05 | INFO | Train Epoch: 13 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.069651 (0.069160) Boundary_loss: 0.013895 (0.013896) Loss: 0.083546 (0.083056) +2025-09-16,07:05:11 | INFO | Train Epoch: 13 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.068398 (0.069157) Boundary_loss: 0.013895 (0.013896) Loss: 0.082293 (0.083053) +2025-09-16,07:06:17 | INFO | Train Epoch: 13 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.052297 (0.069083) Boundary_loss: 0.013896 (0.013896) Loss: 0.066192 (0.082979) +2025-09-16,07:07:23 | INFO | Train Epoch: 13 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.063998 (0.069061) Boundary_loss: 0.013895 (0.013896) Loss: 0.077893 (0.082957) +2025-09-16,07:08:29 | INFO | Train Epoch: 13 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.034025 (0.068910) Boundary_loss: 0.013894 (0.013896) Loss: 0.047919 (0.082806) +2025-09-16,07:09:34 | INFO | Train Epoch: 13 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.060529 (0.068874) Boundary_loss: 0.013895 (0.013896) Loss: 0.074423 (0.082769) +2025-09-16,07:10:40 | INFO | Train Epoch: 13 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.086094 (0.068947) Boundary_loss: 0.013897 (0.013896) Loss: 0.099991 (0.082843) +2025-09-16,07:11:46 | INFO | Train Epoch: 13 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.058640 (0.068903) Boundary_loss: 0.013895 (0.013896) Loss: 0.072535 (0.082799) +2025-09-16,07:12:52 | INFO | Train Epoch: 13 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.059030 (0.068861) Boundary_loss: 0.013896 (0.013896) Loss: 0.072926 (0.082757) +2025-09-16,07:13:58 | INFO | Train Epoch: 13 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.063372 (0.068838) Boundary_loss: 0.013895 (0.013896) Loss: 0.077267 (0.082734) +2025-09-16,07:15:04 | INFO | Train Epoch: 13 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.065698 (0.068825) Boundary_loss: 0.013894 (0.013896) Loss: 0.079592 (0.082721) +2025-09-16,07:16:09 | INFO | Train Epoch: 13 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.069698 (0.068829) Boundary_loss: 0.013895 (0.013896) Loss: 0.083593 (0.082724) +2025-09-16,07:17:15 | INFO | Train Epoch: 13 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.066923 (0.068821) Boundary_loss: 0.013896 (0.013896) Loss: 0.080818 (0.082716) +2025-09-16,07:18:21 | INFO | Train Epoch: 13 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.088513 (0.068903) Boundary_loss: 0.013895 (0.013896) Loss: 0.10241 (0.082798) +2025-09-16,07:19:27 | INFO | Train Epoch: 13 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.061658 (0.068873) Boundary_loss: 0.013896 (0.013896) Loss: 0.075554 (0.082768) +2025-09-16,07:20:33 | INFO | Train Epoch: 13 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.078677 (0.068913) Boundary_loss: 0.013896 (0.013896) Loss: 0.092573 (0.082809) +2025-09-16,07:21:38 | INFO | Train Epoch: 13 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.078220 (0.068951) Boundary_loss: 0.013896 (0.013896) Loss: 0.092116 (0.082847) +2025-09-16,07:22:44 | INFO | Train Epoch: 13 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.054519 (0.068892) Boundary_loss: 0.013896 (0.013896) Loss: 0.068414 (0.082788) +2025-09-16,07:23:50 | INFO | Train Epoch: 13 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.068266 (0.068890) Boundary_loss: 0.013897 (0.013896) Loss: 0.082162 (0.082786) +2025-09-16,07:24:56 | INFO | Train Epoch: 13 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.076888 (0.068922) Boundary_loss: 0.013895 (0.013896) Loss: 0.090783 (0.082818) +2025-09-16,07:26:02 | INFO | Train Epoch: 13 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.085011 (0.068987) Boundary_loss: 0.013895 (0.013896) Loss: 0.098907 (0.082883) +2025-09-16,07:27:07 | INFO | Train Epoch: 13 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.068099 (0.068984) Boundary_loss: 0.013896 (0.013896) Loss: 0.081996 (0.082880) +2025-09-16,07:28:13 | INFO | Train Epoch: 13 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.069983 (0.068988) Boundary_loss: 0.013896 (0.013896) Loss: 0.083879 (0.082884) +2025-09-16,07:29:19 | INFO | Train Epoch: 13 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.055525 (0.068934) Boundary_loss: 0.013896 (0.013896) Loss: 0.069421 (0.082830) +2025-09-16,07:30:25 | INFO | Train Epoch: 13 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.059986 (0.068898) Boundary_loss: 0.013897 (0.013896) Loss: 0.073882 (0.082794) +2025-09-16,07:31:30 | INFO | Train Epoch: 13 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.069440 (0.068900) Boundary_loss: 0.013896 (0.013896) Loss: 0.083336 (0.082796) +2025-09-16,07:32:36 | INFO | Train Epoch: 13 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.071318 (0.068910) Boundary_loss: 0.013895 (0.013896) Loss: 0.085213 (0.082806) +2025-09-16,07:33:42 | INFO | Train Epoch: 13 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.082568 (0.068964) Boundary_loss: 0.013897 (0.013896) Loss: 0.096465 (0.082860) +2025-09-16,07:34:48 | INFO | Train Epoch: 13 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.059200 (0.068925) Boundary_loss: 0.013895 (0.013896) Loss: 0.073095 (0.082821) +2025-09-16,07:35:53 | INFO | Train Epoch: 13 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.049043 (0.068848) Boundary_loss: 0.013895 (0.013896) Loss: 0.062938 (0.082744) +2025-09-16,07:36:59 | INFO | Train Epoch: 13 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.068862 (0.068848) Boundary_loss: 0.013896 (0.013896) Loss: 0.082758 (0.082744) +2025-09-16,07:38:05 | INFO | Train Epoch: 13 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.093390 (0.068943) Boundary_loss: 0.013896 (0.013896) Loss: 0.10729 (0.082839) +2025-09-16,07:39:11 | INFO | Train Epoch: 13 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.063144 (0.068921) Boundary_loss: 0.013895 (0.013896) Loss: 0.077039 (0.082816) +2025-09-16,07:40:17 | INFO | Train Epoch: 13 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.071341 (0.068930) Boundary_loss: 0.013895 (0.013896) Loss: 0.085237 (0.082826) +2025-09-16,07:41:22 | INFO | Train Epoch: 13 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.069920 (0.068934) Boundary_loss: 0.013896 (0.013896) Loss: 0.083816 (0.082830) +2025-09-16,07:42:28 | INFO | Train Epoch: 13 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.066772 (0.068925) Boundary_loss: 0.013895 (0.013896) Loss: 0.080667 (0.082821) +2025-09-16,07:43:34 | INFO | Train Epoch: 13 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.075626 (0.068951) Boundary_loss: 0.013895 (0.013896) Loss: 0.089521 (0.082847) +2025-09-16,07:44:40 | INFO | Train Epoch: 13 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.064093 (0.068933) Boundary_loss: 0.013896 (0.013896) Loss: 0.077990 (0.082828) +2025-09-16,07:45:46 | INFO | Train Epoch: 13 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.068739 (0.068932) Boundary_loss: 0.013897 (0.013896) Loss: 0.082636 (0.082828) +2025-09-16,07:46:52 | INFO | Train Epoch: 13 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.056391 (0.068885) Boundary_loss: 0.013895 (0.013896) Loss: 0.070286 (0.082780) +2025-09-16,07:47:57 | INFO | Train Epoch: 13 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.052193 (0.068822) Boundary_loss: 0.013896 (0.013896) Loss: 0.066088 (0.082718) +2025-09-16,07:49:03 | INFO | Train Epoch: 13 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.080728 (0.068867) Boundary_loss: 0.013896 (0.013896) Loss: 0.094623 (0.082762) +2025-09-16,07:50:09 | INFO | Train Epoch: 13 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.061909 (0.068841) Boundary_loss: 0.013895 (0.013896) Loss: 0.075803 (0.082736) +2025-09-16,07:51:15 | INFO | Train Epoch: 13 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.078673 (0.068877) Boundary_loss: 0.013895 (0.013896) Loss: 0.092568 (0.082773) +2025-09-16,07:52:21 | INFO | Train Epoch: 13 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.048030 (0.068800) Boundary_loss: 0.013896 (0.013896) Loss: 0.061926 (0.082696) +2025-09-16,07:53:27 | INFO | Train Epoch: 13 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.069901 (0.068804) Boundary_loss: 0.013895 (0.013896) Loss: 0.083796 (0.082700) +2025-09-16,07:54:32 | INFO | Train Epoch: 13 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.057364 (0.068762) Boundary_loss: 0.013895 (0.013896) Loss: 0.071260 (0.082658) +2025-09-16,07:55:38 | INFO | Train Epoch: 13 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.072369 (0.068775) Boundary_loss: 0.013896 (0.013896) Loss: 0.086264 (0.082671) +2025-09-16,07:56:44 | INFO | Train Epoch: 13 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.070383 (0.068781) Boundary_loss: 0.013895 (0.013896) Loss: 0.084278 (0.082677) +2025-09-16,07:57:50 | INFO | Train Epoch: 13 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.079718 (0.068821) Boundary_loss: 0.013896 (0.013896) Loss: 0.093613 (0.082717) +2025-09-16,07:58:56 | INFO | Train Epoch: 13 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.081128 (0.068865) Boundary_loss: 0.013894 (0.013896) Loss: 0.095022 (0.082761) +2025-09-16,08:00:02 | INFO | Train Epoch: 13 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.080050 (0.068906) Boundary_loss: 0.013896 (0.013896) Loss: 0.093946 (0.082801) +2025-09-16,08:01:08 | INFO | Train Epoch: 13 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.064273 (0.068889) Boundary_loss: 0.013897 (0.013896) Loss: 0.078170 (0.082785) +2025-09-16,08:02:13 | INFO | Train Epoch: 13 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.049694 (0.068820) Boundary_loss: 0.013895 (0.013896) Loss: 0.063589 (0.082716) +2025-09-16,08:03:19 | INFO | Train Epoch: 13 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.068930 (0.068821) Boundary_loss: 0.013895 (0.013896) Loss: 0.082825 (0.082717) +2025-09-16,08:04:25 | INFO | Train Epoch: 13 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.043260 (0.068730) Boundary_loss: 0.013895 (0.013896) Loss: 0.057155 (0.082626) +2025-09-16,08:05:31 | INFO | Train Epoch: 13 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.089847 (0.068805) Boundary_loss: 0.013895 (0.013896) Loss: 0.10374 (0.082701) +2025-09-16,08:06:37 | INFO | Train Epoch: 13 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.038841 (0.068699) Boundary_loss: 0.013895 (0.013896) Loss: 0.052736 (0.082595) +2025-09-16,08:07:43 | INFO | Train Epoch: 13 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.069998 (0.068704) Boundary_loss: 0.013895 (0.013896) Loss: 0.083894 (0.082600) +2025-09-16,08:08:48 | INFO | Train Epoch: 13 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.057110 (0.068663) Boundary_loss: 0.013895 (0.013896) Loss: 0.071005 (0.082559) +2025-09-16,08:09:54 | INFO | Train Epoch: 13 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.054271 (0.068613) Boundary_loss: 0.013896 (0.013896) Loss: 0.068168 (0.082509) +2025-09-16,08:11:00 | INFO | Train Epoch: 13 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.090208 (0.068688) Boundary_loss: 0.013896 (0.013896) Loss: 0.10410 (0.082584) +2025-09-16,08:12:06 | INFO | Train Epoch: 13 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.069196 (0.068690) Boundary_loss: 0.013896 (0.013896) Loss: 0.083091 (0.082586) +2025-09-16,08:13:12 | INFO | Train Epoch: 13 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.056829 (0.068649) Boundary_loss: 0.013895 (0.013896) Loss: 0.070723 (0.082545) +2025-09-16,08:14:18 | INFO | Train Epoch: 13 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.067193 (0.068644) Boundary_loss: 0.013896 (0.013896) Loss: 0.081089 (0.082540) +2025-09-16,08:15:24 | INFO | Train Epoch: 13 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.079072 (0.068680) Boundary_loss: 0.013896 (0.013896) Loss: 0.092968 (0.082576) +2025-09-16,08:16:29 | INFO | Train Epoch: 13 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.065816 (0.068670) Boundary_loss: 0.013895 (0.013896) Loss: 0.079711 (0.082566) +2025-09-16,08:17:35 | INFO | Train Epoch: 13 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.075665 (0.068694) Boundary_loss: 0.013895 (0.013896) Loss: 0.089560 (0.082590) +2025-09-16,08:18:41 | INFO | Train Epoch: 13 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.089851 (0.068765) Boundary_loss: 0.013896 (0.013896) Loss: 0.10375 (0.082661) +2025-09-16,08:19:47 | INFO | Train Epoch: 13 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.076145 (0.068790) Boundary_loss: 0.013895 (0.013896) Loss: 0.090040 (0.082686) +2025-09-16,08:20:53 | INFO | Train Epoch: 13 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.060260 (0.068762) Boundary_loss: 0.013894 (0.013896) Loss: 0.074155 (0.082657) +2025-09-16,08:21:59 | INFO | Train Epoch: 13 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.051509 (0.068704) Boundary_loss: 0.013895 (0.013896) Loss: 0.065404 (0.082600) +2025-09-16,08:23:04 | INFO | Train Epoch: 13 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.074401 (0.068723) Boundary_loss: 0.013895 (0.013896) Loss: 0.088296 (0.082619) +2025-09-16,08:24:10 | INFO | Train Epoch: 13 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.062881 (0.068703) Boundary_loss: 0.013895 (0.013896) Loss: 0.076776 (0.082599) +2025-09-16,08:25:16 | INFO | Train Epoch: 13 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.073358 (0.068719) Boundary_loss: 0.013897 (0.013896) Loss: 0.087254 (0.082615) +2025-09-16,08:26:22 | INFO | Train Epoch: 13 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.080136 (0.068757) Boundary_loss: 0.013896 (0.013896) Loss: 0.094032 (0.082652) +2025-09-16,08:27:28 | INFO | Train Epoch: 13 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.089371 (0.068825) Boundary_loss: 0.013896 (0.013896) Loss: 0.10327 (0.082720) +2025-09-16,08:28:34 | INFO | Train Epoch: 13 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.030314 (0.068698) Boundary_loss: 0.013895 (0.013896) Loss: 0.044209 (0.082594) +2025-09-16,08:29:40 | INFO | Train Epoch: 13 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.058097 (0.068663) Boundary_loss: 0.013896 (0.013896) Loss: 0.071992 (0.082559) +2025-09-16,08:30:45 | INFO | Train Epoch: 13 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.064537 (0.068650) Boundary_loss: 0.013895 (0.013896) Loss: 0.078432 (0.082546) +2025-09-16,08:31:51 | INFO | Train Epoch: 13 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.063135 (0.068632) Boundary_loss: 0.013897 (0.013896) Loss: 0.077032 (0.082528) +2025-09-16,08:32:57 | INFO | Train Epoch: 13 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.087939 (0.068694) Boundary_loss: 0.013896 (0.013896) Loss: 0.10184 (0.082590) +2025-09-16,08:34:03 | INFO | Train Epoch: 13 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.058351 (0.068661) Boundary_loss: 0.013895 (0.013896) Loss: 0.072246 (0.082557) +2025-09-16,08:35:09 | INFO | Train Epoch: 13 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.085595 (0.068716) Boundary_loss: 0.013895 (0.013896) Loss: 0.099490 (0.082611) +2025-09-16,08:36:15 | INFO | Train Epoch: 13 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.089743 (0.068783) Boundary_loss: 0.013895 (0.013896) Loss: 0.10364 (0.082679) +2025-09-16,08:37:20 | INFO | Train Epoch: 13 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.064028 (0.068768) Boundary_loss: 0.013895 (0.013896) Loss: 0.077923 (0.082664) +2025-09-16,08:38:26 | INFO | Train Epoch: 13 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.082595 (0.068812) Boundary_loss: 0.013896 (0.013896) Loss: 0.096491 (0.082708) +2025-09-16,08:39:32 | INFO | Train Epoch: 13 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.080309 (0.068849) Boundary_loss: 0.013895 (0.013896) Loss: 0.094204 (0.082745) +2025-09-16,08:40:38 | INFO | Train Epoch: 13 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.076408 (0.068873) Boundary_loss: 0.013896 (0.013896) Loss: 0.090303 (0.082769) +2025-09-16,08:41:44 | INFO | Train Epoch: 13 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.079640 (0.068907) Boundary_loss: 0.013895 (0.013896) Loss: 0.093535 (0.082803) +2025-09-16,08:42:49 | INFO | Train Epoch: 13 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.067774 (0.068903) Boundary_loss: 0.013896 (0.013896) Loss: 0.081670 (0.082799) +2025-09-16,08:43:55 | INFO | Train Epoch: 13 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.061733 (0.068881) Boundary_loss: 0.013896 (0.013896) Loss: 0.075628 (0.082776) +2025-09-16,08:45:01 | INFO | Train Epoch: 13 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.069517 (0.068883) Boundary_loss: 0.013896 (0.013896) Loss: 0.083413 (0.082778) +2025-09-16,08:46:07 | INFO | Train Epoch: 13 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.039886 (0.068792) Boundary_loss: 0.013896 (0.013896) Loss: 0.053781 (0.082688) +2025-09-16,08:47:13 | INFO | Train Epoch: 13 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.074985 (0.068811) Boundary_loss: 0.013897 (0.013896) Loss: 0.088882 (0.082707) +2025-09-16,08:48:19 | INFO | Train Epoch: 13 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.067140 (0.068806) Boundary_loss: 0.013896 (0.013896) Loss: 0.081036 (0.082702) +2025-09-16,08:49:24 | INFO | Train Epoch: 13 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.080882 (0.068844) Boundary_loss: 0.013896 (0.013896) Loss: 0.094778 (0.082739) +2025-09-16,08:50:30 | INFO | Train Epoch: 13 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.088026 (0.068903) Boundary_loss: 0.013895 (0.013896) Loss: 0.10192 (0.082799) +2025-09-16,08:51:36 | INFO | Train Epoch: 13 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.067457 (0.068898) Boundary_loss: 0.013896 (0.013896) Loss: 0.081353 (0.082794) +2025-09-16,08:52:42 | INFO | Train Epoch: 13 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.076975 (0.068923) Boundary_loss: 0.013896 (0.013896) Loss: 0.090871 (0.082819) +2025-09-16,08:53:48 | INFO | Train Epoch: 13 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.057784 (0.068889) Boundary_loss: 0.013896 (0.013896) Loss: 0.071679 (0.082785) +2025-09-16,08:54:54 | INFO | Train Epoch: 13 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.089248 (0.068951) Boundary_loss: 0.013895 (0.013896) Loss: 0.10314 (0.082847) +2025-09-16,08:56:00 | INFO | Train Epoch: 13 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.061736 (0.068929) Boundary_loss: 0.013896 (0.013896) Loss: 0.075632 (0.082825) +2025-09-16,08:57:05 | INFO | Train Epoch: 13 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.085207 (0.068979) Boundary_loss: 0.013894 (0.013896) Loss: 0.099102 (0.082874) +2025-09-16,08:58:11 | INFO | Train Epoch: 13 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.074618 (0.068996) Boundary_loss: 0.013896 (0.013896) Loss: 0.088514 (0.082891) +2025-09-16,08:59:17 | INFO | Train Epoch: 13 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.089726 (0.069058) Boundary_loss: 0.013895 (0.013896) Loss: 0.10362 (0.082954) +2025-09-16,09:00:23 | INFO | Train Epoch: 13 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.063067 (0.069040) Boundary_loss: 0.013896 (0.013896) Loss: 0.076963 (0.082936) +2025-09-16,09:01:29 | INFO | Train Epoch: 13 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.077912 (0.069067) Boundary_loss: 0.013895 (0.013896) Loss: 0.091806 (0.082962) +2025-09-16,09:02:35 | INFO | Train Epoch: 13 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.087985 (0.069123) Boundary_loss: 0.013896 (0.013896) Loss: 0.10188 (0.083019) +2025-09-16,09:03:41 | INFO | Train Epoch: 13 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.054242 (0.069079) Boundary_loss: 0.013895 (0.013896) Loss: 0.068137 (0.082975) +2025-09-16,09:04:47 | INFO | Train Epoch: 13 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.078632 (0.069107) Boundary_loss: 0.013895 (0.013896) Loss: 0.092527 (0.083003) +2025-09-16,09:05:52 | INFO | Train Epoch: 13 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.086252 (0.069158) Boundary_loss: 0.013896 (0.013896) Loss: 0.10015 (0.083054) +2025-09-16,09:06:58 | INFO | Train Epoch: 13 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.076787 (0.069180) Boundary_loss: 0.013896 (0.013896) Loss: 0.090683 (0.083076) +2025-09-16,09:08:04 | INFO | Train Epoch: 13 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.070848 (0.069185) Boundary_loss: 0.013896 (0.013896) Loss: 0.084744 (0.083081) +2025-09-16,09:09:10 | INFO | Train Epoch: 13 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.070014 (0.069188) Boundary_loss: 0.013896 (0.013896) Loss: 0.083910 (0.083083) +2025-09-16,09:10:16 | INFO | Train Epoch: 13 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.081433 (0.069224) Boundary_loss: 0.013895 (0.013896) Loss: 0.095328 (0.083119) +2025-09-16,09:11:22 | INFO | Train Epoch: 13 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.040975 (0.069141) Boundary_loss: 0.013896 (0.013896) Loss: 0.054872 (0.083037) +2025-09-16,09:12:28 | INFO | Train Epoch: 13 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.052369 (0.069092) Boundary_loss: 0.013896 (0.013896) Loss: 0.066265 (0.082988) +2025-09-16,09:13:33 | INFO | Train Epoch: 13 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.051756 (0.069042) Boundary_loss: 0.013895 (0.013896) Loss: 0.065651 (0.082938) +2025-09-16,09:14:39 | INFO | Train Epoch: 13 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.073112 (0.069054) Boundary_loss: 0.013895 (0.013896) Loss: 0.087008 (0.082950) +2025-09-16,09:15:45 | INFO | Train Epoch: 13 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.045742 (0.068987) Boundary_loss: 0.013897 (0.013896) Loss: 0.059639 (0.082882) +2025-09-16,09:16:51 | INFO | Train Epoch: 13 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.061010 (0.068964) Boundary_loss: 0.013896 (0.013896) Loss: 0.074906 (0.082860) +2025-09-16,09:17:57 | INFO | Train Epoch: 13 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.096186 (0.069042) Boundary_loss: 0.013896 (0.013896) Loss: 0.11008 (0.082938) +2025-09-16,09:19:03 | INFO | Train Epoch: 13 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.056331 (0.069005) Boundary_loss: 0.013895 (0.013896) Loss: 0.070227 (0.082901) +2025-09-16,09:20:09 | INFO | Train Epoch: 13 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.077234 (0.069029) Boundary_loss: 0.013895 (0.013896) Loss: 0.091129 (0.082925) +2025-09-16,09:21:14 | INFO | Train Epoch: 13 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.052094 (0.068981) Boundary_loss: 0.013894 (0.013896) Loss: 0.065989 (0.082877) +2025-09-16,09:22:20 | INFO | Train Epoch: 13 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.047300 (0.068919) Boundary_loss: 0.013895 (0.013896) Loss: 0.061194 (0.082815) +2025-09-16,09:23:26 | INFO | Train Epoch: 13 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.050176 (0.068866) Boundary_loss: 0.013895 (0.013896) Loss: 0.064071 (0.082762) +2025-09-16,09:24:32 | INFO | Train Epoch: 13 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.075887 (0.068886) Boundary_loss: 0.013896 (0.013896) Loss: 0.089783 (0.082782) +2025-09-16,09:25:38 | INFO | Train Epoch: 13 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.052402 (0.068840) Boundary_loss: 0.013895 (0.013896) Loss: 0.066297 (0.082736) +2025-09-16,09:26:44 | INFO | Train Epoch: 13 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.057758 (0.068809) Boundary_loss: 0.013896 (0.013896) Loss: 0.071654 (0.082705) +2025-09-16,09:27:50 | INFO | Train Epoch: 13 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.065554 (0.068800) Boundary_loss: 0.013895 (0.013896) Loss: 0.079449 (0.082695) +2025-09-16,09:28:55 | INFO | Train Epoch: 13 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.057389 (0.068768) Boundary_loss: 0.013896 (0.013896) Loss: 0.071286 (0.082664) +2025-09-16,09:30:01 | INFO | Train Epoch: 13 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.069973 (0.068771) Boundary_loss: 0.013896 (0.013896) Loss: 0.083869 (0.082667) +2025-09-16,09:31:07 | INFO | Train Epoch: 13 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.023147 (0.068645) Boundary_loss: 0.013895 (0.013896) Loss: 0.037041 (0.082541) +2025-09-16,09:32:13 | INFO | Train Epoch: 13 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.088584 (0.068700) Boundary_loss: 0.013896 (0.013896) Loss: 0.10248 (0.082596) +2025-09-16,09:33:19 | INFO | Train Epoch: 13 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.062182 (0.068682) Boundary_loss: 0.013895 (0.013896) Loss: 0.076077 (0.082578) +2025-09-16,09:34:25 | INFO | Train Epoch: 13 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.079360 (0.068711) Boundary_loss: 0.013897 (0.013896) Loss: 0.093257 (0.082607) +2025-09-16,09:35:31 | INFO | Train Epoch: 13 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.051712 (0.068665) Boundary_loss: 0.013896 (0.013896) Loss: 0.065608 (0.082561) +2025-09-16,09:36:36 | INFO | Train Epoch: 13 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.082939 (0.068704) Boundary_loss: 0.013897 (0.013896) Loss: 0.096836 (0.082600) +2025-09-16,09:37:42 | INFO | Train Epoch: 13 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.048042 (0.068648) Boundary_loss: 0.013896 (0.013896) Loss: 0.061938 (0.082543) +2025-09-16,09:38:48 | INFO | Train Epoch: 13 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.068758 (0.068648) Boundary_loss: 0.013895 (0.013896) Loss: 0.082653 (0.082544) +2025-09-16,09:39:54 | INFO | Train Epoch: 13 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.055460 (0.068612) Boundary_loss: 0.013896 (0.013896) Loss: 0.069356 (0.082508) +2025-09-16,09:41:00 | INFO | Train Epoch: 13 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.067045 (0.068608) Boundary_loss: 0.013896 (0.013896) Loss: 0.080941 (0.082504) +2025-09-16,09:42:06 | INFO | Train Epoch: 13 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.071519 (0.068616) Boundary_loss: 0.013897 (0.013896) Loss: 0.085416 (0.082511) +2025-09-16,09:43:12 | INFO | Train Epoch: 13 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.070663 (0.068621) Boundary_loss: 0.013896 (0.013896) Loss: 0.084559 (0.082517) +2025-09-16,09:44:18 | INFO | Train Epoch: 13 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.092625 (0.068686) Boundary_loss: 0.013896 (0.013896) Loss: 0.10652 (0.082581) +2025-09-16,09:45:23 | INFO | Train Epoch: 13 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.092355 (0.068749) Boundary_loss: 0.013895 (0.013896) Loss: 0.10625 (0.082645) +2025-09-16,09:46:29 | INFO | Train Epoch: 13 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.053337 (0.068708) Boundary_loss: 0.013896 (0.013896) Loss: 0.067233 (0.082603) +2025-09-16,09:47:35 | INFO | Train Epoch: 13 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.074103 (0.068722) Boundary_loss: 0.013896 (0.013896) Loss: 0.087998 (0.082618) +2025-09-16,09:48:41 | INFO | Train Epoch: 13 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.068330 (0.068721) Boundary_loss: 0.013895 (0.013896) Loss: 0.082225 (0.082617) +2025-09-16,09:49:47 | INFO | Train Epoch: 13 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.059469 (0.068697) Boundary_loss: 0.013896 (0.013896) Loss: 0.073364 (0.082592) +2025-09-16,09:50:53 | INFO | Train Epoch: 13 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.073064 (0.068708) Boundary_loss: 0.013897 (0.013896) Loss: 0.086961 (0.082604) +2025-09-16,09:51:59 | INFO | Train Epoch: 13 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.035038 (0.068620) Boundary_loss: 0.013896 (0.013896) Loss: 0.048933 (0.082515) +2025-09-16,09:53:04 | INFO | Train Epoch: 13 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.081005 (0.068652) Boundary_loss: 0.013896 (0.013896) Loss: 0.094901 (0.082548) +2025-09-16,09:54:10 | INFO | Train Epoch: 13 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.069284 (0.068654) Boundary_loss: 0.013895 (0.013896) Loss: 0.083179 (0.082549) +2025-09-16,09:55:16 | INFO | Train Epoch: 13 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.052357 (0.068611) Boundary_loss: 0.013897 (0.013896) Loss: 0.066254 (0.082507) +2025-09-16,09:56:22 | INFO | Train Epoch: 13 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.086939 (0.068659) Boundary_loss: 0.013895 (0.013896) Loss: 0.10083 (0.082555) +2025-09-16,09:57:28 | INFO | Train Epoch: 13 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.065691 (0.068651) Boundary_loss: 0.013895 (0.013896) Loss: 0.079586 (0.082547) +2025-09-16,09:58:34 | INFO | Train Epoch: 13 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.049002 (0.068600) Boundary_loss: 0.013896 (0.013896) Loss: 0.062898 (0.082496) +2025-09-16,09:59:39 | INFO | Train Epoch: 13 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.051979 (0.068557) Boundary_loss: 0.013897 (0.013896) Loss: 0.065876 (0.082453) +2025-09-16,10:00:45 | INFO | Train Epoch: 13 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.048944 (0.068507) Boundary_loss: 0.013896 (0.013896) Loss: 0.062840 (0.082402) +2025-09-16,10:01:51 | INFO | Train Epoch: 13 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.042011 (0.068439) Boundary_loss: 0.013894 (0.013896) Loss: 0.055905 (0.082334) +2025-09-16,10:02:57 | INFO | Train Epoch: 13 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.040837 (0.068368) Boundary_loss: 0.013896 (0.013896) Loss: 0.054732 (0.082264) +2025-09-16,10:04:03 | INFO | Train Epoch: 13 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.051466 (0.068325) Boundary_loss: 0.013896 (0.013896) Loss: 0.065362 (0.082220) +2025-09-16,10:05:09 | INFO | Train Epoch: 13 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.080024 (0.068354) Boundary_loss: 0.013896 (0.013896) Loss: 0.093920 (0.082250) +2025-09-16,10:06:14 | INFO | Train Epoch: 13 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.087105 (0.068402) Boundary_loss: 0.013897 (0.013896) Loss: 0.10100 (0.082298) +2025-09-16,10:07:20 | INFO | Train Epoch: 13 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.083628 (0.068441) Boundary_loss: 0.013896 (0.013896) Loss: 0.097524 (0.082337) +2025-09-16,10:08:26 | INFO | Train Epoch: 13 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.055190 (0.068407) Boundary_loss: 0.013895 (0.013896) Loss: 0.069085 (0.082303) +2025-09-16,10:09:32 | INFO | Train Epoch: 13 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.044334 (0.068346) Boundary_loss: 0.013895 (0.013896) Loss: 0.058229 (0.082242) +2025-09-16,10:10:38 | INFO | Train Epoch: 13 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.044652 (0.068287) Boundary_loss: 0.013895 (0.013896) Loss: 0.058548 (0.082183) +2025-09-16,10:11:44 | INFO | Train Epoch: 13 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.050373 (0.068242) Boundary_loss: 0.013895 (0.013896) Loss: 0.064268 (0.082138) +2025-09-16,10:12:50 | INFO | Train Epoch: 13 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.089633 (0.068295) Boundary_loss: 0.013896 (0.013896) Loss: 0.10353 (0.082191) +2025-09-16,10:13:55 | INFO | Train Epoch: 13 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.058190 (0.068270) Boundary_loss: 0.013895 (0.013896) Loss: 0.072086 (0.082166) +2025-09-16,10:15:01 | INFO | Train Epoch: 13 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.072594 (0.068281) Boundary_loss: 0.013895 (0.013896) Loss: 0.086489 (0.082177) +2025-09-16,10:16:07 | INFO | Train Epoch: 13 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.066132 (0.068276) Boundary_loss: 0.013897 (0.013896) Loss: 0.080030 (0.082171) +2025-09-16,10:17:13 | INFO | Train Epoch: 13 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.050326 (0.068231) Boundary_loss: 0.013896 (0.013896) Loss: 0.064222 (0.082127) +2025-09-16,10:18:19 | INFO | Train Epoch: 13 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.084879 (0.068272) Boundary_loss: 0.013897 (0.013896) Loss: 0.098776 (0.082168) +2025-09-16,10:19:25 | INFO | Train Epoch: 13 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.061422 (0.068255) Boundary_loss: 0.013895 (0.013896) Loss: 0.075317 (0.082151) +2025-09-16,10:20:31 | INFO | Train Epoch: 13 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.079235 (0.068282) Boundary_loss: 0.013895 (0.013896) Loss: 0.093130 (0.082178) +2025-09-16,10:21:36 | INFO | Train Epoch: 13 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.056195 (0.068253) Boundary_loss: 0.013896 (0.013896) Loss: 0.070090 (0.082148) +2025-09-16,10:22:42 | INFO | Train Epoch: 13 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.080442 (0.068283) Boundary_loss: 0.013895 (0.013896) Loss: 0.094338 (0.082178) +2025-09-16,10:23:48 | INFO | Train Epoch: 13 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.058393 (0.068258) Boundary_loss: 0.013895 (0.013896) Loss: 0.072288 (0.082154) +2025-09-16,10:24:54 | INFO | Train Epoch: 13 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.074538 (0.068274) Boundary_loss: 0.013896 (0.013896) Loss: 0.088434 (0.082169) +2025-09-16,10:26:00 | INFO | Train Epoch: 13 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.061870 (0.068258) Boundary_loss: 0.013895 (0.013896) Loss: 0.075765 (0.082154) +2025-09-16,10:27:06 | INFO | Train Epoch: 13 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.060096 (0.068238) Boundary_loss: 0.013895 (0.013896) Loss: 0.073991 (0.082134) +2025-09-16,10:28:11 | INFO | Train Epoch: 13 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.073375 (0.068251) Boundary_loss: 0.013895 (0.013896) Loss: 0.087269 (0.082146) +2025-09-16,10:29:17 | INFO | Train Epoch: 13 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10130 (0.068331) Boundary_loss: 0.013896 (0.013896) Loss: 0.11519 (0.082226) +2025-09-16,10:30:23 | INFO | Train Epoch: 13 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.058403 (0.068307) Boundary_loss: 0.013895 (0.013896) Loss: 0.072298 (0.082202) +2025-09-16,10:31:29 | INFO | Train Epoch: 13 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.060878 (0.068289) Boundary_loss: 0.013896 (0.013896) Loss: 0.074774 (0.082184) +2025-09-16,10:32:35 | INFO | Train Epoch: 13 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.056070 (0.068259) Boundary_loss: 0.013896 (0.013896) Loss: 0.069965 (0.082155) +2025-09-16,10:33:41 | INFO | Train Epoch: 13 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.085393 (0.068300) Boundary_loss: 0.013896 (0.013896) Loss: 0.099289 (0.082196) +2025-09-16,10:34:47 | INFO | Train Epoch: 13 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.050722 (0.068259) Boundary_loss: 0.013896 (0.013896) Loss: 0.064618 (0.082154) +2025-09-16,10:35:52 | INFO | Train Epoch: 13 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.053188 (0.068223) Boundary_loss: 0.013895 (0.013896) Loss: 0.067084 (0.082118) +2025-09-16,10:36:58 | INFO | Train Epoch: 13 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.062764 (0.068210) Boundary_loss: 0.013897 (0.013896) Loss: 0.076660 (0.082105) +2025-09-16,10:38:04 | INFO | Train Epoch: 13 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.044779 (0.068154) Boundary_loss: 0.013896 (0.013896) Loss: 0.058675 (0.082050) +2025-09-16,10:39:10 | INFO | Train Epoch: 13 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.082112 (0.068187) Boundary_loss: 0.013896 (0.013896) Loss: 0.096007 (0.082083) +2025-09-16,10:40:16 | INFO | Train Epoch: 13 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.051520 (0.068148) Boundary_loss: 0.013895 (0.013896) Loss: 0.065415 (0.082044) +2025-09-16,10:41:21 | INFO | Train Epoch: 13 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.039131 (0.068080) Boundary_loss: 0.013896 (0.013896) Loss: 0.053027 (0.081975) +2025-09-16,10:42:27 | INFO | Train Epoch: 13 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.065307 (0.068073) Boundary_loss: 0.013895 (0.013896) Loss: 0.079201 (0.081969) +2025-09-16,10:43:33 | INFO | Train Epoch: 13 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.048372 (0.068027) Boundary_loss: 0.013895 (0.013896) Loss: 0.062267 (0.081923) +2025-09-16,10:44:39 | INFO | Train Epoch: 13 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.057339 (0.068002) Boundary_loss: 0.013896 (0.013896) Loss: 0.071236 (0.081898) +2025-09-16,10:45:45 | INFO | Train Epoch: 13 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.097619 (0.068071) Boundary_loss: 0.013895 (0.013896) Loss: 0.11151 (0.081967) +2025-09-16,10:46:50 | INFO | Train Epoch: 13 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.062129 (0.068057) Boundary_loss: 0.013895 (0.013896) Loss: 0.076025 (0.081953) +2025-09-16,10:47:56 | INFO | Train Epoch: 13 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.058359 (0.068035) Boundary_loss: 0.013896 (0.013896) Loss: 0.072254 (0.081930) +2025-09-16,10:49:02 | INFO | Train Epoch: 13 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.077201 (0.068056) Boundary_loss: 0.013896 (0.013896) Loss: 0.091097 (0.081952) +2025-09-16,10:50:08 | INFO | Train Epoch: 13 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.043230 (0.067999) Boundary_loss: 0.013895 (0.013896) Loss: 0.057125 (0.081894) +2025-09-16,10:51:14 | INFO | Train Epoch: 13 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.077789 (0.068021) Boundary_loss: 0.013896 (0.013896) Loss: 0.091685 (0.081917) +2025-09-16,10:52:19 | INFO | Train Epoch: 13 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.076284 (0.068040) Boundary_loss: 0.013895 (0.013896) Loss: 0.090180 (0.081936) +2025-09-16,10:53:25 | INFO | Train Epoch: 13 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.053403 (0.068007) Boundary_loss: 0.013896 (0.013896) Loss: 0.067299 (0.081902) +2025-09-16,10:54:31 | INFO | Train Epoch: 13 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.068692 (0.068008) Boundary_loss: 0.013896 (0.013896) Loss: 0.082588 (0.081904) +2025-09-16,10:55:37 | INFO | Train Epoch: 13 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.049582 (0.067966) Boundary_loss: 0.013896 (0.013896) Loss: 0.063477 (0.081862) +2025-09-16,10:56:43 | INFO | Train Epoch: 13 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.072281 (0.067976) Boundary_loss: 0.013894 (0.013896) Loss: 0.086175 (0.081872) +2025-09-16,10:57:48 | INFO | Train Epoch: 13 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.056147 (0.067949) Boundary_loss: 0.013896 (0.013896) Loss: 0.070043 (0.081845) +2025-09-16,10:58:54 | INFO | Train Epoch: 13 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.097858 (0.068017) Boundary_loss: 0.013896 (0.013896) Loss: 0.11175 (0.081913) +2025-09-16,11:00:00 | INFO | Train Epoch: 13 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.090562 (0.068068) Boundary_loss: 0.013896 (0.013896) Loss: 0.10446 (0.081964) +2025-09-16,11:01:06 | INFO | Train Epoch: 13 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.057144 (0.068043) Boundary_loss: 0.013895 (0.013896) Loss: 0.071039 (0.081939) +2025-09-16,11:02:11 | INFO | Train Epoch: 13 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.051411 (0.068006) Boundary_loss: 0.013896 (0.013896) Loss: 0.065307 (0.081901) +2025-09-16,11:03:17 | INFO | Train Epoch: 13 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.049487 (0.067964) Boundary_loss: 0.013897 (0.013896) Loss: 0.063384 (0.081860) +2025-09-16,11:04:23 | INFO | Train Epoch: 13 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.087646 (0.068008) Boundary_loss: 0.013896 (0.013896) Loss: 0.10154 (0.081904) +2025-09-16,11:05:29 | INFO | Train Epoch: 13 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.037490 (0.067940) Boundary_loss: 0.013895 (0.013896) Loss: 0.051385 (0.081836) +2025-09-16,11:06:35 | INFO | Train Epoch: 13 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.084715 (0.067977) Boundary_loss: 0.013896 (0.013896) Loss: 0.098611 (0.081873) +2025-09-16,11:07:40 | INFO | Train Epoch: 13 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.056124 (0.067951) Boundary_loss: 0.013896 (0.013896) Loss: 0.070020 (0.081847) +2025-09-16,11:08:46 | INFO | Train Epoch: 13 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.078954 (0.067975) Boundary_loss: 0.013896 (0.013896) Loss: 0.092850 (0.081871) +2025-09-16,11:09:52 | INFO | Train Epoch: 13 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.076822 (0.067995) Boundary_loss: 0.013894 (0.013896) Loss: 0.090716 (0.081891) +2025-09-16,11:10:58 | INFO | Train Epoch: 13 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.048816 (0.067953) Boundary_loss: 0.013895 (0.013896) Loss: 0.062711 (0.081848) +2025-09-16,11:12:03 | INFO | Train Epoch: 13 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.070702 (0.067959) Boundary_loss: 0.013897 (0.013896) Loss: 0.084599 (0.081854) +2025-09-16,11:13:09 | INFO | Train Epoch: 13 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.048632 (0.067916) Boundary_loss: 0.013894 (0.013896) Loss: 0.062526 (0.081812) +2025-09-16,11:14:15 | INFO | Train Epoch: 13 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.064520 (0.067909) Boundary_loss: 0.013895 (0.013896) Loss: 0.078415 (0.081804) +2025-09-16,11:15:21 | INFO | Train Epoch: 13 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.040206 (0.067848) Boundary_loss: 0.013899 (0.013896) Loss: 0.054105 (0.081744) +2025-09-16,11:16:27 | INFO | Train Epoch: 13 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.059044 (0.067829) Boundary_loss: 0.013896 (0.013896) Loss: 0.072940 (0.081724) +2025-09-16,11:17:33 | INFO | Train Epoch: 13 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.055897 (0.067803) Boundary_loss: 0.013896 (0.013896) Loss: 0.069793 (0.081698) +2025-09-16,11:18:39 | INFO | Train Epoch: 13 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.060517 (0.067787) Boundary_loss: 0.013895 (0.013896) Loss: 0.074413 (0.081682) +2025-09-16,11:19:45 | INFO | Train Epoch: 13 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.065148 (0.067781) Boundary_loss: 0.013895 (0.013896) Loss: 0.079043 (0.081677) +2025-09-16,11:20:51 | INFO | Train Epoch: 13 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.071456 (0.067789) Boundary_loss: 0.013895 (0.013896) Loss: 0.085352 (0.081685) +2025-09-16,11:21:56 | INFO | Train Epoch: 13 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.063105 (0.067779) Boundary_loss: 0.013896 (0.013896) Loss: 0.077001 (0.081675) +2025-09-16,11:23:02 | INFO | Train Epoch: 13 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.083877 (0.067814) Boundary_loss: 0.013895 (0.013896) Loss: 0.097772 (0.081709) +2025-09-16,11:24:08 | INFO | Train Epoch: 13 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.058576 (0.067794) Boundary_loss: 0.013896 (0.013896) Loss: 0.072472 (0.081689) +2025-09-16,11:25:14 | INFO | Train Epoch: 13 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.067526 (0.067793) Boundary_loss: 0.013895 (0.013896) Loss: 0.081421 (0.081689) +2025-09-16,11:26:20 | INFO | Train Epoch: 13 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.075327 (0.067809) Boundary_loss: 0.013895 (0.013896) Loss: 0.089222 (0.081705) +2025-09-16,11:27:25 | INFO | Train Epoch: 13 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.081649 (0.067839) Boundary_loss: 0.013896 (0.013896) Loss: 0.095544 (0.081735) +2025-09-16,11:28:31 | INFO | Train Epoch: 13 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.057142 (0.067816) Boundary_loss: 0.013896 (0.013896) Loss: 0.071038 (0.081712) +2025-09-16,11:29:37 | INFO | Train Epoch: 13 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.042950 (0.067763) Boundary_loss: 0.013895 (0.013896) Loss: 0.056845 (0.081659) +2025-09-16,11:30:43 | INFO | Train Epoch: 13 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.064156 (0.067755) Boundary_loss: 0.013896 (0.013896) Loss: 0.078051 (0.081651) +2025-09-16,11:31:49 | INFO | Train Epoch: 13 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10308 (0.067830) Boundary_loss: 0.013896 (0.013896) Loss: 0.11697 (0.081726) +2025-09-16,11:32:55 | INFO | Train Epoch: 13 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.044319 (0.067781) Boundary_loss: 0.013895 (0.013896) Loss: 0.058214 (0.081676) +2025-09-16,11:34:00 | INFO | Train Epoch: 13 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.061188 (0.067767) Boundary_loss: 0.013896 (0.013896) Loss: 0.075084 (0.081662) +2025-09-16,11:35:06 | INFO | Train Epoch: 13 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.048948 (0.067727) Boundary_loss: 0.013896 (0.013896) Loss: 0.062845 (0.081623) +2025-09-16,11:36:12 | INFO | Train Epoch: 13 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.060758 (0.067712) Boundary_loss: 0.013895 (0.013896) Loss: 0.074652 (0.081608) +2025-09-16,11:37:18 | INFO | Train Epoch: 13 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.079772 (0.067738) Boundary_loss: 0.013896 (0.013896) Loss: 0.093667 (0.081633) +2025-09-16,11:38:24 | INFO | Train Epoch: 13 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.053108 (0.067707) Boundary_loss: 0.013895 (0.013896) Loss: 0.067003 (0.081603) +2025-09-16,11:39:29 | INFO | Train Epoch: 13 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.053742 (0.067678) Boundary_loss: 0.013896 (0.013896) Loss: 0.067638 (0.081573) +2025-09-16,11:40:35 | INFO | Train Epoch: 13 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.094688 (0.067734) Boundary_loss: 0.013895 (0.013896) Loss: 0.10858 (0.081630) +2025-09-16,11:41:41 | INFO | Train Epoch: 13 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.046582 (0.067690) Boundary_loss: 0.013895 (0.013896) Loss: 0.060477 (0.081586) +2025-09-16,11:42:47 | INFO | Train Epoch: 13 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.095207 (0.067747) Boundary_loss: 0.013895 (0.013896) Loss: 0.10910 (0.081643) +2025-09-16,11:43:53 | INFO | Train Epoch: 13 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.056809 (0.067724) Boundary_loss: 0.013896 (0.013896) Loss: 0.070705 (0.081620) +2025-09-16,11:44:59 | INFO | Train Epoch: 13 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.061837 (0.067712) Boundary_loss: 0.013896 (0.013896) Loss: 0.075733 (0.081608) +2025-09-16,11:46:04 | INFO | Train Epoch: 13 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.075602 (0.067729) Boundary_loss: 0.013896 (0.013896) Loss: 0.089498 (0.081624) +2025-09-16,11:47:10 | INFO | Train Epoch: 13 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.058115 (0.067709) Boundary_loss: 0.013894 (0.013896) Loss: 0.072009 (0.081604) +2025-09-16,11:48:16 | INFO | Train Epoch: 13 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.043630 (0.067659) Boundary_loss: 0.013895 (0.013896) Loss: 0.057525 (0.081555) +2025-09-16,11:49:22 | INFO | Train Epoch: 13 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.054704 (0.067633) Boundary_loss: 0.013895 (0.013896) Loss: 0.068599 (0.081528) +2025-09-16,11:50:28 | INFO | Train Epoch: 13 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.047950 (0.067592) Boundary_loss: 0.013895 (0.013896) Loss: 0.061844 (0.081488) +2025-09-16,11:51:34 | INFO | Train Epoch: 13 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.066080 (0.067589) Boundary_loss: 0.013895 (0.013896) Loss: 0.079975 (0.081485) +2025-09-16,11:52:39 | INFO | Train Epoch: 13 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.049082 (0.067551) Boundary_loss: 0.013895 (0.013896) Loss: 0.062978 (0.081447) +2025-09-16,11:53:45 | INFO | Train Epoch: 13 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.056371 (0.067529) Boundary_loss: 0.013895 (0.013896) Loss: 0.070266 (0.081424) +2025-09-16,11:54:51 | INFO | Train Epoch: 13 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.069435 (0.067533) Boundary_loss: 0.013896 (0.013896) Loss: 0.083330 (0.081428) +2025-09-16,11:55:57 | INFO | Train Epoch: 13 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.055632 (0.067508) Boundary_loss: 0.013896 (0.013896) Loss: 0.069527 (0.081404) +2025-09-16,11:57:03 | INFO | Train Epoch: 13 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.060286 (0.067494) Boundary_loss: 0.013895 (0.013896) Loss: 0.074180 (0.081389) +2025-09-16,11:58:09 | INFO | Train Epoch: 13 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.080215 (0.067519) Boundary_loss: 0.013896 (0.013896) Loss: 0.094111 (0.081415) +2025-09-16,11:59:15 | INFO | Train Epoch: 13 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.073054 (0.067531) Boundary_loss: 0.013896 (0.013896) Loss: 0.086950 (0.081426) +2025-09-16,12:00:20 | INFO | Train Epoch: 13 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.080225 (0.067556) Boundary_loss: 0.013895 (0.013896) Loss: 0.094120 (0.081452) +2025-09-16,12:01:26 | INFO | Train Epoch: 13 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10842 (0.067638) Boundary_loss: 0.013896 (0.013896) Loss: 0.12231 (0.081534) +2025-09-16,12:02:32 | INFO | Train Epoch: 13 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.069162 (0.067641) Boundary_loss: 0.013895 (0.013896) Loss: 0.083058 (0.081537) +2025-09-16,12:03:38 | INFO | Train Epoch: 13 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.048322 (0.067603) Boundary_loss: 0.013896 (0.013896) Loss: 0.062219 (0.081498) +2025-09-16,12:04:44 | INFO | Train Epoch: 13 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.063756 (0.067595) Boundary_loss: 0.013895 (0.013896) Loss: 0.077651 (0.081491) +2025-09-16,12:05:50 | INFO | Train Epoch: 13 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.078569 (0.067617) Boundary_loss: 0.013895 (0.013896) Loss: 0.092464 (0.081513) +2025-09-16,12:06:55 | INFO | Train Epoch: 13 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.062012 (0.067606) Boundary_loss: 0.013896 (0.013896) Loss: 0.075907 (0.081501) +2025-09-16,12:08:01 | INFO | Train Epoch: 13 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.069952 (0.067610) Boundary_loss: 0.013897 (0.013896) Loss: 0.083848 (0.081506) +2025-09-16,12:09:07 | INFO | Train Epoch: 13 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.078102 (0.067631) Boundary_loss: 0.013895 (0.013896) Loss: 0.091997 (0.081527) +2025-09-16,12:10:13 | INFO | Train Epoch: 13 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.060005 (0.067616) Boundary_loss: 0.013895 (0.013896) Loss: 0.073901 (0.081512) +2025-09-16,12:11:19 | INFO | Train Epoch: 13 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.064158 (0.067609) Boundary_loss: 0.013895 (0.013896) Loss: 0.078053 (0.081505) +2025-09-16,12:12:25 | INFO | Train Epoch: 13 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.064259 (0.067603) Boundary_loss: 0.013895 (0.013896) Loss: 0.078154 (0.081498) +2025-09-16,12:13:31 | INFO | Train Epoch: 13 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.047420 (0.067563) Boundary_loss: 0.013895 (0.013896) Loss: 0.061316 (0.081459) +2025-09-16,12:14:36 | INFO | Train Epoch: 13 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.094553 (0.067616) Boundary_loss: 0.013897 (0.013896) Loss: 0.10845 (0.081512) +2025-09-16,12:15:42 | INFO | Train Epoch: 13 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.047640 (0.067577) Boundary_loss: 0.013896 (0.013896) Loss: 0.061535 (0.081472) +2025-09-16,12:16:48 | INFO | Train Epoch: 13 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.091169 (0.067623) Boundary_loss: 0.013896 (0.013896) Loss: 0.10506 (0.081519) +2025-09-16,12:17:54 | INFO | Train Epoch: 13 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.084995 (0.067657) Boundary_loss: 0.013895 (0.013896) Loss: 0.098890 (0.081552) +2025-09-16,12:19:00 | INFO | Train Epoch: 13 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.038783 (0.067601) Boundary_loss: 0.013897 (0.013896) Loss: 0.052681 (0.081496) +2025-09-16,12:20:06 | INFO | Train Epoch: 13 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.036696 (0.067541) Boundary_loss: 0.013896 (0.013896) Loss: 0.050592 (0.081436) +2025-09-16,12:21:08 | INFO | Train Epoch: 13 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.082922 (0.067570) Boundary_loss: 0.013894 (0.013896) Loss: 0.096815 (0.081466) +2025-09-16,12:21:08 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-16,12:21:08 | INFO | [Epoch 13] Average Step Time: 0.661s | Average GPU Memory: 30.8 GB +2025-09-16,12:21:08 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-16,12:21:09 | INFO | Starting zero-shot imagenet. +2025-09-16,12:21:09 | INFO | Building zero-shot classifier +2025-09-16,12:21:18 | INFO | Using classifier +2025-09-16,12:22:44 | INFO | Finished zero-shot imagenet. +2025-09-16,12:22:44 | INFO | Eval Epoch: 14 imagenet-zeroshot-val-top1: 0.3339 imagenet-zeroshot-val-top5: 0.6085 +2025-09-16,12:22:46 | INFO | Start epoch 14 +2025-09-16,12:22:48 | INFO | Train Epoch: 14 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.060902 (0.060902) Boundary_loss: 0.013895 (0.013895) Loss: 0.074797 (0.074797) +2025-09-16,12:23:54 | INFO | Train Epoch: 14 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.050305 (0.055604) Boundary_loss: 0.013896 (0.013895) Loss: 0.064201 (0.069499) +2025-09-16,12:24:59 | INFO | Train Epoch: 14 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.049680 (0.053629) Boundary_loss: 0.013896 (0.013896) Loss: 0.063576 (0.067525) +2025-09-16,12:26:05 | INFO | Train Epoch: 14 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.076930 (0.059454) Boundary_loss: 0.013896 (0.013896) Loss: 0.090826 (0.073350) +2025-09-16,12:27:11 | INFO | Train Epoch: 14 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.034331 (0.054430) Boundary_loss: 0.013894 (0.013895) Loss: 0.048225 (0.068325) +2025-09-16,12:28:16 | INFO | Train Epoch: 14 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.096959 (0.061518) Boundary_loss: 0.013896 (0.013895) Loss: 0.11086 (0.075413) +2025-09-16,12:29:22 | INFO | Train Epoch: 14 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.083432 (0.064648) Boundary_loss: 0.013895 (0.013895) Loss: 0.097327 (0.078544) +2025-09-16,12:30:27 | INFO | Train Epoch: 14 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.077516 (0.066257) Boundary_loss: 0.013895 (0.013895) Loss: 0.091411 (0.080152) +2025-09-16,12:31:33 | INFO | Train Epoch: 14 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.059046 (0.065456) Boundary_loss: 0.013895 (0.013895) Loss: 0.072941 (0.079351) +2025-09-16,12:32:39 | INFO | Train Epoch: 14 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.071705 (0.066081) Boundary_loss: 0.013896 (0.013895) Loss: 0.085601 (0.079976) +2025-09-16,12:33:44 | INFO | Train Epoch: 14 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.065730 (0.066049) Boundary_loss: 0.013895 (0.013895) Loss: 0.079625 (0.079944) +2025-09-16,12:34:50 | INFO | Train Epoch: 14 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.055615 (0.065179) Boundary_loss: 0.013895 (0.013895) Loss: 0.069510 (0.079075) +2025-09-16,12:35:56 | INFO | Train Epoch: 14 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.050691 (0.064065) Boundary_loss: 0.013896 (0.013895) Loss: 0.064587 (0.077960) +2025-09-16,12:37:01 | INFO | Train Epoch: 14 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.082195 (0.065360) Boundary_loss: 0.013895 (0.013895) Loss: 0.096090 (0.079255) +2025-09-16,12:38:07 | INFO | Train Epoch: 14 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.079649 (0.066312) Boundary_loss: 0.013897 (0.013895) Loss: 0.093546 (0.080208) +2025-09-16,12:39:13 | INFO | Train Epoch: 14 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.086188 (0.067555) Boundary_loss: 0.013895 (0.013895) Loss: 0.10008 (0.081450) +2025-09-16,12:40:18 | INFO | Train Epoch: 14 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.064007 (0.067346) Boundary_loss: 0.013895 (0.013895) Loss: 0.077903 (0.081241) +2025-09-16,12:41:24 | INFO | Train Epoch: 14 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.045998 (0.066160) Boundary_loss: 0.013895 (0.013895) Loss: 0.059893 (0.080055) +2025-09-16,12:42:30 | INFO | Train Epoch: 14 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.063992 (0.066046) Boundary_loss: 0.013894 (0.013895) Loss: 0.077886 (0.079941) +2025-09-16,12:43:35 | INFO | Train Epoch: 14 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.065486 (0.066018) Boundary_loss: 0.013896 (0.013895) Loss: 0.079382 (0.079913) +2025-09-16,12:44:41 | INFO | Train Epoch: 14 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.077338 (0.066557) Boundary_loss: 0.013895 (0.013895) Loss: 0.091233 (0.080452) +2025-09-16,12:45:47 | INFO | Train Epoch: 14 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.085351 (0.067411) Boundary_loss: 0.013895 (0.013895) Loss: 0.099245 (0.081306) +2025-09-16,12:46:53 | INFO | Train Epoch: 14 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.070653 (0.067552) Boundary_loss: 0.013896 (0.013895) Loss: 0.084549 (0.081447) +2025-09-16,12:47:58 | INFO | Train Epoch: 14 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.057319 (0.067126) Boundary_loss: 0.013896 (0.013895) Loss: 0.071215 (0.081021) +2025-09-16,12:49:04 | INFO | Train Epoch: 14 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.073381 (0.067376) Boundary_loss: 0.013896 (0.013895) Loss: 0.087277 (0.081271) +2025-09-16,12:50:10 | INFO | Train Epoch: 14 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.071131 (0.067520) Boundary_loss: 0.013895 (0.013895) Loss: 0.085026 (0.081416) +2025-09-16,12:51:15 | INFO | Train Epoch: 14 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.062214 (0.067324) Boundary_loss: 0.013894 (0.013895) Loss: 0.076108 (0.081219) +2025-09-16,12:52:21 | INFO | Train Epoch: 14 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.049531 (0.066688) Boundary_loss: 0.013897 (0.013895) Loss: 0.063428 (0.080584) +2025-09-16,12:53:27 | INFO | Train Epoch: 14 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.065202 (0.066637) Boundary_loss: 0.013895 (0.013895) Loss: 0.079098 (0.080533) +2025-09-16,12:54:33 | INFO | Train Epoch: 14 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.064485 (0.066565) Boundary_loss: 0.013897 (0.013895) Loss: 0.078382 (0.080461) +2025-09-16,12:55:38 | INFO | Train Epoch: 14 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.060318 (0.066364) Boundary_loss: 0.013896 (0.013895) Loss: 0.074214 (0.080259) +2025-09-16,12:56:44 | INFO | Train Epoch: 14 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.051179 (0.065889) Boundary_loss: 0.013896 (0.013895) Loss: 0.065075 (0.079785) +2025-09-16,12:57:50 | INFO | Train Epoch: 14 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.051926 (0.065466) Boundary_loss: 0.013896 (0.013895) Loss: 0.065822 (0.079362) +2025-09-16,12:58:55 | INFO | Train Epoch: 14 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.086025 (0.066071) Boundary_loss: 0.013895 (0.013895) Loss: 0.099920 (0.079966) +2025-09-16,13:00:01 | INFO | Train Epoch: 14 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.035441 (0.065196) Boundary_loss: 0.013897 (0.013895) Loss: 0.049338 (0.079091) +2025-09-16,13:01:07 | INFO | Train Epoch: 14 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.072063 (0.065387) Boundary_loss: 0.013895 (0.013895) Loss: 0.085958 (0.079282) +2025-09-16,13:02:12 | INFO | Train Epoch: 14 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.031957 (0.064483) Boundary_loss: 0.013897 (0.013895) Loss: 0.045853 (0.078378) +2025-09-16,13:03:18 | INFO | Train Epoch: 14 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.047407 (0.064034) Boundary_loss: 0.013896 (0.013896) Loss: 0.061304 (0.077929) +2025-09-16,13:04:24 | INFO | Train Epoch: 14 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.071369 (0.064222) Boundary_loss: 0.013896 (0.013896) Loss: 0.085265 (0.078117) +2025-09-16,13:05:30 | INFO | Train Epoch: 14 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.045245 (0.063747) Boundary_loss: 0.013898 (0.013896) Loss: 0.059144 (0.077643) +2025-09-16,13:06:35 | INFO | Train Epoch: 14 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.064004 (0.063754) Boundary_loss: 0.013895 (0.013896) Loss: 0.077898 (0.077649) +2025-09-16,13:07:41 | INFO | Train Epoch: 14 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.072840 (0.063970) Boundary_loss: 0.013896 (0.013896) Loss: 0.086736 (0.077865) +2025-09-16,13:08:47 | INFO | Train Epoch: 14 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.054046 (0.063739) Boundary_loss: 0.013896 (0.013896) Loss: 0.067942 (0.077635) +2025-09-16,13:09:52 | INFO | Train Epoch: 14 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.051653 (0.063464) Boundary_loss: 0.013895 (0.013896) Loss: 0.065549 (0.077360) +2025-09-16,13:10:58 | INFO | Train Epoch: 14 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.079305 (0.063816) Boundary_loss: 0.013895 (0.013896) Loss: 0.093200 (0.077712) +2025-09-16,13:12:04 | INFO | Train Epoch: 14 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.051896 (0.063557) Boundary_loss: 0.013897 (0.013896) Loss: 0.065792 (0.077453) +2025-09-16,13:13:09 | INFO | Train Epoch: 14 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.045062 (0.063164) Boundary_loss: 0.013895 (0.013896) Loss: 0.058958 (0.077059) +2025-09-16,13:14:15 | INFO | Train Epoch: 14 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.059166 (0.063080) Boundary_loss: 0.013896 (0.013896) Loss: 0.073062 (0.076976) +2025-09-16,13:15:21 | INFO | Train Epoch: 14 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.084654 (0.063521) Boundary_loss: 0.013896 (0.013896) Loss: 0.098550 (0.077416) +2025-09-16,13:16:27 | INFO | Train Epoch: 14 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.056166 (0.063374) Boundary_loss: 0.013894 (0.013896) Loss: 0.070061 (0.077269) +2025-09-16,13:17:32 | INFO | Train Epoch: 14 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.042623 (0.062967) Boundary_loss: 0.013896 (0.013896) Loss: 0.056519 (0.076862) +2025-09-16,13:18:38 | INFO | Train Epoch: 14 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.042183 (0.062567) Boundary_loss: 0.013896 (0.013896) Loss: 0.056078 (0.076463) +2025-09-16,13:19:44 | INFO | Train Epoch: 14 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.090984 (0.063103) Boundary_loss: 0.013894 (0.013896) Loss: 0.10488 (0.076999) +2025-09-16,13:20:49 | INFO | Train Epoch: 14 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.057499 (0.063000) Boundary_loss: 0.013895 (0.013896) Loss: 0.071394 (0.076895) +2025-09-16,13:21:55 | INFO | Train Epoch: 14 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.041832 (0.062615) Boundary_loss: 0.013895 (0.013896) Loss: 0.055727 (0.076510) +2025-09-16,13:23:01 | INFO | Train Epoch: 14 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.033235 (0.062090) Boundary_loss: 0.013895 (0.013896) Loss: 0.047130 (0.075986) +2025-09-16,13:24:07 | INFO | Train Epoch: 14 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.048396 (0.061850) Boundary_loss: 0.013895 (0.013896) Loss: 0.062291 (0.075745) +2025-09-16,13:25:12 | INFO | Train Epoch: 14 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.063855 (0.061884) Boundary_loss: 0.013895 (0.013896) Loss: 0.077750 (0.075780) +2025-09-16,13:26:18 | INFO | Train Epoch: 14 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.059107 (0.061837) Boundary_loss: 0.013895 (0.013896) Loss: 0.073002 (0.075733) +2025-09-16,13:27:24 | INFO | Train Epoch: 14 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.069741 (0.061969) Boundary_loss: 0.013896 (0.013896) Loss: 0.083637 (0.075865) +2025-09-16,13:28:29 | INFO | Train Epoch: 14 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.059253 (0.061924) Boundary_loss: 0.013895 (0.013896) Loss: 0.073149 (0.075820) +2025-09-16,13:29:35 | INFO | Train Epoch: 14 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.055628 (0.061823) Boundary_loss: 0.013895 (0.013896) Loss: 0.069523 (0.075718) +2025-09-16,13:30:41 | INFO | Train Epoch: 14 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.058005 (0.061762) Boundary_loss: 0.013895 (0.013896) Loss: 0.071900 (0.075658) +2025-09-16,13:31:47 | INFO | Train Epoch: 14 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.051515 (0.061602) Boundary_loss: 0.013896 (0.013896) Loss: 0.065411 (0.075498) +2025-09-16,13:32:52 | INFO | Train Epoch: 14 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.071347 (0.061752) Boundary_loss: 0.013895 (0.013896) Loss: 0.085243 (0.075648) +2025-09-16,13:33:58 | INFO | Train Epoch: 14 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.061695 (0.061751) Boundary_loss: 0.013896 (0.013896) Loss: 0.075592 (0.075647) +2025-09-16,13:35:04 | INFO | Train Epoch: 14 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.054115 (0.061637) Boundary_loss: 0.013895 (0.013896) Loss: 0.068010 (0.075533) +2025-09-16,13:36:09 | INFO | Train Epoch: 14 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.074773 (0.061830) Boundary_loss: 0.013896 (0.013896) Loss: 0.088669 (0.075726) +2025-09-16,13:37:15 | INFO | Train Epoch: 14 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.038180 (0.061488) Boundary_loss: 0.013896 (0.013896) Loss: 0.052076 (0.075383) +2025-09-16,13:38:21 | INFO | Train Epoch: 14 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.067768 (0.061577) Boundary_loss: 0.013895 (0.013896) Loss: 0.081663 (0.075473) +2025-09-16,13:39:26 | INFO | Train Epoch: 14 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.065660 (0.061635) Boundary_loss: 0.013896 (0.013896) Loss: 0.079556 (0.075530) +2025-09-16,13:40:32 | INFO | Train Epoch: 14 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.069227 (0.061740) Boundary_loss: 0.013896 (0.013896) Loss: 0.083123 (0.075636) +2025-09-16,13:41:38 | INFO | Train Epoch: 14 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.044579 (0.061505) Boundary_loss: 0.013897 (0.013896) Loss: 0.058477 (0.075401) +2025-09-16,13:42:44 | INFO | Train Epoch: 14 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.053874 (0.061402) Boundary_loss: 0.013896 (0.013896) Loss: 0.067770 (0.075298) +2025-09-16,13:43:49 | INFO | Train Epoch: 14 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.076510 (0.061604) Boundary_loss: 0.013895 (0.013896) Loss: 0.090405 (0.075499) +2025-09-16,13:44:55 | INFO | Train Epoch: 14 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.056085 (0.061531) Boundary_loss: 0.013895 (0.013896) Loss: 0.069980 (0.075426) +2025-09-16,13:46:01 | INFO | Train Epoch: 14 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.060499 (0.061518) Boundary_loss: 0.013895 (0.013896) Loss: 0.074394 (0.075413) +2025-09-16,13:47:06 | INFO | Train Epoch: 14 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.030641 (0.061122) Boundary_loss: 0.013895 (0.013896) Loss: 0.044536 (0.075017) +2025-09-16,13:48:12 | INFO | Train Epoch: 14 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.059360 (0.061099) Boundary_loss: 0.013896 (0.013896) Loss: 0.073256 (0.074995) +2025-09-16,13:49:18 | INFO | Train Epoch: 14 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.067038 (0.061174) Boundary_loss: 0.013895 (0.013896) Loss: 0.080933 (0.075069) +2025-09-16,13:50:24 | INFO | Train Epoch: 14 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.067509 (0.061252) Boundary_loss: 0.013895 (0.013896) Loss: 0.081403 (0.075147) +2025-09-16,13:51:29 | INFO | Train Epoch: 14 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.069128 (0.061348) Boundary_loss: 0.013897 (0.013896) Loss: 0.083025 (0.075243) +2025-09-16,13:52:35 | INFO | Train Epoch: 14 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.074367 (0.061505) Boundary_loss: 0.013895 (0.013896) Loss: 0.088262 (0.075400) +2025-09-16,13:53:41 | INFO | Train Epoch: 14 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.068018 (0.061582) Boundary_loss: 0.013894 (0.013896) Loss: 0.081913 (0.075478) +2025-09-16,13:54:46 | INFO | Train Epoch: 14 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.063903 (0.061610) Boundary_loss: 0.013895 (0.013896) Loss: 0.077798 (0.075505) +2025-09-16,13:55:52 | INFO | Train Epoch: 14 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.072409 (0.061735) Boundary_loss: 0.013895 (0.013896) Loss: 0.086304 (0.075631) +2025-09-16,13:56:58 | INFO | Train Epoch: 14 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.070998 (0.061842) Boundary_loss: 0.013896 (0.013896) Loss: 0.084893 (0.075737) +2025-09-16,13:58:04 | INFO | Train Epoch: 14 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.070255 (0.061937) Boundary_loss: 0.013895 (0.013896) Loss: 0.084149 (0.075833) +2025-09-16,13:59:09 | INFO | Train Epoch: 14 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.050472 (0.061808) Boundary_loss: 0.013895 (0.013896) Loss: 0.064367 (0.075704) +2025-09-16,14:00:15 | INFO | Train Epoch: 14 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.075594 (0.061962) Boundary_loss: 0.013895 (0.013896) Loss: 0.089488 (0.075857) +2025-09-16,14:01:21 | INFO | Train Epoch: 14 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.051225 (0.061844) Boundary_loss: 0.013895 (0.013895) Loss: 0.065120 (0.075739) +2025-09-16,14:02:26 | INFO | Train Epoch: 14 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.060308 (0.061827) Boundary_loss: 0.013895 (0.013895) Loss: 0.074203 (0.075722) +2025-09-16,14:03:32 | INFO | Train Epoch: 14 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.047651 (0.061674) Boundary_loss: 0.013896 (0.013896) Loss: 0.061547 (0.075570) +2025-09-16,14:04:38 | INFO | Train Epoch: 14 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.052798 (0.061580) Boundary_loss: 0.013895 (0.013895) Loss: 0.066692 (0.075476) +2025-09-16,14:05:43 | INFO | Train Epoch: 14 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.048389 (0.061441) Boundary_loss: 0.013897 (0.013896) Loss: 0.062286 (0.075337) +2025-09-16,14:06:49 | INFO | Train Epoch: 14 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.067846 (0.061508) Boundary_loss: 0.013896 (0.013896) Loss: 0.081742 (0.075403) +2025-09-16,14:07:55 | INFO | Train Epoch: 14 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.043838 (0.061326) Boundary_loss: 0.013895 (0.013896) Loss: 0.057733 (0.075221) +2025-09-16,14:09:01 | INFO | Train Epoch: 14 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.069758 (0.061412) Boundary_loss: 0.013895 (0.013896) Loss: 0.083653 (0.075307) +2025-09-16,14:10:06 | INFO | Train Epoch: 14 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.045407 (0.061250) Boundary_loss: 0.013895 (0.013896) Loss: 0.059302 (0.075146) +2025-09-16,14:11:12 | INFO | Train Epoch: 14 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.087888 (0.061516) Boundary_loss: 0.013896 (0.013896) Loss: 0.10178 (0.075412) +2025-09-16,14:12:18 | INFO | Train Epoch: 14 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.063656 (0.061538) Boundary_loss: 0.013896 (0.013896) Loss: 0.077552 (0.075433) +2025-09-16,14:13:23 | INFO | Train Epoch: 14 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.067796 (0.061599) Boundary_loss: 0.013896 (0.013896) Loss: 0.081692 (0.075495) +2025-09-16,14:14:29 | INFO | Train Epoch: 14 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.099307 (0.061965) Boundary_loss: 0.013896 (0.013896) Loss: 0.11320 (0.075861) +2025-09-16,14:15:35 | INFO | Train Epoch: 14 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.055717 (0.061905) Boundary_loss: 0.013896 (0.013896) Loss: 0.069613 (0.075801) +2025-09-16,14:16:41 | INFO | Train Epoch: 14 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.038464 (0.061682) Boundary_loss: 0.013895 (0.013896) Loss: 0.052359 (0.075577) +2025-09-16,14:17:46 | INFO | Train Epoch: 14 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.075789 (0.061815) Boundary_loss: 0.013896 (0.013896) Loss: 0.089685 (0.075710) +2025-09-16,14:18:52 | INFO | Train Epoch: 14 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.048485 (0.061690) Boundary_loss: 0.013896 (0.013896) Loss: 0.062381 (0.075586) +2025-09-16,14:19:58 | INFO | Train Epoch: 14 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.061803 (0.061691) Boundary_loss: 0.013896 (0.013896) Loss: 0.075699 (0.075587) +2025-09-16,14:21:04 | INFO | Train Epoch: 14 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.060933 (0.061684) Boundary_loss: 0.013895 (0.013896) Loss: 0.074828 (0.075580) +2025-09-16,14:22:10 | INFO | Train Epoch: 14 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.046091 (0.061543) Boundary_loss: 0.013896 (0.013896) Loss: 0.059987 (0.075438) +2025-09-16,14:23:15 | INFO | Train Epoch: 14 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.088819 (0.061788) Boundary_loss: 0.013896 (0.013896) Loss: 0.10271 (0.075684) +2025-09-16,14:24:21 | INFO | Train Epoch: 14 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.047754 (0.061663) Boundary_loss: 0.013895 (0.013896) Loss: 0.061649 (0.075559) +2025-09-16,14:25:27 | INFO | Train Epoch: 14 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.074156 (0.061774) Boundary_loss: 0.013896 (0.013896) Loss: 0.088052 (0.075669) +2025-09-16,14:26:33 | INFO | Train Epoch: 14 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.043931 (0.061617) Boundary_loss: 0.013896 (0.013896) Loss: 0.057827 (0.075513) +2025-09-16,14:27:38 | INFO | Train Epoch: 14 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.063855 (0.061637) Boundary_loss: 0.013896 (0.013896) Loss: 0.077751 (0.075532) +2025-09-16,14:28:44 | INFO | Train Epoch: 14 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.071035 (0.061718) Boundary_loss: 0.013897 (0.013896) Loss: 0.084932 (0.075613) +2025-09-16,14:29:50 | INFO | Train Epoch: 14 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.049545 (0.061614) Boundary_loss: 0.013894 (0.013896) Loss: 0.063439 (0.075509) +2025-09-16,14:30:56 | INFO | Train Epoch: 14 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.085786 (0.061818) Boundary_loss: 0.013895 (0.013896) Loss: 0.099681 (0.075714) +2025-09-16,14:32:01 | INFO | Train Epoch: 14 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.045227 (0.061679) Boundary_loss: 0.013895 (0.013896) Loss: 0.059122 (0.075575) +2025-09-16,14:33:07 | INFO | Train Epoch: 14 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.058353 (0.061651) Boundary_loss: 0.013895 (0.013896) Loss: 0.072247 (0.075547) +2025-09-16,14:34:13 | INFO | Train Epoch: 14 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.060506 (0.061642) Boundary_loss: 0.013895 (0.013896) Loss: 0.074400 (0.075537) +2025-09-16,14:35:19 | INFO | Train Epoch: 14 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.049159 (0.061539) Boundary_loss: 0.013897 (0.013896) Loss: 0.063055 (0.075435) +2025-09-16,14:36:24 | INFO | Train Epoch: 14 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.057286 (0.061505) Boundary_loss: 0.013895 (0.013896) Loss: 0.071180 (0.075400) +2025-09-16,14:37:30 | INFO | Train Epoch: 14 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.065978 (0.061541) Boundary_loss: 0.013896 (0.013896) Loss: 0.079874 (0.075437) +2025-09-16,14:38:36 | INFO | Train Epoch: 14 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.064987 (0.061569) Boundary_loss: 0.013896 (0.013896) Loss: 0.078882 (0.075464) +2025-09-16,14:39:42 | INFO | Train Epoch: 14 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.064304 (0.061590) Boundary_loss: 0.013895 (0.013896) Loss: 0.078198 (0.075486) +2025-09-16,14:40:47 | INFO | Train Epoch: 14 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.059991 (0.061578) Boundary_loss: 0.013896 (0.013896) Loss: 0.073887 (0.075473) +2025-09-16,14:41:53 | INFO | Train Epoch: 14 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.066050 (0.061613) Boundary_loss: 0.013894 (0.013896) Loss: 0.079944 (0.075508) +2025-09-16,14:42:59 | INFO | Train Epoch: 14 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.040063 (0.061446) Boundary_loss: 0.013895 (0.013896) Loss: 0.053958 (0.075341) +2025-09-16,14:44:04 | INFO | Train Epoch: 14 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.048969 (0.061350) Boundary_loss: 0.013895 (0.013896) Loss: 0.062864 (0.075245) +2025-09-16,14:45:10 | INFO | Train Epoch: 14 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.051109 (0.061271) Boundary_loss: 0.013897 (0.013896) Loss: 0.065006 (0.075167) +2025-09-16,14:46:16 | INFO | Train Epoch: 14 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.059235 (0.061256) Boundary_loss: 0.013895 (0.013896) Loss: 0.073130 (0.075151) +2025-09-16,14:47:21 | INFO | Train Epoch: 14 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.067410 (0.061302) Boundary_loss: 0.013896 (0.013896) Loss: 0.081306 (0.075198) +2025-09-16,14:48:27 | INFO | Train Epoch: 14 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.069823 (0.061366) Boundary_loss: 0.013897 (0.013896) Loss: 0.083720 (0.075261) +2025-09-16,14:49:33 | INFO | Train Epoch: 14 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.047743 (0.061265) Boundary_loss: 0.013895 (0.013896) Loss: 0.061638 (0.075160) +2025-09-16,14:50:38 | INFO | Train Epoch: 14 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.049315 (0.061177) Boundary_loss: 0.013895 (0.013896) Loss: 0.063211 (0.075073) +2025-09-16,14:51:44 | INFO | Train Epoch: 14 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.062966 (0.061190) Boundary_loss: 0.013895 (0.013896) Loss: 0.076862 (0.075086) +2025-09-16,14:52:50 | INFO | Train Epoch: 14 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.053819 (0.061137) Boundary_loss: 0.013896 (0.013896) Loss: 0.067714 (0.075032) +2025-09-16,14:53:56 | INFO | Train Epoch: 14 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.034402 (0.060944) Boundary_loss: 0.013896 (0.013896) Loss: 0.048298 (0.074840) +2025-09-16,14:55:01 | INFO | Train Epoch: 14 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.063296 (0.060961) Boundary_loss: 0.013895 (0.013896) Loss: 0.077191 (0.074857) +2025-09-16,14:56:07 | INFO | Train Epoch: 14 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.054898 (0.060918) Boundary_loss: 0.013896 (0.013896) Loss: 0.068794 (0.074814) +2025-09-16,14:57:13 | INFO | Train Epoch: 14 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.078078 (0.061039) Boundary_loss: 0.013895 (0.013896) Loss: 0.091973 (0.074935) +2025-09-16,14:58:18 | INFO | Train Epoch: 14 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.064350 (0.061062) Boundary_loss: 0.013895 (0.013896) Loss: 0.078245 (0.074958) +2025-09-16,14:59:24 | INFO | Train Epoch: 14 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.049302 (0.060980) Boundary_loss: 0.013896 (0.013896) Loss: 0.063198 (0.074876) +2025-09-16,15:00:30 | INFO | Train Epoch: 14 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.059939 (0.060973) Boundary_loss: 0.013895 (0.013896) Loss: 0.073834 (0.074869) +2025-09-16,15:01:35 | INFO | Train Epoch: 14 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.044932 (0.060863) Boundary_loss: 0.013895 (0.013896) Loss: 0.058827 (0.074759) +2025-09-16,15:02:41 | INFO | Train Epoch: 14 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.064273 (0.060887) Boundary_loss: 0.013895 (0.013896) Loss: 0.078168 (0.074782) +2025-09-16,15:03:47 | INFO | Train Epoch: 14 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.066625 (0.060925) Boundary_loss: 0.013895 (0.013896) Loss: 0.080521 (0.074821) +2025-09-16,15:04:52 | INFO | Train Epoch: 14 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.066179 (0.060961) Boundary_loss: 0.013895 (0.013896) Loss: 0.080075 (0.074856) +2025-09-16,15:05:58 | INFO | Train Epoch: 14 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.068364 (0.061010) Boundary_loss: 0.013896 (0.013896) Loss: 0.082260 (0.074906) +2025-09-16,15:07:04 | INFO | Train Epoch: 14 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.071820 (0.061082) Boundary_loss: 0.013896 (0.013896) Loss: 0.085715 (0.074977) +2025-09-16,15:08:10 | INFO | Train Epoch: 14 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.061051 (0.061081) Boundary_loss: 0.013894 (0.013896) Loss: 0.074945 (0.074977) +2025-09-16,15:09:15 | INFO | Train Epoch: 14 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.073426 (0.061162) Boundary_loss: 0.013896 (0.013896) Loss: 0.087322 (0.075058) +2025-09-16,15:10:21 | INFO | Train Epoch: 14 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.073383 (0.061241) Boundary_loss: 0.013895 (0.013896) Loss: 0.087278 (0.075137) +2025-09-16,15:11:27 | INFO | Train Epoch: 14 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.054566 (0.061198) Boundary_loss: 0.013895 (0.013896) Loss: 0.068461 (0.075094) +2025-09-16,15:12:32 | INFO | Train Epoch: 14 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.068457 (0.061245) Boundary_loss: 0.013896 (0.013896) Loss: 0.082353 (0.075140) +2025-09-16,15:13:38 | INFO | Train Epoch: 14 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.074043 (0.061326) Boundary_loss: 0.013895 (0.013896) Loss: 0.087939 (0.075222) +2025-09-16,15:14:44 | INFO | Train Epoch: 14 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.073074 (0.061401) Boundary_loss: 0.013896 (0.013896) Loss: 0.086970 (0.075296) +2025-09-16,15:15:49 | INFO | Train Epoch: 14 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.052334 (0.061344) Boundary_loss: 0.013895 (0.013896) Loss: 0.066229 (0.075239) +2025-09-16,15:16:55 | INFO | Train Epoch: 14 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.069520 (0.061395) Boundary_loss: 0.013896 (0.013896) Loss: 0.083416 (0.075290) +2025-09-16,15:18:01 | INFO | Train Epoch: 14 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.057095 (0.061368) Boundary_loss: 0.013895 (0.013896) Loss: 0.070991 (0.075264) +2025-09-16,15:19:06 | INFO | Train Epoch: 14 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.079486 (0.061480) Boundary_loss: 0.013895 (0.013896) Loss: 0.093381 (0.075375) +2025-09-16,15:20:12 | INFO | Train Epoch: 14 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.058534 (0.061462) Boundary_loss: 0.013895 (0.013896) Loss: 0.072429 (0.075357) +2025-09-16,15:21:18 | INFO | Train Epoch: 14 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.035910 (0.061306) Boundary_loss: 0.013896 (0.013896) Loss: 0.049805 (0.075202) +2025-09-16,15:22:24 | INFO | Train Epoch: 14 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.053219 (0.061257) Boundary_loss: 0.013896 (0.013896) Loss: 0.067115 (0.075153) +2025-09-16,15:23:29 | INFO | Train Epoch: 14 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.054762 (0.061218) Boundary_loss: 0.013895 (0.013896) Loss: 0.068657 (0.075113) +2025-09-16,15:24:35 | INFO | Train Epoch: 14 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.052990 (0.061169) Boundary_loss: 0.013895 (0.013896) Loss: 0.066885 (0.075064) +2025-09-16,15:25:41 | INFO | Train Epoch: 14 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.067355 (0.061206) Boundary_loss: 0.013896 (0.013896) Loss: 0.081250 (0.075101) +2025-09-16,15:26:46 | INFO | Train Epoch: 14 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.052484 (0.061154) Boundary_loss: 0.013895 (0.013896) Loss: 0.066379 (0.075049) +2025-09-16,15:27:52 | INFO | Train Epoch: 14 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.045459 (0.061062) Boundary_loss: 0.013896 (0.013896) Loss: 0.059355 (0.074957) +2025-09-16,15:28:58 | INFO | Train Epoch: 14 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.042185 (0.060951) Boundary_loss: 0.013896 (0.013896) Loss: 0.056081 (0.074847) +2025-09-16,15:30:04 | INFO | Train Epoch: 14 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.039627 (0.060827) Boundary_loss: 0.013895 (0.013896) Loss: 0.053522 (0.074723) +2025-09-16,15:31:09 | INFO | Train Epoch: 14 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.059920 (0.060822) Boundary_loss: 0.013895 (0.013896) Loss: 0.073816 (0.074717) +2025-09-16,15:32:15 | INFO | Train Epoch: 14 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.069357 (0.060871) Boundary_loss: 0.013894 (0.013896) Loss: 0.083251 (0.074767) +2025-09-16,15:33:21 | INFO | Train Epoch: 14 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.059977 (0.060866) Boundary_loss: 0.013895 (0.013896) Loss: 0.073871 (0.074761) +2025-09-16,15:34:26 | INFO | Train Epoch: 14 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.079605 (0.060972) Boundary_loss: 0.013896 (0.013896) Loss: 0.093500 (0.074868) +2025-09-16,15:35:32 | INFO | Train Epoch: 14 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.081891 (0.061091) Boundary_loss: 0.013895 (0.013896) Loss: 0.095786 (0.074986) +2025-09-16,15:36:38 | INFO | Train Epoch: 14 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.052445 (0.061042) Boundary_loss: 0.013896 (0.013896) Loss: 0.066342 (0.074938) +2025-09-16,15:37:44 | INFO | Train Epoch: 14 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.056093 (0.061014) Boundary_loss: 0.013896 (0.013896) Loss: 0.069989 (0.074910) +2025-09-16,15:38:49 | INFO | Train Epoch: 14 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.050287 (0.060955) Boundary_loss: 0.013895 (0.013896) Loss: 0.064182 (0.074850) +2025-09-16,15:39:55 | INFO | Train Epoch: 14 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.077289 (0.061045) Boundary_loss: 0.013896 (0.013896) Loss: 0.091185 (0.074941) +2025-09-16,15:41:01 | INFO | Train Epoch: 14 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.069759 (0.061093) Boundary_loss: 0.013895 (0.013896) Loss: 0.083654 (0.074988) +2025-09-16,15:42:06 | INFO | Train Epoch: 14 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.075520 (0.061172) Boundary_loss: 0.013896 (0.013896) Loss: 0.089415 (0.075067) +2025-09-16,15:43:12 | INFO | Train Epoch: 14 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.061396 (0.061173) Boundary_loss: 0.013895 (0.013896) Loss: 0.075292 (0.075068) +2025-09-16,15:44:18 | INFO | Train Epoch: 14 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.055873 (0.061144) Boundary_loss: 0.013895 (0.013896) Loss: 0.069767 (0.075040) +2025-09-16,15:45:23 | INFO | Train Epoch: 14 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.044031 (0.061052) Boundary_loss: 0.013896 (0.013896) Loss: 0.057927 (0.074948) +2025-09-16,15:46:29 | INFO | Train Epoch: 14 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.096636 (0.061243) Boundary_loss: 0.013895 (0.013896) Loss: 0.11053 (0.075138) +2025-09-16,15:47:35 | INFO | Train Epoch: 14 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.059739 (0.061235) Boundary_loss: 0.013895 (0.013896) Loss: 0.073634 (0.075130) +2025-09-16,15:48:41 | INFO | Train Epoch: 14 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.071452 (0.061289) Boundary_loss: 0.013895 (0.013896) Loss: 0.085347 (0.075184) +2025-09-16,15:49:46 | INFO | Train Epoch: 14 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.068723 (0.061328) Boundary_loss: 0.013895 (0.013896) Loss: 0.082618 (0.075223) +2025-09-16,15:50:52 | INFO | Train Epoch: 14 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.051787 (0.061278) Boundary_loss: 0.013895 (0.013896) Loss: 0.065682 (0.075173) +2025-09-16,15:51:58 | INFO | Train Epoch: 14 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.075155 (0.061350) Boundary_loss: 0.013895 (0.013895) Loss: 0.089049 (0.075246) +2025-09-16,15:53:03 | INFO | Train Epoch: 14 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.048973 (0.061286) Boundary_loss: 0.013895 (0.013895) Loss: 0.062868 (0.075181) +2025-09-16,15:54:09 | INFO | Train Epoch: 14 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.073323 (0.061348) Boundary_loss: 0.013895 (0.013895) Loss: 0.087218 (0.075243) +2025-09-16,15:55:15 | INFO | Train Epoch: 14 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.034670 (0.061211) Boundary_loss: 0.013894 (0.013895) Loss: 0.048565 (0.075107) +2025-09-16,15:56:21 | INFO | Train Epoch: 14 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.065925 (0.061235) Boundary_loss: 0.013894 (0.013895) Loss: 0.079819 (0.075131) +2025-09-16,15:57:26 | INFO | Train Epoch: 14 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.071944 (0.061290) Boundary_loss: 0.013897 (0.013895) Loss: 0.085841 (0.075185) +2025-09-16,15:58:32 | INFO | Train Epoch: 14 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.047706 (0.061221) Boundary_loss: 0.013896 (0.013895) Loss: 0.061602 (0.075116) +2025-09-16,15:59:38 | INFO | Train Epoch: 14 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.053804 (0.061184) Boundary_loss: 0.013896 (0.013895) Loss: 0.067699 (0.075079) +2025-09-16,16:00:44 | INFO | Train Epoch: 14 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.048194 (0.061119) Boundary_loss: 0.013895 (0.013895) Loss: 0.062090 (0.075014) +2025-09-16,16:01:49 | INFO | Train Epoch: 14 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.078166 (0.061204) Boundary_loss: 0.013894 (0.013895) Loss: 0.092060 (0.075099) +2025-09-16,16:02:55 | INFO | Train Epoch: 14 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.061836 (0.061207) Boundary_loss: 0.013896 (0.013895) Loss: 0.075732 (0.075102) +2025-09-16,16:04:01 | INFO | Train Epoch: 14 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.085783 (0.061328) Boundary_loss: 0.013895 (0.013895) Loss: 0.099678 (0.075223) +2025-09-16,16:05:07 | INFO | Train Epoch: 14 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.046976 (0.061257) Boundary_loss: 0.013895 (0.013895) Loss: 0.060871 (0.075153) +2025-09-16,16:06:12 | INFO | Train Epoch: 14 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.049477 (0.061200) Boundary_loss: 0.013895 (0.013895) Loss: 0.063373 (0.075095) +2025-09-16,16:07:18 | INFO | Train Epoch: 14 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.054927 (0.061170) Boundary_loss: 0.013896 (0.013895) Loss: 0.068823 (0.075065) +2025-09-16,16:08:24 | INFO | Train Epoch: 14 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.075295 (0.061238) Boundary_loss: 0.013896 (0.013895) Loss: 0.089191 (0.075133) +2025-09-16,16:09:29 | INFO | Train Epoch: 14 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.060495 (0.061234) Boundary_loss: 0.013895 (0.013895) Loss: 0.074390 (0.075130) +2025-09-16,16:10:35 | INFO | Train Epoch: 14 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.055071 (0.061205) Boundary_loss: 0.013895 (0.013895) Loss: 0.068966 (0.075100) +2025-09-16,16:11:41 | INFO | Train Epoch: 14 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.062746 (0.061212) Boundary_loss: 0.013895 (0.013895) Loss: 0.076641 (0.075108) +2025-09-16,16:12:46 | INFO | Train Epoch: 14 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.068341 (0.061246) Boundary_loss: 0.013894 (0.013895) Loss: 0.082236 (0.075141) +2025-09-16,16:13:52 | INFO | Train Epoch: 14 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.068246 (0.061279) Boundary_loss: 0.013895 (0.013895) Loss: 0.082142 (0.075174) +2025-09-16,16:14:58 | INFO | Train Epoch: 14 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.049570 (0.061224) Boundary_loss: 0.013895 (0.013895) Loss: 0.063465 (0.075119) +2025-09-16,16:16:04 | INFO | Train Epoch: 14 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.051635 (0.061179) Boundary_loss: 0.013895 (0.013895) Loss: 0.065531 (0.075075) +2025-09-16,16:17:09 | INFO | Train Epoch: 14 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.060106 (0.061174) Boundary_loss: 0.013896 (0.013895) Loss: 0.074002 (0.075070) +2025-09-16,16:18:15 | INFO | Train Epoch: 14 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.053981 (0.061141) Boundary_loss: 0.013896 (0.013895) Loss: 0.067876 (0.075036) +2025-09-16,16:19:21 | INFO | Train Epoch: 14 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.095474 (0.061299) Boundary_loss: 0.013896 (0.013895) Loss: 0.10937 (0.075194) +2025-09-16,16:20:26 | INFO | Train Epoch: 14 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.076851 (0.061370) Boundary_loss: 0.013897 (0.013895) Loss: 0.090748 (0.075266) +2025-09-16,16:21:32 | INFO | Train Epoch: 14 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.039013 (0.061268) Boundary_loss: 0.013895 (0.013895) Loss: 0.052909 (0.075164) +2025-09-16,16:22:38 | INFO | Train Epoch: 14 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.054997 (0.061240) Boundary_loss: 0.013897 (0.013895) Loss: 0.068893 (0.075135) +2025-09-16,16:23:44 | INFO | Train Epoch: 14 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.061552 (0.061241) Boundary_loss: 0.013895 (0.013895) Loss: 0.075447 (0.075137) +2025-09-16,16:24:49 | INFO | Train Epoch: 14 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.053987 (0.061208) Boundary_loss: 0.013896 (0.013895) Loss: 0.067882 (0.075104) +2025-09-16,16:25:55 | INFO | Train Epoch: 14 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.041953 (0.061122) Boundary_loss: 0.013895 (0.013895) Loss: 0.055848 (0.075018) +2025-09-16,16:27:01 | INFO | Train Epoch: 14 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.053199 (0.061087) Boundary_loss: 0.013896 (0.013895) Loss: 0.067095 (0.074982) +2025-09-16,16:28:06 | INFO | Train Epoch: 14 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.087269 (0.061203) Boundary_loss: 0.013895 (0.013895) Loss: 0.10116 (0.075099) +2025-09-16,16:29:12 | INFO | Train Epoch: 14 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.057535 (0.061187) Boundary_loss: 0.013895 (0.013895) Loss: 0.071430 (0.075082) +2025-09-16,16:30:18 | INFO | Train Epoch: 14 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.058430 (0.061175) Boundary_loss: 0.013896 (0.013895) Loss: 0.072326 (0.075070) +2025-09-16,16:31:23 | INFO | Train Epoch: 14 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.043902 (0.061099) Boundary_loss: 0.013895 (0.013895) Loss: 0.057797 (0.074994) +2025-09-16,16:32:29 | INFO | Train Epoch: 14 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.064740 (0.061115) Boundary_loss: 0.013895 (0.013895) Loss: 0.078634 (0.075010) +2025-09-16,16:33:35 | INFO | Train Epoch: 14 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.061208 (0.061115) Boundary_loss: 0.013895 (0.013895) Loss: 0.075103 (0.075011) +2025-09-16,16:34:40 | INFO | Train Epoch: 14 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.047535 (0.061056) Boundary_loss: 0.013895 (0.013895) Loss: 0.061430 (0.074952) +2025-09-16,16:35:46 | INFO | Train Epoch: 14 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.075889 (0.061120) Boundary_loss: 0.013896 (0.013895) Loss: 0.089784 (0.075016) +2025-09-16,16:36:52 | INFO | Train Epoch: 14 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.048774 (0.061067) Boundary_loss: 0.013895 (0.013895) Loss: 0.062670 (0.074963) +2025-09-16,16:37:57 | INFO | Train Epoch: 14 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.050601 (0.061023) Boundary_loss: 0.013894 (0.013895) Loss: 0.064495 (0.074918) +2025-09-16,16:39:03 | INFO | Train Epoch: 14 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.032886 (0.060903) Boundary_loss: 0.013896 (0.013895) Loss: 0.046782 (0.074798) +2025-09-16,16:40:09 | INFO | Train Epoch: 14 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.052175 (0.060866) Boundary_loss: 0.013895 (0.013895) Loss: 0.066069 (0.074761) +2025-09-16,16:41:14 | INFO | Train Epoch: 14 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.040999 (0.060782) Boundary_loss: 0.013895 (0.013895) Loss: 0.054894 (0.074678) +2025-09-16,16:42:20 | INFO | Train Epoch: 14 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.089743 (0.060904) Boundary_loss: 0.013896 (0.013895) Loss: 0.10364 (0.074799) +2025-09-16,16:43:26 | INFO | Train Epoch: 14 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.046062 (0.060842) Boundary_loss: 0.013896 (0.013895) Loss: 0.059958 (0.074737) +2025-09-16,16:44:32 | INFO | Train Epoch: 14 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.057954 (0.060830) Boundary_loss: 0.013895 (0.013895) Loss: 0.071850 (0.074725) +2025-09-16,16:45:37 | INFO | Train Epoch: 14 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.064384 (0.060844) Boundary_loss: 0.013894 (0.013895) Loss: 0.078278 (0.074740) +2025-09-16,16:46:43 | INFO | Train Epoch: 14 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.058406 (0.060834) Boundary_loss: 0.013896 (0.013895) Loss: 0.072302 (0.074730) +2025-09-16,16:47:49 | INFO | Train Epoch: 14 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.049234 (0.060787) Boundary_loss: 0.013896 (0.013895) Loss: 0.063130 (0.074682) +2025-09-16,16:48:54 | INFO | Train Epoch: 14 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.061195 (0.060788) Boundary_loss: 0.013895 (0.013895) Loss: 0.075091 (0.074684) +2025-09-16,16:50:00 | INFO | Train Epoch: 14 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.056321 (0.060770) Boundary_loss: 0.013895 (0.013895) Loss: 0.070217 (0.074666) +2025-09-16,16:51:06 | INFO | Train Epoch: 14 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.048583 (0.060721) Boundary_loss: 0.013894 (0.013895) Loss: 0.062477 (0.074616) +2025-09-16,16:52:11 | INFO | Train Epoch: 14 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.060871 (0.060721) Boundary_loss: 0.013895 (0.013895) Loss: 0.074767 (0.074617) +2025-09-16,16:53:17 | INFO | Train Epoch: 14 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.051848 (0.060685) Boundary_loss: 0.013897 (0.013895) Loss: 0.065744 (0.074581) +2025-09-16,16:54:23 | INFO | Train Epoch: 14 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.044459 (0.060620) Boundary_loss: 0.013896 (0.013895) Loss: 0.058355 (0.074516) +2025-09-16,16:55:28 | INFO | Train Epoch: 14 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.079103 (0.060694) Boundary_loss: 0.013895 (0.013895) Loss: 0.092998 (0.074590) +2025-09-16,16:56:34 | INFO | Train Epoch: 14 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.059996 (0.060691) Boundary_loss: 0.013896 (0.013895) Loss: 0.073892 (0.074587) +2025-09-16,16:57:40 | INFO | Train Epoch: 14 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.058173 (0.060681) Boundary_loss: 0.013895 (0.013895) Loss: 0.072068 (0.074577) +2025-09-16,16:58:46 | INFO | Train Epoch: 14 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.054314 (0.060656) Boundary_loss: 0.013896 (0.013895) Loss: 0.068210 (0.074552) +2025-09-16,16:59:51 | INFO | Train Epoch: 14 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.043610 (0.060589) Boundary_loss: 0.013895 (0.013895) Loss: 0.057505 (0.074485) +2025-09-16,17:00:57 | INFO | Train Epoch: 14 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.035082 (0.060489) Boundary_loss: 0.013896 (0.013895) Loss: 0.048978 (0.074385) +2025-09-16,17:02:03 | INFO | Train Epoch: 14 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.062161 (0.060496) Boundary_loss: 0.013896 (0.013895) Loss: 0.076058 (0.074391) +2025-09-16,17:03:08 | INFO | Train Epoch: 14 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.050403 (0.060456) Boundary_loss: 0.013896 (0.013895) Loss: 0.064299 (0.074352) +2025-09-16,17:04:14 | INFO | Train Epoch: 14 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.039149 (0.060374) Boundary_loss: 0.013895 (0.013895) Loss: 0.053044 (0.074269) +2025-09-16,17:05:20 | INFO | Train Epoch: 14 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.070783 (0.060414) Boundary_loss: 0.013895 (0.013895) Loss: 0.084679 (0.074309) +2025-09-16,17:06:25 | INFO | Train Epoch: 14 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.047625 (0.060365) Boundary_loss: 0.013896 (0.013895) Loss: 0.061521 (0.074260) +2025-09-16,17:07:31 | INFO | Train Epoch: 14 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.042050 (0.060295) Boundary_loss: 0.013895 (0.013895) Loss: 0.055944 (0.074190) +2025-09-16,17:08:37 | INFO | Train Epoch: 14 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.094836 (0.060426) Boundary_loss: 0.013894 (0.013895) Loss: 0.10873 (0.074322) +2025-09-16,17:09:43 | INFO | Train Epoch: 14 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.099075 (0.060573) Boundary_loss: 0.013896 (0.013895) Loss: 0.11297 (0.074469) +2025-09-16,17:10:49 | INFO | Train Epoch: 14 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.054003 (0.060548) Boundary_loss: 0.013895 (0.013895) Loss: 0.067898 (0.074444) +2025-09-16,17:11:55 | INFO | Train Epoch: 14 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.044053 (0.060486) Boundary_loss: 0.013897 (0.013895) Loss: 0.057949 (0.074382) +2025-09-16,17:13:00 | INFO | Train Epoch: 14 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.061887 (0.060491) Boundary_loss: 0.013897 (0.013895) Loss: 0.075784 (0.074387) +2025-09-16,17:14:06 | INFO | Train Epoch: 14 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.064871 (0.060508) Boundary_loss: 0.013895 (0.013895) Loss: 0.078766 (0.074403) +2025-09-16,17:15:12 | INFO | Train Epoch: 14 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.040772 (0.060434) Boundary_loss: 0.013894 (0.013895) Loss: 0.054666 (0.074330) +2025-09-16,17:16:18 | INFO | Train Epoch: 14 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.10022 (0.060582) Boundary_loss: 0.013896 (0.013895) Loss: 0.11412 (0.074478) +2025-09-16,17:17:24 | INFO | Train Epoch: 14 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.055513 (0.060563) Boundary_loss: 0.013895 (0.013895) Loss: 0.069408 (0.074459) +2025-09-16,17:18:29 | INFO | Train Epoch: 14 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.068089 (0.060591) Boundary_loss: 0.013896 (0.013895) Loss: 0.081984 (0.074487) +2025-09-16,17:19:35 | INFO | Train Epoch: 14 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.073159 (0.060637) Boundary_loss: 0.013895 (0.013895) Loss: 0.087054 (0.074533) +2025-09-16,17:20:41 | INFO | Train Epoch: 14 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.053939 (0.060613) Boundary_loss: 0.013897 (0.013895) Loss: 0.067836 (0.074508) +2025-09-16,17:21:47 | INFO | Train Epoch: 14 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.094321 (0.060736) Boundary_loss: 0.013896 (0.013895) Loss: 0.10822 (0.074631) +2025-09-16,17:22:53 | INFO | Train Epoch: 14 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.062807 (0.060743) Boundary_loss: 0.013895 (0.013895) Loss: 0.076702 (0.074639) +2025-09-16,17:23:58 | INFO | Train Epoch: 14 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.084452 (0.060829) Boundary_loss: 0.013895 (0.013895) Loss: 0.098347 (0.074725) +2025-09-16,17:25:04 | INFO | Train Epoch: 14 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.042912 (0.060765) Boundary_loss: 0.013897 (0.013895) Loss: 0.056808 (0.074660) +2025-09-16,17:26:10 | INFO | Train Epoch: 14 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.061333 (0.060767) Boundary_loss: 0.013895 (0.013895) Loss: 0.075228 (0.074662) +2025-09-16,17:27:16 | INFO | Train Epoch: 14 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.062896 (0.060774) Boundary_loss: 0.013895 (0.013895) Loss: 0.076791 (0.074670) +2025-09-16,17:28:22 | INFO | Train Epoch: 14 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.061324 (0.060776) Boundary_loss: 0.013895 (0.013895) Loss: 0.075219 (0.074672) +2025-09-16,17:29:28 | INFO | Train Epoch: 14 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.058534 (0.060768) Boundary_loss: 0.013896 (0.013895) Loss: 0.072430 (0.074664) +2025-09-16,17:30:33 | INFO | Train Epoch: 14 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.046147 (0.060716) Boundary_loss: 0.013895 (0.013895) Loss: 0.060042 (0.074612) +2025-09-16,17:31:39 | INFO | Train Epoch: 14 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.049500 (0.060677) Boundary_loss: 0.013896 (0.013895) Loss: 0.063396 (0.074572) +2025-09-16,17:32:45 | INFO | Train Epoch: 14 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.063327 (0.060686) Boundary_loss: 0.013896 (0.013895) Loss: 0.077223 (0.074582) +2025-09-16,17:33:51 | INFO | Train Epoch: 14 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.077750 (0.060746) Boundary_loss: 0.013894 (0.013895) Loss: 0.091645 (0.074641) +2025-09-16,17:34:57 | INFO | Train Epoch: 14 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.069011 (0.060775) Boundary_loss: 0.013895 (0.013895) Loss: 0.082906 (0.074670) +2025-09-16,17:36:02 | INFO | Train Epoch: 14 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.058553 (0.060767) Boundary_loss: 0.013897 (0.013895) Loss: 0.072450 (0.074663) +2025-09-16,17:37:08 | INFO | Train Epoch: 14 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.063913 (0.060778) Boundary_loss: 0.013894 (0.013895) Loss: 0.077807 (0.074674) +2025-09-16,17:38:14 | INFO | Train Epoch: 14 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.060620 (0.060778) Boundary_loss: 0.013896 (0.013895) Loss: 0.074516 (0.074673) +2025-09-16,17:39:20 | INFO | Train Epoch: 14 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.073931 (0.060823) Boundary_loss: 0.013894 (0.013895) Loss: 0.087826 (0.074718) +2025-09-16,17:40:26 | INFO | Train Epoch: 14 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.088636 (0.060918) Boundary_loss: 0.013896 (0.013895) Loss: 0.10253 (0.074814) +2025-09-16,17:41:32 | INFO | Train Epoch: 14 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.049590 (0.060880) Boundary_loss: 0.013895 (0.013895) Loss: 0.063485 (0.074775) +2025-09-16,17:42:37 | INFO | Train Epoch: 14 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.040638 (0.060811) Boundary_loss: 0.013895 (0.013895) Loss: 0.054533 (0.074706) +2025-09-16,17:43:43 | INFO | Train Epoch: 14 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.056323 (0.060795) Boundary_loss: 0.013895 (0.013895) Loss: 0.070218 (0.074691) +2025-09-16,17:44:49 | INFO | Train Epoch: 14 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.045925 (0.060745) Boundary_loss: 0.013896 (0.013895) Loss: 0.059821 (0.074640) +2025-09-16,17:45:55 | INFO | Train Epoch: 14 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.075966 (0.060796) Boundary_loss: 0.013895 (0.013895) Loss: 0.089861 (0.074692) +2025-09-16,17:47:01 | INFO | Train Epoch: 14 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.060999 (0.060797) Boundary_loss: 0.013895 (0.013895) Loss: 0.074894 (0.074692) +2025-09-16,17:48:06 | INFO | Train Epoch: 14 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.074223 (0.060842) Boundary_loss: 0.013895 (0.013895) Loss: 0.088119 (0.074738) +2025-09-16,17:49:12 | INFO | Train Epoch: 14 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.050196 (0.060806) Boundary_loss: 0.013895 (0.013895) Loss: 0.064091 (0.074702) +2025-09-16,17:50:18 | INFO | Train Epoch: 14 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.065628 (0.060823) Boundary_loss: 0.013895 (0.013895) Loss: 0.079523 (0.074718) +2025-09-16,17:51:24 | INFO | Train Epoch: 14 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.046169 (0.060774) Boundary_loss: 0.013896 (0.013895) Loss: 0.060065 (0.074669) +2025-09-16,17:52:30 | INFO | Train Epoch: 14 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.066129 (0.060792) Boundary_loss: 0.013896 (0.013895) Loss: 0.080025 (0.074687) +2025-09-16,17:53:36 | INFO | Train Epoch: 14 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.064290 (0.060803) Boundary_loss: 0.013894 (0.013895) Loss: 0.078184 (0.074699) +2025-09-16,17:54:41 | INFO | Train Epoch: 14 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.044367 (0.060749) Boundary_loss: 0.013897 (0.013895) Loss: 0.058264 (0.074645) +2025-09-16,17:55:47 | INFO | Train Epoch: 14 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.040056 (0.060681) Boundary_loss: 0.013894 (0.013895) Loss: 0.053951 (0.074577) +2025-09-16,17:56:53 | INFO | Train Epoch: 14 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.078116 (0.060738) Boundary_loss: 0.013896 (0.013895) Loss: 0.092013 (0.074634) +2025-09-16,17:57:59 | INFO | Train Epoch: 14 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.051793 (0.060709) Boundary_loss: 0.013895 (0.013895) Loss: 0.065688 (0.074605) +2025-09-16,17:59:05 | INFO | Train Epoch: 14 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.039704 (0.060641) Boundary_loss: 0.013895 (0.013895) Loss: 0.053599 (0.074536) +2025-09-16,18:00:11 | INFO | Train Epoch: 14 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.040290 (0.060575) Boundary_loss: 0.013896 (0.013895) Loss: 0.054186 (0.074470) +2025-09-16,18:01:16 | INFO | Train Epoch: 14 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.032999 (0.060486) Boundary_loss: 0.013896 (0.013895) Loss: 0.046895 (0.074381) +2025-09-16,18:02:22 | INFO | Train Epoch: 14 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.056701 (0.060474) Boundary_loss: 0.013896 (0.013895) Loss: 0.070596 (0.074369) +2025-09-16,18:03:28 | INFO | Train Epoch: 14 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.061150 (0.060476) Boundary_loss: 0.013894 (0.013895) Loss: 0.075044 (0.074371) +2025-09-16,18:04:34 | INFO | Train Epoch: 14 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.064052 (0.060487) Boundary_loss: 0.013897 (0.013895) Loss: 0.077948 (0.074383) +2025-09-16,18:05:40 | INFO | Train Epoch: 14 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.064338 (0.060500) Boundary_loss: 0.013896 (0.013895) Loss: 0.078234 (0.074395) +2025-09-16,18:06:46 | INFO | Train Epoch: 14 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.061176 (0.060502) Boundary_loss: 0.013895 (0.013895) Loss: 0.075071 (0.074397) +2025-09-16,18:07:51 | INFO | Train Epoch: 14 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.070849 (0.060535) Boundary_loss: 0.013896 (0.013895) Loss: 0.084745 (0.074430) +2025-09-16,18:08:57 | INFO | Train Epoch: 14 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.074750 (0.060579) Boundary_loss: 0.013896 (0.013895) Loss: 0.088646 (0.074475) +2025-09-16,18:10:03 | INFO | Train Epoch: 14 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.051656 (0.060551) Boundary_loss: 0.013895 (0.013895) Loss: 0.065552 (0.074447) +2025-09-16,18:11:08 | INFO | Train Epoch: 14 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.053740 (0.060530) Boundary_loss: 0.013895 (0.013895) Loss: 0.067635 (0.074425) +2025-09-16,18:12:14 | INFO | Train Epoch: 14 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.043472 (0.060477) Boundary_loss: 0.013895 (0.013895) Loss: 0.057367 (0.074372) +2025-09-16,18:13:20 | INFO | Train Epoch: 14 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.049076 (0.060441) Boundary_loss: 0.013896 (0.013895) Loss: 0.062972 (0.074337) +2025-09-16,18:14:26 | INFO | Train Epoch: 14 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.051658 (0.060414) Boundary_loss: 0.013895 (0.013895) Loss: 0.065553 (0.074309) +2025-09-16,18:15:31 | INFO | Train Epoch: 14 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.065527 (0.060430) Boundary_loss: 0.013895 (0.013895) Loss: 0.079422 (0.074325) +2025-09-16,18:16:37 | INFO | Train Epoch: 14 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.072410 (0.060467) Boundary_loss: 0.013896 (0.013895) Loss: 0.086306 (0.074362) +2025-09-16,18:17:43 | INFO | Train Epoch: 14 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.068670 (0.060492) Boundary_loss: 0.013895 (0.013895) Loss: 0.082565 (0.074387) +2025-09-16,18:18:48 | INFO | Train Epoch: 14 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.061234 (0.060494) Boundary_loss: 0.013895 (0.013895) Loss: 0.075129 (0.074390) +2025-09-16,18:19:54 | INFO | Train Epoch: 14 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.036166 (0.060420) Boundary_loss: 0.013895 (0.013895) Loss: 0.050061 (0.074315) +2025-09-16,18:21:00 | INFO | Train Epoch: 14 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.052535 (0.060396) Boundary_loss: 0.013895 (0.013895) Loss: 0.066429 (0.074291) +2025-09-16,18:22:06 | INFO | Train Epoch: 14 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.054092 (0.060377) Boundary_loss: 0.013896 (0.013895) Loss: 0.067988 (0.074272) +2025-09-16,18:23:11 | INFO | Train Epoch: 14 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.082220 (0.060443) Boundary_loss: 0.013896 (0.013895) Loss: 0.096116 (0.074338) +2025-09-16,18:24:17 | INFO | Train Epoch: 14 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.045784 (0.060399) Boundary_loss: 0.013895 (0.013895) Loss: 0.059679 (0.074294) +2025-09-16,18:25:23 | INFO | Train Epoch: 14 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.047487 (0.060360) Boundary_loss: 0.013895 (0.013895) Loss: 0.061382 (0.074255) +2025-09-16,18:26:29 | INFO | Train Epoch: 14 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.080393 (0.060420) Boundary_loss: 0.013895 (0.013895) Loss: 0.094288 (0.074315) +2025-09-16,18:27:34 | INFO | Train Epoch: 14 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.043950 (0.060371) Boundary_loss: 0.013895 (0.013895) Loss: 0.057845 (0.074266) +2025-09-16,18:28:40 | INFO | Train Epoch: 14 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.066707 (0.060389) Boundary_loss: 0.013896 (0.013895) Loss: 0.080604 (0.074285) +2025-09-16,18:29:46 | INFO | Train Epoch: 14 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.075435 (0.060434) Boundary_loss: 0.013895 (0.013895) Loss: 0.089330 (0.074330) +2025-09-16,18:30:52 | INFO | Train Epoch: 14 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.047000 (0.060394) Boundary_loss: 0.013895 (0.013895) Loss: 0.060895 (0.074290) +2025-09-16,18:31:57 | INFO | Train Epoch: 14 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.089955 (0.060482) Boundary_loss: 0.013895 (0.013895) Loss: 0.10385 (0.074377) +2025-09-16,18:33:03 | INFO | Train Epoch: 14 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.062484 (0.060488) Boundary_loss: 0.013896 (0.013895) Loss: 0.076380 (0.074383) +2025-09-16,18:34:09 | INFO | Train Epoch: 14 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.050100 (0.060457) Boundary_loss: 0.013898 (0.013895) Loss: 0.063998 (0.074353) +2025-09-16,18:35:15 | INFO | Train Epoch: 14 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.068162 (0.060480) Boundary_loss: 0.013896 (0.013895) Loss: 0.082058 (0.074375) +2025-09-16,18:36:21 | INFO | Train Epoch: 14 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.073420 (0.060518) Boundary_loss: 0.013895 (0.013895) Loss: 0.087314 (0.074413) +2025-09-16,18:37:26 | INFO | Train Epoch: 14 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.056121 (0.060505) Boundary_loss: 0.013895 (0.013895) Loss: 0.070015 (0.074400) +2025-09-16,18:38:32 | INFO | Train Epoch: 14 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.053986 (0.060486) Boundary_loss: 0.013896 (0.013895) Loss: 0.067881 (0.074381) +2025-09-16,18:39:38 | INFO | Train Epoch: 14 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.061543 (0.060489) Boundary_loss: 0.013895 (0.013895) Loss: 0.075437 (0.074384) +2025-09-16,18:40:44 | INFO | Train Epoch: 14 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.074348 (0.060529) Boundary_loss: 0.013896 (0.013895) Loss: 0.088244 (0.074424) +2025-09-16,18:41:49 | INFO | Train Epoch: 14 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.083532 (0.060595) Boundary_loss: 0.013895 (0.013895) Loss: 0.097427 (0.074491) +2025-09-16,18:42:55 | INFO | Train Epoch: 14 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.053290 (0.060574) Boundary_loss: 0.013896 (0.013895) Loss: 0.067186 (0.074470) +2025-09-16,18:44:01 | INFO | Train Epoch: 14 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.094614 (0.060672) Boundary_loss: 0.013895 (0.013895) Loss: 0.10851 (0.074567) +2025-09-16,18:45:07 | INFO | Train Epoch: 14 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.071600 (0.060703) Boundary_loss: 0.013895 (0.013895) Loss: 0.085495 (0.074598) +2025-09-16,18:46:13 | INFO | Train Epoch: 14 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.052304 (0.060679) Boundary_loss: 0.013895 (0.013895) Loss: 0.066199 (0.074575) +2025-09-16,18:47:18 | INFO | Train Epoch: 14 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.029182 (0.060590) Boundary_loss: 0.013896 (0.013895) Loss: 0.043078 (0.074485) +2025-09-16,18:48:24 | INFO | Train Epoch: 14 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.063177 (0.060597) Boundary_loss: 0.013896 (0.013895) Loss: 0.077073 (0.074492) +2025-09-16,18:49:30 | INFO | Train Epoch: 14 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.077609 (0.060645) Boundary_loss: 0.013897 (0.013895) Loss: 0.091506 (0.074540) +2025-09-16,18:50:36 | INFO | Train Epoch: 14 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.051047 (0.060618) Boundary_loss: 0.013894 (0.013895) Loss: 0.064941 (0.074513) +2025-09-16,18:51:42 | INFO | Train Epoch: 14 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.061629 (0.060621) Boundary_loss: 0.013895 (0.013895) Loss: 0.075525 (0.074516) +2025-09-16,18:52:48 | INFO | Train Epoch: 14 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.051838 (0.060596) Boundary_loss: 0.013895 (0.013895) Loss: 0.065733 (0.074492) +2025-09-16,18:53:54 | INFO | Train Epoch: 14 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.080701 (0.060652) Boundary_loss: 0.013894 (0.013895) Loss: 0.094595 (0.074548) +2025-09-16,18:54:59 | INFO | Train Epoch: 14 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.079236 (0.060704) Boundary_loss: 0.013896 (0.013895) Loss: 0.093131 (0.074600) +2025-09-16,18:56:05 | INFO | Train Epoch: 14 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.052589 (0.060682) Boundary_loss: 0.013896 (0.013895) Loss: 0.066485 (0.074577) +2025-09-16,18:57:11 | INFO | Train Epoch: 14 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.035776 (0.060613) Boundary_loss: 0.013895 (0.013895) Loss: 0.049672 (0.074508) +2025-09-16,18:58:17 | INFO | Train Epoch: 14 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.058602 (0.060607) Boundary_loss: 0.013896 (0.013895) Loss: 0.072497 (0.074502) +2025-09-16,18:59:23 | INFO | Train Epoch: 14 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.057778 (0.060599) Boundary_loss: 0.013895 (0.013895) Loss: 0.071674 (0.074495) +2025-09-16,19:00:29 | INFO | Train Epoch: 14 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.045848 (0.060559) Boundary_loss: 0.013895 (0.013895) Loss: 0.059743 (0.074454) +2025-09-16,19:01:35 | INFO | Train Epoch: 14 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.071628 (0.060589) Boundary_loss: 0.013894 (0.013895) Loss: 0.085522 (0.074484) +2025-09-16,19:02:40 | INFO | Train Epoch: 14 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.057209 (0.060580) Boundary_loss: 0.013895 (0.013895) Loss: 0.071103 (0.074475) +2025-09-16,19:03:46 | INFO | Train Epoch: 14 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.036374 (0.060514) Boundary_loss: 0.013896 (0.013895) Loss: 0.050269 (0.074409) +2025-09-16,19:04:52 | INFO | Train Epoch: 14 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.051773 (0.060490) Boundary_loss: 0.013896 (0.013895) Loss: 0.065669 (0.074386) +2025-09-16,19:05:58 | INFO | Train Epoch: 14 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.078307 (0.060538) Boundary_loss: 0.013895 (0.013895) Loss: 0.092202 (0.074434) +2025-09-16,19:07:04 | INFO | Train Epoch: 14 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.055484 (0.060525) Boundary_loss: 0.013896 (0.013895) Loss: 0.069380 (0.074420) +2025-09-16,19:08:10 | INFO | Train Epoch: 14 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.062414 (0.060530) Boundary_loss: 0.013894 (0.013895) Loss: 0.076308 (0.074425) +2025-09-16,19:09:15 | INFO | Train Epoch: 14 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.076172 (0.060572) Boundary_loss: 0.013895 (0.013895) Loss: 0.090067 (0.074467) +2025-09-16,19:10:21 | INFO | Train Epoch: 14 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.067535 (0.060591) Boundary_loss: 0.013894 (0.013895) Loss: 0.081429 (0.074486) +2025-09-16,19:11:27 | INFO | Train Epoch: 14 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.050912 (0.060565) Boundary_loss: 0.013895 (0.013895) Loss: 0.064807 (0.074460) +2025-09-16,19:12:33 | INFO | Train Epoch: 14 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.071756 (0.060594) Boundary_loss: 0.013895 (0.013895) Loss: 0.085651 (0.074490) +2025-09-16,19:13:39 | INFO | Train Epoch: 14 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.069697 (0.060619) Boundary_loss: 0.013896 (0.013895) Loss: 0.083593 (0.074514) +2025-09-16,19:14:45 | INFO | Train Epoch: 14 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.028142 (0.060533) Boundary_loss: 0.013895 (0.013895) Loss: 0.042037 (0.074428) +2025-09-16,19:15:50 | INFO | Train Epoch: 14 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.066880 (0.060549) Boundary_loss: 0.013896 (0.013895) Loss: 0.080776 (0.074445) +2025-09-16,19:16:56 | INFO | Train Epoch: 14 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.041390 (0.060499) Boundary_loss: 0.013896 (0.013895) Loss: 0.055286 (0.074394) +2025-09-16,19:18:02 | INFO | Train Epoch: 14 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.095245 (0.060590) Boundary_loss: 0.013895 (0.013895) Loss: 0.10914 (0.074486) +2025-09-16,19:19:08 | INFO | Train Epoch: 14 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.076377 (0.060632) Boundary_loss: 0.013896 (0.013895) Loss: 0.090273 (0.074527) +2025-09-16,19:20:14 | INFO | Train Epoch: 14 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.052232 (0.060610) Boundary_loss: 0.013894 (0.013895) Loss: 0.066127 (0.074505) +2025-09-16,19:21:20 | INFO | Train Epoch: 14 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.059470 (0.060607) Boundary_loss: 0.013896 (0.013895) Loss: 0.073366 (0.074502) +2025-09-16,19:22:26 | INFO | Train Epoch: 14 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.057407 (0.060598) Boundary_loss: 0.013896 (0.013895) Loss: 0.071303 (0.074494) +2025-09-16,19:23:31 | INFO | Train Epoch: 14 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.045446 (0.060559) Boundary_loss: 0.013896 (0.013895) Loss: 0.059342 (0.074454) +2025-09-16,19:24:37 | INFO | Train Epoch: 14 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.045220 (0.060519) Boundary_loss: 0.013895 (0.013895) Loss: 0.059115 (0.074415) +2025-09-16,19:25:43 | INFO | Train Epoch: 14 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.064292 (0.060529) Boundary_loss: 0.013896 (0.013895) Loss: 0.078188 (0.074424) +2025-09-16,19:26:49 | INFO | Train Epoch: 14 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.065504 (0.060542) Boundary_loss: 0.013895 (0.013895) Loss: 0.079399 (0.074437) +2025-09-16,19:27:55 | INFO | Train Epoch: 14 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.044266 (0.060500) Boundary_loss: 0.013895 (0.013895) Loss: 0.058161 (0.074395) +2025-09-16,19:29:01 | INFO | Train Epoch: 14 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.078771 (0.060547) Boundary_loss: 0.013894 (0.013895) Loss: 0.092665 (0.074442) +2025-09-16,19:30:06 | INFO | Train Epoch: 14 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.074284 (0.060582) Boundary_loss: 0.013896 (0.013895) Loss: 0.088179 (0.074477) +2025-09-16,19:31:12 | INFO | Train Epoch: 14 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.077466 (0.060625) Boundary_loss: 0.013895 (0.013895) Loss: 0.091361 (0.074520) +2025-09-16,19:32:18 | INFO | Train Epoch: 14 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.068491 (0.060645) Boundary_loss: 0.013896 (0.013895) Loss: 0.082387 (0.074541) +2025-09-16,19:33:24 | INFO | Train Epoch: 14 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.077792 (0.060689) Boundary_loss: 0.013894 (0.013895) Loss: 0.091686 (0.074584) +2025-09-16,19:34:30 | INFO | Train Epoch: 14 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.044214 (0.060647) Boundary_loss: 0.013895 (0.013895) Loss: 0.058109 (0.074542) +2025-09-16,19:35:36 | INFO | Train Epoch: 14 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.072135 (0.060676) Boundary_loss: 0.013895 (0.013895) Loss: 0.086030 (0.074571) +2025-09-16,19:36:41 | INFO | Train Epoch: 14 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.063035 (0.060682) Boundary_loss: 0.013895 (0.013895) Loss: 0.076930 (0.074577) +2025-09-16,19:37:47 | INFO | Train Epoch: 14 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.048039 (0.060650) Boundary_loss: 0.013896 (0.013895) Loss: 0.061935 (0.074546) +2025-09-16,19:38:53 | INFO | Train Epoch: 14 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.035515 (0.060587) Boundary_loss: 0.013896 (0.013895) Loss: 0.049411 (0.074483) +2025-09-16,19:39:59 | INFO | Train Epoch: 14 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.066792 (0.060603) Boundary_loss: 0.013895 (0.013895) Loss: 0.080688 (0.074498) +2025-09-16,19:41:05 | INFO | Train Epoch: 14 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.054623 (0.060588) Boundary_loss: 0.013896 (0.013895) Loss: 0.068519 (0.074483) +2025-09-16,19:42:11 | INFO | Train Epoch: 14 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.041837 (0.060541) Boundary_loss: 0.013896 (0.013895) Loss: 0.055733 (0.074436) +2025-09-16,19:43:17 | INFO | Train Epoch: 14 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.046255 (0.060506) Boundary_loss: 0.013895 (0.013895) Loss: 0.060149 (0.074401) +2025-09-16,19:44:22 | INFO | Train Epoch: 14 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.050156 (0.060480) Boundary_loss: 0.013896 (0.013895) Loss: 0.064052 (0.074375) +2025-09-16,19:45:28 | INFO | Train Epoch: 14 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.065869 (0.060493) Boundary_loss: 0.013895 (0.013895) Loss: 0.079763 (0.074389) +2025-09-16,19:46:34 | INFO | Train Epoch: 14 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.045064 (0.060455) Boundary_loss: 0.013896 (0.013895) Loss: 0.058960 (0.074351) +2025-09-16,19:47:40 | INFO | Train Epoch: 14 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.040870 (0.060407) Boundary_loss: 0.013895 (0.013895) Loss: 0.054765 (0.074303) +2025-09-16,19:48:46 | INFO | Train Epoch: 14 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.040914 (0.060359) Boundary_loss: 0.013895 (0.013895) Loss: 0.054809 (0.074255) +2025-09-16,19:49:52 | INFO | Train Epoch: 14 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.035775 (0.060299) Boundary_loss: 0.013895 (0.013895) Loss: 0.049670 (0.074195) +2025-09-16,19:50:58 | INFO | Train Epoch: 14 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.064680 (0.060310) Boundary_loss: 0.013895 (0.013895) Loss: 0.078574 (0.074205) +2025-09-16,19:52:04 | INFO | Train Epoch: 14 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.038942 (0.060258) Boundary_loss: 0.013895 (0.013895) Loss: 0.052837 (0.074153) +2025-09-16,19:53:09 | INFO | Train Epoch: 14 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.041050 (0.060211) Boundary_loss: 0.013895 (0.013895) Loss: 0.054945 (0.074107) +2025-09-16,19:54:15 | INFO | Train Epoch: 14 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.060492 (0.060212) Boundary_loss: 0.013895 (0.013895) Loss: 0.074387 (0.074107) +2025-09-16,19:55:21 | INFO | Train Epoch: 14 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.057948 (0.060207) Boundary_loss: 0.013894 (0.013895) Loss: 0.071843 (0.074102) +2025-09-16,19:56:27 | INFO | Train Epoch: 14 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.044169 (0.060168) Boundary_loss: 0.013895 (0.013895) Loss: 0.058064 (0.074063) +2025-09-16,19:57:33 | INFO | Train Epoch: 14 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.069428 (0.060190) Boundary_loss: 0.013895 (0.013895) Loss: 0.083323 (0.074086) +2025-09-16,19:58:39 | INFO | Train Epoch: 14 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.076098 (0.060228) Boundary_loss: 0.013895 (0.013895) Loss: 0.089993 (0.074124) +2025-09-16,19:59:44 | INFO | Train Epoch: 14 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.058663 (0.060225) Boundary_loss: 0.013895 (0.013895) Loss: 0.072558 (0.074120) +2025-09-16,20:00:50 | INFO | Train Epoch: 14 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.048542 (0.060197) Boundary_loss: 0.013894 (0.013895) Loss: 0.062437 (0.074092) +2025-09-16,20:01:56 | INFO | Train Epoch: 14 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.063225 (0.060204) Boundary_loss: 0.013895 (0.013895) Loss: 0.077120 (0.074099) +2025-09-16,20:03:02 | INFO | Train Epoch: 14 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.037097 (0.060149) Boundary_loss: 0.013896 (0.013895) Loss: 0.050993 (0.074044) +2025-09-16,20:04:08 | INFO | Train Epoch: 14 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.078390 (0.060192) Boundary_loss: 0.013894 (0.013895) Loss: 0.092284 (0.074088) +2025-09-16,20:05:14 | INFO | Train Epoch: 14 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.058508 (0.060188) Boundary_loss: 0.013896 (0.013895) Loss: 0.072403 (0.074084) +2025-09-16,20:06:20 | INFO | Train Epoch: 14 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.050181 (0.060165) Boundary_loss: 0.013895 (0.013895) Loss: 0.064076 (0.074060) +2025-09-16,20:07:25 | INFO | Train Epoch: 14 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.064772 (0.060175) Boundary_loss: 0.013896 (0.013895) Loss: 0.078669 (0.074071) +2025-09-16,20:08:31 | INFO | Train Epoch: 14 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.072576 (0.060205) Boundary_loss: 0.013896 (0.013895) Loss: 0.086472 (0.074100) +2025-09-16,20:09:37 | INFO | Train Epoch: 14 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.034318 (0.060144) Boundary_loss: 0.013895 (0.013895) Loss: 0.048213 (0.074039) +2025-09-16,20:10:43 | INFO | Train Epoch: 14 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.042001 (0.060102) Boundary_loss: 0.013896 (0.013895) Loss: 0.055897 (0.073997) +2025-09-16,20:11:49 | INFO | Train Epoch: 14 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.078127 (0.060144) Boundary_loss: 0.013896 (0.013895) Loss: 0.092023 (0.074039) +2025-09-16,20:12:55 | INFO | Train Epoch: 14 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.052932 (0.060127) Boundary_loss: 0.013895 (0.013895) Loss: 0.066827 (0.074022) +2025-09-16,20:14:01 | INFO | Train Epoch: 14 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.045966 (0.060094) Boundary_loss: 0.013895 (0.013895) Loss: 0.059861 (0.073989) +2025-09-16,20:15:07 | INFO | Train Epoch: 14 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.043069 (0.060055) Boundary_loss: 0.013895 (0.013895) Loss: 0.056964 (0.073950) +2025-09-16,20:16:12 | INFO | Train Epoch: 14 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.048274 (0.060027) Boundary_loss: 0.013895 (0.013895) Loss: 0.062169 (0.073923) +2025-09-16,20:17:18 | INFO | Train Epoch: 14 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.040854 (0.059983) Boundary_loss: 0.013896 (0.013895) Loss: 0.054750 (0.073879) +2025-09-16,20:18:24 | INFO | Train Epoch: 14 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.079430 (0.060028) Boundary_loss: 0.013896 (0.013895) Loss: 0.093326 (0.073923) +2025-09-16,20:19:30 | INFO | Train Epoch: 14 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.070088 (0.060051) Boundary_loss: 0.013895 (0.013895) Loss: 0.083983 (0.073946) +2025-09-16,20:20:36 | INFO | Train Epoch: 14 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.081954 (0.060101) Boundary_loss: 0.013894 (0.013895) Loss: 0.095848 (0.073996) +2025-09-16,20:21:42 | INFO | Train Epoch: 14 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.075942 (0.060137) Boundary_loss: 0.013896 (0.013895) Loss: 0.089838 (0.074033) +2025-09-16,20:22:48 | INFO | Train Epoch: 14 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.074905 (0.060171) Boundary_loss: 0.013895 (0.013895) Loss: 0.088800 (0.074066) +2025-09-16,20:23:53 | INFO | Train Epoch: 14 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.069019 (0.060191) Boundary_loss: 0.013895 (0.013895) Loss: 0.082914 (0.074086) +2025-09-16,20:24:59 | INFO | Train Epoch: 14 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.055008 (0.060179) Boundary_loss: 0.013897 (0.013895) Loss: 0.068904 (0.074075) +2025-09-16,20:26:05 | INFO | Train Epoch: 14 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.070528 (0.060203) Boundary_loss: 0.013895 (0.013895) Loss: 0.084423 (0.074098) +2025-09-16,20:27:11 | INFO | Train Epoch: 14 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.068055 (0.060220) Boundary_loss: 0.013895 (0.013895) Loss: 0.081949 (0.074116) +2025-09-16,20:28:17 | INFO | Train Epoch: 14 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.062990 (0.060227) Boundary_loss: 0.013895 (0.013895) Loss: 0.076885 (0.074122) +2025-09-16,20:29:23 | INFO | Train Epoch: 14 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.041125 (0.060184) Boundary_loss: 0.013895 (0.013895) Loss: 0.055020 (0.074079) +2025-09-16,20:30:29 | INFO | Train Epoch: 14 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.061817 (0.060187) Boundary_loss: 0.013896 (0.013895) Loss: 0.075712 (0.074083) +2025-09-16,20:31:35 | INFO | Train Epoch: 14 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.047163 (0.060158) Boundary_loss: 0.013895 (0.013895) Loss: 0.061059 (0.074054) +2025-09-16,20:32:40 | INFO | Train Epoch: 14 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.069528 (0.060179) Boundary_loss: 0.013896 (0.013895) Loss: 0.083425 (0.074075) +2025-09-16,20:33:46 | INFO | Train Epoch: 14 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.052298 (0.060162) Boundary_loss: 0.013896 (0.013895) Loss: 0.066193 (0.074057) +2025-09-16,20:34:52 | INFO | Train Epoch: 14 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.054905 (0.060150) Boundary_loss: 0.013895 (0.013895) Loss: 0.068800 (0.074045) +2025-09-16,20:35:58 | INFO | Train Epoch: 14 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.053039 (0.060134) Boundary_loss: 0.013896 (0.013895) Loss: 0.066935 (0.074030) +2025-09-16,20:37:04 | INFO | Train Epoch: 14 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.041854 (0.060094) Boundary_loss: 0.013896 (0.013895) Loss: 0.055750 (0.073989) +2025-09-16,20:38:10 | INFO | Train Epoch: 14 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.055735 (0.060084) Boundary_loss: 0.013896 (0.013895) Loss: 0.069631 (0.073979) +2025-09-16,20:39:16 | INFO | Train Epoch: 14 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.066047 (0.060097) Boundary_loss: 0.013895 (0.013895) Loss: 0.079943 (0.073993) +2025-09-16,20:40:22 | INFO | Train Epoch: 14 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.058632 (0.060094) Boundary_loss: 0.013896 (0.013895) Loss: 0.072529 (0.073989) +2025-09-16,20:41:27 | INFO | Train Epoch: 14 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.060613 (0.060095) Boundary_loss: 0.013895 (0.013895) Loss: 0.074508 (0.073991) +2025-09-16,20:42:33 | INFO | Train Epoch: 14 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.062729 (0.060101) Boundary_loss: 0.013894 (0.013895) Loss: 0.076624 (0.073996) +2025-09-16,20:43:39 | INFO | Train Epoch: 14 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.046346 (0.060071) Boundary_loss: 0.013895 (0.013895) Loss: 0.060241 (0.073966) +2025-09-16,20:44:45 | INFO | Train Epoch: 14 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.071103 (0.060095) Boundary_loss: 0.013897 (0.013895) Loss: 0.084999 (0.073990) +2025-09-16,20:45:51 | INFO | Train Epoch: 14 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.043957 (0.060060) Boundary_loss: 0.013894 (0.013895) Loss: 0.057852 (0.073955) +2025-09-16,20:46:57 | INFO | Train Epoch: 14 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.048939 (0.060036) Boundary_loss: 0.013896 (0.013895) Loss: 0.062836 (0.073931) +2025-09-16,20:48:03 | INFO | Train Epoch: 14 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.059062 (0.060034) Boundary_loss: 0.013895 (0.013895) Loss: 0.072957 (0.073929) +2025-09-16,20:49:09 | INFO | Train Epoch: 14 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.040577 (0.059992) Boundary_loss: 0.013896 (0.013895) Loss: 0.054473 (0.073887) +2025-09-16,20:50:14 | INFO | Train Epoch: 14 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.068686 (0.060010) Boundary_loss: 0.013895 (0.013895) Loss: 0.082581 (0.073906) +2025-09-16,20:51:20 | INFO | Train Epoch: 14 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.048723 (0.059986) Boundary_loss: 0.013895 (0.013895) Loss: 0.062618 (0.073881) +2025-09-16,20:52:26 | INFO | Train Epoch: 14 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.063890 (0.059994) Boundary_loss: 0.013895 (0.013895) Loss: 0.077785 (0.073890) +2025-09-16,20:53:32 | INFO | Train Epoch: 14 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.038929 (0.059949) Boundary_loss: 0.013895 (0.013895) Loss: 0.052825 (0.073845) +2025-09-16,20:54:38 | INFO | Train Epoch: 14 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.058862 (0.059947) Boundary_loss: 0.013895 (0.013895) Loss: 0.072757 (0.073842) +2025-09-16,20:55:44 | INFO | Train Epoch: 14 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.065161 (0.059958) Boundary_loss: 0.013896 (0.013895) Loss: 0.079057 (0.073854) +2025-09-16,20:56:50 | INFO | Train Epoch: 14 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.060907 (0.059960) Boundary_loss: 0.013896 (0.013895) Loss: 0.074804 (0.073856) +2025-09-16,20:57:56 | INFO | Train Epoch: 14 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.054852 (0.059949) Boundary_loss: 0.013896 (0.013895) Loss: 0.068748 (0.073845) +2025-09-16,20:59:01 | INFO | Train Epoch: 14 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.054683 (0.059938) Boundary_loss: 0.013894 (0.013895) Loss: 0.068577 (0.073834) +2025-09-16,21:00:07 | INFO | Train Epoch: 14 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.050951 (0.059919) Boundary_loss: 0.013896 (0.013895) Loss: 0.064847 (0.073815) +2025-09-16,21:01:13 | INFO | Train Epoch: 14 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.039577 (0.059876) Boundary_loss: 0.013897 (0.013895) Loss: 0.053474 (0.073772) +2025-09-16,21:02:19 | INFO | Train Epoch: 14 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.066144 (0.059889) Boundary_loss: 0.013897 (0.013895) Loss: 0.080042 (0.073785) +2025-09-16,21:03:25 | INFO | Train Epoch: 14 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.088745 (0.059950) Boundary_loss: 0.013896 (0.013895) Loss: 0.10264 (0.073845) +2025-09-16,21:04:31 | INFO | Train Epoch: 14 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.068676 (0.059968) Boundary_loss: 0.013896 (0.013895) Loss: 0.082571 (0.073864) +2025-09-16,21:05:37 | INFO | Train Epoch: 14 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.060370 (0.059969) Boundary_loss: 0.013895 (0.013895) Loss: 0.074264 (0.073865) +2025-09-16,21:06:43 | INFO | Train Epoch: 14 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.060530 (0.059970) Boundary_loss: 0.013896 (0.013895) Loss: 0.074427 (0.073866) +2025-09-16,21:07:49 | INFO | Train Epoch: 14 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.090325 (0.060034) Boundary_loss: 0.013896 (0.013895) Loss: 0.10422 (0.073929) +2025-09-16,21:08:54 | INFO | Train Epoch: 14 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.048975 (0.060011) Boundary_loss: 0.013895 (0.013895) Loss: 0.062870 (0.073906) +2025-09-16,21:10:00 | INFO | Train Epoch: 14 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.048768 (0.059987) Boundary_loss: 0.013895 (0.013895) Loss: 0.062663 (0.073883) +2025-09-16,21:11:06 | INFO | Train Epoch: 14 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.065268 (0.059998) Boundary_loss: 0.013894 (0.013895) Loss: 0.079162 (0.073894) +2025-09-16,21:12:12 | INFO | Train Epoch: 14 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.083989 (0.060048) Boundary_loss: 0.013895 (0.013895) Loss: 0.097883 (0.073943) +2025-09-16,21:13:18 | INFO | Train Epoch: 14 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.056924 (0.060041) Boundary_loss: 0.013895 (0.013895) Loss: 0.070819 (0.073937) +2025-09-16,21:14:24 | INFO | Train Epoch: 14 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.041673 (0.060003) Boundary_loss: 0.013897 (0.013895) Loss: 0.055570 (0.073899) +2025-09-16,21:15:30 | INFO | Train Epoch: 14 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.045895 (0.059975) Boundary_loss: 0.013896 (0.013895) Loss: 0.059791 (0.073870) +2025-09-16,21:16:36 | INFO | Train Epoch: 14 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.058814 (0.059972) Boundary_loss: 0.013897 (0.013895) Loss: 0.072711 (0.073868) +2025-09-16,21:17:41 | INFO | Train Epoch: 14 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.053570 (0.059959) Boundary_loss: 0.013895 (0.013895) Loss: 0.067465 (0.073854) +2025-09-16,21:18:47 | INFO | Train Epoch: 14 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.027461 (0.059893) Boundary_loss: 0.013895 (0.013895) Loss: 0.041356 (0.073788) +2025-09-16,21:19:53 | INFO | Train Epoch: 14 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.057496 (0.059888) Boundary_loss: 0.013896 (0.013895) Loss: 0.071393 (0.073783) +2025-09-16,21:20:59 | INFO | Train Epoch: 14 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.036067 (0.059839) Boundary_loss: 0.013895 (0.013895) Loss: 0.049962 (0.073735) +2025-09-16,21:22:05 | INFO | Train Epoch: 14 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.065813 (0.059852) Boundary_loss: 0.013897 (0.013895) Loss: 0.079710 (0.073747) +2025-09-16,21:23:11 | INFO | Train Epoch: 14 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.085027 (0.059903) Boundary_loss: 0.013894 (0.013895) Loss: 0.098922 (0.073798) +2025-09-16,21:24:17 | INFO | Train Epoch: 14 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.058531 (0.059900) Boundary_loss: 0.013896 (0.013895) Loss: 0.072426 (0.073795) +2025-09-16,21:25:23 | INFO | Train Epoch: 14 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.046831 (0.059873) Boundary_loss: 0.013895 (0.013895) Loss: 0.060726 (0.073769) +2025-09-16,21:26:28 | INFO | Train Epoch: 14 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.080254 (0.059914) Boundary_loss: 0.013896 (0.013895) Loss: 0.094150 (0.073810) +2025-09-16,21:27:34 | INFO | Train Epoch: 14 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.054014 (0.059903) Boundary_loss: 0.013895 (0.013895) Loss: 0.067910 (0.073798) +2025-09-16,21:28:40 | INFO | Train Epoch: 14 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.060008 (0.059903) Boundary_loss: 0.013895 (0.013895) Loss: 0.073903 (0.073798) +2025-09-16,21:29:46 | INFO | Train Epoch: 14 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.049272 (0.059881) Boundary_loss: 0.013896 (0.013895) Loss: 0.063168 (0.073777) +2025-09-16,21:30:52 | INFO | Train Epoch: 14 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.050476 (0.059863) Boundary_loss: 0.013896 (0.013895) Loss: 0.064372 (0.073758) +2025-09-16,21:31:58 | INFO | Train Epoch: 14 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.045852 (0.059835) Boundary_loss: 0.013894 (0.013895) Loss: 0.059746 (0.073730) +2025-09-16,21:33:04 | INFO | Train Epoch: 14 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.032264 (0.059780) Boundary_loss: 0.013896 (0.013895) Loss: 0.046160 (0.073675) +2025-09-16,21:34:10 | INFO | Train Epoch: 14 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.075058 (0.059810) Boundary_loss: 0.013895 (0.013895) Loss: 0.088953 (0.073706) +2025-09-16,21:35:15 | INFO | Train Epoch: 14 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.038246 (0.059768) Boundary_loss: 0.013895 (0.013895) Loss: 0.052141 (0.073663) +2025-09-16,21:36:21 | INFO | Train Epoch: 14 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.048178 (0.059745) Boundary_loss: 0.013895 (0.013895) Loss: 0.062073 (0.073640) +2025-09-16,21:37:27 | INFO | Train Epoch: 14 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.046992 (0.059720) Boundary_loss: 0.013896 (0.013895) Loss: 0.060888 (0.073615) +2025-09-16,21:38:33 | INFO | Train Epoch: 14 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.048816 (0.059698) Boundary_loss: 0.013895 (0.013895) Loss: 0.062712 (0.073594) +2025-09-16,21:39:39 | INFO | Train Epoch: 14 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.032824 (0.059645) Boundary_loss: 0.013897 (0.013895) Loss: 0.046721 (0.073541) +2025-09-16,21:40:45 | INFO | Train Epoch: 14 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.055876 (0.059638) Boundary_loss: 0.013896 (0.013895) Loss: 0.069772 (0.073533) +2025-09-16,21:41:51 | INFO | Train Epoch: 14 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.059290 (0.059637) Boundary_loss: 0.013895 (0.013895) Loss: 0.073185 (0.073533) +2025-09-16,21:42:57 | INFO | Train Epoch: 14 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.051043 (0.059620) Boundary_loss: 0.013895 (0.013895) Loss: 0.064939 (0.073516) +2025-09-16,21:44:03 | INFO | Train Epoch: 14 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.082639 (0.059665) Boundary_loss: 0.013895 (0.013895) Loss: 0.096534 (0.073561) +2025-09-16,21:45:09 | INFO | Train Epoch: 14 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.068275 (0.059682) Boundary_loss: 0.013896 (0.013895) Loss: 0.082171 (0.073577) +2025-09-16,21:46:15 | INFO | Train Epoch: 14 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.032225 (0.059629) Boundary_loss: 0.013895 (0.013895) Loss: 0.046120 (0.073524) +2025-09-16,21:47:17 | INFO | Train Epoch: 14 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.063709 (0.059637) Boundary_loss: 0.013896 (0.013895) Loss: 0.077605 (0.073532) +2025-09-16,21:47:17 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-16,21:47:17 | INFO | [Epoch 14] Average Step Time: 0.661s | Average GPU Memory: 30.8 GB +2025-09-16,21:47:17 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-16,21:47:17 | INFO | Starting zero-shot imagenet. +2025-09-16,21:47:17 | INFO | Building zero-shot classifier +2025-09-16,21:47:27 | INFO | Using classifier +2025-09-16,21:48:55 | INFO | Finished zero-shot imagenet. +2025-09-16,21:48:55 | INFO | Eval Epoch: 15 imagenet-zeroshot-val-top1: 0.3359 imagenet-zeroshot-val-top5: 0.6121