diff --git "a/DRIP_4x_16_ViT_2_10/out.log" "b/DRIP_4x_16_ViT_2_10/out.log" new file mode 100644--- /dev/null +++ "b/DRIP_4x_16_ViT_2_10/out.log" @@ -0,0 +1,8047 @@ +2025-09-12,06:49:14 | INFO | Running with a single process. Device cuda. +2025-09-12,06:49:14 | INFO | Loaded ViT-B-16 model config. +2025-09-12,06:49:15 | INFO | Model: +2025-09-12,06:49:15 | 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( + (0-1): 2 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( + (0-9): 10 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) +) +2025-09-12,06:49:15 | INFO | Params: +2025-09-12,06:49:15 | INFO | DTP: True +2025-09-12,06:49:15 | INFO | accum_freq: 1 +2025-09-12,06:49:15 | INFO | aug_cfg: {} +2025-09-12,06:49:15 | INFO | batch_size: 512 +2025-09-12,06:49:15 | INFO | beta1: 0.9 +2025-09-12,06:49:15 | INFO | beta2: 0.98 +2025-09-12,06:49:15 | INFO | cache_dir: None +2025-09-12,06:49:15 | INFO | checkpoint_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_09_12-06_49_14-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/checkpoints +2025-09-12,06:49:15 | INFO | coca_caption_loss_weight: 2.0 +2025-09-12,06:49:15 | INFO | coca_contrastive_loss_weight: 1.0 +2025-09-12,06:49:15 | INFO | copy_codebase: False +2025-09-12,06:49:15 | INFO | csv_caption_key: title +2025-09-12,06:49:15 | INFO | csv_img_key: filepath +2025-09-12,06:49:15 | INFO | csv_separator: +2025-09-12,06:49:15 | INFO | dataset_resampled: False +2025-09-12,06:49:15 | INFO | dataset_type: webdataset +2025-09-12,06:49:15 | INFO | ddp_static_graph: False +2025-09-12,06:49:15 | INFO | debug: False +2025-09-12,06:49:15 | INFO | delete_previous_checkpoint: False +2025-09-12,06:49:15 | INFO | device: cuda +2025-09-12,06:49:15 | INFO | dist_backend: None +2025-09-12,06:49:15 | INFO | dist_url: None +2025-09-12,06:49:15 | INFO | distill: False +2025-09-12,06:49:15 | INFO | distill_model: None +2025-09-12,06:49:15 | INFO | distill_pretrained: None +2025-09-12,06:49:15 | INFO | distributed: False +2025-09-12,06:49:15 | INFO | epochs: 15 +2025-09-12,06:49:15 | INFO | epochs_cooldown: None +2025-09-12,06:49:15 | INFO | eps: 1e-06 +2025-09-12,06:49:15 | INFO | force_custom_text: False +2025-09-12,06:49:15 | INFO | force_image_size: None +2025-09-12,06:49:15 | INFO | force_patch_dropout: None +2025-09-12,06:49:15 | INFO | force_quick_gelu: False +2025-09-12,06:49:15 | INFO | gather_with_grad: False +2025-09-12,06:49:15 | INFO | grad_checkpointing: False +2025-09-12,06:49:15 | INFO | grad_clip_norm: None +2025-09-12,06:49:15 | INFO | horovod: False +2025-09-12,06:49:15 | INFO | image_interpolation: None +2025-09-12,06:49:15 | INFO | image_mean: None +2025-09-12,06:49:15 | INFO | image_resize_mode: None +2025-09-12,06:49:15 | INFO | image_std: None +2025-09-12,06:49:15 | INFO | imagenet_v2: None +2025-09-12,06:49:15 | INFO | imagenet_val: /fs/scratch/PAS2836/yusenpeng_dataset/val +2025-09-12,06:49:15 | INFO | local_loss: False +2025-09-12,06:49:15 | INFO | local_rank: 0 +2025-09-12,06:49:15 | INFO | lock_image: False +2025-09-12,06:49:15 | INFO | lock_image_freeze_bn_stats: False +2025-09-12,06:49:15 | INFO | lock_image_unlocked_groups: 0 +2025-09-12,06:49:15 | INFO | lock_text: False +2025-09-12,06:49:15 | INFO | lock_text_freeze_layer_norm: False +2025-09-12,06:49:15 | INFO | lock_text_unlocked_layers: 0 +2025-09-12,06:49:15 | INFO | log_every_n_steps: 100 +2025-09-12,06:49:15 | INFO | log_level: 20 +2025-09-12,06:49:15 | INFO | log_local: False +2025-09-12,06:49:15 | INFO | log_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_09_12-06_49_14-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/out.log +2025-09-12,06:49:15 | INFO | logs: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/ +2025-09-12,06:49:15 | INFO | loss_dist_impl: None +2025-09-12,06:49:15 | INFO | lr: 5e-05 +2025-09-12,06:49:15 | INFO | lr_cooldown_end: 0.0 +2025-09-12,06:49:15 | INFO | lr_cooldown_power: 1.0 +2025-09-12,06:49:15 | INFO | lr_scheduler: cosine +2025-09-12,06:49:15 | INFO | model: ViT-B-16 +2025-09-12,06:49:15 | INFO | momentum: None +2025-09-12,06:49:15 | INFO | name: 2025_09_12-06_49_14-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp +2025-09-12,06:49:15 | INFO | no_set_device_rank: False +2025-09-12,06:49:15 | INFO | opt: adamw +2025-09-12,06:49:15 | INFO | precision: amp +2025-09-12,06:49:15 | INFO | pretrained: +2025-09-12,06:49:15 | INFO | pretrained_image: False +2025-09-12,06:49:15 | INFO | rank: 0 +2025-09-12,06:49:15 | INFO | remote_sync: None +2025-09-12,06:49:15 | INFO | remote_sync_frequency: 300 +2025-09-12,06:49:15 | INFO | remote_sync_protocol: s3 +2025-09-12,06:49:15 | INFO | report_to: tensorboard +2025-09-12,06:49:15 | INFO | resume: None +2025-09-12,06:49:15 | INFO | save_frequency: 1 +2025-09-12,06:49:15 | INFO | save_most_recent: False +2025-09-12,06:49:15 | INFO | seed: 0 +2025-09-12,06:49:15 | INFO | siglip: False +2025-09-12,06:49:15 | INFO | skip_scheduler: False +2025-09-12,06:49:15 | INFO | tensorboard: True +2025-09-12,06:49:15 | INFO | tensorboard_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_09_12-06_49_14-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/tensorboard +2025-09-12,06:49:15 | INFO | torchcompile: False +2025-09-12,06:49:15 | INFO | torchscript: False +2025-09-12,06:49:15 | INFO | trace: False +2025-09-12,06:49:15 | INFO | train_data: 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+2025-09-12,06:49:15 | INFO | train_data_upsampling_factors: None +2025-09-12,06:49:15 | INFO | train_num_samples: 26365716 +2025-09-12,06:49:15 | INFO | use_bn_sync: False +2025-09-12,06:49:15 | INFO | use_bnb_linear: None +2025-09-12,06:49:15 | INFO | val_data: None +2025-09-12,06:49:15 | INFO | val_frequency: 1 +2025-09-12,06:49:15 | INFO | val_num_samples: None +2025-09-12,06:49:15 | INFO | wandb: False +2025-09-12,06:49:15 | INFO | wandb_notes: +2025-09-12,06:49:15 | INFO | wandb_project_name: open-clip +2025-09-12,06:49:15 | INFO | warmup: 50 +2025-09-12,06:49:15 | INFO | wd: 0.1 +2025-09-12,06:49:15 | INFO | workers: 8 +2025-09-12,06:49:15 | INFO | world_size: 1 +2025-09-12,06:49:15 | INFO | zeroshot_frequency: 1 +2025-09-12,06:49:15 | 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 +2025-09-12,06:49:16 | INFO | Start epoch 0 +2025-09-12,06:49:26 | INFO | Train Epoch: 0 [ 512/26365952 (0%)] Avg Boundaries (per batch): 92.484 Boundary Ratio: 0.472 Contrastive_loss: 6.3296 (6.3296) Boundary_loss: 0.13238 (0.13238) Loss: 6.4620 (6.4620) +2025-09-12,06:50:02 | INFO | Train Epoch: 0 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 6.1059 (6.2177) Boundary_loss: 0.016700 (0.074540) Loss: 6.1226 (6.2923) +2025-09-12,06:50:35 | INFO | Train Epoch: 0 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 47.920 Boundary Ratio: 0.244 Contrastive_loss: 5.8968 (6.1108) Boundary_loss: 0.016602 (0.055228) Loss: 5.9134 (6.1660) +2025-09-12,06:51:08 | INFO | Train Epoch: 0 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 5.7499 (6.0205) Boundary_loss: 0.016704 (0.045597) Loss: 5.7666 (6.0661) +2025-09-12,06:51:41 | INFO | Train Epoch: 0 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 5.6606 (5.9486) Boundary_loss: 0.016590 (0.039795) Loss: 5.6772 (5.9883) +2025-09-12,06:52:14 | INFO | Train Epoch: 0 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 51.201 Boundary Ratio: 0.261 Contrastive_loss: 5.5502 (5.8822) Boundary_loss: 0.016859 (0.035973) Loss: 5.5671 (5.9181) +2025-09-12,06:52:48 | INFO | Train Epoch: 0 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 49.182 Boundary Ratio: 0.251 Contrastive_loss: 5.4243 (5.8168) Boundary_loss: 0.016635 (0.033210) Loss: 5.4410 (5.8500) +2025-09-12,06:53:21 | INFO | Train Epoch: 0 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 5.3206 (5.7547) Boundary_loss: 0.016730 (0.031150) Loss: 5.3374 (5.7859) +2025-09-12,06:53:54 | INFO | Train Epoch: 0 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 49.359 Boundary Ratio: 0.252 Contrastive_loss: 5.3656 (5.7115) Boundary_loss: 0.016479 (0.029520) Loss: 5.3820 (5.7410) +2025-09-12,06:54:27 | INFO | Train Epoch: 0 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 5.0071 (5.6411) Boundary_loss: 0.016301 (0.028198) Loss: 5.0234 (5.6693) +2025-09-12,06:55:01 | INFO | Train Epoch: 0 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.008 Boundary Ratio: 0.245 Contrastive_loss: 5.0256 (5.5851) Boundary_loss: 0.016530 (0.027137) Loss: 5.0421 (5.6122) +2025-09-12,06:55:34 | INFO | Train Epoch: 0 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 4.9836 (5.5350) Boundary_loss: 0.016219 (0.026228) Loss: 4.9999 (5.5612) +2025-09-12,06:56:07 | INFO | Train Epoch: 0 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 5.0112 (5.4947) Boundary_loss: 0.016794 (0.025502) Loss: 5.0280 (5.5202) +2025-09-12,06:56:41 | INFO | Train Epoch: 0 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.324 Boundary Ratio: 0.247 Contrastive_loss: 4.9563 (5.4562) Boundary_loss: 0.016500 (0.024859) Loss: 4.9728 (5.4811) +2025-09-12,06:57:14 | INFO | Train Epoch: 0 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 4.8986 (5.4191) Boundary_loss: 0.016192 (0.024281) Loss: 4.9148 (5.4434) +2025-09-12,06:57:47 | INFO | Train Epoch: 0 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 4.9738 (5.3912) Boundary_loss: 0.016429 (0.023790) Loss: 4.9902 (5.4150) +2025-09-12,06:58:21 | INFO | Train Epoch: 0 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 49.371 Boundary Ratio: 0.252 Contrastive_loss: 4.7163 (5.3515) Boundary_loss: 0.016384 (0.023355) Loss: 4.7327 (5.3749) +2025-09-12,06:58:55 | INFO | Train Epoch: 0 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 4.7234 (5.3166) Boundary_loss: 0.016432 (0.022970) Loss: 4.7398 (5.3396) +2025-09-12,06:59:28 | INFO | Train Epoch: 0 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 4.8696 (5.2931) Boundary_loss: 0.016462 (0.022628) Loss: 4.8860 (5.3157) +2025-09-12,07:00:02 | INFO | Train Epoch: 0 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 4.6655 (5.2617) Boundary_loss: 0.016563 (0.022324) Loss: 4.6821 (5.2841) +2025-09-12,07:00:35 | INFO | Train Epoch: 0 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 50.352 Boundary Ratio: 0.257 Contrastive_loss: 4.7183 (5.2359) Boundary_loss: 0.016512 (0.022048) Loss: 4.7348 (5.2579) +2025-09-12,07:01:09 | INFO | Train Epoch: 0 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 50.299 Boundary Ratio: 0.257 Contrastive_loss: 4.6272 (5.2082) Boundary_loss: 0.016435 (0.021792) Loss: 4.6437 (5.2300) +2025-09-12,07:01:42 | INFO | Train Epoch: 0 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 47.557 Boundary Ratio: 0.243 Contrastive_loss: 4.5661 (5.1803) Boundary_loss: 0.016377 (0.021557) Loss: 4.5825 (5.2018) +2025-09-12,07:02:16 | INFO | Train Epoch: 0 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 4.6789 (5.1594) Boundary_loss: 0.016301 (0.021338) Loss: 4.6952 (5.1807) +2025-09-12,07:02:50 | INFO | Train Epoch: 0 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 47.180 Boundary Ratio: 0.241 Contrastive_loss: 4.6023 (5.1371) Boundary_loss: 0.016469 (0.021143) Loss: 4.6187 (5.1582) +2025-09-12,07:03:23 | INFO | Train Epoch: 0 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.197 Boundary Ratio: 0.246 Contrastive_loss: 4.5681 (5.1152) Boundary_loss: 0.016642 (0.020970) Loss: 4.5847 (5.1362) +2025-09-12,07:03:57 | INFO | Train Epoch: 0 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 4.5414 (5.0940) Boundary_loss: 0.016417 (0.020801) Loss: 4.5578 (5.1148) +2025-09-12,07:04:30 | INFO | Train Epoch: 0 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 49.762 Boundary Ratio: 0.254 Contrastive_loss: 4.4646 (5.0715) Boundary_loss: 0.016723 (0.020656) Loss: 4.4813 (5.0921) +2025-09-12,07:05:04 | INFO | Train Epoch: 0 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 47.574 Boundary Ratio: 0.243 Contrastive_loss: 4.4624 (5.0505) Boundary_loss: 0.016608 (0.020516) Loss: 4.4790 (5.0710) +2025-09-12,07:05:38 | INFO | Train Epoch: 0 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 50.373 Boundary Ratio: 0.257 Contrastive_loss: 4.4302 (5.0298) Boundary_loss: 0.016518 (0.020383) Loss: 4.4467 (5.0502) +2025-09-12,07:06:11 | INFO | Train Epoch: 0 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 50.477 Boundary Ratio: 0.258 Contrastive_loss: 4.4155 (5.0100) Boundary_loss: 0.016928 (0.020271) Loss: 4.4324 (5.0303) +2025-09-12,07:06:45 | INFO | Train Epoch: 0 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 4.3538 (4.9895) Boundary_loss: 0.016366 (0.020149) Loss: 4.3702 (5.0096) +2025-09-12,07:07:19 | INFO | Train Epoch: 0 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 47.963 Boundary Ratio: 0.245 Contrastive_loss: 4.2292 (4.9664) Boundary_loss: 0.016469 (0.020038) Loss: 4.2456 (4.9865) +2025-09-12,07:07:53 | INFO | Train Epoch: 0 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 4.4959 (4.9526) Boundary_loss: 0.016334 (0.019929) Loss: 4.5122 (4.9725) +2025-09-12,07:08:26 | INFO | Train Epoch: 0 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 49.654 Boundary Ratio: 0.253 Contrastive_loss: 4.3262 (4.9347) Boundary_loss: 0.016477 (0.019830) Loss: 4.3427 (4.9545) +2025-09-12,07:09:00 | INFO | Train Epoch: 0 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.109 Boundary Ratio: 0.245 Contrastive_loss: 4.3331 (4.9180) Boundary_loss: 0.016189 (0.019729) Loss: 4.3493 (4.9377) +2025-09-12,07:09:34 | INFO | Train Epoch: 0 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.262 Boundary Ratio: 0.246 Contrastive_loss: 4.2055 (4.8987) Boundary_loss: 0.016252 (0.019635) Loss: 4.2218 (4.9184) +2025-09-12,07:10:07 | INFO | Train Epoch: 0 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 4.1512 (4.8791) Boundary_loss: 0.016298 (0.019547) Loss: 4.1675 (4.8986) +2025-09-12,07:10:41 | INFO | Train Epoch: 0 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 4.2453 (4.8628) Boundary_loss: 0.016552 (0.019471) Loss: 4.2618 (4.8823) +2025-09-12,07:11:15 | INFO | Train Epoch: 0 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.354 Boundary Ratio: 0.247 Contrastive_loss: 4.1796 (4.8457) Boundary_loss: 0.016464 (0.019395) Loss: 4.1961 (4.8651) +2025-09-12,07:11:49 | INFO | Train Epoch: 0 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.260 Boundary Ratio: 0.251 Contrastive_loss: 4.0868 (4.8272) Boundary_loss: 0.016521 (0.019325) Loss: 4.1033 (4.8466) +2025-09-12,07:12:22 | INFO | Train Epoch: 0 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 47.664 Boundary Ratio: 0.243 Contrastive_loss: 4.2688 (4.8139) Boundary_loss: 0.016410 (0.019256) Loss: 4.2852 (4.8332) +2025-09-12,07:12:56 | INFO | Train Epoch: 0 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 4.1218 (4.7978) Boundary_loss: 0.016417 (0.019190) Loss: 4.1382 (4.8170) +2025-09-12,07:13:30 | INFO | Train Epoch: 0 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 49.588 Boundary Ratio: 0.253 Contrastive_loss: 4.1255 (4.7826) Boundary_loss: 0.016430 (0.019127) Loss: 4.1420 (4.8017) +2025-09-12,07:14:03 | INFO | Train Epoch: 0 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 3.9544 (4.7642) Boundary_loss: 0.016323 (0.019065) Loss: 3.9707 (4.7832) +2025-09-12,07:14:37 | INFO | Train Epoch: 0 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 3.9928 (4.7474) Boundary_loss: 0.016332 (0.019005) Loss: 4.0091 (4.7664) +2025-09-12,07:15:11 | INFO | Train Epoch: 0 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 4.0080 (4.7317) Boundary_loss: 0.016476 (0.018952) Loss: 4.0245 (4.7506) +2025-09-12,07:15:45 | INFO | Train Epoch: 0 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 49.260 Boundary Ratio: 0.251 Contrastive_loss: 3.8338 (4.7129) Boundary_loss: 0.016050 (0.018891) Loss: 3.8498 (4.7318) +2025-09-12,07:16:18 | INFO | Train Epoch: 0 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 3.8501 (4.6953) Boundary_loss: 0.016039 (0.018833) Loss: 3.8661 (4.7142) +2025-09-12,07:16:52 | INFO | Train Epoch: 0 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 4.1480 (4.6844) Boundary_loss: 0.016608 (0.018788) Loss: 4.1646 (4.7032) +2025-09-12,07:17:26 | INFO | Train Epoch: 0 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 3.9038 (4.6691) Boundary_loss: 0.016388 (0.018741) Loss: 3.9202 (4.6878) +2025-09-12,07:18:00 | INFO | Train Epoch: 0 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 49.404 Boundary Ratio: 0.252 Contrastive_loss: 4.0121 (4.6564) Boundary_loss: 0.016448 (0.018697) Loss: 4.0285 (4.6751) +2025-09-12,07:18:34 | INFO | Train Epoch: 0 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 3.8463 (4.6412) Boundary_loss: 0.016362 (0.018653) Loss: 3.8627 (4.6598) +2025-09-12,07:19:08 | INFO | Train Epoch: 0 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 3.8473 (4.6265) Boundary_loss: 0.016445 (0.018612) Loss: 3.8637 (4.6451) +2025-09-12,07:19:42 | INFO | Train Epoch: 0 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.162 Boundary Ratio: 0.246 Contrastive_loss: 3.7306 (4.6102) Boundary_loss: 0.016546 (0.018575) Loss: 3.7472 (4.6287) +2025-09-12,07:20:17 | INFO | Train Epoch: 0 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.008 Boundary Ratio: 0.245 Contrastive_loss: 3.8087 (4.5959) Boundary_loss: 0.016281 (0.018534) Loss: 3.8250 (4.6144) +2025-09-12,07:20:50 | INFO | Train Epoch: 0 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 49.307 Boundary Ratio: 0.252 Contrastive_loss: 3.8013 (4.5819) Boundary_loss: 0.016526 (0.018499) Loss: 3.8179 (4.6004) +2025-09-12,07:21:25 | INFO | Train Epoch: 0 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 3.7414 (4.5674) Boundary_loss: 0.016460 (0.018463) Loss: 3.7579 (4.5859) +2025-09-12,07:21:59 | INFO | Train Epoch: 0 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 3.8504 (4.5553) Boundary_loss: 0.016304 (0.018427) Loss: 3.8667 (4.5737) +2025-09-12,07:22:33 | INFO | Train Epoch: 0 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.664 Boundary Ratio: 0.253 Contrastive_loss: 3.8232 (4.5431) Boundary_loss: 0.016329 (0.018392) Loss: 3.8395 (4.5615) +2025-09-12,07:23:07 | INFO | Train Epoch: 0 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.076 Boundary Ratio: 0.245 Contrastive_loss: 3.8824 (4.5322) Boundary_loss: 0.016658 (0.018363) Loss: 3.8991 (4.5506) +2025-09-12,07:23:41 | INFO | Train Epoch: 0 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 3.7323 (4.5193) Boundary_loss: 0.016759 (0.018338) Loss: 3.7490 (4.5377) +2025-09-12,07:24:15 | INFO | Train Epoch: 0 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 3.7666 (4.5074) Boundary_loss: 0.016664 (0.018311) Loss: 3.7833 (4.5257) +2025-09-12,07:24:49 | INFO | Train Epoch: 0 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 3.5859 (4.4930) Boundary_loss: 0.016311 (0.018280) Loss: 3.6022 (4.5113) +2025-09-12,07:25:22 | INFO | Train Epoch: 0 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.182 Boundary Ratio: 0.246 Contrastive_loss: 3.8030 (4.4824) Boundary_loss: 0.016468 (0.018252) Loss: 3.8195 (4.5006) +2025-09-12,07:25:56 | INFO | Train Epoch: 0 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 3.5981 (4.4690) Boundary_loss: 0.016260 (0.018222) Loss: 3.6144 (4.4872) +2025-09-12,07:26:30 | INFO | Train Epoch: 0 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 3.5865 (4.4558) Boundary_loss: 0.016454 (0.018195) Loss: 3.6029 (4.4740) +2025-09-12,07:27:04 | INFO | Train Epoch: 0 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.570 Boundary Ratio: 0.253 Contrastive_loss: 3.7197 (4.4450) Boundary_loss: 0.016566 (0.018171) Loss: 3.7362 (4.4632) +2025-09-12,07:27:38 | INFO | Train Epoch: 0 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 3.5985 (4.4327) Boundary_loss: 0.016399 (0.018146) Loss: 3.6149 (4.4509) +2025-09-12,07:28:11 | INFO | Train Epoch: 0 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.189 Boundary Ratio: 0.246 Contrastive_loss: 3.6223 (4.4211) Boundary_loss: 0.016631 (0.018124) Loss: 3.6389 (4.4393) +2025-09-12,07:28:45 | INFO | Train Epoch: 0 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 3.3950 (4.4067) Boundary_loss: 0.016482 (0.018101) Loss: 3.4115 (4.4248) +2025-09-12,07:29:19 | INFO | Train Epoch: 0 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.934 Boundary Ratio: 0.255 Contrastive_loss: 3.6252 (4.3958) Boundary_loss: 0.016567 (0.018080) Loss: 3.6418 (4.4139) +2025-09-12,07:29:53 | INFO | Train Epoch: 0 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 3.6115 (4.3851) Boundary_loss: 0.016420 (0.018057) Loss: 3.6280 (4.4031) +2025-09-12,07:30:26 | INFO | Train Epoch: 0 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 3.5093 (4.3733) Boundary_loss: 0.016612 (0.018037) Loss: 3.5259 (4.3913) +2025-09-12,07:31:00 | INFO | Train Epoch: 0 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 49.443 Boundary Ratio: 0.252 Contrastive_loss: 3.4619 (4.3611) Boundary_loss: 0.016323 (0.018014) Loss: 3.4782 (4.3791) +2025-09-12,07:31:34 | INFO | Train Epoch: 0 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 3.6041 (4.3511) Boundary_loss: 0.016430 (0.017994) Loss: 3.6206 (4.3691) +2025-09-12,07:32:07 | INFO | Train Epoch: 0 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 3.4041 (4.3388) Boundary_loss: 0.015868 (0.017966) Loss: 3.4200 (4.3568) +2025-09-12,07:32:41 | INFO | Train Epoch: 0 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.189 Boundary Ratio: 0.246 Contrastive_loss: 3.2976 (4.3255) Boundary_loss: 0.016743 (0.017950) Loss: 3.3143 (4.3434) +2025-09-12,07:33:15 | INFO | Train Epoch: 0 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 3.4426 (4.3143) Boundary_loss: 0.016526 (0.017932) Loss: 3.4591 (4.3323) +2025-09-12,07:33:48 | INFO | Train Epoch: 0 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 3.4018 (4.3029) Boundary_loss: 0.016461 (0.017914) Loss: 3.4183 (4.3208) +2025-09-12,07:34:22 | INFO | Train Epoch: 0 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 3.4941 (4.2929) Boundary_loss: 0.016303 (0.017894) Loss: 3.5104 (4.3108) +2025-09-12,07:34:56 | INFO | Train Epoch: 0 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 3.4491 (4.2826) Boundary_loss: 0.016497 (0.017877) Loss: 3.4656 (4.3005) +2025-09-12,07:35:30 | INFO | Train Epoch: 0 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 3.3735 (4.2717) Boundary_loss: 0.016269 (0.017858) Loss: 3.3897 (4.2895) +2025-09-12,07:36:03 | INFO | Train Epoch: 0 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 50.066 Boundary Ratio: 0.255 Contrastive_loss: 3.4641 (4.2621) Boundary_loss: 0.016532 (0.017842) Loss: 3.4806 (4.2799) +2025-09-12,07:36:37 | INFO | Train Epoch: 0 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 3.3454 (4.2513) Boundary_loss: 0.016353 (0.017824) Loss: 3.3618 (4.2691) +2025-09-12,07:37:10 | INFO | Train Epoch: 0 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 47.754 Boundary Ratio: 0.244 Contrastive_loss: 3.2595 (4.2398) Boundary_loss: 0.016516 (0.017809) Loss: 3.2760 (4.2576) +2025-09-12,07:37:44 | INFO | Train Epoch: 0 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 3.2739 (4.2286) Boundary_loss: 0.016401 (0.017793) Loss: 3.2903 (4.2464) +2025-09-12,07:38:18 | INFO | Train Epoch: 0 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 47.666 Boundary Ratio: 0.243 Contrastive_loss: 3.3009 (4.2181) Boundary_loss: 0.016475 (0.017778) Loss: 3.3174 (4.2359) +2025-09-12,07:38:51 | INFO | Train Epoch: 0 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 3.2891 (4.2077) Boundary_loss: 0.016397 (0.017762) Loss: 3.3055 (4.2254) +2025-09-12,07:39:25 | INFO | Train Epoch: 0 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 3.4549 (4.1993) Boundary_loss: 0.016674 (0.017750) Loss: 3.4715 (4.2171) +2025-09-12,07:39:59 | INFO | Train Epoch: 0 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 49.791 Boundary Ratio: 0.254 Contrastive_loss: 3.2272 (4.1886) Boundary_loss: 0.016684 (0.017739) Loss: 3.2439 (4.2064) +2025-09-12,07:40:33 | INFO | Train Epoch: 0 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 3.4127 (4.1802) Boundary_loss: 0.016515 (0.017725) Loss: 3.4292 (4.1979) +2025-09-12,07:41:06 | INFO | Train Epoch: 0 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 49.342 Boundary Ratio: 0.252 Contrastive_loss: 3.3035 (4.1708) Boundary_loss: 0.016459 (0.017712) Loss: 3.3200 (4.1885) +2025-09-12,07:41:40 | INFO | Train Epoch: 0 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 3.3367 (4.1619) Boundary_loss: 0.016472 (0.017699) Loss: 3.3532 (4.1796) +2025-09-12,07:42:14 | INFO | Train Epoch: 0 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 3.3576 (4.1534) Boundary_loss: 0.016425 (0.017685) Loss: 3.3740 (4.1711) +2025-09-12,07:42:47 | INFO | Train Epoch: 0 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 49.609 Boundary Ratio: 0.253 Contrastive_loss: 3.1754 (4.1432) Boundary_loss: 0.016449 (0.017672) Loss: 3.1918 (4.1609) +2025-09-12,07:43:21 | INFO | Train Epoch: 0 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 3.2130 (4.1336) Boundary_loss: 0.016529 (0.017660) Loss: 3.2295 (4.1513) +2025-09-12,07:43:55 | INFO | Train Epoch: 0 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 3.4298 (4.1265) Boundary_loss: 0.016226 (0.017646) Loss: 3.4460 (4.1441) +2025-09-12,07:44:28 | INFO | Train Epoch: 0 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 3.1380 (4.1165) Boundary_loss: 0.016262 (0.017632) Loss: 3.1542 (4.1341) +2025-09-12,07:45:02 | INFO | Train Epoch: 0 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 47.992 Boundary Ratio: 0.245 Contrastive_loss: 3.1652 (4.1070) Boundary_loss: 0.016548 (0.017621) Loss: 3.1818 (4.1246) +2025-09-12,07:45:36 | INFO | Train Epoch: 0 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 49.293 Boundary Ratio: 0.251 Contrastive_loss: 3.1603 (4.0976) Boundary_loss: 0.016567 (0.017611) Loss: 3.1769 (4.1152) +2025-09-12,07:46:09 | INFO | Train Epoch: 0 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 49.871 Boundary Ratio: 0.254 Contrastive_loss: 3.2528 (4.0893) Boundary_loss: 0.016503 (0.017600) Loss: 3.2693 (4.1069) +2025-09-12,07:46:43 | INFO | Train Epoch: 0 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.438 Boundary Ratio: 0.247 Contrastive_loss: 3.1506 (4.0802) Boundary_loss: 0.016391 (0.017588) Loss: 3.1670 (4.0978) +2025-09-12,07:47:17 | INFO | Train Epoch: 0 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 49.311 Boundary Ratio: 0.252 Contrastive_loss: 3.2379 (4.0721) Boundary_loss: 0.016420 (0.017577) Loss: 3.2543 (4.0897) +2025-09-12,07:47:50 | INFO | Train Epoch: 0 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.188 Boundary Ratio: 0.246 Contrastive_loss: 3.2139 (4.0639) Boundary_loss: 0.016501 (0.017566) Loss: 3.2304 (4.0815) +2025-09-12,07:48:24 | INFO | Train Epoch: 0 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.020 Boundary Ratio: 0.245 Contrastive_loss: 3.1871 (4.0557) Boundary_loss: 0.016409 (0.017556) Loss: 3.2035 (4.0732) +2025-09-12,07:48:58 | INFO | Train Epoch: 0 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 3.2078 (4.0477) Boundary_loss: 0.016291 (0.017544) Loss: 3.2240 (4.0653) +2025-09-12,07:49:31 | INFO | Train Epoch: 0 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.307 Boundary Ratio: 0.246 Contrastive_loss: 2.8845 (4.0370) Boundary_loss: 0.016376 (0.017533) Loss: 2.9009 (4.0545) +2025-09-12,07:50:05 | INFO | Train Epoch: 0 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.205 Boundary Ratio: 0.246 Contrastive_loss: 3.1313 (4.0286) Boundary_loss: 0.016328 (0.017522) Loss: 3.1476 (4.0462) +2025-09-12,07:50:39 | INFO | Train Epoch: 0 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 3.1197 (4.0204) Boundary_loss: 0.016675 (0.017514) Loss: 3.1364 (4.0379) +2025-09-12,07:51:12 | INFO | Train Epoch: 0 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 3.0836 (4.0119) Boundary_loss: 0.016544 (0.017505) Loss: 3.1001 (4.0295) +2025-09-12,07:51:46 | INFO | Train Epoch: 0 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 3.0067 (4.0030) Boundary_loss: 0.016337 (0.017495) Loss: 3.0230 (4.0205) +2025-09-12,07:52:20 | INFO | Train Epoch: 0 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 3.2414 (3.9962) Boundary_loss: 0.016490 (0.017486) Loss: 3.2579 (4.0137) +2025-09-12,07:52:53 | INFO | Train Epoch: 0 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.330 Boundary Ratio: 0.247 Contrastive_loss: 2.9794 (3.9873) Boundary_loss: 0.016674 (0.017479) Loss: 2.9961 (4.0048) +2025-09-12,07:53:27 | INFO | Train Epoch: 0 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 3.0863 (3.9795) Boundary_loss: 0.016386 (0.017469) Loss: 3.1027 (3.9969) +2025-09-12,07:54:01 | INFO | Train Epoch: 0 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 49.494 Boundary Ratio: 0.253 Contrastive_loss: 2.9525 (3.9706) Boundary_loss: 0.016158 (0.017458) Loss: 2.9687 (3.9881) +2025-09-12,07:54:34 | INFO | Train Epoch: 0 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 3.0998 (3.9632) Boundary_loss: 0.016616 (0.017451) Loss: 3.1164 (3.9806) +2025-09-12,07:55:08 | INFO | Train Epoch: 0 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 49.639 Boundary Ratio: 0.253 Contrastive_loss: 3.1283 (3.9561) Boundary_loss: 0.016321 (0.017441) Loss: 3.1446 (3.9735) +2025-09-12,07:55:42 | INFO | Train Epoch: 0 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.426 Boundary Ratio: 0.252 Contrastive_loss: 2.9506 (3.9477) Boundary_loss: 0.016206 (0.017431) Loss: 2.9668 (3.9651) +2025-09-12,07:56:15 | INFO | Train Epoch: 0 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 2.8504 (3.9385) Boundary_loss: 0.016169 (0.017421) Loss: 2.8666 (3.9559) +2025-09-12,07:56:49 | INFO | Train Epoch: 0 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 2.9817 (3.9306) Boundary_loss: 0.016426 (0.017412) Loss: 2.9981 (3.9480) +2025-09-12,07:57:23 | INFO | Train Epoch: 0 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 2.9832 (3.9228) Boundary_loss: 0.016339 (0.017403) Loss: 2.9996 (3.9402) +2025-09-12,07:57:56 | INFO | Train Epoch: 0 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 2.8906 (3.9144) Boundary_loss: 0.016436 (0.017396) Loss: 2.9070 (3.9318) +2025-09-12,07:58:30 | INFO | Train Epoch: 0 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.246 Boundary Ratio: 0.246 Contrastive_loss: 2.9340 (3.9065) Boundary_loss: 0.016484 (0.017388) Loss: 2.9504 (3.9239) +2025-09-12,07:59:03 | INFO | Train Epoch: 0 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 2.9763 (3.8991) Boundary_loss: 0.016256 (0.017379) Loss: 2.9926 (3.9165) +2025-09-12,07:59:37 | INFO | Train Epoch: 0 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 2.9446 (3.8915) Boundary_loss: 0.016685 (0.017374) Loss: 2.9613 (3.9089) +2025-09-12,08:00:11 | INFO | Train Epoch: 0 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 3.1963 (3.8860) Boundary_loss: 0.016173 (0.017364) Loss: 3.2125 (3.9034) +2025-09-12,08:00:44 | INFO | Train Epoch: 0 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 2.9425 (3.8787) Boundary_loss: 0.016325 (0.017356) Loss: 2.9588 (3.8960) +2025-09-12,08:01:18 | INFO | Train Epoch: 0 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 2.8186 (3.8705) Boundary_loss: 0.016399 (0.017349) Loss: 2.8350 (3.8878) +2025-09-12,08:01:51 | INFO | Train Epoch: 0 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 2.7709 (3.8620) Boundary_loss: 0.016392 (0.017341) Loss: 2.7873 (3.8793) +2025-09-12,08:02:25 | INFO | Train Epoch: 0 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 3.0791 (3.8560) Boundary_loss: 0.016371 (0.017334) Loss: 3.0955 (3.8734) +2025-09-12,08:02:59 | INFO | Train Epoch: 0 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 2.7964 (3.8480) Boundary_loss: 0.016154 (0.017325) Loss: 2.8125 (3.8653) +2025-09-12,08:03:32 | INFO | Train Epoch: 0 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.941 Boundary Ratio: 0.255 Contrastive_loss: 2.8842 (3.8408) Boundary_loss: 0.016471 (0.017319) Loss: 2.9007 (3.8581) +2025-09-12,08:04:06 | INFO | Train Epoch: 0 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 3.2156 (3.8361) Boundary_loss: 0.016401 (0.017312) Loss: 3.2320 (3.8534) +2025-09-12,08:04:39 | INFO | Train Epoch: 0 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 2.9173 (3.8293) Boundary_loss: 0.016651 (0.017307) Loss: 2.9340 (3.8466) +2025-09-12,08:05:13 | INFO | Train Epoch: 0 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 49.580 Boundary Ratio: 0.253 Contrastive_loss: 2.8252 (3.8219) Boundary_loss: 0.016487 (0.017301) Loss: 2.8417 (3.8392) +2025-09-12,08:05:47 | INFO | Train Epoch: 0 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 2.9650 (3.8156) Boundary_loss: 0.016370 (0.017294) Loss: 2.9814 (3.8329) +2025-09-12,08:06:20 | INFO | Train Epoch: 0 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 2.7219 (3.8077) Boundary_loss: 0.016225 (0.017286) Loss: 2.7381 (3.8250) +2025-09-12,08:06:54 | INFO | Train Epoch: 0 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 2.7783 (3.8003) Boundary_loss: 0.016389 (0.017280) Loss: 2.7947 (3.8176) +2025-09-12,08:07:27 | INFO | Train Epoch: 0 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 2.8872 (3.7938) Boundary_loss: 0.016409 (0.017274) Loss: 2.9036 (3.8111) +2025-09-12,08:08:01 | INFO | Train Epoch: 0 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 47.787 Boundary Ratio: 0.244 Contrastive_loss: 2.8299 (3.7870) Boundary_loss: 0.016255 (0.017266) Loss: 2.8461 (3.8042) +2025-09-12,08:08:34 | INFO | Train Epoch: 0 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 2.6563 (3.7790) Boundary_loss: 0.016501 (0.017261) Loss: 2.6728 (3.7963) +2025-09-12,08:09:08 | INFO | Train Epoch: 0 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 49.268 Boundary Ratio: 0.251 Contrastive_loss: 2.9839 (3.7734) Boundary_loss: 0.016193 (0.017254) Loss: 3.0001 (3.7907) +2025-09-12,08:09:41 | INFO | Train Epoch: 0 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.861 Boundary Ratio: 0.254 Contrastive_loss: 2.8727 (3.7672) Boundary_loss: 0.016503 (0.017248) Loss: 2.8892 (3.7844) +2025-09-12,08:10:15 | INFO | Train Epoch: 0 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 2.7298 (3.7600) Boundary_loss: 0.016487 (0.017243) Loss: 2.7462 (3.7773) +2025-09-12,08:10:49 | INFO | Train Epoch: 0 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 2.7860 (3.7533) Boundary_loss: 0.016217 (0.017236) Loss: 2.8023 (3.7706) +2025-09-12,08:11:23 | INFO | Train Epoch: 0 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 2.7360 (3.7464) Boundary_loss: 0.016300 (0.017230) Loss: 2.7523 (3.7637) +2025-09-12,08:11:57 | INFO | Train Epoch: 0 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 2.5468 (3.7383) Boundary_loss: 0.016193 (0.017223) Loss: 2.5630 (3.7555) +2025-09-12,08:12:31 | INFO | Train Epoch: 0 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.314 Boundary Ratio: 0.252 Contrastive_loss: 2.6782 (3.7312) Boundary_loss: 0.016248 (0.017216) Loss: 2.6944 (3.7484) +2025-09-12,08:13:05 | INFO | Train Epoch: 0 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 2.7567 (3.7247) Boundary_loss: 0.016338 (0.017210) Loss: 2.7731 (3.7419) +2025-09-12,08:13:40 | INFO | Train Epoch: 0 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 2.7398 (3.7182) Boundary_loss: 0.016427 (0.017205) Loss: 2.7562 (3.7354) +2025-09-12,08:14:14 | INFO | Train Epoch: 0 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 2.6348 (3.7111) Boundary_loss: 0.016357 (0.017199) Loss: 2.6511 (3.7283) +2025-09-12,08:14:48 | INFO | Train Epoch: 0 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 47.984 Boundary Ratio: 0.245 Contrastive_loss: 2.8400 (3.7054) Boundary_loss: 0.016361 (0.017194) Loss: 2.8564 (3.7226) +2025-09-12,08:15:23 | INFO | Train Epoch: 0 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 2.7877 (3.6994) Boundary_loss: 0.016490 (0.017189) Loss: 2.8042 (3.7166) +2025-09-12,08:15:57 | INFO | Train Epoch: 0 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.225 Boundary Ratio: 0.246 Contrastive_loss: 2.7474 (3.6933) Boundary_loss: 0.016510 (0.017185) Loss: 2.7639 (3.7105) +2025-09-12,08:16:31 | INFO | Train Epoch: 0 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 2.7395 (3.6872) Boundary_loss: 0.016485 (0.017181) Loss: 2.7560 (3.7043) +2025-09-12,08:17:06 | INFO | Train Epoch: 0 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 2.6788 (3.6807) Boundary_loss: 0.016397 (0.017176) Loss: 2.6952 (3.6979) +2025-09-12,08:17:40 | INFO | Train Epoch: 0 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 2.8060 (3.6752) Boundary_loss: 0.016267 (0.017170) Loss: 2.8223 (3.6924) +2025-09-12,08:18:15 | INFO | Train Epoch: 0 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.428 Boundary Ratio: 0.252 Contrastive_loss: 2.7105 (3.6691) Boundary_loss: 0.016443 (0.017165) Loss: 2.7270 (3.6863) +2025-09-12,08:18:49 | INFO | Train Epoch: 0 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 49.646 Boundary Ratio: 0.253 Contrastive_loss: 2.7032 (3.6631) Boundary_loss: 0.016315 (0.017160) Loss: 2.7195 (3.6802) +2025-09-12,08:19:24 | INFO | Train Epoch: 0 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 2.5552 (3.6562) Boundary_loss: 0.016316 (0.017155) Loss: 2.5716 (3.6734) +2025-09-12,08:19:58 | INFO | Train Epoch: 0 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.846 Boundary Ratio: 0.254 Contrastive_loss: 2.5707 (3.6495) Boundary_loss: 0.016350 (0.017150) Loss: 2.5870 (3.6667) +2025-09-12,08:20:33 | INFO | Train Epoch: 0 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 2.7915 (3.6442) Boundary_loss: 0.016544 (0.017146) Loss: 2.8081 (3.6614) +2025-09-12,08:21:07 | INFO | Train Epoch: 0 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.053 Boundary Ratio: 0.245 Contrastive_loss: 2.5376 (3.6375) Boundary_loss: 0.016446 (0.017142) Loss: 2.5540 (3.6546) +2025-09-12,08:21:42 | INFO | Train Epoch: 0 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 2.8286 (3.6326) Boundary_loss: 0.016300 (0.017137) Loss: 2.8449 (3.6497) +2025-09-12,08:22:16 | INFO | Train Epoch: 0 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 2.5506 (3.6261) Boundary_loss: 0.016155 (0.017131) Loss: 2.5668 (3.6432) +2025-09-12,08:22:51 | INFO | Train Epoch: 0 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.191 Boundary Ratio: 0.246 Contrastive_loss: 2.5554 (3.6197) Boundary_loss: 0.016390 (0.017126) Loss: 2.5718 (3.6368) +2025-09-12,08:23:26 | INFO | Train Epoch: 0 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 47.934 Boundary Ratio: 0.245 Contrastive_loss: 2.6320 (3.6138) Boundary_loss: 0.016270 (0.017121) Loss: 2.6482 (3.6309) +2025-09-12,08:24:00 | INFO | Train Epoch: 0 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 2.9087 (3.6096) Boundary_loss: 0.016356 (0.017117) Loss: 2.9251 (3.6267) +2025-09-12,08:24:35 | INFO | Train Epoch: 0 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 2.6634 (3.6040) Boundary_loss: 0.016319 (0.017112) Loss: 2.6797 (3.6212) +2025-09-12,08:25:09 | INFO | Train Epoch: 0 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.098 Boundary Ratio: 0.245 Contrastive_loss: 2.5777 (3.5980) Boundary_loss: 0.016096 (0.017106) Loss: 2.5938 (3.6152) +2025-09-12,08:25:44 | INFO | Train Epoch: 0 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 2.7065 (3.5929) Boundary_loss: 0.016222 (0.017101) Loss: 2.7228 (3.6100) +2025-09-12,08:26:19 | INFO | Train Epoch: 0 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 49.926 Boundary Ratio: 0.255 Contrastive_loss: 2.5165 (3.5866) Boundary_loss: 0.016347 (0.017097) Loss: 2.5328 (3.6037) +2025-09-12,08:26:53 | INFO | Train Epoch: 0 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 2.5685 (3.5808) Boundary_loss: 0.016167 (0.017091) Loss: 2.5847 (3.5979) +2025-09-12,08:27:28 | INFO | Train Epoch: 0 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 2.7031 (3.5758) Boundary_loss: 0.016199 (0.017086) Loss: 2.7193 (3.5929) +2025-09-12,08:28:02 | INFO | Train Epoch: 0 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 2.5178 (3.5698) Boundary_loss: 0.016381 (0.017082) Loss: 2.5342 (3.5868) +2025-09-12,08:28:37 | INFO | Train Epoch: 0 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 47.896 Boundary Ratio: 0.244 Contrastive_loss: 2.5802 (3.5642) Boundary_loss: 0.016413 (0.017078) Loss: 2.5966 (3.5812) +2025-09-12,08:29:11 | INFO | Train Epoch: 0 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.025 Boundary Ratio: 0.245 Contrastive_loss: 2.5295 (3.5584) Boundary_loss: 0.016386 (0.017074) Loss: 2.5459 (3.5754) +2025-09-12,08:29:46 | INFO | Train Epoch: 0 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 49.469 Boundary Ratio: 0.252 Contrastive_loss: 2.5863 (3.5529) Boundary_loss: 0.016288 (0.017070) Loss: 2.6026 (3.5700) +2025-09-12,08:30:20 | INFO | Train Epoch: 0 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.246 Boundary Ratio: 0.246 Contrastive_loss: 2.6723 (3.5480) Boundary_loss: 0.016173 (0.017065) Loss: 2.6885 (3.5651) +2025-09-12,08:30:55 | INFO | Train Epoch: 0 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 2.5979 (3.5428) Boundary_loss: 0.016085 (0.017060) Loss: 2.6140 (3.5598) +2025-09-12,08:31:29 | INFO | Train Epoch: 0 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.678 Boundary Ratio: 0.253 Contrastive_loss: 2.5195 (3.5372) Boundary_loss: 0.016277 (0.017055) Loss: 2.5358 (3.5542) +2025-09-12,08:32:04 | INFO | Train Epoch: 0 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 2.5582 (3.5318) Boundary_loss: 0.016193 (0.017051) Loss: 2.5744 (3.5489) +2025-09-12,08:32:38 | INFO | Train Epoch: 0 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 49.689 Boundary Ratio: 0.254 Contrastive_loss: 2.6854 (3.5272) Boundary_loss: 0.016215 (0.017046) Loss: 2.7017 (3.5443) +2025-09-12,08:33:13 | INFO | Train Epoch: 0 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 2.5276 (3.5218) Boundary_loss: 0.016267 (0.017042) Loss: 2.5439 (3.5389) +2025-09-12,08:33:48 | INFO | Train Epoch: 0 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 2.4506 (3.5161) Boundary_loss: 0.016158 (0.017037) Loss: 2.4668 (3.5331) +2025-09-12,08:34:22 | INFO | Train Epoch: 0 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 2.6518 (3.5114) Boundary_loss: 0.016326 (0.017033) Loss: 2.6681 (3.5285) +2025-09-12,08:34:57 | INFO | Train Epoch: 0 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 47.834 Boundary Ratio: 0.244 Contrastive_loss: 2.6149 (3.5067) Boundary_loss: 0.016261 (0.017029) Loss: 2.6312 (3.5237) +2025-09-12,08:35:31 | INFO | Train Epoch: 0 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 2.4632 (3.5011) Boundary_loss: 0.015935 (0.017023) Loss: 2.4791 (3.5182) +2025-09-12,08:36:06 | INFO | Train Epoch: 0 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 2.4605 (3.4957) Boundary_loss: 0.016243 (0.017019) Loss: 2.4767 (3.5127) +2025-09-12,08:36:40 | INFO | Train Epoch: 0 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.584 Boundary Ratio: 0.253 Contrastive_loss: 2.4423 (3.4901) Boundary_loss: 0.016005 (0.017014) Loss: 2.4583 (3.5072) +2025-09-12,08:37:15 | INFO | Train Epoch: 0 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 2.3187 (3.4840) Boundary_loss: 0.016388 (0.017011) Loss: 2.3351 (3.5011) +2025-09-12,08:37:49 | INFO | Train Epoch: 0 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 2.5315 (3.4791) Boundary_loss: 0.016207 (0.017007) Loss: 2.5477 (3.4961) +2025-09-12,08:38:24 | INFO | Train Epoch: 0 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.346 Boundary Ratio: 0.252 Contrastive_loss: 2.4424 (3.4738) Boundary_loss: 0.016292 (0.017003) Loss: 2.4586 (3.4908) +2025-09-12,08:38:59 | INFO | Train Epoch: 0 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.979 Boundary Ratio: 0.255 Contrastive_loss: 2.4062 (3.4683) Boundary_loss: 0.016092 (0.016998) Loss: 2.4222 (3.4853) +2025-09-12,08:39:33 | INFO | Train Epoch: 0 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 2.5466 (3.4636) Boundary_loss: 0.016218 (0.016994) Loss: 2.5628 (3.4806) +2025-09-12,08:40:08 | INFO | Train Epoch: 0 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 2.5226 (3.4588) Boundary_loss: 0.016379 (0.016991) Loss: 2.5390 (3.4758) +2025-09-12,08:40:43 | INFO | Train Epoch: 0 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 2.6327 (3.4546) Boundary_loss: 0.016153 (0.016987) Loss: 2.6489 (3.4716) +2025-09-12,08:41:17 | INFO | Train Epoch: 0 [10138112/26365952 (38%)] Avg Boundaries (per batch): 49.221 Boundary Ratio: 0.251 Contrastive_loss: 2.4526 (3.4496) Boundary_loss: 0.016250 (0.016983) Loss: 2.4688 (3.4666) +2025-09-12,08:41:52 | INFO | Train Epoch: 0 [10189312/26365952 (39%)] Avg Boundaries (per batch): 47.625 Boundary Ratio: 0.243 Contrastive_loss: 2.4163 (3.4444) Boundary_loss: 0.016158 (0.016979) Loss: 2.4324 (3.4614) +2025-09-12,08:42:26 | INFO | Train Epoch: 0 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.914 Boundary Ratio: 0.255 Contrastive_loss: 2.7136 (3.4408) Boundary_loss: 0.016164 (0.016975) Loss: 2.7298 (3.4578) +2025-09-12,08:43:01 | INFO | Train Epoch: 0 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 2.4359 (3.4358) Boundary_loss: 0.016201 (0.016971) Loss: 2.4521 (3.4528) +2025-09-12,08:43:35 | INFO | Train Epoch: 0 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 2.3936 (3.4307) Boundary_loss: 0.016231 (0.016968) Loss: 2.4098 (3.4477) +2025-09-12,08:44:10 | INFO | Train Epoch: 0 [10394112/26365952 (39%)] Avg Boundaries (per batch): 52.170 Boundary Ratio: 0.266 Contrastive_loss: 2.4000 (3.4256) Boundary_loss: 0.016831 (0.016967) Loss: 2.4169 (3.4426) +2025-09-12,08:44:44 | INFO | Train Epoch: 0 [10445312/26365952 (40%)] Avg Boundaries (per batch): 47.607 Boundary Ratio: 0.243 Contrastive_loss: 2.4597 (3.4209) Boundary_loss: 0.016168 (0.016963) Loss: 2.4758 (3.4379) +2025-09-12,08:45:18 | INFO | Train Epoch: 0 [10496512/26365952 (40%)] Avg Boundaries (per batch): 47.486 Boundary Ratio: 0.242 Contrastive_loss: 2.4245 (3.4161) Boundary_loss: 0.016344 (0.016960) Loss: 2.4409 (3.4331) +2025-09-12,08:45:53 | INFO | Train Epoch: 0 [10547712/26365952 (40%)] Avg Boundaries (per batch): 47.959 Boundary Ratio: 0.245 Contrastive_loss: 2.3429 (3.4109) Boundary_loss: 0.016444 (0.016957) Loss: 2.3594 (3.4279) +2025-09-12,08:46:27 | INFO | Train Epoch: 0 [10598912/26365952 (40%)] Avg Boundaries (per batch): 46.621 Boundary Ratio: 0.238 Contrastive_loss: 2.2298 (3.4052) Boundary_loss: 0.016221 (0.016954) Loss: 2.2460 (3.4222) +2025-09-12,08:47:01 | INFO | Train Epoch: 0 [10650112/26365952 (40%)] Avg Boundaries (per batch): 50.242 Boundary Ratio: 0.256 Contrastive_loss: 2.3517 (3.4002) Boundary_loss: 0.016075 (0.016950) Loss: 2.3677 (3.4171) +2025-09-12,08:47:35 | INFO | Train Epoch: 0 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 2.5340 (3.3961) Boundary_loss: 0.016379 (0.016947) Loss: 2.5504 (3.4130) +2025-09-12,08:48:10 | INFO | Train Epoch: 0 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.895 Boundary Ratio: 0.255 Contrastive_loss: 2.3366 (3.3910) Boundary_loss: 0.016237 (0.016944) Loss: 2.3529 (3.4080) +2025-09-12,08:48:44 | INFO | Train Epoch: 0 [10803712/26365952 (41%)] Avg Boundaries (per batch): 46.805 Boundary Ratio: 0.239 Contrastive_loss: 2.4123 (3.3864) Boundary_loss: 0.016151 (0.016940) Loss: 2.4285 (3.4034) +2025-09-12,08:49:18 | INFO | Train Epoch: 0 [10854912/26365952 (41%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 2.4048 (3.3818) Boundary_loss: 0.015992 (0.016935) Loss: 2.4208 (3.3988) +2025-09-12,08:49:52 | INFO | Train Epoch: 0 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 2.2382 (3.3765) Boundary_loss: 0.016023 (0.016931) Loss: 2.2542 (3.3934) +2025-09-12,08:50:26 | INFO | Train Epoch: 0 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 2.4789 (3.3723) Boundary_loss: 0.016087 (0.016927) Loss: 2.4949 (3.3892) +2025-09-12,08:51:00 | INFO | Train Epoch: 0 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 2.4212 (3.3679) Boundary_loss: 0.016046 (0.016923) Loss: 2.4372 (3.3848) +2025-09-12,08:51:35 | INFO | Train Epoch: 0 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.898 Boundary Ratio: 0.255 Contrastive_loss: 2.3912 (3.3634) Boundary_loss: 0.016036 (0.016919) Loss: 2.4073 (3.3803) +2025-09-12,08:52:09 | INFO | Train Epoch: 0 [11110912/26365952 (42%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 2.2527 (3.3583) Boundary_loss: 0.016165 (0.016916) Loss: 2.2689 (3.3752) +2025-09-12,08:52:43 | INFO | Train Epoch: 0 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 2.2280 (3.3531) Boundary_loss: 0.015898 (0.016911) Loss: 2.2439 (3.3701) +2025-09-12,08:53:17 | INFO | Train Epoch: 0 [11213312/26365952 (43%)] Avg Boundaries (per batch): 47.941 Boundary Ratio: 0.245 Contrastive_loss: 2.2111 (3.3479) Boundary_loss: 0.016239 (0.016908) Loss: 2.2273 (3.3649) +2025-09-12,08:53:51 | INFO | Train Epoch: 0 [11264512/26365952 (43%)] Avg Boundaries (per batch): 49.805 Boundary Ratio: 0.254 Contrastive_loss: 2.4100 (3.3437) Boundary_loss: 0.016107 (0.016904) Loss: 2.4261 (3.3606) +2025-09-12,08:54:25 | INFO | Train Epoch: 0 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.078 Boundary Ratio: 0.245 Contrastive_loss: 2.4819 (3.3398) Boundary_loss: 0.016019 (0.016900) Loss: 2.4979 (3.3567) +2025-09-12,08:54:59 | INFO | Train Epoch: 0 [11366912/26365952 (43%)] Avg Boundaries (per batch): 46.895 Boundary Ratio: 0.239 Contrastive_loss: 2.3972 (3.3356) Boundary_loss: 0.016326 (0.016898) Loss: 2.4135 (3.3525) +2025-09-12,08:55:33 | INFO | Train Epoch: 0 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 2.3772 (3.3313) Boundary_loss: 0.016098 (0.016894) Loss: 2.3933 (3.3482) +2025-09-12,08:56:07 | INFO | Train Epoch: 0 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 2.4854 (3.3276) Boundary_loss: 0.016182 (0.016891) Loss: 2.5016 (3.3444) +2025-09-12,08:56:42 | INFO | Train Epoch: 0 [11520512/26365952 (44%)] Avg Boundaries (per batch): 47.990 Boundary Ratio: 0.245 Contrastive_loss: 2.3123 (3.3231) Boundary_loss: 0.015915 (0.016887) Loss: 2.3282 (3.3400) +2025-09-12,08:57:16 | INFO | Train Epoch: 0 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 2.3474 (3.3188) Boundary_loss: 0.016033 (0.016883) Loss: 2.3634 (3.3356) +2025-09-12,08:57:49 | INFO | Train Epoch: 0 [11622912/26365952 (44%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 2.2992 (3.3143) Boundary_loss: 0.015897 (0.016879) Loss: 2.3151 (3.3312) +2025-09-12,08:58:24 | INFO | Train Epoch: 0 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.855 Boundary Ratio: 0.254 Contrastive_loss: 2.2031 (3.3094) Boundary_loss: 0.016230 (0.016876) Loss: 2.2194 (3.3263) +2025-09-12,08:58:57 | INFO | Train Epoch: 0 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.094 Boundary Ratio: 0.245 Contrastive_loss: 2.3478 (3.3053) Boundary_loss: 0.016075 (0.016872) Loss: 2.3639 (3.3221) +2025-09-12,08:59:32 | INFO | Train Epoch: 0 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 2.4853 (3.3017) Boundary_loss: 0.015790 (0.016868) Loss: 2.5011 (3.3186) +2025-09-12,09:00:06 | INFO | Train Epoch: 0 [11827712/26365952 (45%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 2.2777 (3.2973) Boundary_loss: 0.016041 (0.016864) Loss: 2.2938 (3.3142) +2025-09-12,09:00:40 | INFO | Train Epoch: 0 [11878912/26365952 (45%)] Avg Boundaries (per batch): 47.746 Boundary Ratio: 0.244 Contrastive_loss: 2.2081 (3.2926) Boundary_loss: 0.015864 (0.016860) Loss: 2.2240 (3.3095) +2025-09-12,09:01:14 | INFO | Train Epoch: 0 [11930112/26365952 (45%)] Avg Boundaries (per batch): 47.770 Boundary Ratio: 0.244 Contrastive_loss: 2.4395 (3.2890) Boundary_loss: 0.016352 (0.016858) Loss: 2.4559 (3.3058) +2025-09-12,09:01:48 | INFO | Train Epoch: 0 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.246 Boundary Ratio: 0.246 Contrastive_loss: 2.2177 (3.2844) Boundary_loss: 0.015808 (0.016853) Loss: 2.2335 (3.3013) +2025-09-12,09:02:22 | INFO | Train Epoch: 0 [12032512/26365952 (46%)] Avg Boundaries (per batch): 47.205 Boundary Ratio: 0.241 Contrastive_loss: 2.4416 (3.2808) Boundary_loss: 0.016069 (0.016850) Loss: 2.4577 (3.2977) +2025-09-12,09:02:56 | INFO | Train Epoch: 0 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 2.0085 (3.2755) Boundary_loss: 0.015771 (0.016845) Loss: 2.0242 (3.2923) +2025-09-12,09:03:30 | INFO | Train Epoch: 0 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 2.2869 (3.2713) Boundary_loss: 0.015925 (0.016841) Loss: 2.3029 (3.2882) +2025-09-12,09:04:04 | INFO | Train Epoch: 0 [12186112/26365952 (46%)] Avg Boundaries (per batch): 49.729 Boundary Ratio: 0.254 Contrastive_loss: 2.3379 (3.2674) Boundary_loss: 0.016182 (0.016839) Loss: 2.3541 (3.2843) +2025-09-12,09:04:38 | INFO | Train Epoch: 0 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 2.2615 (3.2632) Boundary_loss: 0.015857 (0.016835) Loss: 2.2773 (3.2801) +2025-09-12,09:05:12 | INFO | Train Epoch: 0 [12288512/26365952 (47%)] Avg Boundaries (per batch): 47.809 Boundary Ratio: 0.244 Contrastive_loss: 2.1811 (3.2587) Boundary_loss: 0.016075 (0.016831) Loss: 2.1972 (3.2756) +2025-09-12,09:05:46 | INFO | Train Epoch: 0 [12339712/26365952 (47%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 2.3876 (3.2551) Boundary_loss: 0.016136 (0.016828) Loss: 2.4038 (3.2720) +2025-09-12,09:06:20 | INFO | Train Epoch: 0 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 2.2779 (3.2511) Boundary_loss: 0.015991 (0.016825) Loss: 2.2939 (3.2679) +2025-09-12,09:06:54 | INFO | Train Epoch: 0 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.053 Boundary Ratio: 0.245 Contrastive_loss: 2.4684 (3.2479) Boundary_loss: 0.015697 (0.016820) Loss: 2.4841 (3.2647) +2025-09-12,09:07:28 | INFO | Train Epoch: 0 [12493312/26365952 (47%)] Avg Boundaries (per batch): 47.828 Boundary Ratio: 0.244 Contrastive_loss: 2.1115 (3.2433) Boundary_loss: 0.015947 (0.016817) Loss: 2.1275 (3.2601) +2025-09-12,09:08:02 | INFO | Train Epoch: 0 [12544512/26365952 (48%)] Avg Boundaries (per batch): 47.908 Boundary Ratio: 0.244 Contrastive_loss: 2.2188 (3.2391) Boundary_loss: 0.015947 (0.016813) Loss: 2.2347 (3.2559) +2025-09-12,09:08:37 | INFO | Train Epoch: 0 [12595712/26365952 (48%)] Avg Boundaries (per batch): 50.053 Boundary Ratio: 0.255 Contrastive_loss: 2.3635 (3.2356) Boundary_loss: 0.016091 (0.016810) Loss: 2.3796 (3.2524) +2025-09-12,09:09:11 | INFO | Train Epoch: 0 [12646912/26365952 (48%)] Avg Boundaries (per batch): 49.418 Boundary Ratio: 0.252 Contrastive_loss: 2.2752 (3.2317) Boundary_loss: 0.015973 (0.016807) Loss: 2.2911 (3.2485) +2025-09-12,09:09:44 | INFO | Train Epoch: 0 [12698112/26365952 (48%)] Avg Boundaries (per batch): 49.574 Boundary Ratio: 0.253 Contrastive_loss: 2.4676 (3.2286) Boundary_loss: 0.015758 (0.016803) Loss: 2.4834 (3.2454) +2025-09-12,09:10:18 | INFO | Train Epoch: 0 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 2.3588 (3.2251) Boundary_loss: 0.015808 (0.016799) Loss: 2.3746 (3.2419) +2025-09-12,09:10:52 | INFO | Train Epoch: 0 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 2.1392 (3.2208) Boundary_loss: 0.016050 (0.016796) Loss: 2.1552 (3.2376) +2025-09-12,09:11:26 | INFO | Train Epoch: 0 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.121 Boundary Ratio: 0.246 Contrastive_loss: 2.2878 (3.2171) Boundary_loss: 0.016057 (0.016793) Loss: 2.3039 (3.2339) +2025-09-12,09:12:00 | INFO | Train Epoch: 0 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 2.2486 (3.2133) Boundary_loss: 0.015831 (0.016789) Loss: 2.2645 (3.2301) +2025-09-12,09:12:34 | INFO | Train Epoch: 0 [12954112/26365952 (49%)] Avg Boundaries (per batch): 51.590 Boundary Ratio: 0.263 Contrastive_loss: 2.2184 (3.2094) Boundary_loss: 0.016656 (0.016789) Loss: 2.2351 (3.2262) +2025-09-12,09:13:07 | INFO | Train Epoch: 0 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 2.2709 (3.2057) Boundary_loss: 0.015749 (0.016785) Loss: 2.2866 (3.2225) +2025-09-12,09:13:40 | INFO | Train Epoch: 0 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 2.2268 (3.2019) Boundary_loss: 0.016006 (0.016781) Loss: 2.2429 (3.2186) +2025-09-12,09:14:13 | INFO | Train Epoch: 0 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.115 Boundary Ratio: 0.245 Contrastive_loss: 2.3487 (3.1985) Boundary_loss: 0.015932 (0.016778) Loss: 2.3646 (3.2153) +2025-09-12,09:14:47 | INFO | Train Epoch: 0 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 2.3080 (3.1951) Boundary_loss: 0.015754 (0.016774) Loss: 2.3237 (3.2119) +2025-09-12,09:15:20 | INFO | Train Epoch: 0 [13210112/26365952 (50%)] Avg Boundaries (per batch): 47.926 Boundary Ratio: 0.245 Contrastive_loss: 2.3763 (3.1919) Boundary_loss: 0.015921 (0.016771) Loss: 2.3922 (3.2087) +2025-09-12,09:15:53 | INFO | Train Epoch: 0 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.369 Boundary Ratio: 0.247 Contrastive_loss: 2.2298 (3.1882) Boundary_loss: 0.015795 (0.016767) Loss: 2.2456 (3.2050) +2025-09-12,09:16:26 | INFO | Train Epoch: 0 [13312512/26365952 (50%)] Avg Boundaries (per batch): 50.451 Boundary Ratio: 0.257 Contrastive_loss: 2.2014 (3.1845) Boundary_loss: 0.016011 (0.016764) Loss: 2.2174 (3.2012) +2025-09-12,09:17:00 | INFO | Train Epoch: 0 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 2.1808 (3.1806) Boundary_loss: 0.015858 (0.016761) Loss: 2.1967 (3.1974) +2025-09-12,09:17:33 | INFO | Train Epoch: 0 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.760 Boundary Ratio: 0.254 Contrastive_loss: 2.2845 (3.1772) Boundary_loss: 0.015829 (0.016757) Loss: 2.3004 (3.1940) +2025-09-12,09:18:06 | INFO | Train Epoch: 0 [13466112/26365952 (51%)] Avg Boundaries (per batch): 50.131 Boundary Ratio: 0.256 Contrastive_loss: 2.2141 (3.1736) Boundary_loss: 0.016255 (0.016755) Loss: 2.2304 (3.1903) +2025-09-12,09:18:39 | INFO | Train Epoch: 0 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 2.2706 (3.1702) Boundary_loss: 0.015752 (0.016752) Loss: 2.2863 (3.1869) +2025-09-12,09:19:12 | INFO | Train Epoch: 0 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.029 Boundary Ratio: 0.245 Contrastive_loss: 2.2462 (3.1667) Boundary_loss: 0.015949 (0.016749) Loss: 2.2622 (3.1834) +2025-09-12,09:19:46 | INFO | Train Epoch: 0 [13619712/26365952 (52%)] Avg Boundaries (per batch): 49.746 Boundary Ratio: 0.254 Contrastive_loss: 2.0241 (3.1624) Boundary_loss: 0.015779 (0.016745) Loss: 2.0399 (3.1791) +2025-09-12,09:20:19 | INFO | Train Epoch: 0 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 2.1543 (3.1586) Boundary_loss: 0.015687 (0.016741) Loss: 2.1700 (3.1754) +2025-09-12,09:20:52 | INFO | Train Epoch: 0 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.188 Boundary Ratio: 0.246 Contrastive_loss: 2.2495 (3.1553) Boundary_loss: 0.016014 (0.016738) Loss: 2.2655 (3.1720) +2025-09-12,09:21:25 | INFO | Train Epoch: 0 [13773312/26365952 (52%)] Avg Boundaries (per batch): 47.938 Boundary Ratio: 0.245 Contrastive_loss: 2.1126 (3.1514) Boundary_loss: 0.015829 (0.016735) Loss: 2.1284 (3.1681) +2025-09-12,09:21:58 | INFO | Train Epoch: 0 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.281 Boundary Ratio: 0.251 Contrastive_loss: 2.2083 (3.1479) Boundary_loss: 0.015593 (0.016731) Loss: 2.2239 (3.1647) +2025-09-12,09:22:31 | INFO | Train Epoch: 0 [13875712/26365952 (53%)] Avg Boundaries (per batch): 49.922 Boundary Ratio: 0.255 Contrastive_loss: 2.2858 (3.1448) Boundary_loss: 0.016100 (0.016728) Loss: 2.3019 (3.1615) +2025-09-12,09:23:04 | INFO | Train Epoch: 0 [13926912/26365952 (53%)] Avg Boundaries (per batch): 49.539 Boundary Ratio: 0.253 Contrastive_loss: 2.2344 (3.1414) Boundary_loss: 0.015789 (0.016725) Loss: 2.2502 (3.1581) +2025-09-12,09:23:37 | INFO | Train Epoch: 0 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.156 Boundary Ratio: 0.246 Contrastive_loss: 2.2319 (3.1381) Boundary_loss: 0.015543 (0.016721) Loss: 2.2474 (3.1548) +2025-09-12,09:24:10 | INFO | Train Epoch: 0 [14029312/26365952 (53%)] Avg Boundaries (per batch): 47.275 Boundary Ratio: 0.241 Contrastive_loss: 2.1870 (3.1346) Boundary_loss: 0.015680 (0.016717) Loss: 2.2027 (3.1514) +2025-09-12,09:24:43 | INFO | Train Epoch: 0 [14080512/26365952 (53%)] Avg Boundaries (per batch): 51.396 Boundary Ratio: 0.262 Contrastive_loss: 2.1405 (3.1310) Boundary_loss: 0.016205 (0.016715) Loss: 2.1567 (3.1478) +2025-09-12,09:25:17 | INFO | Train Epoch: 0 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 2.0762 (3.1272) Boundary_loss: 0.015746 (0.016711) Loss: 2.0920 (3.1439) +2025-09-12,09:25:50 | INFO | Train Epoch: 0 [14182912/26365952 (54%)] Avg Boundaries (per batch): 47.096 Boundary Ratio: 0.240 Contrastive_loss: 2.2183 (3.1240) Boundary_loss: 0.016420 (0.016710) Loss: 2.2347 (3.1407) +2025-09-12,09:26:23 | INFO | Train Epoch: 0 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 1.9629 (3.1198) Boundary_loss: 0.015803 (0.016707) Loss: 1.9787 (3.1365) +2025-09-12,09:26:56 | INFO | Train Epoch: 0 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.070 Boundary Ratio: 0.245 Contrastive_loss: 2.1769 (3.1164) Boundary_loss: 0.015764 (0.016704) Loss: 2.1926 (3.1331) +2025-09-12,09:27:29 | INFO | Train Epoch: 0 [14336512/26365952 (54%)] Avg Boundaries (per batch): 47.918 Boundary Ratio: 0.244 Contrastive_loss: 2.2244 (3.1133) Boundary_loss: 0.015843 (0.016701) Loss: 2.2402 (3.1300) +2025-09-12,09:28:02 | INFO | Train Epoch: 0 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 2.1904 (3.1100) Boundary_loss: 0.015668 (0.016697) Loss: 2.2061 (3.1267) +2025-09-12,09:28:35 | INFO | Train Epoch: 0 [14438912/26365952 (55%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 2.0523 (3.1062) Boundary_loss: 0.015817 (0.016694) Loss: 2.0681 (3.1229) +2025-09-12,09:29:08 | INFO | Train Epoch: 0 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 2.2001 (3.1031) Boundary_loss: 0.015860 (0.016691) Loss: 2.2160 (3.1197) +2025-09-12,09:29:41 | INFO | Train Epoch: 0 [14541312/26365952 (55%)] Avg Boundaries (per batch): 49.881 Boundary Ratio: 0.254 Contrastive_loss: 2.0647 (3.0994) Boundary_loss: 0.015686 (0.016687) Loss: 2.0803 (3.1161) +2025-09-12,09:30:14 | INFO | Train Epoch: 0 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.197 Boundary Ratio: 0.246 Contrastive_loss: 2.2847 (3.0966) Boundary_loss: 0.015599 (0.016684) Loss: 2.3003 (3.1132) +2025-09-12,09:30:48 | INFO | Train Epoch: 0 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 2.1897 (3.0934) Boundary_loss: 0.015735 (0.016680) Loss: 2.2054 (3.1101) +2025-09-12,09:31:21 | INFO | Train Epoch: 0 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 2.0781 (3.0899) Boundary_loss: 0.015759 (0.016677) Loss: 2.0938 (3.1066) +2025-09-12,09:31:54 | INFO | Train Epoch: 0 [14746112/26365952 (56%)] Avg Boundaries (per batch): 50.174 Boundary Ratio: 0.256 Contrastive_loss: 1.9651 (3.0860) Boundary_loss: 0.015568 (0.016673) Loss: 1.9807 (3.1027) +2025-09-12,09:32:27 | INFO | Train Epoch: 0 [14797312/26365952 (56%)] Avg Boundaries (per batch): 46.863 Boundary Ratio: 0.239 Contrastive_loss: 2.1735 (3.0828) Boundary_loss: 0.015712 (0.016670) Loss: 2.1892 (3.0995) +2025-09-12,09:33:00 | INFO | Train Epoch: 0 [14848512/26365952 (56%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 2.1000 (3.0795) Boundary_loss: 0.015812 (0.016667) Loss: 2.1158 (3.0961) +2025-09-12,09:33:33 | INFO | Train Epoch: 0 [14899712/26365952 (57%)] Avg Boundaries (per batch): 47.293 Boundary Ratio: 0.241 Contrastive_loss: 2.0054 (3.0758) Boundary_loss: 0.015729 (0.016664) Loss: 2.0212 (3.0924) +2025-09-12,09:34:06 | INFO | Train Epoch: 0 [14950912/26365952 (57%)] Avg Boundaries (per batch): 47.473 Boundary Ratio: 0.242 Contrastive_loss: 2.1827 (3.0727) Boundary_loss: 0.015719 (0.016661) Loss: 2.1984 (3.0894) +2025-09-12,09:34:39 | INFO | Train Epoch: 0 [15002112/26365952 (57%)] Avg Boundaries (per batch): 50.602 Boundary Ratio: 0.258 Contrastive_loss: 2.0839 (3.0694) Boundary_loss: 0.015895 (0.016658) Loss: 2.0998 (3.0860) +2025-09-12,09:35:12 | INFO | Train Epoch: 0 [15053312/26365952 (57%)] Avg Boundaries (per batch): 47.541 Boundary Ratio: 0.243 Contrastive_loss: 2.0782 (3.0660) Boundary_loss: 0.015778 (0.016655) Loss: 2.0940 (3.0827) +2025-09-12,09:35:45 | INFO | Train Epoch: 0 [15104512/26365952 (57%)] Avg Boundaries (per batch): 50.090 Boundary Ratio: 0.256 Contrastive_loss: 2.1276 (3.0628) Boundary_loss: 0.016016 (0.016653) Loss: 2.1436 (3.0795) +2025-09-12,09:36:18 | INFO | Train Epoch: 0 [15155712/26365952 (57%)] Avg Boundaries (per batch): 50.564 Boundary Ratio: 0.258 Contrastive_loss: 2.0233 (3.0593) Boundary_loss: 0.015723 (0.016650) Loss: 2.0390 (3.0760) +2025-09-12,09:36:50 | INFO | Train Epoch: 0 [15206912/26365952 (58%)] Avg Boundaries (per batch): 47.379 Boundary Ratio: 0.242 Contrastive_loss: 2.2070 (3.0565) Boundary_loss: 0.015541 (0.016646) Loss: 2.2225 (3.0731) +2025-09-12,09:37:23 | INFO | Train Epoch: 0 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.268 Boundary Ratio: 0.246 Contrastive_loss: 2.1615 (3.0535) Boundary_loss: 0.015604 (0.016643) Loss: 2.1771 (3.0701) +2025-09-12,09:37:56 | INFO | Train Epoch: 0 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 2.1411 (3.0504) Boundary_loss: 0.015513 (0.016639) Loss: 2.1566 (3.0671) +2025-09-12,09:38:29 | INFO | Train Epoch: 0 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.092 Boundary Ratio: 0.245 Contrastive_loss: 2.0378 (3.0471) Boundary_loss: 0.015593 (0.016635) Loss: 2.0534 (3.0637) +2025-09-12,09:39:02 | INFO | Train Epoch: 0 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 2.0646 (3.0438) Boundary_loss: 0.015752 (0.016632) Loss: 2.0803 (3.0605) +2025-09-12,09:39:35 | INFO | Train Epoch: 0 [15462912/26365952 (59%)] Avg Boundaries (per batch): 47.848 Boundary Ratio: 0.244 Contrastive_loss: 2.3066 (3.0414) Boundary_loss: 0.015777 (0.016630) Loss: 2.3224 (3.0580) +2025-09-12,09:40:08 | INFO | Train Epoch: 0 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 2.1733 (3.0385) Boundary_loss: 0.015487 (0.016626) Loss: 2.1887 (3.0552) +2025-09-12,09:40:41 | INFO | Train Epoch: 0 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 2.1292 (3.0356) Boundary_loss: 0.015745 (0.016623) Loss: 2.1449 (3.0522) +2025-09-12,09:41:14 | INFO | Train Epoch: 0 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 2.2753 (3.0331) Boundary_loss: 0.015572 (0.016619) Loss: 2.2909 (3.0497) +2025-09-12,09:41:47 | INFO | Train Epoch: 0 [15667712/26365952 (59%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 2.0565 (3.0299) Boundary_loss: 0.015660 (0.016616) Loss: 2.0721 (3.0465) +2025-09-12,09:42:20 | INFO | Train Epoch: 0 [15718912/26365952 (60%)] Avg Boundaries (per batch): 50.832 Boundary Ratio: 0.259 Contrastive_loss: 2.0161 (3.0266) Boundary_loss: 0.015768 (0.016614) Loss: 2.0319 (3.0432) +2025-09-12,09:42:53 | INFO | Train Epoch: 0 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 1.9727 (3.0232) Boundary_loss: 0.015262 (0.016609) Loss: 1.9880 (3.0398) +2025-09-12,09:43:26 | INFO | Train Epoch: 0 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 2.1750 (3.0205) Boundary_loss: 0.015499 (0.016606) Loss: 2.1905 (3.0371) +2025-09-12,09:43:59 | INFO | Train Epoch: 0 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 1.9590 (3.0170) Boundary_loss: 0.015580 (0.016602) Loss: 1.9746 (3.0336) +2025-09-12,09:44:31 | INFO | Train Epoch: 0 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 2.1135 (3.0141) Boundary_loss: 0.015482 (0.016599) Loss: 2.1289 (3.0307) +2025-09-12,09:45:04 | INFO | Train Epoch: 0 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.166 Boundary Ratio: 0.246 Contrastive_loss: 2.0206 (3.0110) Boundary_loss: 0.015515 (0.016595) Loss: 2.0361 (3.0276) +2025-09-12,09:45:37 | INFO | Train Epoch: 0 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.232 Boundary Ratio: 0.246 Contrastive_loss: 1.9719 (3.0077) Boundary_loss: 0.015558 (0.016592) Loss: 1.9875 (3.0243) +2025-09-12,09:46:10 | INFO | Train Epoch: 0 [16077312/26365952 (61%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 1.9411 (3.0043) Boundary_loss: 0.015367 (0.016588) Loss: 1.9565 (3.0209) +2025-09-12,09:46:44 | INFO | Train Epoch: 0 [16128512/26365952 (61%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 2.0795 (3.0014) Boundary_loss: 0.015492 (0.016585) Loss: 2.0950 (3.0179) +2025-09-12,09:47:17 | INFO | Train Epoch: 0 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.215 Boundary Ratio: 0.246 Contrastive_loss: 2.1697 (2.9987) Boundary_loss: 0.015639 (0.016582) Loss: 2.1854 (3.0153) +2025-09-12,09:47:50 | INFO | Train Epoch: 0 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 1.9738 (2.9955) Boundary_loss: 0.015667 (0.016579) Loss: 1.9894 (3.0121) +2025-09-12,09:48:23 | INFO | Train Epoch: 0 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 2.2730 (2.9932) Boundary_loss: 0.015771 (0.016576) Loss: 2.2888 (3.0098) +2025-09-12,09:48:56 | INFO | Train Epoch: 0 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 2.0922 (2.9904) Boundary_loss: 0.015478 (0.016573) Loss: 2.1076 (3.0070) +2025-09-12,09:49:30 | INFO | Train Epoch: 0 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 1.9335 (2.9871) Boundary_loss: 0.015466 (0.016569) Loss: 1.9490 (3.0037) +2025-09-12,09:50:03 | INFO | Train Epoch: 0 [16435712/26365952 (62%)] Avg Boundaries (per batch): 49.295 Boundary Ratio: 0.252 Contrastive_loss: 2.0480 (2.9842) Boundary_loss: 0.015634 (0.016566) Loss: 2.0636 (3.0008) +2025-09-12,09:50:36 | INFO | Train Epoch: 0 [16486912/26365952 (63%)] Avg Boundaries (per batch): 46.695 Boundary Ratio: 0.238 Contrastive_loss: 2.2023 (2.9818) Boundary_loss: 0.015613 (0.016564) Loss: 2.2180 (2.9984) +2025-09-12,09:51:09 | INFO | Train Epoch: 0 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 2.0410 (2.9789) Boundary_loss: 0.015507 (0.016560) Loss: 2.0565 (2.9955) +2025-09-12,09:51:42 | INFO | Train Epoch: 0 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 2.0692 (2.9761) Boundary_loss: 0.015389 (0.016557) Loss: 2.0846 (2.9926) +2025-09-12,09:52:16 | INFO | Train Epoch: 0 [16640512/26365952 (63%)] Avg Boundaries (per batch): 50.303 Boundary Ratio: 0.257 Contrastive_loss: 1.9694 (2.9730) Boundary_loss: 0.015697 (0.016554) Loss: 1.9851 (2.9896) +2025-09-12,09:52:49 | INFO | Train Epoch: 0 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 1.9638 (2.9699) Boundary_loss: 0.015566 (0.016551) Loss: 1.9794 (2.9865) +2025-09-12,09:53:22 | INFO | Train Epoch: 0 [16742912/26365952 (64%)] Avg Boundaries (per batch): 50.164 Boundary Ratio: 0.256 Contrastive_loss: 2.0421 (2.9671) Boundary_loss: 0.015527 (0.016548) Loss: 2.0576 (2.9836) +2025-09-12,09:53:55 | INFO | Train Epoch: 0 [16794112/26365952 (64%)] Avg Boundaries (per batch): 46.674 Boundary Ratio: 0.238 Contrastive_loss: 2.0268 (2.9642) Boundary_loss: 0.015805 (0.016546) Loss: 2.0426 (2.9808) +2025-09-12,09:54:28 | INFO | Train Epoch: 0 [16845312/26365952 (64%)] Avg Boundaries (per batch): 47.855 Boundary Ratio: 0.244 Contrastive_loss: 1.9343 (2.9611) Boundary_loss: 0.015507 (0.016542) Loss: 1.9498 (2.9777) +2025-09-12,09:55:02 | INFO | Train Epoch: 0 [16896512/26365952 (64%)] Avg Boundaries (per batch): 46.828 Boundary Ratio: 0.239 Contrastive_loss: 1.9232 (2.9580) Boundary_loss: 0.015569 (0.016540) Loss: 1.9387 (2.9745) +2025-09-12,09:55:35 | INFO | Train Epoch: 0 [16947712/26365952 (64%)] Avg Boundaries (per batch): 49.316 Boundary Ratio: 0.252 Contrastive_loss: 1.9427 (2.9549) Boundary_loss: 0.015468 (0.016536) Loss: 1.9582 (2.9715) +2025-09-12,09:56:08 | INFO | Train Epoch: 0 [16998912/26365952 (64%)] Avg Boundaries (per batch): 50.676 Boundary Ratio: 0.259 Contrastive_loss: 1.9964 (2.9520) Boundary_loss: 0.015773 (0.016534) Loss: 2.0121 (2.9686) +2025-09-12,09:56:41 | INFO | Train Epoch: 0 [17050112/26365952 (65%)] Avg Boundaries (per batch): 50.139 Boundary Ratio: 0.256 Contrastive_loss: 1.9690 (2.9491) Boundary_loss: 0.015838 (0.016532) Loss: 1.9849 (2.9656) +2025-09-12,09:57:14 | INFO | Train Epoch: 0 [17101312/26365952 (65%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 1.8571 (2.9458) Boundary_loss: 0.015481 (0.016529) Loss: 1.8726 (2.9624) +2025-09-12,09:57:47 | INFO | Train Epoch: 0 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.189 Boundary Ratio: 0.246 Contrastive_loss: 1.9010 (2.9427) Boundary_loss: 0.015466 (0.016526) Loss: 1.9165 (2.9592) +2025-09-12,09:58:19 | INFO | Train Epoch: 0 [17203712/26365952 (65%)] Avg Boundaries (per batch): 50.064 Boundary Ratio: 0.255 Contrastive_loss: 2.0493 (2.9401) Boundary_loss: 0.015538 (0.016523) Loss: 2.0649 (2.9566) +2025-09-12,09:58:52 | INFO | Train Epoch: 0 [17254912/26365952 (65%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 2.0194 (2.9373) Boundary_loss: 0.015242 (0.016519) Loss: 2.0346 (2.9539) +2025-09-12,09:59:25 | INFO | Train Epoch: 0 [17306112/26365952 (66%)] Avg Boundaries (per batch): 47.512 Boundary Ratio: 0.242 Contrastive_loss: 1.8529 (2.9342) Boundary_loss: 0.015410 (0.016516) Loss: 1.8683 (2.9507) +2025-09-12,09:59:57 | INFO | Train Epoch: 0 [17357312/26365952 (66%)] Avg Boundaries (per batch): 47.318 Boundary Ratio: 0.241 Contrastive_loss: 1.9970 (2.9314) Boundary_loss: 0.015431 (0.016512) Loss: 2.0124 (2.9479) +2025-09-12,10:00:30 | INFO | Train Epoch: 0 [17408512/26365952 (66%)] Avg Boundaries (per batch): 50.309 Boundary Ratio: 0.257 Contrastive_loss: 2.0113 (2.9287) Boundary_loss: 0.015534 (0.016510) Loss: 2.0269 (2.9452) +2025-09-12,10:01:03 | INFO | Train Epoch: 0 [17459712/26365952 (66%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 2.0739 (2.9262) Boundary_loss: 0.015663 (0.016507) Loss: 2.0895 (2.9427) +2025-09-12,10:01:36 | INFO | Train Epoch: 0 [17510912/26365952 (66%)] Avg Boundaries (per batch): 49.352 Boundary Ratio: 0.252 Contrastive_loss: 1.9371 (2.9233) Boundary_loss: 0.015361 (0.016504) Loss: 1.9525 (2.9398) +2025-09-12,10:02:09 | INFO | Train Epoch: 0 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 1.9916 (2.9206) Boundary_loss: 0.015208 (0.016500) Loss: 2.0068 (2.9371) +2025-09-12,10:02:42 | INFO | Train Epoch: 0 [17613312/26365952 (67%)] Avg Boundaries (per batch): 47.439 Boundary Ratio: 0.242 Contrastive_loss: 1.9466 (2.9178) Boundary_loss: 0.015581 (0.016497) Loss: 1.9622 (2.9343) +2025-09-12,10:03:14 | INFO | Train Epoch: 0 [17664512/26365952 (67%)] Avg Boundaries (per batch): 50.025 Boundary Ratio: 0.255 Contrastive_loss: 1.9242 (2.9149) Boundary_loss: 0.015474 (0.016494) Loss: 1.9397 (2.9314) +2025-09-12,10:03:47 | INFO | Train Epoch: 0 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.846 Boundary Ratio: 0.254 Contrastive_loss: 1.8853 (2.9119) Boundary_loss: 0.015334 (0.016491) Loss: 1.9007 (2.9284) +2025-09-12,10:04:20 | INFO | Train Epoch: 0 [17766912/26365952 (67%)] Avg Boundaries (per batch): 49.533 Boundary Ratio: 0.253 Contrastive_loss: 1.9809 (2.9093) Boundary_loss: 0.015283 (0.016488) Loss: 1.9961 (2.9258) +2025-09-12,10:04:52 | INFO | Train Epoch: 0 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.789 Boundary Ratio: 0.254 Contrastive_loss: 1.9334 (2.9065) Boundary_loss: 0.015474 (0.016485) Loss: 1.9489 (2.9230) +2025-09-12,10:05:25 | INFO | Train Epoch: 0 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.355 Boundary Ratio: 0.252 Contrastive_loss: 1.9247 (2.9037) Boundary_loss: 0.015134 (0.016481) Loss: 1.9398 (2.9201) +2025-09-12,10:05:58 | INFO | Train Epoch: 0 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 1.9559 (2.9010) Boundary_loss: 0.015745 (0.016479) Loss: 1.9717 (2.9174) +2025-09-12,10:06:31 | INFO | Train Epoch: 0 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 1.9086 (2.8981) Boundary_loss: 0.015360 (0.016476) Loss: 1.9239 (2.9146) +2025-09-12,10:07:04 | INFO | Train Epoch: 0 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 1.9942 (2.8956) Boundary_loss: 0.015447 (0.016473) Loss: 2.0096 (2.9121) +2025-09-12,10:07:37 | INFO | Train Epoch: 0 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 1.8839 (2.8927) Boundary_loss: 0.015383 (0.016470) Loss: 1.8993 (2.9092) +2025-09-12,10:08:10 | INFO | Train Epoch: 0 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 1.7182 (2.8894) Boundary_loss: 0.015307 (0.016466) Loss: 1.7335 (2.9059) +2025-09-12,10:08:43 | INFO | Train Epoch: 0 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 1.8101 (2.8864) Boundary_loss: 0.015784 (0.016464) Loss: 1.8259 (2.9029) +2025-09-12,10:09:16 | INFO | Train Epoch: 0 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 2.0622 (2.8841) Boundary_loss: 0.015314 (0.016461) Loss: 2.0775 (2.9005) +2025-09-12,10:09:49 | INFO | Train Epoch: 0 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 1.9087 (2.8814) Boundary_loss: 0.015426 (0.016458) Loss: 1.9241 (2.8978) +2025-09-12,10:10:22 | INFO | Train Epoch: 0 [18330112/26365952 (70%)] Avg Boundaries (per batch): 50.436 Boundary Ratio: 0.257 Contrastive_loss: 1.9065 (2.8786) Boundary_loss: 0.015445 (0.016455) Loss: 1.9220 (2.8951) +2025-09-12,10:10:55 | INFO | Train Epoch: 0 [18381312/26365952 (70%)] Avg Boundaries (per batch): 49.467 Boundary Ratio: 0.252 Contrastive_loss: 1.9723 (2.8761) Boundary_loss: 0.015257 (0.016452) Loss: 1.9875 (2.8926) +2025-09-12,10:11:28 | INFO | Train Epoch: 0 [18432512/26365952 (70%)] Avg Boundaries (per batch): 47.465 Boundary Ratio: 0.242 Contrastive_loss: 1.9779 (2.8736) Boundary_loss: 0.015561 (0.016450) Loss: 1.9935 (2.8901) +2025-09-12,10:12:01 | INFO | Train Epoch: 0 [18483712/26365952 (70%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 1.9519 (2.8711) Boundary_loss: 0.015105 (0.016446) Loss: 1.9670 (2.8875) +2025-09-12,10:12:34 | INFO | Train Epoch: 0 [18534912/26365952 (70%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 1.9388 (2.8685) Boundary_loss: 0.015210 (0.016442) Loss: 1.9540 (2.8850) +2025-09-12,10:13:06 | INFO | Train Epoch: 0 [18586112/26365952 (70%)] Avg Boundaries (per batch): 49.598 Boundary Ratio: 0.253 Contrastive_loss: 1.8739 (2.8658) Boundary_loss: 0.015228 (0.016439) Loss: 1.8892 (2.8822) +2025-09-12,10:13:39 | INFO | Train Epoch: 0 [18637312/26365952 (71%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 1.7554 (2.8627) Boundary_loss: 0.015402 (0.016436) Loss: 1.7708 (2.8792) +2025-09-12,10:14:12 | INFO | Train Epoch: 0 [18688512/26365952 (71%)] Avg Boundaries (per batch): 49.457 Boundary Ratio: 0.252 Contrastive_loss: 1.8781 (2.8601) Boundary_loss: 0.015293 (0.016433) Loss: 1.8934 (2.8765) +2025-09-12,10:14:45 | INFO | Train Epoch: 0 [18739712/26365952 (71%)] Avg Boundaries (per batch): 50.895 Boundary Ratio: 0.260 Contrastive_loss: 1.9057 (2.8575) Boundary_loss: 0.015508 (0.016431) Loss: 1.9212 (2.8739) +2025-09-12,10:15:17 | INFO | Train Epoch: 0 [18790912/26365952 (71%)] Avg Boundaries (per batch): 49.785 Boundary Ratio: 0.254 Contrastive_loss: 1.9498 (2.8550) Boundary_loss: 0.015395 (0.016428) Loss: 1.9652 (2.8714) +2025-09-12,10:15:50 | INFO | Train Epoch: 0 [18842112/26365952 (71%)] Avg Boundaries (per batch): 50.582 Boundary Ratio: 0.258 Contrastive_loss: 1.7917 (2.8521) Boundary_loss: 0.015549 (0.016425) Loss: 1.8073 (2.8685) +2025-09-12,10:16:22 | INFO | Train Epoch: 0 [18893312/26365952 (72%)] Avg Boundaries (per batch): 49.646 Boundary Ratio: 0.253 Contrastive_loss: 1.9480 (2.8497) Boundary_loss: 0.015273 (0.016422) Loss: 1.9633 (2.8661) +2025-09-12,10:16:55 | INFO | Train Epoch: 0 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 1.8967 (2.8471) Boundary_loss: 0.015233 (0.016419) Loss: 1.9120 (2.8635) +2025-09-12,10:17:27 | INFO | Train Epoch: 0 [18995712/26365952 (72%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 1.9221 (2.8446) Boundary_loss: 0.015211 (0.016416) Loss: 1.9373 (2.8610) +2025-09-12,10:18:00 | INFO | Train Epoch: 0 [19046912/26365952 (72%)] Avg Boundaries (per batch): 47.391 Boundary Ratio: 0.242 Contrastive_loss: 1.8161 (2.8418) Boundary_loss: 0.015322 (0.016413) Loss: 1.8314 (2.8583) +2025-09-12,10:18:33 | INFO | Train Epoch: 0 [19098112/26365952 (72%)] Avg Boundaries (per batch): 47.496 Boundary Ratio: 0.242 Contrastive_loss: 2.0616 (2.8398) Boundary_loss: 0.015297 (0.016410) Loss: 2.0769 (2.8562) +2025-09-12,10:19:05 | INFO | Train Epoch: 0 [19149312/26365952 (73%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 1.8331 (2.8371) Boundary_loss: 0.015262 (0.016407) Loss: 1.8483 (2.8535) +2025-09-12,10:19:38 | INFO | Train Epoch: 0 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 1.9733 (2.8348) Boundary_loss: 0.015728 (0.016405) Loss: 1.9890 (2.8512) +2025-09-12,10:20:10 | INFO | Train Epoch: 0 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 1.8495 (2.8322) Boundary_loss: 0.015101 (0.016402) Loss: 1.8646 (2.8486) +2025-09-12,10:20:43 | INFO | Train Epoch: 0 [19302912/26365952 (73%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 1.8348 (2.8295) Boundary_loss: 0.015269 (0.016399) Loss: 1.8500 (2.8459) +2025-09-12,10:21:15 | INFO | Train Epoch: 0 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.7971 (2.8268) Boundary_loss: 0.015223 (0.016396) Loss: 1.8123 (2.8432) +2025-09-12,10:21:48 | INFO | Train Epoch: 0 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 1.7091 (2.8239) Boundary_loss: 0.015257 (0.016393) Loss: 1.7244 (2.8403) +2025-09-12,10:22:20 | INFO | Train Epoch: 0 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 1.9462 (2.8216) Boundary_loss: 0.015330 (0.016390) Loss: 1.9615 (2.8379) +2025-09-12,10:22:53 | INFO | Train Epoch: 0 [19507712/26365952 (74%)] Avg Boundaries (per batch): 47.840 Boundary Ratio: 0.244 Contrastive_loss: 1.8299 (2.8190) Boundary_loss: 0.015290 (0.016387) Loss: 1.8451 (2.8354) +2025-09-12,10:23:25 | INFO | Train Epoch: 0 [19558912/26365952 (74%)] Avg Boundaries (per batch): 47.379 Boundary Ratio: 0.242 Contrastive_loss: 2.0367 (2.8169) Boundary_loss: 0.015187 (0.016384) Loss: 2.0519 (2.8333) +2025-09-12,10:23:58 | INFO | Train Epoch: 0 [19610112/26365952 (74%)] Avg Boundaries (per batch): 50.529 Boundary Ratio: 0.258 Contrastive_loss: 1.8685 (2.8145) Boundary_loss: 0.015430 (0.016381) Loss: 1.8840 (2.8308) +2025-09-12,10:24:30 | INFO | Train Epoch: 0 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.9569 (2.8122) Boundary_loss: 0.015105 (0.016378) Loss: 1.9720 (2.8286) +2025-09-12,10:25:03 | INFO | Train Epoch: 0 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.9117 (2.8099) Boundary_loss: 0.015219 (0.016375) Loss: 1.9269 (2.8263) +2025-09-12,10:25:35 | INFO | Train Epoch: 0 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 1.9987 (2.8078) Boundary_loss: 0.015446 (0.016373) Loss: 2.0142 (2.8242) +2025-09-12,10:26:08 | INFO | Train Epoch: 0 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 1.8921 (2.8054) Boundary_loss: 0.015186 (0.016369) Loss: 1.9073 (2.8218) +2025-09-12,10:26:40 | INFO | Train Epoch: 0 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 1.7678 (2.8028) Boundary_loss: 0.015173 (0.016366) Loss: 1.7830 (2.8191) +2025-09-12,10:27:12 | INFO | Train Epoch: 0 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.301 Boundary Ratio: 0.246 Contrastive_loss: 1.9743 (2.8006) Boundary_loss: 0.015262 (0.016364) Loss: 1.9896 (2.8170) +2025-09-12,10:27:45 | INFO | Train Epoch: 0 [19968512/26365952 (76%)] Avg Boundaries (per batch): 47.168 Boundary Ratio: 0.241 Contrastive_loss: 1.8529 (2.7982) Boundary_loss: 0.015487 (0.016361) Loss: 1.8684 (2.8146) +2025-09-12,10:28:17 | INFO | Train Epoch: 0 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 1.8346 (2.7958) Boundary_loss: 0.015223 (0.016358) Loss: 1.8498 (2.8121) +2025-09-12,10:28:50 | INFO | Train Epoch: 0 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 1.9706 (2.7937) Boundary_loss: 0.015158 (0.016355) Loss: 1.9858 (2.8100) +2025-09-12,10:29:23 | INFO | Train Epoch: 0 [20122112/26365952 (76%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 1.7948 (2.7911) Boundary_loss: 0.015097 (0.016352) Loss: 1.8099 (2.8075) +2025-09-12,10:29:55 | INFO | Train Epoch: 0 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.098 Boundary Ratio: 0.245 Contrastive_loss: 1.8245 (2.7887) Boundary_loss: 0.014881 (0.016348) Loss: 1.8394 (2.8050) +2025-09-12,10:30:28 | INFO | Train Epoch: 0 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 2.0419 (2.7868) Boundary_loss: 0.015083 (0.016345) Loss: 2.0570 (2.8031) +2025-09-12,10:31:01 | INFO | Train Epoch: 0 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 1.8767 (2.7845) Boundary_loss: 0.015085 (0.016342) Loss: 1.8918 (2.8008) +2025-09-12,10:31:33 | INFO | Train Epoch: 0 [20326912/26365952 (77%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 1.8054 (2.7820) Boundary_loss: 0.015460 (0.016340) Loss: 1.8208 (2.7984) +2025-09-12,10:32:06 | INFO | Train Epoch: 0 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.166 Boundary Ratio: 0.246 Contrastive_loss: 1.6898 (2.7793) Boundary_loss: 0.015211 (0.016337) Loss: 1.7050 (2.7956) +2025-09-12,10:32:39 | INFO | Train Epoch: 0 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 1.6574 (2.7765) Boundary_loss: 0.015253 (0.016334) Loss: 1.6726 (2.7928) +2025-09-12,10:33:12 | INFO | Train Epoch: 0 [20480512/26365952 (78%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 1.7823 (2.7740) Boundary_loss: 0.015152 (0.016331) Loss: 1.7974 (2.7904) +2025-09-12,10:33:45 | INFO | Train Epoch: 0 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.203 Boundary Ratio: 0.246 Contrastive_loss: 1.8129 (2.7716) Boundary_loss: 0.015200 (0.016329) Loss: 1.8281 (2.7880) +2025-09-12,10:34:18 | INFO | Train Epoch: 0 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 1.8128 (2.7693) Boundary_loss: 0.015100 (0.016326) Loss: 1.8279 (2.7856) +2025-09-12,10:34:50 | INFO | Train Epoch: 0 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 1.6808 (2.7666) Boundary_loss: 0.015137 (0.016323) Loss: 1.6959 (2.7829) +2025-09-12,10:35:23 | INFO | Train Epoch: 0 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.205 Boundary Ratio: 0.246 Contrastive_loss: 1.7715 (2.7641) Boundary_loss: 0.015032 (0.016319) Loss: 1.7865 (2.7804) +2025-09-12,10:35:56 | INFO | Train Epoch: 0 [20736512/26365952 (79%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 1.8236 (2.7618) Boundary_loss: 0.014946 (0.016316) Loss: 1.8385 (2.7781) +2025-09-12,10:36:29 | INFO | Train Epoch: 0 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 1.6937 (2.7592) Boundary_loss: 0.015198 (0.016313) Loss: 1.7089 (2.7755) +2025-09-12,10:37:02 | INFO | Train Epoch: 0 [20838912/26365952 (79%)] Avg Boundaries (per batch): 46.787 Boundary Ratio: 0.239 Contrastive_loss: 1.8640 (2.7570) Boundary_loss: 0.015244 (0.016311) Loss: 1.8793 (2.7733) +2025-09-12,10:37:35 | INFO | Train Epoch: 0 [20890112/26365952 (79%)] Avg Boundaries (per batch): 50.043 Boundary Ratio: 0.255 Contrastive_loss: 1.9151 (2.7549) Boundary_loss: 0.015277 (0.016308) Loss: 1.9303 (2.7712) +2025-09-12,10:38:07 | INFO | Train Epoch: 0 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 1.6946 (2.7523) Boundary_loss: 0.014840 (0.016305) Loss: 1.7094 (2.7686) +2025-09-12,10:38:40 | INFO | Train Epoch: 0 [20992512/26365952 (80%)] Avg Boundaries (per batch): 49.449 Boundary Ratio: 0.252 Contrastive_loss: 1.8202 (2.7501) Boundary_loss: 0.014906 (0.016301) Loss: 1.8351 (2.7664) +2025-09-12,10:39:13 | INFO | Train Epoch: 0 [21043712/26365952 (80%)] Avg Boundaries (per batch): 46.105 Boundary Ratio: 0.235 Contrastive_loss: 1.8450 (2.7479) Boundary_loss: 0.015654 (0.016300) Loss: 1.8607 (2.7642) +2025-09-12,10:39:46 | INFO | Train Epoch: 0 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 1.7704 (2.7455) Boundary_loss: 0.015107 (0.016297) Loss: 1.7855 (2.7618) +2025-09-12,10:40:19 | INFO | Train Epoch: 0 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 1.8558 (2.7433) Boundary_loss: 0.014904 (0.016293) Loss: 1.8707 (2.7596) +2025-09-12,10:40:52 | INFO | Train Epoch: 0 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.236 Boundary Ratio: 0.246 Contrastive_loss: 1.9159 (2.7413) Boundary_loss: 0.014988 (0.016290) Loss: 1.9309 (2.7576) +2025-09-12,10:41:24 | INFO | Train Epoch: 0 [21248512/26365952 (81%)] Avg Boundaries (per batch): 46.324 Boundary Ratio: 0.236 Contrastive_loss: 1.7474 (2.7390) Boundary_loss: 0.015435 (0.016288) Loss: 1.7628 (2.7552) +2025-09-12,10:41:57 | INFO | Train Epoch: 0 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.111 Boundary Ratio: 0.245 Contrastive_loss: 1.7303 (2.7365) Boundary_loss: 0.014820 (0.016285) Loss: 1.7451 (2.7528) +2025-09-12,10:42:30 | INFO | Train Epoch: 0 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.186 Boundary Ratio: 0.246 Contrastive_loss: 1.7388 (2.7342) Boundary_loss: 0.015037 (0.016282) Loss: 1.7538 (2.7504) +2025-09-12,10:43:03 | INFO | Train Epoch: 0 [21402112/26365952 (81%)] Avg Boundaries (per batch): 47.428 Boundary Ratio: 0.242 Contrastive_loss: 1.7653 (2.7318) Boundary_loss: 0.015265 (0.016279) Loss: 1.7805 (2.7481) +2025-09-12,10:43:36 | INFO | Train Epoch: 0 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 1.7772 (2.7296) Boundary_loss: 0.015017 (0.016276) Loss: 1.7922 (2.7458) +2025-09-12,10:44:08 | INFO | Train Epoch: 0 [21504512/26365952 (82%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 1.7592 (2.7273) Boundary_loss: 0.014973 (0.016273) Loss: 1.7742 (2.7435) +2025-09-12,10:44:41 | INFO | Train Epoch: 0 [21555712/26365952 (82%)] Avg Boundaries (per batch): 49.615 Boundary Ratio: 0.253 Contrastive_loss: 1.6592 (2.7247) Boundary_loss: 0.015272 (0.016271) Loss: 1.6744 (2.7410) +2025-09-12,10:45:14 | INFO | Train Epoch: 0 [21606912/26365952 (82%)] Avg Boundaries (per batch): 51.648 Boundary Ratio: 0.264 Contrastive_loss: 1.6652 (2.7222) Boundary_loss: 0.015714 (0.016269) Loss: 1.6809 (2.7385) +2025-09-12,10:45:47 | INFO | Train Epoch: 0 [21658112/26365952 (82%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 1.9109 (2.7203) Boundary_loss: 0.014856 (0.016266) Loss: 1.9258 (2.7366) +2025-09-12,10:46:20 | INFO | Train Epoch: 0 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 1.7497 (2.7180) Boundary_loss: 0.014966 (0.016263) Loss: 1.7647 (2.7343) +2025-09-12,10:46:52 | INFO | Train Epoch: 0 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 1.8658 (2.7160) Boundary_loss: 0.014980 (0.016260) Loss: 1.8808 (2.7323) +2025-09-12,10:47:25 | INFO | Train Epoch: 0 [21811712/26365952 (83%)] Avg Boundaries (per batch): 49.295 Boundary Ratio: 0.252 Contrastive_loss: 1.7430 (2.7137) Boundary_loss: 0.015048 (0.016257) Loss: 1.7581 (2.7300) +2025-09-12,10:47:58 | INFO | Train Epoch: 0 [21862912/26365952 (83%)] Avg Boundaries (per batch): 49.832 Boundary Ratio: 0.254 Contrastive_loss: 1.8390 (2.7117) Boundary_loss: 0.014907 (0.016254) Loss: 1.8539 (2.7280) +2025-09-12,10:48:30 | INFO | Train Epoch: 0 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 1.7820 (2.7095) Boundary_loss: 0.014773 (0.016251) Loss: 1.7968 (2.7258) +2025-09-12,10:49:03 | INFO | Train Epoch: 0 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 1.6896 (2.7072) Boundary_loss: 0.015108 (0.016248) Loss: 1.7047 (2.7234) +2025-09-12,10:49:35 | INFO | Train Epoch: 0 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 1.7212 (2.7049) Boundary_loss: 0.014905 (0.016245) Loss: 1.7361 (2.7211) +2025-09-12,10:50:08 | INFO | Train Epoch: 0 [22067712/26365952 (84%)] Avg Boundaries (per batch): 51.068 Boundary Ratio: 0.261 Contrastive_loss: 1.7278 (2.7026) Boundary_loss: 0.015586 (0.016243) Loss: 1.7433 (2.7189) +2025-09-12,10:50:40 | INFO | Train Epoch: 0 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 1.7372 (2.7004) Boundary_loss: 0.014839 (0.016240) Loss: 1.7520 (2.7166) +2025-09-12,10:51:13 | INFO | Train Epoch: 0 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 1.6812 (2.6980) Boundary_loss: 0.014842 (0.016237) Loss: 1.6960 (2.7143) +2025-09-12,10:51:46 | INFO | Train Epoch: 0 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 1.7565 (2.6959) Boundary_loss: 0.014859 (0.016234) Loss: 1.7713 (2.7121) +2025-09-12,10:52:18 | INFO | Train Epoch: 0 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 1.8058 (2.6938) Boundary_loss: 0.014676 (0.016230) Loss: 1.8204 (2.7101) +2025-09-12,10:52:51 | INFO | Train Epoch: 0 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.031 Boundary Ratio: 0.245 Contrastive_loss: 1.7263 (2.6916) Boundary_loss: 0.014920 (0.016227) Loss: 1.7412 (2.7078) +2025-09-12,10:53:23 | INFO | Train Epoch: 0 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 1.8018 (2.6896) Boundary_loss: 0.014788 (0.016224) Loss: 1.8166 (2.7058) +2025-09-12,10:53:56 | INFO | Train Epoch: 0 [22426112/26365952 (85%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 1.7369 (2.6874) Boundary_loss: 0.014820 (0.016221) Loss: 1.7517 (2.7036) +2025-09-12,10:54:29 | INFO | Train Epoch: 0 [22477312/26365952 (85%)] Avg Boundaries (per batch): 50.219 Boundary Ratio: 0.256 Contrastive_loss: 1.7524 (2.6853) Boundary_loss: 0.014804 (0.016217) Loss: 1.7672 (2.7015) +2025-09-12,10:55:01 | INFO | Train Epoch: 0 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 1.8643 (2.6834) Boundary_loss: 0.014920 (0.016214) Loss: 1.8792 (2.6996) +2025-09-12,10:55:34 | INFO | Train Epoch: 0 [22579712/26365952 (86%)] Avg Boundaries (per batch): 49.832 Boundary Ratio: 0.254 Contrastive_loss: 1.7548 (2.6813) Boundary_loss: 0.014845 (0.016211) Loss: 1.7696 (2.6975) +2025-09-12,10:56:06 | INFO | Train Epoch: 0 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.184 Boundary Ratio: 0.246 Contrastive_loss: 1.8689 (2.6795) Boundary_loss: 0.014710 (0.016208) Loss: 1.8836 (2.6957) +2025-09-12,10:56:39 | INFO | Train Epoch: 0 [22682112/26365952 (86%)] Avg Boundaries (per batch): 50.207 Boundary Ratio: 0.256 Contrastive_loss: 1.7002 (2.6773) Boundary_loss: 0.014742 (0.016205) Loss: 1.7149 (2.6935) +2025-09-12,10:57:11 | INFO | Train Epoch: 0 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 1.7302 (2.6752) Boundary_loss: 0.014638 (0.016201) Loss: 1.7448 (2.6914) +2025-09-12,10:57:44 | INFO | Train Epoch: 0 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.5873 (2.6727) Boundary_loss: 0.014658 (0.016198) Loss: 1.6019 (2.6889) +2025-09-12,10:58:16 | INFO | Train Epoch: 0 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.225 Boundary Ratio: 0.246 Contrastive_loss: 2.0384 (2.6713) Boundary_loss: 0.014641 (0.016194) Loss: 2.0531 (2.6875) +2025-09-12,10:58:48 | INFO | Train Epoch: 0 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.9134 (2.6696) Boundary_loss: 0.014596 (0.016191) Loss: 1.9280 (2.6858) +2025-09-12,10:59:21 | INFO | Train Epoch: 0 [22938112/26365952 (87%)] Avg Boundaries (per batch): 47.518 Boundary Ratio: 0.242 Contrastive_loss: 1.7796 (2.6676) Boundary_loss: 0.014736 (0.016187) Loss: 1.7943 (2.6838) +2025-09-12,10:59:53 | INFO | Train Epoch: 0 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 1.6935 (2.6655) Boundary_loss: 0.014561 (0.016184) Loss: 1.7081 (2.6816) +2025-09-12,11:00:26 | INFO | Train Epoch: 0 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.010 Boundary Ratio: 0.245 Contrastive_loss: 1.8503 (2.6637) Boundary_loss: 0.014518 (0.016180) Loss: 1.8649 (2.6798) +2025-09-12,11:00:58 | INFO | Train Epoch: 0 [23091712/26365952 (88%)] Avg Boundaries (per batch): 47.150 Boundary Ratio: 0.241 Contrastive_loss: 1.7525 (2.6616) Boundary_loss: 0.014879 (0.016177) Loss: 1.7674 (2.6778) +2025-09-12,11:01:31 | INFO | Train Epoch: 0 [23142912/26365952 (88%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 1.8117 (2.6598) Boundary_loss: 0.014543 (0.016174) Loss: 1.8262 (2.6759) +2025-09-12,11:02:03 | INFO | Train Epoch: 0 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.328 Boundary Ratio: 0.247 Contrastive_loss: 1.6425 (2.6575) Boundary_loss: 0.014542 (0.016170) Loss: 1.6571 (2.6737) +2025-09-12,11:02:35 | INFO | Train Epoch: 0 [23245312/26365952 (88%)] Avg Boundaries (per batch): 47.572 Boundary Ratio: 0.243 Contrastive_loss: 1.6831 (2.6554) Boundary_loss: 0.014601 (0.016167) Loss: 1.6977 (2.6715) +2025-09-12,11:03:07 | INFO | Train Epoch: 0 [23296512/26365952 (88%)] Avg Boundaries (per batch): 47.721 Boundary Ratio: 0.243 Contrastive_loss: 1.7468 (2.6534) Boundary_loss: 0.014527 (0.016163) Loss: 1.7614 (2.6696) +2025-09-12,11:03:39 | INFO | Train Epoch: 0 [23347712/26365952 (89%)] Avg Boundaries (per batch): 50.475 Boundary Ratio: 0.258 Contrastive_loss: 1.8144 (2.6516) Boundary_loss: 0.014726 (0.016160) Loss: 1.8292 (2.6677) +2025-09-12,11:04:11 | INFO | Train Epoch: 0 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 1.6988 (2.6495) Boundary_loss: 0.014584 (0.016156) Loss: 1.7133 (2.6656) +2025-09-12,11:04:43 | INFO | Train Epoch: 0 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 1.6625 (2.6473) Boundary_loss: 0.014580 (0.016153) Loss: 1.6771 (2.6635) +2025-09-12,11:05:16 | INFO | Train Epoch: 0 [23501312/26365952 (89%)] Avg Boundaries (per batch): 47.273 Boundary Ratio: 0.241 Contrastive_loss: 1.5600 (2.6450) Boundary_loss: 0.014589 (0.016149) Loss: 1.5746 (2.6611) +2025-09-12,11:05:48 | INFO | Train Epoch: 0 [23552512/26365952 (89%)] Avg Boundaries (per batch): 49.525 Boundary Ratio: 0.253 Contrastive_loss: 1.8940 (2.6433) Boundary_loss: 0.014698 (0.016146) Loss: 1.9087 (2.6595) +2025-09-12,11:06:20 | INFO | Train Epoch: 0 [23603712/26365952 (90%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 1.8137 (2.6415) Boundary_loss: 0.014500 (0.016143) Loss: 1.8282 (2.6577) +2025-09-12,11:06:52 | INFO | Train Epoch: 0 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 1.8045 (2.6397) Boundary_loss: 0.014478 (0.016139) Loss: 1.8190 (2.6559) +2025-09-12,11:07:25 | INFO | Train Epoch: 0 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 1.6840 (2.6377) Boundary_loss: 0.014404 (0.016135) Loss: 1.6984 (2.6538) +2025-09-12,11:07:57 | INFO | Train Epoch: 0 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 1.7793 (2.6358) Boundary_loss: 0.014409 (0.016132) Loss: 1.7937 (2.6520) +2025-09-12,11:08:29 | INFO | Train Epoch: 0 [23808512/26365952 (90%)] Avg Boundaries (per batch): 49.660 Boundary Ratio: 0.253 Contrastive_loss: 1.8224 (2.6341) Boundary_loss: 0.014519 (0.016128) Loss: 1.8369 (2.6502) +2025-09-12,11:09:02 | INFO | Train Epoch: 0 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.160 Boundary Ratio: 0.246 Contrastive_loss: 1.6621 (2.6320) Boundary_loss: 0.014445 (0.016125) Loss: 1.6765 (2.6481) +2025-09-12,11:09:34 | INFO | Train Epoch: 0 [23910912/26365952 (91%)] Avg Boundaries (per batch): 47.420 Boundary Ratio: 0.242 Contrastive_loss: 1.5981 (2.6298) Boundary_loss: 0.014478 (0.016121) Loss: 1.6126 (2.6459) +2025-09-12,11:10:06 | INFO | Train Epoch: 0 [23962112/26365952 (91%)] Avg Boundaries (per batch): 49.701 Boundary Ratio: 0.254 Contrastive_loss: 1.7425 (2.6279) Boundary_loss: 0.014381 (0.016117) Loss: 1.7569 (2.6440) +2025-09-12,11:10:39 | INFO | Train Epoch: 0 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 1.8389 (2.6262) Boundary_loss: 0.014451 (0.016114) Loss: 1.8533 (2.6423) +2025-09-12,11:11:11 | INFO | Train Epoch: 0 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 1.6753 (2.6242) Boundary_loss: 0.014383 (0.016110) Loss: 1.6897 (2.6403) +2025-09-12,11:11:44 | INFO | Train Epoch: 0 [24115712/26365952 (91%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 1.6482 (2.6221) Boundary_loss: 0.014293 (0.016106) Loss: 1.6625 (2.6382) +2025-09-12,11:12:16 | INFO | Train Epoch: 0 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 1.7654 (2.6203) Boundary_loss: 0.014265 (0.016102) Loss: 1.7797 (2.6364) +2025-09-12,11:12:48 | INFO | Train Epoch: 0 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 1.6720 (2.6183) Boundary_loss: 0.014309 (0.016099) Loss: 1.6863 (2.6344) +2025-09-12,11:13:20 | INFO | Train Epoch: 0 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 1.7909 (2.6166) Boundary_loss: 0.014288 (0.016095) Loss: 1.8052 (2.6327) +2025-09-12,11:13:53 | INFO | Train Epoch: 0 [24320512/26365952 (92%)] Avg Boundaries (per batch): 49.754 Boundary Ratio: 0.254 Contrastive_loss: 1.8488 (2.6150) Boundary_loss: 0.014321 (0.016091) Loss: 1.8632 (2.6311) +2025-09-12,11:14:25 | INFO | Train Epoch: 0 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 1.8084 (2.6133) Boundary_loss: 0.014277 (0.016087) Loss: 1.8227 (2.6294) +2025-09-12,11:14:57 | INFO | Train Epoch: 0 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 1.6705 (2.6113) Boundary_loss: 0.014256 (0.016084) Loss: 1.6847 (2.6274) +2025-09-12,11:15:29 | INFO | Train Epoch: 0 [24474112/26365952 (93%)] Avg Boundaries (per batch): 49.301 Boundary Ratio: 0.252 Contrastive_loss: 1.8020 (2.6096) Boundary_loss: 0.014172 (0.016080) Loss: 1.8161 (2.6257) +2025-09-12,11:16:02 | INFO | Train Epoch: 0 [24525312/26365952 (93%)] Avg Boundaries (per batch): 49.588 Boundary Ratio: 0.253 Contrastive_loss: 1.6868 (2.6077) Boundary_loss: 0.014274 (0.016076) Loss: 1.7011 (2.6238) +2025-09-12,11:16:34 | INFO | Train Epoch: 0 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 1.6195 (2.6056) Boundary_loss: 0.014312 (0.016072) Loss: 1.6338 (2.6217) +2025-09-12,11:17:06 | INFO | Train Epoch: 0 [24627712/26365952 (93%)] Avg Boundaries (per batch): 50.053 Boundary Ratio: 0.255 Contrastive_loss: 1.7198 (2.6038) Boundary_loss: 0.014358 (0.016069) Loss: 1.7342 (2.6199) +2025-09-12,11:17:38 | INFO | Train Epoch: 0 [24678912/26365952 (94%)] Avg Boundaries (per batch): 49.467 Boundary Ratio: 0.252 Contrastive_loss: 1.7014 (2.6019) Boundary_loss: 0.014324 (0.016065) Loss: 1.7158 (2.6180) +2025-09-12,11:18:10 | INFO | Train Epoch: 0 [24730112/26365952 (94%)] Avg Boundaries (per batch): 47.691 Boundary Ratio: 0.243 Contrastive_loss: 1.7567 (2.6002) Boundary_loss: 0.014327 (0.016061) Loss: 1.7710 (2.6162) +2025-09-12,11:18:42 | INFO | Train Epoch: 0 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.072 Boundary Ratio: 0.245 Contrastive_loss: 1.6211 (2.5982) Boundary_loss: 0.014355 (0.016058) Loss: 1.6354 (2.6142) +2025-09-12,11:19:14 | INFO | Train Epoch: 0 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.283 Boundary Ratio: 0.251 Contrastive_loss: 1.6989 (2.5963) Boundary_loss: 0.014226 (0.016054) Loss: 1.7131 (2.6124) +2025-09-12,11:19:46 | INFO | Train Epoch: 0 [24883712/26365952 (94%)] Avg Boundaries (per batch): 49.744 Boundary Ratio: 0.254 Contrastive_loss: 1.7197 (2.5945) Boundary_loss: 0.014380 (0.016051) Loss: 1.7340 (2.6106) +2025-09-12,11:20:18 | INFO | Train Epoch: 0 [24934912/26365952 (95%)] Avg Boundaries (per batch): 50.359 Boundary Ratio: 0.257 Contrastive_loss: 1.6068 (2.5925) Boundary_loss: 0.014501 (0.016047) Loss: 1.6213 (2.6085) +2025-09-12,11:20:50 | INFO | Train Epoch: 0 [24986112/26365952 (95%)] Avg Boundaries (per batch): 50.576 Boundary Ratio: 0.258 Contrastive_loss: 1.5788 (2.5904) Boundary_loss: 0.014711 (0.016045) Loss: 1.5935 (2.6065) +2025-09-12,11:21:22 | INFO | Train Epoch: 0 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.5528 (2.5883) Boundary_loss: 0.014157 (0.016041) Loss: 1.5670 (2.6043) +2025-09-12,11:21:54 | INFO | Train Epoch: 0 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 1.6492 (2.5864) Boundary_loss: 0.014119 (0.016037) Loss: 1.6633 (2.6024) +2025-09-12,11:22:26 | INFO | Train Epoch: 0 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 1.7417 (2.5847) Boundary_loss: 0.014195 (0.016033) Loss: 1.7559 (2.6007) +2025-09-12,11:22:58 | INFO | Train Epoch: 0 [25190912/26365952 (96%)] Avg Boundaries (per batch): 50.406 Boundary Ratio: 0.257 Contrastive_loss: 1.6528 (2.5828) Boundary_loss: 0.014620 (0.016030) Loss: 1.6674 (2.5988) +2025-09-12,11:23:29 | INFO | Train Epoch: 0 [25242112/26365952 (96%)] Avg Boundaries (per batch): 49.281 Boundary Ratio: 0.251 Contrastive_loss: 1.6392 (2.5809) Boundary_loss: 0.014199 (0.016027) Loss: 1.6534 (2.5969) +2025-09-12,11:24:01 | INFO | Train Epoch: 0 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 1.6412 (2.5790) Boundary_loss: 0.014141 (0.016023) Loss: 1.6553 (2.5950) +2025-09-12,11:24:33 | INFO | Train Epoch: 0 [25344512/26365952 (96%)] Avg Boundaries (per batch): 47.998 Boundary Ratio: 0.245 Contrastive_loss: 1.6250 (2.5770) Boundary_loss: 0.014237 (0.016019) Loss: 1.6392 (2.5931) +2025-09-12,11:25:05 | INFO | Train Epoch: 0 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 1.5902 (2.5751) Boundary_loss: 0.014088 (0.016015) Loss: 1.6043 (2.5911) +2025-09-12,11:25:37 | INFO | Train Epoch: 0 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 1.5244 (2.5729) Boundary_loss: 0.014066 (0.016011) Loss: 1.5384 (2.5890) +2025-09-12,11:26:09 | INFO | Train Epoch: 0 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.613 Boundary Ratio: 0.253 Contrastive_loss: 1.8054 (2.5714) Boundary_loss: 0.014319 (0.016008) Loss: 1.8197 (2.5874) +2025-09-12,11:26:41 | INFO | Train Epoch: 0 [25549312/26365952 (97%)] Avg Boundaries (per batch): 47.758 Boundary Ratio: 0.244 Contrastive_loss: 1.7355 (2.5697) Boundary_loss: 0.014181 (0.016004) Loss: 1.7497 (2.5857) +2025-09-12,11:27:13 | INFO | Train Epoch: 0 [25600512/26365952 (97%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 1.6514 (2.5679) Boundary_loss: 0.014222 (0.016001) Loss: 1.6656 (2.5839) +2025-09-12,11:27:44 | INFO | Train Epoch: 0 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 1.6508 (2.5661) Boundary_loss: 0.014140 (0.015997) Loss: 1.6649 (2.5821) +2025-09-12,11:28:16 | INFO | Train Epoch: 0 [25702912/26365952 (97%)] Avg Boundaries (per batch): 49.561 Boundary Ratio: 0.253 Contrastive_loss: 1.4567 (2.5639) Boundary_loss: 0.014331 (0.015994) Loss: 1.4710 (2.5799) +2025-09-12,11:28:47 | INFO | Train Epoch: 0 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 1.5513 (2.5619) Boundary_loss: 0.014051 (0.015990) Loss: 1.5653 (2.5779) +2025-09-12,11:29:19 | INFO | Train Epoch: 0 [25805312/26365952 (98%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 1.5601 (2.5599) Boundary_loss: 0.014083 (0.015986) Loss: 1.5742 (2.5759) +2025-09-12,11:29:50 | INFO | Train Epoch: 0 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 1.6915 (2.5582) Boundary_loss: 0.014041 (0.015982) Loss: 1.7056 (2.5741) +2025-09-12,11:30:22 | INFO | Train Epoch: 0 [25907712/26365952 (98%)] Avg Boundaries (per batch): 49.973 Boundary Ratio: 0.255 Contrastive_loss: 1.6403 (2.5564) Boundary_loss: 0.014299 (0.015979) Loss: 1.6546 (2.5723) +2025-09-12,11:30:53 | INFO | Train Epoch: 0 [25958912/26365952 (98%)] Avg Boundaries (per batch): 47.674 Boundary Ratio: 0.243 Contrastive_loss: 1.8886 (2.5550) Boundary_loss: 0.014204 (0.015976) Loss: 1.9028 (2.5710) +2025-09-12,11:31:24 | INFO | Train Epoch: 0 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 1.7900 (2.5535) Boundary_loss: 0.014095 (0.015972) Loss: 1.8041 (2.5695) +2025-09-12,11:31:56 | INFO | Train Epoch: 0 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.285 Boundary Ratio: 0.246 Contrastive_loss: 1.6643 (2.5518) Boundary_loss: 0.014097 (0.015968) Loss: 1.6784 (2.5678) +2025-09-12,11:32:27 | INFO | Train Epoch: 0 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.8587 (2.5504) Boundary_loss: 0.014050 (0.015964) Loss: 1.8727 (2.5664) +2025-09-12,11:32:59 | INFO | Train Epoch: 0 [26163712/26365952 (99%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 1.5616 (2.5485) Boundary_loss: 0.014115 (0.015961) Loss: 1.5757 (2.5645) +2025-09-12,11:33:30 | INFO | Train Epoch: 0 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 1.6620 (2.5468) Boundary_loss: 0.014032 (0.015957) Loss: 1.6760 (2.5627) +2025-09-12,11:34:01 | INFO | Train Epoch: 0 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.145 Boundary Ratio: 0.246 Contrastive_loss: 1.6386 (2.5450) Boundary_loss: 0.014168 (0.015954) Loss: 1.6528 (2.5610) +2025-09-12,11:34:33 | INFO | Train Epoch: 0 [26317312/26365952 (100%)] Avg Boundaries (per batch): 49.428 Boundary Ratio: 0.252 Contrastive_loss: 1.6528 (2.5433) Boundary_loss: 0.014200 (0.015950) Loss: 1.6670 (2.5592) +2025-09-12,11:35:02 | INFO | Train Epoch: 0 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 1.5495 (2.5414) Boundary_loss: 0.014085 (0.015947) Loss: 1.5636 (2.5573) +2025-09-12,11:35:02 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,11:35:02 | INFO | [Epoch 0] Average Step Time: 0.352s | Average GPU Memory: 27.2 GB +2025-09-12,11:35:02 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,11:35:02 | INFO | Starting zero-shot imagenet. +2025-09-12,11:35:02 | INFO | Building zero-shot classifier +2025-09-12,11:35:08 | INFO | Using classifier +2025-09-12,11:35:48 | INFO | Finished zero-shot imagenet. +2025-09-12,11:35:48 | INFO | Eval Epoch: 1 imagenet-zeroshot-val-top1: 0.1216 imagenet-zeroshot-val-top5: 0.2842 +2025-09-12,11:35:49 | INFO | Start epoch 1 +2025-09-12,11:35:51 | INFO | Train Epoch: 1 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.6053 (1.6053) Boundary_loss: 0.014145 (0.014145) Loss: 1.6194 (1.6194) +2025-09-12,11:36:22 | INFO | Train Epoch: 1 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 1.6563 (1.6308) Boundary_loss: 0.014059 (0.014102) Loss: 1.6704 (1.6449) +2025-09-12,11:36:54 | INFO | Train Epoch: 1 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.285 Boundary Ratio: 0.246 Contrastive_loss: 1.3500 (1.5372) Boundary_loss: 0.014083 (0.014096) Loss: 1.3640 (1.5513) +2025-09-12,11:37:25 | INFO | Train Epoch: 1 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.461 Boundary Ratio: 0.252 Contrastive_loss: 1.6047 (1.5540) Boundary_loss: 0.014161 (0.014112) Loss: 1.6188 (1.5682) +2025-09-12,11:37:57 | INFO | Train Epoch: 1 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 49.916 Boundary Ratio: 0.255 Contrastive_loss: 1.5544 (1.5541) Boundary_loss: 0.014271 (0.014144) Loss: 1.5686 (1.5683) +2025-09-12,11:38:29 | INFO | Train Epoch: 1 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 1.7481 (1.5865) Boundary_loss: 0.014056 (0.014129) Loss: 1.7622 (1.6006) +2025-09-12,11:39:01 | INFO | Train Epoch: 1 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.3794 (1.5569) Boundary_loss: 0.014054 (0.014118) Loss: 1.3934 (1.5710) +2025-09-12,11:39:32 | INFO | Train Epoch: 1 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 1.5391 (1.5547) Boundary_loss: 0.014035 (0.014108) Loss: 1.5532 (1.5688) +2025-09-12,11:40:04 | INFO | Train Epoch: 1 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 1.5865 (1.5582) Boundary_loss: 0.014128 (0.014110) Loss: 1.6006 (1.5723) +2025-09-12,11:40:36 | INFO | Train Epoch: 1 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 47.967 Boundary Ratio: 0.245 Contrastive_loss: 1.7528 (1.5776) Boundary_loss: 0.014132 (0.014112) Loss: 1.7670 (1.5918) +2025-09-12,11:41:08 | INFO | Train Epoch: 1 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 1.6620 (1.5853) Boundary_loss: 0.014103 (0.014112) Loss: 1.6762 (1.5994) +2025-09-12,11:41:40 | INFO | Train Epoch: 1 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 1.4702 (1.5757) Boundary_loss: 0.014080 (0.014109) Loss: 1.4843 (1.5898) +2025-09-12,11:42:12 | INFO | Train Epoch: 1 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.102 Boundary Ratio: 0.245 Contrastive_loss: 1.6787 (1.5836) Boundary_loss: 0.014124 (0.014110) Loss: 1.6928 (1.5978) +2025-09-12,11:42:43 | INFO | Train Epoch: 1 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 1.5930 (1.5843) Boundary_loss: 0.014105 (0.014110) Loss: 1.6071 (1.5984) +2025-09-12,11:43:15 | INFO | Train Epoch: 1 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 1.5631 (1.5829) Boundary_loss: 0.014093 (0.014109) Loss: 1.5772 (1.5970) +2025-09-12,11:43:47 | INFO | Train Epoch: 1 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 49.408 Boundary Ratio: 0.252 Contrastive_loss: 1.7117 (1.5909) Boundary_loss: 0.014085 (0.014107) Loss: 1.7258 (1.6051) +2025-09-12,11:44:19 | INFO | Train Epoch: 1 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 1.6434 (1.5940) Boundary_loss: 0.014022 (0.014102) Loss: 1.6575 (1.6081) +2025-09-12,11:44:51 | INFO | Train Epoch: 1 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 1.5786 (1.5932) Boundary_loss: 0.014103 (0.014102) Loss: 1.5927 (1.6073) +2025-09-12,11:45:23 | INFO | Train Epoch: 1 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 1.6126 (1.5942) Boundary_loss: 0.014062 (0.014100) Loss: 1.6267 (1.6083) +2025-09-12,11:45:55 | INFO | Train Epoch: 1 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 1.4972 (1.5893) Boundary_loss: 0.014012 (0.014096) Loss: 1.5112 (1.6034) +2025-09-12,11:46:27 | INFO | Train Epoch: 1 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.461 Boundary Ratio: 0.252 Contrastive_loss: 1.5346 (1.5867) Boundary_loss: 0.014080 (0.014095) Loss: 1.5487 (1.6008) +2025-09-12,11:46:59 | INFO | Train Epoch: 1 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 1.4363 (1.5799) Boundary_loss: 0.014192 (0.014099) Loss: 1.4505 (1.5940) +2025-09-12,11:47:30 | INFO | Train Epoch: 1 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.5446 (1.5784) Boundary_loss: 0.014032 (0.014096) Loss: 1.5586 (1.5925) +2025-09-12,11:48:02 | INFO | Train Epoch: 1 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.312 Boundary Ratio: 0.246 Contrastive_loss: 1.4593 (1.5734) Boundary_loss: 0.014072 (0.014095) Loss: 1.4734 (1.5875) +2025-09-12,11:48:34 | INFO | Train Epoch: 1 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 1.5716 (1.5733) Boundary_loss: 0.014067 (0.014094) Loss: 1.5857 (1.5874) +2025-09-12,11:49:06 | INFO | Train Epoch: 1 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 1.5187 (1.5712) Boundary_loss: 0.014005 (0.014091) Loss: 1.5327 (1.5853) +2025-09-12,11:49:38 | INFO | Train Epoch: 1 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 1.3858 (1.5644) Boundary_loss: 0.014109 (0.014091) Loss: 1.3999 (1.5785) +2025-09-12,11:50:10 | INFO | Train Epoch: 1 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 1.6654 (1.5680) Boundary_loss: 0.014016 (0.014089) Loss: 1.6794 (1.5821) +2025-09-12,11:50:42 | INFO | Train Epoch: 1 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 49.246 Boundary Ratio: 0.251 Contrastive_loss: 1.7727 (1.5750) Boundary_loss: 0.014160 (0.014091) Loss: 1.7868 (1.5891) +2025-09-12,11:51:14 | INFO | Train Epoch: 1 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 1.6502 (1.5775) Boundary_loss: 0.014069 (0.014090) Loss: 1.6642 (1.5916) +2025-09-12,11:51:46 | INFO | Train Epoch: 1 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 1.7285 (1.5824) Boundary_loss: 0.014127 (0.014092) Loss: 1.7426 (1.5965) +2025-09-12,11:52:18 | INFO | Train Epoch: 1 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 1.5803 (1.5823) Boundary_loss: 0.014005 (0.014089) Loss: 1.5943 (1.5964) +2025-09-12,11:52:49 | INFO | Train Epoch: 1 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 1.6249 (1.5836) Boundary_loss: 0.014092 (0.014089) Loss: 1.6390 (1.5977) +2025-09-12,11:53:21 | INFO | Train Epoch: 1 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.6992 (1.5870) Boundary_loss: 0.013978 (0.014086) Loss: 1.7131 (1.6011) +2025-09-12,11:53:53 | INFO | Train Epoch: 1 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 1.6563 (1.5890) Boundary_loss: 0.014021 (0.014084) Loss: 1.6703 (1.6031) +2025-09-12,11:54:25 | INFO | Train Epoch: 1 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 1.4956 (1.5864) Boundary_loss: 0.014000 (0.014082) Loss: 1.5096 (1.6005) +2025-09-12,11:54:56 | INFO | Train Epoch: 1 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 1.5578 (1.5856) Boundary_loss: 0.014011 (0.014080) Loss: 1.5719 (1.5997) +2025-09-12,11:55:28 | INFO | Train Epoch: 1 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 1.4955 (1.5833) Boundary_loss: 0.014024 (0.014078) Loss: 1.5095 (1.5973) +2025-09-12,11:55:59 | INFO | Train Epoch: 1 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 1.6134 (1.5840) Boundary_loss: 0.014057 (0.014078) Loss: 1.6275 (1.5981) +2025-09-12,11:56:31 | INFO | Train Epoch: 1 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 1.6353 (1.5853) Boundary_loss: 0.014117 (0.014079) Loss: 1.6494 (1.5994) +2025-09-12,11:57:02 | INFO | Train Epoch: 1 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 1.5446 (1.5843) Boundary_loss: 0.014037 (0.014078) Loss: 1.5587 (1.5984) +2025-09-12,11:57:34 | INFO | Train Epoch: 1 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 1.5602 (1.5838) Boundary_loss: 0.014026 (0.014076) Loss: 1.5742 (1.5978) +2025-09-12,11:58:05 | INFO | Train Epoch: 1 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 1.5330 (1.5826) Boundary_loss: 0.014073 (0.014076) Loss: 1.5470 (1.5966) +2025-09-12,11:58:37 | INFO | Train Epoch: 1 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 1.5701 (1.5823) Boundary_loss: 0.014007 (0.014075) Loss: 1.5841 (1.5964) +2025-09-12,11:59:09 | INFO | Train Epoch: 1 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 1.4636 (1.5797) Boundary_loss: 0.014022 (0.014074) Loss: 1.4776 (1.5937) +2025-09-12,11:59:40 | INFO | Train Epoch: 1 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 1.7307 (1.5829) Boundary_loss: 0.014122 (0.014075) Loss: 1.7448 (1.5970) +2025-09-12,12:00:12 | INFO | Train Epoch: 1 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 1.5236 (1.5817) Boundary_loss: 0.014113 (0.014075) Loss: 1.5378 (1.5957) +2025-09-12,12:00:44 | INFO | Train Epoch: 1 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 1.6005 (1.5821) Boundary_loss: 0.014090 (0.014076) Loss: 1.6146 (1.5961) +2025-09-12,12:01:15 | INFO | Train Epoch: 1 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 1.4352 (1.5791) Boundary_loss: 0.014116 (0.014077) Loss: 1.4493 (1.5931) +2025-09-12,12:01:47 | INFO | Train Epoch: 1 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 1.7036 (1.5816) Boundary_loss: 0.014262 (0.014080) Loss: 1.7179 (1.5956) +2025-09-12,12:02:19 | INFO | Train Epoch: 1 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.375 Boundary Ratio: 0.247 Contrastive_loss: 1.4699 (1.5794) Boundary_loss: 0.014018 (0.014079) Loss: 1.4839 (1.5934) +2025-09-12,12:02:50 | INFO | Train Epoch: 1 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 1.5340 (1.5785) Boundary_loss: 0.014152 (0.014080) Loss: 1.5482 (1.5926) +2025-09-12,12:03:22 | INFO | Train Epoch: 1 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 1.6031 (1.5790) Boundary_loss: 0.013983 (0.014079) Loss: 1.6171 (1.5930) +2025-09-12,12:03:54 | INFO | Train Epoch: 1 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.076 Boundary Ratio: 0.245 Contrastive_loss: 1.6428 (1.5801) Boundary_loss: 0.014046 (0.014078) Loss: 1.6568 (1.5942) +2025-09-12,12:04:25 | INFO | Train Epoch: 1 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.354 Boundary Ratio: 0.247 Contrastive_loss: 1.7503 (1.5832) Boundary_loss: 0.014037 (0.014077) Loss: 1.7643 (1.5973) +2025-09-12,12:04:57 | INFO | Train Epoch: 1 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 1.4451 (1.5808) Boundary_loss: 0.014192 (0.014079) Loss: 1.4593 (1.5949) +2025-09-12,12:05:29 | INFO | Train Epoch: 1 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.5954 (1.5810) Boundary_loss: 0.014110 (0.014080) Loss: 1.6095 (1.5951) +2025-09-12,12:06:00 | INFO | Train Epoch: 1 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 1.5028 (1.5797) Boundary_loss: 0.014064 (0.014080) Loss: 1.5169 (1.5938) +2025-09-12,12:06:32 | INFO | Train Epoch: 1 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 1.4548 (1.5776) Boundary_loss: 0.013996 (0.014078) Loss: 1.4688 (1.5916) +2025-09-12,12:07:04 | INFO | Train Epoch: 1 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 1.6587 (1.5789) Boundary_loss: 0.014053 (0.014078) Loss: 1.6728 (1.5930) +2025-09-12,12:07:35 | INFO | Train Epoch: 1 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 49.352 Boundary Ratio: 0.252 Contrastive_loss: 1.5565 (1.5785) Boundary_loss: 0.014232 (0.014080) Loss: 1.5707 (1.5926) +2025-09-12,12:08:07 | INFO | Train Epoch: 1 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 1.5681 (1.5784) Boundary_loss: 0.014020 (0.014079) Loss: 1.5821 (1.5925) +2025-09-12,12:08:39 | INFO | Train Epoch: 1 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 1.5592 (1.5781) Boundary_loss: 0.014001 (0.014078) Loss: 1.5732 (1.5922) +2025-09-12,12:09:10 | INFO | Train Epoch: 1 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.096 Boundary Ratio: 0.245 Contrastive_loss: 1.5029 (1.5769) Boundary_loss: 0.014193 (0.014080) Loss: 1.5171 (1.5910) +2025-09-12,12:09:42 | INFO | Train Epoch: 1 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.438 Boundary Ratio: 0.247 Contrastive_loss: 1.5101 (1.5759) Boundary_loss: 0.014068 (0.014080) Loss: 1.5242 (1.5900) +2025-09-12,12:10:14 | INFO | Train Epoch: 1 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 1.4415 (1.5738) Boundary_loss: 0.013983 (0.014078) Loss: 1.4555 (1.5879) +2025-09-12,12:10:46 | INFO | Train Epoch: 1 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.041 Boundary Ratio: 0.245 Contrastive_loss: 1.4558 (1.5721) Boundary_loss: 0.014187 (0.014080) Loss: 1.4700 (1.5862) +2025-09-12,12:11:18 | INFO | Train Epoch: 1 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 1.4819 (1.5708) Boundary_loss: 0.013991 (0.014079) Loss: 1.4959 (1.5848) +2025-09-12,12:11:50 | INFO | Train Epoch: 1 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.4942 (1.5696) Boundary_loss: 0.014025 (0.014078) Loss: 1.5082 (1.5837) +2025-09-12,12:12:21 | INFO | Train Epoch: 1 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 1.6559 (1.5709) Boundary_loss: 0.014025 (0.014077) Loss: 1.6699 (1.5849) +2025-09-12,12:12:53 | INFO | Train Epoch: 1 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 1.4745 (1.5695) Boundary_loss: 0.014002 (0.014076) Loss: 1.4885 (1.5836) +2025-09-12,12:13:25 | INFO | Train Epoch: 1 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 1.4793 (1.5683) Boundary_loss: 0.014046 (0.014076) Loss: 1.4934 (1.5823) +2025-09-12,12:13:56 | INFO | Train Epoch: 1 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 1.5432 (1.5679) Boundary_loss: 0.013997 (0.014074) Loss: 1.5572 (1.5820) +2025-09-12,12:14:28 | INFO | Train Epoch: 1 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 1.4698 (1.5666) Boundary_loss: 0.014053 (0.014074) Loss: 1.4838 (1.5807) +2025-09-12,12:15:00 | INFO | Train Epoch: 1 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 1.5146 (1.5659) Boundary_loss: 0.014061 (0.014074) Loss: 1.5287 (1.5800) +2025-09-12,12:15:31 | INFO | Train Epoch: 1 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 1.5650 (1.5659) Boundary_loss: 0.014394 (0.014078) Loss: 1.5794 (1.5800) +2025-09-12,12:16:03 | INFO | Train Epoch: 1 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.4744 (1.5647) Boundary_loss: 0.013976 (0.014077) Loss: 1.4884 (1.5788) +2025-09-12,12:16:35 | INFO | Train Epoch: 1 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 1.4584 (1.5633) Boundary_loss: 0.014219 (0.014079) Loss: 1.4726 (1.5774) +2025-09-12,12:17:06 | INFO | Train Epoch: 1 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.557 Boundary Ratio: 0.253 Contrastive_loss: 1.5713 (1.5634) Boundary_loss: 0.014235 (0.014081) Loss: 1.5856 (1.5775) +2025-09-12,12:17:38 | INFO | Train Epoch: 1 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 1.5152 (1.5628) Boundary_loss: 0.013990 (0.014080) Loss: 1.5292 (1.5769) +2025-09-12,12:18:10 | INFO | Train Epoch: 1 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 1.6640 (1.5641) Boundary_loss: 0.014084 (0.014080) Loss: 1.6780 (1.5782) +2025-09-12,12:18:41 | INFO | Train Epoch: 1 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 1.6207 (1.5648) Boundary_loss: 0.014127 (0.014080) Loss: 1.6348 (1.5789) +2025-09-12,12:19:13 | INFO | Train Epoch: 1 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 1.5321 (1.5644) Boundary_loss: 0.014052 (0.014080) Loss: 1.5461 (1.5785) +2025-09-12,12:19:45 | INFO | Train Epoch: 1 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.3526 (1.5619) Boundary_loss: 0.014017 (0.014079) Loss: 1.3666 (1.5759) +2025-09-12,12:20:17 | INFO | Train Epoch: 1 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 1.6066 (1.5624) Boundary_loss: 0.014004 (0.014078) Loss: 1.6206 (1.5765) +2025-09-12,12:20:49 | INFO | Train Epoch: 1 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 1.3069 (1.5594) Boundary_loss: 0.013965 (0.014077) Loss: 1.3208 (1.5735) +2025-09-12,12:21:20 | INFO | Train Epoch: 1 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 1.4564 (1.5582) Boundary_loss: 0.013992 (0.014076) Loss: 1.4704 (1.5723) +2025-09-12,12:21:52 | INFO | Train Epoch: 1 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.6572 (1.5594) Boundary_loss: 0.014022 (0.014075) Loss: 1.6712 (1.5734) +2025-09-12,12:22:24 | INFO | Train Epoch: 1 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 1.5679 (1.5595) Boundary_loss: 0.014046 (0.014075) Loss: 1.5820 (1.5735) +2025-09-12,12:22:56 | INFO | Train Epoch: 1 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 1.5356 (1.5592) Boundary_loss: 0.014020 (0.014074) Loss: 1.5496 (1.5733) +2025-09-12,12:23:28 | INFO | Train Epoch: 1 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 1.4673 (1.5582) Boundary_loss: 0.014063 (0.014074) Loss: 1.4814 (1.5723) +2025-09-12,12:24:00 | INFO | Train Epoch: 1 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.012 Boundary Ratio: 0.245 Contrastive_loss: 1.3114 (1.5555) Boundary_loss: 0.014188 (0.014075) Loss: 1.3256 (1.5696) +2025-09-12,12:24:31 | INFO | Train Epoch: 1 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 1.4277 (1.5541) Boundary_loss: 0.013973 (0.014074) Loss: 1.4417 (1.5682) +2025-09-12,12:25:03 | INFO | Train Epoch: 1 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 1.3539 (1.5520) Boundary_loss: 0.013979 (0.014073) Loss: 1.3679 (1.5661) +2025-09-12,12:25:34 | INFO | Train Epoch: 1 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 1.4839 (1.5513) Boundary_loss: 0.013989 (0.014072) Loss: 1.4979 (1.5653) +2025-09-12,12:26:06 | INFO | Train Epoch: 1 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 1.5368 (1.5511) Boundary_loss: 0.014073 (0.014072) Loss: 1.5508 (1.5652) +2025-09-12,12:26:38 | INFO | Train Epoch: 1 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.092 Boundary Ratio: 0.245 Contrastive_loss: 1.4116 (1.5497) Boundary_loss: 0.014093 (0.014073) Loss: 1.4257 (1.5638) +2025-09-12,12:27:10 | INFO | Train Epoch: 1 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 1.5847 (1.5500) Boundary_loss: 0.013987 (0.014072) Loss: 1.5987 (1.5641) +2025-09-12,12:27:41 | INFO | Train Epoch: 1 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 1.4011 (1.5485) Boundary_loss: 0.014145 (0.014073) Loss: 1.4152 (1.5626) +2025-09-12,12:28:13 | INFO | Train Epoch: 1 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 1.5364 (1.5484) Boundary_loss: 0.013999 (0.014072) Loss: 1.5503 (1.5625) +2025-09-12,12:28:45 | INFO | Train Epoch: 1 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 1.4229 (1.5472) Boundary_loss: 0.014050 (0.014072) Loss: 1.4370 (1.5612) +2025-09-12,12:29:16 | INFO | Train Epoch: 1 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 1.5008 (1.5467) Boundary_loss: 0.014058 (0.014071) Loss: 1.5149 (1.5608) +2025-09-12,12:29:48 | INFO | Train Epoch: 1 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.3638 (1.5449) Boundary_loss: 0.013997 (0.014071) Loss: 1.3778 (1.5590) +2025-09-12,12:30:19 | INFO | Train Epoch: 1 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 1.4958 (1.5445) Boundary_loss: 0.014182 (0.014072) Loss: 1.5100 (1.5585) +2025-09-12,12:30:50 | INFO | Train Epoch: 1 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 1.4257 (1.5433) Boundary_loss: 0.013997 (0.014071) Loss: 1.4397 (1.5574) +2025-09-12,12:31:22 | INFO | Train Epoch: 1 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 47.777 Boundary Ratio: 0.244 Contrastive_loss: 1.4638 (1.5426) Boundary_loss: 0.014193 (0.014072) Loss: 1.4780 (1.5567) +2025-09-12,12:31:53 | INFO | Train Epoch: 1 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 1.3084 (1.5404) Boundary_loss: 0.014107 (0.014073) Loss: 1.3225 (1.5545) +2025-09-12,12:32:25 | INFO | Train Epoch: 1 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 1.4872 (1.5399) Boundary_loss: 0.013962 (0.014072) Loss: 1.5012 (1.5540) +2025-09-12,12:32:56 | INFO | Train Epoch: 1 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.4046 (1.5387) Boundary_loss: 0.013999 (0.014071) Loss: 1.4186 (1.5527) +2025-09-12,12:33:28 | INFO | Train Epoch: 1 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 49.281 Boundary Ratio: 0.251 Contrastive_loss: 1.4901 (1.5382) Boundary_loss: 0.014184 (0.014072) Loss: 1.5043 (1.5523) +2025-09-12,12:33:59 | INFO | Train Epoch: 1 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 1.4305 (1.5373) Boundary_loss: 0.014130 (0.014072) Loss: 1.4446 (1.5513) +2025-09-12,12:34:31 | INFO | Train Epoch: 1 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 1.4169 (1.5362) Boundary_loss: 0.013992 (0.014072) Loss: 1.4309 (1.5503) +2025-09-12,12:35:02 | INFO | Train Epoch: 1 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 1.3603 (1.5346) Boundary_loss: 0.014037 (0.014071) Loss: 1.3743 (1.5487) +2025-09-12,12:35:33 | INFO | Train Epoch: 1 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 1.4921 (1.5342) Boundary_loss: 0.013991 (0.014071) Loss: 1.5061 (1.5483) +2025-09-12,12:36:05 | INFO | Train Epoch: 1 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 49.580 Boundary Ratio: 0.253 Contrastive_loss: 1.5179 (1.5341) Boundary_loss: 0.014099 (0.014071) Loss: 1.5320 (1.5482) +2025-09-12,12:36:37 | INFO | Train Epoch: 1 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.377 Boundary Ratio: 0.247 Contrastive_loss: 1.5181 (1.5340) Boundary_loss: 0.013999 (0.014070) Loss: 1.5321 (1.5480) +2025-09-12,12:37:08 | INFO | Train Epoch: 1 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 1.5164 (1.5338) Boundary_loss: 0.014004 (0.014070) Loss: 1.5304 (1.5479) +2025-09-12,12:37:40 | INFO | Train Epoch: 1 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 1.5038 (1.5336) Boundary_loss: 0.013977 (0.014069) Loss: 1.5178 (1.5476) +2025-09-12,12:38:12 | INFO | Train Epoch: 1 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 1.4401 (1.5328) Boundary_loss: 0.013978 (0.014068) Loss: 1.4541 (1.5468) +2025-09-12,12:38:44 | INFO | Train Epoch: 1 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 1.4647 (1.5322) Boundary_loss: 0.014113 (0.014069) Loss: 1.4788 (1.5463) +2025-09-12,12:39:16 | INFO | Train Epoch: 1 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 1.4392 (1.5314) Boundary_loss: 0.014109 (0.014069) Loss: 1.4533 (1.5455) +2025-09-12,12:39:47 | INFO | Train Epoch: 1 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 1.5311 (1.5314) Boundary_loss: 0.014070 (0.014069) Loss: 1.5451 (1.5455) +2025-09-12,12:40:19 | INFO | Train Epoch: 1 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 1.3863 (1.5303) Boundary_loss: 0.013980 (0.014068) Loss: 1.4003 (1.5443) +2025-09-12,12:40:51 | INFO | Train Epoch: 1 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 1.5970 (1.5308) Boundary_loss: 0.014107 (0.014069) Loss: 1.6111 (1.5449) +2025-09-12,12:41:23 | INFO | Train Epoch: 1 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 1.4926 (1.5305) Boundary_loss: 0.014021 (0.014068) Loss: 1.5066 (1.5446) +2025-09-12,12:41:54 | INFO | Train Epoch: 1 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 1.2918 (1.5286) Boundary_loss: 0.013997 (0.014068) Loss: 1.3058 (1.5427) +2025-09-12,12:42:26 | INFO | Train Epoch: 1 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 1.3806 (1.5274) Boundary_loss: 0.014065 (0.014068) Loss: 1.3946 (1.5415) +2025-09-12,12:42:58 | INFO | Train Epoch: 1 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 1.4058 (1.5265) Boundary_loss: 0.014098 (0.014068) Loss: 1.4199 (1.5405) +2025-09-12,12:43:29 | INFO | Train Epoch: 1 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 47.758 Boundary Ratio: 0.244 Contrastive_loss: 1.4905 (1.5262) Boundary_loss: 0.014344 (0.014070) Loss: 1.5048 (1.5403) +2025-09-12,12:44:01 | INFO | Train Epoch: 1 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 1.6285 (1.5270) Boundary_loss: 0.013984 (0.014069) Loss: 1.6425 (1.5411) +2025-09-12,12:44:33 | INFO | Train Epoch: 1 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 1.4194 (1.5262) Boundary_loss: 0.013986 (0.014069) Loss: 1.4333 (1.5402) +2025-09-12,12:45:04 | INFO | Train Epoch: 1 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 1.4007 (1.5252) Boundary_loss: 0.013971 (0.014068) Loss: 1.4147 (1.5393) +2025-09-12,12:45:36 | INFO | Train Epoch: 1 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 1.2942 (1.5235) Boundary_loss: 0.014004 (0.014067) Loss: 1.3082 (1.5375) +2025-09-12,12:46:08 | INFO | Train Epoch: 1 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 1.5189 (1.5234) Boundary_loss: 0.014047 (0.014067) Loss: 1.5329 (1.5375) +2025-09-12,12:46:39 | INFO | Train Epoch: 1 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 1.4612 (1.5230) Boundary_loss: 0.014015 (0.014067) Loss: 1.4753 (1.5371) +2025-09-12,12:47:11 | INFO | Train Epoch: 1 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.375 Boundary Ratio: 0.247 Contrastive_loss: 1.4338 (1.5223) Boundary_loss: 0.013991 (0.014066) Loss: 1.4478 (1.5364) +2025-09-12,12:47:43 | INFO | Train Epoch: 1 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 1.4076 (1.5215) Boundary_loss: 0.013988 (0.014066) Loss: 1.4216 (1.5356) +2025-09-12,12:48:14 | INFO | Train Epoch: 1 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 1.2657 (1.5196) Boundary_loss: 0.014199 (0.014067) Loss: 1.2799 (1.5337) +2025-09-12,12:48:46 | INFO | Train Epoch: 1 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.4859 (1.5194) Boundary_loss: 0.014013 (0.014066) Loss: 1.4999 (1.5335) +2025-09-12,12:49:18 | INFO | Train Epoch: 1 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.336 Boundary Ratio: 0.247 Contrastive_loss: 1.5267 (1.5194) Boundary_loss: 0.014060 (0.014066) Loss: 1.5408 (1.5335) +2025-09-12,12:49:49 | INFO | Train Epoch: 1 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 1.5587 (1.5197) Boundary_loss: 0.013967 (0.014066) Loss: 1.5727 (1.5338) +2025-09-12,12:50:21 | INFO | Train Epoch: 1 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.4769 (1.5194) Boundary_loss: 0.014022 (0.014065) Loss: 1.4909 (1.5335) +2025-09-12,12:50:53 | INFO | Train Epoch: 1 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 1.4047 (1.5186) Boundary_loss: 0.014017 (0.014065) Loss: 1.4187 (1.5327) +2025-09-12,12:51:24 | INFO | Train Epoch: 1 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 1.4304 (1.5180) Boundary_loss: 0.014000 (0.014064) Loss: 1.4444 (1.5321) +2025-09-12,12:51:56 | INFO | Train Epoch: 1 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 1.2759 (1.5163) Boundary_loss: 0.013984 (0.014064) Loss: 1.2899 (1.5304) +2025-09-12,12:52:28 | INFO | Train Epoch: 1 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 1.3813 (1.5154) Boundary_loss: 0.013992 (0.014063) Loss: 1.3953 (1.5295) +2025-09-12,12:52:59 | INFO | Train Epoch: 1 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 1.3292 (1.5141) Boundary_loss: 0.014012 (0.014063) Loss: 1.3432 (1.5282) +2025-09-12,12:53:31 | INFO | Train Epoch: 1 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 1.5727 (1.5145) Boundary_loss: 0.014018 (0.014063) Loss: 1.5867 (1.5286) +2025-09-12,12:54:03 | INFO | Train Epoch: 1 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 1.3616 (1.5135) Boundary_loss: 0.014080 (0.014063) Loss: 1.3757 (1.5276) +2025-09-12,12:54:34 | INFO | Train Epoch: 1 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 1.4088 (1.5128) Boundary_loss: 0.014061 (0.014063) Loss: 1.4229 (1.5269) +2025-09-12,12:55:06 | INFO | Train Epoch: 1 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 1.4221 (1.5122) Boundary_loss: 0.014025 (0.014063) Loss: 1.4361 (1.5263) +2025-09-12,12:55:38 | INFO | Train Epoch: 1 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 1.3188 (1.5109) Boundary_loss: 0.013995 (0.014062) Loss: 1.3327 (1.5250) +2025-09-12,12:56:09 | INFO | Train Epoch: 1 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 1.4811 (1.5108) Boundary_loss: 0.014284 (0.014064) Loss: 1.4954 (1.5248) +2025-09-12,12:56:41 | INFO | Train Epoch: 1 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 1.3757 (1.5099) Boundary_loss: 0.013971 (0.014063) Loss: 1.3897 (1.5239) +2025-09-12,12:57:13 | INFO | Train Epoch: 1 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 1.4994 (1.5098) Boundary_loss: 0.014025 (0.014063) Loss: 1.5135 (1.5239) +2025-09-12,12:57:45 | INFO | Train Epoch: 1 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 1.5180 (1.5099) Boundary_loss: 0.014028 (0.014063) Loss: 1.5320 (1.5239) +2025-09-12,12:58:17 | INFO | Train Epoch: 1 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 1.3571 (1.5089) Boundary_loss: 0.013959 (0.014062) Loss: 1.3711 (1.5229) +2025-09-12,12:58:48 | INFO | Train Epoch: 1 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 1.5617 (1.5092) Boundary_loss: 0.013971 (0.014061) Loss: 1.5757 (1.5233) +2025-09-12,12:59:20 | INFO | Train Epoch: 1 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 1.4359 (1.5088) Boundary_loss: 0.014059 (0.014061) Loss: 1.4500 (1.5228) +2025-09-12,12:59:51 | INFO | Train Epoch: 1 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.4688 (1.5085) Boundary_loss: 0.014010 (0.014061) Loss: 1.4828 (1.5226) +2025-09-12,13:00:23 | INFO | Train Epoch: 1 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 1.5197 (1.5086) Boundary_loss: 0.013960 (0.014060) Loss: 1.5337 (1.5226) +2025-09-12,13:00:55 | INFO | Train Epoch: 1 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 1.3233 (1.5074) Boundary_loss: 0.013991 (0.014060) Loss: 1.3372 (1.5215) +2025-09-12,13:01:26 | INFO | Train Epoch: 1 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 1.3839 (1.5067) Boundary_loss: 0.013974 (0.014059) Loss: 1.3978 (1.5207) +2025-09-12,13:01:58 | INFO | Train Epoch: 1 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.4449 (1.5063) Boundary_loss: 0.013991 (0.014059) Loss: 1.4589 (1.5204) +2025-09-12,13:02:30 | INFO | Train Epoch: 1 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 1.3373 (1.5053) Boundary_loss: 0.013956 (0.014058) Loss: 1.3512 (1.5193) +2025-09-12,13:03:01 | INFO | Train Epoch: 1 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 1.5431 (1.5055) Boundary_loss: 0.014032 (0.014058) Loss: 1.5571 (1.5196) +2025-09-12,13:03:33 | INFO | Train Epoch: 1 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 1.4609 (1.5052) Boundary_loss: 0.013986 (0.014058) Loss: 1.4749 (1.5193) +2025-09-12,13:04:05 | INFO | Train Epoch: 1 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 1.4139 (1.5047) Boundary_loss: 0.013984 (0.014057) Loss: 1.4279 (1.5188) +2025-09-12,13:04:37 | INFO | Train Epoch: 1 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 1.3536 (1.5038) Boundary_loss: 0.013958 (0.014057) Loss: 1.3675 (1.5179) +2025-09-12,13:05:08 | INFO | Train Epoch: 1 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.3337 (1.5028) Boundary_loss: 0.014065 (0.014057) Loss: 1.3478 (1.5169) +2025-09-12,13:05:40 | INFO | Train Epoch: 1 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 1.4174 (1.5023) Boundary_loss: 0.014014 (0.014057) Loss: 1.4315 (1.5164) +2025-09-12,13:06:12 | INFO | Train Epoch: 1 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 1.2914 (1.5011) Boundary_loss: 0.013977 (0.014056) Loss: 1.3053 (1.5151) +2025-09-12,13:06:43 | INFO | Train Epoch: 1 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 1.2699 (1.4997) Boundary_loss: 0.013991 (0.014056) Loss: 1.2838 (1.5138) +2025-09-12,13:07:15 | INFO | Train Epoch: 1 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 1.4361 (1.4994) Boundary_loss: 0.014049 (0.014056) Loss: 1.4502 (1.5134) +2025-09-12,13:07:47 | INFO | Train Epoch: 1 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 1.4710 (1.4992) Boundary_loss: 0.013969 (0.014055) Loss: 1.4849 (1.5133) +2025-09-12,13:08:19 | INFO | Train Epoch: 1 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 1.4037 (1.4987) Boundary_loss: 0.013988 (0.014055) Loss: 1.4176 (1.5127) +2025-09-12,13:08:51 | INFO | Train Epoch: 1 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 1.3377 (1.4978) Boundary_loss: 0.013993 (0.014054) Loss: 1.3517 (1.5118) +2025-09-12,13:09:22 | INFO | Train Epoch: 1 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 1.3799 (1.4971) Boundary_loss: 0.013966 (0.014054) Loss: 1.3939 (1.5111) +2025-09-12,13:09:54 | INFO | Train Epoch: 1 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.4433 (1.4968) Boundary_loss: 0.013977 (0.014054) Loss: 1.4573 (1.5108) +2025-09-12,13:10:26 | INFO | Train Epoch: 1 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 1.3928 (1.4962) Boundary_loss: 0.013953 (0.014053) Loss: 1.4068 (1.5103) +2025-09-12,13:10:57 | INFO | Train Epoch: 1 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 1.4843 (1.4962) Boundary_loss: 0.014027 (0.014053) Loss: 1.4983 (1.5102) +2025-09-12,13:11:29 | INFO | Train Epoch: 1 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.5042 (1.4962) Boundary_loss: 0.014054 (0.014053) Loss: 1.5183 (1.5102) +2025-09-12,13:12:01 | INFO | Train Epoch: 1 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.3410 (1.4953) Boundary_loss: 0.013946 (0.014052) Loss: 1.3550 (1.5094) +2025-09-12,13:12:32 | INFO | Train Epoch: 1 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 1.4879 (1.4953) Boundary_loss: 0.013973 (0.014052) Loss: 1.5019 (1.5094) +2025-09-12,13:13:04 | INFO | Train Epoch: 1 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 1.5284 (1.4955) Boundary_loss: 0.014307 (0.014053) Loss: 1.5427 (1.5095) +2025-09-12,13:13:36 | INFO | Train Epoch: 1 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.281 Boundary Ratio: 0.246 Contrastive_loss: 1.3764 (1.4948) Boundary_loss: 0.014036 (0.014053) Loss: 1.3904 (1.5089) +2025-09-12,13:14:08 | INFO | Train Epoch: 1 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 1.3548 (1.4941) Boundary_loss: 0.014246 (0.014054) Loss: 1.3690 (1.5082) +2025-09-12,13:14:39 | INFO | Train Epoch: 1 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 49.221 Boundary Ratio: 0.251 Contrastive_loss: 1.3789 (1.4935) Boundary_loss: 0.013993 (0.014054) Loss: 1.3929 (1.5075) +2025-09-12,13:15:11 | INFO | Train Epoch: 1 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 49.301 Boundary Ratio: 0.252 Contrastive_loss: 1.2799 (1.4924) Boundary_loss: 0.014047 (0.014054) Loss: 1.2940 (1.5064) +2025-09-12,13:15:43 | INFO | Train Epoch: 1 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 1.3084 (1.4914) Boundary_loss: 0.014022 (0.014054) Loss: 1.3224 (1.5054) +2025-09-12,13:16:14 | INFO | Train Epoch: 1 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.311 Boundary Ratio: 0.252 Contrastive_loss: 1.4733 (1.4913) Boundary_loss: 0.013995 (0.014053) Loss: 1.4873 (1.5053) +2025-09-12,13:16:46 | INFO | Train Epoch: 1 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 1.2556 (1.4901) Boundary_loss: 0.013941 (0.014053) Loss: 1.2695 (1.5041) +2025-09-12,13:17:17 | INFO | Train Epoch: 1 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 49.264 Boundary Ratio: 0.251 Contrastive_loss: 1.3743 (1.4895) Boundary_loss: 0.014215 (0.014054) Loss: 1.3885 (1.5035) +2025-09-12,13:17:49 | INFO | Train Epoch: 1 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 1.3888 (1.4889) Boundary_loss: 0.013985 (0.014053) Loss: 1.4028 (1.5030) +2025-09-12,13:18:21 | INFO | Train Epoch: 1 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 1.3765 (1.4884) Boundary_loss: 0.013964 (0.014053) Loss: 1.3904 (1.5024) +2025-09-12,13:18:52 | INFO | Train Epoch: 1 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 1.4590 (1.4882) Boundary_loss: 0.013981 (0.014052) Loss: 1.4730 (1.5023) +2025-09-12,13:19:24 | INFO | Train Epoch: 1 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 1.5469 (1.4885) Boundary_loss: 0.013986 (0.014052) Loss: 1.5609 (1.5026) +2025-09-12,13:19:55 | INFO | Train Epoch: 1 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 1.4186 (1.4882) Boundary_loss: 0.013993 (0.014052) Loss: 1.4326 (1.5022) +2025-09-12,13:20:26 | INFO | Train Epoch: 1 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.2613 (1.4870) Boundary_loss: 0.014184 (0.014052) Loss: 1.2754 (1.5011) +2025-09-12,13:20:58 | INFO | Train Epoch: 1 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 1.4912 (1.4870) Boundary_loss: 0.013973 (0.014052) Loss: 1.5051 (1.5011) +2025-09-12,13:21:30 | INFO | Train Epoch: 1 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 1.3212 (1.4862) Boundary_loss: 0.013957 (0.014052) Loss: 1.3351 (1.5003) +2025-09-12,13:22:01 | INFO | Train Epoch: 1 [10291712/26365952 (39%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 1.4613 (1.4861) Boundary_loss: 0.014079 (0.014052) Loss: 1.4754 (1.5001) +2025-09-12,13:22:33 | INFO | Train Epoch: 1 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 1.4610 (1.4860) Boundary_loss: 0.013997 (0.014051) Loss: 1.4750 (1.5000) +2025-09-12,13:23:05 | INFO | Train Epoch: 1 [10394112/26365952 (39%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 1.3838 (1.4855) Boundary_loss: 0.014035 (0.014051) Loss: 1.3978 (1.4995) +2025-09-12,13:23:36 | INFO | Train Epoch: 1 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 1.4300 (1.4852) Boundary_loss: 0.014352 (0.014053) Loss: 1.4443 (1.4993) +2025-09-12,13:24:08 | INFO | Train Epoch: 1 [10496512/26365952 (40%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 1.2989 (1.4843) Boundary_loss: 0.013963 (0.014052) Loss: 1.3129 (1.4983) +2025-09-12,13:24:40 | INFO | Train Epoch: 1 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 1.3755 (1.4838) Boundary_loss: 0.013983 (0.014052) Loss: 1.3895 (1.4978) +2025-09-12,13:25:11 | INFO | Train Epoch: 1 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 1.4029 (1.4834) Boundary_loss: 0.014013 (0.014052) Loss: 1.4169 (1.4974) +2025-09-12,13:25:43 | INFO | Train Epoch: 1 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.3076 (1.4825) Boundary_loss: 0.013960 (0.014051) Loss: 1.3216 (1.4966) +2025-09-12,13:26:14 | INFO | Train Epoch: 1 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 1.3544 (1.4819) Boundary_loss: 0.014015 (0.014051) Loss: 1.3685 (1.4960) +2025-09-12,13:26:46 | INFO | Train Epoch: 1 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 1.3915 (1.4815) Boundary_loss: 0.014070 (0.014051) Loss: 1.4056 (1.4956) +2025-09-12,13:27:17 | INFO | Train Epoch: 1 [10803712/26365952 (41%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 1.4494 (1.4813) Boundary_loss: 0.013952 (0.014051) Loss: 1.4633 (1.4954) +2025-09-12,13:27:48 | INFO | Train Epoch: 1 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 1.1776 (1.4799) Boundary_loss: 0.014004 (0.014051) Loss: 1.1916 (1.4940) +2025-09-12,13:28:20 | INFO | Train Epoch: 1 [10906112/26365952 (41%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 1.4454 (1.4798) Boundary_loss: 0.013972 (0.014050) Loss: 1.4594 (1.4938) +2025-09-12,13:28:51 | INFO | Train Epoch: 1 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 1.4200 (1.4795) Boundary_loss: 0.014046 (0.014050) Loss: 1.4340 (1.4935) +2025-09-12,13:29:23 | INFO | Train Epoch: 1 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.4905 (1.4795) Boundary_loss: 0.013979 (0.014050) Loss: 1.5045 (1.4936) +2025-09-12,13:29:55 | INFO | Train Epoch: 1 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 1.2988 (1.4787) Boundary_loss: 0.014143 (0.014050) Loss: 1.3129 (1.4928) +2025-09-12,13:30:26 | INFO | Train Epoch: 1 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 1.4099 (1.4784) Boundary_loss: 0.013993 (0.014050) Loss: 1.4239 (1.4924) +2025-09-12,13:30:58 | INFO | Train Epoch: 1 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 1.3518 (1.4778) Boundary_loss: 0.013985 (0.014050) Loss: 1.3658 (1.4919) +2025-09-12,13:31:29 | INFO | Train Epoch: 1 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 1.3362 (1.4772) Boundary_loss: 0.014017 (0.014050) Loss: 1.3502 (1.4912) +2025-09-12,13:32:00 | INFO | Train Epoch: 1 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 1.4555 (1.4771) Boundary_loss: 0.013966 (0.014049) Loss: 1.4695 (1.4911) +2025-09-12,13:32:32 | INFO | Train Epoch: 1 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 1.3268 (1.4764) Boundary_loss: 0.014039 (0.014049) Loss: 1.3409 (1.4904) +2025-09-12,13:33:03 | INFO | Train Epoch: 1 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 1.1906 (1.4751) Boundary_loss: 0.013977 (0.014049) Loss: 1.2046 (1.4892) +2025-09-12,13:33:35 | INFO | Train Epoch: 1 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 1.3692 (1.4746) Boundary_loss: 0.013989 (0.014049) Loss: 1.3832 (1.4887) +2025-09-12,13:34:06 | INFO | Train Epoch: 1 [11469312/26365952 (44%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 1.4985 (1.4747) Boundary_loss: 0.013983 (0.014048) Loss: 1.5125 (1.4888) +2025-09-12,13:34:37 | INFO | Train Epoch: 1 [11520512/26365952 (44%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 1.4704 (1.4747) Boundary_loss: 0.014038 (0.014048) Loss: 1.4845 (1.4888) +2025-09-12,13:35:09 | INFO | Train Epoch: 1 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 1.3565 (1.4742) Boundary_loss: 0.014034 (0.014048) Loss: 1.3705 (1.4882) +2025-09-12,13:35:40 | INFO | Train Epoch: 1 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 1.4425 (1.4741) Boundary_loss: 0.013999 (0.014048) Loss: 1.4565 (1.4881) +2025-09-12,13:36:12 | INFO | Train Epoch: 1 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 1.2838 (1.4732) Boundary_loss: 0.014053 (0.014048) Loss: 1.2979 (1.4873) +2025-09-12,13:36:43 | INFO | Train Epoch: 1 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 1.4265 (1.4730) Boundary_loss: 0.013988 (0.014048) Loss: 1.4405 (1.4871) +2025-09-12,13:37:15 | INFO | Train Epoch: 1 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 1.3396 (1.4725) Boundary_loss: 0.013966 (0.014047) Loss: 1.3535 (1.4865) +2025-09-12,13:37:46 | INFO | Train Epoch: 1 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 1.3759 (1.4720) Boundary_loss: 0.013942 (0.014047) Loss: 1.3899 (1.4861) +2025-09-12,13:38:18 | INFO | Train Epoch: 1 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.242 Boundary Ratio: 0.246 Contrastive_loss: 1.3173 (1.4714) Boundary_loss: 0.014072 (0.014047) Loss: 1.3314 (1.4854) +2025-09-12,13:38:49 | INFO | Train Epoch: 1 [11930112/26365952 (45%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 1.3379 (1.4708) Boundary_loss: 0.014050 (0.014047) Loss: 1.3519 (1.4848) +2025-09-12,13:39:20 | INFO | Train Epoch: 1 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 1.3665 (1.4704) Boundary_loss: 0.013978 (0.014047) Loss: 1.3804 (1.4844) +2025-09-12,13:39:52 | INFO | Train Epoch: 1 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.4069 (1.4701) Boundary_loss: 0.013960 (0.014046) Loss: 1.4209 (1.4841) +2025-09-12,13:40:23 | INFO | Train Epoch: 1 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.4351 (1.4699) Boundary_loss: 0.014040 (0.014046) Loss: 1.4491 (1.4840) +2025-09-12,13:40:54 | INFO | Train Epoch: 1 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 1.4244 (1.4697) Boundary_loss: 0.014018 (0.014046) Loss: 1.4384 (1.4838) +2025-09-12,13:41:26 | INFO | Train Epoch: 1 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 1.3983 (1.4694) Boundary_loss: 0.013950 (0.014046) Loss: 1.4122 (1.4835) +2025-09-12,13:41:57 | INFO | Train Epoch: 1 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 1.4386 (1.4693) Boundary_loss: 0.013948 (0.014045) Loss: 1.4525 (1.4834) +2025-09-12,13:42:29 | INFO | Train Epoch: 1 [12288512/26365952 (47%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 1.4794 (1.4694) Boundary_loss: 0.014098 (0.014046) Loss: 1.4935 (1.4834) +2025-09-12,13:43:00 | INFO | Train Epoch: 1 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 1.2736 (1.4686) Boundary_loss: 0.013943 (0.014045) Loss: 1.2875 (1.4826) +2025-09-12,13:43:32 | INFO | Train Epoch: 1 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 1.3068 (1.4679) Boundary_loss: 0.014037 (0.014045) Loss: 1.3208 (1.4819) +2025-09-12,13:44:03 | INFO | Train Epoch: 1 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 1.4613 (1.4679) Boundary_loss: 0.013957 (0.014045) Loss: 1.4752 (1.4819) +2025-09-12,13:44:35 | INFO | Train Epoch: 1 [12493312/26365952 (47%)] Avg Boundaries (per batch): 49.416 Boundary Ratio: 0.252 Contrastive_loss: 1.4372 (1.4677) Boundary_loss: 0.014000 (0.014045) Loss: 1.4512 (1.4818) +2025-09-12,13:45:06 | INFO | Train Epoch: 1 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 1.4230 (1.4676) Boundary_loss: 0.014251 (0.014045) Loss: 1.4373 (1.4816) +2025-09-12,13:45:38 | INFO | Train Epoch: 1 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 1.4397 (1.4674) Boundary_loss: 0.013970 (0.014045) Loss: 1.4537 (1.4815) +2025-09-12,13:46:09 | INFO | Train Epoch: 1 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 1.4348 (1.4673) Boundary_loss: 0.014377 (0.014047) Loss: 1.4492 (1.4814) +2025-09-12,13:46:40 | INFO | Train Epoch: 1 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 1.3332 (1.4668) Boundary_loss: 0.013951 (0.014046) Loss: 1.3472 (1.4808) +2025-09-12,13:47:12 | INFO | Train Epoch: 1 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 1.3951 (1.4665) Boundary_loss: 0.014014 (0.014046) Loss: 1.4092 (1.4805) +2025-09-12,13:47:43 | INFO | Train Epoch: 1 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 1.3612 (1.4661) Boundary_loss: 0.014019 (0.014046) Loss: 1.3752 (1.4801) +2025-09-12,13:48:14 | INFO | Train Epoch: 1 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 1.3791 (1.4657) Boundary_loss: 0.013973 (0.014046) Loss: 1.3931 (1.4798) +2025-09-12,13:48:46 | INFO | Train Epoch: 1 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 1.5288 (1.4660) Boundary_loss: 0.013948 (0.014045) Loss: 1.5428 (1.4800) +2025-09-12,13:49:17 | INFO | Train Epoch: 1 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 1.3872 (1.4657) Boundary_loss: 0.013991 (0.014045) Loss: 1.4012 (1.4797) +2025-09-12,13:49:49 | INFO | Train Epoch: 1 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 1.3703 (1.4653) Boundary_loss: 0.014000 (0.014045) Loss: 1.3843 (1.4793) +2025-09-12,13:50:20 | INFO | Train Epoch: 1 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 1.4685 (1.4653) Boundary_loss: 0.013992 (0.014045) Loss: 1.4825 (1.4793) +2025-09-12,13:50:52 | INFO | Train Epoch: 1 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 1.3088 (1.4647) Boundary_loss: 0.013964 (0.014044) Loss: 1.3227 (1.4787) +2025-09-12,13:51:23 | INFO | Train Epoch: 1 [13158912/26365952 (50%)] Avg Boundaries (per batch): 49.383 Boundary Ratio: 0.252 Contrastive_loss: 1.3864 (1.4644) Boundary_loss: 0.014010 (0.014044) Loss: 1.4004 (1.4784) +2025-09-12,13:51:55 | INFO | Train Epoch: 1 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 1.2584 (1.4636) Boundary_loss: 0.014120 (0.014044) Loss: 1.2726 (1.4776) +2025-09-12,13:52:26 | INFO | Train Epoch: 1 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 1.3483 (1.4631) Boundary_loss: 0.013987 (0.014044) Loss: 1.3623 (1.4772) +2025-09-12,13:52:57 | INFO | Train Epoch: 1 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 1.2885 (1.4625) Boundary_loss: 0.014167 (0.014045) Loss: 1.3026 (1.4765) +2025-09-12,13:53:28 | INFO | Train Epoch: 1 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 1.2170 (1.4615) Boundary_loss: 0.013999 (0.014045) Loss: 1.2310 (1.4756) +2025-09-12,13:54:00 | INFO | Train Epoch: 1 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 1.3883 (1.4613) Boundary_loss: 0.014016 (0.014044) Loss: 1.4023 (1.4753) +2025-09-12,13:54:31 | INFO | Train Epoch: 1 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 1.2546 (1.4605) Boundary_loss: 0.014039 (0.014044) Loss: 1.2686 (1.4745) +2025-09-12,13:55:02 | INFO | Train Epoch: 1 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 1.1772 (1.4594) Boundary_loss: 0.013959 (0.014044) Loss: 1.1911 (1.4735) +2025-09-12,13:55:34 | INFO | Train Epoch: 1 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 1.2299 (1.4585) Boundary_loss: 0.013966 (0.014044) Loss: 1.2439 (1.4726) +2025-09-12,13:56:05 | INFO | Train Epoch: 1 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.3964 (1.4583) Boundary_loss: 0.013966 (0.014044) Loss: 1.4103 (1.4724) +2025-09-12,13:56:36 | INFO | Train Epoch: 1 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 1.3167 (1.4578) Boundary_loss: 0.013985 (0.014043) Loss: 1.3306 (1.4718) +2025-09-12,13:57:07 | INFO | Train Epoch: 1 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.2866 (1.4572) Boundary_loss: 0.013946 (0.014043) Loss: 1.3005 (1.4712) +2025-09-12,13:57:39 | INFO | Train Epoch: 1 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 1.3410 (1.4567) Boundary_loss: 0.013954 (0.014043) Loss: 1.3549 (1.4708) +2025-09-12,13:58:10 | INFO | Train Epoch: 1 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 1.3817 (1.4564) Boundary_loss: 0.013964 (0.014042) Loss: 1.3957 (1.4705) +2025-09-12,13:58:41 | INFO | Train Epoch: 1 [13875712/26365952 (53%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 1.2948 (1.4558) Boundary_loss: 0.013984 (0.014042) Loss: 1.3088 (1.4699) +2025-09-12,13:59:13 | INFO | Train Epoch: 1 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 1.3554 (1.4555) Boundary_loss: 0.013989 (0.014042) Loss: 1.3694 (1.4695) +2025-09-12,13:59:44 | INFO | Train Epoch: 1 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 1.3497 (1.4551) Boundary_loss: 0.013971 (0.014042) Loss: 1.3637 (1.4691) +2025-09-12,14:00:16 | INFO | Train Epoch: 1 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.3585 (1.4547) Boundary_loss: 0.013972 (0.014041) Loss: 1.3725 (1.4688) +2025-09-12,14:00:47 | INFO | Train Epoch: 1 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.1907 (1.4538) Boundary_loss: 0.013929 (0.014041) Loss: 1.2047 (1.4678) +2025-09-12,14:01:18 | INFO | Train Epoch: 1 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 1.4573 (1.4538) Boundary_loss: 0.013982 (0.014041) Loss: 1.4712 (1.4678) +2025-09-12,14:01:50 | INFO | Train Epoch: 1 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.2747 (1.4532) Boundary_loss: 0.013940 (0.014040) Loss: 1.2887 (1.4672) +2025-09-12,14:02:21 | INFO | Train Epoch: 1 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 1.2401 (1.4524) Boundary_loss: 0.013987 (0.014040) Loss: 1.2541 (1.4664) +2025-09-12,14:02:53 | INFO | Train Epoch: 1 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 1.2042 (1.4515) Boundary_loss: 0.013992 (0.014040) Loss: 1.2182 (1.4655) +2025-09-12,14:03:24 | INFO | Train Epoch: 1 [14336512/26365952 (54%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 1.2231 (1.4507) Boundary_loss: 0.013990 (0.014040) Loss: 1.2371 (1.4647) +2025-09-12,14:03:56 | INFO | Train Epoch: 1 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 1.2148 (1.4499) Boundary_loss: 0.013971 (0.014040) Loss: 1.2287 (1.4639) +2025-09-12,14:04:27 | INFO | Train Epoch: 1 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.2644 (1.4492) Boundary_loss: 0.014000 (0.014039) Loss: 1.2784 (1.4632) +2025-09-12,14:04:59 | INFO | Train Epoch: 1 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 1.3535 (1.4489) Boundary_loss: 0.013949 (0.014039) Loss: 1.3675 (1.4629) +2025-09-12,14:05:31 | INFO | Train Epoch: 1 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 1.4617 (1.4489) Boundary_loss: 0.013974 (0.014039) Loss: 1.4757 (1.4629) +2025-09-12,14:06:02 | INFO | Train Epoch: 1 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 1.3125 (1.4484) Boundary_loss: 0.013953 (0.014039) Loss: 1.3265 (1.4625) +2025-09-12,14:06:34 | INFO | Train Epoch: 1 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 1.2378 (1.4477) Boundary_loss: 0.013973 (0.014038) Loss: 1.2518 (1.4617) +2025-09-12,14:07:06 | INFO | Train Epoch: 1 [14694912/26365952 (56%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 1.1930 (1.4468) Boundary_loss: 0.013964 (0.014038) Loss: 1.2070 (1.4609) +2025-09-12,14:07:37 | INFO | Train Epoch: 1 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 1.3672 (1.4465) Boundary_loss: 0.013960 (0.014038) Loss: 1.3812 (1.4606) +2025-09-12,14:08:09 | INFO | Train Epoch: 1 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 1.3280 (1.4461) Boundary_loss: 0.014018 (0.014038) Loss: 1.3421 (1.4602) +2025-09-12,14:08:41 | INFO | Train Epoch: 1 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 1.3583 (1.4458) Boundary_loss: 0.013959 (0.014038) Loss: 1.3722 (1.4599) +2025-09-12,14:09:12 | INFO | Train Epoch: 1 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 1.3177 (1.4454) Boundary_loss: 0.013988 (0.014037) Loss: 1.3317 (1.4594) +2025-09-12,14:09:44 | INFO | Train Epoch: 1 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 1.2890 (1.4449) Boundary_loss: 0.014007 (0.014037) Loss: 1.3030 (1.4589) +2025-09-12,14:10:15 | INFO | Train Epoch: 1 [15002112/26365952 (57%)] Avg Boundaries (per batch): 49.410 Boundary Ratio: 0.252 Contrastive_loss: 1.3095 (1.4444) Boundary_loss: 0.014363 (0.014038) Loss: 1.3239 (1.4584) +2025-09-12,14:10:47 | INFO | Train Epoch: 1 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.1956 (1.4436) Boundary_loss: 0.014037 (0.014038) Loss: 1.2097 (1.4576) +2025-09-12,14:11:18 | INFO | Train Epoch: 1 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 1.4398 (1.4435) Boundary_loss: 0.014007 (0.014038) Loss: 1.4538 (1.4576) +2025-09-12,14:11:50 | INFO | Train Epoch: 1 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 1.2515 (1.4429) Boundary_loss: 0.013992 (0.014038) Loss: 1.2655 (1.4569) +2025-09-12,14:12:22 | INFO | Train Epoch: 1 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 1.3220 (1.4425) Boundary_loss: 0.013934 (0.014038) Loss: 1.3360 (1.4565) +2025-09-12,14:12:53 | INFO | Train Epoch: 1 [15258112/26365952 (58%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 1.3387 (1.4421) Boundary_loss: 0.014102 (0.014038) Loss: 1.3528 (1.4562) +2025-09-12,14:13:25 | INFO | Train Epoch: 1 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 1.2827 (1.4416) Boundary_loss: 0.013936 (0.014038) Loss: 1.2967 (1.4556) +2025-09-12,14:13:56 | INFO | Train Epoch: 1 [15360512/26365952 (58%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 1.4179 (1.4415) Boundary_loss: 0.014005 (0.014038) Loss: 1.4320 (1.4556) +2025-09-12,14:14:28 | INFO | Train Epoch: 1 [15411712/26365952 (58%)] Avg Boundaries (per batch): 49.457 Boundary Ratio: 0.252 Contrastive_loss: 1.2770 (1.4410) Boundary_loss: 0.014113 (0.014038) Loss: 1.2911 (1.4550) +2025-09-12,14:15:00 | INFO | Train Epoch: 1 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 1.2811 (1.4405) Boundary_loss: 0.013991 (0.014038) Loss: 1.2951 (1.4545) +2025-09-12,14:15:31 | INFO | Train Epoch: 1 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 1.3314 (1.4401) Boundary_loss: 0.013953 (0.014037) Loss: 1.3454 (1.4541) +2025-09-12,14:16:03 | INFO | Train Epoch: 1 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 1.2719 (1.4395) Boundary_loss: 0.013991 (0.014037) Loss: 1.2859 (1.4536) +2025-09-12,14:16:35 | INFO | Train Epoch: 1 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 1.2951 (1.4391) Boundary_loss: 0.013951 (0.014037) Loss: 1.3090 (1.4531) +2025-09-12,14:17:06 | INFO | Train Epoch: 1 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 1.3373 (1.4387) Boundary_loss: 0.014066 (0.014037) Loss: 1.3514 (1.4528) +2025-09-12,14:17:38 | INFO | Train Epoch: 1 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 1.2657 (1.4382) Boundary_loss: 0.013944 (0.014037) Loss: 1.2796 (1.4522) +2025-09-12,14:18:09 | INFO | Train Epoch: 1 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 1.3900 (1.4380) Boundary_loss: 0.013944 (0.014036) Loss: 1.4039 (1.4521) +2025-09-12,14:18:41 | INFO | Train Epoch: 1 [15821312/26365952 (60%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 1.5059 (1.4382) Boundary_loss: 0.013992 (0.014036) Loss: 1.5199 (1.4523) +2025-09-12,14:19:13 | INFO | Train Epoch: 1 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 1.3013 (1.4378) Boundary_loss: 0.013944 (0.014036) Loss: 1.3152 (1.4518) +2025-09-12,14:19:45 | INFO | Train Epoch: 1 [15923712/26365952 (60%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 1.4146 (1.4377) Boundary_loss: 0.013996 (0.014036) Loss: 1.4286 (1.4518) +2025-09-12,14:20:16 | INFO | Train Epoch: 1 [15974912/26365952 (61%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 1.2312 (1.4371) Boundary_loss: 0.013982 (0.014036) Loss: 1.2452 (1.4511) +2025-09-12,14:20:48 | INFO | Train Epoch: 1 [16026112/26365952 (61%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 1.1696 (1.4362) Boundary_loss: 0.013966 (0.014035) Loss: 1.1836 (1.4503) +2025-09-12,14:21:20 | INFO | Train Epoch: 1 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 1.4213 (1.4362) Boundary_loss: 0.014081 (0.014036) Loss: 1.4354 (1.4502) +2025-09-12,14:21:51 | INFO | Train Epoch: 1 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 1.2722 (1.4357) Boundary_loss: 0.014018 (0.014036) Loss: 1.2863 (1.4497) +2025-09-12,14:22:23 | INFO | Train Epoch: 1 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 1.3496 (1.4354) Boundary_loss: 0.013945 (0.014035) Loss: 1.3636 (1.4494) +2025-09-12,14:22:54 | INFO | Train Epoch: 1 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 1.4100 (1.4353) Boundary_loss: 0.013961 (0.014035) Loss: 1.4240 (1.4493) +2025-09-12,14:23:25 | INFO | Train Epoch: 1 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 1.2039 (1.4346) Boundary_loss: 0.014021 (0.014035) Loss: 1.2179 (1.4486) +2025-09-12,14:23:57 | INFO | Train Epoch: 1 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 1.2268 (1.4339) Boundary_loss: 0.014035 (0.014035) Loss: 1.2408 (1.4480) +2025-09-12,14:24:28 | INFO | Train Epoch: 1 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 1.4562 (1.4340) Boundary_loss: 0.013966 (0.014035) Loss: 1.4702 (1.4480) +2025-09-12,14:25:00 | INFO | Train Epoch: 1 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 1.2470 (1.4334) Boundary_loss: 0.013949 (0.014034) Loss: 1.2609 (1.4474) +2025-09-12,14:25:31 | INFO | Train Epoch: 1 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.2660 (1.4329) Boundary_loss: 0.014360 (0.014036) Loss: 1.2804 (1.4469) +2025-09-12,14:26:03 | INFO | Train Epoch: 1 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.2795 (1.4324) Boundary_loss: 0.013932 (0.014035) Loss: 1.2934 (1.4465) +2025-09-12,14:26:34 | INFO | Train Epoch: 1 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 1.1635 (1.4316) Boundary_loss: 0.013981 (0.014035) Loss: 1.1775 (1.4456) +2025-09-12,14:27:06 | INFO | Train Epoch: 1 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 1.3076 (1.4312) Boundary_loss: 0.014255 (0.014036) Loss: 1.3218 (1.4453) +2025-09-12,14:27:37 | INFO | Train Epoch: 1 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 1.3369 (1.4309) Boundary_loss: 0.013975 (0.014036) Loss: 1.3509 (1.4450) +2025-09-12,14:28:09 | INFO | Train Epoch: 1 [16742912/26365952 (64%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 1.3457 (1.4307) Boundary_loss: 0.013945 (0.014035) Loss: 1.3596 (1.4447) +2025-09-12,14:28:41 | INFO | Train Epoch: 1 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.2773 (1.4302) Boundary_loss: 0.013925 (0.014035) Loss: 1.2912 (1.4442) +2025-09-12,14:29:12 | INFO | Train Epoch: 1 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 1.2008 (1.4295) Boundary_loss: 0.013951 (0.014035) Loss: 1.2148 (1.4435) +2025-09-12,14:29:43 | INFO | Train Epoch: 1 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 1.2131 (1.4289) Boundary_loss: 0.013944 (0.014034) Loss: 1.2271 (1.4429) +2025-09-12,14:30:15 | INFO | Train Epoch: 1 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.2823 (1.4284) Boundary_loss: 0.013942 (0.014034) Loss: 1.2962 (1.4424) +2025-09-12,14:30:46 | INFO | Train Epoch: 1 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.2105 (1.4278) Boundary_loss: 0.013954 (0.014034) Loss: 1.2245 (1.4418) +2025-09-12,14:31:18 | INFO | Train Epoch: 1 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 1.1419 (1.4269) Boundary_loss: 0.013941 (0.014034) Loss: 1.1559 (1.4409) +2025-09-12,14:31:49 | INFO | Train Epoch: 1 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 1.2196 (1.4263) Boundary_loss: 0.013942 (0.014033) Loss: 1.2335 (1.4403) +2025-09-12,14:32:21 | INFO | Train Epoch: 1 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 1.2643 (1.4258) Boundary_loss: 0.013953 (0.014033) Loss: 1.2782 (1.4398) +2025-09-12,14:32:52 | INFO | Train Epoch: 1 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 1.3124 (1.4255) Boundary_loss: 0.014060 (0.014033) Loss: 1.3264 (1.4395) +2025-09-12,14:33:24 | INFO | Train Epoch: 1 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.508 Boundary Ratio: 0.247 Contrastive_loss: 1.2860 (1.4251) Boundary_loss: 0.013995 (0.014033) Loss: 1.3000 (1.4391) +2025-09-12,14:33:55 | INFO | Train Epoch: 1 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.2839 (1.4246) Boundary_loss: 0.013957 (0.014033) Loss: 1.2979 (1.4387) +2025-09-12,14:34:27 | INFO | Train Epoch: 1 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 1.3094 (1.4243) Boundary_loss: 0.014175 (0.014033) Loss: 1.3236 (1.4383) +2025-09-12,14:34:58 | INFO | Train Epoch: 1 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 1.3176 (1.4240) Boundary_loss: 0.014037 (0.014033) Loss: 1.3316 (1.4380) +2025-09-12,14:35:29 | INFO | Train Epoch: 1 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 1.2802 (1.4236) Boundary_loss: 0.013947 (0.014033) Loss: 1.2941 (1.4376) +2025-09-12,14:36:00 | INFO | Train Epoch: 1 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 1.2727 (1.4231) Boundary_loss: 0.014027 (0.014033) Loss: 1.2868 (1.4372) +2025-09-12,14:36:32 | INFO | Train Epoch: 1 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 1.2514 (1.4226) Boundary_loss: 0.013988 (0.014033) Loss: 1.2654 (1.4367) +2025-09-12,14:37:03 | INFO | Train Epoch: 1 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.1963 (1.4220) Boundary_loss: 0.014007 (0.014033) Loss: 1.2103 (1.4360) +2025-09-12,14:37:34 | INFO | Train Epoch: 1 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.2946 (1.4216) Boundary_loss: 0.013949 (0.014033) Loss: 1.3086 (1.4356) +2025-09-12,14:38:06 | INFO | Train Epoch: 1 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.492 Boundary Ratio: 0.247 Contrastive_loss: 1.2834 (1.4212) Boundary_loss: 0.014023 (0.014032) Loss: 1.2974 (1.4352) +2025-09-12,14:38:37 | INFO | Train Epoch: 1 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.1758 (1.4205) Boundary_loss: 0.013930 (0.014032) Loss: 1.1898 (1.4345) +2025-09-12,14:39:08 | INFO | Train Epoch: 1 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 1.1555 (1.4197) Boundary_loss: 0.013963 (0.014032) Loss: 1.1694 (1.4338) +2025-09-12,14:39:40 | INFO | Train Epoch: 1 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.2102 (1.4191) Boundary_loss: 0.014016 (0.014032) Loss: 1.2243 (1.4332) +2025-09-12,14:40:11 | INFO | Train Epoch: 1 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 1.4030 (1.4191) Boundary_loss: 0.013954 (0.014032) Loss: 1.4170 (1.4331) +2025-09-12,14:40:43 | INFO | Train Epoch: 1 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 1.3203 (1.4188) Boundary_loss: 0.014138 (0.014032) Loss: 1.3345 (1.4328) +2025-09-12,14:41:14 | INFO | Train Epoch: 1 [18022912/26365952 (68%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 1.4057 (1.4188) Boundary_loss: 0.014122 (0.014032) Loss: 1.4198 (1.4328) +2025-09-12,14:41:46 | INFO | Train Epoch: 1 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 1.1681 (1.4181) Boundary_loss: 0.013966 (0.014032) Loss: 1.1821 (1.4321) +2025-09-12,14:42:17 | INFO | Train Epoch: 1 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 1.2827 (1.4177) Boundary_loss: 0.014117 (0.014032) Loss: 1.2968 (1.4317) +2025-09-12,14:42:49 | INFO | Train Epoch: 1 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 1.3705 (1.4176) Boundary_loss: 0.013942 (0.014032) Loss: 1.3845 (1.4316) +2025-09-12,14:43:20 | INFO | Train Epoch: 1 [18227712/26365952 (69%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 1.2120 (1.4170) Boundary_loss: 0.013982 (0.014032) Loss: 1.2260 (1.4310) +2025-09-12,14:43:51 | INFO | Train Epoch: 1 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.2040 (1.4164) Boundary_loss: 0.013946 (0.014032) Loss: 1.2180 (1.4304) +2025-09-12,14:44:22 | INFO | Train Epoch: 1 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 1.2442 (1.4159) Boundary_loss: 0.013969 (0.014032) Loss: 1.2582 (1.4299) +2025-09-12,14:44:53 | INFO | Train Epoch: 1 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 1.2967 (1.4156) Boundary_loss: 0.014091 (0.014032) Loss: 1.3108 (1.4296) +2025-09-12,14:45:25 | INFO | Train Epoch: 1 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 1.0759 (1.4146) Boundary_loss: 0.013960 (0.014031) Loss: 1.0899 (1.4287) +2025-09-12,14:45:56 | INFO | Train Epoch: 1 [18483712/26365952 (70%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 1.2897 (1.4143) Boundary_loss: 0.014018 (0.014031) Loss: 1.3037 (1.4283) +2025-09-12,14:46:27 | INFO | Train Epoch: 1 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 1.1096 (1.4134) Boundary_loss: 0.013933 (0.014031) Loss: 1.1235 (1.4275) +2025-09-12,14:46:59 | INFO | Train Epoch: 1 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 1.3033 (1.4131) Boundary_loss: 0.013953 (0.014031) Loss: 1.3173 (1.4272) +2025-09-12,14:47:30 | INFO | Train Epoch: 1 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.2908 (1.4128) Boundary_loss: 0.013995 (0.014031) Loss: 1.3048 (1.4268) +2025-09-12,14:48:01 | INFO | Train Epoch: 1 [18688512/26365952 (71%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 1.2145 (1.4123) Boundary_loss: 0.014028 (0.014031) Loss: 1.2285 (1.4263) +2025-09-12,14:48:33 | INFO | Train Epoch: 1 [18739712/26365952 (71%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 1.1994 (1.4117) Boundary_loss: 0.013949 (0.014031) Loss: 1.2133 (1.4257) +2025-09-12,14:49:05 | INFO | Train Epoch: 1 [18790912/26365952 (71%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 1.1680 (1.4110) Boundary_loss: 0.013934 (0.014030) Loss: 1.1819 (1.4251) +2025-09-12,14:49:36 | INFO | Train Epoch: 1 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.004 Boundary Ratio: 0.245 Contrastive_loss: 1.1726 (1.4104) Boundary_loss: 0.014182 (0.014031) Loss: 1.1868 (1.4244) +2025-09-12,14:50:08 | INFO | Train Epoch: 1 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.2051 (1.4098) Boundary_loss: 0.014052 (0.014031) Loss: 1.2191 (1.4239) +2025-09-12,14:50:40 | INFO | Train Epoch: 1 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 1.3500 (1.4097) Boundary_loss: 0.013943 (0.014031) Loss: 1.3640 (1.4237) +2025-09-12,14:51:11 | INFO | Train Epoch: 1 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.3985 (1.4096) Boundary_loss: 0.013966 (0.014030) Loss: 1.4125 (1.4237) +2025-09-12,14:51:43 | INFO | Train Epoch: 1 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.1494 (1.4089) Boundary_loss: 0.013947 (0.014030) Loss: 1.1633 (1.4230) +2025-09-12,14:52:14 | INFO | Train Epoch: 1 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.3170 (1.4087) Boundary_loss: 0.013994 (0.014030) Loss: 1.3310 (1.4227) +2025-09-12,14:52:45 | INFO | Train Epoch: 1 [19149312/26365952 (73%)] Avg Boundaries (per batch): 49.320 Boundary Ratio: 0.252 Contrastive_loss: 1.2899 (1.4084) Boundary_loss: 0.013995 (0.014030) Loss: 1.3039 (1.4224) +2025-09-12,14:53:17 | INFO | Train Epoch: 1 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.1302 (1.4076) Boundary_loss: 0.013975 (0.014030) Loss: 1.1442 (1.4217) +2025-09-12,14:53:48 | INFO | Train Epoch: 1 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 1.3004 (1.4073) Boundary_loss: 0.013974 (0.014030) Loss: 1.3144 (1.4214) +2025-09-12,14:54:20 | INFO | Train Epoch: 1 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 1.4104 (1.4074) Boundary_loss: 0.013952 (0.014030) Loss: 1.4243 (1.4214) +2025-09-12,14:54:51 | INFO | Train Epoch: 1 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 1.3444 (1.4072) Boundary_loss: 0.013965 (0.014029) Loss: 1.3584 (1.4212) +2025-09-12,14:55:23 | INFO | Train Epoch: 1 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 1.2639 (1.4068) Boundary_loss: 0.013964 (0.014029) Loss: 1.2778 (1.4208) +2025-09-12,14:55:54 | INFO | Train Epoch: 1 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 1.2387 (1.4064) Boundary_loss: 0.013921 (0.014029) Loss: 1.2526 (1.4204) +2025-09-12,14:56:26 | INFO | Train Epoch: 1 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 1.2902 (1.4061) Boundary_loss: 0.014005 (0.014029) Loss: 1.3042 (1.4201) +2025-09-12,14:56:57 | INFO | Train Epoch: 1 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 1.2701 (1.4057) Boundary_loss: 0.013959 (0.014029) Loss: 1.2841 (1.4197) +2025-09-12,14:57:28 | INFO | Train Epoch: 1 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.3091 (1.4055) Boundary_loss: 0.013955 (0.014028) Loss: 1.3230 (1.4195) +2025-09-12,14:58:00 | INFO | Train Epoch: 1 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 1.3350 (1.4053) Boundary_loss: 0.013965 (0.014028) Loss: 1.3490 (1.4193) +2025-09-12,14:58:31 | INFO | Train Epoch: 1 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 1.1840 (1.4047) Boundary_loss: 0.013938 (0.014028) Loss: 1.1979 (1.4187) +2025-09-12,14:59:03 | INFO | Train Epoch: 1 [19763712/26365952 (75%)] Avg Boundaries (per batch): 49.535 Boundary Ratio: 0.253 Contrastive_loss: 1.3646 (1.4046) Boundary_loss: 0.014130 (0.014028) Loss: 1.3787 (1.4186) +2025-09-12,14:59:34 | INFO | Train Epoch: 1 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 1.2083 (1.4041) Boundary_loss: 0.013934 (0.014028) Loss: 1.2222 (1.4181) +2025-09-12,15:00:06 | INFO | Train Epoch: 1 [19866112/26365952 (75%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 1.1488 (1.4034) Boundary_loss: 0.013940 (0.014028) Loss: 1.1627 (1.4175) +2025-09-12,15:00:37 | INFO | Train Epoch: 1 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 1.1468 (1.4028) Boundary_loss: 0.013982 (0.014028) Loss: 1.1608 (1.4168) +2025-09-12,15:01:09 | INFO | Train Epoch: 1 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.1809 (1.4022) Boundary_loss: 0.013927 (0.014027) Loss: 1.1948 (1.4162) +2025-09-12,15:01:40 | INFO | Train Epoch: 1 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 1.0063 (1.4012) Boundary_loss: 0.013940 (0.014027) Loss: 1.0202 (1.4152) +2025-09-12,15:02:12 | INFO | Train Epoch: 1 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 1.2626 (1.4008) Boundary_loss: 0.013955 (0.014027) Loss: 1.2766 (1.4149) +2025-09-12,15:02:43 | INFO | Train Epoch: 1 [20122112/26365952 (76%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 1.2134 (1.4004) Boundary_loss: 0.013994 (0.014027) Loss: 1.2274 (1.4144) +2025-09-12,15:03:15 | INFO | Train Epoch: 1 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 1.2887 (1.4001) Boundary_loss: 0.013932 (0.014027) Loss: 1.3026 (1.4141) +2025-09-12,15:03:46 | INFO | Train Epoch: 1 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.516 Boundary Ratio: 0.248 Contrastive_loss: 1.3638 (1.4000) Boundary_loss: 0.013975 (0.014027) Loss: 1.3777 (1.4140) +2025-09-12,15:04:18 | INFO | Train Epoch: 1 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 1.3537 (1.3999) Boundary_loss: 0.013928 (0.014026) Loss: 1.3676 (1.4139) +2025-09-12,15:04:49 | INFO | Train Epoch: 1 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 1.1994 (1.3994) Boundary_loss: 0.014057 (0.014026) Loss: 1.2134 (1.4134) +2025-09-12,15:05:21 | INFO | Train Epoch: 1 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 1.1517 (1.3988) Boundary_loss: 0.013972 (0.014026) Loss: 1.1657 (1.4128) +2025-09-12,15:05:52 | INFO | Train Epoch: 1 [20429312/26365952 (77%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 1.2518 (1.3984) Boundary_loss: 0.013926 (0.014026) Loss: 1.2657 (1.4124) +2025-09-12,15:06:23 | INFO | Train Epoch: 1 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 1.1424 (1.3978) Boundary_loss: 0.013972 (0.014026) Loss: 1.1564 (1.4118) +2025-09-12,15:06:55 | INFO | Train Epoch: 1 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 1.1665 (1.3972) Boundary_loss: 0.013955 (0.014026) Loss: 1.1804 (1.4112) +2025-09-12,15:07:26 | INFO | Train Epoch: 1 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 1.3544 (1.3971) Boundary_loss: 0.013988 (0.014026) Loss: 1.3684 (1.4111) +2025-09-12,15:07:57 | INFO | Train Epoch: 1 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.2590 (1.3967) Boundary_loss: 0.013945 (0.014025) Loss: 1.2729 (1.4108) +2025-09-12,15:08:27 | INFO | Train Epoch: 1 [20685312/26365952 (78%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 1.1526 (1.3961) Boundary_loss: 0.014012 (0.014025) Loss: 1.1666 (1.4102) +2025-09-12,15:08:59 | INFO | Train Epoch: 1 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 1.2171 (1.3957) Boundary_loss: 0.013963 (0.014025) Loss: 1.2311 (1.4097) +2025-09-12,15:09:30 | INFO | Train Epoch: 1 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.1983 (1.3952) Boundary_loss: 0.013934 (0.014025) Loss: 1.2123 (1.4092) +2025-09-12,15:10:01 | INFO | Train Epoch: 1 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 1.1207 (1.3945) Boundary_loss: 0.013941 (0.014025) Loss: 1.1346 (1.4086) +2025-09-12,15:10:32 | INFO | Train Epoch: 1 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 1.3381 (1.3944) Boundary_loss: 0.013932 (0.014025) Loss: 1.3520 (1.4084) +2025-09-12,15:11:03 | INFO | Train Epoch: 1 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 1.2737 (1.3941) Boundary_loss: 0.013958 (0.014024) Loss: 1.2877 (1.4081) +2025-09-12,15:11:34 | INFO | Train Epoch: 1 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 1.3140 (1.3939) Boundary_loss: 0.013963 (0.014024) Loss: 1.3280 (1.4079) +2025-09-12,15:12:05 | INFO | Train Epoch: 1 [21043712/26365952 (80%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 1.1516 (1.3933) Boundary_loss: 0.014059 (0.014024) Loss: 1.1657 (1.4073) +2025-09-12,15:12:36 | INFO | Train Epoch: 1 [21094912/26365952 (80%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 1.1807 (1.3928) Boundary_loss: 0.013950 (0.014024) Loss: 1.1946 (1.4068) +2025-09-12,15:13:07 | INFO | Train Epoch: 1 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.1436 (1.3922) Boundary_loss: 0.013924 (0.014024) Loss: 1.1575 (1.4062) +2025-09-12,15:13:38 | INFO | Train Epoch: 1 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 1.2404 (1.3918) Boundary_loss: 0.014008 (0.014024) Loss: 1.2544 (1.4059) +2025-09-12,15:14:09 | INFO | Train Epoch: 1 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 1.1747 (1.3913) Boundary_loss: 0.013930 (0.014024) Loss: 1.1887 (1.4053) +2025-09-12,15:14:40 | INFO | Train Epoch: 1 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.3190 (1.3911) Boundary_loss: 0.014103 (0.014024) Loss: 1.3331 (1.4052) +2025-09-12,15:15:11 | INFO | Train Epoch: 1 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 1.0811 (1.3904) Boundary_loss: 0.013928 (0.014024) Loss: 1.0951 (1.4044) +2025-09-12,15:15:42 | INFO | Train Epoch: 1 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.1238 (1.3898) Boundary_loss: 0.013928 (0.014023) Loss: 1.1377 (1.4038) +2025-09-12,15:16:13 | INFO | Train Epoch: 1 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 1.3405 (1.3896) Boundary_loss: 0.013957 (0.014023) Loss: 1.3545 (1.4037) +2025-09-12,15:16:44 | INFO | Train Epoch: 1 [21504512/26365952 (82%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 1.1830 (1.3891) Boundary_loss: 0.013940 (0.014023) Loss: 1.1969 (1.4032) +2025-09-12,15:17:15 | INFO | Train Epoch: 1 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 1.1737 (1.3886) Boundary_loss: 0.014029 (0.014023) Loss: 1.1877 (1.4027) +2025-09-12,15:17:46 | INFO | Train Epoch: 1 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 1.1690 (1.3881) Boundary_loss: 0.013966 (0.014023) Loss: 1.1830 (1.4021) +2025-09-12,15:18:17 | INFO | Train Epoch: 1 [21658112/26365952 (82%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 1.1400 (1.3875) Boundary_loss: 0.013964 (0.014023) Loss: 1.1540 (1.4016) +2025-09-12,15:18:48 | INFO | Train Epoch: 1 [21709312/26365952 (82%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 1.2649 (1.3872) Boundary_loss: 0.013936 (0.014023) Loss: 1.2789 (1.4013) +2025-09-12,15:19:19 | INFO | Train Epoch: 1 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 1.1644 (1.3867) Boundary_loss: 0.013996 (0.014023) Loss: 1.1784 (1.4007) +2025-09-12,15:19:50 | INFO | Train Epoch: 1 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 1.1053 (1.3861) Boundary_loss: 0.013951 (0.014022) Loss: 1.1192 (1.4001) +2025-09-12,15:20:21 | INFO | Train Epoch: 1 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 1.2815 (1.3858) Boundary_loss: 0.013985 (0.014022) Loss: 1.2955 (1.3998) +2025-09-12,15:20:53 | INFO | Train Epoch: 1 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 1.1212 (1.3852) Boundary_loss: 0.013937 (0.014022) Loss: 1.1352 (1.3992) +2025-09-12,15:21:24 | INFO | Train Epoch: 1 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 1.3745 (1.3852) Boundary_loss: 0.013933 (0.014022) Loss: 1.3885 (1.3992) +2025-09-12,15:21:55 | INFO | Train Epoch: 1 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 1.2630 (1.3849) Boundary_loss: 0.013947 (0.014022) Loss: 1.2770 (1.3989) +2025-09-12,15:22:27 | INFO | Train Epoch: 1 [22067712/26365952 (84%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 1.4120 (1.3850) Boundary_loss: 0.013987 (0.014022) Loss: 1.4260 (1.3990) +2025-09-12,15:22:58 | INFO | Train Epoch: 1 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 1.1625 (1.3844) Boundary_loss: 0.013959 (0.014022) Loss: 1.1765 (1.3985) +2025-09-12,15:23:29 | INFO | Train Epoch: 1 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 1.1117 (1.3838) Boundary_loss: 0.013977 (0.014021) Loss: 1.1257 (1.3978) +2025-09-12,15:24:01 | INFO | Train Epoch: 1 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.1176 (1.3832) Boundary_loss: 0.013944 (0.014021) Loss: 1.1316 (1.3972) +2025-09-12,15:24:32 | INFO | Train Epoch: 1 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 1.2321 (1.3829) Boundary_loss: 0.013939 (0.014021) Loss: 1.2460 (1.3969) +2025-09-12,15:25:04 | INFO | Train Epoch: 1 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 1.2346 (1.3825) Boundary_loss: 0.013946 (0.014021) Loss: 1.2486 (1.3965) +2025-09-12,15:25:35 | INFO | Train Epoch: 1 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 1.2739 (1.3823) Boundary_loss: 0.013982 (0.014021) Loss: 1.2878 (1.3963) +2025-09-12,15:26:07 | INFO | Train Epoch: 1 [22426112/26365952 (85%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 1.2034 (1.3819) Boundary_loss: 0.013940 (0.014021) Loss: 1.2173 (1.3959) +2025-09-12,15:26:38 | INFO | Train Epoch: 1 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 1.1258 (1.3813) Boundary_loss: 0.013955 (0.014020) Loss: 1.1398 (1.3953) +2025-09-12,15:27:10 | INFO | Train Epoch: 1 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.0886 (1.3806) Boundary_loss: 0.014003 (0.014020) Loss: 1.1026 (1.3946) +2025-09-12,15:27:41 | INFO | Train Epoch: 1 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 1.3354 (1.3805) Boundary_loss: 0.013946 (0.014020) Loss: 1.3494 (1.3945) +2025-09-12,15:28:13 | INFO | Train Epoch: 1 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 1.3014 (1.3803) Boundary_loss: 0.013936 (0.014020) Loss: 1.3154 (1.3944) +2025-09-12,15:28:45 | INFO | Train Epoch: 1 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 1.2197 (1.3800) Boundary_loss: 0.013978 (0.014020) Loss: 1.2337 (1.3940) +2025-09-12,15:29:16 | INFO | Train Epoch: 1 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.436 Boundary Ratio: 0.252 Contrastive_loss: 1.1980 (1.3796) Boundary_loss: 0.014007 (0.014020) Loss: 1.2120 (1.3936) +2025-09-12,15:29:48 | INFO | Train Epoch: 1 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.2008 (1.3792) Boundary_loss: 0.013940 (0.014020) Loss: 1.2147 (1.3932) +2025-09-12,15:30:19 | INFO | Train Epoch: 1 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 1.1597 (1.3787) Boundary_loss: 0.013939 (0.014020) Loss: 1.1736 (1.3927) +2025-09-12,15:30:50 | INFO | Train Epoch: 1 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.1225 (1.3781) Boundary_loss: 0.013952 (0.014019) Loss: 1.1364 (1.3921) +2025-09-12,15:31:22 | INFO | Train Epoch: 1 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 1.3565 (1.3781) Boundary_loss: 0.013919 (0.014019) Loss: 1.3705 (1.3921) +2025-09-12,15:31:53 | INFO | Train Epoch: 1 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 1.2080 (1.3777) Boundary_loss: 0.014002 (0.014019) Loss: 1.2220 (1.3917) +2025-09-12,15:32:24 | INFO | Train Epoch: 1 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 1.2161 (1.3773) Boundary_loss: 0.013945 (0.014019) Loss: 1.2300 (1.3913) +2025-09-12,15:32:55 | INFO | Train Epoch: 1 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.1783 (1.3769) Boundary_loss: 0.013917 (0.014019) Loss: 1.1922 (1.3909) +2025-09-12,15:33:26 | INFO | Train Epoch: 1 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 1.2790 (1.3767) Boundary_loss: 0.013940 (0.014019) Loss: 1.2929 (1.3907) +2025-09-12,15:33:58 | INFO | Train Epoch: 1 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.1154 (1.3761) Boundary_loss: 0.013938 (0.014018) Loss: 1.1293 (1.3901) +2025-09-12,15:34:29 | INFO | Train Epoch: 1 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.1622 (1.3756) Boundary_loss: 0.013946 (0.014018) Loss: 1.1762 (1.3896) +2025-09-12,15:35:00 | INFO | Train Epoch: 1 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 1.1829 (1.3752) Boundary_loss: 0.013971 (0.014018) Loss: 1.1969 (1.3892) +2025-09-12,15:35:32 | INFO | Train Epoch: 1 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 1.1989 (1.3748) Boundary_loss: 0.013947 (0.014018) Loss: 1.2128 (1.3888) +2025-09-12,15:36:03 | INFO | Train Epoch: 1 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 1.3254 (1.3747) Boundary_loss: 0.013969 (0.014018) Loss: 1.3394 (1.3887) +2025-09-12,15:36:34 | INFO | Train Epoch: 1 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 1.1918 (1.3743) Boundary_loss: 0.013937 (0.014018) Loss: 1.2057 (1.3883) +2025-09-12,15:37:06 | INFO | Train Epoch: 1 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.1115 (1.3737) Boundary_loss: 0.013966 (0.014018) Loss: 1.1254 (1.3877) +2025-09-12,15:37:37 | INFO | Train Epoch: 1 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 1.3226 (1.3736) Boundary_loss: 0.013927 (0.014017) Loss: 1.3365 (1.3876) +2025-09-12,15:38:09 | INFO | Train Epoch: 1 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.2338 (1.3733) Boundary_loss: 0.013968 (0.014017) Loss: 1.2477 (1.3873) +2025-09-12,15:38:40 | INFO | Train Epoch: 1 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 1.0877 (1.3727) Boundary_loss: 0.013935 (0.014017) Loss: 1.1017 (1.3867) +2025-09-12,15:39:12 | INFO | Train Epoch: 1 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.1702 (1.3723) Boundary_loss: 0.013960 (0.014017) Loss: 1.1842 (1.3863) +2025-09-12,15:39:43 | INFO | Train Epoch: 1 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 1.1984 (1.3719) Boundary_loss: 0.013943 (0.014017) Loss: 1.2124 (1.3859) +2025-09-12,15:40:14 | INFO | Train Epoch: 1 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.1931 (1.3715) Boundary_loss: 0.013986 (0.014017) Loss: 1.2071 (1.3855) +2025-09-12,15:40:45 | INFO | Train Epoch: 1 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 1.1375 (1.3710) Boundary_loss: 0.013961 (0.014017) Loss: 1.1514 (1.3850) +2025-09-12,15:41:16 | INFO | Train Epoch: 1 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 1.2262 (1.3707) Boundary_loss: 0.014058 (0.014017) Loss: 1.2403 (1.3847) +2025-09-12,15:41:47 | INFO | Train Epoch: 1 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 1.0828 (1.3701) Boundary_loss: 0.013928 (0.014017) Loss: 1.0967 (1.3841) +2025-09-12,15:42:18 | INFO | Train Epoch: 1 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.2103 (1.3697) Boundary_loss: 0.014017 (0.014017) Loss: 1.2243 (1.3838) +2025-09-12,15:42:49 | INFO | Train Epoch: 1 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.2855 (1.3696) Boundary_loss: 0.013921 (0.014016) Loss: 1.2995 (1.3836) +2025-09-12,15:43:20 | INFO | Train Epoch: 1 [24115712/26365952 (91%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 1.2488 (1.3693) Boundary_loss: 0.013959 (0.014016) Loss: 1.2627 (1.3833) +2025-09-12,15:43:51 | INFO | Train Epoch: 1 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 1.2027 (1.3690) Boundary_loss: 0.013955 (0.014016) Loss: 1.2167 (1.3830) +2025-09-12,15:44:22 | INFO | Train Epoch: 1 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 1.3073 (1.3688) Boundary_loss: 0.013965 (0.014016) Loss: 1.3213 (1.3828) +2025-09-12,15:44:53 | INFO | Train Epoch: 1 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 1.1125 (1.3683) Boundary_loss: 0.013942 (0.014016) Loss: 1.1264 (1.3823) +2025-09-12,15:45:24 | INFO | Train Epoch: 1 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 1.0548 (1.3676) Boundary_loss: 0.014004 (0.014016) Loss: 1.0688 (1.3816) +2025-09-12,15:45:56 | INFO | Train Epoch: 1 [24371712/26365952 (92%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 1.1493 (1.3672) Boundary_loss: 0.013941 (0.014016) Loss: 1.1633 (1.3812) +2025-09-12,15:46:27 | INFO | Train Epoch: 1 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.1808 (1.3668) Boundary_loss: 0.013938 (0.014015) Loss: 1.1947 (1.3808) +2025-09-12,15:46:58 | INFO | Train Epoch: 1 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 1.1211 (1.3663) Boundary_loss: 0.013977 (0.014015) Loss: 1.1350 (1.3803) +2025-09-12,15:47:29 | INFO | Train Epoch: 1 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 1.1052 (1.3657) Boundary_loss: 0.013971 (0.014015) Loss: 1.1192 (1.3797) +2025-09-12,15:48:00 | INFO | Train Epoch: 1 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.2369 (1.3655) Boundary_loss: 0.013928 (0.014015) Loss: 1.2509 (1.3795) +2025-09-12,15:48:32 | INFO | Train Epoch: 1 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 1.1804 (1.3651) Boundary_loss: 0.014007 (0.014015) Loss: 1.1944 (1.3791) +2025-09-12,15:49:03 | INFO | Train Epoch: 1 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 1.2235 (1.3648) Boundary_loss: 0.013930 (0.014015) Loss: 1.2374 (1.3788) +2025-09-12,15:49:34 | INFO | Train Epoch: 1 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 1.1978 (1.3644) Boundary_loss: 0.013933 (0.014015) Loss: 1.2118 (1.3784) +2025-09-12,15:50:06 | INFO | Train Epoch: 1 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.1855 (1.3641) Boundary_loss: 0.013942 (0.014015) Loss: 1.1995 (1.3781) +2025-09-12,15:50:37 | INFO | Train Epoch: 1 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.2316 (1.3638) Boundary_loss: 0.013948 (0.014014) Loss: 1.2455 (1.3778) +2025-09-12,15:51:08 | INFO | Train Epoch: 1 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 1.0577 (1.3632) Boundary_loss: 0.013962 (0.014014) Loss: 1.0717 (1.3772) +2025-09-12,15:51:40 | INFO | Train Epoch: 1 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 1.2666 (1.3630) Boundary_loss: 0.013983 (0.014014) Loss: 1.2806 (1.3770) +2025-09-12,15:52:11 | INFO | Train Epoch: 1 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 1.3198 (1.3629) Boundary_loss: 0.013947 (0.014014) Loss: 1.3337 (1.3769) +2025-09-12,15:52:43 | INFO | Train Epoch: 1 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.1199 (1.3624) Boundary_loss: 0.013947 (0.014014) Loss: 1.1339 (1.3764) +2025-09-12,15:53:14 | INFO | Train Epoch: 1 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 1.1311 (1.3619) Boundary_loss: 0.013976 (0.014014) Loss: 1.1451 (1.3759) +2025-09-12,15:53:45 | INFO | Train Epoch: 1 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 1.0535 (1.3613) Boundary_loss: 0.013929 (0.014014) Loss: 1.0675 (1.3753) +2025-09-12,15:54:17 | INFO | Train Epoch: 1 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.1565 (1.3609) Boundary_loss: 0.013950 (0.014014) Loss: 1.1705 (1.3749) +2025-09-12,15:54:48 | INFO | Train Epoch: 1 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 1.1918 (1.3605) Boundary_loss: 0.013943 (0.014013) Loss: 1.2058 (1.3745) +2025-09-12,15:55:19 | INFO | Train Epoch: 1 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.2163 (1.3602) Boundary_loss: 0.013948 (0.014013) Loss: 1.2302 (1.3742) +2025-09-12,15:55:51 | INFO | Train Epoch: 1 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 1.2770 (1.3601) Boundary_loss: 0.013948 (0.014013) Loss: 1.2909 (1.3741) +2025-09-12,15:56:22 | INFO | Train Epoch: 1 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 1.2176 (1.3598) Boundary_loss: 0.013990 (0.014013) Loss: 1.2316 (1.3738) +2025-09-12,15:56:54 | INFO | Train Epoch: 1 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 1.2620 (1.3596) Boundary_loss: 0.013926 (0.014013) Loss: 1.2759 (1.3736) +2025-09-12,15:57:25 | INFO | Train Epoch: 1 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.0410 (1.3589) Boundary_loss: 0.013917 (0.014013) Loss: 1.0549 (1.3730) +2025-09-12,15:57:57 | INFO | Train Epoch: 1 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 1.1000 (1.3584) Boundary_loss: 0.013961 (0.014013) Loss: 1.1140 (1.3724) +2025-09-12,15:58:28 | INFO | Train Epoch: 1 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 1.1430 (1.3580) Boundary_loss: 0.013945 (0.014013) Loss: 1.1569 (1.3720) +2025-09-12,15:59:00 | INFO | Train Epoch: 1 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 1.2589 (1.3578) Boundary_loss: 0.013940 (0.014012) Loss: 1.2728 (1.3718) +2025-09-12,15:59:32 | INFO | Train Epoch: 1 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 1.1459 (1.3574) Boundary_loss: 0.013957 (0.014012) Loss: 1.1599 (1.3714) +2025-09-12,16:00:03 | INFO | Train Epoch: 1 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 1.1245 (1.3569) Boundary_loss: 0.013948 (0.014012) Loss: 1.1385 (1.3709) +2025-09-12,16:00:35 | INFO | Train Epoch: 1 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 1.1524 (1.3565) Boundary_loss: 0.013926 (0.014012) Loss: 1.1664 (1.3705) +2025-09-12,16:01:06 | INFO | Train Epoch: 1 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 1.2337 (1.3563) Boundary_loss: 0.013999 (0.014012) Loss: 1.2477 (1.3703) +2025-09-12,16:01:38 | INFO | Train Epoch: 1 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 1.1935 (1.3559) Boundary_loss: 0.013988 (0.014012) Loss: 1.2075 (1.3700) +2025-09-12,16:02:09 | INFO | Train Epoch: 1 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 1.1635 (1.3556) Boundary_loss: 0.013952 (0.014012) Loss: 1.1774 (1.3696) +2025-09-12,16:02:41 | INFO | Train Epoch: 1 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 1.1623 (1.3552) Boundary_loss: 0.013916 (0.014012) Loss: 1.1762 (1.3692) +2025-09-12,16:03:12 | INFO | Train Epoch: 1 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 1.1656 (1.3548) Boundary_loss: 0.013928 (0.014011) Loss: 1.1796 (1.3688) +2025-09-12,16:03:44 | INFO | Train Epoch: 1 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 1.0891 (1.3543) Boundary_loss: 0.013949 (0.014011) Loss: 1.1030 (1.3683) +2025-09-12,16:04:16 | INFO | Train Epoch: 1 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 1.1608 (1.3539) Boundary_loss: 0.013938 (0.014011) Loss: 1.1747 (1.3679) +2025-09-12,16:04:47 | INFO | Train Epoch: 1 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.0411 (1.3533) Boundary_loss: 0.013937 (0.014011) Loss: 1.0550 (1.3673) +2025-09-12,16:05:19 | INFO | Train Epoch: 1 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 1.2136 (1.3530) Boundary_loss: 0.013930 (0.014011) Loss: 1.2275 (1.3670) +2025-09-12,16:05:51 | INFO | Train Epoch: 1 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 1.3208 (1.3530) Boundary_loss: 0.013970 (0.014011) Loss: 1.3348 (1.3670) +2025-09-12,16:06:21 | INFO | Train Epoch: 1 [26365952/26365952 (100%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 1.2218 (1.3527) Boundary_loss: 0.013983 (0.014011) Loss: 1.2358 (1.3667) +2025-09-12,16:06:21 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,16:06:21 | INFO | [Epoch 1] Average Step Time: 0.318s | Average GPU Memory: 25.8 GB +2025-09-12,16:06:21 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,16:06:21 | INFO | Starting zero-shot imagenet. +2025-09-12,16:06:21 | INFO | Building zero-shot classifier +2025-09-12,16:06:27 | INFO | Using classifier +2025-09-12,16:07:10 | INFO | Finished zero-shot imagenet. +2025-09-12,16:07:10 | INFO | Eval Epoch: 2 imagenet-zeroshot-val-top1: 0.1647 imagenet-zeroshot-val-top5: 0.3635 +2025-09-12,16:07:11 | INFO | Start epoch 2 +2025-09-12,16:07:13 | INFO | Train Epoch: 2 [ 512/26365952 (0%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 1.0978 (1.0978) Boundary_loss: 0.013987 (0.013987) Loss: 1.1118 (1.1118) +2025-09-12,16:07:45 | INFO | Train Epoch: 2 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.0801 (1.0889) Boundary_loss: 0.013945 (0.013966) Loss: 1.0940 (1.1029) +2025-09-12,16:08:16 | INFO | Train Epoch: 2 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 1.1756 (1.1178) Boundary_loss: 0.013931 (0.013954) Loss: 1.1896 (1.1318) +2025-09-12,16:08:47 | INFO | Train Epoch: 2 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 1.0300 (1.0959) Boundary_loss: 0.013935 (0.013950) Loss: 1.0439 (1.1098) +2025-09-12,16:09:19 | INFO | Train Epoch: 2 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.2098 (1.1187) Boundary_loss: 0.013961 (0.013952) Loss: 1.2237 (1.1326) +2025-09-12,16:09:50 | INFO | Train Epoch: 2 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 1.1436 (1.1228) Boundary_loss: 0.013924 (0.013947) Loss: 1.1575 (1.1368) +2025-09-12,16:10:21 | INFO | Train Epoch: 2 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.96185 (1.0998) Boundary_loss: 0.013931 (0.013945) Loss: 0.97578 (1.1138) +2025-09-12,16:10:53 | INFO | Train Epoch: 2 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 1.1049 (1.1005) Boundary_loss: 0.013937 (0.013944) Loss: 1.1189 (1.1144) +2025-09-12,16:11:24 | INFO | Train Epoch: 2 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 1.1366 (1.1045) Boundary_loss: 0.013934 (0.013943) Loss: 1.1506 (1.1184) +2025-09-12,16:11:55 | INFO | Train Epoch: 2 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 1.1325 (1.1073) Boundary_loss: 0.013925 (0.013941) Loss: 1.1465 (1.1212) +2025-09-12,16:12:27 | INFO | Train Epoch: 2 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 1.1045 (1.1070) Boundary_loss: 0.013935 (0.013940) Loss: 1.1184 (1.1210) +2025-09-12,16:12:58 | INFO | Train Epoch: 2 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 1.0438 (1.1018) Boundary_loss: 0.013929 (0.013939) Loss: 1.0577 (1.1157) +2025-09-12,16:13:29 | INFO | Train Epoch: 2 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 1.0668 (1.0991) Boundary_loss: 0.013972 (0.013942) Loss: 1.0808 (1.1130) +2025-09-12,16:14:00 | INFO | Train Epoch: 2 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.97126 (1.0899) Boundary_loss: 0.013921 (0.013940) Loss: 0.98518 (1.1039) +2025-09-12,16:14:31 | INFO | Train Epoch: 2 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 1.1248 (1.0923) Boundary_loss: 0.013926 (0.013940) Loss: 1.1387 (1.1062) +2025-09-12,16:15:02 | INFO | Train Epoch: 2 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 1.0935 (1.0923) Boundary_loss: 0.013945 (0.013940) Loss: 1.1075 (1.1063) +2025-09-12,16:15:33 | INFO | Train Epoch: 2 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 1.0907 (1.0922) Boundary_loss: 0.013934 (0.013939) Loss: 1.1046 (1.1062) +2025-09-12,16:16:04 | INFO | Train Epoch: 2 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 1.0742 (1.0912) Boundary_loss: 0.013951 (0.013940) Loss: 1.0881 (1.1052) +2025-09-12,16:16:35 | INFO | Train Epoch: 2 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 1.0627 (1.0897) Boundary_loss: 0.013983 (0.013942) Loss: 1.0767 (1.1037) +2025-09-12,16:17:06 | INFO | Train Epoch: 2 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 1.1444 (1.0925) Boundary_loss: 0.013926 (0.013942) Loss: 1.1583 (1.1064) +2025-09-12,16:17:36 | INFO | Train Epoch: 2 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 1.1848 (1.0969) Boundary_loss: 0.013939 (0.013941) Loss: 1.1987 (1.1108) +2025-09-12,16:18:07 | INFO | Train Epoch: 2 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 1.0794 (1.0961) Boundary_loss: 0.013927 (0.013941) Loss: 1.0933 (1.1100) +2025-09-12,16:18:38 | INFO | Train Epoch: 2 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 1.1103 (1.0967) Boundary_loss: 0.013954 (0.013941) Loss: 1.1242 (1.1106) +2025-09-12,16:19:09 | INFO | Train Epoch: 2 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 1.1028 (1.0969) Boundary_loss: 0.013939 (0.013941) Loss: 1.1167 (1.1109) +2025-09-12,16:19:40 | INFO | Train Epoch: 2 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 1.0826 (1.0964) Boundary_loss: 0.013936 (0.013941) Loss: 1.0965 (1.1103) +2025-09-12,16:20:11 | INFO | Train Epoch: 2 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 1.1748 (1.0994) Boundary_loss: 0.013957 (0.013942) Loss: 1.1888 (1.1133) +2025-09-12,16:20:42 | INFO | Train Epoch: 2 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 1.0901 (1.0990) Boundary_loss: 0.013965 (0.013943) Loss: 1.1040 (1.1130) +2025-09-12,16:21:13 | INFO | Train Epoch: 2 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 1.2620 (1.1049) Boundary_loss: 0.014012 (0.013945) Loss: 1.2760 (1.1188) +2025-09-12,16:21:44 | INFO | Train Epoch: 2 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 1.1734 (1.1072) Boundary_loss: 0.013921 (0.013944) Loss: 1.1873 (1.1212) +2025-09-12,16:22:16 | INFO | Train Epoch: 2 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 1.0827 (1.1064) Boundary_loss: 0.013997 (0.013946) Loss: 1.0967 (1.1204) +2025-09-12,16:22:47 | INFO | Train Epoch: 2 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 1.0612 (1.1049) Boundary_loss: 0.013918 (0.013945) Loss: 1.0751 (1.1189) +2025-09-12,16:23:18 | INFO | Train Epoch: 2 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 1.0598 (1.1035) Boundary_loss: 0.014018 (0.013947) Loss: 1.0738 (1.1175) +2025-09-12,16:23:49 | INFO | Train Epoch: 2 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.96493 (1.0993) Boundary_loss: 0.013931 (0.013947) Loss: 0.97886 (1.1133) +2025-09-12,16:24:21 | INFO | Train Epoch: 2 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 1.1080 (1.0996) Boundary_loss: 0.013981 (0.013948) Loss: 1.1220 (1.1135) +2025-09-12,16:24:52 | INFO | Train Epoch: 2 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.1131 (1.1000) Boundary_loss: 0.013945 (0.013948) Loss: 1.1270 (1.1139) +2025-09-12,16:25:23 | INFO | Train Epoch: 2 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.96399 (1.0962) Boundary_loss: 0.013967 (0.013948) Loss: 0.97796 (1.1101) +2025-09-12,16:25:54 | INFO | Train Epoch: 2 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 1.1125 (1.0966) Boundary_loss: 0.013941 (0.013948) Loss: 1.1264 (1.1106) +2025-09-12,16:26:26 | INFO | Train Epoch: 2 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 1.1194 (1.0972) Boundary_loss: 0.013928 (0.013948) Loss: 1.1333 (1.1112) +2025-09-12,16:26:57 | INFO | Train Epoch: 2 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 1.0000 (1.0947) Boundary_loss: 0.013968 (0.013948) Loss: 1.0140 (1.1087) +2025-09-12,16:27:28 | INFO | Train Epoch: 2 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.99230 (1.0922) Boundary_loss: 0.013932 (0.013948) Loss: 1.0062 (1.1061) +2025-09-12,16:27:59 | INFO | Train Epoch: 2 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 1.1595 (1.0938) Boundary_loss: 0.013979 (0.013949) Loss: 1.1735 (1.1078) +2025-09-12,16:28:31 | INFO | Train Epoch: 2 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 1.0970 (1.0939) Boundary_loss: 0.013953 (0.013949) Loss: 1.1110 (1.1078) +2025-09-12,16:29:02 | INFO | Train Epoch: 2 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 1.0751 (1.0935) Boundary_loss: 0.013921 (0.013948) Loss: 1.0890 (1.1074) +2025-09-12,16:29:33 | INFO | Train Epoch: 2 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 1.1850 (1.0955) Boundary_loss: 0.013953 (0.013948) Loss: 1.1990 (1.1095) +2025-09-12,16:30:05 | INFO | Train Epoch: 2 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 1.1189 (1.0961) Boundary_loss: 0.013947 (0.013948) Loss: 1.1329 (1.1100) +2025-09-12,16:30:36 | INFO | Train Epoch: 2 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 1.2204 (1.0988) Boundary_loss: 0.014013 (0.013949) Loss: 1.2344 (1.1127) +2025-09-12,16:31:07 | INFO | Train Epoch: 2 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 1.1284 (1.0994) Boundary_loss: 0.013926 (0.013949) Loss: 1.1424 (1.1133) +2025-09-12,16:31:38 | INFO | Train Epoch: 2 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 1.0764 (1.0989) Boundary_loss: 0.013936 (0.013949) Loss: 1.0903 (1.1129) +2025-09-12,16:32:10 | INFO | Train Epoch: 2 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 1.1885 (1.1007) Boundary_loss: 0.013940 (0.013949) Loss: 1.2024 (1.1147) +2025-09-12,16:32:41 | INFO | Train Epoch: 2 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 49.428 Boundary Ratio: 0.252 Contrastive_loss: 1.0609 (1.0999) Boundary_loss: 0.014006 (0.013950) Loss: 1.0749 (1.1139) +2025-09-12,16:33:12 | INFO | Train Epoch: 2 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 1.1706 (1.1013) Boundary_loss: 0.013929 (0.013949) Loss: 1.1845 (1.1153) +2025-09-12,16:33:43 | INFO | Train Epoch: 2 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.1684 (1.1026) Boundary_loss: 0.013930 (0.013949) Loss: 1.1824 (1.1166) +2025-09-12,16:34:14 | INFO | Train Epoch: 2 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 1.0710 (1.1020) Boundary_loss: 0.013972 (0.013949) Loss: 1.0849 (1.1160) +2025-09-12,16:34:45 | INFO | Train Epoch: 2 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.508 Boundary Ratio: 0.247 Contrastive_loss: 0.95285 (1.0993) Boundary_loss: 0.013968 (0.013950) Loss: 0.96682 (1.1132) +2025-09-12,16:35:16 | INFO | Train Epoch: 2 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 1.0794 (1.0989) Boundary_loss: 0.013931 (0.013949) Loss: 1.0933 (1.1129) +2025-09-12,16:35:47 | INFO | Train Epoch: 2 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 1.1354 (1.0996) Boundary_loss: 0.013951 (0.013949) Loss: 1.1493 (1.1135) +2025-09-12,16:36:18 | INFO | Train Epoch: 2 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 1.0706 (1.0990) Boundary_loss: 0.013989 (0.013950) Loss: 1.0846 (1.1130) +2025-09-12,16:36:49 | INFO | Train Epoch: 2 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 1.0618 (1.0984) Boundary_loss: 0.013987 (0.013951) Loss: 1.0758 (1.1124) +2025-09-12,16:37:21 | INFO | Train Epoch: 2 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 1.0953 (1.0984) Boundary_loss: 0.014001 (0.013952) Loss: 1.1093 (1.1123) +2025-09-12,16:37:52 | INFO | Train Epoch: 2 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 1.1090 (1.0985) Boundary_loss: 0.013919 (0.013951) Loss: 1.1230 (1.1125) +2025-09-12,16:38:23 | INFO | Train Epoch: 2 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 1.0575 (1.0979) Boundary_loss: 0.013982 (0.013952) Loss: 1.0715 (1.1118) +2025-09-12,16:38:55 | INFO | Train Epoch: 2 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.0357 (1.0969) Boundary_loss: 0.013933 (0.013951) Loss: 1.0496 (1.1108) +2025-09-12,16:39:26 | INFO | Train Epoch: 2 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 1.1658 (1.0979) Boundary_loss: 0.013943 (0.013951) Loss: 1.1797 (1.1119) +2025-09-12,16:39:58 | INFO | Train Epoch: 2 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 1.0880 (1.0978) Boundary_loss: 0.013965 (0.013951) Loss: 1.1020 (1.1117) +2025-09-12,16:40:29 | INFO | Train Epoch: 2 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 1.0740 (1.0974) Boundary_loss: 0.013983 (0.013952) Loss: 1.0880 (1.1114) +2025-09-12,16:41:00 | INFO | Train Epoch: 2 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 1.1308 (1.0979) Boundary_loss: 0.013972 (0.013952) Loss: 1.1448 (1.1119) +2025-09-12,16:41:32 | INFO | Train Epoch: 2 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.96505 (1.0959) Boundary_loss: 0.013922 (0.013952) Loss: 0.97898 (1.1099) +2025-09-12,16:42:04 | INFO | Train Epoch: 2 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 1.1973 (1.0974) Boundary_loss: 0.013955 (0.013952) Loss: 1.2113 (1.1114) +2025-09-12,16:42:35 | INFO | Train Epoch: 2 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.98651 (1.0958) Boundary_loss: 0.013942 (0.013952) Loss: 1.0005 (1.1098) +2025-09-12,16:43:06 | INFO | Train Epoch: 2 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 1.1778 (1.0970) Boundary_loss: 0.013931 (0.013951) Loss: 1.1918 (1.1110) +2025-09-12,16:43:38 | INFO | Train Epoch: 2 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.88135 (1.0940) Boundary_loss: 0.013931 (0.013951) Loss: 0.89528 (1.1079) +2025-09-12,16:44:09 | INFO | Train Epoch: 2 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 1.1354 (1.0945) Boundary_loss: 0.013938 (0.013951) Loss: 1.1493 (1.1085) +2025-09-12,16:44:41 | INFO | Train Epoch: 2 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.96955 (1.0928) Boundary_loss: 0.013920 (0.013950) Loss: 0.98347 (1.1068) +2025-09-12,16:45:12 | INFO | Train Epoch: 2 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 1.0476 (1.0922) Boundary_loss: 0.013918 (0.013950) Loss: 1.0615 (1.1062) +2025-09-12,16:45:44 | INFO | Train Epoch: 2 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 1.1068 (1.0924) Boundary_loss: 0.013921 (0.013950) Loss: 1.1207 (1.1064) +2025-09-12,16:46:15 | INFO | Train Epoch: 2 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 1.2134 (1.0940) Boundary_loss: 0.013943 (0.013949) Loss: 1.2273 (1.1080) +2025-09-12,16:46:47 | INFO | Train Epoch: 2 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 1.0293 (1.0932) Boundary_loss: 0.013938 (0.013949) Loss: 1.0433 (1.1071) +2025-09-12,16:47:18 | INFO | Train Epoch: 2 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 1.0695 (1.0929) Boundary_loss: 0.013949 (0.013949) Loss: 1.0835 (1.1068) +2025-09-12,16:47:50 | INFO | Train Epoch: 2 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 1.0784 (1.0927) Boundary_loss: 0.014000 (0.013950) Loss: 1.0924 (1.1066) +2025-09-12,16:48:21 | INFO | Train Epoch: 2 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 1.0867 (1.0926) Boundary_loss: 0.013962 (0.013950) Loss: 1.1007 (1.1066) +2025-09-12,16:48:53 | INFO | Train Epoch: 2 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 1.0590 (1.0922) Boundary_loss: 0.013941 (0.013950) Loss: 1.0729 (1.1061) +2025-09-12,16:49:24 | INFO | Train Epoch: 2 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 1.0827 (1.0921) Boundary_loss: 0.013963 (0.013950) Loss: 1.0967 (1.1060) +2025-09-12,16:49:55 | INFO | Train Epoch: 2 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.88705 (1.0896) Boundary_loss: 0.013975 (0.013950) Loss: 0.90103 (1.1036) +2025-09-12,16:50:27 | INFO | Train Epoch: 2 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 1.0697 (1.0894) Boundary_loss: 0.013946 (0.013950) Loss: 1.0837 (1.1033) +2025-09-12,16:50:58 | INFO | Train Epoch: 2 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.95108 (1.0877) Boundary_loss: 0.013969 (0.013951) Loss: 0.96505 (1.1017) +2025-09-12,16:51:30 | INFO | Train Epoch: 2 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 1.1284 (1.0882) Boundary_loss: 0.013956 (0.013951) Loss: 1.1424 (1.1022) +2025-09-12,16:52:01 | INFO | Train Epoch: 2 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.90450 (1.0861) Boundary_loss: 0.013949 (0.013951) Loss: 0.91845 (1.1001) +2025-09-12,16:52:32 | INFO | Train Epoch: 2 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.95888 (1.0847) Boundary_loss: 0.014015 (0.013951) Loss: 0.97290 (1.0986) +2025-09-12,16:53:04 | INFO | Train Epoch: 2 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 1.0277 (1.0840) Boundary_loss: 0.013942 (0.013951) Loss: 1.0417 (1.0980) +2025-09-12,16:53:35 | INFO | Train Epoch: 2 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 1.0492 (1.0836) Boundary_loss: 0.013923 (0.013951) Loss: 1.0631 (1.0976) +2025-09-12,16:54:07 | INFO | Train Epoch: 2 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 1.2036 (1.0849) Boundary_loss: 0.013935 (0.013951) Loss: 1.2175 (1.0989) +2025-09-12,16:54:38 | INFO | Train Epoch: 2 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.1763 (1.0859) Boundary_loss: 0.013951 (0.013951) Loss: 1.1902 (1.0999) +2025-09-12,16:55:09 | INFO | Train Epoch: 2 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 1.1147 (1.0862) Boundary_loss: 0.013947 (0.013951) Loss: 1.1287 (1.1002) +2025-09-12,16:55:40 | INFO | Train Epoch: 2 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 49.342 Boundary Ratio: 0.252 Contrastive_loss: 1.0449 (1.0858) Boundary_loss: 0.014054 (0.013952) Loss: 1.0590 (1.0998) +2025-09-12,16:56:11 | INFO | Train Epoch: 2 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 1.0550 (1.0855) Boundary_loss: 0.013959 (0.013952) Loss: 1.0689 (1.0994) +2025-09-12,16:56:42 | INFO | Train Epoch: 2 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 1.1543 (1.0862) Boundary_loss: 0.013948 (0.013952) Loss: 1.1682 (1.1002) +2025-09-12,16:57:13 | INFO | Train Epoch: 2 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 1.1560 (1.0869) Boundary_loss: 0.013957 (0.013952) Loss: 1.1699 (1.1009) +2025-09-12,16:57:44 | INFO | Train Epoch: 2 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 1.0414 (1.0865) Boundary_loss: 0.013922 (0.013952) Loss: 1.0554 (1.1004) +2025-09-12,16:58:15 | INFO | Train Epoch: 2 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.89756 (1.0845) Boundary_loss: 0.013916 (0.013951) Loss: 0.91148 (1.0985) +2025-09-12,16:58:46 | INFO | Train Epoch: 2 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.93291 (1.0830) Boundary_loss: 0.013939 (0.013951) Loss: 0.94685 (1.0970) +2025-09-12,16:59:17 | INFO | Train Epoch: 2 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 1.1185 (1.0834) Boundary_loss: 0.013939 (0.013951) Loss: 1.1324 (1.0973) +2025-09-12,16:59:48 | INFO | Train Epoch: 2 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 1.0167 (1.0827) Boundary_loss: 0.013945 (0.013951) Loss: 1.0306 (1.0967) +2025-09-12,17:00:20 | INFO | Train Epoch: 2 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.1844 (1.0837) Boundary_loss: 0.013959 (0.013951) Loss: 1.1984 (1.0977) +2025-09-12,17:00:51 | INFO | Train Epoch: 2 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.94063 (1.0823) Boundary_loss: 0.013932 (0.013951) Loss: 0.95456 (1.0963) +2025-09-12,17:01:22 | INFO | Train Epoch: 2 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 1.1088 (1.0826) Boundary_loss: 0.013936 (0.013951) Loss: 1.1227 (1.0965) +2025-09-12,17:01:54 | INFO | Train Epoch: 2 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.99690 (1.0818) Boundary_loss: 0.013959 (0.013951) Loss: 1.0109 (1.0957) +2025-09-12,17:02:25 | INFO | Train Epoch: 2 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 1.0356 (1.0814) Boundary_loss: 0.013924 (0.013951) Loss: 1.0495 (1.0953) +2025-09-12,17:02:56 | INFO | Train Epoch: 2 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.0482 (1.0810) Boundary_loss: 0.013932 (0.013950) Loss: 1.0621 (1.0950) +2025-09-12,17:03:27 | INFO | Train Epoch: 2 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 1.0538 (1.0808) Boundary_loss: 0.013920 (0.013950) Loss: 1.0677 (1.0947) +2025-09-12,17:03:59 | INFO | Train Epoch: 2 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 1.0867 (1.0808) Boundary_loss: 0.013929 (0.013950) Loss: 1.1007 (1.0948) +2025-09-12,17:04:30 | INFO | Train Epoch: 2 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 1.0037 (1.0802) Boundary_loss: 0.013955 (0.013950) Loss: 1.0177 (1.0941) +2025-09-12,17:05:01 | INFO | Train Epoch: 2 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 1.0362 (1.0798) Boundary_loss: 0.013938 (0.013950) Loss: 1.0501 (1.0937) +2025-09-12,17:05:32 | INFO | Train Epoch: 2 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.98955 (1.0790) Boundary_loss: 0.013933 (0.013950) Loss: 1.0035 (1.0929) +2025-09-12,17:06:03 | INFO | Train Epoch: 2 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 1.1015 (1.0792) Boundary_loss: 0.014002 (0.013950) Loss: 1.1155 (1.0931) +2025-09-12,17:06:35 | INFO | Train Epoch: 2 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.92433 (1.0778) Boundary_loss: 0.013951 (0.013950) Loss: 0.93828 (1.0918) +2025-09-12,17:07:06 | INFO | Train Epoch: 2 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.95133 (1.0767) Boundary_loss: 0.013959 (0.013950) Loss: 0.96529 (1.0907) +2025-09-12,17:07:37 | INFO | Train Epoch: 2 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.99340 (1.0760) Boundary_loss: 0.013950 (0.013950) Loss: 1.0074 (1.0900) +2025-09-12,17:08:08 | INFO | Train Epoch: 2 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 1.0099 (1.0755) Boundary_loss: 0.013931 (0.013950) Loss: 1.0238 (1.0894) +2025-09-12,17:08:39 | INFO | Train Epoch: 2 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 1.0767 (1.0755) Boundary_loss: 0.013924 (0.013950) Loss: 1.0906 (1.0894) +2025-09-12,17:09:10 | INFO | Train Epoch: 2 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 1.0787 (1.0755) Boundary_loss: 0.013935 (0.013950) Loss: 1.0926 (1.0894) +2025-09-12,17:09:42 | INFO | Train Epoch: 2 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 1.0056 (1.0749) Boundary_loss: 0.013940 (0.013950) Loss: 1.0195 (1.0889) +2025-09-12,17:10:13 | INFO | Train Epoch: 2 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.94513 (1.0738) Boundary_loss: 0.013924 (0.013949) Loss: 0.95906 (1.0878) +2025-09-12,17:10:44 | INFO | Train Epoch: 2 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.97499 (1.0730) Boundary_loss: 0.013952 (0.013949) Loss: 0.98895 (1.0870) +2025-09-12,17:11:15 | INFO | Train Epoch: 2 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 1.0326 (1.0727) Boundary_loss: 0.013969 (0.013950) Loss: 1.0465 (1.0867) +2025-09-12,17:11:47 | INFO | Train Epoch: 2 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 1.0116 (1.0722) Boundary_loss: 0.013934 (0.013950) Loss: 1.0255 (1.0862) +2025-09-12,17:12:18 | INFO | Train Epoch: 2 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 1.2040 (1.0733) Boundary_loss: 0.013952 (0.013950) Loss: 1.2180 (1.0872) +2025-09-12,17:12:49 | INFO | Train Epoch: 2 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.1588 (1.0739) Boundary_loss: 0.013931 (0.013949) Loss: 1.1727 (1.0879) +2025-09-12,17:13:20 | INFO | Train Epoch: 2 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 1.0771 (1.0740) Boundary_loss: 0.013964 (0.013950) Loss: 1.0911 (1.0879) +2025-09-12,17:13:52 | INFO | Train Epoch: 2 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 1.0625 (1.0739) Boundary_loss: 0.013990 (0.013950) Loss: 1.0765 (1.0878) +2025-09-12,17:14:23 | INFO | Train Epoch: 2 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.0113 (1.0734) Boundary_loss: 0.013929 (0.013950) Loss: 1.0253 (1.0874) +2025-09-12,17:14:54 | INFO | Train Epoch: 2 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.98193 (1.0727) Boundary_loss: 0.013917 (0.013949) Loss: 0.99585 (1.0867) +2025-09-12,17:15:25 | INFO | Train Epoch: 2 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 1.1397 (1.0732) Boundary_loss: 0.013974 (0.013950) Loss: 1.1536 (1.0872) +2025-09-12,17:15:56 | INFO | Train Epoch: 2 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 1.0775 (1.0732) Boundary_loss: 0.014028 (0.013950) Loss: 1.0915 (1.0872) +2025-09-12,17:16:27 | INFO | Train Epoch: 2 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.97209 (1.0725) Boundary_loss: 0.013916 (0.013950) Loss: 0.98601 (1.0864) +2025-09-12,17:16:59 | INFO | Train Epoch: 2 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 1.0538 (1.0723) Boundary_loss: 0.013934 (0.013950) Loss: 1.0677 (1.0863) +2025-09-12,17:17:30 | INFO | Train Epoch: 2 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.1889 (1.0732) Boundary_loss: 0.013923 (0.013950) Loss: 1.2028 (1.0872) +2025-09-12,17:18:01 | INFO | Train Epoch: 2 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 1.0794 (1.0733) Boundary_loss: 0.013982 (0.013950) Loss: 1.0934 (1.0872) +2025-09-12,17:18:32 | INFO | Train Epoch: 2 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 1.1423 (1.0738) Boundary_loss: 0.013939 (0.013950) Loss: 1.1562 (1.0877) +2025-09-12,17:19:03 | INFO | Train Epoch: 2 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.0085 (1.0733) Boundary_loss: 0.013940 (0.013950) Loss: 1.0224 (1.0872) +2025-09-12,17:19:34 | INFO | Train Epoch: 2 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.98079 (1.0726) Boundary_loss: 0.013989 (0.013950) Loss: 0.99478 (1.0866) +2025-09-12,17:20:05 | INFO | Train Epoch: 2 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.0614 (1.0725) Boundary_loss: 0.013925 (0.013950) Loss: 1.0753 (1.0865) +2025-09-12,17:20:36 | INFO | Train Epoch: 2 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 1.0863 (1.0726) Boundary_loss: 0.013920 (0.013950) Loss: 1.1002 (1.0866) +2025-09-12,17:21:08 | INFO | Train Epoch: 2 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.94230 (1.0717) Boundary_loss: 0.013922 (0.013949) Loss: 0.95623 (1.0857) +2025-09-12,17:21:39 | INFO | Train Epoch: 2 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 1.0473 (1.0716) Boundary_loss: 0.013923 (0.013949) Loss: 1.0612 (1.0855) +2025-09-12,17:22:10 | INFO | Train Epoch: 2 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 1.0298 (1.0713) Boundary_loss: 0.013934 (0.013949) Loss: 1.0437 (1.0852) +2025-09-12,17:22:42 | INFO | Train Epoch: 2 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.0414 (1.0711) Boundary_loss: 0.013935 (0.013949) Loss: 1.0553 (1.0850) +2025-09-12,17:23:13 | INFO | Train Epoch: 2 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.93678 (1.0702) Boundary_loss: 0.013925 (0.013949) Loss: 0.95071 (1.0841) +2025-09-12,17:23:44 | INFO | Train Epoch: 2 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.99717 (1.0697) Boundary_loss: 0.013996 (0.013949) Loss: 1.0112 (1.0836) +2025-09-12,17:24:16 | INFO | Train Epoch: 2 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.97609 (1.0690) Boundary_loss: 0.013951 (0.013949) Loss: 0.99005 (1.0830) +2025-09-12,17:24:47 | INFO | Train Epoch: 2 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.80479 (1.0673) Boundary_loss: 0.013928 (0.013949) Loss: 0.81872 (1.0812) +2025-09-12,17:25:19 | INFO | Train Epoch: 2 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 1.0950 (1.0675) Boundary_loss: 0.013935 (0.013949) Loss: 1.1089 (1.0814) +2025-09-12,17:25:50 | INFO | Train Epoch: 2 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 1.0059 (1.0670) Boundary_loss: 0.013918 (0.013949) Loss: 1.0198 (1.0810) +2025-09-12,17:26:22 | INFO | Train Epoch: 2 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 1.0460 (1.0669) Boundary_loss: 0.013923 (0.013949) Loss: 1.0599 (1.0809) +2025-09-12,17:26:53 | INFO | Train Epoch: 2 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.0006 (1.0665) Boundary_loss: 0.013989 (0.013949) Loss: 1.0146 (1.0804) +2025-09-12,17:27:24 | INFO | Train Epoch: 2 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.99280 (1.0660) Boundary_loss: 0.013925 (0.013949) Loss: 1.0067 (1.0800) +2025-09-12,17:27:56 | INFO | Train Epoch: 2 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 1.0043 (1.0656) Boundary_loss: 0.013956 (0.013949) Loss: 1.0183 (1.0796) +2025-09-12,17:28:27 | INFO | Train Epoch: 2 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.98518 (1.0651) Boundary_loss: 0.013928 (0.013949) Loss: 0.99910 (1.0790) +2025-09-12,17:28:59 | INFO | Train Epoch: 2 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.92666 (1.0642) Boundary_loss: 0.013927 (0.013948) Loss: 0.94059 (1.0782) +2025-09-12,17:29:30 | INFO | Train Epoch: 2 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.93948 (1.0634) Boundary_loss: 0.013961 (0.013949) Loss: 0.95344 (1.0774) +2025-09-12,17:30:01 | INFO | Train Epoch: 2 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 1.0409 (1.0633) Boundary_loss: 0.013936 (0.013948) Loss: 1.0548 (1.0772) +2025-09-12,17:30:33 | INFO | Train Epoch: 2 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 1.1556 (1.0639) Boundary_loss: 0.013914 (0.013948) Loss: 1.1695 (1.0778) +2025-09-12,17:31:04 | INFO | Train Epoch: 2 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.0358 (1.0637) Boundary_loss: 0.013942 (0.013948) Loss: 1.0498 (1.0776) +2025-09-12,17:31:35 | INFO | Train Epoch: 2 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.98065 (1.0632) Boundary_loss: 0.013969 (0.013948) Loss: 0.99461 (1.0771) +2025-09-12,17:32:07 | INFO | Train Epoch: 2 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.97447 (1.0626) Boundary_loss: 0.013936 (0.013948) Loss: 0.98841 (1.0766) +2025-09-12,17:32:38 | INFO | Train Epoch: 2 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 1.0216 (1.0624) Boundary_loss: 0.013931 (0.013948) Loss: 1.0356 (1.0763) +2025-09-12,17:33:09 | INFO | Train Epoch: 2 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 1.1196 (1.0627) Boundary_loss: 0.013927 (0.013948) Loss: 1.1335 (1.0767) +2025-09-12,17:33:41 | INFO | Train Epoch: 2 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 1.0518 (1.0627) Boundary_loss: 0.013926 (0.013948) Loss: 1.0657 (1.0766) +2025-09-12,17:34:12 | INFO | Train Epoch: 2 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 1.1842 (1.0634) Boundary_loss: 0.013932 (0.013948) Loss: 1.1981 (1.0773) +2025-09-12,17:34:43 | INFO | Train Epoch: 2 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.98714 (1.0629) Boundary_loss: 0.013932 (0.013948) Loss: 1.0011 (1.0769) +2025-09-12,17:35:14 | INFO | Train Epoch: 2 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.1230 (1.0633) Boundary_loss: 0.013948 (0.013948) Loss: 1.1370 (1.0772) +2025-09-12,17:35:46 | INFO | Train Epoch: 2 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 1.0978 (1.0635) Boundary_loss: 0.013920 (0.013948) Loss: 1.1117 (1.0774) +2025-09-12,17:36:17 | INFO | Train Epoch: 2 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.90358 (1.0626) Boundary_loss: 0.013934 (0.013947) Loss: 0.91752 (1.0765) +2025-09-12,17:36:48 | INFO | Train Epoch: 2 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.1892 (1.0633) Boundary_loss: 0.013928 (0.013947) Loss: 1.2031 (1.0773) +2025-09-12,17:37:19 | INFO | Train Epoch: 2 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 1.1760 (1.0640) Boundary_loss: 0.013987 (0.013948) Loss: 1.1900 (1.0779) +2025-09-12,17:37:51 | INFO | Train Epoch: 2 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.98004 (1.0635) Boundary_loss: 0.013920 (0.013947) Loss: 0.99396 (1.0774) +2025-09-12,17:38:22 | INFO | Train Epoch: 2 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 1.0293 (1.0633) Boundary_loss: 0.013909 (0.013947) Loss: 1.0432 (1.0772) +2025-09-12,17:38:53 | INFO | Train Epoch: 2 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.95324 (1.0627) Boundary_loss: 0.013936 (0.013947) Loss: 0.96718 (1.0766) +2025-09-12,17:39:24 | INFO | Train Epoch: 2 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 1.0210 (1.0624) Boundary_loss: 0.013921 (0.013947) Loss: 1.0349 (1.0764) +2025-09-12,17:39:55 | INFO | Train Epoch: 2 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 1.1896 (1.0631) Boundary_loss: 0.013923 (0.013947) Loss: 1.2036 (1.0771) +2025-09-12,17:40:27 | INFO | Train Epoch: 2 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 1.0468 (1.0630) Boundary_loss: 0.013935 (0.013947) Loss: 1.0607 (1.0770) +2025-09-12,17:40:58 | INFO | Train Epoch: 2 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.93547 (1.0623) Boundary_loss: 0.013927 (0.013947) Loss: 0.94940 (1.0763) +2025-09-12,17:41:29 | INFO | Train Epoch: 2 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.96681 (1.0618) Boundary_loss: 0.013926 (0.013947) Loss: 0.98074 (1.0758) +2025-09-12,17:42:00 | INFO | Train Epoch: 2 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 1.0114 (1.0615) Boundary_loss: 0.013917 (0.013946) Loss: 1.0253 (1.0755) +2025-09-12,17:42:32 | INFO | Train Epoch: 2 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 1.0083 (1.0612) Boundary_loss: 0.013924 (0.013946) Loss: 1.0222 (1.0752) +2025-09-12,17:43:03 | INFO | Train Epoch: 2 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 1.0418 (1.0611) Boundary_loss: 0.013911 (0.013946) Loss: 1.0557 (1.0751) +2025-09-12,17:43:34 | INFO | Train Epoch: 2 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 1.1074 (1.0614) Boundary_loss: 0.013962 (0.013946) Loss: 1.1214 (1.0753) +2025-09-12,17:44:06 | INFO | Train Epoch: 2 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.91899 (1.0606) Boundary_loss: 0.013925 (0.013946) Loss: 0.93292 (1.0746) +2025-09-12,17:44:37 | INFO | Train Epoch: 2 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.90754 (1.0598) Boundary_loss: 0.013931 (0.013946) Loss: 0.92147 (1.0738) +2025-09-12,17:45:09 | INFO | Train Epoch: 2 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.96028 (1.0593) Boundary_loss: 0.013939 (0.013946) Loss: 0.97422 (1.0732) +2025-09-12,17:45:40 | INFO | Train Epoch: 2 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.87211 (1.0583) Boundary_loss: 0.013926 (0.013946) Loss: 0.88604 (1.0722) +2025-09-12,17:46:11 | INFO | Train Epoch: 2 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 1.0106 (1.0581) Boundary_loss: 0.013928 (0.013946) Loss: 1.0245 (1.0720) +2025-09-12,17:46:42 | INFO | Train Epoch: 2 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.97307 (1.0576) Boundary_loss: 0.013928 (0.013946) Loss: 0.98699 (1.0716) +2025-09-12,17:47:14 | INFO | Train Epoch: 2 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.91981 (1.0569) Boundary_loss: 0.013937 (0.013946) Loss: 0.93374 (1.0708) +2025-09-12,17:47:45 | INFO | Train Epoch: 2 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 1.0505 (1.0569) Boundary_loss: 0.013921 (0.013945) Loss: 1.0644 (1.0708) +2025-09-12,17:48:16 | INFO | Train Epoch: 2 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.93413 (1.0562) Boundary_loss: 0.013968 (0.013946) Loss: 0.94810 (1.0702) +2025-09-12,17:48:48 | INFO | Train Epoch: 2 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.0873 (1.0564) Boundary_loss: 0.013924 (0.013945) Loss: 1.1013 (1.0703) +2025-09-12,17:49:19 | INFO | Train Epoch: 2 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 1.0594 (1.0564) Boundary_loss: 0.013919 (0.013945) Loss: 1.0733 (1.0704) +2025-09-12,17:49:50 | INFO | Train Epoch: 2 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.94781 (1.0559) Boundary_loss: 0.013909 (0.013945) Loss: 0.96172 (1.0698) +2025-09-12,17:50:21 | INFO | Train Epoch: 2 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.99555 (1.0556) Boundary_loss: 0.013941 (0.013945) Loss: 1.0095 (1.0695) +2025-09-12,17:50:53 | INFO | Train Epoch: 2 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.93858 (1.0550) Boundary_loss: 0.013929 (0.013945) Loss: 0.95251 (1.0689) +2025-09-12,17:51:24 | INFO | Train Epoch: 2 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 1.1252 (1.0553) Boundary_loss: 0.013942 (0.013945) Loss: 1.1392 (1.0693) +2025-09-12,17:51:55 | INFO | Train Epoch: 2 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 1.0629 (1.0554) Boundary_loss: 0.013940 (0.013945) Loss: 1.0769 (1.0693) +2025-09-12,17:52:27 | INFO | Train Epoch: 2 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.0443 (1.0553) Boundary_loss: 0.013922 (0.013945) Loss: 1.0582 (1.0692) +2025-09-12,17:52:58 | INFO | Train Epoch: 2 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.0124 (1.0551) Boundary_loss: 0.013915 (0.013945) Loss: 1.0263 (1.0690) +2025-09-12,17:53:29 | INFO | Train Epoch: 2 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 1.0503 (1.0551) Boundary_loss: 0.013928 (0.013945) Loss: 1.0642 (1.0690) +2025-09-12,17:54:00 | INFO | Train Epoch: 2 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.92845 (1.0545) Boundary_loss: 0.013994 (0.013945) Loss: 0.94245 (1.0684) +2025-09-12,17:54:31 | INFO | Train Epoch: 2 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.92836 (1.0538) Boundary_loss: 0.013914 (0.013945) Loss: 0.94228 (1.0678) +2025-09-12,17:55:02 | INFO | Train Epoch: 2 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 1.0936 (1.0540) Boundary_loss: 0.013959 (0.013945) Loss: 1.1076 (1.0680) +2025-09-12,17:55:33 | INFO | Train Epoch: 2 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.92781 (1.0534) Boundary_loss: 0.013943 (0.013945) Loss: 0.94176 (1.0674) +2025-09-12,17:56:04 | INFO | Train Epoch: 2 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.94342 (1.0529) Boundary_loss: 0.013909 (0.013945) Loss: 0.95733 (1.0669) +2025-09-12,17:56:35 | INFO | Train Epoch: 2 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.95095 (1.0524) Boundary_loss: 0.013918 (0.013945) Loss: 0.96487 (1.0664) +2025-09-12,17:57:06 | INFO | Train Epoch: 2 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.0150 (1.0523) Boundary_loss: 0.013926 (0.013944) Loss: 1.0289 (1.0662) +2025-09-12,17:57:38 | INFO | Train Epoch: 2 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.97525 (1.0519) Boundary_loss: 0.013948 (0.013944) Loss: 0.98920 (1.0658) +2025-09-12,17:58:09 | INFO | Train Epoch: 2 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.95460 (1.0514) Boundary_loss: 0.013936 (0.013944) Loss: 0.96853 (1.0654) +2025-09-12,17:58:40 | INFO | Train Epoch: 2 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.88588 (1.0507) Boundary_loss: 0.013927 (0.013944) Loss: 0.89981 (1.0646) +2025-09-12,17:59:11 | INFO | Train Epoch: 2 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 1.0303 (1.0506) Boundary_loss: 0.013937 (0.013944) Loss: 1.0442 (1.0645) +2025-09-12,17:59:42 | INFO | Train Epoch: 2 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.1806 (1.0512) Boundary_loss: 0.013912 (0.013944) Loss: 1.1945 (1.0651) +2025-09-12,18:00:13 | INFO | Train Epoch: 2 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 1.1132 (1.0515) Boundary_loss: 0.013915 (0.013944) Loss: 1.1271 (1.0654) +2025-09-12,18:00:44 | INFO | Train Epoch: 2 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 1.0485 (1.0514) Boundary_loss: 0.013927 (0.013944) Loss: 1.0624 (1.0654) +2025-09-12,18:01:15 | INFO | Train Epoch: 2 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.94417 (1.0510) Boundary_loss: 0.013918 (0.013944) Loss: 0.95808 (1.0649) +2025-09-12,18:01:47 | INFO | Train Epoch: 2 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.98791 (1.0507) Boundary_loss: 0.013953 (0.013944) Loss: 1.0019 (1.0646) +2025-09-12,18:02:18 | INFO | Train Epoch: 2 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.90536 (1.0500) Boundary_loss: 0.013939 (0.013944) Loss: 0.91930 (1.0640) +2025-09-12,18:02:49 | INFO | Train Epoch: 2 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.0105 (1.0498) Boundary_loss: 0.013957 (0.013944) Loss: 1.0244 (1.0638) +2025-09-12,18:03:20 | INFO | Train Epoch: 2 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.0260 (1.0497) Boundary_loss: 0.013917 (0.013944) Loss: 1.0399 (1.0637) +2025-09-12,18:03:51 | INFO | Train Epoch: 2 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.99119 (1.0495) Boundary_loss: 0.013918 (0.013944) Loss: 1.0051 (1.0634) +2025-09-12,18:04:23 | INFO | Train Epoch: 2 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.0247 (1.0494) Boundary_loss: 0.013911 (0.013944) Loss: 1.0386 (1.0633) +2025-09-12,18:04:54 | INFO | Train Epoch: 2 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 1.0251 (1.0493) Boundary_loss: 0.013939 (0.013944) Loss: 1.0391 (1.0632) +2025-09-12,18:05:25 | INFO | Train Epoch: 2 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.88789 (1.0485) Boundary_loss: 0.013936 (0.013943) Loss: 0.90183 (1.0625) +2025-09-12,18:05:56 | INFO | Train Epoch: 2 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 1.0430 (1.0485) Boundary_loss: 0.013917 (0.013943) Loss: 1.0570 (1.0625) +2025-09-12,18:06:27 | INFO | Train Epoch: 2 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.91760 (1.0480) Boundary_loss: 0.013932 (0.013943) Loss: 0.93153 (1.0619) +2025-09-12,18:06:58 | INFO | Train Epoch: 2 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.85837 (1.0471) Boundary_loss: 0.013915 (0.013943) Loss: 0.87229 (1.0611) +2025-09-12,18:07:29 | INFO | Train Epoch: 2 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 1.0063 (1.0470) Boundary_loss: 0.013917 (0.013943) Loss: 1.0202 (1.0609) +2025-09-12,18:08:00 | INFO | Train Epoch: 2 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.97759 (1.0467) Boundary_loss: 0.013913 (0.013943) Loss: 0.99150 (1.0606) +2025-09-12,18:08:32 | INFO | Train Epoch: 2 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 1.0179 (1.0465) Boundary_loss: 0.013908 (0.013943) Loss: 1.0318 (1.0605) +2025-09-12,18:09:03 | INFO | Train Epoch: 2 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 1.1013 (1.0468) Boundary_loss: 0.013910 (0.013943) Loss: 1.1152 (1.0607) +2025-09-12,18:09:35 | INFO | Train Epoch: 2 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.95389 (1.0464) Boundary_loss: 0.013956 (0.013943) Loss: 0.96784 (1.0603) +2025-09-12,18:10:06 | INFO | Train Epoch: 2 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.92151 (1.0458) Boundary_loss: 0.013946 (0.013943) Loss: 0.93546 (1.0598) +2025-09-12,18:10:37 | INFO | Train Epoch: 2 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.96327 (1.0455) Boundary_loss: 0.013929 (0.013943) Loss: 0.97720 (1.0594) +2025-09-12,18:11:09 | INFO | Train Epoch: 2 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.0238 (1.0454) Boundary_loss: 0.013914 (0.013943) Loss: 1.0377 (1.0594) +2025-09-12,18:11:40 | INFO | Train Epoch: 2 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 1.0408 (1.0454) Boundary_loss: 0.013929 (0.013942) Loss: 1.0547 (1.0593) +2025-09-12,18:12:11 | INFO | Train Epoch: 2 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.94016 (1.0450) Boundary_loss: 0.013928 (0.013942) Loss: 0.95409 (1.0589) +2025-09-12,18:12:42 | INFO | Train Epoch: 2 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.0415 (1.0449) Boundary_loss: 0.013930 (0.013942) Loss: 1.0555 (1.0589) +2025-09-12,18:13:13 | INFO | Train Epoch: 2 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 1.0273 (1.0449) Boundary_loss: 0.013924 (0.013942) Loss: 1.0413 (1.0588) +2025-09-12,18:13:45 | INFO | Train Epoch: 2 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.99722 (1.0447) Boundary_loss: 0.013915 (0.013942) Loss: 1.0111 (1.0586) +2025-09-12,18:14:16 | INFO | Train Epoch: 2 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.96654 (1.0444) Boundary_loss: 0.013922 (0.013942) Loss: 0.98046 (1.0583) +2025-09-12,18:14:47 | INFO | Train Epoch: 2 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.98181 (1.0441) Boundary_loss: 0.013915 (0.013942) Loss: 0.99573 (1.0580) +2025-09-12,18:15:19 | INFO | Train Epoch: 2 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.94700 (1.0437) Boundary_loss: 0.013945 (0.013942) Loss: 0.96094 (1.0576) +2025-09-12,18:15:50 | INFO | Train Epoch: 2 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.0377 (1.0437) Boundary_loss: 0.013912 (0.013942) Loss: 1.0517 (1.0576) +2025-09-12,18:16:21 | INFO | Train Epoch: 2 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.83376 (1.0428) Boundary_loss: 0.013928 (0.013942) Loss: 0.84769 (1.0568) +2025-09-12,18:16:53 | INFO | Train Epoch: 2 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.0815 (1.0430) Boundary_loss: 0.013931 (0.013942) Loss: 1.0954 (1.0569) +2025-09-12,18:17:24 | INFO | Train Epoch: 2 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.84682 (1.0422) Boundary_loss: 0.013936 (0.013942) Loss: 0.86075 (1.0562) +2025-09-12,18:17:55 | INFO | Train Epoch: 2 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 1.0005 (1.0420) Boundary_loss: 0.013919 (0.013942) Loss: 1.0144 (1.0560) +2025-09-12,18:18:27 | INFO | Train Epoch: 2 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.99912 (1.0419) Boundary_loss: 0.013914 (0.013942) Loss: 1.0130 (1.0558) +2025-09-12,18:18:58 | INFO | Train Epoch: 2 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 1.1423 (1.0423) Boundary_loss: 0.013923 (0.013942) Loss: 1.1563 (1.0562) +2025-09-12,18:19:29 | INFO | Train Epoch: 2 [13005312/26365952 (49%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.98812 (1.0421) Boundary_loss: 0.013965 (0.013942) Loss: 1.0021 (1.0560) +2025-09-12,18:20:00 | INFO | Train Epoch: 2 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 1.0158 (1.0420) Boundary_loss: 0.013914 (0.013941) Loss: 1.0297 (1.0559) +2025-09-12,18:20:32 | INFO | Train Epoch: 2 [13107712/26365952 (50%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 1.0252 (1.0419) Boundary_loss: 0.014024 (0.013942) Loss: 1.0392 (1.0558) +2025-09-12,18:21:03 | INFO | Train Epoch: 2 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.91053 (1.0414) Boundary_loss: 0.013919 (0.013942) Loss: 0.92445 (1.0553) +2025-09-12,18:21:34 | INFO | Train Epoch: 2 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.95185 (1.0410) Boundary_loss: 0.013944 (0.013942) Loss: 0.96579 (1.0550) +2025-09-12,18:22:05 | INFO | Train Epoch: 2 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.90964 (1.0405) Boundary_loss: 0.013966 (0.013942) Loss: 0.92361 (1.0545) +2025-09-12,18:22:37 | INFO | Train Epoch: 2 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.98049 (1.0403) Boundary_loss: 0.013955 (0.013942) Loss: 0.99445 (1.0542) +2025-09-12,18:23:08 | INFO | Train Epoch: 2 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.0223 (1.0402) Boundary_loss: 0.013914 (0.013942) Loss: 1.0362 (1.0542) +2025-09-12,18:23:39 | INFO | Train Epoch: 2 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.93672 (1.0398) Boundary_loss: 0.013935 (0.013942) Loss: 0.95065 (1.0538) +2025-09-12,18:24:10 | INFO | Train Epoch: 2 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.92764 (1.0394) Boundary_loss: 0.013976 (0.013942) Loss: 0.94161 (1.0534) +2025-09-12,18:24:41 | INFO | Train Epoch: 2 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 1.1218 (1.0397) Boundary_loss: 0.013910 (0.013942) Loss: 1.1358 (1.0537) +2025-09-12,18:25:13 | INFO | Train Epoch: 2 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 1.0360 (1.0397) Boundary_loss: 0.013915 (0.013942) Loss: 1.0499 (1.0537) +2025-09-12,18:25:44 | INFO | Train Epoch: 2 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.87706 (1.0391) Boundary_loss: 0.013936 (0.013942) Loss: 0.89099 (1.0530) +2025-09-12,18:26:15 | INFO | Train Epoch: 2 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.89089 (1.0385) Boundary_loss: 0.013911 (0.013942) Loss: 0.90480 (1.0525) +2025-09-12,18:26:45 | INFO | Train Epoch: 2 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 1.0335 (1.0385) Boundary_loss: 0.013919 (0.013941) Loss: 1.0474 (1.0525) +2025-09-12,18:27:16 | INFO | Train Epoch: 2 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 1.0205 (1.0385) Boundary_loss: 0.013910 (0.013941) Loss: 1.0344 (1.0524) +2025-09-12,18:27:48 | INFO | Train Epoch: 2 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 1.2522 (1.0393) Boundary_loss: 0.013917 (0.013941) Loss: 1.2661 (1.0532) +2025-09-12,18:28:19 | INFO | Train Epoch: 2 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.95575 (1.0389) Boundary_loss: 0.013959 (0.013941) Loss: 0.96971 (1.0529) +2025-09-12,18:28:50 | INFO | Train Epoch: 2 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.91070 (1.0385) Boundary_loss: 0.013928 (0.013941) Loss: 0.92463 (1.0524) +2025-09-12,18:29:21 | INFO | Train Epoch: 2 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.96442 (1.0382) Boundary_loss: 0.013930 (0.013941) Loss: 0.97835 (1.0521) +2025-09-12,18:29:52 | INFO | Train Epoch: 2 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.89383 (1.0377) Boundary_loss: 0.013933 (0.013941) Loss: 0.90776 (1.0516) +2025-09-12,18:30:24 | INFO | Train Epoch: 2 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.84491 (1.0370) Boundary_loss: 0.013917 (0.013941) Loss: 0.85883 (1.0509) +2025-09-12,18:30:55 | INFO | Train Epoch: 2 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.91387 (1.0365) Boundary_loss: 0.013937 (0.013941) Loss: 0.92780 (1.0505) +2025-09-12,18:31:26 | INFO | Train Epoch: 2 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 1.0382 (1.0365) Boundary_loss: 0.013912 (0.013941) Loss: 1.0521 (1.0505) +2025-09-12,18:31:57 | INFO | Train Epoch: 2 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.0003 (1.0364) Boundary_loss: 0.013929 (0.013941) Loss: 1.0142 (1.0504) +2025-09-12,18:32:29 | INFO | Train Epoch: 2 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.85991 (1.0358) Boundary_loss: 0.013912 (0.013941) Loss: 0.87382 (1.0497) +2025-09-12,18:33:00 | INFO | Train Epoch: 2 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 1.1584 (1.0362) Boundary_loss: 0.013907 (0.013941) Loss: 1.1723 (1.0502) +2025-09-12,18:33:31 | INFO | Train Epoch: 2 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.97365 (1.0360) Boundary_loss: 0.013934 (0.013941) Loss: 0.98759 (1.0499) +2025-09-12,18:34:02 | INFO | Train Epoch: 2 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.97800 (1.0358) Boundary_loss: 0.013914 (0.013941) Loss: 0.99191 (1.0497) +2025-09-12,18:34:33 | INFO | Train Epoch: 2 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 1.0825 (1.0360) Boundary_loss: 0.013928 (0.013941) Loss: 1.0964 (1.0499) +2025-09-12,18:35:04 | INFO | Train Epoch: 2 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.94786 (1.0356) Boundary_loss: 0.013933 (0.013941) Loss: 0.96179 (1.0496) +2025-09-12,18:35:35 | INFO | Train Epoch: 2 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.89148 (1.0351) Boundary_loss: 0.013907 (0.013940) Loss: 0.90538 (1.0491) +2025-09-12,18:36:06 | INFO | Train Epoch: 2 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.95156 (1.0349) Boundary_loss: 0.013935 (0.013940) Loss: 0.96550 (1.0488) +2025-09-12,18:36:37 | INFO | Train Epoch: 2 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.97116 (1.0346) Boundary_loss: 0.013913 (0.013940) Loss: 0.98507 (1.0486) +2025-09-12,18:37:08 | INFO | Train Epoch: 2 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.80956 (1.0339) Boundary_loss: 0.013920 (0.013940) Loss: 0.82348 (1.0478) +2025-09-12,18:37:40 | INFO | Train Epoch: 2 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.0560 (1.0339) Boundary_loss: 0.013909 (0.013940) Loss: 1.0699 (1.0479) +2025-09-12,18:38:11 | INFO | Train Epoch: 2 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 1.0169 (1.0339) Boundary_loss: 0.013920 (0.013940) Loss: 1.0309 (1.0478) +2025-09-12,18:38:42 | INFO | Train Epoch: 2 [14899712/26365952 (57%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 1.0223 (1.0338) Boundary_loss: 0.013949 (0.013940) Loss: 1.0363 (1.0478) +2025-09-12,18:39:13 | INFO | Train Epoch: 2 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 1.0057 (1.0337) Boundary_loss: 0.013919 (0.013940) Loss: 1.0196 (1.0477) +2025-09-12,18:39:44 | INFO | Train Epoch: 2 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.0983 (1.0340) Boundary_loss: 0.013985 (0.013940) Loss: 1.1122 (1.0479) +2025-09-12,18:40:15 | INFO | Train Epoch: 2 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.84280 (1.0333) Boundary_loss: 0.013919 (0.013940) Loss: 0.85672 (1.0472) +2025-09-12,18:40:47 | INFO | Train Epoch: 2 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.98028 (1.0331) Boundary_loss: 0.013914 (0.013940) Loss: 0.99419 (1.0471) +2025-09-12,18:41:18 | INFO | Train Epoch: 2 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.84254 (1.0325) Boundary_loss: 0.013914 (0.013940) Loss: 0.85645 (1.0464) +2025-09-12,18:41:49 | INFO | Train Epoch: 2 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 1.0115 (1.0324) Boundary_loss: 0.013916 (0.013940) Loss: 1.0254 (1.0464) +2025-09-12,18:42:21 | INFO | Train Epoch: 2 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.88986 (1.0319) Boundary_loss: 0.013916 (0.013940) Loss: 0.90377 (1.0459) +2025-09-12,18:42:52 | INFO | Train Epoch: 2 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.0487 (1.0320) Boundary_loss: 0.013916 (0.013940) Loss: 1.0626 (1.0459) +2025-09-12,18:43:23 | INFO | Train Epoch: 2 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 1.0419 (1.0320) Boundary_loss: 0.013912 (0.013940) Loss: 1.0558 (1.0460) +2025-09-12,18:43:55 | INFO | Train Epoch: 2 [15411712/26365952 (58%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.96055 (1.0318) Boundary_loss: 0.013932 (0.013940) Loss: 0.97448 (1.0457) +2025-09-12,18:44:26 | INFO | Train Epoch: 2 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 1.0121 (1.0317) Boundary_loss: 0.013930 (0.013940) Loss: 1.0260 (1.0457) +2025-09-12,18:44:57 | INFO | Train Epoch: 2 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.91040 (1.0313) Boundary_loss: 0.014042 (0.013940) Loss: 0.92445 (1.0453) +2025-09-12,18:45:28 | INFO | Train Epoch: 2 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.76366 (1.0304) Boundary_loss: 0.013915 (0.013940) Loss: 0.77757 (1.0444) +2025-09-12,18:45:59 | INFO | Train Epoch: 2 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.92292 (1.0301) Boundary_loss: 0.013922 (0.013940) Loss: 0.93684 (1.0440) +2025-09-12,18:46:30 | INFO | Train Epoch: 2 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 1.0547 (1.0302) Boundary_loss: 0.013937 (0.013940) Loss: 1.0686 (1.0441) +2025-09-12,18:47:01 | INFO | Train Epoch: 2 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.90388 (1.0298) Boundary_loss: 0.013908 (0.013940) Loss: 0.91779 (1.0437) +2025-09-12,18:47:33 | INFO | Train Epoch: 2 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.99326 (1.0296) Boundary_loss: 0.013931 (0.013940) Loss: 1.0072 (1.0436) +2025-09-12,18:48:04 | INFO | Train Epoch: 2 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.90700 (1.0293) Boundary_loss: 0.013920 (0.013940) Loss: 0.92092 (1.0432) +2025-09-12,18:48:35 | INFO | Train Epoch: 2 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.99768 (1.0292) Boundary_loss: 0.013914 (0.013939) Loss: 1.0116 (1.0431) +2025-09-12,18:49:07 | INFO | Train Epoch: 2 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.92430 (1.0288) Boundary_loss: 0.013916 (0.013939) Loss: 0.93821 (1.0428) +2025-09-12,18:49:38 | INFO | Train Epoch: 2 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.80625 (1.0281) Boundary_loss: 0.013923 (0.013939) Loss: 0.82017 (1.0420) +2025-09-12,18:50:09 | INFO | Train Epoch: 2 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.97325 (1.0279) Boundary_loss: 0.013936 (0.013939) Loss: 0.98719 (1.0419) +2025-09-12,18:50:40 | INFO | Train Epoch: 2 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 1.0284 (1.0279) Boundary_loss: 0.013920 (0.013939) Loss: 1.0423 (1.0419) +2025-09-12,18:51:12 | INFO | Train Epoch: 2 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.92370 (1.0276) Boundary_loss: 0.013905 (0.013939) Loss: 0.93761 (1.0415) +2025-09-12,18:51:43 | INFO | Train Epoch: 2 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.0165 (1.0276) Boundary_loss: 0.013914 (0.013939) Loss: 1.0305 (1.0415) +2025-09-12,18:52:14 | INFO | Train Epoch: 2 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.98488 (1.0274) Boundary_loss: 0.013903 (0.013939) Loss: 0.99878 (1.0414) +2025-09-12,18:52:45 | INFO | Train Epoch: 2 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 1.0660 (1.0276) Boundary_loss: 0.013917 (0.013939) Loss: 1.0799 (1.0415) +2025-09-12,18:53:17 | INFO | Train Epoch: 2 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.91568 (1.0272) Boundary_loss: 0.013917 (0.013939) Loss: 0.92959 (1.0411) +2025-09-12,18:53:48 | INFO | Train Epoch: 2 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 1.0831 (1.0274) Boundary_loss: 0.013914 (0.013939) Loss: 1.0970 (1.0413) +2025-09-12,18:54:19 | INFO | Train Epoch: 2 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.91287 (1.0270) Boundary_loss: 0.013916 (0.013939) Loss: 0.92678 (1.0410) +2025-09-12,18:54:50 | INFO | Train Epoch: 2 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.96247 (1.0268) Boundary_loss: 0.013923 (0.013939) Loss: 0.97640 (1.0408) +2025-09-12,18:55:22 | INFO | Train Epoch: 2 [16538112/26365952 (63%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 0.92024 (1.0265) Boundary_loss: 0.013956 (0.013939) Loss: 0.93420 (1.0404) +2025-09-12,18:55:53 | INFO | Train Epoch: 2 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 1.1307 (1.0268) Boundary_loss: 0.013904 (0.013939) Loss: 1.1446 (1.0408) +2025-09-12,18:56:24 | INFO | Train Epoch: 2 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.90830 (1.0265) Boundary_loss: 0.013907 (0.013938) Loss: 0.92221 (1.0404) +2025-09-12,18:56:55 | INFO | Train Epoch: 2 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.92203 (1.0261) Boundary_loss: 0.013917 (0.013938) Loss: 0.93595 (1.0401) +2025-09-12,18:57:26 | INFO | Train Epoch: 2 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.94949 (1.0259) Boundary_loss: 0.013921 (0.013938) Loss: 0.96341 (1.0398) +2025-09-12,18:57:57 | INFO | Train Epoch: 2 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 1.0939 (1.0261) Boundary_loss: 0.013916 (0.013938) Loss: 1.1079 (1.0400) +2025-09-12,18:58:28 | INFO | Train Epoch: 2 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.97468 (1.0259) Boundary_loss: 0.013915 (0.013938) Loss: 0.98859 (1.0399) +2025-09-12,18:58:59 | INFO | Train Epoch: 2 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.91270 (1.0256) Boundary_loss: 0.013932 (0.013938) Loss: 0.92664 (1.0395) +2025-09-12,18:59:30 | INFO | Train Epoch: 2 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.79602 (1.0249) Boundary_loss: 0.013921 (0.013938) Loss: 0.80994 (1.0389) +2025-09-12,19:00:01 | INFO | Train Epoch: 2 [16998912/26365952 (64%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 1.0967 (1.0251) Boundary_loss: 0.013942 (0.013938) Loss: 1.1106 (1.0391) +2025-09-12,19:00:32 | INFO | Train Epoch: 2 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 1.0991 (1.0254) Boundary_loss: 0.013907 (0.013938) Loss: 1.1131 (1.0393) +2025-09-12,19:01:03 | INFO | Train Epoch: 2 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.90276 (1.0250) Boundary_loss: 0.013918 (0.013938) Loss: 0.91668 (1.0389) +2025-09-12,19:01:35 | INFO | Train Epoch: 2 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.86538 (1.0245) Boundary_loss: 0.013907 (0.013938) Loss: 0.87929 (1.0384) +2025-09-12,19:02:06 | INFO | Train Epoch: 2 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.94609 (1.0243) Boundary_loss: 0.013930 (0.013938) Loss: 0.96002 (1.0382) +2025-09-12,19:02:37 | INFO | Train Epoch: 2 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.0649 (1.0244) Boundary_loss: 0.013916 (0.013938) Loss: 1.0788 (1.0383) +2025-09-12,19:03:08 | INFO | Train Epoch: 2 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.97993 (1.0243) Boundary_loss: 0.013953 (0.013938) Loss: 0.99388 (1.0382) +2025-09-12,19:03:39 | INFO | Train Epoch: 2 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.92326 (1.0240) Boundary_loss: 0.013935 (0.013938) Loss: 0.93719 (1.0379) +2025-09-12,19:04:10 | INFO | Train Epoch: 2 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.92589 (1.0237) Boundary_loss: 0.013924 (0.013938) Loss: 0.93982 (1.0376) +2025-09-12,19:04:42 | INFO | Train Epoch: 2 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.0902 (1.0239) Boundary_loss: 0.013912 (0.013938) Loss: 1.1042 (1.0378) +2025-09-12,19:05:13 | INFO | Train Epoch: 2 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.85087 (1.0234) Boundary_loss: 0.013917 (0.013938) Loss: 0.86479 (1.0373) +2025-09-12,19:05:44 | INFO | Train Epoch: 2 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.95849 (1.0232) Boundary_loss: 0.013921 (0.013938) Loss: 0.97241 (1.0371) +2025-09-12,19:06:15 | INFO | Train Epoch: 2 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.92668 (1.0229) Boundary_loss: 0.013916 (0.013938) Loss: 0.94059 (1.0368) +2025-09-12,19:06:46 | INFO | Train Epoch: 2 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 1.0421 (1.0230) Boundary_loss: 0.013909 (0.013937) Loss: 1.0560 (1.0369) +2025-09-12,19:07:17 | INFO | Train Epoch: 2 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.91796 (1.0227) Boundary_loss: 0.013905 (0.013937) Loss: 0.93186 (1.0366) +2025-09-12,19:07:49 | INFO | Train Epoch: 2 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 1.0403 (1.0227) Boundary_loss: 0.013935 (0.013937) Loss: 1.0542 (1.0366) +2025-09-12,19:08:20 | INFO | Train Epoch: 2 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.83175 (1.0222) Boundary_loss: 0.013920 (0.013937) Loss: 0.84567 (1.0361) +2025-09-12,19:08:51 | INFO | Train Epoch: 2 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.0201 (1.0222) Boundary_loss: 0.013907 (0.013937) Loss: 1.0340 (1.0361) +2025-09-12,19:09:22 | INFO | Train Epoch: 2 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.0679 (1.0223) Boundary_loss: 0.013913 (0.013937) Loss: 1.0818 (1.0362) +2025-09-12,19:09:54 | INFO | Train Epoch: 2 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.92536 (1.0220) Boundary_loss: 0.013915 (0.013937) Loss: 0.93927 (1.0359) +2025-09-12,19:10:25 | INFO | Train Epoch: 2 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.92234 (1.0217) Boundary_loss: 0.013905 (0.013937) Loss: 0.93625 (1.0357) +2025-09-12,19:10:56 | INFO | Train Epoch: 2 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.0495 (1.0218) Boundary_loss: 0.013982 (0.013937) Loss: 1.0635 (1.0357) +2025-09-12,19:11:27 | INFO | Train Epoch: 2 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.0399 (1.0219) Boundary_loss: 0.013912 (0.013937) Loss: 1.0538 (1.0358) +2025-09-12,19:11:58 | INFO | Train Epoch: 2 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.90765 (1.0215) Boundary_loss: 0.013922 (0.013937) Loss: 0.92157 (1.0355) +2025-09-12,19:12:29 | INFO | Train Epoch: 2 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.90287 (1.0212) Boundary_loss: 0.013904 (0.013937) Loss: 0.91678 (1.0351) +2025-09-12,19:13:01 | INFO | Train Epoch: 2 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 1.0029 (1.0212) Boundary_loss: 0.013925 (0.013937) Loss: 1.0169 (1.0351) +2025-09-12,19:13:32 | INFO | Train Epoch: 2 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.92780 (1.0209) Boundary_loss: 0.013910 (0.013937) Loss: 0.94171 (1.0348) +2025-09-12,19:14:03 | INFO | Train Epoch: 2 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.99249 (1.0208) Boundary_loss: 0.013910 (0.013937) Loss: 1.0064 (1.0348) +2025-09-12,19:14:34 | INFO | Train Epoch: 2 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.95952 (1.0206) Boundary_loss: 0.013908 (0.013937) Loss: 0.97343 (1.0346) +2025-09-12,19:15:05 | INFO | Train Epoch: 2 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.91978 (1.0204) Boundary_loss: 0.013947 (0.013937) Loss: 0.93373 (1.0343) +2025-09-12,19:15:37 | INFO | Train Epoch: 2 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.91999 (1.0201) Boundary_loss: 0.013911 (0.013937) Loss: 0.93390 (1.0340) +2025-09-12,19:16:08 | INFO | Train Epoch: 2 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.97317 (1.0200) Boundary_loss: 0.013906 (0.013937) Loss: 0.98708 (1.0339) +2025-09-12,19:16:39 | INFO | Train Epoch: 2 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.95935 (1.0198) Boundary_loss: 0.013943 (0.013937) Loss: 0.97329 (1.0337) +2025-09-12,19:17:10 | INFO | Train Epoch: 2 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.95539 (1.0196) Boundary_loss: 0.013912 (0.013936) Loss: 0.96930 (1.0336) +2025-09-12,19:17:41 | INFO | Train Epoch: 2 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.87913 (1.0192) Boundary_loss: 0.013915 (0.013936) Loss: 0.89305 (1.0332) +2025-09-12,19:18:12 | INFO | Train Epoch: 2 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.0529 (1.0193) Boundary_loss: 0.013914 (0.013936) Loss: 1.0668 (1.0333) +2025-09-12,19:18:44 | INFO | Train Epoch: 2 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.97626 (1.0192) Boundary_loss: 0.013940 (0.013936) Loss: 0.99020 (1.0331) +2025-09-12,19:19:15 | INFO | Train Epoch: 2 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.95131 (1.0190) Boundary_loss: 0.013908 (0.013936) Loss: 0.96522 (1.0330) +2025-09-12,19:19:45 | INFO | Train Epoch: 2 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.86820 (1.0186) Boundary_loss: 0.013911 (0.013936) Loss: 0.88211 (1.0326) +2025-09-12,19:20:16 | INFO | Train Epoch: 2 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.96903 (1.0185) Boundary_loss: 0.013902 (0.013936) Loss: 0.98294 (1.0324) +2025-09-12,19:20:48 | INFO | Train Epoch: 2 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.98170 (1.0184) Boundary_loss: 0.013909 (0.013936) Loss: 0.99560 (1.0323) +2025-09-12,19:21:19 | INFO | Train Epoch: 2 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.95326 (1.0182) Boundary_loss: 0.013914 (0.013936) Loss: 0.96717 (1.0321) +2025-09-12,19:21:50 | INFO | Train Epoch: 2 [19149312/26365952 (73%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.87968 (1.0178) Boundary_loss: 0.013929 (0.013936) Loss: 0.89361 (1.0318) +2025-09-12,19:22:21 | INFO | Train Epoch: 2 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.81667 (1.0173) Boundary_loss: 0.013905 (0.013936) Loss: 0.83058 (1.0312) +2025-09-12,19:22:53 | INFO | Train Epoch: 2 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 1.0790 (1.0175) Boundary_loss: 0.013911 (0.013936) Loss: 1.0929 (1.0314) +2025-09-12,19:23:24 | INFO | Train Epoch: 2 [19302912/26365952 (73%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 0.96296 (1.0173) Boundary_loss: 0.013915 (0.013936) Loss: 0.97688 (1.0313) +2025-09-12,19:23:56 | INFO | Train Epoch: 2 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.88284 (1.0170) Boundary_loss: 0.013902 (0.013936) Loss: 0.89675 (1.0309) +2025-09-12,19:24:27 | INFO | Train Epoch: 2 [19405312/26365952 (74%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 1.0454 (1.0170) Boundary_loss: 0.013934 (0.013936) Loss: 1.0593 (1.0310) +2025-09-12,19:24:59 | INFO | Train Epoch: 2 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.0233 (1.0171) Boundary_loss: 0.013918 (0.013936) Loss: 1.0372 (1.0310) +2025-09-12,19:25:30 | INFO | Train Epoch: 2 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.96045 (1.0169) Boundary_loss: 0.013922 (0.013936) Loss: 0.97437 (1.0309) +2025-09-12,19:26:01 | INFO | Train Epoch: 2 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.0870 (1.0171) Boundary_loss: 0.013914 (0.013936) Loss: 1.1009 (1.0310) +2025-09-12,19:26:32 | INFO | Train Epoch: 2 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.85500 (1.0167) Boundary_loss: 0.013911 (0.013935) Loss: 0.86891 (1.0306) +2025-09-12,19:27:03 | INFO | Train Epoch: 2 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.90264 (1.0164) Boundary_loss: 0.013913 (0.013935) Loss: 0.91655 (1.0303) +2025-09-12,19:27:35 | INFO | Train Epoch: 2 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.92697 (1.0161) Boundary_loss: 0.013954 (0.013935) Loss: 0.94093 (1.0301) +2025-09-12,19:28:06 | INFO | Train Epoch: 2 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.84909 (1.0157) Boundary_loss: 0.013908 (0.013935) Loss: 0.86300 (1.0297) +2025-09-12,19:28:37 | INFO | Train Epoch: 2 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.93993 (1.0155) Boundary_loss: 0.013919 (0.013935) Loss: 0.95385 (1.0295) +2025-09-12,19:29:08 | INFO | Train Epoch: 2 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.94548 (1.0153) Boundary_loss: 0.013935 (0.013935) Loss: 0.95942 (1.0293) +2025-09-12,19:29:40 | INFO | Train Epoch: 2 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.85073 (1.0149) Boundary_loss: 0.013935 (0.013935) Loss: 0.86466 (1.0289) +2025-09-12,19:30:11 | INFO | Train Epoch: 2 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.91559 (1.0147) Boundary_loss: 0.013963 (0.013935) Loss: 0.92955 (1.0286) +2025-09-12,19:30:42 | INFO | Train Epoch: 2 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.88806 (1.0143) Boundary_loss: 0.013911 (0.013935) Loss: 0.90197 (1.0283) +2025-09-12,19:31:13 | INFO | Train Epoch: 2 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.87835 (1.0140) Boundary_loss: 0.013905 (0.013935) Loss: 0.89225 (1.0279) +2025-09-12,19:31:44 | INFO | Train Epoch: 2 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.99265 (1.0139) Boundary_loss: 0.013943 (0.013935) Loss: 1.0066 (1.0279) +2025-09-12,19:32:15 | INFO | Train Epoch: 2 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.92584 (1.0137) Boundary_loss: 0.013923 (0.013935) Loss: 0.93976 (1.0277) +2025-09-12,19:32:46 | INFO | Train Epoch: 2 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 1.0688 (1.0139) Boundary_loss: 0.013914 (0.013935) Loss: 1.0828 (1.0278) +2025-09-12,19:33:17 | INFO | Train Epoch: 2 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.92715 (1.0136) Boundary_loss: 0.013930 (0.013935) Loss: 0.94108 (1.0276) +2025-09-12,19:33:48 | INFO | Train Epoch: 2 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.90664 (1.0134) Boundary_loss: 0.013914 (0.013935) Loss: 0.92055 (1.0273) +2025-09-12,19:34:19 | INFO | Train Epoch: 2 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.96766 (1.0133) Boundary_loss: 0.013913 (0.013935) Loss: 0.98158 (1.0272) +2025-09-12,19:34:50 | INFO | Train Epoch: 2 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.85919 (1.0129) Boundary_loss: 0.013919 (0.013935) Loss: 0.87311 (1.0268) +2025-09-12,19:35:21 | INFO | Train Epoch: 2 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.94917 (1.0127) Boundary_loss: 0.013914 (0.013935) Loss: 0.96308 (1.0266) +2025-09-12,19:35:52 | INFO | Train Epoch: 2 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.0665 (1.0128) Boundary_loss: 0.013942 (0.013935) Loss: 1.0804 (1.0268) +2025-09-12,19:36:23 | INFO | Train Epoch: 2 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.98882 (1.0128) Boundary_loss: 0.013906 (0.013935) Loss: 1.0027 (1.0267) +2025-09-12,19:36:54 | INFO | Train Epoch: 2 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.94762 (1.0126) Boundary_loss: 0.013981 (0.013935) Loss: 0.96160 (1.0266) +2025-09-12,19:37:25 | INFO | Train Epoch: 2 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.96424 (1.0125) Boundary_loss: 0.013904 (0.013935) Loss: 0.97814 (1.0264) +2025-09-12,19:37:56 | INFO | Train Epoch: 2 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.93174 (1.0123) Boundary_loss: 0.013908 (0.013935) Loss: 0.94565 (1.0262) +2025-09-12,19:38:27 | INFO | Train Epoch: 2 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.90735 (1.0120) Boundary_loss: 0.013917 (0.013935) Loss: 0.92127 (1.0260) +2025-09-12,19:38:58 | INFO | Train Epoch: 2 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.82252 (1.0116) Boundary_loss: 0.013916 (0.013935) Loss: 0.83644 (1.0255) +2025-09-12,19:39:29 | INFO | Train Epoch: 2 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.97403 (1.0115) Boundary_loss: 0.013918 (0.013935) Loss: 0.98795 (1.0254) +2025-09-12,19:40:00 | INFO | Train Epoch: 2 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 1.0333 (1.0115) Boundary_loss: 0.013930 (0.013935) Loss: 1.0472 (1.0255) +2025-09-12,19:40:31 | INFO | Train Epoch: 2 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 1.0914 (1.0117) Boundary_loss: 0.013932 (0.013935) Loss: 1.1053 (1.0257) +2025-09-12,19:41:02 | INFO | Train Epoch: 2 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.87581 (1.0114) Boundary_loss: 0.013911 (0.013935) Loss: 0.88972 (1.0253) +2025-09-12,19:41:33 | INFO | Train Epoch: 2 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.96429 (1.0113) Boundary_loss: 0.013903 (0.013935) Loss: 0.97819 (1.0252) +2025-09-12,19:42:04 | INFO | Train Epoch: 2 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.89827 (1.0110) Boundary_loss: 0.013904 (0.013935) Loss: 0.91217 (1.0250) +2025-09-12,19:42:35 | INFO | Train Epoch: 2 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.96575 (1.0109) Boundary_loss: 0.013912 (0.013935) Loss: 0.97966 (1.0248) +2025-09-12,19:43:06 | INFO | Train Epoch: 2 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.97777 (1.0108) Boundary_loss: 0.013915 (0.013934) Loss: 0.99168 (1.0248) +2025-09-12,19:43:37 | INFO | Train Epoch: 2 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 1.0196 (1.0109) Boundary_loss: 0.013923 (0.013934) Loss: 1.0335 (1.0248) +2025-09-12,19:44:08 | INFO | Train Epoch: 2 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.98754 (1.0108) Boundary_loss: 0.013928 (0.013934) Loss: 1.0015 (1.0247) +2025-09-12,19:44:39 | INFO | Train Epoch: 2 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.99485 (1.0108) Boundary_loss: 0.013918 (0.013934) Loss: 1.0088 (1.0247) +2025-09-12,19:45:10 | INFO | Train Epoch: 2 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.98740 (1.0107) Boundary_loss: 0.013924 (0.013934) Loss: 1.0013 (1.0246) +2025-09-12,19:45:42 | INFO | Train Epoch: 2 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.99806 (1.0107) Boundary_loss: 0.013917 (0.013934) Loss: 1.0120 (1.0246) +2025-09-12,19:46:13 | INFO | Train Epoch: 2 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.96233 (1.0106) Boundary_loss: 0.013905 (0.013934) Loss: 0.97623 (1.0245) +2025-09-12,19:46:44 | INFO | Train Epoch: 2 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 1.0554 (1.0107) Boundary_loss: 0.013923 (0.013934) Loss: 1.0693 (1.0246) +2025-09-12,19:47:15 | INFO | Train Epoch: 2 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.86143 (1.0103) Boundary_loss: 0.013908 (0.013934) Loss: 0.87534 (1.0243) +2025-09-12,19:47:46 | INFO | Train Epoch: 2 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 1.0496 (1.0104) Boundary_loss: 0.013923 (0.013934) Loss: 1.0635 (1.0243) +2025-09-12,19:48:17 | INFO | Train Epoch: 2 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.83118 (1.0100) Boundary_loss: 0.013903 (0.013934) Loss: 0.84509 (1.0239) +2025-09-12,19:48:48 | INFO | Train Epoch: 2 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.91741 (1.0098) Boundary_loss: 0.013909 (0.013934) Loss: 0.93131 (1.0237) +2025-09-12,19:49:19 | INFO | Train Epoch: 2 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.98605 (1.0097) Boundary_loss: 0.013911 (0.013934) Loss: 0.99996 (1.0236) +2025-09-12,19:49:50 | INFO | Train Epoch: 2 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.92362 (1.0095) Boundary_loss: 0.013907 (0.013934) Loss: 0.93753 (1.0234) +2025-09-12,19:50:21 | INFO | Train Epoch: 2 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.96190 (1.0094) Boundary_loss: 0.013951 (0.013934) Loss: 0.97585 (1.0233) +2025-09-12,19:50:52 | INFO | Train Epoch: 2 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 1.0435 (1.0095) Boundary_loss: 0.013906 (0.013934) Loss: 1.0574 (1.0234) +2025-09-12,19:51:23 | INFO | Train Epoch: 2 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.88747 (1.0092) Boundary_loss: 0.013984 (0.013934) Loss: 0.90145 (1.0231) +2025-09-12,19:51:54 | INFO | Train Epoch: 2 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.94061 (1.0090) Boundary_loss: 0.013910 (0.013934) Loss: 0.95452 (1.0230) +2025-09-12,19:52:25 | INFO | Train Epoch: 2 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.85554 (1.0087) Boundary_loss: 0.013907 (0.013934) Loss: 0.86945 (1.0226) +2025-09-12,19:52:56 | INFO | Train Epoch: 2 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.86382 (1.0084) Boundary_loss: 0.013921 (0.013934) Loss: 0.87774 (1.0223) +2025-09-12,19:53:27 | INFO | Train Epoch: 2 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.87709 (1.0081) Boundary_loss: 0.013909 (0.013934) Loss: 0.89100 (1.0220) +2025-09-12,19:53:58 | INFO | Train Epoch: 2 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.95056 (1.0079) Boundary_loss: 0.013917 (0.013934) Loss: 0.96448 (1.0219) +2025-09-12,19:54:29 | INFO | Train Epoch: 2 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.95281 (1.0078) Boundary_loss: 0.013909 (0.013934) Loss: 0.96672 (1.0217) +2025-09-12,19:55:00 | INFO | Train Epoch: 2 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.90197 (1.0076) Boundary_loss: 0.013903 (0.013934) Loss: 0.91587 (1.0215) +2025-09-12,19:55:31 | INFO | Train Epoch: 2 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.98550 (1.0075) Boundary_loss: 0.013949 (0.013934) Loss: 0.99945 (1.0214) +2025-09-12,19:56:02 | INFO | Train Epoch: 2 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.97906 (1.0074) Boundary_loss: 0.013915 (0.013934) Loss: 0.99298 (1.0214) +2025-09-12,19:56:33 | INFO | Train Epoch: 2 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.87128 (1.0071) Boundary_loss: 0.013912 (0.013934) Loss: 0.88519 (1.0211) +2025-09-12,19:57:04 | INFO | Train Epoch: 2 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.98911 (1.0071) Boundary_loss: 0.013930 (0.013934) Loss: 1.0030 (1.0210) +2025-09-12,19:57:35 | INFO | Train Epoch: 2 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.89318 (1.0068) Boundary_loss: 0.013913 (0.013934) Loss: 0.90709 (1.0208) +2025-09-12,19:58:07 | INFO | Train Epoch: 2 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.90358 (1.0066) Boundary_loss: 0.013928 (0.013933) Loss: 0.91751 (1.0205) +2025-09-12,19:58:38 | INFO | Train Epoch: 2 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.96046 (1.0065) Boundary_loss: 0.013927 (0.013933) Loss: 0.97439 (1.0204) +2025-09-12,19:59:09 | INFO | Train Epoch: 2 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.0035 (1.0065) Boundary_loss: 0.013919 (0.013933) Loss: 1.0174 (1.0204) +2025-09-12,19:59:41 | INFO | Train Epoch: 2 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.85608 (1.0062) Boundary_loss: 0.013945 (0.013933) Loss: 0.87002 (1.0201) +2025-09-12,20:00:12 | INFO | Train Epoch: 2 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.91929 (1.0060) Boundary_loss: 0.013916 (0.013933) Loss: 0.93321 (1.0199) +2025-09-12,20:00:43 | INFO | Train Epoch: 2 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.86518 (1.0057) Boundary_loss: 0.013913 (0.013933) Loss: 0.87909 (1.0196) +2025-09-12,20:01:15 | INFO | Train Epoch: 2 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.97070 (1.0056) Boundary_loss: 0.013918 (0.013933) Loss: 0.98462 (1.0195) +2025-09-12,20:01:46 | INFO | Train Epoch: 2 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.88538 (1.0053) Boundary_loss: 0.013911 (0.013933) Loss: 0.89929 (1.0192) +2025-09-12,20:02:17 | INFO | Train Epoch: 2 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.86598 (1.0050) Boundary_loss: 0.013916 (0.013933) Loss: 0.87990 (1.0189) +2025-09-12,20:02:48 | INFO | Train Epoch: 2 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.96986 (1.0049) Boundary_loss: 0.013909 (0.013933) Loss: 0.98377 (1.0189) +2025-09-12,20:03:19 | INFO | Train Epoch: 2 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.93610 (1.0048) Boundary_loss: 0.013914 (0.013933) Loss: 0.95001 (1.0187) +2025-09-12,20:03:50 | INFO | Train Epoch: 2 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 1.1109 (1.0050) Boundary_loss: 0.013927 (0.013933) Loss: 1.1248 (1.0189) +2025-09-12,20:04:21 | INFO | Train Epoch: 2 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.95574 (1.0049) Boundary_loss: 0.013922 (0.013933) Loss: 0.96966 (1.0188) +2025-09-12,20:04:52 | INFO | Train Epoch: 2 [23398912/26365952 (89%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.84512 (1.0045) Boundary_loss: 0.013919 (0.013933) Loss: 0.85904 (1.0185) +2025-09-12,20:05:24 | INFO | Train Epoch: 2 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.88870 (1.0043) Boundary_loss: 0.013914 (0.013933) Loss: 0.90261 (1.0182) +2025-09-12,20:05:55 | INFO | Train Epoch: 2 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.95735 (1.0042) Boundary_loss: 0.013920 (0.013933) Loss: 0.97127 (1.0181) +2025-09-12,20:06:26 | INFO | Train Epoch: 2 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.92831 (1.0040) Boundary_loss: 0.013906 (0.013933) Loss: 0.94221 (1.0180) +2025-09-12,20:06:57 | INFO | Train Epoch: 2 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.98644 (1.0040) Boundary_loss: 0.013916 (0.013933) Loss: 1.0004 (1.0179) +2025-09-12,20:07:28 | INFO | Train Epoch: 2 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 1.0354 (1.0041) Boundary_loss: 0.013907 (0.013933) Loss: 1.0493 (1.0180) +2025-09-12,20:07:59 | INFO | Train Epoch: 2 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.84495 (1.0037) Boundary_loss: 0.013904 (0.013933) Loss: 0.85886 (1.0176) +2025-09-12,20:08:30 | INFO | Train Epoch: 2 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.92145 (1.0035) Boundary_loss: 0.013911 (0.013933) Loss: 0.93537 (1.0175) +2025-09-12,20:09:01 | INFO | Train Epoch: 2 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.87309 (1.0033) Boundary_loss: 0.013913 (0.013933) Loss: 0.88701 (1.0172) +2025-09-12,20:09:32 | INFO | Train Epoch: 2 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.92494 (1.0031) Boundary_loss: 0.013907 (0.013933) Loss: 0.93885 (1.0170) +2025-09-12,20:10:03 | INFO | Train Epoch: 2 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.98115 (1.0030) Boundary_loss: 0.013912 (0.013933) Loss: 0.99506 (1.0170) +2025-09-12,20:10:34 | INFO | Train Epoch: 2 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.89151 (1.0028) Boundary_loss: 0.013906 (0.013933) Loss: 0.90542 (1.0167) +2025-09-12,20:11:05 | INFO | Train Epoch: 2 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.89008 (1.0026) Boundary_loss: 0.013914 (0.013933) Loss: 0.90399 (1.0165) +2025-09-12,20:11:36 | INFO | Train Epoch: 2 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.92205 (1.0024) Boundary_loss: 0.013916 (0.013933) Loss: 0.93597 (1.0163) +2025-09-12,20:12:07 | INFO | Train Epoch: 2 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.84393 (1.0021) Boundary_loss: 0.013926 (0.013932) Loss: 0.85786 (1.0160) +2025-09-12,20:12:38 | INFO | Train Epoch: 2 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.94946 (1.0019) Boundary_loss: 0.013910 (0.013932) Loss: 0.96337 (1.0159) +2025-09-12,20:13:08 | INFO | Train Epoch: 2 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.98141 (1.0019) Boundary_loss: 0.013905 (0.013932) Loss: 0.99532 (1.0158) +2025-09-12,20:13:39 | INFO | Train Epoch: 2 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.81520 (1.0015) Boundary_loss: 0.013914 (0.013932) Loss: 0.82911 (1.0154) +2025-09-12,20:14:10 | INFO | Train Epoch: 2 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.92095 (1.0013) Boundary_loss: 0.013903 (0.013932) Loss: 0.93485 (1.0153) +2025-09-12,20:14:41 | INFO | Train Epoch: 2 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.95961 (1.0013) Boundary_loss: 0.013905 (0.013932) Loss: 0.97351 (1.0152) +2025-09-12,20:15:13 | INFO | Train Epoch: 2 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.95220 (1.0012) Boundary_loss: 0.013912 (0.013932) Loss: 0.96612 (1.0151) +2025-09-12,20:15:44 | INFO | Train Epoch: 2 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.77462 (1.0007) Boundary_loss: 0.013906 (0.013932) Loss: 0.78853 (1.0146) +2025-09-12,20:16:15 | INFO | Train Epoch: 2 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.88634 (1.0004) Boundary_loss: 0.013908 (0.013932) Loss: 0.90025 (1.0144) +2025-09-12,20:16:46 | INFO | Train Epoch: 2 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.87248 (1.0002) Boundary_loss: 0.013911 (0.013932) Loss: 0.88639 (1.0141) +2025-09-12,20:17:18 | INFO | Train Epoch: 2 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.93584 (1.0000) Boundary_loss: 0.013915 (0.013932) Loss: 0.94976 (1.0140) +2025-09-12,20:17:49 | INFO | Train Epoch: 2 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 1.0505 (1.0001) Boundary_loss: 0.013911 (0.013932) Loss: 1.0644 (1.0141) +2025-09-12,20:18:20 | INFO | Train Epoch: 2 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.92151 (0.99998) Boundary_loss: 0.013920 (0.013932) Loss: 0.93543 (1.0139) +2025-09-12,20:18:51 | INFO | Train Epoch: 2 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.82723 (0.99963) Boundary_loss: 0.013903 (0.013932) Loss: 0.84113 (1.0136) +2025-09-12,20:19:22 | INFO | Train Epoch: 2 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.86802 (0.99936) Boundary_loss: 0.013922 (0.013932) Loss: 0.88195 (1.0133) +2025-09-12,20:19:53 | INFO | Train Epoch: 2 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.89990 (0.99915) Boundary_loss: 0.013903 (0.013932) Loss: 0.91380 (1.0131) +2025-09-12,20:20:24 | INFO | Train Epoch: 2 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.93114 (0.99901) Boundary_loss: 0.013913 (0.013932) Loss: 0.94506 (1.0129) +2025-09-12,20:20:55 | INFO | Train Epoch: 2 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.93908 (0.99889) Boundary_loss: 0.013914 (0.013932) Loss: 0.95300 (1.0128) +2025-09-12,20:21:26 | INFO | Train Epoch: 2 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 1.0096 (0.99891) Boundary_loss: 0.013909 (0.013932) Loss: 1.0236 (1.0128) +2025-09-12,20:21:57 | INFO | Train Epoch: 2 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.83175 (0.99857) Boundary_loss: 0.013920 (0.013932) Loss: 0.84567 (1.0125) +2025-09-12,20:22:28 | INFO | Train Epoch: 2 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.92238 (0.99842) Boundary_loss: 0.013905 (0.013932) Loss: 0.93629 (1.0123) +2025-09-12,20:23:00 | INFO | Train Epoch: 2 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.97109 (0.99836) Boundary_loss: 0.013911 (0.013932) Loss: 0.98500 (1.0123) +2025-09-12,20:23:31 | INFO | Train Epoch: 2 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.90861 (0.99818) Boundary_loss: 0.013930 (0.013932) Loss: 0.92254 (1.0121) +2025-09-12,20:24:02 | INFO | Train Epoch: 2 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 1.0338 (0.99825) Boundary_loss: 0.013910 (0.013932) Loss: 1.0477 (1.0122) +2025-09-12,20:24:33 | INFO | Train Epoch: 2 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.82718 (0.99791) Boundary_loss: 0.013917 (0.013931) Loss: 0.84110 (1.0118) +2025-09-12,20:25:04 | INFO | Train Epoch: 2 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.92120 (0.99775) Boundary_loss: 0.013915 (0.013931) Loss: 0.93511 (1.0117) +2025-09-12,20:25:35 | INFO | Train Epoch: 2 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.98923 (0.99774) Boundary_loss: 0.013907 (0.013931) Loss: 1.0031 (1.0117) +2025-09-12,20:26:07 | INFO | Train Epoch: 2 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.89491 (0.99753) Boundary_loss: 0.013925 (0.013931) Loss: 0.90884 (1.0115) +2025-09-12,20:26:38 | INFO | Train Epoch: 2 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.84916 (0.99723) Boundary_loss: 0.013911 (0.013931) Loss: 0.86307 (1.0112) +2025-09-12,20:27:09 | INFO | Train Epoch: 2 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.88922 (0.99702) Boundary_loss: 0.013913 (0.013931) Loss: 0.90313 (1.0109) +2025-09-12,20:27:40 | INFO | Train Epoch: 2 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.91957 (0.99686) Boundary_loss: 0.013914 (0.013931) Loss: 0.93348 (1.0108) +2025-09-12,20:28:11 | INFO | Train Epoch: 2 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.89378 (0.99666) Boundary_loss: 0.013902 (0.013931) Loss: 0.90768 (1.0106) +2025-09-12,20:28:43 | INFO | Train Epoch: 2 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.86604 (0.99640) Boundary_loss: 0.013903 (0.013931) Loss: 0.87995 (1.0103) +2025-09-12,20:29:14 | INFO | Train Epoch: 2 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.87931 (0.99617) Boundary_loss: 0.013907 (0.013931) Loss: 0.89322 (1.0101) +2025-09-12,20:29:45 | INFO | Train Epoch: 2 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.96281 (0.99610) Boundary_loss: 0.013922 (0.013931) Loss: 0.97673 (1.0100) +2025-09-12,20:30:16 | INFO | Train Epoch: 2 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.89245 (0.99590) Boundary_loss: 0.013910 (0.013931) Loss: 0.90636 (1.0098) +2025-09-12,20:30:48 | INFO | Train Epoch: 2 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.92977 (0.99577) Boundary_loss: 0.013913 (0.013931) Loss: 0.94368 (1.0097) +2025-09-12,20:31:19 | INFO | Train Epoch: 2 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.0135 (0.99580) Boundary_loss: 0.013904 (0.013931) Loss: 1.0274 (1.0097) +2025-09-12,20:31:50 | INFO | Train Epoch: 2 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.0640 (0.99594) Boundary_loss: 0.013911 (0.013931) Loss: 1.0779 (1.0099) +2025-09-12,20:32:21 | INFO | Train Epoch: 2 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.92122 (0.99579) Boundary_loss: 0.013906 (0.013931) Loss: 0.93513 (1.0097) +2025-09-12,20:32:52 | INFO | Train Epoch: 2 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.87815 (0.99556) Boundary_loss: 0.013920 (0.013931) Loss: 0.89207 (1.0095) +2025-09-12,20:33:23 | INFO | Train Epoch: 2 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.96219 (0.99549) Boundary_loss: 0.013921 (0.013931) Loss: 0.97611 (1.0094) +2025-09-12,20:33:54 | INFO | Train Epoch: 2 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.89683 (0.99530) Boundary_loss: 0.013932 (0.013931) Loss: 0.91076 (1.0092) +2025-09-12,20:34:25 | INFO | Train Epoch: 2 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.94130 (0.99520) Boundary_loss: 0.013915 (0.013931) Loss: 0.95521 (1.0091) +2025-09-12,20:34:55 | INFO | Train Epoch: 2 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 1.0001 (0.99521) Boundary_loss: 0.013911 (0.013931) Loss: 1.0140 (1.0091) +2025-09-12,20:34:55 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,20:34:55 | INFO | [Epoch 2] Average Step Time: 0.314s | Average GPU Memory: 25.5 GB +2025-09-12,20:34:55 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-12,20:34:55 | INFO | Starting zero-shot imagenet. +2025-09-12,20:34:55 | INFO | Building zero-shot classifier +2025-09-12,20:35:01 | INFO | Using classifier +2025-09-12,20:35:46 | INFO | Finished zero-shot imagenet. +2025-09-12,20:35:46 | INFO | Eval Epoch: 3 imagenet-zeroshot-val-top1: 0.1928 imagenet-zeroshot-val-top5: 0.4097 +2025-09-12,20:35:47 | INFO | Start epoch 3 +2025-09-12,20:35:49 | INFO | Train Epoch: 3 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.80587 (0.80587) Boundary_loss: 0.013912 (0.013912) Loss: 0.81978 (0.81978) +2025-09-12,20:36:20 | INFO | Train Epoch: 3 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.88644 (0.84615) Boundary_loss: 0.013904 (0.013908) Loss: 0.90035 (0.86006) +2025-09-12,20:36:51 | INFO | Train Epoch: 3 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.82594 (0.83942) Boundary_loss: 0.013911 (0.013909) Loss: 0.83985 (0.85333) +2025-09-12,20:37:22 | INFO | Train Epoch: 3 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.77490 (0.82329) Boundary_loss: 0.013925 (0.013913) Loss: 0.78883 (0.83720) +2025-09-12,20:37:54 | INFO | Train Epoch: 3 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.68965 (0.79656) Boundary_loss: 0.013911 (0.013913) Loss: 0.70356 (0.81047) +2025-09-12,20:38:25 | INFO | Train Epoch: 3 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.80787 (0.79845) Boundary_loss: 0.013909 (0.013912) Loss: 0.82178 (0.81236) +2025-09-12,20:38:56 | INFO | Train Epoch: 3 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.81784 (0.80122) Boundary_loss: 0.013903 (0.013911) Loss: 0.83174 (0.81513) +2025-09-12,20:39:27 | INFO | Train Epoch: 3 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.74824 (0.79459) Boundary_loss: 0.013920 (0.013912) Loss: 0.76216 (0.80851) +2025-09-12,20:39:58 | INFO | Train Epoch: 3 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.77501 (0.79242) Boundary_loss: 0.013905 (0.013911) Loss: 0.78891 (0.80633) +2025-09-12,20:40:30 | INFO | Train Epoch: 3 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.91892 (0.80507) Boundary_loss: 0.013903 (0.013910) Loss: 0.93282 (0.81898) +2025-09-12,20:41:01 | INFO | Train Epoch: 3 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.83048 (0.80738) Boundary_loss: 0.013908 (0.013910) Loss: 0.84439 (0.82129) +2025-09-12,20:41:32 | INFO | Train Epoch: 3 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.72950 (0.80089) Boundary_loss: 0.013910 (0.013910) Loss: 0.74341 (0.81480) +2025-09-12,20:42:03 | INFO | Train Epoch: 3 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 1.0448 (0.81965) Boundary_loss: 0.013902 (0.013909) Loss: 1.0587 (0.83356) +2025-09-12,20:42:34 | INFO | Train Epoch: 3 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.68693 (0.81017) Boundary_loss: 0.013922 (0.013910) Loss: 0.70085 (0.82408) +2025-09-12,20:43:05 | INFO | Train Epoch: 3 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.87519 (0.81450) Boundary_loss: 0.013927 (0.013912) Loss: 0.88912 (0.82842) +2025-09-12,20:43:37 | INFO | Train Epoch: 3 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.78626 (0.81274) Boundary_loss: 0.013929 (0.013913) Loss: 0.80018 (0.82665) +2025-09-12,20:44:08 | INFO | Train Epoch: 3 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.91467 (0.81874) Boundary_loss: 0.013934 (0.013914) Loss: 0.92861 (0.83265) +2025-09-12,20:44:39 | INFO | Train Epoch: 3 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.76310 (0.81564) Boundary_loss: 0.013904 (0.013913) Loss: 0.77700 (0.82956) +2025-09-12,20:45:10 | INFO | Train Epoch: 3 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.75167 (0.81228) Boundary_loss: 0.013909 (0.013913) Loss: 0.76558 (0.82619) +2025-09-12,20:45:41 | INFO | Train Epoch: 3 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.86935 (0.81513) Boundary_loss: 0.013919 (0.013913) Loss: 0.88327 (0.82904) +2025-09-12,20:46:12 | INFO | Train Epoch: 3 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.80361 (0.81458) Boundary_loss: 0.013911 (0.013913) Loss: 0.81752 (0.82850) +2025-09-12,20:46:43 | INFO | Train Epoch: 3 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.84853 (0.81613) Boundary_loss: 0.013918 (0.013913) Loss: 0.86245 (0.83004) +2025-09-12,20:47:14 | INFO | Train Epoch: 3 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.77675 (0.81441) Boundary_loss: 0.013905 (0.013913) Loss: 0.79065 (0.82833) +2025-09-12,20:47:45 | INFO | Train Epoch: 3 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.69404 (0.80940) Boundary_loss: 0.013920 (0.013913) Loss: 0.70796 (0.82331) +2025-09-12,20:48:17 | INFO | Train Epoch: 3 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.85245 (0.81112) Boundary_loss: 0.013932 (0.013914) Loss: 0.86638 (0.82503) +2025-09-12,20:48:48 | INFO | Train Epoch: 3 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.81430 (0.81124) Boundary_loss: 0.013926 (0.013915) Loss: 0.82823 (0.82516) +2025-09-12,20:49:19 | INFO | Train Epoch: 3 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.87378 (0.81356) Boundary_loss: 0.013912 (0.013914) Loss: 0.88769 (0.82747) +2025-09-12,20:49:50 | INFO | Train Epoch: 3 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.82029 (0.81380) Boundary_loss: 0.013969 (0.013916) Loss: 0.83425 (0.82771) +2025-09-12,20:50:21 | INFO | Train Epoch: 3 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.82553 (0.81420) Boundary_loss: 0.013912 (0.013916) Loss: 0.83944 (0.82812) +2025-09-12,20:50:52 | INFO | Train Epoch: 3 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.0273 (0.82131) Boundary_loss: 0.013910 (0.013916) Loss: 1.0412 (0.83522) +2025-09-12,20:51:23 | INFO | Train Epoch: 3 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.87163 (0.82293) Boundary_loss: 0.013908 (0.013916) Loss: 0.88553 (0.83685) +2025-09-12,20:51:55 | INFO | Train Epoch: 3 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.81434 (0.82266) Boundary_loss: 0.013913 (0.013916) Loss: 0.82826 (0.83658) +2025-09-12,20:52:26 | INFO | Train Epoch: 3 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.84647 (0.82338) Boundary_loss: 0.013916 (0.013916) Loss: 0.86039 (0.83730) +2025-09-12,20:52:57 | INFO | Train Epoch: 3 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.85586 (0.82434) Boundary_loss: 0.013921 (0.013916) Loss: 0.86978 (0.83825) +2025-09-12,20:53:28 | INFO | Train Epoch: 3 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.82687 (0.82441) Boundary_loss: 0.013910 (0.013916) Loss: 0.84078 (0.83833) +2025-09-12,20:53:59 | INFO | Train Epoch: 3 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.80832 (0.82396) Boundary_loss: 0.013917 (0.013916) Loss: 0.82223 (0.83788) +2025-09-12,20:54:31 | INFO | Train Epoch: 3 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.67786 (0.82001) Boundary_loss: 0.013908 (0.013916) Loss: 0.69177 (0.83393) +2025-09-12,20:55:02 | INFO | Train Epoch: 3 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.99381 (0.82459) Boundary_loss: 0.013925 (0.013916) Loss: 1.0077 (0.83850) +2025-09-12,20:55:33 | INFO | Train Epoch: 3 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.87710 (0.82593) Boundary_loss: 0.013903 (0.013915) Loss: 0.89100 (0.83985) +2025-09-12,20:56:04 | INFO | Train Epoch: 3 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.85210 (0.82659) Boundary_loss: 0.013947 (0.013916) Loss: 0.86605 (0.84051) +2025-09-12,20:56:35 | INFO | Train Epoch: 3 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.77772 (0.82540) Boundary_loss: 0.013905 (0.013916) Loss: 0.79163 (0.83931) +2025-09-12,20:57:06 | INFO | Train Epoch: 3 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.81400 (0.82513) Boundary_loss: 0.013936 (0.013916) Loss: 0.82794 (0.83904) +2025-09-12,20:57:37 | INFO | Train Epoch: 3 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.81035 (0.82478) Boundary_loss: 0.013906 (0.013916) Loss: 0.82425 (0.83870) +2025-09-12,20:58:09 | INFO | Train Epoch: 3 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.93121 (0.82720) Boundary_loss: 0.013911 (0.013916) Loss: 0.94512 (0.84112) +2025-09-12,20:58:40 | INFO | Train Epoch: 3 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.92025 (0.82927) Boundary_loss: 0.013922 (0.013916) Loss: 0.93417 (0.84319) +2025-09-12,20:59:11 | INFO | Train Epoch: 3 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.77733 (0.82814) Boundary_loss: 0.013904 (0.013916) Loss: 0.79124 (0.84206) +2025-09-12,20:59:42 | INFO | Train Epoch: 3 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.0044 (0.83189) Boundary_loss: 0.013905 (0.013916) Loss: 1.0183 (0.84581) +2025-09-12,21:00:13 | INFO | Train Epoch: 3 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.88645 (0.83303) Boundary_loss: 0.013948 (0.013916) Loss: 0.90040 (0.84694) +2025-09-12,21:00:44 | INFO | Train Epoch: 3 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.90144 (0.83442) Boundary_loss: 0.013907 (0.013916) Loss: 0.91535 (0.84834) +2025-09-12,21:01:15 | INFO | Train Epoch: 3 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.81119 (0.83396) Boundary_loss: 0.013930 (0.013916) Loss: 0.82512 (0.84787) +2025-09-12,21:01:46 | INFO | Train Epoch: 3 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.79068 (0.83311) Boundary_loss: 0.013920 (0.013917) Loss: 0.80460 (0.84703) +2025-09-12,21:02:17 | INFO | Train Epoch: 3 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.90034 (0.83440) Boundary_loss: 0.013907 (0.013916) Loss: 0.91425 (0.84832) +2025-09-12,21:02:48 | INFO | Train Epoch: 3 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.88250 (0.83531) Boundary_loss: 0.013906 (0.013916) Loss: 0.89640 (0.84923) +2025-09-12,21:03:19 | INFO | Train Epoch: 3 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.87288 (0.83601) Boundary_loss: 0.013904 (0.013916) Loss: 0.88678 (0.84992) +2025-09-12,21:03:50 | INFO | Train Epoch: 3 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.82198 (0.83575) Boundary_loss: 0.013905 (0.013916) Loss: 0.83589 (0.84967) +2025-09-12,21:04:21 | INFO | Train Epoch: 3 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.78770 (0.83489) Boundary_loss: 0.013915 (0.013916) Loss: 0.80161 (0.84881) +2025-09-12,21:04:53 | INFO | Train Epoch: 3 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.77314 (0.83381) Boundary_loss: 0.013903 (0.013916) Loss: 0.78705 (0.84772) +2025-09-12,21:05:24 | INFO | Train Epoch: 3 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.99793 (0.83664) Boundary_loss: 0.013908 (0.013915) Loss: 1.0118 (0.85055) +2025-09-12,21:05:55 | INFO | Train Epoch: 3 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.76339 (0.83540) Boundary_loss: 0.013901 (0.013915) Loss: 0.77730 (0.84931) +2025-09-12,21:06:26 | INFO | Train Epoch: 3 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.77228 (0.83435) Boundary_loss: 0.013911 (0.013915) Loss: 0.78619 (0.84826) +2025-09-12,21:06:57 | INFO | Train Epoch: 3 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.76398 (0.83319) Boundary_loss: 0.013907 (0.013915) Loss: 0.77789 (0.84711) +2025-09-12,21:07:28 | INFO | Train Epoch: 3 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.65796 (0.83037) Boundary_loss: 0.013907 (0.013915) Loss: 0.67187 (0.84428) +2025-09-12,21:07:59 | INFO | Train Epoch: 3 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.73425 (0.82884) Boundary_loss: 0.013928 (0.013915) Loss: 0.74817 (0.84275) +2025-09-12,21:08:30 | INFO | Train Epoch: 3 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.85784 (0.82929) Boundary_loss: 0.013927 (0.013915) Loss: 0.87177 (0.84321) +2025-09-12,21:09:02 | INFO | Train Epoch: 3 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.85690 (0.82972) Boundary_loss: 0.013906 (0.013915) Loss: 0.87080 (0.84363) +2025-09-12,21:09:33 | INFO | Train Epoch: 3 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.81999 (0.82957) Boundary_loss: 0.013920 (0.013915) Loss: 0.83391 (0.84349) +2025-09-12,21:10:04 | INFO | Train Epoch: 3 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.70925 (0.82777) Boundary_loss: 0.013902 (0.013915) Loss: 0.72315 (0.84169) +2025-09-12,21:10:35 | INFO | Train Epoch: 3 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.92005 (0.82913) Boundary_loss: 0.013903 (0.013915) Loss: 0.93395 (0.84305) +2025-09-12,21:11:07 | INFO | Train Epoch: 3 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.86508 (0.82965) Boundary_loss: 0.013900 (0.013915) Loss: 0.87898 (0.84357) +2025-09-12,21:11:38 | INFO | Train Epoch: 3 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.80936 (0.82936) Boundary_loss: 0.013911 (0.013914) Loss: 0.82327 (0.84328) +2025-09-12,21:12:09 | INFO | Train Epoch: 3 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.93666 (0.83087) Boundary_loss: 0.013910 (0.013914) Loss: 0.95057 (0.84479) +2025-09-12,21:12:40 | INFO | Train Epoch: 3 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.73757 (0.82958) Boundary_loss: 0.013911 (0.013914) Loss: 0.75148 (0.84349) +2025-09-12,21:13:12 | INFO | Train Epoch: 3 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.74695 (0.82845) Boundary_loss: 0.013907 (0.013914) Loss: 0.76085 (0.84236) +2025-09-12,21:13:43 | INFO | Train Epoch: 3 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.90317 (0.82946) Boundary_loss: 0.013906 (0.013914) Loss: 0.91707 (0.84337) +2025-09-12,21:14:14 | INFO | Train Epoch: 3 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.84518 (0.82967) Boundary_loss: 0.013911 (0.013914) Loss: 0.85909 (0.84358) +2025-09-12,21:14:45 | INFO | Train Epoch: 3 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.73496 (0.82842) Boundary_loss: 0.013911 (0.013914) Loss: 0.74887 (0.84233) +2025-09-12,21:15:16 | INFO | Train Epoch: 3 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.68538 (0.82656) Boundary_loss: 0.013903 (0.013914) Loss: 0.69928 (0.84048) +2025-09-12,21:15:47 | INFO | Train Epoch: 3 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.80430 (0.82628) Boundary_loss: 0.013910 (0.013914) Loss: 0.81821 (0.84019) +2025-09-12,21:16:18 | INFO | Train Epoch: 3 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.84177 (0.82647) Boundary_loss: 0.013908 (0.013914) Loss: 0.85568 (0.84039) +2025-09-12,21:16:50 | INFO | Train Epoch: 3 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.75556 (0.82559) Boundary_loss: 0.013907 (0.013914) Loss: 0.76946 (0.83950) +2025-09-12,21:17:21 | INFO | Train Epoch: 3 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.87836 (0.82624) Boundary_loss: 0.013899 (0.013914) Loss: 0.89226 (0.84015) +2025-09-12,21:17:52 | INFO | Train Epoch: 3 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.86004 (0.82665) Boundary_loss: 0.013924 (0.013914) Loss: 0.87397 (0.84056) +2025-09-12,21:18:23 | INFO | Train Epoch: 3 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.88259 (0.82732) Boundary_loss: 0.013911 (0.013914) Loss: 0.89650 (0.84124) +2025-09-12,21:18:54 | INFO | Train Epoch: 3 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.82161 (0.82726) Boundary_loss: 0.013910 (0.013914) Loss: 0.83551 (0.84117) +2025-09-12,21:19:25 | INFO | Train Epoch: 3 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.90503 (0.82817) Boundary_loss: 0.013908 (0.013914) Loss: 0.91894 (0.84208) +2025-09-12,21:19:57 | INFO | Train Epoch: 3 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.68819 (0.82654) Boundary_loss: 0.013909 (0.013913) Loss: 0.70210 (0.84046) +2025-09-12,21:20:28 | INFO | Train Epoch: 3 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.95432 (0.82801) Boundary_loss: 0.013904 (0.013913) Loss: 0.96823 (0.84192) +2025-09-12,21:20:59 | INFO | Train Epoch: 3 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.99595 (0.82992) Boundary_loss: 0.013917 (0.013913) Loss: 1.0099 (0.84383) +2025-09-12,21:21:30 | INFO | Train Epoch: 3 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.84267 (0.83006) Boundary_loss: 0.013909 (0.013913) Loss: 0.85658 (0.84398) +2025-09-12,21:22:01 | INFO | Train Epoch: 3 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.80424 (0.82978) Boundary_loss: 0.013906 (0.013913) Loss: 0.81814 (0.84369) +2025-09-12,21:22:32 | INFO | Train Epoch: 3 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.79377 (0.82938) Boundary_loss: 0.013917 (0.013913) Loss: 0.80769 (0.84329) +2025-09-12,21:23:04 | INFO | Train Epoch: 3 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.83990 (0.82949) Boundary_loss: 0.013906 (0.013913) Loss: 0.85381 (0.84341) +2025-09-12,21:23:35 | INFO | Train Epoch: 3 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.82153 (0.82941) Boundary_loss: 0.013908 (0.013913) Loss: 0.83544 (0.84332) +2025-09-12,21:24:06 | INFO | Train Epoch: 3 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.86049 (0.82974) Boundary_loss: 0.013903 (0.013913) Loss: 0.87439 (0.84365) +2025-09-12,21:24:37 | INFO | Train Epoch: 3 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.88533 (0.83032) Boundary_loss: 0.013909 (0.013913) Loss: 0.89923 (0.84424) +2025-09-12,21:25:09 | INFO | Train Epoch: 3 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.76007 (0.82959) Boundary_loss: 0.013904 (0.013913) Loss: 0.77397 (0.84351) +2025-09-12,21:25:40 | INFO | Train Epoch: 3 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.86414 (0.82995) Boundary_loss: 0.013902 (0.013913) Loss: 0.87804 (0.84386) +2025-09-12,21:26:11 | INFO | Train Epoch: 3 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.86588 (0.83032) Boundary_loss: 0.013904 (0.013913) Loss: 0.87978 (0.84423) +2025-09-12,21:26:42 | INFO | Train Epoch: 3 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.77809 (0.82979) Boundary_loss: 0.013904 (0.013913) Loss: 0.79199 (0.84370) +2025-09-12,21:27:13 | INFO | Train Epoch: 3 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 1.0110 (0.83160) Boundary_loss: 0.013923 (0.013913) Loss: 1.0249 (0.84551) +2025-09-12,21:27:44 | INFO | Train Epoch: 3 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.78150 (0.83110) Boundary_loss: 0.013903 (0.013913) Loss: 0.79540 (0.84502) +2025-09-12,21:28:15 | INFO | Train Epoch: 3 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.80005 (0.83080) Boundary_loss: 0.013910 (0.013913) Loss: 0.81396 (0.84471) +2025-09-12,21:28:46 | INFO | Train Epoch: 3 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.92078 (0.83167) Boundary_loss: 0.013904 (0.013913) Loss: 0.93468 (0.84559) +2025-09-12,21:29:17 | INFO | Train Epoch: 3 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.71481 (0.83055) Boundary_loss: 0.013906 (0.013912) Loss: 0.72872 (0.84446) +2025-09-12,21:29:48 | INFO | Train Epoch: 3 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.88692 (0.83109) Boundary_loss: 0.013917 (0.013913) Loss: 0.90084 (0.84500) +2025-09-12,21:30:19 | INFO | Train Epoch: 3 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.85259 (0.83129) Boundary_loss: 0.013902 (0.013912) Loss: 0.86649 (0.84520) +2025-09-12,21:30:50 | INFO | Train Epoch: 3 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.77194 (0.83073) Boundary_loss: 0.013907 (0.013912) Loss: 0.78585 (0.84465) +2025-09-12,21:31:21 | INFO | Train Epoch: 3 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.87310 (0.83113) Boundary_loss: 0.013908 (0.013912) Loss: 0.88701 (0.84504) +2025-09-12,21:31:51 | INFO | Train Epoch: 3 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.83689 (0.83118) Boundary_loss: 0.013906 (0.013912) Loss: 0.85080 (0.84509) +2025-09-12,21:32:22 | INFO | Train Epoch: 3 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.88887 (0.83170) Boundary_loss: 0.013908 (0.013912) Loss: 0.90278 (0.84562) +2025-09-12,21:32:52 | INFO | Train Epoch: 3 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.82074 (0.83161) Boundary_loss: 0.013906 (0.013912) Loss: 0.83465 (0.84552) +2025-09-12,21:33:23 | INFO | Train Epoch: 3 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.66975 (0.83016) Boundary_loss: 0.013908 (0.013912) Loss: 0.68366 (0.84407) +2025-09-12,21:33:54 | INFO | Train Epoch: 3 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.92990 (0.83104) Boundary_loss: 0.013909 (0.013912) Loss: 0.94381 (0.84495) +2025-09-12,21:34:25 | INFO | Train Epoch: 3 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.83555 (0.83108) Boundary_loss: 0.013906 (0.013912) Loss: 0.84945 (0.84499) +2025-09-12,21:34:56 | INFO | Train Epoch: 3 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.82819 (0.83106) Boundary_loss: 0.013912 (0.013912) Loss: 0.84211 (0.84497) +2025-09-12,21:35:27 | INFO | Train Epoch: 3 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.85632 (0.83128) Boundary_loss: 0.013990 (0.013913) Loss: 0.87031 (0.84519) +2025-09-12,21:35:58 | INFO | Train Epoch: 3 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.77950 (0.83083) Boundary_loss: 0.013911 (0.013913) Loss: 0.79341 (0.84475) +2025-09-12,21:36:29 | INFO | Train Epoch: 3 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.79062 (0.83049) Boundary_loss: 0.013907 (0.013913) Loss: 0.80453 (0.84440) +2025-09-12,21:37:00 | INFO | Train Epoch: 3 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.79332 (0.83018) Boundary_loss: 0.013906 (0.013913) Loss: 0.80722 (0.84409) +2025-09-12,21:37:31 | INFO | Train Epoch: 3 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.78903 (0.82984) Boundary_loss: 0.013899 (0.013912) Loss: 0.80293 (0.84375) +2025-09-12,21:38:02 | INFO | Train Epoch: 3 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.84254 (0.82994) Boundary_loss: 0.013904 (0.013912) Loss: 0.85645 (0.84385) +2025-09-12,21:38:34 | INFO | Train Epoch: 3 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.96235 (0.83103) Boundary_loss: 0.013920 (0.013912) Loss: 0.97627 (0.84494) +2025-09-12,21:39:05 | INFO | Train Epoch: 3 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.87399 (0.83138) Boundary_loss: 0.013905 (0.013912) Loss: 0.88790 (0.84529) +2025-09-12,21:39:36 | INFO | Train Epoch: 3 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.83771 (0.83143) Boundary_loss: 0.013904 (0.013912) Loss: 0.85162 (0.84534) +2025-09-12,21:40:07 | INFO | Train Epoch: 3 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.93927 (0.83229) Boundary_loss: 0.013906 (0.013912) Loss: 0.95317 (0.84620) +2025-09-12,21:40:38 | INFO | Train Epoch: 3 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.84081 (0.83236) Boundary_loss: 0.013906 (0.013912) Loss: 0.85471 (0.84627) +2025-09-12,21:41:09 | INFO | Train Epoch: 3 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.76757 (0.83185) Boundary_loss: 0.013903 (0.013912) Loss: 0.78148 (0.84576) +2025-09-12,21:41:40 | INFO | Train Epoch: 3 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.75142 (0.83122) Boundary_loss: 0.013940 (0.013912) Loss: 0.76536 (0.84513) +2025-09-12,21:42:11 | INFO | Train Epoch: 3 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.81338 (0.83108) Boundary_loss: 0.013933 (0.013913) Loss: 0.82732 (0.84499) +2025-09-12,21:42:42 | INFO | Train Epoch: 3 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.95125 (0.83201) Boundary_loss: 0.013909 (0.013913) Loss: 0.96516 (0.84592) +2025-09-12,21:43:13 | INFO | Train Epoch: 3 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.76256 (0.83148) Boundary_loss: 0.013925 (0.013913) Loss: 0.77648 (0.84539) +2025-09-12,21:43:44 | INFO | Train Epoch: 3 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.74144 (0.83079) Boundary_loss: 0.013902 (0.013913) Loss: 0.75535 (0.84471) +2025-09-12,21:44:15 | INFO | Train Epoch: 3 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.85397 (0.83097) Boundary_loss: 0.013908 (0.013913) Loss: 0.86788 (0.84488) +2025-09-12,21:44:46 | INFO | Train Epoch: 3 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.79641 (0.83071) Boundary_loss: 0.013907 (0.013912) Loss: 0.81031 (0.84462) +2025-09-12,21:45:17 | INFO | Train Epoch: 3 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.78110 (0.83034) Boundary_loss: 0.013912 (0.013912) Loss: 0.79501 (0.84425) +2025-09-12,21:45:48 | INFO | Train Epoch: 3 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.79991 (0.83012) Boundary_loss: 0.013905 (0.013912) Loss: 0.81381 (0.84403) +2025-09-12,21:46:19 | INFO | Train Epoch: 3 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.90849 (0.83069) Boundary_loss: 0.013910 (0.013912) Loss: 0.92240 (0.84460) +2025-09-12,21:46:50 | INFO | Train Epoch: 3 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.79962 (0.83047) Boundary_loss: 0.013917 (0.013912) Loss: 0.81354 (0.84438) +2025-09-12,21:47:20 | INFO | Train Epoch: 3 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.76023 (0.82996) Boundary_loss: 0.013906 (0.013912) Loss: 0.77413 (0.84387) +2025-09-12,21:47:51 | INFO | Train Epoch: 3 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.79734 (0.82973) Boundary_loss: 0.013924 (0.013912) Loss: 0.81126 (0.84364) +2025-09-12,21:48:22 | INFO | Train Epoch: 3 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.83259 (0.82975) Boundary_loss: 0.013900 (0.013912) Loss: 0.84649 (0.84366) +2025-09-12,21:48:53 | INFO | Train Epoch: 3 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.83331 (0.82977) Boundary_loss: 0.013910 (0.013912) Loss: 0.84722 (0.84368) +2025-09-12,21:49:24 | INFO | Train Epoch: 3 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.91412 (0.83036) Boundary_loss: 0.013913 (0.013912) Loss: 0.92803 (0.84427) +2025-09-12,21:49:55 | INFO | Train Epoch: 3 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.87213 (0.83065) Boundary_loss: 0.013930 (0.013912) Loss: 0.88606 (0.84456) +2025-09-12,21:50:26 | INFO | Train Epoch: 3 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.83108 (0.83066) Boundary_loss: 0.013914 (0.013912) Loss: 0.84499 (0.84457) +2025-09-12,21:50:57 | INFO | Train Epoch: 3 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.81610 (0.83056) Boundary_loss: 0.013910 (0.013912) Loss: 0.83001 (0.84447) +2025-09-12,21:51:27 | INFO | Train Epoch: 3 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.87112 (0.83083) Boundary_loss: 0.013920 (0.013913) Loss: 0.88504 (0.84474) +2025-09-12,21:51:58 | INFO | Train Epoch: 3 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.67930 (0.82981) Boundary_loss: 0.013911 (0.013913) Loss: 0.69321 (0.84372) +2025-09-12,21:52:29 | INFO | Train Epoch: 3 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.84384 (0.82990) Boundary_loss: 0.013906 (0.013912) Loss: 0.85774 (0.84381) +2025-09-12,21:53:00 | INFO | Train Epoch: 3 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.79646 (0.82968) Boundary_loss: 0.013901 (0.013912) Loss: 0.81036 (0.84359) +2025-09-12,21:53:31 | INFO | Train Epoch: 3 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.81028 (0.82955) Boundary_loss: 0.013904 (0.013912) Loss: 0.82419 (0.84346) +2025-09-12,21:54:02 | INFO | Train Epoch: 3 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.65282 (0.82839) Boundary_loss: 0.013908 (0.013912) Loss: 0.66673 (0.84230) +2025-09-12,21:54:33 | INFO | Train Epoch: 3 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.71451 (0.82764) Boundary_loss: 0.013906 (0.013912) Loss: 0.72842 (0.84156) +2025-09-12,21:55:04 | INFO | Train Epoch: 3 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.81024 (0.82753) Boundary_loss: 0.013905 (0.013912) Loss: 0.82415 (0.84144) +2025-09-12,21:55:36 | INFO | Train Epoch: 3 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.77445 (0.82719) Boundary_loss: 0.013906 (0.013912) Loss: 0.78836 (0.84110) +2025-09-12,21:56:06 | INFO | Train Epoch: 3 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.84488 (0.82730) Boundary_loss: 0.013910 (0.013912) Loss: 0.85879 (0.84121) +2025-09-12,21:56:38 | INFO | Train Epoch: 3 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.86688 (0.82755) Boundary_loss: 0.013903 (0.013912) Loss: 0.88078 (0.84147) +2025-09-12,21:57:09 | INFO | Train Epoch: 3 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.82475 (0.82754) Boundary_loss: 0.013903 (0.013912) Loss: 0.83866 (0.84145) +2025-09-12,21:57:40 | INFO | Train Epoch: 3 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.71126 (0.82680) Boundary_loss: 0.013906 (0.013912) Loss: 0.72517 (0.84072) +2025-09-12,21:58:11 | INFO | Train Epoch: 3 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.68110 (0.82589) Boundary_loss: 0.013905 (0.013912) Loss: 0.69500 (0.83981) +2025-09-12,21:58:42 | INFO | Train Epoch: 3 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.94671 (0.82664) Boundary_loss: 0.013902 (0.013912) Loss: 0.96061 (0.84056) +2025-09-12,21:59:13 | INFO | Train Epoch: 3 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.81529 (0.82657) Boundary_loss: 0.013907 (0.013912) Loss: 0.82920 (0.84049) +2025-09-12,21:59:44 | INFO | Train Epoch: 3 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.76862 (0.82622) Boundary_loss: 0.013906 (0.013912) Loss: 0.78252 (0.84013) +2025-09-12,22:00:15 | INFO | Train Epoch: 3 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.89674 (0.82665) Boundary_loss: 0.013907 (0.013912) Loss: 0.91065 (0.84056) +2025-09-12,22:00:46 | INFO | Train Epoch: 3 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.76185 (0.82626) Boundary_loss: 0.013904 (0.013912) Loss: 0.77575 (0.84017) +2025-09-12,22:01:17 | INFO | Train Epoch: 3 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.81346 (0.82618) Boundary_loss: 0.013915 (0.013912) Loss: 0.82738 (0.84009) +2025-09-12,22:01:48 | INFO | Train Epoch: 3 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.81679 (0.82612) Boundary_loss: 0.013906 (0.013912) Loss: 0.83069 (0.84003) +2025-09-12,22:02:20 | INFO | Train Epoch: 3 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.74807 (0.82566) Boundary_loss: 0.013902 (0.013912) Loss: 0.76198 (0.83957) +2025-09-12,22:02:51 | INFO | Train Epoch: 3 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.77898 (0.82538) Boundary_loss: 0.013910 (0.013912) Loss: 0.79289 (0.83929) +2025-09-12,22:03:22 | INFO | Train Epoch: 3 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.80519 (0.82526) Boundary_loss: 0.013900 (0.013912) Loss: 0.81909 (0.83917) +2025-09-12,22:03:53 | INFO | Train Epoch: 3 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.82857 (0.82528) Boundary_loss: 0.013901 (0.013912) Loss: 0.84247 (0.83919) +2025-09-12,22:04:24 | INFO | Train Epoch: 3 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.85052 (0.82543) Boundary_loss: 0.013905 (0.013912) Loss: 0.86442 (0.83934) +2025-09-12,22:04:55 | INFO | Train Epoch: 3 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.84459 (0.82554) Boundary_loss: 0.013903 (0.013911) Loss: 0.85849 (0.83945) +2025-09-12,22:05:26 | INFO | Train Epoch: 3 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.87944 (0.82585) Boundary_loss: 0.013901 (0.013911) Loss: 0.89334 (0.83976) +2025-09-12,22:05:57 | INFO | Train Epoch: 3 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.89369 (0.82624) Boundary_loss: 0.013904 (0.013911) Loss: 0.90760 (0.84015) +2025-09-12,22:06:28 | INFO | Train Epoch: 3 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.90283 (0.82667) Boundary_loss: 0.013904 (0.013911) Loss: 0.91674 (0.84058) +2025-09-12,22:06:59 | INFO | Train Epoch: 3 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.79879 (0.82651) Boundary_loss: 0.013901 (0.013911) Loss: 0.81269 (0.84043) +2025-09-12,22:07:30 | INFO | Train Epoch: 3 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.82042 (0.82648) Boundary_loss: 0.013902 (0.013911) Loss: 0.83432 (0.84039) +2025-09-12,22:08:01 | INFO | Train Epoch: 3 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.82434 (0.82647) Boundary_loss: 0.013905 (0.013911) Loss: 0.83825 (0.84038) +2025-09-12,22:08:32 | INFO | Train Epoch: 3 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.85537 (0.82663) Boundary_loss: 0.013902 (0.013911) Loss: 0.86927 (0.84054) +2025-09-12,22:09:03 | INFO | Train Epoch: 3 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.84797 (0.82675) Boundary_loss: 0.013949 (0.013911) Loss: 0.86192 (0.84066) +2025-09-12,22:09:34 | INFO | Train Epoch: 3 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.89819 (0.82714) Boundary_loss: 0.013900 (0.013911) Loss: 0.91209 (0.84105) +2025-09-12,22:10:05 | INFO | Train Epoch: 3 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.73243 (0.82662) Boundary_loss: 0.013897 (0.013911) Loss: 0.74633 (0.84053) +2025-09-12,22:10:36 | INFO | Train Epoch: 3 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.94976 (0.82729) Boundary_loss: 0.013906 (0.013911) Loss: 0.96366 (0.84120) +2025-09-12,22:11:07 | INFO | Train Epoch: 3 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.76164 (0.82694) Boundary_loss: 0.013909 (0.013911) Loss: 0.77555 (0.84085) +2025-09-12,22:11:38 | INFO | Train Epoch: 3 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.67763 (0.82613) Boundary_loss: 0.013897 (0.013911) Loss: 0.69153 (0.84004) +2025-09-12,22:12:09 | INFO | Train Epoch: 3 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.76341 (0.82580) Boundary_loss: 0.013902 (0.013911) Loss: 0.77731 (0.83971) +2025-09-12,22:12:40 | INFO | Train Epoch: 3 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.76243 (0.82546) Boundary_loss: 0.013904 (0.013911) Loss: 0.77633 (0.83937) +2025-09-12,22:13:11 | INFO | Train Epoch: 3 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.87439 (0.82572) Boundary_loss: 0.013913 (0.013911) Loss: 0.88830 (0.83963) +2025-09-12,22:13:42 | INFO | Train Epoch: 3 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.86429 (0.82592) Boundary_loss: 0.013905 (0.013911) Loss: 0.87819 (0.83983) +2025-09-12,22:14:13 | INFO | Train Epoch: 3 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.91313 (0.82638) Boundary_loss: 0.013909 (0.013911) Loss: 0.92704 (0.84029) +2025-09-12,22:14:44 | INFO | Train Epoch: 3 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.68294 (0.82563) Boundary_loss: 0.013922 (0.013911) Loss: 0.69686 (0.83954) +2025-09-12,22:15:16 | INFO | Train Epoch: 3 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.75218 (0.82525) Boundary_loss: 0.013899 (0.013911) Loss: 0.76608 (0.83916) +2025-09-12,22:15:46 | INFO | Train Epoch: 3 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.78282 (0.82503) Boundary_loss: 0.013901 (0.013911) Loss: 0.79673 (0.83894) +2025-09-12,22:16:17 | INFO | Train Epoch: 3 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.81248 (0.82497) Boundary_loss: 0.013904 (0.013911) Loss: 0.82638 (0.83888) +2025-09-12,22:16:48 | INFO | Train Epoch: 3 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.81310 (0.82491) Boundary_loss: 0.013898 (0.013911) Loss: 0.82700 (0.83882) +2025-09-12,22:17:19 | INFO | Train Epoch: 3 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.80665 (0.82482) Boundary_loss: 0.013902 (0.013911) Loss: 0.82055 (0.83873) +2025-09-12,22:17:50 | INFO | Train Epoch: 3 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.76964 (0.82454) Boundary_loss: 0.013931 (0.013911) Loss: 0.78357 (0.83845) +2025-09-12,22:18:21 | INFO | Train Epoch: 3 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.81851 (0.82451) Boundary_loss: 0.013902 (0.013911) Loss: 0.83241 (0.83842) +2025-09-12,22:18:52 | INFO | Train Epoch: 3 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.76420 (0.82421) Boundary_loss: 0.013908 (0.013911) Loss: 0.77810 (0.83812) +2025-09-12,22:19:23 | INFO | Train Epoch: 3 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.97500 (0.82496) Boundary_loss: 0.013908 (0.013911) Loss: 0.98891 (0.83887) +2025-09-12,22:19:54 | INFO | Train Epoch: 3 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.83668 (0.82501) Boundary_loss: 0.013903 (0.013911) Loss: 0.85059 (0.83892) +2025-09-12,22:20:26 | INFO | Train Epoch: 3 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.82040 (0.82499) Boundary_loss: 0.013901 (0.013911) Loss: 0.83431 (0.83890) +2025-09-12,22:20:57 | INFO | Train Epoch: 3 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.84190 (0.82507) Boundary_loss: 0.013930 (0.013911) Loss: 0.85583 (0.83898) +2025-09-12,22:21:28 | INFO | Train Epoch: 3 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.70419 (0.82448) Boundary_loss: 0.013904 (0.013911) Loss: 0.71809 (0.83839) +2025-09-12,22:21:59 | INFO | Train Epoch: 3 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.78225 (0.82428) Boundary_loss: 0.013909 (0.013911) Loss: 0.79616 (0.83819) +2025-09-12,22:22:30 | INFO | Train Epoch: 3 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.89061 (0.82460) Boundary_loss: 0.013904 (0.013911) Loss: 0.90452 (0.83851) +2025-09-12,22:23:01 | INFO | Train Epoch: 3 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.90787 (0.82500) Boundary_loss: 0.013906 (0.013911) Loss: 0.92177 (0.83891) +2025-09-12,22:23:32 | INFO | Train Epoch: 3 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.72047 (0.82450) Boundary_loss: 0.013912 (0.013911) Loss: 0.73438 (0.83841) +2025-09-12,22:24:04 | INFO | Train Epoch: 3 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.86852 (0.82471) Boundary_loss: 0.013905 (0.013911) Loss: 0.88242 (0.83862) +2025-09-12,22:24:35 | INFO | Train Epoch: 3 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.73663 (0.82429) Boundary_loss: 0.013928 (0.013911) Loss: 0.75056 (0.83820) +2025-09-12,22:25:06 | INFO | Train Epoch: 3 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.82866 (0.82431) Boundary_loss: 0.013913 (0.013911) Loss: 0.84258 (0.83822) +2025-09-12,22:25:37 | INFO | Train Epoch: 3 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.66202 (0.82355) Boundary_loss: 0.013913 (0.013911) Loss: 0.67594 (0.83746) +2025-09-12,22:26:08 | INFO | Train Epoch: 3 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.77377 (0.82332) Boundary_loss: 0.013905 (0.013911) Loss: 0.78767 (0.83723) +2025-09-12,22:26:38 | INFO | Train Epoch: 3 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.71475 (0.82281) Boundary_loss: 0.013904 (0.013911) Loss: 0.72865 (0.83672) +2025-09-12,22:27:09 | INFO | Train Epoch: 3 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.88146 (0.82308) Boundary_loss: 0.013902 (0.013911) Loss: 0.89536 (0.83699) +2025-09-12,22:27:40 | INFO | Train Epoch: 3 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.86667 (0.82329) Boundary_loss: 0.013908 (0.013911) Loss: 0.88058 (0.83720) +2025-09-12,22:28:11 | INFO | Train Epoch: 3 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.84817 (0.82340) Boundary_loss: 0.013912 (0.013911) Loss: 0.86209 (0.83731) +2025-09-12,22:28:42 | INFO | Train Epoch: 3 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.85944 (0.82356) Boundary_loss: 0.013900 (0.013911) Loss: 0.87334 (0.83747) +2025-09-12,22:29:13 | INFO | Train Epoch: 3 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.76266 (0.82329) Boundary_loss: 0.013897 (0.013911) Loss: 0.77656 (0.83720) +2025-09-12,22:29:44 | INFO | Train Epoch: 3 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.68428 (0.82266) Boundary_loss: 0.013904 (0.013911) Loss: 0.69818 (0.83657) +2025-09-12,22:30:15 | INFO | Train Epoch: 3 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.76767 (0.82241) Boundary_loss: 0.013907 (0.013911) Loss: 0.78157 (0.83632) +2025-09-12,22:30:46 | INFO | Train Epoch: 3 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.82441 (0.82242) Boundary_loss: 0.013903 (0.013910) Loss: 0.83832 (0.83633) +2025-09-12,22:31:17 | INFO | Train Epoch: 3 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.71293 (0.82193) Boundary_loss: 0.013904 (0.013910) Loss: 0.72684 (0.83584) +2025-09-12,22:31:48 | INFO | Train Epoch: 3 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.86704 (0.82213) Boundary_loss: 0.013902 (0.013910) Loss: 0.88094 (0.83604) +2025-09-12,22:32:19 | INFO | Train Epoch: 3 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.77577 (0.82193) Boundary_loss: 0.013900 (0.013910) Loss: 0.78967 (0.83584) +2025-09-12,22:32:50 | INFO | Train Epoch: 3 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.71701 (0.82146) Boundary_loss: 0.013912 (0.013910) Loss: 0.73093 (0.83537) +2025-09-12,22:33:21 | INFO | Train Epoch: 3 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.81323 (0.82143) Boundary_loss: 0.013907 (0.013910) Loss: 0.82714 (0.83534) +2025-09-12,22:33:52 | INFO | Train Epoch: 3 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.81145 (0.82138) Boundary_loss: 0.013897 (0.013910) Loss: 0.82534 (0.83529) +2025-09-12,22:34:24 | INFO | Train Epoch: 3 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.85327 (0.82152) Boundary_loss: 0.013906 (0.013910) Loss: 0.86718 (0.83543) +2025-09-12,22:34:55 | INFO | Train Epoch: 3 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.85474 (0.82167) Boundary_loss: 0.013902 (0.013910) Loss: 0.86865 (0.83558) +2025-09-12,22:35:26 | INFO | Train Epoch: 3 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.84565 (0.82177) Boundary_loss: 0.013904 (0.013910) Loss: 0.85955 (0.83568) +2025-09-12,22:35:57 | INFO | Train Epoch: 3 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.89101 (0.82207) Boundary_loss: 0.013914 (0.013910) Loss: 0.90492 (0.83598) +2025-09-12,22:36:28 | INFO | Train Epoch: 3 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.78398 (0.82190) Boundary_loss: 0.013916 (0.013910) Loss: 0.79790 (0.83581) +2025-09-12,22:36:59 | INFO | Train Epoch: 3 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.69099 (0.82135) Boundary_loss: 0.013906 (0.013910) Loss: 0.70489 (0.83526) +2025-09-12,22:37:30 | INFO | Train Epoch: 3 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.77142 (0.82114) Boundary_loss: 0.013900 (0.013910) Loss: 0.78532 (0.83505) +2025-09-12,22:38:01 | INFO | Train Epoch: 3 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.89376 (0.82144) Boundary_loss: 0.013902 (0.013910) Loss: 0.90766 (0.83535) +2025-09-12,22:38:32 | INFO | Train Epoch: 3 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.86877 (0.82164) Boundary_loss: 0.013901 (0.013910) Loss: 0.88268 (0.83555) +2025-09-12,22:39:03 | INFO | Train Epoch: 3 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.89905 (0.82196) Boundary_loss: 0.013901 (0.013910) Loss: 0.91295 (0.83587) +2025-09-12,22:39:34 | INFO | Train Epoch: 3 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.92071 (0.82238) Boundary_loss: 0.013905 (0.013910) Loss: 0.93461 (0.83629) +2025-09-12,22:40:05 | INFO | Train Epoch: 3 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.83303 (0.82242) Boundary_loss: 0.013900 (0.013910) Loss: 0.84693 (0.83633) +2025-09-12,22:40:36 | INFO | Train Epoch: 3 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.74539 (0.82210) Boundary_loss: 0.013901 (0.013910) Loss: 0.75929 (0.83601) +2025-09-12,22:41:07 | INFO | Train Epoch: 3 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.88214 (0.82235) Boundary_loss: 0.013902 (0.013910) Loss: 0.89604 (0.83626) +2025-09-12,22:41:38 | INFO | Train Epoch: 3 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.84885 (0.82246) Boundary_loss: 0.013904 (0.013910) Loss: 0.86276 (0.83637) +2025-09-12,22:42:09 | INFO | Train Epoch: 3 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.81794 (0.82244) Boundary_loss: 0.013903 (0.013910) Loss: 0.83184 (0.83635) +2025-09-12,22:42:40 | INFO | Train Epoch: 3 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.88846 (0.82271) Boundary_loss: 0.013903 (0.013910) Loss: 0.90236 (0.83662) +2025-09-12,22:43:11 | INFO | Train Epoch: 3 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.75766 (0.82244) Boundary_loss: 0.013904 (0.013910) Loss: 0.77156 (0.83635) +2025-09-12,22:43:42 | INFO | Train Epoch: 3 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.88612 (0.82270) Boundary_loss: 0.013902 (0.013910) Loss: 0.90002 (0.83661) +2025-09-12,22:44:13 | INFO | Train Epoch: 3 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.75574 (0.82243) Boundary_loss: 0.013910 (0.013910) Loss: 0.76965 (0.83634) +2025-09-12,22:44:44 | INFO | Train Epoch: 3 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.74519 (0.82212) Boundary_loss: 0.013906 (0.013910) Loss: 0.75910 (0.83603) +2025-09-12,22:45:15 | INFO | Train Epoch: 3 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.77734 (0.82194) Boundary_loss: 0.013913 (0.013910) Loss: 0.79125 (0.83585) +2025-09-12,22:45:46 | INFO | Train Epoch: 3 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.78982 (0.82182) Boundary_loss: 0.013899 (0.013910) Loss: 0.80372 (0.83573) +2025-09-12,22:46:17 | INFO | Train Epoch: 3 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.71469 (0.82139) Boundary_loss: 0.013903 (0.013910) Loss: 0.72859 (0.83530) +2025-09-12,22:46:49 | INFO | Train Epoch: 3 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.75578 (0.82114) Boundary_loss: 0.013900 (0.013910) Loss: 0.76968 (0.83505) +2025-09-12,22:47:20 | INFO | Train Epoch: 3 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.72077 (0.82074) Boundary_loss: 0.013903 (0.013910) Loss: 0.73468 (0.83465) +2025-09-12,22:47:51 | INFO | Train Epoch: 3 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.85148 (0.82086) Boundary_loss: 0.013902 (0.013910) Loss: 0.86538 (0.83477) +2025-09-12,22:48:22 | INFO | Train Epoch: 3 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.64818 (0.82019) Boundary_loss: 0.013908 (0.013910) Loss: 0.66209 (0.83410) +2025-09-12,22:48:53 | INFO | Train Epoch: 3 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.78710 (0.82006) Boundary_loss: 0.013903 (0.013910) Loss: 0.80101 (0.83397) +2025-09-12,22:49:24 | INFO | Train Epoch: 3 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.90182 (0.82038) Boundary_loss: 0.013909 (0.013910) Loss: 0.91573 (0.83429) +2025-09-12,22:49:55 | INFO | Train Epoch: 3 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.76150 (0.82015) Boundary_loss: 0.013908 (0.013910) Loss: 0.77541 (0.83406) +2025-09-12,22:50:26 | INFO | Train Epoch: 3 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.81574 (0.82013) Boundary_loss: 0.013903 (0.013910) Loss: 0.82964 (0.83404) +2025-09-12,22:50:57 | INFO | Train Epoch: 3 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.71385 (0.81973) Boundary_loss: 0.013899 (0.013910) Loss: 0.72775 (0.83364) +2025-09-12,22:51:28 | INFO | Train Epoch: 3 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.82611 (0.81975) Boundary_loss: 0.013904 (0.013910) Loss: 0.84002 (0.83366) +2025-09-12,22:51:59 | INFO | Train Epoch: 3 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.72595 (0.81940) Boundary_loss: 0.013901 (0.013909) Loss: 0.73985 (0.83331) +2025-09-12,22:52:30 | INFO | Train Epoch: 3 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.74327 (0.81911) Boundary_loss: 0.013903 (0.013909) Loss: 0.75718 (0.83302) +2025-09-12,22:53:01 | INFO | Train Epoch: 3 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.76411 (0.81890) Boundary_loss: 0.013903 (0.013909) Loss: 0.77802 (0.83281) +2025-09-12,22:53:32 | INFO | Train Epoch: 3 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.80414 (0.81885) Boundary_loss: 0.013911 (0.013909) Loss: 0.81806 (0.83276) +2025-09-12,22:54:03 | INFO | Train Epoch: 3 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.81750 (0.81884) Boundary_loss: 0.013917 (0.013909) Loss: 0.83141 (0.83275) +2025-09-12,22:54:35 | INFO | Train Epoch: 3 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.67371 (0.81830) Boundary_loss: 0.013917 (0.013909) Loss: 0.68762 (0.83221) +2025-09-12,22:55:06 | INFO | Train Epoch: 3 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.69794 (0.81786) Boundary_loss: 0.013902 (0.013909) Loss: 0.71185 (0.83177) +2025-09-12,22:55:37 | INFO | Train Epoch: 3 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.77296 (0.81769) Boundary_loss: 0.013909 (0.013909) Loss: 0.78687 (0.83160) +2025-09-12,22:56:08 | INFO | Train Epoch: 3 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.85264 (0.81782) Boundary_loss: 0.013902 (0.013909) Loss: 0.86655 (0.83173) +2025-09-12,22:56:39 | INFO | Train Epoch: 3 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.81342 (0.81780) Boundary_loss: 0.013903 (0.013909) Loss: 0.82733 (0.83171) +2025-09-12,22:57:10 | INFO | Train Epoch: 3 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.72809 (0.81748) Boundary_loss: 0.013904 (0.013909) Loss: 0.74200 (0.83139) +2025-09-12,22:57:41 | INFO | Train Epoch: 3 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.85765 (0.81762) Boundary_loss: 0.013913 (0.013909) Loss: 0.87156 (0.83153) +2025-09-12,22:58:12 | INFO | Train Epoch: 3 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.80277 (0.81757) Boundary_loss: 0.013904 (0.013909) Loss: 0.81668 (0.83148) +2025-09-12,22:58:43 | INFO | Train Epoch: 3 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.76632 (0.81738) Boundary_loss: 0.013901 (0.013909) Loss: 0.78022 (0.83129) +2025-09-12,22:59:14 | INFO | Train Epoch: 3 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.76108 (0.81718) Boundary_loss: 0.013903 (0.013909) Loss: 0.77498 (0.83109) +2025-09-12,22:59:45 | INFO | Train Epoch: 3 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.74154 (0.81691) Boundary_loss: 0.013924 (0.013909) Loss: 0.75546 (0.83082) +2025-09-12,23:00:16 | INFO | Train Epoch: 3 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.70340 (0.81651) Boundary_loss: 0.013908 (0.013909) Loss: 0.71731 (0.83041) +2025-09-12,23:00:47 | INFO | Train Epoch: 3 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.85297 (0.81664) Boundary_loss: 0.013902 (0.013909) Loss: 0.86687 (0.83054) +2025-09-12,23:01:18 | INFO | Train Epoch: 3 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.77514 (0.81649) Boundary_loss: 0.013910 (0.013909) Loss: 0.78905 (0.83040) +2025-09-12,23:01:49 | INFO | Train Epoch: 3 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.81065 (0.81647) Boundary_loss: 0.013903 (0.013909) Loss: 0.82455 (0.83038) +2025-09-12,23:02:20 | INFO | Train Epoch: 3 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.71966 (0.81613) Boundary_loss: 0.013900 (0.013909) Loss: 0.73356 (0.83004) +2025-09-12,23:02:51 | INFO | Train Epoch: 3 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.83052 (0.81618) Boundary_loss: 0.013902 (0.013909) Loss: 0.84442 (0.83009) +2025-09-12,23:03:23 | INFO | Train Epoch: 3 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.76695 (0.81600) Boundary_loss: 0.013903 (0.013909) Loss: 0.78085 (0.82991) +2025-09-12,23:03:54 | INFO | Train Epoch: 3 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.83515 (0.81607) Boundary_loss: 0.013925 (0.013909) Loss: 0.84908 (0.82998) +2025-09-12,23:04:25 | INFO | Train Epoch: 3 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.74204 (0.81581) Boundary_loss: 0.013900 (0.013909) Loss: 0.75594 (0.82972) +2025-09-12,23:04:56 | INFO | Train Epoch: 3 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.76464 (0.81564) Boundary_loss: 0.013899 (0.013909) Loss: 0.77854 (0.82955) +2025-09-12,23:05:27 | INFO | Train Epoch: 3 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.72399 (0.81532) Boundary_loss: 0.013899 (0.013909) Loss: 0.73789 (0.82923) +2025-09-12,23:05:58 | INFO | Train Epoch: 3 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.84762 (0.81543) Boundary_loss: 0.013902 (0.013909) Loss: 0.86152 (0.82934) +2025-09-12,23:06:28 | INFO | Train Epoch: 3 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.83807 (0.81551) Boundary_loss: 0.013905 (0.013909) Loss: 0.85198 (0.82942) +2025-09-12,23:06:59 | INFO | Train Epoch: 3 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.66056 (0.81498) Boundary_loss: 0.013911 (0.013909) Loss: 0.67447 (0.82889) +2025-09-12,23:07:30 | INFO | Train Epoch: 3 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.75015 (0.81476) Boundary_loss: 0.013905 (0.013909) Loss: 0.76405 (0.82867) +2025-09-12,23:08:01 | INFO | Train Epoch: 3 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.75497 (0.81456) Boundary_loss: 0.013903 (0.013909) Loss: 0.76887 (0.82847) +2025-09-12,23:08:32 | INFO | Train Epoch: 3 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.81239 (0.81455) Boundary_loss: 0.013905 (0.013909) Loss: 0.82629 (0.82846) +2025-09-12,23:09:03 | INFO | Train Epoch: 3 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.64987 (0.81400) Boundary_loss: 0.013904 (0.013909) Loss: 0.66378 (0.82791) +2025-09-12,23:09:33 | INFO | Train Epoch: 3 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.89163 (0.81426) Boundary_loss: 0.013903 (0.013909) Loss: 0.90553 (0.82817) +2025-09-12,23:10:04 | INFO | Train Epoch: 3 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.91748 (0.81460) Boundary_loss: 0.013897 (0.013909) Loss: 0.93137 (0.82851) +2025-09-12,23:10:35 | INFO | Train Epoch: 3 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.75209 (0.81439) Boundary_loss: 0.013905 (0.013909) Loss: 0.76599 (0.82830) +2025-09-12,23:11:06 | INFO | Train Epoch: 3 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.76177 (0.81422) Boundary_loss: 0.013906 (0.013909) Loss: 0.77568 (0.82813) +2025-09-12,23:11:37 | INFO | Train Epoch: 3 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.66412 (0.81372) Boundary_loss: 0.013905 (0.013909) Loss: 0.67802 (0.82763) +2025-09-12,23:12:08 | INFO | Train Epoch: 3 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.84271 (0.81382) Boundary_loss: 0.013901 (0.013909) Loss: 0.85661 (0.82773) +2025-09-12,23:12:39 | INFO | Train Epoch: 3 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 0.73676 (0.81356) Boundary_loss: 0.013920 (0.013909) Loss: 0.75068 (0.82747) +2025-09-12,23:13:10 | INFO | Train Epoch: 3 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.79185 (0.81349) Boundary_loss: 0.013897 (0.013909) Loss: 0.80575 (0.82740) +2025-09-12,23:13:41 | INFO | Train Epoch: 3 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.92015 (0.81384) Boundary_loss: 0.013902 (0.013909) Loss: 0.93405 (0.82775) +2025-09-12,23:14:12 | INFO | Train Epoch: 3 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.70946 (0.81350) Boundary_loss: 0.013926 (0.013909) Loss: 0.72339 (0.82741) +2025-09-12,23:14:43 | INFO | Train Epoch: 3 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.71505 (0.81318) Boundary_loss: 0.013904 (0.013909) Loss: 0.72896 (0.82709) +2025-09-12,23:15:13 | INFO | Train Epoch: 3 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.80723 (0.81316) Boundary_loss: 0.013900 (0.013909) Loss: 0.82113 (0.82707) +2025-09-12,23:15:45 | INFO | Train Epoch: 3 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.88002 (0.81338) Boundary_loss: 0.013900 (0.013909) Loss: 0.89391 (0.82729) +2025-09-12,23:16:16 | INFO | Train Epoch: 3 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.71698 (0.81307) Boundary_loss: 0.013904 (0.013909) Loss: 0.73088 (0.82698) +2025-09-12,23:16:47 | INFO | Train Epoch: 3 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.83678 (0.81314) Boundary_loss: 0.013899 (0.013909) Loss: 0.85068 (0.82705) +2025-09-12,23:17:18 | INFO | Train Epoch: 3 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.81579 (0.81315) Boundary_loss: 0.013899 (0.013909) Loss: 0.82969 (0.82706) +2025-09-12,23:17:49 | INFO | Train Epoch: 3 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.72613 (0.81288) Boundary_loss: 0.013911 (0.013909) Loss: 0.74005 (0.82678) +2025-09-12,23:18:20 | INFO | Train Epoch: 3 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.84355 (0.81297) Boundary_loss: 0.013900 (0.013909) Loss: 0.85745 (0.82688) +2025-09-12,23:18:51 | INFO | Train Epoch: 3 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.81081 (0.81297) Boundary_loss: 0.013904 (0.013909) Loss: 0.82471 (0.82687) +2025-09-12,23:19:22 | INFO | Train Epoch: 3 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.86865 (0.81314) Boundary_loss: 0.013902 (0.013909) Loss: 0.88255 (0.82705) +2025-09-12,23:19:54 | INFO | Train Epoch: 3 [16230912/26365952 (62%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.77842 (0.81303) Boundary_loss: 0.013911 (0.013909) Loss: 0.79233 (0.82694) +2025-09-12,23:20:25 | INFO | Train Epoch: 3 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.86350 (0.81319) Boundary_loss: 0.013910 (0.013909) Loss: 0.87741 (0.82710) +2025-09-12,23:20:56 | INFO | Train Epoch: 3 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.88686 (0.81342) Boundary_loss: 0.013899 (0.013909) Loss: 0.90076 (0.82733) +2025-09-12,23:21:27 | INFO | Train Epoch: 3 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.87084 (0.81360) Boundary_loss: 0.013910 (0.013909) Loss: 0.88475 (0.82751) +2025-09-12,23:21:57 | INFO | Train Epoch: 3 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.86752 (0.81377) Boundary_loss: 0.013914 (0.013909) Loss: 0.88144 (0.82768) +2025-09-12,23:22:28 | INFO | Train Epoch: 3 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.78567 (0.81368) Boundary_loss: 0.013906 (0.013909) Loss: 0.79958 (0.82759) +2025-09-12,23:22:59 | INFO | Train Epoch: 3 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.86066 (0.81383) Boundary_loss: 0.013899 (0.013909) Loss: 0.87456 (0.82773) +2025-09-12,23:23:30 | INFO | Train Epoch: 3 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.82088 (0.81385) Boundary_loss: 0.013900 (0.013909) Loss: 0.83478 (0.82776) +2025-09-12,23:24:00 | INFO | Train Epoch: 3 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.82217 (0.81387) Boundary_loss: 0.013907 (0.013909) Loss: 0.83608 (0.82778) +2025-09-12,23:24:31 | INFO | Train Epoch: 3 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.79636 (0.81382) Boundary_loss: 0.013898 (0.013909) Loss: 0.81026 (0.82773) +2025-09-12,23:25:03 | INFO | Train Epoch: 3 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.84293 (0.81391) Boundary_loss: 0.013905 (0.013909) Loss: 0.85683 (0.82782) +2025-09-12,23:25:34 | INFO | Train Epoch: 3 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.73393 (0.81366) Boundary_loss: 0.013904 (0.013909) Loss: 0.74784 (0.82757) +2025-09-12,23:26:05 | INFO | Train Epoch: 3 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.75265 (0.81348) Boundary_loss: 0.013918 (0.013909) Loss: 0.76657 (0.82739) +2025-09-12,23:26:36 | INFO | Train Epoch: 3 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.88641 (0.81370) Boundary_loss: 0.013899 (0.013909) Loss: 0.90031 (0.82761) +2025-09-12,23:27:07 | INFO | Train Epoch: 3 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.81204 (0.81369) Boundary_loss: 0.013903 (0.013909) Loss: 0.82594 (0.82760) +2025-09-12,23:27:39 | INFO | Train Epoch: 3 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.79946 (0.81365) Boundary_loss: 0.013917 (0.013909) Loss: 0.81337 (0.82756) +2025-09-12,23:28:10 | INFO | Train Epoch: 3 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.87772 (0.81384) Boundary_loss: 0.013906 (0.013909) Loss: 0.89163 (0.82775) +2025-09-12,23:28:41 | INFO | Train Epoch: 3 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.82110 (0.81387) Boundary_loss: 0.013901 (0.013909) Loss: 0.83500 (0.82777) +2025-09-12,23:29:12 | INFO | Train Epoch: 3 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.78033 (0.81377) Boundary_loss: 0.013903 (0.013909) Loss: 0.79423 (0.82767) +2025-09-12,23:29:43 | INFO | Train Epoch: 3 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.70759 (0.81345) Boundary_loss: 0.013912 (0.013909) Loss: 0.72150 (0.82736) +2025-09-12,23:30:15 | INFO | Train Epoch: 3 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.78163 (0.81336) Boundary_loss: 0.013928 (0.013909) Loss: 0.79556 (0.82727) +2025-09-12,23:30:46 | INFO | Train Epoch: 3 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.82069 (0.81338) Boundary_loss: 0.013909 (0.013909) Loss: 0.83459 (0.82729) +2025-09-12,23:31:17 | INFO | Train Epoch: 3 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.85672 (0.81351) Boundary_loss: 0.013919 (0.013909) Loss: 0.87064 (0.82741) +2025-09-12,23:31:48 | INFO | Train Epoch: 3 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.78062 (0.81341) Boundary_loss: 0.013900 (0.013909) Loss: 0.79452 (0.82732) +2025-09-12,23:32:19 | INFO | Train Epoch: 3 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.69591 (0.81307) Boundary_loss: 0.013900 (0.013909) Loss: 0.70981 (0.82697) +2025-09-12,23:32:50 | INFO | Train Epoch: 3 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.79047 (0.81300) Boundary_loss: 0.013902 (0.013909) Loss: 0.80438 (0.82691) +2025-09-12,23:33:22 | INFO | Train Epoch: 3 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.85123 (0.81311) Boundary_loss: 0.013904 (0.013909) Loss: 0.86514 (0.82702) +2025-09-12,23:33:53 | INFO | Train Epoch: 3 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.81787 (0.81312) Boundary_loss: 0.013908 (0.013909) Loss: 0.83178 (0.82703) +2025-09-12,23:34:23 | INFO | Train Epoch: 3 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.79728 (0.81308) Boundary_loss: 0.013907 (0.013909) Loss: 0.81119 (0.82699) +2025-09-12,23:34:54 | INFO | Train Epoch: 3 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.76944 (0.81295) Boundary_loss: 0.013912 (0.013909) Loss: 0.78335 (0.82686) +2025-09-12,23:35:25 | INFO | Train Epoch: 3 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.63684 (0.81245) Boundary_loss: 0.013900 (0.013909) Loss: 0.65074 (0.82636) +2025-09-12,23:35:57 | INFO | Train Epoch: 3 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.85345 (0.81256) Boundary_loss: 0.013900 (0.013909) Loss: 0.86735 (0.82647) +2025-09-12,23:36:28 | INFO | Train Epoch: 3 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.69970 (0.81224) Boundary_loss: 0.013904 (0.013909) Loss: 0.71361 (0.82615) +2025-09-12,23:36:59 | INFO | Train Epoch: 3 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.64613 (0.81177) Boundary_loss: 0.013903 (0.013909) Loss: 0.66003 (0.82568) +2025-09-12,23:37:30 | INFO | Train Epoch: 3 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.81100 (0.81177) Boundary_loss: 0.013906 (0.013909) Loss: 0.82490 (0.82568) +2025-09-12,23:38:01 | INFO | Train Epoch: 3 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.83008 (0.81182) Boundary_loss: 0.013901 (0.013909) Loss: 0.84398 (0.82573) +2025-09-12,23:38:32 | INFO | Train Epoch: 3 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.71047 (0.81153) Boundary_loss: 0.013902 (0.013909) Loss: 0.72437 (0.82544) +2025-09-12,23:39:03 | INFO | Train Epoch: 3 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.90049 (0.81178) Boundary_loss: 0.013899 (0.013908) Loss: 0.91439 (0.82569) +2025-09-12,23:39:34 | INFO | Train Epoch: 3 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.65265 (0.81134) Boundary_loss: 0.013903 (0.013908) Loss: 0.66655 (0.82524) +2025-09-12,23:40:05 | INFO | Train Epoch: 3 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.75071 (0.81117) Boundary_loss: 0.013904 (0.013908) Loss: 0.76461 (0.82507) +2025-09-12,23:40:36 | INFO | Train Epoch: 3 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.82581 (0.81121) Boundary_loss: 0.013903 (0.013908) Loss: 0.83972 (0.82512) +2025-09-12,23:41:07 | INFO | Train Epoch: 3 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.76728 (0.81108) Boundary_loss: 0.013901 (0.013908) Loss: 0.78118 (0.82499) +2025-09-12,23:41:38 | INFO | Train Epoch: 3 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.82606 (0.81113) Boundary_loss: 0.013911 (0.013908) Loss: 0.83997 (0.82503) +2025-09-12,23:42:09 | INFO | Train Epoch: 3 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.77305 (0.81102) Boundary_loss: 0.013904 (0.013908) Loss: 0.78696 (0.82493) +2025-09-12,23:42:40 | INFO | Train Epoch: 3 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.73692 (0.81082) Boundary_loss: 0.013902 (0.013908) Loss: 0.75083 (0.82472) +2025-09-12,23:43:11 | INFO | Train Epoch: 3 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.81851 (0.81084) Boundary_loss: 0.013899 (0.013908) Loss: 0.83241 (0.82475) +2025-09-12,23:43:41 | INFO | Train Epoch: 3 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.78547 (0.81077) Boundary_loss: 0.013903 (0.013908) Loss: 0.79937 (0.82468) +2025-09-12,23:44:12 | INFO | Train Epoch: 3 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.71513 (0.81051) Boundary_loss: 0.013918 (0.013908) Loss: 0.72904 (0.82441) +2025-09-12,23:44:43 | INFO | Train Epoch: 3 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.79744 (0.81047) Boundary_loss: 0.013904 (0.013908) Loss: 0.81134 (0.82438) +2025-09-12,23:45:14 | INFO | Train Epoch: 3 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.77417 (0.81037) Boundary_loss: 0.013903 (0.013908) Loss: 0.78807 (0.82428) +2025-09-12,23:45:45 | INFO | Train Epoch: 3 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.70353 (0.81008) Boundary_loss: 0.013899 (0.013908) Loss: 0.71743 (0.82399) +2025-09-12,23:46:16 | INFO | Train Epoch: 3 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.67309 (0.80971) Boundary_loss: 0.013910 (0.013908) Loss: 0.68700 (0.82362) +2025-09-12,23:46:47 | INFO | Train Epoch: 3 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.64612 (0.80927) Boundary_loss: 0.013901 (0.013908) Loss: 0.66002 (0.82318) +2025-09-12,23:47:18 | INFO | Train Epoch: 3 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.73842 (0.80908) Boundary_loss: 0.013903 (0.013908) Loss: 0.75232 (0.82298) +2025-09-12,23:47:49 | INFO | Train Epoch: 3 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.75753 (0.80894) Boundary_loss: 0.013900 (0.013908) Loss: 0.77143 (0.82285) +2025-09-12,23:48:21 | INFO | Train Epoch: 3 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.72538 (0.80871) Boundary_loss: 0.013901 (0.013908) Loss: 0.73928 (0.82262) +2025-09-12,23:48:52 | INFO | Train Epoch: 3 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.72581 (0.80849) Boundary_loss: 0.013900 (0.013908) Loss: 0.73971 (0.82240) +2025-09-12,23:49:23 | INFO | Train Epoch: 3 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.74292 (0.80832) Boundary_loss: 0.013904 (0.013908) Loss: 0.75683 (0.82223) +2025-09-12,23:49:54 | INFO | Train Epoch: 3 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.68681 (0.80799) Boundary_loss: 0.013899 (0.013908) Loss: 0.70071 (0.82190) +2025-09-12,23:50:25 | INFO | Train Epoch: 3 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.82153 (0.80803) Boundary_loss: 0.013897 (0.013908) Loss: 0.83543 (0.82194) +2025-09-12,23:50:56 | INFO | Train Epoch: 3 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.87194 (0.80820) Boundary_loss: 0.013905 (0.013908) Loss: 0.88585 (0.82211) +2025-09-12,23:51:26 | INFO | Train Epoch: 3 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.81287 (0.80821) Boundary_loss: 0.013905 (0.013908) Loss: 0.82678 (0.82212) +2025-09-12,23:51:57 | INFO | Train Epoch: 3 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.87194 (0.80838) Boundary_loss: 0.013899 (0.013908) Loss: 0.88584 (0.82229) +2025-09-12,23:52:28 | INFO | Train Epoch: 3 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.77871 (0.80830) Boundary_loss: 0.013909 (0.013908) Loss: 0.79262 (0.82221) +2025-09-12,23:52:59 | INFO | Train Epoch: 3 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.67663 (0.80796) Boundary_loss: 0.013905 (0.013908) Loss: 0.69054 (0.82186) +2025-09-12,23:53:29 | INFO | Train Epoch: 3 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.85261 (0.80807) Boundary_loss: 0.013928 (0.013908) Loss: 0.86654 (0.82198) +2025-09-12,23:54:00 | INFO | Train Epoch: 3 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.87078 (0.80824) Boundary_loss: 0.013922 (0.013908) Loss: 0.88470 (0.82214) +2025-09-12,23:54:31 | INFO | Train Epoch: 3 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.73890 (0.80806) Boundary_loss: 0.013912 (0.013908) Loss: 0.75281 (0.82196) +2025-09-12,23:55:02 | INFO | Train Epoch: 3 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.74821 (0.80790) Boundary_loss: 0.013907 (0.013908) Loss: 0.76212 (0.82181) +2025-09-12,23:55:33 | INFO | Train Epoch: 3 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.78871 (0.80785) Boundary_loss: 0.013917 (0.013908) Loss: 0.80262 (0.82176) +2025-09-12,23:56:04 | INFO | Train Epoch: 3 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.70332 (0.80758) Boundary_loss: 0.013904 (0.013908) Loss: 0.71722 (0.82149) +2025-09-12,23:56:35 | INFO | Train Epoch: 3 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.71417 (0.80734) Boundary_loss: 0.013900 (0.013908) Loss: 0.72807 (0.82125) +2025-09-12,23:57:06 | INFO | Train Epoch: 3 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.84509 (0.80744) Boundary_loss: 0.013903 (0.013908) Loss: 0.85900 (0.82135) +2025-09-12,23:57:37 | INFO | Train Epoch: 3 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.73010 (0.80724) Boundary_loss: 0.013901 (0.013908) Loss: 0.74400 (0.82115) +2025-09-12,23:58:08 | INFO | Train Epoch: 3 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.75037 (0.80710) Boundary_loss: 0.013902 (0.013908) Loss: 0.76428 (0.82100) +2025-09-12,23:58:39 | INFO | Train Epoch: 3 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.92448 (0.80739) Boundary_loss: 0.013907 (0.013908) Loss: 0.93838 (0.82130) +2025-09-12,23:59:11 | INFO | Train Epoch: 3 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.75506 (0.80726) Boundary_loss: 0.013899 (0.013908) Loss: 0.76896 (0.82117) +2025-09-12,23:59:42 | INFO | Train Epoch: 3 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.82034 (0.80729) Boundary_loss: 0.013899 (0.013908) Loss: 0.83424 (0.82120) +2025-09-13,00:00:13 | INFO | Train Epoch: 3 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.75061 (0.80715) Boundary_loss: 0.013908 (0.013908) Loss: 0.76452 (0.82106) +2025-09-13,00:00:44 | INFO | Train Epoch: 3 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.80681 (0.80715) Boundary_loss: 0.013898 (0.013908) Loss: 0.82070 (0.82106) +2025-09-13,00:01:15 | INFO | Train Epoch: 3 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.78758 (0.80710) Boundary_loss: 0.013900 (0.013908) Loss: 0.80148 (0.82101) +2025-09-13,00:01:46 | INFO | Train Epoch: 3 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.79021 (0.80706) Boundary_loss: 0.013900 (0.013908) Loss: 0.80411 (0.82097) +2025-09-13,00:02:17 | INFO | Train Epoch: 3 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.71795 (0.80684) Boundary_loss: 0.013906 (0.013908) Loss: 0.73186 (0.82074) +2025-09-13,00:02:48 | INFO | Train Epoch: 3 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.92678 (0.80714) Boundary_loss: 0.013900 (0.013908) Loss: 0.94068 (0.82104) +2025-09-13,00:03:19 | INFO | Train Epoch: 3 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.74699 (0.80699) Boundary_loss: 0.013906 (0.013908) Loss: 0.76090 (0.82089) +2025-09-13,00:03:50 | INFO | Train Epoch: 3 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.77584 (0.80691) Boundary_loss: 0.013903 (0.013908) Loss: 0.78975 (0.82082) +2025-09-13,00:04:22 | INFO | Train Epoch: 3 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.77547 (0.80683) Boundary_loss: 0.013904 (0.013908) Loss: 0.78938 (0.82074) +2025-09-13,00:04:53 | INFO | Train Epoch: 3 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.75560 (0.80670) Boundary_loss: 0.013916 (0.013908) Loss: 0.76951 (0.82061) +2025-09-13,00:05:24 | INFO | Train Epoch: 3 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.83786 (0.80678) Boundary_loss: 0.013904 (0.013908) Loss: 0.85176 (0.82069) +2025-09-13,00:05:54 | INFO | Train Epoch: 3 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.69089 (0.80650) Boundary_loss: 0.013908 (0.013908) Loss: 0.70480 (0.82040) +2025-09-13,00:06:25 | INFO | Train Epoch: 3 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.66221 (0.80614) Boundary_loss: 0.013900 (0.013908) Loss: 0.67611 (0.82005) +2025-09-13,00:06:56 | INFO | Train Epoch: 3 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.73189 (0.80596) Boundary_loss: 0.013903 (0.013908) Loss: 0.74579 (0.81987) +2025-09-13,00:07:27 | INFO | Train Epoch: 3 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.70646 (0.80572) Boundary_loss: 0.013899 (0.013908) Loss: 0.72036 (0.81963) +2025-09-13,00:07:58 | INFO | Train Epoch: 3 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.72832 (0.80553) Boundary_loss: 0.013905 (0.013908) Loss: 0.74222 (0.81944) +2025-09-13,00:08:29 | INFO | Train Epoch: 3 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.72874 (0.80534) Boundary_loss: 0.013899 (0.013908) Loss: 0.74264 (0.81925) +2025-09-13,00:09:00 | INFO | Train Epoch: 3 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.82125 (0.80538) Boundary_loss: 0.013903 (0.013908) Loss: 0.83515 (0.81929) +2025-09-13,00:09:31 | INFO | Train Epoch: 3 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.81099 (0.80540) Boundary_loss: 0.013903 (0.013908) Loss: 0.82490 (0.81930) +2025-09-13,00:10:02 | INFO | Train Epoch: 3 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.73533 (0.80523) Boundary_loss: 0.013907 (0.013908) Loss: 0.74924 (0.81914) +2025-09-13,00:10:33 | INFO | Train Epoch: 3 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.74112 (0.80507) Boundary_loss: 0.013905 (0.013908) Loss: 0.75503 (0.81898) +2025-09-13,00:11:04 | INFO | Train Epoch: 3 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.77170 (0.80499) Boundary_loss: 0.013912 (0.013908) Loss: 0.78561 (0.81890) +2025-09-13,00:11:35 | INFO | Train Epoch: 3 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.66473 (0.80466) Boundary_loss: 0.013910 (0.013908) Loss: 0.67864 (0.81857) +2025-09-13,00:12:07 | INFO | Train Epoch: 3 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.75736 (0.80454) Boundary_loss: 0.013911 (0.013908) Loss: 0.77127 (0.81845) +2025-09-13,00:12:38 | INFO | Train Epoch: 3 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.78492 (0.80450) Boundary_loss: 0.013900 (0.013908) Loss: 0.79882 (0.81841) +2025-09-13,00:13:09 | INFO | Train Epoch: 3 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.75938 (0.80439) Boundary_loss: 0.013900 (0.013908) Loss: 0.77328 (0.81830) +2025-09-13,00:13:40 | INFO | Train Epoch: 3 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.63754 (0.80400) Boundary_loss: 0.013898 (0.013908) Loss: 0.65144 (0.81790) +2025-09-13,00:14:11 | INFO | Train Epoch: 3 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.75770 (0.80389) Boundary_loss: 0.013914 (0.013908) Loss: 0.77161 (0.81779) +2025-09-13,00:14:42 | INFO | Train Epoch: 3 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.73227 (0.80372) Boundary_loss: 0.013901 (0.013908) Loss: 0.74617 (0.81762) +2025-09-13,00:15:13 | INFO | Train Epoch: 3 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.74881 (0.80359) Boundary_loss: 0.013900 (0.013908) Loss: 0.76271 (0.81750) +2025-09-13,00:15:44 | INFO | Train Epoch: 3 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.86564 (0.80373) Boundary_loss: 0.013903 (0.013908) Loss: 0.87955 (0.81764) +2025-09-13,00:16:15 | INFO | Train Epoch: 3 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.71051 (0.80352) Boundary_loss: 0.013901 (0.013908) Loss: 0.72441 (0.81742) +2025-09-13,00:16:46 | INFO | Train Epoch: 3 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.71912 (0.80332) Boundary_loss: 0.013909 (0.013908) Loss: 0.73302 (0.81723) +2025-09-13,00:17:17 | INFO | Train Epoch: 3 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.86617 (0.80346) Boundary_loss: 0.013918 (0.013908) Loss: 0.88008 (0.81737) +2025-09-13,00:17:47 | INFO | Train Epoch: 3 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.77284 (0.80339) Boundary_loss: 0.013907 (0.013908) Loss: 0.78674 (0.81730) +2025-09-13,00:18:18 | INFO | Train Epoch: 3 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.81775 (0.80343) Boundary_loss: 0.013900 (0.013908) Loss: 0.83165 (0.81733) +2025-09-13,00:18:49 | INFO | Train Epoch: 3 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.78875 (0.80339) Boundary_loss: 0.013899 (0.013908) Loss: 0.80265 (0.81730) +2025-09-13,00:19:20 | INFO | Train Epoch: 3 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.79894 (0.80338) Boundary_loss: 0.013902 (0.013908) Loss: 0.81284 (0.81729) +2025-09-13,00:19:52 | INFO | Train Epoch: 3 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.78855 (0.80335) Boundary_loss: 0.013903 (0.013908) Loss: 0.80245 (0.81726) +2025-09-13,00:20:23 | INFO | Train Epoch: 3 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.79156 (0.80332) Boundary_loss: 0.013900 (0.013908) Loss: 0.80546 (0.81723) +2025-09-13,00:20:54 | INFO | Train Epoch: 3 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.77713 (0.80326) Boundary_loss: 0.013901 (0.013908) Loss: 0.79103 (0.81717) +2025-09-13,00:21:25 | INFO | Train Epoch: 3 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.80271 (0.80326) Boundary_loss: 0.013899 (0.013908) Loss: 0.81661 (0.81717) +2025-09-13,00:21:56 | INFO | Train Epoch: 3 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.80985 (0.80327) Boundary_loss: 0.013900 (0.013908) Loss: 0.82375 (0.81718) +2025-09-13,00:22:27 | INFO | Train Epoch: 3 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.77583 (0.80321) Boundary_loss: 0.013900 (0.013908) Loss: 0.78973 (0.81712) +2025-09-13,00:22:58 | INFO | Train Epoch: 3 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.69381 (0.80296) Boundary_loss: 0.013905 (0.013908) Loss: 0.70772 (0.81687) +2025-09-13,00:23:29 | INFO | Train Epoch: 3 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.79391 (0.80294) Boundary_loss: 0.013902 (0.013908) Loss: 0.80781 (0.81685) +2025-09-13,00:24:00 | INFO | Train Epoch: 3 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.73776 (0.80280) Boundary_loss: 0.013900 (0.013908) Loss: 0.75166 (0.81670) +2025-09-13,00:24:31 | INFO | Train Epoch: 3 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.73293 (0.80264) Boundary_loss: 0.013899 (0.013908) Loss: 0.74683 (0.81655) +2025-09-13,00:25:02 | INFO | Train Epoch: 3 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.73952 (0.80250) Boundary_loss: 0.013906 (0.013908) Loss: 0.75343 (0.81640) +2025-09-13,00:25:33 | INFO | Train Epoch: 3 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.82371 (0.80254) Boundary_loss: 0.013909 (0.013908) Loss: 0.83762 (0.81645) +2025-09-13,00:26:04 | INFO | Train Epoch: 3 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.71706 (0.80235) Boundary_loss: 0.013904 (0.013908) Loss: 0.73097 (0.81626) +2025-09-13,00:26:35 | INFO | Train Epoch: 3 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.80680 (0.80236) Boundary_loss: 0.013904 (0.013908) Loss: 0.82071 (0.81627) +2025-09-13,00:27:06 | INFO | Train Epoch: 3 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.65927 (0.80204) Boundary_loss: 0.013905 (0.013908) Loss: 0.67318 (0.81595) +2025-09-13,00:27:37 | INFO | Train Epoch: 3 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.74480 (0.80191) Boundary_loss: 0.013905 (0.013908) Loss: 0.75870 (0.81582) +2025-09-13,00:28:08 | INFO | Train Epoch: 3 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.68411 (0.80165) Boundary_loss: 0.013902 (0.013908) Loss: 0.69801 (0.81556) +2025-09-13,00:28:40 | INFO | Train Epoch: 3 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.98139 (0.80205) Boundary_loss: 0.013899 (0.013908) Loss: 0.99529 (0.81596) +2025-09-13,00:29:10 | INFO | Train Epoch: 3 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.67473 (0.80177) Boundary_loss: 0.013898 (0.013908) Loss: 0.68863 (0.81568) +2025-09-13,00:29:41 | INFO | Train Epoch: 3 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.75755 (0.80167) Boundary_loss: 0.013909 (0.013908) Loss: 0.77146 (0.81558) +2025-09-13,00:30:12 | INFO | Train Epoch: 3 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.73144 (0.80152) Boundary_loss: 0.013903 (0.013908) Loss: 0.74534 (0.81542) +2025-09-13,00:30:43 | INFO | Train Epoch: 3 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.65649 (0.80120) Boundary_loss: 0.013911 (0.013908) Loss: 0.67040 (0.81511) +2025-09-13,00:31:14 | INFO | Train Epoch: 3 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.85267 (0.80131) Boundary_loss: 0.013901 (0.013908) Loss: 0.86657 (0.81522) +2025-09-13,00:31:45 | INFO | Train Epoch: 3 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.69838 (0.80109) Boundary_loss: 0.013903 (0.013908) Loss: 0.71229 (0.81499) +2025-09-13,00:32:16 | INFO | Train Epoch: 3 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.78192 (0.80104) Boundary_loss: 0.013899 (0.013908) Loss: 0.79582 (0.81495) +2025-09-13,00:32:47 | INFO | Train Epoch: 3 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.70736 (0.80084) Boundary_loss: 0.013898 (0.013907) Loss: 0.72126 (0.81475) +2025-09-13,00:33:18 | INFO | Train Epoch: 3 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.80306 (0.80085) Boundary_loss: 0.013899 (0.013907) Loss: 0.81696 (0.81475) +2025-09-13,00:33:49 | INFO | Train Epoch: 3 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.70055 (0.80063) Boundary_loss: 0.013899 (0.013907) Loss: 0.71445 (0.81454) +2025-09-13,00:34:20 | INFO | Train Epoch: 3 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.76114 (0.80054) Boundary_loss: 0.013902 (0.013907) Loss: 0.77505 (0.81445) +2025-09-13,00:34:51 | INFO | Train Epoch: 3 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.70570 (0.80034) Boundary_loss: 0.013904 (0.013907) Loss: 0.71960 (0.81424) +2025-09-13,00:35:22 | INFO | Train Epoch: 3 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.79777 (0.80033) Boundary_loss: 0.013900 (0.013907) Loss: 0.81167 (0.81424) +2025-09-13,00:35:53 | INFO | Train Epoch: 3 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.86576 (0.80047) Boundary_loss: 0.013901 (0.013907) Loss: 0.87966 (0.81438) +2025-09-13,00:36:24 | INFO | Train Epoch: 3 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.69391 (0.80024) Boundary_loss: 0.013931 (0.013907) Loss: 0.70784 (0.81415) +2025-09-13,00:36:55 | INFO | Train Epoch: 3 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.77941 (0.80020) Boundary_loss: 0.013898 (0.013907) Loss: 0.79331 (0.81411) +2025-09-13,00:37:26 | INFO | Train Epoch: 3 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.73939 (0.80007) Boundary_loss: 0.013899 (0.013907) Loss: 0.75328 (0.81398) +2025-09-13,00:37:57 | INFO | Train Epoch: 3 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.73134 (0.79992) Boundary_loss: 0.013900 (0.013907) Loss: 0.74524 (0.81383) +2025-09-13,00:38:28 | INFO | Train Epoch: 3 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.73344 (0.79978) Boundary_loss: 0.013907 (0.013907) Loss: 0.74735 (0.81369) +2025-09-13,00:38:59 | INFO | Train Epoch: 3 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.82304 (0.79983) Boundary_loss: 0.013903 (0.013907) Loss: 0.83694 (0.81374) +2025-09-13,00:39:30 | INFO | Train Epoch: 3 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.79380 (0.79982) Boundary_loss: 0.013901 (0.013907) Loss: 0.80770 (0.81373) +2025-09-13,00:40:00 | INFO | Train Epoch: 3 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.77124 (0.79976) Boundary_loss: 0.013901 (0.013907) Loss: 0.78514 (0.81366) +2025-09-13,00:40:31 | INFO | Train Epoch: 3 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.68707 (0.79952) Boundary_loss: 0.013900 (0.013907) Loss: 0.70097 (0.81343) +2025-09-13,00:41:02 | INFO | Train Epoch: 3 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.69419 (0.79930) Boundary_loss: 0.013908 (0.013907) Loss: 0.70810 (0.81321) +2025-09-13,00:41:33 | INFO | Train Epoch: 3 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.83322 (0.79937) Boundary_loss: 0.013899 (0.013907) Loss: 0.84712 (0.81328) +2025-09-13,00:42:04 | INFO | Train Epoch: 3 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.83107 (0.79944) Boundary_loss: 0.013900 (0.013907) Loss: 0.84497 (0.81334) +2025-09-13,00:42:35 | INFO | Train Epoch: 3 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.80643 (0.79945) Boundary_loss: 0.013898 (0.013907) Loss: 0.82033 (0.81336) +2025-09-13,00:43:06 | INFO | Train Epoch: 3 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.70396 (0.79925) Boundary_loss: 0.013900 (0.013907) Loss: 0.71786 (0.81316) +2025-09-13,00:43:37 | INFO | Train Epoch: 3 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.81947 (0.79929) Boundary_loss: 0.013912 (0.013907) Loss: 0.83338 (0.81320) +2025-09-13,00:44:09 | INFO | Train Epoch: 3 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.70844 (0.79910) Boundary_loss: 0.013905 (0.013907) Loss: 0.72235 (0.81301) +2025-09-13,00:44:39 | INFO | Train Epoch: 3 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.87168 (0.79925) Boundary_loss: 0.013899 (0.013907) Loss: 0.88558 (0.81316) +2025-09-13,00:45:10 | INFO | Train Epoch: 3 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.69321 (0.79904) Boundary_loss: 0.013898 (0.013907) Loss: 0.70710 (0.81294) +2025-09-13,00:45:41 | INFO | Train Epoch: 3 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.72283 (0.79888) Boundary_loss: 0.013901 (0.013907) Loss: 0.73673 (0.81279) +2025-09-13,00:46:12 | INFO | Train Epoch: 3 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.75979 (0.79880) Boundary_loss: 0.013899 (0.013907) Loss: 0.77369 (0.81270) +2025-09-13,00:46:44 | INFO | Train Epoch: 3 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.79329 (0.79879) Boundary_loss: 0.013904 (0.013907) Loss: 0.80719 (0.81269) +2025-09-13,00:47:15 | INFO | Train Epoch: 3 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.74925 (0.79868) Boundary_loss: 0.013905 (0.013907) Loss: 0.76316 (0.81259) +2025-09-13,00:47:46 | INFO | Train Epoch: 3 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.68113 (0.79844) Boundary_loss: 0.013896 (0.013907) Loss: 0.69502 (0.81235) +2025-09-13,00:48:17 | INFO | Train Epoch: 3 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.72327 (0.79829) Boundary_loss: 0.013906 (0.013907) Loss: 0.73718 (0.81220) +2025-09-13,00:48:48 | INFO | Train Epoch: 3 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.76911 (0.79823) Boundary_loss: 0.013900 (0.013907) Loss: 0.78302 (0.81214) +2025-09-13,00:49:19 | INFO | Train Epoch: 3 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.72817 (0.79809) Boundary_loss: 0.013901 (0.013907) Loss: 0.74208 (0.81199) +2025-09-13,00:49:50 | INFO | Train Epoch: 3 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.79050 (0.79807) Boundary_loss: 0.013914 (0.013907) Loss: 0.80441 (0.81198) +2025-09-13,00:50:21 | INFO | Train Epoch: 3 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.73470 (0.79794) Boundary_loss: 0.013904 (0.013907) Loss: 0.74860 (0.81185) +2025-09-13,00:50:52 | INFO | Train Epoch: 3 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.72112 (0.79779) Boundary_loss: 0.013906 (0.013907) Loss: 0.73503 (0.81170) +2025-09-13,00:51:23 | INFO | Train Epoch: 3 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.82314 (0.79784) Boundary_loss: 0.013899 (0.013907) Loss: 0.83704 (0.81175) +2025-09-13,00:51:54 | INFO | Train Epoch: 3 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.93519 (0.79812) Boundary_loss: 0.013901 (0.013907) Loss: 0.94909 (0.81202) +2025-09-13,00:52:25 | INFO | Train Epoch: 3 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.77559 (0.79807) Boundary_loss: 0.013916 (0.013907) Loss: 0.78951 (0.81198) +2025-09-13,00:52:55 | INFO | Train Epoch: 3 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.75988 (0.79799) Boundary_loss: 0.013930 (0.013907) Loss: 0.77381 (0.81190) +2025-09-13,00:53:26 | INFO | Train Epoch: 3 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.73262 (0.79786) Boundary_loss: 0.013902 (0.013907) Loss: 0.74652 (0.81177) +2025-09-13,00:53:57 | INFO | Train Epoch: 3 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.65958 (0.79759) Boundary_loss: 0.013899 (0.013907) Loss: 0.67348 (0.81149) +2025-09-13,00:54:28 | INFO | Train Epoch: 3 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.68243 (0.79736) Boundary_loss: 0.013901 (0.013907) Loss: 0.69633 (0.81126) +2025-09-13,00:54:59 | INFO | Train Epoch: 3 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.73554 (0.79723) Boundary_loss: 0.013907 (0.013907) Loss: 0.74945 (0.81114) +2025-09-13,00:55:30 | INFO | Train Epoch: 3 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.73775 (0.79712) Boundary_loss: 0.013898 (0.013907) Loss: 0.75165 (0.81102) +2025-09-13,00:56:01 | INFO | Train Epoch: 3 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.75241 (0.79703) Boundary_loss: 0.013900 (0.013907) Loss: 0.76631 (0.81093) +2025-09-13,00:56:32 | INFO | Train Epoch: 3 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.78140 (0.79700) Boundary_loss: 0.013902 (0.013907) Loss: 0.79530 (0.81090) +2025-09-13,00:57:03 | INFO | Train Epoch: 3 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.77558 (0.79695) Boundary_loss: 0.013901 (0.013907) Loss: 0.78948 (0.81086) +2025-09-13,00:57:34 | INFO | Train Epoch: 3 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.76138 (0.79688) Boundary_loss: 0.013899 (0.013907) Loss: 0.77528 (0.81079) +2025-09-13,00:58:05 | INFO | Train Epoch: 3 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.83798 (0.79696) Boundary_loss: 0.013899 (0.013907) Loss: 0.85188 (0.81087) +2025-09-13,00:58:36 | INFO | Train Epoch: 3 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.86133 (0.79709) Boundary_loss: 0.013898 (0.013907) Loss: 0.87523 (0.81100) +2025-09-13,00:59:07 | INFO | Train Epoch: 3 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.76315 (0.79702) Boundary_loss: 0.013904 (0.013907) Loss: 0.77705 (0.81093) +2025-09-13,00:59:38 | INFO | Train Epoch: 3 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.79377 (0.79702) Boundary_loss: 0.013902 (0.013907) Loss: 0.80767 (0.81092) +2025-09-13,01:00:09 | INFO | Train Epoch: 3 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.79435 (0.79701) Boundary_loss: 0.013901 (0.013907) Loss: 0.80825 (0.81092) +2025-09-13,01:00:40 | INFO | Train Epoch: 3 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.76283 (0.79695) Boundary_loss: 0.013914 (0.013907) Loss: 0.77675 (0.81085) +2025-09-13,01:01:11 | INFO | Train Epoch: 3 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.71286 (0.79678) Boundary_loss: 0.013900 (0.013907) Loss: 0.72676 (0.81069) +2025-09-13,01:01:42 | INFO | Train Epoch: 3 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.66635 (0.79653) Boundary_loss: 0.013909 (0.013907) Loss: 0.68026 (0.81044) +2025-09-13,01:02:11 | INFO | Train Epoch: 3 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.72925 (0.79640) Boundary_loss: 0.013920 (0.013907) Loss: 0.74317 (0.81031) +2025-09-13,01:02:11 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,01:02:11 | INFO | [Epoch 3] Average Step Time: 0.313s | Average GPU Memory: 25.4 GB +2025-09-13,01:02:11 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,01:02:11 | INFO | Starting zero-shot imagenet. +2025-09-13,01:02:11 | INFO | Building zero-shot classifier +2025-09-13,01:02:18 | INFO | Using classifier +2025-09-13,01:03:02 | INFO | Finished zero-shot imagenet. +2025-09-13,01:03:02 | INFO | Eval Epoch: 4 imagenet-zeroshot-val-top1: 0.2141 imagenet-zeroshot-val-top5: 0.4470 +2025-09-13,01:03:03 | INFO | Start epoch 4 +2025-09-13,01:03:04 | INFO | Train Epoch: 4 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.53629 (0.53629) Boundary_loss: 0.013911 (0.013911) Loss: 0.55020 (0.55020) +2025-09-13,01:03:36 | INFO | Train Epoch: 4 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.59509 (0.56569) Boundary_loss: 0.013901 (0.013906) Loss: 0.60899 (0.57960) +2025-09-13,01:04:07 | INFO | Train Epoch: 4 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.66381 (0.59840) Boundary_loss: 0.013899 (0.013904) Loss: 0.67771 (0.61230) +2025-09-13,01:04:38 | INFO | Train Epoch: 4 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.55808 (0.58832) Boundary_loss: 0.013902 (0.013903) Loss: 0.57199 (0.60222) +2025-09-13,01:05:09 | INFO | Train Epoch: 4 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.65881 (0.60242) Boundary_loss: 0.013910 (0.013905) Loss: 0.67272 (0.61632) +2025-09-13,01:05:40 | INFO | Train Epoch: 4 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.72592 (0.62300) Boundary_loss: 0.013899 (0.013904) Loss: 0.73982 (0.63690) +2025-09-13,01:06:11 | INFO | Train Epoch: 4 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.69330 (0.63304) Boundary_loss: 0.013903 (0.013904) Loss: 0.70720 (0.64695) +2025-09-13,01:06:42 | INFO | Train Epoch: 4 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.75229 (0.64795) Boundary_loss: 0.013900 (0.013903) Loss: 0.76619 (0.66185) +2025-09-13,01:07:13 | INFO | Train Epoch: 4 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.68341 (0.65189) Boundary_loss: 0.013905 (0.013903) Loss: 0.69732 (0.66579) +2025-09-13,01:07:45 | INFO | Train Epoch: 4 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.57418 (0.64412) Boundary_loss: 0.013898 (0.013903) Loss: 0.58808 (0.65802) +2025-09-13,01:08:16 | INFO | Train Epoch: 4 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.69683 (0.64891) Boundary_loss: 0.013904 (0.013903) Loss: 0.71073 (0.66281) +2025-09-13,01:08:47 | INFO | Train Epoch: 4 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.72435 (0.65520) Boundary_loss: 0.013905 (0.013903) Loss: 0.73826 (0.66910) +2025-09-13,01:09:18 | INFO | Train Epoch: 4 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.70083 (0.65871) Boundary_loss: 0.013902 (0.013903) Loss: 0.71473 (0.67261) +2025-09-13,01:09:49 | INFO | Train Epoch: 4 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.65782 (0.65864) Boundary_loss: 0.013909 (0.013903) Loss: 0.67173 (0.67255) +2025-09-13,01:10:20 | INFO | Train Epoch: 4 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.81479 (0.66905) Boundary_loss: 0.013920 (0.013905) Loss: 0.82871 (0.68296) +2025-09-13,01:10:51 | INFO | Train Epoch: 4 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.66757 (0.66896) Boundary_loss: 0.013898 (0.013904) Loss: 0.68147 (0.68287) +2025-09-13,01:11:22 | INFO | Train Epoch: 4 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.77299 (0.67508) Boundary_loss: 0.013900 (0.013904) Loss: 0.78689 (0.68899) +2025-09-13,01:11:53 | INFO | Train Epoch: 4 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.70225 (0.67659) Boundary_loss: 0.013905 (0.013904) Loss: 0.71615 (0.69049) +2025-09-13,01:12:24 | INFO | Train Epoch: 4 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.82566 (0.68444) Boundary_loss: 0.013901 (0.013904) Loss: 0.83956 (0.69834) +2025-09-13,01:12:55 | INFO | Train Epoch: 4 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.72900 (0.68666) Boundary_loss: 0.013920 (0.013905) Loss: 0.74292 (0.70057) +2025-09-13,01:13:26 | INFO | Train Epoch: 4 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.79077 (0.69162) Boundary_loss: 0.013901 (0.013905) Loss: 0.80467 (0.70553) +2025-09-13,01:13:57 | INFO | Train Epoch: 4 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.63079 (0.68886) Boundary_loss: 0.013908 (0.013905) Loss: 0.64470 (0.70276) +2025-09-13,01:14:29 | INFO | Train Epoch: 4 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.71741 (0.69010) Boundary_loss: 0.013897 (0.013904) Loss: 0.73130 (0.70400) +2025-09-13,01:15:00 | INFO | Train Epoch: 4 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.77416 (0.69360) Boundary_loss: 0.013899 (0.013904) Loss: 0.78806 (0.70750) +2025-09-13,01:15:31 | INFO | Train Epoch: 4 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.67246 (0.69275) Boundary_loss: 0.013903 (0.013904) Loss: 0.68636 (0.70666) +2025-09-13,01:16:02 | INFO | Train Epoch: 4 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.70335 (0.69316) Boundary_loss: 0.013905 (0.013904) Loss: 0.71726 (0.70707) +2025-09-13,01:16:33 | INFO | Train Epoch: 4 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.72422 (0.69431) Boundary_loss: 0.013901 (0.013904) Loss: 0.73812 (0.70822) +2025-09-13,01:17:04 | INFO | Train Epoch: 4 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.71379 (0.69501) Boundary_loss: 0.013901 (0.013904) Loss: 0.72769 (0.70891) +2025-09-13,01:17:36 | INFO | Train Epoch: 4 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.61601 (0.69228) Boundary_loss: 0.013900 (0.013904) Loss: 0.62991 (0.70619) +2025-09-13,01:18:07 | INFO | Train Epoch: 4 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.62920 (0.69018) Boundary_loss: 0.013906 (0.013904) Loss: 0.64310 (0.70408) +2025-09-13,01:18:38 | INFO | Train Epoch: 4 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.74879 (0.69207) Boundary_loss: 0.013903 (0.013904) Loss: 0.76270 (0.70598) +2025-09-13,01:19:09 | INFO | Train Epoch: 4 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.66640 (0.69127) Boundary_loss: 0.013931 (0.013905) Loss: 0.68033 (0.70517) +2025-09-13,01:19:40 | INFO | Train Epoch: 4 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.72005 (0.69214) Boundary_loss: 0.013906 (0.013905) Loss: 0.73396 (0.70605) +2025-09-13,01:20:11 | INFO | Train Epoch: 4 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.60903 (0.68970) Boundary_loss: 0.013901 (0.013905) Loss: 0.62293 (0.70360) +2025-09-13,01:20:42 | INFO | Train Epoch: 4 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.67102 (0.68916) Boundary_loss: 0.013903 (0.013905) Loss: 0.68493 (0.70307) +2025-09-13,01:21:13 | INFO | Train Epoch: 4 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.74313 (0.69066) Boundary_loss: 0.013899 (0.013904) Loss: 0.75703 (0.70457) +2025-09-13,01:21:44 | INFO | Train Epoch: 4 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.61738 (0.68868) Boundary_loss: 0.013905 (0.013904) Loss: 0.63129 (0.70259) +2025-09-13,01:22:15 | INFO | Train Epoch: 4 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.54770 (0.68497) Boundary_loss: 0.013906 (0.013904) Loss: 0.56160 (0.69888) +2025-09-13,01:22:46 | INFO | Train Epoch: 4 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.66181 (0.68438) Boundary_loss: 0.013904 (0.013904) Loss: 0.67572 (0.69828) +2025-09-13,01:23:17 | INFO | Train Epoch: 4 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.74243 (0.68583) Boundary_loss: 0.013900 (0.013904) Loss: 0.75633 (0.69973) +2025-09-13,01:23:48 | INFO | Train Epoch: 4 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.66271 (0.68527) Boundary_loss: 0.013901 (0.013904) Loss: 0.67661 (0.69917) +2025-09-13,01:24:19 | INFO | Train Epoch: 4 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.81322 (0.68831) Boundary_loss: 0.013903 (0.013904) Loss: 0.82712 (0.70222) +2025-09-13,01:24:50 | INFO | Train Epoch: 4 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.62588 (0.68686) Boundary_loss: 0.013906 (0.013904) Loss: 0.63978 (0.70076) +2025-09-13,01:25:21 | INFO | Train Epoch: 4 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.72871 (0.68781) Boundary_loss: 0.013904 (0.013904) Loss: 0.74262 (0.70172) +2025-09-13,01:25:52 | INFO | Train Epoch: 4 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.63830 (0.68671) Boundary_loss: 0.013905 (0.013904) Loss: 0.65220 (0.70062) +2025-09-13,01:26:24 | INFO | Train Epoch: 4 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.71059 (0.68723) Boundary_loss: 0.013901 (0.013904) Loss: 0.72449 (0.70113) +2025-09-13,01:26:55 | INFO | Train Epoch: 4 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.64060 (0.68624) Boundary_loss: 0.013899 (0.013904) Loss: 0.65450 (0.70014) +2025-09-13,01:27:26 | INFO | Train Epoch: 4 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.63918 (0.68526) Boundary_loss: 0.013903 (0.013904) Loss: 0.65308 (0.69916) +2025-09-13,01:27:57 | INFO | Train Epoch: 4 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.76728 (0.68693) Boundary_loss: 0.013898 (0.013904) Loss: 0.78118 (0.70084) +2025-09-13,01:28:28 | INFO | Train Epoch: 4 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.70267 (0.68725) Boundary_loss: 0.013911 (0.013904) Loss: 0.71658 (0.70115) +2025-09-13,01:28:59 | INFO | Train Epoch: 4 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.68800 (0.68726) Boundary_loss: 0.013902 (0.013904) Loss: 0.70190 (0.70117) +2025-09-13,01:29:30 | INFO | Train Epoch: 4 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.67094 (0.68695) Boundary_loss: 0.013897 (0.013904) Loss: 0.68483 (0.70085) +2025-09-13,01:30:01 | INFO | Train Epoch: 4 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.60186 (0.68534) Boundary_loss: 0.013935 (0.013904) Loss: 0.61579 (0.69925) +2025-09-13,01:30:32 | INFO | Train Epoch: 4 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.77619 (0.68702) Boundary_loss: 0.013902 (0.013904) Loss: 0.79009 (0.70093) +2025-09-13,01:31:03 | INFO | Train Epoch: 4 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.64200 (0.68621) Boundary_loss: 0.013902 (0.013904) Loss: 0.65590 (0.70011) +2025-09-13,01:31:34 | INFO | Train Epoch: 4 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.74588 (0.68727) Boundary_loss: 0.013901 (0.013904) Loss: 0.75978 (0.70118) +2025-09-13,01:32:05 | INFO | Train Epoch: 4 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.63270 (0.68631) Boundary_loss: 0.013904 (0.013904) Loss: 0.64660 (0.70022) +2025-09-13,01:32:36 | INFO | Train Epoch: 4 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.70121 (0.68657) Boundary_loss: 0.013903 (0.013904) Loss: 0.71511 (0.70047) +2025-09-13,01:33:07 | INFO | Train Epoch: 4 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.69936 (0.68679) Boundary_loss: 0.013901 (0.013904) Loss: 0.71326 (0.70069) +2025-09-13,01:33:38 | INFO | Train Epoch: 4 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.64346 (0.68607) Boundary_loss: 0.013920 (0.013904) Loss: 0.65738 (0.69997) +2025-09-13,01:34:09 | INFO | Train Epoch: 4 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.70465 (0.68637) Boundary_loss: 0.013901 (0.013904) Loss: 0.71855 (0.70027) +2025-09-13,01:34:41 | INFO | Train Epoch: 4 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.63528 (0.68555) Boundary_loss: 0.013900 (0.013904) Loss: 0.64918 (0.69945) +2025-09-13,01:35:11 | INFO | Train Epoch: 4 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.81949 (0.68767) Boundary_loss: 0.013901 (0.013904) Loss: 0.83339 (0.70158) +2025-09-13,01:35:42 | INFO | Train Epoch: 4 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.73999 (0.68849) Boundary_loss: 0.013904 (0.013904) Loss: 0.75389 (0.70239) +2025-09-13,01:36:13 | INFO | Train Epoch: 4 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.67118 (0.68822) Boundary_loss: 0.013902 (0.013904) Loss: 0.68509 (0.70213) +2025-09-13,01:36:44 | INFO | Train Epoch: 4 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.67487 (0.68802) Boundary_loss: 0.013902 (0.013904) Loss: 0.68877 (0.70192) +2025-09-13,01:37:15 | INFO | Train Epoch: 4 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.60791 (0.68682) Boundary_loss: 0.013901 (0.013904) Loss: 0.62181 (0.70073) +2025-09-13,01:37:46 | INFO | Train Epoch: 4 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.71084 (0.68718) Boundary_loss: 0.013900 (0.013904) Loss: 0.72474 (0.70108) +2025-09-13,01:38:17 | INFO | Train Epoch: 4 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.65348 (0.68669) Boundary_loss: 0.013903 (0.013904) Loss: 0.66739 (0.70059) +2025-09-13,01:38:48 | INFO | Train Epoch: 4 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.63297 (0.68592) Boundary_loss: 0.013902 (0.013904) Loss: 0.64687 (0.69983) +2025-09-13,01:39:19 | INFO | Train Epoch: 4 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.56457 (0.68421) Boundary_loss: 0.013901 (0.013904) Loss: 0.57847 (0.69812) +2025-09-13,01:39:50 | INFO | Train Epoch: 4 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.67285 (0.68406) Boundary_loss: 0.013898 (0.013904) Loss: 0.68675 (0.69796) +2025-09-13,01:40:21 | INFO | Train Epoch: 4 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.69994 (0.68427) Boundary_loss: 0.013900 (0.013904) Loss: 0.71384 (0.69818) +2025-09-13,01:40:52 | INFO | Train Epoch: 4 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.73326 (0.68493) Boundary_loss: 0.013901 (0.013904) Loss: 0.74716 (0.69884) +2025-09-13,01:41:23 | INFO | Train Epoch: 4 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.61385 (0.68399) Boundary_loss: 0.013898 (0.013904) Loss: 0.62775 (0.69789) +2025-09-13,01:41:54 | INFO | Train Epoch: 4 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.61075 (0.68302) Boundary_loss: 0.013921 (0.013904) Loss: 0.62467 (0.69693) +2025-09-13,01:42:25 | INFO | Train Epoch: 4 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.63151 (0.68235) Boundary_loss: 0.013897 (0.013904) Loss: 0.64541 (0.69626) +2025-09-13,01:42:57 | INFO | Train Epoch: 4 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.86145 (0.68465) Boundary_loss: 0.013898 (0.013904) Loss: 0.87535 (0.69855) +2025-09-13,01:43:28 | INFO | Train Epoch: 4 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.73349 (0.68527) Boundary_loss: 0.013902 (0.013904) Loss: 0.74739 (0.69917) +2025-09-13,01:43:59 | INFO | Train Epoch: 4 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.74701 (0.68604) Boundary_loss: 0.013903 (0.013904) Loss: 0.76091 (0.69994) +2025-09-13,01:44:30 | INFO | Train Epoch: 4 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.69544 (0.68616) Boundary_loss: 0.013901 (0.013904) Loss: 0.70934 (0.70006) +2025-09-13,01:45:01 | INFO | Train Epoch: 4 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.68046 (0.68609) Boundary_loss: 0.013921 (0.013904) Loss: 0.69438 (0.69999) +2025-09-13,01:45:32 | INFO | Train Epoch: 4 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.62400 (0.68534) Boundary_loss: 0.013900 (0.013904) Loss: 0.63790 (0.69924) +2025-09-13,01:46:04 | INFO | Train Epoch: 4 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.67695 (0.68524) Boundary_loss: 0.013905 (0.013904) Loss: 0.69085 (0.69914) +2025-09-13,01:46:35 | INFO | Train Epoch: 4 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.78591 (0.68642) Boundary_loss: 0.013903 (0.013904) Loss: 0.79982 (0.70033) +2025-09-13,01:47:06 | INFO | Train Epoch: 4 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.71216 (0.68672) Boundary_loss: 0.013905 (0.013904) Loss: 0.72607 (0.70063) +2025-09-13,01:47:37 | INFO | Train Epoch: 4 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.72169 (0.68712) Boundary_loss: 0.013902 (0.013904) Loss: 0.73559 (0.70103) +2025-09-13,01:48:08 | INFO | Train Epoch: 4 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.74794 (0.68782) Boundary_loss: 0.013898 (0.013904) Loss: 0.76184 (0.70172) +2025-09-13,01:48:39 | INFO | Train Epoch: 4 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.59476 (0.68677) Boundary_loss: 0.013903 (0.013904) Loss: 0.60867 (0.70067) +2025-09-13,01:49:10 | INFO | Train Epoch: 4 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.66815 (0.68656) Boundary_loss: 0.013902 (0.013904) Loss: 0.68205 (0.70047) +2025-09-13,01:49:41 | INFO | Train Epoch: 4 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.81933 (0.68802) Boundary_loss: 0.013902 (0.013904) Loss: 0.83323 (0.70193) +2025-09-13,01:50:12 | INFO | Train Epoch: 4 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.68553 (0.68800) Boundary_loss: 0.013898 (0.013904) Loss: 0.69942 (0.70190) +2025-09-13,01:50:43 | INFO | Train Epoch: 4 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.67482 (0.68785) Boundary_loss: 0.013900 (0.013904) Loss: 0.68872 (0.70176) +2025-09-13,01:51:14 | INFO | Train Epoch: 4 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.67004 (0.68766) Boundary_loss: 0.013901 (0.013904) Loss: 0.68394 (0.70157) +2025-09-13,01:51:45 | INFO | Train Epoch: 4 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.72909 (0.68810) Boundary_loss: 0.013899 (0.013904) Loss: 0.74299 (0.70200) +2025-09-13,01:52:16 | INFO | Train Epoch: 4 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.77936 (0.68905) Boundary_loss: 0.013898 (0.013904) Loss: 0.79325 (0.70295) +2025-09-13,01:52:47 | INFO | Train Epoch: 4 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.76562 (0.68984) Boundary_loss: 0.013902 (0.013904) Loss: 0.77952 (0.70374) +2025-09-13,01:53:18 | INFO | Train Epoch: 4 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.74636 (0.69042) Boundary_loss: 0.013943 (0.013904) Loss: 0.76030 (0.70432) +2025-09-13,01:53:49 | INFO | Train Epoch: 4 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.62042 (0.68971) Boundary_loss: 0.013902 (0.013904) Loss: 0.63432 (0.70361) +2025-09-13,01:54:20 | INFO | Train Epoch: 4 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.72070 (0.69002) Boundary_loss: 0.013898 (0.013904) Loss: 0.73460 (0.70392) +2025-09-13,01:54:51 | INFO | Train Epoch: 4 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.71003 (0.69022) Boundary_loss: 0.013899 (0.013904) Loss: 0.72393 (0.70412) +2025-09-13,01:55:22 | INFO | Train Epoch: 4 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.51886 (0.68854) Boundary_loss: 0.013902 (0.013904) Loss: 0.53276 (0.70244) +2025-09-13,01:55:53 | INFO | Train Epoch: 4 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.76101 (0.68924) Boundary_loss: 0.013901 (0.013904) Loss: 0.77491 (0.70315) +2025-09-13,01:56:24 | INFO | Train Epoch: 4 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.67594 (0.68911) Boundary_loss: 0.013912 (0.013904) Loss: 0.68986 (0.70302) +2025-09-13,01:56:55 | INFO | Train Epoch: 4 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.62828 (0.68853) Boundary_loss: 0.013903 (0.013904) Loss: 0.64218 (0.70244) +2025-09-13,01:57:26 | INFO | Train Epoch: 4 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.67688 (0.68842) Boundary_loss: 0.013905 (0.013904) Loss: 0.69079 (0.70233) +2025-09-13,01:57:57 | INFO | Train Epoch: 4 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.58009 (0.68741) Boundary_loss: 0.013902 (0.013904) Loss: 0.59399 (0.70132) +2025-09-13,01:58:28 | INFO | Train Epoch: 4 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.77100 (0.68819) Boundary_loss: 0.013910 (0.013904) Loss: 0.78491 (0.70209) +2025-09-13,01:58:59 | INFO | Train Epoch: 4 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.64802 (0.68782) Boundary_loss: 0.013906 (0.013904) Loss: 0.66193 (0.70172) +2025-09-13,01:59:30 | INFO | Train Epoch: 4 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.66777 (0.68764) Boundary_loss: 0.013900 (0.013904) Loss: 0.68167 (0.70154) +2025-09-13,02:00:01 | INFO | Train Epoch: 4 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.58172 (0.68668) Boundary_loss: 0.013901 (0.013904) Loss: 0.59562 (0.70058) +2025-09-13,02:00:32 | INFO | Train Epoch: 4 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.66289 (0.68647) Boundary_loss: 0.013901 (0.013904) Loss: 0.67679 (0.70037) +2025-09-13,02:01:03 | INFO | Train Epoch: 4 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.77486 (0.68725) Boundary_loss: 0.013900 (0.013904) Loss: 0.78876 (0.70115) +2025-09-13,02:01:34 | INFO | Train Epoch: 4 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.67831 (0.68717) Boundary_loss: 0.013905 (0.013904) Loss: 0.69222 (0.70108) +2025-09-13,02:02:05 | INFO | Train Epoch: 4 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.69504 (0.68724) Boundary_loss: 0.013900 (0.013904) Loss: 0.70894 (0.70114) +2025-09-13,02:02:36 | INFO | Train Epoch: 4 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.77763 (0.68802) Boundary_loss: 0.013899 (0.013904) Loss: 0.79153 (0.70192) +2025-09-13,02:03:07 | INFO | Train Epoch: 4 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.67661 (0.68792) Boundary_loss: 0.013903 (0.013904) Loss: 0.69052 (0.70183) +2025-09-13,02:03:39 | INFO | Train Epoch: 4 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.61949 (0.68734) Boundary_loss: 0.013904 (0.013904) Loss: 0.63339 (0.70125) +2025-09-13,02:04:10 | INFO | Train Epoch: 4 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.73240 (0.68772) Boundary_loss: 0.013903 (0.013904) Loss: 0.74630 (0.70162) +2025-09-13,02:04:41 | INFO | Train Epoch: 4 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.70813 (0.68789) Boundary_loss: 0.013906 (0.013904) Loss: 0.72204 (0.70179) +2025-09-13,02:05:11 | INFO | Train Epoch: 4 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.80177 (0.68883) Boundary_loss: 0.013898 (0.013904) Loss: 0.81567 (0.70274) +2025-09-13,02:05:42 | INFO | Train Epoch: 4 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.62281 (0.68829) Boundary_loss: 0.013901 (0.013904) Loss: 0.63671 (0.70219) +2025-09-13,02:06:13 | INFO | Train Epoch: 4 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.69633 (0.68836) Boundary_loss: 0.013899 (0.013904) Loss: 0.71023 (0.70226) +2025-09-13,02:06:44 | INFO | Train Epoch: 4 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.71213 (0.68855) Boundary_loss: 0.013901 (0.013904) Loss: 0.72603 (0.70245) +2025-09-13,02:07:15 | INFO | Train Epoch: 4 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.68357 (0.68851) Boundary_loss: 0.013922 (0.013904) Loss: 0.69750 (0.70241) +2025-09-13,02:07:46 | INFO | Train Epoch: 4 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.69755 (0.68858) Boundary_loss: 0.013900 (0.013904) Loss: 0.71145 (0.70248) +2025-09-13,02:08:17 | INFO | Train Epoch: 4 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.62581 (0.68809) Boundary_loss: 0.013909 (0.013904) Loss: 0.63972 (0.70199) +2025-09-13,02:08:48 | INFO | Train Epoch: 4 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59749 (0.68738) Boundary_loss: 0.013896 (0.013904) Loss: 0.61139 (0.70128) +2025-09-13,02:09:19 | INFO | Train Epoch: 4 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.66466 (0.68720) Boundary_loss: 0.013900 (0.013904) Loss: 0.67856 (0.70111) +2025-09-13,02:09:50 | INFO | Train Epoch: 4 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.64124 (0.68685) Boundary_loss: 0.013900 (0.013904) Loss: 0.65514 (0.70075) +2025-09-13,02:10:20 | INFO | Train Epoch: 4 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.65882 (0.68663) Boundary_loss: 0.013908 (0.013904) Loss: 0.67272 (0.70054) +2025-09-13,02:10:51 | INFO | Train Epoch: 4 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.61790 (0.68611) Boundary_loss: 0.013901 (0.013904) Loss: 0.63180 (0.70002) +2025-09-13,02:11:22 | INFO | Train Epoch: 4 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.65294 (0.68586) Boundary_loss: 0.013897 (0.013904) Loss: 0.66684 (0.69977) +2025-09-13,02:11:53 | INFO | Train Epoch: 4 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.68606 (0.68587) Boundary_loss: 0.013905 (0.013904) Loss: 0.69997 (0.69977) +2025-09-13,02:12:24 | INFO | Train Epoch: 4 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.74705 (0.68632) Boundary_loss: 0.013899 (0.013904) Loss: 0.76095 (0.70022) +2025-09-13,02:12:55 | INFO | Train Epoch: 4 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.69813 (0.68641) Boundary_loss: 0.013900 (0.013904) Loss: 0.71203 (0.70031) +2025-09-13,02:13:26 | INFO | Train Epoch: 4 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.72185 (0.68666) Boundary_loss: 0.013913 (0.013904) Loss: 0.73576 (0.70057) +2025-09-13,02:13:57 | INFO | Train Epoch: 4 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.64042 (0.68633) Boundary_loss: 0.013897 (0.013904) Loss: 0.65432 (0.70023) +2025-09-13,02:14:28 | INFO | Train Epoch: 4 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.62196 (0.68587) Boundary_loss: 0.013899 (0.013904) Loss: 0.63586 (0.69977) +2025-09-13,02:14:58 | INFO | Train Epoch: 4 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.69028 (0.68590) Boundary_loss: 0.013899 (0.013904) Loss: 0.70418 (0.69980) +2025-09-13,02:15:29 | INFO | Train Epoch: 4 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.63515 (0.68554) Boundary_loss: 0.013903 (0.013904) Loss: 0.64905 (0.69944) +2025-09-13,02:16:00 | INFO | Train Epoch: 4 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.68867 (0.68556) Boundary_loss: 0.013909 (0.013904) Loss: 0.70257 (0.69946) +2025-09-13,02:16:31 | INFO | Train Epoch: 4 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.59227 (0.68491) Boundary_loss: 0.013898 (0.013904) Loss: 0.60617 (0.69881) +2025-09-13,02:17:02 | INFO | Train Epoch: 4 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.51683 (0.68374) Boundary_loss: 0.013899 (0.013903) Loss: 0.53072 (0.69764) +2025-09-13,02:17:33 | INFO | Train Epoch: 4 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.68777 (0.68377) Boundary_loss: 0.013905 (0.013904) Loss: 0.70167 (0.69767) +2025-09-13,02:18:04 | INFO | Train Epoch: 4 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.60375 (0.68322) Boundary_loss: 0.013908 (0.013904) Loss: 0.61766 (0.69712) +2025-09-13,02:18:34 | INFO | Train Epoch: 4 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.59016 (0.68259) Boundary_loss: 0.013900 (0.013904) Loss: 0.60406 (0.69649) +2025-09-13,02:19:05 | INFO | Train Epoch: 4 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.60445 (0.68206) Boundary_loss: 0.013903 (0.013904) Loss: 0.61836 (0.69596) +2025-09-13,02:19:36 | INFO | Train Epoch: 4 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.60945 (0.68157) Boundary_loss: 0.013901 (0.013903) Loss: 0.62335 (0.69548) +2025-09-13,02:20:07 | INFO | Train Epoch: 4 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.70655 (0.68174) Boundary_loss: 0.013898 (0.013903) Loss: 0.72045 (0.69564) +2025-09-13,02:20:38 | INFO | Train Epoch: 4 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.59740 (0.68118) Boundary_loss: 0.013900 (0.013903) Loss: 0.61130 (0.69508) +2025-09-13,02:21:09 | INFO | Train Epoch: 4 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.77876 (0.68182) Boundary_loss: 0.013923 (0.013904) Loss: 0.79268 (0.69573) +2025-09-13,02:21:40 | INFO | Train Epoch: 4 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.64104 (0.68156) Boundary_loss: 0.013903 (0.013904) Loss: 0.65495 (0.69546) +2025-09-13,02:22:11 | INFO | Train Epoch: 4 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.67781 (0.68153) Boundary_loss: 0.013905 (0.013904) Loss: 0.69171 (0.69543) +2025-09-13,02:22:42 | INFO | Train Epoch: 4 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.67503 (0.68149) Boundary_loss: 0.013897 (0.013904) Loss: 0.68893 (0.69539) +2025-09-13,02:23:13 | INFO | Train Epoch: 4 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.61327 (0.68105) Boundary_loss: 0.013902 (0.013904) Loss: 0.62717 (0.69496) +2025-09-13,02:23:44 | INFO | Train Epoch: 4 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.63187 (0.68074) Boundary_loss: 0.013916 (0.013904) Loss: 0.64579 (0.69464) +2025-09-13,02:24:15 | INFO | Train Epoch: 4 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.60817 (0.68028) Boundary_loss: 0.013900 (0.013904) Loss: 0.62207 (0.69418) +2025-09-13,02:24:46 | INFO | Train Epoch: 4 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.66158 (0.68016) Boundary_loss: 0.013900 (0.013904) Loss: 0.67548 (0.69407) +2025-09-13,02:25:17 | INFO | Train Epoch: 4 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.62579 (0.67982) Boundary_loss: 0.013899 (0.013904) Loss: 0.63968 (0.69373) +2025-09-13,02:25:48 | INFO | Train Epoch: 4 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.59423 (0.67929) Boundary_loss: 0.013898 (0.013903) Loss: 0.60813 (0.69319) +2025-09-13,02:26:19 | INFO | Train Epoch: 4 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.67578 (0.67927) Boundary_loss: 0.013900 (0.013903) Loss: 0.68968 (0.69317) +2025-09-13,02:26:50 | INFO | Train Epoch: 4 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.73360 (0.67960) Boundary_loss: 0.013898 (0.013903) Loss: 0.74750 (0.69351) +2025-09-13,02:27:21 | INFO | Train Epoch: 4 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.66808 (0.67953) Boundary_loss: 0.013900 (0.013903) Loss: 0.68198 (0.69343) +2025-09-13,02:27:52 | INFO | Train Epoch: 4 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.73974 (0.67990) Boundary_loss: 0.013900 (0.013903) Loss: 0.75364 (0.69380) +2025-09-13,02:28:23 | INFO | Train Epoch: 4 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.69747 (0.68000) Boundary_loss: 0.013905 (0.013903) Loss: 0.71138 (0.69391) +2025-09-13,02:28:54 | INFO | Train Epoch: 4 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.70577 (0.68016) Boundary_loss: 0.013899 (0.013903) Loss: 0.71967 (0.69406) +2025-09-13,02:29:25 | INFO | Train Epoch: 4 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.71277 (0.68035) Boundary_loss: 0.013898 (0.013903) Loss: 0.72667 (0.69425) +2025-09-13,02:29:56 | INFO | Train Epoch: 4 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.60674 (0.67992) Boundary_loss: 0.013897 (0.013903) Loss: 0.62063 (0.69382) +2025-09-13,02:30:27 | INFO | Train Epoch: 4 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.78672 (0.68054) Boundary_loss: 0.013898 (0.013903) Loss: 0.80061 (0.69445) +2025-09-13,02:30:58 | INFO | Train Epoch: 4 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.68057 (0.68054) Boundary_loss: 0.013900 (0.013903) Loss: 0.69447 (0.69445) +2025-09-13,02:31:29 | INFO | Train Epoch: 4 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.74260 (0.68090) Boundary_loss: 0.013900 (0.013903) Loss: 0.75650 (0.69481) +2025-09-13,02:32:00 | INFO | Train Epoch: 4 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.58689 (0.68036) Boundary_loss: 0.013899 (0.013903) Loss: 0.60078 (0.69426) +2025-09-13,02:32:31 | INFO | Train Epoch: 4 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.67720 (0.68034) Boundary_loss: 0.013901 (0.013903) Loss: 0.69110 (0.69425) +2025-09-13,02:33:02 | INFO | Train Epoch: 4 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.73522 (0.68066) Boundary_loss: 0.013898 (0.013903) Loss: 0.74912 (0.69456) +2025-09-13,02:33:33 | INFO | Train Epoch: 4 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.71623 (0.68086) Boundary_loss: 0.013899 (0.013903) Loss: 0.73013 (0.69476) +2025-09-13,02:34:04 | INFO | Train Epoch: 4 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.70971 (0.68102) Boundary_loss: 0.013907 (0.013903) Loss: 0.72362 (0.69492) +2025-09-13,02:34:35 | INFO | Train Epoch: 4 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.62039 (0.68068) Boundary_loss: 0.013952 (0.013903) Loss: 0.63434 (0.69458) +2025-09-13,02:35:05 | INFO | Train Epoch: 4 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.60951 (0.68028) Boundary_loss: 0.013909 (0.013903) Loss: 0.62342 (0.69419) +2025-09-13,02:35:37 | INFO | Train Epoch: 4 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.57282 (0.67969) Boundary_loss: 0.013898 (0.013903) Loss: 0.58672 (0.69359) +2025-09-13,02:36:08 | INFO | Train Epoch: 4 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.69353 (0.67976) Boundary_loss: 0.013923 (0.013904) Loss: 0.70746 (0.69367) +2025-09-13,02:36:39 | INFO | Train Epoch: 4 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.72611 (0.68002) Boundary_loss: 0.013901 (0.013904) Loss: 0.74001 (0.69392) +2025-09-13,02:37:10 | INFO | Train Epoch: 4 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.60883 (0.67963) Boundary_loss: 0.013899 (0.013904) Loss: 0.62273 (0.69353) +2025-09-13,02:37:41 | INFO | Train Epoch: 4 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.73864 (0.67995) Boundary_loss: 0.013899 (0.013903) Loss: 0.75254 (0.69385) +2025-09-13,02:38:11 | INFO | Train Epoch: 4 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.69563 (0.68003) Boundary_loss: 0.013900 (0.013903) Loss: 0.70953 (0.69394) +2025-09-13,02:38:42 | INFO | Train Epoch: 4 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.69716 (0.68013) Boundary_loss: 0.013900 (0.013903) Loss: 0.71106 (0.69403) +2025-09-13,02:39:13 | INFO | Train Epoch: 4 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.64208 (0.67992) Boundary_loss: 0.013900 (0.013903) Loss: 0.65598 (0.69383) +2025-09-13,02:39:44 | INFO | Train Epoch: 4 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.64502 (0.67974) Boundary_loss: 0.013901 (0.013903) Loss: 0.65892 (0.69364) +2025-09-13,02:40:16 | INFO | Train Epoch: 4 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.68868 (0.67978) Boundary_loss: 0.013898 (0.013903) Loss: 0.70258 (0.69369) +2025-09-13,02:40:47 | INFO | Train Epoch: 4 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.63989 (0.67957) Boundary_loss: 0.013898 (0.013903) Loss: 0.65379 (0.69348) +2025-09-13,02:41:18 | INFO | Train Epoch: 4 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.61104 (0.67922) Boundary_loss: 0.013898 (0.013903) Loss: 0.62494 (0.69312) +2025-09-13,02:41:48 | INFO | Train Epoch: 4 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.69219 (0.67928) Boundary_loss: 0.013901 (0.013903) Loss: 0.70609 (0.69319) +2025-09-13,02:42:19 | INFO | Train Epoch: 4 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.86778 (0.68026) Boundary_loss: 0.013904 (0.013903) Loss: 0.88168 (0.69416) +2025-09-13,02:42:50 | INFO | Train Epoch: 4 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.56838 (0.67968) Boundary_loss: 0.013899 (0.013903) Loss: 0.58228 (0.69359) +2025-09-13,02:43:21 | INFO | Train Epoch: 4 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.77862 (0.68019) Boundary_loss: 0.013904 (0.013903) Loss: 0.79252 (0.69409) +2025-09-13,02:43:52 | INFO | Train Epoch: 4 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.81598 (0.68088) Boundary_loss: 0.013898 (0.013903) Loss: 0.82988 (0.69479) +2025-09-13,02:44:23 | INFO | Train Epoch: 4 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.68299 (0.68089) Boundary_loss: 0.013900 (0.013903) Loss: 0.69689 (0.69480) +2025-09-13,02:44:54 | INFO | Train Epoch: 4 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.71213 (0.68105) Boundary_loss: 0.013903 (0.013903) Loss: 0.72604 (0.69495) +2025-09-13,02:45:25 | INFO | Train Epoch: 4 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.66067 (0.68095) Boundary_loss: 0.013898 (0.013903) Loss: 0.67457 (0.69485) +2025-09-13,02:45:56 | INFO | Train Epoch: 4 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.77830 (0.68144) Boundary_loss: 0.013903 (0.013903) Loss: 0.79220 (0.69534) +2025-09-13,02:46:28 | INFO | Train Epoch: 4 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.58665 (0.68096) Boundary_loss: 0.013898 (0.013903) Loss: 0.60055 (0.69487) +2025-09-13,02:46:59 | INFO | Train Epoch: 4 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.63148 (0.68072) Boundary_loss: 0.013898 (0.013903) Loss: 0.64538 (0.69462) +2025-09-13,02:47:30 | INFO | Train Epoch: 4 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.77496 (0.68118) Boundary_loss: 0.013901 (0.013903) Loss: 0.78886 (0.69509) +2025-09-13,02:48:01 | INFO | Train Epoch: 4 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.64131 (0.68099) Boundary_loss: 0.013900 (0.013903) Loss: 0.65521 (0.69489) +2025-09-13,02:48:32 | INFO | Train Epoch: 4 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.59956 (0.68059) Boundary_loss: 0.013900 (0.013903) Loss: 0.61346 (0.69449) +2025-09-13,02:49:03 | INFO | Train Epoch: 4 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.68114 (0.68059) Boundary_loss: 0.013898 (0.013903) Loss: 0.69504 (0.69450) +2025-09-13,02:49:34 | INFO | Train Epoch: 4 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.76759 (0.68101) Boundary_loss: 0.013911 (0.013903) Loss: 0.78150 (0.69492) +2025-09-13,02:50:05 | INFO | Train Epoch: 4 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.64042 (0.68082) Boundary_loss: 0.013900 (0.013903) Loss: 0.65432 (0.69472) +2025-09-13,02:50:36 | INFO | Train Epoch: 4 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.66331 (0.68073) Boundary_loss: 0.013904 (0.013903) Loss: 0.67721 (0.69464) +2025-09-13,02:51:07 | INFO | Train Epoch: 4 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.57568 (0.68023) Boundary_loss: 0.013898 (0.013903) Loss: 0.58957 (0.69414) +2025-09-13,02:51:38 | INFO | Train Epoch: 4 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.65887 (0.68013) Boundary_loss: 0.013900 (0.013903) Loss: 0.67277 (0.69404) +2025-09-13,02:52:09 | INFO | Train Epoch: 4 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.62403 (0.67987) Boundary_loss: 0.013899 (0.013903) Loss: 0.63793 (0.69377) +2025-09-13,02:52:40 | INFO | Train Epoch: 4 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.67340 (0.67984) Boundary_loss: 0.013905 (0.013903) Loss: 0.68731 (0.69374) +2025-09-13,02:53:11 | INFO | Train Epoch: 4 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.75304 (0.68018) Boundary_loss: 0.013900 (0.013903) Loss: 0.76694 (0.69408) +2025-09-13,02:53:42 | INFO | Train Epoch: 4 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.70192 (0.68028) Boundary_loss: 0.013896 (0.013903) Loss: 0.71582 (0.69418) +2025-09-13,02:54:13 | INFO | Train Epoch: 4 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.68132 (0.68029) Boundary_loss: 0.013899 (0.013903) Loss: 0.69522 (0.69419) +2025-09-13,02:54:44 | INFO | Train Epoch: 4 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.63438 (0.68007) Boundary_loss: 0.013901 (0.013903) Loss: 0.64828 (0.69398) +2025-09-13,02:55:14 | INFO | Train Epoch: 4 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.62804 (0.67984) Boundary_loss: 0.013896 (0.013903) Loss: 0.64194 (0.69374) +2025-09-13,02:55:45 | INFO | Train Epoch: 4 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.63329 (0.67962) Boundary_loss: 0.013897 (0.013903) Loss: 0.64718 (0.69353) +2025-09-13,02:56:17 | INFO | Train Epoch: 4 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.65638 (0.67952) Boundary_loss: 0.013897 (0.013903) Loss: 0.67027 (0.69342) +2025-09-13,02:56:47 | INFO | Train Epoch: 4 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.67184 (0.67948) Boundary_loss: 0.013904 (0.013903) Loss: 0.68575 (0.69339) +2025-09-13,02:57:18 | INFO | Train Epoch: 4 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.59631 (0.67911) Boundary_loss: 0.013902 (0.013903) Loss: 0.61022 (0.69301) +2025-09-13,02:57:49 | INFO | Train Epoch: 4 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.58068 (0.67867) Boundary_loss: 0.013899 (0.013903) Loss: 0.59458 (0.69257) +2025-09-13,02:58:20 | INFO | Train Epoch: 4 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.64487 (0.67852) Boundary_loss: 0.013901 (0.013903) Loss: 0.65877 (0.69242) +2025-09-13,02:58:51 | INFO | Train Epoch: 4 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.70099 (0.67862) Boundary_loss: 0.013898 (0.013903) Loss: 0.71489 (0.69252) +2025-09-13,02:59:22 | INFO | Train Epoch: 4 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.67012 (0.67858) Boundary_loss: 0.013898 (0.013903) Loss: 0.68402 (0.69248) +2025-09-13,02:59:53 | INFO | Train Epoch: 4 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.78408 (0.67904) Boundary_loss: 0.013922 (0.013903) Loss: 0.79800 (0.69295) +2025-09-13,03:00:24 | INFO | Train Epoch: 4 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.67711 (0.67903) Boundary_loss: 0.013901 (0.013903) Loss: 0.69101 (0.69294) +2025-09-13,03:00:55 | INFO | Train Epoch: 4 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.70338 (0.67914) Boundary_loss: 0.013898 (0.013903) Loss: 0.71728 (0.69304) +2025-09-13,03:01:26 | INFO | Train Epoch: 4 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.72309 (0.67933) Boundary_loss: 0.013902 (0.013903) Loss: 0.73699 (0.69324) +2025-09-13,03:01:57 | INFO | Train Epoch: 4 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.65154 (0.67921) Boundary_loss: 0.013901 (0.013903) Loss: 0.66544 (0.69311) +2025-09-13,03:02:28 | INFO | Train Epoch: 4 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.74496 (0.67950) Boundary_loss: 0.013901 (0.013903) Loss: 0.75887 (0.69340) +2025-09-13,03:02:59 | INFO | Train Epoch: 4 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.58526 (0.67909) Boundary_loss: 0.013900 (0.013903) Loss: 0.59916 (0.69299) +2025-09-13,03:03:30 | INFO | Train Epoch: 4 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.53552 (0.67848) Boundary_loss: 0.013902 (0.013903) Loss: 0.54943 (0.69238) +2025-09-13,03:04:01 | INFO | Train Epoch: 4 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59972 (0.67814) Boundary_loss: 0.013902 (0.013903) Loss: 0.61362 (0.69205) +2025-09-13,03:04:32 | INFO | Train Epoch: 4 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.70968 (0.67828) Boundary_loss: 0.013900 (0.013903) Loss: 0.72358 (0.69218) +2025-09-13,03:05:03 | INFO | Train Epoch: 4 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.70049 (0.67837) Boundary_loss: 0.013901 (0.013903) Loss: 0.71439 (0.69227) +2025-09-13,03:05:34 | INFO | Train Epoch: 4 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.57724 (0.67794) Boundary_loss: 0.013899 (0.013903) Loss: 0.59114 (0.69185) +2025-09-13,03:06:05 | INFO | Train Epoch: 4 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.71351 (0.67809) Boundary_loss: 0.013910 (0.013903) Loss: 0.72742 (0.69200) +2025-09-13,03:06:36 | INFO | Train Epoch: 4 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.78143 (0.67852) Boundary_loss: 0.013907 (0.013903) Loss: 0.79533 (0.69243) +2025-09-13,03:07:07 | INFO | Train Epoch: 4 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.57131 (0.67808) Boundary_loss: 0.013908 (0.013903) Loss: 0.58522 (0.69198) +2025-09-13,03:07:38 | INFO | Train Epoch: 4 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.75228 (0.67839) Boundary_loss: 0.013900 (0.013903) Loss: 0.76618 (0.69229) +2025-09-13,03:08:09 | INFO | Train Epoch: 4 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.67254 (0.67836) Boundary_loss: 0.013900 (0.013903) Loss: 0.68644 (0.69226) +2025-09-13,03:08:40 | INFO | Train Epoch: 4 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.62680 (0.67815) Boundary_loss: 0.013897 (0.013903) Loss: 0.64070 (0.69205) +2025-09-13,03:09:11 | INFO | Train Epoch: 4 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.65049 (0.67804) Boundary_loss: 0.013903 (0.013903) Loss: 0.66440 (0.69194) +2025-09-13,03:09:42 | INFO | Train Epoch: 4 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.70214 (0.67814) Boundary_loss: 0.013898 (0.013903) Loss: 0.71604 (0.69204) +2025-09-13,03:10:13 | INFO | Train Epoch: 4 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.60281 (0.67783) Boundary_loss: 0.013897 (0.013903) Loss: 0.61671 (0.69173) +2025-09-13,03:10:44 | INFO | Train Epoch: 4 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.74571 (0.67810) Boundary_loss: 0.013905 (0.013903) Loss: 0.75962 (0.69201) +2025-09-13,03:11:15 | INFO | Train Epoch: 4 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.68252 (0.67812) Boundary_loss: 0.013901 (0.013903) Loss: 0.69642 (0.69202) +2025-09-13,03:11:46 | INFO | Train Epoch: 4 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.58009 (0.67773) Boundary_loss: 0.013899 (0.013903) Loss: 0.59399 (0.69163) +2025-09-13,03:12:17 | INFO | Train Epoch: 4 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.54662 (0.67721) Boundary_loss: 0.013899 (0.013903) Loss: 0.56052 (0.69111) +2025-09-13,03:12:48 | INFO | Train Epoch: 4 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.62100 (0.67698) Boundary_loss: 0.013911 (0.013903) Loss: 0.63491 (0.69089) +2025-09-13,03:13:19 | INFO | Train Epoch: 4 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.71679 (0.67714) Boundary_loss: 0.013898 (0.013903) Loss: 0.73069 (0.69104) +2025-09-13,03:13:50 | INFO | Train Epoch: 4 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.71721 (0.67730) Boundary_loss: 0.013901 (0.013903) Loss: 0.73111 (0.69120) +2025-09-13,03:14:20 | INFO | Train Epoch: 4 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.63720 (0.67714) Boundary_loss: 0.013900 (0.013903) Loss: 0.65110 (0.69105) +2025-09-13,03:14:51 | INFO | Train Epoch: 4 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.64196 (0.67700) Boundary_loss: 0.013901 (0.013903) Loss: 0.65586 (0.69091) +2025-09-13,03:15:22 | INFO | Train Epoch: 4 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.70164 (0.67710) Boundary_loss: 0.013898 (0.013903) Loss: 0.71554 (0.69100) +2025-09-13,03:15:53 | INFO | Train Epoch: 4 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.66526 (0.67705) Boundary_loss: 0.013898 (0.013903) Loss: 0.67916 (0.69096) +2025-09-13,03:16:24 | INFO | Train Epoch: 4 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.51096 (0.67641) Boundary_loss: 0.013899 (0.013903) Loss: 0.52486 (0.69032) +2025-09-13,03:16:55 | INFO | Train Epoch: 4 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.69427 (0.67648) Boundary_loss: 0.013899 (0.013903) Loss: 0.70817 (0.69039) +2025-09-13,03:17:26 | INFO | Train Epoch: 4 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.63292 (0.67632) Boundary_loss: 0.013899 (0.013903) Loss: 0.64682 (0.69022) +2025-09-13,03:17:57 | INFO | Train Epoch: 4 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.61344 (0.67608) Boundary_loss: 0.013899 (0.013903) Loss: 0.62734 (0.68998) +2025-09-13,03:18:28 | INFO | Train Epoch: 4 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.67720 (0.67608) Boundary_loss: 0.013902 (0.013903) Loss: 0.69110 (0.68998) +2025-09-13,03:18:59 | INFO | Train Epoch: 4 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.64087 (0.67595) Boundary_loss: 0.013897 (0.013903) Loss: 0.65476 (0.68985) +2025-09-13,03:19:30 | INFO | Train Epoch: 4 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.72333 (0.67613) Boundary_loss: 0.013898 (0.013903) Loss: 0.73722 (0.69003) +2025-09-13,03:20:01 | INFO | Train Epoch: 4 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.63515 (0.67597) Boundary_loss: 0.013906 (0.013903) Loss: 0.64906 (0.68987) +2025-09-13,03:20:31 | INFO | Train Epoch: 4 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.56742 (0.67556) Boundary_loss: 0.013899 (0.013903) Loss: 0.58132 (0.68947) +2025-09-13,03:21:02 | INFO | Train Epoch: 4 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.56962 (0.67517) Boundary_loss: 0.013896 (0.013903) Loss: 0.58352 (0.68907) +2025-09-13,03:21:33 | INFO | Train Epoch: 4 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.80976 (0.67567) Boundary_loss: 0.013899 (0.013903) Loss: 0.82366 (0.68957) +2025-09-13,03:22:04 | INFO | Train Epoch: 4 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.55315 (0.67522) Boundary_loss: 0.013899 (0.013903) Loss: 0.56705 (0.68912) +2025-09-13,03:22:35 | INFO | Train Epoch: 4 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.70037 (0.67531) Boundary_loss: 0.013905 (0.013903) Loss: 0.71428 (0.68921) +2025-09-13,03:23:06 | INFO | Train Epoch: 4 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.62307 (0.67512) Boundary_loss: 0.013899 (0.013903) Loss: 0.63697 (0.68902) +2025-09-13,03:23:37 | INFO | Train Epoch: 4 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.66303 (0.67507) Boundary_loss: 0.013902 (0.013903) Loss: 0.67694 (0.68897) +2025-09-13,03:24:07 | INFO | Train Epoch: 4 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.72796 (0.67527) Boundary_loss: 0.013900 (0.013903) Loss: 0.74186 (0.68917) +2025-09-13,03:24:38 | INFO | Train Epoch: 4 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.66552 (0.67523) Boundary_loss: 0.013909 (0.013903) Loss: 0.67943 (0.68913) +2025-09-13,03:25:09 | INFO | Train Epoch: 4 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.70633 (0.67534) Boundary_loss: 0.013898 (0.013903) Loss: 0.72023 (0.68925) +2025-09-13,03:25:40 | INFO | Train Epoch: 4 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.68551 (0.67538) Boundary_loss: 0.013899 (0.013903) Loss: 0.69941 (0.68928) +2025-09-13,03:26:10 | INFO | Train Epoch: 4 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.72257 (0.67555) Boundary_loss: 0.013898 (0.013903) Loss: 0.73647 (0.68945) +2025-09-13,03:26:41 | INFO | Train Epoch: 4 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.72711 (0.67573) Boundary_loss: 0.013900 (0.013903) Loss: 0.74101 (0.68964) +2025-09-13,03:27:12 | INFO | Train Epoch: 4 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.72899 (0.67592) Boundary_loss: 0.013899 (0.013903) Loss: 0.74289 (0.68983) +2025-09-13,03:27:43 | INFO | Train Epoch: 4 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.68263 (0.67595) Boundary_loss: 0.013900 (0.013903) Loss: 0.69653 (0.68985) +2025-09-13,03:28:14 | INFO | Train Epoch: 4 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.59029 (0.67564) Boundary_loss: 0.013900 (0.013903) Loss: 0.60419 (0.68955) +2025-09-13,03:28:45 | INFO | Train Epoch: 4 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.63294 (0.67549) Boundary_loss: 0.013904 (0.013903) Loss: 0.64684 (0.68940) +2025-09-13,03:29:16 | INFO | Train Epoch: 4 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.51494 (0.67493) Boundary_loss: 0.013898 (0.013903) Loss: 0.52884 (0.68883) +2025-09-13,03:29:47 | INFO | Train Epoch: 4 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.71295 (0.67506) Boundary_loss: 0.013897 (0.013902) Loss: 0.72685 (0.68896) +2025-09-13,03:30:18 | INFO | Train Epoch: 4 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.65023 (0.67497) Boundary_loss: 0.013898 (0.013902) Loss: 0.66413 (0.68888) +2025-09-13,03:30:49 | INFO | Train Epoch: 4 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.83478 (0.67553) Boundary_loss: 0.013901 (0.013902) Loss: 0.84868 (0.68943) +2025-09-13,03:31:19 | INFO | Train Epoch: 4 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.69435 (0.67560) Boundary_loss: 0.013897 (0.013902) Loss: 0.70825 (0.68950) +2025-09-13,03:31:50 | INFO | Train Epoch: 4 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.65433 (0.67552) Boundary_loss: 0.013897 (0.013902) Loss: 0.66823 (0.68943) +2025-09-13,03:32:21 | INFO | Train Epoch: 4 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.66780 (0.67550) Boundary_loss: 0.013900 (0.013902) Loss: 0.68170 (0.68940) +2025-09-13,03:32:52 | INFO | Train Epoch: 4 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.64381 (0.67539) Boundary_loss: 0.013898 (0.013902) Loss: 0.65771 (0.68929) +2025-09-13,03:33:23 | INFO | Train Epoch: 4 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.55591 (0.67498) Boundary_loss: 0.013900 (0.013902) Loss: 0.56981 (0.68888) +2025-09-13,03:33:54 | INFO | Train Epoch: 4 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.65787 (0.67492) Boundary_loss: 0.013899 (0.013902) Loss: 0.67177 (0.68882) +2025-09-13,03:34:25 | INFO | Train Epoch: 4 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.68383 (0.67495) Boundary_loss: 0.013900 (0.013902) Loss: 0.69773 (0.68885) +2025-09-13,03:34:56 | INFO | Train Epoch: 4 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.64693 (0.67486) Boundary_loss: 0.013899 (0.013902) Loss: 0.66083 (0.68876) +2025-09-13,03:35:27 | INFO | Train Epoch: 4 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.65491 (0.67479) Boundary_loss: 0.013898 (0.013902) Loss: 0.66881 (0.68869) +2025-09-13,03:35:58 | INFO | Train Epoch: 4 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.61728 (0.67459) Boundary_loss: 0.013903 (0.013902) Loss: 0.63119 (0.68850) +2025-09-13,03:36:29 | INFO | Train Epoch: 4 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.58897 (0.67431) Boundary_loss: 0.013900 (0.013902) Loss: 0.60287 (0.68821) +2025-09-13,03:37:00 | INFO | Train Epoch: 4 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.66818 (0.67429) Boundary_loss: 0.013900 (0.013902) Loss: 0.68208 (0.68819) +2025-09-13,03:37:31 | INFO | Train Epoch: 4 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.81028 (0.67474) Boundary_loss: 0.013898 (0.013902) Loss: 0.82418 (0.68864) +2025-09-13,03:38:02 | INFO | Train Epoch: 4 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.66977 (0.67472) Boundary_loss: 0.013903 (0.013902) Loss: 0.68368 (0.68863) +2025-09-13,03:38:33 | INFO | Train Epoch: 4 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.55881 (0.67434) Boundary_loss: 0.013903 (0.013902) Loss: 0.57272 (0.68824) +2025-09-13,03:39:04 | INFO | Train Epoch: 4 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.61728 (0.67415) Boundary_loss: 0.013902 (0.013902) Loss: 0.63118 (0.68805) +2025-09-13,03:39:35 | INFO | Train Epoch: 4 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.68216 (0.67418) Boundary_loss: 0.013908 (0.013902) Loss: 0.69607 (0.68808) +2025-09-13,03:40:06 | INFO | Train Epoch: 4 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.63953 (0.67406) Boundary_loss: 0.013907 (0.013902) Loss: 0.65344 (0.68797) +2025-09-13,03:40:37 | INFO | Train Epoch: 4 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.63706 (0.67394) Boundary_loss: 0.013900 (0.013902) Loss: 0.65096 (0.68785) +2025-09-13,03:41:08 | INFO | Train Epoch: 4 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.70155 (0.67403) Boundary_loss: 0.013901 (0.013902) Loss: 0.71545 (0.68794) +2025-09-13,03:41:39 | INFO | Train Epoch: 4 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.60083 (0.67380) Boundary_loss: 0.013898 (0.013902) Loss: 0.61473 (0.68770) +2025-09-13,03:42:10 | INFO | Train Epoch: 4 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.57722 (0.67348) Boundary_loss: 0.013899 (0.013902) Loss: 0.59112 (0.68739) +2025-09-13,03:42:41 | INFO | Train Epoch: 4 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.62314 (0.67332) Boundary_loss: 0.013902 (0.013902) Loss: 0.63704 (0.68722) +2025-09-13,03:43:12 | INFO | Train Epoch: 4 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.59107 (0.67306) Boundary_loss: 0.013900 (0.013902) Loss: 0.60497 (0.68696) +2025-09-13,03:43:42 | INFO | Train Epoch: 4 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.63566 (0.67294) Boundary_loss: 0.013898 (0.013902) Loss: 0.64956 (0.68684) +2025-09-13,03:44:13 | INFO | Train Epoch: 4 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.70814 (0.67305) Boundary_loss: 0.013898 (0.013902) Loss: 0.72204 (0.68695) +2025-09-13,03:44:43 | INFO | Train Epoch: 4 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.61599 (0.67287) Boundary_loss: 0.013901 (0.013902) Loss: 0.62989 (0.68677) +2025-09-13,03:45:14 | INFO | Train Epoch: 4 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.56792 (0.67253) Boundary_loss: 0.013896 (0.013902) Loss: 0.58182 (0.68644) +2025-09-13,03:45:44 | INFO | Train Epoch: 4 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.66636 (0.67251) Boundary_loss: 0.013906 (0.013902) Loss: 0.68027 (0.68642) +2025-09-13,03:46:15 | INFO | Train Epoch: 4 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.62133 (0.67235) Boundary_loss: 0.013899 (0.013902) Loss: 0.63522 (0.68625) +2025-09-13,03:46:46 | INFO | Train Epoch: 4 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.73557 (0.67255) Boundary_loss: 0.013902 (0.013902) Loss: 0.74947 (0.68645) +2025-09-13,03:47:16 | INFO | Train Epoch: 4 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.68077 (0.67258) Boundary_loss: 0.013896 (0.013902) Loss: 0.69467 (0.68648) +2025-09-13,03:47:47 | INFO | Train Epoch: 4 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.73268 (0.67277) Boundary_loss: 0.013902 (0.013902) Loss: 0.74658 (0.68667) +2025-09-13,03:48:18 | INFO | Train Epoch: 4 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.68298 (0.67280) Boundary_loss: 0.013898 (0.013902) Loss: 0.69688 (0.68670) +2025-09-13,03:48:49 | INFO | Train Epoch: 4 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.64473 (0.67271) Boundary_loss: 0.013898 (0.013902) Loss: 0.65863 (0.68661) +2025-09-13,03:49:19 | INFO | Train Epoch: 4 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.66870 (0.67270) Boundary_loss: 0.013899 (0.013902) Loss: 0.68260 (0.68660) +2025-09-13,03:49:51 | INFO | Train Epoch: 4 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.67857 (0.67272) Boundary_loss: 0.013899 (0.013902) Loss: 0.69247 (0.68662) +2025-09-13,03:50:21 | INFO | Train Epoch: 4 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.67339 (0.67272) Boundary_loss: 0.013899 (0.013902) Loss: 0.68729 (0.68662) +2025-09-13,03:50:52 | INFO | Train Epoch: 4 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.66835 (0.67270) Boundary_loss: 0.013901 (0.013902) Loss: 0.68225 (0.68661) +2025-09-13,03:51:23 | INFO | Train Epoch: 4 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.59588 (0.67247) Boundary_loss: 0.013899 (0.013902) Loss: 0.60978 (0.68637) +2025-09-13,03:51:54 | INFO | Train Epoch: 4 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.70690 (0.67257) Boundary_loss: 0.013899 (0.013902) Loss: 0.72080 (0.68648) +2025-09-13,03:52:25 | INFO | Train Epoch: 4 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.71000 (0.67269) Boundary_loss: 0.013898 (0.013902) Loss: 0.72390 (0.68659) +2025-09-13,03:52:56 | INFO | Train Epoch: 4 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.64167 (0.67259) Boundary_loss: 0.013900 (0.013902) Loss: 0.65557 (0.68650) +2025-09-13,03:53:27 | INFO | Train Epoch: 4 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.68075 (0.67262) Boundary_loss: 0.013896 (0.013902) Loss: 0.69465 (0.68652) +2025-09-13,03:53:58 | INFO | Train Epoch: 4 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.81730 (0.67305) Boundary_loss: 0.013898 (0.013902) Loss: 0.83120 (0.68696) +2025-09-13,03:54:29 | INFO | Train Epoch: 4 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.66816 (0.67304) Boundary_loss: 0.013913 (0.013902) Loss: 0.68207 (0.68694) +2025-09-13,03:55:00 | INFO | Train Epoch: 4 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.68435 (0.67307) Boundary_loss: 0.013899 (0.013902) Loss: 0.69825 (0.68698) +2025-09-13,03:55:31 | INFO | Train Epoch: 4 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.59091 (0.67283) Boundary_loss: 0.013899 (0.013902) Loss: 0.60481 (0.68673) +2025-09-13,03:56:02 | INFO | Train Epoch: 4 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.74157 (0.67303) Boundary_loss: 0.013900 (0.013902) Loss: 0.75547 (0.68693) +2025-09-13,03:56:33 | INFO | Train Epoch: 4 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.69478 (0.67310) Boundary_loss: 0.013901 (0.013902) Loss: 0.70868 (0.68700) +2025-09-13,03:57:04 | INFO | Train Epoch: 4 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.64199 (0.67301) Boundary_loss: 0.013899 (0.013902) Loss: 0.65589 (0.68691) +2025-09-13,03:57:35 | INFO | Train Epoch: 4 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.74425 (0.67322) Boundary_loss: 0.013900 (0.013902) Loss: 0.75815 (0.68712) +2025-09-13,03:58:06 | INFO | Train Epoch: 4 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.61510 (0.67304) Boundary_loss: 0.013897 (0.013902) Loss: 0.62900 (0.68695) +2025-09-13,03:58:36 | INFO | Train Epoch: 4 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.51725 (0.67259) Boundary_loss: 0.013897 (0.013902) Loss: 0.53115 (0.68649) +2025-09-13,03:59:07 | INFO | Train Epoch: 4 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.66952 (0.67258) Boundary_loss: 0.013899 (0.013902) Loss: 0.68342 (0.68648) +2025-09-13,03:59:38 | INFO | Train Epoch: 4 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.65471 (0.67253) Boundary_loss: 0.013896 (0.013902) Loss: 0.66861 (0.68643) +2025-09-13,04:00:09 | INFO | Train Epoch: 4 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.66670 (0.67251) Boundary_loss: 0.013902 (0.013902) Loss: 0.68060 (0.68641) +2025-09-13,04:00:40 | INFO | Train Epoch: 4 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.77367 (0.67280) Boundary_loss: 0.013901 (0.013902) Loss: 0.78757 (0.68670) +2025-09-13,04:01:11 | INFO | Train Epoch: 4 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.74708 (0.67302) Boundary_loss: 0.013898 (0.013902) Loss: 0.76098 (0.68692) +2025-09-13,04:01:42 | INFO | Train Epoch: 4 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.55402 (0.67267) Boundary_loss: 0.013898 (0.013902) Loss: 0.56792 (0.68658) +2025-09-13,04:02:13 | INFO | Train Epoch: 4 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.72335 (0.67282) Boundary_loss: 0.013900 (0.013902) Loss: 0.73725 (0.68672) +2025-09-13,04:02:44 | INFO | Train Epoch: 4 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.62236 (0.67268) Boundary_loss: 0.013898 (0.013902) Loss: 0.63626 (0.68658) +2025-09-13,04:03:15 | INFO | Train Epoch: 4 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.54491 (0.67231) Boundary_loss: 0.013900 (0.013902) Loss: 0.55881 (0.68621) +2025-09-13,04:03:46 | INFO | Train Epoch: 4 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.64034 (0.67222) Boundary_loss: 0.013896 (0.013902) Loss: 0.65423 (0.68612) +2025-09-13,04:04:17 | INFO | Train Epoch: 4 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.62016 (0.67207) Boundary_loss: 0.013897 (0.013902) Loss: 0.63406 (0.68597) +2025-09-13,04:04:47 | INFO | Train Epoch: 4 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.58940 (0.67184) Boundary_loss: 0.013898 (0.013902) Loss: 0.60329 (0.68574) +2025-09-13,04:05:18 | INFO | Train Epoch: 4 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.56086 (0.67152) Boundary_loss: 0.013899 (0.013902) Loss: 0.57476 (0.68543) +2025-09-13,04:05:49 | INFO | Train Epoch: 4 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.60120 (0.67133) Boundary_loss: 0.013898 (0.013902) Loss: 0.61510 (0.68523) +2025-09-13,04:06:20 | INFO | Train Epoch: 4 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.59479 (0.67111) Boundary_loss: 0.013909 (0.013902) Loss: 0.60870 (0.68501) +2025-09-13,04:06:51 | INFO | Train Epoch: 4 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.59495 (0.67090) Boundary_loss: 0.013896 (0.013902) Loss: 0.60885 (0.68480) +2025-09-13,04:07:22 | INFO | Train Epoch: 4 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.63251 (0.67079) Boundary_loss: 0.013898 (0.013902) Loss: 0.64640 (0.68469) +2025-09-13,04:07:53 | INFO | Train Epoch: 4 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.72470 (0.67094) Boundary_loss: 0.013901 (0.013902) Loss: 0.73860 (0.68484) +2025-09-13,04:08:24 | INFO | Train Epoch: 4 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.62459 (0.67081) Boundary_loss: 0.013899 (0.013902) Loss: 0.63849 (0.68471) +2025-09-13,04:08:55 | INFO | Train Epoch: 4 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.62357 (0.67068) Boundary_loss: 0.013901 (0.013902) Loss: 0.63747 (0.68458) +2025-09-13,04:09:26 | INFO | Train Epoch: 4 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.62877 (0.67057) Boundary_loss: 0.013898 (0.013902) Loss: 0.64267 (0.68447) +2025-09-13,04:09:56 | INFO | Train Epoch: 4 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.68727 (0.67061) Boundary_loss: 0.013902 (0.013902) Loss: 0.70117 (0.68451) +2025-09-13,04:10:27 | INFO | Train Epoch: 4 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.71984 (0.67075) Boundary_loss: 0.013899 (0.013902) Loss: 0.73374 (0.68465) +2025-09-13,04:10:58 | INFO | Train Epoch: 4 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.58569 (0.67051) Boundary_loss: 0.013901 (0.013902) Loss: 0.59959 (0.68442) +2025-09-13,04:11:29 | INFO | Train Epoch: 4 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.55320 (0.67019) Boundary_loss: 0.013898 (0.013902) Loss: 0.56709 (0.68409) +2025-09-13,04:12:00 | INFO | Train Epoch: 4 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.64152 (0.67011) Boundary_loss: 0.013900 (0.013902) Loss: 0.65542 (0.68402) +2025-09-13,04:12:31 | INFO | Train Epoch: 4 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.57897 (0.66987) Boundary_loss: 0.013898 (0.013902) Loss: 0.59287 (0.68377) +2025-09-13,04:13:02 | INFO | Train Epoch: 4 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.65222 (0.66982) Boundary_loss: 0.013900 (0.013902) Loss: 0.66612 (0.68372) +2025-09-13,04:13:33 | INFO | Train Epoch: 4 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.62615 (0.66970) Boundary_loss: 0.013897 (0.013902) Loss: 0.64004 (0.68360) +2025-09-13,04:14:04 | INFO | Train Epoch: 4 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.71544 (0.66982) Boundary_loss: 0.013900 (0.013902) Loss: 0.72934 (0.68373) +2025-09-13,04:14:35 | INFO | Train Epoch: 4 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.61034 (0.66966) Boundary_loss: 0.013900 (0.013902) Loss: 0.62423 (0.68357) +2025-09-13,04:15:06 | INFO | Train Epoch: 4 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.62886 (0.66956) Boundary_loss: 0.013896 (0.013902) Loss: 0.64276 (0.68346) +2025-09-13,04:15:37 | INFO | Train Epoch: 4 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.59788 (0.66936) Boundary_loss: 0.013900 (0.013902) Loss: 0.61178 (0.68327) +2025-09-13,04:16:08 | INFO | Train Epoch: 4 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.60373 (0.66919) Boundary_loss: 0.013896 (0.013902) Loss: 0.61762 (0.68309) +2025-09-13,04:16:39 | INFO | Train Epoch: 4 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.68515 (0.66923) Boundary_loss: 0.013898 (0.013902) Loss: 0.69905 (0.68313) +2025-09-13,04:17:09 | INFO | Train Epoch: 4 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.69403 (0.66930) Boundary_loss: 0.013899 (0.013902) Loss: 0.70793 (0.68320) +2025-09-13,04:17:40 | INFO | Train Epoch: 4 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.66425 (0.66928) Boundary_loss: 0.013900 (0.013902) Loss: 0.67815 (0.68319) +2025-09-13,04:18:11 | INFO | Train Epoch: 4 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.62350 (0.66916) Boundary_loss: 0.013897 (0.013902) Loss: 0.63740 (0.68306) +2025-09-13,04:18:42 | INFO | Train Epoch: 4 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.63105 (0.66906) Boundary_loss: 0.013898 (0.013902) Loss: 0.64495 (0.68296) +2025-09-13,04:19:13 | INFO | Train Epoch: 4 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.64300 (0.66899) Boundary_loss: 0.013902 (0.013902) Loss: 0.65690 (0.68290) +2025-09-13,04:19:44 | INFO | Train Epoch: 4 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.66392 (0.66898) Boundary_loss: 0.013897 (0.013902) Loss: 0.67782 (0.68288) +2025-09-13,04:20:15 | INFO | Train Epoch: 4 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.59162 (0.66878) Boundary_loss: 0.013898 (0.013902) Loss: 0.60551 (0.68268) +2025-09-13,04:20:46 | INFO | Train Epoch: 4 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.62446 (0.66866) Boundary_loss: 0.013902 (0.013902) Loss: 0.63836 (0.68256) +2025-09-13,04:21:17 | INFO | Train Epoch: 4 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.68971 (0.66872) Boundary_loss: 0.013901 (0.013902) Loss: 0.70361 (0.68262) +2025-09-13,04:21:48 | INFO | Train Epoch: 4 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.72440 (0.66886) Boundary_loss: 0.013897 (0.013902) Loss: 0.73830 (0.68276) +2025-09-13,04:22:19 | INFO | Train Epoch: 4 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.68233 (0.66890) Boundary_loss: 0.013898 (0.013902) Loss: 0.69623 (0.68280) +2025-09-13,04:22:50 | INFO | Train Epoch: 4 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.60083 (0.66872) Boundary_loss: 0.013898 (0.013902) Loss: 0.61473 (0.68262) +2025-09-13,04:23:21 | INFO | Train Epoch: 4 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.80133 (0.66906) Boundary_loss: 0.013907 (0.013902) Loss: 0.81524 (0.68296) +2025-09-13,04:23:52 | INFO | Train Epoch: 4 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.57005 (0.66881) Boundary_loss: 0.013897 (0.013902) Loss: 0.58394 (0.68271) +2025-09-13,04:24:23 | INFO | Train Epoch: 4 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.68808 (0.66886) Boundary_loss: 0.013897 (0.013902) Loss: 0.70198 (0.68276) +2025-09-13,04:24:54 | INFO | Train Epoch: 4 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.56905 (0.66860) Boundary_loss: 0.013900 (0.013902) Loss: 0.58295 (0.68250) +2025-09-13,04:25:25 | INFO | Train Epoch: 4 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.51299 (0.66821) Boundary_loss: 0.013895 (0.013902) Loss: 0.52689 (0.68211) +2025-09-13,04:25:56 | INFO | Train Epoch: 4 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.57252 (0.66796) Boundary_loss: 0.013903 (0.013902) Loss: 0.58642 (0.68187) +2025-09-13,04:26:27 | INFO | Train Epoch: 4 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.60312 (0.66780) Boundary_loss: 0.013898 (0.013902) Loss: 0.61702 (0.68170) +2025-09-13,04:26:58 | INFO | Train Epoch: 4 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.60802 (0.66765) Boundary_loss: 0.013898 (0.013902) Loss: 0.62191 (0.68155) +2025-09-13,04:27:29 | INFO | Train Epoch: 4 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.70720 (0.66775) Boundary_loss: 0.013897 (0.013902) Loss: 0.72110 (0.68165) +2025-09-13,04:28:00 | INFO | Train Epoch: 4 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.75139 (0.66796) Boundary_loss: 0.013898 (0.013902) Loss: 0.76529 (0.68186) +2025-09-13,04:28:31 | INFO | Train Epoch: 4 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.70562 (0.66805) Boundary_loss: 0.013916 (0.013902) Loss: 0.71953 (0.68196) +2025-09-13,04:29:01 | INFO | Train Epoch: 4 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.63434 (0.66797) Boundary_loss: 0.013897 (0.013902) Loss: 0.64824 (0.68187) +2025-09-13,04:29:32 | INFO | Train Epoch: 4 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.63707 (0.66789) Boundary_loss: 0.013900 (0.013902) Loss: 0.65097 (0.68179) +2025-09-13,04:30:04 | INFO | Train Epoch: 4 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.68245 (0.66793) Boundary_loss: 0.013897 (0.013902) Loss: 0.69635 (0.68183) +2025-09-13,04:30:35 | INFO | Train Epoch: 4 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.61552 (0.66780) Boundary_loss: 0.013903 (0.013902) Loss: 0.62942 (0.68170) +2025-09-13,04:31:06 | INFO | Train Epoch: 4 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.54234 (0.66749) Boundary_loss: 0.013898 (0.013902) Loss: 0.55623 (0.68139) +2025-09-13,04:31:37 | INFO | Train Epoch: 4 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.61968 (0.66737) Boundary_loss: 0.013899 (0.013902) Loss: 0.63358 (0.68127) +2025-09-13,04:32:08 | INFO | Train Epoch: 4 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.66636 (0.66737) Boundary_loss: 0.013897 (0.013902) Loss: 0.68026 (0.68127) +2025-09-13,04:32:39 | INFO | Train Epoch: 4 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.70314 (0.66745) Boundary_loss: 0.013899 (0.013902) Loss: 0.71704 (0.68136) +2025-09-13,04:33:10 | INFO | Train Epoch: 4 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.59860 (0.66729) Boundary_loss: 0.013899 (0.013902) Loss: 0.61250 (0.68119) +2025-09-13,04:33:41 | INFO | Train Epoch: 4 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.71585 (0.66740) Boundary_loss: 0.013899 (0.013902) Loss: 0.72975 (0.68131) +2025-09-13,04:34:12 | INFO | Train Epoch: 4 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59027 (0.66722) Boundary_loss: 0.013899 (0.013902) Loss: 0.60417 (0.68112) +2025-09-13,04:34:42 | INFO | Train Epoch: 4 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.58453 (0.66702) Boundary_loss: 0.013897 (0.013902) Loss: 0.59843 (0.68092) +2025-09-13,04:35:13 | INFO | Train Epoch: 4 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.61979 (0.66690) Boundary_loss: 0.013897 (0.013902) Loss: 0.63368 (0.68080) +2025-09-13,04:35:44 | INFO | Train Epoch: 4 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.54321 (0.66660) Boundary_loss: 0.013898 (0.013902) Loss: 0.55711 (0.68050) +2025-09-13,04:36:15 | INFO | Train Epoch: 4 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59898 (0.66644) Boundary_loss: 0.013898 (0.013902) Loss: 0.61288 (0.68034) +2025-09-13,04:36:46 | INFO | Train Epoch: 4 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.58929 (0.66625) Boundary_loss: 0.013898 (0.013902) Loss: 0.60318 (0.68015) +2025-09-13,04:37:17 | INFO | Train Epoch: 4 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.70001 (0.66633) Boundary_loss: 0.013898 (0.013902) Loss: 0.71390 (0.68023) +2025-09-13,04:37:48 | INFO | Train Epoch: 4 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.64975 (0.66629) Boundary_loss: 0.013899 (0.013902) Loss: 0.66365 (0.68020) +2025-09-13,04:38:19 | INFO | Train Epoch: 4 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.69224 (0.66636) Boundary_loss: 0.013900 (0.013902) Loss: 0.70614 (0.68026) +2025-09-13,04:38:50 | INFO | Train Epoch: 4 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.68856 (0.66641) Boundary_loss: 0.013912 (0.013902) Loss: 0.70248 (0.68031) +2025-09-13,04:39:21 | INFO | Train Epoch: 4 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.67572 (0.66643) Boundary_loss: 0.013899 (0.013902) Loss: 0.68962 (0.68033) +2025-09-13,04:39:52 | INFO | Train Epoch: 4 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.53093 (0.66611) Boundary_loss: 0.013897 (0.013902) Loss: 0.54483 (0.68001) +2025-09-13,04:40:23 | INFO | Train Epoch: 4 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.68226 (0.66615) Boundary_loss: 0.013909 (0.013902) Loss: 0.69616 (0.68005) +2025-09-13,04:40:53 | INFO | Train Epoch: 4 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.72354 (0.66628) Boundary_loss: 0.013913 (0.013902) Loss: 0.73746 (0.68018) +2025-09-13,04:41:24 | INFO | Train Epoch: 4 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.70749 (0.66638) Boundary_loss: 0.013907 (0.013902) Loss: 0.72140 (0.68028) +2025-09-13,04:41:55 | INFO | Train Epoch: 4 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.66123 (0.66637) Boundary_loss: 0.013900 (0.013902) Loss: 0.67513 (0.68027) +2025-09-13,04:42:26 | INFO | Train Epoch: 4 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.68948 (0.66642) Boundary_loss: 0.013901 (0.013902) Loss: 0.70338 (0.68032) +2025-09-13,04:42:57 | INFO | Train Epoch: 4 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59689 (0.66626) Boundary_loss: 0.013898 (0.013902) Loss: 0.61079 (0.68016) +2025-09-13,04:43:28 | INFO | Train Epoch: 4 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.63987 (0.66620) Boundary_loss: 0.013897 (0.013902) Loss: 0.65377 (0.68010) +2025-09-13,04:43:59 | INFO | Train Epoch: 4 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.69015 (0.66625) Boundary_loss: 0.013900 (0.013902) Loss: 0.70406 (0.68016) +2025-09-13,04:44:30 | INFO | Train Epoch: 4 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.59791 (0.66609) Boundary_loss: 0.013903 (0.013902) Loss: 0.61181 (0.68000) +2025-09-13,04:45:01 | INFO | Train Epoch: 4 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.56379 (0.66586) Boundary_loss: 0.013902 (0.013902) Loss: 0.57770 (0.67976) +2025-09-13,04:45:32 | INFO | Train Epoch: 4 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.73473 (0.66602) Boundary_loss: 0.013900 (0.013902) Loss: 0.74863 (0.67992) +2025-09-13,04:46:03 | INFO | Train Epoch: 4 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.68827 (0.66607) Boundary_loss: 0.013897 (0.013902) Loss: 0.70217 (0.67997) +2025-09-13,04:46:34 | INFO | Train Epoch: 4 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.61611 (0.66595) Boundary_loss: 0.013898 (0.013902) Loss: 0.63001 (0.67985) +2025-09-13,04:47:05 | INFO | Train Epoch: 4 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.71023 (0.66605) Boundary_loss: 0.013898 (0.013902) Loss: 0.72413 (0.67996) +2025-09-13,04:47:36 | INFO | Train Epoch: 4 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.66823 (0.66606) Boundary_loss: 0.013901 (0.013902) Loss: 0.68213 (0.67996) +2025-09-13,04:48:07 | INFO | Train Epoch: 4 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.60029 (0.66591) Boundary_loss: 0.013900 (0.013902) Loss: 0.61419 (0.67981) +2025-09-13,04:48:37 | INFO | Train Epoch: 4 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.56764 (0.66568) Boundary_loss: 0.013898 (0.013902) Loss: 0.58154 (0.67959) +2025-09-13,04:49:08 | INFO | Train Epoch: 4 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.66566 (0.66568) Boundary_loss: 0.013898 (0.013902) Loss: 0.67956 (0.67959) +2025-09-13,04:49:39 | INFO | Train Epoch: 4 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.60823 (0.66555) Boundary_loss: 0.013901 (0.013902) Loss: 0.62213 (0.67946) +2025-09-13,04:50:10 | INFO | Train Epoch: 4 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.67542 (0.66558) Boundary_loss: 0.013900 (0.013902) Loss: 0.68932 (0.67948) +2025-09-13,04:50:41 | INFO | Train Epoch: 4 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.65709 (0.66556) Boundary_loss: 0.013902 (0.013902) Loss: 0.67100 (0.67946) +2025-09-13,04:51:12 | INFO | Train Epoch: 4 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.63965 (0.66550) Boundary_loss: 0.013899 (0.013902) Loss: 0.65355 (0.67940) +2025-09-13,04:51:43 | INFO | Train Epoch: 4 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.53612 (0.66521) Boundary_loss: 0.013899 (0.013902) Loss: 0.55002 (0.67911) +2025-09-13,04:52:14 | INFO | Train Epoch: 4 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.73216 (0.66536) Boundary_loss: 0.013903 (0.013902) Loss: 0.74606 (0.67926) +2025-09-13,04:52:45 | INFO | Train Epoch: 4 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.62303 (0.66526) Boundary_loss: 0.013899 (0.013902) Loss: 0.63693 (0.67916) +2025-09-13,04:53:16 | INFO | Train Epoch: 4 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.74516 (0.66544) Boundary_loss: 0.013906 (0.013902) Loss: 0.75907 (0.67934) +2025-09-13,04:53:47 | INFO | Train Epoch: 4 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.57939 (0.66525) Boundary_loss: 0.013898 (0.013902) Loss: 0.59329 (0.67915) +2025-09-13,04:54:18 | INFO | Train Epoch: 4 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.62063 (0.66515) Boundary_loss: 0.013897 (0.013902) Loss: 0.63453 (0.67905) +2025-09-13,04:54:49 | INFO | Train Epoch: 4 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.70354 (0.66524) Boundary_loss: 0.013897 (0.013901) Loss: 0.71743 (0.67914) +2025-09-13,04:55:20 | INFO | Train Epoch: 4 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.65951 (0.66522) Boundary_loss: 0.013901 (0.013901) Loss: 0.67341 (0.67912) +2025-09-13,04:55:51 | INFO | Train Epoch: 4 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.65142 (0.66519) Boundary_loss: 0.013898 (0.013901) Loss: 0.66532 (0.67909) +2025-09-13,04:56:22 | INFO | Train Epoch: 4 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.56699 (0.66498) Boundary_loss: 0.013898 (0.013901) Loss: 0.58089 (0.67888) +2025-09-13,04:56:53 | INFO | Train Epoch: 4 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.65773 (0.66496) Boundary_loss: 0.013898 (0.013901) Loss: 0.67163 (0.67886) +2025-09-13,04:57:24 | INFO | Train Epoch: 4 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.64827 (0.66492) Boundary_loss: 0.013910 (0.013901) Loss: 0.66218 (0.67882) +2025-09-13,04:57:54 | INFO | Train Epoch: 4 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.63124 (0.66485) Boundary_loss: 0.013896 (0.013901) Loss: 0.64513 (0.67875) +2025-09-13,04:58:25 | INFO | Train Epoch: 4 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.61880 (0.66475) Boundary_loss: 0.013902 (0.013901) Loss: 0.63270 (0.67865) +2025-09-13,04:58:56 | INFO | Train Epoch: 4 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.66617 (0.66475) Boundary_loss: 0.013902 (0.013901) Loss: 0.68008 (0.67865) +2025-09-13,04:59:27 | INFO | Train Epoch: 4 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.63013 (0.66468) Boundary_loss: 0.013899 (0.013901) Loss: 0.64403 (0.67858) +2025-09-13,04:59:58 | INFO | Train Epoch: 4 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.56057 (0.66445) Boundary_loss: 0.013900 (0.013901) Loss: 0.57447 (0.67835) +2025-09-13,05:00:29 | INFO | Train Epoch: 4 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.62954 (0.66437) Boundary_loss: 0.013899 (0.013901) Loss: 0.64344 (0.67828) +2025-09-13,05:01:00 | INFO | Train Epoch: 4 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.72096 (0.66450) Boundary_loss: 0.013900 (0.013901) Loss: 0.73486 (0.67840) +2025-09-13,05:01:31 | INFO | Train Epoch: 4 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.63154 (0.66443) Boundary_loss: 0.013908 (0.013901) Loss: 0.64545 (0.67833) +2025-09-13,05:02:02 | INFO | Train Epoch: 4 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.60053 (0.66429) Boundary_loss: 0.013900 (0.013901) Loss: 0.61443 (0.67819) +2025-09-13,05:02:33 | INFO | Train Epoch: 4 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.59372 (0.66414) Boundary_loss: 0.013902 (0.013901) Loss: 0.60762 (0.67804) +2025-09-13,05:03:04 | INFO | Train Epoch: 4 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.61184 (0.66402) Boundary_loss: 0.013897 (0.013901) Loss: 0.62573 (0.67793) +2025-09-13,05:03:35 | INFO | Train Epoch: 4 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.50272 (0.66368) Boundary_loss: 0.013900 (0.013901) Loss: 0.51662 (0.67758) +2025-09-13,05:04:06 | INFO | Train Epoch: 4 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.63292 (0.66361) Boundary_loss: 0.013908 (0.013901) Loss: 0.64683 (0.67751) +2025-09-13,05:04:37 | INFO | Train Epoch: 4 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.72707 (0.66375) Boundary_loss: 0.013897 (0.013901) Loss: 0.74097 (0.67765) +2025-09-13,05:05:08 | INFO | Train Epoch: 4 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.75663 (0.66395) Boundary_loss: 0.013898 (0.013901) Loss: 0.77052 (0.67785) +2025-09-13,05:05:39 | INFO | Train Epoch: 4 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.57315 (0.66375) Boundary_loss: 0.013900 (0.013901) Loss: 0.58705 (0.67765) +2025-09-13,05:06:09 | INFO | Train Epoch: 4 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.68942 (0.66381) Boundary_loss: 0.013902 (0.013901) Loss: 0.70332 (0.67771) +2025-09-13,05:06:40 | INFO | Train Epoch: 4 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.60042 (0.66367) Boundary_loss: 0.013897 (0.013901) Loss: 0.61431 (0.67757) +2025-09-13,05:07:11 | INFO | Train Epoch: 4 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.74249 (0.66384) Boundary_loss: 0.013896 (0.013901) Loss: 0.75639 (0.67774) +2025-09-13,05:07:42 | INFO | Train Epoch: 4 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.66691 (0.66385) Boundary_loss: 0.013899 (0.013901) Loss: 0.68081 (0.67775) +2025-09-13,05:08:13 | INFO | Train Epoch: 4 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.66513 (0.66385) Boundary_loss: 0.013900 (0.013901) Loss: 0.67903 (0.67775) +2025-09-13,05:08:44 | INFO | Train Epoch: 4 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.74944 (0.66403) Boundary_loss: 0.013903 (0.013901) Loss: 0.76335 (0.67793) +2025-09-13,05:09:15 | INFO | Train Epoch: 4 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.53620 (0.66376) Boundary_loss: 0.013899 (0.013901) Loss: 0.55010 (0.67766) +2025-09-13,05:09:46 | INFO | Train Epoch: 4 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.73105 (0.66390) Boundary_loss: 0.013898 (0.013901) Loss: 0.74495 (0.67780) +2025-09-13,05:10:17 | INFO | Train Epoch: 4 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.66871 (0.66391) Boundary_loss: 0.013897 (0.013901) Loss: 0.68261 (0.67781) +2025-09-13,05:10:48 | INFO | Train Epoch: 4 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.74668 (0.66408) Boundary_loss: 0.013900 (0.013901) Loss: 0.76058 (0.67798) +2025-09-13,05:11:19 | INFO | Train Epoch: 4 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.65742 (0.66407) Boundary_loss: 0.013897 (0.013901) Loss: 0.67131 (0.67797) +2025-09-13,05:11:51 | INFO | Train Epoch: 4 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.68790 (0.66412) Boundary_loss: 0.013897 (0.013901) Loss: 0.70180 (0.67802) +2025-09-13,05:12:22 | INFO | Train Epoch: 4 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.54265 (0.66387) Boundary_loss: 0.013900 (0.013901) Loss: 0.55655 (0.67777) +2025-09-13,05:12:53 | INFO | Train Epoch: 4 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.75645 (0.66406) Boundary_loss: 0.013899 (0.013901) Loss: 0.77035 (0.67796) +2025-09-13,05:13:24 | INFO | Train Epoch: 4 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.59641 (0.66392) Boundary_loss: 0.013899 (0.013901) Loss: 0.61031 (0.67782) +2025-09-13,05:13:55 | INFO | Train Epoch: 4 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.71818 (0.66403) Boundary_loss: 0.013898 (0.013901) Loss: 0.73208 (0.67793) +2025-09-13,05:14:26 | INFO | Train Epoch: 4 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.64601 (0.66399) Boundary_loss: 0.013897 (0.013901) Loss: 0.65991 (0.67790) +2025-09-13,05:14:56 | INFO | Train Epoch: 4 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.81227 (0.66430) Boundary_loss: 0.013897 (0.013901) Loss: 0.82616 (0.67820) +2025-09-13,05:15:27 | INFO | Train Epoch: 4 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.78745 (0.66455) Boundary_loss: 0.013903 (0.013901) Loss: 0.80136 (0.67845) +2025-09-13,05:15:58 | INFO | Train Epoch: 4 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.67768 (0.66458) Boundary_loss: 0.013898 (0.013901) Loss: 0.69158 (0.67848) +2025-09-13,05:16:29 | INFO | Train Epoch: 4 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.61068 (0.66447) Boundary_loss: 0.013897 (0.013901) Loss: 0.62458 (0.67837) +2025-09-13,05:17:00 | INFO | Train Epoch: 4 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.56881 (0.66427) Boundary_loss: 0.013901 (0.013901) Loss: 0.58271 (0.67817) +2025-09-13,05:17:31 | INFO | Train Epoch: 4 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.69279 (0.66433) Boundary_loss: 0.013900 (0.013901) Loss: 0.70669 (0.67823) +2025-09-13,05:18:02 | INFO | Train Epoch: 4 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.65562 (0.66431) Boundary_loss: 0.013897 (0.013901) Loss: 0.66951 (0.67821) +2025-09-13,05:18:33 | INFO | Train Epoch: 4 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.63986 (0.66426) Boundary_loss: 0.013897 (0.013901) Loss: 0.65375 (0.67816) +2025-09-13,05:19:04 | INFO | Train Epoch: 4 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.70428 (0.66434) Boundary_loss: 0.013897 (0.013901) Loss: 0.71818 (0.67824) +2025-09-13,05:19:35 | INFO | Train Epoch: 4 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.73710 (0.66449) Boundary_loss: 0.013898 (0.013901) Loss: 0.75100 (0.67839) +2025-09-13,05:20:06 | INFO | Train Epoch: 4 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.64220 (0.66444) Boundary_loss: 0.013896 (0.013901) Loss: 0.65609 (0.67835) +2025-09-13,05:20:37 | INFO | Train Epoch: 4 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.65190 (0.66442) Boundary_loss: 0.013897 (0.013901) Loss: 0.66580 (0.67832) +2025-09-13,05:21:08 | INFO | Train Epoch: 4 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.73905 (0.66457) Boundary_loss: 0.013900 (0.013901) Loss: 0.75295 (0.67847) +2025-09-13,05:21:39 | INFO | Train Epoch: 4 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.66127 (0.66456) Boundary_loss: 0.013899 (0.013901) Loss: 0.67517 (0.67846) +2025-09-13,05:22:10 | INFO | Train Epoch: 4 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.67619 (0.66458) Boundary_loss: 0.013897 (0.013901) Loss: 0.69009 (0.67849) +2025-09-13,05:22:41 | INFO | Train Epoch: 4 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.62958 (0.66452) Boundary_loss: 0.013900 (0.013901) Loss: 0.64348 (0.67842) +2025-09-13,05:23:12 | INFO | Train Epoch: 4 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.62519 (0.66444) Boundary_loss: 0.013905 (0.013901) Loss: 0.63910 (0.67834) +2025-09-13,05:23:43 | INFO | Train Epoch: 4 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.64252 (0.66439) Boundary_loss: 0.013899 (0.013901) Loss: 0.65642 (0.67830) +2025-09-13,05:24:14 | INFO | Train Epoch: 4 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.67874 (0.66442) Boundary_loss: 0.013902 (0.013901) Loss: 0.69264 (0.67832) +2025-09-13,05:24:45 | INFO | Train Epoch: 4 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.61149 (0.66432) Boundary_loss: 0.013896 (0.013901) Loss: 0.62538 (0.67822) +2025-09-13,05:25:16 | INFO | Train Epoch: 4 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.63040 (0.66425) Boundary_loss: 0.013897 (0.013901) Loss: 0.64430 (0.67815) +2025-09-13,05:25:47 | INFO | Train Epoch: 4 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.57343 (0.66407) Boundary_loss: 0.013896 (0.013901) Loss: 0.58733 (0.67797) +2025-09-13,05:26:18 | INFO | Train Epoch: 4 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.59859 (0.66395) Boundary_loss: 0.013897 (0.013901) Loss: 0.61249 (0.67785) +2025-09-13,05:26:49 | INFO | Train Epoch: 4 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.57054 (0.66376) Boundary_loss: 0.013899 (0.013901) Loss: 0.58444 (0.67766) +2025-09-13,05:27:21 | INFO | Train Epoch: 4 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.56677 (0.66357) Boundary_loss: 0.013901 (0.013901) Loss: 0.58067 (0.67748) +2025-09-13,05:27:52 | INFO | Train Epoch: 4 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.72334 (0.66369) Boundary_loss: 0.013905 (0.013901) Loss: 0.73725 (0.67759) +2025-09-13,05:28:23 | INFO | Train Epoch: 4 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.58945 (0.66355) Boundary_loss: 0.013898 (0.013901) Loss: 0.60334 (0.67745) +2025-09-13,05:28:52 | INFO | Train Epoch: 4 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.52286 (0.66327) Boundary_loss: 0.013898 (0.013901) Loss: 0.53676 (0.67717) +2025-09-13,05:28:52 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,05:28:52 | INFO | [Epoch 4] Average Step Time: 0.312s | Average GPU Memory: 25.3 GB +2025-09-13,05:28:52 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,05:28:52 | INFO | Starting zero-shot imagenet. +2025-09-13,05:28:52 | INFO | Building zero-shot classifier +2025-09-13,05:28:58 | INFO | Using classifier +2025-09-13,05:29:42 | INFO | Finished zero-shot imagenet. +2025-09-13,05:29:42 | INFO | Eval Epoch: 5 imagenet-zeroshot-val-top1: 0.2246 imagenet-zeroshot-val-top5: 0.4595 +2025-09-13,05:29:43 | INFO | Start epoch 5 +2025-09-13,05:29:45 | INFO | Train Epoch: 5 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.57728 (0.57728) Boundary_loss: 0.013896 (0.013896) Loss: 0.59118 (0.59118) +2025-09-13,05:30:16 | INFO | Train Epoch: 5 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.53026 (0.55377) Boundary_loss: 0.013903 (0.013900) Loss: 0.54416 (0.56767) +2025-09-13,05:30:47 | INFO | Train Epoch: 5 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.57725 (0.56160) Boundary_loss: 0.013901 (0.013900) Loss: 0.59115 (0.57550) +2025-09-13,05:31:18 | INFO | Train Epoch: 5 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.46105 (0.53646) Boundary_loss: 0.013897 (0.013899) Loss: 0.47495 (0.55036) +2025-09-13,05:31:49 | INFO | Train Epoch: 5 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.62988 (0.55514) Boundary_loss: 0.013899 (0.013899) Loss: 0.64378 (0.56904) +2025-09-13,05:32:20 | INFO | Train Epoch: 5 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.56793 (0.55728) Boundary_loss: 0.013897 (0.013899) Loss: 0.58183 (0.57117) +2025-09-13,05:32:51 | INFO | Train Epoch: 5 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.57123 (0.55927) Boundary_loss: 0.013897 (0.013899) Loss: 0.58513 (0.57317) +2025-09-13,05:33:22 | INFO | Train Epoch: 5 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.54375 (0.55733) Boundary_loss: 0.013897 (0.013899) Loss: 0.55764 (0.57123) +2025-09-13,05:33:53 | INFO | Train Epoch: 5 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.55356 (0.55691) Boundary_loss: 0.013900 (0.013899) Loss: 0.56746 (0.57081) +2025-09-13,05:34:24 | INFO | Train Epoch: 5 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.63899 (0.56512) Boundary_loss: 0.013898 (0.013899) Loss: 0.65289 (0.57902) +2025-09-13,05:34:55 | INFO | Train Epoch: 5 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.64875 (0.57272) Boundary_loss: 0.013899 (0.013899) Loss: 0.66265 (0.58662) +2025-09-13,05:35:26 | INFO | Train Epoch: 5 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.57086 (0.57257) Boundary_loss: 0.013898 (0.013899) Loss: 0.58475 (0.58646) +2025-09-13,05:35:57 | INFO | Train Epoch: 5 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.68576 (0.58127) Boundary_loss: 0.013898 (0.013899) Loss: 0.69965 (0.59517) +2025-09-13,05:36:27 | INFO | Train Epoch: 5 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.50579 (0.57588) Boundary_loss: 0.013898 (0.013899) Loss: 0.51969 (0.58978) +2025-09-13,05:36:58 | INFO | Train Epoch: 5 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.59995 (0.57749) Boundary_loss: 0.013896 (0.013898) Loss: 0.61385 (0.59138) +2025-09-13,05:37:29 | INFO | Train Epoch: 5 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.53551 (0.57486) Boundary_loss: 0.013899 (0.013898) Loss: 0.54941 (0.58876) +2025-09-13,05:38:00 | INFO | Train Epoch: 5 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.52218 (0.57176) Boundary_loss: 0.013896 (0.013898) Loss: 0.53608 (0.58566) +2025-09-13,05:38:31 | INFO | Train Epoch: 5 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.51322 (0.56851) Boundary_loss: 0.013898 (0.013898) Loss: 0.52712 (0.58241) +2025-09-13,05:39:02 | INFO | Train Epoch: 5 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.53402 (0.56670) Boundary_loss: 0.013896 (0.013898) Loss: 0.54792 (0.58059) +2025-09-13,05:39:33 | INFO | Train Epoch: 5 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.44747 (0.56073) Boundary_loss: 0.013899 (0.013898) Loss: 0.46137 (0.57463) +2025-09-13,05:40:04 | INFO | Train Epoch: 5 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.56717 (0.56104) Boundary_loss: 0.013898 (0.013898) Loss: 0.58106 (0.57494) +2025-09-13,05:40:35 | INFO | Train Epoch: 5 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.50465 (0.55848) Boundary_loss: 0.013898 (0.013898) Loss: 0.51855 (0.57238) +2025-09-13,05:41:07 | INFO | Train Epoch: 5 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.58739 (0.55973) Boundary_loss: 0.013898 (0.013898) Loss: 0.60128 (0.57363) +2025-09-13,05:41:38 | INFO | Train Epoch: 5 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.51510 (0.55788) Boundary_loss: 0.013898 (0.013898) Loss: 0.52900 (0.57177) +2025-09-13,05:42:09 | INFO | Train Epoch: 5 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.57845 (0.55870) Boundary_loss: 0.013901 (0.013898) Loss: 0.59236 (0.57260) +2025-09-13,05:42:40 | INFO | Train Epoch: 5 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.53991 (0.55798) Boundary_loss: 0.013896 (0.013898) Loss: 0.55380 (0.57187) +2025-09-13,05:43:11 | INFO | Train Epoch: 5 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.63869 (0.56097) Boundary_loss: 0.013937 (0.013900) Loss: 0.65263 (0.57486) +2025-09-13,05:43:42 | INFO | Train Epoch: 5 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.59380 (0.56214) Boundary_loss: 0.013900 (0.013900) Loss: 0.60770 (0.57604) +2025-09-13,05:44:13 | INFO | Train Epoch: 5 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.66979 (0.56585) Boundary_loss: 0.013898 (0.013900) Loss: 0.68369 (0.57975) +2025-09-13,05:44:44 | INFO | Train Epoch: 5 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.66190 (0.56905) Boundary_loss: 0.013896 (0.013899) Loss: 0.67579 (0.58295) +2025-09-13,05:45:15 | INFO | Train Epoch: 5 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.57539 (0.56926) Boundary_loss: 0.013900 (0.013899) Loss: 0.58929 (0.58316) +2025-09-13,05:45:46 | INFO | Train Epoch: 5 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.65510 (0.57194) Boundary_loss: 0.013899 (0.013899) Loss: 0.66900 (0.58584) +2025-09-13,05:46:17 | INFO | Train Epoch: 5 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.50567 (0.56993) Boundary_loss: 0.013896 (0.013899) Loss: 0.51956 (0.58383) +2025-09-13,05:46:48 | INFO | Train Epoch: 5 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.50527 (0.56803) Boundary_loss: 0.013902 (0.013899) Loss: 0.51918 (0.58193) +2025-09-13,05:47:19 | INFO | Train Epoch: 5 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.61870 (0.56948) Boundary_loss: 0.013902 (0.013899) Loss: 0.63260 (0.58338) +2025-09-13,05:47:50 | INFO | Train Epoch: 5 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.61728 (0.57080) Boundary_loss: 0.013917 (0.013900) Loss: 0.63120 (0.58470) +2025-09-13,05:48:21 | INFO | Train Epoch: 5 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.61859 (0.57210) Boundary_loss: 0.013898 (0.013900) Loss: 0.63248 (0.58600) +2025-09-13,05:48:51 | INFO | Train Epoch: 5 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.59526 (0.57271) Boundary_loss: 0.013899 (0.013900) Loss: 0.60916 (0.58661) +2025-09-13,05:49:22 | INFO | Train Epoch: 5 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.54000 (0.57187) Boundary_loss: 0.013911 (0.013900) Loss: 0.55391 (0.58577) +2025-09-13,05:49:53 | INFO | Train Epoch: 5 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.57505 (0.57195) Boundary_loss: 0.013898 (0.013900) Loss: 0.58895 (0.58585) +2025-09-13,05:50:24 | INFO | Train Epoch: 5 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.54599 (0.57131) Boundary_loss: 0.013898 (0.013900) Loss: 0.55989 (0.58521) +2025-09-13,05:50:55 | INFO | Train Epoch: 5 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.51845 (0.57005) Boundary_loss: 0.013897 (0.013900) Loss: 0.53235 (0.58395) +2025-09-13,05:51:27 | INFO | Train Epoch: 5 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.55196 (0.56963) Boundary_loss: 0.013896 (0.013900) Loss: 0.56586 (0.58353) +2025-09-13,05:51:58 | INFO | Train Epoch: 5 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.45156 (0.56695) Boundary_loss: 0.013897 (0.013900) Loss: 0.46546 (0.58085) +2025-09-13,05:52:29 | INFO | Train Epoch: 5 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.60867 (0.56788) Boundary_loss: 0.013901 (0.013900) Loss: 0.62257 (0.58178) +2025-09-13,05:52:59 | INFO | Train Epoch: 5 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.58483 (0.56825) Boundary_loss: 0.013901 (0.013900) Loss: 0.59873 (0.58215) +2025-09-13,05:53:30 | INFO | Train Epoch: 5 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.49075 (0.56660) Boundary_loss: 0.013898 (0.013900) Loss: 0.50464 (0.58050) +2025-09-13,05:54:01 | INFO | Train Epoch: 5 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.55625 (0.56638) Boundary_loss: 0.013898 (0.013900) Loss: 0.57014 (0.58028) +2025-09-13,05:54:32 | INFO | Train Epoch: 5 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.61240 (0.56732) Boundary_loss: 0.013902 (0.013900) Loss: 0.62630 (0.58122) +2025-09-13,05:55:03 | INFO | Train Epoch: 5 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.61618 (0.56830) Boundary_loss: 0.013895 (0.013900) Loss: 0.63007 (0.58220) +2025-09-13,05:55:34 | INFO | Train Epoch: 5 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.51577 (0.56727) Boundary_loss: 0.013897 (0.013900) Loss: 0.52966 (0.58117) +2025-09-13,05:56:05 | INFO | Train Epoch: 5 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.54432 (0.56683) Boundary_loss: 0.013898 (0.013900) Loss: 0.55822 (0.58073) +2025-09-13,05:56:35 | INFO | Train Epoch: 5 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.53572 (0.56624) Boundary_loss: 0.013900 (0.013900) Loss: 0.54962 (0.58014) +2025-09-13,05:57:06 | INFO | Train Epoch: 5 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.57069 (0.56632) Boundary_loss: 0.013897 (0.013900) Loss: 0.58458 (0.58022) +2025-09-13,05:57:37 | INFO | Train Epoch: 5 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.49422 (0.56501) Boundary_loss: 0.013898 (0.013900) Loss: 0.50812 (0.57891) +2025-09-13,05:58:08 | INFO | Train Epoch: 5 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.69214 (0.56728) Boundary_loss: 0.013897 (0.013900) Loss: 0.70603 (0.58118) +2025-09-13,05:58:39 | INFO | Train Epoch: 5 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.59573 (0.56778) Boundary_loss: 0.013902 (0.013900) Loss: 0.60963 (0.58168) +2025-09-13,05:59:10 | INFO | Train Epoch: 5 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.56736 (0.56777) Boundary_loss: 0.013897 (0.013900) Loss: 0.58125 (0.58167) +2025-09-13,05:59:41 | INFO | Train Epoch: 5 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.74881 (0.57084) Boundary_loss: 0.013897 (0.013899) Loss: 0.76271 (0.58474) +2025-09-13,06:00:12 | INFO | Train Epoch: 5 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.62689 (0.57178) Boundary_loss: 0.013896 (0.013899) Loss: 0.64078 (0.58567) +2025-09-13,06:00:43 | INFO | Train Epoch: 5 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.48256 (0.57031) Boundary_loss: 0.013896 (0.013899) Loss: 0.49646 (0.58421) +2025-09-13,06:01:14 | INFO | Train Epoch: 5 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.57170 (0.57034) Boundary_loss: 0.013898 (0.013899) Loss: 0.58560 (0.58423) +2025-09-13,06:01:45 | INFO | Train Epoch: 5 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.66731 (0.57187) Boundary_loss: 0.013897 (0.013899) Loss: 0.68121 (0.58577) +2025-09-13,06:02:15 | INFO | Train Epoch: 5 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.56757 (0.57181) Boundary_loss: 0.013897 (0.013899) Loss: 0.58147 (0.58571) +2025-09-13,06:02:46 | INFO | Train Epoch: 5 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.62361 (0.57260) Boundary_loss: 0.013899 (0.013899) Loss: 0.63751 (0.58650) +2025-09-13,06:03:17 | INFO | Train Epoch: 5 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.52379 (0.57186) Boundary_loss: 0.013900 (0.013899) Loss: 0.53769 (0.58576) +2025-09-13,06:03:48 | INFO | Train Epoch: 5 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.59506 (0.57221) Boundary_loss: 0.013901 (0.013899) Loss: 0.60896 (0.58611) +2025-09-13,06:04:19 | INFO | Train Epoch: 5 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.40809 (0.56980) Boundary_loss: 0.013900 (0.013899) Loss: 0.42199 (0.58370) +2025-09-13,06:04:50 | INFO | Train Epoch: 5 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.63152 (0.57069) Boundary_loss: 0.013903 (0.013899) Loss: 0.64542 (0.58459) +2025-09-13,06:05:21 | INFO | Train Epoch: 5 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.58971 (0.57096) Boundary_loss: 0.013898 (0.013899) Loss: 0.60361 (0.58486) +2025-09-13,06:05:52 | INFO | Train Epoch: 5 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.59744 (0.57134) Boundary_loss: 0.013899 (0.013899) Loss: 0.61134 (0.58524) +2025-09-13,06:06:23 | INFO | Train Epoch: 5 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.60519 (0.57181) Boundary_loss: 0.013900 (0.013899) Loss: 0.61909 (0.58571) +2025-09-13,06:06:53 | INFO | Train Epoch: 5 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.51429 (0.57102) Boundary_loss: 0.013901 (0.013899) Loss: 0.52819 (0.58492) +2025-09-13,06:07:24 | INFO | Train Epoch: 5 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.60740 (0.57151) Boundary_loss: 0.013898 (0.013899) Loss: 0.62130 (0.58541) +2025-09-13,06:07:55 | INFO | Train Epoch: 5 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.58357 (0.57167) Boundary_loss: 0.013904 (0.013899) Loss: 0.59747 (0.58557) +2025-09-13,06:08:26 | INFO | Train Epoch: 5 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.61084 (0.57219) Boundary_loss: 0.013900 (0.013899) Loss: 0.62474 (0.58609) +2025-09-13,06:08:57 | INFO | Train Epoch: 5 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.56755 (0.57213) Boundary_loss: 0.013900 (0.013899) Loss: 0.58145 (0.58603) +2025-09-13,06:09:28 | INFO | Train Epoch: 5 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.58852 (0.57234) Boundary_loss: 0.013902 (0.013899) Loss: 0.60243 (0.58624) +2025-09-13,06:09:59 | INFO | Train Epoch: 5 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.60685 (0.57277) Boundary_loss: 0.013896 (0.013899) Loss: 0.62074 (0.58667) +2025-09-13,06:10:30 | INFO | Train Epoch: 5 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.53169 (0.57226) Boundary_loss: 0.013896 (0.013899) Loss: 0.54558 (0.58616) +2025-09-13,06:11:01 | INFO | Train Epoch: 5 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.52113 (0.57163) Boundary_loss: 0.013907 (0.013899) Loss: 0.53504 (0.58553) +2025-09-13,06:11:32 | INFO | Train Epoch: 5 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.55230 (0.57139) Boundary_loss: 0.013901 (0.013899) Loss: 0.56620 (0.58529) +2025-09-13,06:12:03 | INFO | Train Epoch: 5 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.61321 (0.57190) Boundary_loss: 0.013898 (0.013899) Loss: 0.62711 (0.58580) +2025-09-13,06:12:34 | INFO | Train Epoch: 5 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.64776 (0.57280) Boundary_loss: 0.013897 (0.013899) Loss: 0.66166 (0.58670) +2025-09-13,06:13:05 | INFO | Train Epoch: 5 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.55598 (0.57260) Boundary_loss: 0.013896 (0.013899) Loss: 0.56987 (0.58650) +2025-09-13,06:13:36 | INFO | Train Epoch: 5 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.54436 (0.57227) Boundary_loss: 0.013896 (0.013899) Loss: 0.55826 (0.58617) +2025-09-13,06:14:07 | INFO | Train Epoch: 5 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.63955 (0.57305) Boundary_loss: 0.013897 (0.013899) Loss: 0.65345 (0.58695) +2025-09-13,06:14:38 | INFO | Train Epoch: 5 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.52824 (0.57254) Boundary_loss: 0.013896 (0.013899) Loss: 0.54213 (0.58644) +2025-09-13,06:15:09 | INFO | Train Epoch: 5 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.62792 (0.57316) Boundary_loss: 0.013902 (0.013899) Loss: 0.64183 (0.58706) +2025-09-13,06:15:40 | INFO | Train Epoch: 5 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.54795 (0.57288) Boundary_loss: 0.013902 (0.013899) Loss: 0.56185 (0.58678) +2025-09-13,06:16:11 | INFO | Train Epoch: 5 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.58199 (0.57298) Boundary_loss: 0.013903 (0.013899) Loss: 0.59589 (0.58688) +2025-09-13,06:16:42 | INFO | Train Epoch: 5 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.46296 (0.57178) Boundary_loss: 0.013896 (0.013899) Loss: 0.47686 (0.58568) +2025-09-13,06:17:13 | INFO | Train Epoch: 5 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.58590 (0.57194) Boundary_loss: 0.013900 (0.013899) Loss: 0.59980 (0.58584) +2025-09-13,06:17:44 | INFO | Train Epoch: 5 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.59333 (0.57216) Boundary_loss: 0.013904 (0.013899) Loss: 0.60724 (0.58606) +2025-09-13,06:18:15 | INFO | Train Epoch: 5 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.54324 (0.57186) Boundary_loss: 0.013897 (0.013899) Loss: 0.55714 (0.58576) +2025-09-13,06:18:46 | INFO | Train Epoch: 5 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.54472 (0.57158) Boundary_loss: 0.013899 (0.013899) Loss: 0.55862 (0.58548) +2025-09-13,06:19:17 | INFO | Train Epoch: 5 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.47619 (0.57059) Boundary_loss: 0.013900 (0.013899) Loss: 0.49009 (0.58449) +2025-09-13,06:19:48 | INFO | Train Epoch: 5 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.67210 (0.57163) Boundary_loss: 0.013901 (0.013899) Loss: 0.68600 (0.58553) +2025-09-13,06:20:18 | INFO | Train Epoch: 5 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.62640 (0.57218) Boundary_loss: 0.013897 (0.013899) Loss: 0.64029 (0.58608) +2025-09-13,06:20:49 | INFO | Train Epoch: 5 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.69224 (0.57338) Boundary_loss: 0.013897 (0.013899) Loss: 0.70614 (0.58728) +2025-09-13,06:21:20 | INFO | Train Epoch: 5 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.49654 (0.57262) Boundary_loss: 0.013897 (0.013899) Loss: 0.51044 (0.58652) +2025-09-13,06:21:51 | INFO | Train Epoch: 5 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.61440 (0.57303) Boundary_loss: 0.013899 (0.013899) Loss: 0.62830 (0.58693) +2025-09-13,06:22:22 | INFO | Train Epoch: 5 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.62925 (0.57358) Boundary_loss: 0.013896 (0.013899) Loss: 0.64315 (0.58748) +2025-09-13,06:22:52 | INFO | Train Epoch: 5 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.55022 (0.57335) Boundary_loss: 0.013898 (0.013899) Loss: 0.56412 (0.58725) +2025-09-13,06:23:23 | INFO | Train Epoch: 5 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.46814 (0.57235) Boundary_loss: 0.013896 (0.013899) Loss: 0.48203 (0.58625) +2025-09-13,06:23:54 | INFO | Train Epoch: 5 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.54502 (0.57209) Boundary_loss: 0.013901 (0.013899) Loss: 0.55892 (0.58599) +2025-09-13,06:24:25 | INFO | Train Epoch: 5 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.64999 (0.57282) Boundary_loss: 0.013910 (0.013899) Loss: 0.66390 (0.58672) +2025-09-13,06:24:56 | INFO | Train Epoch: 5 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.52813 (0.57241) Boundary_loss: 0.013898 (0.013899) Loss: 0.54202 (0.58631) +2025-09-13,06:25:27 | INFO | Train Epoch: 5 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.50338 (0.57177) Boundary_loss: 0.013899 (0.013899) Loss: 0.51728 (0.58567) +2025-09-13,06:25:58 | INFO | Train Epoch: 5 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.69459 (0.57289) Boundary_loss: 0.013895 (0.013899) Loss: 0.70849 (0.58679) +2025-09-13,06:26:28 | INFO | Train Epoch: 5 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.51089 (0.57233) Boundary_loss: 0.013904 (0.013899) Loss: 0.52479 (0.58623) +2025-09-13,06:26:59 | INFO | Train Epoch: 5 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.53609 (0.57201) Boundary_loss: 0.013897 (0.013899) Loss: 0.54999 (0.58591) +2025-09-13,06:27:30 | INFO | Train Epoch: 5 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.54007 (0.57173) Boundary_loss: 0.013897 (0.013899) Loss: 0.55397 (0.58562) +2025-09-13,06:28:01 | INFO | Train Epoch: 5 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.48780 (0.57099) Boundary_loss: 0.013901 (0.013899) Loss: 0.50170 (0.58489) +2025-09-13,06:28:32 | INFO | Train Epoch: 5 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.52610 (0.57060) Boundary_loss: 0.013898 (0.013899) Loss: 0.54000 (0.58450) +2025-09-13,06:29:02 | INFO | Train Epoch: 5 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.55651 (0.57048) Boundary_loss: 0.013900 (0.013899) Loss: 0.57041 (0.58438) +2025-09-13,06:29:34 | INFO | Train Epoch: 5 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.56419 (0.57042) Boundary_loss: 0.013897 (0.013899) Loss: 0.57808 (0.58432) +2025-09-13,06:30:05 | INFO | Train Epoch: 5 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.71208 (0.57162) Boundary_loss: 0.013899 (0.013899) Loss: 0.72598 (0.58552) +2025-09-13,06:30:36 | INFO | Train Epoch: 5 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.60997 (0.57195) Boundary_loss: 0.013896 (0.013899) Loss: 0.62387 (0.58585) +2025-09-13,06:31:07 | INFO | Train Epoch: 5 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.54670 (0.57174) Boundary_loss: 0.013898 (0.013899) Loss: 0.56060 (0.58564) +2025-09-13,06:31:38 | INFO | Train Epoch: 5 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.49511 (0.57110) Boundary_loss: 0.013900 (0.013899) Loss: 0.50901 (0.58500) +2025-09-13,06:32:09 | INFO | Train Epoch: 5 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.64181 (0.57168) Boundary_loss: 0.013897 (0.013899) Loss: 0.65571 (0.58558) +2025-09-13,06:32:40 | INFO | Train Epoch: 5 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.52178 (0.57128) Boundary_loss: 0.013898 (0.013899) Loss: 0.53568 (0.58518) +2025-09-13,06:33:11 | INFO | Train Epoch: 5 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.54660 (0.57108) Boundary_loss: 0.013898 (0.013899) Loss: 0.56049 (0.58498) +2025-09-13,06:33:42 | INFO | Train Epoch: 5 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.56526 (0.57103) Boundary_loss: 0.013900 (0.013899) Loss: 0.57916 (0.58493) +2025-09-13,06:34:12 | INFO | Train Epoch: 5 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.49477 (0.57043) Boundary_loss: 0.013898 (0.013899) Loss: 0.50867 (0.58433) +2025-09-13,06:34:43 | INFO | Train Epoch: 5 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59049 (0.57058) Boundary_loss: 0.013896 (0.013899) Loss: 0.60439 (0.58448) +2025-09-13,06:35:14 | INFO | Train Epoch: 5 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.53652 (0.57032) Boundary_loss: 0.013902 (0.013899) Loss: 0.55043 (0.58422) +2025-09-13,06:35:45 | INFO | Train Epoch: 5 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.62927 (0.57077) Boundary_loss: 0.013897 (0.013899) Loss: 0.64316 (0.58467) +2025-09-13,06:36:16 | INFO | Train Epoch: 5 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.65009 (0.57138) Boundary_loss: 0.013899 (0.013899) Loss: 0.66399 (0.58528) +2025-09-13,06:36:47 | INFO | Train Epoch: 5 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.48130 (0.57070) Boundary_loss: 0.013898 (0.013899) Loss: 0.49520 (0.58460) +2025-09-13,06:37:18 | INFO | Train Epoch: 5 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.50663 (0.57021) Boundary_loss: 0.013897 (0.013899) Loss: 0.52052 (0.58411) +2025-09-13,06:37:49 | INFO | Train Epoch: 5 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.59687 (0.57041) Boundary_loss: 0.013897 (0.013899) Loss: 0.61077 (0.58431) +2025-09-13,06:38:20 | INFO | Train Epoch: 5 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.64383 (0.57096) Boundary_loss: 0.013897 (0.013899) Loss: 0.65773 (0.58486) +2025-09-13,06:38:51 | INFO | Train Epoch: 5 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.58836 (0.57109) Boundary_loss: 0.013898 (0.013899) Loss: 0.60226 (0.58499) +2025-09-13,06:39:22 | INFO | Train Epoch: 5 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.49058 (0.57050) Boundary_loss: 0.013898 (0.013899) Loss: 0.50448 (0.58440) +2025-09-13,06:39:53 | INFO | Train Epoch: 5 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.57499 (0.57053) Boundary_loss: 0.013898 (0.013899) Loss: 0.58889 (0.58443) +2025-09-13,06:40:24 | INFO | Train Epoch: 5 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.68492 (0.57136) Boundary_loss: 0.013896 (0.013899) Loss: 0.69881 (0.58526) +2025-09-13,06:40:55 | INFO | Train Epoch: 5 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.53231 (0.57108) Boundary_loss: 0.013897 (0.013899) Loss: 0.54620 (0.58498) +2025-09-13,06:41:26 | INFO | Train Epoch: 5 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.59056 (0.57122) Boundary_loss: 0.013897 (0.013899) Loss: 0.60446 (0.58512) +2025-09-13,06:41:57 | INFO | Train Epoch: 5 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.61226 (0.57151) Boundary_loss: 0.013896 (0.013899) Loss: 0.62616 (0.58541) +2025-09-13,06:42:28 | INFO | Train Epoch: 5 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.57926 (0.57156) Boundary_loss: 0.013899 (0.013899) Loss: 0.59316 (0.58546) +2025-09-13,06:42:59 | INFO | Train Epoch: 5 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.57675 (0.57160) Boundary_loss: 0.013899 (0.013899) Loss: 0.59065 (0.58550) +2025-09-13,06:43:30 | INFO | Train Epoch: 5 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.62592 (0.57198) Boundary_loss: 0.013898 (0.013899) Loss: 0.63982 (0.58588) +2025-09-13,06:44:01 | INFO | Train Epoch: 5 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.60170 (0.57218) Boundary_loss: 0.013899 (0.013899) Loss: 0.61560 (0.58608) +2025-09-13,06:44:32 | INFO | Train Epoch: 5 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.56307 (0.57212) Boundary_loss: 0.013898 (0.013899) Loss: 0.57697 (0.58602) +2025-09-13,06:45:03 | INFO | Train Epoch: 5 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.56373 (0.57206) Boundary_loss: 0.013896 (0.013899) Loss: 0.57763 (0.58596) +2025-09-13,06:45:34 | INFO | Train Epoch: 5 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.52041 (0.57171) Boundary_loss: 0.013896 (0.013899) Loss: 0.53430 (0.58561) +2025-09-13,06:46:05 | INFO | Train Epoch: 5 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.63990 (0.57217) Boundary_loss: 0.013899 (0.013899) Loss: 0.65380 (0.58607) +2025-09-13,06:46:36 | INFO | Train Epoch: 5 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.50386 (0.57171) Boundary_loss: 0.013899 (0.013899) Loss: 0.51776 (0.58561) +2025-09-13,06:47:06 | INFO | Train Epoch: 5 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.62803 (0.57209) Boundary_loss: 0.013902 (0.013899) Loss: 0.64193 (0.58599) +2025-09-13,06:47:37 | INFO | Train Epoch: 5 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.62904 (0.57246) Boundary_loss: 0.013896 (0.013899) Loss: 0.64294 (0.58636) +2025-09-13,06:48:08 | INFO | Train Epoch: 5 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.56139 (0.57239) Boundary_loss: 0.013897 (0.013899) Loss: 0.57529 (0.58629) +2025-09-13,06:48:39 | INFO | Train Epoch: 5 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.48903 (0.57185) Boundary_loss: 0.013896 (0.013899) Loss: 0.50292 (0.58575) +2025-09-13,06:49:10 | INFO | Train Epoch: 5 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.55748 (0.57176) Boundary_loss: 0.013904 (0.013899) Loss: 0.57139 (0.58566) +2025-09-13,06:49:40 | INFO | Train Epoch: 5 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46866 (0.57110) Boundary_loss: 0.013898 (0.013899) Loss: 0.48256 (0.58499) +2025-09-13,06:50:11 | INFO | Train Epoch: 5 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.52826 (0.57082) Boundary_loss: 0.013908 (0.013899) Loss: 0.54217 (0.58472) +2025-09-13,06:50:42 | INFO | Train Epoch: 5 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.54704 (0.57067) Boundary_loss: 0.013897 (0.013899) Loss: 0.56094 (0.58457) +2025-09-13,06:51:13 | INFO | Train Epoch: 5 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.69429 (0.57145) Boundary_loss: 0.013896 (0.013899) Loss: 0.70819 (0.58535) +2025-09-13,06:51:44 | INFO | Train Epoch: 5 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.55513 (0.57135) Boundary_loss: 0.013900 (0.013899) Loss: 0.56903 (0.58525) +2025-09-13,06:52:15 | INFO | Train Epoch: 5 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.60509 (0.57156) Boundary_loss: 0.013898 (0.013899) Loss: 0.61899 (0.58546) +2025-09-13,06:52:46 | INFO | Train Epoch: 5 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.52121 (0.57125) Boundary_loss: 0.013896 (0.013899) Loss: 0.53510 (0.58515) +2025-09-13,06:53:17 | INFO | Train Epoch: 5 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.59297 (0.57138) Boundary_loss: 0.013900 (0.013899) Loss: 0.60688 (0.58528) +2025-09-13,06:53:48 | INFO | Train Epoch: 5 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.58392 (0.57146) Boundary_loss: 0.013898 (0.013899) Loss: 0.59782 (0.58536) +2025-09-13,06:54:19 | INFO | Train Epoch: 5 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.61039 (0.57169) Boundary_loss: 0.013896 (0.013899) Loss: 0.62429 (0.58559) +2025-09-13,06:54:50 | INFO | Train Epoch: 5 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.59105 (0.57181) Boundary_loss: 0.013897 (0.013899) Loss: 0.60494 (0.58571) +2025-09-13,06:55:21 | INFO | Train Epoch: 5 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.55696 (0.57172) Boundary_loss: 0.013899 (0.013899) Loss: 0.57085 (0.58562) +2025-09-13,06:55:52 | INFO | Train Epoch: 5 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.51622 (0.57139) Boundary_loss: 0.013897 (0.013899) Loss: 0.53012 (0.58529) +2025-09-13,06:56:23 | INFO | Train Epoch: 5 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.62432 (0.57170) Boundary_loss: 0.013897 (0.013899) Loss: 0.63822 (0.58560) +2025-09-13,06:56:53 | INFO | Train Epoch: 5 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.59519 (0.57184) Boundary_loss: 0.013897 (0.013899) Loss: 0.60909 (0.58574) +2025-09-13,06:57:24 | INFO | Train Epoch: 5 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.53646 (0.57163) Boundary_loss: 0.013896 (0.013899) Loss: 0.55036 (0.58553) +2025-09-13,06:57:55 | INFO | Train Epoch: 5 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.63143 (0.57198) Boundary_loss: 0.013897 (0.013899) Loss: 0.64533 (0.58588) +2025-09-13,06:58:26 | INFO | Train Epoch: 5 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.52725 (0.57172) Boundary_loss: 0.013901 (0.013899) Loss: 0.54116 (0.58562) +2025-09-13,06:58:56 | INFO | Train Epoch: 5 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.54372 (0.57156) Boundary_loss: 0.013898 (0.013899) Loss: 0.55762 (0.58546) +2025-09-13,06:59:27 | INFO | Train Epoch: 5 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.46559 (0.57096) Boundary_loss: 0.013898 (0.013899) Loss: 0.47949 (0.58486) +2025-09-13,06:59:58 | INFO | Train Epoch: 5 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.51390 (0.57063) Boundary_loss: 0.013896 (0.013899) Loss: 0.52779 (0.58453) +2025-09-13,07:00:29 | INFO | Train Epoch: 5 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.56746 (0.57061) Boundary_loss: 0.013899 (0.013899) Loss: 0.58136 (0.58451) +2025-09-13,07:01:00 | INFO | Train Epoch: 5 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.55226 (0.57051) Boundary_loss: 0.013896 (0.013899) Loss: 0.56616 (0.58441) +2025-09-13,07:01:30 | INFO | Train Epoch: 5 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.52777 (0.57027) Boundary_loss: 0.013931 (0.013899) Loss: 0.54170 (0.58417) +2025-09-13,07:02:02 | INFO | Train Epoch: 5 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.51091 (0.56994) Boundary_loss: 0.013897 (0.013899) Loss: 0.52481 (0.58384) +2025-09-13,07:02:33 | INFO | Train Epoch: 5 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.59012 (0.57005) Boundary_loss: 0.013897 (0.013899) Loss: 0.60401 (0.58395) +2025-09-13,07:03:04 | INFO | Train Epoch: 5 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.69984 (0.57077) Boundary_loss: 0.013900 (0.013899) Loss: 0.71374 (0.58467) +2025-09-13,07:03:34 | INFO | Train Epoch: 5 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.61891 (0.57103) Boundary_loss: 0.013896 (0.013899) Loss: 0.63280 (0.58493) +2025-09-13,07:04:05 | INFO | Train Epoch: 5 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.52903 (0.57080) Boundary_loss: 0.013900 (0.013899) Loss: 0.54293 (0.58470) +2025-09-13,07:04:36 | INFO | Train Epoch: 5 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.70543 (0.57153) Boundary_loss: 0.013898 (0.013899) Loss: 0.71933 (0.58543) +2025-09-13,07:05:07 | INFO | Train Epoch: 5 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.58140 (0.57158) Boundary_loss: 0.013899 (0.013899) Loss: 0.59530 (0.58548) +2025-09-13,07:05:38 | INFO | Train Epoch: 5 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.56795 (0.57156) Boundary_loss: 0.013897 (0.013899) Loss: 0.58185 (0.58546) +2025-09-13,07:06:09 | INFO | Train Epoch: 5 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.57236 (0.57157) Boundary_loss: 0.013895 (0.013899) Loss: 0.58625 (0.58547) +2025-09-13,07:06:39 | INFO | Train Epoch: 5 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.48555 (0.57111) Boundary_loss: 0.013897 (0.013899) Loss: 0.49944 (0.58501) +2025-09-13,07:07:10 | INFO | Train Epoch: 5 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.61930 (0.57137) Boundary_loss: 0.013894 (0.013899) Loss: 0.63320 (0.58527) +2025-09-13,07:07:41 | INFO | Train Epoch: 5 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.43064 (0.57063) Boundary_loss: 0.013910 (0.013899) Loss: 0.44455 (0.58453) +2025-09-13,07:08:12 | INFO | Train Epoch: 5 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.52460 (0.57039) Boundary_loss: 0.013897 (0.013899) Loss: 0.53850 (0.58429) +2025-09-13,07:08:43 | INFO | Train Epoch: 5 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.59284 (0.57051) Boundary_loss: 0.013900 (0.013899) Loss: 0.60674 (0.58441) +2025-09-13,07:09:14 | INFO | Train Epoch: 5 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.58733 (0.57059) Boundary_loss: 0.013897 (0.013899) Loss: 0.60123 (0.58449) +2025-09-13,07:09:45 | INFO | Train Epoch: 5 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.60000 (0.57074) Boundary_loss: 0.013898 (0.013899) Loss: 0.61390 (0.58464) +2025-09-13,07:10:16 | INFO | Train Epoch: 5 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.53089 (0.57054) Boundary_loss: 0.013900 (0.013899) Loss: 0.54479 (0.58444) +2025-09-13,07:10:47 | INFO | Train Epoch: 5 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.57152 (0.57055) Boundary_loss: 0.013897 (0.013899) Loss: 0.58542 (0.58444) +2025-09-13,07:11:18 | INFO | Train Epoch: 5 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.44985 (0.56994) Boundary_loss: 0.013903 (0.013899) Loss: 0.46375 (0.58383) +2025-09-13,07:11:49 | INFO | Train Epoch: 5 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.51553 (0.56966) Boundary_loss: 0.013898 (0.013899) Loss: 0.52943 (0.58356) +2025-09-13,07:12:20 | INFO | Train Epoch: 5 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.56678 (0.56965) Boundary_loss: 0.013897 (0.013899) Loss: 0.58068 (0.58355) +2025-09-13,07:12:50 | INFO | Train Epoch: 5 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.59223 (0.56976) Boundary_loss: 0.013897 (0.013899) Loss: 0.60613 (0.58366) +2025-09-13,07:13:21 | INFO | Train Epoch: 5 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.59738 (0.56990) Boundary_loss: 0.013897 (0.013899) Loss: 0.61127 (0.58380) +2025-09-13,07:13:52 | INFO | Train Epoch: 5 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.57156 (0.56991) Boundary_loss: 0.013898 (0.013899) Loss: 0.58546 (0.58380) +2025-09-13,07:14:23 | INFO | Train Epoch: 5 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.59381 (0.57002) Boundary_loss: 0.013896 (0.013899) Loss: 0.60770 (0.58392) +2025-09-13,07:14:54 | INFO | Train Epoch: 5 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.62142 (0.57027) Boundary_loss: 0.013898 (0.013899) Loss: 0.63532 (0.58417) +2025-09-13,07:15:25 | INFO | Train Epoch: 5 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.70159 (0.57091) Boundary_loss: 0.013898 (0.013899) Loss: 0.71549 (0.58481) +2025-09-13,07:15:56 | INFO | Train Epoch: 5 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.52157 (0.57067) Boundary_loss: 0.013897 (0.013899) Loss: 0.53546 (0.58457) +2025-09-13,07:16:26 | INFO | Train Epoch: 5 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.54759 (0.57056) Boundary_loss: 0.013899 (0.013899) Loss: 0.56149 (0.58446) +2025-09-13,07:16:57 | INFO | Train Epoch: 5 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.41600 (0.56982) Boundary_loss: 0.013898 (0.013899) Loss: 0.42989 (0.58372) +2025-09-13,07:17:28 | INFO | Train Epoch: 5 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.54124 (0.56969) Boundary_loss: 0.013897 (0.013899) Loss: 0.55514 (0.58358) +2025-09-13,07:17:59 | INFO | Train Epoch: 5 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.56287 (0.56965) Boundary_loss: 0.013899 (0.013899) Loss: 0.57677 (0.58355) +2025-09-13,07:18:30 | INFO | Train Epoch: 5 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.58705 (0.56974) Boundary_loss: 0.013897 (0.013899) Loss: 0.60095 (0.58363) +2025-09-13,07:19:01 | INFO | Train Epoch: 5 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.63309 (0.57003) Boundary_loss: 0.013896 (0.013899) Loss: 0.64699 (0.58393) +2025-09-13,07:19:32 | INFO | Train Epoch: 5 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.48761 (0.56965) Boundary_loss: 0.013897 (0.013899) Loss: 0.50151 (0.58355) +2025-09-13,07:20:03 | INFO | Train Epoch: 5 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.56874 (0.56964) Boundary_loss: 0.013900 (0.013899) Loss: 0.58264 (0.58354) +2025-09-13,07:20:34 | INFO | Train Epoch: 5 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.64271 (0.56998) Boundary_loss: 0.013895 (0.013899) Loss: 0.65660 (0.58388) +2025-09-13,07:21:05 | INFO | Train Epoch: 5 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.60244 (0.57013) Boundary_loss: 0.013900 (0.013899) Loss: 0.61634 (0.58403) +2025-09-13,07:21:36 | INFO | Train Epoch: 5 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.64044 (0.57045) Boundary_loss: 0.013896 (0.013899) Loss: 0.65433 (0.58435) +2025-09-13,07:22:07 | INFO | Train Epoch: 5 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.57990 (0.57050) Boundary_loss: 0.013897 (0.013899) Loss: 0.59379 (0.58440) +2025-09-13,07:22:38 | INFO | Train Epoch: 5 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.54767 (0.57039) Boundary_loss: 0.013898 (0.013899) Loss: 0.56157 (0.58429) +2025-09-13,07:23:09 | INFO | Train Epoch: 5 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.56285 (0.57036) Boundary_loss: 0.013898 (0.013899) Loss: 0.57675 (0.58426) +2025-09-13,07:23:40 | INFO | Train Epoch: 5 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.51174 (0.57009) Boundary_loss: 0.013898 (0.013899) Loss: 0.52564 (0.58399) +2025-09-13,07:24:11 | INFO | Train Epoch: 5 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.65613 (0.57048) Boundary_loss: 0.013897 (0.013899) Loss: 0.67003 (0.58438) +2025-09-13,07:24:42 | INFO | Train Epoch: 5 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.58002 (0.57052) Boundary_loss: 0.013898 (0.013899) Loss: 0.59392 (0.58442) +2025-09-13,07:25:13 | INFO | Train Epoch: 5 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.48112 (0.57013) Boundary_loss: 0.013898 (0.013899) Loss: 0.49502 (0.58402) +2025-09-13,07:25:44 | INFO | Train Epoch: 5 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.61585 (0.57033) Boundary_loss: 0.013898 (0.013899) Loss: 0.62975 (0.58423) +2025-09-13,07:26:15 | INFO | Train Epoch: 5 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.53116 (0.57016) Boundary_loss: 0.013898 (0.013899) Loss: 0.54505 (0.58405) +2025-09-13,07:26:46 | INFO | Train Epoch: 5 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.49477 (0.56983) Boundary_loss: 0.013899 (0.013899) Loss: 0.50867 (0.58372) +2025-09-13,07:27:17 | INFO | Train Epoch: 5 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.54927 (0.56974) Boundary_loss: 0.013898 (0.013899) Loss: 0.56317 (0.58363) +2025-09-13,07:27:47 | INFO | Train Epoch: 5 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.58849 (0.56982) Boundary_loss: 0.013901 (0.013899) Loss: 0.60240 (0.58372) +2025-09-13,07:28:18 | INFO | Train Epoch: 5 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.69898 (0.57038) Boundary_loss: 0.013897 (0.013899) Loss: 0.71288 (0.58427) +2025-09-13,07:28:49 | INFO | Train Epoch: 5 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.57793 (0.57041) Boundary_loss: 0.013897 (0.013899) Loss: 0.59183 (0.58431) +2025-09-13,07:29:20 | INFO | Train Epoch: 5 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.48494 (0.57004) Boundary_loss: 0.013898 (0.013899) Loss: 0.49884 (0.58394) +2025-09-13,07:29:50 | INFO | Train Epoch: 5 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.51738 (0.56982) Boundary_loss: 0.013897 (0.013899) Loss: 0.53128 (0.58372) +2025-09-13,07:30:21 | INFO | Train Epoch: 5 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.46039 (0.56935) Boundary_loss: 0.013898 (0.013899) Loss: 0.47429 (0.58325) +2025-09-13,07:30:52 | INFO | Train Epoch: 5 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.47140 (0.56894) Boundary_loss: 0.013896 (0.013899) Loss: 0.48530 (0.58283) +2025-09-13,07:31:23 | INFO | Train Epoch: 5 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.54547 (0.56884) Boundary_loss: 0.013898 (0.013899) Loss: 0.55937 (0.58274) +2025-09-13,07:31:54 | INFO | Train Epoch: 5 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.52180 (0.56864) Boundary_loss: 0.013897 (0.013899) Loss: 0.53570 (0.58254) +2025-09-13,07:32:24 | INFO | Train Epoch: 5 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.60432 (0.56879) Boundary_loss: 0.013897 (0.013899) Loss: 0.61822 (0.58269) +2025-09-13,07:32:55 | INFO | Train Epoch: 5 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.54933 (0.56871) Boundary_loss: 0.013899 (0.013899) Loss: 0.56322 (0.58261) +2025-09-13,07:33:26 | INFO | Train Epoch: 5 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.50522 (0.56844) Boundary_loss: 0.013896 (0.013899) Loss: 0.51911 (0.58234) +2025-09-13,07:33:57 | INFO | Train Epoch: 5 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.55765 (0.56840) Boundary_loss: 0.013898 (0.013899) Loss: 0.57155 (0.58230) +2025-09-13,07:34:27 | INFO | Train Epoch: 5 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.49597 (0.56810) Boundary_loss: 0.013896 (0.013899) Loss: 0.50986 (0.58200) +2025-09-13,07:34:58 | INFO | Train Epoch: 5 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.50808 (0.56786) Boundary_loss: 0.013897 (0.013899) Loss: 0.52198 (0.58175) +2025-09-13,07:35:28 | INFO | Train Epoch: 5 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.56537 (0.56785) Boundary_loss: 0.013896 (0.013899) Loss: 0.57926 (0.58174) +2025-09-13,07:35:59 | INFO | Train Epoch: 5 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.53148 (0.56770) Boundary_loss: 0.013897 (0.013899) Loss: 0.54537 (0.58160) +2025-09-13,07:36:30 | INFO | Train Epoch: 5 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.59161 (0.56779) Boundary_loss: 0.013898 (0.013899) Loss: 0.60551 (0.58169) +2025-09-13,07:37:01 | INFO | Train Epoch: 5 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.45436 (0.56734) Boundary_loss: 0.013896 (0.013899) Loss: 0.46826 (0.58124) +2025-09-13,07:37:32 | INFO | Train Epoch: 5 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.51679 (0.56713) Boundary_loss: 0.013897 (0.013899) Loss: 0.53069 (0.58103) +2025-09-13,07:38:02 | INFO | Train Epoch: 5 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.50505 (0.56689) Boundary_loss: 0.013897 (0.013899) Loss: 0.51895 (0.58078) +2025-09-13,07:38:33 | INFO | Train Epoch: 5 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.57367 (0.56691) Boundary_loss: 0.013897 (0.013899) Loss: 0.58756 (0.58081) +2025-09-13,07:39:04 | INFO | Train Epoch: 5 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.51469 (0.56671) Boundary_loss: 0.013896 (0.013899) Loss: 0.52858 (0.58060) +2025-09-13,07:39:35 | INFO | Train Epoch: 5 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.51823 (0.56651) Boundary_loss: 0.013896 (0.013899) Loss: 0.53213 (0.58041) +2025-09-13,07:40:05 | INFO | Train Epoch: 5 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.51712 (0.56632) Boundary_loss: 0.013895 (0.013899) Loss: 0.53101 (0.58022) +2025-09-13,07:40:36 | INFO | Train Epoch: 5 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.57791 (0.56636) Boundary_loss: 0.013897 (0.013899) Loss: 0.59181 (0.58026) +2025-09-13,07:41:07 | INFO | Train Epoch: 5 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.56469 (0.56636) Boundary_loss: 0.013902 (0.013899) Loss: 0.57859 (0.58026) +2025-09-13,07:41:38 | INFO | Train Epoch: 5 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.58214 (0.56642) Boundary_loss: 0.013896 (0.013899) Loss: 0.59603 (0.58032) +2025-09-13,07:42:08 | INFO | Train Epoch: 5 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.57460 (0.56645) Boundary_loss: 0.013898 (0.013899) Loss: 0.58850 (0.58035) +2025-09-13,07:42:39 | INFO | Train Epoch: 5 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.56114 (0.56643) Boundary_loss: 0.013902 (0.013899) Loss: 0.57504 (0.58033) +2025-09-13,07:43:10 | INFO | Train Epoch: 5 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.55504 (0.56639) Boundary_loss: 0.013901 (0.013899) Loss: 0.56894 (0.58029) +2025-09-13,07:43:41 | INFO | Train Epoch: 5 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.58492 (0.56646) Boundary_loss: 0.013896 (0.013899) Loss: 0.59882 (0.58036) +2025-09-13,07:44:11 | INFO | Train Epoch: 5 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.46212 (0.56606) Boundary_loss: 0.013898 (0.013899) Loss: 0.47602 (0.57996) +2025-09-13,07:44:42 | INFO | Train Epoch: 5 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.52267 (0.56589) Boundary_loss: 0.013898 (0.013899) Loss: 0.53657 (0.57979) +2025-09-13,07:45:13 | INFO | Train Epoch: 5 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.52681 (0.56575) Boundary_loss: 0.013902 (0.013899) Loss: 0.54071 (0.57965) +2025-09-13,07:45:44 | INFO | Train Epoch: 5 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.55371 (0.56570) Boundary_loss: 0.013896 (0.013899) Loss: 0.56761 (0.57960) +2025-09-13,07:46:14 | INFO | Train Epoch: 5 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.55794 (0.56567) Boundary_loss: 0.013900 (0.013899) Loss: 0.57184 (0.57957) +2025-09-13,07:46:45 | INFO | Train Epoch: 5 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.50129 (0.56543) Boundary_loss: 0.013897 (0.013899) Loss: 0.51518 (0.57933) +2025-09-13,07:47:16 | INFO | Train Epoch: 5 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.52785 (0.56529) Boundary_loss: 0.013897 (0.013899) Loss: 0.54175 (0.57919) +2025-09-13,07:47:47 | INFO | Train Epoch: 5 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.54558 (0.56522) Boundary_loss: 0.013898 (0.013899) Loss: 0.55947 (0.57912) +2025-09-13,07:48:17 | INFO | Train Epoch: 5 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.52889 (0.56508) Boundary_loss: 0.013898 (0.013899) Loss: 0.54278 (0.57898) +2025-09-13,07:48:48 | INFO | Train Epoch: 5 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.62996 (0.56532) Boundary_loss: 0.013905 (0.013899) Loss: 0.64386 (0.57922) +2025-09-13,07:49:19 | INFO | Train Epoch: 5 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.60145 (0.56546) Boundary_loss: 0.013897 (0.013899) Loss: 0.61534 (0.57935) +2025-09-13,07:49:50 | INFO | Train Epoch: 5 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.57245 (0.56548) Boundary_loss: 0.013898 (0.013899) Loss: 0.58634 (0.57938) +2025-09-13,07:50:21 | INFO | Train Epoch: 5 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.57392 (0.56551) Boundary_loss: 0.013901 (0.013899) Loss: 0.58782 (0.57941) +2025-09-13,07:50:51 | INFO | Train Epoch: 5 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.54761 (0.56545) Boundary_loss: 0.013901 (0.013899) Loss: 0.56151 (0.57935) +2025-09-13,07:51:22 | INFO | Train Epoch: 5 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.57780 (0.56549) Boundary_loss: 0.013896 (0.013899) Loss: 0.59170 (0.57939) +2025-09-13,07:51:53 | INFO | Train Epoch: 5 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.57513 (0.56553) Boundary_loss: 0.013896 (0.013899) Loss: 0.58903 (0.57942) +2025-09-13,07:52:24 | INFO | Train Epoch: 5 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.60361 (0.56566) Boundary_loss: 0.013899 (0.013899) Loss: 0.61751 (0.57956) +2025-09-13,07:52:55 | INFO | Train Epoch: 5 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.45034 (0.56525) Boundary_loss: 0.013897 (0.013899) Loss: 0.46424 (0.57915) +2025-09-13,07:53:25 | INFO | Train Epoch: 5 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.55771 (0.56522) Boundary_loss: 0.013898 (0.013899) Loss: 0.57161 (0.57912) +2025-09-13,07:53:56 | INFO | Train Epoch: 5 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.64591 (0.56551) Boundary_loss: 0.013897 (0.013899) Loss: 0.65980 (0.57941) +2025-09-13,07:54:27 | INFO | Train Epoch: 5 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.58914 (0.56559) Boundary_loss: 0.013917 (0.013899) Loss: 0.60306 (0.57949) +2025-09-13,07:54:58 | INFO | Train Epoch: 5 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.54224 (0.56551) Boundary_loss: 0.013901 (0.013899) Loss: 0.55614 (0.57941) +2025-09-13,07:55:29 | INFO | Train Epoch: 5 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.48648 (0.56523) Boundary_loss: 0.013897 (0.013899) Loss: 0.50038 (0.57913) +2025-09-13,07:56:00 | INFO | Train Epoch: 5 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.62582 (0.56545) Boundary_loss: 0.013896 (0.013899) Loss: 0.63972 (0.57934) +2025-09-13,07:56:31 | INFO | Train Epoch: 5 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.46652 (0.56510) Boundary_loss: 0.013899 (0.013899) Loss: 0.48042 (0.57900) +2025-09-13,07:57:02 | INFO | Train Epoch: 5 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.58070 (0.56515) Boundary_loss: 0.013900 (0.013899) Loss: 0.59460 (0.57905) +2025-09-13,07:57:33 | INFO | Train Epoch: 5 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.56770 (0.56516) Boundary_loss: 0.013896 (0.013899) Loss: 0.58160 (0.57906) +2025-09-13,07:58:04 | INFO | Train Epoch: 5 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.62053 (0.56535) Boundary_loss: 0.013898 (0.013899) Loss: 0.63442 (0.57925) +2025-09-13,07:58:35 | INFO | Train Epoch: 5 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.50301 (0.56514) Boundary_loss: 0.013900 (0.013899) Loss: 0.51691 (0.57904) +2025-09-13,07:59:06 | INFO | Train Epoch: 5 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.54648 (0.56508) Boundary_loss: 0.013896 (0.013899) Loss: 0.56037 (0.57897) +2025-09-13,07:59:37 | INFO | Train Epoch: 5 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.49033 (0.56482) Boundary_loss: 0.013900 (0.013899) Loss: 0.50423 (0.57872) +2025-09-13,08:00:08 | INFO | Train Epoch: 5 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.59207 (0.56491) Boundary_loss: 0.013897 (0.013899) Loss: 0.60597 (0.57881) +2025-09-13,08:00:39 | INFO | Train Epoch: 5 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.58226 (0.56497) Boundary_loss: 0.013896 (0.013899) Loss: 0.59615 (0.57887) +2025-09-13,08:01:10 | INFO | Train Epoch: 5 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.50534 (0.56477) Boundary_loss: 0.013897 (0.013899) Loss: 0.51924 (0.57867) +2025-09-13,08:01:41 | INFO | Train Epoch: 5 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.57383 (0.56480) Boundary_loss: 0.013897 (0.013899) Loss: 0.58773 (0.57870) +2025-09-13,08:02:12 | INFO | Train Epoch: 5 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.58839 (0.56488) Boundary_loss: 0.013899 (0.013899) Loss: 0.60229 (0.57878) +2025-09-13,08:02:43 | INFO | Train Epoch: 5 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.48480 (0.56461) Boundary_loss: 0.013897 (0.013899) Loss: 0.49870 (0.57851) +2025-09-13,08:03:14 | INFO | Train Epoch: 5 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.57109 (0.56463) Boundary_loss: 0.013898 (0.013899) Loss: 0.58499 (0.57853) +2025-09-13,08:03:45 | INFO | Train Epoch: 5 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.53063 (0.56452) Boundary_loss: 0.013900 (0.013899) Loss: 0.54453 (0.57842) +2025-09-13,08:04:15 | INFO | Train Epoch: 5 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.52959 (0.56440) Boundary_loss: 0.013897 (0.013899) Loss: 0.54349 (0.57830) +2025-09-13,08:04:46 | INFO | Train Epoch: 5 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.52648 (0.56428) Boundary_loss: 0.013897 (0.013899) Loss: 0.54037 (0.57818) +2025-09-13,08:05:17 | INFO | Train Epoch: 5 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.60505 (0.56441) Boundary_loss: 0.013897 (0.013899) Loss: 0.61895 (0.57831) +2025-09-13,08:05:48 | INFO | Train Epoch: 5 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.53574 (0.56432) Boundary_loss: 0.013897 (0.013899) Loss: 0.54964 (0.57822) +2025-09-13,08:06:19 | INFO | Train Epoch: 5 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.63114 (0.56454) Boundary_loss: 0.013896 (0.013899) Loss: 0.64503 (0.57844) +2025-09-13,08:06:50 | INFO | Train Epoch: 5 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.54570 (0.56447) Boundary_loss: 0.013896 (0.013899) Loss: 0.55960 (0.57837) +2025-09-13,08:07:21 | INFO | Train Epoch: 5 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.52791 (0.56436) Boundary_loss: 0.013896 (0.013899) Loss: 0.54181 (0.57825) +2025-09-13,08:07:52 | INFO | Train Epoch: 5 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.58301 (0.56442) Boundary_loss: 0.013899 (0.013899) Loss: 0.59691 (0.57832) +2025-09-13,08:08:23 | INFO | Train Epoch: 5 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.51864 (0.56427) Boundary_loss: 0.013901 (0.013899) Loss: 0.53254 (0.57817) +2025-09-13,08:08:54 | INFO | Train Epoch: 5 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.50491 (0.56408) Boundary_loss: 0.013897 (0.013899) Loss: 0.51880 (0.57798) +2025-09-13,08:09:24 | INFO | Train Epoch: 5 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.66397 (0.56440) Boundary_loss: 0.013896 (0.013899) Loss: 0.67787 (0.57830) +2025-09-13,08:09:55 | INFO | Train Epoch: 5 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.46431 (0.56408) Boundary_loss: 0.013896 (0.013899) Loss: 0.47821 (0.57798) +2025-09-13,08:10:26 | INFO | Train Epoch: 5 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.48711 (0.56383) Boundary_loss: 0.013915 (0.013899) Loss: 0.50102 (0.57773) +2025-09-13,08:10:57 | INFO | Train Epoch: 5 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.48963 (0.56360) Boundary_loss: 0.013897 (0.013899) Loss: 0.50353 (0.57749) +2025-09-13,08:11:28 | INFO | Train Epoch: 5 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.47397 (0.56331) Boundary_loss: 0.013896 (0.013899) Loss: 0.48787 (0.57721) +2025-09-13,08:11:59 | INFO | Train Epoch: 5 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.67168 (0.56365) Boundary_loss: 0.013901 (0.013899) Loss: 0.68558 (0.57755) +2025-09-13,08:12:30 | INFO | Train Epoch: 5 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.55359 (0.56362) Boundary_loss: 0.013902 (0.013899) Loss: 0.56749 (0.57752) +2025-09-13,08:13:01 | INFO | Train Epoch: 5 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59271 (0.56371) Boundary_loss: 0.013895 (0.013899) Loss: 0.60661 (0.57761) +2025-09-13,08:13:32 | INFO | Train Epoch: 5 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.54073 (0.56364) Boundary_loss: 0.013897 (0.013899) Loss: 0.55463 (0.57754) +2025-09-13,08:14:03 | INFO | Train Epoch: 5 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.52122 (0.56351) Boundary_loss: 0.013895 (0.013899) Loss: 0.53512 (0.57741) +2025-09-13,08:14:34 | INFO | Train Epoch: 5 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.60754 (0.56365) Boundary_loss: 0.013895 (0.013899) Loss: 0.62143 (0.57754) +2025-09-13,08:15:05 | INFO | Train Epoch: 5 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.49265 (0.56343) Boundary_loss: 0.013896 (0.013899) Loss: 0.50655 (0.57732) +2025-09-13,08:15:36 | INFO | Train Epoch: 5 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.47910 (0.56316) Boundary_loss: 0.013896 (0.013899) Loss: 0.49300 (0.57706) +2025-09-13,08:16:07 | INFO | Train Epoch: 5 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.51866 (0.56303) Boundary_loss: 0.013902 (0.013899) Loss: 0.53256 (0.57693) +2025-09-13,08:16:38 | INFO | Train Epoch: 5 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.52301 (0.56290) Boundary_loss: 0.013900 (0.013899) Loss: 0.53691 (0.57680) +2025-09-13,08:17:09 | INFO | Train Epoch: 5 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.49841 (0.56271) Boundary_loss: 0.013897 (0.013899) Loss: 0.51230 (0.57660) +2025-09-13,08:17:40 | INFO | Train Epoch: 5 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.66600 (0.56302) Boundary_loss: 0.013897 (0.013899) Loss: 0.67990 (0.57692) +2025-09-13,08:18:10 | INFO | Train Epoch: 5 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.61205 (0.56317) Boundary_loss: 0.013898 (0.013899) Loss: 0.62595 (0.57707) +2025-09-13,08:18:41 | INFO | Train Epoch: 5 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.55890 (0.56316) Boundary_loss: 0.013897 (0.013899) Loss: 0.57279 (0.57706) +2025-09-13,08:19:12 | INFO | Train Epoch: 5 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.55766 (0.56314) Boundary_loss: 0.013897 (0.013899) Loss: 0.57155 (0.57704) +2025-09-13,08:19:43 | INFO | Train Epoch: 5 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.57147 (0.56317) Boundary_loss: 0.013895 (0.013899) Loss: 0.58536 (0.57707) +2025-09-13,08:20:14 | INFO | Train Epoch: 5 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.62206 (0.56334) Boundary_loss: 0.013899 (0.013899) Loss: 0.63596 (0.57724) +2025-09-13,08:20:44 | INFO | Train Epoch: 5 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.55000 (0.56330) Boundary_loss: 0.013896 (0.013899) Loss: 0.56390 (0.57720) +2025-09-13,08:21:15 | INFO | Train Epoch: 5 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.64397 (0.56355) Boundary_loss: 0.013904 (0.013899) Loss: 0.65788 (0.57744) +2025-09-13,08:21:46 | INFO | Train Epoch: 5 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.66892 (0.56386) Boundary_loss: 0.013898 (0.013899) Loss: 0.68282 (0.57776) +2025-09-13,08:22:17 | INFO | Train Epoch: 5 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.56807 (0.56387) Boundary_loss: 0.013907 (0.013899) Loss: 0.58198 (0.57777) +2025-09-13,08:22:47 | INFO | Train Epoch: 5 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.53029 (0.56377) Boundary_loss: 0.013897 (0.013899) Loss: 0.54418 (0.57767) +2025-09-13,08:23:18 | INFO | Train Epoch: 5 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.46681 (0.56349) Boundary_loss: 0.013900 (0.013899) Loss: 0.48071 (0.57738) +2025-09-13,08:23:49 | INFO | Train Epoch: 5 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.54668 (0.56344) Boundary_loss: 0.013900 (0.013899) Loss: 0.56058 (0.57734) +2025-09-13,08:24:20 | INFO | Train Epoch: 5 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.47011 (0.56316) Boundary_loss: 0.013899 (0.013899) Loss: 0.48401 (0.57706) +2025-09-13,08:24:51 | INFO | Train Epoch: 5 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.56041 (0.56315) Boundary_loss: 0.013899 (0.013899) Loss: 0.57431 (0.57705) +2025-09-13,08:25:22 | INFO | Train Epoch: 5 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.55647 (0.56313) Boundary_loss: 0.013898 (0.013899) Loss: 0.57036 (0.57703) +2025-09-13,08:25:53 | INFO | Train Epoch: 5 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.69481 (0.56352) Boundary_loss: 0.013896 (0.013899) Loss: 0.70870 (0.57742) +2025-09-13,08:26:24 | INFO | Train Epoch: 5 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.58154 (0.56357) Boundary_loss: 0.013896 (0.013899) Loss: 0.59544 (0.57747) +2025-09-13,08:26:55 | INFO | Train Epoch: 5 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.50545 (0.56340) Boundary_loss: 0.013895 (0.013899) Loss: 0.51934 (0.57730) +2025-09-13,08:27:25 | INFO | Train Epoch: 5 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.51972 (0.56328) Boundary_loss: 0.013898 (0.013899) Loss: 0.53361 (0.57717) +2025-09-13,08:27:56 | INFO | Train Epoch: 5 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.56405 (0.56328) Boundary_loss: 0.013896 (0.013899) Loss: 0.57795 (0.57718) +2025-09-13,08:28:27 | INFO | Train Epoch: 5 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.54919 (0.56324) Boundary_loss: 0.013897 (0.013899) Loss: 0.56308 (0.57714) +2025-09-13,08:28:58 | INFO | Train Epoch: 5 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.61000 (0.56337) Boundary_loss: 0.013895 (0.013899) Loss: 0.62389 (0.57727) +2025-09-13,08:29:29 | INFO | Train Epoch: 5 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.55841 (0.56336) Boundary_loss: 0.013898 (0.013899) Loss: 0.57230 (0.57726) +2025-09-13,08:30:00 | INFO | Train Epoch: 5 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.44543 (0.56302) Boundary_loss: 0.013898 (0.013899) Loss: 0.45933 (0.57692) +2025-09-13,08:30:31 | INFO | Train Epoch: 5 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.53905 (0.56295) Boundary_loss: 0.013896 (0.013899) Loss: 0.55295 (0.57685) +2025-09-13,08:31:01 | INFO | Train Epoch: 5 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.53252 (0.56287) Boundary_loss: 0.013897 (0.013899) Loss: 0.54642 (0.57677) +2025-09-13,08:31:32 | INFO | Train Epoch: 5 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.55598 (0.56285) Boundary_loss: 0.013897 (0.013899) Loss: 0.56987 (0.57675) +2025-09-13,08:32:03 | INFO | Train Epoch: 5 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.54597 (0.56280) Boundary_loss: 0.013898 (0.013899) Loss: 0.55987 (0.57670) +2025-09-13,08:32:34 | INFO | Train Epoch: 5 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.61003 (0.56293) Boundary_loss: 0.013896 (0.013899) Loss: 0.62392 (0.57683) +2025-09-13,08:33:05 | INFO | Train Epoch: 5 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.67040 (0.56323) Boundary_loss: 0.013896 (0.013899) Loss: 0.68430 (0.57713) +2025-09-13,08:33:36 | INFO | Train Epoch: 5 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.56375 (0.56324) Boundary_loss: 0.013898 (0.013899) Loss: 0.57764 (0.57713) +2025-09-13,08:34:07 | INFO | Train Epoch: 5 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.56304 (0.56323) Boundary_loss: 0.013896 (0.013899) Loss: 0.57693 (0.57713) +2025-09-13,08:34:37 | INFO | Train Epoch: 5 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.60743 (0.56336) Boundary_loss: 0.013897 (0.013899) Loss: 0.62132 (0.57726) +2025-09-13,08:35:08 | INFO | Train Epoch: 5 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.50724 (0.56320) Boundary_loss: 0.013896 (0.013899) Loss: 0.52113 (0.57710) +2025-09-13,08:35:39 | INFO | Train Epoch: 5 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.62573 (0.56337) Boundary_loss: 0.013897 (0.013899) Loss: 0.63963 (0.57727) +2025-09-13,08:36:09 | INFO | Train Epoch: 5 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.53946 (0.56331) Boundary_loss: 0.013897 (0.013899) Loss: 0.55336 (0.57721) +2025-09-13,08:36:40 | INFO | Train Epoch: 5 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.55081 (0.56327) Boundary_loss: 0.013901 (0.013899) Loss: 0.56471 (0.57717) +2025-09-13,08:37:11 | INFO | Train Epoch: 5 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.54322 (0.56322) Boundary_loss: 0.013895 (0.013899) Loss: 0.55712 (0.57712) +2025-09-13,08:37:42 | INFO | Train Epoch: 5 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.52544 (0.56312) Boundary_loss: 0.013898 (0.013899) Loss: 0.53934 (0.57701) +2025-09-13,08:38:12 | INFO | Train Epoch: 5 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.58281 (0.56317) Boundary_loss: 0.013910 (0.013899) Loss: 0.59672 (0.57707) +2025-09-13,08:38:43 | INFO | Train Epoch: 5 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.57181 (0.56319) Boundary_loss: 0.013899 (0.013899) Loss: 0.58571 (0.57709) +2025-09-13,08:39:14 | INFO | Train Epoch: 5 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.46879 (0.56294) Boundary_loss: 0.013898 (0.013899) Loss: 0.48269 (0.57684) +2025-09-13,08:39:44 | INFO | Train Epoch: 5 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.56933 (0.56295) Boundary_loss: 0.013910 (0.013899) Loss: 0.58324 (0.57685) +2025-09-13,08:40:15 | INFO | Train Epoch: 5 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.56561 (0.56296) Boundary_loss: 0.013899 (0.013899) Loss: 0.57951 (0.57686) +2025-09-13,08:40:46 | INFO | Train Epoch: 5 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.51933 (0.56284) Boundary_loss: 0.013899 (0.013899) Loss: 0.53323 (0.57674) +2025-09-13,08:41:17 | INFO | Train Epoch: 5 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.49685 (0.56267) Boundary_loss: 0.013898 (0.013899) Loss: 0.51074 (0.57657) +2025-09-13,08:41:47 | INFO | Train Epoch: 5 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.63882 (0.56287) Boundary_loss: 0.013896 (0.013899) Loss: 0.65272 (0.57677) +2025-09-13,08:42:18 | INFO | Train Epoch: 5 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.39832 (0.56243) Boundary_loss: 0.013897 (0.013899) Loss: 0.41222 (0.57633) +2025-09-13,08:42:49 | INFO | Train Epoch: 5 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.49023 (0.56224) Boundary_loss: 0.013895 (0.013899) Loss: 0.50412 (0.57614) +2025-09-13,08:43:19 | INFO | Train Epoch: 5 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.68369 (0.56256) Boundary_loss: 0.013903 (0.013899) Loss: 0.69759 (0.57646) +2025-09-13,08:43:50 | INFO | Train Epoch: 5 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.57178 (0.56259) Boundary_loss: 0.013897 (0.013899) Loss: 0.58568 (0.57649) +2025-09-13,08:44:21 | INFO | Train Epoch: 5 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.49792 (0.56242) Boundary_loss: 0.013897 (0.013899) Loss: 0.51182 (0.57632) +2025-09-13,08:44:52 | INFO | Train Epoch: 5 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.56863 (0.56243) Boundary_loss: 0.013900 (0.013899) Loss: 0.58253 (0.57633) +2025-09-13,08:45:22 | INFO | Train Epoch: 5 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.59805 (0.56253) Boundary_loss: 0.013901 (0.013899) Loss: 0.61195 (0.57643) +2025-09-13,08:45:53 | INFO | Train Epoch: 5 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.60844 (0.56265) Boundary_loss: 0.013896 (0.013899) Loss: 0.62233 (0.57655) +2025-09-13,08:46:24 | INFO | Train Epoch: 5 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.52973 (0.56256) Boundary_loss: 0.013896 (0.013899) Loss: 0.54363 (0.57646) +2025-09-13,08:46:55 | INFO | Train Epoch: 5 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.61424 (0.56270) Boundary_loss: 0.013900 (0.013899) Loss: 0.62814 (0.57659) +2025-09-13,08:47:26 | INFO | Train Epoch: 5 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.56426 (0.56270) Boundary_loss: 0.013897 (0.013899) Loss: 0.57816 (0.57660) +2025-09-13,08:47:57 | INFO | Train Epoch: 5 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.68432 (0.56301) Boundary_loss: 0.013897 (0.013899) Loss: 0.69822 (0.57691) +2025-09-13,08:48:28 | INFO | Train Epoch: 5 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.43803 (0.56269) Boundary_loss: 0.013903 (0.013899) Loss: 0.45193 (0.57659) +2025-09-13,08:48:58 | INFO | Train Epoch: 5 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.42891 (0.56235) Boundary_loss: 0.013896 (0.013899) Loss: 0.44280 (0.57625) +2025-09-13,08:49:29 | INFO | Train Epoch: 5 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.52183 (0.56224) Boundary_loss: 0.013897 (0.013899) Loss: 0.53573 (0.57614) +2025-09-13,08:50:00 | INFO | Train Epoch: 5 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.62951 (0.56241) Boundary_loss: 0.013899 (0.013899) Loss: 0.64341 (0.57631) +2025-09-13,08:50:31 | INFO | Train Epoch: 5 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.60900 (0.56253) Boundary_loss: 0.013906 (0.013899) Loss: 0.62291 (0.57643) +2025-09-13,08:51:02 | INFO | Train Epoch: 5 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.59397 (0.56261) Boundary_loss: 0.013896 (0.013899) Loss: 0.60787 (0.57651) +2025-09-13,08:51:33 | INFO | Train Epoch: 5 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.54000 (0.56256) Boundary_loss: 0.013899 (0.013899) Loss: 0.55390 (0.57646) +2025-09-13,08:52:04 | INFO | Train Epoch: 5 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.43450 (0.56223) Boundary_loss: 0.013896 (0.013899) Loss: 0.44839 (0.57613) +2025-09-13,08:52:34 | INFO | Train Epoch: 5 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.54906 (0.56220) Boundary_loss: 0.013899 (0.013899) Loss: 0.56296 (0.57610) +2025-09-13,08:53:05 | INFO | Train Epoch: 5 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.55995 (0.56219) Boundary_loss: 0.013897 (0.013899) Loss: 0.57385 (0.57609) +2025-09-13,08:53:36 | INFO | Train Epoch: 5 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.53259 (0.56212) Boundary_loss: 0.013897 (0.013899) Loss: 0.54649 (0.57602) +2025-09-13,08:54:07 | INFO | Train Epoch: 5 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.67418 (0.56240) Boundary_loss: 0.013897 (0.013899) Loss: 0.68808 (0.57630) +2025-09-13,08:54:38 | INFO | Train Epoch: 5 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.53375 (0.56233) Boundary_loss: 0.013897 (0.013899) Loss: 0.54765 (0.57623) +2025-09-13,08:55:09 | INFO | Train Epoch: 5 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.61314 (0.56245) Boundary_loss: 0.013899 (0.013899) Loss: 0.62703 (0.57635) +2025-09-13,08:55:40 | INFO | Train Epoch: 5 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.51287 (0.56233) Boundary_loss: 0.013896 (0.013899) Loss: 0.52677 (0.57623) +2025-09-13,08:56:11 | INFO | Train Epoch: 5 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.62526 (0.56249) Boundary_loss: 0.013896 (0.013899) Loss: 0.63915 (0.57639) +2025-09-13,08:56:42 | INFO | Train Epoch: 5 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.58142 (0.56253) Boundary_loss: 0.013899 (0.013899) Loss: 0.59532 (0.57643) +2025-09-13,08:57:13 | INFO | Train Epoch: 5 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.53042 (0.56246) Boundary_loss: 0.013895 (0.013899) Loss: 0.54431 (0.57635) +2025-09-13,08:57:44 | INFO | Train Epoch: 5 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.57460 (0.56249) Boundary_loss: 0.013898 (0.013899) Loss: 0.58850 (0.57638) +2025-09-13,08:58:15 | INFO | Train Epoch: 5 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.54364 (0.56244) Boundary_loss: 0.013896 (0.013899) Loss: 0.55754 (0.57634) +2025-09-13,08:58:46 | INFO | Train Epoch: 5 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.61111 (0.56256) Boundary_loss: 0.013896 (0.013899) Loss: 0.62500 (0.57646) +2025-09-13,08:59:16 | INFO | Train Epoch: 5 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.52910 (0.56248) Boundary_loss: 0.013896 (0.013899) Loss: 0.54300 (0.57638) +2025-09-13,08:59:47 | INFO | Train Epoch: 5 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.49660 (0.56232) Boundary_loss: 0.013901 (0.013899) Loss: 0.51050 (0.57621) +2025-09-13,09:00:18 | INFO | Train Epoch: 5 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.65513 (0.56254) Boundary_loss: 0.013896 (0.013899) Loss: 0.66903 (0.57644) +2025-09-13,09:00:49 | INFO | Train Epoch: 5 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.49855 (0.56239) Boundary_loss: 0.013896 (0.013899) Loss: 0.51244 (0.57628) +2025-09-13,09:01:20 | INFO | Train Epoch: 5 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.62352 (0.56253) Boundary_loss: 0.013897 (0.013899) Loss: 0.63742 (0.57643) +2025-09-13,09:01:51 | INFO | Train Epoch: 5 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.62693 (0.56269) Boundary_loss: 0.013897 (0.013899) Loss: 0.64083 (0.57659) +2025-09-13,09:02:22 | INFO | Train Epoch: 5 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.57500 (0.56272) Boundary_loss: 0.013900 (0.013899) Loss: 0.58890 (0.57662) +2025-09-13,09:02:53 | INFO | Train Epoch: 5 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.52422 (0.56263) Boundary_loss: 0.013896 (0.013899) Loss: 0.53811 (0.57653) +2025-09-13,09:03:24 | INFO | Train Epoch: 5 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.58732 (0.56269) Boundary_loss: 0.013904 (0.013899) Loss: 0.60122 (0.57659) +2025-09-13,09:03:55 | INFO | Train Epoch: 5 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.63013 (0.56285) Boundary_loss: 0.013898 (0.013899) Loss: 0.64403 (0.57675) +2025-09-13,09:04:26 | INFO | Train Epoch: 5 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.64612 (0.56305) Boundary_loss: 0.013900 (0.013899) Loss: 0.66002 (0.57695) +2025-09-13,09:04:57 | INFO | Train Epoch: 5 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.50436 (0.56291) Boundary_loss: 0.013896 (0.013899) Loss: 0.51826 (0.57681) +2025-09-13,09:05:28 | INFO | Train Epoch: 5 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.57126 (0.56293) Boundary_loss: 0.013902 (0.013899) Loss: 0.58516 (0.57683) +2025-09-13,09:05:59 | INFO | Train Epoch: 5 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.58018 (0.56297) Boundary_loss: 0.013896 (0.013899) Loss: 0.59408 (0.57687) +2025-09-13,09:06:30 | INFO | Train Epoch: 5 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.56495 (0.56297) Boundary_loss: 0.013896 (0.013899) Loss: 0.57885 (0.57687) +2025-09-13,09:07:01 | INFO | Train Epoch: 5 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.55984 (0.56297) Boundary_loss: 0.013898 (0.013899) Loss: 0.57374 (0.57686) +2025-09-13,09:07:31 | INFO | Train Epoch: 5 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.55882 (0.56296) Boundary_loss: 0.013896 (0.013899) Loss: 0.57272 (0.57685) +2025-09-13,09:08:02 | INFO | Train Epoch: 5 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.45335 (0.56270) Boundary_loss: 0.013898 (0.013898) Loss: 0.46724 (0.57660) +2025-09-13,09:08:33 | INFO | Train Epoch: 5 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.52333 (0.56261) Boundary_loss: 0.013898 (0.013898) Loss: 0.53723 (0.57650) +2025-09-13,09:09:04 | INFO | Train Epoch: 5 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.45577 (0.56236) Boundary_loss: 0.013901 (0.013899) Loss: 0.46967 (0.57625) +2025-09-13,09:09:35 | INFO | Train Epoch: 5 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.49561 (0.56220) Boundary_loss: 0.013898 (0.013899) Loss: 0.50951 (0.57610) +2025-09-13,09:10:06 | INFO | Train Epoch: 5 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.54935 (0.56217) Boundary_loss: 0.013897 (0.013898) Loss: 0.56325 (0.57607) +2025-09-13,09:10:37 | INFO | Train Epoch: 5 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.58312 (0.56222) Boundary_loss: 0.013896 (0.013898) Loss: 0.59702 (0.57612) +2025-09-13,09:11:08 | INFO | Train Epoch: 5 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.57717 (0.56225) Boundary_loss: 0.013895 (0.013898) Loss: 0.59106 (0.57615) +2025-09-13,09:11:39 | INFO | Train Epoch: 5 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.60496 (0.56235) Boundary_loss: 0.013899 (0.013898) Loss: 0.61886 (0.57625) +2025-09-13,09:12:10 | INFO | Train Epoch: 5 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.47459 (0.56215) Boundary_loss: 0.013898 (0.013898) Loss: 0.48849 (0.57605) +2025-09-13,09:12:41 | INFO | Train Epoch: 5 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.50115 (0.56201) Boundary_loss: 0.013903 (0.013898) Loss: 0.51506 (0.57591) +2025-09-13,09:13:12 | INFO | Train Epoch: 5 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.50670 (0.56188) Boundary_loss: 0.013897 (0.013898) Loss: 0.52060 (0.57578) +2025-09-13,09:13:43 | INFO | Train Epoch: 5 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.63925 (0.56206) Boundary_loss: 0.013897 (0.013898) Loss: 0.65314 (0.57596) +2025-09-13,09:14:14 | INFO | Train Epoch: 5 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.54085 (0.56201) Boundary_loss: 0.013897 (0.013898) Loss: 0.55475 (0.57591) +2025-09-13,09:14:45 | INFO | Train Epoch: 5 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.55490 (0.56199) Boundary_loss: 0.013900 (0.013898) Loss: 0.56880 (0.57589) +2025-09-13,09:15:16 | INFO | Train Epoch: 5 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.55279 (0.56197) Boundary_loss: 0.013896 (0.013898) Loss: 0.56669 (0.57587) +2025-09-13,09:15:47 | INFO | Train Epoch: 5 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.59261 (0.56204) Boundary_loss: 0.013896 (0.013898) Loss: 0.60650 (0.57594) +2025-09-13,09:16:18 | INFO | Train Epoch: 5 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.53250 (0.56198) Boundary_loss: 0.013897 (0.013898) Loss: 0.54640 (0.57587) +2025-09-13,09:16:49 | INFO | Train Epoch: 5 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.51852 (0.56188) Boundary_loss: 0.013906 (0.013898) Loss: 0.53242 (0.57578) +2025-09-13,09:17:20 | INFO | Train Epoch: 5 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.58378 (0.56193) Boundary_loss: 0.013896 (0.013898) Loss: 0.59767 (0.57583) +2025-09-13,09:17:51 | INFO | Train Epoch: 5 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.57690 (0.56196) Boundary_loss: 0.013902 (0.013898) Loss: 0.59081 (0.57586) +2025-09-13,09:18:22 | INFO | Train Epoch: 5 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.70515 (0.56228) Boundary_loss: 0.013898 (0.013898) Loss: 0.71905 (0.57618) +2025-09-13,09:18:53 | INFO | Train Epoch: 5 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.55830 (0.56227) Boundary_loss: 0.013897 (0.013898) Loss: 0.57220 (0.57617) +2025-09-13,09:19:24 | INFO | Train Epoch: 5 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.52483 (0.56219) Boundary_loss: 0.013896 (0.013898) Loss: 0.53873 (0.57609) +2025-09-13,09:19:55 | INFO | Train Epoch: 5 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.57489 (0.56222) Boundary_loss: 0.013899 (0.013898) Loss: 0.58879 (0.57612) +2025-09-13,09:20:26 | INFO | Train Epoch: 5 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.52862 (0.56214) Boundary_loss: 0.013896 (0.013898) Loss: 0.54252 (0.57604) +2025-09-13,09:20:57 | INFO | Train Epoch: 5 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59352 (0.56221) Boundary_loss: 0.013896 (0.013898) Loss: 0.60742 (0.57611) +2025-09-13,09:21:28 | INFO | Train Epoch: 5 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.57687 (0.56225) Boundary_loss: 0.013897 (0.013898) Loss: 0.59077 (0.57614) +2025-09-13,09:21:59 | INFO | Train Epoch: 5 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.57669 (0.56228) Boundary_loss: 0.013897 (0.013898) Loss: 0.59059 (0.57618) +2025-09-13,09:22:30 | INFO | Train Epoch: 5 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.65860 (0.56249) Boundary_loss: 0.013897 (0.013898) Loss: 0.67250 (0.57639) +2025-09-13,09:23:01 | INFO | Train Epoch: 5 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.55140 (0.56247) Boundary_loss: 0.013898 (0.013898) Loss: 0.56530 (0.57636) +2025-09-13,09:23:31 | INFO | Train Epoch: 5 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.53005 (0.56239) Boundary_loss: 0.013896 (0.013898) Loss: 0.54394 (0.57629) +2025-09-13,09:24:03 | INFO | Train Epoch: 5 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.64562 (0.56258) Boundary_loss: 0.013895 (0.013898) Loss: 0.65951 (0.57648) +2025-09-13,09:24:33 | INFO | Train Epoch: 5 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.49047 (0.56242) Boundary_loss: 0.013897 (0.013898) Loss: 0.50437 (0.57632) +2025-09-13,09:25:04 | INFO | Train Epoch: 5 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.50993 (0.56230) Boundary_loss: 0.013896 (0.013898) Loss: 0.52383 (0.57620) +2025-09-13,09:25:35 | INFO | Train Epoch: 5 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.56094 (0.56230) Boundary_loss: 0.013894 (0.013898) Loss: 0.57484 (0.57620) +2025-09-13,09:26:06 | INFO | Train Epoch: 5 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.55873 (0.56229) Boundary_loss: 0.013898 (0.013898) Loss: 0.57263 (0.57619) +2025-09-13,09:26:37 | INFO | Train Epoch: 5 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.50172 (0.56216) Boundary_loss: 0.013900 (0.013898) Loss: 0.51562 (0.57606) +2025-09-13,09:27:08 | INFO | Train Epoch: 5 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.56167 (0.56216) Boundary_loss: 0.013897 (0.013898) Loss: 0.57557 (0.57606) +2025-09-13,09:27:39 | INFO | Train Epoch: 5 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.56137 (0.56216) Boundary_loss: 0.013899 (0.013898) Loss: 0.57527 (0.57606) +2025-09-13,09:28:10 | INFO | Train Epoch: 5 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.55426 (0.56214) Boundary_loss: 0.013896 (0.013898) Loss: 0.56815 (0.57604) +2025-09-13,09:28:40 | INFO | Train Epoch: 5 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.48317 (0.56197) Boundary_loss: 0.013895 (0.013898) Loss: 0.49707 (0.57587) +2025-09-13,09:29:11 | INFO | Train Epoch: 5 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.43989 (0.56171) Boundary_loss: 0.013896 (0.013898) Loss: 0.45379 (0.57561) +2025-09-13,09:29:42 | INFO | Train Epoch: 5 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.47725 (0.56153) Boundary_loss: 0.013897 (0.013898) Loss: 0.49114 (0.57543) +2025-09-13,09:30:13 | INFO | Train Epoch: 5 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.48681 (0.56137) Boundary_loss: 0.013897 (0.013898) Loss: 0.50071 (0.57527) +2025-09-13,09:30:44 | INFO | Train Epoch: 5 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.54275 (0.56133) Boundary_loss: 0.013896 (0.013898) Loss: 0.55664 (0.57523) +2025-09-13,09:31:15 | INFO | Train Epoch: 5 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.60118 (0.56142) Boundary_loss: 0.013903 (0.013898) Loss: 0.61508 (0.57531) +2025-09-13,09:31:46 | INFO | Train Epoch: 5 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.63987 (0.56158) Boundary_loss: 0.013898 (0.013898) Loss: 0.65377 (0.57548) +2025-09-13,09:32:17 | INFO | Train Epoch: 5 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.52894 (0.56151) Boundary_loss: 0.013897 (0.013898) Loss: 0.54283 (0.57541) +2025-09-13,09:32:48 | INFO | Train Epoch: 5 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.56483 (0.56152) Boundary_loss: 0.013896 (0.013898) Loss: 0.57873 (0.57542) +2025-09-13,09:33:19 | INFO | Train Epoch: 5 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.50992 (0.56141) Boundary_loss: 0.013896 (0.013898) Loss: 0.52381 (0.57531) +2025-09-13,09:33:49 | INFO | Train Epoch: 5 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.57749 (0.56144) Boundary_loss: 0.013897 (0.013898) Loss: 0.59138 (0.57534) +2025-09-13,09:34:20 | INFO | Train Epoch: 5 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.57482 (0.56147) Boundary_loss: 0.013898 (0.013898) Loss: 0.58872 (0.57537) +2025-09-13,09:34:51 | INFO | Train Epoch: 5 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.59686 (0.56155) Boundary_loss: 0.013897 (0.013898) Loss: 0.61076 (0.57545) +2025-09-13,09:35:22 | INFO | Train Epoch: 5 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.58399 (0.56159) Boundary_loss: 0.013897 (0.013898) Loss: 0.59789 (0.57549) +2025-09-13,09:35:52 | INFO | Train Epoch: 5 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.57812 (0.56163) Boundary_loss: 0.013895 (0.013898) Loss: 0.59201 (0.57553) +2025-09-13,09:36:23 | INFO | Train Epoch: 5 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.50889 (0.56152) Boundary_loss: 0.013897 (0.013898) Loss: 0.52279 (0.57542) +2025-09-13,09:36:54 | INFO | Train Epoch: 5 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.51915 (0.56143) Boundary_loss: 0.013896 (0.013898) Loss: 0.53305 (0.57533) +2025-09-13,09:37:25 | INFO | Train Epoch: 5 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.49141 (0.56129) Boundary_loss: 0.013898 (0.013898) Loss: 0.50531 (0.57518) +2025-09-13,09:37:55 | INFO | Train Epoch: 5 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.52401 (0.56121) Boundary_loss: 0.013899 (0.013898) Loss: 0.53791 (0.57511) +2025-09-13,09:38:26 | INFO | Train Epoch: 5 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.53274 (0.56115) Boundary_loss: 0.013897 (0.013898) Loss: 0.54663 (0.57505) +2025-09-13,09:38:57 | INFO | Train Epoch: 5 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.52591 (0.56108) Boundary_loss: 0.013897 (0.013898) Loss: 0.53980 (0.57498) +2025-09-13,09:39:28 | INFO | Train Epoch: 5 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.54811 (0.56105) Boundary_loss: 0.013896 (0.013898) Loss: 0.56201 (0.57495) +2025-09-13,09:39:58 | INFO | Train Epoch: 5 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.60065 (0.56113) Boundary_loss: 0.013896 (0.013898) Loss: 0.61455 (0.57503) +2025-09-13,09:40:29 | INFO | Train Epoch: 5 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.56597 (0.56114) Boundary_loss: 0.013897 (0.013898) Loss: 0.57987 (0.57504) +2025-09-13,09:41:00 | INFO | Train Epoch: 5 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.54067 (0.56110) Boundary_loss: 0.013897 (0.013898) Loss: 0.55457 (0.57500) +2025-09-13,09:41:31 | INFO | Train Epoch: 5 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.55713 (0.56109) Boundary_loss: 0.013899 (0.013898) Loss: 0.57103 (0.57499) +2025-09-13,09:42:02 | INFO | Train Epoch: 5 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.52848 (0.56102) Boundary_loss: 0.013896 (0.013898) Loss: 0.54238 (0.57492) +2025-09-13,09:42:32 | INFO | Train Epoch: 5 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.52975 (0.56096) Boundary_loss: 0.013906 (0.013898) Loss: 0.54366 (0.57486) +2025-09-13,09:43:03 | INFO | Train Epoch: 5 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.46484 (0.56077) Boundary_loss: 0.013901 (0.013898) Loss: 0.47874 (0.57466) +2025-09-13,09:43:34 | INFO | Train Epoch: 5 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.51920 (0.56068) Boundary_loss: 0.013898 (0.013898) Loss: 0.53310 (0.57458) +2025-09-13,09:44:05 | INFO | Train Epoch: 5 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.53938 (0.56064) Boundary_loss: 0.013899 (0.013898) Loss: 0.55328 (0.57454) +2025-09-13,09:44:36 | INFO | Train Epoch: 5 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.52867 (0.56057) Boundary_loss: 0.013896 (0.013898) Loss: 0.54257 (0.57447) +2025-09-13,09:45:07 | INFO | Train Epoch: 5 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.53073 (0.56051) Boundary_loss: 0.013897 (0.013898) Loss: 0.54463 (0.57441) +2025-09-13,09:45:37 | INFO | Train Epoch: 5 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.49993 (0.56039) Boundary_loss: 0.013903 (0.013898) Loss: 0.51383 (0.57429) +2025-09-13,09:46:08 | INFO | Train Epoch: 5 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.39116 (0.56005) Boundary_loss: 0.013898 (0.013898) Loss: 0.40506 (0.57395) +2025-09-13,09:46:39 | INFO | Train Epoch: 5 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.51910 (0.55997) Boundary_loss: 0.013900 (0.013898) Loss: 0.53300 (0.57387) +2025-09-13,09:47:10 | INFO | Train Epoch: 5 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.49949 (0.55985) Boundary_loss: 0.013896 (0.013898) Loss: 0.51338 (0.57375) +2025-09-13,09:47:41 | INFO | Train Epoch: 5 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.55554 (0.55984) Boundary_loss: 0.013897 (0.013898) Loss: 0.56943 (0.57374) +2025-09-13,09:48:12 | INFO | Train Epoch: 5 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.59070 (0.55990) Boundary_loss: 0.013897 (0.013898) Loss: 0.60460 (0.57380) +2025-09-13,09:48:42 | INFO | Train Epoch: 5 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.55807 (0.55990) Boundary_loss: 0.013898 (0.013898) Loss: 0.57196 (0.57380) +2025-09-13,09:49:13 | INFO | Train Epoch: 5 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.56390 (0.55991) Boundary_loss: 0.013897 (0.013898) Loss: 0.57780 (0.57381) +2025-09-13,09:49:44 | INFO | Train Epoch: 5 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.50740 (0.55980) Boundary_loss: 0.013898 (0.013898) Loss: 0.52130 (0.57370) +2025-09-13,09:50:15 | INFO | Train Epoch: 5 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.49005 (0.55967) Boundary_loss: 0.013903 (0.013898) Loss: 0.50395 (0.57357) +2025-09-13,09:50:46 | INFO | Train Epoch: 5 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.56805 (0.55968) Boundary_loss: 0.013897 (0.013898) Loss: 0.58195 (0.57358) +2025-09-13,09:51:17 | INFO | Train Epoch: 5 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.51839 (0.55960) Boundary_loss: 0.013898 (0.013898) Loss: 0.53228 (0.57350) +2025-09-13,09:51:48 | INFO | Train Epoch: 5 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.53725 (0.55956) Boundary_loss: 0.013906 (0.013898) Loss: 0.55116 (0.57346) +2025-09-13,09:52:18 | INFO | Train Epoch: 5 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.55338 (0.55955) Boundary_loss: 0.013897 (0.013898) Loss: 0.56727 (0.57344) +2025-09-13,09:52:49 | INFO | Train Epoch: 5 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.56504 (0.55956) Boundary_loss: 0.013898 (0.013898) Loss: 0.57894 (0.57346) +2025-09-13,09:53:20 | INFO | Train Epoch: 5 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.55543 (0.55955) Boundary_loss: 0.013900 (0.013898) Loss: 0.56933 (0.57345) +2025-09-13,09:53:51 | INFO | Train Epoch: 5 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.45870 (0.55935) Boundary_loss: 0.013896 (0.013898) Loss: 0.47260 (0.57325) +2025-09-13,09:54:22 | INFO | Train Epoch: 5 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.51858 (0.55927) Boundary_loss: 0.013897 (0.013898) Loss: 0.53248 (0.57317) +2025-09-13,09:54:51 | INFO | Train Epoch: 5 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.63703 (0.55942) Boundary_loss: 0.013900 (0.013898) Loss: 0.65093 (0.57332) +2025-09-13,09:54:51 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,09:54:51 | INFO | [Epoch 5] Average Step Time: 0.311s | Average GPU Memory: 25.3 GB +2025-09-13,09:54:51 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,09:54:51 | INFO | Starting zero-shot imagenet. +2025-09-13,09:54:51 | INFO | Building zero-shot classifier +2025-09-13,09:54:57 | INFO | Using classifier +2025-09-13,09:55:43 | INFO | Finished zero-shot imagenet. +2025-09-13,09:55:43 | INFO | Eval Epoch: 6 imagenet-zeroshot-val-top1: 0.2388 imagenet-zeroshot-val-top5: 0.4846 +2025-09-13,09:55:44 | INFO | Start epoch 6 +2025-09-13,09:55:46 | INFO | Train Epoch: 6 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.47104 (0.47104) Boundary_loss: 0.013897 (0.013897) Loss: 0.48494 (0.48494) +2025-09-13,09:56:17 | INFO | Train Epoch: 6 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.48376 (0.47740) Boundary_loss: 0.013896 (0.013897) Loss: 0.49766 (0.49130) +2025-09-13,09:56:48 | INFO | Train Epoch: 6 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.51646 (0.49042) Boundary_loss: 0.013897 (0.013897) Loss: 0.53036 (0.50432) +2025-09-13,09:57:19 | INFO | Train Epoch: 6 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.56573 (0.50925) Boundary_loss: 0.013899 (0.013897) Loss: 0.57963 (0.52315) +2025-09-13,09:57:50 | INFO | Train Epoch: 6 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.37607 (0.48261) Boundary_loss: 0.013902 (0.013898) Loss: 0.38997 (0.49651) +2025-09-13,09:58:21 | INFO | Train Epoch: 6 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.39660 (0.46828) Boundary_loss: 0.013901 (0.013899) Loss: 0.41050 (0.48218) +2025-09-13,09:58:52 | INFO | Train Epoch: 6 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.44924 (0.46556) Boundary_loss: 0.013895 (0.013898) Loss: 0.46314 (0.47946) +2025-09-13,09:59:23 | INFO | Train Epoch: 6 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.50082 (0.46996) Boundary_loss: 0.013897 (0.013898) Loss: 0.51471 (0.48386) +2025-09-13,09:59:53 | INFO | Train Epoch: 6 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.55086 (0.47895) Boundary_loss: 0.013897 (0.013898) Loss: 0.56475 (0.49285) +2025-09-13,10:00:24 | INFO | Train Epoch: 6 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.46355 (0.47741) Boundary_loss: 0.013901 (0.013898) Loss: 0.47745 (0.49131) +2025-09-13,10:00:55 | INFO | Train Epoch: 6 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.54438 (0.48350) Boundary_loss: 0.013899 (0.013898) Loss: 0.55828 (0.49740) +2025-09-13,10:01:26 | INFO | Train Epoch: 6 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.47346 (0.48266) Boundary_loss: 0.013896 (0.013898) Loss: 0.48736 (0.49656) +2025-09-13,10:01:57 | INFO | Train Epoch: 6 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.45720 (0.48070) Boundary_loss: 0.013902 (0.013898) Loss: 0.47110 (0.49460) +2025-09-13,10:02:28 | INFO | Train Epoch: 6 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.41059 (0.47570) Boundary_loss: 0.013898 (0.013898) Loss: 0.42449 (0.48959) +2025-09-13,10:02:59 | INFO | Train Epoch: 6 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.44015 (0.47333) Boundary_loss: 0.013898 (0.013898) Loss: 0.45405 (0.48722) +2025-09-13,10:03:30 | INFO | Train Epoch: 6 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.43691 (0.47105) Boundary_loss: 0.013898 (0.013898) Loss: 0.45080 (0.48495) +2025-09-13,10:04:01 | INFO | Train Epoch: 6 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.50609 (0.47311) Boundary_loss: 0.013897 (0.013898) Loss: 0.51999 (0.48701) +2025-09-13,10:04:32 | INFO | Train Epoch: 6 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.50819 (0.47506) Boundary_loss: 0.013899 (0.013898) Loss: 0.52209 (0.48896) +2025-09-13,10:05:03 | INFO | Train Epoch: 6 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.39909 (0.47106) Boundary_loss: 0.013904 (0.013898) Loss: 0.41300 (0.48496) +2025-09-13,10:05:33 | INFO | Train Epoch: 6 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.46281 (0.47065) Boundary_loss: 0.013896 (0.013898) Loss: 0.47671 (0.48455) +2025-09-13,10:06:04 | INFO | Train Epoch: 6 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.59456 (0.47655) Boundary_loss: 0.013897 (0.013898) Loss: 0.60845 (0.49045) +2025-09-13,10:06:35 | INFO | Train Epoch: 6 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.51171 (0.47815) Boundary_loss: 0.013899 (0.013898) Loss: 0.52560 (0.49205) +2025-09-13,10:07:06 | INFO | Train Epoch: 6 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.49880 (0.47905) Boundary_loss: 0.013896 (0.013898) Loss: 0.51270 (0.49294) +2025-09-13,10:07:37 | INFO | Train Epoch: 6 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.51971 (0.48074) Boundary_loss: 0.013897 (0.013898) Loss: 0.53361 (0.49464) +2025-09-13,10:08:08 | INFO | Train Epoch: 6 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.42247 (0.47841) Boundary_loss: 0.013897 (0.013898) Loss: 0.43637 (0.49231) +2025-09-13,10:08:39 | INFO | Train Epoch: 6 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.38831 (0.47494) Boundary_loss: 0.013896 (0.013898) Loss: 0.40220 (0.48884) +2025-09-13,10:09:10 | INFO | Train Epoch: 6 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.54195 (0.47743) Boundary_loss: 0.013897 (0.013898) Loss: 0.55584 (0.49132) +2025-09-13,10:09:41 | INFO | Train Epoch: 6 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.38624 (0.47417) Boundary_loss: 0.013896 (0.013898) Loss: 0.40013 (0.48807) +2025-09-13,10:10:12 | INFO | Train Epoch: 6 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.45213 (0.47341) Boundary_loss: 0.013897 (0.013898) Loss: 0.46603 (0.48731) +2025-09-13,10:10:42 | INFO | Train Epoch: 6 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.60298 (0.47773) Boundary_loss: 0.013899 (0.013898) Loss: 0.61687 (0.49163) +2025-09-13,10:11:13 | INFO | Train Epoch: 6 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.46671 (0.47737) Boundary_loss: 0.013899 (0.013898) Loss: 0.48061 (0.49127) +2025-09-13,10:11:44 | INFO | Train Epoch: 6 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.40506 (0.47511) Boundary_loss: 0.013899 (0.013898) Loss: 0.41896 (0.48901) +2025-09-13,10:12:15 | INFO | Train Epoch: 6 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.45658 (0.47455) Boundary_loss: 0.013896 (0.013898) Loss: 0.47048 (0.48845) +2025-09-13,10:12:46 | INFO | Train Epoch: 6 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.40446 (0.47249) Boundary_loss: 0.013895 (0.013898) Loss: 0.41835 (0.48639) +2025-09-13,10:13:17 | INFO | Train Epoch: 6 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.52195 (0.47390) Boundary_loss: 0.013896 (0.013898) Loss: 0.53585 (0.48780) +2025-09-13,10:13:48 | INFO | Train Epoch: 6 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.51518 (0.47505) Boundary_loss: 0.013896 (0.013898) Loss: 0.52907 (0.48895) +2025-09-13,10:14:19 | INFO | Train Epoch: 6 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.42025 (0.47357) Boundary_loss: 0.013897 (0.013898) Loss: 0.43415 (0.48747) +2025-09-13,10:14:50 | INFO | Train Epoch: 6 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.53933 (0.47530) Boundary_loss: 0.013898 (0.013898) Loss: 0.55323 (0.48920) +2025-09-13,10:15:21 | INFO | Train Epoch: 6 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.47856 (0.47538) Boundary_loss: 0.013896 (0.013898) Loss: 0.49246 (0.48928) +2025-09-13,10:15:52 | INFO | Train Epoch: 6 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.46929 (0.47523) Boundary_loss: 0.013900 (0.013898) Loss: 0.48319 (0.48913) +2025-09-13,10:16:23 | INFO | Train Epoch: 6 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.49366 (0.47568) Boundary_loss: 0.013896 (0.013898) Loss: 0.50756 (0.48958) +2025-09-13,10:16:54 | INFO | Train Epoch: 6 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.48400 (0.47588) Boundary_loss: 0.013896 (0.013898) Loss: 0.49790 (0.48978) +2025-09-13,10:17:25 | INFO | Train Epoch: 6 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.54963 (0.47759) Boundary_loss: 0.013900 (0.013898) Loss: 0.56353 (0.49149) +2025-09-13,10:17:56 | INFO | Train Epoch: 6 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.51286 (0.47839) Boundary_loss: 0.013897 (0.013898) Loss: 0.52676 (0.49229) +2025-09-13,10:18:27 | INFO | Train Epoch: 6 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.55323 (0.48006) Boundary_loss: 0.013899 (0.013898) Loss: 0.56713 (0.49396) +2025-09-13,10:18:58 | INFO | Train Epoch: 6 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.46826 (0.47980) Boundary_loss: 0.013897 (0.013898) Loss: 0.48216 (0.49370) +2025-09-13,10:19:29 | INFO | Train Epoch: 6 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.44690 (0.47910) Boundary_loss: 0.013896 (0.013898) Loss: 0.46079 (0.49300) +2025-09-13,10:20:00 | INFO | Train Epoch: 6 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.41286 (0.47772) Boundary_loss: 0.013899 (0.013898) Loss: 0.42676 (0.49162) +2025-09-13,10:20:31 | INFO | Train Epoch: 6 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.47907 (0.47775) Boundary_loss: 0.013898 (0.013898) Loss: 0.49297 (0.49165) +2025-09-13,10:21:02 | INFO | Train Epoch: 6 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.57122 (0.47962) Boundary_loss: 0.013897 (0.013898) Loss: 0.58512 (0.49352) +2025-09-13,10:21:33 | INFO | Train Epoch: 6 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.45785 (0.47919) Boundary_loss: 0.013898 (0.013898) Loss: 0.47175 (0.49309) +2025-09-13,10:22:04 | INFO | Train Epoch: 6 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.45335 (0.47869) Boundary_loss: 0.013912 (0.013898) Loss: 0.46727 (0.49259) +2025-09-13,10:22:35 | INFO | Train Epoch: 6 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.54640 (0.47997) Boundary_loss: 0.013898 (0.013898) Loss: 0.56030 (0.49387) +2025-09-13,10:23:06 | INFO | Train Epoch: 6 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.49552 (0.48026) Boundary_loss: 0.013899 (0.013898) Loss: 0.50942 (0.49416) +2025-09-13,10:23:37 | INFO | Train Epoch: 6 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.51593 (0.48091) Boundary_loss: 0.013895 (0.013898) Loss: 0.52982 (0.49481) +2025-09-13,10:24:08 | INFO | Train Epoch: 6 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.45904 (0.48052) Boundary_loss: 0.013898 (0.013898) Loss: 0.47294 (0.49442) +2025-09-13,10:24:39 | INFO | Train Epoch: 6 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.49648 (0.48080) Boundary_loss: 0.013896 (0.013898) Loss: 0.51037 (0.49470) +2025-09-13,10:25:10 | INFO | Train Epoch: 6 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.45081 (0.48028) Boundary_loss: 0.013904 (0.013898) Loss: 0.46471 (0.49418) +2025-09-13,10:25:40 | INFO | Train Epoch: 6 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.42353 (0.47932) Boundary_loss: 0.013900 (0.013898) Loss: 0.43743 (0.49322) +2025-09-13,10:26:11 | INFO | Train Epoch: 6 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.43117 (0.47852) Boundary_loss: 0.013898 (0.013898) Loss: 0.44507 (0.49241) +2025-09-13,10:26:42 | INFO | Train Epoch: 6 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.50931 (0.47902) Boundary_loss: 0.013898 (0.013898) Loss: 0.52321 (0.49292) +2025-09-13,10:27:13 | INFO | Train Epoch: 6 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.43200 (0.47826) Boundary_loss: 0.013898 (0.013898) Loss: 0.44589 (0.49216) +2025-09-13,10:27:44 | INFO | Train Epoch: 6 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.49219 (0.47848) Boundary_loss: 0.013898 (0.013898) Loss: 0.50609 (0.49238) +2025-09-13,10:28:15 | INFO | Train Epoch: 6 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.38948 (0.47709) Boundary_loss: 0.013913 (0.013898) Loss: 0.40339 (0.49099) +2025-09-13,10:28:46 | INFO | Train Epoch: 6 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.43154 (0.47639) Boundary_loss: 0.013900 (0.013898) Loss: 0.44544 (0.49029) +2025-09-13,10:29:17 | INFO | Train Epoch: 6 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.53877 (0.47734) Boundary_loss: 0.013899 (0.013898) Loss: 0.55267 (0.49124) +2025-09-13,10:29:48 | INFO | Train Epoch: 6 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.42098 (0.47650) Boundary_loss: 0.013899 (0.013898) Loss: 0.43488 (0.49039) +2025-09-13,10:30:19 | INFO | Train Epoch: 6 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.55363 (0.47763) Boundary_loss: 0.013898 (0.013898) Loss: 0.56753 (0.49153) +2025-09-13,10:30:50 | INFO | Train Epoch: 6 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.45668 (0.47733) Boundary_loss: 0.013898 (0.013898) Loss: 0.47058 (0.49123) +2025-09-13,10:31:21 | INFO | Train Epoch: 6 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.39139 (0.47610) Boundary_loss: 0.013896 (0.013898) Loss: 0.40528 (0.49000) +2025-09-13,10:31:52 | INFO | Train Epoch: 6 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.42973 (0.47545) Boundary_loss: 0.013897 (0.013898) Loss: 0.44363 (0.48934) +2025-09-13,10:32:22 | INFO | Train Epoch: 6 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.57749 (0.47686) Boundary_loss: 0.013897 (0.013898) Loss: 0.59139 (0.49076) +2025-09-13,10:32:53 | INFO | Train Epoch: 6 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.55060 (0.47787) Boundary_loss: 0.013896 (0.013898) Loss: 0.56450 (0.49177) +2025-09-13,10:33:24 | INFO | Train Epoch: 6 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.43978 (0.47736) Boundary_loss: 0.013897 (0.013898) Loss: 0.45367 (0.49126) +2025-09-13,10:33:55 | INFO | Train Epoch: 6 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.51643 (0.47788) Boundary_loss: 0.013897 (0.013898) Loss: 0.53033 (0.49178) +2025-09-13,10:34:26 | INFO | Train Epoch: 6 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.53998 (0.47870) Boundary_loss: 0.013898 (0.013898) Loss: 0.55388 (0.49260) +2025-09-13,10:34:57 | INFO | Train Epoch: 6 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.47472 (0.47865) Boundary_loss: 0.013897 (0.013898) Loss: 0.48861 (0.49254) +2025-09-13,10:35:28 | INFO | Train Epoch: 6 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.42700 (0.47798) Boundary_loss: 0.013898 (0.013898) Loss: 0.44090 (0.49188) +2025-09-13,10:35:59 | INFO | Train Epoch: 6 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.50748 (0.47836) Boundary_loss: 0.013895 (0.013898) Loss: 0.52137 (0.49225) +2025-09-13,10:36:30 | INFO | Train Epoch: 6 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.49824 (0.47860) Boundary_loss: 0.013896 (0.013898) Loss: 0.51213 (0.49250) +2025-09-13,10:37:01 | INFO | Train Epoch: 6 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40464 (0.47769) Boundary_loss: 0.013898 (0.013898) Loss: 0.41854 (0.49159) +2025-09-13,10:37:32 | INFO | Train Epoch: 6 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.49700 (0.47793) Boundary_loss: 0.013898 (0.013898) Loss: 0.51090 (0.49183) +2025-09-13,10:38:02 | INFO | Train Epoch: 6 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.47777 (0.47793) Boundary_loss: 0.013896 (0.013898) Loss: 0.49166 (0.49182) +2025-09-13,10:38:33 | INFO | Train Epoch: 6 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.54592 (0.47873) Boundary_loss: 0.013896 (0.013898) Loss: 0.55982 (0.49263) +2025-09-13,10:39:04 | INFO | Train Epoch: 6 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.41584 (0.47799) Boundary_loss: 0.013897 (0.013898) Loss: 0.42973 (0.49189) +2025-09-13,10:39:35 | INFO | Train Epoch: 6 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.52265 (0.47851) Boundary_loss: 0.013897 (0.013898) Loss: 0.53654 (0.49241) +2025-09-13,10:40:06 | INFO | Train Epoch: 6 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40906 (0.47772) Boundary_loss: 0.013897 (0.013898) Loss: 0.42295 (0.49161) +2025-09-13,10:40:37 | INFO | Train Epoch: 6 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.47214 (0.47765) Boundary_loss: 0.013897 (0.013898) Loss: 0.48603 (0.49155) +2025-09-13,10:41:07 | INFO | Train Epoch: 6 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.49999 (0.47790) Boundary_loss: 0.013897 (0.013898) Loss: 0.51389 (0.49180) +2025-09-13,10:41:38 | INFO | Train Epoch: 6 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.42109 (0.47727) Boundary_loss: 0.013897 (0.013898) Loss: 0.43499 (0.49117) +2025-09-13,10:42:09 | INFO | Train Epoch: 6 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.49132 (0.47743) Boundary_loss: 0.013896 (0.013898) Loss: 0.50521 (0.49132) +2025-09-13,10:42:40 | INFO | Train Epoch: 6 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.45870 (0.47722) Boundary_loss: 0.013896 (0.013898) Loss: 0.47260 (0.49112) +2025-09-13,10:43:11 | INFO | Train Epoch: 6 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.44024 (0.47683) Boundary_loss: 0.013897 (0.013898) Loss: 0.45413 (0.49072) +2025-09-13,10:43:42 | INFO | Train Epoch: 6 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.50969 (0.47717) Boundary_loss: 0.013896 (0.013898) Loss: 0.52358 (0.49107) +2025-09-13,10:44:13 | INFO | Train Epoch: 6 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.45068 (0.47690) Boundary_loss: 0.013898 (0.013898) Loss: 0.46458 (0.49079) +2025-09-13,10:44:43 | INFO | Train Epoch: 6 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.45982 (0.47672) Boundary_loss: 0.013895 (0.013898) Loss: 0.47372 (0.49062) +2025-09-13,10:45:14 | INFO | Train Epoch: 6 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.45313 (0.47647) Boundary_loss: 0.013897 (0.013898) Loss: 0.46703 (0.49037) +2025-09-13,10:45:45 | INFO | Train Epoch: 6 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.53984 (0.47712) Boundary_loss: 0.013896 (0.013898) Loss: 0.55373 (0.49102) +2025-09-13,10:46:16 | INFO | Train Epoch: 6 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.51366 (0.47749) Boundary_loss: 0.013902 (0.013898) Loss: 0.52756 (0.49139) +2025-09-13,10:46:47 | INFO | Train Epoch: 6 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.47603 (0.47748) Boundary_loss: 0.013896 (0.013898) Loss: 0.48993 (0.49137) +2025-09-13,10:47:17 | INFO | Train Epoch: 6 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.44470 (0.47715) Boundary_loss: 0.013898 (0.013898) Loss: 0.45860 (0.49105) +2025-09-13,10:47:48 | INFO | Train Epoch: 6 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.47089 (0.47709) Boundary_loss: 0.013895 (0.013898) Loss: 0.48479 (0.49099) +2025-09-13,10:48:19 | INFO | Train Epoch: 6 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.44062 (0.47674) Boundary_loss: 0.013898 (0.013898) Loss: 0.45451 (0.49063) +2025-09-13,10:48:50 | INFO | Train Epoch: 6 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.51738 (0.47713) Boundary_loss: 0.013897 (0.013898) Loss: 0.53127 (0.49102) +2025-09-13,10:49:20 | INFO | Train Epoch: 6 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.48186 (0.47717) Boundary_loss: 0.013896 (0.013898) Loss: 0.49575 (0.49107) +2025-09-13,10:49:51 | INFO | Train Epoch: 6 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.47696 (0.47717) Boundary_loss: 0.013896 (0.013898) Loss: 0.49085 (0.49107) +2025-09-13,10:50:22 | INFO | Train Epoch: 6 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.52548 (0.47762) Boundary_loss: 0.013895 (0.013898) Loss: 0.53937 (0.49152) +2025-09-13,10:50:53 | INFO | Train Epoch: 6 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.52225 (0.47803) Boundary_loss: 0.013896 (0.013898) Loss: 0.53615 (0.49193) +2025-09-13,10:51:24 | INFO | Train Epoch: 6 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.48977 (0.47814) Boundary_loss: 0.013896 (0.013898) Loss: 0.50366 (0.49204) +2025-09-13,10:51:55 | INFO | Train Epoch: 6 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.46890 (0.47806) Boundary_loss: 0.013897 (0.013898) Loss: 0.48280 (0.49196) +2025-09-13,10:52:25 | INFO | Train Epoch: 6 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42601 (0.47759) Boundary_loss: 0.013896 (0.013898) Loss: 0.43990 (0.49149) +2025-09-13,10:52:56 | INFO | Train Epoch: 6 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.48840 (0.47769) Boundary_loss: 0.013897 (0.013898) Loss: 0.50230 (0.49158) +2025-09-13,10:53:27 | INFO | Train Epoch: 6 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.56845 (0.47849) Boundary_loss: 0.013900 (0.013898) Loss: 0.58235 (0.49239) +2025-09-13,10:53:58 | INFO | Train Epoch: 6 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.51261 (0.47879) Boundary_loss: 0.013897 (0.013898) Loss: 0.52651 (0.49269) +2025-09-13,10:54:29 | INFO | Train Epoch: 6 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.48738 (0.47886) Boundary_loss: 0.013898 (0.013898) Loss: 0.50127 (0.49276) +2025-09-13,10:55:00 | INFO | Train Epoch: 6 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.53525 (0.47935) Boundary_loss: 0.013897 (0.013898) Loss: 0.54915 (0.49325) +2025-09-13,10:55:31 | INFO | Train Epoch: 6 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.48733 (0.47942) Boundary_loss: 0.013900 (0.013898) Loss: 0.50123 (0.49331) +2025-09-13,10:56:01 | INFO | Train Epoch: 6 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.46826 (0.47932) Boundary_loss: 0.013896 (0.013898) Loss: 0.48215 (0.49322) +2025-09-13,10:56:32 | INFO | Train Epoch: 6 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.45709 (0.47914) Boundary_loss: 0.013897 (0.013898) Loss: 0.47098 (0.49303) +2025-09-13,10:57:03 | INFO | Train Epoch: 6 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.43197 (0.47874) Boundary_loss: 0.013900 (0.013898) Loss: 0.44587 (0.49264) +2025-09-13,10:57:34 | INFO | Train Epoch: 6 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.48501 (0.47879) Boundary_loss: 0.013896 (0.013898) Loss: 0.49891 (0.49269) +2025-09-13,10:58:05 | INFO | Train Epoch: 6 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.45588 (0.47861) Boundary_loss: 0.013897 (0.013898) Loss: 0.46978 (0.49250) +2025-09-13,10:58:36 | INFO | Train Epoch: 6 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.45534 (0.47842) Boundary_loss: 0.013897 (0.013898) Loss: 0.46923 (0.49232) +2025-09-13,10:59:07 | INFO | Train Epoch: 6 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.52581 (0.47880) Boundary_loss: 0.013895 (0.013898) Loss: 0.53970 (0.49270) +2025-09-13,10:59:37 | INFO | Train Epoch: 6 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.43249 (0.47843) Boundary_loss: 0.013897 (0.013898) Loss: 0.44638 (0.49233) +2025-09-13,11:00:08 | INFO | Train Epoch: 6 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.57726 (0.47921) Boundary_loss: 0.013897 (0.013898) Loss: 0.59116 (0.49311) +2025-09-13,11:00:39 | INFO | Train Epoch: 6 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.50328 (0.47940) Boundary_loss: 0.013896 (0.013898) Loss: 0.51717 (0.49330) +2025-09-13,11:01:10 | INFO | Train Epoch: 6 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36503 (0.47851) Boundary_loss: 0.013897 (0.013898) Loss: 0.37893 (0.49241) +2025-09-13,11:01:41 | INFO | Train Epoch: 6 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.44282 (0.47823) Boundary_loss: 0.013896 (0.013898) Loss: 0.45672 (0.49213) +2025-09-13,11:02:12 | INFO | Train Epoch: 6 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.52699 (0.47861) Boundary_loss: 0.013901 (0.013898) Loss: 0.54089 (0.49251) +2025-09-13,11:02:43 | INFO | Train Epoch: 6 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.43806 (0.47830) Boundary_loss: 0.013897 (0.013898) Loss: 0.45195 (0.49220) +2025-09-13,11:03:14 | INFO | Train Epoch: 6 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.43722 (0.47799) Boundary_loss: 0.013896 (0.013898) Loss: 0.45112 (0.49188) +2025-09-13,11:03:45 | INFO | Train Epoch: 6 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.45779 (0.47784) Boundary_loss: 0.013899 (0.013898) Loss: 0.47169 (0.49173) +2025-09-13,11:04:16 | INFO | Train Epoch: 6 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.50131 (0.47801) Boundary_loss: 0.013898 (0.013898) Loss: 0.51520 (0.49191) +2025-09-13,11:04:47 | INFO | Train Epoch: 6 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40724 (0.47749) Boundary_loss: 0.013896 (0.013898) Loss: 0.42113 (0.49138) +2025-09-13,11:05:18 | INFO | Train Epoch: 6 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.57634 (0.47821) Boundary_loss: 0.013895 (0.013898) Loss: 0.59024 (0.49211) +2025-09-13,11:05:49 | INFO | Train Epoch: 6 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.48842 (0.47829) Boundary_loss: 0.013897 (0.013898) Loss: 0.50232 (0.49219) +2025-09-13,11:06:20 | INFO | Train Epoch: 6 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.49978 (0.47844) Boundary_loss: 0.013902 (0.013898) Loss: 0.51368 (0.49234) +2025-09-13,11:06:50 | INFO | Train Epoch: 6 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.48494 (0.47849) Boundary_loss: 0.013902 (0.013898) Loss: 0.49884 (0.49239) +2025-09-13,11:07:21 | INFO | Train Epoch: 6 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.54383 (0.47896) Boundary_loss: 0.013899 (0.013898) Loss: 0.55773 (0.49285) +2025-09-13,11:07:52 | INFO | Train Epoch: 6 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.49518 (0.47907) Boundary_loss: 0.013895 (0.013898) Loss: 0.50908 (0.49297) +2025-09-13,11:08:23 | INFO | Train Epoch: 6 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.55129 (0.47958) Boundary_loss: 0.013897 (0.013898) Loss: 0.56519 (0.49348) +2025-09-13,11:08:54 | INFO | Train Epoch: 6 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.39734 (0.47901) Boundary_loss: 0.013897 (0.013898) Loss: 0.41124 (0.49290) +2025-09-13,11:09:25 | INFO | Train Epoch: 6 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.45857 (0.47886) Boundary_loss: 0.013899 (0.013898) Loss: 0.47247 (0.49276) +2025-09-13,11:09:56 | INFO | Train Epoch: 6 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.52420 (0.47918) Boundary_loss: 0.013897 (0.013898) Loss: 0.53810 (0.49307) +2025-09-13,11:10:27 | INFO | Train Epoch: 6 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.57384 (0.47982) Boundary_loss: 0.013897 (0.013898) Loss: 0.58774 (0.49372) +2025-09-13,11:10:58 | INFO | Train Epoch: 6 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.49904 (0.47996) Boundary_loss: 0.013896 (0.013898) Loss: 0.51293 (0.49385) +2025-09-13,11:11:29 | INFO | Train Epoch: 6 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.47925 (0.47995) Boundary_loss: 0.013896 (0.013898) Loss: 0.49315 (0.49385) +2025-09-13,11:12:00 | INFO | Train Epoch: 6 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.53313 (0.48031) Boundary_loss: 0.013899 (0.013898) Loss: 0.54703 (0.49421) +2025-09-13,11:12:31 | INFO | Train Epoch: 6 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.49497 (0.48041) Boundary_loss: 0.013898 (0.013898) Loss: 0.50887 (0.49430) +2025-09-13,11:13:02 | INFO | Train Epoch: 6 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.52968 (0.48073) Boundary_loss: 0.013896 (0.013898) Loss: 0.54357 (0.49463) +2025-09-13,11:13:33 | INFO | Train Epoch: 6 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.46015 (0.48060) Boundary_loss: 0.013895 (0.013898) Loss: 0.47404 (0.49449) +2025-09-13,11:14:04 | INFO | Train Epoch: 6 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.40410 (0.48010) Boundary_loss: 0.013900 (0.013898) Loss: 0.41800 (0.49399) +2025-09-13,11:14:35 | INFO | Train Epoch: 6 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.53874 (0.48048) Boundary_loss: 0.013900 (0.013898) Loss: 0.55264 (0.49437) +2025-09-13,11:15:05 | INFO | Train Epoch: 6 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.55354 (0.48095) Boundary_loss: 0.013898 (0.013898) Loss: 0.56743 (0.49485) +2025-09-13,11:15:36 | INFO | Train Epoch: 6 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.44854 (0.48074) Boundary_loss: 0.013897 (0.013898) Loss: 0.46243 (0.49464) +2025-09-13,11:16:07 | INFO | Train Epoch: 6 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.58134 (0.48138) Boundary_loss: 0.013898 (0.013898) Loss: 0.59524 (0.49528) +2025-09-13,11:16:38 | INFO | Train Epoch: 6 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40401 (0.48089) Boundary_loss: 0.013896 (0.013898) Loss: 0.41790 (0.49479) +2025-09-13,11:17:09 | INFO | Train Epoch: 6 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.46316 (0.48078) Boundary_loss: 0.013897 (0.013898) Loss: 0.47705 (0.49468) +2025-09-13,11:17:40 | INFO | Train Epoch: 6 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.46883 (0.48071) Boundary_loss: 0.013896 (0.013898) Loss: 0.48273 (0.49460) +2025-09-13,11:18:11 | INFO | Train Epoch: 6 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.46849 (0.48063) Boundary_loss: 0.013896 (0.013898) Loss: 0.48239 (0.49453) +2025-09-13,11:18:42 | INFO | Train Epoch: 6 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.46798 (0.48055) Boundary_loss: 0.013896 (0.013898) Loss: 0.48187 (0.49445) +2025-09-13,11:19:12 | INFO | Train Epoch: 6 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.52898 (0.48085) Boundary_loss: 0.013896 (0.013898) Loss: 0.54287 (0.49475) +2025-09-13,11:19:43 | INFO | Train Epoch: 6 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.46935 (0.48078) Boundary_loss: 0.013897 (0.013898) Loss: 0.48324 (0.49468) +2025-09-13,11:20:14 | INFO | Train Epoch: 6 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.55486 (0.48123) Boundary_loss: 0.013897 (0.013898) Loss: 0.56876 (0.49512) +2025-09-13,11:20:45 | INFO | Train Epoch: 6 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.51573 (0.48144) Boundary_loss: 0.013897 (0.013898) Loss: 0.52962 (0.49533) +2025-09-13,11:21:16 | INFO | Train Epoch: 6 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.44933 (0.48124) Boundary_loss: 0.013895 (0.013898) Loss: 0.46322 (0.49514) +2025-09-13,11:21:47 | INFO | Train Epoch: 6 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.50330 (0.48137) Boundary_loss: 0.013896 (0.013898) Loss: 0.51719 (0.49527) +2025-09-13,11:22:18 | INFO | Train Epoch: 6 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.35494 (0.48063) Boundary_loss: 0.013897 (0.013898) Loss: 0.36884 (0.49452) +2025-09-13,11:22:49 | INFO | Train Epoch: 6 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.57135 (0.48116) Boundary_loss: 0.013903 (0.013898) Loss: 0.58526 (0.49506) +2025-09-13,11:23:20 | INFO | Train Epoch: 6 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.45264 (0.48099) Boundary_loss: 0.013896 (0.013898) Loss: 0.46653 (0.49489) +2025-09-13,11:23:51 | INFO | Train Epoch: 6 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.50438 (0.48113) Boundary_loss: 0.013896 (0.013898) Loss: 0.51827 (0.49503) +2025-09-13,11:24:22 | INFO | Train Epoch: 6 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.50176 (0.48125) Boundary_loss: 0.013897 (0.013898) Loss: 0.51566 (0.49515) +2025-09-13,11:24:53 | INFO | Train Epoch: 6 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.44873 (0.48106) Boundary_loss: 0.013897 (0.013898) Loss: 0.46263 (0.49496) +2025-09-13,11:25:24 | INFO | Train Epoch: 6 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.59192 (0.48169) Boundary_loss: 0.013896 (0.013898) Loss: 0.60581 (0.49559) +2025-09-13,11:25:55 | INFO | Train Epoch: 6 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.53506 (0.48200) Boundary_loss: 0.013896 (0.013898) Loss: 0.54896 (0.49590) +2025-09-13,11:26:26 | INFO | Train Epoch: 6 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.56434 (0.48246) Boundary_loss: 0.013897 (0.013898) Loss: 0.57824 (0.49636) +2025-09-13,11:26:56 | INFO | Train Epoch: 6 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.48212 (0.48246) Boundary_loss: 0.013895 (0.013897) Loss: 0.49602 (0.49636) +2025-09-13,11:27:27 | INFO | Train Epoch: 6 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.44113 (0.48223) Boundary_loss: 0.013900 (0.013898) Loss: 0.45503 (0.49613) +2025-09-13,11:27:58 | INFO | Train Epoch: 6 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.54401 (0.48257) Boundary_loss: 0.013895 (0.013897) Loss: 0.55790 (0.49647) +2025-09-13,11:28:29 | INFO | Train Epoch: 6 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.46396 (0.48247) Boundary_loss: 0.013899 (0.013898) Loss: 0.47786 (0.49637) +2025-09-13,11:29:00 | INFO | Train Epoch: 6 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.47204 (0.48241) Boundary_loss: 0.013895 (0.013897) Loss: 0.48594 (0.49631) +2025-09-13,11:29:31 | INFO | Train Epoch: 6 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.49478 (0.48248) Boundary_loss: 0.013899 (0.013898) Loss: 0.50868 (0.49638) +2025-09-13,11:30:02 | INFO | Train Epoch: 6 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.44343 (0.48227) Boundary_loss: 0.013900 (0.013898) Loss: 0.45733 (0.49617) +2025-09-13,11:30:33 | INFO | Train Epoch: 6 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.48911 (0.48231) Boundary_loss: 0.013899 (0.013898) Loss: 0.50301 (0.49620) +2025-09-13,11:31:04 | INFO | Train Epoch: 6 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.53303 (0.48258) Boundary_loss: 0.013897 (0.013898) Loss: 0.54693 (0.49648) +2025-09-13,11:31:35 | INFO | Train Epoch: 6 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.39547 (0.48211) Boundary_loss: 0.013905 (0.013898) Loss: 0.40937 (0.49601) +2025-09-13,11:32:06 | INFO | Train Epoch: 6 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.45823 (0.48199) Boundary_loss: 0.013896 (0.013898) Loss: 0.47213 (0.49588) +2025-09-13,11:32:37 | INFO | Train Epoch: 6 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.38471 (0.48147) Boundary_loss: 0.013898 (0.013898) Loss: 0.39860 (0.49537) +2025-09-13,11:33:08 | INFO | Train Epoch: 6 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.48261 (0.48148) Boundary_loss: 0.013896 (0.013898) Loss: 0.49650 (0.49537) +2025-09-13,11:33:39 | INFO | Train Epoch: 6 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.47212 (0.48143) Boundary_loss: 0.013900 (0.013898) Loss: 0.48602 (0.49533) +2025-09-13,11:34:10 | INFO | Train Epoch: 6 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.47070 (0.48137) Boundary_loss: 0.013896 (0.013898) Loss: 0.48460 (0.49527) +2025-09-13,11:34:41 | INFO | Train Epoch: 6 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.44805 (0.48120) Boundary_loss: 0.013895 (0.013898) Loss: 0.46194 (0.49510) +2025-09-13,11:35:12 | INFO | Train Epoch: 6 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42943 (0.48093) Boundary_loss: 0.013896 (0.013898) Loss: 0.44333 (0.49483) +2025-09-13,11:35:43 | INFO | Train Epoch: 6 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.41455 (0.48059) Boundary_loss: 0.013895 (0.013898) Loss: 0.42844 (0.49449) +2025-09-13,11:36:14 | INFO | Train Epoch: 6 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.40898 (0.48023) Boundary_loss: 0.013898 (0.013898) Loss: 0.42287 (0.49412) +2025-09-13,11:36:45 | INFO | Train Epoch: 6 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.51155 (0.48039) Boundary_loss: 0.013898 (0.013898) Loss: 0.52545 (0.49428) +2025-09-13,11:37:17 | INFO | Train Epoch: 6 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.43789 (0.48017) Boundary_loss: 0.013899 (0.013898) Loss: 0.45179 (0.49407) +2025-09-13,11:37:47 | INFO | Train Epoch: 6 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.39872 (0.47976) Boundary_loss: 0.013896 (0.013898) Loss: 0.41261 (0.49366) +2025-09-13,11:38:18 | INFO | Train Epoch: 6 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.41174 (0.47942) Boundary_loss: 0.013898 (0.013898) Loss: 0.42563 (0.49332) +2025-09-13,11:38:49 | INFO | Train Epoch: 6 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.49743 (0.47951) Boundary_loss: 0.013898 (0.013898) Loss: 0.51133 (0.49341) +2025-09-13,11:39:20 | INFO | Train Epoch: 6 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.43597 (0.47930) Boundary_loss: 0.013896 (0.013898) Loss: 0.44986 (0.49319) +2025-09-13,11:39:51 | INFO | Train Epoch: 6 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.49012 (0.47935) Boundary_loss: 0.013898 (0.013898) Loss: 0.50402 (0.49325) +2025-09-13,11:40:22 | INFO | Train Epoch: 6 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.48780 (0.47939) Boundary_loss: 0.013898 (0.013898) Loss: 0.50170 (0.49329) +2025-09-13,11:40:52 | INFO | Train Epoch: 6 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.43447 (0.47917) Boundary_loss: 0.013895 (0.013898) Loss: 0.44837 (0.49307) +2025-09-13,11:41:23 | INFO | Train Epoch: 6 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.49405 (0.47924) Boundary_loss: 0.013898 (0.013898) Loss: 0.50795 (0.49314) +2025-09-13,11:41:54 | INFO | Train Epoch: 6 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.41336 (0.47893) Boundary_loss: 0.013896 (0.013898) Loss: 0.42726 (0.49282) +2025-09-13,11:42:25 | INFO | Train Epoch: 6 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.46361 (0.47885) Boundary_loss: 0.013897 (0.013898) Loss: 0.47751 (0.49275) +2025-09-13,11:42:56 | INFO | Train Epoch: 6 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.39243 (0.47844) Boundary_loss: 0.013896 (0.013897) Loss: 0.40633 (0.49234) +2025-09-13,11:43:27 | INFO | Train Epoch: 6 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.47038 (0.47840) Boundary_loss: 0.013896 (0.013897) Loss: 0.48428 (0.49230) +2025-09-13,11:43:58 | INFO | Train Epoch: 6 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.43110 (0.47818) Boundary_loss: 0.013898 (0.013897) Loss: 0.44500 (0.49207) +2025-09-13,11:44:29 | INFO | Train Epoch: 6 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.46848 (0.47813) Boundary_loss: 0.013898 (0.013897) Loss: 0.48238 (0.49203) +2025-09-13,11:45:00 | INFO | Train Epoch: 6 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.43814 (0.47794) Boundary_loss: 0.013895 (0.013897) Loss: 0.45203 (0.49184) +2025-09-13,11:45:31 | INFO | Train Epoch: 6 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.48778 (0.47799) Boundary_loss: 0.013897 (0.013897) Loss: 0.50168 (0.49189) +2025-09-13,11:46:02 | INFO | Train Epoch: 6 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.51943 (0.47818) Boundary_loss: 0.013896 (0.013897) Loss: 0.53332 (0.49208) +2025-09-13,11:46:33 | INFO | Train Epoch: 6 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.48554 (0.47821) Boundary_loss: 0.013897 (0.013897) Loss: 0.49944 (0.49211) +2025-09-13,11:47:03 | INFO | Train Epoch: 6 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.52112 (0.47841) Boundary_loss: 0.013896 (0.013897) Loss: 0.53502 (0.49231) +2025-09-13,11:47:34 | INFO | Train Epoch: 6 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.59453 (0.47895) Boundary_loss: 0.013895 (0.013897) Loss: 0.60842 (0.49284) +2025-09-13,11:48:05 | INFO | Train Epoch: 6 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.50129 (0.47905) Boundary_loss: 0.013896 (0.013897) Loss: 0.51519 (0.49294) +2025-09-13,11:48:36 | INFO | Train Epoch: 6 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.57195 (0.47947) Boundary_loss: 0.013895 (0.013897) Loss: 0.58584 (0.49337) +2025-09-13,11:49:07 | INFO | Train Epoch: 6 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.45443 (0.47936) Boundary_loss: 0.013895 (0.013897) Loss: 0.46833 (0.49325) +2025-09-13,11:49:38 | INFO | Train Epoch: 6 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.47347 (0.47933) Boundary_loss: 0.013895 (0.013897) Loss: 0.48737 (0.49323) +2025-09-13,11:50:09 | INFO | Train Epoch: 6 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.44617 (0.47918) Boundary_loss: 0.013896 (0.013897) Loss: 0.46007 (0.49308) +2025-09-13,11:50:40 | INFO | Train Epoch: 6 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.47127 (0.47915) Boundary_loss: 0.013894 (0.013897) Loss: 0.48516 (0.49304) +2025-09-13,11:51:11 | INFO | Train Epoch: 6 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.56964 (0.47955) Boundary_loss: 0.013896 (0.013897) Loss: 0.58354 (0.49345) +2025-09-13,11:51:42 | INFO | Train Epoch: 6 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46418 (0.47948) Boundary_loss: 0.013896 (0.013897) Loss: 0.47807 (0.49338) +2025-09-13,11:52:13 | INFO | Train Epoch: 6 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.51705 (0.47965) Boundary_loss: 0.013897 (0.013897) Loss: 0.53095 (0.49354) +2025-09-13,11:52:43 | INFO | Train Epoch: 6 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.47403 (0.47962) Boundary_loss: 0.013895 (0.013897) Loss: 0.48792 (0.49352) +2025-09-13,11:53:14 | INFO | Train Epoch: 6 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.49783 (0.47970) Boundary_loss: 0.013895 (0.013897) Loss: 0.51173 (0.49360) +2025-09-13,11:53:45 | INFO | Train Epoch: 6 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.47868 (0.47970) Boundary_loss: 0.013896 (0.013897) Loss: 0.49258 (0.49359) +2025-09-13,11:54:16 | INFO | Train Epoch: 6 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.49018 (0.47974) Boundary_loss: 0.013898 (0.013897) Loss: 0.50408 (0.49364) +2025-09-13,11:54:47 | INFO | Train Epoch: 6 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.50613 (0.47986) Boundary_loss: 0.013896 (0.013897) Loss: 0.52003 (0.49375) +2025-09-13,11:55:18 | INFO | Train Epoch: 6 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.34012 (0.47926) Boundary_loss: 0.013898 (0.013897) Loss: 0.35401 (0.49315) +2025-09-13,11:55:48 | INFO | Train Epoch: 6 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.56021 (0.47960) Boundary_loss: 0.013895 (0.013897) Loss: 0.57410 (0.49350) +2025-09-13,11:56:19 | INFO | Train Epoch: 6 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.54608 (0.47988) Boundary_loss: 0.013898 (0.013897) Loss: 0.55998 (0.49378) +2025-09-13,11:56:50 | INFO | Train Epoch: 6 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.48388 (0.47990) Boundary_loss: 0.013895 (0.013897) Loss: 0.49777 (0.49380) +2025-09-13,11:57:21 | INFO | Train Epoch: 6 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.46244 (0.47983) Boundary_loss: 0.013898 (0.013897) Loss: 0.47634 (0.49372) +2025-09-13,11:57:52 | INFO | Train Epoch: 6 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.48074 (0.47983) Boundary_loss: 0.013896 (0.013897) Loss: 0.49464 (0.49373) +2025-09-13,11:58:23 | INFO | Train Epoch: 6 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.37860 (0.47941) Boundary_loss: 0.013895 (0.013897) Loss: 0.39249 (0.49331) +2025-09-13,11:58:54 | INFO | Train Epoch: 6 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.46455 (0.47935) Boundary_loss: 0.013899 (0.013897) Loss: 0.47845 (0.49324) +2025-09-13,11:59:25 | INFO | Train Epoch: 6 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.45764 (0.47926) Boundary_loss: 0.013896 (0.013897) Loss: 0.47153 (0.49315) +2025-09-13,11:59:56 | INFO | Train Epoch: 6 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.58498 (0.47969) Boundary_loss: 0.013897 (0.013897) Loss: 0.59888 (0.49359) +2025-09-13,12:00:27 | INFO | Train Epoch: 6 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.42164 (0.47945) Boundary_loss: 0.013897 (0.013897) Loss: 0.43554 (0.49335) +2025-09-13,12:00:58 | INFO | Train Epoch: 6 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.44745 (0.47932) Boundary_loss: 0.013896 (0.013897) Loss: 0.46134 (0.49322) +2025-09-13,12:01:29 | INFO | Train Epoch: 6 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.55940 (0.47965) Boundary_loss: 0.013896 (0.013897) Loss: 0.57330 (0.49355) +2025-09-13,12:02:00 | INFO | Train Epoch: 6 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.50177 (0.47974) Boundary_loss: 0.013894 (0.013897) Loss: 0.51566 (0.49364) +2025-09-13,12:02:31 | INFO | Train Epoch: 6 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.45464 (0.47964) Boundary_loss: 0.013897 (0.013897) Loss: 0.46854 (0.49354) +2025-09-13,12:03:01 | INFO | Train Epoch: 6 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.49280 (0.47969) Boundary_loss: 0.013898 (0.013897) Loss: 0.50670 (0.49359) +2025-09-13,12:03:32 | INFO | Train Epoch: 6 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.41668 (0.47944) Boundary_loss: 0.013896 (0.013897) Loss: 0.43058 (0.49334) +2025-09-13,12:04:03 | INFO | Train Epoch: 6 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38099 (0.47904) Boundary_loss: 0.013895 (0.013897) Loss: 0.39488 (0.49294) +2025-09-13,12:04:34 | INFO | Train Epoch: 6 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.45704 (0.47896) Boundary_loss: 0.013897 (0.013897) Loss: 0.47093 (0.49285) +2025-09-13,12:05:05 | INFO | Train Epoch: 6 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.41207 (0.47869) Boundary_loss: 0.013896 (0.013897) Loss: 0.42597 (0.49259) +2025-09-13,12:05:35 | INFO | Train Epoch: 6 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.43245 (0.47851) Boundary_loss: 0.013899 (0.013897) Loss: 0.44635 (0.49241) +2025-09-13,12:06:06 | INFO | Train Epoch: 6 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.42713 (0.47831) Boundary_loss: 0.013896 (0.013897) Loss: 0.44103 (0.49220) +2025-09-13,12:06:37 | INFO | Train Epoch: 6 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.39484 (0.47798) Boundary_loss: 0.013897 (0.013897) Loss: 0.40873 (0.49188) +2025-09-13,12:07:08 | INFO | Train Epoch: 6 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.53538 (0.47820) Boundary_loss: 0.013897 (0.013897) Loss: 0.54928 (0.49210) +2025-09-13,12:07:39 | INFO | Train Epoch: 6 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.44843 (0.47809) Boundary_loss: 0.013896 (0.013897) Loss: 0.46232 (0.49198) +2025-09-13,12:08:10 | INFO | Train Epoch: 6 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.47513 (0.47808) Boundary_loss: 0.013898 (0.013897) Loss: 0.48903 (0.49197) +2025-09-13,12:08:41 | INFO | Train Epoch: 6 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.46845 (0.47804) Boundary_loss: 0.013898 (0.013897) Loss: 0.48235 (0.49194) +2025-09-13,12:09:11 | INFO | Train Epoch: 6 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.46068 (0.47797) Boundary_loss: 0.013897 (0.013897) Loss: 0.47458 (0.49187) +2025-09-13,12:09:42 | INFO | Train Epoch: 6 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.52438 (0.47815) Boundary_loss: 0.013899 (0.013897) Loss: 0.53827 (0.49205) +2025-09-13,12:10:13 | INFO | Train Epoch: 6 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44039 (0.47801) Boundary_loss: 0.013896 (0.013897) Loss: 0.45428 (0.49190) +2025-09-13,12:10:44 | INFO | Train Epoch: 6 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.46252 (0.47795) Boundary_loss: 0.013896 (0.013897) Loss: 0.47641 (0.49184) +2025-09-13,12:11:14 | INFO | Train Epoch: 6 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.49243 (0.47800) Boundary_loss: 0.013898 (0.013897) Loss: 0.50633 (0.49190) +2025-09-13,12:11:45 | INFO | Train Epoch: 6 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.46143 (0.47794) Boundary_loss: 0.013897 (0.013897) Loss: 0.47532 (0.49184) +2025-09-13,12:12:16 | INFO | Train Epoch: 6 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.46980 (0.47791) Boundary_loss: 0.013895 (0.013897) Loss: 0.48370 (0.49181) +2025-09-13,12:12:47 | INFO | Train Epoch: 6 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40645 (0.47764) Boundary_loss: 0.013896 (0.013897) Loss: 0.42035 (0.49154) +2025-09-13,12:13:18 | INFO | Train Epoch: 6 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.43017 (0.47746) Boundary_loss: 0.013896 (0.013897) Loss: 0.44407 (0.49136) +2025-09-13,12:13:48 | INFO | Train Epoch: 6 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.45496 (0.47738) Boundary_loss: 0.013897 (0.013897) Loss: 0.46886 (0.49128) +2025-09-13,12:14:19 | INFO | Train Epoch: 6 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.42737 (0.47719) Boundary_loss: 0.013896 (0.013897) Loss: 0.44127 (0.49109) +2025-09-13,12:14:50 | INFO | Train Epoch: 6 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.45344 (0.47711) Boundary_loss: 0.013896 (0.013897) Loss: 0.46734 (0.49100) +2025-09-13,12:15:21 | INFO | Train Epoch: 6 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.49294 (0.47716) Boundary_loss: 0.013897 (0.013897) Loss: 0.50684 (0.49106) +2025-09-13,12:15:52 | INFO | Train Epoch: 6 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.41560 (0.47694) Boundary_loss: 0.013897 (0.013897) Loss: 0.42949 (0.49084) +2025-09-13,12:16:23 | INFO | Train Epoch: 6 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.49995 (0.47702) Boundary_loss: 0.013896 (0.013897) Loss: 0.51384 (0.49092) +2025-09-13,12:16:54 | INFO | Train Epoch: 6 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.52062 (0.47718) Boundary_loss: 0.013897 (0.013897) Loss: 0.53452 (0.49108) +2025-09-13,12:17:25 | INFO | Train Epoch: 6 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.52947 (0.47737) Boundary_loss: 0.013896 (0.013897) Loss: 0.54337 (0.49127) +2025-09-13,12:17:56 | INFO | Train Epoch: 6 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.46798 (0.47734) Boundary_loss: 0.013895 (0.013897) Loss: 0.48187 (0.49123) +2025-09-13,12:18:27 | INFO | Train Epoch: 6 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.58834 (0.47774) Boundary_loss: 0.013896 (0.013897) Loss: 0.60224 (0.49163) +2025-09-13,12:18:58 | INFO | Train Epoch: 6 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.46678 (0.47770) Boundary_loss: 0.013897 (0.013897) Loss: 0.48068 (0.49159) +2025-09-13,12:19:29 | INFO | Train Epoch: 6 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.49851 (0.47777) Boundary_loss: 0.013899 (0.013897) Loss: 0.51241 (0.49167) +2025-09-13,12:19:59 | INFO | Train Epoch: 6 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.55461 (0.47805) Boundary_loss: 0.013899 (0.013897) Loss: 0.56851 (0.49194) +2025-09-13,12:20:30 | INFO | Train Epoch: 6 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.50370 (0.47814) Boundary_loss: 0.013896 (0.013897) Loss: 0.51759 (0.49203) +2025-09-13,12:21:01 | INFO | Train Epoch: 6 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.35203 (0.47769) Boundary_loss: 0.013897 (0.013897) Loss: 0.36592 (0.49159) +2025-09-13,12:21:32 | INFO | Train Epoch: 6 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.43715 (0.47755) Boundary_loss: 0.013896 (0.013897) Loss: 0.45105 (0.49145) +2025-09-13,12:22:03 | INFO | Train Epoch: 6 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.43818 (0.47741) Boundary_loss: 0.013895 (0.013897) Loss: 0.45208 (0.49131) +2025-09-13,12:22:34 | INFO | Train Epoch: 6 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.47568 (0.47740) Boundary_loss: 0.013896 (0.013897) Loss: 0.48958 (0.49130) +2025-09-13,12:23:04 | INFO | Train Epoch: 6 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.44458 (0.47729) Boundary_loss: 0.013899 (0.013897) Loss: 0.45848 (0.49119) +2025-09-13,12:23:35 | INFO | Train Epoch: 6 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.43414 (0.47714) Boundary_loss: 0.013901 (0.013897) Loss: 0.44804 (0.49104) +2025-09-13,12:24:06 | INFO | Train Epoch: 6 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.45878 (0.47708) Boundary_loss: 0.013896 (0.013897) Loss: 0.47267 (0.49097) +2025-09-13,12:24:37 | INFO | Train Epoch: 6 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.39586 (0.47680) Boundary_loss: 0.013897 (0.013897) Loss: 0.40976 (0.49069) +2025-09-13,12:25:07 | INFO | Train Epoch: 6 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.53149 (0.47698) Boundary_loss: 0.013896 (0.013897) Loss: 0.54539 (0.49088) +2025-09-13,12:25:38 | INFO | Train Epoch: 6 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.40535 (0.47674) Boundary_loss: 0.013897 (0.013897) Loss: 0.41925 (0.49064) +2025-09-13,12:26:09 | INFO | Train Epoch: 6 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.42629 (0.47657) Boundary_loss: 0.013897 (0.013897) Loss: 0.44019 (0.49046) +2025-09-13,12:26:39 | INFO | Train Epoch: 6 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.49678 (0.47664) Boundary_loss: 0.013899 (0.013897) Loss: 0.51067 (0.49053) +2025-09-13,12:27:10 | INFO | Train Epoch: 6 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.47297 (0.47662) Boundary_loss: 0.013896 (0.013897) Loss: 0.48687 (0.49052) +2025-09-13,12:27:41 | INFO | Train Epoch: 6 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.43577 (0.47648) Boundary_loss: 0.013897 (0.013897) Loss: 0.44967 (0.49038) +2025-09-13,12:28:12 | INFO | Train Epoch: 6 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.43007 (0.47633) Boundary_loss: 0.013897 (0.013897) Loss: 0.44396 (0.49023) +2025-09-13,12:28:43 | INFO | Train Epoch: 6 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.43559 (0.47619) Boundary_loss: 0.013896 (0.013897) Loss: 0.44949 (0.49009) +2025-09-13,12:29:14 | INFO | Train Epoch: 6 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.41302 (0.47598) Boundary_loss: 0.013897 (0.013897) Loss: 0.42691 (0.48988) +2025-09-13,12:29:45 | INFO | Train Epoch: 6 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.51642 (0.47612) Boundary_loss: 0.013899 (0.013897) Loss: 0.53032 (0.49001) +2025-09-13,12:30:16 | INFO | Train Epoch: 6 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.54193 (0.47633) Boundary_loss: 0.013896 (0.013897) Loss: 0.55583 (0.49023) +2025-09-13,12:30:47 | INFO | Train Epoch: 6 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.34492 (0.47590) Boundary_loss: 0.013896 (0.013897) Loss: 0.35881 (0.48980) +2025-09-13,12:31:18 | INFO | Train Epoch: 6 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.46792 (0.47587) Boundary_loss: 0.013898 (0.013897) Loss: 0.48182 (0.48977) +2025-09-13,12:31:49 | INFO | Train Epoch: 6 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.47701 (0.47588) Boundary_loss: 0.013895 (0.013897) Loss: 0.49090 (0.48977) +2025-09-13,12:32:20 | INFO | Train Epoch: 6 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.45228 (0.47580) Boundary_loss: 0.013897 (0.013897) Loss: 0.46617 (0.48970) +2025-09-13,12:32:51 | INFO | Train Epoch: 6 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.49116 (0.47585) Boundary_loss: 0.013896 (0.013897) Loss: 0.50505 (0.48975) +2025-09-13,12:33:22 | INFO | Train Epoch: 6 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.39577 (0.47559) Boundary_loss: 0.013896 (0.013897) Loss: 0.40967 (0.48949) +2025-09-13,12:33:53 | INFO | Train Epoch: 6 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.41741 (0.47540) Boundary_loss: 0.013897 (0.013897) Loss: 0.43131 (0.48930) +2025-09-13,12:34:24 | INFO | Train Epoch: 6 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.42673 (0.47524) Boundary_loss: 0.013902 (0.013897) Loss: 0.44063 (0.48914) +2025-09-13,12:34:55 | INFO | Train Epoch: 6 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.50468 (0.47534) Boundary_loss: 0.013899 (0.013897) Loss: 0.51858 (0.48923) +2025-09-13,12:35:26 | INFO | Train Epoch: 6 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.47556 (0.47534) Boundary_loss: 0.013897 (0.013897) Loss: 0.48946 (0.48923) +2025-09-13,12:35:57 | INFO | Train Epoch: 6 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.43955 (0.47522) Boundary_loss: 0.013900 (0.013897) Loss: 0.45344 (0.48912) +2025-09-13,12:36:28 | INFO | Train Epoch: 6 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.51437 (0.47535) Boundary_loss: 0.013896 (0.013897) Loss: 0.52827 (0.48925) +2025-09-13,12:36:59 | INFO | Train Epoch: 6 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.47906 (0.47536) Boundary_loss: 0.013899 (0.013897) Loss: 0.49296 (0.48926) +2025-09-13,12:37:30 | INFO | Train Epoch: 6 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.48387 (0.47539) Boundary_loss: 0.013899 (0.013897) Loss: 0.49777 (0.48928) +2025-09-13,12:38:01 | INFO | Train Epoch: 6 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.43736 (0.47527) Boundary_loss: 0.013897 (0.013897) Loss: 0.45125 (0.48916) +2025-09-13,12:38:31 | INFO | Train Epoch: 6 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.50163 (0.47535) Boundary_loss: 0.013895 (0.013897) Loss: 0.51552 (0.48925) +2025-09-13,12:39:03 | INFO | Train Epoch: 6 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.42511 (0.47519) Boundary_loss: 0.013897 (0.013897) Loss: 0.43901 (0.48909) +2025-09-13,12:39:34 | INFO | Train Epoch: 6 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.42774 (0.47504) Boundary_loss: 0.013896 (0.013897) Loss: 0.44164 (0.48894) +2025-09-13,12:40:05 | INFO | Train Epoch: 6 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.43484 (0.47492) Boundary_loss: 0.013899 (0.013897) Loss: 0.44874 (0.48881) +2025-09-13,12:40:36 | INFO | Train Epoch: 6 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.42957 (0.47478) Boundary_loss: 0.013898 (0.013897) Loss: 0.44346 (0.48867) +2025-09-13,12:41:07 | INFO | Train Epoch: 6 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.45175 (0.47470) Boundary_loss: 0.013895 (0.013897) Loss: 0.46565 (0.48860) +2025-09-13,12:41:38 | INFO | Train Epoch: 6 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.56881 (0.47500) Boundary_loss: 0.013897 (0.013897) Loss: 0.58271 (0.48889) +2025-09-13,12:42:09 | INFO | Train Epoch: 6 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.33794 (0.47457) Boundary_loss: 0.013897 (0.013897) Loss: 0.35183 (0.48847) +2025-09-13,12:42:40 | INFO | Train Epoch: 6 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.45840 (0.47452) Boundary_loss: 0.013899 (0.013897) Loss: 0.47229 (0.48842) +2025-09-13,12:43:11 | INFO | Train Epoch: 6 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.42508 (0.47437) Boundary_loss: 0.013895 (0.013897) Loss: 0.43897 (0.48827) +2025-09-13,12:43:41 | INFO | Train Epoch: 6 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.50454 (0.47446) Boundary_loss: 0.013896 (0.013897) Loss: 0.51843 (0.48836) +2025-09-13,12:44:12 | INFO | Train Epoch: 6 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.44667 (0.47438) Boundary_loss: 0.013898 (0.013897) Loss: 0.46057 (0.48828) +2025-09-13,12:44:43 | INFO | Train Epoch: 6 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.39221 (0.47413) Boundary_loss: 0.013896 (0.013897) Loss: 0.40611 (0.48803) +2025-09-13,12:45:14 | INFO | Train Epoch: 6 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.43634 (0.47401) Boundary_loss: 0.013897 (0.013897) Loss: 0.45023 (0.48791) +2025-09-13,12:45:45 | INFO | Train Epoch: 6 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.49758 (0.47409) Boundary_loss: 0.013896 (0.013897) Loss: 0.51147 (0.48798) +2025-09-13,12:46:15 | INFO | Train Epoch: 6 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.39418 (0.47384) Boundary_loss: 0.013896 (0.013897) Loss: 0.40807 (0.48774) +2025-09-13,12:46:46 | INFO | Train Epoch: 6 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.49232 (0.47390) Boundary_loss: 0.013898 (0.013897) Loss: 0.50622 (0.48780) +2025-09-13,12:47:17 | INFO | Train Epoch: 6 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.49278 (0.47396) Boundary_loss: 0.013900 (0.013897) Loss: 0.50668 (0.48785) +2025-09-13,12:47:48 | INFO | Train Epoch: 6 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.49421 (0.47402) Boundary_loss: 0.013897 (0.013897) Loss: 0.50811 (0.48791) +2025-09-13,12:48:19 | INFO | Train Epoch: 6 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.42484 (0.47387) Boundary_loss: 0.013901 (0.013897) Loss: 0.43874 (0.48777) +2025-09-13,12:48:50 | INFO | Train Epoch: 6 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.45116 (0.47380) Boundary_loss: 0.013896 (0.013897) Loss: 0.46505 (0.48770) +2025-09-13,12:49:22 | INFO | Train Epoch: 6 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.43268 (0.47368) Boundary_loss: 0.013895 (0.013897) Loss: 0.44658 (0.48758) +2025-09-13,12:49:52 | INFO | Train Epoch: 6 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.37183 (0.47338) Boundary_loss: 0.013896 (0.013897) Loss: 0.38572 (0.48728) +2025-09-13,12:50:23 | INFO | Train Epoch: 6 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.48067 (0.47340) Boundary_loss: 0.013896 (0.013897) Loss: 0.49456 (0.48730) +2025-09-13,12:50:54 | INFO | Train Epoch: 6 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.46492 (0.47338) Boundary_loss: 0.013895 (0.013897) Loss: 0.47881 (0.48728) +2025-09-13,12:51:26 | INFO | Train Epoch: 6 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.53982 (0.47357) Boundary_loss: 0.013896 (0.013897) Loss: 0.55372 (0.48747) +2025-09-13,12:51:57 | INFO | Train Epoch: 6 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.35715 (0.47323) Boundary_loss: 0.013896 (0.013897) Loss: 0.37104 (0.48713) +2025-09-13,12:52:28 | INFO | Train Epoch: 6 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.38484 (0.47298) Boundary_loss: 0.013897 (0.013897) Loss: 0.39874 (0.48687) +2025-09-13,12:52:59 | INFO | Train Epoch: 6 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.39697 (0.47276) Boundary_loss: 0.013897 (0.013897) Loss: 0.41087 (0.48665) +2025-09-13,12:53:30 | INFO | Train Epoch: 6 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.55450 (0.47299) Boundary_loss: 0.013900 (0.013897) Loss: 0.56840 (0.48689) +2025-09-13,12:54:01 | INFO | Train Epoch: 6 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.54089 (0.47319) Boundary_loss: 0.013897 (0.013897) Loss: 0.55479 (0.48708) +2025-09-13,12:54:32 | INFO | Train Epoch: 6 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.47590 (0.47320) Boundary_loss: 0.013898 (0.013897) Loss: 0.48980 (0.48709) +2025-09-13,12:55:03 | INFO | Train Epoch: 6 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.49381 (0.47325) Boundary_loss: 0.013896 (0.013897) Loss: 0.50771 (0.48715) +2025-09-13,12:55:34 | INFO | Train Epoch: 6 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.49732 (0.47332) Boundary_loss: 0.013896 (0.013897) Loss: 0.51122 (0.48722) +2025-09-13,12:56:05 | INFO | Train Epoch: 6 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.50901 (0.47342) Boundary_loss: 0.013897 (0.013897) Loss: 0.52290 (0.48732) +2025-09-13,12:56:36 | INFO | Train Epoch: 6 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.52312 (0.47357) Boundary_loss: 0.013896 (0.013897) Loss: 0.53701 (0.48746) +2025-09-13,12:57:07 | INFO | Train Epoch: 6 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.46037 (0.47353) Boundary_loss: 0.013898 (0.013897) Loss: 0.47427 (0.48743) +2025-09-13,12:57:38 | INFO | Train Epoch: 6 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44843 (0.47346) Boundary_loss: 0.013896 (0.013897) Loss: 0.46233 (0.48735) +2025-09-13,12:58:08 | INFO | Train Epoch: 6 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.45631 (0.47341) Boundary_loss: 0.013899 (0.013897) Loss: 0.47021 (0.48731) +2025-09-13,12:58:39 | INFO | Train Epoch: 6 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.48932 (0.47345) Boundary_loss: 0.013895 (0.013897) Loss: 0.50321 (0.48735) +2025-09-13,12:59:10 | INFO | Train Epoch: 6 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.44155 (0.47336) Boundary_loss: 0.013896 (0.013897) Loss: 0.45544 (0.48726) +2025-09-13,12:59:41 | INFO | Train Epoch: 6 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.44619 (0.47329) Boundary_loss: 0.013901 (0.013897) Loss: 0.46009 (0.48719) +2025-09-13,13:00:12 | INFO | Train Epoch: 6 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.43753 (0.47319) Boundary_loss: 0.013896 (0.013897) Loss: 0.45142 (0.48709) +2025-09-13,13:00:42 | INFO | Train Epoch: 6 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.46869 (0.47318) Boundary_loss: 0.013895 (0.013897) Loss: 0.48259 (0.48707) +2025-09-13,13:01:13 | INFO | Train Epoch: 6 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.52003 (0.47331) Boundary_loss: 0.013895 (0.013897) Loss: 0.53392 (0.48720) +2025-09-13,13:01:44 | INFO | Train Epoch: 6 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.44236 (0.47322) Boundary_loss: 0.013897 (0.013897) Loss: 0.45625 (0.48712) +2025-09-13,13:02:15 | INFO | Train Epoch: 6 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.44533 (0.47314) Boundary_loss: 0.013897 (0.013897) Loss: 0.45923 (0.48704) +2025-09-13,13:02:46 | INFO | Train Epoch: 6 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.48788 (0.47318) Boundary_loss: 0.013897 (0.013897) Loss: 0.50177 (0.48708) +2025-09-13,13:03:17 | INFO | Train Epoch: 6 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.34595 (0.47284) Boundary_loss: 0.013895 (0.013897) Loss: 0.35984 (0.48673) +2025-09-13,13:03:47 | INFO | Train Epoch: 6 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.40936 (0.47266) Boundary_loss: 0.013895 (0.013897) Loss: 0.42326 (0.48656) +2025-09-13,13:04:18 | INFO | Train Epoch: 6 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.46008 (0.47263) Boundary_loss: 0.013896 (0.013897) Loss: 0.47398 (0.48653) +2025-09-13,13:04:49 | INFO | Train Epoch: 6 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.48618 (0.47267) Boundary_loss: 0.013896 (0.013897) Loss: 0.50007 (0.48656) +2025-09-13,13:05:20 | INFO | Train Epoch: 6 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.51270 (0.47277) Boundary_loss: 0.013896 (0.013897) Loss: 0.52660 (0.48667) +2025-09-13,13:05:51 | INFO | Train Epoch: 6 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44192 (0.47269) Boundary_loss: 0.013896 (0.013897) Loss: 0.45582 (0.48659) +2025-09-13,13:06:21 | INFO | Train Epoch: 6 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.48053 (0.47271) Boundary_loss: 0.013900 (0.013897) Loss: 0.49443 (0.48661) +2025-09-13,13:06:52 | INFO | Train Epoch: 6 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.46403 (0.47269) Boundary_loss: 0.013896 (0.013897) Loss: 0.47793 (0.48659) +2025-09-13,13:07:23 | INFO | Train Epoch: 6 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.47046 (0.47268) Boundary_loss: 0.013896 (0.013897) Loss: 0.48435 (0.48658) +2025-09-13,13:07:54 | INFO | Train Epoch: 6 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.51778 (0.47280) Boundary_loss: 0.013895 (0.013897) Loss: 0.53168 (0.48670) +2025-09-13,13:08:25 | INFO | Train Epoch: 6 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.47600 (0.47281) Boundary_loss: 0.013898 (0.013897) Loss: 0.48990 (0.48671) +2025-09-13,13:08:55 | INFO | Train Epoch: 6 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.40529 (0.47263) Boundary_loss: 0.013896 (0.013897) Loss: 0.41919 (0.48653) +2025-09-13,13:09:26 | INFO | Train Epoch: 6 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.49555 (0.47269) Boundary_loss: 0.013896 (0.013897) Loss: 0.50945 (0.48659) +2025-09-13,13:09:57 | INFO | Train Epoch: 6 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.45752 (0.47265) Boundary_loss: 0.013896 (0.013897) Loss: 0.47142 (0.48655) +2025-09-13,13:10:28 | INFO | Train Epoch: 6 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.39007 (0.47243) Boundary_loss: 0.013896 (0.013897) Loss: 0.40397 (0.48633) +2025-09-13,13:10:59 | INFO | Train Epoch: 6 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.42801 (0.47232) Boundary_loss: 0.013896 (0.013897) Loss: 0.44190 (0.48621) +2025-09-13,13:11:29 | INFO | Train Epoch: 6 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42346 (0.47219) Boundary_loss: 0.013896 (0.013897) Loss: 0.43735 (0.48609) +2025-09-13,13:12:00 | INFO | Train Epoch: 6 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.51974 (0.47231) Boundary_loss: 0.013897 (0.013897) Loss: 0.53364 (0.48621) +2025-09-13,13:12:31 | INFO | Train Epoch: 6 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.45799 (0.47228) Boundary_loss: 0.013902 (0.013897) Loss: 0.47189 (0.48617) +2025-09-13,13:13:02 | INFO | Train Epoch: 6 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.43014 (0.47217) Boundary_loss: 0.013897 (0.013897) Loss: 0.44404 (0.48606) +2025-09-13,13:13:33 | INFO | Train Epoch: 6 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.41509 (0.47202) Boundary_loss: 0.013895 (0.013897) Loss: 0.42899 (0.48592) +2025-09-13,13:14:03 | INFO | Train Epoch: 6 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.44858 (0.47196) Boundary_loss: 0.013895 (0.013897) Loss: 0.46248 (0.48585) +2025-09-13,13:14:34 | INFO | Train Epoch: 6 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.46789 (0.47195) Boundary_loss: 0.013898 (0.013897) Loss: 0.48179 (0.48584) +2025-09-13,13:15:05 | INFO | Train Epoch: 6 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.43886 (0.47186) Boundary_loss: 0.013897 (0.013897) Loss: 0.45275 (0.48576) +2025-09-13,13:15:36 | INFO | Train Epoch: 6 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.51006 (0.47196) Boundary_loss: 0.013895 (0.013897) Loss: 0.52396 (0.48586) +2025-09-13,13:16:06 | INFO | Train Epoch: 6 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.46723 (0.47195) Boundary_loss: 0.013897 (0.013897) Loss: 0.48112 (0.48585) +2025-09-13,13:16:37 | INFO | Train Epoch: 6 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.54641 (0.47214) Boundary_loss: 0.013897 (0.013897) Loss: 0.56030 (0.48604) +2025-09-13,13:17:08 | INFO | Train Epoch: 6 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.43754 (0.47205) Boundary_loss: 0.013896 (0.013897) Loss: 0.45144 (0.48595) +2025-09-13,13:17:39 | INFO | Train Epoch: 6 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.50132 (0.47212) Boundary_loss: 0.013897 (0.013897) Loss: 0.51522 (0.48602) +2025-09-13,13:18:10 | INFO | Train Epoch: 6 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.43606 (0.47203) Boundary_loss: 0.013897 (0.013897) Loss: 0.44995 (0.48593) +2025-09-13,13:18:40 | INFO | Train Epoch: 6 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.54216 (0.47221) Boundary_loss: 0.013897 (0.013897) Loss: 0.55605 (0.48611) +2025-09-13,13:19:11 | INFO | Train Epoch: 6 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.41592 (0.47207) Boundary_loss: 0.013895 (0.013897) Loss: 0.42981 (0.48597) +2025-09-13,13:19:42 | INFO | Train Epoch: 6 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.51626 (0.47218) Boundary_loss: 0.013896 (0.013897) Loss: 0.53015 (0.48608) +2025-09-13,13:20:13 | INFO | Train Epoch: 6 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.45027 (0.47212) Boundary_loss: 0.013899 (0.013897) Loss: 0.46417 (0.48602) +2025-09-13,13:20:44 | INFO | Train Epoch: 6 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.45173 (0.47207) Boundary_loss: 0.013898 (0.013897) Loss: 0.46562 (0.48597) +2025-09-13,13:21:14 | INFO | Train Epoch: 6 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.52586 (0.47221) Boundary_loss: 0.013897 (0.013897) Loss: 0.53976 (0.48611) +2025-09-13,13:21:45 | INFO | Train Epoch: 6 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.37897 (0.47198) Boundary_loss: 0.013896 (0.013897) Loss: 0.39286 (0.48587) +2025-09-13,13:22:16 | INFO | Train Epoch: 6 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40977 (0.47182) Boundary_loss: 0.013897 (0.013897) Loss: 0.42366 (0.48572) +2025-09-13,13:22:47 | INFO | Train Epoch: 6 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.38976 (0.47162) Boundary_loss: 0.013895 (0.013897) Loss: 0.40365 (0.48551) +2025-09-13,13:23:18 | INFO | Train Epoch: 6 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.54940 (0.47181) Boundary_loss: 0.013897 (0.013897) Loss: 0.56330 (0.48571) +2025-09-13,13:23:48 | INFO | Train Epoch: 6 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.41864 (0.47168) Boundary_loss: 0.013897 (0.013897) Loss: 0.43254 (0.48558) +2025-09-13,13:24:19 | INFO | Train Epoch: 6 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.47603 (0.47169) Boundary_loss: 0.013900 (0.013897) Loss: 0.48993 (0.48559) +2025-09-13,13:24:50 | INFO | Train Epoch: 6 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.42721 (0.47158) Boundary_loss: 0.013895 (0.013897) Loss: 0.44110 (0.48548) +2025-09-13,13:25:21 | INFO | Train Epoch: 6 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.46308 (0.47156) Boundary_loss: 0.013896 (0.013897) Loss: 0.47697 (0.48546) +2025-09-13,13:25:52 | INFO | Train Epoch: 6 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.42128 (0.47144) Boundary_loss: 0.013896 (0.013897) Loss: 0.43517 (0.48533) +2025-09-13,13:26:23 | INFO | Train Epoch: 6 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.45511 (0.47140) Boundary_loss: 0.013895 (0.013897) Loss: 0.46901 (0.48529) +2025-09-13,13:26:54 | INFO | Train Epoch: 6 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.57902 (0.47166) Boundary_loss: 0.013895 (0.013897) Loss: 0.59292 (0.48556) +2025-09-13,13:27:25 | INFO | Train Epoch: 6 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.44959 (0.47160) Boundary_loss: 0.013896 (0.013897) Loss: 0.46348 (0.48550) +2025-09-13,13:27:56 | INFO | Train Epoch: 6 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.54535 (0.47178) Boundary_loss: 0.013895 (0.013897) Loss: 0.55925 (0.48568) +2025-09-13,13:28:27 | INFO | Train Epoch: 6 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46507 (0.47177) Boundary_loss: 0.013895 (0.013897) Loss: 0.47896 (0.48566) +2025-09-13,13:28:58 | INFO | Train Epoch: 6 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.48058 (0.47179) Boundary_loss: 0.013899 (0.013897) Loss: 0.49448 (0.48569) +2025-09-13,13:29:29 | INFO | Train Epoch: 6 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.50489 (0.47187) Boundary_loss: 0.013896 (0.013897) Loss: 0.51879 (0.48576) +2025-09-13,13:29:59 | INFO | Train Epoch: 6 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.54283 (0.47204) Boundary_loss: 0.013895 (0.013897) Loss: 0.55672 (0.48593) +2025-09-13,13:30:31 | INFO | Train Epoch: 6 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.42956 (0.47194) Boundary_loss: 0.013895 (0.013897) Loss: 0.44346 (0.48583) +2025-09-13,13:31:01 | INFO | Train Epoch: 6 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.39334 (0.47175) Boundary_loss: 0.013899 (0.013897) Loss: 0.40724 (0.48565) +2025-09-13,13:31:32 | INFO | Train Epoch: 6 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.44014 (0.47167) Boundary_loss: 0.013895 (0.013897) Loss: 0.45404 (0.48557) +2025-09-13,13:32:03 | INFO | Train Epoch: 6 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.48367 (0.47170) Boundary_loss: 0.013896 (0.013897) Loss: 0.49756 (0.48560) +2025-09-13,13:32:34 | INFO | Train Epoch: 6 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42399 (0.47159) Boundary_loss: 0.013896 (0.013897) Loss: 0.43789 (0.48549) +2025-09-13,13:33:05 | INFO | Train Epoch: 6 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.39102 (0.47140) Boundary_loss: 0.013900 (0.013897) Loss: 0.40492 (0.48530) +2025-09-13,13:33:36 | INFO | Train Epoch: 6 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.49471 (0.47145) Boundary_loss: 0.013898 (0.013897) Loss: 0.50861 (0.48535) +2025-09-13,13:34:07 | INFO | Train Epoch: 6 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.47686 (0.47147) Boundary_loss: 0.013899 (0.013897) Loss: 0.49076 (0.48536) +2025-09-13,13:34:38 | INFO | Train Epoch: 6 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.46260 (0.47145) Boundary_loss: 0.013896 (0.013897) Loss: 0.47650 (0.48534) +2025-09-13,13:35:08 | INFO | Train Epoch: 6 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.38848 (0.47125) Boundary_loss: 0.013900 (0.013897) Loss: 0.40238 (0.48515) +2025-09-13,13:35:39 | INFO | Train Epoch: 6 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.52301 (0.47137) Boundary_loss: 0.013898 (0.013897) Loss: 0.53691 (0.48527) +2025-09-13,13:36:10 | INFO | Train Epoch: 6 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.42348 (0.47126) Boundary_loss: 0.013898 (0.013897) Loss: 0.43738 (0.48516) +2025-09-13,13:36:41 | INFO | Train Epoch: 6 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.45210 (0.47122) Boundary_loss: 0.013900 (0.013897) Loss: 0.46600 (0.48511) +2025-09-13,13:37:12 | INFO | Train Epoch: 6 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.40337 (0.47106) Boundary_loss: 0.013899 (0.013897) Loss: 0.41727 (0.48496) +2025-09-13,13:37:43 | INFO | Train Epoch: 6 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.56389 (0.47127) Boundary_loss: 0.013896 (0.013897) Loss: 0.57779 (0.48517) +2025-09-13,13:38:14 | INFO | Train Epoch: 6 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.45675 (0.47124) Boundary_loss: 0.013895 (0.013897) Loss: 0.47064 (0.48514) +2025-09-13,13:38:45 | INFO | Train Epoch: 6 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.44288 (0.47117) Boundary_loss: 0.013899 (0.013897) Loss: 0.45678 (0.48507) +2025-09-13,13:39:16 | INFO | Train Epoch: 6 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.51953 (0.47129) Boundary_loss: 0.013897 (0.013897) Loss: 0.53343 (0.48518) +2025-09-13,13:39:47 | INFO | Train Epoch: 6 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.44208 (0.47122) Boundary_loss: 0.013898 (0.013897) Loss: 0.45598 (0.48512) +2025-09-13,13:40:18 | INFO | Train Epoch: 6 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44001 (0.47115) Boundary_loss: 0.013897 (0.013897) Loss: 0.45390 (0.48504) +2025-09-13,13:40:48 | INFO | Train Epoch: 6 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.44699 (0.47109) Boundary_loss: 0.013898 (0.013897) Loss: 0.46089 (0.48499) +2025-09-13,13:41:19 | INFO | Train Epoch: 6 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.46550 (0.47108) Boundary_loss: 0.013899 (0.013897) Loss: 0.47940 (0.48498) +2025-09-13,13:41:50 | INFO | Train Epoch: 6 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.55733 (0.47128) Boundary_loss: 0.013897 (0.013897) Loss: 0.57123 (0.48517) +2025-09-13,13:42:21 | INFO | Train Epoch: 6 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.46067 (0.47125) Boundary_loss: 0.013896 (0.013897) Loss: 0.47457 (0.48515) +2025-09-13,13:42:52 | INFO | Train Epoch: 6 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.54809 (0.47142) Boundary_loss: 0.013897 (0.013897) Loss: 0.56199 (0.48532) +2025-09-13,13:43:23 | INFO | Train Epoch: 6 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.47080 (0.47142) Boundary_loss: 0.013897 (0.013897) Loss: 0.48469 (0.48532) +2025-09-13,13:43:54 | INFO | Train Epoch: 6 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.49739 (0.47148) Boundary_loss: 0.013895 (0.013897) Loss: 0.51128 (0.48538) +2025-09-13,13:44:25 | INFO | Train Epoch: 6 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.41797 (0.47136) Boundary_loss: 0.013897 (0.013897) Loss: 0.43186 (0.48526) +2025-09-13,13:44:56 | INFO | Train Epoch: 6 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.43238 (0.47127) Boundary_loss: 0.013897 (0.013897) Loss: 0.44628 (0.48517) +2025-09-13,13:45:27 | INFO | Train Epoch: 6 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.54686 (0.47144) Boundary_loss: 0.013896 (0.013897) Loss: 0.56075 (0.48534) +2025-09-13,13:45:58 | INFO | Train Epoch: 6 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.38550 (0.47125) Boundary_loss: 0.013898 (0.013897) Loss: 0.39940 (0.48515) +2025-09-13,13:46:29 | INFO | Train Epoch: 6 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.47254 (0.47125) Boundary_loss: 0.013897 (0.013897) Loss: 0.48644 (0.48515) +2025-09-13,13:47:00 | INFO | Train Epoch: 6 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.39125 (0.47108) Boundary_loss: 0.013896 (0.013897) Loss: 0.40514 (0.48497) +2025-09-13,13:47:31 | INFO | Train Epoch: 6 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.47234 (0.47108) Boundary_loss: 0.013899 (0.013897) Loss: 0.48623 (0.48498) +2025-09-13,13:48:02 | INFO | Train Epoch: 6 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.53206 (0.47121) Boundary_loss: 0.013897 (0.013897) Loss: 0.54596 (0.48511) +2025-09-13,13:48:33 | INFO | Train Epoch: 6 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.43508 (0.47113) Boundary_loss: 0.013896 (0.013897) Loss: 0.44897 (0.48503) +2025-09-13,13:49:04 | INFO | Train Epoch: 6 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.53944 (0.47129) Boundary_loss: 0.013897 (0.013897) Loss: 0.55333 (0.48518) +2025-09-13,13:49:34 | INFO | Train Epoch: 6 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.49049 (0.47133) Boundary_loss: 0.013895 (0.013897) Loss: 0.50438 (0.48522) +2025-09-13,13:50:05 | INFO | Train Epoch: 6 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.35604 (0.47107) Boundary_loss: 0.013897 (0.013897) Loss: 0.36993 (0.48497) +2025-09-13,13:50:36 | INFO | Train Epoch: 6 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.39592 (0.47091) Boundary_loss: 0.013897 (0.013897) Loss: 0.40982 (0.48481) +2025-09-13,13:51:07 | INFO | Train Epoch: 6 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.40173 (0.47076) Boundary_loss: 0.013895 (0.013897) Loss: 0.41562 (0.48466) +2025-09-13,13:51:37 | INFO | Train Epoch: 6 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.50089 (0.47082) Boundary_loss: 0.013896 (0.013897) Loss: 0.51478 (0.48472) +2025-09-13,13:52:09 | INFO | Train Epoch: 6 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.51803 (0.47093) Boundary_loss: 0.013897 (0.013897) Loss: 0.53192 (0.48482) +2025-09-13,13:52:39 | INFO | Train Epoch: 6 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.55490 (0.47111) Boundary_loss: 0.013895 (0.013897) Loss: 0.56880 (0.48501) +2025-09-13,13:53:10 | INFO | Train Epoch: 6 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.48367 (0.47114) Boundary_loss: 0.013896 (0.013897) Loss: 0.49757 (0.48503) +2025-09-13,13:53:41 | INFO | Train Epoch: 6 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.62642 (0.47147) Boundary_loss: 0.013896 (0.013897) Loss: 0.64032 (0.48537) +2025-09-13,13:54:12 | INFO | Train Epoch: 6 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.49900 (0.47153) Boundary_loss: 0.013895 (0.013897) Loss: 0.51290 (0.48543) +2025-09-13,13:54:43 | INFO | Train Epoch: 6 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.55332 (0.47171) Boundary_loss: 0.013896 (0.013897) Loss: 0.56722 (0.48560) +2025-09-13,13:55:14 | INFO | Train Epoch: 6 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.49872 (0.47177) Boundary_loss: 0.013897 (0.013897) Loss: 0.51262 (0.48566) +2025-09-13,13:55:45 | INFO | Train Epoch: 6 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.38285 (0.47157) Boundary_loss: 0.013904 (0.013897) Loss: 0.39675 (0.48547) +2025-09-13,13:56:16 | INFO | Train Epoch: 6 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.41612 (0.47146) Boundary_loss: 0.013896 (0.013897) Loss: 0.43002 (0.48535) +2025-09-13,13:56:47 | INFO | Train Epoch: 6 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.52981 (0.47158) Boundary_loss: 0.013897 (0.013897) Loss: 0.54371 (0.48548) +2025-09-13,13:57:18 | INFO | Train Epoch: 6 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.46336 (0.47156) Boundary_loss: 0.013895 (0.013897) Loss: 0.47726 (0.48546) +2025-09-13,13:57:49 | INFO | Train Epoch: 6 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.44400 (0.47150) Boundary_loss: 0.013897 (0.013897) Loss: 0.45790 (0.48540) +2025-09-13,13:58:20 | INFO | Train Epoch: 6 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.45932 (0.47148) Boundary_loss: 0.013895 (0.013897) Loss: 0.47321 (0.48538) +2025-09-13,13:58:51 | INFO | Train Epoch: 6 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.34711 (0.47122) Boundary_loss: 0.013895 (0.013897) Loss: 0.36100 (0.48511) +2025-09-13,13:59:22 | INFO | Train Epoch: 6 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.44751 (0.47117) Boundary_loss: 0.013898 (0.013897) Loss: 0.46141 (0.48506) +2025-09-13,13:59:53 | INFO | Train Epoch: 6 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.54178 (0.47131) Boundary_loss: 0.013896 (0.013897) Loss: 0.55567 (0.48521) +2025-09-13,14:00:24 | INFO | Train Epoch: 6 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.39082 (0.47115) Boundary_loss: 0.013896 (0.013897) Loss: 0.40471 (0.48504) +2025-09-13,14:00:55 | INFO | Train Epoch: 6 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.51448 (0.47124) Boundary_loss: 0.013896 (0.013897) Loss: 0.52837 (0.48513) +2025-09-13,14:01:25 | INFO | Train Epoch: 6 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.50321 (0.47130) Boundary_loss: 0.013897 (0.013897) Loss: 0.51711 (0.48520) +2025-09-13,14:01:56 | INFO | Train Epoch: 6 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.48413 (0.47133) Boundary_loss: 0.013895 (0.013897) Loss: 0.49803 (0.48523) +2025-09-13,14:02:28 | INFO | Train Epoch: 6 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.37863 (0.47114) Boundary_loss: 0.013898 (0.013897) Loss: 0.39253 (0.48503) +2025-09-13,14:02:59 | INFO | Train Epoch: 6 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.53937 (0.47128) Boundary_loss: 0.013895 (0.013897) Loss: 0.55327 (0.48518) +2025-09-13,14:03:30 | INFO | Train Epoch: 6 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.46087 (0.47126) Boundary_loss: 0.013898 (0.013897) Loss: 0.47477 (0.48515) +2025-09-13,14:04:01 | INFO | Train Epoch: 6 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.43548 (0.47118) Boundary_loss: 0.013896 (0.013897) Loss: 0.44938 (0.48508) +2025-09-13,14:04:31 | INFO | Train Epoch: 6 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.53348 (0.47131) Boundary_loss: 0.013898 (0.013897) Loss: 0.54738 (0.48521) +2025-09-13,14:05:02 | INFO | Train Epoch: 6 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37234 (0.47111) Boundary_loss: 0.013895 (0.013897) Loss: 0.38624 (0.48500) +2025-09-13,14:05:33 | INFO | Train Epoch: 6 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.45181 (0.47107) Boundary_loss: 0.013896 (0.013897) Loss: 0.46571 (0.48497) +2025-09-13,14:06:04 | INFO | Train Epoch: 6 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.47991 (0.47109) Boundary_loss: 0.013896 (0.013897) Loss: 0.49381 (0.48498) +2025-09-13,14:06:35 | INFO | Train Epoch: 6 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.45454 (0.47105) Boundary_loss: 0.013897 (0.013897) Loss: 0.46844 (0.48495) +2025-09-13,14:07:06 | INFO | Train Epoch: 6 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.37217 (0.47085) Boundary_loss: 0.013895 (0.013897) Loss: 0.38607 (0.48475) +2025-09-13,14:07:36 | INFO | Train Epoch: 6 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.53401 (0.47098) Boundary_loss: 0.013896 (0.013897) Loss: 0.54791 (0.48488) +2025-09-13,14:08:07 | INFO | Train Epoch: 6 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.58261 (0.47121) Boundary_loss: 0.013896 (0.013897) Loss: 0.59651 (0.48510) +2025-09-13,14:08:38 | INFO | Train Epoch: 6 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.46980 (0.47120) Boundary_loss: 0.013895 (0.013897) Loss: 0.48369 (0.48510) +2025-09-13,14:09:09 | INFO | Train Epoch: 6 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.50049 (0.47126) Boundary_loss: 0.013896 (0.013897) Loss: 0.51439 (0.48516) +2025-09-13,14:09:40 | INFO | Train Epoch: 6 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.56391 (0.47145) Boundary_loss: 0.013898 (0.013897) Loss: 0.57780 (0.48535) +2025-09-13,14:10:11 | INFO | Train Epoch: 6 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.42487 (0.47136) Boundary_loss: 0.013896 (0.013897) Loss: 0.43876 (0.48525) +2025-09-13,14:10:41 | INFO | Train Epoch: 6 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.53846 (0.47149) Boundary_loss: 0.013897 (0.013897) Loss: 0.55236 (0.48539) +2025-09-13,14:11:12 | INFO | Train Epoch: 6 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.44060 (0.47143) Boundary_loss: 0.013897 (0.013897) Loss: 0.45450 (0.48533) +2025-09-13,14:11:43 | INFO | Train Epoch: 6 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.52899 (0.47154) Boundary_loss: 0.013898 (0.013897) Loss: 0.54289 (0.48544) +2025-09-13,14:12:14 | INFO | Train Epoch: 6 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.39040 (0.47138) Boundary_loss: 0.013898 (0.013897) Loss: 0.40430 (0.48528) +2025-09-13,14:12:45 | INFO | Train Epoch: 6 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.45574 (0.47135) Boundary_loss: 0.013895 (0.013897) Loss: 0.46964 (0.48525) +2025-09-13,14:13:16 | INFO | Train Epoch: 6 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.47860 (0.47137) Boundary_loss: 0.013898 (0.013897) Loss: 0.49250 (0.48526) +2025-09-13,14:13:47 | INFO | Train Epoch: 6 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.43189 (0.47129) Boundary_loss: 0.013899 (0.013897) Loss: 0.44579 (0.48518) +2025-09-13,14:14:18 | INFO | Train Epoch: 6 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.57338 (0.47149) Boundary_loss: 0.013897 (0.013897) Loss: 0.58727 (0.48539) +2025-09-13,14:14:49 | INFO | Train Epoch: 6 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.44531 (0.47144) Boundary_loss: 0.013897 (0.013897) Loss: 0.45921 (0.48533) +2025-09-13,14:15:20 | INFO | Train Epoch: 6 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.52099 (0.47154) Boundary_loss: 0.013901 (0.013897) Loss: 0.53489 (0.48543) +2025-09-13,14:15:50 | INFO | Train Epoch: 6 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.39323 (0.47138) Boundary_loss: 0.013897 (0.013897) Loss: 0.40712 (0.48528) +2025-09-13,14:16:21 | INFO | Train Epoch: 6 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.39052 (0.47122) Boundary_loss: 0.013895 (0.013897) Loss: 0.40441 (0.48512) +2025-09-13,14:16:52 | INFO | Train Epoch: 6 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.56826 (0.47141) Boundary_loss: 0.013895 (0.013897) Loss: 0.58215 (0.48531) +2025-09-13,14:17:23 | INFO | Train Epoch: 6 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.48079 (0.47143) Boundary_loss: 0.013896 (0.013897) Loss: 0.49469 (0.48533) +2025-09-13,14:17:54 | INFO | Train Epoch: 6 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.55461 (0.47159) Boundary_loss: 0.013897 (0.013897) Loss: 0.56850 (0.48549) +2025-09-13,14:18:25 | INFO | Train Epoch: 6 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.36798 (0.47139) Boundary_loss: 0.013896 (0.013897) Loss: 0.38188 (0.48529) +2025-09-13,14:18:56 | INFO | Train Epoch: 6 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.47266 (0.47139) Boundary_loss: 0.013896 (0.013897) Loss: 0.48656 (0.48529) +2025-09-13,14:19:27 | INFO | Train Epoch: 6 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.48999 (0.47143) Boundary_loss: 0.013899 (0.013897) Loss: 0.50389 (0.48533) +2025-09-13,14:19:58 | INFO | Train Epoch: 6 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.45145 (0.47139) Boundary_loss: 0.013896 (0.013897) Loss: 0.46535 (0.48529) +2025-09-13,14:20:29 | INFO | Train Epoch: 6 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.57998 (0.47160) Boundary_loss: 0.013897 (0.013897) Loss: 0.59388 (0.48550) +2025-09-13,14:20:58 | INFO | Train Epoch: 6 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.45529 (0.47157) Boundary_loss: 0.013897 (0.013897) Loss: 0.46919 (0.48547) +2025-09-13,14:20:58 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,14:20:58 | INFO | [Epoch 6] Average Step Time: 0.312s | Average GPU Memory: 25.3 GB +2025-09-13,14:20:58 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,14:20:58 | INFO | Starting zero-shot imagenet. +2025-09-13,14:20:58 | INFO | Building zero-shot classifier +2025-09-13,14:21:04 | INFO | Using classifier +2025-09-13,14:21:46 | INFO | Finished zero-shot imagenet. +2025-09-13,14:21:46 | INFO | Eval Epoch: 7 imagenet-zeroshot-val-top1: 0.2506 imagenet-zeroshot-val-top5: 0.4997 +2025-09-13,14:21:48 | INFO | Start epoch 7 +2025-09-13,14:21:49 | INFO | Train Epoch: 7 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.34399 (0.34399) Boundary_loss: 0.013895 (0.013895) Loss: 0.35789 (0.35789) +2025-09-13,14:22:20 | INFO | Train Epoch: 7 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.40687 (0.37543) Boundary_loss: 0.013895 (0.013895) Loss: 0.42076 (0.38932) +2025-09-13,14:22:51 | INFO | Train Epoch: 7 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.36074 (0.37053) Boundary_loss: 0.013897 (0.013896) Loss: 0.37464 (0.38443) +2025-09-13,14:23:22 | INFO | Train Epoch: 7 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.37450 (0.37153) Boundary_loss: 0.013904 (0.013898) Loss: 0.38841 (0.38542) +2025-09-13,14:23:53 | INFO | Train Epoch: 7 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.41840 (0.38090) Boundary_loss: 0.013895 (0.013897) Loss: 0.43229 (0.39480) +2025-09-13,14:24:23 | INFO | Train Epoch: 7 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.38740 (0.38198) Boundary_loss: 0.013897 (0.013897) Loss: 0.40130 (0.39588) +2025-09-13,14:24:54 | INFO | Train Epoch: 7 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.53189 (0.40340) Boundary_loss: 0.013895 (0.013897) Loss: 0.54579 (0.41730) +2025-09-13,14:25:25 | INFO | Train Epoch: 7 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.43633 (0.40752) Boundary_loss: 0.013899 (0.013897) Loss: 0.45023 (0.42141) +2025-09-13,14:25:56 | INFO | Train Epoch: 7 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42842 (0.40984) Boundary_loss: 0.013896 (0.013897) Loss: 0.44231 (0.42374) +2025-09-13,14:26:27 | INFO | Train Epoch: 7 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.48215 (0.41707) Boundary_loss: 0.013894 (0.013897) Loss: 0.49604 (0.43097) +2025-09-13,14:26:58 | INFO | Train Epoch: 7 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.37029 (0.41282) Boundary_loss: 0.013897 (0.013897) Loss: 0.38418 (0.42671) +2025-09-13,14:27:29 | INFO | Train Epoch: 7 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.48189 (0.41857) Boundary_loss: 0.013895 (0.013897) Loss: 0.49578 (0.43247) +2025-09-13,14:28:00 | INFO | Train Epoch: 7 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.41260 (0.41811) Boundary_loss: 0.013896 (0.013897) Loss: 0.42650 (0.43201) +2025-09-13,14:28:30 | INFO | Train Epoch: 7 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.34754 (0.41307) Boundary_loss: 0.013898 (0.013897) Loss: 0.36144 (0.42697) +2025-09-13,14:29:01 | INFO | Train Epoch: 7 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.41225 (0.41302) Boundary_loss: 0.013895 (0.013897) Loss: 0.42614 (0.42691) +2025-09-13,14:29:32 | INFO | Train Epoch: 7 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.42247 (0.41361) Boundary_loss: 0.013895 (0.013896) Loss: 0.43637 (0.42750) +2025-09-13,14:30:03 | INFO | Train Epoch: 7 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.40779 (0.41327) Boundary_loss: 0.013896 (0.013896) Loss: 0.42169 (0.42716) +2025-09-13,14:30:34 | INFO | Train Epoch: 7 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.51342 (0.41883) Boundary_loss: 0.013895 (0.013896) Loss: 0.52731 (0.43273) +2025-09-13,14:31:05 | INFO | Train Epoch: 7 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.40624 (0.41817) Boundary_loss: 0.013895 (0.013896) Loss: 0.42013 (0.43206) +2025-09-13,14:31:36 | INFO | Train Epoch: 7 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.49645 (0.42208) Boundary_loss: 0.013898 (0.013896) Loss: 0.51035 (0.43598) +2025-09-13,14:32:06 | INFO | Train Epoch: 7 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.45390 (0.42360) Boundary_loss: 0.013896 (0.013896) Loss: 0.46779 (0.43749) +2025-09-13,14:32:37 | INFO | Train Epoch: 7 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.37344 (0.42132) Boundary_loss: 0.013897 (0.013896) Loss: 0.38733 (0.43521) +2025-09-13,14:33:08 | INFO | Train Epoch: 7 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.47044 (0.42345) Boundary_loss: 0.013901 (0.013897) Loss: 0.48434 (0.43735) +2025-09-13,14:33:39 | INFO | Train Epoch: 7 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.41924 (0.42328) Boundary_loss: 0.013897 (0.013897) Loss: 0.43313 (0.43717) +2025-09-13,14:34:10 | INFO | Train Epoch: 7 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.37166 (0.42121) Boundary_loss: 0.013896 (0.013897) Loss: 0.38555 (0.43511) +2025-09-13,14:34:41 | INFO | Train Epoch: 7 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.54216 (0.42586) Boundary_loss: 0.013895 (0.013896) Loss: 0.55606 (0.43976) +2025-09-13,14:35:12 | INFO | Train Epoch: 7 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.34697 (0.42294) Boundary_loss: 0.013895 (0.013896) Loss: 0.36087 (0.43684) +2025-09-13,14:35:43 | INFO | Train Epoch: 7 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.47458 (0.42479) Boundary_loss: 0.013897 (0.013896) Loss: 0.48848 (0.43868) +2025-09-13,14:36:14 | INFO | Train Epoch: 7 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.48118 (0.42673) Boundary_loss: 0.013897 (0.013896) Loss: 0.49508 (0.44063) +2025-09-13,14:36:45 | INFO | Train Epoch: 7 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.41270 (0.42626) Boundary_loss: 0.013896 (0.013896) Loss: 0.42659 (0.44016) +2025-09-13,14:37:16 | INFO | Train Epoch: 7 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.39467 (0.42524) Boundary_loss: 0.013896 (0.013896) Loss: 0.40856 (0.43914) +2025-09-13,14:37:47 | INFO | Train Epoch: 7 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.41154 (0.42482) Boundary_loss: 0.013895 (0.013896) Loss: 0.42543 (0.43871) +2025-09-13,14:38:18 | INFO | Train Epoch: 7 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.41859 (0.42463) Boundary_loss: 0.013896 (0.013896) Loss: 0.43249 (0.43852) +2025-09-13,14:38:48 | INFO | Train Epoch: 7 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.36599 (0.42290) Boundary_loss: 0.013895 (0.013896) Loss: 0.37989 (0.43680) +2025-09-13,14:39:19 | INFO | Train Epoch: 7 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.44414 (0.42351) Boundary_loss: 0.013896 (0.013896) Loss: 0.45804 (0.43741) +2025-09-13,14:39:50 | INFO | Train Epoch: 7 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.46342 (0.42462) Boundary_loss: 0.013896 (0.013896) Loss: 0.47731 (0.43851) +2025-09-13,14:40:21 | INFO | Train Epoch: 7 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.35719 (0.42280) Boundary_loss: 0.013896 (0.013896) Loss: 0.37109 (0.43669) +2025-09-13,14:40:52 | INFO | Train Epoch: 7 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.52260 (0.42542) Boundary_loss: 0.013895 (0.013896) Loss: 0.53649 (0.43932) +2025-09-13,14:41:23 | INFO | Train Epoch: 7 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.41480 (0.42515) Boundary_loss: 0.013895 (0.013896) Loss: 0.42870 (0.43905) +2025-09-13,14:41:54 | INFO | Train Epoch: 7 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.37502 (0.42390) Boundary_loss: 0.013896 (0.013896) Loss: 0.38892 (0.43779) +2025-09-13,14:42:25 | INFO | Train Epoch: 7 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.36187 (0.42238) Boundary_loss: 0.013897 (0.013896) Loss: 0.37577 (0.43628) +2025-09-13,14:42:56 | INFO | Train Epoch: 7 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.38605 (0.42152) Boundary_loss: 0.013896 (0.013896) Loss: 0.39994 (0.43541) +2025-09-13,14:43:27 | INFO | Train Epoch: 7 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.44000 (0.42195) Boundary_loss: 0.013897 (0.013896) Loss: 0.45390 (0.43584) +2025-09-13,14:43:57 | INFO | Train Epoch: 7 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.41748 (0.42185) Boundary_loss: 0.013898 (0.013896) Loss: 0.43138 (0.43574) +2025-09-13,14:44:28 | INFO | Train Epoch: 7 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.35522 (0.42037) Boundary_loss: 0.013896 (0.013896) Loss: 0.36911 (0.43426) +2025-09-13,14:44:59 | INFO | Train Epoch: 7 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.44050 (0.42080) Boundary_loss: 0.013897 (0.013896) Loss: 0.45439 (0.43470) +2025-09-13,14:45:30 | INFO | Train Epoch: 7 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.38992 (0.42015) Boundary_loss: 0.013894 (0.013896) Loss: 0.40381 (0.43404) +2025-09-13,14:46:01 | INFO | Train Epoch: 7 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.41144 (0.41997) Boundary_loss: 0.013895 (0.013896) Loss: 0.42533 (0.43386) +2025-09-13,14:46:32 | INFO | Train Epoch: 7 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.46415 (0.42087) Boundary_loss: 0.013896 (0.013896) Loss: 0.47805 (0.43476) +2025-09-13,14:47:03 | INFO | Train Epoch: 7 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.37259 (0.41990) Boundary_loss: 0.013897 (0.013896) Loss: 0.38649 (0.43380) +2025-09-13,14:47:33 | INFO | Train Epoch: 7 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.40430 (0.41960) Boundary_loss: 0.013895 (0.013896) Loss: 0.41820 (0.43349) +2025-09-13,14:48:04 | INFO | Train Epoch: 7 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.34172 (0.41810) Boundary_loss: 0.013899 (0.013896) Loss: 0.35562 (0.43199) +2025-09-13,14:48:35 | INFO | Train Epoch: 7 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.47988 (0.41926) Boundary_loss: 0.013897 (0.013896) Loss: 0.49378 (0.43316) +2025-09-13,14:49:06 | INFO | Train Epoch: 7 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.50197 (0.42080) Boundary_loss: 0.013898 (0.013896) Loss: 0.51586 (0.43469) +2025-09-13,14:49:37 | INFO | Train Epoch: 7 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.39345 (0.42030) Boundary_loss: 0.013895 (0.013896) Loss: 0.40734 (0.43419) +2025-09-13,14:50:08 | INFO | Train Epoch: 7 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.35151 (0.41907) Boundary_loss: 0.013896 (0.013896) Loss: 0.36541 (0.43297) +2025-09-13,14:50:39 | INFO | Train Epoch: 7 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.41273 (0.41896) Boundary_loss: 0.013897 (0.013896) Loss: 0.42663 (0.43285) +2025-09-13,14:51:10 | INFO | Train Epoch: 7 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.54793 (0.42118) Boundary_loss: 0.013894 (0.013896) Loss: 0.56182 (0.43508) +2025-09-13,14:51:41 | INFO | Train Epoch: 7 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.43512 (0.42142) Boundary_loss: 0.013895 (0.013896) Loss: 0.44901 (0.43531) +2025-09-13,14:52:12 | INFO | Train Epoch: 7 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.30831 (0.41953) Boundary_loss: 0.013902 (0.013896) Loss: 0.32221 (0.43343) +2025-09-13,14:52:43 | INFO | Train Epoch: 7 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.48526 (0.42061) Boundary_loss: 0.013899 (0.013896) Loss: 0.49916 (0.43451) +2025-09-13,14:53:14 | INFO | Train Epoch: 7 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.51436 (0.42212) Boundary_loss: 0.013898 (0.013896) Loss: 0.52825 (0.43602) +2025-09-13,14:53:45 | INFO | Train Epoch: 7 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.37045 (0.42130) Boundary_loss: 0.013897 (0.013896) Loss: 0.38434 (0.43520) +2025-09-13,14:54:16 | INFO | Train Epoch: 7 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36627 (0.42044) Boundary_loss: 0.013897 (0.013896) Loss: 0.38017 (0.43434) +2025-09-13,14:54:46 | INFO | Train Epoch: 7 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.49988 (0.42166) Boundary_loss: 0.013898 (0.013896) Loss: 0.51377 (0.43556) +2025-09-13,14:55:17 | INFO | Train Epoch: 7 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.39903 (0.42132) Boundary_loss: 0.013897 (0.013896) Loss: 0.41293 (0.43522) +2025-09-13,14:55:48 | INFO | Train Epoch: 7 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.39361 (0.42091) Boundary_loss: 0.013898 (0.013897) Loss: 0.40751 (0.43480) +2025-09-13,14:56:19 | INFO | Train Epoch: 7 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.45600 (0.42142) Boundary_loss: 0.013895 (0.013896) Loss: 0.46990 (0.43532) +2025-09-13,14:56:49 | INFO | Train Epoch: 7 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.39350 (0.42102) Boundary_loss: 0.013896 (0.013896) Loss: 0.40740 (0.43492) +2025-09-13,14:57:20 | INFO | Train Epoch: 7 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.40190 (0.42075) Boundary_loss: 0.013895 (0.013896) Loss: 0.41580 (0.43464) +2025-09-13,14:57:51 | INFO | Train Epoch: 7 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.36081 (0.41990) Boundary_loss: 0.013898 (0.013896) Loss: 0.37471 (0.43380) +2025-09-13,14:58:22 | INFO | Train Epoch: 7 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.39782 (0.41960) Boundary_loss: 0.013897 (0.013896) Loss: 0.41172 (0.43349) +2025-09-13,14:58:53 | INFO | Train Epoch: 7 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.39591 (0.41927) Boundary_loss: 0.013896 (0.013896) Loss: 0.40981 (0.43317) +2025-09-13,14:59:24 | INFO | Train Epoch: 7 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.30483 (0.41772) Boundary_loss: 0.013896 (0.013896) Loss: 0.31872 (0.43162) +2025-09-13,14:59:54 | INFO | Train Epoch: 7 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.47012 (0.41842) Boundary_loss: 0.013896 (0.013896) Loss: 0.48402 (0.43232) +2025-09-13,15:00:25 | INFO | Train Epoch: 7 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.36439 (0.41771) Boundary_loss: 0.013899 (0.013896) Loss: 0.37829 (0.43161) +2025-09-13,15:00:56 | INFO | Train Epoch: 7 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.44783 (0.41810) Boundary_loss: 0.013895 (0.013896) Loss: 0.46173 (0.43200) +2025-09-13,15:01:27 | INFO | Train Epoch: 7 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.37323 (0.41753) Boundary_loss: 0.013895 (0.013896) Loss: 0.38712 (0.43142) +2025-09-13,15:01:58 | INFO | Train Epoch: 7 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.40365 (0.41735) Boundary_loss: 0.013898 (0.013896) Loss: 0.41755 (0.43125) +2025-09-13,15:02:29 | INFO | Train Epoch: 7 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.42472 (0.41744) Boundary_loss: 0.013896 (0.013896) Loss: 0.43862 (0.43134) +2025-09-13,15:03:00 | INFO | Train Epoch: 7 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.41986 (0.41747) Boundary_loss: 0.013896 (0.013896) Loss: 0.43376 (0.43137) +2025-09-13,15:03:31 | INFO | Train Epoch: 7 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.44917 (0.41786) Boundary_loss: 0.013896 (0.013896) Loss: 0.46307 (0.43176) +2025-09-13,15:04:01 | INFO | Train Epoch: 7 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.36795 (0.41726) Boundary_loss: 0.013896 (0.013896) Loss: 0.38185 (0.43116) +2025-09-13,15:04:32 | INFO | Train Epoch: 7 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.39571 (0.41700) Boundary_loss: 0.013899 (0.013896) Loss: 0.40961 (0.43090) +2025-09-13,15:05:03 | INFO | Train Epoch: 7 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.40538 (0.41687) Boundary_loss: 0.013898 (0.013896) Loss: 0.41928 (0.43076) +2025-09-13,15:05:34 | INFO | Train Epoch: 7 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.40862 (0.41677) Boundary_loss: 0.013898 (0.013897) Loss: 0.42252 (0.43067) +2025-09-13,15:06:05 | INFO | Train Epoch: 7 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.42581 (0.41687) Boundary_loss: 0.013897 (0.013897) Loss: 0.43971 (0.43077) +2025-09-13,15:06:35 | INFO | Train Epoch: 7 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.37667 (0.41642) Boundary_loss: 0.013896 (0.013897) Loss: 0.39057 (0.43031) +2025-09-13,15:07:06 | INFO | Train Epoch: 7 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.37216 (0.41592) Boundary_loss: 0.013897 (0.013897) Loss: 0.38606 (0.42982) +2025-09-13,15:07:37 | INFO | Train Epoch: 7 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.30922 (0.41473) Boundary_loss: 0.013896 (0.013897) Loss: 0.32312 (0.42863) +2025-09-13,15:08:09 | INFO | Train Epoch: 7 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.38725 (0.41443) Boundary_loss: 0.013901 (0.013897) Loss: 0.40115 (0.42833) +2025-09-13,15:08:40 | INFO | Train Epoch: 7 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.44018 (0.41471) Boundary_loss: 0.013896 (0.013897) Loss: 0.45408 (0.42861) +2025-09-13,15:09:10 | INFO | Train Epoch: 7 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.39070 (0.41445) Boundary_loss: 0.013901 (0.013897) Loss: 0.40460 (0.42835) +2025-09-13,15:09:42 | INFO | Train Epoch: 7 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44856 (0.41482) Boundary_loss: 0.013896 (0.013897) Loss: 0.46246 (0.42871) +2025-09-13,15:10:12 | INFO | Train Epoch: 7 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.42335 (0.41491) Boundary_loss: 0.013897 (0.013897) Loss: 0.43725 (0.42880) +2025-09-13,15:10:43 | INFO | Train Epoch: 7 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40374 (0.41479) Boundary_loss: 0.013897 (0.013897) Loss: 0.41763 (0.42869) +2025-09-13,15:11:14 | INFO | Train Epoch: 7 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.43389 (0.41499) Boundary_loss: 0.013896 (0.013897) Loss: 0.44779 (0.42888) +2025-09-13,15:11:45 | INFO | Train Epoch: 7 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.37429 (0.41457) Boundary_loss: 0.013897 (0.013897) Loss: 0.38819 (0.42847) +2025-09-13,15:12:16 | INFO | Train Epoch: 7 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.39424 (0.41437) Boundary_loss: 0.013896 (0.013897) Loss: 0.40813 (0.42826) +2025-09-13,15:12:47 | INFO | Train Epoch: 7 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.44147 (0.41464) Boundary_loss: 0.013898 (0.013897) Loss: 0.45537 (0.42853) +2025-09-13,15:13:18 | INFO | Train Epoch: 7 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.38500 (0.41434) Boundary_loss: 0.013896 (0.013897) Loss: 0.39890 (0.42824) +2025-09-13,15:13:49 | INFO | Train Epoch: 7 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40003 (0.41420) Boundary_loss: 0.013897 (0.013897) Loss: 0.41392 (0.42810) +2025-09-13,15:14:19 | INFO | Train Epoch: 7 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.43232 (0.41438) Boundary_loss: 0.013895 (0.013897) Loss: 0.44622 (0.42828) +2025-09-13,15:14:50 | INFO | Train Epoch: 7 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.38827 (0.41413) Boundary_loss: 0.013897 (0.013897) Loss: 0.40217 (0.42803) +2025-09-13,15:15:22 | INFO | Train Epoch: 7 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.42577 (0.41424) Boundary_loss: 0.013896 (0.013897) Loss: 0.43967 (0.42814) +2025-09-13,15:15:53 | INFO | Train Epoch: 7 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.36100 (0.41374) Boundary_loss: 0.013895 (0.013897) Loss: 0.37489 (0.42763) +2025-09-13,15:16:24 | INFO | Train Epoch: 7 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.37667 (0.41339) Boundary_loss: 0.013896 (0.013897) Loss: 0.39056 (0.42729) +2025-09-13,15:16:55 | INFO | Train Epoch: 7 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.39749 (0.41324) Boundary_loss: 0.013896 (0.013897) Loss: 0.41139 (0.42714) +2025-09-13,15:17:26 | INFO | Train Epoch: 7 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.41345 (0.41325) Boundary_loss: 0.013895 (0.013897) Loss: 0.42735 (0.42714) +2025-09-13,15:17:57 | INFO | Train Epoch: 7 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.44043 (0.41349) Boundary_loss: 0.013896 (0.013897) Loss: 0.45432 (0.42739) +2025-09-13,15:18:27 | INFO | Train Epoch: 7 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.34780 (0.41290) Boundary_loss: 0.013896 (0.013897) Loss: 0.36170 (0.42680) +2025-09-13,15:18:58 | INFO | Train Epoch: 7 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.35519 (0.41239) Boundary_loss: 0.013896 (0.013897) Loss: 0.36908 (0.42628) +2025-09-13,15:19:29 | INFO | Train Epoch: 7 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.42661 (0.41251) Boundary_loss: 0.013896 (0.013897) Loss: 0.44050 (0.42641) +2025-09-13,15:20:00 | INFO | Train Epoch: 7 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.40305 (0.41243) Boundary_loss: 0.013895 (0.013897) Loss: 0.41694 (0.42633) +2025-09-13,15:20:31 | INFO | Train Epoch: 7 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.35853 (0.41196) Boundary_loss: 0.013898 (0.013897) Loss: 0.37243 (0.42586) +2025-09-13,15:21:02 | INFO | Train Epoch: 7 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.37872 (0.41167) Boundary_loss: 0.013895 (0.013897) Loss: 0.39262 (0.42557) +2025-09-13,15:21:33 | INFO | Train Epoch: 7 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.35945 (0.41123) Boundary_loss: 0.013897 (0.013897) Loss: 0.37335 (0.42512) +2025-09-13,15:22:03 | INFO | Train Epoch: 7 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.43460 (0.41143) Boundary_loss: 0.013896 (0.013896) Loss: 0.44850 (0.42532) +2025-09-13,15:22:34 | INFO | Train Epoch: 7 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.46837 (0.41190) Boundary_loss: 0.013895 (0.013896) Loss: 0.48226 (0.42580) +2025-09-13,15:23:05 | INFO | Train Epoch: 7 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.37453 (0.41159) Boundary_loss: 0.013897 (0.013896) Loss: 0.38842 (0.42549) +2025-09-13,15:23:36 | INFO | Train Epoch: 7 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.35200 (0.41110) Boundary_loss: 0.013897 (0.013896) Loss: 0.36590 (0.42500) +2025-09-13,15:24:07 | INFO | Train Epoch: 7 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.35604 (0.41065) Boundary_loss: 0.013897 (0.013897) Loss: 0.36994 (0.42455) +2025-09-13,15:24:38 | INFO | Train Epoch: 7 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.49507 (0.41133) Boundary_loss: 0.013898 (0.013897) Loss: 0.50897 (0.42523) +2025-09-13,15:25:09 | INFO | Train Epoch: 7 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.32054 (0.41060) Boundary_loss: 0.013895 (0.013897) Loss: 0.33443 (0.42450) +2025-09-13,15:25:39 | INFO | Train Epoch: 7 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40962 (0.41059) Boundary_loss: 0.013896 (0.013897) Loss: 0.42352 (0.42449) +2025-09-13,15:26:10 | INFO | Train Epoch: 7 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.26980 (0.40948) Boundary_loss: 0.013899 (0.013897) Loss: 0.28370 (0.42337) +2025-09-13,15:26:41 | INFO | Train Epoch: 7 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.43936 (0.40971) Boundary_loss: 0.013899 (0.013897) Loss: 0.45326 (0.42361) +2025-09-13,15:27:12 | INFO | Train Epoch: 7 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.34627 (0.40922) Boundary_loss: 0.013897 (0.013897) Loss: 0.36016 (0.42311) +2025-09-13,15:27:43 | INFO | Train Epoch: 7 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.41275 (0.40924) Boundary_loss: 0.013898 (0.013897) Loss: 0.42665 (0.42314) +2025-09-13,15:28:14 | INFO | Train Epoch: 7 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.39899 (0.40917) Boundary_loss: 0.013896 (0.013897) Loss: 0.41289 (0.42306) +2025-09-13,15:28:45 | INFO | Train Epoch: 7 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.37159 (0.40888) Boundary_loss: 0.013898 (0.013897) Loss: 0.38549 (0.42278) +2025-09-13,15:29:15 | INFO | Train Epoch: 7 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.36129 (0.40852) Boundary_loss: 0.013896 (0.013897) Loss: 0.37518 (0.42241) +2025-09-13,15:29:46 | INFO | Train Epoch: 7 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.42493 (0.40864) Boundary_loss: 0.013897 (0.013897) Loss: 0.43883 (0.42254) +2025-09-13,15:30:17 | INFO | Train Epoch: 7 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.40210 (0.40859) Boundary_loss: 0.013897 (0.013897) Loss: 0.41599 (0.42249) +2025-09-13,15:30:48 | INFO | Train Epoch: 7 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.28964 (0.40771) Boundary_loss: 0.013897 (0.013897) Loss: 0.30354 (0.42161) +2025-09-13,15:31:19 | INFO | Train Epoch: 7 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.41987 (0.40780) Boundary_loss: 0.013898 (0.013897) Loss: 0.43377 (0.42170) +2025-09-13,15:31:50 | INFO | Train Epoch: 7 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.35220 (0.40740) Boundary_loss: 0.013900 (0.013897) Loss: 0.36610 (0.42129) +2025-09-13,15:32:21 | INFO | Train Epoch: 7 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.39018 (0.40727) Boundary_loss: 0.013896 (0.013897) Loss: 0.40407 (0.42117) +2025-09-13,15:32:52 | INFO | Train Epoch: 7 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.40796 (0.40728) Boundary_loss: 0.013898 (0.013897) Loss: 0.42185 (0.42117) +2025-09-13,15:33:22 | INFO | Train Epoch: 7 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.36793 (0.40699) Boundary_loss: 0.013896 (0.013897) Loss: 0.38183 (0.42089) +2025-09-13,15:33:53 | INFO | Train Epoch: 7 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.36625 (0.40671) Boundary_loss: 0.013896 (0.013897) Loss: 0.38015 (0.42060) +2025-09-13,15:34:24 | INFO | Train Epoch: 7 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.36875 (0.40644) Boundary_loss: 0.013896 (0.013897) Loss: 0.38264 (0.42033) +2025-09-13,15:34:55 | INFO | Train Epoch: 7 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.46449 (0.40684) Boundary_loss: 0.013895 (0.013897) Loss: 0.47838 (0.42074) +2025-09-13,15:35:25 | INFO | Train Epoch: 7 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.41015 (0.40687) Boundary_loss: 0.013895 (0.013897) Loss: 0.42404 (0.42076) +2025-09-13,15:35:56 | INFO | Train Epoch: 7 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.46446 (0.40726) Boundary_loss: 0.013896 (0.013897) Loss: 0.47836 (0.42116) +2025-09-13,15:36:27 | INFO | Train Epoch: 7 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.48810 (0.40782) Boundary_loss: 0.013896 (0.013897) Loss: 0.50199 (0.42171) +2025-09-13,15:36:57 | INFO | Train Epoch: 7 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.47048 (0.40824) Boundary_loss: 0.013896 (0.013897) Loss: 0.48438 (0.42214) +2025-09-13,15:37:28 | INFO | Train Epoch: 7 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.38438 (0.40808) Boundary_loss: 0.013896 (0.013897) Loss: 0.39828 (0.42198) +2025-09-13,15:37:59 | INFO | Train Epoch: 7 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.38446 (0.40792) Boundary_loss: 0.013895 (0.013897) Loss: 0.39835 (0.42182) +2025-09-13,15:38:30 | INFO | Train Epoch: 7 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.36300 (0.40762) Boundary_loss: 0.013895 (0.013897) Loss: 0.37690 (0.42152) +2025-09-13,15:39:01 | INFO | Train Epoch: 7 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.37222 (0.40739) Boundary_loss: 0.013902 (0.013897) Loss: 0.38612 (0.42129) +2025-09-13,15:39:32 | INFO | Train Epoch: 7 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.40740 (0.40739) Boundary_loss: 0.013896 (0.013897) Loss: 0.42130 (0.42129) +2025-09-13,15:40:02 | INFO | Train Epoch: 7 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.39488 (0.40731) Boundary_loss: 0.013898 (0.013897) Loss: 0.40877 (0.42121) +2025-09-13,15:40:33 | INFO | Train Epoch: 7 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.30079 (0.40662) Boundary_loss: 0.013896 (0.013897) Loss: 0.31469 (0.42051) +2025-09-13,15:41:04 | INFO | Train Epoch: 7 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.39256 (0.40653) Boundary_loss: 0.013895 (0.013897) Loss: 0.40646 (0.42042) +2025-09-13,15:41:35 | INFO | Train Epoch: 7 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.35503 (0.40620) Boundary_loss: 0.013896 (0.013897) Loss: 0.36892 (0.42009) +2025-09-13,15:42:06 | INFO | Train Epoch: 7 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.38502 (0.40606) Boundary_loss: 0.013895 (0.013897) Loss: 0.39892 (0.41996) +2025-09-13,15:42:37 | INFO | Train Epoch: 7 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.37105 (0.40584) Boundary_loss: 0.013896 (0.013897) Loss: 0.38494 (0.41974) +2025-09-13,15:43:08 | INFO | Train Epoch: 7 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.38930 (0.40574) Boundary_loss: 0.013897 (0.013897) Loss: 0.40320 (0.41963) +2025-09-13,15:43:39 | INFO | Train Epoch: 7 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.47767 (0.40619) Boundary_loss: 0.013897 (0.013897) Loss: 0.49156 (0.42008) +2025-09-13,15:44:10 | INFO | Train Epoch: 7 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.42589 (0.40631) Boundary_loss: 0.013896 (0.013897) Loss: 0.43978 (0.42020) +2025-09-13,15:44:41 | INFO | Train Epoch: 7 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.47515 (0.40673) Boundary_loss: 0.013895 (0.013897) Loss: 0.48905 (0.42063) +2025-09-13,15:45:12 | INFO | Train Epoch: 7 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.37405 (0.40653) Boundary_loss: 0.013896 (0.013897) Loss: 0.38795 (0.42043) +2025-09-13,15:45:42 | INFO | Train Epoch: 7 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.51280 (0.40718) Boundary_loss: 0.013899 (0.013897) Loss: 0.52670 (0.42108) +2025-09-13,15:46:13 | INFO | Train Epoch: 7 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.39212 (0.40709) Boundary_loss: 0.013897 (0.013897) Loss: 0.40601 (0.42099) +2025-09-13,15:46:44 | INFO | Train Epoch: 7 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.42457 (0.40719) Boundary_loss: 0.013895 (0.013897) Loss: 0.43846 (0.42109) +2025-09-13,15:47:15 | INFO | Train Epoch: 7 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.48445 (0.40766) Boundary_loss: 0.013896 (0.013897) Loss: 0.49835 (0.42155) +2025-09-13,15:47:46 | INFO | Train Epoch: 7 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.39201 (0.40756) Boundary_loss: 0.013896 (0.013897) Loss: 0.40591 (0.42146) +2025-09-13,15:48:17 | INFO | Train Epoch: 7 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.39289 (0.40748) Boundary_loss: 0.013896 (0.013897) Loss: 0.40678 (0.42137) +2025-09-13,15:48:48 | INFO | Train Epoch: 7 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.39445 (0.40740) Boundary_loss: 0.013896 (0.013897) Loss: 0.40835 (0.42130) +2025-09-13,15:49:19 | INFO | Train Epoch: 7 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.34977 (0.40706) Boundary_loss: 0.013895 (0.013897) Loss: 0.36367 (0.42096) +2025-09-13,15:49:50 | INFO | Train Epoch: 7 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.41116 (0.40709) Boundary_loss: 0.013896 (0.013897) Loss: 0.42506 (0.42098) +2025-09-13,15:50:21 | INFO | Train Epoch: 7 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.38149 (0.40694) Boundary_loss: 0.013896 (0.013897) Loss: 0.39539 (0.42084) +2025-09-13,15:50:52 | INFO | Train Epoch: 7 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.31387 (0.40640) Boundary_loss: 0.013898 (0.013897) Loss: 0.32777 (0.42030) +2025-09-13,15:51:23 | INFO | Train Epoch: 7 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.34674 (0.40606) Boundary_loss: 0.013895 (0.013897) Loss: 0.36063 (0.41996) +2025-09-13,15:51:54 | INFO | Train Epoch: 7 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.36384 (0.40582) Boundary_loss: 0.013897 (0.013897) Loss: 0.37773 (0.41972) +2025-09-13,15:52:24 | INFO | Train Epoch: 7 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.34620 (0.40549) Boundary_loss: 0.013896 (0.013897) Loss: 0.36009 (0.41938) +2025-09-13,15:52:55 | INFO | Train Epoch: 7 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.31336 (0.40497) Boundary_loss: 0.013897 (0.013897) Loss: 0.32725 (0.41887) +2025-09-13,15:53:26 | INFO | Train Epoch: 7 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.37978 (0.40483) Boundary_loss: 0.013895 (0.013896) Loss: 0.39367 (0.41872) +2025-09-13,15:53:57 | INFO | Train Epoch: 7 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.42450 (0.40494) Boundary_loss: 0.013896 (0.013896) Loss: 0.43839 (0.41883) +2025-09-13,15:54:28 | INFO | Train Epoch: 7 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.29557 (0.40433) Boundary_loss: 0.013895 (0.013896) Loss: 0.30946 (0.41823) +2025-09-13,15:54:59 | INFO | Train Epoch: 7 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.46376 (0.40466) Boundary_loss: 0.013895 (0.013896) Loss: 0.47766 (0.41856) +2025-09-13,15:55:29 | INFO | Train Epoch: 7 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.41966 (0.40474) Boundary_loss: 0.013895 (0.013896) Loss: 0.43356 (0.41864) +2025-09-13,15:56:00 | INFO | Train Epoch: 7 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37422 (0.40458) Boundary_loss: 0.013895 (0.013896) Loss: 0.38812 (0.41847) +2025-09-13,15:56:31 | INFO | Train Epoch: 7 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.41077 (0.40461) Boundary_loss: 0.013901 (0.013896) Loss: 0.42467 (0.41851) +2025-09-13,15:57:02 | INFO | Train Epoch: 7 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.36105 (0.40437) Boundary_loss: 0.013895 (0.013896) Loss: 0.37494 (0.41827) +2025-09-13,15:57:33 | INFO | Train Epoch: 7 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.41954 (0.40446) Boundary_loss: 0.013896 (0.013896) Loss: 0.43344 (0.41835) +2025-09-13,15:58:04 | INFO | Train Epoch: 7 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36035 (0.40422) Boundary_loss: 0.013897 (0.013896) Loss: 0.37425 (0.41812) +2025-09-13,15:58:35 | INFO | Train Epoch: 7 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.40089 (0.40420) Boundary_loss: 0.013897 (0.013896) Loss: 0.41479 (0.41810) +2025-09-13,15:59:06 | INFO | Train Epoch: 7 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.35829 (0.40396) Boundary_loss: 0.013897 (0.013896) Loss: 0.37219 (0.41786) +2025-09-13,15:59:37 | INFO | Train Epoch: 7 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.43674 (0.40413) Boundary_loss: 0.013895 (0.013896) Loss: 0.45063 (0.41803) +2025-09-13,16:00:08 | INFO | Train Epoch: 7 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.39917 (0.40411) Boundary_loss: 0.013896 (0.013896) Loss: 0.41307 (0.41800) +2025-09-13,16:00:38 | INFO | Train Epoch: 7 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.52110 (0.40471) Boundary_loss: 0.013896 (0.013896) Loss: 0.53499 (0.41861) +2025-09-13,16:01:09 | INFO | Train Epoch: 7 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.32452 (0.40430) Boundary_loss: 0.013898 (0.013896) Loss: 0.33842 (0.41820) +2025-09-13,16:01:40 | INFO | Train Epoch: 7 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.38501 (0.40420) Boundary_loss: 0.013896 (0.013896) Loss: 0.39890 (0.41810) +2025-09-13,16:02:11 | INFO | Train Epoch: 7 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.42309 (0.40430) Boundary_loss: 0.013896 (0.013896) Loss: 0.43699 (0.41819) +2025-09-13,16:02:41 | INFO | Train Epoch: 7 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.43080 (0.40443) Boundary_loss: 0.013895 (0.013896) Loss: 0.44469 (0.41833) +2025-09-13,16:03:12 | INFO | Train Epoch: 7 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.44635 (0.40464) Boundary_loss: 0.013898 (0.013896) Loss: 0.46025 (0.41854) +2025-09-13,16:03:43 | INFO | Train Epoch: 7 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.37210 (0.40448) Boundary_loss: 0.013896 (0.013896) Loss: 0.38599 (0.41838) +2025-09-13,16:04:14 | INFO | Train Epoch: 7 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.34139 (0.40417) Boundary_loss: 0.013897 (0.013896) Loss: 0.35529 (0.41806) +2025-09-13,16:04:45 | INFO | Train Epoch: 7 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.41962 (0.40424) Boundary_loss: 0.013896 (0.013896) Loss: 0.43351 (0.41814) +2025-09-13,16:05:16 | INFO | Train Epoch: 7 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.43463 (0.40439) Boundary_loss: 0.013896 (0.013896) Loss: 0.44852 (0.41829) +2025-09-13,16:05:47 | INFO | Train Epoch: 7 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.35065 (0.40413) Boundary_loss: 0.013899 (0.013896) Loss: 0.36455 (0.41802) +2025-09-13,16:06:17 | INFO | Train Epoch: 7 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38934 (0.40406) Boundary_loss: 0.013896 (0.013896) Loss: 0.40324 (0.41795) +2025-09-13,16:06:48 | INFO | Train Epoch: 7 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.35931 (0.40384) Boundary_loss: 0.013897 (0.013896) Loss: 0.37321 (0.41773) +2025-09-13,16:07:19 | INFO | Train Epoch: 7 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.39593 (0.40380) Boundary_loss: 0.013895 (0.013896) Loss: 0.40982 (0.41770) +2025-09-13,16:07:50 | INFO | Train Epoch: 7 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.34387 (0.40351) Boundary_loss: 0.013896 (0.013896) Loss: 0.35777 (0.41741) +2025-09-13,16:08:21 | INFO | Train Epoch: 7 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.42786 (0.40363) Boundary_loss: 0.013896 (0.013896) Loss: 0.44175 (0.41752) +2025-09-13,16:08:52 | INFO | Train Epoch: 7 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42488 (0.40373) Boundary_loss: 0.013896 (0.013896) Loss: 0.43878 (0.41762) +2025-09-13,16:09:23 | INFO | Train Epoch: 7 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.39440 (0.40368) Boundary_loss: 0.013898 (0.013896) Loss: 0.40830 (0.41758) +2025-09-13,16:09:54 | INFO | Train Epoch: 7 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.36865 (0.40352) Boundary_loss: 0.013896 (0.013896) Loss: 0.38254 (0.41741) +2025-09-13,16:10:24 | INFO | Train Epoch: 7 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.33254 (0.40318) Boundary_loss: 0.013898 (0.013896) Loss: 0.34643 (0.41708) +2025-09-13,16:10:55 | INFO | Train Epoch: 7 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.41134 (0.40322) Boundary_loss: 0.013895 (0.013896) Loss: 0.42523 (0.41712) +2025-09-13,16:11:26 | INFO | Train Epoch: 7 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.27070 (0.40260) Boundary_loss: 0.013898 (0.013896) Loss: 0.28460 (0.41650) +2025-09-13,16:11:57 | INFO | Train Epoch: 7 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40730 (0.40262) Boundary_loss: 0.013899 (0.013897) Loss: 0.42120 (0.41652) +2025-09-13,16:12:28 | INFO | Train Epoch: 7 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.44781 (0.40283) Boundary_loss: 0.013900 (0.013897) Loss: 0.46171 (0.41673) +2025-09-13,16:12:59 | INFO | Train Epoch: 7 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.49877 (0.40327) Boundary_loss: 0.013896 (0.013897) Loss: 0.51266 (0.41717) +2025-09-13,16:13:30 | INFO | Train Epoch: 7 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.35417 (0.40305) Boundary_loss: 0.013898 (0.013897) Loss: 0.36807 (0.41695) +2025-09-13,16:14:00 | INFO | Train Epoch: 7 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.37758 (0.40293) Boundary_loss: 0.013895 (0.013897) Loss: 0.39147 (0.41683) +2025-09-13,16:14:31 | INFO | Train Epoch: 7 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.34256 (0.40266) Boundary_loss: 0.013896 (0.013897) Loss: 0.35646 (0.41656) +2025-09-13,16:15:02 | INFO | Train Epoch: 7 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.31854 (0.40228) Boundary_loss: 0.013897 (0.013897) Loss: 0.33243 (0.41617) +2025-09-13,16:15:33 | INFO | Train Epoch: 7 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46811 (0.40257) Boundary_loss: 0.013896 (0.013897) Loss: 0.48200 (0.41647) +2025-09-13,16:16:04 | INFO | Train Epoch: 7 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.44554 (0.40277) Boundary_loss: 0.013897 (0.013897) Loss: 0.45943 (0.41666) +2025-09-13,16:16:35 | INFO | Train Epoch: 7 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.46328 (0.40304) Boundary_loss: 0.013897 (0.013897) Loss: 0.47717 (0.41693) +2025-09-13,16:17:06 | INFO | Train Epoch: 7 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42905 (0.40315) Boundary_loss: 0.013899 (0.013897) Loss: 0.44295 (0.41705) +2025-09-13,16:17:37 | INFO | Train Epoch: 7 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.40463 (0.40316) Boundary_loss: 0.013894 (0.013897) Loss: 0.41852 (0.41706) +2025-09-13,16:18:08 | INFO | Train Epoch: 7 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.41782 (0.40322) Boundary_loss: 0.013896 (0.013897) Loss: 0.43171 (0.41712) +2025-09-13,16:18:39 | INFO | Train Epoch: 7 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42685 (0.40333) Boundary_loss: 0.013897 (0.013897) Loss: 0.44075 (0.41722) +2025-09-13,16:19:09 | INFO | Train Epoch: 7 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46761 (0.40361) Boundary_loss: 0.013895 (0.013897) Loss: 0.48151 (0.41751) +2025-09-13,16:19:40 | INFO | Train Epoch: 7 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.34202 (0.40334) Boundary_loss: 0.013896 (0.013897) Loss: 0.35592 (0.41724) +2025-09-13,16:20:11 | INFO | Train Epoch: 7 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.33837 (0.40306) Boundary_loss: 0.013895 (0.013897) Loss: 0.35226 (0.41696) +2025-09-13,16:20:42 | INFO | Train Epoch: 7 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.41794 (0.40312) Boundary_loss: 0.013894 (0.013896) Loss: 0.43183 (0.41702) +2025-09-13,16:21:13 | INFO | Train Epoch: 7 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37590 (0.40301) Boundary_loss: 0.013897 (0.013897) Loss: 0.38980 (0.41690) +2025-09-13,16:21:44 | INFO | Train Epoch: 7 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.32670 (0.40268) Boundary_loss: 0.013909 (0.013897) Loss: 0.34060 (0.41658) +2025-09-13,16:22:15 | INFO | Train Epoch: 7 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.35125 (0.40246) Boundary_loss: 0.013898 (0.013897) Loss: 0.36515 (0.41636) +2025-09-13,16:22:45 | INFO | Train Epoch: 7 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.28676 (0.40197) Boundary_loss: 0.013897 (0.013897) Loss: 0.30066 (0.41587) +2025-09-13,16:23:16 | INFO | Train Epoch: 7 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.38205 (0.40189) Boundary_loss: 0.013896 (0.013897) Loss: 0.39594 (0.41578) +2025-09-13,16:23:47 | INFO | Train Epoch: 7 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.33446 (0.40160) Boundary_loss: 0.013896 (0.013897) Loss: 0.34835 (0.41550) +2025-09-13,16:24:18 | INFO | Train Epoch: 7 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.45817 (0.40184) Boundary_loss: 0.013896 (0.013897) Loss: 0.47206 (0.41574) +2025-09-13,16:24:49 | INFO | Train Epoch: 7 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.35262 (0.40164) Boundary_loss: 0.013897 (0.013897) Loss: 0.36651 (0.41553) +2025-09-13,16:25:20 | INFO | Train Epoch: 7 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.38920 (0.40158) Boundary_loss: 0.013894 (0.013897) Loss: 0.40309 (0.41548) +2025-09-13,16:25:51 | INFO | Train Epoch: 7 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.46356 (0.40184) Boundary_loss: 0.013896 (0.013897) Loss: 0.47745 (0.41574) +2025-09-13,16:26:22 | INFO | Train Epoch: 7 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.40329 (0.40185) Boundary_loss: 0.013897 (0.013897) Loss: 0.41719 (0.41574) +2025-09-13,16:26:52 | INFO | Train Epoch: 7 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.37317 (0.40173) Boundary_loss: 0.013895 (0.013897) Loss: 0.38707 (0.41563) +2025-09-13,16:27:23 | INFO | Train Epoch: 7 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.43394 (0.40186) Boundary_loss: 0.013897 (0.013897) Loss: 0.44783 (0.41576) +2025-09-13,16:27:54 | INFO | Train Epoch: 7 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.36697 (0.40172) Boundary_loss: 0.013897 (0.013897) Loss: 0.38087 (0.41562) +2025-09-13,16:28:25 | INFO | Train Epoch: 7 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.42307 (0.40180) Boundary_loss: 0.013895 (0.013897) Loss: 0.43697 (0.41570) +2025-09-13,16:28:56 | INFO | Train Epoch: 7 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.42998 (0.40192) Boundary_loss: 0.013896 (0.013897) Loss: 0.44387 (0.41582) +2025-09-13,16:29:27 | INFO | Train Epoch: 7 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.40585 (0.40193) Boundary_loss: 0.013894 (0.013897) Loss: 0.41974 (0.41583) +2025-09-13,16:29:58 | INFO | Train Epoch: 7 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.34259 (0.40170) Boundary_loss: 0.013896 (0.013897) Loss: 0.35649 (0.41559) +2025-09-13,16:30:28 | INFO | Train Epoch: 7 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.33742 (0.40144) Boundary_loss: 0.013896 (0.013897) Loss: 0.35131 (0.41534) +2025-09-13,16:30:59 | INFO | Train Epoch: 7 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.42047 (0.40152) Boundary_loss: 0.013895 (0.013897) Loss: 0.43437 (0.41541) +2025-09-13,16:31:30 | INFO | Train Epoch: 7 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37538 (0.40141) Boundary_loss: 0.013897 (0.013897) Loss: 0.38927 (0.41531) +2025-09-13,16:32:01 | INFO | Train Epoch: 7 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.42013 (0.40149) Boundary_loss: 0.013898 (0.013897) Loss: 0.43403 (0.41538) +2025-09-13,16:32:32 | INFO | Train Epoch: 7 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.36587 (0.40135) Boundary_loss: 0.013898 (0.013897) Loss: 0.37977 (0.41524) +2025-09-13,16:33:02 | INFO | Train Epoch: 7 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.36585 (0.40121) Boundary_loss: 0.013896 (0.013897) Loss: 0.37974 (0.41510) +2025-09-13,16:33:33 | INFO | Train Epoch: 7 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.45797 (0.40143) Boundary_loss: 0.013895 (0.013897) Loss: 0.47187 (0.41533) +2025-09-13,16:34:04 | INFO | Train Epoch: 7 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.39183 (0.40139) Boundary_loss: 0.013897 (0.013897) Loss: 0.40573 (0.41529) +2025-09-13,16:34:35 | INFO | Train Epoch: 7 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.44772 (0.40157) Boundary_loss: 0.013896 (0.013897) Loss: 0.46161 (0.41547) +2025-09-13,16:35:06 | INFO | Train Epoch: 7 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.39073 (0.40153) Boundary_loss: 0.013898 (0.013897) Loss: 0.40462 (0.41543) +2025-09-13,16:35:37 | INFO | Train Epoch: 7 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.40793 (0.40155) Boundary_loss: 0.013897 (0.013897) Loss: 0.42182 (0.41545) +2025-09-13,16:36:07 | INFO | Train Epoch: 7 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.39109 (0.40151) Boundary_loss: 0.013898 (0.013897) Loss: 0.40499 (0.41541) +2025-09-13,16:36:38 | INFO | Train Epoch: 7 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35208 (0.40133) Boundary_loss: 0.013895 (0.013897) Loss: 0.36598 (0.41522) +2025-09-13,16:37:09 | INFO | Train Epoch: 7 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40653 (0.40135) Boundary_loss: 0.013896 (0.013897) Loss: 0.42042 (0.41524) +2025-09-13,16:37:40 | INFO | Train Epoch: 7 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.33830 (0.40111) Boundary_loss: 0.013898 (0.013897) Loss: 0.35220 (0.41500) +2025-09-13,16:38:11 | INFO | Train Epoch: 7 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.37237 (0.40100) Boundary_loss: 0.013899 (0.013897) Loss: 0.38627 (0.41490) +2025-09-13,16:38:42 | INFO | Train Epoch: 7 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.42635 (0.40109) Boundary_loss: 0.013897 (0.013897) Loss: 0.44024 (0.41499) +2025-09-13,16:39:13 | INFO | Train Epoch: 7 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.33759 (0.40086) Boundary_loss: 0.013896 (0.013897) Loss: 0.35148 (0.41475) +2025-09-13,16:39:44 | INFO | Train Epoch: 7 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.34916 (0.40067) Boundary_loss: 0.013898 (0.013897) Loss: 0.36306 (0.41456) +2025-09-13,16:40:14 | INFO | Train Epoch: 7 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.44398 (0.40083) Boundary_loss: 0.013895 (0.013897) Loss: 0.45787 (0.41472) +2025-09-13,16:40:45 | INFO | Train Epoch: 7 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.42484 (0.40091) Boundary_loss: 0.013895 (0.013897) Loss: 0.43873 (0.41481) +2025-09-13,16:41:16 | INFO | Train Epoch: 7 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.33755 (0.40068) Boundary_loss: 0.013897 (0.013897) Loss: 0.35145 (0.41458) +2025-09-13,16:41:47 | INFO | Train Epoch: 7 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.42526 (0.40077) Boundary_loss: 0.013896 (0.013897) Loss: 0.43916 (0.41467) +2025-09-13,16:42:18 | INFO | Train Epoch: 7 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.43894 (0.40091) Boundary_loss: 0.013895 (0.013897) Loss: 0.45283 (0.41481) +2025-09-13,16:42:49 | INFO | Train Epoch: 7 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.36440 (0.40078) Boundary_loss: 0.013896 (0.013897) Loss: 0.37829 (0.41467) +2025-09-13,16:43:20 | INFO | Train Epoch: 7 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.37762 (0.40069) Boundary_loss: 0.013901 (0.013897) Loss: 0.39152 (0.41459) +2025-09-13,16:43:50 | INFO | Train Epoch: 7 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.33538 (0.40046) Boundary_loss: 0.013897 (0.013897) Loss: 0.34928 (0.41435) +2025-09-13,16:44:21 | INFO | Train Epoch: 7 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.36918 (0.40035) Boundary_loss: 0.013897 (0.013897) Loss: 0.38307 (0.41424) +2025-09-13,16:44:52 | INFO | Train Epoch: 7 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.48024 (0.40063) Boundary_loss: 0.013896 (0.013897) Loss: 0.49414 (0.41453) +2025-09-13,16:45:23 | INFO | Train Epoch: 7 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.44541 (0.40079) Boundary_loss: 0.013896 (0.013897) Loss: 0.45930 (0.41469) +2025-09-13,16:45:54 | INFO | Train Epoch: 7 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.41668 (0.40085) Boundary_loss: 0.013896 (0.013897) Loss: 0.43057 (0.41475) +2025-09-13,16:46:25 | INFO | Train Epoch: 7 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.28638 (0.40044) Boundary_loss: 0.013895 (0.013897) Loss: 0.30027 (0.41434) +2025-09-13,16:46:56 | INFO | Train Epoch: 7 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.40575 (0.40046) Boundary_loss: 0.013898 (0.013897) Loss: 0.41965 (0.41436) +2025-09-13,16:47:27 | INFO | Train Epoch: 7 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.41351 (0.40051) Boundary_loss: 0.013897 (0.013897) Loss: 0.42741 (0.41440) +2025-09-13,16:47:58 | INFO | Train Epoch: 7 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.37402 (0.40041) Boundary_loss: 0.013896 (0.013897) Loss: 0.38792 (0.41431) +2025-09-13,16:48:29 | INFO | Train Epoch: 7 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.39006 (0.40038) Boundary_loss: 0.013899 (0.013897) Loss: 0.40396 (0.41427) +2025-09-13,16:49:00 | INFO | Train Epoch: 7 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36278 (0.40025) Boundary_loss: 0.013897 (0.013897) Loss: 0.37668 (0.41414) +2025-09-13,16:49:31 | INFO | Train Epoch: 7 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.43200 (0.40036) Boundary_loss: 0.013895 (0.013897) Loss: 0.44589 (0.41425) +2025-09-13,16:50:01 | INFO | Train Epoch: 7 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.36189 (0.40022) Boundary_loss: 0.013896 (0.013897) Loss: 0.37578 (0.41412) +2025-09-13,16:50:32 | INFO | Train Epoch: 7 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.35736 (0.40008) Boundary_loss: 0.013897 (0.013897) Loss: 0.37125 (0.41397) +2025-09-13,16:51:03 | INFO | Train Epoch: 7 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.37012 (0.39997) Boundary_loss: 0.013895 (0.013897) Loss: 0.38401 (0.41387) +2025-09-13,16:51:34 | INFO | Train Epoch: 7 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40531 (0.39999) Boundary_loss: 0.013898 (0.013897) Loss: 0.41921 (0.41389) +2025-09-13,16:52:05 | INFO | Train Epoch: 7 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.48737 (0.40029) Boundary_loss: 0.013896 (0.013897) Loss: 0.50127 (0.41419) +2025-09-13,16:52:36 | INFO | Train Epoch: 7 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.34418 (0.40010) Boundary_loss: 0.013898 (0.013897) Loss: 0.35808 (0.41400) +2025-09-13,16:53:07 | INFO | Train Epoch: 7 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.38031 (0.40003) Boundary_loss: 0.013896 (0.013897) Loss: 0.39421 (0.41393) +2025-09-13,16:53:38 | INFO | Train Epoch: 7 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.36624 (0.39992) Boundary_loss: 0.013897 (0.013897) Loss: 0.38013 (0.41381) +2025-09-13,16:54:09 | INFO | Train Epoch: 7 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.38377 (0.39986) Boundary_loss: 0.013896 (0.013897) Loss: 0.39767 (0.41376) +2025-09-13,16:54:40 | INFO | Train Epoch: 7 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.38297 (0.39981) Boundary_loss: 0.013895 (0.013897) Loss: 0.39687 (0.41370) +2025-09-13,16:55:10 | INFO | Train Epoch: 7 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.47606 (0.40006) Boundary_loss: 0.013895 (0.013897) Loss: 0.48995 (0.41396) +2025-09-13,16:55:41 | INFO | Train Epoch: 7 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.36549 (0.39995) Boundary_loss: 0.013896 (0.013897) Loss: 0.37938 (0.41384) +2025-09-13,16:56:12 | INFO | Train Epoch: 7 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.45396 (0.40013) Boundary_loss: 0.013897 (0.013897) Loss: 0.46786 (0.41402) +2025-09-13,16:56:43 | INFO | Train Epoch: 7 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.42337 (0.40020) Boundary_loss: 0.013901 (0.013897) Loss: 0.43727 (0.41410) +2025-09-13,16:57:14 | INFO | Train Epoch: 7 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42186 (0.40027) Boundary_loss: 0.013896 (0.013897) Loss: 0.43576 (0.41417) +2025-09-13,16:57:45 | INFO | Train Epoch: 7 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.40390 (0.40029) Boundary_loss: 0.013895 (0.013897) Loss: 0.41779 (0.41418) +2025-09-13,16:58:16 | INFO | Train Epoch: 7 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.29662 (0.39995) Boundary_loss: 0.013896 (0.013897) Loss: 0.31051 (0.41384) +2025-09-13,16:58:47 | INFO | Train Epoch: 7 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.34712 (0.39977) Boundary_loss: 0.013898 (0.013897) Loss: 0.36102 (0.41367) +2025-09-13,16:59:18 | INFO | Train Epoch: 7 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.48463 (0.40005) Boundary_loss: 0.013896 (0.013897) Loss: 0.49853 (0.41395) +2025-09-13,16:59:48 | INFO | Train Epoch: 7 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.45827 (0.40024) Boundary_loss: 0.013898 (0.013897) Loss: 0.47217 (0.41414) +2025-09-13,17:00:19 | INFO | Train Epoch: 7 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.43906 (0.40037) Boundary_loss: 0.013896 (0.013897) Loss: 0.45295 (0.41426) +2025-09-13,17:00:50 | INFO | Train Epoch: 7 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.37398 (0.40028) Boundary_loss: 0.013896 (0.013897) Loss: 0.38788 (0.41418) +2025-09-13,17:01:21 | INFO | Train Epoch: 7 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.33340 (0.40007) Boundary_loss: 0.013898 (0.013897) Loss: 0.34730 (0.41396) +2025-09-13,17:01:52 | INFO | Train Epoch: 7 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.37890 (0.40000) Boundary_loss: 0.013897 (0.013897) Loss: 0.39280 (0.41389) +2025-09-13,17:02:23 | INFO | Train Epoch: 7 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.45243 (0.40016) Boundary_loss: 0.013897 (0.013897) Loss: 0.46633 (0.41406) +2025-09-13,17:02:54 | INFO | Train Epoch: 7 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.40836 (0.40019) Boundary_loss: 0.013896 (0.013897) Loss: 0.42226 (0.41409) +2025-09-13,17:03:25 | INFO | Train Epoch: 7 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44726 (0.40034) Boundary_loss: 0.013897 (0.013897) Loss: 0.46116 (0.41424) +2025-09-13,17:03:56 | INFO | Train Epoch: 7 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.41272 (0.40038) Boundary_loss: 0.013898 (0.013897) Loss: 0.42662 (0.41428) +2025-09-13,17:04:27 | INFO | Train Epoch: 7 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.41355 (0.40042) Boundary_loss: 0.013899 (0.013897) Loss: 0.42745 (0.41432) +2025-09-13,17:04:58 | INFO | Train Epoch: 7 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.41854 (0.40048) Boundary_loss: 0.013896 (0.013897) Loss: 0.43243 (0.41437) +2025-09-13,17:05:28 | INFO | Train Epoch: 7 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.38213 (0.40042) Boundary_loss: 0.013900 (0.013897) Loss: 0.39603 (0.41432) +2025-09-13,17:05:59 | INFO | Train Epoch: 7 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40539 (0.40044) Boundary_loss: 0.013897 (0.013897) Loss: 0.41928 (0.41433) +2025-09-13,17:06:30 | INFO | Train Epoch: 7 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.48883 (0.40071) Boundary_loss: 0.013899 (0.013897) Loss: 0.50273 (0.41461) +2025-09-13,17:07:01 | INFO | Train Epoch: 7 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.49649 (0.40101) Boundary_loss: 0.013896 (0.013897) Loss: 0.51039 (0.41491) +2025-09-13,17:07:32 | INFO | Train Epoch: 7 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.44623 (0.40115) Boundary_loss: 0.013895 (0.013897) Loss: 0.46013 (0.41505) +2025-09-13,17:08:03 | INFO | Train Epoch: 7 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.41491 (0.40119) Boundary_loss: 0.013898 (0.013897) Loss: 0.42881 (0.41509) +2025-09-13,17:08:34 | INFO | Train Epoch: 7 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.40581 (0.40121) Boundary_loss: 0.013895 (0.013897) Loss: 0.41971 (0.41510) +2025-09-13,17:09:05 | INFO | Train Epoch: 7 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.36676 (0.40110) Boundary_loss: 0.013896 (0.013897) Loss: 0.38066 (0.41500) +2025-09-13,17:09:36 | INFO | Train Epoch: 7 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.46159 (0.40128) Boundary_loss: 0.013898 (0.013897) Loss: 0.47549 (0.41518) +2025-09-13,17:10:07 | INFO | Train Epoch: 7 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.45312 (0.40144) Boundary_loss: 0.013898 (0.013897) Loss: 0.46702 (0.41534) +2025-09-13,17:10:38 | INFO | Train Epoch: 7 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.41029 (0.40147) Boundary_loss: 0.013896 (0.013897) Loss: 0.42418 (0.41537) +2025-09-13,17:11:09 | INFO | Train Epoch: 7 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.33309 (0.40126) Boundary_loss: 0.013897 (0.013897) Loss: 0.34699 (0.41516) +2025-09-13,17:11:40 | INFO | Train Epoch: 7 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.37497 (0.40118) Boundary_loss: 0.013895 (0.013897) Loss: 0.38886 (0.41508) +2025-09-13,17:12:10 | INFO | Train Epoch: 7 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.41861 (0.40124) Boundary_loss: 0.013895 (0.013897) Loss: 0.43251 (0.41513) +2025-09-13,17:12:41 | INFO | Train Epoch: 7 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.39003 (0.40120) Boundary_loss: 0.013897 (0.013897) Loss: 0.40392 (0.41510) +2025-09-13,17:13:12 | INFO | Train Epoch: 7 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.39383 (0.40118) Boundary_loss: 0.013894 (0.013897) Loss: 0.40773 (0.41508) +2025-09-13,17:13:43 | INFO | Train Epoch: 7 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.41810 (0.40123) Boundary_loss: 0.013895 (0.013897) Loss: 0.43199 (0.41513) +2025-09-13,17:14:14 | INFO | Train Epoch: 7 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.40043 (0.40123) Boundary_loss: 0.013897 (0.013897) Loss: 0.41433 (0.41512) +2025-09-13,17:14:45 | INFO | Train Epoch: 7 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.29458 (0.40091) Boundary_loss: 0.013895 (0.013897) Loss: 0.30847 (0.41481) +2025-09-13,17:15:16 | INFO | Train Epoch: 7 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.43177 (0.40100) Boundary_loss: 0.013895 (0.013897) Loss: 0.44566 (0.41490) +2025-09-13,17:15:46 | INFO | Train Epoch: 7 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.31171 (0.40074) Boundary_loss: 0.013897 (0.013897) Loss: 0.32561 (0.41464) +2025-09-13,17:16:17 | INFO | Train Epoch: 7 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.30748 (0.40047) Boundary_loss: 0.013901 (0.013897) Loss: 0.32138 (0.41436) +2025-09-13,17:16:48 | INFO | Train Epoch: 7 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.38954 (0.40043) Boundary_loss: 0.013898 (0.013897) Loss: 0.40344 (0.41433) +2025-09-13,17:17:19 | INFO | Train Epoch: 7 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.32965 (0.40023) Boundary_loss: 0.013896 (0.013897) Loss: 0.34355 (0.41412) +2025-09-13,17:17:50 | INFO | Train Epoch: 7 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37061 (0.40014) Boundary_loss: 0.013896 (0.013897) Loss: 0.38450 (0.41404) +2025-09-13,17:18:21 | INFO | Train Epoch: 7 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.49745 (0.40042) Boundary_loss: 0.013897 (0.013897) Loss: 0.51135 (0.41432) +2025-09-13,17:18:52 | INFO | Train Epoch: 7 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.45042 (0.40057) Boundary_loss: 0.013897 (0.013897) Loss: 0.46432 (0.41446) +2025-09-13,17:19:23 | INFO | Train Epoch: 7 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.35409 (0.40043) Boundary_loss: 0.013903 (0.013897) Loss: 0.36799 (0.41433) +2025-09-13,17:19:54 | INFO | Train Epoch: 7 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.37632 (0.40036) Boundary_loss: 0.013896 (0.013897) Loss: 0.39021 (0.41426) +2025-09-13,17:20:24 | INFO | Train Epoch: 7 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.45693 (0.40053) Boundary_loss: 0.013897 (0.013897) Loss: 0.47082 (0.41442) +2025-09-13,17:20:55 | INFO | Train Epoch: 7 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.41844 (0.40058) Boundary_loss: 0.013897 (0.013897) Loss: 0.43233 (0.41447) +2025-09-13,17:21:26 | INFO | Train Epoch: 7 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.40688 (0.40060) Boundary_loss: 0.013899 (0.013897) Loss: 0.42078 (0.41449) +2025-09-13,17:21:57 | INFO | Train Epoch: 7 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.35891 (0.40048) Boundary_loss: 0.013895 (0.013897) Loss: 0.37281 (0.41437) +2025-09-13,17:22:28 | INFO | Train Epoch: 7 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.34021 (0.40031) Boundary_loss: 0.013897 (0.013897) Loss: 0.35411 (0.41420) +2025-09-13,17:22:59 | INFO | Train Epoch: 7 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.33272 (0.40011) Boundary_loss: 0.013895 (0.013897) Loss: 0.34661 (0.41401) +2025-09-13,17:23:29 | INFO | Train Epoch: 7 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.39290 (0.40009) Boundary_loss: 0.013896 (0.013897) Loss: 0.40679 (0.41399) +2025-09-13,17:24:00 | INFO | Train Epoch: 7 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.41109 (0.40012) Boundary_loss: 0.013897 (0.013897) Loss: 0.42499 (0.41402) +2025-09-13,17:24:31 | INFO | Train Epoch: 7 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.40928 (0.40015) Boundary_loss: 0.013897 (0.013897) Loss: 0.42318 (0.41405) +2025-09-13,17:25:02 | INFO | Train Epoch: 7 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.39239 (0.40013) Boundary_loss: 0.013897 (0.013897) Loss: 0.40628 (0.41403) +2025-09-13,17:25:33 | INFO | Train Epoch: 7 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.39664 (0.40012) Boundary_loss: 0.013895 (0.013897) Loss: 0.41053 (0.41402) +2025-09-13,17:26:04 | INFO | Train Epoch: 7 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.43529 (0.40022) Boundary_loss: 0.013895 (0.013897) Loss: 0.44919 (0.41411) +2025-09-13,17:26:35 | INFO | Train Epoch: 7 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.43256 (0.40031) Boundary_loss: 0.013894 (0.013897) Loss: 0.44646 (0.41420) +2025-09-13,17:27:06 | INFO | Train Epoch: 7 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.47714 (0.40052) Boundary_loss: 0.013895 (0.013897) Loss: 0.49103 (0.41442) +2025-09-13,17:27:37 | INFO | Train Epoch: 7 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.42834 (0.40060) Boundary_loss: 0.013897 (0.013897) Loss: 0.44224 (0.41449) +2025-09-13,17:28:08 | INFO | Train Epoch: 7 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40007 (0.40060) Boundary_loss: 0.013897 (0.013897) Loss: 0.41397 (0.41449) +2025-09-13,17:28:39 | INFO | Train Epoch: 7 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.35547 (0.40047) Boundary_loss: 0.013895 (0.013897) Loss: 0.36937 (0.41437) +2025-09-13,17:29:10 | INFO | Train Epoch: 7 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.35478 (0.40035) Boundary_loss: 0.013897 (0.013897) Loss: 0.36868 (0.41424) +2025-09-13,17:29:41 | INFO | Train Epoch: 7 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.37603 (0.40028) Boundary_loss: 0.013896 (0.013897) Loss: 0.38993 (0.41418) +2025-09-13,17:30:12 | INFO | Train Epoch: 7 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.49978 (0.40055) Boundary_loss: 0.013897 (0.013897) Loss: 0.51368 (0.41445) +2025-09-13,17:30:42 | INFO | Train Epoch: 7 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.40407 (0.40056) Boundary_loss: 0.013896 (0.013897) Loss: 0.41796 (0.41446) +2025-09-13,17:31:13 | INFO | Train Epoch: 7 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.35058 (0.40042) Boundary_loss: 0.013896 (0.013897) Loss: 0.36447 (0.41432) +2025-09-13,17:31:44 | INFO | Train Epoch: 7 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38719 (0.40039) Boundary_loss: 0.013897 (0.013897) Loss: 0.40109 (0.41429) +2025-09-13,17:32:15 | INFO | Train Epoch: 7 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36759 (0.40030) Boundary_loss: 0.013897 (0.013897) Loss: 0.38149 (0.41420) +2025-09-13,17:32:46 | INFO | Train Epoch: 7 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.44081 (0.40041) Boundary_loss: 0.013896 (0.013897) Loss: 0.45470 (0.41431) +2025-09-13,17:33:17 | INFO | Train Epoch: 7 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.44681 (0.40053) Boundary_loss: 0.013896 (0.013897) Loss: 0.46070 (0.41443) +2025-09-13,17:33:47 | INFO | Train Epoch: 7 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.40222 (0.40054) Boundary_loss: 0.013896 (0.013897) Loss: 0.41612 (0.41443) +2025-09-13,17:34:18 | INFO | Train Epoch: 7 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.42874 (0.40061) Boundary_loss: 0.013896 (0.013897) Loss: 0.44263 (0.41451) +2025-09-13,17:34:49 | INFO | Train Epoch: 7 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42493 (0.40068) Boundary_loss: 0.013896 (0.013897) Loss: 0.43883 (0.41457) +2025-09-13,17:35:20 | INFO | Train Epoch: 7 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.44042 (0.40078) Boundary_loss: 0.013897 (0.013897) Loss: 0.45431 (0.41468) +2025-09-13,17:35:51 | INFO | Train Epoch: 7 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.34658 (0.40064) Boundary_loss: 0.013895 (0.013897) Loss: 0.36048 (0.41454) +2025-09-13,17:36:22 | INFO | Train Epoch: 7 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.34251 (0.40049) Boundary_loss: 0.013897 (0.013897) Loss: 0.35641 (0.41438) +2025-09-13,17:36:53 | INFO | Train Epoch: 7 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.37818 (0.40043) Boundary_loss: 0.013896 (0.013897) Loss: 0.39208 (0.41432) +2025-09-13,17:37:24 | INFO | Train Epoch: 7 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.37071 (0.40035) Boundary_loss: 0.013896 (0.013897) Loss: 0.38461 (0.41425) +2025-09-13,17:37:55 | INFO | Train Epoch: 7 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.42129 (0.40040) Boundary_loss: 0.013896 (0.013897) Loss: 0.43519 (0.41430) +2025-09-13,17:38:26 | INFO | Train Epoch: 7 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.39886 (0.40040) Boundary_loss: 0.013895 (0.013897) Loss: 0.41276 (0.41430) +2025-09-13,17:38:57 | INFO | Train Epoch: 7 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.45212 (0.40054) Boundary_loss: 0.013899 (0.013897) Loss: 0.46602 (0.41443) +2025-09-13,17:39:28 | INFO | Train Epoch: 7 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.49903 (0.40079) Boundary_loss: 0.013897 (0.013897) Loss: 0.51293 (0.41469) +2025-09-13,17:39:59 | INFO | Train Epoch: 7 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.43454 (0.40088) Boundary_loss: 0.013896 (0.013897) Loss: 0.44844 (0.41478) +2025-09-13,17:40:30 | INFO | Train Epoch: 7 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.42886 (0.40095) Boundary_loss: 0.013896 (0.013897) Loss: 0.44275 (0.41485) +2025-09-13,17:41:01 | INFO | Train Epoch: 7 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.41369 (0.40098) Boundary_loss: 0.013895 (0.013897) Loss: 0.42758 (0.41488) +2025-09-13,17:41:32 | INFO | Train Epoch: 7 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.38288 (0.40094) Boundary_loss: 0.013896 (0.013897) Loss: 0.39677 (0.41483) +2025-09-13,17:42:03 | INFO | Train Epoch: 7 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.44972 (0.40106) Boundary_loss: 0.013895 (0.013897) Loss: 0.46361 (0.41496) +2025-09-13,17:42:35 | INFO | Train Epoch: 7 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.39596 (0.40105) Boundary_loss: 0.013895 (0.013897) Loss: 0.40986 (0.41495) +2025-09-13,17:43:05 | INFO | Train Epoch: 7 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.38189 (0.40100) Boundary_loss: 0.013896 (0.013897) Loss: 0.39579 (0.41490) +2025-09-13,17:43:36 | INFO | Train Epoch: 7 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.44254 (0.40111) Boundary_loss: 0.013896 (0.013897) Loss: 0.45643 (0.41500) +2025-09-13,17:44:07 | INFO | Train Epoch: 7 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.38988 (0.40108) Boundary_loss: 0.013897 (0.013897) Loss: 0.40378 (0.41497) +2025-09-13,17:44:38 | INFO | Train Epoch: 7 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.34510 (0.40094) Boundary_loss: 0.013898 (0.013897) Loss: 0.35900 (0.41483) +2025-09-13,17:45:08 | INFO | Train Epoch: 7 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.39600 (0.40092) Boundary_loss: 0.013896 (0.013897) Loss: 0.40989 (0.41482) +2025-09-13,17:45:39 | INFO | Train Epoch: 7 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.36649 (0.40084) Boundary_loss: 0.013897 (0.013897) Loss: 0.38038 (0.41473) +2025-09-13,17:46:10 | INFO | Train Epoch: 7 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.34685 (0.40070) Boundary_loss: 0.013896 (0.013897) Loss: 0.36074 (0.41460) +2025-09-13,17:46:41 | INFO | Train Epoch: 7 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.35628 (0.40059) Boundary_loss: 0.013897 (0.013897) Loss: 0.37017 (0.41449) +2025-09-13,17:47:12 | INFO | Train Epoch: 7 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.34232 (0.40044) Boundary_loss: 0.013896 (0.013897) Loss: 0.35622 (0.41434) +2025-09-13,17:47:43 | INFO | Train Epoch: 7 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.42258 (0.40050) Boundary_loss: 0.013898 (0.013897) Loss: 0.43648 (0.41440) +2025-09-13,17:48:14 | INFO | Train Epoch: 7 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.41120 (0.40053) Boundary_loss: 0.013896 (0.013897) Loss: 0.42510 (0.41442) +2025-09-13,17:48:45 | INFO | Train Epoch: 7 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.36981 (0.40045) Boundary_loss: 0.013896 (0.013897) Loss: 0.38370 (0.41435) +2025-09-13,17:49:15 | INFO | Train Epoch: 7 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.37377 (0.40038) Boundary_loss: 0.013897 (0.013897) Loss: 0.38767 (0.41428) +2025-09-13,17:49:46 | INFO | Train Epoch: 7 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.39207 (0.40036) Boundary_loss: 0.013895 (0.013897) Loss: 0.40596 (0.41426) +2025-09-13,17:50:17 | INFO | Train Epoch: 7 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.39917 (0.40036) Boundary_loss: 0.013896 (0.013897) Loss: 0.41306 (0.41426) +2025-09-13,17:50:48 | INFO | Train Epoch: 7 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.43007 (0.40043) Boundary_loss: 0.013897 (0.013897) Loss: 0.44396 (0.41433) +2025-09-13,17:51:19 | INFO | Train Epoch: 7 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.42378 (0.40049) Boundary_loss: 0.013896 (0.013897) Loss: 0.43768 (0.41439) +2025-09-13,17:51:50 | INFO | Train Epoch: 7 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.36028 (0.40039) Boundary_loss: 0.013896 (0.013897) Loss: 0.37418 (0.41429) +2025-09-13,17:52:21 | INFO | Train Epoch: 7 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.37130 (0.40032) Boundary_loss: 0.013895 (0.013897) Loss: 0.38519 (0.41422) +2025-09-13,17:52:52 | INFO | Train Epoch: 7 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.37697 (0.40026) Boundary_loss: 0.013898 (0.013897) Loss: 0.39087 (0.41416) +2025-09-13,17:53:23 | INFO | Train Epoch: 7 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.37780 (0.40021) Boundary_loss: 0.013895 (0.013897) Loss: 0.39169 (0.41411) +2025-09-13,17:53:53 | INFO | Train Epoch: 7 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.38924 (0.40018) Boundary_loss: 0.013895 (0.013897) Loss: 0.40314 (0.41408) +2025-09-13,17:54:24 | INFO | Train Epoch: 7 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.37718 (0.40013) Boundary_loss: 0.013896 (0.013897) Loss: 0.39108 (0.41402) +2025-09-13,17:54:55 | INFO | Train Epoch: 7 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.40410 (0.40014) Boundary_loss: 0.013897 (0.013897) Loss: 0.41800 (0.41403) +2025-09-13,17:55:25 | INFO | Train Epoch: 7 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.39893 (0.40013) Boundary_loss: 0.013897 (0.013897) Loss: 0.41282 (0.41403) +2025-09-13,17:55:56 | INFO | Train Epoch: 7 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.39628 (0.40013) Boundary_loss: 0.013898 (0.013897) Loss: 0.41018 (0.41402) +2025-09-13,17:56:27 | INFO | Train Epoch: 7 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.34592 (0.40000) Boundary_loss: 0.013895 (0.013897) Loss: 0.35981 (0.41389) +2025-09-13,17:56:58 | INFO | Train Epoch: 7 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.41651 (0.40004) Boundary_loss: 0.013897 (0.013897) Loss: 0.43040 (0.41393) +2025-09-13,17:57:29 | INFO | Train Epoch: 7 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.37655 (0.39998) Boundary_loss: 0.013896 (0.013897) Loss: 0.39044 (0.41388) +2025-09-13,17:58:00 | INFO | Train Epoch: 7 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.39400 (0.39996) Boundary_loss: 0.013897 (0.013897) Loss: 0.40790 (0.41386) +2025-09-13,17:58:31 | INFO | Train Epoch: 7 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.44503 (0.40007) Boundary_loss: 0.013897 (0.013897) Loss: 0.45892 (0.41397) +2025-09-13,17:59:02 | INFO | Train Epoch: 7 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.41596 (0.40011) Boundary_loss: 0.013896 (0.013897) Loss: 0.42986 (0.41401) +2025-09-13,17:59:33 | INFO | Train Epoch: 7 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.45165 (0.40023) Boundary_loss: 0.013895 (0.013897) Loss: 0.46554 (0.41413) +2025-09-13,18:00:04 | INFO | Train Epoch: 7 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.31572 (0.40003) Boundary_loss: 0.013897 (0.013897) Loss: 0.32962 (0.41393) +2025-09-13,18:00:35 | INFO | Train Epoch: 7 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.41438 (0.40007) Boundary_loss: 0.013896 (0.013897) Loss: 0.42828 (0.41396) +2025-09-13,18:01:06 | INFO | Train Epoch: 7 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.34603 (0.39994) Boundary_loss: 0.013899 (0.013897) Loss: 0.35992 (0.41384) +2025-09-13,18:01:36 | INFO | Train Epoch: 7 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.33950 (0.39980) Boundary_loss: 0.013897 (0.013897) Loss: 0.35339 (0.41369) +2025-09-13,18:02:07 | INFO | Train Epoch: 7 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.42526 (0.39986) Boundary_loss: 0.013897 (0.013897) Loss: 0.43915 (0.41375) +2025-09-13,18:02:38 | INFO | Train Epoch: 7 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.33165 (0.39970) Boundary_loss: 0.013897 (0.013897) Loss: 0.34555 (0.41360) +2025-09-13,18:03:09 | INFO | Train Epoch: 7 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.45616 (0.39983) Boundary_loss: 0.013895 (0.013897) Loss: 0.47005 (0.41373) +2025-09-13,18:03:40 | INFO | Train Epoch: 7 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.33998 (0.39969) Boundary_loss: 0.013897 (0.013897) Loss: 0.35388 (0.41359) +2025-09-13,18:04:11 | INFO | Train Epoch: 7 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.40983 (0.39971) Boundary_loss: 0.013896 (0.013897) Loss: 0.42372 (0.41361) +2025-09-13,18:04:41 | INFO | Train Epoch: 7 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.41230 (0.39974) Boundary_loss: 0.013896 (0.013897) Loss: 0.42619 (0.41364) +2025-09-13,18:05:12 | INFO | Train Epoch: 7 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.44499 (0.39985) Boundary_loss: 0.013894 (0.013897) Loss: 0.45889 (0.41374) +2025-09-13,18:05:43 | INFO | Train Epoch: 7 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.40775 (0.39987) Boundary_loss: 0.013898 (0.013897) Loss: 0.42165 (0.41376) +2025-09-13,18:06:14 | INFO | Train Epoch: 7 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.45068 (0.39998) Boundary_loss: 0.013895 (0.013897) Loss: 0.46457 (0.41388) +2025-09-13,18:06:45 | INFO | Train Epoch: 7 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.35664 (0.39988) Boundary_loss: 0.013896 (0.013897) Loss: 0.37054 (0.41378) +2025-09-13,18:07:16 | INFO | Train Epoch: 7 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.31664 (0.39969) Boundary_loss: 0.013897 (0.013897) Loss: 0.33054 (0.41359) +2025-09-13,18:07:47 | INFO | Train Epoch: 7 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.42715 (0.39976) Boundary_loss: 0.013898 (0.013897) Loss: 0.44105 (0.41365) +2025-09-13,18:08:18 | INFO | Train Epoch: 7 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.36950 (0.39969) Boundary_loss: 0.013895 (0.013897) Loss: 0.38339 (0.41358) +2025-09-13,18:08:49 | INFO | Train Epoch: 7 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.37024 (0.39962) Boundary_loss: 0.013896 (0.013897) Loss: 0.38414 (0.41352) +2025-09-13,18:09:20 | INFO | Train Epoch: 7 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.44081 (0.39971) Boundary_loss: 0.013896 (0.013897) Loss: 0.45471 (0.41361) +2025-09-13,18:09:51 | INFO | Train Epoch: 7 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.33344 (0.39956) Boundary_loss: 0.013897 (0.013897) Loss: 0.34733 (0.41346) +2025-09-13,18:10:22 | INFO | Train Epoch: 7 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.34053 (0.39943) Boundary_loss: 0.013896 (0.013897) Loss: 0.35443 (0.41333) +2025-09-13,18:10:53 | INFO | Train Epoch: 7 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.43501 (0.39951) Boundary_loss: 0.013896 (0.013897) Loss: 0.44891 (0.41341) +2025-09-13,18:11:24 | INFO | Train Epoch: 7 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.42505 (0.39957) Boundary_loss: 0.013902 (0.013897) Loss: 0.43895 (0.41346) +2025-09-13,18:11:55 | INFO | Train Epoch: 7 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.46806 (0.39972) Boundary_loss: 0.013898 (0.013897) Loss: 0.48196 (0.41362) +2025-09-13,18:12:25 | INFO | Train Epoch: 7 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.44030 (0.39981) Boundary_loss: 0.013895 (0.013897) Loss: 0.45419 (0.41371) +2025-09-13,18:12:56 | INFO | Train Epoch: 7 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.37490 (0.39976) Boundary_loss: 0.013896 (0.013897) Loss: 0.38879 (0.41365) +2025-09-13,18:13:27 | INFO | Train Epoch: 7 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.37026 (0.39969) Boundary_loss: 0.013896 (0.013897) Loss: 0.38416 (0.41359) +2025-09-13,18:13:58 | INFO | Train Epoch: 7 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.41214 (0.39972) Boundary_loss: 0.013898 (0.013897) Loss: 0.42603 (0.41361) +2025-09-13,18:14:29 | INFO | Train Epoch: 7 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.40031 (0.39972) Boundary_loss: 0.013895 (0.013897) Loss: 0.41421 (0.41362) +2025-09-13,18:15:00 | INFO | Train Epoch: 7 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.44133 (0.39981) Boundary_loss: 0.013897 (0.013897) Loss: 0.45523 (0.41371) +2025-09-13,18:15:31 | INFO | Train Epoch: 7 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.40751 (0.39983) Boundary_loss: 0.013896 (0.013897) Loss: 0.42140 (0.41372) +2025-09-13,18:16:02 | INFO | Train Epoch: 7 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.41544 (0.39986) Boundary_loss: 0.013896 (0.013897) Loss: 0.42933 (0.41376) +2025-09-13,18:16:33 | INFO | Train Epoch: 7 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.34266 (0.39974) Boundary_loss: 0.013895 (0.013897) Loss: 0.35656 (0.41363) +2025-09-13,18:17:04 | INFO | Train Epoch: 7 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.47610 (0.39990) Boundary_loss: 0.013897 (0.013897) Loss: 0.48999 (0.41380) +2025-09-13,18:17:35 | INFO | Train Epoch: 7 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.31704 (0.39972) Boundary_loss: 0.013896 (0.013897) Loss: 0.33094 (0.41362) +2025-09-13,18:18:06 | INFO | Train Epoch: 7 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.35688 (0.39963) Boundary_loss: 0.013896 (0.013897) Loss: 0.37078 (0.41353) +2025-09-13,18:18:37 | INFO | Train Epoch: 7 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.43188 (0.39970) Boundary_loss: 0.013896 (0.013897) Loss: 0.44578 (0.41360) +2025-09-13,18:19:07 | INFO | Train Epoch: 7 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.31365 (0.39951) Boundary_loss: 0.013895 (0.013896) Loss: 0.32754 (0.41341) +2025-09-13,18:19:38 | INFO | Train Epoch: 7 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.39173 (0.39950) Boundary_loss: 0.013895 (0.013896) Loss: 0.40562 (0.41339) +2025-09-13,18:20:09 | INFO | Train Epoch: 7 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.37285 (0.39944) Boundary_loss: 0.013895 (0.013896) Loss: 0.38674 (0.41334) +2025-09-13,18:20:40 | INFO | Train Epoch: 7 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.32138 (0.39927) Boundary_loss: 0.013896 (0.013896) Loss: 0.33527 (0.41317) +2025-09-13,18:21:11 | INFO | Train Epoch: 7 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.31595 (0.39909) Boundary_loss: 0.013898 (0.013896) Loss: 0.32984 (0.41299) +2025-09-13,18:21:42 | INFO | Train Epoch: 7 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32250 (0.39893) Boundary_loss: 0.013897 (0.013896) Loss: 0.33640 (0.41283) +2025-09-13,18:22:13 | INFO | Train Epoch: 7 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.30561 (0.39873) Boundary_loss: 0.013899 (0.013896) Loss: 0.31951 (0.41263) +2025-09-13,18:22:44 | INFO | Train Epoch: 7 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.36473 (0.39866) Boundary_loss: 0.013897 (0.013897) Loss: 0.37863 (0.41255) +2025-09-13,18:23:14 | INFO | Train Epoch: 7 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37214 (0.39860) Boundary_loss: 0.013896 (0.013896) Loss: 0.38604 (0.41250) +2025-09-13,18:23:45 | INFO | Train Epoch: 7 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.48108 (0.39878) Boundary_loss: 0.013899 (0.013897) Loss: 0.49498 (0.41267) +2025-09-13,18:24:16 | INFO | Train Epoch: 7 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.37443 (0.39872) Boundary_loss: 0.013897 (0.013897) Loss: 0.38833 (0.41262) +2025-09-13,18:24:47 | INFO | Train Epoch: 7 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.34678 (0.39861) Boundary_loss: 0.013896 (0.013897) Loss: 0.36067 (0.41251) +2025-09-13,18:25:18 | INFO | Train Epoch: 7 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.36827 (0.39855) Boundary_loss: 0.013896 (0.013897) Loss: 0.38217 (0.41245) +2025-09-13,18:25:49 | INFO | Train Epoch: 7 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.39197 (0.39854) Boundary_loss: 0.013895 (0.013897) Loss: 0.40587 (0.41243) +2025-09-13,18:26:19 | INFO | Train Epoch: 7 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.43744 (0.39862) Boundary_loss: 0.013897 (0.013897) Loss: 0.45133 (0.41252) +2025-09-13,18:26:50 | INFO | Train Epoch: 7 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.40427 (0.39863) Boundary_loss: 0.013897 (0.013897) Loss: 0.41817 (0.41253) +2025-09-13,18:27:21 | INFO | Train Epoch: 7 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.43620 (0.39871) Boundary_loss: 0.013895 (0.013897) Loss: 0.45009 (0.41261) +2025-09-13,18:27:52 | INFO | Train Epoch: 7 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.39320 (0.39870) Boundary_loss: 0.013897 (0.013897) Loss: 0.40709 (0.41259) +2025-09-13,18:28:23 | INFO | Train Epoch: 7 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.37150 (0.39864) Boundary_loss: 0.013896 (0.013897) Loss: 0.38540 (0.41254) +2025-09-13,18:28:54 | INFO | Train Epoch: 7 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38662 (0.39862) Boundary_loss: 0.013897 (0.013897) Loss: 0.40051 (0.41251) +2025-09-13,18:29:25 | INFO | Train Epoch: 7 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.42789 (0.39868) Boundary_loss: 0.013895 (0.013896) Loss: 0.44179 (0.41257) +2025-09-13,18:29:56 | INFO | Train Epoch: 7 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.34989 (0.39858) Boundary_loss: 0.013895 (0.013896) Loss: 0.36378 (0.41247) +2025-09-13,18:30:27 | INFO | Train Epoch: 7 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.40160 (0.39858) Boundary_loss: 0.013895 (0.013896) Loss: 0.41549 (0.41248) +2025-09-13,18:30:57 | INFO | Train Epoch: 7 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.46745 (0.39872) Boundary_loss: 0.013896 (0.013896) Loss: 0.48135 (0.41262) +2025-09-13,18:31:28 | INFO | Train Epoch: 7 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.40590 (0.39874) Boundary_loss: 0.013897 (0.013896) Loss: 0.41980 (0.41264) +2025-09-13,18:31:59 | INFO | Train Epoch: 7 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.38198 (0.39870) Boundary_loss: 0.013897 (0.013896) Loss: 0.39588 (0.41260) +2025-09-13,18:32:29 | INFO | Train Epoch: 7 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.46978 (0.39885) Boundary_loss: 0.013895 (0.013896) Loss: 0.48367 (0.41275) +2025-09-13,18:33:00 | INFO | Train Epoch: 7 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.41335 (0.39888) Boundary_loss: 0.013897 (0.013896) Loss: 0.42725 (0.41278) +2025-09-13,18:33:31 | INFO | Train Epoch: 7 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.43674 (0.39896) Boundary_loss: 0.013896 (0.013896) Loss: 0.45064 (0.41285) +2025-09-13,18:34:02 | INFO | Train Epoch: 7 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.34205 (0.39884) Boundary_loss: 0.013895 (0.013896) Loss: 0.35595 (0.41274) +2025-09-13,18:34:33 | INFO | Train Epoch: 7 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.36591 (0.39877) Boundary_loss: 0.013895 (0.013896) Loss: 0.37981 (0.41267) +2025-09-13,18:35:03 | INFO | Train Epoch: 7 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.39684 (0.39877) Boundary_loss: 0.013896 (0.013896) Loss: 0.41074 (0.41267) +2025-09-13,18:35:34 | INFO | Train Epoch: 7 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.40702 (0.39879) Boundary_loss: 0.013895 (0.013896) Loss: 0.42092 (0.41268) +2025-09-13,18:36:05 | INFO | Train Epoch: 7 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.45105 (0.39889) Boundary_loss: 0.013897 (0.013896) Loss: 0.46494 (0.41279) +2025-09-13,18:36:36 | INFO | Train Epoch: 7 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.44811 (0.39899) Boundary_loss: 0.013894 (0.013896) Loss: 0.46201 (0.41289) +2025-09-13,18:37:07 | INFO | Train Epoch: 7 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44042 (0.39907) Boundary_loss: 0.013896 (0.013896) Loss: 0.45432 (0.41297) +2025-09-13,18:37:37 | INFO | Train Epoch: 7 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.43944 (0.39916) Boundary_loss: 0.013899 (0.013896) Loss: 0.45334 (0.41305) +2025-09-13,18:38:08 | INFO | Train Epoch: 7 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.34984 (0.39906) Boundary_loss: 0.013896 (0.013896) Loss: 0.36374 (0.41295) +2025-09-13,18:38:39 | INFO | Train Epoch: 7 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.32605 (0.39891) Boundary_loss: 0.013898 (0.013896) Loss: 0.33995 (0.41281) +2025-09-13,18:39:10 | INFO | Train Epoch: 7 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.35982 (0.39883) Boundary_loss: 0.013896 (0.013896) Loss: 0.37371 (0.41273) +2025-09-13,18:39:41 | INFO | Train Epoch: 7 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.39036 (0.39882) Boundary_loss: 0.013895 (0.013896) Loss: 0.40425 (0.41271) +2025-09-13,18:40:11 | INFO | Train Epoch: 7 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40877 (0.39884) Boundary_loss: 0.013895 (0.013896) Loss: 0.42267 (0.41273) +2025-09-13,18:40:42 | INFO | Train Epoch: 7 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.36349 (0.39877) Boundary_loss: 0.013896 (0.013896) Loss: 0.37739 (0.41266) +2025-09-13,18:41:13 | INFO | Train Epoch: 7 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.38220 (0.39873) Boundary_loss: 0.013896 (0.013896) Loss: 0.39609 (0.41263) +2025-09-13,18:41:44 | INFO | Train Epoch: 7 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.40708 (0.39875) Boundary_loss: 0.013896 (0.013896) Loss: 0.42098 (0.41265) +2025-09-13,18:42:15 | INFO | Train Epoch: 7 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.38764 (0.39873) Boundary_loss: 0.013896 (0.013896) Loss: 0.40153 (0.41262) +2025-09-13,18:42:46 | INFO | Train Epoch: 7 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.57051 (0.39907) Boundary_loss: 0.013896 (0.013896) Loss: 0.58441 (0.41296) +2025-09-13,18:43:17 | INFO | Train Epoch: 7 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.37463 (0.39902) Boundary_loss: 0.013894 (0.013896) Loss: 0.38852 (0.41291) +2025-09-13,18:43:48 | INFO | Train Epoch: 7 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40313 (0.39903) Boundary_loss: 0.013895 (0.013896) Loss: 0.41703 (0.41292) +2025-09-13,18:44:18 | INFO | Train Epoch: 7 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.43390 (0.39909) Boundary_loss: 0.013895 (0.013896) Loss: 0.44780 (0.41299) +2025-09-13,18:44:49 | INFO | Train Epoch: 7 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.36736 (0.39903) Boundary_loss: 0.013897 (0.013896) Loss: 0.38126 (0.41293) +2025-09-13,18:45:20 | INFO | Train Epoch: 7 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.37630 (0.39899) Boundary_loss: 0.013896 (0.013896) Loss: 0.39019 (0.41288) +2025-09-13,18:45:51 | INFO | Train Epoch: 7 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.35505 (0.39890) Boundary_loss: 0.013895 (0.013896) Loss: 0.36895 (0.41280) +2025-09-13,18:46:22 | INFO | Train Epoch: 7 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.45633 (0.39901) Boundary_loss: 0.013896 (0.013896) Loss: 0.47022 (0.41291) +2025-09-13,18:46:51 | INFO | Train Epoch: 7 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30386 (0.39883) Boundary_loss: 0.013896 (0.013896) Loss: 0.31775 (0.41273) +2025-09-13,18:46:51 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,18:46:51 | INFO | [Epoch 7] Average Step Time: 0.312s | Average GPU Memory: 25.2 GB +2025-09-13,18:46:51 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,18:46:51 | INFO | Starting zero-shot imagenet. +2025-09-13,18:46:51 | INFO | Building zero-shot classifier +2025-09-13,18:46:57 | INFO | Using classifier +2025-09-13,18:47:40 | INFO | Finished zero-shot imagenet. +2025-09-13,18:47:40 | INFO | Eval Epoch: 8 imagenet-zeroshot-val-top1: 0.2558 imagenet-zeroshot-val-top5: 0.5073 +2025-09-13,18:47:41 | INFO | Start epoch 8 +2025-09-13,18:47:43 | INFO | Train Epoch: 8 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.37326 (0.37326) Boundary_loss: 0.013896 (0.013896) Loss: 0.38715 (0.38715) +2025-09-13,18:48:13 | INFO | Train Epoch: 8 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.40101 (0.38713) Boundary_loss: 0.013896 (0.013896) Loss: 0.41491 (0.40103) +2025-09-13,18:48:44 | INFO | Train Epoch: 8 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.35304 (0.37577) Boundary_loss: 0.013897 (0.013896) Loss: 0.36693 (0.38967) +2025-09-13,18:49:15 | INFO | Train Epoch: 8 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28100 (0.35208) Boundary_loss: 0.013895 (0.013896) Loss: 0.29490 (0.36597) +2025-09-13,18:49:46 | INFO | Train Epoch: 8 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.35949 (0.35356) Boundary_loss: 0.013896 (0.013896) Loss: 0.37339 (0.36746) +2025-09-13,18:50:17 | INFO | Train Epoch: 8 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.23942 (0.33454) Boundary_loss: 0.013896 (0.013896) Loss: 0.25331 (0.34843) +2025-09-13,18:50:48 | INFO | Train Epoch: 8 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.38065 (0.34112) Boundary_loss: 0.013898 (0.013896) Loss: 0.39455 (0.35502) +2025-09-13,18:51:19 | INFO | Train Epoch: 8 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.43423 (0.35276) Boundary_loss: 0.013895 (0.013896) Loss: 0.44813 (0.36666) +2025-09-13,18:51:50 | INFO | Train Epoch: 8 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.38620 (0.35648) Boundary_loss: 0.013896 (0.013896) Loss: 0.40009 (0.37037) +2025-09-13,18:52:21 | INFO | Train Epoch: 8 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.31607 (0.35244) Boundary_loss: 0.013899 (0.013896) Loss: 0.32997 (0.36633) +2025-09-13,18:52:52 | INFO | Train Epoch: 8 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.37395 (0.35439) Boundary_loss: 0.013896 (0.013896) Loss: 0.38785 (0.36829) +2025-09-13,18:53:23 | INFO | Train Epoch: 8 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.38401 (0.35686) Boundary_loss: 0.013897 (0.013896) Loss: 0.39791 (0.37076) +2025-09-13,18:53:54 | INFO | Train Epoch: 8 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37526 (0.35828) Boundary_loss: 0.013897 (0.013896) Loss: 0.38916 (0.37217) +2025-09-13,18:54:24 | INFO | Train Epoch: 8 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30846 (0.35472) Boundary_loss: 0.013899 (0.013897) Loss: 0.32235 (0.36861) +2025-09-13,18:54:56 | INFO | Train Epoch: 8 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.33459 (0.35338) Boundary_loss: 0.013895 (0.013897) Loss: 0.34849 (0.36727) +2025-09-13,18:55:26 | INFO | Train Epoch: 8 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.32845 (0.35182) Boundary_loss: 0.013896 (0.013897) Loss: 0.34235 (0.36572) +2025-09-13,18:55:57 | INFO | Train Epoch: 8 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.30652 (0.34915) Boundary_loss: 0.013895 (0.013896) Loss: 0.32042 (0.36305) +2025-09-13,18:56:28 | INFO | Train Epoch: 8 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.37082 (0.35036) Boundary_loss: 0.013896 (0.013896) Loss: 0.38471 (0.36425) +2025-09-13,18:56:59 | INFO | Train Epoch: 8 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.35110 (0.35040) Boundary_loss: 0.013897 (0.013896) Loss: 0.36499 (0.36429) +2025-09-13,18:57:29 | INFO | Train Epoch: 8 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.30930 (0.34834) Boundary_loss: 0.013896 (0.013896) Loss: 0.32320 (0.36224) +2025-09-13,18:58:00 | INFO | Train Epoch: 8 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31015 (0.34652) Boundary_loss: 0.013896 (0.013896) Loss: 0.32405 (0.36042) +2025-09-13,18:58:31 | INFO | Train Epoch: 8 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.34192 (0.34631) Boundary_loss: 0.013895 (0.013896) Loss: 0.35582 (0.36021) +2025-09-13,18:59:02 | INFO | Train Epoch: 8 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.29491 (0.34408) Boundary_loss: 0.013896 (0.013896) Loss: 0.30881 (0.35798) +2025-09-13,18:59:33 | INFO | Train Epoch: 8 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.40092 (0.34645) Boundary_loss: 0.013897 (0.013896) Loss: 0.41481 (0.36034) +2025-09-13,19:00:04 | INFO | Train Epoch: 8 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35082 (0.34662) Boundary_loss: 0.013897 (0.013896) Loss: 0.36471 (0.36052) +2025-09-13,19:00:34 | INFO | Train Epoch: 8 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.36978 (0.34751) Boundary_loss: 0.013894 (0.013896) Loss: 0.38367 (0.36141) +2025-09-13,19:01:05 | INFO | Train Epoch: 8 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.28639 (0.34525) Boundary_loss: 0.013896 (0.013896) Loss: 0.30029 (0.35915) +2025-09-13,19:01:36 | INFO | Train Epoch: 8 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.34197 (0.34513) Boundary_loss: 0.013895 (0.013896) Loss: 0.35586 (0.35903) +2025-09-13,19:02:07 | INFO | Train Epoch: 8 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.28226 (0.34296) Boundary_loss: 0.013896 (0.013896) Loss: 0.29616 (0.35686) +2025-09-13,19:02:38 | INFO | Train Epoch: 8 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.29219 (0.34127) Boundary_loss: 0.013896 (0.013896) Loss: 0.30608 (0.35517) +2025-09-13,19:03:09 | INFO | Train Epoch: 8 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.36904 (0.34217) Boundary_loss: 0.013895 (0.013896) Loss: 0.38294 (0.35606) +2025-09-13,19:03:39 | INFO | Train Epoch: 8 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.34916 (0.34239) Boundary_loss: 0.013897 (0.013896) Loss: 0.36305 (0.35628) +2025-09-13,19:04:10 | INFO | Train Epoch: 8 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.41110 (0.34447) Boundary_loss: 0.013899 (0.013896) Loss: 0.42500 (0.35836) +2025-09-13,19:04:41 | INFO | Train Epoch: 8 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.35260 (0.34471) Boundary_loss: 0.013896 (0.013896) Loss: 0.36650 (0.35860) +2025-09-13,19:05:12 | INFO | Train Epoch: 8 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.36331 (0.34524) Boundary_loss: 0.013898 (0.013896) Loss: 0.37721 (0.35914) +2025-09-13,19:05:43 | INFO | Train Epoch: 8 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.29673 (0.34389) Boundary_loss: 0.013897 (0.013896) Loss: 0.31063 (0.35779) +2025-09-13,19:06:14 | INFO | Train Epoch: 8 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27382 (0.34200) Boundary_loss: 0.013896 (0.013896) Loss: 0.28772 (0.35589) +2025-09-13,19:06:45 | INFO | Train Epoch: 8 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.33376 (0.34178) Boundary_loss: 0.013896 (0.013896) Loss: 0.34766 (0.35568) +2025-09-13,19:07:16 | INFO | Train Epoch: 8 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.36663 (0.34242) Boundary_loss: 0.013898 (0.013896) Loss: 0.38053 (0.35631) +2025-09-13,19:07:46 | INFO | Train Epoch: 8 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.34142 (0.34239) Boundary_loss: 0.013898 (0.013896) Loss: 0.35532 (0.35629) +2025-09-13,19:08:17 | INFO | Train Epoch: 8 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.32737 (0.34203) Boundary_loss: 0.013895 (0.013896) Loss: 0.34127 (0.35592) +2025-09-13,19:08:48 | INFO | Train Epoch: 8 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.34220 (0.34203) Boundary_loss: 0.013896 (0.013896) Loss: 0.35609 (0.35593) +2025-09-13,19:09:19 | INFO | Train Epoch: 8 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.32654 (0.34167) Boundary_loss: 0.013897 (0.013896) Loss: 0.34044 (0.35557) +2025-09-13,19:09:50 | INFO | Train Epoch: 8 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30345 (0.34080) Boundary_loss: 0.013895 (0.013896) Loss: 0.31735 (0.35470) +2025-09-13,19:10:21 | INFO | Train Epoch: 8 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.27135 (0.33926) Boundary_loss: 0.013896 (0.013896) Loss: 0.28525 (0.35316) +2025-09-13,19:10:51 | INFO | Train Epoch: 8 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.32221 (0.33889) Boundary_loss: 0.013895 (0.013896) Loss: 0.33611 (0.35278) +2025-09-13,19:11:22 | INFO | Train Epoch: 8 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40666 (0.34033) Boundary_loss: 0.013896 (0.013896) Loss: 0.42056 (0.35423) +2025-09-13,19:11:53 | INFO | Train Epoch: 8 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.29206 (0.33932) Boundary_loss: 0.013895 (0.013896) Loss: 0.30596 (0.35322) +2025-09-13,19:12:24 | INFO | Train Epoch: 8 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.45494 (0.34168) Boundary_loss: 0.013895 (0.013896) Loss: 0.46884 (0.35558) +2025-09-13,19:12:55 | INFO | Train Epoch: 8 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.33005 (0.34145) Boundary_loss: 0.013895 (0.013896) Loss: 0.34395 (0.35535) +2025-09-13,19:13:26 | INFO | Train Epoch: 8 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.32964 (0.34122) Boundary_loss: 0.013895 (0.013896) Loss: 0.34353 (0.35512) +2025-09-13,19:13:57 | INFO | Train Epoch: 8 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.29779 (0.34038) Boundary_loss: 0.013897 (0.013896) Loss: 0.31168 (0.35428) +2025-09-13,19:14:28 | INFO | Train Epoch: 8 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.31109 (0.33983) Boundary_loss: 0.013896 (0.013896) Loss: 0.32498 (0.35373) +2025-09-13,19:14:59 | INFO | Train Epoch: 8 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.34936 (0.34001) Boundary_loss: 0.013898 (0.013896) Loss: 0.36325 (0.35390) +2025-09-13,19:15:30 | INFO | Train Epoch: 8 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.40617 (0.34121) Boundary_loss: 0.013898 (0.013896) Loss: 0.42006 (0.35511) +2025-09-13,19:16:00 | INFO | Train Epoch: 8 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.38813 (0.34205) Boundary_loss: 0.013897 (0.013896) Loss: 0.40202 (0.35595) +2025-09-13,19:16:31 | INFO | Train Epoch: 8 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.42026 (0.34342) Boundary_loss: 0.013897 (0.013896) Loss: 0.43415 (0.35732) +2025-09-13,19:17:02 | INFO | Train Epoch: 8 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.25836 (0.34195) Boundary_loss: 0.013897 (0.013896) Loss: 0.27226 (0.35585) +2025-09-13,19:17:33 | INFO | Train Epoch: 8 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.30432 (0.34132) Boundary_loss: 0.013896 (0.013896) Loss: 0.31822 (0.35521) +2025-09-13,19:18:04 | INFO | Train Epoch: 8 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.36891 (0.34178) Boundary_loss: 0.013895 (0.013896) Loss: 0.38280 (0.35567) +2025-09-13,19:18:35 | INFO | Train Epoch: 8 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.33968 (0.34174) Boundary_loss: 0.013895 (0.013896) Loss: 0.35357 (0.35564) +2025-09-13,19:19:06 | INFO | Train Epoch: 8 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.28805 (0.34088) Boundary_loss: 0.013896 (0.013896) Loss: 0.30195 (0.35477) +2025-09-13,19:19:37 | INFO | Train Epoch: 8 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.43361 (0.34235) Boundary_loss: 0.013895 (0.013896) Loss: 0.44750 (0.35624) +2025-09-13,19:20:08 | INFO | Train Epoch: 8 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.27692 (0.34133) Boundary_loss: 0.013897 (0.013896) Loss: 0.29081 (0.35522) +2025-09-13,19:20:39 | INFO | Train Epoch: 8 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.33679 (0.34126) Boundary_loss: 0.013897 (0.013896) Loss: 0.35069 (0.35515) +2025-09-13,19:21:10 | INFO | Train Epoch: 8 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.30925 (0.34077) Boundary_loss: 0.013896 (0.013896) Loss: 0.32315 (0.35467) +2025-09-13,19:21:41 | INFO | Train Epoch: 8 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.41535 (0.34188) Boundary_loss: 0.013896 (0.013896) Loss: 0.42924 (0.35578) +2025-09-13,19:22:12 | INFO | Train Epoch: 8 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.30134 (0.34129) Boundary_loss: 0.013896 (0.013896) Loss: 0.31523 (0.35518) +2025-09-13,19:22:43 | INFO | Train Epoch: 8 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.31439 (0.34090) Boundary_loss: 0.013897 (0.013896) Loss: 0.32828 (0.35479) +2025-09-13,19:23:13 | INFO | Train Epoch: 8 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26199 (0.33977) Boundary_loss: 0.013895 (0.013896) Loss: 0.27588 (0.35367) +2025-09-13,19:23:44 | INFO | Train Epoch: 8 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.43780 (0.34115) Boundary_loss: 0.013897 (0.013896) Loss: 0.45170 (0.35505) +2025-09-13,19:24:15 | INFO | Train Epoch: 8 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.36676 (0.34151) Boundary_loss: 0.013898 (0.013896) Loss: 0.38066 (0.35540) +2025-09-13,19:24:46 | INFO | Train Epoch: 8 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.29758 (0.34091) Boundary_loss: 0.013896 (0.013896) Loss: 0.31148 (0.35480) +2025-09-13,19:25:17 | INFO | Train Epoch: 8 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.35890 (0.34115) Boundary_loss: 0.013895 (0.013896) Loss: 0.37280 (0.35504) +2025-09-13,19:25:48 | INFO | Train Epoch: 8 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.32870 (0.34098) Boundary_loss: 0.013896 (0.013896) Loss: 0.34259 (0.35488) +2025-09-13,19:26:19 | INFO | Train Epoch: 8 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.40355 (0.34181) Boundary_loss: 0.013896 (0.013896) Loss: 0.41745 (0.35570) +2025-09-13,19:26:50 | INFO | Train Epoch: 8 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.34651 (0.34187) Boundary_loss: 0.013895 (0.013896) Loss: 0.36040 (0.35576) +2025-09-13,19:27:21 | INFO | Train Epoch: 8 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.34409 (0.34190) Boundary_loss: 0.013896 (0.013896) Loss: 0.35799 (0.35579) +2025-09-13,19:27:51 | INFO | Train Epoch: 8 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.32810 (0.34172) Boundary_loss: 0.013897 (0.013896) Loss: 0.34200 (0.35562) +2025-09-13,19:28:22 | INFO | Train Epoch: 8 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27962 (0.34094) Boundary_loss: 0.013895 (0.013896) Loss: 0.29352 (0.35484) +2025-09-13,19:28:53 | INFO | Train Epoch: 8 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.39159 (0.34157) Boundary_loss: 0.013896 (0.013896) Loss: 0.40549 (0.35547) +2025-09-13,19:29:24 | INFO | Train Epoch: 8 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.29067 (0.34095) Boundary_loss: 0.013896 (0.013896) Loss: 0.30456 (0.35485) +2025-09-13,19:29:55 | INFO | Train Epoch: 8 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.28858 (0.34032) Boundary_loss: 0.013895 (0.013896) Loss: 0.30248 (0.35421) +2025-09-13,19:30:26 | INFO | Train Epoch: 8 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30006 (0.33984) Boundary_loss: 0.013896 (0.013896) Loss: 0.31395 (0.35374) +2025-09-13,19:30:57 | INFO | Train Epoch: 8 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.32622 (0.33968) Boundary_loss: 0.013897 (0.013896) Loss: 0.34012 (0.35357) +2025-09-13,19:31:28 | INFO | Train Epoch: 8 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.28423 (0.33903) Boundary_loss: 0.013896 (0.013896) Loss: 0.29813 (0.35293) +2025-09-13,19:31:59 | INFO | Train Epoch: 8 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.31992 (0.33881) Boundary_loss: 0.013895 (0.013896) Loss: 0.33381 (0.35271) +2025-09-13,19:32:30 | INFO | Train Epoch: 8 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.29306 (0.33829) Boundary_loss: 0.013896 (0.013896) Loss: 0.30695 (0.35219) +2025-09-13,19:33:01 | INFO | Train Epoch: 8 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.38566 (0.33883) Boundary_loss: 0.013897 (0.013896) Loss: 0.39955 (0.35272) +2025-09-13,19:33:32 | INFO | Train Epoch: 8 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.40086 (0.33952) Boundary_loss: 0.013895 (0.013896) Loss: 0.41475 (0.35341) +2025-09-13,19:34:03 | INFO | Train Epoch: 8 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27653 (0.33882) Boundary_loss: 0.013895 (0.013896) Loss: 0.29042 (0.35272) +2025-09-13,19:34:34 | INFO | Train Epoch: 8 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.41021 (0.33960) Boundary_loss: 0.013896 (0.013896) Loss: 0.42411 (0.35350) +2025-09-13,19:35:04 | INFO | Train Epoch: 8 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.26811 (0.33883) Boundary_loss: 0.013905 (0.013896) Loss: 0.28202 (0.35273) +2025-09-13,19:35:35 | INFO | Train Epoch: 8 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.35055 (0.33896) Boundary_loss: 0.013895 (0.013896) Loss: 0.36445 (0.35285) +2025-09-13,19:36:06 | INFO | Train Epoch: 8 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.44633 (0.34009) Boundary_loss: 0.013895 (0.013896) Loss: 0.46022 (0.35398) +2025-09-13,19:36:37 | INFO | Train Epoch: 8 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.39248 (0.34063) Boundary_loss: 0.013897 (0.013896) Loss: 0.40638 (0.35453) +2025-09-13,19:37:08 | INFO | Train Epoch: 8 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.27448 (0.33995) Boundary_loss: 0.013895 (0.013896) Loss: 0.28837 (0.35385) +2025-09-13,19:37:39 | INFO | Train Epoch: 8 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.39572 (0.34052) Boundary_loss: 0.013904 (0.013896) Loss: 0.40962 (0.35441) +2025-09-13,19:38:10 | INFO | Train Epoch: 8 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.39892 (0.34111) Boundary_loss: 0.013896 (0.013896) Loss: 0.41282 (0.35500) +2025-09-13,19:38:41 | INFO | Train Epoch: 8 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.37305 (0.34143) Boundary_loss: 0.013894 (0.013896) Loss: 0.38695 (0.35532) +2025-09-13,19:39:12 | INFO | Train Epoch: 8 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.40206 (0.34203) Boundary_loss: 0.013897 (0.013896) Loss: 0.41596 (0.35592) +2025-09-13,19:39:43 | INFO | Train Epoch: 8 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.29736 (0.34159) Boundary_loss: 0.013896 (0.013896) Loss: 0.31125 (0.35549) +2025-09-13,19:40:14 | INFO | Train Epoch: 8 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.30036 (0.34119) Boundary_loss: 0.013896 (0.013896) Loss: 0.31426 (0.35509) +2025-09-13,19:40:45 | INFO | Train Epoch: 8 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.34702 (0.34125) Boundary_loss: 0.013896 (0.013896) Loss: 0.36092 (0.35514) +2025-09-13,19:41:15 | INFO | Train Epoch: 8 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.33607 (0.34120) Boundary_loss: 0.013895 (0.013896) Loss: 0.34997 (0.35509) +2025-09-13,19:41:46 | INFO | Train Epoch: 8 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.38691 (0.34163) Boundary_loss: 0.013896 (0.013896) Loss: 0.40080 (0.35552) +2025-09-13,19:42:17 | INFO | Train Epoch: 8 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31076 (0.34134) Boundary_loss: 0.013896 (0.013896) Loss: 0.32466 (0.35524) +2025-09-13,19:42:48 | INFO | Train Epoch: 8 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.33303 (0.34126) Boundary_loss: 0.013896 (0.013896) Loss: 0.34693 (0.35516) +2025-09-13,19:43:19 | INFO | Train Epoch: 8 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.39114 (0.34172) Boundary_loss: 0.013896 (0.013896) Loss: 0.40504 (0.35562) +2025-09-13,19:43:50 | INFO | Train Epoch: 8 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.33238 (0.34164) Boundary_loss: 0.013894 (0.013896) Loss: 0.34627 (0.35553) +2025-09-13,19:44:21 | INFO | Train Epoch: 8 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.38480 (0.34202) Boundary_loss: 0.013895 (0.013896) Loss: 0.39869 (0.35592) +2025-09-13,19:44:52 | INFO | Train Epoch: 8 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.39907 (0.34253) Boundary_loss: 0.013896 (0.013896) Loss: 0.41296 (0.35643) +2025-09-13,19:45:23 | INFO | Train Epoch: 8 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.28262 (0.34200) Boundary_loss: 0.013897 (0.013896) Loss: 0.29652 (0.35590) +2025-09-13,19:45:54 | INFO | Train Epoch: 8 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.37671 (0.34231) Boundary_loss: 0.013897 (0.013896) Loss: 0.39060 (0.35620) +2025-09-13,19:46:25 | INFO | Train Epoch: 8 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26701 (0.34165) Boundary_loss: 0.013896 (0.013896) Loss: 0.28091 (0.35555) +2025-09-13,19:46:56 | INFO | Train Epoch: 8 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.34266 (0.34166) Boundary_loss: 0.013898 (0.013896) Loss: 0.35656 (0.35556) +2025-09-13,19:47:27 | INFO | Train Epoch: 8 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.38269 (0.34201) Boundary_loss: 0.013894 (0.013896) Loss: 0.39658 (0.35591) +2025-09-13,19:47:58 | INFO | Train Epoch: 8 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.36111 (0.34217) Boundary_loss: 0.013896 (0.013896) Loss: 0.37501 (0.35607) +2025-09-13,19:48:29 | INFO | Train Epoch: 8 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.25314 (0.34143) Boundary_loss: 0.013898 (0.013896) Loss: 0.26704 (0.35532) +2025-09-13,19:49:00 | INFO | Train Epoch: 8 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.26487 (0.34079) Boundary_loss: 0.013896 (0.013896) Loss: 0.27876 (0.35468) +2025-09-13,19:49:30 | INFO | Train Epoch: 8 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.33238 (0.34072) Boundary_loss: 0.013895 (0.013896) Loss: 0.34628 (0.35461) +2025-09-13,19:50:01 | INFO | Train Epoch: 8 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.33632 (0.34068) Boundary_loss: 0.013896 (0.013896) Loss: 0.35022 (0.35458) +2025-09-13,19:50:32 | INFO | Train Epoch: 8 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.27535 (0.34015) Boundary_loss: 0.013896 (0.013896) Loss: 0.28925 (0.35405) +2025-09-13,19:51:03 | INFO | Train Epoch: 8 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.34110 (0.34016) Boundary_loss: 0.013895 (0.013896) Loss: 0.35499 (0.35406) +2025-09-13,19:51:33 | INFO | Train Epoch: 8 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28922 (0.33975) Boundary_loss: 0.013896 (0.013896) Loss: 0.30311 (0.35365) +2025-09-13,19:52:04 | INFO | Train Epoch: 8 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.43841 (0.34053) Boundary_loss: 0.013898 (0.013896) Loss: 0.45231 (0.35443) +2025-09-13,19:52:35 | INFO | Train Epoch: 8 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.25675 (0.33987) Boundary_loss: 0.013895 (0.013896) Loss: 0.27065 (0.35377) +2025-09-13,19:53:05 | INFO | Train Epoch: 8 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.33396 (0.33983) Boundary_loss: 0.013896 (0.013896) Loss: 0.34786 (0.35372) +2025-09-13,19:53:36 | INFO | Train Epoch: 8 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27961 (0.33936) Boundary_loss: 0.013896 (0.013896) Loss: 0.29351 (0.35326) +2025-09-13,19:54:07 | INFO | Train Epoch: 8 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.50516 (0.34064) Boundary_loss: 0.013897 (0.013896) Loss: 0.51906 (0.35453) +2025-09-13,19:54:37 | INFO | Train Epoch: 8 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.43454 (0.34135) Boundary_loss: 0.013896 (0.013896) Loss: 0.44844 (0.35525) +2025-09-13,19:55:08 | INFO | Train Epoch: 8 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.36730 (0.34155) Boundary_loss: 0.013896 (0.013896) Loss: 0.38119 (0.35545) +2025-09-13,19:55:39 | INFO | Train Epoch: 8 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.30690 (0.34129) Boundary_loss: 0.013898 (0.013896) Loss: 0.32080 (0.35519) +2025-09-13,19:56:09 | INFO | Train Epoch: 8 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.31491 (0.34109) Boundary_loss: 0.013898 (0.013896) Loss: 0.32880 (0.35499) +2025-09-13,19:56:40 | INFO | Train Epoch: 8 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32728 (0.34099) Boundary_loss: 0.013895 (0.013896) Loss: 0.34117 (0.35489) +2025-09-13,19:57:11 | INFO | Train Epoch: 8 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.39211 (0.34137) Boundary_loss: 0.013895 (0.013896) Loss: 0.40600 (0.35526) +2025-09-13,19:57:41 | INFO | Train Epoch: 8 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.30836 (0.34113) Boundary_loss: 0.013896 (0.013896) Loss: 0.32226 (0.35502) +2025-09-13,19:58:12 | INFO | Train Epoch: 8 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.37124 (0.34134) Boundary_loss: 0.013895 (0.013896) Loss: 0.38514 (0.35524) +2025-09-13,19:58:43 | INFO | Train Epoch: 8 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.36204 (0.34149) Boundary_loss: 0.013895 (0.013896) Loss: 0.37594 (0.35539) +2025-09-13,19:59:13 | INFO | Train Epoch: 8 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.37982 (0.34177) Boundary_loss: 0.013896 (0.013896) Loss: 0.39372 (0.35566) +2025-09-13,19:59:44 | INFO | Train Epoch: 8 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.41385 (0.34228) Boundary_loss: 0.013895 (0.013896) Loss: 0.42774 (0.35617) +2025-09-13,20:00:15 | INFO | Train Epoch: 8 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.35112 (0.34234) Boundary_loss: 0.013895 (0.013896) Loss: 0.36501 (0.35624) +2025-09-13,20:00:46 | INFO | Train Epoch: 8 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.30826 (0.34210) Boundary_loss: 0.013896 (0.013896) Loss: 0.32215 (0.35600) +2025-09-13,20:01:16 | INFO | Train Epoch: 8 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.30194 (0.34182) Boundary_loss: 0.013895 (0.013896) Loss: 0.31584 (0.35572) +2025-09-13,20:01:47 | INFO | Train Epoch: 8 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32737 (0.34172) Boundary_loss: 0.013896 (0.013896) Loss: 0.34127 (0.35562) +2025-09-13,20:02:18 | INFO | Train Epoch: 8 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.31412 (0.34153) Boundary_loss: 0.013897 (0.013896) Loss: 0.32802 (0.35543) +2025-09-13,20:02:48 | INFO | Train Epoch: 8 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.35268 (0.34161) Boundary_loss: 0.013895 (0.013896) Loss: 0.36658 (0.35551) +2025-09-13,20:03:19 | INFO | Train Epoch: 8 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.35910 (0.34173) Boundary_loss: 0.013896 (0.013896) Loss: 0.37300 (0.35562) +2025-09-13,20:03:50 | INFO | Train Epoch: 8 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.33933 (0.34171) Boundary_loss: 0.013896 (0.013896) Loss: 0.35323 (0.35561) +2025-09-13,20:04:20 | INFO | Train Epoch: 8 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35473 (0.34180) Boundary_loss: 0.013896 (0.013896) Loss: 0.36863 (0.35570) +2025-09-13,20:04:51 | INFO | Train Epoch: 8 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.26333 (0.34128) Boundary_loss: 0.013896 (0.013896) Loss: 0.27723 (0.35518) +2025-09-13,20:05:22 | INFO | Train Epoch: 8 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.27203 (0.34082) Boundary_loss: 0.013894 (0.013896) Loss: 0.28593 (0.35472) +2025-09-13,20:05:52 | INFO | Train Epoch: 8 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.25449 (0.34026) Boundary_loss: 0.013897 (0.013896) Loss: 0.26838 (0.35416) +2025-09-13,20:06:23 | INFO | Train Epoch: 8 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.37347 (0.34048) Boundary_loss: 0.013897 (0.013896) Loss: 0.38737 (0.35437) +2025-09-13,20:06:54 | INFO | Train Epoch: 8 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26742 (0.34000) Boundary_loss: 0.013896 (0.013896) Loss: 0.28132 (0.35390) +2025-09-13,20:07:25 | INFO | Train Epoch: 8 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.39843 (0.34038) Boundary_loss: 0.013898 (0.013896) Loss: 0.41233 (0.35427) +2025-09-13,20:07:56 | INFO | Train Epoch: 8 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.36107 (0.34051) Boundary_loss: 0.013895 (0.013896) Loss: 0.37496 (0.35441) +2025-09-13,20:08:26 | INFO | Train Epoch: 8 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.35277 (0.34059) Boundary_loss: 0.013895 (0.013896) Loss: 0.36667 (0.35448) +2025-09-13,20:08:57 | INFO | Train Epoch: 8 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.36881 (0.34077) Boundary_loss: 0.013895 (0.013896) Loss: 0.38271 (0.35466) +2025-09-13,20:09:28 | INFO | Train Epoch: 8 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.39569 (0.34111) Boundary_loss: 0.013895 (0.013896) Loss: 0.40959 (0.35500) +2025-09-13,20:09:59 | INFO | Train Epoch: 8 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.38135 (0.34136) Boundary_loss: 0.013896 (0.013896) Loss: 0.39525 (0.35525) +2025-09-13,20:10:30 | INFO | Train Epoch: 8 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.33439 (0.34132) Boundary_loss: 0.013897 (0.013896) Loss: 0.34829 (0.35521) +2025-09-13,20:11:00 | INFO | Train Epoch: 8 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29402 (0.34103) Boundary_loss: 0.013896 (0.013896) Loss: 0.30791 (0.35492) +2025-09-13,20:11:31 | INFO | Train Epoch: 8 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.30717 (0.34082) Boundary_loss: 0.013896 (0.013896) Loss: 0.32107 (0.35472) +2025-09-13,20:12:02 | INFO | Train Epoch: 8 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.29084 (0.34052) Boundary_loss: 0.013897 (0.013896) Loss: 0.30474 (0.35441) +2025-09-13,20:12:33 | INFO | Train Epoch: 8 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.30249 (0.34029) Boundary_loss: 0.013895 (0.013896) Loss: 0.31639 (0.35418) +2025-09-13,20:13:04 | INFO | Train Epoch: 8 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.36793 (0.34045) Boundary_loss: 0.013895 (0.013896) Loss: 0.38183 (0.35435) +2025-09-13,20:13:35 | INFO | Train Epoch: 8 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.27587 (0.34007) Boundary_loss: 0.013896 (0.013896) Loss: 0.28976 (0.35396) +2025-09-13,20:14:06 | INFO | Train Epoch: 8 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.31757 (0.33993) Boundary_loss: 0.013895 (0.013896) Loss: 0.33146 (0.35383) +2025-09-13,20:14:36 | INFO | Train Epoch: 8 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27467 (0.33955) Boundary_loss: 0.013896 (0.013896) Loss: 0.28856 (0.35345) +2025-09-13,20:15:07 | INFO | Train Epoch: 8 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.34360 (0.33957) Boundary_loss: 0.013898 (0.013896) Loss: 0.35750 (0.35347) +2025-09-13,20:15:38 | INFO | Train Epoch: 8 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.33766 (0.33956) Boundary_loss: 0.013896 (0.013896) Loss: 0.35155 (0.35346) +2025-09-13,20:16:09 | INFO | Train Epoch: 8 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.28502 (0.33925) Boundary_loss: 0.013897 (0.013896) Loss: 0.29891 (0.35314) +2025-09-13,20:16:40 | INFO | Train Epoch: 8 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.36381 (0.33939) Boundary_loss: 0.013895 (0.013896) Loss: 0.37770 (0.35329) +2025-09-13,20:17:10 | INFO | Train Epoch: 8 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.37279 (0.33958) Boundary_loss: 0.013897 (0.013896) Loss: 0.38669 (0.35348) +2025-09-13,20:17:41 | INFO | Train Epoch: 8 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.26426 (0.33915) Boundary_loss: 0.013898 (0.013896) Loss: 0.27816 (0.35305) +2025-09-13,20:18:12 | INFO | Train Epoch: 8 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35371 (0.33923) Boundary_loss: 0.013895 (0.013896) Loss: 0.36760 (0.35313) +2025-09-13,20:18:42 | INFO | Train Epoch: 8 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.33121 (0.33919) Boundary_loss: 0.013895 (0.013896) Loss: 0.34511 (0.35309) +2025-09-13,20:19:13 | INFO | Train Epoch: 8 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.33298 (0.33915) Boundary_loss: 0.013895 (0.013896) Loss: 0.34687 (0.35305) +2025-09-13,20:19:44 | INFO | Train Epoch: 8 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.37552 (0.33936) Boundary_loss: 0.013896 (0.013896) Loss: 0.38942 (0.35325) +2025-09-13,20:20:15 | INFO | Train Epoch: 8 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38526 (0.33961) Boundary_loss: 0.013894 (0.013896) Loss: 0.39915 (0.35351) +2025-09-13,20:20:46 | INFO | Train Epoch: 8 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.22530 (0.33898) Boundary_loss: 0.013898 (0.013896) Loss: 0.23920 (0.35288) +2025-09-13,20:21:17 | INFO | Train Epoch: 8 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.32455 (0.33890) Boundary_loss: 0.013896 (0.013896) Loss: 0.33845 (0.35280) +2025-09-13,20:21:48 | INFO | Train Epoch: 8 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.28148 (0.33859) Boundary_loss: 0.013897 (0.013896) Loss: 0.29538 (0.35249) +2025-09-13,20:22:19 | INFO | Train Epoch: 8 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.33397 (0.33857) Boundary_loss: 0.013896 (0.013896) Loss: 0.34786 (0.35246) +2025-09-13,20:22:50 | INFO | Train Epoch: 8 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.29978 (0.33836) Boundary_loss: 0.013896 (0.013896) Loss: 0.31368 (0.35225) +2025-09-13,20:23:21 | INFO | Train Epoch: 8 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30869 (0.33820) Boundary_loss: 0.013896 (0.013896) Loss: 0.32259 (0.35210) +2025-09-13,20:23:51 | INFO | Train Epoch: 8 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.30100 (0.33800) Boundary_loss: 0.013896 (0.013896) Loss: 0.31489 (0.35190) +2025-09-13,20:24:22 | INFO | Train Epoch: 8 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24865 (0.33753) Boundary_loss: 0.013895 (0.013896) Loss: 0.26255 (0.35142) +2025-09-13,20:24:53 | INFO | Train Epoch: 8 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.39986 (0.33786) Boundary_loss: 0.013894 (0.013896) Loss: 0.41375 (0.35175) +2025-09-13,20:25:24 | INFO | Train Epoch: 8 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.28344 (0.33757) Boundary_loss: 0.013898 (0.013896) Loss: 0.29734 (0.35147) +2025-09-13,20:25:55 | INFO | Train Epoch: 8 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.30290 (0.33739) Boundary_loss: 0.013895 (0.013896) Loss: 0.31680 (0.35129) +2025-09-13,20:26:26 | INFO | Train Epoch: 8 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31791 (0.33729) Boundary_loss: 0.013895 (0.013896) Loss: 0.33180 (0.35119) +2025-09-13,20:26:56 | INFO | Train Epoch: 8 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.30416 (0.33712) Boundary_loss: 0.013896 (0.013896) Loss: 0.31806 (0.35102) +2025-09-13,20:27:27 | INFO | Train Epoch: 8 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.26944 (0.33677) Boundary_loss: 0.013895 (0.013896) Loss: 0.28334 (0.35067) +2025-09-13,20:27:58 | INFO | Train Epoch: 8 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.31780 (0.33668) Boundary_loss: 0.013897 (0.013896) Loss: 0.33170 (0.35057) +2025-09-13,20:28:28 | INFO | Train Epoch: 8 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28931 (0.33644) Boundary_loss: 0.013896 (0.013896) Loss: 0.30321 (0.35033) +2025-09-13,20:28:59 | INFO | Train Epoch: 8 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.35882 (0.33655) Boundary_loss: 0.013895 (0.013896) Loss: 0.37271 (0.35044) +2025-09-13,20:29:30 | INFO | Train Epoch: 8 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.27317 (0.33623) Boundary_loss: 0.013895 (0.013896) Loss: 0.28707 (0.35013) +2025-09-13,20:30:01 | INFO | Train Epoch: 8 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.33294 (0.33621) Boundary_loss: 0.013895 (0.013896) Loss: 0.34684 (0.35011) +2025-09-13,20:30:32 | INFO | Train Epoch: 8 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.33228 (0.33619) Boundary_loss: 0.013896 (0.013896) Loss: 0.34618 (0.35009) +2025-09-13,20:31:03 | INFO | Train Epoch: 8 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.32218 (0.33612) Boundary_loss: 0.013895 (0.013896) Loss: 0.33608 (0.35002) +2025-09-13,20:31:33 | INFO | Train Epoch: 8 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.30742 (0.33598) Boundary_loss: 0.013896 (0.013896) Loss: 0.32131 (0.34988) +2025-09-13,20:32:04 | INFO | Train Epoch: 8 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.33974 (0.33600) Boundary_loss: 0.013896 (0.013896) Loss: 0.35363 (0.34990) +2025-09-13,20:32:35 | INFO | Train Epoch: 8 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.39393 (0.33628) Boundary_loss: 0.013896 (0.013896) Loss: 0.40783 (0.35018) +2025-09-13,20:33:06 | INFO | Train Epoch: 8 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.31018 (0.33616) Boundary_loss: 0.013896 (0.013896) Loss: 0.32408 (0.35005) +2025-09-13,20:33:36 | INFO | Train Epoch: 8 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.30555 (0.33601) Boundary_loss: 0.013896 (0.013896) Loss: 0.31945 (0.34991) +2025-09-13,20:34:07 | INFO | Train Epoch: 8 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.35537 (0.33610) Boundary_loss: 0.013896 (0.013896) Loss: 0.36927 (0.35000) +2025-09-13,20:34:38 | INFO | Train Epoch: 8 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.37522 (0.33629) Boundary_loss: 0.013895 (0.013896) Loss: 0.38912 (0.35019) +2025-09-13,20:35:09 | INFO | Train Epoch: 8 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.31755 (0.33620) Boundary_loss: 0.013895 (0.013896) Loss: 0.33145 (0.35010) +2025-09-13,20:35:39 | INFO | Train Epoch: 8 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.37921 (0.33640) Boundary_loss: 0.013895 (0.013896) Loss: 0.39311 (0.35030) +2025-09-13,20:36:10 | INFO | Train Epoch: 8 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.37550 (0.33659) Boundary_loss: 0.013900 (0.013896) Loss: 0.38940 (0.35048) +2025-09-13,20:36:41 | INFO | Train Epoch: 8 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.37293 (0.33676) Boundary_loss: 0.013895 (0.013896) Loss: 0.38683 (0.35066) +2025-09-13,20:37:11 | INFO | Train Epoch: 8 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.25278 (0.33637) Boundary_loss: 0.013896 (0.013896) Loss: 0.26668 (0.35026) +2025-09-13,20:37:42 | INFO | Train Epoch: 8 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.40090 (0.33667) Boundary_loss: 0.013895 (0.013896) Loss: 0.41480 (0.35056) +2025-09-13,20:38:13 | INFO | Train Epoch: 8 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.27443 (0.33638) Boundary_loss: 0.013895 (0.013896) Loss: 0.28832 (0.35028) +2025-09-13,20:38:44 | INFO | Train Epoch: 8 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.30103 (0.33622) Boundary_loss: 0.013895 (0.013896) Loss: 0.31493 (0.35011) +2025-09-13,20:39:15 | INFO | Train Epoch: 8 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.31281 (0.33611) Boundary_loss: 0.013895 (0.013896) Loss: 0.32671 (0.35000) +2025-09-13,20:39:46 | INFO | Train Epoch: 8 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.37061 (0.33627) Boundary_loss: 0.013896 (0.013896) Loss: 0.38451 (0.35016) +2025-09-13,20:40:16 | INFO | Train Epoch: 8 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.33928 (0.33628) Boundary_loss: 0.013895 (0.013896) Loss: 0.35318 (0.35018) +2025-09-13,20:40:47 | INFO | Train Epoch: 8 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.32337 (0.33622) Boundary_loss: 0.013895 (0.013896) Loss: 0.33726 (0.35012) +2025-09-13,20:41:18 | INFO | Train Epoch: 8 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.33913 (0.33623) Boundary_loss: 0.013897 (0.013896) Loss: 0.35302 (0.35013) +2025-09-13,20:41:49 | INFO | Train Epoch: 8 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.33367 (0.33622) Boundary_loss: 0.013895 (0.013896) Loss: 0.34756 (0.35012) +2025-09-13,20:42:20 | INFO | Train Epoch: 8 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.28223 (0.33598) Boundary_loss: 0.013896 (0.013896) Loss: 0.29612 (0.34988) +2025-09-13,20:42:50 | INFO | Train Epoch: 8 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.33271 (0.33597) Boundary_loss: 0.013896 (0.013896) Loss: 0.34661 (0.34986) +2025-09-13,20:43:21 | INFO | Train Epoch: 8 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28442 (0.33574) Boundary_loss: 0.013895 (0.013896) Loss: 0.29832 (0.34964) +2025-09-13,20:43:51 | INFO | Train Epoch: 8 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29770 (0.33557) Boundary_loss: 0.013897 (0.013896) Loss: 0.31160 (0.34947) +2025-09-13,20:44:22 | INFO | Train Epoch: 8 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.39143 (0.33582) Boundary_loss: 0.013896 (0.013896) Loss: 0.40533 (0.34971) +2025-09-13,20:44:52 | INFO | Train Epoch: 8 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.32304 (0.33576) Boundary_loss: 0.013895 (0.013896) Loss: 0.33693 (0.34966) +2025-09-13,20:45:23 | INFO | Train Epoch: 8 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.32753 (0.33573) Boundary_loss: 0.013895 (0.013896) Loss: 0.34142 (0.34962) +2025-09-13,20:45:54 | INFO | Train Epoch: 8 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.27907 (0.33548) Boundary_loss: 0.013897 (0.013896) Loss: 0.29297 (0.34938) +2025-09-13,20:46:24 | INFO | Train Epoch: 8 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32179 (0.33542) Boundary_loss: 0.013895 (0.013896) Loss: 0.33568 (0.34932) +2025-09-13,20:46:55 | INFO | Train Epoch: 8 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.26027 (0.33510) Boundary_loss: 0.013895 (0.013896) Loss: 0.27417 (0.34899) +2025-09-13,20:47:26 | INFO | Train Epoch: 8 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.26622 (0.33480) Boundary_loss: 0.013895 (0.013896) Loss: 0.28011 (0.34870) +2025-09-13,20:47:57 | INFO | Train Epoch: 8 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.29464 (0.33463) Boundary_loss: 0.013896 (0.013896) Loss: 0.30853 (0.34853) +2025-09-13,20:48:28 | INFO | Train Epoch: 8 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28422 (0.33442) Boundary_loss: 0.013897 (0.013896) Loss: 0.29812 (0.34832) +2025-09-13,20:48:59 | INFO | Train Epoch: 8 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.35466 (0.33450) Boundary_loss: 0.013895 (0.013896) Loss: 0.36856 (0.34840) +2025-09-13,20:49:29 | INFO | Train Epoch: 8 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.35521 (0.33459) Boundary_loss: 0.013896 (0.013896) Loss: 0.36910 (0.34849) +2025-09-13,20:50:00 | INFO | Train Epoch: 8 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.34906 (0.33465) Boundary_loss: 0.013897 (0.013896) Loss: 0.36295 (0.34855) +2025-09-13,20:50:31 | INFO | Train Epoch: 8 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.36413 (0.33478) Boundary_loss: 0.013896 (0.013896) Loss: 0.37803 (0.34867) +2025-09-13,20:51:02 | INFO | Train Epoch: 8 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.30476 (0.33465) Boundary_loss: 0.013895 (0.013896) Loss: 0.31866 (0.34855) +2025-09-13,20:51:33 | INFO | Train Epoch: 8 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.25889 (0.33434) Boundary_loss: 0.013895 (0.013896) Loss: 0.27278 (0.34823) +2025-09-13,20:52:04 | INFO | Train Epoch: 8 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.35601 (0.33443) Boundary_loss: 0.013895 (0.013896) Loss: 0.36991 (0.34832) +2025-09-13,20:52:34 | INFO | Train Epoch: 8 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.28783 (0.33424) Boundary_loss: 0.013895 (0.013896) Loss: 0.30173 (0.34813) +2025-09-13,20:53:05 | INFO | Train Epoch: 8 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.38282 (0.33443) Boundary_loss: 0.013895 (0.013896) Loss: 0.39671 (0.34833) +2025-09-13,20:53:36 | INFO | Train Epoch: 8 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.35343 (0.33451) Boundary_loss: 0.013895 (0.013896) Loss: 0.36733 (0.34841) +2025-09-13,20:54:07 | INFO | Train Epoch: 8 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.30772 (0.33440) Boundary_loss: 0.013894 (0.013896) Loss: 0.32161 (0.34830) +2025-09-13,20:54:37 | INFO | Train Epoch: 8 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.32549 (0.33437) Boundary_loss: 0.013896 (0.013896) Loss: 0.33939 (0.34826) +2025-09-13,20:55:08 | INFO | Train Epoch: 8 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.31702 (0.33430) Boundary_loss: 0.013897 (0.013896) Loss: 0.33092 (0.34819) +2025-09-13,20:55:39 | INFO | Train Epoch: 8 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.34865 (0.33435) Boundary_loss: 0.013895 (0.013896) Loss: 0.36255 (0.34825) +2025-09-13,20:56:10 | INFO | Train Epoch: 8 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.36271 (0.33447) Boundary_loss: 0.013896 (0.013896) Loss: 0.37661 (0.34836) +2025-09-13,20:56:41 | INFO | Train Epoch: 8 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.36873 (0.33460) Boundary_loss: 0.013895 (0.013896) Loss: 0.38262 (0.34850) +2025-09-13,20:57:11 | INFO | Train Epoch: 8 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.28540 (0.33441) Boundary_loss: 0.013895 (0.013896) Loss: 0.29929 (0.34831) +2025-09-13,20:57:42 | INFO | Train Epoch: 8 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.37969 (0.33459) Boundary_loss: 0.013895 (0.013896) Loss: 0.39358 (0.34848) +2025-09-13,20:58:13 | INFO | Train Epoch: 8 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.27739 (0.33436) Boundary_loss: 0.013897 (0.013896) Loss: 0.29129 (0.34826) +2025-09-13,20:58:44 | INFO | Train Epoch: 8 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.26321 (0.33409) Boundary_loss: 0.013896 (0.013896) Loss: 0.27710 (0.34798) +2025-09-13,20:59:15 | INFO | Train Epoch: 8 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.27309 (0.33385) Boundary_loss: 0.013896 (0.013896) Loss: 0.28699 (0.34774) +2025-09-13,20:59:46 | INFO | Train Epoch: 8 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.35325 (0.33392) Boundary_loss: 0.013897 (0.013896) Loss: 0.36715 (0.34782) +2025-09-13,21:00:17 | INFO | Train Epoch: 8 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.25721 (0.33363) Boundary_loss: 0.013898 (0.013896) Loss: 0.27111 (0.34752) +2025-09-13,21:00:48 | INFO | Train Epoch: 8 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.33736 (0.33364) Boundary_loss: 0.013896 (0.013896) Loss: 0.35126 (0.34754) +2025-09-13,21:01:19 | INFO | Train Epoch: 8 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.31198 (0.33356) Boundary_loss: 0.013896 (0.013896) Loss: 0.32587 (0.34745) +2025-09-13,21:01:50 | INFO | Train Epoch: 8 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.33603 (0.33357) Boundary_loss: 0.013895 (0.013896) Loss: 0.34993 (0.34746) +2025-09-13,21:02:20 | INFO | Train Epoch: 8 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.33992 (0.33359) Boundary_loss: 0.013896 (0.013896) Loss: 0.35381 (0.34749) +2025-09-13,21:02:51 | INFO | Train Epoch: 8 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.30980 (0.33350) Boundary_loss: 0.013896 (0.013896) Loss: 0.32370 (0.34740) +2025-09-13,21:03:22 | INFO | Train Epoch: 8 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.31472 (0.33343) Boundary_loss: 0.013894 (0.013896) Loss: 0.32861 (0.34733) +2025-09-13,21:03:53 | INFO | Train Epoch: 8 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.27814 (0.33322) Boundary_loss: 0.013895 (0.013896) Loss: 0.29204 (0.34712) +2025-09-13,21:04:24 | INFO | Train Epoch: 8 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.33050 (0.33321) Boundary_loss: 0.013897 (0.013896) Loss: 0.34440 (0.34711) +2025-09-13,21:04:55 | INFO | Train Epoch: 8 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.35994 (0.33331) Boundary_loss: 0.013896 (0.013896) Loss: 0.37384 (0.34721) +2025-09-13,21:05:26 | INFO | Train Epoch: 8 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.36210 (0.33342) Boundary_loss: 0.013897 (0.013896) Loss: 0.37600 (0.34732) +2025-09-13,21:05:57 | INFO | Train Epoch: 8 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.42748 (0.33377) Boundary_loss: 0.013893 (0.013896) Loss: 0.44137 (0.34766) +2025-09-13,21:06:27 | INFO | Train Epoch: 8 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.34218 (0.33380) Boundary_loss: 0.013894 (0.013896) Loss: 0.35608 (0.34769) +2025-09-13,21:06:58 | INFO | Train Epoch: 8 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.32427 (0.33376) Boundary_loss: 0.013895 (0.013896) Loss: 0.33817 (0.34766) +2025-09-13,21:07:29 | INFO | Train Epoch: 8 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.38052 (0.33394) Boundary_loss: 0.013895 (0.013896) Loss: 0.39441 (0.34783) +2025-09-13,21:07:59 | INFO | Train Epoch: 8 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.28570 (0.33376) Boundary_loss: 0.013898 (0.013896) Loss: 0.29960 (0.34766) +2025-09-13,21:08:30 | INFO | Train Epoch: 8 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.30732 (0.33366) Boundary_loss: 0.013896 (0.013896) Loss: 0.32121 (0.34756) +2025-09-13,21:09:01 | INFO | Train Epoch: 8 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.27859 (0.33346) Boundary_loss: 0.013896 (0.013896) Loss: 0.29249 (0.34736) +2025-09-13,21:09:32 | INFO | Train Epoch: 8 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.29071 (0.33331) Boundary_loss: 0.013894 (0.013896) Loss: 0.30460 (0.34721) +2025-09-13,21:10:03 | INFO | Train Epoch: 8 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.25738 (0.33304) Boundary_loss: 0.013896 (0.013896) Loss: 0.27128 (0.34693) +2025-09-13,21:10:34 | INFO | Train Epoch: 8 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.35030 (0.33310) Boundary_loss: 0.013896 (0.013896) Loss: 0.36419 (0.34699) +2025-09-13,21:11:05 | INFO | Train Epoch: 8 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.31367 (0.33303) Boundary_loss: 0.013897 (0.013896) Loss: 0.32756 (0.34692) +2025-09-13,21:11:35 | INFO | Train Epoch: 8 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.33827 (0.33305) Boundary_loss: 0.013897 (0.013896) Loss: 0.35217 (0.34694) +2025-09-13,21:12:06 | INFO | Train Epoch: 8 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.28612 (0.33288) Boundary_loss: 0.013897 (0.013896) Loss: 0.30002 (0.34678) +2025-09-13,21:12:37 | INFO | Train Epoch: 8 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.35070 (0.33294) Boundary_loss: 0.013896 (0.013896) Loss: 0.36460 (0.34684) +2025-09-13,21:13:08 | INFO | Train Epoch: 8 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.28948 (0.33279) Boundary_loss: 0.013895 (0.013896) Loss: 0.30338 (0.34669) +2025-09-13,21:13:38 | INFO | Train Epoch: 8 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.45483 (0.33322) Boundary_loss: 0.013895 (0.013896) Loss: 0.46872 (0.34711) +2025-09-13,21:14:09 | INFO | Train Epoch: 8 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.41758 (0.33351) Boundary_loss: 0.013898 (0.013896) Loss: 0.43147 (0.34741) +2025-09-13,21:14:40 | INFO | Train Epoch: 8 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.31528 (0.33345) Boundary_loss: 0.013896 (0.013896) Loss: 0.32917 (0.34735) +2025-09-13,21:15:11 | INFO | Train Epoch: 8 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.29914 (0.33333) Boundary_loss: 0.013897 (0.013896) Loss: 0.31304 (0.34723) +2025-09-13,21:15:42 | INFO | Train Epoch: 8 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.33837 (0.33335) Boundary_loss: 0.013898 (0.013896) Loss: 0.35226 (0.34724) +2025-09-13,21:16:13 | INFO | Train Epoch: 8 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.31235 (0.33328) Boundary_loss: 0.013895 (0.013896) Loss: 0.32625 (0.34717) +2025-09-13,21:16:44 | INFO | Train Epoch: 8 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.33673 (0.33329) Boundary_loss: 0.013896 (0.013896) Loss: 0.35063 (0.34718) +2025-09-13,21:17:15 | INFO | Train Epoch: 8 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.35967 (0.33338) Boundary_loss: 0.013897 (0.013896) Loss: 0.37357 (0.34727) +2025-09-13,21:17:46 | INFO | Train Epoch: 8 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.30542 (0.33328) Boundary_loss: 0.013896 (0.013896) Loss: 0.31932 (0.34718) +2025-09-13,21:18:16 | INFO | Train Epoch: 8 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.31714 (0.33323) Boundary_loss: 0.013896 (0.013896) Loss: 0.33103 (0.34712) +2025-09-13,21:18:47 | INFO | Train Epoch: 8 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35133 (0.33329) Boundary_loss: 0.013897 (0.013896) Loss: 0.36522 (0.34719) +2025-09-13,21:19:18 | INFO | Train Epoch: 8 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.34885 (0.33334) Boundary_loss: 0.013895 (0.013896) Loss: 0.36274 (0.34724) +2025-09-13,21:19:49 | INFO | Train Epoch: 8 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.46202 (0.33378) Boundary_loss: 0.013897 (0.013896) Loss: 0.47592 (0.34767) +2025-09-13,21:20:20 | INFO | Train Epoch: 8 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.42159 (0.33407) Boundary_loss: 0.013895 (0.013896) Loss: 0.43548 (0.34797) +2025-09-13,21:20:50 | INFO | Train Epoch: 8 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.32916 (0.33405) Boundary_loss: 0.013896 (0.013896) Loss: 0.34306 (0.34795) +2025-09-13,21:21:21 | INFO | Train Epoch: 8 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.32922 (0.33404) Boundary_loss: 0.013899 (0.013896) Loss: 0.34312 (0.34793) +2025-09-13,21:21:52 | INFO | Train Epoch: 8 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30783 (0.33395) Boundary_loss: 0.013895 (0.013896) Loss: 0.32172 (0.34785) +2025-09-13,21:22:23 | INFO | Train Epoch: 8 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.35758 (0.33403) Boundary_loss: 0.013895 (0.013896) Loss: 0.37148 (0.34792) +2025-09-13,21:22:53 | INFO | Train Epoch: 8 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.37470 (0.33416) Boundary_loss: 0.013895 (0.013896) Loss: 0.38860 (0.34806) +2025-09-13,21:23:24 | INFO | Train Epoch: 8 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.32309 (0.33413) Boundary_loss: 0.013895 (0.013896) Loss: 0.33699 (0.34802) +2025-09-13,21:23:55 | INFO | Train Epoch: 8 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.34223 (0.33415) Boundary_loss: 0.013896 (0.013896) Loss: 0.35612 (0.34805) +2025-09-13,21:24:25 | INFO | Train Epoch: 8 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.41190 (0.33441) Boundary_loss: 0.013896 (0.013896) Loss: 0.42580 (0.34830) +2025-09-13,21:24:56 | INFO | Train Epoch: 8 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.33259 (0.33440) Boundary_loss: 0.013896 (0.013896) Loss: 0.34649 (0.34830) +2025-09-13,21:25:27 | INFO | Train Epoch: 8 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.36885 (0.33451) Boundary_loss: 0.013896 (0.013896) Loss: 0.38274 (0.34841) +2025-09-13,21:25:57 | INFO | Train Epoch: 8 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.25697 (0.33426) Boundary_loss: 0.013896 (0.013896) Loss: 0.27087 (0.34816) +2025-09-13,21:26:28 | INFO | Train Epoch: 8 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.36141 (0.33435) Boundary_loss: 0.013897 (0.013896) Loss: 0.37531 (0.34825) +2025-09-13,21:26:59 | INFO | Train Epoch: 8 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.29629 (0.33423) Boundary_loss: 0.013897 (0.013896) Loss: 0.31018 (0.34812) +2025-09-13,21:27:30 | INFO | Train Epoch: 8 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.24515 (0.33394) Boundary_loss: 0.013898 (0.013896) Loss: 0.25905 (0.34784) +2025-09-13,21:28:01 | INFO | Train Epoch: 8 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.32836 (0.33392) Boundary_loss: 0.013896 (0.013896) Loss: 0.34226 (0.34782) +2025-09-13,21:28:32 | INFO | Train Epoch: 8 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.25501 (0.33367) Boundary_loss: 0.013896 (0.013896) Loss: 0.26890 (0.34757) +2025-09-13,21:29:03 | INFO | Train Epoch: 8 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.22822 (0.33334) Boundary_loss: 0.013895 (0.013896) Loss: 0.24211 (0.34723) +2025-09-13,21:29:34 | INFO | Train Epoch: 8 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.33849 (0.33335) Boundary_loss: 0.013895 (0.013896) Loss: 0.35238 (0.34725) +2025-09-13,21:30:04 | INFO | Train Epoch: 8 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.29821 (0.33324) Boundary_loss: 0.013895 (0.013896) Loss: 0.31211 (0.34714) +2025-09-13,21:30:35 | INFO | Train Epoch: 8 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.44035 (0.33358) Boundary_loss: 0.013895 (0.013896) Loss: 0.45425 (0.34748) +2025-09-13,21:31:06 | INFO | Train Epoch: 8 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.30730 (0.33350) Boundary_loss: 0.013897 (0.013896) Loss: 0.32120 (0.34739) +2025-09-13,21:31:37 | INFO | Train Epoch: 8 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.33132 (0.33349) Boundary_loss: 0.013896 (0.013896) Loss: 0.34521 (0.34739) +2025-09-13,21:32:08 | INFO | Train Epoch: 8 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.32884 (0.33348) Boundary_loss: 0.013895 (0.013896) Loss: 0.34273 (0.34737) +2025-09-13,21:32:39 | INFO | Train Epoch: 8 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.34646 (0.33352) Boundary_loss: 0.013895 (0.013896) Loss: 0.36036 (0.34741) +2025-09-13,21:33:09 | INFO | Train Epoch: 8 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31639 (0.33346) Boundary_loss: 0.013896 (0.013896) Loss: 0.33029 (0.34736) +2025-09-13,21:33:40 | INFO | Train Epoch: 8 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.41771 (0.33372) Boundary_loss: 0.013896 (0.013896) Loss: 0.43161 (0.34762) +2025-09-13,21:34:11 | INFO | Train Epoch: 8 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.35892 (0.33380) Boundary_loss: 0.013894 (0.013896) Loss: 0.37282 (0.34770) +2025-09-13,21:34:42 | INFO | Train Epoch: 8 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.30171 (0.33370) Boundary_loss: 0.013895 (0.013896) Loss: 0.31560 (0.34760) +2025-09-13,21:35:13 | INFO | Train Epoch: 8 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.28529 (0.33355) Boundary_loss: 0.013895 (0.013896) Loss: 0.29918 (0.34745) +2025-09-13,21:35:43 | INFO | Train Epoch: 8 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.27333 (0.33337) Boundary_loss: 0.013897 (0.013896) Loss: 0.28723 (0.34727) +2025-09-13,21:36:14 | INFO | Train Epoch: 8 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.32247 (0.33334) Boundary_loss: 0.013896 (0.013896) Loss: 0.33636 (0.34723) +2025-09-13,21:36:45 | INFO | Train Epoch: 8 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.36285 (0.33343) Boundary_loss: 0.013897 (0.013896) Loss: 0.37675 (0.34732) +2025-09-13,21:37:16 | INFO | Train Epoch: 8 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.34757 (0.33347) Boundary_loss: 0.013895 (0.013896) Loss: 0.36146 (0.34737) +2025-09-13,21:37:47 | INFO | Train Epoch: 8 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27775 (0.33330) Boundary_loss: 0.013897 (0.013896) Loss: 0.29165 (0.34720) +2025-09-13,21:38:18 | INFO | Train Epoch: 8 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.31395 (0.33324) Boundary_loss: 0.013898 (0.013896) Loss: 0.32785 (0.34714) +2025-09-13,21:38:49 | INFO | Train Epoch: 8 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.36076 (0.33333) Boundary_loss: 0.013897 (0.013896) Loss: 0.37466 (0.34722) +2025-09-13,21:39:20 | INFO | Train Epoch: 8 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.30608 (0.33325) Boundary_loss: 0.013894 (0.013896) Loss: 0.31998 (0.34714) +2025-09-13,21:39:50 | INFO | Train Epoch: 8 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.33292 (0.33324) Boundary_loss: 0.013898 (0.013896) Loss: 0.34682 (0.34714) +2025-09-13,21:40:21 | INFO | Train Epoch: 8 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28685 (0.33311) Boundary_loss: 0.013897 (0.013896) Loss: 0.30075 (0.34700) +2025-09-13,21:40:52 | INFO | Train Epoch: 8 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.26414 (0.33290) Boundary_loss: 0.013897 (0.013896) Loss: 0.27804 (0.34680) +2025-09-13,21:41:23 | INFO | Train Epoch: 8 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.27310 (0.33273) Boundary_loss: 0.013898 (0.013896) Loss: 0.28700 (0.34662) +2025-09-13,21:41:54 | INFO | Train Epoch: 8 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.25867 (0.33251) Boundary_loss: 0.013895 (0.013896) Loss: 0.27257 (0.34640) +2025-09-13,21:42:25 | INFO | Train Epoch: 8 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.35447 (0.33257) Boundary_loss: 0.013894 (0.013896) Loss: 0.36836 (0.34647) +2025-09-13,21:42:56 | INFO | Train Epoch: 8 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.27990 (0.33242) Boundary_loss: 0.013895 (0.013896) Loss: 0.29379 (0.34631) +2025-09-13,21:43:27 | INFO | Train Epoch: 8 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.32355 (0.33239) Boundary_loss: 0.013895 (0.013896) Loss: 0.33744 (0.34629) +2025-09-13,21:43:57 | INFO | Train Epoch: 8 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.34270 (0.33242) Boundary_loss: 0.013895 (0.013896) Loss: 0.35659 (0.34632) +2025-09-13,21:44:28 | INFO | Train Epoch: 8 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.34231 (0.33245) Boundary_loss: 0.013896 (0.013896) Loss: 0.35621 (0.34635) +2025-09-13,21:44:59 | INFO | Train Epoch: 8 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.37079 (0.33256) Boundary_loss: 0.013895 (0.013896) Loss: 0.38468 (0.34646) +2025-09-13,21:45:30 | INFO | Train Epoch: 8 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.35172 (0.33262) Boundary_loss: 0.013898 (0.013896) Loss: 0.36562 (0.34651) +2025-09-13,21:46:01 | INFO | Train Epoch: 8 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.36429 (0.33271) Boundary_loss: 0.013896 (0.013896) Loss: 0.37818 (0.34660) +2025-09-13,21:46:32 | INFO | Train Epoch: 8 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.26385 (0.33251) Boundary_loss: 0.013898 (0.013896) Loss: 0.27775 (0.34641) +2025-09-13,21:47:03 | INFO | Train Epoch: 8 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27828 (0.33236) Boundary_loss: 0.013896 (0.013896) Loss: 0.29218 (0.34625) +2025-09-13,21:47:34 | INFO | Train Epoch: 8 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.38431 (0.33250) Boundary_loss: 0.013895 (0.013896) Loss: 0.39821 (0.34640) +2025-09-13,21:48:05 | INFO | Train Epoch: 8 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32188 (0.33247) Boundary_loss: 0.013896 (0.013896) Loss: 0.33578 (0.34637) +2025-09-13,21:48:35 | INFO | Train Epoch: 8 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.30727 (0.33240) Boundary_loss: 0.013896 (0.013896) Loss: 0.32116 (0.34630) +2025-09-13,21:49:06 | INFO | Train Epoch: 8 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.32320 (0.33238) Boundary_loss: 0.013896 (0.013896) Loss: 0.33709 (0.34627) +2025-09-13,21:49:37 | INFO | Train Epoch: 8 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.31383 (0.33232) Boundary_loss: 0.013896 (0.013896) Loss: 0.32773 (0.34622) +2025-09-13,21:50:08 | INFO | Train Epoch: 8 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.31801 (0.33228) Boundary_loss: 0.013896 (0.013896) Loss: 0.33190 (0.34618) +2025-09-13,21:50:39 | INFO | Train Epoch: 8 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.31805 (0.33224) Boundary_loss: 0.013896 (0.013896) Loss: 0.33194 (0.34614) +2025-09-13,21:51:10 | INFO | Train Epoch: 8 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.35384 (0.33230) Boundary_loss: 0.013896 (0.013896) Loss: 0.36774 (0.34620) +2025-09-13,21:51:41 | INFO | Train Epoch: 8 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31657 (0.33226) Boundary_loss: 0.013896 (0.013896) Loss: 0.33047 (0.34616) +2025-09-13,21:52:12 | INFO | Train Epoch: 8 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.32684 (0.33225) Boundary_loss: 0.013896 (0.013896) Loss: 0.34074 (0.34614) +2025-09-13,21:52:43 | INFO | Train Epoch: 8 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.40086 (0.33244) Boundary_loss: 0.013896 (0.013896) Loss: 0.41476 (0.34633) +2025-09-13,21:53:13 | INFO | Train Epoch: 8 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.32771 (0.33242) Boundary_loss: 0.013897 (0.013896) Loss: 0.34161 (0.34632) +2025-09-13,21:53:44 | INFO | Train Epoch: 8 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.36015 (0.33250) Boundary_loss: 0.013895 (0.013896) Loss: 0.37405 (0.34640) +2025-09-13,21:54:15 | INFO | Train Epoch: 8 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.28703 (0.33237) Boundary_loss: 0.013897 (0.013896) Loss: 0.30093 (0.34627) +2025-09-13,21:54:45 | INFO | Train Epoch: 8 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.30332 (0.33229) Boundary_loss: 0.013894 (0.013896) Loss: 0.31721 (0.34619) +2025-09-13,21:55:16 | INFO | Train Epoch: 8 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.30477 (0.33222) Boundary_loss: 0.013894 (0.013896) Loss: 0.31867 (0.34612) +2025-09-13,21:55:47 | INFO | Train Epoch: 8 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.27949 (0.33208) Boundary_loss: 0.013896 (0.013896) Loss: 0.29339 (0.34597) +2025-09-13,21:56:17 | INFO | Train Epoch: 8 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.31222 (0.33202) Boundary_loss: 0.013895 (0.013896) Loss: 0.32611 (0.34592) +2025-09-13,21:56:48 | INFO | Train Epoch: 8 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.35602 (0.33209) Boundary_loss: 0.013896 (0.013896) Loss: 0.36991 (0.34598) +2025-09-13,21:57:19 | INFO | Train Epoch: 8 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.31662 (0.33205) Boundary_loss: 0.013897 (0.013896) Loss: 0.33052 (0.34594) +2025-09-13,21:57:50 | INFO | Train Epoch: 8 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.32787 (0.33203) Boundary_loss: 0.013895 (0.013896) Loss: 0.34176 (0.34593) +2025-09-13,21:58:21 | INFO | Train Epoch: 8 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.39566 (0.33220) Boundary_loss: 0.013896 (0.013896) Loss: 0.40956 (0.34610) +2025-09-13,21:58:51 | INFO | Train Epoch: 8 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.22241 (0.33191) Boundary_loss: 0.013895 (0.013896) Loss: 0.23630 (0.34581) +2025-09-13,21:59:22 | INFO | Train Epoch: 8 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.30778 (0.33185) Boundary_loss: 0.013895 (0.013896) Loss: 0.32168 (0.34574) +2025-09-13,21:59:53 | INFO | Train Epoch: 8 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.34645 (0.33188) Boundary_loss: 0.013896 (0.013896) Loss: 0.36034 (0.34578) +2025-09-13,22:00:24 | INFO | Train Epoch: 8 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.33439 (0.33189) Boundary_loss: 0.013896 (0.013896) Loss: 0.34828 (0.34579) +2025-09-13,22:00:54 | INFO | Train Epoch: 8 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.27080 (0.33173) Boundary_loss: 0.013896 (0.013896) Loss: 0.28470 (0.34563) +2025-09-13,22:01:25 | INFO | Train Epoch: 8 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.30682 (0.33166) Boundary_loss: 0.013895 (0.013896) Loss: 0.32071 (0.34556) +2025-09-13,22:01:56 | INFO | Train Epoch: 8 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.35540 (0.33173) Boundary_loss: 0.013895 (0.013896) Loss: 0.36930 (0.34562) +2025-09-13,22:02:27 | INFO | Train Epoch: 8 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.30675 (0.33166) Boundary_loss: 0.013896 (0.013896) Loss: 0.32065 (0.34556) +2025-09-13,22:02:58 | INFO | Train Epoch: 8 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.30120 (0.33158) Boundary_loss: 0.013895 (0.013896) Loss: 0.31509 (0.34548) +2025-09-13,22:03:28 | INFO | Train Epoch: 8 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35296 (0.33164) Boundary_loss: 0.013895 (0.013896) Loss: 0.36685 (0.34553) +2025-09-13,22:03:59 | INFO | Train Epoch: 8 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.29270 (0.33153) Boundary_loss: 0.013895 (0.013896) Loss: 0.30659 (0.34543) +2025-09-13,22:04:30 | INFO | Train Epoch: 8 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.33811 (0.33155) Boundary_loss: 0.013896 (0.013896) Loss: 0.35200 (0.34545) +2025-09-13,22:05:00 | INFO | Train Epoch: 8 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.29849 (0.33147) Boundary_loss: 0.013897 (0.013896) Loss: 0.31239 (0.34536) +2025-09-13,22:05:31 | INFO | Train Epoch: 8 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27101 (0.33131) Boundary_loss: 0.013896 (0.013896) Loss: 0.28491 (0.34521) +2025-09-13,22:06:02 | INFO | Train Epoch: 8 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.33833 (0.33133) Boundary_loss: 0.013897 (0.013896) Loss: 0.35223 (0.34522) +2025-09-13,22:06:33 | INFO | Train Epoch: 8 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.41693 (0.33155) Boundary_loss: 0.013895 (0.013896) Loss: 0.43083 (0.34544) +2025-09-13,22:07:04 | INFO | Train Epoch: 8 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.31180 (0.33150) Boundary_loss: 0.013897 (0.013896) Loss: 0.32570 (0.34539) +2025-09-13,22:07:34 | INFO | Train Epoch: 8 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.32734 (0.33149) Boundary_loss: 0.013897 (0.013896) Loss: 0.34124 (0.34538) +2025-09-13,22:08:05 | INFO | Train Epoch: 8 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.33114 (0.33149) Boundary_loss: 0.013896 (0.013896) Loss: 0.34504 (0.34538) +2025-09-13,22:08:36 | INFO | Train Epoch: 8 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.27211 (0.33133) Boundary_loss: 0.013895 (0.013896) Loss: 0.28600 (0.34523) +2025-09-13,22:09:07 | INFO | Train Epoch: 8 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.38047 (0.33146) Boundary_loss: 0.013896 (0.013896) Loss: 0.39437 (0.34536) +2025-09-13,22:09:38 | INFO | Train Epoch: 8 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.32044 (0.33143) Boundary_loss: 0.013898 (0.013896) Loss: 0.33433 (0.34533) +2025-09-13,22:10:08 | INFO | Train Epoch: 8 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.28697 (0.33132) Boundary_loss: 0.013895 (0.013896) Loss: 0.30086 (0.34522) +2025-09-13,22:10:39 | INFO | Train Epoch: 8 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.26716 (0.33116) Boundary_loss: 0.013896 (0.013896) Loss: 0.28106 (0.34505) +2025-09-13,22:11:10 | INFO | Train Epoch: 8 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.35317 (0.33121) Boundary_loss: 0.013894 (0.013896) Loss: 0.36707 (0.34511) +2025-09-13,22:11:41 | INFO | Train Epoch: 8 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.35579 (0.33127) Boundary_loss: 0.013895 (0.013896) Loss: 0.36968 (0.34517) +2025-09-13,22:12:12 | INFO | Train Epoch: 8 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31561 (0.33123) Boundary_loss: 0.013895 (0.013896) Loss: 0.32951 (0.34513) +2025-09-13,22:12:43 | INFO | Train Epoch: 8 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.27567 (0.33110) Boundary_loss: 0.013895 (0.013896) Loss: 0.28956 (0.34499) +2025-09-13,22:13:14 | INFO | Train Epoch: 8 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.23407 (0.33085) Boundary_loss: 0.013896 (0.013896) Loss: 0.24796 (0.34475) +2025-09-13,22:13:44 | INFO | Train Epoch: 8 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.29457 (0.33076) Boundary_loss: 0.013894 (0.013896) Loss: 0.30847 (0.34466) +2025-09-13,22:14:15 | INFO | Train Epoch: 8 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.29159 (0.33067) Boundary_loss: 0.013897 (0.013896) Loss: 0.30549 (0.34456) +2025-09-13,22:14:46 | INFO | Train Epoch: 8 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.33539 (0.33068) Boundary_loss: 0.013894 (0.013896) Loss: 0.34928 (0.34457) +2025-09-13,22:15:17 | INFO | Train Epoch: 8 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.31969 (0.33065) Boundary_loss: 0.013897 (0.013896) Loss: 0.33358 (0.34455) +2025-09-13,22:15:48 | INFO | Train Epoch: 8 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.37606 (0.33076) Boundary_loss: 0.013896 (0.013896) Loss: 0.38996 (0.34466) +2025-09-13,22:16:18 | INFO | Train Epoch: 8 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.26674 (0.33061) Boundary_loss: 0.013897 (0.013896) Loss: 0.28064 (0.34450) +2025-09-13,22:16:49 | INFO | Train Epoch: 8 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.30069 (0.33053) Boundary_loss: 0.013895 (0.013896) Loss: 0.31459 (0.34443) +2025-09-13,22:17:20 | INFO | Train Epoch: 8 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27489 (0.33040) Boundary_loss: 0.013895 (0.013896) Loss: 0.28879 (0.34429) +2025-09-13,22:17:50 | INFO | Train Epoch: 8 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.35384 (0.33045) Boundary_loss: 0.013896 (0.013896) Loss: 0.36774 (0.34435) +2025-09-13,22:18:21 | INFO | Train Epoch: 8 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.31699 (0.33042) Boundary_loss: 0.013897 (0.013896) Loss: 0.33089 (0.34432) +2025-09-13,22:18:52 | INFO | Train Epoch: 8 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.30703 (0.33036) Boundary_loss: 0.013895 (0.013896) Loss: 0.32093 (0.34426) +2025-09-13,22:19:22 | INFO | Train Epoch: 8 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.35192 (0.33042) Boundary_loss: 0.013895 (0.013896) Loss: 0.36582 (0.34431) +2025-09-13,22:19:53 | INFO | Train Epoch: 8 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28150 (0.33030) Boundary_loss: 0.013896 (0.013896) Loss: 0.29539 (0.34419) +2025-09-13,22:20:24 | INFO | Train Epoch: 8 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.30555 (0.33024) Boundary_loss: 0.013895 (0.013896) Loss: 0.31944 (0.34413) +2025-09-13,22:20:55 | INFO | Train Epoch: 8 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.35884 (0.33031) Boundary_loss: 0.013896 (0.013896) Loss: 0.37274 (0.34420) +2025-09-13,22:21:26 | INFO | Train Epoch: 8 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.32523 (0.33029) Boundary_loss: 0.013896 (0.013896) Loss: 0.33912 (0.34419) +2025-09-13,22:21:56 | INFO | Train Epoch: 8 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.35181 (0.33035) Boundary_loss: 0.013897 (0.013896) Loss: 0.36571 (0.34424) +2025-09-13,22:22:27 | INFO | Train Epoch: 8 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.36476 (0.33043) Boundary_loss: 0.013896 (0.013896) Loss: 0.37865 (0.34432) +2025-09-13,22:22:58 | INFO | Train Epoch: 8 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.35495 (0.33049) Boundary_loss: 0.013896 (0.013896) Loss: 0.36885 (0.34438) +2025-09-13,22:23:29 | INFO | Train Epoch: 8 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.29414 (0.33040) Boundary_loss: 0.013896 (0.013896) Loss: 0.30803 (0.34430) +2025-09-13,22:23:59 | INFO | Train Epoch: 8 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.28087 (0.33028) Boundary_loss: 0.013895 (0.013896) Loss: 0.29477 (0.34418) +2025-09-13,22:24:30 | INFO | Train Epoch: 8 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.40871 (0.33047) Boundary_loss: 0.013896 (0.013896) Loss: 0.42261 (0.34436) +2025-09-13,22:25:01 | INFO | Train Epoch: 8 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31545 (0.33043) Boundary_loss: 0.013896 (0.013896) Loss: 0.32935 (0.34433) +2025-09-13,22:25:32 | INFO | Train Epoch: 8 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.33070 (0.33043) Boundary_loss: 0.013897 (0.013896) Loss: 0.34459 (0.34433) +2025-09-13,22:26:02 | INFO | Train Epoch: 8 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.32972 (0.33043) Boundary_loss: 0.013896 (0.013896) Loss: 0.34362 (0.34433) +2025-09-13,22:26:33 | INFO | Train Epoch: 8 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.28561 (0.33033) Boundary_loss: 0.013896 (0.013896) Loss: 0.29951 (0.34422) +2025-09-13,22:27:04 | INFO | Train Epoch: 8 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.34039 (0.33035) Boundary_loss: 0.013895 (0.013896) Loss: 0.35429 (0.34425) +2025-09-13,22:27:35 | INFO | Train Epoch: 8 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.38055 (0.33047) Boundary_loss: 0.013896 (0.013896) Loss: 0.39444 (0.34436) +2025-09-13,22:28:06 | INFO | Train Epoch: 8 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.29211 (0.33038) Boundary_loss: 0.013894 (0.013896) Loss: 0.30600 (0.34427) +2025-09-13,22:28:36 | INFO | Train Epoch: 8 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24668 (0.33018) Boundary_loss: 0.013895 (0.013896) Loss: 0.26057 (0.34408) +2025-09-13,22:29:07 | INFO | Train Epoch: 8 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.30367 (0.33012) Boundary_loss: 0.013896 (0.013896) Loss: 0.31756 (0.34402) +2025-09-13,22:29:38 | INFO | Train Epoch: 8 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.35427 (0.33018) Boundary_loss: 0.013896 (0.013896) Loss: 0.36817 (0.34407) +2025-09-13,22:30:08 | INFO | Train Epoch: 8 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.38564 (0.33031) Boundary_loss: 0.013896 (0.013896) Loss: 0.39954 (0.34420) +2025-09-13,22:30:39 | INFO | Train Epoch: 8 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.31147 (0.33026) Boundary_loss: 0.013896 (0.013896) Loss: 0.32536 (0.34416) +2025-09-13,22:31:10 | INFO | Train Epoch: 8 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.34345 (0.33029) Boundary_loss: 0.013896 (0.013896) Loss: 0.35735 (0.34419) +2025-09-13,22:31:41 | INFO | Train Epoch: 8 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.32769 (0.33029) Boundary_loss: 0.013896 (0.013896) Loss: 0.34158 (0.34418) +2025-09-13,22:32:12 | INFO | Train Epoch: 8 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26044 (0.33013) Boundary_loss: 0.013895 (0.013896) Loss: 0.27433 (0.34402) +2025-09-13,22:32:42 | INFO | Train Epoch: 8 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.32855 (0.33012) Boundary_loss: 0.013895 (0.013896) Loss: 0.34244 (0.34402) +2025-09-13,22:33:13 | INFO | Train Epoch: 8 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.24522 (0.32993) Boundary_loss: 0.013894 (0.013896) Loss: 0.25912 (0.34383) +2025-09-13,22:33:44 | INFO | Train Epoch: 8 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.26913 (0.32979) Boundary_loss: 0.013896 (0.013896) Loss: 0.28302 (0.34369) +2025-09-13,22:34:15 | INFO | Train Epoch: 8 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.36854 (0.32988) Boundary_loss: 0.013897 (0.013896) Loss: 0.38244 (0.34378) +2025-09-13,22:34:46 | INFO | Train Epoch: 8 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.31521 (0.32985) Boundary_loss: 0.013898 (0.013896) Loss: 0.32911 (0.34374) +2025-09-13,22:35:16 | INFO | Train Epoch: 8 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.36853 (0.32994) Boundary_loss: 0.013896 (0.013896) Loss: 0.38242 (0.34383) +2025-09-13,22:35:47 | INFO | Train Epoch: 8 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.30588 (0.32988) Boundary_loss: 0.013895 (0.013896) Loss: 0.31977 (0.34378) +2025-09-13,22:36:18 | INFO | Train Epoch: 8 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.41873 (0.33008) Boundary_loss: 0.013896 (0.013896) Loss: 0.43263 (0.34398) +2025-09-13,22:36:49 | INFO | Train Epoch: 8 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.23326 (0.32986) Boundary_loss: 0.013897 (0.013896) Loss: 0.24715 (0.34376) +2025-09-13,22:37:20 | INFO | Train Epoch: 8 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.29072 (0.32978) Boundary_loss: 0.013896 (0.013896) Loss: 0.30461 (0.34367) +2025-09-13,22:37:50 | INFO | Train Epoch: 8 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.30971 (0.32973) Boundary_loss: 0.013895 (0.013896) Loss: 0.32360 (0.34363) +2025-09-13,22:38:21 | INFO | Train Epoch: 8 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.33018 (0.32973) Boundary_loss: 0.013895 (0.013896) Loss: 0.34408 (0.34363) +2025-09-13,22:38:52 | INFO | Train Epoch: 8 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.34082 (0.32976) Boundary_loss: 0.013896 (0.013896) Loss: 0.35471 (0.34365) +2025-09-13,22:39:22 | INFO | Train Epoch: 8 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.34277 (0.32979) Boundary_loss: 0.013896 (0.013896) Loss: 0.35667 (0.34368) +2025-09-13,22:39:53 | INFO | Train Epoch: 8 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.28186 (0.32968) Boundary_loss: 0.013896 (0.013896) Loss: 0.29575 (0.34358) +2025-09-13,22:40:24 | INFO | Train Epoch: 8 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.34670 (0.32972) Boundary_loss: 0.013896 (0.013896) Loss: 0.36059 (0.34361) +2025-09-13,22:40:54 | INFO | Train Epoch: 8 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.32117 (0.32970) Boundary_loss: 0.013897 (0.013896) Loss: 0.33506 (0.34359) +2025-09-13,22:41:25 | INFO | Train Epoch: 8 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.30788 (0.32965) Boundary_loss: 0.013895 (0.013896) Loss: 0.32177 (0.34355) +2025-09-13,22:41:56 | INFO | Train Epoch: 8 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.39814 (0.32980) Boundary_loss: 0.013897 (0.013896) Loss: 0.41204 (0.34370) +2025-09-13,22:42:27 | INFO | Train Epoch: 8 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.29825 (0.32973) Boundary_loss: 0.013895 (0.013896) Loss: 0.31215 (0.34363) +2025-09-13,22:42:58 | INFO | Train Epoch: 8 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.29551 (0.32966) Boundary_loss: 0.013896 (0.013896) Loss: 0.30940 (0.34355) +2025-09-13,22:43:29 | INFO | Train Epoch: 8 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.25429 (0.32949) Boundary_loss: 0.013895 (0.013896) Loss: 0.26818 (0.34339) +2025-09-13,22:44:00 | INFO | Train Epoch: 8 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.30780 (0.32945) Boundary_loss: 0.013898 (0.013896) Loss: 0.32170 (0.34334) +2025-09-13,22:44:31 | INFO | Train Epoch: 8 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.29477 (0.32937) Boundary_loss: 0.013895 (0.013896) Loss: 0.30866 (0.34327) +2025-09-13,22:45:02 | INFO | Train Epoch: 8 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.39709 (0.32952) Boundary_loss: 0.013895 (0.013896) Loss: 0.41099 (0.34341) +2025-09-13,22:45:32 | INFO | Train Epoch: 8 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.38227 (0.32963) Boundary_loss: 0.013896 (0.013896) Loss: 0.39617 (0.34353) +2025-09-13,22:46:03 | INFO | Train Epoch: 8 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.28360 (0.32953) Boundary_loss: 0.013895 (0.013896) Loss: 0.29749 (0.34343) +2025-09-13,22:46:34 | INFO | Train Epoch: 8 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.30810 (0.32949) Boundary_loss: 0.013895 (0.013896) Loss: 0.32200 (0.34338) +2025-09-13,22:47:04 | INFO | Train Epoch: 8 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.35865 (0.32955) Boundary_loss: 0.013898 (0.013896) Loss: 0.37255 (0.34344) +2025-09-13,22:47:35 | INFO | Train Epoch: 8 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.30753 (0.32950) Boundary_loss: 0.013896 (0.013896) Loss: 0.32143 (0.34340) +2025-09-13,22:48:06 | INFO | Train Epoch: 8 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.31647 (0.32947) Boundary_loss: 0.013895 (0.013896) Loss: 0.33037 (0.34337) +2025-09-13,22:48:37 | INFO | Train Epoch: 8 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.34657 (0.32951) Boundary_loss: 0.013895 (0.013896) Loss: 0.36047 (0.34341) +2025-09-13,22:49:07 | INFO | Train Epoch: 8 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.27008 (0.32938) Boundary_loss: 0.013895 (0.013896) Loss: 0.28398 (0.34328) +2025-09-13,22:49:38 | INFO | Train Epoch: 8 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.30635 (0.32934) Boundary_loss: 0.013896 (0.013896) Loss: 0.32025 (0.34323) +2025-09-13,22:50:09 | INFO | Train Epoch: 8 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.37012 (0.32942) Boundary_loss: 0.013895 (0.013896) Loss: 0.38401 (0.34332) +2025-09-13,22:50:39 | INFO | Train Epoch: 8 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.32524 (0.32941) Boundary_loss: 0.013896 (0.013896) Loss: 0.33914 (0.34331) +2025-09-13,22:51:10 | INFO | Train Epoch: 8 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.41149 (0.32959) Boundary_loss: 0.013896 (0.013896) Loss: 0.42538 (0.34348) +2025-09-13,22:51:41 | INFO | Train Epoch: 8 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.35601 (0.32964) Boundary_loss: 0.013898 (0.013896) Loss: 0.36991 (0.34354) +2025-09-13,22:52:12 | INFO | Train Epoch: 8 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.25299 (0.32948) Boundary_loss: 0.013896 (0.013896) Loss: 0.26689 (0.34338) +2025-09-13,22:52:43 | INFO | Train Epoch: 8 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.27304 (0.32936) Boundary_loss: 0.013897 (0.013896) Loss: 0.28694 (0.34326) +2025-09-13,22:53:13 | INFO | Train Epoch: 8 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.33006 (0.32936) Boundary_loss: 0.013895 (0.013896) Loss: 0.34396 (0.34326) +2025-09-13,22:53:44 | INFO | Train Epoch: 8 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.23362 (0.32916) Boundary_loss: 0.013896 (0.013896) Loss: 0.24751 (0.34306) +2025-09-13,22:54:15 | INFO | Train Epoch: 8 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.27302 (0.32905) Boundary_loss: 0.013897 (0.013896) Loss: 0.28692 (0.34294) +2025-09-13,22:54:45 | INFO | Train Epoch: 8 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.36870 (0.32913) Boundary_loss: 0.013895 (0.013896) Loss: 0.38260 (0.34303) +2025-09-13,22:55:16 | INFO | Train Epoch: 8 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.29437 (0.32906) Boundary_loss: 0.013894 (0.013896) Loss: 0.30827 (0.34295) +2025-09-13,22:55:47 | INFO | Train Epoch: 8 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.25553 (0.32891) Boundary_loss: 0.013896 (0.013896) Loss: 0.26943 (0.34280) +2025-09-13,22:56:18 | INFO | Train Epoch: 8 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.28684 (0.32882) Boundary_loss: 0.013896 (0.013896) Loss: 0.30074 (0.34272) +2025-09-13,22:56:49 | INFO | Train Epoch: 8 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.32062 (0.32880) Boundary_loss: 0.013896 (0.013896) Loss: 0.33451 (0.34270) +2025-09-13,22:57:19 | INFO | Train Epoch: 8 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.34355 (0.32883) Boundary_loss: 0.013898 (0.013896) Loss: 0.35745 (0.34273) +2025-09-13,22:57:50 | INFO | Train Epoch: 8 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26390 (0.32870) Boundary_loss: 0.013895 (0.013896) Loss: 0.27780 (0.34260) +2025-09-13,22:58:21 | INFO | Train Epoch: 8 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.28484 (0.32861) Boundary_loss: 0.013895 (0.013896) Loss: 0.29873 (0.34251) +2025-09-13,22:58:51 | INFO | Train Epoch: 8 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.28055 (0.32851) Boundary_loss: 0.013896 (0.013896) Loss: 0.29444 (0.34241) +2025-09-13,22:59:22 | INFO | Train Epoch: 8 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.35887 (0.32857) Boundary_loss: 0.013894 (0.013896) Loss: 0.37277 (0.34247) +2025-09-13,22:59:53 | INFO | Train Epoch: 8 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.31611 (0.32855) Boundary_loss: 0.013896 (0.013896) Loss: 0.33000 (0.34244) +2025-09-13,23:00:23 | INFO | Train Epoch: 8 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.35503 (0.32860) Boundary_loss: 0.013896 (0.013896) Loss: 0.36892 (0.34250) +2025-09-13,23:00:54 | INFO | Train Epoch: 8 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.33062 (0.32861) Boundary_loss: 0.013898 (0.013896) Loss: 0.34452 (0.34250) +2025-09-13,23:01:25 | INFO | Train Epoch: 8 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.32761 (0.32860) Boundary_loss: 0.013896 (0.013896) Loss: 0.34151 (0.34250) +2025-09-13,23:01:56 | INFO | Train Epoch: 8 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.34365 (0.32863) Boundary_loss: 0.013894 (0.013896) Loss: 0.35755 (0.34253) +2025-09-13,23:02:27 | INFO | Train Epoch: 8 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.31564 (0.32861) Boundary_loss: 0.013896 (0.013896) Loss: 0.32954 (0.34250) +2025-09-13,23:02:57 | INFO | Train Epoch: 8 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.28625 (0.32852) Boundary_loss: 0.013897 (0.013896) Loss: 0.30015 (0.34242) +2025-09-13,23:03:28 | INFO | Train Epoch: 8 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.31080 (0.32849) Boundary_loss: 0.013895 (0.013896) Loss: 0.32470 (0.34238) +2025-09-13,23:03:59 | INFO | Train Epoch: 8 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.32808 (0.32849) Boundary_loss: 0.013895 (0.013896) Loss: 0.34198 (0.34238) +2025-09-13,23:04:30 | INFO | Train Epoch: 8 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.36357 (0.32856) Boundary_loss: 0.013894 (0.013896) Loss: 0.37747 (0.34245) +2025-09-13,23:05:00 | INFO | Train Epoch: 8 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.34662 (0.32859) Boundary_loss: 0.013896 (0.013896) Loss: 0.36052 (0.34249) +2025-09-13,23:05:31 | INFO | Train Epoch: 8 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.29399 (0.32852) Boundary_loss: 0.013895 (0.013896) Loss: 0.30788 (0.34242) +2025-09-13,23:06:02 | INFO | Train Epoch: 8 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.33532 (0.32854) Boundary_loss: 0.013897 (0.013896) Loss: 0.34921 (0.34243) +2025-09-13,23:06:33 | INFO | Train Epoch: 8 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.28411 (0.32845) Boundary_loss: 0.013897 (0.013896) Loss: 0.29801 (0.34235) +2025-09-13,23:07:04 | INFO | Train Epoch: 8 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.41755 (0.32863) Boundary_loss: 0.013895 (0.013896) Loss: 0.43144 (0.34252) +2025-09-13,23:07:35 | INFO | Train Epoch: 8 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.27678 (0.32852) Boundary_loss: 0.013897 (0.013896) Loss: 0.29067 (0.34242) +2025-09-13,23:08:06 | INFO | Train Epoch: 8 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.33435 (0.32854) Boundary_loss: 0.013896 (0.013896) Loss: 0.34824 (0.34243) +2025-09-13,23:08:37 | INFO | Train Epoch: 8 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.34389 (0.32857) Boundary_loss: 0.013897 (0.013896) Loss: 0.35778 (0.34246) +2025-09-13,23:09:07 | INFO | Train Epoch: 8 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30839 (0.32853) Boundary_loss: 0.013896 (0.013896) Loss: 0.32229 (0.34242) +2025-09-13,23:09:38 | INFO | Train Epoch: 8 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30479 (0.32848) Boundary_loss: 0.013895 (0.013896) Loss: 0.31868 (0.34238) +2025-09-13,23:10:09 | INFO | Train Epoch: 8 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.34918 (0.32852) Boundary_loss: 0.013896 (0.013896) Loss: 0.36308 (0.34242) +2025-09-13,23:10:40 | INFO | Train Epoch: 8 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.32028 (0.32850) Boundary_loss: 0.013896 (0.013896) Loss: 0.33417 (0.34240) +2025-09-13,23:11:10 | INFO | Train Epoch: 8 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.33000 (0.32851) Boundary_loss: 0.013894 (0.013896) Loss: 0.34390 (0.34240) +2025-09-13,23:11:41 | INFO | Train Epoch: 8 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.30932 (0.32847) Boundary_loss: 0.013895 (0.013896) Loss: 0.32321 (0.34237) +2025-09-13,23:12:10 | INFO | Train Epoch: 8 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27940 (0.32837) Boundary_loss: 0.013895 (0.013896) Loss: 0.29330 (0.34227) +2025-09-13,23:12:10 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,23:12:10 | INFO | [Epoch 8] Average Step Time: 0.310s | Average GPU Memory: 25.2 GB +2025-09-13,23:12:10 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-13,23:12:10 | INFO | Starting zero-shot imagenet. +2025-09-13,23:12:10 | INFO | Building zero-shot classifier +2025-09-13,23:12:16 | INFO | Using classifier +2025-09-13,23:12:54 | INFO | Finished zero-shot imagenet. +2025-09-13,23:12:54 | INFO | Eval Epoch: 9 imagenet-zeroshot-val-top1: 0.2738 imagenet-zeroshot-val-top5: 0.5318 +2025-09-13,23:12:55 | INFO | Start epoch 9 +2025-09-13,23:12:57 | INFO | Train Epoch: 9 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31317 (0.31317) Boundary_loss: 0.013896 (0.013896) Loss: 0.32707 (0.32707) +2025-09-13,23:13:27 | INFO | Train Epoch: 9 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.26261 (0.28789) Boundary_loss: 0.013896 (0.013896) Loss: 0.27650 (0.30179) +2025-09-13,23:13:58 | INFO | Train Epoch: 9 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.35658 (0.31079) Boundary_loss: 0.013896 (0.013896) Loss: 0.37047 (0.32468) +2025-09-13,23:14:29 | INFO | Train Epoch: 9 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.30706 (0.30985) Boundary_loss: 0.013895 (0.013896) Loss: 0.32095 (0.32375) +2025-09-13,23:15:00 | INFO | Train Epoch: 9 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.27540 (0.30296) Boundary_loss: 0.013897 (0.013896) Loss: 0.28930 (0.31686) +2025-09-13,23:15:31 | INFO | Train Epoch: 9 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.34032 (0.30919) Boundary_loss: 0.013895 (0.013896) Loss: 0.35421 (0.32309) +2025-09-13,23:16:02 | INFO | Train Epoch: 9 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.31177 (0.30956) Boundary_loss: 0.013897 (0.013896) Loss: 0.32566 (0.32345) +2025-09-13,23:16:33 | INFO | Train Epoch: 9 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.26255 (0.30368) Boundary_loss: 0.013895 (0.013896) Loss: 0.27644 (0.31758) +2025-09-13,23:17:03 | INFO | Train Epoch: 9 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.24217 (0.29685) Boundary_loss: 0.013896 (0.013896) Loss: 0.25607 (0.31074) +2025-09-13,23:17:34 | INFO | Train Epoch: 9 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.24695 (0.29186) Boundary_loss: 0.013895 (0.013896) Loss: 0.26084 (0.30575) +2025-09-13,23:18:05 | INFO | Train Epoch: 9 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.23013 (0.28625) Boundary_loss: 0.013895 (0.013896) Loss: 0.24403 (0.30014) +2025-09-13,23:18:36 | INFO | Train Epoch: 9 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.29387 (0.28688) Boundary_loss: 0.013898 (0.013896) Loss: 0.30777 (0.30078) +2025-09-13,23:19:07 | INFO | Train Epoch: 9 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.26477 (0.28518) Boundary_loss: 0.013896 (0.013896) Loss: 0.27866 (0.29908) +2025-09-13,23:19:38 | INFO | Train Epoch: 9 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.26908 (0.28403) Boundary_loss: 0.013895 (0.013896) Loss: 0.28297 (0.29793) +2025-09-13,23:20:09 | INFO | Train Epoch: 9 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28978 (0.28441) Boundary_loss: 0.013895 (0.013896) Loss: 0.30367 (0.29831) +2025-09-13,23:20:40 | INFO | Train Epoch: 9 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.25274 (0.28243) Boundary_loss: 0.013898 (0.013896) Loss: 0.26663 (0.29633) +2025-09-13,23:21:11 | INFO | Train Epoch: 9 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.26203 (0.28123) Boundary_loss: 0.013896 (0.013896) Loss: 0.27593 (0.29513) +2025-09-13,23:21:42 | INFO | Train Epoch: 9 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.26764 (0.28048) Boundary_loss: 0.013896 (0.013896) Loss: 0.28154 (0.29437) +2025-09-13,23:22:12 | INFO | Train Epoch: 9 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.25603 (0.27919) Boundary_loss: 0.013897 (0.013896) Loss: 0.26992 (0.29309) +2025-09-13,23:22:43 | INFO | Train Epoch: 9 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.26303 (0.27838) Boundary_loss: 0.013895 (0.013896) Loss: 0.27693 (0.29228) +2025-09-13,23:23:14 | INFO | Train Epoch: 9 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22930 (0.27605) Boundary_loss: 0.013896 (0.013896) Loss: 0.24320 (0.28994) +2025-09-13,23:23:45 | INFO | Train Epoch: 9 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.24594 (0.27468) Boundary_loss: 0.013895 (0.013896) Loss: 0.25983 (0.28857) +2025-09-13,23:24:16 | INFO | Train Epoch: 9 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17300 (0.27026) Boundary_loss: 0.013896 (0.013896) Loss: 0.18689 (0.28415) +2025-09-13,23:24:47 | INFO | Train Epoch: 9 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.28469 (0.27086) Boundary_loss: 0.013896 (0.013896) Loss: 0.29859 (0.28475) +2025-09-13,23:25:18 | INFO | Train Epoch: 9 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.29195 (0.27170) Boundary_loss: 0.013895 (0.013896) Loss: 0.30585 (0.28560) +2025-09-13,23:25:49 | INFO | Train Epoch: 9 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.25311 (0.27099) Boundary_loss: 0.013896 (0.013896) Loss: 0.26701 (0.28488) +2025-09-13,23:26:20 | INFO | Train Epoch: 9 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.30566 (0.27227) Boundary_loss: 0.013895 (0.013896) Loss: 0.31955 (0.28617) +2025-09-13,23:26:51 | INFO | Train Epoch: 9 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26678 (0.27207) Boundary_loss: 0.013896 (0.013896) Loss: 0.28067 (0.28597) +2025-09-13,23:27:22 | INFO | Train Epoch: 9 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.23926 (0.27094) Boundary_loss: 0.013898 (0.013896) Loss: 0.25316 (0.28484) +2025-09-13,23:27:53 | INFO | Train Epoch: 9 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.29681 (0.27181) Boundary_loss: 0.013897 (0.013896) Loss: 0.31070 (0.28570) +2025-09-13,23:28:24 | INFO | Train Epoch: 9 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.21601 (0.27001) Boundary_loss: 0.013895 (0.013896) Loss: 0.22990 (0.28390) +2025-09-13,23:28:55 | INFO | Train Epoch: 9 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24206 (0.26913) Boundary_loss: 0.013896 (0.013896) Loss: 0.25595 (0.28303) +2025-09-13,23:29:26 | INFO | Train Epoch: 9 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.29669 (0.26997) Boundary_loss: 0.013897 (0.013896) Loss: 0.31059 (0.28386) +2025-09-13,23:29:57 | INFO | Train Epoch: 9 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.23922 (0.26906) Boundary_loss: 0.013895 (0.013896) Loss: 0.25311 (0.28296) +2025-09-13,23:30:27 | INFO | Train Epoch: 9 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.27031 (0.26910) Boundary_loss: 0.013895 (0.013896) Loss: 0.28420 (0.28299) +2025-09-13,23:30:58 | INFO | Train Epoch: 9 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21977 (0.26773) Boundary_loss: 0.013896 (0.013896) Loss: 0.23366 (0.28162) +2025-09-13,23:31:29 | INFO | Train Epoch: 9 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27233 (0.26785) Boundary_loss: 0.013895 (0.013896) Loss: 0.28622 (0.28175) +2025-09-13,23:31:59 | INFO | Train Epoch: 9 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.34143 (0.26979) Boundary_loss: 0.013895 (0.013896) Loss: 0.35532 (0.28368) +2025-09-13,23:32:30 | INFO | Train Epoch: 9 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.33147 (0.27137) Boundary_loss: 0.013896 (0.013896) Loss: 0.34537 (0.28527) +2025-09-13,23:33:01 | INFO | Train Epoch: 9 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30015 (0.27209) Boundary_loss: 0.013896 (0.013896) Loss: 0.31404 (0.28599) +2025-09-13,23:33:31 | INFO | Train Epoch: 9 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.29795 (0.27272) Boundary_loss: 0.013895 (0.013896) Loss: 0.31184 (0.28662) +2025-09-13,23:34:02 | INFO | Train Epoch: 9 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.25844 (0.27238) Boundary_loss: 0.013895 (0.013896) Loss: 0.27234 (0.28628) +2025-09-13,23:34:33 | INFO | Train Epoch: 9 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.26343 (0.27217) Boundary_loss: 0.013896 (0.013896) Loss: 0.27732 (0.28607) +2025-09-13,23:35:04 | INFO | Train Epoch: 9 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.32296 (0.27333) Boundary_loss: 0.013895 (0.013896) Loss: 0.33686 (0.28722) +2025-09-13,23:35:35 | INFO | Train Epoch: 9 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.41241 (0.27642) Boundary_loss: 0.013896 (0.013896) Loss: 0.42631 (0.29031) +2025-09-13,23:36:06 | INFO | Train Epoch: 9 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.35051 (0.27803) Boundary_loss: 0.013896 (0.013896) Loss: 0.36441 (0.29192) +2025-09-13,23:36:36 | INFO | Train Epoch: 9 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24078 (0.27724) Boundary_loss: 0.013895 (0.013896) Loss: 0.25468 (0.29113) +2025-09-13,23:37:07 | INFO | Train Epoch: 9 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.22914 (0.27623) Boundary_loss: 0.013896 (0.013896) Loss: 0.24304 (0.29013) +2025-09-13,23:37:38 | INFO | Train Epoch: 9 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26765 (0.27606) Boundary_loss: 0.013896 (0.013896) Loss: 0.28155 (0.28995) +2025-09-13,23:38:09 | INFO | Train Epoch: 9 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30142 (0.27657) Boundary_loss: 0.013897 (0.013896) Loss: 0.31532 (0.29046) +2025-09-13,23:38:40 | INFO | Train Epoch: 9 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.31396 (0.27730) Boundary_loss: 0.013897 (0.013896) Loss: 0.32785 (0.29119) +2025-09-13,23:39:11 | INFO | Train Epoch: 9 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.30548 (0.27784) Boundary_loss: 0.013894 (0.013896) Loss: 0.31937 (0.29174) +2025-09-13,23:39:41 | INFO | Train Epoch: 9 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.31281 (0.27850) Boundary_loss: 0.013895 (0.013896) Loss: 0.32670 (0.29240) +2025-09-13,23:40:12 | INFO | Train Epoch: 9 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.29132 (0.27874) Boundary_loss: 0.013896 (0.013896) Loss: 0.30522 (0.29263) +2025-09-13,23:40:43 | INFO | Train Epoch: 9 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.34841 (0.28000) Boundary_loss: 0.013896 (0.013896) Loss: 0.36230 (0.29390) +2025-09-13,23:41:14 | INFO | Train Epoch: 9 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31227 (0.28058) Boundary_loss: 0.013896 (0.013896) Loss: 0.32616 (0.29448) +2025-09-13,23:41:45 | INFO | Train Epoch: 9 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27062 (0.28041) Boundary_loss: 0.013895 (0.013896) Loss: 0.28452 (0.29430) +2025-09-13,23:42:15 | INFO | Train Epoch: 9 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.25384 (0.27995) Boundary_loss: 0.013896 (0.013896) Loss: 0.26774 (0.29384) +2025-09-13,23:42:46 | INFO | Train Epoch: 9 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.36731 (0.28143) Boundary_loss: 0.013896 (0.013896) Loss: 0.38121 (0.29532) +2025-09-13,23:43:17 | INFO | Train Epoch: 9 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.30476 (0.28182) Boundary_loss: 0.013895 (0.013896) Loss: 0.31865 (0.29571) +2025-09-13,23:43:48 | INFO | Train Epoch: 9 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.27189 (0.28165) Boundary_loss: 0.013896 (0.013896) Loss: 0.28579 (0.29555) +2025-09-13,23:44:19 | INFO | Train Epoch: 9 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.21572 (0.28059) Boundary_loss: 0.013895 (0.013896) Loss: 0.22962 (0.29449) +2025-09-13,23:44:49 | INFO | Train Epoch: 9 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.31162 (0.28108) Boundary_loss: 0.013895 (0.013896) Loss: 0.32552 (0.29498) +2025-09-13,23:45:20 | INFO | Train Epoch: 9 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28326 (0.28112) Boundary_loss: 0.013896 (0.013896) Loss: 0.29715 (0.29501) +2025-09-13,23:45:51 | INFO | Train Epoch: 9 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.28038 (0.28111) Boundary_loss: 0.013896 (0.013896) Loss: 0.29428 (0.29500) +2025-09-13,23:46:22 | INFO | Train Epoch: 9 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.27827 (0.28106) Boundary_loss: 0.013894 (0.013896) Loss: 0.29216 (0.29496) +2025-09-13,23:46:53 | INFO | Train Epoch: 9 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.24599 (0.28054) Boundary_loss: 0.013895 (0.013896) Loss: 0.25989 (0.29444) +2025-09-13,23:47:23 | INFO | Train Epoch: 9 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.31763 (0.28109) Boundary_loss: 0.013895 (0.013896) Loss: 0.33152 (0.29498) +2025-09-13,23:47:54 | INFO | Train Epoch: 9 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31266 (0.28154) Boundary_loss: 0.013895 (0.013896) Loss: 0.32656 (0.29544) +2025-09-13,23:48:25 | INFO | Train Epoch: 9 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.30990 (0.28195) Boundary_loss: 0.013895 (0.013896) Loss: 0.32380 (0.29584) +2025-09-13,23:48:56 | INFO | Train Epoch: 9 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.22429 (0.28114) Boundary_loss: 0.013895 (0.013896) Loss: 0.23819 (0.29503) +2025-09-13,23:49:27 | INFO | Train Epoch: 9 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.22741 (0.28039) Boundary_loss: 0.013896 (0.013896) Loss: 0.24130 (0.29429) +2025-09-13,23:49:58 | INFO | Train Epoch: 9 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.27619 (0.28033) Boundary_loss: 0.013895 (0.013896) Loss: 0.29009 (0.29423) +2025-09-13,23:50:28 | INFO | Train Epoch: 9 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.34029 (0.28114) Boundary_loss: 0.013895 (0.013896) Loss: 0.35418 (0.29504) +2025-09-13,23:50:59 | INFO | Train Epoch: 9 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.28436 (0.28119) Boundary_loss: 0.013895 (0.013896) Loss: 0.29826 (0.29508) +2025-09-13,23:51:30 | INFO | Train Epoch: 9 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26881 (0.28102) Boundary_loss: 0.013895 (0.013896) Loss: 0.28270 (0.29492) +2025-09-13,23:52:01 | INFO | Train Epoch: 9 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.31561 (0.28147) Boundary_loss: 0.013894 (0.013896) Loss: 0.32951 (0.29537) +2025-09-13,23:52:32 | INFO | Train Epoch: 9 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30495 (0.28177) Boundary_loss: 0.013895 (0.013896) Loss: 0.31885 (0.29567) +2025-09-13,23:53:03 | INFO | Train Epoch: 9 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.26913 (0.28161) Boundary_loss: 0.013895 (0.013896) Loss: 0.28302 (0.29551) +2025-09-13,23:53:34 | INFO | Train Epoch: 9 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.30009 (0.28184) Boundary_loss: 0.013896 (0.013896) Loss: 0.31399 (0.29574) +2025-09-13,23:54:05 | INFO | Train Epoch: 9 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.24935 (0.28144) Boundary_loss: 0.013897 (0.013896) Loss: 0.26325 (0.29534) +2025-09-13,23:54:36 | INFO | Train Epoch: 9 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25899 (0.28117) Boundary_loss: 0.013895 (0.013896) Loss: 0.27289 (0.29506) +2025-09-13,23:55:07 | INFO | Train Epoch: 9 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.24506 (0.28073) Boundary_loss: 0.013894 (0.013896) Loss: 0.25895 (0.29463) +2025-09-13,23:55:38 | INFO | Train Epoch: 9 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.20795 (0.27987) Boundary_loss: 0.013895 (0.013896) Loss: 0.22184 (0.29376) +2025-09-13,23:56:08 | INFO | Train Epoch: 9 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28104 (0.27988) Boundary_loss: 0.013894 (0.013896) Loss: 0.29494 (0.29378) +2025-09-13,23:56:39 | INFO | Train Epoch: 9 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.26160 (0.27967) Boundary_loss: 0.013895 (0.013896) Loss: 0.27549 (0.29356) +2025-09-13,23:57:10 | INFO | Train Epoch: 9 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.29253 (0.27982) Boundary_loss: 0.013896 (0.013896) Loss: 0.30642 (0.29371) +2025-09-13,23:57:41 | INFO | Train Epoch: 9 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.26914 (0.27970) Boundary_loss: 0.013896 (0.013896) Loss: 0.28303 (0.29359) +2025-09-13,23:58:12 | INFO | Train Epoch: 9 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.28811 (0.27979) Boundary_loss: 0.013896 (0.013896) Loss: 0.30201 (0.29369) +2025-09-13,23:58:43 | INFO | Train Epoch: 9 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.26294 (0.27960) Boundary_loss: 0.013897 (0.013896) Loss: 0.27683 (0.29350) +2025-09-13,23:59:14 | INFO | Train Epoch: 9 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.22775 (0.27903) Boundary_loss: 0.013895 (0.013896) Loss: 0.24165 (0.29293) +2025-09-13,23:59:45 | INFO | Train Epoch: 9 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.28757 (0.27913) Boundary_loss: 0.013895 (0.013896) Loss: 0.30147 (0.29302) +2025-09-14,00:00:16 | INFO | Train Epoch: 9 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.27384 (0.27907) Boundary_loss: 0.013898 (0.013896) Loss: 0.28773 (0.29296) +2025-09-14,00:00:47 | INFO | Train Epoch: 9 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32997 (0.27961) Boundary_loss: 0.013896 (0.013896) Loss: 0.34387 (0.29351) +2025-09-14,00:01:18 | INFO | Train Epoch: 9 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.19238 (0.27869) Boundary_loss: 0.013895 (0.013896) Loss: 0.20627 (0.29259) +2025-09-14,00:01:49 | INFO | Train Epoch: 9 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.25315 (0.27843) Boundary_loss: 0.013895 (0.013896) Loss: 0.26705 (0.29232) +2025-09-14,00:02:20 | INFO | Train Epoch: 9 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.27582 (0.27840) Boundary_loss: 0.013895 (0.013896) Loss: 0.28971 (0.29229) +2025-09-14,00:02:51 | INFO | Train Epoch: 9 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.29472 (0.27857) Boundary_loss: 0.013894 (0.013896) Loss: 0.30862 (0.29246) +2025-09-14,00:03:22 | INFO | Train Epoch: 9 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.28692 (0.27865) Boundary_loss: 0.013895 (0.013896) Loss: 0.30082 (0.29255) +2025-09-14,00:03:53 | INFO | Train Epoch: 9 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.28323 (0.27870) Boundary_loss: 0.013896 (0.013896) Loss: 0.29712 (0.29259) +2025-09-14,00:04:23 | INFO | Train Epoch: 9 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23672 (0.27828) Boundary_loss: 0.013895 (0.013896) Loss: 0.25061 (0.29218) +2025-09-14,00:04:54 | INFO | Train Epoch: 9 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.34953 (0.27898) Boundary_loss: 0.013897 (0.013896) Loss: 0.36343 (0.29287) +2025-09-14,00:05:25 | INFO | Train Epoch: 9 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23736 (0.27857) Boundary_loss: 0.013896 (0.013896) Loss: 0.25125 (0.29247) +2025-09-14,00:05:56 | INFO | Train Epoch: 9 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.28862 (0.27867) Boundary_loss: 0.013898 (0.013896) Loss: 0.30251 (0.29257) +2025-09-14,00:06:27 | INFO | Train Epoch: 9 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.27809 (0.27867) Boundary_loss: 0.013896 (0.013896) Loss: 0.29198 (0.29256) +2025-09-14,00:06:58 | INFO | Train Epoch: 9 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.28305 (0.27871) Boundary_loss: 0.013897 (0.013896) Loss: 0.29695 (0.29260) +2025-09-14,00:07:29 | INFO | Train Epoch: 9 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24582 (0.27840) Boundary_loss: 0.013896 (0.013896) Loss: 0.25971 (0.29230) +2025-09-14,00:08:00 | INFO | Train Epoch: 9 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24665 (0.27811) Boundary_loss: 0.013895 (0.013896) Loss: 0.26055 (0.29200) +2025-09-14,00:08:31 | INFO | Train Epoch: 9 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.24709 (0.27782) Boundary_loss: 0.013897 (0.013896) Loss: 0.26099 (0.29172) +2025-09-14,00:09:01 | INFO | Train Epoch: 9 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.29252 (0.27795) Boundary_loss: 0.013895 (0.013896) Loss: 0.30641 (0.29185) +2025-09-14,00:09:32 | INFO | Train Epoch: 9 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.29052 (0.27807) Boundary_loss: 0.013896 (0.013896) Loss: 0.30442 (0.29196) +2025-09-14,00:10:03 | INFO | Train Epoch: 9 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.28449 (0.27813) Boundary_loss: 0.013895 (0.013896) Loss: 0.29838 (0.29202) +2025-09-14,00:10:34 | INFO | Train Epoch: 9 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.24633 (0.27784) Boundary_loss: 0.013896 (0.013896) Loss: 0.26022 (0.29174) +2025-09-14,00:11:05 | INFO | Train Epoch: 9 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.22044 (0.27734) Boundary_loss: 0.013895 (0.013896) Loss: 0.23434 (0.29124) +2025-09-14,00:11:36 | INFO | Train Epoch: 9 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.25446 (0.27714) Boundary_loss: 0.013895 (0.013896) Loss: 0.26835 (0.29104) +2025-09-14,00:12:07 | INFO | Train Epoch: 9 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28325 (0.27719) Boundary_loss: 0.013895 (0.013896) Loss: 0.29714 (0.29109) +2025-09-14,00:12:37 | INFO | Train Epoch: 9 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.29164 (0.27732) Boundary_loss: 0.013895 (0.013896) Loss: 0.30554 (0.29121) +2025-09-14,00:13:08 | INFO | Train Epoch: 9 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.29481 (0.27747) Boundary_loss: 0.013895 (0.013896) Loss: 0.30871 (0.29136) +2025-09-14,00:13:39 | INFO | Train Epoch: 9 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20054 (0.27682) Boundary_loss: 0.013895 (0.013896) Loss: 0.21444 (0.29071) +2025-09-14,00:14:10 | INFO | Train Epoch: 9 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22776 (0.27641) Boundary_loss: 0.013896 (0.013896) Loss: 0.24166 (0.29031) +2025-09-14,00:14:40 | INFO | Train Epoch: 9 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25362 (0.27622) Boundary_loss: 0.013895 (0.013896) Loss: 0.26752 (0.29012) +2025-09-14,00:15:11 | INFO | Train Epoch: 9 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24102 (0.27593) Boundary_loss: 0.013895 (0.013896) Loss: 0.25492 (0.28983) +2025-09-14,00:15:42 | INFO | Train Epoch: 9 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.26403 (0.27584) Boundary_loss: 0.013896 (0.013896) Loss: 0.27793 (0.28973) +2025-09-14,00:16:13 | INFO | Train Epoch: 9 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.22241 (0.27541) Boundary_loss: 0.013897 (0.013896) Loss: 0.23631 (0.28930) +2025-09-14,00:16:44 | INFO | Train Epoch: 9 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.29426 (0.27556) Boundary_loss: 0.013896 (0.013896) Loss: 0.30816 (0.28945) +2025-09-14,00:17:14 | INFO | Train Epoch: 9 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.33900 (0.27606) Boundary_loss: 0.013896 (0.013896) Loss: 0.35290 (0.28996) +2025-09-14,00:17:45 | INFO | Train Epoch: 9 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.25154 (0.27587) Boundary_loss: 0.013895 (0.013896) Loss: 0.26544 (0.28976) +2025-09-14,00:18:16 | INFO | Train Epoch: 9 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.21802 (0.27542) Boundary_loss: 0.013897 (0.013896) Loss: 0.23192 (0.28931) +2025-09-14,00:18:47 | INFO | Train Epoch: 9 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.18365 (0.27470) Boundary_loss: 0.013895 (0.013896) Loss: 0.19754 (0.28860) +2025-09-14,00:19:18 | INFO | Train Epoch: 9 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20948 (0.27420) Boundary_loss: 0.013895 (0.013896) Loss: 0.22337 (0.28810) +2025-09-14,00:19:49 | INFO | Train Epoch: 9 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.24082 (0.27395) Boundary_loss: 0.013895 (0.013896) Loss: 0.25471 (0.28784) +2025-09-14,00:20:19 | INFO | Train Epoch: 9 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27531 (0.27396) Boundary_loss: 0.013896 (0.013896) Loss: 0.28921 (0.28785) +2025-09-14,00:20:50 | INFO | Train Epoch: 9 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.32208 (0.27432) Boundary_loss: 0.013898 (0.013896) Loss: 0.33598 (0.28822) +2025-09-14,00:21:21 | INFO | Train Epoch: 9 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.27369 (0.27431) Boundary_loss: 0.013896 (0.013896) Loss: 0.28758 (0.28821) +2025-09-14,00:21:52 | INFO | Train Epoch: 9 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.29806 (0.27449) Boundary_loss: 0.013895 (0.013896) Loss: 0.31196 (0.28839) +2025-09-14,00:22:23 | INFO | Train Epoch: 9 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.23990 (0.27424) Boundary_loss: 0.013896 (0.013896) Loss: 0.25380 (0.28813) +2025-09-14,00:22:54 | INFO | Train Epoch: 9 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.26660 (0.27418) Boundary_loss: 0.013896 (0.013896) Loss: 0.28050 (0.28808) +2025-09-14,00:23:25 | INFO | Train Epoch: 9 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.31769 (0.27450) Boundary_loss: 0.013897 (0.013896) Loss: 0.33159 (0.28839) +2025-09-14,00:23:55 | INFO | Train Epoch: 9 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.25946 (0.27439) Boundary_loss: 0.013896 (0.013896) Loss: 0.27335 (0.28828) +2025-09-14,00:24:26 | INFO | Train Epoch: 9 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.28019 (0.27443) Boundary_loss: 0.013895 (0.013896) Loss: 0.29409 (0.28833) +2025-09-14,00:24:57 | INFO | Train Epoch: 9 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.25145 (0.27427) Boundary_loss: 0.013895 (0.013896) Loss: 0.26535 (0.28816) +2025-09-14,00:25:28 | INFO | Train Epoch: 9 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.31145 (0.27453) Boundary_loss: 0.013895 (0.013896) Loss: 0.32534 (0.28842) +2025-09-14,00:25:59 | INFO | Train Epoch: 9 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.21812 (0.27413) Boundary_loss: 0.013896 (0.013896) Loss: 0.23201 (0.28803) +2025-09-14,00:26:30 | INFO | Train Epoch: 9 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.23275 (0.27385) Boundary_loss: 0.013894 (0.013896) Loss: 0.24664 (0.28774) +2025-09-14,00:27:01 | INFO | Train Epoch: 9 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.28188 (0.27390) Boundary_loss: 0.013896 (0.013896) Loss: 0.29578 (0.28780) +2025-09-14,00:27:32 | INFO | Train Epoch: 9 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.26584 (0.27385) Boundary_loss: 0.013895 (0.013896) Loss: 0.27974 (0.28774) +2025-09-14,00:28:03 | INFO | Train Epoch: 9 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.23900 (0.27361) Boundary_loss: 0.013895 (0.013896) Loss: 0.25289 (0.28751) +2025-09-14,00:28:33 | INFO | Train Epoch: 9 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26845 (0.27357) Boundary_loss: 0.013896 (0.013896) Loss: 0.28234 (0.28747) +2025-09-14,00:29:04 | INFO | Train Epoch: 9 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.28238 (0.27363) Boundary_loss: 0.013895 (0.013896) Loss: 0.29628 (0.28753) +2025-09-14,00:29:35 | INFO | Train Epoch: 9 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26707 (0.27359) Boundary_loss: 0.013895 (0.013896) Loss: 0.28097 (0.28749) +2025-09-14,00:30:06 | INFO | Train Epoch: 9 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.28529 (0.27367) Boundary_loss: 0.013896 (0.013896) Loss: 0.29919 (0.28756) +2025-09-14,00:30:37 | INFO | Train Epoch: 9 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24899 (0.27351) Boundary_loss: 0.013895 (0.013896) Loss: 0.26289 (0.28740) +2025-09-14,00:31:07 | INFO | Train Epoch: 9 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.34531 (0.27397) Boundary_loss: 0.013896 (0.013896) Loss: 0.35920 (0.28787) +2025-09-14,00:31:38 | INFO | Train Epoch: 9 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.24725 (0.27380) Boundary_loss: 0.013896 (0.013896) Loss: 0.26114 (0.28770) +2025-09-14,00:32:08 | INFO | Train Epoch: 9 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27972 (0.27384) Boundary_loss: 0.013896 (0.013896) Loss: 0.29362 (0.28773) +2025-09-14,00:32:39 | INFO | Train Epoch: 9 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.29196 (0.27396) Boundary_loss: 0.013895 (0.013896) Loss: 0.30586 (0.28785) +2025-09-14,00:33:10 | INFO | Train Epoch: 9 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19870 (0.27348) Boundary_loss: 0.013896 (0.013896) Loss: 0.21259 (0.28737) +2025-09-14,00:33:40 | INFO | Train Epoch: 9 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.29180 (0.27359) Boundary_loss: 0.013895 (0.013896) Loss: 0.30569 (0.28749) +2025-09-14,00:34:11 | INFO | Train Epoch: 9 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25186 (0.27346) Boundary_loss: 0.013896 (0.013896) Loss: 0.26575 (0.28735) +2025-09-14,00:34:42 | INFO | Train Epoch: 9 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.32210 (0.27376) Boundary_loss: 0.013896 (0.013896) Loss: 0.33599 (0.28765) +2025-09-14,00:35:12 | INFO | Train Epoch: 9 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26736 (0.27372) Boundary_loss: 0.013895 (0.013896) Loss: 0.28126 (0.28762) +2025-09-14,00:35:43 | INFO | Train Epoch: 9 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.27127 (0.27370) Boundary_loss: 0.013895 (0.013896) Loss: 0.28517 (0.28760) +2025-09-14,00:36:14 | INFO | Train Epoch: 9 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25027 (0.27356) Boundary_loss: 0.013896 (0.013896) Loss: 0.26416 (0.28746) +2025-09-14,00:36:45 | INFO | Train Epoch: 9 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22417 (0.27326) Boundary_loss: 0.013897 (0.013896) Loss: 0.23807 (0.28716) +2025-09-14,00:37:16 | INFO | Train Epoch: 9 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.27513 (0.27327) Boundary_loss: 0.013895 (0.013896) Loss: 0.28902 (0.28717) +2025-09-14,00:37:47 | INFO | Train Epoch: 9 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.26780 (0.27324) Boundary_loss: 0.013895 (0.013896) Loss: 0.28169 (0.28713) +2025-09-14,00:38:18 | INFO | Train Epoch: 9 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.28955 (0.27334) Boundary_loss: 0.013894 (0.013896) Loss: 0.30344 (0.28723) +2025-09-14,00:38:49 | INFO | Train Epoch: 9 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.28232 (0.27339) Boundary_loss: 0.013895 (0.013896) Loss: 0.29621 (0.28728) +2025-09-14,00:39:19 | INFO | Train Epoch: 9 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.25961 (0.27331) Boundary_loss: 0.013896 (0.013896) Loss: 0.27351 (0.28720) +2025-09-14,00:39:50 | INFO | Train Epoch: 9 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28500 (0.27338) Boundary_loss: 0.013895 (0.013896) Loss: 0.29890 (0.28727) +2025-09-14,00:40:21 | INFO | Train Epoch: 9 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21040 (0.27301) Boundary_loss: 0.013896 (0.013896) Loss: 0.22430 (0.28690) +2025-09-14,00:40:52 | INFO | Train Epoch: 9 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22438 (0.27273) Boundary_loss: 0.013895 (0.013896) Loss: 0.23827 (0.28662) +2025-09-14,00:41:23 | INFO | Train Epoch: 9 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31478 (0.27297) Boundary_loss: 0.013895 (0.013896) Loss: 0.32867 (0.28686) +2025-09-14,00:41:54 | INFO | Train Epoch: 9 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24778 (0.27282) Boundary_loss: 0.013897 (0.013896) Loss: 0.26168 (0.28672) +2025-09-14,00:42:24 | INFO | Train Epoch: 9 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.26755 (0.27279) Boundary_loss: 0.013896 (0.013896) Loss: 0.28145 (0.28669) +2025-09-14,00:42:55 | INFO | Train Epoch: 9 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.25914 (0.27272) Boundary_loss: 0.013895 (0.013896) Loss: 0.27304 (0.28661) +2025-09-14,00:43:26 | INFO | Train Epoch: 9 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.21556 (0.27239) Boundary_loss: 0.013895 (0.013896) Loss: 0.22946 (0.28629) +2025-09-14,00:43:57 | INFO | Train Epoch: 9 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.25959 (0.27232) Boundary_loss: 0.013895 (0.013896) Loss: 0.27348 (0.28622) +2025-09-14,00:44:28 | INFO | Train Epoch: 9 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.22002 (0.27203) Boundary_loss: 0.013895 (0.013896) Loss: 0.23392 (0.28592) +2025-09-14,00:44:59 | INFO | Train Epoch: 9 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.29448 (0.27215) Boundary_loss: 0.013896 (0.013896) Loss: 0.30837 (0.28605) +2025-09-14,00:45:29 | INFO | Train Epoch: 9 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.33739 (0.27251) Boundary_loss: 0.013895 (0.013896) Loss: 0.35128 (0.28641) +2025-09-14,00:46:00 | INFO | Train Epoch: 9 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.30050 (0.27267) Boundary_loss: 0.013896 (0.013896) Loss: 0.31440 (0.28656) +2025-09-14,00:46:31 | INFO | Train Epoch: 9 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.29325 (0.27278) Boundary_loss: 0.013895 (0.013896) Loss: 0.30714 (0.28668) +2025-09-14,00:47:02 | INFO | Train Epoch: 9 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.25743 (0.27270) Boundary_loss: 0.013896 (0.013896) Loss: 0.27133 (0.28659) +2025-09-14,00:47:32 | INFO | Train Epoch: 9 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.26644 (0.27266) Boundary_loss: 0.013897 (0.013896) Loss: 0.28033 (0.28656) +2025-09-14,00:48:03 | INFO | Train Epoch: 9 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22439 (0.27240) Boundary_loss: 0.013895 (0.013896) Loss: 0.23828 (0.28630) +2025-09-14,00:48:34 | INFO | Train Epoch: 9 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27957 (0.27244) Boundary_loss: 0.013898 (0.013896) Loss: 0.29346 (0.28634) +2025-09-14,00:49:05 | INFO | Train Epoch: 9 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.26120 (0.27238) Boundary_loss: 0.013896 (0.013896) Loss: 0.27510 (0.28628) +2025-09-14,00:49:36 | INFO | Train Epoch: 9 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.29440 (0.27250) Boundary_loss: 0.013895 (0.013896) Loss: 0.30829 (0.28639) +2025-09-14,00:50:07 | INFO | Train Epoch: 9 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.19136 (0.27207) Boundary_loss: 0.013896 (0.013896) Loss: 0.20525 (0.28597) +2025-09-14,00:50:38 | INFO | Train Epoch: 9 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.32788 (0.27236) Boundary_loss: 0.013897 (0.013896) Loss: 0.34178 (0.28626) +2025-09-14,00:51:08 | INFO | Train Epoch: 9 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.28008 (0.27240) Boundary_loss: 0.013896 (0.013896) Loss: 0.29398 (0.28630) +2025-09-14,00:51:39 | INFO | Train Epoch: 9 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.30277 (0.27256) Boundary_loss: 0.013896 (0.013896) Loss: 0.31666 (0.28646) +2025-09-14,00:52:10 | INFO | Train Epoch: 9 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.18879 (0.27213) Boundary_loss: 0.013895 (0.013896) Loss: 0.20269 (0.28602) +2025-09-14,00:52:41 | INFO | Train Epoch: 9 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.30879 (0.27232) Boundary_loss: 0.013894 (0.013896) Loss: 0.32269 (0.28621) +2025-09-14,00:53:12 | INFO | Train Epoch: 9 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.23471 (0.27213) Boundary_loss: 0.013895 (0.013896) Loss: 0.24860 (0.28602) +2025-09-14,00:53:42 | INFO | Train Epoch: 9 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.24897 (0.27201) Boundary_loss: 0.013896 (0.013896) Loss: 0.26287 (0.28590) +2025-09-14,00:54:13 | INFO | Train Epoch: 9 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.29038 (0.27210) Boundary_loss: 0.013896 (0.013896) Loss: 0.30427 (0.28600) +2025-09-14,00:54:44 | INFO | Train Epoch: 9 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20496 (0.27176) Boundary_loss: 0.013896 (0.013896) Loss: 0.21886 (0.28566) +2025-09-14,00:55:14 | INFO | Train Epoch: 9 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.35328 (0.27217) Boundary_loss: 0.013895 (0.013896) Loss: 0.36718 (0.28607) +2025-09-14,00:55:45 | INFO | Train Epoch: 9 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.28146 (0.27222) Boundary_loss: 0.013895 (0.013896) Loss: 0.29536 (0.28611) +2025-09-14,00:56:16 | INFO | Train Epoch: 9 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.33810 (0.27254) Boundary_loss: 0.013895 (0.013896) Loss: 0.35200 (0.28644) +2025-09-14,00:56:46 | INFO | Train Epoch: 9 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.31230 (0.27274) Boundary_loss: 0.013896 (0.013896) Loss: 0.32620 (0.28663) +2025-09-14,00:57:17 | INFO | Train Epoch: 9 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.30856 (0.27291) Boundary_loss: 0.013895 (0.013896) Loss: 0.32245 (0.28681) +2025-09-14,00:57:48 | INFO | Train Epoch: 9 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.34246 (0.27325) Boundary_loss: 0.013896 (0.013896) Loss: 0.35636 (0.28715) +2025-09-14,00:58:18 | INFO | Train Epoch: 9 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.30876 (0.27343) Boundary_loss: 0.013895 (0.013896) Loss: 0.32265 (0.28732) +2025-09-14,00:58:49 | INFO | Train Epoch: 9 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.31230 (0.27361) Boundary_loss: 0.013895 (0.013896) Loss: 0.32619 (0.28751) +2025-09-14,00:59:20 | INFO | Train Epoch: 9 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.30522 (0.27377) Boundary_loss: 0.013895 (0.013896) Loss: 0.31912 (0.28766) +2025-09-14,00:59:51 | INFO | Train Epoch: 9 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.26786 (0.27374) Boundary_loss: 0.013895 (0.013896) Loss: 0.28175 (0.28763) +2025-09-14,01:00:21 | INFO | Train Epoch: 9 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.28676 (0.27380) Boundary_loss: 0.013894 (0.013896) Loss: 0.30066 (0.28770) +2025-09-14,01:00:52 | INFO | Train Epoch: 9 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.25282 (0.27370) Boundary_loss: 0.013894 (0.013896) Loss: 0.26671 (0.28760) +2025-09-14,01:01:23 | INFO | Train Epoch: 9 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20850 (0.27339) Boundary_loss: 0.013895 (0.013896) Loss: 0.22239 (0.28729) +2025-09-14,01:01:54 | INFO | Train Epoch: 9 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.29624 (0.27350) Boundary_loss: 0.013898 (0.013896) Loss: 0.31013 (0.28740) +2025-09-14,01:02:24 | INFO | Train Epoch: 9 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.28718 (0.27356) Boundary_loss: 0.013895 (0.013896) Loss: 0.30108 (0.28746) +2025-09-14,01:02:55 | INFO | Train Epoch: 9 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.30380 (0.27370) Boundary_loss: 0.013898 (0.013896) Loss: 0.31770 (0.28760) +2025-09-14,01:03:26 | INFO | Train Epoch: 9 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.28253 (0.27375) Boundary_loss: 0.013895 (0.013896) Loss: 0.29642 (0.28764) +2025-09-14,01:03:57 | INFO | Train Epoch: 9 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22316 (0.27351) Boundary_loss: 0.013895 (0.013896) Loss: 0.23706 (0.28741) +2025-09-14,01:04:28 | INFO | Train Epoch: 9 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.22744 (0.27330) Boundary_loss: 0.013895 (0.013896) Loss: 0.24134 (0.28720) +2025-09-14,01:04:59 | INFO | Train Epoch: 9 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21560 (0.27304) Boundary_loss: 0.013896 (0.013896) Loss: 0.22949 (0.28693) +2025-09-14,01:05:30 | INFO | Train Epoch: 9 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19139 (0.27267) Boundary_loss: 0.013895 (0.013896) Loss: 0.20529 (0.28656) +2025-09-14,01:06:01 | INFO | Train Epoch: 9 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24073 (0.27252) Boundary_loss: 0.013896 (0.013896) Loss: 0.25462 (0.28642) +2025-09-14,01:06:32 | INFO | Train Epoch: 9 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.20728 (0.27223) Boundary_loss: 0.013896 (0.013896) Loss: 0.22117 (0.28612) +2025-09-14,01:07:03 | INFO | Train Epoch: 9 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.28737 (0.27230) Boundary_loss: 0.013895 (0.013896) Loss: 0.30127 (0.28619) +2025-09-14,01:07:34 | INFO | Train Epoch: 9 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23825 (0.27214) Boundary_loss: 0.013897 (0.013896) Loss: 0.25215 (0.28604) +2025-09-14,01:08:04 | INFO | Train Epoch: 9 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.29886 (0.27226) Boundary_loss: 0.013895 (0.013896) Loss: 0.31276 (0.28616) +2025-09-14,01:08:35 | INFO | Train Epoch: 9 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28588 (0.27232) Boundary_loss: 0.013894 (0.013896) Loss: 0.29977 (0.28622) +2025-09-14,01:09:06 | INFO | Train Epoch: 9 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.26685 (0.27230) Boundary_loss: 0.013895 (0.013896) Loss: 0.28075 (0.28619) +2025-09-14,01:09:37 | INFO | Train Epoch: 9 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.25970 (0.27224) Boundary_loss: 0.013896 (0.013896) Loss: 0.27360 (0.28614) +2025-09-14,01:10:08 | INFO | Train Epoch: 9 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.22096 (0.27202) Boundary_loss: 0.013895 (0.013896) Loss: 0.23485 (0.28592) +2025-09-14,01:10:38 | INFO | Train Epoch: 9 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.25983 (0.27197) Boundary_loss: 0.013895 (0.013896) Loss: 0.27373 (0.28586) +2025-09-14,01:11:09 | INFO | Train Epoch: 9 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.24692 (0.27186) Boundary_loss: 0.013896 (0.013896) Loss: 0.26081 (0.28575) +2025-09-14,01:11:40 | INFO | Train Epoch: 9 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26623 (0.27183) Boundary_loss: 0.013896 (0.013896) Loss: 0.28012 (0.28573) +2025-09-14,01:12:11 | INFO | Train Epoch: 9 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22680 (0.27164) Boundary_loss: 0.013895 (0.013896) Loss: 0.24069 (0.28554) +2025-09-14,01:12:41 | INFO | Train Epoch: 9 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.25828 (0.27158) Boundary_loss: 0.013895 (0.013896) Loss: 0.27217 (0.28548) +2025-09-14,01:13:12 | INFO | Train Epoch: 9 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.22374 (0.27138) Boundary_loss: 0.013895 (0.013896) Loss: 0.23763 (0.28528) +2025-09-14,01:13:43 | INFO | Train Epoch: 9 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.23381 (0.27122) Boundary_loss: 0.013894 (0.013896) Loss: 0.24770 (0.28512) +2025-09-14,01:14:14 | INFO | Train Epoch: 9 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.23072 (0.27105) Boundary_loss: 0.013895 (0.013896) Loss: 0.24462 (0.28495) +2025-09-14,01:14:44 | INFO | Train Epoch: 9 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27926 (0.27108) Boundary_loss: 0.013895 (0.013896) Loss: 0.29316 (0.28498) +2025-09-14,01:15:15 | INFO | Train Epoch: 9 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.30244 (0.27122) Boundary_loss: 0.013895 (0.013896) Loss: 0.31633 (0.28511) +2025-09-14,01:15:46 | INFO | Train Epoch: 9 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.30315 (0.27135) Boundary_loss: 0.013897 (0.013896) Loss: 0.31705 (0.28524) +2025-09-14,01:16:17 | INFO | Train Epoch: 9 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31290 (0.27152) Boundary_loss: 0.013895 (0.013896) Loss: 0.32680 (0.28542) +2025-09-14,01:16:47 | INFO | Train Epoch: 9 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.28452 (0.27157) Boundary_loss: 0.013896 (0.013896) Loss: 0.29842 (0.28547) +2025-09-14,01:17:18 | INFO | Train Epoch: 9 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27224 (0.27158) Boundary_loss: 0.013897 (0.013896) Loss: 0.28614 (0.28547) +2025-09-14,01:17:49 | INFO | Train Epoch: 9 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.22973 (0.27141) Boundary_loss: 0.013896 (0.013896) Loss: 0.24362 (0.28530) +2025-09-14,01:18:19 | INFO | Train Epoch: 9 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.25147 (0.27132) Boundary_loss: 0.013895 (0.013896) Loss: 0.26537 (0.28522) +2025-09-14,01:18:50 | INFO | Train Epoch: 9 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24666 (0.27122) Boundary_loss: 0.013897 (0.013896) Loss: 0.26055 (0.28512) +2025-09-14,01:19:21 | INFO | Train Epoch: 9 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23067 (0.27106) Boundary_loss: 0.013896 (0.013896) Loss: 0.24456 (0.28496) +2025-09-14,01:19:52 | INFO | Train Epoch: 9 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.28025 (0.27110) Boundary_loss: 0.013896 (0.013896) Loss: 0.29415 (0.28499) +2025-09-14,01:20:23 | INFO | Train Epoch: 9 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23894 (0.27097) Boundary_loss: 0.013896 (0.013896) Loss: 0.25283 (0.28486) +2025-09-14,01:20:54 | INFO | Train Epoch: 9 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.25726 (0.27091) Boundary_loss: 0.013895 (0.013896) Loss: 0.27115 (0.28481) +2025-09-14,01:21:25 | INFO | Train Epoch: 9 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22986 (0.27075) Boundary_loss: 0.013895 (0.013896) Loss: 0.24376 (0.28465) +2025-09-14,01:21:56 | INFO | Train Epoch: 9 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27522 (0.27077) Boundary_loss: 0.013895 (0.013896) Loss: 0.28912 (0.28466) +2025-09-14,01:22:27 | INFO | Train Epoch: 9 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19424 (0.27046) Boundary_loss: 0.013896 (0.013896) Loss: 0.20813 (0.28436) +2025-09-14,01:22:58 | INFO | Train Epoch: 9 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.24085 (0.27035) Boundary_loss: 0.013896 (0.013896) Loss: 0.25475 (0.28424) +2025-09-14,01:23:29 | INFO | Train Epoch: 9 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.25079 (0.27027) Boundary_loss: 0.013895 (0.013896) Loss: 0.26469 (0.28417) +2025-09-14,01:24:00 | INFO | Train Epoch: 9 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.25814 (0.27022) Boundary_loss: 0.013897 (0.013896) Loss: 0.27203 (0.28412) +2025-09-14,01:24:31 | INFO | Train Epoch: 9 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22768 (0.27006) Boundary_loss: 0.013896 (0.013896) Loss: 0.24158 (0.28395) +2025-09-14,01:25:01 | INFO | Train Epoch: 9 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21426 (0.26984) Boundary_loss: 0.013898 (0.013896) Loss: 0.22815 (0.28374) +2025-09-14,01:25:32 | INFO | Train Epoch: 9 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.27158 (0.26985) Boundary_loss: 0.013895 (0.013896) Loss: 0.28548 (0.28374) +2025-09-14,01:26:03 | INFO | Train Epoch: 9 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.22154 (0.26966) Boundary_loss: 0.013896 (0.013896) Loss: 0.23544 (0.28356) +2025-09-14,01:26:34 | INFO | Train Epoch: 9 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.28352 (0.26972) Boundary_loss: 0.013895 (0.013896) Loss: 0.29742 (0.28361) +2025-09-14,01:27:05 | INFO | Train Epoch: 9 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.26249 (0.26969) Boundary_loss: 0.013897 (0.013896) Loss: 0.27639 (0.28358) +2025-09-14,01:27:36 | INFO | Train Epoch: 9 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.23428 (0.26955) Boundary_loss: 0.013896 (0.013896) Loss: 0.24818 (0.28345) +2025-09-14,01:28:06 | INFO | Train Epoch: 9 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.25317 (0.26949) Boundary_loss: 0.013896 (0.013896) Loss: 0.26707 (0.28339) +2025-09-14,01:28:37 | INFO | Train Epoch: 9 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.25210 (0.26943) Boundary_loss: 0.013895 (0.013896) Loss: 0.26599 (0.28332) +2025-09-14,01:29:07 | INFO | Train Epoch: 9 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.25047 (0.26936) Boundary_loss: 0.013895 (0.013896) Loss: 0.26436 (0.28325) +2025-09-14,01:29:38 | INFO | Train Epoch: 9 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.27803 (0.26939) Boundary_loss: 0.013895 (0.013896) Loss: 0.29192 (0.28328) +2025-09-14,01:30:09 | INFO | Train Epoch: 9 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.26284 (0.26936) Boundary_loss: 0.013896 (0.013896) Loss: 0.27673 (0.28326) +2025-09-14,01:30:39 | INFO | Train Epoch: 9 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.21557 (0.26916) Boundary_loss: 0.013897 (0.013896) Loss: 0.22947 (0.28306) +2025-09-14,01:31:10 | INFO | Train Epoch: 9 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21359 (0.26896) Boundary_loss: 0.013896 (0.013896) Loss: 0.22749 (0.28285) +2025-09-14,01:31:40 | INFO | Train Epoch: 9 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.28630 (0.26902) Boundary_loss: 0.013895 (0.013896) Loss: 0.30019 (0.28292) +2025-09-14,01:32:11 | INFO | Train Epoch: 9 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.18566 (0.26872) Boundary_loss: 0.013895 (0.013896) Loss: 0.19955 (0.28261) +2025-09-14,01:32:41 | INFO | Train Epoch: 9 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.29500 (0.26881) Boundary_loss: 0.013895 (0.013896) Loss: 0.30890 (0.28271) +2025-09-14,01:33:12 | INFO | Train Epoch: 9 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.27791 (0.26884) Boundary_loss: 0.013896 (0.013896) Loss: 0.29181 (0.28274) +2025-09-14,01:33:42 | INFO | Train Epoch: 9 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.25726 (0.26880) Boundary_loss: 0.013896 (0.013896) Loss: 0.27115 (0.28270) +2025-09-14,01:34:13 | INFO | Train Epoch: 9 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26767 (0.26880) Boundary_loss: 0.013896 (0.013896) Loss: 0.28156 (0.28269) +2025-09-14,01:34:44 | INFO | Train Epoch: 9 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.28248 (0.26885) Boundary_loss: 0.013895 (0.013896) Loss: 0.29638 (0.28274) +2025-09-14,01:35:14 | INFO | Train Epoch: 9 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.23043 (0.26871) Boundary_loss: 0.013896 (0.013896) Loss: 0.24432 (0.28261) +2025-09-14,01:35:45 | INFO | Train Epoch: 9 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.20039 (0.26846) Boundary_loss: 0.013895 (0.013896) Loss: 0.21428 (0.28236) +2025-09-14,01:36:15 | INFO | Train Epoch: 9 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.22433 (0.26831) Boundary_loss: 0.013896 (0.013896) Loss: 0.23822 (0.28220) +2025-09-14,01:36:46 | INFO | Train Epoch: 9 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.24724 (0.26823) Boundary_loss: 0.013895 (0.013896) Loss: 0.26114 (0.28213) +2025-09-14,01:37:16 | INFO | Train Epoch: 9 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.24933 (0.26817) Boundary_loss: 0.013895 (0.013896) Loss: 0.26323 (0.28206) +2025-09-14,01:37:47 | INFO | Train Epoch: 9 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.25767 (0.26813) Boundary_loss: 0.013895 (0.013896) Loss: 0.27156 (0.28202) +2025-09-14,01:38:18 | INFO | Train Epoch: 9 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.30872 (0.26827) Boundary_loss: 0.013896 (0.013896) Loss: 0.32261 (0.28217) +2025-09-14,01:38:49 | INFO | Train Epoch: 9 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.32930 (0.26848) Boundary_loss: 0.013895 (0.013896) Loss: 0.34320 (0.28238) +2025-09-14,01:39:19 | INFO | Train Epoch: 9 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.25448 (0.26844) Boundary_loss: 0.013895 (0.013896) Loss: 0.26838 (0.28233) +2025-09-14,01:39:50 | INFO | Train Epoch: 9 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.28876 (0.26851) Boundary_loss: 0.013897 (0.013896) Loss: 0.30266 (0.28240) +2025-09-14,01:40:21 | INFO | Train Epoch: 9 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.21032 (0.26830) Boundary_loss: 0.013896 (0.013896) Loss: 0.22422 (0.28220) +2025-09-14,01:40:52 | INFO | Train Epoch: 9 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.28151 (0.26835) Boundary_loss: 0.013896 (0.013896) Loss: 0.29540 (0.28225) +2025-09-14,01:41:22 | INFO | Train Epoch: 9 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26788 (0.26835) Boundary_loss: 0.013896 (0.013896) Loss: 0.28177 (0.28224) +2025-09-14,01:41:53 | INFO | Train Epoch: 9 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.34981 (0.26863) Boundary_loss: 0.013895 (0.013896) Loss: 0.36371 (0.28252) +2025-09-14,01:42:24 | INFO | Train Epoch: 9 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.20074 (0.26840) Boundary_loss: 0.013895 (0.013896) Loss: 0.21464 (0.28229) +2025-09-14,01:42:55 | INFO | Train Epoch: 9 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.24604 (0.26832) Boundary_loss: 0.013896 (0.013896) Loss: 0.25994 (0.28222) +2025-09-14,01:43:26 | INFO | Train Epoch: 9 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.26284 (0.26830) Boundary_loss: 0.013895 (0.013896) Loss: 0.27674 (0.28220) +2025-09-14,01:43:56 | INFO | Train Epoch: 9 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.26763 (0.26830) Boundary_loss: 0.013895 (0.013896) Loss: 0.28152 (0.28219) +2025-09-14,01:44:27 | INFO | Train Epoch: 9 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.24902 (0.26823) Boundary_loss: 0.013896 (0.013896) Loss: 0.26292 (0.28213) +2025-09-14,01:44:58 | INFO | Train Epoch: 9 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.21741 (0.26806) Boundary_loss: 0.013898 (0.013896) Loss: 0.23130 (0.28196) +2025-09-14,01:45:29 | INFO | Train Epoch: 9 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.18374 (0.26778) Boundary_loss: 0.013895 (0.013896) Loss: 0.19764 (0.28168) +2025-09-14,01:45:59 | INFO | Train Epoch: 9 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.24489 (0.26770) Boundary_loss: 0.013895 (0.013896) Loss: 0.25878 (0.28160) +2025-09-14,01:46:30 | INFO | Train Epoch: 9 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.26525 (0.26770) Boundary_loss: 0.013895 (0.013896) Loss: 0.27915 (0.28159) +2025-09-14,01:47:01 | INFO | Train Epoch: 9 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19477 (0.26745) Boundary_loss: 0.013895 (0.013896) Loss: 0.20866 (0.28135) +2025-09-14,01:47:32 | INFO | Train Epoch: 9 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.31833 (0.26762) Boundary_loss: 0.013895 (0.013896) Loss: 0.33222 (0.28152) +2025-09-14,01:48:02 | INFO | Train Epoch: 9 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.20427 (0.26741) Boundary_loss: 0.013898 (0.013896) Loss: 0.21817 (0.28131) +2025-09-14,01:48:33 | INFO | Train Epoch: 9 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28814 (0.26748) Boundary_loss: 0.013894 (0.013896) Loss: 0.30203 (0.28138) +2025-09-14,01:49:04 | INFO | Train Epoch: 9 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.22942 (0.26736) Boundary_loss: 0.013895 (0.013896) Loss: 0.24331 (0.28125) +2025-09-14,01:49:35 | INFO | Train Epoch: 9 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.25636 (0.26732) Boundary_loss: 0.013895 (0.013896) Loss: 0.27025 (0.28122) +2025-09-14,01:50:06 | INFO | Train Epoch: 9 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.25426 (0.26728) Boundary_loss: 0.013894 (0.013896) Loss: 0.26815 (0.28117) +2025-09-14,01:50:36 | INFO | Train Epoch: 9 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.24358 (0.26720) Boundary_loss: 0.013895 (0.013896) Loss: 0.25748 (0.28110) +2025-09-14,01:51:07 | INFO | Train Epoch: 9 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.26920 (0.26721) Boundary_loss: 0.013896 (0.013896) Loss: 0.28310 (0.28110) +2025-09-14,01:51:38 | INFO | Train Epoch: 9 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22376 (0.26707) Boundary_loss: 0.013898 (0.013896) Loss: 0.23766 (0.28096) +2025-09-14,01:52:09 | INFO | Train Epoch: 9 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.30218 (0.26718) Boundary_loss: 0.013895 (0.013896) Loss: 0.31607 (0.28108) +2025-09-14,01:52:39 | INFO | Train Epoch: 9 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.24162 (0.26710) Boundary_loss: 0.013896 (0.013896) Loss: 0.25552 (0.28099) +2025-09-14,01:53:10 | INFO | Train Epoch: 9 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.31202 (0.26724) Boundary_loss: 0.013897 (0.013896) Loss: 0.32592 (0.28114) +2025-09-14,01:53:41 | INFO | Train Epoch: 9 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.22334 (0.26710) Boundary_loss: 0.013897 (0.013896) Loss: 0.23724 (0.28100) +2025-09-14,01:54:12 | INFO | Train Epoch: 9 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24525 (0.26703) Boundary_loss: 0.013896 (0.013896) Loss: 0.25915 (0.28093) +2025-09-14,01:54:43 | INFO | Train Epoch: 9 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.27200 (0.26705) Boundary_loss: 0.013895 (0.013896) Loss: 0.28590 (0.28094) +2025-09-14,01:55:14 | INFO | Train Epoch: 9 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.30582 (0.26717) Boundary_loss: 0.013895 (0.013896) Loss: 0.31971 (0.28107) +2025-09-14,01:55:44 | INFO | Train Epoch: 9 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.23967 (0.26708) Boundary_loss: 0.013895 (0.013896) Loss: 0.25357 (0.28098) +2025-09-14,01:56:15 | INFO | Train Epoch: 9 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21515 (0.26692) Boundary_loss: 0.013895 (0.013896) Loss: 0.22904 (0.28082) +2025-09-14,01:56:45 | INFO | Train Epoch: 9 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.26874 (0.26693) Boundary_loss: 0.013895 (0.013896) Loss: 0.28264 (0.28082) +2025-09-14,01:57:16 | INFO | Train Epoch: 9 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.25535 (0.26689) Boundary_loss: 0.013895 (0.013896) Loss: 0.26925 (0.28079) +2025-09-14,01:57:47 | INFO | Train Epoch: 9 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32041 (0.26706) Boundary_loss: 0.013896 (0.013896) Loss: 0.33430 (0.28095) +2025-09-14,01:58:18 | INFO | Train Epoch: 9 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.27436 (0.26708) Boundary_loss: 0.013895 (0.013896) Loss: 0.28825 (0.28097) +2025-09-14,01:58:49 | INFO | Train Epoch: 9 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21443 (0.26692) Boundary_loss: 0.013895 (0.013896) Loss: 0.22833 (0.28081) +2025-09-14,01:59:20 | INFO | Train Epoch: 9 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.22827 (0.26680) Boundary_loss: 0.013896 (0.013896) Loss: 0.24217 (0.28069) +2025-09-14,01:59:50 | INFO | Train Epoch: 9 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.23512 (0.26670) Boundary_loss: 0.013895 (0.013896) Loss: 0.24901 (0.28060) +2025-09-14,02:00:21 | INFO | Train Epoch: 9 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.24135 (0.26662) Boundary_loss: 0.013896 (0.013896) Loss: 0.25525 (0.28052) +2025-09-14,02:00:52 | INFO | Train Epoch: 9 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.27611 (0.26665) Boundary_loss: 0.013896 (0.013896) Loss: 0.29001 (0.28055) +2025-09-14,02:01:23 | INFO | Train Epoch: 9 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24097 (0.26657) Boundary_loss: 0.013894 (0.013896) Loss: 0.25487 (0.28047) +2025-09-14,02:01:53 | INFO | Train Epoch: 9 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.26785 (0.26658) Boundary_loss: 0.013894 (0.013896) Loss: 0.28174 (0.28047) +2025-09-14,02:02:24 | INFO | Train Epoch: 9 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17041 (0.26629) Boundary_loss: 0.013896 (0.013896) Loss: 0.18430 (0.28018) +2025-09-14,02:02:55 | INFO | Train Epoch: 9 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.23070 (0.26618) Boundary_loss: 0.013897 (0.013896) Loss: 0.24460 (0.28008) +2025-09-14,02:03:25 | INFO | Train Epoch: 9 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27996 (0.26622) Boundary_loss: 0.013895 (0.013896) Loss: 0.29385 (0.28012) +2025-09-14,02:03:56 | INFO | Train Epoch: 9 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.25868 (0.26620) Boundary_loss: 0.013895 (0.013896) Loss: 0.27257 (0.28009) +2025-09-14,02:04:27 | INFO | Train Epoch: 9 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.29451 (0.26628) Boundary_loss: 0.013896 (0.013896) Loss: 0.30840 (0.28018) +2025-09-14,02:04:58 | INFO | Train Epoch: 9 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.25802 (0.26626) Boundary_loss: 0.013895 (0.013896) Loss: 0.27191 (0.28015) +2025-09-14,02:05:29 | INFO | Train Epoch: 9 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22728 (0.26614) Boundary_loss: 0.013896 (0.013896) Loss: 0.24118 (0.28004) +2025-09-14,02:05:59 | INFO | Train Epoch: 9 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.27907 (0.26618) Boundary_loss: 0.013896 (0.013896) Loss: 0.29296 (0.28008) +2025-09-14,02:06:30 | INFO | Train Epoch: 9 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28574 (0.26624) Boundary_loss: 0.013895 (0.013896) Loss: 0.29963 (0.28013) +2025-09-14,02:07:01 | INFO | Train Epoch: 9 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.31864 (0.26639) Boundary_loss: 0.013896 (0.013896) Loss: 0.33254 (0.28029) +2025-09-14,02:07:32 | INFO | Train Epoch: 9 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.26019 (0.26637) Boundary_loss: 0.013895 (0.013896) Loss: 0.27409 (0.28027) +2025-09-14,02:08:03 | INFO | Train Epoch: 9 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.35523 (0.26663) Boundary_loss: 0.013894 (0.013896) Loss: 0.36913 (0.28053) +2025-09-14,02:08:34 | INFO | Train Epoch: 9 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.25466 (0.26660) Boundary_loss: 0.013895 (0.013896) Loss: 0.26855 (0.28050) +2025-09-14,02:09:04 | INFO | Train Epoch: 9 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.24389 (0.26653) Boundary_loss: 0.013896 (0.013896) Loss: 0.25779 (0.28043) +2025-09-14,02:09:35 | INFO | Train Epoch: 9 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.25875 (0.26651) Boundary_loss: 0.013896 (0.013896) Loss: 0.27264 (0.28041) +2025-09-14,02:10:06 | INFO | Train Epoch: 9 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.22695 (0.26640) Boundary_loss: 0.013897 (0.013896) Loss: 0.24085 (0.28029) +2025-09-14,02:10:36 | INFO | Train Epoch: 9 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30918 (0.26652) Boundary_loss: 0.013896 (0.013896) Loss: 0.32307 (0.28042) +2025-09-14,02:11:07 | INFO | Train Epoch: 9 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.26792 (0.26652) Boundary_loss: 0.013896 (0.013896) Loss: 0.28181 (0.28042) +2025-09-14,02:11:38 | INFO | Train Epoch: 9 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21636 (0.26638) Boundary_loss: 0.013895 (0.013896) Loss: 0.23025 (0.28028) +2025-09-14,02:12:09 | INFO | Train Epoch: 9 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19802 (0.26619) Boundary_loss: 0.013895 (0.013896) Loss: 0.21192 (0.28008) +2025-09-14,02:12:40 | INFO | Train Epoch: 9 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.24850 (0.26613) Boundary_loss: 0.013895 (0.013896) Loss: 0.26239 (0.28003) +2025-09-14,02:13:11 | INFO | Train Epoch: 9 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.24228 (0.26607) Boundary_loss: 0.013895 (0.013896) Loss: 0.25617 (0.27996) +2025-09-14,02:13:41 | INFO | Train Epoch: 9 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.27226 (0.26608) Boundary_loss: 0.013895 (0.013896) Loss: 0.28616 (0.27998) +2025-09-14,02:14:12 | INFO | Train Epoch: 9 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.25871 (0.26606) Boundary_loss: 0.013894 (0.013896) Loss: 0.27260 (0.27996) +2025-09-14,02:14:43 | INFO | Train Epoch: 9 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.25162 (0.26602) Boundary_loss: 0.013895 (0.013896) Loss: 0.26552 (0.27992) +2025-09-14,02:15:14 | INFO | Train Epoch: 9 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.23696 (0.26594) Boundary_loss: 0.013896 (0.013896) Loss: 0.25085 (0.27984) +2025-09-14,02:15:44 | INFO | Train Epoch: 9 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.28343 (0.26599) Boundary_loss: 0.013896 (0.013896) Loss: 0.29733 (0.27989) +2025-09-14,02:16:15 | INFO | Train Epoch: 9 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.29718 (0.26608) Boundary_loss: 0.013894 (0.013896) Loss: 0.31108 (0.27997) +2025-09-14,02:16:46 | INFO | Train Epoch: 9 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.24937 (0.26603) Boundary_loss: 0.013896 (0.013896) Loss: 0.26326 (0.27993) +2025-09-14,02:17:16 | INFO | Train Epoch: 9 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.25739 (0.26601) Boundary_loss: 0.013895 (0.013896) Loss: 0.27128 (0.27990) +2025-09-14,02:17:47 | INFO | Train Epoch: 9 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23162 (0.26591) Boundary_loss: 0.013896 (0.013896) Loss: 0.24552 (0.27981) +2025-09-14,02:18:17 | INFO | Train Epoch: 9 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.21561 (0.26577) Boundary_loss: 0.013896 (0.013896) Loss: 0.22951 (0.27967) +2025-09-14,02:18:48 | INFO | Train Epoch: 9 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21985 (0.26565) Boundary_loss: 0.013895 (0.013896) Loss: 0.23374 (0.27954) +2025-09-14,02:19:19 | INFO | Train Epoch: 9 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.30556 (0.26576) Boundary_loss: 0.013896 (0.013896) Loss: 0.31946 (0.27965) +2025-09-14,02:19:50 | INFO | Train Epoch: 9 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.27423 (0.26578) Boundary_loss: 0.013896 (0.013896) Loss: 0.28813 (0.27967) +2025-09-14,02:20:21 | INFO | Train Epoch: 9 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22450 (0.26567) Boundary_loss: 0.013896 (0.013896) Loss: 0.23839 (0.27956) +2025-09-14,02:20:51 | INFO | Train Epoch: 9 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.32992 (0.26584) Boundary_loss: 0.013894 (0.013896) Loss: 0.34381 (0.27974) +2025-09-14,02:21:22 | INFO | Train Epoch: 9 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.25495 (0.26581) Boundary_loss: 0.013896 (0.013896) Loss: 0.26884 (0.27971) +2025-09-14,02:21:53 | INFO | Train Epoch: 9 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22712 (0.26571) Boundary_loss: 0.013896 (0.013896) Loss: 0.24102 (0.27960) +2025-09-14,02:22:24 | INFO | Train Epoch: 9 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.25736 (0.26568) Boundary_loss: 0.013897 (0.013896) Loss: 0.27125 (0.27958) +2025-09-14,02:22:54 | INFO | Train Epoch: 9 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.28383 (0.26573) Boundary_loss: 0.013895 (0.013896) Loss: 0.29773 (0.27963) +2025-09-14,02:23:25 | INFO | Train Epoch: 9 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.21763 (0.26560) Boundary_loss: 0.013895 (0.013896) Loss: 0.23152 (0.27950) +2025-09-14,02:23:56 | INFO | Train Epoch: 9 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.27676 (0.26563) Boundary_loss: 0.013899 (0.013896) Loss: 0.29066 (0.27953) +2025-09-14,02:24:27 | INFO | Train Epoch: 9 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.26654 (0.26564) Boundary_loss: 0.013897 (0.013896) Loss: 0.28044 (0.27953) +2025-09-14,02:24:57 | INFO | Train Epoch: 9 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.25814 (0.26562) Boundary_loss: 0.013896 (0.013896) Loss: 0.27203 (0.27951) +2025-09-14,02:25:28 | INFO | Train Epoch: 9 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.33244 (0.26579) Boundary_loss: 0.013895 (0.013896) Loss: 0.34634 (0.27969) +2025-09-14,02:25:59 | INFO | Train Epoch: 9 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.29043 (0.26586) Boundary_loss: 0.013896 (0.013896) Loss: 0.30432 (0.27975) +2025-09-14,02:26:30 | INFO | Train Epoch: 9 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.29682 (0.26594) Boundary_loss: 0.013897 (0.013896) Loss: 0.31071 (0.27984) +2025-09-14,02:27:01 | INFO | Train Epoch: 9 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.31580 (0.26607) Boundary_loss: 0.013896 (0.013896) Loss: 0.32970 (0.27997) +2025-09-14,02:27:32 | INFO | Train Epoch: 9 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.23961 (0.26600) Boundary_loss: 0.013895 (0.013896) Loss: 0.25351 (0.27990) +2025-09-14,02:28:03 | INFO | Train Epoch: 9 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.25723 (0.26598) Boundary_loss: 0.013893 (0.013896) Loss: 0.27113 (0.27988) +2025-09-14,02:28:34 | INFO | Train Epoch: 9 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.25185 (0.26594) Boundary_loss: 0.013896 (0.013896) Loss: 0.26574 (0.27984) +2025-09-14,02:29:05 | INFO | Train Epoch: 9 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22554 (0.26584) Boundary_loss: 0.013896 (0.013896) Loss: 0.23944 (0.27973) +2025-09-14,02:29:35 | INFO | Train Epoch: 9 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28428 (0.26589) Boundary_loss: 0.013895 (0.013896) Loss: 0.29817 (0.27978) +2025-09-14,02:30:06 | INFO | Train Epoch: 9 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.22364 (0.26578) Boundary_loss: 0.013895 (0.013896) Loss: 0.23753 (0.27967) +2025-09-14,02:30:37 | INFO | Train Epoch: 9 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27164 (0.26579) Boundary_loss: 0.013897 (0.013896) Loss: 0.28554 (0.27969) +2025-09-14,02:31:08 | INFO | Train Epoch: 9 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.27285 (0.26581) Boundary_loss: 0.013897 (0.013896) Loss: 0.28675 (0.27971) +2025-09-14,02:31:39 | INFO | Train Epoch: 9 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.29762 (0.26589) Boundary_loss: 0.013895 (0.013896) Loss: 0.31151 (0.27979) +2025-09-14,02:32:10 | INFO | Train Epoch: 9 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.24781 (0.26584) Boundary_loss: 0.013894 (0.013896) Loss: 0.26170 (0.27974) +2025-09-14,02:32:40 | INFO | Train Epoch: 9 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.25834 (0.26583) Boundary_loss: 0.013897 (0.013896) Loss: 0.27224 (0.27972) +2025-09-14,02:33:11 | INFO | Train Epoch: 9 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31627 (0.26595) Boundary_loss: 0.013895 (0.013896) Loss: 0.33017 (0.27985) +2025-09-14,02:33:42 | INFO | Train Epoch: 9 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.25441 (0.26593) Boundary_loss: 0.013896 (0.013896) Loss: 0.26830 (0.27982) +2025-09-14,02:34:13 | INFO | Train Epoch: 9 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.25014 (0.26589) Boundary_loss: 0.013894 (0.013896) Loss: 0.26403 (0.27978) +2025-09-14,02:34:43 | INFO | Train Epoch: 9 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.26749 (0.26589) Boundary_loss: 0.013895 (0.013896) Loss: 0.28138 (0.27978) +2025-09-14,02:35:14 | INFO | Train Epoch: 9 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.23062 (0.26580) Boundary_loss: 0.013895 (0.013896) Loss: 0.24451 (0.27970) +2025-09-14,02:35:45 | INFO | Train Epoch: 9 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28242 (0.26584) Boundary_loss: 0.013895 (0.013896) Loss: 0.29632 (0.27974) +2025-09-14,02:36:16 | INFO | Train Epoch: 9 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.28457 (0.26589) Boundary_loss: 0.013894 (0.013896) Loss: 0.29847 (0.27978) +2025-09-14,02:36:47 | INFO | Train Epoch: 9 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24572 (0.26584) Boundary_loss: 0.013896 (0.013896) Loss: 0.25961 (0.27973) +2025-09-14,02:37:18 | INFO | Train Epoch: 9 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.31463 (0.26596) Boundary_loss: 0.013894 (0.013896) Loss: 0.32853 (0.27986) +2025-09-14,02:37:49 | INFO | Train Epoch: 9 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26020 (0.26595) Boundary_loss: 0.013897 (0.013896) Loss: 0.27410 (0.27984) +2025-09-14,02:38:19 | INFO | Train Epoch: 9 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25446 (0.26592) Boundary_loss: 0.013895 (0.013896) Loss: 0.26836 (0.27981) +2025-09-14,02:38:50 | INFO | Train Epoch: 9 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.26421 (0.26591) Boundary_loss: 0.013894 (0.013896) Loss: 0.27810 (0.27981) +2025-09-14,02:39:21 | INFO | Train Epoch: 9 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.26327 (0.26591) Boundary_loss: 0.013897 (0.013896) Loss: 0.27717 (0.27980) +2025-09-14,02:39:52 | INFO | Train Epoch: 9 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.27117 (0.26592) Boundary_loss: 0.013895 (0.013896) Loss: 0.28507 (0.27982) +2025-09-14,02:40:23 | INFO | Train Epoch: 9 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.29611 (0.26599) Boundary_loss: 0.013896 (0.013896) Loss: 0.31000 (0.27989) +2025-09-14,02:40:54 | INFO | Train Epoch: 9 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.23363 (0.26591) Boundary_loss: 0.013896 (0.013896) Loss: 0.24752 (0.27981) +2025-09-14,02:41:25 | INFO | Train Epoch: 9 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22207 (0.26581) Boundary_loss: 0.013895 (0.013896) Loss: 0.23597 (0.27970) +2025-09-14,02:41:56 | INFO | Train Epoch: 9 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28747 (0.26586) Boundary_loss: 0.013895 (0.013896) Loss: 0.30137 (0.27976) +2025-09-14,02:42:26 | INFO | Train Epoch: 9 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.30771 (0.26596) Boundary_loss: 0.013894 (0.013896) Loss: 0.32160 (0.27986) +2025-09-14,02:42:57 | INFO | Train Epoch: 9 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.37444 (0.26623) Boundary_loss: 0.013896 (0.013896) Loss: 0.38834 (0.28012) +2025-09-14,02:43:28 | INFO | Train Epoch: 9 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.31427 (0.26634) Boundary_loss: 0.013896 (0.013896) Loss: 0.32816 (0.28024) +2025-09-14,02:43:59 | INFO | Train Epoch: 9 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.24368 (0.26629) Boundary_loss: 0.013897 (0.013896) Loss: 0.25758 (0.28018) +2025-09-14,02:44:30 | INFO | Train Epoch: 9 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.27210 (0.26630) Boundary_loss: 0.013895 (0.013896) Loss: 0.28600 (0.28020) +2025-09-14,02:45:00 | INFO | Train Epoch: 9 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.26021 (0.26629) Boundary_loss: 0.013895 (0.013896) Loss: 0.27410 (0.28018) +2025-09-14,02:45:31 | INFO | Train Epoch: 9 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.23384 (0.26621) Boundary_loss: 0.013897 (0.013896) Loss: 0.24773 (0.28011) +2025-09-14,02:46:02 | INFO | Train Epoch: 9 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.24545 (0.26616) Boundary_loss: 0.013895 (0.013896) Loss: 0.25935 (0.28006) +2025-09-14,02:46:33 | INFO | Train Epoch: 9 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.19080 (0.26598) Boundary_loss: 0.013896 (0.013896) Loss: 0.20470 (0.27987) +2025-09-14,02:47:04 | INFO | Train Epoch: 9 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.25106 (0.26594) Boundary_loss: 0.013896 (0.013896) Loss: 0.26496 (0.27984) +2025-09-14,02:47:35 | INFO | Train Epoch: 9 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.24439 (0.26589) Boundary_loss: 0.013895 (0.013896) Loss: 0.25828 (0.27979) +2025-09-14,02:48:05 | INFO | Train Epoch: 9 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23273 (0.26581) Boundary_loss: 0.013896 (0.013896) Loss: 0.24663 (0.27971) +2025-09-14,02:48:36 | INFO | Train Epoch: 9 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.35678 (0.26603) Boundary_loss: 0.013895 (0.013896) Loss: 0.37067 (0.27992) +2025-09-14,02:49:07 | INFO | Train Epoch: 9 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.26820 (0.26603) Boundary_loss: 0.013894 (0.013896) Loss: 0.28209 (0.27993) +2025-09-14,02:49:38 | INFO | Train Epoch: 9 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24185 (0.26598) Boundary_loss: 0.013895 (0.013896) Loss: 0.25574 (0.27987) +2025-09-14,02:50:09 | INFO | Train Epoch: 9 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.23524 (0.26590) Boundary_loss: 0.013896 (0.013896) Loss: 0.24914 (0.27980) +2025-09-14,02:50:39 | INFO | Train Epoch: 9 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.26861 (0.26591) Boundary_loss: 0.013897 (0.013896) Loss: 0.28251 (0.27981) +2025-09-14,02:51:10 | INFO | Train Epoch: 9 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.25766 (0.26589) Boundary_loss: 0.013896 (0.013896) Loss: 0.27156 (0.27979) +2025-09-14,02:51:40 | INFO | Train Epoch: 9 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22206 (0.26579) Boundary_loss: 0.013895 (0.013896) Loss: 0.23596 (0.27968) +2025-09-14,02:52:11 | INFO | Train Epoch: 9 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.19936 (0.26563) Boundary_loss: 0.013896 (0.013896) Loss: 0.21325 (0.27953) +2025-09-14,02:52:42 | INFO | Train Epoch: 9 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.25120 (0.26560) Boundary_loss: 0.013896 (0.013896) Loss: 0.26509 (0.27950) +2025-09-14,02:53:13 | INFO | Train Epoch: 9 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.30260 (0.26569) Boundary_loss: 0.013896 (0.013896) Loss: 0.31650 (0.27958) +2025-09-14,02:53:43 | INFO | Train Epoch: 9 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.28089 (0.26572) Boundary_loss: 0.013896 (0.013896) Loss: 0.29479 (0.27962) +2025-09-14,02:54:14 | INFO | Train Epoch: 9 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.26885 (0.26573) Boundary_loss: 0.013895 (0.013896) Loss: 0.28275 (0.27962) +2025-09-14,02:54:45 | INFO | Train Epoch: 9 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.28703 (0.26578) Boundary_loss: 0.013897 (0.013896) Loss: 0.30092 (0.27967) +2025-09-14,02:55:15 | INFO | Train Epoch: 9 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.36268 (0.26600) Boundary_loss: 0.013897 (0.013896) Loss: 0.37658 (0.27990) +2025-09-14,02:55:46 | INFO | Train Epoch: 9 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.28224 (0.26604) Boundary_loss: 0.013894 (0.013896) Loss: 0.29613 (0.27993) +2025-09-14,02:56:17 | INFO | Train Epoch: 9 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.31714 (0.26616) Boundary_loss: 0.013895 (0.013896) Loss: 0.33104 (0.28005) +2025-09-14,02:56:48 | INFO | Train Epoch: 9 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.34323 (0.26633) Boundary_loss: 0.013895 (0.013896) Loss: 0.35712 (0.28023) +2025-09-14,02:57:18 | INFO | Train Epoch: 9 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.27756 (0.26636) Boundary_loss: 0.013894 (0.013896) Loss: 0.29145 (0.28025) +2025-09-14,02:57:49 | INFO | Train Epoch: 9 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.28954 (0.26641) Boundary_loss: 0.013894 (0.013896) Loss: 0.30343 (0.28031) +2025-09-14,02:58:20 | INFO | Train Epoch: 9 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.28437 (0.26645) Boundary_loss: 0.013894 (0.013896) Loss: 0.29826 (0.28035) +2025-09-14,02:58:51 | INFO | Train Epoch: 9 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.24892 (0.26641) Boundary_loss: 0.013896 (0.013896) Loss: 0.26281 (0.28031) +2025-09-14,02:59:22 | INFO | Train Epoch: 9 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.28520 (0.26645) Boundary_loss: 0.013895 (0.013896) Loss: 0.29909 (0.28035) +2025-09-14,02:59:52 | INFO | Train Epoch: 9 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.35048 (0.26664) Boundary_loss: 0.013894 (0.013896) Loss: 0.36437 (0.28054) +2025-09-14,03:00:23 | INFO | Train Epoch: 9 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.22370 (0.26655) Boundary_loss: 0.013896 (0.013896) Loss: 0.23759 (0.28044) +2025-09-14,03:00:54 | INFO | Train Epoch: 9 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.30906 (0.26664) Boundary_loss: 0.013895 (0.013896) Loss: 0.32296 (0.28054) +2025-09-14,03:01:25 | INFO | Train Epoch: 9 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.29213 (0.26670) Boundary_loss: 0.013895 (0.013896) Loss: 0.30602 (0.28060) +2025-09-14,03:01:56 | INFO | Train Epoch: 9 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.23597 (0.26663) Boundary_loss: 0.013895 (0.013896) Loss: 0.24986 (0.28053) +2025-09-14,03:02:27 | INFO | Train Epoch: 9 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.18121 (0.26644) Boundary_loss: 0.013897 (0.013896) Loss: 0.19511 (0.28034) +2025-09-14,03:02:58 | INFO | Train Epoch: 9 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.26666 (0.26644) Boundary_loss: 0.013896 (0.013896) Loss: 0.28055 (0.28034) +2025-09-14,03:03:29 | INFO | Train Epoch: 9 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.23713 (0.26638) Boundary_loss: 0.013896 (0.013896) Loss: 0.25103 (0.28027) +2025-09-14,03:04:00 | INFO | Train Epoch: 9 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23094 (0.26630) Boundary_loss: 0.013896 (0.013896) Loss: 0.24483 (0.28019) +2025-09-14,03:04:31 | INFO | Train Epoch: 9 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19028 (0.26613) Boundary_loss: 0.013895 (0.013896) Loss: 0.20418 (0.28002) +2025-09-14,03:05:02 | INFO | Train Epoch: 9 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.30561 (0.26622) Boundary_loss: 0.013897 (0.013896) Loss: 0.31951 (0.28011) +2025-09-14,03:05:33 | INFO | Train Epoch: 9 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.26344 (0.26621) Boundary_loss: 0.013895 (0.013896) Loss: 0.27733 (0.28011) +2025-09-14,03:06:04 | INFO | Train Epoch: 9 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.27877 (0.26624) Boundary_loss: 0.013895 (0.013896) Loss: 0.29267 (0.28013) +2025-09-14,03:06:35 | INFO | Train Epoch: 9 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.28921 (0.26629) Boundary_loss: 0.013895 (0.013896) Loss: 0.30311 (0.28018) +2025-09-14,03:07:06 | INFO | Train Epoch: 9 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30045 (0.26636) Boundary_loss: 0.013895 (0.013896) Loss: 0.31434 (0.28026) +2025-09-14,03:07:37 | INFO | Train Epoch: 9 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.26445 (0.26636) Boundary_loss: 0.013897 (0.013896) Loss: 0.27835 (0.28025) +2025-09-14,03:08:08 | INFO | Train Epoch: 9 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.27409 (0.26638) Boundary_loss: 0.013897 (0.013896) Loss: 0.28799 (0.28027) +2025-09-14,03:08:39 | INFO | Train Epoch: 9 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.28720 (0.26642) Boundary_loss: 0.013896 (0.013896) Loss: 0.30110 (0.28032) +2025-09-14,03:09:09 | INFO | Train Epoch: 9 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.24069 (0.26636) Boundary_loss: 0.013895 (0.013896) Loss: 0.25459 (0.28026) +2025-09-14,03:09:40 | INFO | Train Epoch: 9 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.27955 (0.26639) Boundary_loss: 0.013896 (0.013896) Loss: 0.29344 (0.28029) +2025-09-14,03:10:11 | INFO | Train Epoch: 9 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24077 (0.26634) Boundary_loss: 0.013895 (0.013896) Loss: 0.25467 (0.28023) +2025-09-14,03:10:42 | INFO | Train Epoch: 9 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.25966 (0.26632) Boundary_loss: 0.013895 (0.013896) Loss: 0.27356 (0.28022) +2025-09-14,03:11:13 | INFO | Train Epoch: 9 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.28514 (0.26636) Boundary_loss: 0.013896 (0.013896) Loss: 0.29904 (0.28026) +2025-09-14,03:11:44 | INFO | Train Epoch: 9 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.20516 (0.26623) Boundary_loss: 0.013895 (0.013896) Loss: 0.21905 (0.28013) +2025-09-14,03:12:15 | INFO | Train Epoch: 9 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.22961 (0.26615) Boundary_loss: 0.013896 (0.013896) Loss: 0.24351 (0.28005) +2025-09-14,03:12:46 | INFO | Train Epoch: 9 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.25388 (0.26613) Boundary_loss: 0.013897 (0.013896) Loss: 0.26778 (0.28002) +2025-09-14,03:13:17 | INFO | Train Epoch: 9 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.27808 (0.26615) Boundary_loss: 0.013896 (0.013896) Loss: 0.29197 (0.28005) +2025-09-14,03:13:48 | INFO | Train Epoch: 9 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.28445 (0.26619) Boundary_loss: 0.013895 (0.013896) Loss: 0.29835 (0.28009) +2025-09-14,03:14:18 | INFO | Train Epoch: 9 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.30057 (0.26627) Boundary_loss: 0.013897 (0.013896) Loss: 0.31446 (0.28016) +2025-09-14,03:14:49 | INFO | Train Epoch: 9 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.27532 (0.26628) Boundary_loss: 0.013897 (0.013896) Loss: 0.28922 (0.28018) +2025-09-14,03:15:20 | INFO | Train Epoch: 9 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.26387 (0.26628) Boundary_loss: 0.013895 (0.013896) Loss: 0.27776 (0.28018) +2025-09-14,03:15:51 | INFO | Train Epoch: 9 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.29328 (0.26634) Boundary_loss: 0.013896 (0.013896) Loss: 0.30717 (0.28023) +2025-09-14,03:16:22 | INFO | Train Epoch: 9 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.24243 (0.26629) Boundary_loss: 0.013896 (0.013896) Loss: 0.25633 (0.28018) +2025-09-14,03:16:53 | INFO | Train Epoch: 9 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.27505 (0.26630) Boundary_loss: 0.013896 (0.013896) Loss: 0.28895 (0.28020) +2025-09-14,03:17:24 | INFO | Train Epoch: 9 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.28718 (0.26635) Boundary_loss: 0.013895 (0.013896) Loss: 0.30107 (0.28024) +2025-09-14,03:17:54 | INFO | Train Epoch: 9 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.22777 (0.26627) Boundary_loss: 0.013895 (0.013896) Loss: 0.24166 (0.28016) +2025-09-14,03:18:25 | INFO | Train Epoch: 9 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29131 (0.26632) Boundary_loss: 0.013897 (0.013896) Loss: 0.30521 (0.28022) +2025-09-14,03:18:56 | INFO | Train Epoch: 9 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.20141 (0.26618) Boundary_loss: 0.013895 (0.013896) Loss: 0.21531 (0.28008) +2025-09-14,03:19:27 | INFO | Train Epoch: 9 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.31419 (0.26628) Boundary_loss: 0.013896 (0.013896) Loss: 0.32808 (0.28018) +2025-09-14,03:19:58 | INFO | Train Epoch: 9 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.21356 (0.26618) Boundary_loss: 0.013896 (0.013896) Loss: 0.22745 (0.28007) +2025-09-14,03:20:29 | INFO | Train Epoch: 9 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.23195 (0.26610) Boundary_loss: 0.013896 (0.013896) Loss: 0.24584 (0.28000) +2025-09-14,03:20:59 | INFO | Train Epoch: 9 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30595 (0.26619) Boundary_loss: 0.013894 (0.013896) Loss: 0.31984 (0.28008) +2025-09-14,03:21:30 | INFO | Train Epoch: 9 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.32528 (0.26631) Boundary_loss: 0.013895 (0.013896) Loss: 0.33917 (0.28020) +2025-09-14,03:22:01 | INFO | Train Epoch: 9 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22550 (0.26622) Boundary_loss: 0.013896 (0.013896) Loss: 0.23940 (0.28012) +2025-09-14,03:22:32 | INFO | Train Epoch: 9 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.25249 (0.26620) Boundary_loss: 0.013897 (0.013896) Loss: 0.26639 (0.28009) +2025-09-14,03:23:03 | INFO | Train Epoch: 9 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30155 (0.26627) Boundary_loss: 0.013896 (0.013896) Loss: 0.31545 (0.28016) +2025-09-14,03:23:33 | INFO | Train Epoch: 9 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22761 (0.26619) Boundary_loss: 0.013895 (0.013896) Loss: 0.24150 (0.28009) +2025-09-14,03:24:04 | INFO | Train Epoch: 9 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.23542 (0.26613) Boundary_loss: 0.013896 (0.013896) Loss: 0.24931 (0.28002) +2025-09-14,03:24:35 | INFO | Train Epoch: 9 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23410 (0.26606) Boundary_loss: 0.013897 (0.013896) Loss: 0.24799 (0.27996) +2025-09-14,03:25:06 | INFO | Train Epoch: 9 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.26532 (0.26606) Boundary_loss: 0.013894 (0.013896) Loss: 0.27922 (0.27996) +2025-09-14,03:25:37 | INFO | Train Epoch: 9 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.24593 (0.26602) Boundary_loss: 0.013895 (0.013896) Loss: 0.25983 (0.27991) +2025-09-14,03:26:08 | INFO | Train Epoch: 9 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.29567 (0.26608) Boundary_loss: 0.013895 (0.013896) Loss: 0.30956 (0.27997) +2025-09-14,03:26:39 | INFO | Train Epoch: 9 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18786 (0.26592) Boundary_loss: 0.013895 (0.013896) Loss: 0.20176 (0.27982) +2025-09-14,03:27:10 | INFO | Train Epoch: 9 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.33060 (0.26605) Boundary_loss: 0.013896 (0.013896) Loss: 0.34450 (0.27995) +2025-09-14,03:27:40 | INFO | Train Epoch: 9 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24717 (0.26601) Boundary_loss: 0.013894 (0.013896) Loss: 0.26107 (0.27991) +2025-09-14,03:28:11 | INFO | Train Epoch: 9 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.26089 (0.26600) Boundary_loss: 0.013896 (0.013896) Loss: 0.27478 (0.27990) +2025-09-14,03:28:42 | INFO | Train Epoch: 9 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.21041 (0.26589) Boundary_loss: 0.013896 (0.013896) Loss: 0.22430 (0.27979) +2025-09-14,03:29:13 | INFO | Train Epoch: 9 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.27065 (0.26590) Boundary_loss: 0.013895 (0.013896) Loss: 0.28455 (0.27980) +2025-09-14,03:29:44 | INFO | Train Epoch: 9 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.25526 (0.26588) Boundary_loss: 0.013895 (0.013896) Loss: 0.26916 (0.27978) +2025-09-14,03:30:15 | INFO | Train Epoch: 9 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.30199 (0.26595) Boundary_loss: 0.013896 (0.013896) Loss: 0.31589 (0.27985) +2025-09-14,03:30:46 | INFO | Train Epoch: 9 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.24623 (0.26591) Boundary_loss: 0.013897 (0.013896) Loss: 0.26013 (0.27981) +2025-09-14,03:31:17 | INFO | Train Epoch: 9 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.26014 (0.26590) Boundary_loss: 0.013896 (0.013896) Loss: 0.27403 (0.27980) +2025-09-14,03:31:48 | INFO | Train Epoch: 9 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.31301 (0.26599) Boundary_loss: 0.013896 (0.013896) Loss: 0.32690 (0.27989) +2025-09-14,03:32:19 | INFO | Train Epoch: 9 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.30096 (0.26606) Boundary_loss: 0.013897 (0.013896) Loss: 0.31486 (0.27996) +2025-09-14,03:32:49 | INFO | Train Epoch: 9 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.32242 (0.26618) Boundary_loss: 0.013895 (0.013896) Loss: 0.33632 (0.28007) +2025-09-14,03:33:20 | INFO | Train Epoch: 9 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.24802 (0.26614) Boundary_loss: 0.013896 (0.013896) Loss: 0.26192 (0.28004) +2025-09-14,03:33:51 | INFO | Train Epoch: 9 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.29494 (0.26620) Boundary_loss: 0.013894 (0.013896) Loss: 0.30883 (0.28009) +2025-09-14,03:34:22 | INFO | Train Epoch: 9 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.30332 (0.26627) Boundary_loss: 0.013896 (0.013896) Loss: 0.31722 (0.28016) +2025-09-14,03:34:53 | INFO | Train Epoch: 9 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20480 (0.26615) Boundary_loss: 0.013896 (0.013896) Loss: 0.21869 (0.28004) +2025-09-14,03:35:23 | INFO | Train Epoch: 9 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24326 (0.26610) Boundary_loss: 0.013895 (0.013896) Loss: 0.25715 (0.28000) +2025-09-14,03:35:54 | INFO | Train Epoch: 9 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.25096 (0.26607) Boundary_loss: 0.013895 (0.013896) Loss: 0.26486 (0.27997) +2025-09-14,03:36:25 | INFO | Train Epoch: 9 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26079 (0.26606) Boundary_loss: 0.013895 (0.013896) Loss: 0.27469 (0.27996) +2025-09-14,03:36:56 | INFO | Train Epoch: 9 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24075 (0.26601) Boundary_loss: 0.013895 (0.013896) Loss: 0.25464 (0.27991) +2025-09-14,03:37:25 | INFO | Train Epoch: 9 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24254 (0.26597) Boundary_loss: 0.013895 (0.013896) Loss: 0.25644 (0.27986) +2025-09-14,03:37:25 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,03:37:25 | INFO | [Epoch 9] Average Step Time: 0.311s | Average GPU Memory: 25.2 GB +2025-09-14,03:37:25 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,03:37:25 | INFO | Starting zero-shot imagenet. +2025-09-14,03:37:25 | INFO | Building zero-shot classifier +2025-09-14,03:37:31 | INFO | Using classifier +2025-09-14,03:38:08 | INFO | Finished zero-shot imagenet. +2025-09-14,03:38:08 | INFO | Eval Epoch: 10 imagenet-zeroshot-val-top1: 0.2849 imagenet-zeroshot-val-top5: 0.5432 +2025-09-14,03:38:10 | INFO | Start epoch 10 +2025-09-14,03:38:11 | INFO | Train Epoch: 10 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.15692 (0.15692) Boundary_loss: 0.013896 (0.013896) Loss: 0.17081 (0.17081) +2025-09-14,03:38:42 | INFO | Train Epoch: 10 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.25587 (0.20639) Boundary_loss: 0.013894 (0.013895) Loss: 0.26976 (0.22029) +2025-09-14,03:39:13 | INFO | Train Epoch: 10 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.22132 (0.21137) Boundary_loss: 0.013895 (0.013895) Loss: 0.23522 (0.22526) +2025-09-14,03:39:43 | INFO | Train Epoch: 10 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22804 (0.21554) Boundary_loss: 0.013895 (0.013895) Loss: 0.24194 (0.22943) +2025-09-14,03:40:14 | INFO | Train Epoch: 10 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.25369 (0.22317) Boundary_loss: 0.013895 (0.013895) Loss: 0.26758 (0.23706) +2025-09-14,03:40:44 | INFO | Train Epoch: 10 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15460 (0.21174) Boundary_loss: 0.013896 (0.013895) Loss: 0.16850 (0.22563) +2025-09-14,03:41:14 | INFO | Train Epoch: 10 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17738 (0.20683) Boundary_loss: 0.013896 (0.013895) Loss: 0.19127 (0.22073) +2025-09-14,03:41:45 | INFO | Train Epoch: 10 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.20816 (0.20700) Boundary_loss: 0.013895 (0.013895) Loss: 0.22206 (0.22089) +2025-09-14,03:42:16 | INFO | Train Epoch: 10 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.21148 (0.20749) Boundary_loss: 0.013894 (0.013895) Loss: 0.22537 (0.22139) +2025-09-14,03:42:46 | INFO | Train Epoch: 10 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20442 (0.20719) Boundary_loss: 0.013895 (0.013895) Loss: 0.21831 (0.22108) +2025-09-14,03:43:17 | INFO | Train Epoch: 10 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23255 (0.20949) Boundary_loss: 0.013896 (0.013895) Loss: 0.24645 (0.22339) +2025-09-14,03:43:48 | INFO | Train Epoch: 10 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.28760 (0.21600) Boundary_loss: 0.013896 (0.013895) Loss: 0.30150 (0.22990) +2025-09-14,03:44:19 | INFO | Train Epoch: 10 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.27225 (0.22033) Boundary_loss: 0.013896 (0.013895) Loss: 0.28615 (0.23422) +2025-09-14,03:44:50 | INFO | Train Epoch: 10 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.19858 (0.21878) Boundary_loss: 0.013896 (0.013895) Loss: 0.21247 (0.23267) +2025-09-14,03:45:20 | INFO | Train Epoch: 10 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20559 (0.21790) Boundary_loss: 0.013895 (0.013895) Loss: 0.21948 (0.23179) +2025-09-14,03:45:51 | INFO | Train Epoch: 10 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23041 (0.21868) Boundary_loss: 0.013896 (0.013895) Loss: 0.24430 (0.23257) +2025-09-14,03:46:22 | INFO | Train Epoch: 10 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.27502 (0.22199) Boundary_loss: 0.013895 (0.013895) Loss: 0.28892 (0.23589) +2025-09-14,03:46:53 | INFO | Train Epoch: 10 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.18107 (0.21972) Boundary_loss: 0.013895 (0.013895) Loss: 0.19496 (0.23361) +2025-09-14,03:47:23 | INFO | Train Epoch: 10 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.23227 (0.22038) Boundary_loss: 0.013896 (0.013895) Loss: 0.24617 (0.23428) +2025-09-14,03:47:54 | INFO | Train Epoch: 10 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.21650 (0.22019) Boundary_loss: 0.013898 (0.013895) Loss: 0.23040 (0.23408) +2025-09-14,03:48:25 | INFO | Train Epoch: 10 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.19038 (0.21877) Boundary_loss: 0.013897 (0.013896) Loss: 0.20428 (0.23266) +2025-09-14,03:48:56 | INFO | Train Epoch: 10 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19865 (0.21785) Boundary_loss: 0.013895 (0.013896) Loss: 0.21255 (0.23175) +2025-09-14,03:49:26 | INFO | Train Epoch: 10 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22512 (0.21817) Boundary_loss: 0.013896 (0.013896) Loss: 0.23902 (0.23206) +2025-09-14,03:49:57 | INFO | Train Epoch: 10 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21024 (0.21784) Boundary_loss: 0.013896 (0.013896) Loss: 0.22413 (0.23173) +2025-09-14,03:50:28 | INFO | Train Epoch: 10 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.20292 (0.21724) Boundary_loss: 0.013895 (0.013896) Loss: 0.21682 (0.23114) +2025-09-14,03:50:59 | INFO | Train Epoch: 10 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.23397 (0.21788) Boundary_loss: 0.013896 (0.013896) Loss: 0.24786 (0.23178) +2025-09-14,03:51:30 | INFO | Train Epoch: 10 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.28808 (0.22048) Boundary_loss: 0.013895 (0.013896) Loss: 0.30198 (0.23438) +2025-09-14,03:52:00 | INFO | Train Epoch: 10 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19477 (0.21957) Boundary_loss: 0.013895 (0.013896) Loss: 0.20867 (0.23346) +2025-09-14,03:52:31 | INFO | Train Epoch: 10 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.23401 (0.22006) Boundary_loss: 0.013895 (0.013896) Loss: 0.24790 (0.23396) +2025-09-14,03:53:02 | INFO | Train Epoch: 10 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.25227 (0.22114) Boundary_loss: 0.013896 (0.013896) Loss: 0.26616 (0.23503) +2025-09-14,03:53:33 | INFO | Train Epoch: 10 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.22535 (0.22127) Boundary_loss: 0.013895 (0.013896) Loss: 0.23925 (0.23517) +2025-09-14,03:54:04 | INFO | Train Epoch: 10 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.22808 (0.22149) Boundary_loss: 0.013895 (0.013896) Loss: 0.24198 (0.23538) +2025-09-14,03:54:35 | INFO | Train Epoch: 10 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.15122 (0.21936) Boundary_loss: 0.013895 (0.013895) Loss: 0.16512 (0.23325) +2025-09-14,03:55:06 | INFO | Train Epoch: 10 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.29848 (0.22168) Boundary_loss: 0.013895 (0.013895) Loss: 0.31238 (0.23558) +2025-09-14,03:55:36 | INFO | Train Epoch: 10 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.26238 (0.22285) Boundary_loss: 0.013894 (0.013895) Loss: 0.27627 (0.23674) +2025-09-14,03:56:07 | INFO | Train Epoch: 10 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.22339 (0.22286) Boundary_loss: 0.013894 (0.013895) Loss: 0.23729 (0.23676) +2025-09-14,03:56:37 | INFO | Train Epoch: 10 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.24594 (0.22349) Boundary_loss: 0.013896 (0.013895) Loss: 0.25983 (0.23738) +2025-09-14,03:57:07 | INFO | Train Epoch: 10 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.25692 (0.22437) Boundary_loss: 0.013896 (0.013895) Loss: 0.27082 (0.23826) +2025-09-14,03:57:38 | INFO | Train Epoch: 10 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21933 (0.22424) Boundary_loss: 0.013896 (0.013895) Loss: 0.23322 (0.23813) +2025-09-14,03:58:08 | INFO | Train Epoch: 10 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.22617 (0.22429) Boundary_loss: 0.013896 (0.013895) Loss: 0.24006 (0.23818) +2025-09-14,03:58:39 | INFO | Train Epoch: 10 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24916 (0.22489) Boundary_loss: 0.013896 (0.013895) Loss: 0.26306 (0.23879) +2025-09-14,03:59:10 | INFO | Train Epoch: 10 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22266 (0.22484) Boundary_loss: 0.013895 (0.013895) Loss: 0.23656 (0.23873) +2025-09-14,03:59:41 | INFO | Train Epoch: 10 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.16740 (0.22350) Boundary_loss: 0.013895 (0.013895) Loss: 0.18129 (0.23740) +2025-09-14,04:00:12 | INFO | Train Epoch: 10 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20102 (0.22299) Boundary_loss: 0.013895 (0.013895) Loss: 0.21492 (0.23689) +2025-09-14,04:00:43 | INFO | Train Epoch: 10 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.25047 (0.22360) Boundary_loss: 0.013895 (0.013895) Loss: 0.26437 (0.23750) +2025-09-14,04:01:14 | INFO | Train Epoch: 10 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26282 (0.22446) Boundary_loss: 0.013895 (0.013895) Loss: 0.27671 (0.23835) +2025-09-14,04:01:45 | INFO | Train Epoch: 10 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24660 (0.22493) Boundary_loss: 0.013895 (0.013895) Loss: 0.26050 (0.23882) +2025-09-14,04:02:15 | INFO | Train Epoch: 10 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19844 (0.22437) Boundary_loss: 0.013896 (0.013895) Loss: 0.21233 (0.23827) +2025-09-14,04:02:46 | INFO | Train Epoch: 10 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.21104 (0.22410) Boundary_loss: 0.013895 (0.013895) Loss: 0.22493 (0.23800) +2025-09-14,04:03:17 | INFO | Train Epoch: 10 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22919 (0.22420) Boundary_loss: 0.013895 (0.013895) Loss: 0.24308 (0.23810) +2025-09-14,04:03:48 | INFO | Train Epoch: 10 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19119 (0.22356) Boundary_loss: 0.013895 (0.013895) Loss: 0.20508 (0.23745) +2025-09-14,04:04:19 | INFO | Train Epoch: 10 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.26140 (0.22428) Boundary_loss: 0.013895 (0.013895) Loss: 0.27529 (0.23818) +2025-09-14,04:04:50 | INFO | Train Epoch: 10 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.28751 (0.22548) Boundary_loss: 0.013896 (0.013895) Loss: 0.30141 (0.23937) +2025-09-14,04:05:21 | INFO | Train Epoch: 10 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.18289 (0.22469) Boundary_loss: 0.013895 (0.013895) Loss: 0.19678 (0.23858) +2025-09-14,04:05:52 | INFO | Train Epoch: 10 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.21172 (0.22445) Boundary_loss: 0.013895 (0.013895) Loss: 0.22561 (0.23835) +2025-09-14,04:06:23 | INFO | Train Epoch: 10 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.20829 (0.22416) Boundary_loss: 0.013895 (0.013895) Loss: 0.22218 (0.23806) +2025-09-14,04:06:53 | INFO | Train Epoch: 10 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.25486 (0.22470) Boundary_loss: 0.013896 (0.013895) Loss: 0.26876 (0.23860) +2025-09-14,04:07:24 | INFO | Train Epoch: 10 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20861 (0.22443) Boundary_loss: 0.013896 (0.013895) Loss: 0.22250 (0.23832) +2025-09-14,04:07:55 | INFO | Train Epoch: 10 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19310 (0.22389) Boundary_loss: 0.013897 (0.013895) Loss: 0.20699 (0.23779) +2025-09-14,04:08:26 | INFO | Train Epoch: 10 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17430 (0.22307) Boundary_loss: 0.013895 (0.013895) Loss: 0.18819 (0.23696) +2025-09-14,04:08:57 | INFO | Train Epoch: 10 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.20858 (0.22283) Boundary_loss: 0.013894 (0.013895) Loss: 0.22247 (0.23673) +2025-09-14,04:09:27 | INFO | Train Epoch: 10 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.23207 (0.22298) Boundary_loss: 0.013895 (0.013895) Loss: 0.24596 (0.23687) +2025-09-14,04:09:58 | INFO | Train Epoch: 10 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21871 (0.22291) Boundary_loss: 0.013897 (0.013895) Loss: 0.23260 (0.23681) +2025-09-14,04:10:29 | INFO | Train Epoch: 10 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.17183 (0.22211) Boundary_loss: 0.013895 (0.013895) Loss: 0.18573 (0.23601) +2025-09-14,04:11:00 | INFO | Train Epoch: 10 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26781 (0.22282) Boundary_loss: 0.013896 (0.013895) Loss: 0.28170 (0.23671) +2025-09-14,04:11:31 | INFO | Train Epoch: 10 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.23160 (0.22295) Boundary_loss: 0.013895 (0.013895) Loss: 0.24550 (0.23684) +2025-09-14,04:12:02 | INFO | Train Epoch: 10 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20539 (0.22269) Boundary_loss: 0.013895 (0.013895) Loss: 0.21928 (0.23658) +2025-09-14,04:12:33 | INFO | Train Epoch: 10 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21345 (0.22255) Boundary_loss: 0.013896 (0.013895) Loss: 0.22735 (0.23645) +2025-09-14,04:13:04 | INFO | Train Epoch: 10 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.29425 (0.22359) Boundary_loss: 0.013896 (0.013895) Loss: 0.30815 (0.23749) +2025-09-14,04:13:35 | INFO | Train Epoch: 10 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.23689 (0.22378) Boundary_loss: 0.013896 (0.013895) Loss: 0.25079 (0.23768) +2025-09-14,04:14:06 | INFO | Train Epoch: 10 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19662 (0.22340) Boundary_loss: 0.013895 (0.013895) Loss: 0.21051 (0.23729) +2025-09-14,04:14:37 | INFO | Train Epoch: 10 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.21719 (0.22331) Boundary_loss: 0.013897 (0.013895) Loss: 0.23109 (0.23721) +2025-09-14,04:15:08 | INFO | Train Epoch: 10 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.25651 (0.22377) Boundary_loss: 0.013895 (0.013895) Loss: 0.27040 (0.23766) +2025-09-14,04:15:38 | INFO | Train Epoch: 10 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21195 (0.22361) Boundary_loss: 0.013895 (0.013895) Loss: 0.22584 (0.23750) +2025-09-14,04:16:09 | INFO | Train Epoch: 10 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22528 (0.22363) Boundary_loss: 0.013895 (0.013895) Loss: 0.23918 (0.23752) +2025-09-14,04:16:40 | INFO | Train Epoch: 10 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.19399 (0.22324) Boundary_loss: 0.013894 (0.013895) Loss: 0.20789 (0.23713) +2025-09-14,04:17:11 | INFO | Train Epoch: 10 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29105 (0.22412) Boundary_loss: 0.013896 (0.013895) Loss: 0.30494 (0.23802) +2025-09-14,04:17:42 | INFO | Train Epoch: 10 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19924 (0.22380) Boundary_loss: 0.013895 (0.013895) Loss: 0.21314 (0.23770) +2025-09-14,04:18:13 | INFO | Train Epoch: 10 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19645 (0.22345) Boundary_loss: 0.013896 (0.013895) Loss: 0.21035 (0.23735) +2025-09-14,04:18:44 | INFO | Train Epoch: 10 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.26371 (0.22396) Boundary_loss: 0.013898 (0.013895) Loss: 0.27761 (0.23785) +2025-09-14,04:19:15 | INFO | Train Epoch: 10 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.21284 (0.22382) Boundary_loss: 0.013897 (0.013895) Loss: 0.22674 (0.23772) +2025-09-14,04:19:46 | INFO | Train Epoch: 10 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18053 (0.22329) Boundary_loss: 0.013895 (0.013895) Loss: 0.19443 (0.23719) +2025-09-14,04:20:17 | INFO | Train Epoch: 10 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.22711 (0.22334) Boundary_loss: 0.013899 (0.013895) Loss: 0.24100 (0.23723) +2025-09-14,04:20:48 | INFO | Train Epoch: 10 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18063 (0.22283) Boundary_loss: 0.013896 (0.013895) Loss: 0.19453 (0.23673) +2025-09-14,04:21:19 | INFO | Train Epoch: 10 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.20271 (0.22259) Boundary_loss: 0.013895 (0.013895) Loss: 0.21661 (0.23649) +2025-09-14,04:21:50 | INFO | Train Epoch: 10 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20511 (0.22239) Boundary_loss: 0.013897 (0.013896) Loss: 0.21901 (0.23629) +2025-09-14,04:22:20 | INFO | Train Epoch: 10 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.24035 (0.22260) Boundary_loss: 0.013895 (0.013896) Loss: 0.25425 (0.23649) +2025-09-14,04:22:51 | INFO | Train Epoch: 10 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.17266 (0.22203) Boundary_loss: 0.013895 (0.013895) Loss: 0.18656 (0.23592) +2025-09-14,04:23:22 | INFO | Train Epoch: 10 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.22839 (0.22210) Boundary_loss: 0.013895 (0.013895) Loss: 0.24229 (0.23600) +2025-09-14,04:23:53 | INFO | Train Epoch: 10 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.23561 (0.22225) Boundary_loss: 0.013894 (0.013895) Loss: 0.24951 (0.23615) +2025-09-14,04:24:24 | INFO | Train Epoch: 10 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.23544 (0.22240) Boundary_loss: 0.013895 (0.013895) Loss: 0.24933 (0.23629) +2025-09-14,04:24:55 | INFO | Train Epoch: 10 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.21647 (0.22233) Boundary_loss: 0.013894 (0.013895) Loss: 0.23036 (0.23623) +2025-09-14,04:25:26 | INFO | Train Epoch: 10 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26635 (0.22280) Boundary_loss: 0.013895 (0.013895) Loss: 0.28024 (0.23670) +2025-09-14,04:25:57 | INFO | Train Epoch: 10 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.25897 (0.22319) Boundary_loss: 0.013896 (0.013895) Loss: 0.27287 (0.23708) +2025-09-14,04:26:28 | INFO | Train Epoch: 10 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.19624 (0.22291) Boundary_loss: 0.013895 (0.013895) Loss: 0.21013 (0.23680) +2025-09-14,04:26:59 | INFO | Train Epoch: 10 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.15705 (0.22222) Boundary_loss: 0.013895 (0.013895) Loss: 0.17095 (0.23612) +2025-09-14,04:27:29 | INFO | Train Epoch: 10 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.21396 (0.22213) Boundary_loss: 0.013897 (0.013895) Loss: 0.22785 (0.23603) +2025-09-14,04:28:00 | INFO | Train Epoch: 10 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.22096 (0.22212) Boundary_loss: 0.013896 (0.013895) Loss: 0.23485 (0.23602) +2025-09-14,04:28:31 | INFO | Train Epoch: 10 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.21363 (0.22204) Boundary_loss: 0.013895 (0.013895) Loss: 0.22753 (0.23593) +2025-09-14,04:29:02 | INFO | Train Epoch: 10 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.19323 (0.22175) Boundary_loss: 0.013896 (0.013895) Loss: 0.20712 (0.23564) +2025-09-14,04:29:33 | INFO | Train Epoch: 10 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.22221 (0.22175) Boundary_loss: 0.013896 (0.013895) Loss: 0.23611 (0.23565) +2025-09-14,04:30:04 | INFO | Train Epoch: 10 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.23989 (0.22193) Boundary_loss: 0.013897 (0.013895) Loss: 0.25378 (0.23583) +2025-09-14,04:30:35 | INFO | Train Epoch: 10 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.24526 (0.22216) Boundary_loss: 0.013896 (0.013895) Loss: 0.25916 (0.23605) +2025-09-14,04:31:05 | INFO | Train Epoch: 10 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15520 (0.22151) Boundary_loss: 0.013896 (0.013895) Loss: 0.16909 (0.23541) +2025-09-14,04:31:36 | INFO | Train Epoch: 10 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.22046 (0.22150) Boundary_loss: 0.013895 (0.013895) Loss: 0.23435 (0.23540) +2025-09-14,04:32:07 | INFO | Train Epoch: 10 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19513 (0.22125) Boundary_loss: 0.013896 (0.013895) Loss: 0.20902 (0.23515) +2025-09-14,04:32:38 | INFO | Train Epoch: 10 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24321 (0.22146) Boundary_loss: 0.013896 (0.013895) Loss: 0.25711 (0.23536) +2025-09-14,04:33:09 | INFO | Train Epoch: 10 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.20619 (0.22132) Boundary_loss: 0.013895 (0.013895) Loss: 0.22009 (0.23521) +2025-09-14,04:33:39 | INFO | Train Epoch: 10 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.19203 (0.22105) Boundary_loss: 0.013897 (0.013896) Loss: 0.20592 (0.23495) +2025-09-14,04:34:10 | INFO | Train Epoch: 10 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.21234 (0.22097) Boundary_loss: 0.013896 (0.013896) Loss: 0.22623 (0.23487) +2025-09-14,04:34:41 | INFO | Train Epoch: 10 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.23287 (0.22108) Boundary_loss: 0.013895 (0.013896) Loss: 0.24677 (0.23497) +2025-09-14,04:35:12 | INFO | Train Epoch: 10 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.22357 (0.22110) Boundary_loss: 0.013895 (0.013895) Loss: 0.23747 (0.23500) +2025-09-14,04:35:43 | INFO | Train Epoch: 10 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.24894 (0.22135) Boundary_loss: 0.013895 (0.013895) Loss: 0.26284 (0.23524) +2025-09-14,04:36:14 | INFO | Train Epoch: 10 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24167 (0.22153) Boundary_loss: 0.013895 (0.013895) Loss: 0.25556 (0.23542) +2025-09-14,04:36:45 | INFO | Train Epoch: 10 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.22992 (0.22160) Boundary_loss: 0.013895 (0.013895) Loss: 0.24381 (0.23549) +2025-09-14,04:37:16 | INFO | Train Epoch: 10 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17379 (0.22119) Boundary_loss: 0.013896 (0.013895) Loss: 0.18769 (0.23508) +2025-09-14,04:37:47 | INFO | Train Epoch: 10 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15653 (0.22063) Boundary_loss: 0.013895 (0.013895) Loss: 0.17043 (0.23453) +2025-09-14,04:38:18 | INFO | Train Epoch: 10 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19603 (0.22042) Boundary_loss: 0.013897 (0.013895) Loss: 0.20992 (0.23432) +2025-09-14,04:38:49 | INFO | Train Epoch: 10 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.17244 (0.22002) Boundary_loss: 0.013895 (0.013895) Loss: 0.18633 (0.23392) +2025-09-14,04:39:19 | INFO | Train Epoch: 10 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.19436 (0.21981) Boundary_loss: 0.013895 (0.013895) Loss: 0.20825 (0.23370) +2025-09-14,04:39:50 | INFO | Train Epoch: 10 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.22872 (0.21988) Boundary_loss: 0.013895 (0.013895) Loss: 0.24262 (0.23378) +2025-09-14,04:40:21 | INFO | Train Epoch: 10 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21659 (0.21985) Boundary_loss: 0.013896 (0.013895) Loss: 0.23049 (0.23375) +2025-09-14,04:40:51 | INFO | Train Epoch: 10 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.26567 (0.22023) Boundary_loss: 0.013896 (0.013895) Loss: 0.27957 (0.23412) +2025-09-14,04:41:22 | INFO | Train Epoch: 10 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.29994 (0.22087) Boundary_loss: 0.013895 (0.013895) Loss: 0.31384 (0.23477) +2025-09-14,04:41:53 | INFO | Train Epoch: 10 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.19622 (0.22067) Boundary_loss: 0.013895 (0.013895) Loss: 0.21011 (0.23457) +2025-09-14,04:42:24 | INFO | Train Epoch: 10 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.20300 (0.22053) Boundary_loss: 0.013895 (0.013895) Loss: 0.21689 (0.23443) +2025-09-14,04:42:54 | INFO | Train Epoch: 10 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17961 (0.22021) Boundary_loss: 0.013895 (0.013895) Loss: 0.19351 (0.23411) +2025-09-14,04:43:25 | INFO | Train Epoch: 10 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13612 (0.21955) Boundary_loss: 0.013896 (0.013895) Loss: 0.15002 (0.23345) +2025-09-14,04:43:55 | INFO | Train Epoch: 10 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.27941 (0.22002) Boundary_loss: 0.013895 (0.013895) Loss: 0.29331 (0.23391) +2025-09-14,04:44:26 | INFO | Train Epoch: 10 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.25920 (0.22032) Boundary_loss: 0.013895 (0.013895) Loss: 0.27310 (0.23421) +2025-09-14,04:44:57 | INFO | Train Epoch: 10 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.20140 (0.22017) Boundary_loss: 0.013896 (0.013895) Loss: 0.21530 (0.23407) +2025-09-14,04:45:28 | INFO | Train Epoch: 10 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.21301 (0.22012) Boundary_loss: 0.013896 (0.013895) Loss: 0.22690 (0.23402) +2025-09-14,04:45:58 | INFO | Train Epoch: 10 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19815 (0.21995) Boundary_loss: 0.013895 (0.013895) Loss: 0.21204 (0.23385) +2025-09-14,04:46:29 | INFO | Train Epoch: 10 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.23743 (0.22009) Boundary_loss: 0.013896 (0.013895) Loss: 0.25132 (0.23398) +2025-09-14,04:47:00 | INFO | Train Epoch: 10 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.23236 (0.22018) Boundary_loss: 0.013894 (0.013895) Loss: 0.24625 (0.23407) +2025-09-14,04:47:30 | INFO | Train Epoch: 10 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22683 (0.22022) Boundary_loss: 0.013895 (0.013895) Loss: 0.24073 (0.23412) +2025-09-14,04:48:01 | INFO | Train Epoch: 10 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23068 (0.22030) Boundary_loss: 0.013896 (0.013895) Loss: 0.24457 (0.23420) +2025-09-14,04:48:32 | INFO | Train Epoch: 10 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.19794 (0.22014) Boundary_loss: 0.013895 (0.013895) Loss: 0.21183 (0.23403) +2025-09-14,04:49:03 | INFO | Train Epoch: 10 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.18805 (0.21991) Boundary_loss: 0.013895 (0.013895) Loss: 0.20195 (0.23380) +2025-09-14,04:49:33 | INFO | Train Epoch: 10 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.28829 (0.22040) Boundary_loss: 0.013894 (0.013895) Loss: 0.30219 (0.23429) +2025-09-14,04:50:04 | INFO | Train Epoch: 10 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.23591 (0.22051) Boundary_loss: 0.013895 (0.013895) Loss: 0.24980 (0.23440) +2025-09-14,04:50:35 | INFO | Train Epoch: 10 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19495 (0.22033) Boundary_loss: 0.013895 (0.013895) Loss: 0.20884 (0.23422) +2025-09-14,04:51:06 | INFO | Train Epoch: 10 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.24441 (0.22050) Boundary_loss: 0.013895 (0.013895) Loss: 0.25830 (0.23439) +2025-09-14,04:51:37 | INFO | Train Epoch: 10 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21397 (0.22045) Boundary_loss: 0.013896 (0.013895) Loss: 0.22787 (0.23435) +2025-09-14,04:52:07 | INFO | Train Epoch: 10 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.22322 (0.22047) Boundary_loss: 0.013894 (0.013895) Loss: 0.23712 (0.23436) +2025-09-14,04:52:38 | INFO | Train Epoch: 10 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19996 (0.22033) Boundary_loss: 0.013897 (0.013895) Loss: 0.21386 (0.23422) +2025-09-14,04:53:09 | INFO | Train Epoch: 10 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15472 (0.21988) Boundary_loss: 0.013895 (0.013895) Loss: 0.16861 (0.23378) +2025-09-14,04:53:40 | INFO | Train Epoch: 10 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22097 (0.21989) Boundary_loss: 0.013895 (0.013895) Loss: 0.23487 (0.23379) +2025-09-14,04:54:11 | INFO | Train Epoch: 10 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.21519 (0.21986) Boundary_loss: 0.013896 (0.013895) Loss: 0.22908 (0.23375) +2025-09-14,04:54:42 | INFO | Train Epoch: 10 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.23600 (0.21997) Boundary_loss: 0.013894 (0.013895) Loss: 0.24989 (0.23386) +2025-09-14,04:55:13 | INFO | Train Epoch: 10 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.21573 (0.21994) Boundary_loss: 0.013895 (0.013895) Loss: 0.22962 (0.23383) +2025-09-14,04:55:44 | INFO | Train Epoch: 10 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16807 (0.21960) Boundary_loss: 0.013895 (0.013895) Loss: 0.18197 (0.23349) +2025-09-14,04:56:15 | INFO | Train Epoch: 10 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19028 (0.21940) Boundary_loss: 0.013896 (0.013895) Loss: 0.20418 (0.23330) +2025-09-14,04:56:46 | INFO | Train Epoch: 10 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.28484 (0.21983) Boundary_loss: 0.013895 (0.013895) Loss: 0.29873 (0.23373) +2025-09-14,04:57:16 | INFO | Train Epoch: 10 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.21136 (0.21977) Boundary_loss: 0.013895 (0.013895) Loss: 0.22525 (0.23367) +2025-09-14,04:57:47 | INFO | Train Epoch: 10 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23587 (0.21988) Boundary_loss: 0.013896 (0.013895) Loss: 0.24976 (0.23377) +2025-09-14,04:58:18 | INFO | Train Epoch: 10 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21655 (0.21986) Boundary_loss: 0.013896 (0.013895) Loss: 0.23044 (0.23375) +2025-09-14,04:58:48 | INFO | Train Epoch: 10 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.19716 (0.21971) Boundary_loss: 0.013894 (0.013895) Loss: 0.21105 (0.23361) +2025-09-14,04:59:19 | INFO | Train Epoch: 10 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.21497 (0.21968) Boundary_loss: 0.013895 (0.013895) Loss: 0.22887 (0.23358) +2025-09-14,04:59:50 | INFO | Train Epoch: 10 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.18025 (0.21944) Boundary_loss: 0.013894 (0.013895) Loss: 0.19415 (0.23333) +2025-09-14,05:00:21 | INFO | Train Epoch: 10 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.19373 (0.21928) Boundary_loss: 0.013898 (0.013895) Loss: 0.20763 (0.23317) +2025-09-14,05:00:51 | INFO | Train Epoch: 10 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22478 (0.21931) Boundary_loss: 0.013896 (0.013895) Loss: 0.23867 (0.23321) +2025-09-14,05:01:22 | INFO | Train Epoch: 10 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.23388 (0.21940) Boundary_loss: 0.013894 (0.013895) Loss: 0.24777 (0.23330) +2025-09-14,05:01:53 | INFO | Train Epoch: 10 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.18057 (0.21916) Boundary_loss: 0.013895 (0.013895) Loss: 0.19446 (0.23306) +2025-09-14,05:02:23 | INFO | Train Epoch: 10 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15887 (0.21880) Boundary_loss: 0.013897 (0.013895) Loss: 0.17277 (0.23269) +2025-09-14,05:02:54 | INFO | Train Epoch: 10 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.18557 (0.21860) Boundary_loss: 0.013897 (0.013895) Loss: 0.19947 (0.23249) +2025-09-14,05:03:25 | INFO | Train Epoch: 10 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.20624 (0.21852) Boundary_loss: 0.013895 (0.013895) Loss: 0.22014 (0.23242) +2025-09-14,05:03:55 | INFO | Train Epoch: 10 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.22566 (0.21857) Boundary_loss: 0.013897 (0.013895) Loss: 0.23956 (0.23246) +2025-09-14,05:04:26 | INFO | Train Epoch: 10 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24333 (0.21871) Boundary_loss: 0.013896 (0.013895) Loss: 0.25722 (0.23261) +2025-09-14,05:04:57 | INFO | Train Epoch: 10 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18501 (0.21852) Boundary_loss: 0.013895 (0.013895) Loss: 0.19890 (0.23241) +2025-09-14,05:05:28 | INFO | Train Epoch: 10 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20845 (0.21846) Boundary_loss: 0.013895 (0.013895) Loss: 0.22235 (0.23235) +2025-09-14,05:05:59 | INFO | Train Epoch: 10 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.19647 (0.21833) Boundary_loss: 0.013894 (0.013895) Loss: 0.21037 (0.23222) +2025-09-14,05:06:30 | INFO | Train Epoch: 10 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17199 (0.21806) Boundary_loss: 0.013895 (0.013895) Loss: 0.18589 (0.23196) +2025-09-14,05:07:01 | INFO | Train Epoch: 10 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20214 (0.21797) Boundary_loss: 0.013895 (0.013895) Loss: 0.21604 (0.23186) +2025-09-14,05:07:31 | INFO | Train Epoch: 10 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24063 (0.21810) Boundary_loss: 0.013895 (0.013895) Loss: 0.25453 (0.23199) +2025-09-14,05:08:02 | INFO | Train Epoch: 10 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.20964 (0.21805) Boundary_loss: 0.013896 (0.013895) Loss: 0.22354 (0.23195) +2025-09-14,05:08:33 | INFO | Train Epoch: 10 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.23383 (0.21814) Boundary_loss: 0.013895 (0.013895) Loss: 0.24773 (0.23204) +2025-09-14,05:09:04 | INFO | Train Epoch: 10 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15796 (0.21780) Boundary_loss: 0.013896 (0.013895) Loss: 0.17186 (0.23170) +2025-09-14,05:09:34 | INFO | Train Epoch: 10 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.22749 (0.21786) Boundary_loss: 0.013896 (0.013895) Loss: 0.24139 (0.23175) +2025-09-14,05:10:05 | INFO | Train Epoch: 10 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.20031 (0.21776) Boundary_loss: 0.013895 (0.013895) Loss: 0.21421 (0.23165) +2025-09-14,05:10:36 | INFO | Train Epoch: 10 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.31177 (0.21828) Boundary_loss: 0.013894 (0.013895) Loss: 0.32566 (0.23217) +2025-09-14,05:11:07 | INFO | Train Epoch: 10 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15585 (0.21793) Boundary_loss: 0.013895 (0.013895) Loss: 0.16974 (0.23183) +2025-09-14,05:11:38 | INFO | Train Epoch: 10 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.16194 (0.21763) Boundary_loss: 0.013894 (0.013895) Loss: 0.17583 (0.23152) +2025-09-14,05:12:09 | INFO | Train Epoch: 10 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19903 (0.21753) Boundary_loss: 0.013895 (0.013895) Loss: 0.21292 (0.23142) +2025-09-14,05:12:40 | INFO | Train Epoch: 10 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17583 (0.21730) Boundary_loss: 0.013895 (0.013895) Loss: 0.18973 (0.23120) +2025-09-14,05:13:11 | INFO | Train Epoch: 10 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19690 (0.21719) Boundary_loss: 0.013896 (0.013895) Loss: 0.21079 (0.23109) +2025-09-14,05:13:41 | INFO | Train Epoch: 10 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.26236 (0.21743) Boundary_loss: 0.013895 (0.013895) Loss: 0.27625 (0.23133) +2025-09-14,05:14:12 | INFO | Train Epoch: 10 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.21126 (0.21740) Boundary_loss: 0.013895 (0.013895) Loss: 0.22516 (0.23130) +2025-09-14,05:14:43 | INFO | Train Epoch: 10 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.20171 (0.21732) Boundary_loss: 0.013895 (0.013895) Loss: 0.21561 (0.23121) +2025-09-14,05:15:14 | INFO | Train Epoch: 10 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18764 (0.21716) Boundary_loss: 0.013895 (0.013895) Loss: 0.20153 (0.23106) +2025-09-14,05:15:45 | INFO | Train Epoch: 10 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.22079 (0.21718) Boundary_loss: 0.013896 (0.013895) Loss: 0.23469 (0.23108) +2025-09-14,05:16:16 | INFO | Train Epoch: 10 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16918 (0.21693) Boundary_loss: 0.013896 (0.013895) Loss: 0.18307 (0.23083) +2025-09-14,05:16:46 | INFO | Train Epoch: 10 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.20136 (0.21685) Boundary_loss: 0.013896 (0.013895) Loss: 0.21525 (0.23075) +2025-09-14,05:17:17 | INFO | Train Epoch: 10 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.21631 (0.21685) Boundary_loss: 0.013895 (0.013895) Loss: 0.23021 (0.23074) +2025-09-14,05:17:48 | INFO | Train Epoch: 10 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16335 (0.21657) Boundary_loss: 0.013895 (0.013895) Loss: 0.17724 (0.23047) +2025-09-14,05:18:19 | INFO | Train Epoch: 10 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.24074 (0.21670) Boundary_loss: 0.013897 (0.013895) Loss: 0.25464 (0.23059) +2025-09-14,05:18:50 | INFO | Train Epoch: 10 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23279 (0.21678) Boundary_loss: 0.013896 (0.013895) Loss: 0.24669 (0.23067) +2025-09-14,05:19:21 | INFO | Train Epoch: 10 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.24654 (0.21693) Boundary_loss: 0.013895 (0.013895) Loss: 0.26044 (0.23082) +2025-09-14,05:19:51 | INFO | Train Epoch: 10 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.21039 (0.21690) Boundary_loss: 0.013897 (0.013895) Loss: 0.22429 (0.23079) +2025-09-14,05:20:22 | INFO | Train Epoch: 10 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.24139 (0.21702) Boundary_loss: 0.013896 (0.013895) Loss: 0.25529 (0.23091) +2025-09-14,05:20:53 | INFO | Train Epoch: 10 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19003 (0.21688) Boundary_loss: 0.013895 (0.013895) Loss: 0.20393 (0.23078) +2025-09-14,05:21:24 | INFO | Train Epoch: 10 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.21783 (0.21689) Boundary_loss: 0.013895 (0.013895) Loss: 0.23172 (0.23078) +2025-09-14,05:21:55 | INFO | Train Epoch: 10 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.21339 (0.21687) Boundary_loss: 0.013895 (0.013895) Loss: 0.22729 (0.23077) +2025-09-14,05:22:25 | INFO | Train Epoch: 10 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19934 (0.21679) Boundary_loss: 0.013896 (0.013895) Loss: 0.21324 (0.23068) +2025-09-14,05:22:56 | INFO | Train Epoch: 10 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.17528 (0.21658) Boundary_loss: 0.013896 (0.013895) Loss: 0.18917 (0.23048) +2025-09-14,05:23:27 | INFO | Train Epoch: 10 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.15680 (0.21629) Boundary_loss: 0.013898 (0.013895) Loss: 0.17069 (0.23019) +2025-09-14,05:23:58 | INFO | Train Epoch: 10 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.18825 (0.21616) Boundary_loss: 0.013894 (0.013895) Loss: 0.20214 (0.23005) +2025-09-14,05:24:29 | INFO | Train Epoch: 10 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.21293 (0.21614) Boundary_loss: 0.013897 (0.013895) Loss: 0.22682 (0.23004) +2025-09-14,05:24:59 | INFO | Train Epoch: 10 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.22000 (0.21616) Boundary_loss: 0.013895 (0.013895) Loss: 0.23389 (0.23006) +2025-09-14,05:25:30 | INFO | Train Epoch: 10 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.18034 (0.21599) Boundary_loss: 0.013895 (0.013895) Loss: 0.19423 (0.22988) +2025-09-14,05:26:01 | INFO | Train Epoch: 10 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20152 (0.21592) Boundary_loss: 0.013895 (0.013895) Loss: 0.21542 (0.22982) +2025-09-14,05:26:32 | INFO | Train Epoch: 10 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.23411 (0.21601) Boundary_loss: 0.013896 (0.013895) Loss: 0.24801 (0.22990) +2025-09-14,05:27:03 | INFO | Train Epoch: 10 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19351 (0.21590) Boundary_loss: 0.013897 (0.013895) Loss: 0.20741 (0.22980) +2025-09-14,05:27:33 | INFO | Train Epoch: 10 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.15251 (0.21560) Boundary_loss: 0.013895 (0.013895) Loss: 0.16640 (0.22950) +2025-09-14,05:28:04 | INFO | Train Epoch: 10 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.22010 (0.21563) Boundary_loss: 0.013897 (0.013895) Loss: 0.23400 (0.22952) +2025-09-14,05:28:35 | INFO | Train Epoch: 10 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.23048 (0.21569) Boundary_loss: 0.013895 (0.013895) Loss: 0.24438 (0.22959) +2025-09-14,05:29:06 | INFO | Train Epoch: 10 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17630 (0.21551) Boundary_loss: 0.013897 (0.013895) Loss: 0.19019 (0.22941) +2025-09-14,05:29:37 | INFO | Train Epoch: 10 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17076 (0.21531) Boundary_loss: 0.013895 (0.013895) Loss: 0.18466 (0.22920) +2025-09-14,05:30:08 | INFO | Train Epoch: 10 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.27245 (0.21557) Boundary_loss: 0.013894 (0.013895) Loss: 0.28634 (0.22946) +2025-09-14,05:30:39 | INFO | Train Epoch: 10 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.18856 (0.21545) Boundary_loss: 0.013894 (0.013895) Loss: 0.20245 (0.22934) +2025-09-14,05:31:10 | INFO | Train Epoch: 10 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22027 (0.21547) Boundary_loss: 0.013895 (0.013895) Loss: 0.23417 (0.22936) +2025-09-14,05:31:41 | INFO | Train Epoch: 10 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.30547 (0.21587) Boundary_loss: 0.013895 (0.013895) Loss: 0.31937 (0.22977) +2025-09-14,05:32:11 | INFO | Train Epoch: 10 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.23453 (0.21596) Boundary_loss: 0.013895 (0.013895) Loss: 0.24843 (0.22985) +2025-09-14,05:32:42 | INFO | Train Epoch: 10 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14589 (0.21564) Boundary_loss: 0.013895 (0.013895) Loss: 0.15978 (0.22954) +2025-09-14,05:33:13 | INFO | Train Epoch: 10 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.19369 (0.21555) Boundary_loss: 0.013895 (0.013895) Loss: 0.20759 (0.22944) +2025-09-14,05:33:44 | INFO | Train Epoch: 10 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19377 (0.21545) Boundary_loss: 0.013897 (0.013895) Loss: 0.20766 (0.22935) +2025-09-14,05:34:15 | INFO | Train Epoch: 10 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17608 (0.21528) Boundary_loss: 0.013895 (0.013895) Loss: 0.18998 (0.22917) +2025-09-14,05:34:46 | INFO | Train Epoch: 10 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.26467 (0.21549) Boundary_loss: 0.013894 (0.013895) Loss: 0.27857 (0.22939) +2025-09-14,05:35:17 | INFO | Train Epoch: 10 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14851 (0.21520) Boundary_loss: 0.013896 (0.013895) Loss: 0.16241 (0.22910) +2025-09-14,05:35:48 | INFO | Train Epoch: 10 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25250 (0.21536) Boundary_loss: 0.013895 (0.013895) Loss: 0.26639 (0.22926) +2025-09-14,05:36:18 | INFO | Train Epoch: 10 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16506 (0.21515) Boundary_loss: 0.013896 (0.013895) Loss: 0.17896 (0.22904) +2025-09-14,05:36:49 | INFO | Train Epoch: 10 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.24135 (0.21526) Boundary_loss: 0.013897 (0.013895) Loss: 0.25524 (0.22915) +2025-09-14,05:37:20 | INFO | Train Epoch: 10 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24987 (0.21541) Boundary_loss: 0.013894 (0.013895) Loss: 0.26376 (0.22930) +2025-09-14,05:37:51 | INFO | Train Epoch: 10 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.18625 (0.21528) Boundary_loss: 0.013896 (0.013895) Loss: 0.20015 (0.22918) +2025-09-14,05:38:22 | INFO | Train Epoch: 10 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21816 (0.21529) Boundary_loss: 0.013895 (0.013895) Loss: 0.23206 (0.22919) +2025-09-14,05:38:53 | INFO | Train Epoch: 10 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.20819 (0.21526) Boundary_loss: 0.013895 (0.013895) Loss: 0.22208 (0.22916) +2025-09-14,05:39:24 | INFO | Train Epoch: 10 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24346 (0.21538) Boundary_loss: 0.013895 (0.013895) Loss: 0.25736 (0.22928) +2025-09-14,05:39:55 | INFO | Train Epoch: 10 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.23895 (0.21548) Boundary_loss: 0.013895 (0.013895) Loss: 0.25284 (0.22938) +2025-09-14,05:40:25 | INFO | Train Epoch: 10 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.21669 (0.21549) Boundary_loss: 0.013894 (0.013895) Loss: 0.23059 (0.22938) +2025-09-14,05:40:56 | INFO | Train Epoch: 10 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.18505 (0.21536) Boundary_loss: 0.013896 (0.013895) Loss: 0.19895 (0.22926) +2025-09-14,05:41:26 | INFO | Train Epoch: 10 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.24241 (0.21547) Boundary_loss: 0.013896 (0.013895) Loss: 0.25631 (0.22937) +2025-09-14,05:41:57 | INFO | Train Epoch: 10 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.18446 (0.21534) Boundary_loss: 0.013895 (0.013895) Loss: 0.19835 (0.22924) +2025-09-14,05:42:28 | INFO | Train Epoch: 10 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16690 (0.21515) Boundary_loss: 0.013895 (0.013895) Loss: 0.18079 (0.22904) +2025-09-14,05:42:59 | INFO | Train Epoch: 10 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.16538 (0.21494) Boundary_loss: 0.013895 (0.013895) Loss: 0.17927 (0.22884) +2025-09-14,05:43:30 | INFO | Train Epoch: 10 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.23497 (0.21502) Boundary_loss: 0.013896 (0.013895) Loss: 0.24886 (0.22892) +2025-09-14,05:44:01 | INFO | Train Epoch: 10 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20095 (0.21497) Boundary_loss: 0.013896 (0.013895) Loss: 0.21485 (0.22886) +2025-09-14,05:44:31 | INFO | Train Epoch: 10 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22701 (0.21501) Boundary_loss: 0.013896 (0.013895) Loss: 0.24091 (0.22891) +2025-09-14,05:45:02 | INFO | Train Epoch: 10 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.18003 (0.21487) Boundary_loss: 0.013895 (0.013895) Loss: 0.19393 (0.22877) +2025-09-14,05:45:33 | INFO | Train Epoch: 10 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.24775 (0.21501) Boundary_loss: 0.013894 (0.013895) Loss: 0.26165 (0.22890) +2025-09-14,05:46:04 | INFO | Train Epoch: 10 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.22624 (0.21505) Boundary_loss: 0.013896 (0.013895) Loss: 0.24014 (0.22895) +2025-09-14,05:46:35 | INFO | Train Epoch: 10 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19766 (0.21498) Boundary_loss: 0.013895 (0.013895) Loss: 0.21155 (0.22888) +2025-09-14,05:47:05 | INFO | Train Epoch: 10 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.16489 (0.21478) Boundary_loss: 0.013895 (0.013895) Loss: 0.17879 (0.22868) +2025-09-14,05:47:36 | INFO | Train Epoch: 10 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.21654 (0.21479) Boundary_loss: 0.013895 (0.013895) Loss: 0.23044 (0.22868) +2025-09-14,05:48:07 | INFO | Train Epoch: 10 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18901 (0.21469) Boundary_loss: 0.013896 (0.013895) Loss: 0.20291 (0.22858) +2025-09-14,05:48:38 | INFO | Train Epoch: 10 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.18842 (0.21458) Boundary_loss: 0.013896 (0.013895) Loss: 0.20232 (0.22848) +2025-09-14,05:49:09 | INFO | Train Epoch: 10 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.19097 (0.21449) Boundary_loss: 0.013895 (0.013895) Loss: 0.20487 (0.22839) +2025-09-14,05:49:40 | INFO | Train Epoch: 10 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.19551 (0.21442) Boundary_loss: 0.013895 (0.013895) Loss: 0.20941 (0.22831) +2025-09-14,05:50:10 | INFO | Train Epoch: 10 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.24044 (0.21452) Boundary_loss: 0.013894 (0.013895) Loss: 0.25433 (0.22842) +2025-09-14,05:50:41 | INFO | Train Epoch: 10 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.18537 (0.21441) Boundary_loss: 0.013897 (0.013895) Loss: 0.19927 (0.22830) +2025-09-14,05:51:12 | INFO | Train Epoch: 10 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22577 (0.21445) Boundary_loss: 0.013897 (0.013895) Loss: 0.23967 (0.22835) +2025-09-14,05:51:42 | INFO | Train Epoch: 10 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.22191 (0.21448) Boundary_loss: 0.013895 (0.013895) Loss: 0.23580 (0.22837) +2025-09-14,05:52:13 | INFO | Train Epoch: 10 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19070 (0.21439) Boundary_loss: 0.013896 (0.013895) Loss: 0.20459 (0.22828) +2025-09-14,05:52:45 | INFO | Train Epoch: 10 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.22368 (0.21442) Boundary_loss: 0.013895 (0.013895) Loss: 0.23758 (0.22832) +2025-09-14,05:53:16 | INFO | Train Epoch: 10 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.22094 (0.21445) Boundary_loss: 0.013896 (0.013895) Loss: 0.23484 (0.22834) +2025-09-14,05:53:47 | INFO | Train Epoch: 10 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20607 (0.21442) Boundary_loss: 0.013895 (0.013895) Loss: 0.21997 (0.22831) +2025-09-14,05:54:18 | INFO | Train Epoch: 10 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.24754 (0.21454) Boundary_loss: 0.013895 (0.013895) Loss: 0.26144 (0.22844) +2025-09-14,05:54:49 | INFO | Train Epoch: 10 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.25439 (0.21469) Boundary_loss: 0.013895 (0.013895) Loss: 0.26828 (0.22859) +2025-09-14,05:55:19 | INFO | Train Epoch: 10 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19970 (0.21463) Boundary_loss: 0.013896 (0.013895) Loss: 0.21359 (0.22853) +2025-09-14,05:55:50 | INFO | Train Epoch: 10 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22650 (0.21468) Boundary_loss: 0.013895 (0.013895) Loss: 0.24040 (0.22857) +2025-09-14,05:56:21 | INFO | Train Epoch: 10 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13044 (0.21437) Boundary_loss: 0.013896 (0.013895) Loss: 0.14434 (0.22826) +2025-09-14,05:56:52 | INFO | Train Epoch: 10 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21786 (0.21438) Boundary_loss: 0.013896 (0.013895) Loss: 0.23176 (0.22828) +2025-09-14,05:57:23 | INFO | Train Epoch: 10 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.26082 (0.21455) Boundary_loss: 0.013895 (0.013895) Loss: 0.27471 (0.22845) +2025-09-14,05:57:53 | INFO | Train Epoch: 10 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.23492 (0.21463) Boundary_loss: 0.013896 (0.013895) Loss: 0.24881 (0.22852) +2025-09-14,05:58:24 | INFO | Train Epoch: 10 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.18450 (0.21452) Boundary_loss: 0.013896 (0.013895) Loss: 0.19840 (0.22841) +2025-09-14,05:58:55 | INFO | Train Epoch: 10 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20331 (0.21447) Boundary_loss: 0.013894 (0.013895) Loss: 0.21720 (0.22837) +2025-09-14,05:59:26 | INFO | Train Epoch: 10 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18066 (0.21435) Boundary_loss: 0.013896 (0.013895) Loss: 0.19455 (0.22825) +2025-09-14,05:59:56 | INFO | Train Epoch: 10 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19120 (0.21427) Boundary_loss: 0.013895 (0.013895) Loss: 0.20509 (0.22816) +2025-09-14,06:00:27 | INFO | Train Epoch: 10 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20966 (0.21425) Boundary_loss: 0.013895 (0.013895) Loss: 0.22356 (0.22815) +2025-09-14,06:00:58 | INFO | Train Epoch: 10 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22626 (0.21429) Boundary_loss: 0.013895 (0.013895) Loss: 0.24016 (0.22819) +2025-09-14,06:01:29 | INFO | Train Epoch: 10 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22578 (0.21434) Boundary_loss: 0.013897 (0.013895) Loss: 0.23968 (0.22823) +2025-09-14,06:02:00 | INFO | Train Epoch: 10 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.19141 (0.21425) Boundary_loss: 0.013895 (0.013895) Loss: 0.20531 (0.22815) +2025-09-14,06:02:31 | INFO | Train Epoch: 10 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.23240 (0.21432) Boundary_loss: 0.013896 (0.013895) Loss: 0.24630 (0.22821) +2025-09-14,06:03:01 | INFO | Train Epoch: 10 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24761 (0.21444) Boundary_loss: 0.013894 (0.013895) Loss: 0.26150 (0.22833) +2025-09-14,06:03:32 | INFO | Train Epoch: 10 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.19433 (0.21437) Boundary_loss: 0.013895 (0.013895) Loss: 0.20823 (0.22826) +2025-09-14,06:04:03 | INFO | Train Epoch: 10 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20860 (0.21435) Boundary_loss: 0.013895 (0.013895) Loss: 0.22250 (0.22824) +2025-09-14,06:04:34 | INFO | Train Epoch: 10 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.18525 (0.21424) Boundary_loss: 0.013895 (0.013895) Loss: 0.19915 (0.22814) +2025-09-14,06:05:05 | INFO | Train Epoch: 10 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.23399 (0.21431) Boundary_loss: 0.013895 (0.013895) Loss: 0.24788 (0.22821) +2025-09-14,06:05:36 | INFO | Train Epoch: 10 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.20029 (0.21426) Boundary_loss: 0.013896 (0.013895) Loss: 0.21419 (0.22816) +2025-09-14,06:06:07 | INFO | Train Epoch: 10 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18246 (0.21415) Boundary_loss: 0.013895 (0.013895) Loss: 0.19635 (0.22805) +2025-09-14,06:06:37 | INFO | Train Epoch: 10 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19107 (0.21407) Boundary_loss: 0.013896 (0.013895) Loss: 0.20496 (0.22797) +2025-09-14,06:07:08 | INFO | Train Epoch: 10 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19051 (0.21399) Boundary_loss: 0.013896 (0.013895) Loss: 0.20440 (0.22789) +2025-09-14,06:07:39 | INFO | Train Epoch: 10 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.20903 (0.21398) Boundary_loss: 0.013896 (0.013895) Loss: 0.22293 (0.22787) +2025-09-14,06:08:10 | INFO | Train Epoch: 10 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26675 (0.21416) Boundary_loss: 0.013895 (0.013895) Loss: 0.28065 (0.22805) +2025-09-14,06:08:41 | INFO | Train Epoch: 10 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.20042 (0.21411) Boundary_loss: 0.013894 (0.013895) Loss: 0.21432 (0.22800) +2025-09-14,06:09:12 | INFO | Train Epoch: 10 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16052 (0.21393) Boundary_loss: 0.013895 (0.013895) Loss: 0.17442 (0.22782) +2025-09-14,06:09:43 | INFO | Train Epoch: 10 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18538 (0.21383) Boundary_loss: 0.013897 (0.013895) Loss: 0.19928 (0.22773) +2025-09-14,06:10:13 | INFO | Train Epoch: 10 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.29867 (0.21412) Boundary_loss: 0.013897 (0.013895) Loss: 0.31256 (0.22801) +2025-09-14,06:10:44 | INFO | Train Epoch: 10 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.21346 (0.21411) Boundary_loss: 0.013895 (0.013895) Loss: 0.22735 (0.22801) +2025-09-14,06:11:15 | INFO | Train Epoch: 10 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.26567 (0.21429) Boundary_loss: 0.013895 (0.013895) Loss: 0.27957 (0.22818) +2025-09-14,06:11:46 | INFO | Train Epoch: 10 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20658 (0.21426) Boundary_loss: 0.013895 (0.013895) Loss: 0.22048 (0.22816) +2025-09-14,06:12:17 | INFO | Train Epoch: 10 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.20502 (0.21423) Boundary_loss: 0.013894 (0.013895) Loss: 0.21891 (0.22813) +2025-09-14,06:12:48 | INFO | Train Epoch: 10 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.18283 (0.21413) Boundary_loss: 0.013896 (0.013895) Loss: 0.19673 (0.22802) +2025-09-14,06:13:18 | INFO | Train Epoch: 10 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18022 (0.21401) Boundary_loss: 0.013895 (0.013895) Loss: 0.19411 (0.22791) +2025-09-14,06:13:49 | INFO | Train Epoch: 10 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19657 (0.21396) Boundary_loss: 0.013895 (0.013895) Loss: 0.21047 (0.22785) +2025-09-14,06:14:20 | INFO | Train Epoch: 10 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.22219 (0.21398) Boundary_loss: 0.013894 (0.013895) Loss: 0.23608 (0.22788) +2025-09-14,06:14:51 | INFO | Train Epoch: 10 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20145 (0.21394) Boundary_loss: 0.013895 (0.013895) Loss: 0.21535 (0.22784) +2025-09-14,06:15:22 | INFO | Train Epoch: 10 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.18839 (0.21386) Boundary_loss: 0.013896 (0.013895) Loss: 0.20229 (0.22776) +2025-09-14,06:15:52 | INFO | Train Epoch: 10 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.26756 (0.21403) Boundary_loss: 0.013897 (0.013895) Loss: 0.28146 (0.22793) +2025-09-14,06:16:23 | INFO | Train Epoch: 10 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16247 (0.21387) Boundary_loss: 0.013896 (0.013895) Loss: 0.17637 (0.22776) +2025-09-14,06:16:54 | INFO | Train Epoch: 10 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22249 (0.21390) Boundary_loss: 0.013896 (0.013895) Loss: 0.23639 (0.22779) +2025-09-14,06:17:25 | INFO | Train Epoch: 10 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19003 (0.21382) Boundary_loss: 0.013896 (0.013895) Loss: 0.20392 (0.22771) +2025-09-14,06:17:56 | INFO | Train Epoch: 10 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.21109 (0.21381) Boundary_loss: 0.013895 (0.013895) Loss: 0.22498 (0.22771) +2025-09-14,06:18:27 | INFO | Train Epoch: 10 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.16748 (0.21366) Boundary_loss: 0.013895 (0.013895) Loss: 0.18138 (0.22756) +2025-09-14,06:18:57 | INFO | Train Epoch: 10 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21068 (0.21365) Boundary_loss: 0.013896 (0.013895) Loss: 0.22458 (0.22755) +2025-09-14,06:19:28 | INFO | Train Epoch: 10 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.19214 (0.21358) Boundary_loss: 0.013895 (0.013895) Loss: 0.20603 (0.22748) +2025-09-14,06:19:59 | INFO | Train Epoch: 10 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.23616 (0.21366) Boundary_loss: 0.013896 (0.013895) Loss: 0.25006 (0.22755) +2025-09-14,06:20:30 | INFO | Train Epoch: 10 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.22045 (0.21368) Boundary_loss: 0.013895 (0.013895) Loss: 0.23434 (0.22757) +2025-09-14,06:21:01 | INFO | Train Epoch: 10 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.23690 (0.21375) Boundary_loss: 0.013895 (0.013895) Loss: 0.25079 (0.22765) +2025-09-14,06:21:31 | INFO | Train Epoch: 10 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.25255 (0.21387) Boundary_loss: 0.013894 (0.013895) Loss: 0.26645 (0.22777) +2025-09-14,06:22:02 | INFO | Train Epoch: 10 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14995 (0.21367) Boundary_loss: 0.013895 (0.013895) Loss: 0.16384 (0.22757) +2025-09-14,06:22:33 | INFO | Train Epoch: 10 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.19840 (0.21362) Boundary_loss: 0.013895 (0.013895) Loss: 0.21230 (0.22752) +2025-09-14,06:23:03 | INFO | Train Epoch: 10 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.20392 (0.21359) Boundary_loss: 0.013896 (0.013895) Loss: 0.21782 (0.22749) +2025-09-14,06:23:34 | INFO | Train Epoch: 10 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17925 (0.21349) Boundary_loss: 0.013897 (0.013895) Loss: 0.19315 (0.22738) +2025-09-14,06:24:05 | INFO | Train Epoch: 10 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.18256 (0.21339) Boundary_loss: 0.013895 (0.013895) Loss: 0.19645 (0.22729) +2025-09-14,06:24:35 | INFO | Train Epoch: 10 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13934 (0.21316) Boundary_loss: 0.013895 (0.013895) Loss: 0.15324 (0.22706) +2025-09-14,06:25:06 | INFO | Train Epoch: 10 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.19667 (0.21311) Boundary_loss: 0.013895 (0.013895) Loss: 0.21057 (0.22701) +2025-09-14,06:25:37 | INFO | Train Epoch: 10 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20774 (0.21310) Boundary_loss: 0.013895 (0.013895) Loss: 0.22163 (0.22699) +2025-09-14,06:26:07 | INFO | Train Epoch: 10 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.25402 (0.21322) Boundary_loss: 0.013895 (0.013895) Loss: 0.26791 (0.22712) +2025-09-14,06:26:38 | INFO | Train Epoch: 10 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18613 (0.21314) Boundary_loss: 0.013895 (0.013895) Loss: 0.20003 (0.22704) +2025-09-14,06:27:09 | INFO | Train Epoch: 10 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.20439 (0.21311) Boundary_loss: 0.013895 (0.013895) Loss: 0.21828 (0.22701) +2025-09-14,06:27:39 | INFO | Train Epoch: 10 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16617 (0.21297) Boundary_loss: 0.013896 (0.013895) Loss: 0.18006 (0.22687) +2025-09-14,06:28:10 | INFO | Train Epoch: 10 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16585 (0.21283) Boundary_loss: 0.013897 (0.013895) Loss: 0.17975 (0.22673) +2025-09-14,06:28:41 | INFO | Train Epoch: 10 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.23974 (0.21291) Boundary_loss: 0.013896 (0.013895) Loss: 0.25364 (0.22681) +2025-09-14,06:29:12 | INFO | Train Epoch: 10 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.18349 (0.21282) Boundary_loss: 0.013894 (0.013895) Loss: 0.19739 (0.22672) +2025-09-14,06:29:43 | INFO | Train Epoch: 10 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.18460 (0.21274) Boundary_loss: 0.013895 (0.013895) Loss: 0.19849 (0.22663) +2025-09-14,06:30:13 | INFO | Train Epoch: 10 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16690 (0.21260) Boundary_loss: 0.013895 (0.013895) Loss: 0.18079 (0.22650) +2025-09-14,06:30:44 | INFO | Train Epoch: 10 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.25585 (0.21273) Boundary_loss: 0.013894 (0.013895) Loss: 0.26974 (0.22663) +2025-09-14,06:31:15 | INFO | Train Epoch: 10 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21322 (0.21273) Boundary_loss: 0.013896 (0.013895) Loss: 0.22712 (0.22663) +2025-09-14,06:31:46 | INFO | Train Epoch: 10 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22513 (0.21277) Boundary_loss: 0.013895 (0.013895) Loss: 0.23902 (0.22666) +2025-09-14,06:32:17 | INFO | Train Epoch: 10 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.18676 (0.21269) Boundary_loss: 0.013896 (0.013895) Loss: 0.20065 (0.22659) +2025-09-14,06:32:47 | INFO | Train Epoch: 10 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16491 (0.21255) Boundary_loss: 0.013895 (0.013895) Loss: 0.17881 (0.22645) +2025-09-14,06:33:18 | INFO | Train Epoch: 10 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.25598 (0.21268) Boundary_loss: 0.013896 (0.013895) Loss: 0.26988 (0.22657) +2025-09-14,06:33:49 | INFO | Train Epoch: 10 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.24333 (0.21277) Boundary_loss: 0.013896 (0.013895) Loss: 0.25723 (0.22666) +2025-09-14,06:34:20 | INFO | Train Epoch: 10 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.24015 (0.21285) Boundary_loss: 0.013894 (0.013895) Loss: 0.25405 (0.22674) +2025-09-14,06:34:51 | INFO | Train Epoch: 10 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19375 (0.21279) Boundary_loss: 0.013897 (0.013895) Loss: 0.20765 (0.22669) +2025-09-14,06:35:22 | INFO | Train Epoch: 10 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22912 (0.21284) Boundary_loss: 0.013895 (0.013895) Loss: 0.24302 (0.22673) +2025-09-14,06:35:52 | INFO | Train Epoch: 10 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.25344 (0.21296) Boundary_loss: 0.013896 (0.013895) Loss: 0.26734 (0.22685) +2025-09-14,06:36:23 | INFO | Train Epoch: 10 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.28336 (0.21316) Boundary_loss: 0.013896 (0.013895) Loss: 0.29726 (0.22705) +2025-09-14,06:36:54 | INFO | Train Epoch: 10 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.21668 (0.21317) Boundary_loss: 0.013895 (0.013895) Loss: 0.23058 (0.22706) +2025-09-14,06:37:25 | INFO | Train Epoch: 10 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.19070 (0.21310) Boundary_loss: 0.013894 (0.013895) Loss: 0.20459 (0.22700) +2025-09-14,06:37:56 | INFO | Train Epoch: 10 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21841 (0.21312) Boundary_loss: 0.013896 (0.013895) Loss: 0.23231 (0.22702) +2025-09-14,06:38:27 | INFO | Train Epoch: 10 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.23294 (0.21318) Boundary_loss: 0.013895 (0.013895) Loss: 0.24683 (0.22707) +2025-09-14,06:38:57 | INFO | Train Epoch: 10 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.18771 (0.21310) Boundary_loss: 0.013894 (0.013895) Loss: 0.20160 (0.22700) +2025-09-14,06:39:28 | INFO | Train Epoch: 10 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17618 (0.21300) Boundary_loss: 0.013895 (0.013895) Loss: 0.19008 (0.22690) +2025-09-14,06:39:59 | INFO | Train Epoch: 10 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.21624 (0.21301) Boundary_loss: 0.013895 (0.013895) Loss: 0.23014 (0.22690) +2025-09-14,06:40:30 | INFO | Train Epoch: 10 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20872 (0.21300) Boundary_loss: 0.013896 (0.013895) Loss: 0.22262 (0.22689) +2025-09-14,06:41:01 | INFO | Train Epoch: 10 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.21473 (0.21300) Boundary_loss: 0.013894 (0.013895) Loss: 0.22862 (0.22690) +2025-09-14,06:41:31 | INFO | Train Epoch: 10 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16932 (0.21288) Boundary_loss: 0.013895 (0.013895) Loss: 0.18322 (0.22677) +2025-09-14,06:42:02 | INFO | Train Epoch: 10 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.27650 (0.21306) Boundary_loss: 0.013895 (0.013895) Loss: 0.29039 (0.22695) +2025-09-14,06:42:33 | INFO | Train Epoch: 10 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17865 (0.21296) Boundary_loss: 0.013897 (0.013895) Loss: 0.19255 (0.22686) +2025-09-14,06:43:04 | INFO | Train Epoch: 10 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.17137 (0.21285) Boundary_loss: 0.013895 (0.013895) Loss: 0.18526 (0.22674) +2025-09-14,06:43:35 | INFO | Train Epoch: 10 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.18733 (0.21278) Boundary_loss: 0.013896 (0.013895) Loss: 0.20123 (0.22667) +2025-09-14,06:44:06 | INFO | Train Epoch: 10 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.18223 (0.21269) Boundary_loss: 0.013896 (0.013895) Loss: 0.19612 (0.22659) +2025-09-14,06:44:36 | INFO | Train Epoch: 10 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.19516 (0.21264) Boundary_loss: 0.013895 (0.013895) Loss: 0.20906 (0.22654) +2025-09-14,06:45:07 | INFO | Train Epoch: 10 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.24955 (0.21274) Boundary_loss: 0.013894 (0.013895) Loss: 0.26345 (0.22664) +2025-09-14,06:45:38 | INFO | Train Epoch: 10 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21942 (0.21276) Boundary_loss: 0.013896 (0.013895) Loss: 0.23331 (0.22666) +2025-09-14,06:46:09 | INFO | Train Epoch: 10 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.23601 (0.21283) Boundary_loss: 0.013896 (0.013895) Loss: 0.24990 (0.22672) +2025-09-14,06:46:40 | INFO | Train Epoch: 10 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.19758 (0.21278) Boundary_loss: 0.013897 (0.013895) Loss: 0.21148 (0.22668) +2025-09-14,06:47:10 | INFO | Train Epoch: 10 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.21765 (0.21280) Boundary_loss: 0.013894 (0.013895) Loss: 0.23155 (0.22669) +2025-09-14,06:47:41 | INFO | Train Epoch: 10 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.21908 (0.21281) Boundary_loss: 0.013897 (0.013895) Loss: 0.23298 (0.22671) +2025-09-14,06:48:12 | INFO | Train Epoch: 10 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.20516 (0.21279) Boundary_loss: 0.013895 (0.013895) Loss: 0.21905 (0.22669) +2025-09-14,06:48:43 | INFO | Train Epoch: 10 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20035 (0.21276) Boundary_loss: 0.013895 (0.013895) Loss: 0.21424 (0.22666) +2025-09-14,06:49:14 | INFO | Train Epoch: 10 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.21116 (0.21276) Boundary_loss: 0.013896 (0.013895) Loss: 0.22506 (0.22665) +2025-09-14,06:49:44 | INFO | Train Epoch: 10 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17613 (0.21266) Boundary_loss: 0.013895 (0.013895) Loss: 0.19003 (0.22655) +2025-09-14,06:50:15 | INFO | Train Epoch: 10 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22743 (0.21270) Boundary_loss: 0.013896 (0.013895) Loss: 0.24132 (0.22659) +2025-09-14,06:50:46 | INFO | Train Epoch: 10 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.19693 (0.21266) Boundary_loss: 0.013894 (0.013895) Loss: 0.21083 (0.22655) +2025-09-14,06:51:17 | INFO | Train Epoch: 10 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.19280 (0.21260) Boundary_loss: 0.013896 (0.013895) Loss: 0.20669 (0.22650) +2025-09-14,06:51:48 | INFO | Train Epoch: 10 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.23526 (0.21266) Boundary_loss: 0.013895 (0.013895) Loss: 0.24916 (0.22656) +2025-09-14,06:52:19 | INFO | Train Epoch: 10 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17531 (0.21256) Boundary_loss: 0.013895 (0.013895) Loss: 0.18920 (0.22646) +2025-09-14,06:52:49 | INFO | Train Epoch: 10 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.21871 (0.21258) Boundary_loss: 0.013896 (0.013895) Loss: 0.23261 (0.22648) +2025-09-14,06:53:20 | INFO | Train Epoch: 10 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16722 (0.21246) Boundary_loss: 0.013894 (0.013895) Loss: 0.18111 (0.22636) +2025-09-14,06:53:51 | INFO | Train Epoch: 10 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.26375 (0.21260) Boundary_loss: 0.013895 (0.013895) Loss: 0.27765 (0.22649) +2025-09-14,06:54:22 | INFO | Train Epoch: 10 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19164 (0.21254) Boundary_loss: 0.013895 (0.013895) Loss: 0.20553 (0.22644) +2025-09-14,06:54:53 | INFO | Train Epoch: 10 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.19553 (0.21250) Boundary_loss: 0.013895 (0.013895) Loss: 0.20942 (0.22639) +2025-09-14,06:55:24 | INFO | Train Epoch: 10 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20115 (0.21247) Boundary_loss: 0.013896 (0.013895) Loss: 0.21505 (0.22636) +2025-09-14,06:55:54 | INFO | Train Epoch: 10 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.24187 (0.21254) Boundary_loss: 0.013896 (0.013895) Loss: 0.25577 (0.22644) +2025-09-14,06:56:25 | INFO | Train Epoch: 10 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20151 (0.21252) Boundary_loss: 0.013895 (0.013895) Loss: 0.21540 (0.22641) +2025-09-14,06:56:56 | INFO | Train Epoch: 10 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.20420 (0.21249) Boundary_loss: 0.013895 (0.013895) Loss: 0.21809 (0.22639) +2025-09-14,06:57:27 | INFO | Train Epoch: 10 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.23726 (0.21256) Boundary_loss: 0.013894 (0.013895) Loss: 0.25115 (0.22645) +2025-09-14,06:57:58 | INFO | Train Epoch: 10 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20843 (0.21255) Boundary_loss: 0.013895 (0.013895) Loss: 0.22233 (0.22644) +2025-09-14,06:58:28 | INFO | Train Epoch: 10 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20295 (0.21252) Boundary_loss: 0.013895 (0.013895) Loss: 0.21685 (0.22642) +2025-09-14,06:58:59 | INFO | Train Epoch: 10 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.20365 (0.21250) Boundary_loss: 0.013894 (0.013895) Loss: 0.21755 (0.22639) +2025-09-14,06:59:30 | INFO | Train Epoch: 10 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.16137 (0.21237) Boundary_loss: 0.013895 (0.013895) Loss: 0.17526 (0.22626) +2025-09-14,07:00:01 | INFO | Train Epoch: 10 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.22768 (0.21241) Boundary_loss: 0.013896 (0.013895) Loss: 0.24157 (0.22630) +2025-09-14,07:00:31 | INFO | Train Epoch: 10 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.17029 (0.21230) Boundary_loss: 0.013896 (0.013895) Loss: 0.18418 (0.22620) +2025-09-14,07:01:02 | INFO | Train Epoch: 10 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.19268 (0.21225) Boundary_loss: 0.013895 (0.013895) Loss: 0.20658 (0.22615) +2025-09-14,07:01:33 | INFO | Train Epoch: 10 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.23770 (0.21232) Boundary_loss: 0.013894 (0.013895) Loss: 0.25159 (0.22621) +2025-09-14,07:02:04 | INFO | Train Epoch: 10 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.23255 (0.21237) Boundary_loss: 0.013896 (0.013895) Loss: 0.24644 (0.22626) +2025-09-14,07:02:35 | INFO | Train Epoch: 10 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.20723 (0.21235) Boundary_loss: 0.013895 (0.013895) Loss: 0.22113 (0.22625) +2025-09-14,07:03:06 | INFO | Train Epoch: 10 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.25511 (0.21246) Boundary_loss: 0.013896 (0.013895) Loss: 0.26900 (0.22636) +2025-09-14,07:03:36 | INFO | Train Epoch: 10 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.21657 (0.21247) Boundary_loss: 0.013895 (0.013895) Loss: 0.23047 (0.22637) +2025-09-14,07:04:07 | INFO | Train Epoch: 10 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.23168 (0.21252) Boundary_loss: 0.013895 (0.013895) Loss: 0.24557 (0.22641) +2025-09-14,07:04:38 | INFO | Train Epoch: 10 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.19488 (0.21248) Boundary_loss: 0.013895 (0.013895) Loss: 0.20877 (0.22637) +2025-09-14,07:05:09 | INFO | Train Epoch: 10 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.17478 (0.21238) Boundary_loss: 0.013894 (0.013895) Loss: 0.18867 (0.22628) +2025-09-14,07:05:40 | INFO | Train Epoch: 10 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15799 (0.21225) Boundary_loss: 0.013896 (0.013895) Loss: 0.17188 (0.22614) +2025-09-14,07:06:10 | INFO | Train Epoch: 10 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.18152 (0.21217) Boundary_loss: 0.013896 (0.013895) Loss: 0.19542 (0.22607) +2025-09-14,07:06:41 | INFO | Train Epoch: 10 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20418 (0.21215) Boundary_loss: 0.013894 (0.013895) Loss: 0.21807 (0.22605) +2025-09-14,07:07:12 | INFO | Train Epoch: 10 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.22793 (0.21219) Boundary_loss: 0.013895 (0.013895) Loss: 0.24182 (0.22609) +2025-09-14,07:07:43 | INFO | Train Epoch: 10 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24229 (0.21226) Boundary_loss: 0.013896 (0.013895) Loss: 0.25619 (0.22616) +2025-09-14,07:08:14 | INFO | Train Epoch: 10 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.21007 (0.21226) Boundary_loss: 0.013896 (0.013895) Loss: 0.22396 (0.22615) +2025-09-14,07:08:44 | INFO | Train Epoch: 10 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15761 (0.21213) Boundary_loss: 0.013895 (0.013895) Loss: 0.17150 (0.22602) +2025-09-14,07:09:15 | INFO | Train Epoch: 10 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.20461 (0.21211) Boundary_loss: 0.013895 (0.013895) Loss: 0.21850 (0.22600) +2025-09-14,07:09:46 | INFO | Train Epoch: 10 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.19787 (0.21207) Boundary_loss: 0.013896 (0.013895) Loss: 0.21177 (0.22597) +2025-09-14,07:10:17 | INFO | Train Epoch: 10 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.23129 (0.21212) Boundary_loss: 0.013897 (0.013895) Loss: 0.24519 (0.22602) +2025-09-14,07:10:48 | INFO | Train Epoch: 10 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19791 (0.21209) Boundary_loss: 0.013895 (0.013895) Loss: 0.21180 (0.22598) +2025-09-14,07:11:19 | INFO | Train Epoch: 10 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20564 (0.21207) Boundary_loss: 0.013895 (0.013895) Loss: 0.21954 (0.22597) +2025-09-14,07:11:49 | INFO | Train Epoch: 10 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.18117 (0.21200) Boundary_loss: 0.013894 (0.013895) Loss: 0.19507 (0.22589) +2025-09-14,07:12:20 | INFO | Train Epoch: 10 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.20716 (0.21198) Boundary_loss: 0.013895 (0.013895) Loss: 0.22106 (0.22588) +2025-09-14,07:12:51 | INFO | Train Epoch: 10 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15448 (0.21185) Boundary_loss: 0.013897 (0.013895) Loss: 0.16838 (0.22574) +2025-09-14,07:13:22 | INFO | Train Epoch: 10 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.19651 (0.21181) Boundary_loss: 0.013894 (0.013895) Loss: 0.21040 (0.22571) +2025-09-14,07:13:53 | INFO | Train Epoch: 10 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.19466 (0.21177) Boundary_loss: 0.013895 (0.013895) Loss: 0.20856 (0.22567) +2025-09-14,07:14:24 | INFO | Train Epoch: 10 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16466 (0.21166) Boundary_loss: 0.013895 (0.013895) Loss: 0.17856 (0.22555) +2025-09-14,07:14:55 | INFO | Train Epoch: 10 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.21896 (0.21168) Boundary_loss: 0.013895 (0.013895) Loss: 0.23286 (0.22557) +2025-09-14,07:15:26 | INFO | Train Epoch: 10 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18681 (0.21162) Boundary_loss: 0.013895 (0.013895) Loss: 0.20070 (0.22551) +2025-09-14,07:15:56 | INFO | Train Epoch: 10 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.19158 (0.21157) Boundary_loss: 0.013895 (0.013895) Loss: 0.20548 (0.22547) +2025-09-14,07:16:27 | INFO | Train Epoch: 10 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.21447 (0.21158) Boundary_loss: 0.013895 (0.013895) Loss: 0.22836 (0.22547) +2025-09-14,07:16:58 | INFO | Train Epoch: 10 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.18541 (0.21152) Boundary_loss: 0.013895 (0.013895) Loss: 0.19931 (0.22541) +2025-09-14,07:17:29 | INFO | Train Epoch: 10 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17509 (0.21143) Boundary_loss: 0.013895 (0.013895) Loss: 0.18899 (0.22533) +2025-09-14,07:18:00 | INFO | Train Epoch: 10 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.22931 (0.21147) Boundary_loss: 0.013896 (0.013895) Loss: 0.24320 (0.22537) +2025-09-14,07:18:30 | INFO | Train Epoch: 10 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.25413 (0.21157) Boundary_loss: 0.013895 (0.013895) Loss: 0.26802 (0.22547) +2025-09-14,07:19:01 | INFO | Train Epoch: 10 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20285 (0.21155) Boundary_loss: 0.013895 (0.013895) Loss: 0.21675 (0.22545) +2025-09-14,07:19:32 | INFO | Train Epoch: 10 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.22039 (0.21157) Boundary_loss: 0.013895 (0.013895) Loss: 0.23429 (0.22547) +2025-09-14,07:20:02 | INFO | Train Epoch: 10 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14970 (0.21143) Boundary_loss: 0.013895 (0.013895) Loss: 0.16360 (0.22532) +2025-09-14,07:20:33 | INFO | Train Epoch: 10 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19080 (0.21138) Boundary_loss: 0.013895 (0.013895) Loss: 0.20469 (0.22528) +2025-09-14,07:21:03 | INFO | Train Epoch: 10 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18650 (0.21132) Boundary_loss: 0.013895 (0.013895) Loss: 0.20040 (0.22522) +2025-09-14,07:21:34 | INFO | Train Epoch: 10 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24818 (0.21141) Boundary_loss: 0.013895 (0.013895) Loss: 0.26208 (0.22530) +2025-09-14,07:22:05 | INFO | Train Epoch: 10 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.18673 (0.21135) Boundary_loss: 0.013895 (0.013895) Loss: 0.20063 (0.22525) +2025-09-14,07:22:35 | INFO | Train Epoch: 10 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.20298 (0.21133) Boundary_loss: 0.013895 (0.013895) Loss: 0.21687 (0.22523) +2025-09-14,07:23:06 | INFO | Train Epoch: 10 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.18058 (0.21126) Boundary_loss: 0.013895 (0.013895) Loss: 0.19448 (0.22516) +2025-09-14,07:23:37 | INFO | Train Epoch: 10 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.27133 (0.21140) Boundary_loss: 0.013895 (0.013895) Loss: 0.28522 (0.22529) +2025-09-14,07:24:08 | INFO | Train Epoch: 10 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.17807 (0.21132) Boundary_loss: 0.013896 (0.013895) Loss: 0.19197 (0.22522) +2025-09-14,07:24:39 | INFO | Train Epoch: 10 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.18505 (0.21126) Boundary_loss: 0.013895 (0.013895) Loss: 0.19894 (0.22516) +2025-09-14,07:25:10 | INFO | Train Epoch: 10 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.15351 (0.21113) Boundary_loss: 0.013895 (0.013895) Loss: 0.16740 (0.22503) +2025-09-14,07:25:40 | INFO | Train Epoch: 10 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.19412 (0.21110) Boundary_loss: 0.013897 (0.013895) Loss: 0.20801 (0.22499) +2025-09-14,07:26:11 | INFO | Train Epoch: 10 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19849 (0.21107) Boundary_loss: 0.013895 (0.013895) Loss: 0.21239 (0.22496) +2025-09-14,07:26:42 | INFO | Train Epoch: 10 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.23312 (0.21112) Boundary_loss: 0.013895 (0.013895) Loss: 0.24702 (0.22501) +2025-09-14,07:27:13 | INFO | Train Epoch: 10 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.21803 (0.21113) Boundary_loss: 0.013895 (0.013895) Loss: 0.23193 (0.22503) +2025-09-14,07:27:44 | INFO | Train Epoch: 10 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.22352 (0.21116) Boundary_loss: 0.013895 (0.013895) Loss: 0.23742 (0.22506) +2025-09-14,07:28:14 | INFO | Train Epoch: 10 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18025 (0.21109) Boundary_loss: 0.013895 (0.013895) Loss: 0.19415 (0.22499) +2025-09-14,07:28:45 | INFO | Train Epoch: 10 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14801 (0.21095) Boundary_loss: 0.013895 (0.013895) Loss: 0.16190 (0.22485) +2025-09-14,07:29:16 | INFO | Train Epoch: 10 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.22295 (0.21098) Boundary_loss: 0.013895 (0.013895) Loss: 0.23684 (0.22487) +2025-09-14,07:29:47 | INFO | Train Epoch: 10 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.23944 (0.21104) Boundary_loss: 0.013896 (0.013895) Loss: 0.25333 (0.22494) +2025-09-14,07:30:18 | INFO | Train Epoch: 10 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15959 (0.21093) Boundary_loss: 0.013895 (0.013895) Loss: 0.17349 (0.22482) +2025-09-14,07:30:49 | INFO | Train Epoch: 10 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16402 (0.21082) Boundary_loss: 0.013897 (0.013895) Loss: 0.17791 (0.22472) +2025-09-14,07:31:19 | INFO | Train Epoch: 10 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15626 (0.21070) Boundary_loss: 0.013896 (0.013895) Loss: 0.17016 (0.22460) +2025-09-14,07:31:50 | INFO | Train Epoch: 10 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13121 (0.21053) Boundary_loss: 0.013895 (0.013895) Loss: 0.14511 (0.22442) +2025-09-14,07:32:21 | INFO | Train Epoch: 10 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14558 (0.21039) Boundary_loss: 0.013895 (0.013895) Loss: 0.15947 (0.22428) +2025-09-14,07:32:52 | INFO | Train Epoch: 10 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15389 (0.21026) Boundary_loss: 0.013894 (0.013895) Loss: 0.16778 (0.22416) +2025-09-14,07:33:23 | INFO | Train Epoch: 10 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19608 (0.21023) Boundary_loss: 0.013895 (0.013895) Loss: 0.20998 (0.22413) +2025-09-14,07:33:54 | INFO | Train Epoch: 10 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24206 (0.21030) Boundary_loss: 0.013895 (0.013895) Loss: 0.25596 (0.22420) +2025-09-14,07:34:24 | INFO | Train Epoch: 10 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.23960 (0.21037) Boundary_loss: 0.013894 (0.013895) Loss: 0.25349 (0.22426) +2025-09-14,07:34:55 | INFO | Train Epoch: 10 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19950 (0.21034) Boundary_loss: 0.013896 (0.013895) Loss: 0.21339 (0.22424) +2025-09-14,07:35:26 | INFO | Train Epoch: 10 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16232 (0.21024) Boundary_loss: 0.013895 (0.013895) Loss: 0.17622 (0.22413) +2025-09-14,07:35:57 | INFO | Train Epoch: 10 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.24615 (0.21032) Boundary_loss: 0.013895 (0.013895) Loss: 0.26005 (0.22421) +2025-09-14,07:36:28 | INFO | Train Epoch: 10 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.19125 (0.21027) Boundary_loss: 0.013896 (0.013895) Loss: 0.20515 (0.22417) +2025-09-14,07:36:59 | INFO | Train Epoch: 10 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16629 (0.21018) Boundary_loss: 0.013894 (0.013895) Loss: 0.18018 (0.22408) +2025-09-14,07:37:30 | INFO | Train Epoch: 10 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17585 (0.21011) Boundary_loss: 0.013894 (0.013895) Loss: 0.18974 (0.22400) +2025-09-14,07:38:01 | INFO | Train Epoch: 10 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19308 (0.21007) Boundary_loss: 0.013895 (0.013895) Loss: 0.20697 (0.22397) +2025-09-14,07:38:31 | INFO | Train Epoch: 10 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.22624 (0.21010) Boundary_loss: 0.013894 (0.013895) Loss: 0.24013 (0.22400) +2025-09-14,07:39:02 | INFO | Train Epoch: 10 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.22932 (0.21015) Boundary_loss: 0.013895 (0.013895) Loss: 0.24321 (0.22404) +2025-09-14,07:39:33 | INFO | Train Epoch: 10 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16118 (0.21004) Boundary_loss: 0.013895 (0.013895) Loss: 0.17507 (0.22394) +2025-09-14,07:40:04 | INFO | Train Epoch: 10 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18644 (0.20999) Boundary_loss: 0.013895 (0.013895) Loss: 0.20034 (0.22389) +2025-09-14,07:40:35 | INFO | Train Epoch: 10 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.21670 (0.21001) Boundary_loss: 0.013895 (0.013895) Loss: 0.23060 (0.22390) +2025-09-14,07:41:06 | INFO | Train Epoch: 10 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.28075 (0.21016) Boundary_loss: 0.013894 (0.013895) Loss: 0.29464 (0.22405) +2025-09-14,07:41:37 | INFO | Train Epoch: 10 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.17205 (0.21008) Boundary_loss: 0.013895 (0.013895) Loss: 0.18594 (0.22397) +2025-09-14,07:42:08 | INFO | Train Epoch: 10 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.21121 (0.21008) Boundary_loss: 0.013895 (0.013895) Loss: 0.22511 (0.22397) +2025-09-14,07:42:38 | INFO | Train Epoch: 10 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.26372 (0.21019) Boundary_loss: 0.013896 (0.013895) Loss: 0.27761 (0.22409) +2025-09-14,07:43:09 | INFO | Train Epoch: 10 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.20174 (0.21017) Boundary_loss: 0.013895 (0.013895) Loss: 0.21563 (0.22407) +2025-09-14,07:43:40 | INFO | Train Epoch: 10 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.23903 (0.21023) Boundary_loss: 0.013894 (0.013895) Loss: 0.25292 (0.22413) +2025-09-14,07:44:10 | INFO | Train Epoch: 10 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.19933 (0.21021) Boundary_loss: 0.013896 (0.013895) Loss: 0.21323 (0.22411) +2025-09-14,07:44:41 | INFO | Train Epoch: 10 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.21965 (0.21023) Boundary_loss: 0.013894 (0.013895) Loss: 0.23355 (0.22412) +2025-09-14,07:45:11 | INFO | Train Epoch: 10 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13087 (0.21006) Boundary_loss: 0.013896 (0.013895) Loss: 0.14477 (0.22396) +2025-09-14,07:45:42 | INFO | Train Epoch: 10 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.22275 (0.21009) Boundary_loss: 0.013896 (0.013895) Loss: 0.23665 (0.22399) +2025-09-14,07:46:13 | INFO | Train Epoch: 10 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.24941 (0.21017) Boundary_loss: 0.013895 (0.013895) Loss: 0.26330 (0.22407) +2025-09-14,07:46:43 | INFO | Train Epoch: 10 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.23623 (0.21023) Boundary_loss: 0.013894 (0.013895) Loss: 0.25012 (0.22412) +2025-09-14,07:47:14 | INFO | Train Epoch: 10 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22752 (0.21026) Boundary_loss: 0.013894 (0.013895) Loss: 0.24142 (0.22416) +2025-09-14,07:47:44 | INFO | Train Epoch: 10 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.21860 (0.21028) Boundary_loss: 0.013894 (0.013895) Loss: 0.23249 (0.22417) +2025-09-14,07:48:15 | INFO | Train Epoch: 10 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.14871 (0.21015) Boundary_loss: 0.013894 (0.013895) Loss: 0.16260 (0.22405) +2025-09-14,07:48:46 | INFO | Train Epoch: 10 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.24052 (0.21021) Boundary_loss: 0.013896 (0.013895) Loss: 0.25441 (0.22411) +2025-09-14,07:49:16 | INFO | Train Epoch: 10 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21791 (0.21023) Boundary_loss: 0.013895 (0.013895) Loss: 0.23181 (0.22413) +2025-09-14,07:49:47 | INFO | Train Epoch: 10 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14830 (0.21010) Boundary_loss: 0.013895 (0.013895) Loss: 0.16220 (0.22400) +2025-09-14,07:50:17 | INFO | Train Epoch: 10 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20834 (0.21010) Boundary_loss: 0.013895 (0.013895) Loss: 0.22224 (0.22400) +2025-09-14,07:50:48 | INFO | Train Epoch: 10 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13915 (0.20996) Boundary_loss: 0.013895 (0.013895) Loss: 0.15305 (0.22385) +2025-09-14,07:51:19 | INFO | Train Epoch: 10 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.15355 (0.20984) Boundary_loss: 0.013895 (0.013895) Loss: 0.16745 (0.22374) +2025-09-14,07:51:49 | INFO | Train Epoch: 10 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.12810 (0.20968) Boundary_loss: 0.013894 (0.013895) Loss: 0.14199 (0.22357) +2025-09-14,07:52:20 | INFO | Train Epoch: 10 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.23771 (0.20973) Boundary_loss: 0.013895 (0.013895) Loss: 0.25160 (0.22363) +2025-09-14,07:52:51 | INFO | Train Epoch: 10 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.20168 (0.20972) Boundary_loss: 0.013897 (0.013895) Loss: 0.21558 (0.22361) +2025-09-14,07:53:21 | INFO | Train Epoch: 10 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.18287 (0.20966) Boundary_loss: 0.013895 (0.013895) Loss: 0.19676 (0.22356) +2025-09-14,07:53:52 | INFO | Train Epoch: 10 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18706 (0.20962) Boundary_loss: 0.013896 (0.013895) Loss: 0.20095 (0.22351) +2025-09-14,07:54:22 | INFO | Train Epoch: 10 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.16099 (0.20952) Boundary_loss: 0.013897 (0.013895) Loss: 0.17489 (0.22342) +2025-09-14,07:54:53 | INFO | Train Epoch: 10 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.23964 (0.20958) Boundary_loss: 0.013896 (0.013895) Loss: 0.25354 (0.22348) +2025-09-14,07:55:23 | INFO | Train Epoch: 10 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13917 (0.20944) Boundary_loss: 0.013895 (0.013895) Loss: 0.15306 (0.22334) +2025-09-14,07:55:54 | INFO | Train Epoch: 10 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.16745 (0.20936) Boundary_loss: 0.013895 (0.013895) Loss: 0.18135 (0.22325) +2025-09-14,07:56:24 | INFO | Train Epoch: 10 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16018 (0.20926) Boundary_loss: 0.013895 (0.013895) Loss: 0.17408 (0.22316) +2025-09-14,07:56:55 | INFO | Train Epoch: 10 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.14435 (0.20913) Boundary_loss: 0.013895 (0.013895) Loss: 0.15825 (0.22303) +2025-09-14,07:57:26 | INFO | Train Epoch: 10 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18986 (0.20909) Boundary_loss: 0.013895 (0.013895) Loss: 0.20376 (0.22299) +2025-09-14,07:57:56 | INFO | Train Epoch: 10 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.24630 (0.20917) Boundary_loss: 0.013895 (0.013895) Loss: 0.26020 (0.22306) +2025-09-14,07:58:27 | INFO | Train Epoch: 10 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.22351 (0.20920) Boundary_loss: 0.013896 (0.013895) Loss: 0.23741 (0.22309) +2025-09-14,07:58:58 | INFO | Train Epoch: 10 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20756 (0.20919) Boundary_loss: 0.013895 (0.013895) Loss: 0.22145 (0.22309) +2025-09-14,07:59:28 | INFO | Train Epoch: 10 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.19330 (0.20916) Boundary_loss: 0.013894 (0.013895) Loss: 0.20720 (0.22306) +2025-09-14,07:59:59 | INFO | Train Epoch: 10 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.19643 (0.20914) Boundary_loss: 0.013895 (0.013895) Loss: 0.21033 (0.22303) +2025-09-14,08:00:30 | INFO | Train Epoch: 10 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12732 (0.20898) Boundary_loss: 0.013895 (0.013895) Loss: 0.14122 (0.22287) +2025-09-14,08:01:00 | INFO | Train Epoch: 10 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.22298 (0.20900) Boundary_loss: 0.013897 (0.013895) Loss: 0.23688 (0.22290) +2025-09-14,08:01:31 | INFO | Train Epoch: 10 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18480 (0.20896) Boundary_loss: 0.013895 (0.013895) Loss: 0.19870 (0.22285) +2025-09-14,08:02:01 | INFO | Train Epoch: 10 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.23327 (0.20900) Boundary_loss: 0.013895 (0.013895) Loss: 0.24716 (0.22290) +2025-09-14,08:02:30 | INFO | Train Epoch: 10 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.19460 (0.20898) Boundary_loss: 0.013895 (0.013895) Loss: 0.20850 (0.22287) +2025-09-14,08:02:30 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,08:02:30 | INFO | [Epoch 10] Average Step Time: 0.311s | Average GPU Memory: 25.2 GB +2025-09-14,08:02:30 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,08:02:30 | INFO | Starting zero-shot imagenet. +2025-09-14,08:02:30 | INFO | Building zero-shot classifier +2025-09-14,08:02:36 | INFO | Using classifier +2025-09-14,08:03:13 | INFO | Finished zero-shot imagenet. +2025-09-14,08:03:13 | INFO | Eval Epoch: 11 imagenet-zeroshot-val-top1: 0.2906 imagenet-zeroshot-val-top5: 0.5561 +2025-09-14,08:03:14 | INFO | Start epoch 11 +2025-09-14,08:03:16 | INFO | Train Epoch: 11 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17181 (0.17181) Boundary_loss: 0.013896 (0.013896) Loss: 0.18571 (0.18571) +2025-09-14,08:03:47 | INFO | Train Epoch: 11 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17457 (0.17319) Boundary_loss: 0.013895 (0.013895) Loss: 0.18846 (0.18708) +2025-09-14,08:04:18 | INFO | Train Epoch: 11 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15620 (0.16753) Boundary_loss: 0.013895 (0.013895) Loss: 0.17009 (0.18142) +2025-09-14,08:04:48 | INFO | Train Epoch: 11 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.18500 (0.17189) Boundary_loss: 0.013895 (0.013895) Loss: 0.19889 (0.18579) +2025-09-14,08:05:19 | INFO | Train Epoch: 11 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17359 (0.17223) Boundary_loss: 0.013895 (0.013895) Loss: 0.18748 (0.18613) +2025-09-14,08:05:50 | INFO | Train Epoch: 11 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11105 (0.16204) Boundary_loss: 0.013896 (0.013895) Loss: 0.12495 (0.17593) +2025-09-14,08:06:20 | INFO | Train Epoch: 11 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.15364 (0.16084) Boundary_loss: 0.013895 (0.013895) Loss: 0.16753 (0.17473) +2025-09-14,08:06:51 | INFO | Train Epoch: 11 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.20677 (0.16658) Boundary_loss: 0.013895 (0.013895) Loss: 0.22066 (0.18047) +2025-09-14,08:07:22 | INFO | Train Epoch: 11 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.17652 (0.16768) Boundary_loss: 0.013895 (0.013895) Loss: 0.19042 (0.18158) +2025-09-14,08:07:52 | INFO | Train Epoch: 11 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12947 (0.16386) Boundary_loss: 0.013895 (0.013895) Loss: 0.14336 (0.17776) +2025-09-14,08:08:23 | INFO | Train Epoch: 11 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16754 (0.16419) Boundary_loss: 0.013896 (0.013895) Loss: 0.18144 (0.17809) +2025-09-14,08:08:54 | INFO | Train Epoch: 11 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19817 (0.16703) Boundary_loss: 0.013895 (0.013895) Loss: 0.21206 (0.18092) +2025-09-14,08:09:25 | INFO | Train Epoch: 11 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12870 (0.16408) Boundary_loss: 0.013896 (0.013895) Loss: 0.14259 (0.17797) +2025-09-14,08:09:56 | INFO | Train Epoch: 11 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13977 (0.16234) Boundary_loss: 0.013896 (0.013895) Loss: 0.15367 (0.17624) +2025-09-14,08:10:26 | INFO | Train Epoch: 11 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.21109 (0.16559) Boundary_loss: 0.013896 (0.013895) Loss: 0.22498 (0.17949) +2025-09-14,08:10:57 | INFO | Train Epoch: 11 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.16347 (0.16546) Boundary_loss: 0.013897 (0.013895) Loss: 0.17736 (0.17935) +2025-09-14,08:11:28 | INFO | Train Epoch: 11 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11816 (0.16268) Boundary_loss: 0.013895 (0.013895) Loss: 0.13205 (0.17657) +2025-09-14,08:11:59 | INFO | Train Epoch: 11 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15049 (0.16200) Boundary_loss: 0.013895 (0.013895) Loss: 0.16439 (0.17589) +2025-09-14,08:12:29 | INFO | Train Epoch: 11 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14559 (0.16114) Boundary_loss: 0.013896 (0.013895) Loss: 0.15948 (0.17503) +2025-09-14,08:13:00 | INFO | Train Epoch: 11 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13519 (0.15984) Boundary_loss: 0.013895 (0.013895) Loss: 0.14908 (0.17373) +2025-09-14,08:13:31 | INFO | Train Epoch: 11 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18949 (0.16125) Boundary_loss: 0.013896 (0.013895) Loss: 0.20339 (0.17515) +2025-09-14,08:14:02 | INFO | Train Epoch: 11 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14087 (0.16032) Boundary_loss: 0.013895 (0.013895) Loss: 0.15477 (0.17422) +2025-09-14,08:14:32 | INFO | Train Epoch: 11 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18021 (0.16119) Boundary_loss: 0.013896 (0.013895) Loss: 0.19411 (0.17508) +2025-09-14,08:15:03 | INFO | Train Epoch: 11 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.16327 (0.16128) Boundary_loss: 0.013895 (0.013895) Loss: 0.17716 (0.17517) +2025-09-14,08:15:34 | INFO | Train Epoch: 11 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.15763 (0.16113) Boundary_loss: 0.013895 (0.013895) Loss: 0.17153 (0.17502) +2025-09-14,08:16:05 | INFO | Train Epoch: 11 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.17772 (0.16177) Boundary_loss: 0.013894 (0.013895) Loss: 0.19161 (0.17566) +2025-09-14,08:16:36 | INFO | Train Epoch: 11 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16158 (0.16176) Boundary_loss: 0.013896 (0.013895) Loss: 0.17547 (0.17566) +2025-09-14,08:17:06 | INFO | Train Epoch: 11 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.22445 (0.16400) Boundary_loss: 0.013895 (0.013895) Loss: 0.23834 (0.17789) +2025-09-14,08:17:37 | INFO | Train Epoch: 11 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13774 (0.16309) Boundary_loss: 0.013894 (0.013895) Loss: 0.15163 (0.17699) +2025-09-14,08:18:08 | INFO | Train Epoch: 11 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13738 (0.16224) Boundary_loss: 0.013895 (0.013895) Loss: 0.15128 (0.17613) +2025-09-14,08:18:39 | INFO | Train Epoch: 11 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12789 (0.16113) Boundary_loss: 0.013895 (0.013895) Loss: 0.14179 (0.17502) +2025-09-14,08:19:10 | INFO | Train Epoch: 11 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17569 (0.16158) Boundary_loss: 0.013895 (0.013895) Loss: 0.18958 (0.17548) +2025-09-14,08:19:41 | INFO | Train Epoch: 11 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16462 (0.16168) Boundary_loss: 0.013895 (0.013895) Loss: 0.17851 (0.17557) +2025-09-14,08:20:11 | INFO | Train Epoch: 11 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14067 (0.16106) Boundary_loss: 0.013896 (0.013895) Loss: 0.15456 (0.17495) +2025-09-14,08:20:42 | INFO | Train Epoch: 11 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.16530 (0.16118) Boundary_loss: 0.013894 (0.013895) Loss: 0.17920 (0.17507) +2025-09-14,08:21:13 | INFO | Train Epoch: 11 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14558 (0.16075) Boundary_loss: 0.013896 (0.013895) Loss: 0.15948 (0.17464) +2025-09-14,08:21:43 | INFO | Train Epoch: 11 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19419 (0.16165) Boundary_loss: 0.013896 (0.013895) Loss: 0.20809 (0.17555) +2025-09-14,08:22:14 | INFO | Train Epoch: 11 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15817 (0.16156) Boundary_loss: 0.013895 (0.013895) Loss: 0.17206 (0.17545) +2025-09-14,08:22:45 | INFO | Train Epoch: 11 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19888 (0.16252) Boundary_loss: 0.013895 (0.013895) Loss: 0.21277 (0.17641) +2025-09-14,08:23:16 | INFO | Train Epoch: 11 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14586 (0.16210) Boundary_loss: 0.013895 (0.013895) Loss: 0.15975 (0.17599) +2025-09-14,08:23:46 | INFO | Train Epoch: 11 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19714 (0.16295) Boundary_loss: 0.013895 (0.013895) Loss: 0.21103 (0.17685) +2025-09-14,08:24:17 | INFO | Train Epoch: 11 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17103 (0.16315) Boundary_loss: 0.013895 (0.013895) Loss: 0.18492 (0.17704) +2025-09-14,08:24:48 | INFO | Train Epoch: 11 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13655 (0.16253) Boundary_loss: 0.013895 (0.013895) Loss: 0.15044 (0.17642) +2025-09-14,08:25:19 | INFO | Train Epoch: 11 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14084 (0.16203) Boundary_loss: 0.013895 (0.013895) Loss: 0.15474 (0.17593) +2025-09-14,08:25:50 | INFO | Train Epoch: 11 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14313 (0.16161) Boundary_loss: 0.013895 (0.013895) Loss: 0.15702 (0.17551) +2025-09-14,08:26:21 | INFO | Train Epoch: 11 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17823 (0.16198) Boundary_loss: 0.013895 (0.013895) Loss: 0.19213 (0.17587) +2025-09-14,08:26:52 | INFO | Train Epoch: 11 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17124 (0.16217) Boundary_loss: 0.013895 (0.013895) Loss: 0.18513 (0.17607) +2025-09-14,08:27:23 | INFO | Train Epoch: 11 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10783 (0.16104) Boundary_loss: 0.013895 (0.013895) Loss: 0.12172 (0.17494) +2025-09-14,08:27:53 | INFO | Train Epoch: 11 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17163 (0.16126) Boundary_loss: 0.013895 (0.013895) Loss: 0.18553 (0.17515) +2025-09-14,08:28:24 | INFO | Train Epoch: 11 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.18312 (0.16169) Boundary_loss: 0.013895 (0.013895) Loss: 0.19702 (0.17559) +2025-09-14,08:28:55 | INFO | Train Epoch: 11 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14914 (0.16145) Boundary_loss: 0.013895 (0.013895) Loss: 0.16303 (0.17534) +2025-09-14,08:29:26 | INFO | Train Epoch: 11 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.23462 (0.16285) Boundary_loss: 0.013896 (0.013895) Loss: 0.24852 (0.17675) +2025-09-14,08:29:57 | INFO | Train Epoch: 11 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.16476 (0.16289) Boundary_loss: 0.013896 (0.013895) Loss: 0.17866 (0.17679) +2025-09-14,08:30:28 | INFO | Train Epoch: 11 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15399 (0.16273) Boundary_loss: 0.013895 (0.013895) Loss: 0.16789 (0.17662) +2025-09-14,08:30:58 | INFO | Train Epoch: 11 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16365 (0.16274) Boundary_loss: 0.013895 (0.013895) Loss: 0.17755 (0.17664) +2025-09-14,08:31:29 | INFO | Train Epoch: 11 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.17281 (0.16292) Boundary_loss: 0.013895 (0.013895) Loss: 0.18670 (0.17682) +2025-09-14,08:31:59 | INFO | Train Epoch: 11 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.19853 (0.16355) Boundary_loss: 0.013895 (0.013895) Loss: 0.21243 (0.17744) +2025-09-14,08:32:30 | INFO | Train Epoch: 11 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16143 (0.16351) Boundary_loss: 0.013895 (0.013895) Loss: 0.17532 (0.17741) +2025-09-14,08:33:01 | INFO | Train Epoch: 11 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12910 (0.16293) Boundary_loss: 0.013895 (0.013895) Loss: 0.14300 (0.17682) +2025-09-14,08:33:31 | INFO | Train Epoch: 11 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.13564 (0.16247) Boundary_loss: 0.013896 (0.013895) Loss: 0.14954 (0.17637) +2025-09-14,08:34:02 | INFO | Train Epoch: 11 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15689 (0.16238) Boundary_loss: 0.013895 (0.013895) Loss: 0.17079 (0.17628) +2025-09-14,08:34:33 | INFO | Train Epoch: 11 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14136 (0.16204) Boundary_loss: 0.013896 (0.013895) Loss: 0.15526 (0.17594) +2025-09-14,08:35:03 | INFO | Train Epoch: 11 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.24390 (0.16334) Boundary_loss: 0.013897 (0.013895) Loss: 0.25780 (0.17724) +2025-09-14,08:35:34 | INFO | Train Epoch: 11 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.15768 (0.16325) Boundary_loss: 0.013896 (0.013895) Loss: 0.17158 (0.17715) +2025-09-14,08:36:05 | INFO | Train Epoch: 11 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14836 (0.16302) Boundary_loss: 0.013897 (0.013895) Loss: 0.16226 (0.17692) +2025-09-14,08:36:35 | INFO | Train Epoch: 11 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19996 (0.16358) Boundary_loss: 0.013896 (0.013895) Loss: 0.21385 (0.17748) +2025-09-14,08:37:06 | INFO | Train Epoch: 11 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.16780 (0.16365) Boundary_loss: 0.013895 (0.013895) Loss: 0.18169 (0.17754) +2025-09-14,08:37:36 | INFO | Train Epoch: 11 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14858 (0.16343) Boundary_loss: 0.013895 (0.013895) Loss: 0.16247 (0.17732) +2025-09-14,08:38:07 | INFO | Train Epoch: 11 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18150 (0.16369) Boundary_loss: 0.013895 (0.013895) Loss: 0.19540 (0.17758) +2025-09-14,08:38:38 | INFO | Train Epoch: 11 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.16334 (0.16368) Boundary_loss: 0.013894 (0.013895) Loss: 0.17724 (0.17758) +2025-09-14,08:39:09 | INFO | Train Epoch: 11 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.17189 (0.16380) Boundary_loss: 0.013894 (0.013895) Loss: 0.18578 (0.17769) +2025-09-14,08:39:40 | INFO | Train Epoch: 11 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15076 (0.16362) Boundary_loss: 0.013896 (0.013895) Loss: 0.16466 (0.17751) +2025-09-14,08:40:11 | INFO | Train Epoch: 11 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.18104 (0.16386) Boundary_loss: 0.013895 (0.013895) Loss: 0.19494 (0.17775) +2025-09-14,08:40:42 | INFO | Train Epoch: 11 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.19863 (0.16433) Boundary_loss: 0.013895 (0.013895) Loss: 0.21253 (0.17822) +2025-09-14,08:41:12 | INFO | Train Epoch: 11 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15625 (0.16422) Boundary_loss: 0.013895 (0.013895) Loss: 0.17015 (0.17811) +2025-09-14,08:41:43 | INFO | Train Epoch: 11 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14978 (0.16403) Boundary_loss: 0.013895 (0.013895) Loss: 0.16368 (0.17792) +2025-09-14,08:42:14 | INFO | Train Epoch: 11 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.24171 (0.16504) Boundary_loss: 0.013895 (0.013895) Loss: 0.25560 (0.17893) +2025-09-14,08:42:45 | INFO | Train Epoch: 11 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15167 (0.16487) Boundary_loss: 0.013895 (0.013895) Loss: 0.16557 (0.17876) +2025-09-14,08:43:16 | INFO | Train Epoch: 11 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.098630 (0.16403) Boundary_loss: 0.013896 (0.013895) Loss: 0.11253 (0.17792) +2025-09-14,08:43:47 | INFO | Train Epoch: 11 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13957 (0.16372) Boundary_loss: 0.013894 (0.013895) Loss: 0.15346 (0.17762) +2025-09-14,08:44:17 | INFO | Train Epoch: 11 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20437 (0.16422) Boundary_loss: 0.013894 (0.013895) Loss: 0.21827 (0.17812) +2025-09-14,08:44:48 | INFO | Train Epoch: 11 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.16209 (0.16420) Boundary_loss: 0.013894 (0.013895) Loss: 0.17598 (0.17809) +2025-09-14,08:45:19 | INFO | Train Epoch: 11 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.17809 (0.16436) Boundary_loss: 0.013896 (0.013895) Loss: 0.19199 (0.17826) +2025-09-14,08:45:50 | INFO | Train Epoch: 11 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.15419 (0.16424) Boundary_loss: 0.013895 (0.013895) Loss: 0.16809 (0.17814) +2025-09-14,08:46:20 | INFO | Train Epoch: 11 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.17307 (0.16435) Boundary_loss: 0.013894 (0.013895) Loss: 0.18697 (0.17824) +2025-09-14,08:46:51 | INFO | Train Epoch: 11 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.18661 (0.16461) Boundary_loss: 0.013894 (0.013895) Loss: 0.20051 (0.17850) +2025-09-14,08:47:22 | INFO | Train Epoch: 11 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10359 (0.16390) Boundary_loss: 0.013895 (0.013895) Loss: 0.11748 (0.17780) +2025-09-14,08:47:53 | INFO | Train Epoch: 11 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17479 (0.16403) Boundary_loss: 0.013895 (0.013895) Loss: 0.18868 (0.17792) +2025-09-14,08:48:24 | INFO | Train Epoch: 11 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.16089 (0.16399) Boundary_loss: 0.013895 (0.013895) Loss: 0.17478 (0.17789) +2025-09-14,08:48:54 | INFO | Train Epoch: 11 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.16490 (0.16400) Boundary_loss: 0.013897 (0.013895) Loss: 0.17879 (0.17790) +2025-09-14,08:49:25 | INFO | Train Epoch: 11 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.18416 (0.16422) Boundary_loss: 0.013895 (0.013895) Loss: 0.19805 (0.17812) +2025-09-14,08:49:56 | INFO | Train Epoch: 11 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16569 (0.16424) Boundary_loss: 0.013895 (0.013895) Loss: 0.17958 (0.17814) +2025-09-14,08:50:27 | INFO | Train Epoch: 11 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.21657 (0.16480) Boundary_loss: 0.013895 (0.013895) Loss: 0.23047 (0.17870) +2025-09-14,08:50:57 | INFO | Train Epoch: 11 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15274 (0.16467) Boundary_loss: 0.013896 (0.013895) Loss: 0.16664 (0.17857) +2025-09-14,08:51:28 | INFO | Train Epoch: 11 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14658 (0.16448) Boundary_loss: 0.013896 (0.013895) Loss: 0.16048 (0.17838) +2025-09-14,08:51:59 | INFO | Train Epoch: 11 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16851 (0.16453) Boundary_loss: 0.013895 (0.013895) Loss: 0.18241 (0.17842) +2025-09-14,08:52:29 | INFO | Train Epoch: 11 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20699 (0.16496) Boundary_loss: 0.013896 (0.013895) Loss: 0.22089 (0.17886) +2025-09-14,08:53:00 | INFO | Train Epoch: 11 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16346 (0.16495) Boundary_loss: 0.013895 (0.013895) Loss: 0.17736 (0.17884) +2025-09-14,08:53:31 | INFO | Train Epoch: 11 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.22363 (0.16554) Boundary_loss: 0.013895 (0.013895) Loss: 0.23753 (0.17944) +2025-09-14,08:54:01 | INFO | Train Epoch: 11 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20852 (0.16597) Boundary_loss: 0.013895 (0.013895) Loss: 0.22242 (0.17987) +2025-09-14,08:54:32 | INFO | Train Epoch: 11 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15759 (0.16589) Boundary_loss: 0.013895 (0.013895) Loss: 0.17149 (0.17978) +2025-09-14,08:55:03 | INFO | Train Epoch: 11 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16859 (0.16591) Boundary_loss: 0.013895 (0.013895) Loss: 0.18249 (0.17981) +2025-09-14,08:55:33 | INFO | Train Epoch: 11 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.14794 (0.16574) Boundary_loss: 0.013894 (0.013895) Loss: 0.16184 (0.17964) +2025-09-14,08:56:04 | INFO | Train Epoch: 11 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16340 (0.16572) Boundary_loss: 0.013895 (0.013895) Loss: 0.17730 (0.17961) +2025-09-14,08:56:35 | INFO | Train Epoch: 11 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.19746 (0.16602) Boundary_loss: 0.013895 (0.013895) Loss: 0.21135 (0.17992) +2025-09-14,08:57:06 | INFO | Train Epoch: 11 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.15282 (0.16590) Boundary_loss: 0.013894 (0.013895) Loss: 0.16671 (0.17979) +2025-09-14,08:57:36 | INFO | Train Epoch: 11 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13390 (0.16560) Boundary_loss: 0.013896 (0.013895) Loss: 0.14780 (0.17949) +2025-09-14,08:58:07 | INFO | Train Epoch: 11 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.19725 (0.16589) Boundary_loss: 0.013895 (0.013895) Loss: 0.21114 (0.17978) +2025-09-14,08:58:38 | INFO | Train Epoch: 11 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19562 (0.16616) Boundary_loss: 0.013896 (0.013895) Loss: 0.20951 (0.18006) +2025-09-14,08:59:09 | INFO | Train Epoch: 11 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17385 (0.16623) Boundary_loss: 0.013896 (0.013895) Loss: 0.18775 (0.18013) +2025-09-14,08:59:40 | INFO | Train Epoch: 11 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14475 (0.16604) Boundary_loss: 0.013895 (0.013895) Loss: 0.15865 (0.17993) +2025-09-14,09:00:10 | INFO | Train Epoch: 11 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16074 (0.16599) Boundary_loss: 0.013895 (0.013895) Loss: 0.17464 (0.17989) +2025-09-14,09:00:41 | INFO | Train Epoch: 11 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17016 (0.16603) Boundary_loss: 0.013894 (0.013895) Loss: 0.18405 (0.17992) +2025-09-14,09:01:12 | INFO | Train Epoch: 11 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15759 (0.16595) Boundary_loss: 0.013896 (0.013895) Loss: 0.17148 (0.17985) +2025-09-14,09:01:43 | INFO | Train Epoch: 11 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.21043 (0.16634) Boundary_loss: 0.013895 (0.013895) Loss: 0.22433 (0.18024) +2025-09-14,09:02:14 | INFO | Train Epoch: 11 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16504 (0.16633) Boundary_loss: 0.013895 (0.013895) Loss: 0.17893 (0.18022) +2025-09-14,09:02:44 | INFO | Train Epoch: 11 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.16062 (0.16628) Boundary_loss: 0.013894 (0.013895) Loss: 0.17451 (0.18018) +2025-09-14,09:03:15 | INFO | Train Epoch: 11 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.13948 (0.16605) Boundary_loss: 0.013896 (0.013895) Loss: 0.15337 (0.17995) +2025-09-14,09:03:46 | INFO | Train Epoch: 11 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15350 (0.16595) Boundary_loss: 0.013895 (0.013895) Loss: 0.16739 (0.17984) +2025-09-14,09:04:17 | INFO | Train Epoch: 11 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13809 (0.16572) Boundary_loss: 0.013895 (0.013895) Loss: 0.15199 (0.17961) +2025-09-14,09:04:48 | INFO | Train Epoch: 11 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16359 (0.16570) Boundary_loss: 0.013895 (0.013895) Loss: 0.17749 (0.17959) +2025-09-14,09:05:19 | INFO | Train Epoch: 11 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.15590 (0.16562) Boundary_loss: 0.013895 (0.013895) Loss: 0.16979 (0.17951) +2025-09-14,09:05:49 | INFO | Train Epoch: 11 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13455 (0.16537) Boundary_loss: 0.013896 (0.013895) Loss: 0.14844 (0.17926) +2025-09-14,09:06:20 | INFO | Train Epoch: 11 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19993 (0.16564) Boundary_loss: 0.013895 (0.013895) Loss: 0.21382 (0.17954) +2025-09-14,09:06:51 | INFO | Train Epoch: 11 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17863 (0.16575) Boundary_loss: 0.013895 (0.013895) Loss: 0.19252 (0.17964) +2025-09-14,09:07:22 | INFO | Train Epoch: 11 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18386 (0.16589) Boundary_loss: 0.013894 (0.013895) Loss: 0.19775 (0.17979) +2025-09-14,09:07:53 | INFO | Train Epoch: 11 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.21192 (0.16625) Boundary_loss: 0.013896 (0.013895) Loss: 0.22582 (0.18015) +2025-09-14,09:08:23 | INFO | Train Epoch: 11 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13222 (0.16599) Boundary_loss: 0.013896 (0.013895) Loss: 0.14612 (0.17988) +2025-09-14,09:08:54 | INFO | Train Epoch: 11 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18219 (0.16611) Boundary_loss: 0.013895 (0.013895) Loss: 0.19608 (0.18001) +2025-09-14,09:09:25 | INFO | Train Epoch: 11 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.21904 (0.16652) Boundary_loss: 0.013896 (0.013895) Loss: 0.23293 (0.18042) +2025-09-14,09:09:56 | INFO | Train Epoch: 11 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.20143 (0.16679) Boundary_loss: 0.013895 (0.013895) Loss: 0.21532 (0.18068) +2025-09-14,09:10:27 | INFO | Train Epoch: 11 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20940 (0.16711) Boundary_loss: 0.013894 (0.013895) Loss: 0.22329 (0.18101) +2025-09-14,09:10:57 | INFO | Train Epoch: 11 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19745 (0.16734) Boundary_loss: 0.013895 (0.013895) Loss: 0.21135 (0.18123) +2025-09-14,09:11:28 | INFO | Train Epoch: 11 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18640 (0.16748) Boundary_loss: 0.013894 (0.013895) Loss: 0.20029 (0.18138) +2025-09-14,09:11:59 | INFO | Train Epoch: 11 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.16745 (0.16748) Boundary_loss: 0.013894 (0.013895) Loss: 0.18134 (0.18138) +2025-09-14,09:12:30 | INFO | Train Epoch: 11 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.17493 (0.16754) Boundary_loss: 0.013895 (0.013895) Loss: 0.18883 (0.18143) +2025-09-14,09:13:01 | INFO | Train Epoch: 11 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16116 (0.16749) Boundary_loss: 0.013895 (0.013895) Loss: 0.17506 (0.18138) +2025-09-14,09:13:31 | INFO | Train Epoch: 11 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.12808 (0.16720) Boundary_loss: 0.013894 (0.013895) Loss: 0.14197 (0.18110) +2025-09-14,09:14:02 | INFO | Train Epoch: 11 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18713 (0.16735) Boundary_loss: 0.013895 (0.013895) Loss: 0.20102 (0.18124) +2025-09-14,09:14:33 | INFO | Train Epoch: 11 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19415 (0.16754) Boundary_loss: 0.013896 (0.013895) Loss: 0.20804 (0.18143) +2025-09-14,09:15:03 | INFO | Train Epoch: 11 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14728 (0.16739) Boundary_loss: 0.013895 (0.013895) Loss: 0.16118 (0.18129) +2025-09-14,09:15:34 | INFO | Train Epoch: 11 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.091778 (0.16686) Boundary_loss: 0.013895 (0.013895) Loss: 0.10567 (0.18076) +2025-09-14,09:16:05 | INFO | Train Epoch: 11 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.17184 (0.16690) Boundary_loss: 0.013895 (0.013895) Loss: 0.18573 (0.18079) +2025-09-14,09:16:36 | INFO | Train Epoch: 11 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15392 (0.16681) Boundary_loss: 0.013895 (0.013895) Loss: 0.16782 (0.18070) +2025-09-14,09:17:07 | INFO | Train Epoch: 11 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17059 (0.16683) Boundary_loss: 0.013895 (0.013895) Loss: 0.18449 (0.18073) +2025-09-14,09:17:38 | INFO | Train Epoch: 11 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.17064 (0.16686) Boundary_loss: 0.013895 (0.013895) Loss: 0.18454 (0.18075) +2025-09-14,09:18:08 | INFO | Train Epoch: 11 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15018 (0.16675) Boundary_loss: 0.013895 (0.013895) Loss: 0.16408 (0.18064) +2025-09-14,09:18:39 | INFO | Train Epoch: 11 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14630 (0.16661) Boundary_loss: 0.013895 (0.013895) Loss: 0.16020 (0.18050) +2025-09-14,09:19:10 | INFO | Train Epoch: 11 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17598 (0.16667) Boundary_loss: 0.013895 (0.013895) Loss: 0.18988 (0.18057) +2025-09-14,09:19:41 | INFO | Train Epoch: 11 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14822 (0.16655) Boundary_loss: 0.013895 (0.013895) Loss: 0.16212 (0.18044) +2025-09-14,09:20:12 | INFO | Train Epoch: 11 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.15231 (0.16645) Boundary_loss: 0.013895 (0.013895) Loss: 0.16620 (0.18035) +2025-09-14,09:20:43 | INFO | Train Epoch: 11 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15946 (0.16641) Boundary_loss: 0.013894 (0.013895) Loss: 0.17336 (0.18030) +2025-09-14,09:21:13 | INFO | Train Epoch: 11 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.14755 (0.16628) Boundary_loss: 0.013895 (0.013895) Loss: 0.16145 (0.18018) +2025-09-14,09:21:44 | INFO | Train Epoch: 11 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15302 (0.16620) Boundary_loss: 0.013895 (0.013895) Loss: 0.16692 (0.18009) +2025-09-14,09:22:15 | INFO | Train Epoch: 11 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20167 (0.16643) Boundary_loss: 0.013895 (0.013895) Loss: 0.21556 (0.18032) +2025-09-14,09:22:46 | INFO | Train Epoch: 11 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15356 (0.16634) Boundary_loss: 0.013897 (0.013895) Loss: 0.16746 (0.18024) +2025-09-14,09:23:17 | INFO | Train Epoch: 11 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13059 (0.16612) Boundary_loss: 0.013897 (0.013895) Loss: 0.14449 (0.18001) +2025-09-14,09:23:47 | INFO | Train Epoch: 11 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.15642 (0.16605) Boundary_loss: 0.013895 (0.013895) Loss: 0.17032 (0.17995) +2025-09-14,09:24:18 | INFO | Train Epoch: 11 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16566 (0.16605) Boundary_loss: 0.013895 (0.013895) Loss: 0.17955 (0.17995) +2025-09-14,09:24:49 | INFO | Train Epoch: 11 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15643 (0.16599) Boundary_loss: 0.013895 (0.013895) Loss: 0.17033 (0.17989) +2025-09-14,09:25:20 | INFO | Train Epoch: 11 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.16795 (0.16600) Boundary_loss: 0.013895 (0.013895) Loss: 0.18184 (0.17990) +2025-09-14,09:25:51 | INFO | Train Epoch: 11 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16950 (0.16603) Boundary_loss: 0.013895 (0.013895) Loss: 0.18340 (0.17992) +2025-09-14,09:26:22 | INFO | Train Epoch: 11 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13845 (0.16586) Boundary_loss: 0.013895 (0.013895) Loss: 0.15234 (0.17975) +2025-09-14,09:26:53 | INFO | Train Epoch: 11 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.14942 (0.16576) Boundary_loss: 0.013895 (0.013895) Loss: 0.16332 (0.17965) +2025-09-14,09:27:24 | INFO | Train Epoch: 11 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.15729 (0.16571) Boundary_loss: 0.013895 (0.013895) Loss: 0.17118 (0.17960) +2025-09-14,09:27:55 | INFO | Train Epoch: 11 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18366 (0.16581) Boundary_loss: 0.013896 (0.013895) Loss: 0.19755 (0.17971) +2025-09-14,09:28:26 | INFO | Train Epoch: 11 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.098814 (0.16541) Boundary_loss: 0.013895 (0.013895) Loss: 0.11271 (0.17931) +2025-09-14,09:28:57 | INFO | Train Epoch: 11 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15821 (0.16537) Boundary_loss: 0.013895 (0.013895) Loss: 0.17210 (0.17926) +2025-09-14,09:29:27 | INFO | Train Epoch: 11 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14610 (0.16526) Boundary_loss: 0.013897 (0.013895) Loss: 0.16000 (0.17915) +2025-09-14,09:29:58 | INFO | Train Epoch: 11 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16413 (0.16525) Boundary_loss: 0.013895 (0.013895) Loss: 0.17802 (0.17914) +2025-09-14,09:30:29 | INFO | Train Epoch: 11 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16891 (0.16527) Boundary_loss: 0.013895 (0.013895) Loss: 0.18281 (0.17917) +2025-09-14,09:30:59 | INFO | Train Epoch: 11 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.16459 (0.16527) Boundary_loss: 0.013898 (0.013895) Loss: 0.17849 (0.17916) +2025-09-14,09:31:30 | INFO | Train Epoch: 11 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.17057 (0.16530) Boundary_loss: 0.013895 (0.013895) Loss: 0.18447 (0.17919) +2025-09-14,09:32:00 | INFO | Train Epoch: 11 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16946 (0.16532) Boundary_loss: 0.013895 (0.013895) Loss: 0.18336 (0.17922) +2025-09-14,09:32:31 | INFO | Train Epoch: 11 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.17949 (0.16540) Boundary_loss: 0.013894 (0.013895) Loss: 0.19338 (0.17930) +2025-09-14,09:33:02 | INFO | Train Epoch: 11 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.099362 (0.16503) Boundary_loss: 0.013895 (0.013895) Loss: 0.11326 (0.17892) +2025-09-14,09:33:32 | INFO | Train Epoch: 11 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.20603 (0.16526) Boundary_loss: 0.013896 (0.013895) Loss: 0.21992 (0.17915) +2025-09-14,09:34:03 | INFO | Train Epoch: 11 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18917 (0.16539) Boundary_loss: 0.013895 (0.013895) Loss: 0.20306 (0.17929) +2025-09-14,09:34:34 | INFO | Train Epoch: 11 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14388 (0.16527) Boundary_loss: 0.013895 (0.013895) Loss: 0.15778 (0.17917) +2025-09-14,09:35:05 | INFO | Train Epoch: 11 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11366 (0.16499) Boundary_loss: 0.013895 (0.013895) Loss: 0.12756 (0.17888) +2025-09-14,09:35:36 | INFO | Train Epoch: 11 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13238 (0.16481) Boundary_loss: 0.013896 (0.013895) Loss: 0.14628 (0.17870) +2025-09-14,09:36:07 | INFO | Train Epoch: 11 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14131 (0.16468) Boundary_loss: 0.013895 (0.013895) Loss: 0.15520 (0.17857) +2025-09-14,09:36:37 | INFO | Train Epoch: 11 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13197 (0.16450) Boundary_loss: 0.013897 (0.013895) Loss: 0.14587 (0.17839) +2025-09-14,09:37:08 | INFO | Train Epoch: 11 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16335 (0.16449) Boundary_loss: 0.013895 (0.013895) Loss: 0.17724 (0.17839) +2025-09-14,09:37:39 | INFO | Train Epoch: 11 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.20419 (0.16471) Boundary_loss: 0.013895 (0.013895) Loss: 0.21809 (0.17860) +2025-09-14,09:38:10 | INFO | Train Epoch: 11 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18604 (0.16482) Boundary_loss: 0.013895 (0.013895) Loss: 0.19993 (0.17872) +2025-09-14,09:38:40 | INFO | Train Epoch: 11 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14506 (0.16472) Boundary_loss: 0.013895 (0.013895) Loss: 0.15896 (0.17861) +2025-09-14,09:39:11 | INFO | Train Epoch: 11 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.17906 (0.16479) Boundary_loss: 0.013894 (0.013895) Loss: 0.19295 (0.17869) +2025-09-14,09:39:42 | INFO | Train Epoch: 11 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.17021 (0.16482) Boundary_loss: 0.013895 (0.013895) Loss: 0.18410 (0.17872) +2025-09-14,09:40:13 | INFO | Train Epoch: 11 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14119 (0.16470) Boundary_loss: 0.013895 (0.013895) Loss: 0.15508 (0.17859) +2025-09-14,09:40:44 | INFO | Train Epoch: 11 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.19302 (0.16484) Boundary_loss: 0.013895 (0.013895) Loss: 0.20691 (0.17874) +2025-09-14,09:41:15 | INFO | Train Epoch: 11 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12328 (0.16463) Boundary_loss: 0.013895 (0.013895) Loss: 0.13717 (0.17852) +2025-09-14,09:41:45 | INFO | Train Epoch: 11 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.18836 (0.16475) Boundary_loss: 0.013894 (0.013895) Loss: 0.20225 (0.17865) +2025-09-14,09:42:16 | INFO | Train Epoch: 11 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.15764 (0.16471) Boundary_loss: 0.013895 (0.013895) Loss: 0.17154 (0.17861) +2025-09-14,09:42:47 | INFO | Train Epoch: 11 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13923 (0.16458) Boundary_loss: 0.013895 (0.013895) Loss: 0.15313 (0.17848) +2025-09-14,09:43:17 | INFO | Train Epoch: 11 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14346 (0.16448) Boundary_loss: 0.013895 (0.013895) Loss: 0.15735 (0.17837) +2025-09-14,09:43:48 | INFO | Train Epoch: 11 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15797 (0.16444) Boundary_loss: 0.013895 (0.013895) Loss: 0.17186 (0.17834) +2025-09-14,09:44:19 | INFO | Train Epoch: 11 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.18164 (0.16453) Boundary_loss: 0.013896 (0.013895) Loss: 0.19554 (0.17842) +2025-09-14,09:44:50 | INFO | Train Epoch: 11 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15699 (0.16449) Boundary_loss: 0.013894 (0.013895) Loss: 0.17089 (0.17839) +2025-09-14,09:45:20 | INFO | Train Epoch: 11 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.20111 (0.16467) Boundary_loss: 0.013895 (0.013895) Loss: 0.21501 (0.17857) +2025-09-14,09:45:51 | INFO | Train Epoch: 11 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.16468 (0.16467) Boundary_loss: 0.013896 (0.013895) Loss: 0.17858 (0.17857) +2025-09-14,09:46:22 | INFO | Train Epoch: 11 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11690 (0.16444) Boundary_loss: 0.013896 (0.013895) Loss: 0.13079 (0.17833) +2025-09-14,09:46:53 | INFO | Train Epoch: 11 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.10810 (0.16416) Boundary_loss: 0.013897 (0.013895) Loss: 0.12199 (0.17806) +2025-09-14,09:47:23 | INFO | Train Epoch: 11 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17684 (0.16422) Boundary_loss: 0.013895 (0.013895) Loss: 0.19073 (0.17812) +2025-09-14,09:47:54 | INFO | Train Epoch: 11 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14873 (0.16415) Boundary_loss: 0.013895 (0.013895) Loss: 0.16262 (0.17804) +2025-09-14,09:48:25 | INFO | Train Epoch: 11 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.20204 (0.16433) Boundary_loss: 0.013895 (0.013895) Loss: 0.21593 (0.17823) +2025-09-14,09:48:56 | INFO | Train Epoch: 11 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17188 (0.16437) Boundary_loss: 0.013896 (0.013895) Loss: 0.18578 (0.17826) +2025-09-14,09:49:26 | INFO | Train Epoch: 11 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.13921 (0.16425) Boundary_loss: 0.013895 (0.013895) Loss: 0.15311 (0.17814) +2025-09-14,09:49:57 | INFO | Train Epoch: 11 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16345 (0.16424) Boundary_loss: 0.013894 (0.013895) Loss: 0.17734 (0.17814) +2025-09-14,09:50:28 | INFO | Train Epoch: 11 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13274 (0.16409) Boundary_loss: 0.013895 (0.013895) Loss: 0.14664 (0.17799) +2025-09-14,09:50:59 | INFO | Train Epoch: 11 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17951 (0.16417) Boundary_loss: 0.013895 (0.013895) Loss: 0.19341 (0.17806) +2025-09-14,09:51:30 | INFO | Train Epoch: 11 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17208 (0.16420) Boundary_loss: 0.013895 (0.013895) Loss: 0.18597 (0.17810) +2025-09-14,09:52:00 | INFO | Train Epoch: 11 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.13694 (0.16407) Boundary_loss: 0.013896 (0.013895) Loss: 0.15083 (0.17797) +2025-09-14,09:52:31 | INFO | Train Epoch: 11 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21598 (0.16432) Boundary_loss: 0.013895 (0.013895) Loss: 0.22987 (0.17821) +2025-09-14,09:53:02 | INFO | Train Epoch: 11 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13869 (0.16420) Boundary_loss: 0.013895 (0.013895) Loss: 0.15258 (0.17809) +2025-09-14,09:53:33 | INFO | Train Epoch: 11 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15378 (0.16415) Boundary_loss: 0.013895 (0.013895) Loss: 0.16767 (0.17805) +2025-09-14,09:54:03 | INFO | Train Epoch: 11 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10047 (0.16386) Boundary_loss: 0.013895 (0.013895) Loss: 0.11437 (0.17775) +2025-09-14,09:54:34 | INFO | Train Epoch: 11 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.17513 (0.16391) Boundary_loss: 0.013895 (0.013895) Loss: 0.18902 (0.17780) +2025-09-14,09:55:04 | INFO | Train Epoch: 11 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.20540 (0.16410) Boundary_loss: 0.013894 (0.013895) Loss: 0.21930 (0.17799) +2025-09-14,09:55:35 | INFO | Train Epoch: 11 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14425 (0.16401) Boundary_loss: 0.013895 (0.013895) Loss: 0.15815 (0.17790) +2025-09-14,09:56:06 | INFO | Train Epoch: 11 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.15732 (0.16398) Boundary_loss: 0.013895 (0.013895) Loss: 0.17121 (0.17787) +2025-09-14,09:56:37 | INFO | Train Epoch: 11 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15021 (0.16392) Boundary_loss: 0.013896 (0.013895) Loss: 0.16411 (0.17781) +2025-09-14,09:57:07 | INFO | Train Epoch: 11 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16160 (0.16390) Boundary_loss: 0.013895 (0.013895) Loss: 0.17549 (0.17780) +2025-09-14,09:57:38 | INFO | Train Epoch: 11 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18665 (0.16401) Boundary_loss: 0.013894 (0.013895) Loss: 0.20054 (0.17790) +2025-09-14,09:58:09 | INFO | Train Epoch: 11 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12665 (0.16384) Boundary_loss: 0.013896 (0.013895) Loss: 0.14054 (0.17774) +2025-09-14,09:58:40 | INFO | Train Epoch: 11 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.19035 (0.16396) Boundary_loss: 0.013895 (0.013895) Loss: 0.20424 (0.17785) +2025-09-14,09:59:10 | INFO | Train Epoch: 11 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.20837 (0.16415) Boundary_loss: 0.013895 (0.013895) Loss: 0.22226 (0.17805) +2025-09-14,09:59:41 | INFO | Train Epoch: 11 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16179 (0.16414) Boundary_loss: 0.013895 (0.013895) Loss: 0.17569 (0.17804) +2025-09-14,10:00:12 | INFO | Train Epoch: 11 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.18925 (0.16425) Boundary_loss: 0.013895 (0.013895) Loss: 0.20315 (0.17815) +2025-09-14,10:00:43 | INFO | Train Epoch: 11 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11606 (0.16404) Boundary_loss: 0.013895 (0.013895) Loss: 0.12995 (0.17794) +2025-09-14,10:01:14 | INFO | Train Epoch: 11 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.16375 (0.16404) Boundary_loss: 0.013894 (0.013895) Loss: 0.17764 (0.17794) +2025-09-14,10:01:44 | INFO | Train Epoch: 11 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19180 (0.16416) Boundary_loss: 0.013895 (0.013895) Loss: 0.20569 (0.17806) +2025-09-14,10:02:15 | INFO | Train Epoch: 11 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.15998 (0.16414) Boundary_loss: 0.013895 (0.013895) Loss: 0.17387 (0.17804) +2025-09-14,10:02:46 | INFO | Train Epoch: 11 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14680 (0.16407) Boundary_loss: 0.013895 (0.013895) Loss: 0.16069 (0.17796) +2025-09-14,10:03:16 | INFO | Train Epoch: 11 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15022 (0.16401) Boundary_loss: 0.013895 (0.013895) Loss: 0.16412 (0.17791) +2025-09-14,10:03:47 | INFO | Train Epoch: 11 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16172 (0.16400) Boundary_loss: 0.013895 (0.013895) Loss: 0.17562 (0.17790) +2025-09-14,10:04:18 | INFO | Train Epoch: 11 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12512 (0.16384) Boundary_loss: 0.013895 (0.013895) Loss: 0.13902 (0.17773) +2025-09-14,10:04:49 | INFO | Train Epoch: 11 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13559 (0.16372) Boundary_loss: 0.013895 (0.013895) Loss: 0.14948 (0.17761) +2025-09-14,10:05:20 | INFO | Train Epoch: 11 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.12880 (0.16357) Boundary_loss: 0.013895 (0.013895) Loss: 0.14270 (0.17747) +2025-09-14,10:05:51 | INFO | Train Epoch: 11 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14652 (0.16350) Boundary_loss: 0.013894 (0.013895) Loss: 0.16042 (0.17740) +2025-09-14,10:06:22 | INFO | Train Epoch: 11 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.18312 (0.16358) Boundary_loss: 0.013897 (0.013895) Loss: 0.19701 (0.17748) +2025-09-14,10:06:53 | INFO | Train Epoch: 11 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.21122 (0.16378) Boundary_loss: 0.013895 (0.013895) Loss: 0.22511 (0.17767) +2025-09-14,10:07:23 | INFO | Train Epoch: 11 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12246 (0.16361) Boundary_loss: 0.013895 (0.013895) Loss: 0.13635 (0.17750) +2025-09-14,10:07:54 | INFO | Train Epoch: 11 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13639 (0.16350) Boundary_loss: 0.013896 (0.013895) Loss: 0.15029 (0.17739) +2025-09-14,10:08:25 | INFO | Train Epoch: 11 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20979 (0.16369) Boundary_loss: 0.013895 (0.013895) Loss: 0.22369 (0.17758) +2025-09-14,10:08:56 | INFO | Train Epoch: 11 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14474 (0.16361) Boundary_loss: 0.013895 (0.013895) Loss: 0.15864 (0.17750) +2025-09-14,10:09:27 | INFO | Train Epoch: 11 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.14127 (0.16352) Boundary_loss: 0.013895 (0.013895) Loss: 0.15516 (0.17741) +2025-09-14,10:09:57 | INFO | Train Epoch: 11 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13742 (0.16341) Boundary_loss: 0.013895 (0.013895) Loss: 0.15132 (0.17731) +2025-09-14,10:10:28 | INFO | Train Epoch: 11 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.22399 (0.16366) Boundary_loss: 0.013894 (0.013895) Loss: 0.23788 (0.17755) +2025-09-14,10:10:59 | INFO | Train Epoch: 11 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18881 (0.16376) Boundary_loss: 0.013895 (0.013895) Loss: 0.20270 (0.17765) +2025-09-14,10:11:30 | INFO | Train Epoch: 11 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.19095 (0.16387) Boundary_loss: 0.013895 (0.013895) Loss: 0.20485 (0.17776) +2025-09-14,10:12:01 | INFO | Train Epoch: 11 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15222 (0.16382) Boundary_loss: 0.013896 (0.013895) Loss: 0.16612 (0.17771) +2025-09-14,10:12:31 | INFO | Train Epoch: 11 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12751 (0.16368) Boundary_loss: 0.013895 (0.013895) Loss: 0.14141 (0.17757) +2025-09-14,10:13:02 | INFO | Train Epoch: 11 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18067 (0.16374) Boundary_loss: 0.013895 (0.013895) Loss: 0.19456 (0.17764) +2025-09-14,10:13:33 | INFO | Train Epoch: 11 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13878 (0.16365) Boundary_loss: 0.013896 (0.013895) Loss: 0.15267 (0.17754) +2025-09-14,10:14:04 | INFO | Train Epoch: 11 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.12383 (0.16349) Boundary_loss: 0.013895 (0.013895) Loss: 0.13773 (0.17738) +2025-09-14,10:14:34 | INFO | Train Epoch: 11 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11975 (0.16332) Boundary_loss: 0.013894 (0.013895) Loss: 0.13365 (0.17721) +2025-09-14,10:15:05 | INFO | Train Epoch: 11 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.19072 (0.16343) Boundary_loss: 0.013895 (0.013895) Loss: 0.20462 (0.17732) +2025-09-14,10:15:36 | INFO | Train Epoch: 11 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.17163 (0.16346) Boundary_loss: 0.013896 (0.013895) Loss: 0.18552 (0.17735) +2025-09-14,10:16:07 | INFO | Train Epoch: 11 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.20750 (0.16363) Boundary_loss: 0.013894 (0.013895) Loss: 0.22140 (0.17752) +2025-09-14,10:16:37 | INFO | Train Epoch: 11 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17861 (0.16368) Boundary_loss: 0.013894 (0.013895) Loss: 0.19250 (0.17758) +2025-09-14,10:17:08 | INFO | Train Epoch: 11 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14212 (0.16360) Boundary_loss: 0.013895 (0.013895) Loss: 0.15602 (0.17750) +2025-09-14,10:17:39 | INFO | Train Epoch: 11 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15184 (0.16356) Boundary_loss: 0.013896 (0.013895) Loss: 0.16574 (0.17745) +2025-09-14,10:18:10 | INFO | Train Epoch: 11 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11484 (0.16337) Boundary_loss: 0.013894 (0.013895) Loss: 0.12874 (0.17727) +2025-09-14,10:18:41 | INFO | Train Epoch: 11 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13854 (0.16328) Boundary_loss: 0.013895 (0.013895) Loss: 0.15243 (0.17717) +2025-09-14,10:19:11 | INFO | Train Epoch: 11 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15133 (0.16323) Boundary_loss: 0.013895 (0.013895) Loss: 0.16522 (0.17713) +2025-09-14,10:19:42 | INFO | Train Epoch: 11 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.19402 (0.16335) Boundary_loss: 0.013895 (0.013895) Loss: 0.20791 (0.17724) +2025-09-14,10:20:12 | INFO | Train Epoch: 11 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12887 (0.16322) Boundary_loss: 0.013895 (0.013895) Loss: 0.14277 (0.17712) +2025-09-14,10:20:43 | INFO | Train Epoch: 11 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13908 (0.16313) Boundary_loss: 0.013895 (0.013895) Loss: 0.15298 (0.17703) +2025-09-14,10:21:14 | INFO | Train Epoch: 11 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.12435 (0.16299) Boundary_loss: 0.013894 (0.013895) Loss: 0.13824 (0.17688) +2025-09-14,10:21:45 | INFO | Train Epoch: 11 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.17640 (0.16304) Boundary_loss: 0.013895 (0.013895) Loss: 0.19030 (0.17693) +2025-09-14,10:22:15 | INFO | Train Epoch: 11 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15294 (0.16300) Boundary_loss: 0.013895 (0.013895) Loss: 0.16684 (0.17689) +2025-09-14,10:22:46 | INFO | Train Epoch: 11 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11103 (0.16281) Boundary_loss: 0.013895 (0.013895) Loss: 0.12492 (0.17670) +2025-09-14,10:23:17 | INFO | Train Epoch: 11 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16011 (0.16280) Boundary_loss: 0.013897 (0.013895) Loss: 0.17401 (0.17669) +2025-09-14,10:23:48 | INFO | Train Epoch: 11 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15837 (0.16278) Boundary_loss: 0.013894 (0.013895) Loss: 0.17227 (0.17668) +2025-09-14,10:24:19 | INFO | Train Epoch: 11 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13766 (0.16269) Boundary_loss: 0.013895 (0.013895) Loss: 0.15155 (0.17659) +2025-09-14,10:24:50 | INFO | Train Epoch: 11 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15193 (0.16265) Boundary_loss: 0.013894 (0.013895) Loss: 0.16582 (0.17655) +2025-09-14,10:25:21 | INFO | Train Epoch: 11 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11880 (0.16250) Boundary_loss: 0.013896 (0.013895) Loss: 0.13270 (0.17639) +2025-09-14,10:25:52 | INFO | Train Epoch: 11 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14976 (0.16245) Boundary_loss: 0.013895 (0.013895) Loss: 0.16365 (0.17635) +2025-09-14,10:26:23 | INFO | Train Epoch: 11 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14935 (0.16240) Boundary_loss: 0.013895 (0.013895) Loss: 0.16325 (0.17630) +2025-09-14,10:26:53 | INFO | Train Epoch: 11 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13421 (0.16230) Boundary_loss: 0.013895 (0.013895) Loss: 0.14811 (0.17620) +2025-09-14,10:27:24 | INFO | Train Epoch: 11 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.23600 (0.16256) Boundary_loss: 0.013895 (0.013895) Loss: 0.24990 (0.17646) +2025-09-14,10:27:55 | INFO | Train Epoch: 11 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14102 (0.16249) Boundary_loss: 0.013895 (0.013895) Loss: 0.15492 (0.17638) +2025-09-14,10:28:25 | INFO | Train Epoch: 11 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16391 (0.16249) Boundary_loss: 0.013895 (0.013895) Loss: 0.17781 (0.17639) +2025-09-14,10:28:56 | INFO | Train Epoch: 11 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.18644 (0.16258) Boundary_loss: 0.013895 (0.013895) Loss: 0.20033 (0.17647) +2025-09-14,10:29:27 | INFO | Train Epoch: 11 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14381 (0.16251) Boundary_loss: 0.013897 (0.013895) Loss: 0.15770 (0.17641) +2025-09-14,10:29:57 | INFO | Train Epoch: 11 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.14896 (0.16246) Boundary_loss: 0.013896 (0.013895) Loss: 0.16286 (0.17636) +2025-09-14,10:30:28 | INFO | Train Epoch: 11 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14158 (0.16239) Boundary_loss: 0.013895 (0.013895) Loss: 0.15547 (0.17629) +2025-09-14,10:30:59 | INFO | Train Epoch: 11 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.20375 (0.16254) Boundary_loss: 0.013895 (0.013895) Loss: 0.21765 (0.17643) +2025-09-14,10:31:29 | INFO | Train Epoch: 11 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.15022 (0.16249) Boundary_loss: 0.013894 (0.013895) Loss: 0.16412 (0.17639) +2025-09-14,10:32:00 | INFO | Train Epoch: 11 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13535 (0.16240) Boundary_loss: 0.013895 (0.013895) Loss: 0.14924 (0.17629) +2025-09-14,10:32:31 | INFO | Train Epoch: 11 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14171 (0.16233) Boundary_loss: 0.013895 (0.013895) Loss: 0.15560 (0.17622) +2025-09-14,10:33:01 | INFO | Train Epoch: 11 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14999 (0.16229) Boundary_loss: 0.013894 (0.013895) Loss: 0.16389 (0.17618) +2025-09-14,10:33:32 | INFO | Train Epoch: 11 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11796 (0.16214) Boundary_loss: 0.013894 (0.013895) Loss: 0.13185 (0.17603) +2025-09-14,10:34:03 | INFO | Train Epoch: 11 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17633 (0.16218) Boundary_loss: 0.013895 (0.013895) Loss: 0.19023 (0.17608) +2025-09-14,10:34:34 | INFO | Train Epoch: 11 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14847 (0.16214) Boundary_loss: 0.013895 (0.013895) Loss: 0.16236 (0.17603) +2025-09-14,10:35:05 | INFO | Train Epoch: 11 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.15452 (0.16211) Boundary_loss: 0.013894 (0.013895) Loss: 0.16841 (0.17601) +2025-09-14,10:35:35 | INFO | Train Epoch: 11 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12610 (0.16199) Boundary_loss: 0.013895 (0.013895) Loss: 0.14000 (0.17589) +2025-09-14,10:36:06 | INFO | Train Epoch: 11 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.12224 (0.16186) Boundary_loss: 0.013894 (0.013895) Loss: 0.13613 (0.17575) +2025-09-14,10:36:37 | INFO | Train Epoch: 11 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16598 (0.16187) Boundary_loss: 0.013895 (0.013895) Loss: 0.17988 (0.17577) +2025-09-14,10:37:08 | INFO | Train Epoch: 11 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17986 (0.16193) Boundary_loss: 0.013894 (0.013895) Loss: 0.19376 (0.17583) +2025-09-14,10:37:38 | INFO | Train Epoch: 11 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12274 (0.16180) Boundary_loss: 0.013896 (0.013895) Loss: 0.13664 (0.17570) +2025-09-14,10:38:09 | INFO | Train Epoch: 11 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11479 (0.16165) Boundary_loss: 0.013894 (0.013895) Loss: 0.12869 (0.17554) +2025-09-14,10:38:40 | INFO | Train Epoch: 11 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20863 (0.16180) Boundary_loss: 0.013895 (0.013895) Loss: 0.22252 (0.17570) +2025-09-14,10:39:11 | INFO | Train Epoch: 11 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13573 (0.16172) Boundary_loss: 0.013894 (0.013895) Loss: 0.14962 (0.17561) +2025-09-14,10:39:41 | INFO | Train Epoch: 11 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.094163 (0.16149) Boundary_loss: 0.013895 (0.013895) Loss: 0.10806 (0.17539) +2025-09-14,10:40:12 | INFO | Train Epoch: 11 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14872 (0.16145) Boundary_loss: 0.013894 (0.013895) Loss: 0.16261 (0.17535) +2025-09-14,10:40:43 | INFO | Train Epoch: 11 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.15002 (0.16142) Boundary_loss: 0.013895 (0.013895) Loss: 0.16392 (0.17531) +2025-09-14,10:41:14 | INFO | Train Epoch: 11 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.13176 (0.16132) Boundary_loss: 0.013896 (0.013895) Loss: 0.14566 (0.17522) +2025-09-14,10:41:44 | INFO | Train Epoch: 11 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.14634 (0.16127) Boundary_loss: 0.013896 (0.013895) Loss: 0.16024 (0.17517) +2025-09-14,10:42:15 | INFO | Train Epoch: 11 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17876 (0.16133) Boundary_loss: 0.013894 (0.013895) Loss: 0.19265 (0.17522) +2025-09-14,10:42:46 | INFO | Train Epoch: 11 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12051 (0.16120) Boundary_loss: 0.013895 (0.013895) Loss: 0.13441 (0.17509) +2025-09-14,10:43:17 | INFO | Train Epoch: 11 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.22913 (0.16141) Boundary_loss: 0.013895 (0.013895) Loss: 0.24303 (0.17531) +2025-09-14,10:43:47 | INFO | Train Epoch: 11 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.19051 (0.16151) Boundary_loss: 0.013896 (0.013895) Loss: 0.20441 (0.17540) +2025-09-14,10:44:18 | INFO | Train Epoch: 11 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16412 (0.16152) Boundary_loss: 0.013895 (0.013895) Loss: 0.17801 (0.17541) +2025-09-14,10:44:49 | INFO | Train Epoch: 11 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.17925 (0.16157) Boundary_loss: 0.013895 (0.013895) Loss: 0.19314 (0.17547) +2025-09-14,10:45:20 | INFO | Train Epoch: 11 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14899 (0.16153) Boundary_loss: 0.013895 (0.013895) Loss: 0.16288 (0.17543) +2025-09-14,10:45:50 | INFO | Train Epoch: 11 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14249 (0.16147) Boundary_loss: 0.013895 (0.013895) Loss: 0.15638 (0.17537) +2025-09-14,10:46:21 | INFO | Train Epoch: 11 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.19020 (0.16156) Boundary_loss: 0.013895 (0.013895) Loss: 0.20410 (0.17546) +2025-09-14,10:46:52 | INFO | Train Epoch: 11 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.11366 (0.16141) Boundary_loss: 0.013894 (0.013895) Loss: 0.12755 (0.17531) +2025-09-14,10:47:23 | INFO | Train Epoch: 11 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16116 (0.16141) Boundary_loss: 0.013895 (0.013895) Loss: 0.17505 (0.17531) +2025-09-14,10:47:54 | INFO | Train Epoch: 11 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.14264 (0.16135) Boundary_loss: 0.013895 (0.013895) Loss: 0.15654 (0.17525) +2025-09-14,10:48:24 | INFO | Train Epoch: 11 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.16647 (0.16137) Boundary_loss: 0.013895 (0.013895) Loss: 0.18036 (0.17526) +2025-09-14,10:48:55 | INFO | Train Epoch: 11 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13897 (0.16130) Boundary_loss: 0.013894 (0.013895) Loss: 0.15286 (0.17519) +2025-09-14,10:49:26 | INFO | Train Epoch: 11 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.20918 (0.16145) Boundary_loss: 0.013895 (0.013895) Loss: 0.22308 (0.17534) +2025-09-14,10:49:57 | INFO | Train Epoch: 11 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15820 (0.16144) Boundary_loss: 0.013895 (0.013895) Loss: 0.17209 (0.17533) +2025-09-14,10:50:27 | INFO | Train Epoch: 11 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17691 (0.16148) Boundary_loss: 0.013894 (0.013895) Loss: 0.19081 (0.17538) +2025-09-14,10:50:58 | INFO | Train Epoch: 11 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.16274 (0.16149) Boundary_loss: 0.013895 (0.013895) Loss: 0.17663 (0.17538) +2025-09-14,10:51:29 | INFO | Train Epoch: 11 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.15433 (0.16147) Boundary_loss: 0.013895 (0.013895) Loss: 0.16823 (0.17536) +2025-09-14,10:52:00 | INFO | Train Epoch: 11 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.13006 (0.16137) Boundary_loss: 0.013896 (0.013895) Loss: 0.14396 (0.17527) +2025-09-14,10:52:30 | INFO | Train Epoch: 11 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15525 (0.16135) Boundary_loss: 0.013895 (0.013895) Loss: 0.16915 (0.17525) +2025-09-14,10:53:01 | INFO | Train Epoch: 11 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14861 (0.16131) Boundary_loss: 0.013895 (0.013895) Loss: 0.16251 (0.17521) +2025-09-14,10:53:32 | INFO | Train Epoch: 11 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.18259 (0.16138) Boundary_loss: 0.013895 (0.013895) Loss: 0.19648 (0.17527) +2025-09-14,10:54:03 | INFO | Train Epoch: 11 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.16667 (0.16139) Boundary_loss: 0.013896 (0.013895) Loss: 0.18057 (0.17529) +2025-09-14,10:54:33 | INFO | Train Epoch: 11 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16591 (0.16141) Boundary_loss: 0.013894 (0.013895) Loss: 0.17981 (0.17530) +2025-09-14,10:55:04 | INFO | Train Epoch: 11 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16171 (0.16141) Boundary_loss: 0.013895 (0.013895) Loss: 0.17560 (0.17530) +2025-09-14,10:55:35 | INFO | Train Epoch: 11 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.16311 (0.16141) Boundary_loss: 0.013896 (0.013895) Loss: 0.17701 (0.17531) +2025-09-14,10:56:06 | INFO | Train Epoch: 11 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13746 (0.16134) Boundary_loss: 0.013895 (0.013895) Loss: 0.15135 (0.17524) +2025-09-14,10:56:36 | INFO | Train Epoch: 11 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.14274 (0.16129) Boundary_loss: 0.013894 (0.013895) Loss: 0.15663 (0.17518) +2025-09-14,10:57:07 | INFO | Train Epoch: 11 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.13666 (0.16122) Boundary_loss: 0.013894 (0.013895) Loss: 0.15055 (0.17511) +2025-09-14,10:57:38 | INFO | Train Epoch: 11 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14372 (0.16116) Boundary_loss: 0.013894 (0.013895) Loss: 0.15761 (0.17506) +2025-09-14,10:58:08 | INFO | Train Epoch: 11 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12022 (0.16104) Boundary_loss: 0.013895 (0.013895) Loss: 0.13411 (0.17494) +2025-09-14,10:58:39 | INFO | Train Epoch: 11 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17005 (0.16107) Boundary_loss: 0.013895 (0.013895) Loss: 0.18394 (0.17497) +2025-09-14,10:59:10 | INFO | Train Epoch: 11 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15048 (0.16104) Boundary_loss: 0.013894 (0.013895) Loss: 0.16437 (0.17493) +2025-09-14,10:59:40 | INFO | Train Epoch: 11 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14009 (0.16098) Boundary_loss: 0.013894 (0.013895) Loss: 0.15399 (0.17487) +2025-09-14,11:00:11 | INFO | Train Epoch: 11 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14457 (0.16093) Boundary_loss: 0.013894 (0.013895) Loss: 0.15847 (0.17483) +2025-09-14,11:00:42 | INFO | Train Epoch: 11 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13189 (0.16085) Boundary_loss: 0.013896 (0.013895) Loss: 0.14578 (0.17474) +2025-09-14,11:01:12 | INFO | Train Epoch: 11 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.16208 (0.16085) Boundary_loss: 0.013895 (0.013895) Loss: 0.17598 (0.17475) +2025-09-14,11:01:43 | INFO | Train Epoch: 11 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.18686 (0.16093) Boundary_loss: 0.013895 (0.013895) Loss: 0.20075 (0.17482) +2025-09-14,11:02:13 | INFO | Train Epoch: 11 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14675 (0.16089) Boundary_loss: 0.013895 (0.013895) Loss: 0.16064 (0.17478) +2025-09-14,11:02:44 | INFO | Train Epoch: 11 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.21894 (0.16105) Boundary_loss: 0.013894 (0.013895) Loss: 0.23283 (0.17495) +2025-09-14,11:03:15 | INFO | Train Epoch: 11 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.15461 (0.16103) Boundary_loss: 0.013894 (0.013895) Loss: 0.16850 (0.17493) +2025-09-14,11:03:46 | INFO | Train Epoch: 11 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15246 (0.16101) Boundary_loss: 0.013895 (0.013895) Loss: 0.16635 (0.17490) +2025-09-14,11:04:16 | INFO | Train Epoch: 11 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16640 (0.16102) Boundary_loss: 0.013896 (0.013895) Loss: 0.18030 (0.17492) +2025-09-14,11:04:47 | INFO | Train Epoch: 11 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14072 (0.16097) Boundary_loss: 0.013895 (0.013895) Loss: 0.15462 (0.17486) +2025-09-14,11:05:18 | INFO | Train Epoch: 11 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17179 (0.16100) Boundary_loss: 0.013895 (0.013895) Loss: 0.18568 (0.17489) +2025-09-14,11:05:49 | INFO | Train Epoch: 11 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.17591 (0.16104) Boundary_loss: 0.013896 (0.013895) Loss: 0.18981 (0.17493) +2025-09-14,11:06:20 | INFO | Train Epoch: 11 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.19748 (0.16114) Boundary_loss: 0.013895 (0.013895) Loss: 0.21138 (0.17504) +2025-09-14,11:06:51 | INFO | Train Epoch: 11 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11968 (0.16102) Boundary_loss: 0.013895 (0.013895) Loss: 0.13357 (0.17492) +2025-09-14,11:07:21 | INFO | Train Epoch: 11 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14601 (0.16098) Boundary_loss: 0.013895 (0.013895) Loss: 0.15991 (0.17488) +2025-09-14,11:07:52 | INFO | Train Epoch: 11 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13007 (0.16090) Boundary_loss: 0.013895 (0.013895) Loss: 0.14396 (0.17479) +2025-09-14,11:08:23 | INFO | Train Epoch: 11 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11168 (0.16076) Boundary_loss: 0.013895 (0.013895) Loss: 0.12558 (0.17466) +2025-09-14,11:08:54 | INFO | Train Epoch: 11 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.16423 (0.16077) Boundary_loss: 0.013896 (0.013895) Loss: 0.17813 (0.17467) +2025-09-14,11:09:25 | INFO | Train Epoch: 11 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.20053 (0.16088) Boundary_loss: 0.013895 (0.013895) Loss: 0.21443 (0.17478) +2025-09-14,11:09:55 | INFO | Train Epoch: 11 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20463 (0.16100) Boundary_loss: 0.013895 (0.013895) Loss: 0.21852 (0.17490) +2025-09-14,11:10:26 | INFO | Train Epoch: 11 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16007 (0.16100) Boundary_loss: 0.013895 (0.013895) Loss: 0.17396 (0.17489) +2025-09-14,11:10:57 | INFO | Train Epoch: 11 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18960 (0.16108) Boundary_loss: 0.013895 (0.013895) Loss: 0.20350 (0.17497) +2025-09-14,11:11:28 | INFO | Train Epoch: 11 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14940 (0.16104) Boundary_loss: 0.013895 (0.013895) Loss: 0.16329 (0.17494) +2025-09-14,11:11:59 | INFO | Train Epoch: 11 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14298 (0.16099) Boundary_loss: 0.013895 (0.013895) Loss: 0.15688 (0.17489) +2025-09-14,11:12:29 | INFO | Train Epoch: 11 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.13243 (0.16092) Boundary_loss: 0.013896 (0.013895) Loss: 0.14632 (0.17481) +2025-09-14,11:13:00 | INFO | Train Epoch: 11 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.15162 (0.16089) Boundary_loss: 0.013896 (0.013895) Loss: 0.16551 (0.17479) +2025-09-14,11:13:31 | INFO | Train Epoch: 11 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15882 (0.16089) Boundary_loss: 0.013894 (0.013895) Loss: 0.17271 (0.17478) +2025-09-14,11:14:02 | INFO | Train Epoch: 11 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11567 (0.16077) Boundary_loss: 0.013895 (0.013895) Loss: 0.12957 (0.17466) +2025-09-14,11:14:32 | INFO | Train Epoch: 11 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12398 (0.16067) Boundary_loss: 0.013895 (0.013895) Loss: 0.13788 (0.17456) +2025-09-14,11:15:03 | INFO | Train Epoch: 11 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.17717 (0.16071) Boundary_loss: 0.013894 (0.013895) Loss: 0.19107 (0.17461) +2025-09-14,11:15:34 | INFO | Train Epoch: 11 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13358 (0.16064) Boundary_loss: 0.013896 (0.013895) Loss: 0.14748 (0.17453) +2025-09-14,11:16:04 | INFO | Train Epoch: 11 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.18243 (0.16070) Boundary_loss: 0.013895 (0.013895) Loss: 0.19632 (0.17459) +2025-09-14,11:16:35 | INFO | Train Epoch: 11 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10647 (0.16055) Boundary_loss: 0.013896 (0.013895) Loss: 0.12036 (0.17445) +2025-09-14,11:17:06 | INFO | Train Epoch: 11 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14796 (0.16052) Boundary_loss: 0.013895 (0.013895) Loss: 0.16185 (0.17442) +2025-09-14,11:17:37 | INFO | Train Epoch: 11 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10627 (0.16038) Boundary_loss: 0.013895 (0.013895) Loss: 0.12017 (0.17427) +2025-09-14,11:18:08 | INFO | Train Epoch: 11 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.21732 (0.16053) Boundary_loss: 0.013897 (0.013895) Loss: 0.23122 (0.17442) +2025-09-14,11:18:38 | INFO | Train Epoch: 11 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12534 (0.16044) Boundary_loss: 0.013895 (0.013895) Loss: 0.13923 (0.17433) +2025-09-14,11:19:09 | INFO | Train Epoch: 11 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.16030 (0.16043) Boundary_loss: 0.013895 (0.013895) Loss: 0.17420 (0.17433) +2025-09-14,11:19:40 | INFO | Train Epoch: 11 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.15396 (0.16042) Boundary_loss: 0.013895 (0.013895) Loss: 0.16786 (0.17431) +2025-09-14,11:20:11 | INFO | Train Epoch: 11 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14446 (0.16038) Boundary_loss: 0.013895 (0.013895) Loss: 0.15835 (0.17427) +2025-09-14,11:20:42 | INFO | Train Epoch: 11 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13980 (0.16032) Boundary_loss: 0.013895 (0.013895) Loss: 0.15370 (0.17422) +2025-09-14,11:21:12 | INFO | Train Epoch: 11 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14603 (0.16029) Boundary_loss: 0.013895 (0.013895) Loss: 0.15993 (0.17418) +2025-09-14,11:21:43 | INFO | Train Epoch: 11 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14943 (0.16026) Boundary_loss: 0.013896 (0.013895) Loss: 0.16332 (0.17415) +2025-09-14,11:22:13 | INFO | Train Epoch: 11 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.14695 (0.16022) Boundary_loss: 0.013897 (0.013895) Loss: 0.16085 (0.17412) +2025-09-14,11:22:44 | INFO | Train Epoch: 11 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13236 (0.16015) Boundary_loss: 0.013895 (0.013895) Loss: 0.14626 (0.17405) +2025-09-14,11:23:14 | INFO | Train Epoch: 11 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.18755 (0.16022) Boundary_loss: 0.013894 (0.013895) Loss: 0.20144 (0.17412) +2025-09-14,11:23:45 | INFO | Train Epoch: 11 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.18575 (0.16029) Boundary_loss: 0.013894 (0.013895) Loss: 0.19964 (0.17418) +2025-09-14,11:24:15 | INFO | Train Epoch: 11 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.19470 (0.16038) Boundary_loss: 0.013896 (0.013895) Loss: 0.20859 (0.17427) +2025-09-14,11:24:46 | INFO | Train Epoch: 11 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14062 (0.16033) Boundary_loss: 0.013894 (0.013895) Loss: 0.15451 (0.17422) +2025-09-14,11:25:17 | INFO | Train Epoch: 11 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.13623 (0.16026) Boundary_loss: 0.013894 (0.013895) Loss: 0.15012 (0.17416) +2025-09-14,11:25:47 | INFO | Train Epoch: 11 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.17194 (0.16029) Boundary_loss: 0.013895 (0.013895) Loss: 0.18583 (0.17419) +2025-09-14,11:26:18 | INFO | Train Epoch: 11 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11055 (0.16017) Boundary_loss: 0.013895 (0.013895) Loss: 0.12445 (0.17406) +2025-09-14,11:26:48 | INFO | Train Epoch: 11 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.14581 (0.16013) Boundary_loss: 0.013895 (0.013895) Loss: 0.15971 (0.17403) +2025-09-14,11:27:19 | INFO | Train Epoch: 11 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.24554 (0.16035) Boundary_loss: 0.013896 (0.013895) Loss: 0.25944 (0.17424) +2025-09-14,11:27:50 | INFO | Train Epoch: 11 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.14527 (0.16031) Boundary_loss: 0.013894 (0.013895) Loss: 0.15917 (0.17420) +2025-09-14,11:28:21 | INFO | Train Epoch: 11 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13095 (0.16024) Boundary_loss: 0.013895 (0.013895) Loss: 0.14485 (0.17413) +2025-09-14,11:28:51 | INFO | Train Epoch: 11 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12960 (0.16016) Boundary_loss: 0.013895 (0.013895) Loss: 0.14350 (0.17405) +2025-09-14,11:29:22 | INFO | Train Epoch: 11 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.20089 (0.16026) Boundary_loss: 0.013895 (0.013895) Loss: 0.21478 (0.17416) +2025-09-14,11:29:52 | INFO | Train Epoch: 11 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.15725 (0.16025) Boundary_loss: 0.013894 (0.013895) Loss: 0.17114 (0.17415) +2025-09-14,11:30:23 | INFO | Train Epoch: 11 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14737 (0.16022) Boundary_loss: 0.013895 (0.013895) Loss: 0.16127 (0.17412) +2025-09-14,11:30:53 | INFO | Train Epoch: 11 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13652 (0.16016) Boundary_loss: 0.013895 (0.013895) Loss: 0.15041 (0.17406) +2025-09-14,11:31:24 | INFO | Train Epoch: 11 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.15776 (0.16016) Boundary_loss: 0.013894 (0.013895) Loss: 0.17166 (0.17405) +2025-09-14,11:31:55 | INFO | Train Epoch: 11 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13337 (0.16009) Boundary_loss: 0.013894 (0.013895) Loss: 0.14727 (0.17399) +2025-09-14,11:32:25 | INFO | Train Epoch: 11 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14966 (0.16007) Boundary_loss: 0.013894 (0.013895) Loss: 0.16355 (0.17396) +2025-09-14,11:32:56 | INFO | Train Epoch: 11 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16112 (0.16007) Boundary_loss: 0.013896 (0.013895) Loss: 0.17502 (0.17396) +2025-09-14,11:33:27 | INFO | Train Epoch: 11 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.17491 (0.16010) Boundary_loss: 0.013895 (0.013895) Loss: 0.18881 (0.17400) +2025-09-14,11:33:58 | INFO | Train Epoch: 11 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12823 (0.16003) Boundary_loss: 0.013895 (0.013895) Loss: 0.14212 (0.17392) +2025-09-14,11:34:29 | INFO | Train Epoch: 11 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.18023 (0.16008) Boundary_loss: 0.013896 (0.013895) Loss: 0.19412 (0.17397) +2025-09-14,11:34:59 | INFO | Train Epoch: 11 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14748 (0.16005) Boundary_loss: 0.013896 (0.013895) Loss: 0.16138 (0.17394) +2025-09-14,11:35:30 | INFO | Train Epoch: 11 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.12785 (0.15997) Boundary_loss: 0.013895 (0.013895) Loss: 0.14174 (0.17386) +2025-09-14,11:36:01 | INFO | Train Epoch: 11 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17519 (0.16000) Boundary_loss: 0.013896 (0.013895) Loss: 0.18909 (0.17390) +2025-09-14,11:36:32 | INFO | Train Epoch: 11 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10908 (0.15988) Boundary_loss: 0.013895 (0.013895) Loss: 0.12298 (0.17378) +2025-09-14,11:37:03 | INFO | Train Epoch: 11 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.17869 (0.15993) Boundary_loss: 0.013895 (0.013895) Loss: 0.19258 (0.17382) +2025-09-14,11:37:34 | INFO | Train Epoch: 11 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.16747 (0.15995) Boundary_loss: 0.013894 (0.013895) Loss: 0.18136 (0.17384) +2025-09-14,11:38:05 | INFO | Train Epoch: 11 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12322 (0.15986) Boundary_loss: 0.013895 (0.013895) Loss: 0.13711 (0.17375) +2025-09-14,11:38:36 | INFO | Train Epoch: 11 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.14890 (0.15983) Boundary_loss: 0.013894 (0.013895) Loss: 0.16280 (0.17373) +2025-09-14,11:39:07 | INFO | Train Epoch: 11 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.21190 (0.15996) Boundary_loss: 0.013894 (0.013895) Loss: 0.22579 (0.17385) +2025-09-14,11:39:38 | INFO | Train Epoch: 11 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.20445 (0.16006) Boundary_loss: 0.013894 (0.013895) Loss: 0.21835 (0.17396) +2025-09-14,11:40:09 | INFO | Train Epoch: 11 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13402 (0.16000) Boundary_loss: 0.013895 (0.013895) Loss: 0.14791 (0.17389) +2025-09-14,11:40:40 | INFO | Train Epoch: 11 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.21451 (0.16013) Boundary_loss: 0.013896 (0.013895) Loss: 0.22840 (0.17402) +2025-09-14,11:41:11 | INFO | Train Epoch: 11 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12285 (0.16004) Boundary_loss: 0.013895 (0.013895) Loss: 0.13674 (0.17393) +2025-09-14,11:41:41 | INFO | Train Epoch: 11 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15736 (0.16003) Boundary_loss: 0.013895 (0.013895) Loss: 0.17126 (0.17393) +2025-09-14,11:42:12 | INFO | Train Epoch: 11 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15791 (0.16003) Boundary_loss: 0.013896 (0.013895) Loss: 0.17181 (0.17392) +2025-09-14,11:42:42 | INFO | Train Epoch: 11 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17099 (0.16005) Boundary_loss: 0.013895 (0.013895) Loss: 0.18488 (0.17395) +2025-09-14,11:43:12 | INFO | Train Epoch: 11 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11960 (0.15996) Boundary_loss: 0.013894 (0.013895) Loss: 0.13350 (0.17386) +2025-09-14,11:43:43 | INFO | Train Epoch: 11 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15813 (0.15996) Boundary_loss: 0.013895 (0.013895) Loss: 0.17203 (0.17385) +2025-09-14,11:44:14 | INFO | Train Epoch: 11 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13660 (0.15990) Boundary_loss: 0.013895 (0.013895) Loss: 0.15050 (0.17380) +2025-09-14,11:44:45 | INFO | Train Epoch: 11 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.16271 (0.15991) Boundary_loss: 0.013896 (0.013895) Loss: 0.17660 (0.17380) +2025-09-14,11:45:16 | INFO | Train Epoch: 11 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.16566 (0.15992) Boundary_loss: 0.013895 (0.013895) Loss: 0.17956 (0.17382) +2025-09-14,11:45:47 | INFO | Train Epoch: 11 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16276 (0.15993) Boundary_loss: 0.013895 (0.013895) Loss: 0.17666 (0.17382) +2025-09-14,11:46:17 | INFO | Train Epoch: 11 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13468 (0.15987) Boundary_loss: 0.013896 (0.013895) Loss: 0.14858 (0.17377) +2025-09-14,11:46:48 | INFO | Train Epoch: 11 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.17083 (0.15990) Boundary_loss: 0.013894 (0.013895) Loss: 0.18472 (0.17379) +2025-09-14,11:47:19 | INFO | Train Epoch: 11 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.19358 (0.15997) Boundary_loss: 0.013895 (0.013895) Loss: 0.20747 (0.17387) +2025-09-14,11:47:49 | INFO | Train Epoch: 11 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.13601 (0.15992) Boundary_loss: 0.013896 (0.013895) Loss: 0.14990 (0.17381) +2025-09-14,11:48:20 | INFO | Train Epoch: 11 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.14254 (0.15988) Boundary_loss: 0.013896 (0.013895) Loss: 0.15644 (0.17377) +2025-09-14,11:48:51 | INFO | Train Epoch: 11 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15315 (0.15986) Boundary_loss: 0.013894 (0.013895) Loss: 0.16704 (0.17376) +2025-09-14,11:49:21 | INFO | Train Epoch: 11 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12091 (0.15977) Boundary_loss: 0.013895 (0.013895) Loss: 0.13480 (0.17367) +2025-09-14,11:49:52 | INFO | Train Epoch: 11 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12684 (0.15970) Boundary_loss: 0.013895 (0.013895) Loss: 0.14074 (0.17360) +2025-09-14,11:50:23 | INFO | Train Epoch: 11 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13690 (0.15965) Boundary_loss: 0.013895 (0.013895) Loss: 0.15080 (0.17354) +2025-09-14,11:50:54 | INFO | Train Epoch: 11 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14015 (0.15960) Boundary_loss: 0.013895 (0.013895) Loss: 0.15404 (0.17350) +2025-09-14,11:51:25 | INFO | Train Epoch: 11 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.17483 (0.15964) Boundary_loss: 0.013894 (0.013895) Loss: 0.18872 (0.17353) +2025-09-14,11:51:56 | INFO | Train Epoch: 11 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15289 (0.15962) Boundary_loss: 0.013895 (0.013895) Loss: 0.16678 (0.17352) +2025-09-14,11:52:26 | INFO | Train Epoch: 11 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.17778 (0.15966) Boundary_loss: 0.013896 (0.013895) Loss: 0.19168 (0.17356) +2025-09-14,11:52:57 | INFO | Train Epoch: 11 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.21665 (0.15979) Boundary_loss: 0.013894 (0.013895) Loss: 0.23055 (0.17369) +2025-09-14,11:53:28 | INFO | Train Epoch: 11 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15147 (0.15977) Boundary_loss: 0.013895 (0.013895) Loss: 0.16537 (0.17367) +2025-09-14,11:53:59 | INFO | Train Epoch: 11 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16093 (0.15978) Boundary_loss: 0.013895 (0.013895) Loss: 0.17483 (0.17367) +2025-09-14,11:54:29 | INFO | Train Epoch: 11 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.13747 (0.15973) Boundary_loss: 0.013895 (0.013895) Loss: 0.15136 (0.17362) +2025-09-14,11:55:00 | INFO | Train Epoch: 11 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14440 (0.15969) Boundary_loss: 0.013895 (0.013895) Loss: 0.15830 (0.17359) +2025-09-14,11:55:31 | INFO | Train Epoch: 11 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.13479 (0.15964) Boundary_loss: 0.013894 (0.013895) Loss: 0.14868 (0.17353) +2025-09-14,11:56:02 | INFO | Train Epoch: 11 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.16926 (0.15966) Boundary_loss: 0.013897 (0.013895) Loss: 0.18316 (0.17355) +2025-09-14,11:56:33 | INFO | Train Epoch: 11 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16142 (0.15966) Boundary_loss: 0.013895 (0.013895) Loss: 0.17531 (0.17356) +2025-09-14,11:57:04 | INFO | Train Epoch: 11 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12809 (0.15959) Boundary_loss: 0.013896 (0.013895) Loss: 0.14199 (0.17349) +2025-09-14,11:57:34 | INFO | Train Epoch: 11 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16869 (0.15961) Boundary_loss: 0.013895 (0.013895) Loss: 0.18258 (0.17351) +2025-09-14,11:58:05 | INFO | Train Epoch: 11 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12376 (0.15954) Boundary_loss: 0.013895 (0.013895) Loss: 0.13766 (0.17343) +2025-09-14,11:58:36 | INFO | Train Epoch: 11 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.20775 (0.15964) Boundary_loss: 0.013895 (0.013895) Loss: 0.22165 (0.17354) +2025-09-14,11:59:07 | INFO | Train Epoch: 11 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15249 (0.15962) Boundary_loss: 0.013895 (0.013895) Loss: 0.16638 (0.17352) +2025-09-14,11:59:38 | INFO | Train Epoch: 11 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.15096 (0.15961) Boundary_loss: 0.013894 (0.013895) Loss: 0.16486 (0.17350) +2025-09-14,12:00:08 | INFO | Train Epoch: 11 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15016 (0.15959) Boundary_loss: 0.013895 (0.013895) Loss: 0.16405 (0.17348) +2025-09-14,12:00:39 | INFO | Train Epoch: 11 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15192 (0.15957) Boundary_loss: 0.013896 (0.013895) Loss: 0.16582 (0.17346) +2025-09-14,12:01:10 | INFO | Train Epoch: 11 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.18171 (0.15962) Boundary_loss: 0.013894 (0.013895) Loss: 0.19561 (0.17351) +2025-09-14,12:01:41 | INFO | Train Epoch: 11 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16109 (0.15962) Boundary_loss: 0.013896 (0.013895) Loss: 0.17498 (0.17351) +2025-09-14,12:02:12 | INFO | Train Epoch: 11 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11602 (0.15953) Boundary_loss: 0.013895 (0.013895) Loss: 0.12992 (0.17342) +2025-09-14,12:02:42 | INFO | Train Epoch: 11 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14773 (0.15950) Boundary_loss: 0.013895 (0.013895) Loss: 0.16162 (0.17340) +2025-09-14,12:03:12 | INFO | Train Epoch: 11 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.20064 (0.15959) Boundary_loss: 0.013895 (0.013895) Loss: 0.21453 (0.17348) +2025-09-14,12:03:43 | INFO | Train Epoch: 11 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.19196 (0.15966) Boundary_loss: 0.013896 (0.013895) Loss: 0.20586 (0.17355) +2025-09-14,12:04:14 | INFO | Train Epoch: 11 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.20491 (0.15975) Boundary_loss: 0.013894 (0.013895) Loss: 0.21881 (0.17365) +2025-09-14,12:04:44 | INFO | Train Epoch: 11 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.15150 (0.15974) Boundary_loss: 0.013894 (0.013895) Loss: 0.16540 (0.17363) +2025-09-14,12:05:15 | INFO | Train Epoch: 11 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13104 (0.15968) Boundary_loss: 0.013895 (0.013895) Loss: 0.14493 (0.17357) +2025-09-14,12:05:46 | INFO | Train Epoch: 11 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15362 (0.15966) Boundary_loss: 0.013894 (0.013895) Loss: 0.16751 (0.17356) +2025-09-14,12:06:17 | INFO | Train Epoch: 11 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.16635 (0.15968) Boundary_loss: 0.013895 (0.013895) Loss: 0.18025 (0.17357) +2025-09-14,12:06:48 | INFO | Train Epoch: 11 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14821 (0.15965) Boundary_loss: 0.013895 (0.013895) Loss: 0.16210 (0.17355) +2025-09-14,12:07:19 | INFO | Train Epoch: 11 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.17222 (0.15968) Boundary_loss: 0.013894 (0.013895) Loss: 0.18611 (0.17357) +2025-09-14,12:07:50 | INFO | Train Epoch: 11 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11471 (0.15959) Boundary_loss: 0.013894 (0.013895) Loss: 0.12861 (0.17348) +2025-09-14,12:08:20 | INFO | Train Epoch: 11 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.16477 (0.15960) Boundary_loss: 0.013894 (0.013895) Loss: 0.17866 (0.17349) +2025-09-14,12:08:51 | INFO | Train Epoch: 11 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.18979 (0.15966) Boundary_loss: 0.013897 (0.013895) Loss: 0.20369 (0.17355) +2025-09-14,12:09:22 | INFO | Train Epoch: 11 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.17499 (0.15969) Boundary_loss: 0.013894 (0.013895) Loss: 0.18888 (0.17359) +2025-09-14,12:09:53 | INFO | Train Epoch: 11 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10652 (0.15958) Boundary_loss: 0.013895 (0.013895) Loss: 0.12042 (0.17348) +2025-09-14,12:10:23 | INFO | Train Epoch: 11 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.17190 (0.15961) Boundary_loss: 0.013895 (0.013895) Loss: 0.18580 (0.17350) +2025-09-14,12:10:54 | INFO | Train Epoch: 11 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.20028 (0.15969) Boundary_loss: 0.013895 (0.013895) Loss: 0.21418 (0.17358) +2025-09-14,12:11:25 | INFO | Train Epoch: 11 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11614 (0.15960) Boundary_loss: 0.013895 (0.013895) Loss: 0.13003 (0.17350) +2025-09-14,12:11:56 | INFO | Train Epoch: 11 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14544 (0.15957) Boundary_loss: 0.013895 (0.013895) Loss: 0.15934 (0.17347) +2025-09-14,12:12:27 | INFO | Train Epoch: 11 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11816 (0.15949) Boundary_loss: 0.013895 (0.013895) Loss: 0.13206 (0.17338) +2025-09-14,12:12:57 | INFO | Train Epoch: 11 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15757 (0.15948) Boundary_loss: 0.013895 (0.013895) Loss: 0.17147 (0.17338) +2025-09-14,12:13:28 | INFO | Train Epoch: 11 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13490 (0.15943) Boundary_loss: 0.013895 (0.013895) Loss: 0.14880 (0.17333) +2025-09-14,12:13:59 | INFO | Train Epoch: 11 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14100 (0.15939) Boundary_loss: 0.013895 (0.013895) Loss: 0.15490 (0.17329) +2025-09-14,12:14:30 | INFO | Train Epoch: 11 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10540 (0.15928) Boundary_loss: 0.013895 (0.013895) Loss: 0.11930 (0.17318) +2025-09-14,12:15:00 | INFO | Train Epoch: 11 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.16448 (0.15929) Boundary_loss: 0.013896 (0.013895) Loss: 0.17837 (0.17319) +2025-09-14,12:15:31 | INFO | Train Epoch: 11 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17984 (0.15934) Boundary_loss: 0.013894 (0.013895) Loss: 0.19374 (0.17323) +2025-09-14,12:16:02 | INFO | Train Epoch: 11 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.17359 (0.15937) Boundary_loss: 0.013895 (0.013895) Loss: 0.18748 (0.17326) +2025-09-14,12:16:33 | INFO | Train Epoch: 11 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15792 (0.15936) Boundary_loss: 0.013895 (0.013895) Loss: 0.17182 (0.17326) +2025-09-14,12:17:03 | INFO | Train Epoch: 11 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16175 (0.15937) Boundary_loss: 0.013894 (0.013895) Loss: 0.17564 (0.17326) +2025-09-14,12:17:34 | INFO | Train Epoch: 11 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.14104 (0.15933) Boundary_loss: 0.013896 (0.013895) Loss: 0.15494 (0.17323) +2025-09-14,12:18:05 | INFO | Train Epoch: 11 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.16509 (0.15934) Boundary_loss: 0.013894 (0.013895) Loss: 0.17898 (0.17324) +2025-09-14,12:18:36 | INFO | Train Epoch: 11 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.12547 (0.15927) Boundary_loss: 0.013897 (0.013895) Loss: 0.13937 (0.17317) +2025-09-14,12:19:06 | INFO | Train Epoch: 11 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.17163 (0.15930) Boundary_loss: 0.013894 (0.013895) Loss: 0.18553 (0.17319) +2025-09-14,12:19:37 | INFO | Train Epoch: 11 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15787 (0.15930) Boundary_loss: 0.013896 (0.013895) Loss: 0.17177 (0.17319) +2025-09-14,12:20:08 | INFO | Train Epoch: 11 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16093 (0.15930) Boundary_loss: 0.013894 (0.013895) Loss: 0.17483 (0.17319) +2025-09-14,12:20:39 | INFO | Train Epoch: 11 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14478 (0.15927) Boundary_loss: 0.013895 (0.013895) Loss: 0.15867 (0.17317) +2025-09-14,12:21:10 | INFO | Train Epoch: 11 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14114 (0.15923) Boundary_loss: 0.013896 (0.013895) Loss: 0.15504 (0.17313) +2025-09-14,12:21:40 | INFO | Train Epoch: 11 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12747 (0.15917) Boundary_loss: 0.013895 (0.013895) Loss: 0.14136 (0.17307) +2025-09-14,12:22:11 | INFO | Train Epoch: 11 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.14717 (0.15915) Boundary_loss: 0.013895 (0.013895) Loss: 0.16107 (0.17304) +2025-09-14,12:22:42 | INFO | Train Epoch: 11 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16557 (0.15916) Boundary_loss: 0.013896 (0.013895) Loss: 0.17947 (0.17306) +2025-09-14,12:23:13 | INFO | Train Epoch: 11 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14674 (0.15914) Boundary_loss: 0.013895 (0.013895) Loss: 0.16063 (0.17303) +2025-09-14,12:23:43 | INFO | Train Epoch: 11 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.18930 (0.15920) Boundary_loss: 0.013895 (0.013895) Loss: 0.20320 (0.17309) +2025-09-14,12:24:14 | INFO | Train Epoch: 11 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15558 (0.15919) Boundary_loss: 0.013896 (0.013895) Loss: 0.16948 (0.17308) +2025-09-14,12:24:45 | INFO | Train Epoch: 11 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13963 (0.15915) Boundary_loss: 0.013895 (0.013895) Loss: 0.15353 (0.17304) +2025-09-14,12:25:16 | INFO | Train Epoch: 11 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.20681 (0.15924) Boundary_loss: 0.013895 (0.013895) Loss: 0.22070 (0.17314) +2025-09-14,12:25:47 | INFO | Train Epoch: 11 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15732 (0.15924) Boundary_loss: 0.013895 (0.013895) Loss: 0.17121 (0.17313) +2025-09-14,12:26:17 | INFO | Train Epoch: 11 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12654 (0.15918) Boundary_loss: 0.013895 (0.013895) Loss: 0.14043 (0.17307) +2025-09-14,12:26:48 | INFO | Train Epoch: 11 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10537 (0.15907) Boundary_loss: 0.013895 (0.013895) Loss: 0.11927 (0.17297) +2025-09-14,12:27:17 | INFO | Train Epoch: 11 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11630 (0.15899) Boundary_loss: 0.013895 (0.013895) Loss: 0.13020 (0.17288) +2025-09-14,12:27:17 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,12:27:17 | INFO | [Epoch 11] Average Step Time: 0.310s | Average GPU Memory: 25.2 GB +2025-09-14,12:27:17 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,12:27:17 | INFO | Starting zero-shot imagenet. +2025-09-14,12:27:17 | INFO | Building zero-shot classifier +2025-09-14,12:27:23 | INFO | Using classifier +2025-09-14,12:28:01 | INFO | Finished zero-shot imagenet. +2025-09-14,12:28:01 | INFO | Eval Epoch: 12 imagenet-zeroshot-val-top1: 0.3008 imagenet-zeroshot-val-top5: 0.5623 +2025-09-14,12:28:02 | INFO | Start epoch 12 +2025-09-14,12:28:04 | INFO | Train Epoch: 12 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11279 (0.11279) Boundary_loss: 0.013894 (0.013894) Loss: 0.12669 (0.12669) +2025-09-14,12:28:34 | INFO | Train Epoch: 12 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.087528 (0.10016) Boundary_loss: 0.013894 (0.013894) Loss: 0.10142 (0.11405) +2025-09-14,12:29:05 | INFO | Train Epoch: 12 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10125 (0.10052) Boundary_loss: 0.013894 (0.013894) Loss: 0.11514 (0.11442) +2025-09-14,12:29:35 | INFO | Train Epoch: 12 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12706 (0.10716) Boundary_loss: 0.013895 (0.013895) Loss: 0.14096 (0.12105) +2025-09-14,12:30:06 | INFO | Train Epoch: 12 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11552 (0.10883) Boundary_loss: 0.013895 (0.013895) Loss: 0.12942 (0.12272) +2025-09-14,12:30:36 | INFO | Train Epoch: 12 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13088 (0.11250) Boundary_loss: 0.013894 (0.013895) Loss: 0.14477 (0.12640) +2025-09-14,12:31:07 | INFO | Train Epoch: 12 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12906 (0.11487) Boundary_loss: 0.013894 (0.013895) Loss: 0.14295 (0.12876) +2025-09-14,12:31:38 | INFO | Train Epoch: 12 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.13851 (0.11782) Boundary_loss: 0.013896 (0.013895) Loss: 0.15241 (0.13172) +2025-09-14,12:32:09 | INFO | Train Epoch: 12 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10009 (0.11585) Boundary_loss: 0.013895 (0.013895) Loss: 0.11399 (0.12975) +2025-09-14,12:32:39 | INFO | Train Epoch: 12 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12143 (0.11641) Boundary_loss: 0.013896 (0.013895) Loss: 0.13533 (0.13031) +2025-09-14,12:33:10 | INFO | Train Epoch: 12 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.098924 (0.11482) Boundary_loss: 0.013894 (0.013895) Loss: 0.11282 (0.12872) +2025-09-14,12:33:41 | INFO | Train Epoch: 12 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13453 (0.11646) Boundary_loss: 0.013894 (0.013895) Loss: 0.14842 (0.13036) +2025-09-14,12:34:12 | INFO | Train Epoch: 12 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14463 (0.11863) Boundary_loss: 0.013895 (0.013895) Loss: 0.15853 (0.13253) +2025-09-14,12:34:42 | INFO | Train Epoch: 12 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11610 (0.11845) Boundary_loss: 0.013895 (0.013895) Loss: 0.12999 (0.13234) +2025-09-14,12:35:13 | INFO | Train Epoch: 12 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13636 (0.11964) Boundary_loss: 0.013895 (0.013895) Loss: 0.15025 (0.13354) +2025-09-14,12:35:44 | INFO | Train Epoch: 12 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11595 (0.11941) Boundary_loss: 0.013896 (0.013895) Loss: 0.12985 (0.13331) +2025-09-14,12:36:15 | INFO | Train Epoch: 12 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10916 (0.11881) Boundary_loss: 0.013895 (0.013895) Loss: 0.12306 (0.13270) +2025-09-14,12:36:46 | INFO | Train Epoch: 12 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.12293 (0.11904) Boundary_loss: 0.013896 (0.013895) Loss: 0.13683 (0.13293) +2025-09-14,12:37:16 | INFO | Train Epoch: 12 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15128 (0.12074) Boundary_loss: 0.013895 (0.013895) Loss: 0.16518 (0.13463) +2025-09-14,12:37:47 | INFO | Train Epoch: 12 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.16365 (0.12288) Boundary_loss: 0.013894 (0.013895) Loss: 0.17755 (0.13678) +2025-09-14,12:38:18 | INFO | Train Epoch: 12 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12344 (0.12291) Boundary_loss: 0.013895 (0.013895) Loss: 0.13733 (0.13680) +2025-09-14,12:38:49 | INFO | Train Epoch: 12 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11796 (0.12268) Boundary_loss: 0.013895 (0.013895) Loss: 0.13186 (0.13658) +2025-09-14,12:39:19 | INFO | Train Epoch: 12 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13538 (0.12324) Boundary_loss: 0.013895 (0.013895) Loss: 0.14927 (0.13713) +2025-09-14,12:39:50 | INFO | Train Epoch: 12 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13448 (0.12370) Boundary_loss: 0.013895 (0.013895) Loss: 0.14837 (0.13760) +2025-09-14,12:40:21 | INFO | Train Epoch: 12 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.11594 (0.12339) Boundary_loss: 0.013894 (0.013895) Loss: 0.12984 (0.13729) +2025-09-14,12:40:52 | INFO | Train Epoch: 12 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14609 (0.12427) Boundary_loss: 0.013895 (0.013895) Loss: 0.15998 (0.13816) +2025-09-14,12:41:22 | INFO | Train Epoch: 12 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17364 (0.12609) Boundary_loss: 0.013896 (0.013895) Loss: 0.18754 (0.13999) +2025-09-14,12:41:53 | INFO | Train Epoch: 12 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13758 (0.12650) Boundary_loss: 0.013895 (0.013895) Loss: 0.15147 (0.14040) +2025-09-14,12:42:24 | INFO | Train Epoch: 12 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14234 (0.12705) Boundary_loss: 0.013895 (0.013895) Loss: 0.15623 (0.14095) +2025-09-14,12:42:55 | INFO | Train Epoch: 12 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11615 (0.12669) Boundary_loss: 0.013895 (0.013895) Loss: 0.13004 (0.14058) +2025-09-14,12:43:26 | INFO | Train Epoch: 12 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11336 (0.12626) Boundary_loss: 0.013895 (0.013895) Loss: 0.12725 (0.14015) +2025-09-14,12:43:56 | INFO | Train Epoch: 12 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14032 (0.12670) Boundary_loss: 0.013895 (0.013895) Loss: 0.15421 (0.14059) +2025-09-14,12:44:27 | INFO | Train Epoch: 12 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.087087 (0.12550) Boundary_loss: 0.013895 (0.013895) Loss: 0.10098 (0.13939) +2025-09-14,12:44:58 | INFO | Train Epoch: 12 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15762 (0.12644) Boundary_loss: 0.013895 (0.013895) Loss: 0.17151 (0.14034) +2025-09-14,12:45:29 | INFO | Train Epoch: 12 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11538 (0.12613) Boundary_loss: 0.013895 (0.013895) Loss: 0.12927 (0.14002) +2025-09-14,12:46:00 | INFO | Train Epoch: 12 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12584 (0.12612) Boundary_loss: 0.013896 (0.013895) Loss: 0.13974 (0.14001) +2025-09-14,12:46:30 | INFO | Train Epoch: 12 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.088760 (0.12511) Boundary_loss: 0.013895 (0.013895) Loss: 0.10266 (0.13900) +2025-09-14,12:47:01 | INFO | Train Epoch: 12 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.12807 (0.12519) Boundary_loss: 0.013895 (0.013895) Loss: 0.14197 (0.13908) +2025-09-14,12:47:32 | INFO | Train Epoch: 12 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.13625 (0.12547) Boundary_loss: 0.013895 (0.013895) Loss: 0.15015 (0.13936) +2025-09-14,12:48:02 | INFO | Train Epoch: 12 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10127 (0.12486) Boundary_loss: 0.013894 (0.013895) Loss: 0.11516 (0.13876) +2025-09-14,12:48:33 | INFO | Train Epoch: 12 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.11999 (0.12475) Boundary_loss: 0.013895 (0.013895) Loss: 0.13389 (0.13864) +2025-09-14,12:49:04 | INFO | Train Epoch: 12 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13505 (0.12499) Boundary_loss: 0.013895 (0.013895) Loss: 0.14895 (0.13889) +2025-09-14,12:49:35 | INFO | Train Epoch: 12 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.094576 (0.12428) Boundary_loss: 0.013895 (0.013895) Loss: 0.10847 (0.13818) +2025-09-14,12:50:05 | INFO | Train Epoch: 12 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11907 (0.12417) Boundary_loss: 0.013895 (0.013895) Loss: 0.13297 (0.13806) +2025-09-14,12:50:36 | INFO | Train Epoch: 12 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13397 (0.12438) Boundary_loss: 0.013897 (0.013895) Loss: 0.14787 (0.13828) +2025-09-14,12:51:07 | INFO | Train Epoch: 12 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11638 (0.12421) Boundary_loss: 0.013894 (0.013895) Loss: 0.13028 (0.13810) +2025-09-14,12:51:38 | INFO | Train Epoch: 12 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10566 (0.12381) Boundary_loss: 0.013895 (0.013895) Loss: 0.11955 (0.13771) +2025-09-14,12:52:08 | INFO | Train Epoch: 12 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15985 (0.12457) Boundary_loss: 0.013894 (0.013895) Loss: 0.17374 (0.13846) +2025-09-14,12:52:39 | INFO | Train Epoch: 12 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.090557 (0.12387) Boundary_loss: 0.013896 (0.013895) Loss: 0.10445 (0.13777) +2025-09-14,12:53:10 | INFO | Train Epoch: 12 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.12911 (0.12398) Boundary_loss: 0.013894 (0.013895) Loss: 0.14301 (0.13787) +2025-09-14,12:53:41 | INFO | Train Epoch: 12 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15113 (0.12451) Boundary_loss: 0.013896 (0.013895) Loss: 0.16502 (0.13840) +2025-09-14,12:54:12 | INFO | Train Epoch: 12 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11284 (0.12428) Boundary_loss: 0.013895 (0.013895) Loss: 0.12674 (0.13818) +2025-09-14,12:54:42 | INFO | Train Epoch: 12 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.15012 (0.12477) Boundary_loss: 0.013894 (0.013895) Loss: 0.16402 (0.13867) +2025-09-14,12:55:13 | INFO | Train Epoch: 12 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11882 (0.12466) Boundary_loss: 0.013896 (0.013895) Loss: 0.13271 (0.13856) +2025-09-14,12:55:44 | INFO | Train Epoch: 12 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13190 (0.12479) Boundary_loss: 0.013894 (0.013895) Loss: 0.14580 (0.13869) +2025-09-14,12:56:15 | INFO | Train Epoch: 12 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11514 (0.12462) Boundary_loss: 0.013895 (0.013895) Loss: 0.12904 (0.13852) +2025-09-14,12:56:46 | INFO | Train Epoch: 12 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14147 (0.12492) Boundary_loss: 0.013896 (0.013895) Loss: 0.15536 (0.13881) +2025-09-14,12:57:16 | INFO | Train Epoch: 12 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11600 (0.12476) Boundary_loss: 0.013896 (0.013895) Loss: 0.12990 (0.13866) +2025-09-14,12:57:47 | INFO | Train Epoch: 12 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17389 (0.12560) Boundary_loss: 0.013894 (0.013895) Loss: 0.18779 (0.13949) +2025-09-14,12:58:18 | INFO | Train Epoch: 12 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.17244 (0.12638) Boundary_loss: 0.013895 (0.013895) Loss: 0.18633 (0.14027) +2025-09-14,12:58:49 | INFO | Train Epoch: 12 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10729 (0.12606) Boundary_loss: 0.013894 (0.013895) Loss: 0.12118 (0.13996) +2025-09-14,12:59:20 | INFO | Train Epoch: 12 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11996 (0.12596) Boundary_loss: 0.013895 (0.013895) Loss: 0.13385 (0.13986) +2025-09-14,12:59:50 | INFO | Train Epoch: 12 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.12962 (0.12602) Boundary_loss: 0.013894 (0.013895) Loss: 0.14351 (0.13992) +2025-09-14,13:00:21 | INFO | Train Epoch: 12 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13495 (0.12616) Boundary_loss: 0.013895 (0.013895) Loss: 0.14885 (0.14006) +2025-09-14,13:00:52 | INFO | Train Epoch: 12 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.15054 (0.12654) Boundary_loss: 0.013895 (0.013895) Loss: 0.16443 (0.14043) +2025-09-14,13:01:23 | INFO | Train Epoch: 12 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.12076 (0.12645) Boundary_loss: 0.013896 (0.013895) Loss: 0.13466 (0.14034) +2025-09-14,13:01:54 | INFO | Train Epoch: 12 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.099051 (0.12604) Boundary_loss: 0.013894 (0.013895) Loss: 0.11294 (0.13994) +2025-09-14,13:02:25 | INFO | Train Epoch: 12 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11404 (0.12586) Boundary_loss: 0.013895 (0.013895) Loss: 0.12794 (0.13976) +2025-09-14,13:02:56 | INFO | Train Epoch: 12 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11045 (0.12564) Boundary_loss: 0.013895 (0.013895) Loss: 0.12435 (0.13954) +2025-09-14,13:03:27 | INFO | Train Epoch: 12 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15202 (0.12602) Boundary_loss: 0.013897 (0.013895) Loss: 0.16592 (0.13991) +2025-09-14,13:03:58 | INFO | Train Epoch: 12 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11172 (0.12582) Boundary_loss: 0.013895 (0.013895) Loss: 0.12561 (0.13971) +2025-09-14,13:04:28 | INFO | Train Epoch: 12 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.17869 (0.12655) Boundary_loss: 0.013894 (0.013895) Loss: 0.19258 (0.14045) +2025-09-14,13:04:59 | INFO | Train Epoch: 12 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11662 (0.12641) Boundary_loss: 0.013895 (0.013895) Loss: 0.13051 (0.14031) +2025-09-14,13:05:30 | INFO | Train Epoch: 12 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11366 (0.12624) Boundary_loss: 0.013895 (0.013895) Loss: 0.12755 (0.14014) +2025-09-14,13:06:01 | INFO | Train Epoch: 12 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11641 (0.12611) Boundary_loss: 0.013894 (0.013895) Loss: 0.13030 (0.14001) +2025-09-14,13:06:32 | INFO | Train Epoch: 12 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12992 (0.12616) Boundary_loss: 0.013895 (0.013895) Loss: 0.14382 (0.14006) +2025-09-14,13:07:02 | INFO | Train Epoch: 12 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.090525 (0.12570) Boundary_loss: 0.013895 (0.013895) Loss: 0.10442 (0.13959) +2025-09-14,13:07:33 | INFO | Train Epoch: 12 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.14729 (0.12598) Boundary_loss: 0.013894 (0.013895) Loss: 0.16119 (0.13987) +2025-09-14,13:08:04 | INFO | Train Epoch: 12 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12579 (0.12597) Boundary_loss: 0.013895 (0.013895) Loss: 0.13969 (0.13987) +2025-09-14,13:08:35 | INFO | Train Epoch: 12 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.087318 (0.12549) Boundary_loss: 0.013896 (0.013895) Loss: 0.10121 (0.13938) +2025-09-14,13:09:05 | INFO | Train Epoch: 12 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.13473 (0.12560) Boundary_loss: 0.013895 (0.013895) Loss: 0.14863 (0.13950) +2025-09-14,13:09:36 | INFO | Train Epoch: 12 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.18294 (0.12630) Boundary_loss: 0.013895 (0.013895) Loss: 0.19683 (0.14020) +2025-09-14,13:10:07 | INFO | Train Epoch: 12 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.16932 (0.12682) Boundary_loss: 0.013894 (0.013895) Loss: 0.18321 (0.14072) +2025-09-14,13:10:38 | INFO | Train Epoch: 12 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.095365 (0.12645) Boundary_loss: 0.013895 (0.013895) Loss: 0.10926 (0.14034) +2025-09-14,13:11:08 | INFO | Train Epoch: 12 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11754 (0.12634) Boundary_loss: 0.013895 (0.013895) Loss: 0.13144 (0.14024) +2025-09-14,13:11:39 | INFO | Train Epoch: 12 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.14266 (0.12653) Boundary_loss: 0.013897 (0.013895) Loss: 0.15656 (0.14043) +2025-09-14,13:12:10 | INFO | Train Epoch: 12 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15491 (0.12686) Boundary_loss: 0.013894 (0.013895) Loss: 0.16881 (0.14075) +2025-09-14,13:12:41 | INFO | Train Epoch: 12 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14867 (0.12711) Boundary_loss: 0.013894 (0.013895) Loss: 0.16257 (0.14100) +2025-09-14,13:13:11 | INFO | Train Epoch: 12 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.10110 (0.12681) Boundary_loss: 0.013894 (0.013895) Loss: 0.11499 (0.14071) +2025-09-14,13:13:42 | INFO | Train Epoch: 12 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.091321 (0.12642) Boundary_loss: 0.013894 (0.013895) Loss: 0.10522 (0.14031) +2025-09-14,13:14:13 | INFO | Train Epoch: 12 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11670 (0.12631) Boundary_loss: 0.013895 (0.013895) Loss: 0.13060 (0.14021) +2025-09-14,13:14:44 | INFO | Train Epoch: 12 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12443 (0.12629) Boundary_loss: 0.013894 (0.013895) Loss: 0.13833 (0.14019) +2025-09-14,13:15:14 | INFO | Train Epoch: 12 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10707 (0.12609) Boundary_loss: 0.013895 (0.013895) Loss: 0.12096 (0.13998) +2025-09-14,13:15:45 | INFO | Train Epoch: 12 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.10243 (0.12583) Boundary_loss: 0.013894 (0.013895) Loss: 0.11633 (0.13973) +2025-09-14,13:16:16 | INFO | Train Epoch: 12 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16916 (0.12629) Boundary_loss: 0.013894 (0.013895) Loss: 0.18305 (0.14018) +2025-09-14,13:16:47 | INFO | Train Epoch: 12 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12061 (0.12623) Boundary_loss: 0.013894 (0.013895) Loss: 0.13450 (0.14013) +2025-09-14,13:17:18 | INFO | Train Epoch: 12 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.090562 (0.12586) Boundary_loss: 0.013895 (0.013895) Loss: 0.10446 (0.13976) +2025-09-14,13:17:48 | INFO | Train Epoch: 12 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.16205 (0.12623) Boundary_loss: 0.013895 (0.013895) Loss: 0.17595 (0.14013) +2025-09-14,13:18:19 | INFO | Train Epoch: 12 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14729 (0.12644) Boundary_loss: 0.013896 (0.013895) Loss: 0.16118 (0.14034) +2025-09-14,13:18:50 | INFO | Train Epoch: 12 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12261 (0.12641) Boundary_loss: 0.013895 (0.013895) Loss: 0.13651 (0.14030) +2025-09-14,13:19:21 | INFO | Train Epoch: 12 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21060 (0.12724) Boundary_loss: 0.013895 (0.013895) Loss: 0.22449 (0.14114) +2025-09-14,13:19:51 | INFO | Train Epoch: 12 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15994 (0.12756) Boundary_loss: 0.013895 (0.013895) Loss: 0.17384 (0.14146) +2025-09-14,13:20:22 | INFO | Train Epoch: 12 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14559 (0.12774) Boundary_loss: 0.013894 (0.013895) Loss: 0.15948 (0.14163) +2025-09-14,13:20:53 | INFO | Train Epoch: 12 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.098564 (0.12746) Boundary_loss: 0.013896 (0.013895) Loss: 0.11246 (0.14135) +2025-09-14,13:21:24 | INFO | Train Epoch: 12 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13026 (0.12748) Boundary_loss: 0.013894 (0.013895) Loss: 0.14415 (0.14138) +2025-09-14,13:21:55 | INFO | Train Epoch: 12 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16086 (0.12780) Boundary_loss: 0.013895 (0.013895) Loss: 0.17475 (0.14169) +2025-09-14,13:22:26 | INFO | Train Epoch: 12 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10749 (0.12761) Boundary_loss: 0.013895 (0.013895) Loss: 0.12138 (0.14150) +2025-09-14,13:22:56 | INFO | Train Epoch: 12 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.099169 (0.12734) Boundary_loss: 0.013894 (0.013895) Loss: 0.11306 (0.14124) +2025-09-14,13:23:27 | INFO | Train Epoch: 12 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12495 (0.12732) Boundary_loss: 0.013896 (0.013895) Loss: 0.13884 (0.14122) +2025-09-14,13:23:57 | INFO | Train Epoch: 12 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.15284 (0.12755) Boundary_loss: 0.013895 (0.013895) Loss: 0.16673 (0.14145) +2025-09-14,13:24:28 | INFO | Train Epoch: 12 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11273 (0.12742) Boundary_loss: 0.013896 (0.013895) Loss: 0.12662 (0.14132) +2025-09-14,13:24:59 | INFO | Train Epoch: 12 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11328 (0.12729) Boundary_loss: 0.013896 (0.013895) Loss: 0.12718 (0.14119) +2025-09-14,13:25:29 | INFO | Train Epoch: 12 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14145 (0.12742) Boundary_loss: 0.013896 (0.013895) Loss: 0.15534 (0.14131) +2025-09-14,13:26:00 | INFO | Train Epoch: 12 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.12384 (0.12739) Boundary_loss: 0.013897 (0.013895) Loss: 0.13773 (0.14128) +2025-09-14,13:26:30 | INFO | Train Epoch: 12 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13843 (0.12748) Boundary_loss: 0.013895 (0.013895) Loss: 0.15233 (0.14138) +2025-09-14,13:27:01 | INFO | Train Epoch: 12 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13670 (0.12756) Boundary_loss: 0.013896 (0.013895) Loss: 0.15059 (0.14146) +2025-09-14,13:27:32 | INFO | Train Epoch: 12 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14102 (0.12768) Boundary_loss: 0.013895 (0.013895) Loss: 0.15491 (0.14157) +2025-09-14,13:28:02 | INFO | Train Epoch: 12 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16524 (0.12800) Boundary_loss: 0.013895 (0.013895) Loss: 0.17913 (0.14189) +2025-09-14,13:28:33 | INFO | Train Epoch: 12 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13028 (0.12802) Boundary_loss: 0.013894 (0.013895) Loss: 0.14417 (0.14191) +2025-09-14,13:29:04 | INFO | Train Epoch: 12 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15160 (0.12821) Boundary_loss: 0.013895 (0.013895) Loss: 0.16550 (0.14211) +2025-09-14,13:29:35 | INFO | Train Epoch: 12 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12576 (0.12819) Boundary_loss: 0.013896 (0.013895) Loss: 0.13966 (0.14209) +2025-09-14,13:30:05 | INFO | Train Epoch: 12 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13544 (0.12825) Boundary_loss: 0.013895 (0.013895) Loss: 0.14933 (0.14215) +2025-09-14,13:30:36 | INFO | Train Epoch: 12 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.18000 (0.12867) Boundary_loss: 0.013895 (0.013895) Loss: 0.19390 (0.14257) +2025-09-14,13:31:07 | INFO | Train Epoch: 12 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10738 (0.12850) Boundary_loss: 0.013895 (0.013895) Loss: 0.12128 (0.14240) +2025-09-14,13:31:37 | INFO | Train Epoch: 12 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12780 (0.12849) Boundary_loss: 0.013897 (0.013895) Loss: 0.14170 (0.14239) +2025-09-14,13:32:08 | INFO | Train Epoch: 12 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14677 (0.12864) Boundary_loss: 0.013895 (0.013895) Loss: 0.16066 (0.14253) +2025-09-14,13:32:39 | INFO | Train Epoch: 12 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12614 (0.12862) Boundary_loss: 0.013895 (0.013895) Loss: 0.14003 (0.14252) +2025-09-14,13:33:10 | INFO | Train Epoch: 12 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10742 (0.12845) Boundary_loss: 0.013895 (0.013895) Loss: 0.12131 (0.14235) +2025-09-14,13:33:40 | INFO | Train Epoch: 12 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.087360 (0.12814) Boundary_loss: 0.013896 (0.013895) Loss: 0.10126 (0.14203) +2025-09-14,13:34:11 | INFO | Train Epoch: 12 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12937 (0.12815) Boundary_loss: 0.013895 (0.013895) Loss: 0.14326 (0.14204) +2025-09-14,13:34:42 | INFO | Train Epoch: 12 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12406 (0.12811) Boundary_loss: 0.013894 (0.013895) Loss: 0.13795 (0.14201) +2025-09-14,13:35:13 | INFO | Train Epoch: 12 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12457 (0.12809) Boundary_loss: 0.013896 (0.013895) Loss: 0.13847 (0.14198) +2025-09-14,13:35:43 | INFO | Train Epoch: 12 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11132 (0.12796) Boundary_loss: 0.013895 (0.013895) Loss: 0.12522 (0.14186) +2025-09-14,13:36:14 | INFO | Train Epoch: 12 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10582 (0.12780) Boundary_loss: 0.013895 (0.013895) Loss: 0.11971 (0.14169) +2025-09-14,13:36:45 | INFO | Train Epoch: 12 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12778 (0.12780) Boundary_loss: 0.013895 (0.013895) Loss: 0.14168 (0.14169) +2025-09-14,13:37:16 | INFO | Train Epoch: 12 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10468 (0.12763) Boundary_loss: 0.013894 (0.013895) Loss: 0.11858 (0.14152) +2025-09-14,13:37:46 | INFO | Train Epoch: 12 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13817 (0.12770) Boundary_loss: 0.013895 (0.013895) Loss: 0.15207 (0.14160) +2025-09-14,13:38:17 | INFO | Train Epoch: 12 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12618 (0.12769) Boundary_loss: 0.013895 (0.013895) Loss: 0.14007 (0.14159) +2025-09-14,13:38:47 | INFO | Train Epoch: 12 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13126 (0.12772) Boundary_loss: 0.013895 (0.013895) Loss: 0.14515 (0.14161) +2025-09-14,13:39:18 | INFO | Train Epoch: 12 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10028 (0.12752) Boundary_loss: 0.013895 (0.013895) Loss: 0.11417 (0.14142) +2025-09-14,13:39:49 | INFO | Train Epoch: 12 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.096132 (0.12730) Boundary_loss: 0.013894 (0.013895) Loss: 0.11003 (0.14119) +2025-09-14,13:40:20 | INFO | Train Epoch: 12 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.097740 (0.12709) Boundary_loss: 0.013894 (0.013895) Loss: 0.11163 (0.14099) +2025-09-14,13:40:51 | INFO | Train Epoch: 12 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10793 (0.12696) Boundary_loss: 0.013895 (0.013895) Loss: 0.12183 (0.14085) +2025-09-14,13:41:21 | INFO | Train Epoch: 12 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15499 (0.12715) Boundary_loss: 0.013895 (0.013895) Loss: 0.16888 (0.14105) +2025-09-14,13:41:52 | INFO | Train Epoch: 12 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13185 (0.12718) Boundary_loss: 0.013895 (0.013895) Loss: 0.14574 (0.14108) +2025-09-14,13:42:23 | INFO | Train Epoch: 12 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13886 (0.12726) Boundary_loss: 0.013894 (0.013895) Loss: 0.15275 (0.14116) +2025-09-14,13:42:54 | INFO | Train Epoch: 12 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11810 (0.12720) Boundary_loss: 0.013896 (0.013895) Loss: 0.13199 (0.14110) +2025-09-14,13:43:25 | INFO | Train Epoch: 12 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18007 (0.12756) Boundary_loss: 0.013895 (0.013895) Loss: 0.19396 (0.14145) +2025-09-14,13:43:55 | INFO | Train Epoch: 12 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10525 (0.12741) Boundary_loss: 0.013894 (0.013895) Loss: 0.11915 (0.14130) +2025-09-14,13:44:26 | INFO | Train Epoch: 12 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13942 (0.12749) Boundary_loss: 0.013894 (0.013895) Loss: 0.15331 (0.14138) +2025-09-14,13:44:57 | INFO | Train Epoch: 12 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.098047 (0.12729) Boundary_loss: 0.013895 (0.013895) Loss: 0.11194 (0.14119) +2025-09-14,13:45:27 | INFO | Train Epoch: 12 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14155 (0.12739) Boundary_loss: 0.013895 (0.013895) Loss: 0.15545 (0.14128) +2025-09-14,13:45:58 | INFO | Train Epoch: 12 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.18715 (0.12778) Boundary_loss: 0.013894 (0.013895) Loss: 0.20104 (0.14167) +2025-09-14,13:46:29 | INFO | Train Epoch: 12 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10699 (0.12764) Boundary_loss: 0.013895 (0.013895) Loss: 0.12088 (0.14154) +2025-09-14,13:47:00 | INFO | Train Epoch: 12 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13798 (0.12771) Boundary_loss: 0.013895 (0.013895) Loss: 0.15187 (0.14161) +2025-09-14,13:47:31 | INFO | Train Epoch: 12 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14034 (0.12779) Boundary_loss: 0.013894 (0.013895) Loss: 0.15423 (0.14169) +2025-09-14,13:48:01 | INFO | Train Epoch: 12 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.16206 (0.12801) Boundary_loss: 0.013895 (0.013895) Loss: 0.17596 (0.14190) +2025-09-14,13:48:32 | INFO | Train Epoch: 12 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13288 (0.12804) Boundary_loss: 0.013895 (0.013895) Loss: 0.14677 (0.14194) +2025-09-14,13:49:03 | INFO | Train Epoch: 12 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12242 (0.12800) Boundary_loss: 0.013896 (0.013895) Loss: 0.13631 (0.14190) +2025-09-14,13:49:34 | INFO | Train Epoch: 12 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11139 (0.12790) Boundary_loss: 0.013895 (0.013895) Loss: 0.12528 (0.14180) +2025-09-14,13:50:04 | INFO | Train Epoch: 12 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11264 (0.12781) Boundary_loss: 0.013895 (0.013895) Loss: 0.12653 (0.14170) +2025-09-14,13:50:35 | INFO | Train Epoch: 12 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11458 (0.12772) Boundary_loss: 0.013895 (0.013895) Loss: 0.12848 (0.14162) +2025-09-14,13:51:06 | INFO | Train Epoch: 12 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11680 (0.12766) Boundary_loss: 0.013894 (0.013895) Loss: 0.13070 (0.14155) +2025-09-14,13:51:36 | INFO | Train Epoch: 12 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12252 (0.12763) Boundary_loss: 0.013895 (0.013895) Loss: 0.13642 (0.14152) +2025-09-14,13:52:07 | INFO | Train Epoch: 12 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13366 (0.12766) Boundary_loss: 0.013894 (0.013895) Loss: 0.14755 (0.14156) +2025-09-14,13:52:38 | INFO | Train Epoch: 12 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11746 (0.12760) Boundary_loss: 0.013894 (0.013895) Loss: 0.13136 (0.14150) +2025-09-14,13:53:09 | INFO | Train Epoch: 12 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13709 (0.12766) Boundary_loss: 0.013895 (0.013895) Loss: 0.15099 (0.14155) +2025-09-14,13:53:39 | INFO | Train Epoch: 12 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10507 (0.12752) Boundary_loss: 0.013895 (0.013895) Loss: 0.11896 (0.14142) +2025-09-14,13:54:10 | INFO | Train Epoch: 12 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.13542 (0.12757) Boundary_loss: 0.013894 (0.013895) Loss: 0.14931 (0.14147) +2025-09-14,13:54:41 | INFO | Train Epoch: 12 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.18733 (0.12792) Boundary_loss: 0.013895 (0.013895) Loss: 0.20122 (0.14182) +2025-09-14,13:55:11 | INFO | Train Epoch: 12 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10065 (0.12776) Boundary_loss: 0.013897 (0.013895) Loss: 0.11455 (0.14166) +2025-09-14,13:55:42 | INFO | Train Epoch: 12 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14407 (0.12786) Boundary_loss: 0.013895 (0.013895) Loss: 0.15797 (0.14175) +2025-09-14,13:56:13 | INFO | Train Epoch: 12 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.094524 (0.12766) Boundary_loss: 0.013895 (0.013895) Loss: 0.10842 (0.14156) +2025-09-14,13:56:44 | INFO | Train Epoch: 12 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15032 (0.12779) Boundary_loss: 0.013895 (0.013895) Loss: 0.16422 (0.14169) +2025-09-14,13:57:15 | INFO | Train Epoch: 12 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.14439 (0.12789) Boundary_loss: 0.013895 (0.013895) Loss: 0.15828 (0.14178) +2025-09-14,13:57:45 | INFO | Train Epoch: 12 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.14055 (0.12796) Boundary_loss: 0.013897 (0.013895) Loss: 0.15445 (0.14186) +2025-09-14,13:58:16 | INFO | Train Epoch: 12 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17657 (0.12824) Boundary_loss: 0.013895 (0.013895) Loss: 0.19046 (0.14213) +2025-09-14,13:58:47 | INFO | Train Epoch: 12 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13975 (0.12830) Boundary_loss: 0.013895 (0.013895) Loss: 0.15364 (0.14220) +2025-09-14,13:59:18 | INFO | Train Epoch: 12 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11867 (0.12825) Boundary_loss: 0.013895 (0.013895) Loss: 0.13257 (0.14214) +2025-09-14,13:59:49 | INFO | Train Epoch: 12 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.15234 (0.12838) Boundary_loss: 0.013895 (0.013895) Loss: 0.16624 (0.14228) +2025-09-14,14:00:19 | INFO | Train Epoch: 12 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.098161 (0.12821) Boundary_loss: 0.013895 (0.013895) Loss: 0.11206 (0.14211) +2025-09-14,14:00:50 | INFO | Train Epoch: 12 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12790 (0.12821) Boundary_loss: 0.013895 (0.013895) Loss: 0.14180 (0.14211) +2025-09-14,14:01:21 | INFO | Train Epoch: 12 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.076021 (0.12793) Boundary_loss: 0.013894 (0.013895) Loss: 0.089915 (0.14182) +2025-09-14,14:01:52 | INFO | Train Epoch: 12 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.078354 (0.12766) Boundary_loss: 0.013895 (0.013895) Loss: 0.092249 (0.14155) +2025-09-14,14:02:22 | INFO | Train Epoch: 12 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10602 (0.12754) Boundary_loss: 0.013895 (0.013895) Loss: 0.11991 (0.14144) +2025-09-14,14:02:53 | INFO | Train Epoch: 12 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.14650 (0.12764) Boundary_loss: 0.013894 (0.013895) Loss: 0.16040 (0.14154) +2025-09-14,14:03:23 | INFO | Train Epoch: 12 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11687 (0.12758) Boundary_loss: 0.013895 (0.013895) Loss: 0.13076 (0.14148) +2025-09-14,14:03:54 | INFO | Train Epoch: 12 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10966 (0.12749) Boundary_loss: 0.013895 (0.013895) Loss: 0.12355 (0.14138) +2025-09-14,14:04:25 | INFO | Train Epoch: 12 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14107 (0.12756) Boundary_loss: 0.013895 (0.013895) Loss: 0.15496 (0.14146) +2025-09-14,14:04:55 | INFO | Train Epoch: 12 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10845 (0.12746) Boundary_loss: 0.013895 (0.013895) Loss: 0.12234 (0.14136) +2025-09-14,14:05:26 | INFO | Train Epoch: 12 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12582 (0.12745) Boundary_loss: 0.013894 (0.013895) Loss: 0.13971 (0.14135) +2025-09-14,14:05:56 | INFO | Train Epoch: 12 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11827 (0.12740) Boundary_loss: 0.013895 (0.013895) Loss: 0.13216 (0.14130) +2025-09-14,14:06:27 | INFO | Train Epoch: 12 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12527 (0.12739) Boundary_loss: 0.013896 (0.013895) Loss: 0.13917 (0.14129) +2025-09-14,14:06:58 | INFO | Train Epoch: 12 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12600 (0.12739) Boundary_loss: 0.013896 (0.013895) Loss: 0.13990 (0.14128) +2025-09-14,14:07:28 | INFO | Train Epoch: 12 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.12515 (0.12737) Boundary_loss: 0.013895 (0.013895) Loss: 0.13904 (0.14127) +2025-09-14,14:07:59 | INFO | Train Epoch: 12 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.093840 (0.12720) Boundary_loss: 0.013895 (0.013895) Loss: 0.10773 (0.14110) +2025-09-14,14:08:30 | INFO | Train Epoch: 12 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13863 (0.12726) Boundary_loss: 0.013895 (0.013895) Loss: 0.15252 (0.14116) +2025-09-14,14:09:00 | INFO | Train Epoch: 12 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.12198 (0.12723) Boundary_loss: 0.013896 (0.013895) Loss: 0.13587 (0.14113) +2025-09-14,14:09:31 | INFO | Train Epoch: 12 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13428 (0.12727) Boundary_loss: 0.013896 (0.013895) Loss: 0.14818 (0.14117) +2025-09-14,14:10:02 | INFO | Train Epoch: 12 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.099697 (0.12713) Boundary_loss: 0.013895 (0.013895) Loss: 0.11359 (0.14103) +2025-09-14,14:10:33 | INFO | Train Epoch: 12 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.12222 (0.12711) Boundary_loss: 0.013894 (0.013895) Loss: 0.13612 (0.14100) +2025-09-14,14:11:03 | INFO | Train Epoch: 12 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11472 (0.12705) Boundary_loss: 0.013895 (0.013895) Loss: 0.12862 (0.14094) +2025-09-14,14:11:34 | INFO | Train Epoch: 12 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10741 (0.12695) Boundary_loss: 0.013895 (0.013895) Loss: 0.12130 (0.14084) +2025-09-14,14:12:05 | INFO | Train Epoch: 12 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.14535 (0.12704) Boundary_loss: 0.013894 (0.013895) Loss: 0.15924 (0.14094) +2025-09-14,14:12:36 | INFO | Train Epoch: 12 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11782 (0.12700) Boundary_loss: 0.013895 (0.013895) Loss: 0.13171 (0.14089) +2025-09-14,14:13:06 | INFO | Train Epoch: 12 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13038 (0.12701) Boundary_loss: 0.013895 (0.013895) Loss: 0.14428 (0.14091) +2025-09-14,14:13:37 | INFO | Train Epoch: 12 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.098394 (0.12687) Boundary_loss: 0.013894 (0.013895) Loss: 0.11229 (0.14077) +2025-09-14,14:14:08 | INFO | Train Epoch: 12 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12179 (0.12685) Boundary_loss: 0.013894 (0.013895) Loss: 0.13569 (0.14074) +2025-09-14,14:14:38 | INFO | Train Epoch: 12 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12627 (0.12685) Boundary_loss: 0.013895 (0.013895) Loss: 0.14017 (0.14074) +2025-09-14,14:15:09 | INFO | Train Epoch: 12 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12516 (0.12684) Boundary_loss: 0.013894 (0.013895) Loss: 0.13905 (0.14073) +2025-09-14,14:15:40 | INFO | Train Epoch: 12 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.22151 (0.12729) Boundary_loss: 0.013894 (0.013895) Loss: 0.23541 (0.14118) +2025-09-14,14:16:10 | INFO | Train Epoch: 12 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14104 (0.12735) Boundary_loss: 0.013894 (0.013895) Loss: 0.15493 (0.14125) +2025-09-14,14:16:41 | INFO | Train Epoch: 12 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10954 (0.12727) Boundary_loss: 0.013894 (0.013895) Loss: 0.12344 (0.14116) +2025-09-14,14:17:12 | INFO | Train Epoch: 12 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.13271 (0.12729) Boundary_loss: 0.013894 (0.013895) Loss: 0.14661 (0.14119) +2025-09-14,14:17:42 | INFO | Train Epoch: 12 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13880 (0.12735) Boundary_loss: 0.013894 (0.013895) Loss: 0.15269 (0.14124) +2025-09-14,14:18:13 | INFO | Train Epoch: 12 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11658 (0.12730) Boundary_loss: 0.013895 (0.013895) Loss: 0.13048 (0.14119) +2025-09-14,14:18:43 | INFO | Train Epoch: 12 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.082953 (0.12709) Boundary_loss: 0.013895 (0.013895) Loss: 0.096848 (0.14099) +2025-09-14,14:19:14 | INFO | Train Epoch: 12 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13857 (0.12715) Boundary_loss: 0.013895 (0.013895) Loss: 0.15246 (0.14104) +2025-09-14,14:19:45 | INFO | Train Epoch: 12 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13230 (0.12717) Boundary_loss: 0.013895 (0.013895) Loss: 0.14620 (0.14106) +2025-09-14,14:20:15 | INFO | Train Epoch: 12 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10342 (0.12706) Boundary_loss: 0.013896 (0.013895) Loss: 0.11731 (0.14096) +2025-09-14,14:20:46 | INFO | Train Epoch: 12 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12129 (0.12704) Boundary_loss: 0.013894 (0.013895) Loss: 0.13518 (0.14093) +2025-09-14,14:21:17 | INFO | Train Epoch: 12 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11151 (0.12697) Boundary_loss: 0.013894 (0.013895) Loss: 0.12541 (0.14086) +2025-09-14,14:21:48 | INFO | Train Epoch: 12 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11581 (0.12692) Boundary_loss: 0.013895 (0.013895) Loss: 0.12970 (0.14081) +2025-09-14,14:22:18 | INFO | Train Epoch: 12 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.10370 (0.12681) Boundary_loss: 0.013894 (0.013895) Loss: 0.11760 (0.14071) +2025-09-14,14:22:49 | INFO | Train Epoch: 12 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12165 (0.12679) Boundary_loss: 0.013895 (0.013895) Loss: 0.13554 (0.14068) +2025-09-14,14:23:20 | INFO | Train Epoch: 12 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11083 (0.12672) Boundary_loss: 0.013895 (0.013895) Loss: 0.12472 (0.14061) +2025-09-14,14:23:50 | INFO | Train Epoch: 12 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.15673 (0.12685) Boundary_loss: 0.013894 (0.013895) Loss: 0.17062 (0.14074) +2025-09-14,14:24:21 | INFO | Train Epoch: 12 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12286 (0.12683) Boundary_loss: 0.013896 (0.013895) Loss: 0.13675 (0.14073) +2025-09-14,14:24:52 | INFO | Train Epoch: 12 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.096200 (0.12670) Boundary_loss: 0.013895 (0.013895) Loss: 0.11010 (0.14059) +2025-09-14,14:25:22 | INFO | Train Epoch: 12 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.098135 (0.12657) Boundary_loss: 0.013895 (0.013895) Loss: 0.11203 (0.14047) +2025-09-14,14:25:53 | INFO | Train Epoch: 12 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12462 (0.12657) Boundary_loss: 0.013895 (0.013895) Loss: 0.13851 (0.14046) +2025-09-14,14:26:24 | INFO | Train Epoch: 12 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16190 (0.12672) Boundary_loss: 0.013895 (0.013895) Loss: 0.17579 (0.14061) +2025-09-14,14:26:55 | INFO | Train Epoch: 12 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11380 (0.12666) Boundary_loss: 0.013895 (0.013895) Loss: 0.12769 (0.14056) +2025-09-14,14:27:26 | INFO | Train Epoch: 12 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14581 (0.12674) Boundary_loss: 0.013895 (0.013895) Loss: 0.15970 (0.14064) +2025-09-14,14:27:56 | INFO | Train Epoch: 12 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.15082 (0.12685) Boundary_loss: 0.013895 (0.013895) Loss: 0.16471 (0.14074) +2025-09-14,14:28:27 | INFO | Train Epoch: 12 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.14668 (0.12693) Boundary_loss: 0.013894 (0.013895) Loss: 0.16058 (0.14083) +2025-09-14,14:28:58 | INFO | Train Epoch: 12 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.096971 (0.12680) Boundary_loss: 0.013895 (0.013895) Loss: 0.11087 (0.14070) +2025-09-14,14:29:29 | INFO | Train Epoch: 12 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.16258 (0.12696) Boundary_loss: 0.013895 (0.013895) Loss: 0.17647 (0.14085) +2025-09-14,14:29:59 | INFO | Train Epoch: 12 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13704 (0.12700) Boundary_loss: 0.013895 (0.013895) Loss: 0.15093 (0.14089) +2025-09-14,14:30:30 | INFO | Train Epoch: 12 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.095990 (0.12687) Boundary_loss: 0.013894 (0.013895) Loss: 0.10988 (0.14076) +2025-09-14,14:31:01 | INFO | Train Epoch: 12 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12230 (0.12685) Boundary_loss: 0.013895 (0.013895) Loss: 0.13620 (0.14074) +2025-09-14,14:31:32 | INFO | Train Epoch: 12 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13463 (0.12688) Boundary_loss: 0.013896 (0.013895) Loss: 0.14853 (0.14078) +2025-09-14,14:32:03 | INFO | Train Epoch: 12 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12548 (0.12688) Boundary_loss: 0.013894 (0.013895) Loss: 0.13938 (0.14077) +2025-09-14,14:32:33 | INFO | Train Epoch: 12 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.094740 (0.12674) Boundary_loss: 0.013895 (0.013895) Loss: 0.10863 (0.14064) +2025-09-14,14:33:04 | INFO | Train Epoch: 12 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10407 (0.12665) Boundary_loss: 0.013896 (0.013895) Loss: 0.11796 (0.14055) +2025-09-14,14:33:35 | INFO | Train Epoch: 12 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.17464 (0.12685) Boundary_loss: 0.013896 (0.013895) Loss: 0.18854 (0.14074) +2025-09-14,14:34:06 | INFO | Train Epoch: 12 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10101 (0.12674) Boundary_loss: 0.013895 (0.013895) Loss: 0.11490 (0.14064) +2025-09-14,14:34:37 | INFO | Train Epoch: 12 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13400 (0.12677) Boundary_loss: 0.013894 (0.013895) Loss: 0.14790 (0.14067) +2025-09-14,14:35:08 | INFO | Train Epoch: 12 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13431 (0.12680) Boundary_loss: 0.013894 (0.013895) Loss: 0.14820 (0.14070) +2025-09-14,14:35:39 | INFO | Train Epoch: 12 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13768 (0.12684) Boundary_loss: 0.013896 (0.013895) Loss: 0.15157 (0.14074) +2025-09-14,14:36:10 | INFO | Train Epoch: 12 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10051 (0.12674) Boundary_loss: 0.013894 (0.013895) Loss: 0.11440 (0.14063) +2025-09-14,14:36:40 | INFO | Train Epoch: 12 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13474 (0.12677) Boundary_loss: 0.013895 (0.013895) Loss: 0.14864 (0.14067) +2025-09-14,14:37:11 | INFO | Train Epoch: 12 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11143 (0.12671) Boundary_loss: 0.013895 (0.013895) Loss: 0.12533 (0.14061) +2025-09-14,14:37:42 | INFO | Train Epoch: 12 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12543 (0.12671) Boundary_loss: 0.013896 (0.013895) Loss: 0.13933 (0.14060) +2025-09-14,14:38:13 | INFO | Train Epoch: 12 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.10867 (0.12664) Boundary_loss: 0.013894 (0.013895) Loss: 0.12257 (0.14053) +2025-09-14,14:38:43 | INFO | Train Epoch: 12 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13344 (0.12666) Boundary_loss: 0.013895 (0.013895) Loss: 0.14733 (0.14056) +2025-09-14,14:39:14 | INFO | Train Epoch: 12 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12568 (0.12666) Boundary_loss: 0.013894 (0.013895) Loss: 0.13958 (0.14055) +2025-09-14,14:39:45 | INFO | Train Epoch: 12 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.095241 (0.12654) Boundary_loss: 0.013896 (0.013895) Loss: 0.10914 (0.14043) +2025-09-14,14:40:15 | INFO | Train Epoch: 12 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.14989 (0.12663) Boundary_loss: 0.013896 (0.013895) Loss: 0.16379 (0.14052) +2025-09-14,14:40:46 | INFO | Train Epoch: 12 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11589 (0.12659) Boundary_loss: 0.013895 (0.013895) Loss: 0.12978 (0.14048) +2025-09-14,14:41:17 | INFO | Train Epoch: 12 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14104 (0.12664) Boundary_loss: 0.013895 (0.013895) Loss: 0.15494 (0.14054) +2025-09-14,14:41:48 | INFO | Train Epoch: 12 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11353 (0.12659) Boundary_loss: 0.013894 (0.013895) Loss: 0.12743 (0.14049) +2025-09-14,14:42:18 | INFO | Train Epoch: 12 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.087902 (0.12644) Boundary_loss: 0.013895 (0.013895) Loss: 0.10180 (0.14034) +2025-09-14,14:42:49 | INFO | Train Epoch: 12 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10631 (0.12637) Boundary_loss: 0.013895 (0.013895) Loss: 0.12021 (0.14026) +2025-09-14,14:43:20 | INFO | Train Epoch: 12 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.098608 (0.12626) Boundary_loss: 0.013895 (0.013895) Loss: 0.11250 (0.14016) +2025-09-14,14:43:51 | INFO | Train Epoch: 12 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.095128 (0.12615) Boundary_loss: 0.013896 (0.013895) Loss: 0.10902 (0.14004) +2025-09-14,14:44:21 | INFO | Train Epoch: 12 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10293 (0.12606) Boundary_loss: 0.013894 (0.013895) Loss: 0.11683 (0.13995) +2025-09-14,14:44:52 | INFO | Train Epoch: 12 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12483 (0.12605) Boundary_loss: 0.013895 (0.013895) Loss: 0.13872 (0.13995) +2025-09-14,14:45:23 | INFO | Train Epoch: 12 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14220 (0.12611) Boundary_loss: 0.013895 (0.013895) Loss: 0.15609 (0.14001) +2025-09-14,14:45:54 | INFO | Train Epoch: 12 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12053 (0.12609) Boundary_loss: 0.013894 (0.013895) Loss: 0.13442 (0.13999) +2025-09-14,14:46:24 | INFO | Train Epoch: 12 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.072918 (0.12590) Boundary_loss: 0.013895 (0.013895) Loss: 0.086814 (0.13979) +2025-09-14,14:46:55 | INFO | Train Epoch: 12 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.086646 (0.12575) Boundary_loss: 0.013895 (0.013895) Loss: 0.10054 (0.13965) +2025-09-14,14:47:26 | INFO | Train Epoch: 12 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13606 (0.12579) Boundary_loss: 0.013894 (0.013895) Loss: 0.14995 (0.13969) +2025-09-14,14:47:57 | INFO | Train Epoch: 12 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13229 (0.12581) Boundary_loss: 0.013896 (0.013895) Loss: 0.14618 (0.13971) +2025-09-14,14:48:28 | INFO | Train Epoch: 12 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.13109 (0.12583) Boundary_loss: 0.013894 (0.013895) Loss: 0.14499 (0.13973) +2025-09-14,14:48:58 | INFO | Train Epoch: 12 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11857 (0.12581) Boundary_loss: 0.013894 (0.013895) Loss: 0.13246 (0.13970) +2025-09-14,14:49:29 | INFO | Train Epoch: 12 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14238 (0.12587) Boundary_loss: 0.013895 (0.013895) Loss: 0.15627 (0.13976) +2025-09-14,14:49:59 | INFO | Train Epoch: 12 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13865 (0.12591) Boundary_loss: 0.013895 (0.013895) Loss: 0.15255 (0.13981) +2025-09-14,14:50:30 | INFO | Train Epoch: 12 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16474 (0.12605) Boundary_loss: 0.013895 (0.013895) Loss: 0.17864 (0.13995) +2025-09-14,14:51:01 | INFO | Train Epoch: 12 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12170 (0.12604) Boundary_loss: 0.013895 (0.013895) Loss: 0.13560 (0.13993) +2025-09-14,14:51:31 | INFO | Train Epoch: 12 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.098483 (0.12594) Boundary_loss: 0.013896 (0.013895) Loss: 0.11238 (0.13983) +2025-09-14,14:52:02 | INFO | Train Epoch: 12 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.086357 (0.12580) Boundary_loss: 0.013895 (0.013895) Loss: 0.10025 (0.13969) +2025-09-14,14:52:32 | INFO | Train Epoch: 12 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10422 (0.12572) Boundary_loss: 0.013895 (0.013895) Loss: 0.11811 (0.13962) +2025-09-14,14:53:03 | INFO | Train Epoch: 12 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.16462 (0.12586) Boundary_loss: 0.013894 (0.013895) Loss: 0.17851 (0.13975) +2025-09-14,14:53:34 | INFO | Train Epoch: 12 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14407 (0.12592) Boundary_loss: 0.013896 (0.013895) Loss: 0.15797 (0.13982) +2025-09-14,14:54:04 | INFO | Train Epoch: 12 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.095681 (0.12582) Boundary_loss: 0.013895 (0.013895) Loss: 0.10958 (0.13971) +2025-09-14,14:54:35 | INFO | Train Epoch: 12 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14995 (0.12590) Boundary_loss: 0.013895 (0.013895) Loss: 0.16384 (0.13980) +2025-09-14,14:55:05 | INFO | Train Epoch: 12 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.15503 (0.12600) Boundary_loss: 0.013896 (0.013895) Loss: 0.16892 (0.13990) +2025-09-14,14:55:36 | INFO | Train Epoch: 12 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11796 (0.12597) Boundary_loss: 0.013896 (0.013895) Loss: 0.13186 (0.13987) +2025-09-14,14:56:07 | INFO | Train Epoch: 12 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11603 (0.12594) Boundary_loss: 0.013896 (0.013895) Loss: 0.12993 (0.13983) +2025-09-14,14:56:37 | INFO | Train Epoch: 12 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13751 (0.12598) Boundary_loss: 0.013895 (0.013895) Loss: 0.15140 (0.13987) +2025-09-14,14:57:08 | INFO | Train Epoch: 12 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.10100 (0.12589) Boundary_loss: 0.013894 (0.013895) Loss: 0.11489 (0.13979) +2025-09-14,14:57:38 | INFO | Train Epoch: 12 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15588 (0.12600) Boundary_loss: 0.013895 (0.013895) Loss: 0.16978 (0.13989) +2025-09-14,14:58:09 | INFO | Train Epoch: 12 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.099688 (0.12591) Boundary_loss: 0.013894 (0.013895) Loss: 0.11358 (0.13980) +2025-09-14,14:58:40 | INFO | Train Epoch: 12 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15549 (0.12601) Boundary_loss: 0.013895 (0.013895) Loss: 0.16938 (0.13990) +2025-09-14,14:59:11 | INFO | Train Epoch: 12 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11435 (0.12597) Boundary_loss: 0.013895 (0.013895) Loss: 0.12825 (0.13986) +2025-09-14,14:59:41 | INFO | Train Epoch: 12 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.17873 (0.12615) Boundary_loss: 0.013895 (0.013895) Loss: 0.19262 (0.14004) +2025-09-14,15:00:12 | INFO | Train Epoch: 12 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13591 (0.12618) Boundary_loss: 0.013895 (0.013895) Loss: 0.14980 (0.14007) +2025-09-14,15:00:42 | INFO | Train Epoch: 12 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.082900 (0.12603) Boundary_loss: 0.013895 (0.013895) Loss: 0.096795 (0.13993) +2025-09-14,15:01:13 | INFO | Train Epoch: 12 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11456 (0.12600) Boundary_loss: 0.013896 (0.013895) Loss: 0.12845 (0.13989) +2025-09-14,15:01:44 | INFO | Train Epoch: 12 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10798 (0.12594) Boundary_loss: 0.013895 (0.013895) Loss: 0.12188 (0.13983) +2025-09-14,15:02:15 | INFO | Train Epoch: 12 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.082866 (0.12579) Boundary_loss: 0.013894 (0.013895) Loss: 0.096760 (0.13969) +2025-09-14,15:02:46 | INFO | Train Epoch: 12 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11900 (0.12577) Boundary_loss: 0.013894 (0.013895) Loss: 0.13289 (0.13967) +2025-09-14,15:03:16 | INFO | Train Epoch: 12 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12941 (0.12578) Boundary_loss: 0.013896 (0.013895) Loss: 0.14330 (0.13968) +2025-09-14,15:03:47 | INFO | Train Epoch: 12 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11517 (0.12575) Boundary_loss: 0.013896 (0.013895) Loss: 0.12906 (0.13964) +2025-09-14,15:04:18 | INFO | Train Epoch: 12 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13193 (0.12577) Boundary_loss: 0.013895 (0.013895) Loss: 0.14582 (0.13966) +2025-09-14,15:04:49 | INFO | Train Epoch: 12 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.098331 (0.12568) Boundary_loss: 0.013895 (0.013895) Loss: 0.11223 (0.13957) +2025-09-14,15:05:20 | INFO | Train Epoch: 12 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.15050 (0.12576) Boundary_loss: 0.013895 (0.013895) Loss: 0.16439 (0.13965) +2025-09-14,15:05:50 | INFO | Train Epoch: 12 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.15118 (0.12584) Boundary_loss: 0.013896 (0.013895) Loss: 0.16507 (0.13974) +2025-09-14,15:06:21 | INFO | Train Epoch: 12 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10286 (0.12577) Boundary_loss: 0.013895 (0.013895) Loss: 0.11676 (0.13966) +2025-09-14,15:06:52 | INFO | Train Epoch: 12 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.098056 (0.12568) Boundary_loss: 0.013895 (0.013895) Loss: 0.11195 (0.13957) +2025-09-14,15:07:23 | INFO | Train Epoch: 12 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11052 (0.12563) Boundary_loss: 0.013895 (0.013895) Loss: 0.12442 (0.13952) +2025-09-14,15:07:54 | INFO | Train Epoch: 12 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11837 (0.12561) Boundary_loss: 0.013894 (0.013895) Loss: 0.13226 (0.13950) +2025-09-14,15:08:25 | INFO | Train Epoch: 12 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.16077 (0.12572) Boundary_loss: 0.013895 (0.013895) Loss: 0.17466 (0.13961) +2025-09-14,15:08:55 | INFO | Train Epoch: 12 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13937 (0.12576) Boundary_loss: 0.013895 (0.013895) Loss: 0.15326 (0.13966) +2025-09-14,15:09:26 | INFO | Train Epoch: 12 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13029 (0.12578) Boundary_loss: 0.013895 (0.013895) Loss: 0.14419 (0.13967) +2025-09-14,15:09:57 | INFO | Train Epoch: 12 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12992 (0.12579) Boundary_loss: 0.013894 (0.013895) Loss: 0.14382 (0.13968) +2025-09-14,15:10:28 | INFO | Train Epoch: 12 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.094643 (0.12569) Boundary_loss: 0.013895 (0.013895) Loss: 0.10854 (0.13959) +2025-09-14,15:10:58 | INFO | Train Epoch: 12 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.089588 (0.12558) Boundary_loss: 0.013895 (0.013895) Loss: 0.10348 (0.13947) +2025-09-14,15:11:29 | INFO | Train Epoch: 12 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12299 (0.12557) Boundary_loss: 0.013895 (0.013895) Loss: 0.13689 (0.13946) +2025-09-14,15:12:00 | INFO | Train Epoch: 12 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11104 (0.12552) Boundary_loss: 0.013895 (0.013895) Loss: 0.12493 (0.13942) +2025-09-14,15:12:31 | INFO | Train Epoch: 12 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12398 (0.12552) Boundary_loss: 0.013895 (0.013895) Loss: 0.13788 (0.13941) +2025-09-14,15:13:01 | INFO | Train Epoch: 12 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11132 (0.12548) Boundary_loss: 0.013895 (0.013895) Loss: 0.12522 (0.13937) +2025-09-14,15:13:32 | INFO | Train Epoch: 12 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11038 (0.12543) Boundary_loss: 0.013895 (0.013895) Loss: 0.12427 (0.13932) +2025-09-14,15:14:03 | INFO | Train Epoch: 12 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11656 (0.12540) Boundary_loss: 0.013894 (0.013895) Loss: 0.13045 (0.13930) +2025-09-14,15:14:34 | INFO | Train Epoch: 12 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13298 (0.12543) Boundary_loss: 0.013894 (0.013895) Loss: 0.14687 (0.13932) +2025-09-14,15:15:04 | INFO | Train Epoch: 12 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11471 (0.12539) Boundary_loss: 0.013895 (0.013895) Loss: 0.12861 (0.13929) +2025-09-14,15:15:35 | INFO | Train Epoch: 12 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12591 (0.12539) Boundary_loss: 0.013895 (0.013895) Loss: 0.13981 (0.13929) +2025-09-14,15:16:06 | INFO | Train Epoch: 12 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11050 (0.12535) Boundary_loss: 0.013894 (0.013895) Loss: 0.12439 (0.13924) +2025-09-14,15:16:37 | INFO | Train Epoch: 12 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.098971 (0.12527) Boundary_loss: 0.013895 (0.013895) Loss: 0.11287 (0.13916) +2025-09-14,15:17:07 | INFO | Train Epoch: 12 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.067882 (0.12510) Boundary_loss: 0.013894 (0.013895) Loss: 0.081776 (0.13899) +2025-09-14,15:17:37 | INFO | Train Epoch: 12 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14567 (0.12516) Boundary_loss: 0.013895 (0.013895) Loss: 0.15956 (0.13905) +2025-09-14,15:18:08 | INFO | Train Epoch: 12 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14458 (0.12522) Boundary_loss: 0.013895 (0.013895) Loss: 0.15847 (0.13911) +2025-09-14,15:18:39 | INFO | Train Epoch: 12 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.16606 (0.12534) Boundary_loss: 0.013895 (0.013895) Loss: 0.17995 (0.13923) +2025-09-14,15:19:10 | INFO | Train Epoch: 12 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.13777 (0.12538) Boundary_loss: 0.013895 (0.013895) Loss: 0.15167 (0.13927) +2025-09-14,15:19:41 | INFO | Train Epoch: 12 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13039 (0.12539) Boundary_loss: 0.013895 (0.013895) Loss: 0.14428 (0.13928) +2025-09-14,15:20:12 | INFO | Train Epoch: 12 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12922 (0.12540) Boundary_loss: 0.013896 (0.013895) Loss: 0.14311 (0.13930) +2025-09-14,15:20:43 | INFO | Train Epoch: 12 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.13185 (0.12542) Boundary_loss: 0.013894 (0.013895) Loss: 0.14574 (0.13932) +2025-09-14,15:21:14 | INFO | Train Epoch: 12 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12370 (0.12542) Boundary_loss: 0.013895 (0.013895) Loss: 0.13759 (0.13931) +2025-09-14,15:21:45 | INFO | Train Epoch: 12 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.14355 (0.12547) Boundary_loss: 0.013895 (0.013895) Loss: 0.15744 (0.13936) +2025-09-14,15:22:16 | INFO | Train Epoch: 12 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.095743 (0.12538) Boundary_loss: 0.013894 (0.013895) Loss: 0.10964 (0.13928) +2025-09-14,15:22:47 | INFO | Train Epoch: 12 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.096709 (0.12530) Boundary_loss: 0.013896 (0.013895) Loss: 0.11060 (0.13919) +2025-09-14,15:23:17 | INFO | Train Epoch: 12 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12678 (0.12530) Boundary_loss: 0.013895 (0.013895) Loss: 0.14067 (0.13920) +2025-09-14,15:23:48 | INFO | Train Epoch: 12 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.16606 (0.12542) Boundary_loss: 0.013895 (0.013895) Loss: 0.17995 (0.13932) +2025-09-14,15:24:19 | INFO | Train Epoch: 12 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.099136 (0.12534) Boundary_loss: 0.013894 (0.013895) Loss: 0.11303 (0.13924) +2025-09-14,15:24:50 | INFO | Train Epoch: 12 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.087465 (0.12523) Boundary_loss: 0.013894 (0.013895) Loss: 0.10136 (0.13913) +2025-09-14,15:25:22 | INFO | Train Epoch: 12 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12270 (0.12523) Boundary_loss: 0.013896 (0.013895) Loss: 0.13660 (0.13912) +2025-09-14,15:25:53 | INFO | Train Epoch: 12 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.10839 (0.12518) Boundary_loss: 0.013894 (0.013895) Loss: 0.12228 (0.13907) +2025-09-14,15:26:24 | INFO | Train Epoch: 12 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.18934 (0.12536) Boundary_loss: 0.013896 (0.013895) Loss: 0.20323 (0.13926) +2025-09-14,15:26:55 | INFO | Train Epoch: 12 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.098458 (0.12529) Boundary_loss: 0.013895 (0.013895) Loss: 0.11235 (0.13918) +2025-09-14,15:27:26 | INFO | Train Epoch: 12 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14075 (0.12533) Boundary_loss: 0.013895 (0.013895) Loss: 0.15464 (0.13923) +2025-09-14,15:27:57 | INFO | Train Epoch: 12 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10670 (0.12528) Boundary_loss: 0.013895 (0.013895) Loss: 0.12060 (0.13917) +2025-09-14,15:28:28 | INFO | Train Epoch: 12 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13484 (0.12530) Boundary_loss: 0.013895 (0.013895) Loss: 0.14873 (0.13920) +2025-09-14,15:28:59 | INFO | Train Epoch: 12 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.088807 (0.12520) Boundary_loss: 0.013894 (0.013895) Loss: 0.10270 (0.13910) +2025-09-14,15:29:30 | INFO | Train Epoch: 12 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12426 (0.12520) Boundary_loss: 0.013895 (0.013895) Loss: 0.13815 (0.13909) +2025-09-14,15:30:00 | INFO | Train Epoch: 12 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11186 (0.12516) Boundary_loss: 0.013895 (0.013895) Loss: 0.12575 (0.13906) +2025-09-14,15:30:31 | INFO | Train Epoch: 12 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10019 (0.12509) Boundary_loss: 0.013894 (0.013895) Loss: 0.11409 (0.13899) +2025-09-14,15:31:03 | INFO | Train Epoch: 12 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10533 (0.12504) Boundary_loss: 0.013896 (0.013895) Loss: 0.11923 (0.13893) +2025-09-14,15:31:34 | INFO | Train Epoch: 12 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13546 (0.12506) Boundary_loss: 0.013894 (0.013895) Loss: 0.14935 (0.13896) +2025-09-14,15:32:05 | INFO | Train Epoch: 12 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.082222 (0.12495) Boundary_loss: 0.013895 (0.013895) Loss: 0.096117 (0.13884) +2025-09-14,15:32:36 | INFO | Train Epoch: 12 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.13201 (0.12497) Boundary_loss: 0.013894 (0.013895) Loss: 0.14591 (0.13886) +2025-09-14,15:33:07 | INFO | Train Epoch: 12 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10150 (0.12490) Boundary_loss: 0.013894 (0.013895) Loss: 0.11539 (0.13880) +2025-09-14,15:33:38 | INFO | Train Epoch: 12 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12841 (0.12491) Boundary_loss: 0.013895 (0.013895) Loss: 0.14231 (0.13881) +2025-09-14,15:34:08 | INFO | Train Epoch: 12 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.089390 (0.12481) Boundary_loss: 0.013896 (0.013895) Loss: 0.10329 (0.13871) +2025-09-14,15:34:39 | INFO | Train Epoch: 12 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10969 (0.12477) Boundary_loss: 0.013895 (0.013895) Loss: 0.12359 (0.13867) +2025-09-14,15:35:10 | INFO | Train Epoch: 12 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.11795 (0.12475) Boundary_loss: 0.013894 (0.013895) Loss: 0.13184 (0.13865) +2025-09-14,15:35:41 | INFO | Train Epoch: 12 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.096851 (0.12468) Boundary_loss: 0.013895 (0.013895) Loss: 0.11075 (0.13857) +2025-09-14,15:36:12 | INFO | Train Epoch: 12 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12559 (0.12468) Boundary_loss: 0.013894 (0.013895) Loss: 0.13948 (0.13857) +2025-09-14,15:36:42 | INFO | Train Epoch: 12 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10706 (0.12463) Boundary_loss: 0.013896 (0.013895) Loss: 0.12096 (0.13853) +2025-09-14,15:37:13 | INFO | Train Epoch: 12 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.18285 (0.12479) Boundary_loss: 0.013894 (0.013895) Loss: 0.19675 (0.13868) +2025-09-14,15:37:44 | INFO | Train Epoch: 12 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14361 (0.12484) Boundary_loss: 0.013895 (0.013895) Loss: 0.15750 (0.13873) +2025-09-14,15:38:14 | INFO | Train Epoch: 12 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.14288 (0.12489) Boundary_loss: 0.013894 (0.013895) Loss: 0.15677 (0.13878) +2025-09-14,15:38:45 | INFO | Train Epoch: 12 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13972 (0.12493) Boundary_loss: 0.013896 (0.013895) Loss: 0.15362 (0.13882) +2025-09-14,15:39:16 | INFO | Train Epoch: 12 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10039 (0.12486) Boundary_loss: 0.013895 (0.013895) Loss: 0.11429 (0.13876) +2025-09-14,15:39:47 | INFO | Train Epoch: 12 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14349 (0.12491) Boundary_loss: 0.013895 (0.013895) Loss: 0.15739 (0.13881) +2025-09-14,15:40:18 | INFO | Train Epoch: 12 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.16266 (0.12501) Boundary_loss: 0.013894 (0.013895) Loss: 0.17655 (0.13891) +2025-09-14,15:40:49 | INFO | Train Epoch: 12 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.12419 (0.12501) Boundary_loss: 0.013894 (0.013895) Loss: 0.13808 (0.13890) +2025-09-14,15:41:19 | INFO | Train Epoch: 12 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.19189 (0.12519) Boundary_loss: 0.013894 (0.013895) Loss: 0.20578 (0.13908) +2025-09-14,15:41:50 | INFO | Train Epoch: 12 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10383 (0.12513) Boundary_loss: 0.013894 (0.013895) Loss: 0.11772 (0.13903) +2025-09-14,15:42:21 | INFO | Train Epoch: 12 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16096 (0.12522) Boundary_loss: 0.013896 (0.013895) Loss: 0.17485 (0.13912) +2025-09-14,15:42:52 | INFO | Train Epoch: 12 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11814 (0.12521) Boundary_loss: 0.013896 (0.013895) Loss: 0.13203 (0.13910) +2025-09-14,15:43:23 | INFO | Train Epoch: 12 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16276 (0.12530) Boundary_loss: 0.013895 (0.013895) Loss: 0.17665 (0.13920) +2025-09-14,15:43:54 | INFO | Train Epoch: 12 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15136 (0.12537) Boundary_loss: 0.013895 (0.013895) Loss: 0.16526 (0.13927) +2025-09-14,15:44:25 | INFO | Train Epoch: 12 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11512 (0.12535) Boundary_loss: 0.013895 (0.013895) Loss: 0.12902 (0.13924) +2025-09-14,15:44:55 | INFO | Train Epoch: 12 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11188 (0.12531) Boundary_loss: 0.013896 (0.013895) Loss: 0.12578 (0.13921) +2025-09-14,15:45:26 | INFO | Train Epoch: 12 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11520 (0.12528) Boundary_loss: 0.013895 (0.013895) Loss: 0.12910 (0.13918) +2025-09-14,15:45:57 | INFO | Train Epoch: 12 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12834 (0.12529) Boundary_loss: 0.013895 (0.013895) Loss: 0.14223 (0.13919) +2025-09-14,15:46:28 | INFO | Train Epoch: 12 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.094251 (0.12521) Boundary_loss: 0.013895 (0.013895) Loss: 0.10815 (0.13911) +2025-09-14,15:46:58 | INFO | Train Epoch: 12 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.14358 (0.12526) Boundary_loss: 0.013894 (0.013895) Loss: 0.15747 (0.13915) +2025-09-14,15:47:29 | INFO | Train Epoch: 12 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.087711 (0.12516) Boundary_loss: 0.013895 (0.013895) Loss: 0.10161 (0.13906) +2025-09-14,15:48:00 | INFO | Train Epoch: 12 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.099965 (0.12510) Boundary_loss: 0.013894 (0.013895) Loss: 0.11386 (0.13899) +2025-09-14,15:48:30 | INFO | Train Epoch: 12 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.15433 (0.12517) Boundary_loss: 0.013896 (0.013895) Loss: 0.16823 (0.13907) +2025-09-14,15:49:01 | INFO | Train Epoch: 12 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18021 (0.12531) Boundary_loss: 0.013895 (0.013895) Loss: 0.19410 (0.13921) +2025-09-14,15:49:32 | INFO | Train Epoch: 12 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.097494 (0.12524) Boundary_loss: 0.013895 (0.013895) Loss: 0.11139 (0.13914) +2025-09-14,15:50:03 | INFO | Train Epoch: 12 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12950 (0.12525) Boundary_loss: 0.013895 (0.013895) Loss: 0.14340 (0.13915) +2025-09-14,15:50:33 | INFO | Train Epoch: 12 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10468 (0.12520) Boundary_loss: 0.013895 (0.013895) Loss: 0.11857 (0.13910) +2025-09-14,15:51:04 | INFO | Train Epoch: 12 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11254 (0.12517) Boundary_loss: 0.013896 (0.013895) Loss: 0.12644 (0.13906) +2025-09-14,15:51:35 | INFO | Train Epoch: 12 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13648 (0.12520) Boundary_loss: 0.013894 (0.013895) Loss: 0.15038 (0.13909) +2025-09-14,15:52:05 | INFO | Train Epoch: 12 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.14092 (0.12524) Boundary_loss: 0.013894 (0.013895) Loss: 0.15482 (0.13913) +2025-09-14,15:52:36 | INFO | Train Epoch: 12 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.12835 (0.12525) Boundary_loss: 0.013895 (0.013895) Loss: 0.14225 (0.13914) +2025-09-14,15:53:07 | INFO | Train Epoch: 12 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11396 (0.12522) Boundary_loss: 0.013894 (0.013895) Loss: 0.12785 (0.13911) +2025-09-14,15:53:37 | INFO | Train Epoch: 12 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.098758 (0.12515) Boundary_loss: 0.013896 (0.013895) Loss: 0.11265 (0.13905) +2025-09-14,15:54:08 | INFO | Train Epoch: 12 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.14420 (0.12520) Boundary_loss: 0.013894 (0.013895) Loss: 0.15810 (0.13909) +2025-09-14,15:54:39 | INFO | Train Epoch: 12 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11670 (0.12518) Boundary_loss: 0.013894 (0.013895) Loss: 0.13059 (0.13907) +2025-09-14,15:55:10 | INFO | Train Epoch: 12 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10569 (0.12513) Boundary_loss: 0.013894 (0.013895) Loss: 0.11959 (0.13902) +2025-09-14,15:55:40 | INFO | Train Epoch: 12 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11959 (0.12512) Boundary_loss: 0.013895 (0.013895) Loss: 0.13348 (0.13901) +2025-09-14,15:56:11 | INFO | Train Epoch: 12 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16710 (0.12522) Boundary_loss: 0.013896 (0.013895) Loss: 0.18099 (0.13911) +2025-09-14,15:56:42 | INFO | Train Epoch: 12 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11763 (0.12520) Boundary_loss: 0.013895 (0.013895) Loss: 0.13153 (0.13910) +2025-09-14,15:57:13 | INFO | Train Epoch: 12 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15175 (0.12527) Boundary_loss: 0.013895 (0.013895) Loss: 0.16565 (0.13916) +2025-09-14,15:57:44 | INFO | Train Epoch: 12 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.12764 (0.12527) Boundary_loss: 0.013894 (0.013895) Loss: 0.14153 (0.13917) +2025-09-14,15:58:14 | INFO | Train Epoch: 12 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11341 (0.12524) Boundary_loss: 0.013895 (0.013895) Loss: 0.12730 (0.13914) +2025-09-14,15:58:45 | INFO | Train Epoch: 12 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.12456 (0.12524) Boundary_loss: 0.013895 (0.013895) Loss: 0.13846 (0.13914) +2025-09-14,15:59:16 | INFO | Train Epoch: 12 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12259 (0.12523) Boundary_loss: 0.013895 (0.013895) Loss: 0.13649 (0.13913) +2025-09-14,15:59:47 | INFO | Train Epoch: 12 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.14183 (0.12527) Boundary_loss: 0.013897 (0.013895) Loss: 0.15573 (0.13917) +2025-09-14,16:00:18 | INFO | Train Epoch: 12 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.15797 (0.12535) Boundary_loss: 0.013896 (0.013895) Loss: 0.17186 (0.13925) +2025-09-14,16:00:48 | INFO | Train Epoch: 12 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.14483 (0.12540) Boundary_loss: 0.013894 (0.013895) Loss: 0.15872 (0.13930) +2025-09-14,16:01:19 | INFO | Train Epoch: 12 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13546 (0.12542) Boundary_loss: 0.013894 (0.013895) Loss: 0.14935 (0.13932) +2025-09-14,16:01:50 | INFO | Train Epoch: 12 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.085132 (0.12533) Boundary_loss: 0.013895 (0.013895) Loss: 0.099027 (0.13922) +2025-09-14,16:02:21 | INFO | Train Epoch: 12 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.12707 (0.12533) Boundary_loss: 0.013895 (0.013895) Loss: 0.14096 (0.13923) +2025-09-14,16:02:52 | INFO | Train Epoch: 12 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10986 (0.12530) Boundary_loss: 0.013896 (0.013895) Loss: 0.12376 (0.13919) +2025-09-14,16:03:23 | INFO | Train Epoch: 12 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11579 (0.12527) Boundary_loss: 0.013895 (0.013895) Loss: 0.12969 (0.13917) +2025-09-14,16:03:53 | INFO | Train Epoch: 12 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.090210 (0.12519) Boundary_loss: 0.013895 (0.013895) Loss: 0.10410 (0.13908) +2025-09-14,16:04:24 | INFO | Train Epoch: 12 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.12775 (0.12520) Boundary_loss: 0.013896 (0.013895) Loss: 0.14165 (0.13909) +2025-09-14,16:04:55 | INFO | Train Epoch: 12 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11849 (0.12518) Boundary_loss: 0.013894 (0.013895) Loss: 0.13238 (0.13907) +2025-09-14,16:05:25 | INFO | Train Epoch: 12 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13683 (0.12521) Boundary_loss: 0.013896 (0.013895) Loss: 0.15072 (0.13910) +2025-09-14,16:05:56 | INFO | Train Epoch: 12 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.099809 (0.12515) Boundary_loss: 0.013895 (0.013895) Loss: 0.11370 (0.13904) +2025-09-14,16:06:27 | INFO | Train Epoch: 12 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.15064 (0.12521) Boundary_loss: 0.013894 (0.013895) Loss: 0.16453 (0.13910) +2025-09-14,16:06:57 | INFO | Train Epoch: 12 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.096813 (0.12514) Boundary_loss: 0.013895 (0.013895) Loss: 0.11071 (0.13904) +2025-09-14,16:07:28 | INFO | Train Epoch: 12 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.12745 (0.12515) Boundary_loss: 0.013894 (0.013895) Loss: 0.14134 (0.13904) +2025-09-14,16:07:58 | INFO | Train Epoch: 12 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.17454 (0.12526) Boundary_loss: 0.013895 (0.013895) Loss: 0.18844 (0.13916) +2025-09-14,16:08:29 | INFO | Train Epoch: 12 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11757 (0.12524) Boundary_loss: 0.013894 (0.013895) Loss: 0.13147 (0.13914) +2025-09-14,16:09:00 | INFO | Train Epoch: 12 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10519 (0.12520) Boundary_loss: 0.013895 (0.013895) Loss: 0.11908 (0.13909) +2025-09-14,16:09:31 | INFO | Train Epoch: 12 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11587 (0.12518) Boundary_loss: 0.013895 (0.013895) Loss: 0.12976 (0.13907) +2025-09-14,16:10:01 | INFO | Train Epoch: 12 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12178 (0.12517) Boundary_loss: 0.013896 (0.013895) Loss: 0.13567 (0.13906) +2025-09-14,16:10:32 | INFO | Train Epoch: 12 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13243 (0.12518) Boundary_loss: 0.013894 (0.013895) Loss: 0.14632 (0.13908) +2025-09-14,16:11:02 | INFO | Train Epoch: 12 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12150 (0.12518) Boundary_loss: 0.013895 (0.013895) Loss: 0.13539 (0.13907) +2025-09-14,16:11:33 | INFO | Train Epoch: 12 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.092428 (0.12510) Boundary_loss: 0.013895 (0.013895) Loss: 0.10632 (0.13900) +2025-09-14,16:12:04 | INFO | Train Epoch: 12 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10323 (0.12505) Boundary_loss: 0.013896 (0.013895) Loss: 0.11713 (0.13895) +2025-09-14,16:12:34 | INFO | Train Epoch: 12 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11346 (0.12502) Boundary_loss: 0.013896 (0.013895) Loss: 0.12735 (0.13892) +2025-09-14,16:13:05 | INFO | Train Epoch: 12 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11855 (0.12501) Boundary_loss: 0.013895 (0.013895) Loss: 0.13244 (0.13890) +2025-09-14,16:13:36 | INFO | Train Epoch: 12 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12217 (0.12500) Boundary_loss: 0.013894 (0.013895) Loss: 0.13606 (0.13890) +2025-09-14,16:14:06 | INFO | Train Epoch: 12 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13119 (0.12502) Boundary_loss: 0.013897 (0.013895) Loss: 0.14508 (0.13891) +2025-09-14,16:14:37 | INFO | Train Epoch: 12 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.10422 (0.12497) Boundary_loss: 0.013894 (0.013895) Loss: 0.11811 (0.13887) +2025-09-14,16:15:08 | INFO | Train Epoch: 12 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11973 (0.12496) Boundary_loss: 0.013895 (0.013895) Loss: 0.13363 (0.13885) +2025-09-14,16:15:38 | INFO | Train Epoch: 12 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.090703 (0.12488) Boundary_loss: 0.013896 (0.013895) Loss: 0.10460 (0.13878) +2025-09-14,16:16:09 | INFO | Train Epoch: 12 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.097596 (0.12482) Boundary_loss: 0.013896 (0.013895) Loss: 0.11149 (0.13872) +2025-09-14,16:16:39 | INFO | Train Epoch: 12 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.13061 (0.12483) Boundary_loss: 0.013895 (0.013895) Loss: 0.14451 (0.13873) +2025-09-14,16:17:10 | INFO | Train Epoch: 12 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13198 (0.12485) Boundary_loss: 0.013894 (0.013895) Loss: 0.14587 (0.13874) +2025-09-14,16:17:41 | INFO | Train Epoch: 12 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11689 (0.12483) Boundary_loss: 0.013895 (0.013895) Loss: 0.13079 (0.13873) +2025-09-14,16:18:12 | INFO | Train Epoch: 12 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13007 (0.12484) Boundary_loss: 0.013895 (0.013895) Loss: 0.14396 (0.13874) +2025-09-14,16:18:43 | INFO | Train Epoch: 12 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.085611 (0.12476) Boundary_loss: 0.013895 (0.013895) Loss: 0.099507 (0.13865) +2025-09-14,16:19:14 | INFO | Train Epoch: 12 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.16415 (0.12484) Boundary_loss: 0.013894 (0.013895) Loss: 0.17805 (0.13874) +2025-09-14,16:19:44 | INFO | Train Epoch: 12 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13740 (0.12487) Boundary_loss: 0.013896 (0.013895) Loss: 0.15129 (0.13877) +2025-09-14,16:20:15 | INFO | Train Epoch: 12 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13058 (0.12488) Boundary_loss: 0.013896 (0.013895) Loss: 0.14448 (0.13878) +2025-09-14,16:20:46 | INFO | Train Epoch: 12 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.084727 (0.12480) Boundary_loss: 0.013895 (0.013895) Loss: 0.098621 (0.13869) +2025-09-14,16:21:17 | INFO | Train Epoch: 12 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10391 (0.12475) Boundary_loss: 0.013895 (0.013895) Loss: 0.11781 (0.13864) +2025-09-14,16:21:48 | INFO | Train Epoch: 12 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10381 (0.12470) Boundary_loss: 0.013895 (0.013895) Loss: 0.11771 (0.13860) +2025-09-14,16:22:19 | INFO | Train Epoch: 12 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.16249 (0.12479) Boundary_loss: 0.013896 (0.013895) Loss: 0.17639 (0.13868) +2025-09-14,16:22:49 | INFO | Train Epoch: 12 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11907 (0.12477) Boundary_loss: 0.013895 (0.013895) Loss: 0.13296 (0.13867) +2025-09-14,16:23:20 | INFO | Train Epoch: 12 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10473 (0.12473) Boundary_loss: 0.013895 (0.013895) Loss: 0.11863 (0.13863) +2025-09-14,16:23:51 | INFO | Train Epoch: 12 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12535 (0.12473) Boundary_loss: 0.013896 (0.013895) Loss: 0.13925 (0.13863) +2025-09-14,16:24:22 | INFO | Train Epoch: 12 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.084344 (0.12464) Boundary_loss: 0.013895 (0.013895) Loss: 0.098239 (0.13854) +2025-09-14,16:24:53 | INFO | Train Epoch: 12 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14444 (0.12469) Boundary_loss: 0.013895 (0.013895) Loss: 0.15833 (0.13858) +2025-09-14,16:25:23 | INFO | Train Epoch: 12 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10918 (0.12465) Boundary_loss: 0.013895 (0.013895) Loss: 0.12308 (0.13855) +2025-09-14,16:25:54 | INFO | Train Epoch: 12 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10799 (0.12462) Boundary_loss: 0.013896 (0.013895) Loss: 0.12189 (0.13851) +2025-09-14,16:26:25 | INFO | Train Epoch: 12 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.099564 (0.12456) Boundary_loss: 0.013894 (0.013895) Loss: 0.11346 (0.13846) +2025-09-14,16:26:55 | INFO | Train Epoch: 12 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14556 (0.12461) Boundary_loss: 0.013895 (0.013895) Loss: 0.15946 (0.13850) +2025-09-14,16:27:26 | INFO | Train Epoch: 12 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11375 (0.12459) Boundary_loss: 0.013895 (0.013895) Loss: 0.12764 (0.13848) +2025-09-14,16:27:57 | INFO | Train Epoch: 12 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12689 (0.12459) Boundary_loss: 0.013895 (0.013895) Loss: 0.14078 (0.13849) +2025-09-14,16:28:27 | INFO | Train Epoch: 12 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.15319 (0.12465) Boundary_loss: 0.013895 (0.013895) Loss: 0.16709 (0.13855) +2025-09-14,16:28:58 | INFO | Train Epoch: 12 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.079762 (0.12456) Boundary_loss: 0.013894 (0.013895) Loss: 0.093656 (0.13845) +2025-09-14,16:29:29 | INFO | Train Epoch: 12 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11901 (0.12454) Boundary_loss: 0.013894 (0.013895) Loss: 0.13290 (0.13844) +2025-09-14,16:29:59 | INFO | Train Epoch: 12 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10127 (0.12450) Boundary_loss: 0.013895 (0.013895) Loss: 0.11517 (0.13839) +2025-09-14,16:30:30 | INFO | Train Epoch: 12 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14450 (0.12454) Boundary_loss: 0.013895 (0.013895) Loss: 0.15839 (0.13843) +2025-09-14,16:31:01 | INFO | Train Epoch: 12 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.13441 (0.12456) Boundary_loss: 0.013896 (0.013895) Loss: 0.14830 (0.13845) +2025-09-14,16:31:32 | INFO | Train Epoch: 12 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13103 (0.12457) Boundary_loss: 0.013894 (0.013895) Loss: 0.14492 (0.13847) +2025-09-14,16:32:03 | INFO | Train Epoch: 12 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.16276 (0.12465) Boundary_loss: 0.013894 (0.013895) Loss: 0.17666 (0.13855) +2025-09-14,16:32:34 | INFO | Train Epoch: 12 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.066411 (0.12453) Boundary_loss: 0.013896 (0.013895) Loss: 0.080306 (0.13842) +2025-09-14,16:33:04 | INFO | Train Epoch: 12 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10328 (0.12449) Boundary_loss: 0.013895 (0.013895) Loss: 0.11718 (0.13838) +2025-09-14,16:33:35 | INFO | Train Epoch: 12 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.099998 (0.12443) Boundary_loss: 0.013894 (0.013895) Loss: 0.11389 (0.13833) +2025-09-14,16:34:06 | INFO | Train Epoch: 12 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.12580 (0.12444) Boundary_loss: 0.013894 (0.013895) Loss: 0.13969 (0.13833) +2025-09-14,16:34:36 | INFO | Train Epoch: 12 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.093207 (0.12437) Boundary_loss: 0.013895 (0.013895) Loss: 0.10710 (0.13827) +2025-09-14,16:35:07 | INFO | Train Epoch: 12 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11779 (0.12436) Boundary_loss: 0.013895 (0.013895) Loss: 0.13169 (0.13825) +2025-09-14,16:35:38 | INFO | Train Epoch: 12 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12410 (0.12436) Boundary_loss: 0.013895 (0.013895) Loss: 0.13800 (0.13825) +2025-09-14,16:36:09 | INFO | Train Epoch: 12 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.14106 (0.12439) Boundary_loss: 0.013895 (0.013895) Loss: 0.15495 (0.13829) +2025-09-14,16:36:40 | INFO | Train Epoch: 12 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.096531 (0.12434) Boundary_loss: 0.013894 (0.013895) Loss: 0.11043 (0.13823) +2025-09-14,16:37:10 | INFO | Train Epoch: 12 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15915 (0.12441) Boundary_loss: 0.013895 (0.013895) Loss: 0.17305 (0.13830) +2025-09-14,16:37:41 | INFO | Train Epoch: 12 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11470 (0.12439) Boundary_loss: 0.013895 (0.013895) Loss: 0.12859 (0.13828) +2025-09-14,16:38:12 | INFO | Train Epoch: 12 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12189 (0.12438) Boundary_loss: 0.013894 (0.013895) Loss: 0.13578 (0.13828) +2025-09-14,16:38:42 | INFO | Train Epoch: 12 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11821 (0.12437) Boundary_loss: 0.013895 (0.013895) Loss: 0.13210 (0.13826) +2025-09-14,16:39:13 | INFO | Train Epoch: 12 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.099583 (0.12432) Boundary_loss: 0.013895 (0.013895) Loss: 0.11348 (0.13821) +2025-09-14,16:39:44 | INFO | Train Epoch: 12 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12494 (0.12432) Boundary_loss: 0.013894 (0.013895) Loss: 0.13883 (0.13822) +2025-09-14,16:40:15 | INFO | Train Epoch: 12 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.13186 (0.12434) Boundary_loss: 0.013895 (0.013895) Loss: 0.14575 (0.13823) +2025-09-14,16:40:45 | INFO | Train Epoch: 12 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11244 (0.12431) Boundary_loss: 0.013895 (0.013895) Loss: 0.12634 (0.13821) +2025-09-14,16:41:16 | INFO | Train Epoch: 12 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12275 (0.12431) Boundary_loss: 0.013895 (0.013895) Loss: 0.13664 (0.13820) +2025-09-14,16:41:46 | INFO | Train Epoch: 12 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14179 (0.12434) Boundary_loss: 0.013895 (0.013895) Loss: 0.15569 (0.13824) +2025-09-14,16:42:17 | INFO | Train Epoch: 12 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11686 (0.12433) Boundary_loss: 0.013894 (0.013895) Loss: 0.13076 (0.13822) +2025-09-14,16:42:48 | INFO | Train Epoch: 12 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11802 (0.12432) Boundary_loss: 0.013895 (0.013895) Loss: 0.13191 (0.13821) +2025-09-14,16:43:19 | INFO | Train Epoch: 12 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11092 (0.12429) Boundary_loss: 0.013895 (0.013895) Loss: 0.12482 (0.13818) +2025-09-14,16:43:50 | INFO | Train Epoch: 12 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11284 (0.12427) Boundary_loss: 0.013895 (0.013895) Loss: 0.12674 (0.13816) +2025-09-14,16:44:20 | INFO | Train Epoch: 12 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.096252 (0.12421) Boundary_loss: 0.013895 (0.013895) Loss: 0.11015 (0.13811) +2025-09-14,16:44:51 | INFO | Train Epoch: 12 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10110 (0.12416) Boundary_loss: 0.013895 (0.013895) Loss: 0.11500 (0.13806) +2025-09-14,16:45:22 | INFO | Train Epoch: 12 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.15652 (0.12423) Boundary_loss: 0.013895 (0.013895) Loss: 0.17041 (0.13812) +2025-09-14,16:45:53 | INFO | Train Epoch: 12 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.13807 (0.12426) Boundary_loss: 0.013895 (0.013895) Loss: 0.15197 (0.13815) +2025-09-14,16:46:24 | INFO | Train Epoch: 12 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.093399 (0.12419) Boundary_loss: 0.013895 (0.013895) Loss: 0.10729 (0.13809) +2025-09-14,16:46:54 | INFO | Train Epoch: 12 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10992 (0.12417) Boundary_loss: 0.013896 (0.013895) Loss: 0.12382 (0.13806) +2025-09-14,16:47:25 | INFO | Train Epoch: 12 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.099381 (0.12412) Boundary_loss: 0.013895 (0.013895) Loss: 0.11328 (0.13801) +2025-09-14,16:47:56 | INFO | Train Epoch: 12 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15239 (0.12417) Boundary_loss: 0.013894 (0.013895) Loss: 0.16628 (0.13807) +2025-09-14,16:48:27 | INFO | Train Epoch: 12 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10117 (0.12413) Boundary_loss: 0.013894 (0.013895) Loss: 0.11506 (0.13802) +2025-09-14,16:48:58 | INFO | Train Epoch: 12 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11048 (0.12410) Boundary_loss: 0.013895 (0.013895) Loss: 0.12438 (0.13800) +2025-09-14,16:49:28 | INFO | Train Epoch: 12 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.095527 (0.12405) Boundary_loss: 0.013894 (0.013895) Loss: 0.10942 (0.13794) +2025-09-14,16:49:59 | INFO | Train Epoch: 12 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.091240 (0.12398) Boundary_loss: 0.013895 (0.013895) Loss: 0.10513 (0.13788) +2025-09-14,16:50:30 | INFO | Train Epoch: 12 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11075 (0.12396) Boundary_loss: 0.013896 (0.013895) Loss: 0.12465 (0.13785) +2025-09-14,16:51:01 | INFO | Train Epoch: 12 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10049 (0.12391) Boundary_loss: 0.013895 (0.013895) Loss: 0.11438 (0.13780) +2025-09-14,16:51:32 | INFO | Train Epoch: 12 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11002 (0.12388) Boundary_loss: 0.013894 (0.013895) Loss: 0.12391 (0.13778) +2025-09-14,16:52:01 | INFO | Train Epoch: 12 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11338 (0.12386) Boundary_loss: 0.013895 (0.013895) Loss: 0.12727 (0.13776) +2025-09-14,16:52:01 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,16:52:01 | INFO | [Epoch 12] Average Step Time: 0.310s | Average GPU Memory: 25.2 GB +2025-09-14,16:52:01 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,16:52:01 | INFO | Starting zero-shot imagenet. +2025-09-14,16:52:01 | INFO | Building zero-shot classifier +2025-09-14,16:52:07 | INFO | Using classifier +2025-09-14,16:52:44 | INFO | Finished zero-shot imagenet. +2025-09-14,16:52:44 | INFO | Eval Epoch: 13 imagenet-zeroshot-val-top1: 0.3090 imagenet-zeroshot-val-top5: 0.5740 +2025-09-14,16:52:45 | INFO | Start epoch 13 +2025-09-14,16:52:46 | INFO | Train Epoch: 13 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.071031 (0.071031) Boundary_loss: 0.013895 (0.013895) Loss: 0.084926 (0.084926) +2025-09-14,16:53:17 | INFO | Train Epoch: 13 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13284 (0.10194) Boundary_loss: 0.013895 (0.013895) Loss: 0.14673 (0.11583) +2025-09-14,16:53:48 | INFO | Train Epoch: 13 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.059852 (0.087908) Boundary_loss: 0.013896 (0.013895) Loss: 0.073747 (0.10180) +2025-09-14,16:54:19 | INFO | Train Epoch: 13 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.098571 (0.090573) Boundary_loss: 0.013895 (0.013895) Loss: 0.11247 (0.10447) +2025-09-14,16:54:49 | INFO | Train Epoch: 13 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.12463 (0.097385) Boundary_loss: 0.013895 (0.013895) Loss: 0.13853 (0.11128) +2025-09-14,16:55:20 | INFO | Train Epoch: 13 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.069624 (0.092758) Boundary_loss: 0.013895 (0.013895) Loss: 0.083519 (0.10665) +2025-09-14,16:55:50 | INFO | Train Epoch: 13 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.069590 (0.089449) Boundary_loss: 0.013894 (0.013895) Loss: 0.083485 (0.10334) +2025-09-14,16:56:21 | INFO | Train Epoch: 13 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11050 (0.092080) Boundary_loss: 0.013894 (0.013895) Loss: 0.12440 (0.10598) +2025-09-14,16:56:52 | INFO | Train Epoch: 13 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.094264 (0.092323) Boundary_loss: 0.013895 (0.013895) Loss: 0.10816 (0.10622) +2025-09-14,16:57:22 | INFO | Train Epoch: 13 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.078601 (0.090951) Boundary_loss: 0.013894 (0.013895) Loss: 0.092495 (0.10485) +2025-09-14,16:57:53 | INFO | Train Epoch: 13 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13323 (0.094795) Boundary_loss: 0.013895 (0.013895) Loss: 0.14713 (0.10869) +2025-09-14,16:58:23 | INFO | Train Epoch: 13 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11281 (0.096296) Boundary_loss: 0.013895 (0.013895) Loss: 0.12670 (0.11019) +2025-09-14,16:58:54 | INFO | Train Epoch: 13 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.081498 (0.095158) Boundary_loss: 0.013895 (0.013895) Loss: 0.095393 (0.10905) +2025-09-14,16:59:24 | INFO | Train Epoch: 13 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13119 (0.097731) Boundary_loss: 0.013894 (0.013895) Loss: 0.14508 (0.11163) +2025-09-14,16:59:55 | INFO | Train Epoch: 13 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10870 (0.098462) Boundary_loss: 0.013895 (0.013895) Loss: 0.12259 (0.11236) +2025-09-14,17:00:26 | INFO | Train Epoch: 13 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.14018 (0.10107) Boundary_loss: 0.013894 (0.013895) Loss: 0.15407 (0.11496) +2025-09-14,17:00:56 | INFO | Train Epoch: 13 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.098894 (0.10094) Boundary_loss: 0.013896 (0.013895) Loss: 0.11279 (0.11484) +2025-09-14,17:01:27 | INFO | Train Epoch: 13 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.098465 (0.10080) Boundary_loss: 0.013895 (0.013895) Loss: 0.11236 (0.11470) +2025-09-14,17:01:57 | INFO | Train Epoch: 13 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.091076 (0.10029) Boundary_loss: 0.013895 (0.013895) Loss: 0.10497 (0.11419) +2025-09-14,17:02:28 | INFO | Train Epoch: 13 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.16344 (0.10345) Boundary_loss: 0.013895 (0.013895) Loss: 0.17733 (0.11734) +2025-09-14,17:02:58 | INFO | Train Epoch: 13 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.079044 (0.10229) Boundary_loss: 0.013894 (0.013895) Loss: 0.092939 (0.11618) +2025-09-14,17:03:29 | INFO | Train Epoch: 13 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.10336 (0.10234) Boundary_loss: 0.013895 (0.013895) Loss: 0.11725 (0.11623) +2025-09-14,17:03:59 | INFO | Train Epoch: 13 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.11704 (0.10297) Boundary_loss: 0.013894 (0.013895) Loss: 0.13093 (0.11687) +2025-09-14,17:04:30 | INFO | Train Epoch: 13 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.13840 (0.10445) Boundary_loss: 0.013895 (0.013895) Loss: 0.15229 (0.11835) +2025-09-14,17:05:00 | INFO | Train Epoch: 13 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.099154 (0.10424) Boundary_loss: 0.013895 (0.013895) Loss: 0.11305 (0.11813) +2025-09-14,17:05:31 | INFO | Train Epoch: 13 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.073234 (0.10305) Boundary_loss: 0.013894 (0.013895) Loss: 0.087128 (0.11694) +2025-09-14,17:06:02 | INFO | Train Epoch: 13 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10319 (0.10305) Boundary_loss: 0.013895 (0.013895) Loss: 0.11709 (0.11695) +2025-09-14,17:06:32 | INFO | Train Epoch: 13 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14072 (0.10440) Boundary_loss: 0.013895 (0.013895) Loss: 0.15461 (0.11829) +2025-09-14,17:07:03 | INFO | Train Epoch: 13 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12385 (0.10507) Boundary_loss: 0.013895 (0.013895) Loss: 0.13774 (0.11896) +2025-09-14,17:07:33 | INFO | Train Epoch: 13 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11948 (0.10555) Boundary_loss: 0.013894 (0.013895) Loss: 0.13337 (0.11944) +2025-09-14,17:08:04 | INFO | Train Epoch: 13 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10525 (0.10554) Boundary_loss: 0.013895 (0.013895) Loss: 0.11914 (0.11943) +2025-09-14,17:08:34 | INFO | Train Epoch: 13 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.089525 (0.10504) Boundary_loss: 0.013894 (0.013895) Loss: 0.10342 (0.11893) +2025-09-14,17:09:05 | INFO | Train Epoch: 13 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.072513 (0.10405) Boundary_loss: 0.013894 (0.013895) Loss: 0.086407 (0.11795) +2025-09-14,17:09:36 | INFO | Train Epoch: 13 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11711 (0.10444) Boundary_loss: 0.013895 (0.013895) Loss: 0.13100 (0.11833) +2025-09-14,17:10:06 | INFO | Train Epoch: 13 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12907 (0.10514) Boundary_loss: 0.013895 (0.013895) Loss: 0.14296 (0.11903) +2025-09-14,17:10:37 | INFO | Train Epoch: 13 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.092900 (0.10480) Boundary_loss: 0.013894 (0.013895) Loss: 0.10679 (0.11869) +2025-09-14,17:11:08 | INFO | Train Epoch: 13 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10435 (0.10479) Boundary_loss: 0.013894 (0.013895) Loss: 0.11825 (0.11868) +2025-09-14,17:11:38 | INFO | Train Epoch: 13 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.074158 (0.10398) Boundary_loss: 0.013894 (0.013895) Loss: 0.088053 (0.11788) +2025-09-14,17:12:09 | INFO | Train Epoch: 13 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10956 (0.10413) Boundary_loss: 0.013895 (0.013895) Loss: 0.12346 (0.11802) +2025-09-14,17:12:40 | INFO | Train Epoch: 13 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.097032 (0.10395) Boundary_loss: 0.013895 (0.013895) Loss: 0.11093 (0.11784) +2025-09-14,17:13:10 | INFO | Train Epoch: 13 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10808 (0.10405) Boundary_loss: 0.013895 (0.013895) Loss: 0.12197 (0.11794) +2025-09-14,17:13:41 | INFO | Train Epoch: 13 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12512 (0.10455) Boundary_loss: 0.013894 (0.013895) Loss: 0.13901 (0.11844) +2025-09-14,17:14:12 | INFO | Train Epoch: 13 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.088008 (0.10417) Boundary_loss: 0.013895 (0.013895) Loss: 0.10190 (0.11806) +2025-09-14,17:14:43 | INFO | Train Epoch: 13 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.080294 (0.10362) Boundary_loss: 0.013895 (0.013895) Loss: 0.094189 (0.11752) +2025-09-14,17:15:14 | INFO | Train Epoch: 13 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11309 (0.10383) Boundary_loss: 0.013895 (0.013895) Loss: 0.12698 (0.11773) +2025-09-14,17:15:45 | INFO | Train Epoch: 13 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.12038 (0.10419) Boundary_loss: 0.013895 (0.013895) Loss: 0.13427 (0.11809) +2025-09-14,17:16:15 | INFO | Train Epoch: 13 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.065889 (0.10338) Boundary_loss: 0.013895 (0.013895) Loss: 0.079784 (0.11727) +2025-09-14,17:16:46 | INFO | Train Epoch: 13 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.095745 (0.10322) Boundary_loss: 0.013894 (0.013895) Loss: 0.10964 (0.11711) +2025-09-14,17:17:17 | INFO | Train Epoch: 13 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.098448 (0.10312) Boundary_loss: 0.013896 (0.013895) Loss: 0.11234 (0.11702) +2025-09-14,17:17:48 | INFO | Train Epoch: 13 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.080427 (0.10267) Boundary_loss: 0.013895 (0.013895) Loss: 0.094322 (0.11656) +2025-09-14,17:18:18 | INFO | Train Epoch: 13 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.10029 (0.10262) Boundary_loss: 0.013894 (0.013895) Loss: 0.11418 (0.11652) +2025-09-14,17:18:49 | INFO | Train Epoch: 13 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.097061 (0.10251) Boundary_loss: 0.013897 (0.013895) Loss: 0.11096 (0.11641) +2025-09-14,17:19:20 | INFO | Train Epoch: 13 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10032 (0.10247) Boundary_loss: 0.013895 (0.013895) Loss: 0.11421 (0.11637) +2025-09-14,17:19:51 | INFO | Train Epoch: 13 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10497 (0.10252) Boundary_loss: 0.013894 (0.013895) Loss: 0.11886 (0.11641) +2025-09-14,17:20:22 | INFO | Train Epoch: 13 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10721 (0.10260) Boundary_loss: 0.013894 (0.013895) Loss: 0.12110 (0.11650) +2025-09-14,17:20:53 | INFO | Train Epoch: 13 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.062323 (0.10188) Boundary_loss: 0.013895 (0.013895) Loss: 0.076218 (0.11578) +2025-09-14,17:21:23 | INFO | Train Epoch: 13 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.098434 (0.10182) Boundary_loss: 0.013894 (0.013895) Loss: 0.11233 (0.11572) +2025-09-14,17:21:54 | INFO | Train Epoch: 13 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10810 (0.10193) Boundary_loss: 0.013896 (0.013895) Loss: 0.12199 (0.11583) +2025-09-14,17:22:25 | INFO | Train Epoch: 13 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.088731 (0.10171) Boundary_loss: 0.013894 (0.013895) Loss: 0.10263 (0.11560) +2025-09-14,17:22:56 | INFO | Train Epoch: 13 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13490 (0.10226) Boundary_loss: 0.013894 (0.013895) Loss: 0.14880 (0.11616) +2025-09-14,17:23:27 | INFO | Train Epoch: 13 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10691 (0.10234) Boundary_loss: 0.013894 (0.013895) Loss: 0.12080 (0.11623) +2025-09-14,17:23:57 | INFO | Train Epoch: 13 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.13521 (0.10287) Boundary_loss: 0.013894 (0.013895) Loss: 0.14911 (0.11676) +2025-09-14,17:24:28 | INFO | Train Epoch: 13 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10807 (0.10295) Boundary_loss: 0.013895 (0.013895) Loss: 0.12196 (0.11685) +2025-09-14,17:24:59 | INFO | Train Epoch: 13 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10511 (0.10298) Boundary_loss: 0.013895 (0.013895) Loss: 0.11900 (0.11688) +2025-09-14,17:25:30 | INFO | Train Epoch: 13 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11235 (0.10313) Boundary_loss: 0.013894 (0.013895) Loss: 0.12624 (0.11702) +2025-09-14,17:26:00 | INFO | Train Epoch: 13 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.092438 (0.10297) Boundary_loss: 0.013895 (0.013895) Loss: 0.10633 (0.11686) +2025-09-14,17:26:31 | INFO | Train Epoch: 13 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.094958 (0.10285) Boundary_loss: 0.013895 (0.013895) Loss: 0.10885 (0.11674) +2025-09-14,17:27:02 | INFO | Train Epoch: 13 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11934 (0.10309) Boundary_loss: 0.013894 (0.013895) Loss: 0.13324 (0.11698) +2025-09-14,17:27:32 | INFO | Train Epoch: 13 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.13342 (0.10353) Boundary_loss: 0.013895 (0.013895) Loss: 0.14731 (0.11742) +2025-09-14,17:28:03 | INFO | Train Epoch: 13 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.085760 (0.10328) Boundary_loss: 0.013894 (0.013895) Loss: 0.099655 (0.11717) +2025-09-14,17:28:34 | INFO | Train Epoch: 13 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11646 (0.10346) Boundary_loss: 0.013894 (0.013895) Loss: 0.13035 (0.11736) +2025-09-14,17:29:05 | INFO | Train Epoch: 13 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.11610 (0.10364) Boundary_loss: 0.013894 (0.013895) Loss: 0.12999 (0.11753) +2025-09-14,17:29:36 | INFO | Train Epoch: 13 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13002 (0.10400) Boundary_loss: 0.013895 (0.013895) Loss: 0.14391 (0.11789) +2025-09-14,17:30:07 | INFO | Train Epoch: 13 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10339 (0.10399) Boundary_loss: 0.013895 (0.013895) Loss: 0.11728 (0.11788) +2025-09-14,17:30:37 | INFO | Train Epoch: 13 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.086024 (0.10375) Boundary_loss: 0.013895 (0.013895) Loss: 0.099919 (0.11764) +2025-09-14,17:31:08 | INFO | Train Epoch: 13 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.054957 (0.10311) Boundary_loss: 0.013894 (0.013895) Loss: 0.068851 (0.11700) +2025-09-14,17:31:38 | INFO | Train Epoch: 13 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.085613 (0.10288) Boundary_loss: 0.013895 (0.013895) Loss: 0.099508 (0.11678) +2025-09-14,17:32:09 | INFO | Train Epoch: 13 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11294 (0.10301) Boundary_loss: 0.013895 (0.013895) Loss: 0.12684 (0.11690) +2025-09-14,17:32:40 | INFO | Train Epoch: 13 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.085089 (0.10278) Boundary_loss: 0.013895 (0.013895) Loss: 0.098984 (0.11668) +2025-09-14,17:33:11 | INFO | Train Epoch: 13 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.087412 (0.10259) Boundary_loss: 0.013894 (0.013895) Loss: 0.10131 (0.11649) +2025-09-14,17:33:42 | INFO | Train Epoch: 13 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10670 (0.10264) Boundary_loss: 0.013896 (0.013895) Loss: 0.12060 (0.11654) +2025-09-14,17:34:12 | INFO | Train Epoch: 13 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10866 (0.10272) Boundary_loss: 0.013894 (0.013895) Loss: 0.12255 (0.11661) +2025-09-14,17:34:43 | INFO | Train Epoch: 13 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11004 (0.10280) Boundary_loss: 0.013894 (0.013895) Loss: 0.12394 (0.11670) +2025-09-14,17:35:14 | INFO | Train Epoch: 13 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.080766 (0.10254) Boundary_loss: 0.013895 (0.013895) Loss: 0.094661 (0.11644) +2025-09-14,17:35:45 | INFO | Train Epoch: 13 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14875 (0.10308) Boundary_loss: 0.013895 (0.013895) Loss: 0.16265 (0.11698) +2025-09-14,17:36:15 | INFO | Train Epoch: 13 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12602 (0.10335) Boundary_loss: 0.013896 (0.013895) Loss: 0.13991 (0.11725) +2025-09-14,17:36:46 | INFO | Train Epoch: 13 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.081933 (0.10311) Boundary_loss: 0.013895 (0.013895) Loss: 0.095828 (0.11700) +2025-09-14,17:37:17 | INFO | Train Epoch: 13 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.099604 (0.10307) Boundary_loss: 0.013895 (0.013895) Loss: 0.11350 (0.11696) +2025-09-14,17:37:48 | INFO | Train Epoch: 13 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.069466 (0.10269) Boundary_loss: 0.013895 (0.013895) Loss: 0.083361 (0.11658) +2025-09-14,17:38:19 | INFO | Train Epoch: 13 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.11031 (0.10277) Boundary_loss: 0.013896 (0.013895) Loss: 0.12421 (0.11667) +2025-09-14,17:38:50 | INFO | Train Epoch: 13 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.077493 (0.10249) Boundary_loss: 0.013895 (0.013895) Loss: 0.091388 (0.11639) +2025-09-14,17:39:21 | INFO | Train Epoch: 13 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10205 (0.10249) Boundary_loss: 0.013895 (0.013895) Loss: 0.11595 (0.11638) +2025-09-14,17:39:51 | INFO | Train Epoch: 13 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11453 (0.10262) Boundary_loss: 0.013895 (0.013895) Loss: 0.12843 (0.11651) +2025-09-14,17:40:22 | INFO | Train Epoch: 13 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10243 (0.10262) Boundary_loss: 0.013895 (0.013895) Loss: 0.11632 (0.11651) +2025-09-14,17:40:53 | INFO | Train Epoch: 13 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13020 (0.10291) Boundary_loss: 0.013895 (0.013895) Loss: 0.14409 (0.11680) +2025-09-14,17:41:23 | INFO | Train Epoch: 13 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.091998 (0.10279) Boundary_loss: 0.013897 (0.013895) Loss: 0.10589 (0.11669) +2025-09-14,17:41:54 | INFO | Train Epoch: 13 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.094744 (0.10271) Boundary_loss: 0.013895 (0.013895) Loss: 0.10864 (0.11661) +2025-09-14,17:42:25 | INFO | Train Epoch: 13 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11453 (0.10283) Boundary_loss: 0.013895 (0.013895) Loss: 0.12843 (0.11673) +2025-09-14,17:42:56 | INFO | Train Epoch: 13 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.093914 (0.10274) Boundary_loss: 0.013894 (0.013895) Loss: 0.10781 (0.11664) +2025-09-14,17:43:27 | INFO | Train Epoch: 13 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.12668 (0.10298) Boundary_loss: 0.013895 (0.013895) Loss: 0.14058 (0.11688) +2025-09-14,17:43:57 | INFO | Train Epoch: 13 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.11241 (0.10307) Boundary_loss: 0.013894 (0.013895) Loss: 0.12630 (0.11697) +2025-09-14,17:44:28 | INFO | Train Epoch: 13 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.098834 (0.10303) Boundary_loss: 0.013894 (0.013895) Loss: 0.11273 (0.11693) +2025-09-14,17:44:59 | INFO | Train Epoch: 13 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11401 (0.10314) Boundary_loss: 0.013894 (0.013895) Loss: 0.12791 (0.11703) +2025-09-14,17:45:30 | INFO | Train Epoch: 13 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.074866 (0.10287) Boundary_loss: 0.013895 (0.013895) Loss: 0.088761 (0.11676) +2025-09-14,17:46:01 | INFO | Train Epoch: 13 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10098 (0.10285) Boundary_loss: 0.013895 (0.013895) Loss: 0.11487 (0.11674) +2025-09-14,17:46:32 | INFO | Train Epoch: 13 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10519 (0.10287) Boundary_loss: 0.013895 (0.013895) Loss: 0.11908 (0.11677) +2025-09-14,17:47:02 | INFO | Train Epoch: 13 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12857 (0.10311) Boundary_loss: 0.013895 (0.013895) Loss: 0.14247 (0.11701) +2025-09-14,17:47:33 | INFO | Train Epoch: 13 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.096681 (0.10305) Boundary_loss: 0.013895 (0.013895) Loss: 0.11058 (0.11695) +2025-09-14,17:48:04 | INFO | Train Epoch: 13 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11440 (0.10316) Boundary_loss: 0.013895 (0.013895) Loss: 0.12829 (0.11705) +2025-09-14,17:48:34 | INFO | Train Epoch: 13 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.093149 (0.10307) Boundary_loss: 0.013895 (0.013895) Loss: 0.10704 (0.11696) +2025-09-14,17:49:05 | INFO | Train Epoch: 13 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12610 (0.10327) Boundary_loss: 0.013895 (0.013895) Loss: 0.14000 (0.11717) +2025-09-14,17:49:36 | INFO | Train Epoch: 13 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.071646 (0.10299) Boundary_loss: 0.013894 (0.013895) Loss: 0.085541 (0.11689) +2025-09-14,17:50:07 | INFO | Train Epoch: 13 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.081474 (0.10280) Boundary_loss: 0.013896 (0.013895) Loss: 0.095370 (0.11669) +2025-09-14,17:50:37 | INFO | Train Epoch: 13 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12424 (0.10299) Boundary_loss: 0.013896 (0.013895) Loss: 0.13814 (0.11688) +2025-09-14,17:51:08 | INFO | Train Epoch: 13 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14228 (0.10333) Boundary_loss: 0.013895 (0.013895) Loss: 0.15618 (0.11722) +2025-09-14,17:51:39 | INFO | Train Epoch: 13 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10060 (0.10331) Boundary_loss: 0.013894 (0.013895) Loss: 0.11450 (0.11720) +2025-09-14,17:52:10 | INFO | Train Epoch: 13 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.13414 (0.10357) Boundary_loss: 0.013894 (0.013895) Loss: 0.14803 (0.11746) +2025-09-14,17:52:40 | INFO | Train Epoch: 13 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.060355 (0.10320) Boundary_loss: 0.013895 (0.013895) Loss: 0.074249 (0.11710) +2025-09-14,17:53:11 | INFO | Train Epoch: 13 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.074305 (0.10296) Boundary_loss: 0.013895 (0.013895) Loss: 0.088200 (0.11686) +2025-09-14,17:53:42 | INFO | Train Epoch: 13 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.095632 (0.10290) Boundary_loss: 0.013895 (0.013895) Loss: 0.10953 (0.11679) +2025-09-14,17:54:13 | INFO | Train Epoch: 13 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.074842 (0.10267) Boundary_loss: 0.013896 (0.013895) Loss: 0.088737 (0.11656) +2025-09-14,17:54:43 | INFO | Train Epoch: 13 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.075213 (0.10244) Boundary_loss: 0.013894 (0.013895) Loss: 0.089108 (0.11634) +2025-09-14,17:55:14 | INFO | Train Epoch: 13 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.066335 (0.10215) Boundary_loss: 0.013895 (0.013895) Loss: 0.080230 (0.11604) +2025-09-14,17:55:45 | INFO | Train Epoch: 13 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.082108 (0.10199) Boundary_loss: 0.013895 (0.013895) Loss: 0.096003 (0.11588) +2025-09-14,17:56:15 | INFO | Train Epoch: 13 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.099291 (0.10197) Boundary_loss: 0.013895 (0.013895) Loss: 0.11319 (0.11586) +2025-09-14,17:56:46 | INFO | Train Epoch: 13 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.074085 (0.10174) Boundary_loss: 0.013894 (0.013895) Loss: 0.087979 (0.11564) +2025-09-14,17:57:17 | INFO | Train Epoch: 13 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.096456 (0.10170) Boundary_loss: 0.013895 (0.013895) Loss: 0.11035 (0.11560) +2025-09-14,17:57:47 | INFO | Train Epoch: 13 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13175 (0.10194) Boundary_loss: 0.013895 (0.013895) Loss: 0.14564 (0.11583) +2025-09-14,17:58:18 | INFO | Train Epoch: 13 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.094817 (0.10188) Boundary_loss: 0.013895 (0.013895) Loss: 0.10871 (0.11578) +2025-09-14,17:58:49 | INFO | Train Epoch: 13 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10961 (0.10194) Boundary_loss: 0.013896 (0.013895) Loss: 0.12350 (0.11584) +2025-09-14,17:59:19 | INFO | Train Epoch: 13 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12346 (0.10211) Boundary_loss: 0.013894 (0.013895) Loss: 0.13735 (0.11600) +2025-09-14,17:59:50 | INFO | Train Epoch: 13 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12199 (0.10226) Boundary_loss: 0.013895 (0.013895) Loss: 0.13588 (0.11615) +2025-09-14,18:00:20 | INFO | Train Epoch: 13 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.071015 (0.10202) Boundary_loss: 0.013894 (0.013895) Loss: 0.084909 (0.11592) +2025-09-14,18:00:51 | INFO | Train Epoch: 13 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.088254 (0.10192) Boundary_loss: 0.013894 (0.013895) Loss: 0.10215 (0.11581) +2025-09-14,18:01:21 | INFO | Train Epoch: 13 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.097332 (0.10189) Boundary_loss: 0.013894 (0.013895) Loss: 0.11123 (0.11578) +2025-09-14,18:01:52 | INFO | Train Epoch: 13 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.11037 (0.10195) Boundary_loss: 0.013896 (0.013895) Loss: 0.12426 (0.11584) +2025-09-14,18:02:23 | INFO | Train Epoch: 13 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11503 (0.10204) Boundary_loss: 0.013895 (0.013895) Loss: 0.12892 (0.11594) +2025-09-14,18:02:54 | INFO | Train Epoch: 13 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11861 (0.10216) Boundary_loss: 0.013895 (0.013895) Loss: 0.13251 (0.11606) +2025-09-14,18:03:24 | INFO | Train Epoch: 13 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.097954 (0.10213) Boundary_loss: 0.013894 (0.013895) Loss: 0.11185 (0.11603) +2025-09-14,18:03:55 | INFO | Train Epoch: 13 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.10087 (0.10212) Boundary_loss: 0.013894 (0.013895) Loss: 0.11476 (0.11602) +2025-09-14,18:04:25 | INFO | Train Epoch: 13 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10450 (0.10214) Boundary_loss: 0.013895 (0.013895) Loss: 0.11839 (0.11604) +2025-09-14,18:04:56 | INFO | Train Epoch: 13 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10349 (0.10215) Boundary_loss: 0.013894 (0.013895) Loss: 0.11739 (0.11605) +2025-09-14,18:05:26 | INFO | Train Epoch: 13 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12239 (0.10229) Boundary_loss: 0.013895 (0.013895) Loss: 0.13629 (0.11619) +2025-09-14,18:05:57 | INFO | Train Epoch: 13 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11425 (0.10237) Boundary_loss: 0.013895 (0.013895) Loss: 0.12815 (0.11627) +2025-09-14,18:06:28 | INFO | Train Epoch: 13 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.12323 (0.10252) Boundary_loss: 0.013895 (0.013895) Loss: 0.13713 (0.11641) +2025-09-14,18:06:59 | INFO | Train Epoch: 13 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12017 (0.10264) Boundary_loss: 0.013895 (0.013895) Loss: 0.13406 (0.11653) +2025-09-14,18:07:29 | INFO | Train Epoch: 13 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.098724 (0.10261) Boundary_loss: 0.013895 (0.013895) Loss: 0.11262 (0.11651) +2025-09-14,18:08:00 | INFO | Train Epoch: 13 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.095652 (0.10257) Boundary_loss: 0.013896 (0.013895) Loss: 0.10955 (0.11646) +2025-09-14,18:08:31 | INFO | Train Epoch: 13 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.074932 (0.10238) Boundary_loss: 0.013896 (0.013895) Loss: 0.088828 (0.11628) +2025-09-14,18:09:02 | INFO | Train Epoch: 13 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.090866 (0.10230) Boundary_loss: 0.013895 (0.013895) Loss: 0.10476 (0.11620) +2025-09-14,18:09:33 | INFO | Train Epoch: 13 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.062703 (0.10204) Boundary_loss: 0.013894 (0.013895) Loss: 0.076597 (0.11594) +2025-09-14,18:10:04 | INFO | Train Epoch: 13 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.081652 (0.10191) Boundary_loss: 0.013895 (0.013895) Loss: 0.095547 (0.11580) +2025-09-14,18:10:34 | INFO | Train Epoch: 13 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.096792 (0.10187) Boundary_loss: 0.013894 (0.013895) Loss: 0.11069 (0.11577) +2025-09-14,18:11:05 | INFO | Train Epoch: 13 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.091696 (0.10181) Boundary_loss: 0.013894 (0.013895) Loss: 0.10559 (0.11570) +2025-09-14,18:11:36 | INFO | Train Epoch: 13 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.069530 (0.10160) Boundary_loss: 0.013894 (0.013895) Loss: 0.083424 (0.11549) +2025-09-14,18:12:07 | INFO | Train Epoch: 13 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10883 (0.10165) Boundary_loss: 0.013895 (0.013895) Loss: 0.12272 (0.11554) +2025-09-14,18:12:37 | INFO | Train Epoch: 13 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12936 (0.10182) Boundary_loss: 0.013894 (0.013895) Loss: 0.14326 (0.11572) +2025-09-14,18:13:08 | INFO | Train Epoch: 13 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.086354 (0.10172) Boundary_loss: 0.013894 (0.013895) Loss: 0.10025 (0.11562) +2025-09-14,18:13:39 | INFO | Train Epoch: 13 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11288 (0.10179) Boundary_loss: 0.013895 (0.013895) Loss: 0.12677 (0.11569) +2025-09-14,18:14:10 | INFO | Train Epoch: 13 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10772 (0.10183) Boundary_loss: 0.013895 (0.013895) Loss: 0.12161 (0.11573) +2025-09-14,18:14:41 | INFO | Train Epoch: 13 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11133 (0.10189) Boundary_loss: 0.013894 (0.013895) Loss: 0.12522 (0.11579) +2025-09-14,18:15:12 | INFO | Train Epoch: 13 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.082122 (0.10177) Boundary_loss: 0.013895 (0.013895) Loss: 0.096017 (0.11566) +2025-09-14,18:15:42 | INFO | Train Epoch: 13 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10959 (0.10182) Boundary_loss: 0.013895 (0.013895) Loss: 0.12348 (0.11571) +2025-09-14,18:16:13 | INFO | Train Epoch: 13 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.090972 (0.10175) Boundary_loss: 0.013895 (0.013895) Loss: 0.10487 (0.11565) +2025-09-14,18:16:44 | INFO | Train Epoch: 13 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10517 (0.10177) Boundary_loss: 0.013894 (0.013895) Loss: 0.11906 (0.11567) +2025-09-14,18:17:14 | INFO | Train Epoch: 13 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11003 (0.10182) Boundary_loss: 0.013895 (0.013895) Loss: 0.12393 (0.11572) +2025-09-14,18:17:45 | INFO | Train Epoch: 13 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.084556 (0.10172) Boundary_loss: 0.013894 (0.013895) Loss: 0.098451 (0.11561) +2025-09-14,18:18:16 | INFO | Train Epoch: 13 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.096857 (0.10169) Boundary_loss: 0.013895 (0.013895) Loss: 0.11075 (0.11558) +2025-09-14,18:18:47 | INFO | Train Epoch: 13 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.086838 (0.10160) Boundary_loss: 0.013895 (0.013895) Loss: 0.10073 (0.11550) +2025-09-14,18:19:18 | INFO | Train Epoch: 13 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.087089 (0.10152) Boundary_loss: 0.013896 (0.013895) Loss: 0.10098 (0.11541) +2025-09-14,18:19:48 | INFO | Train Epoch: 13 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.092523 (0.10146) Boundary_loss: 0.013895 (0.013895) Loss: 0.10642 (0.11536) +2025-09-14,18:20:19 | INFO | Train Epoch: 13 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.092723 (0.10141) Boundary_loss: 0.013895 (0.013895) Loss: 0.10662 (0.11531) +2025-09-14,18:20:49 | INFO | Train Epoch: 13 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.068265 (0.10122) Boundary_loss: 0.013895 (0.013895) Loss: 0.082160 (0.11512) +2025-09-14,18:21:20 | INFO | Train Epoch: 13 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.084560 (0.10112) Boundary_loss: 0.013895 (0.013895) Loss: 0.098456 (0.11502) +2025-09-14,18:21:51 | INFO | Train Epoch: 13 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.086595 (0.10104) Boundary_loss: 0.013895 (0.013895) Loss: 0.10049 (0.11494) +2025-09-14,18:22:22 | INFO | Train Epoch: 13 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10740 (0.10108) Boundary_loss: 0.013895 (0.013895) Loss: 0.12130 (0.11497) +2025-09-14,18:22:52 | INFO | Train Epoch: 13 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.10494 (0.10110) Boundary_loss: 0.013894 (0.013895) Loss: 0.11883 (0.11499) +2025-09-14,18:23:23 | INFO | Train Epoch: 13 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10312 (0.10111) Boundary_loss: 0.013895 (0.013895) Loss: 0.11701 (0.11501) +2025-09-14,18:23:54 | INFO | Train Epoch: 13 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.099712 (0.10110) Boundary_loss: 0.013895 (0.013895) Loss: 0.11361 (0.11500) +2025-09-14,18:24:25 | INFO | Train Epoch: 13 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.10755 (0.10114) Boundary_loss: 0.013894 (0.013895) Loss: 0.12144 (0.11503) +2025-09-14,18:24:56 | INFO | Train Epoch: 13 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.082489 (0.10104) Boundary_loss: 0.013895 (0.013895) Loss: 0.096384 (0.11493) +2025-09-14,18:25:26 | INFO | Train Epoch: 13 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.074333 (0.10089) Boundary_loss: 0.013894 (0.013895) Loss: 0.088227 (0.11478) +2025-09-14,18:25:57 | INFO | Train Epoch: 13 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13288 (0.10106) Boundary_loss: 0.013895 (0.013895) Loss: 0.14677 (0.11496) +2025-09-14,18:26:28 | INFO | Train Epoch: 13 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.099174 (0.10105) Boundary_loss: 0.013895 (0.013895) Loss: 0.11307 (0.11495) +2025-09-14,18:26:58 | INFO | Train Epoch: 13 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.090740 (0.10100) Boundary_loss: 0.013894 (0.013895) Loss: 0.10463 (0.11489) +2025-09-14,18:27:29 | INFO | Train Epoch: 13 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.098653 (0.10099) Boundary_loss: 0.013895 (0.013895) Loss: 0.11255 (0.11488) +2025-09-14,18:28:00 | INFO | Train Epoch: 13 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.12305 (0.10110) Boundary_loss: 0.013894 (0.013895) Loss: 0.13694 (0.11500) +2025-09-14,18:28:31 | INFO | Train Epoch: 13 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10273 (0.10111) Boundary_loss: 0.013895 (0.013895) Loss: 0.11663 (0.11501) +2025-09-14,18:29:01 | INFO | Train Epoch: 13 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11413 (0.10118) Boundary_loss: 0.013895 (0.013895) Loss: 0.12802 (0.11508) +2025-09-14,18:29:32 | INFO | Train Epoch: 13 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12860 (0.10133) Boundary_loss: 0.013895 (0.013895) Loss: 0.14249 (0.11522) +2025-09-14,18:30:03 | INFO | Train Epoch: 13 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10771 (0.10136) Boundary_loss: 0.013895 (0.013895) Loss: 0.12160 (0.11525) +2025-09-14,18:30:34 | INFO | Train Epoch: 13 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.10725 (0.10139) Boundary_loss: 0.013894 (0.013895) Loss: 0.12114 (0.11528) +2025-09-14,18:31:05 | INFO | Train Epoch: 13 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11943 (0.10148) Boundary_loss: 0.013894 (0.013895) Loss: 0.13333 (0.11538) +2025-09-14,18:31:35 | INFO | Train Epoch: 13 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.077899 (0.10136) Boundary_loss: 0.013895 (0.013895) Loss: 0.091795 (0.11526) +2025-09-14,18:32:06 | INFO | Train Epoch: 13 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10505 (0.10138) Boundary_loss: 0.013894 (0.013895) Loss: 0.11895 (0.11527) +2025-09-14,18:32:37 | INFO | Train Epoch: 13 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.078772 (0.10126) Boundary_loss: 0.013895 (0.013895) Loss: 0.092667 (0.11516) +2025-09-14,18:33:08 | INFO | Train Epoch: 13 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10381 (0.10128) Boundary_loss: 0.013895 (0.013895) Loss: 0.11771 (0.11517) +2025-09-14,18:33:38 | INFO | Train Epoch: 13 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.084160 (0.10119) Boundary_loss: 0.013895 (0.013895) Loss: 0.098055 (0.11509) +2025-09-14,18:34:09 | INFO | Train Epoch: 13 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10443 (0.10121) Boundary_loss: 0.013895 (0.013895) Loss: 0.11833 (0.11510) +2025-09-14,18:34:40 | INFO | Train Epoch: 13 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.10066 (0.10120) Boundary_loss: 0.013894 (0.013895) Loss: 0.11456 (0.11510) +2025-09-14,18:35:11 | INFO | Train Epoch: 13 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11920 (0.10129) Boundary_loss: 0.013894 (0.013895) Loss: 0.13309 (0.11519) +2025-09-14,18:35:41 | INFO | Train Epoch: 13 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.097203 (0.10127) Boundary_loss: 0.013894 (0.013895) Loss: 0.11110 (0.11517) +2025-09-14,18:36:12 | INFO | Train Epoch: 13 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.092159 (0.10123) Boundary_loss: 0.013895 (0.013895) Loss: 0.10605 (0.11512) +2025-09-14,18:36:43 | INFO | Train Epoch: 13 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.13467 (0.10139) Boundary_loss: 0.013894 (0.013895) Loss: 0.14856 (0.11529) +2025-09-14,18:37:13 | INFO | Train Epoch: 13 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11682 (0.10147) Boundary_loss: 0.013895 (0.013895) Loss: 0.13071 (0.11536) +2025-09-14,18:37:44 | INFO | Train Epoch: 13 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.099264 (0.10146) Boundary_loss: 0.013894 (0.013895) Loss: 0.11316 (0.11535) +2025-09-14,18:38:15 | INFO | Train Epoch: 13 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.081275 (0.10136) Boundary_loss: 0.013895 (0.013895) Loss: 0.095170 (0.11525) +2025-09-14,18:38:46 | INFO | Train Epoch: 13 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.079032 (0.10125) Boundary_loss: 0.013895 (0.013895) Loss: 0.092927 (0.11515) +2025-09-14,18:39:17 | INFO | Train Epoch: 13 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10268 (0.10126) Boundary_loss: 0.013895 (0.013895) Loss: 0.11658 (0.11515) +2025-09-14,18:39:47 | INFO | Train Epoch: 13 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.072524 (0.10112) Boundary_loss: 0.013894 (0.013895) Loss: 0.086418 (0.11502) +2025-09-14,18:40:18 | INFO | Train Epoch: 13 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11095 (0.10117) Boundary_loss: 0.013894 (0.013895) Loss: 0.12484 (0.11506) +2025-09-14,18:40:48 | INFO | Train Epoch: 13 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.087739 (0.10111) Boundary_loss: 0.013895 (0.013895) Loss: 0.10163 (0.11500) +2025-09-14,18:41:19 | INFO | Train Epoch: 13 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.081475 (0.10101) Boundary_loss: 0.013895 (0.013895) Loss: 0.095370 (0.11491) +2025-09-14,18:41:50 | INFO | Train Epoch: 13 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.081234 (0.10092) Boundary_loss: 0.013895 (0.013895) Loss: 0.095129 (0.11482) +2025-09-14,18:42:21 | INFO | Train Epoch: 13 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11614 (0.10099) Boundary_loss: 0.013895 (0.013895) Loss: 0.13003 (0.11489) +2025-09-14,18:42:52 | INFO | Train Epoch: 13 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.091449 (0.10095) Boundary_loss: 0.013894 (0.013895) Loss: 0.10534 (0.11484) +2025-09-14,18:43:22 | INFO | Train Epoch: 13 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.071509 (0.10081) Boundary_loss: 0.013895 (0.013895) Loss: 0.085404 (0.11471) +2025-09-14,18:43:53 | INFO | Train Epoch: 13 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11435 (0.10087) Boundary_loss: 0.013895 (0.013895) Loss: 0.12824 (0.11477) +2025-09-14,18:44:24 | INFO | Train Epoch: 13 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.087699 (0.10081) Boundary_loss: 0.013894 (0.013895) Loss: 0.10159 (0.11471) +2025-09-14,18:44:55 | INFO | Train Epoch: 13 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11285 (0.10087) Boundary_loss: 0.013895 (0.013895) Loss: 0.12674 (0.11476) +2025-09-14,18:45:25 | INFO | Train Epoch: 13 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.079070 (0.10077) Boundary_loss: 0.013896 (0.013895) Loss: 0.092966 (0.11467) +2025-09-14,18:45:56 | INFO | Train Epoch: 13 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.063300 (0.10060) Boundary_loss: 0.013894 (0.013895) Loss: 0.077194 (0.11450) +2025-09-14,18:46:27 | INFO | Train Epoch: 13 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.071115 (0.10047) Boundary_loss: 0.013895 (0.013895) Loss: 0.085010 (0.11436) +2025-09-14,18:46:57 | INFO | Train Epoch: 13 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.11413 (0.10053) Boundary_loss: 0.013895 (0.013895) Loss: 0.12803 (0.11443) +2025-09-14,18:47:28 | INFO | Train Epoch: 13 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.12404 (0.10063) Boundary_loss: 0.013894 (0.013895) Loss: 0.13793 (0.11453) +2025-09-14,18:47:59 | INFO | Train Epoch: 13 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.078214 (0.10054) Boundary_loss: 0.013895 (0.013895) Loss: 0.092109 (0.11443) +2025-09-14,18:48:30 | INFO | Train Epoch: 13 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.099725 (0.10053) Boundary_loss: 0.013894 (0.013895) Loss: 0.11362 (0.11443) +2025-09-14,18:49:01 | INFO | Train Epoch: 13 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.11742 (0.10061) Boundary_loss: 0.013894 (0.013895) Loss: 0.13131 (0.11450) +2025-09-14,18:49:31 | INFO | Train Epoch: 13 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.085434 (0.10054) Boundary_loss: 0.013894 (0.013895) Loss: 0.099328 (0.11443) +2025-09-14,18:50:02 | INFO | Train Epoch: 13 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.062894 (0.10038) Boundary_loss: 0.013895 (0.013895) Loss: 0.076790 (0.11427) +2025-09-14,18:50:33 | INFO | Train Epoch: 13 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.085282 (0.10031) Boundary_loss: 0.013895 (0.013895) Loss: 0.099177 (0.11421) +2025-09-14,18:51:03 | INFO | Train Epoch: 13 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.079771 (0.10022) Boundary_loss: 0.013895 (0.013895) Loss: 0.093666 (0.11412) +2025-09-14,18:51:34 | INFO | Train Epoch: 13 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.055427 (0.10003) Boundary_loss: 0.013895 (0.013895) Loss: 0.069323 (0.11392) +2025-09-14,18:52:04 | INFO | Train Epoch: 13 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12066 (0.10012) Boundary_loss: 0.013895 (0.013895) Loss: 0.13455 (0.11401) +2025-09-14,18:52:35 | INFO | Train Epoch: 13 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.14014 (0.10029) Boundary_loss: 0.013895 (0.013895) Loss: 0.15404 (0.11418) +2025-09-14,18:53:06 | INFO | Train Epoch: 13 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.077320 (0.10019) Boundary_loss: 0.013895 (0.013895) Loss: 0.091216 (0.11409) +2025-09-14,18:53:37 | INFO | Train Epoch: 13 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10177 (0.10020) Boundary_loss: 0.013895 (0.013895) Loss: 0.11566 (0.11409) +2025-09-14,18:54:07 | INFO | Train Epoch: 13 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12476 (0.10030) Boundary_loss: 0.013895 (0.013895) Loss: 0.13866 (0.11420) +2025-09-14,18:54:38 | INFO | Train Epoch: 13 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10427 (0.10032) Boundary_loss: 0.013894 (0.013895) Loss: 0.11816 (0.11421) +2025-09-14,18:55:08 | INFO | Train Epoch: 13 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.074334 (0.10021) Boundary_loss: 0.013895 (0.013895) Loss: 0.088229 (0.11410) +2025-09-14,18:55:39 | INFO | Train Epoch: 13 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.099389 (0.10021) Boundary_loss: 0.013894 (0.013895) Loss: 0.11328 (0.11410) +2025-09-14,18:56:10 | INFO | Train Epoch: 13 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.11951 (0.10029) Boundary_loss: 0.013894 (0.013895) Loss: 0.13341 (0.11418) +2025-09-14,18:56:41 | INFO | Train Epoch: 13 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.098534 (0.10028) Boundary_loss: 0.013894 (0.013895) Loss: 0.11243 (0.11417) +2025-09-14,18:57:12 | INFO | Train Epoch: 13 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.14457 (0.10046) Boundary_loss: 0.013894 (0.013895) Loss: 0.15846 (0.11435) +2025-09-14,18:57:43 | INFO | Train Epoch: 13 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10895 (0.10049) Boundary_loss: 0.013895 (0.013895) Loss: 0.12284 (0.11439) +2025-09-14,18:58:14 | INFO | Train Epoch: 13 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13277 (0.10063) Boundary_loss: 0.013894 (0.013895) Loss: 0.14666 (0.11452) +2025-09-14,18:58:44 | INFO | Train Epoch: 13 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10669 (0.10065) Boundary_loss: 0.013895 (0.013895) Loss: 0.12058 (0.11455) +2025-09-14,18:59:15 | INFO | Train Epoch: 13 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.071780 (0.10053) Boundary_loss: 0.013894 (0.013895) Loss: 0.085674 (0.11443) +2025-09-14,18:59:46 | INFO | Train Epoch: 13 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11639 (0.10060) Boundary_loss: 0.013895 (0.013895) Loss: 0.13028 (0.11449) +2025-09-14,19:00:17 | INFO | Train Epoch: 13 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.058261 (0.10043) Boundary_loss: 0.013894 (0.013895) Loss: 0.072156 (0.11432) +2025-09-14,19:00:48 | INFO | Train Epoch: 13 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11679 (0.10049) Boundary_loss: 0.013895 (0.013895) Loss: 0.13069 (0.11439) +2025-09-14,19:01:19 | INFO | Train Epoch: 13 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.099918 (0.10049) Boundary_loss: 0.013895 (0.013895) Loss: 0.11381 (0.11439) +2025-09-14,19:01:50 | INFO | Train Epoch: 13 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.074740 (0.10039) Boundary_loss: 0.013895 (0.013895) Loss: 0.088634 (0.11428) +2025-09-14,19:02:20 | INFO | Train Epoch: 13 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.087355 (0.10034) Boundary_loss: 0.013895 (0.013895) Loss: 0.10125 (0.11423) +2025-09-14,19:02:51 | INFO | Train Epoch: 13 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10286 (0.10035) Boundary_loss: 0.013895 (0.013895) Loss: 0.11675 (0.11424) +2025-09-14,19:03:22 | INFO | Train Epoch: 13 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.099502 (0.10034) Boundary_loss: 0.013895 (0.013895) Loss: 0.11340 (0.11424) +2025-09-14,19:03:53 | INFO | Train Epoch: 13 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.085975 (0.10029) Boundary_loss: 0.013896 (0.013895) Loss: 0.099871 (0.11418) +2025-09-14,19:04:23 | INFO | Train Epoch: 13 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11268 (0.10034) Boundary_loss: 0.013895 (0.013895) Loss: 0.12657 (0.11423) +2025-09-14,19:04:54 | INFO | Train Epoch: 13 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.075313 (0.10024) Boundary_loss: 0.013894 (0.013895) Loss: 0.089207 (0.11413) +2025-09-14,19:05:25 | INFO | Train Epoch: 13 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.093100 (0.10021) Boundary_loss: 0.013895 (0.013895) Loss: 0.10700 (0.11411) +2025-09-14,19:05:56 | INFO | Train Epoch: 13 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10932 (0.10025) Boundary_loss: 0.013894 (0.013895) Loss: 0.12321 (0.11414) +2025-09-14,19:06:26 | INFO | Train Epoch: 13 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.060557 (0.10010) Boundary_loss: 0.013896 (0.013895) Loss: 0.074452 (0.11399) +2025-09-14,19:06:57 | INFO | Train Epoch: 13 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.12064 (0.10017) Boundary_loss: 0.013894 (0.013895) Loss: 0.13453 (0.11407) +2025-09-14,19:07:28 | INFO | Train Epoch: 13 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.097989 (0.10017) Boundary_loss: 0.013895 (0.013895) Loss: 0.11188 (0.11406) +2025-09-14,19:07:59 | INFO | Train Epoch: 13 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11290 (0.10021) Boundary_loss: 0.013894 (0.013895) Loss: 0.12679 (0.11411) +2025-09-14,19:08:29 | INFO | Train Epoch: 13 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.091334 (0.10018) Boundary_loss: 0.013895 (0.013895) Loss: 0.10523 (0.11408) +2025-09-14,19:09:00 | INFO | Train Epoch: 13 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.067332 (0.10006) Boundary_loss: 0.013895 (0.013895) Loss: 0.081228 (0.11395) +2025-09-14,19:09:31 | INFO | Train Epoch: 13 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.086009 (0.10001) Boundary_loss: 0.013896 (0.013895) Loss: 0.099904 (0.11390) +2025-09-14,19:10:02 | INFO | Train Epoch: 13 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.11696 (0.10007) Boundary_loss: 0.013894 (0.013895) Loss: 0.13085 (0.11396) +2025-09-14,19:10:33 | INFO | Train Epoch: 13 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11541 (0.10013) Boundary_loss: 0.013894 (0.013895) Loss: 0.12930 (0.11402) +2025-09-14,19:11:04 | INFO | Train Epoch: 13 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.092597 (0.10010) Boundary_loss: 0.013895 (0.013895) Loss: 0.10649 (0.11399) +2025-09-14,19:11:35 | INFO | Train Epoch: 13 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.098113 (0.10009) Boundary_loss: 0.013894 (0.013895) Loss: 0.11201 (0.11398) +2025-09-14,19:12:05 | INFO | Train Epoch: 13 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.098009 (0.10008) Boundary_loss: 0.013895 (0.013895) Loss: 0.11190 (0.11398) +2025-09-14,19:12:36 | INFO | Train Epoch: 13 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10223 (0.10009) Boundary_loss: 0.013895 (0.013895) Loss: 0.11612 (0.11398) +2025-09-14,19:13:07 | INFO | Train Epoch: 13 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.083254 (0.10003) Boundary_loss: 0.013893 (0.013895) Loss: 0.097147 (0.11392) +2025-09-14,19:13:38 | INFO | Train Epoch: 13 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10085 (0.10003) Boundary_loss: 0.013895 (0.013895) Loss: 0.11474 (0.11393) +2025-09-14,19:14:09 | INFO | Train Epoch: 13 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.094371 (0.10001) Boundary_loss: 0.013894 (0.013895) Loss: 0.10827 (0.11391) +2025-09-14,19:14:39 | INFO | Train Epoch: 13 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.089015 (0.099972) Boundary_loss: 0.013895 (0.013895) Loss: 0.10291 (0.11387) +2025-09-14,19:15:10 | INFO | Train Epoch: 13 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.096540 (0.099960) Boundary_loss: 0.013894 (0.013895) Loss: 0.11043 (0.11385) +2025-09-14,19:15:41 | INFO | Train Epoch: 13 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.10354 (0.099972) Boundary_loss: 0.013894 (0.013895) Loss: 0.11744 (0.11387) +2025-09-14,19:16:11 | INFO | Train Epoch: 13 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.086108 (0.099923) Boundary_loss: 0.013894 (0.013895) Loss: 0.10000 (0.11382) +2025-09-14,19:16:42 | INFO | Train Epoch: 13 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12857 (0.10002) Boundary_loss: 0.013894 (0.013895) Loss: 0.14246 (0.11392) +2025-09-14,19:17:12 | INFO | Train Epoch: 13 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.097355 (0.10002) Boundary_loss: 0.013895 (0.013895) Loss: 0.11125 (0.11391) +2025-09-14,19:17:43 | INFO | Train Epoch: 13 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10188 (0.10002) Boundary_loss: 0.013894 (0.013895) Loss: 0.11577 (0.11392) +2025-09-14,19:18:14 | INFO | Train Epoch: 13 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10032 (0.10002) Boundary_loss: 0.013894 (0.013895) Loss: 0.11421 (0.11392) +2025-09-14,19:18:44 | INFO | Train Epoch: 13 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11188 (0.10006) Boundary_loss: 0.013895 (0.013895) Loss: 0.12578 (0.11396) +2025-09-14,19:19:15 | INFO | Train Epoch: 13 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.066547 (0.099947) Boundary_loss: 0.013895 (0.013895) Loss: 0.080442 (0.11384) +2025-09-14,19:19:46 | INFO | Train Epoch: 13 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13453 (0.10007) Boundary_loss: 0.013895 (0.013895) Loss: 0.14842 (0.11396) +2025-09-14,19:20:16 | INFO | Train Epoch: 13 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10069 (0.10007) Boundary_loss: 0.013895 (0.013895) Loss: 0.11459 (0.11396) +2025-09-14,19:20:47 | INFO | Train Epoch: 13 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.096445 (0.10006) Boundary_loss: 0.013895 (0.013895) Loss: 0.11034 (0.11395) +2025-09-14,19:21:18 | INFO | Train Epoch: 13 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.074586 (0.099970) Boundary_loss: 0.013895 (0.013895) Loss: 0.088480 (0.11386) +2025-09-14,19:21:48 | INFO | Train Epoch: 13 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.083609 (0.099914) Boundary_loss: 0.013894 (0.013895) Loss: 0.097503 (0.11381) +2025-09-14,19:22:19 | INFO | Train Epoch: 13 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11444 (0.099963) Boundary_loss: 0.013894 (0.013895) Loss: 0.12834 (0.11386) +2025-09-14,19:22:50 | INFO | Train Epoch: 13 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.14019 (0.10010) Boundary_loss: 0.013894 (0.013895) Loss: 0.15408 (0.11399) +2025-09-14,19:23:21 | INFO | Train Epoch: 13 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.083443 (0.10004) Boundary_loss: 0.013894 (0.013895) Loss: 0.097336 (0.11394) +2025-09-14,19:23:51 | INFO | Train Epoch: 13 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.084819 (0.099992) Boundary_loss: 0.013895 (0.013895) Loss: 0.098714 (0.11389) +2025-09-14,19:24:22 | INFO | Train Epoch: 13 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10034 (0.099993) Boundary_loss: 0.013894 (0.013895) Loss: 0.11423 (0.11389) +2025-09-14,19:24:53 | INFO | Train Epoch: 13 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.079322 (0.099924) Boundary_loss: 0.013895 (0.013895) Loss: 0.093217 (0.11382) +2025-09-14,19:25:23 | INFO | Train Epoch: 13 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.083105 (0.099868) Boundary_loss: 0.013895 (0.013895) Loss: 0.097000 (0.11376) +2025-09-14,19:25:54 | INFO | Train Epoch: 13 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.092473 (0.099843) Boundary_loss: 0.013896 (0.013895) Loss: 0.10637 (0.11374) +2025-09-14,19:26:25 | INFO | Train Epoch: 13 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.12312 (0.099920) Boundary_loss: 0.013895 (0.013895) Loss: 0.13702 (0.11382) +2025-09-14,19:26:56 | INFO | Train Epoch: 13 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.080579 (0.099856) Boundary_loss: 0.013895 (0.013895) Loss: 0.094475 (0.11375) +2025-09-14,19:27:27 | INFO | Train Epoch: 13 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12121 (0.099927) Boundary_loss: 0.013894 (0.013895) Loss: 0.13511 (0.11382) +2025-09-14,19:27:57 | INFO | Train Epoch: 13 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10718 (0.099951) Boundary_loss: 0.013894 (0.013895) Loss: 0.12107 (0.11385) +2025-09-14,19:28:28 | INFO | Train Epoch: 13 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.081740 (0.099891) Boundary_loss: 0.013894 (0.013895) Loss: 0.095634 (0.11379) +2025-09-14,19:28:59 | INFO | Train Epoch: 13 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11957 (0.099955) Boundary_loss: 0.013894 (0.013895) Loss: 0.13346 (0.11385) +2025-09-14,19:29:30 | INFO | Train Epoch: 13 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10312 (0.099966) Boundary_loss: 0.013897 (0.013895) Loss: 0.11702 (0.11386) +2025-09-14,19:30:01 | INFO | Train Epoch: 13 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.086087 (0.099921) Boundary_loss: 0.013895 (0.013895) Loss: 0.099982 (0.11382) +2025-09-14,19:30:32 | INFO | Train Epoch: 13 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.098681 (0.099917) Boundary_loss: 0.013894 (0.013895) Loss: 0.11258 (0.11381) +2025-09-14,19:31:02 | INFO | Train Epoch: 13 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.090179 (0.099885) Boundary_loss: 0.013895 (0.013895) Loss: 0.10407 (0.11378) +2025-09-14,19:31:33 | INFO | Train Epoch: 13 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.098852 (0.099882) Boundary_loss: 0.013895 (0.013895) Loss: 0.11275 (0.11378) +2025-09-14,19:32:04 | INFO | Train Epoch: 13 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12274 (0.099955) Boundary_loss: 0.013895 (0.013895) Loss: 0.13663 (0.11385) +2025-09-14,19:32:35 | INFO | Train Epoch: 13 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10310 (0.099965) Boundary_loss: 0.013895 (0.013895) Loss: 0.11699 (0.11386) +2025-09-14,19:33:05 | INFO | Train Epoch: 13 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.093764 (0.099945) Boundary_loss: 0.013894 (0.013895) Loss: 0.10766 (0.11384) +2025-09-14,19:33:36 | INFO | Train Epoch: 13 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11874 (0.10001) Boundary_loss: 0.013895 (0.013895) Loss: 0.13263 (0.11390) +2025-09-14,19:34:07 | INFO | Train Epoch: 13 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.081522 (0.099947) Boundary_loss: 0.013895 (0.013895) Loss: 0.095417 (0.11384) +2025-09-14,19:34:38 | INFO | Train Epoch: 13 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11218 (0.099985) Boundary_loss: 0.013895 (0.013895) Loss: 0.12607 (0.11388) +2025-09-14,19:35:09 | INFO | Train Epoch: 13 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.085959 (0.099941) Boundary_loss: 0.013896 (0.013895) Loss: 0.099855 (0.11384) +2025-09-14,19:35:39 | INFO | Train Epoch: 13 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10428 (0.099955) Boundary_loss: 0.013894 (0.013895) Loss: 0.11817 (0.11385) +2025-09-14,19:36:10 | INFO | Train Epoch: 13 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.083997 (0.099905) Boundary_loss: 0.013895 (0.013895) Loss: 0.097892 (0.11380) +2025-09-14,19:36:41 | INFO | Train Epoch: 13 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10052 (0.099907) Boundary_loss: 0.013896 (0.013895) Loss: 0.11441 (0.11380) +2025-09-14,19:37:12 | INFO | Train Epoch: 13 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.087000 (0.099867) Boundary_loss: 0.013895 (0.013895) Loss: 0.10090 (0.11376) +2025-09-14,19:37:42 | INFO | Train Epoch: 13 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.093813 (0.099848) Boundary_loss: 0.013895 (0.013895) Loss: 0.10771 (0.11374) +2025-09-14,19:38:13 | INFO | Train Epoch: 13 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.092268 (0.099824) Boundary_loss: 0.013895 (0.013895) Loss: 0.10616 (0.11372) +2025-09-14,19:38:44 | INFO | Train Epoch: 13 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.096674 (0.099815) Boundary_loss: 0.013896 (0.013895) Loss: 0.11057 (0.11371) +2025-09-14,19:39:15 | INFO | Train Epoch: 13 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11012 (0.099846) Boundary_loss: 0.013895 (0.013895) Loss: 0.12402 (0.11374) +2025-09-14,19:39:46 | INFO | Train Epoch: 13 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.084856 (0.099800) Boundary_loss: 0.013894 (0.013895) Loss: 0.098750 (0.11370) +2025-09-14,19:40:16 | INFO | Train Epoch: 13 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10686 (0.099822) Boundary_loss: 0.013895 (0.013895) Loss: 0.12075 (0.11372) +2025-09-14,19:40:47 | INFO | Train Epoch: 13 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.068483 (0.099727) Boundary_loss: 0.013894 (0.013895) Loss: 0.082378 (0.11362) +2025-09-14,19:41:18 | INFO | Train Epoch: 13 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.15295 (0.099888) Boundary_loss: 0.013894 (0.013895) Loss: 0.16685 (0.11378) +2025-09-14,19:41:48 | INFO | Train Epoch: 13 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10259 (0.099896) Boundary_loss: 0.013895 (0.013895) Loss: 0.11648 (0.11379) +2025-09-14,19:42:19 | INFO | Train Epoch: 13 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.069140 (0.099804) Boundary_loss: 0.013895 (0.013895) Loss: 0.083035 (0.11370) +2025-09-14,19:42:50 | INFO | Train Epoch: 13 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.086495 (0.099764) Boundary_loss: 0.013894 (0.013895) Loss: 0.10039 (0.11366) +2025-09-14,19:43:20 | INFO | Train Epoch: 13 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.064566 (0.099658) Boundary_loss: 0.013895 (0.013895) Loss: 0.078462 (0.11355) +2025-09-14,19:43:51 | INFO | Train Epoch: 13 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.095130 (0.099645) Boundary_loss: 0.013896 (0.013895) Loss: 0.10903 (0.11354) +2025-09-14,19:44:21 | INFO | Train Epoch: 13 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.089496 (0.099614) Boundary_loss: 0.013895 (0.013895) Loss: 0.10339 (0.11351) +2025-09-14,19:44:52 | INFO | Train Epoch: 13 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.074626 (0.099540) Boundary_loss: 0.013894 (0.013895) Loss: 0.088520 (0.11344) +2025-09-14,19:45:22 | INFO | Train Epoch: 13 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.086842 (0.099503) Boundary_loss: 0.013894 (0.013895) Loss: 0.10074 (0.11340) +2025-09-14,19:45:53 | INFO | Train Epoch: 13 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.12628 (0.099582) Boundary_loss: 0.013894 (0.013895) Loss: 0.14018 (0.11348) +2025-09-14,19:46:24 | INFO | Train Epoch: 13 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.12123 (0.099645) Boundary_loss: 0.013895 (0.013895) Loss: 0.13512 (0.11354) +2025-09-14,19:46:55 | INFO | Train Epoch: 13 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.092725 (0.099625) Boundary_loss: 0.013894 (0.013895) Loss: 0.10662 (0.11352) +2025-09-14,19:47:25 | INFO | Train Epoch: 13 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.079514 (0.099566) Boundary_loss: 0.013895 (0.013895) Loss: 0.093410 (0.11346) +2025-09-14,19:47:56 | INFO | Train Epoch: 13 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10854 (0.099592) Boundary_loss: 0.013895 (0.013895) Loss: 0.12243 (0.11349) +2025-09-14,19:48:27 | INFO | Train Epoch: 13 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.065366 (0.099493) Boundary_loss: 0.013895 (0.013895) Loss: 0.079260 (0.11339) +2025-09-14,19:48:57 | INFO | Train Epoch: 13 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.072552 (0.099415) Boundary_loss: 0.013895 (0.013895) Loss: 0.086447 (0.11331) +2025-09-14,19:49:28 | INFO | Train Epoch: 13 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12844 (0.099499) Boundary_loss: 0.013895 (0.013895) Loss: 0.14233 (0.11339) +2025-09-14,19:49:59 | INFO | Train Epoch: 13 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10336 (0.099510) Boundary_loss: 0.013894 (0.013895) Loss: 0.11726 (0.11340) +2025-09-14,19:50:29 | INFO | Train Epoch: 13 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10362 (0.099522) Boundary_loss: 0.013895 (0.013895) Loss: 0.11751 (0.11342) +2025-09-14,19:51:00 | INFO | Train Epoch: 13 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.073172 (0.099446) Boundary_loss: 0.013894 (0.013895) Loss: 0.087067 (0.11334) +2025-09-14,19:51:31 | INFO | Train Epoch: 13 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.12689 (0.099525) Boundary_loss: 0.013895 (0.013895) Loss: 0.14078 (0.11342) +2025-09-14,19:52:02 | INFO | Train Epoch: 13 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.098687 (0.099522) Boundary_loss: 0.013894 (0.013895) Loss: 0.11258 (0.11342) +2025-09-14,19:52:32 | INFO | Train Epoch: 13 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.069075 (0.099436) Boundary_loss: 0.013895 (0.013895) Loss: 0.082970 (0.11333) +2025-09-14,19:53:03 | INFO | Train Epoch: 13 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.091413 (0.099413) Boundary_loss: 0.013894 (0.013895) Loss: 0.10531 (0.11331) +2025-09-14,19:53:34 | INFO | Train Epoch: 13 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10527 (0.099430) Boundary_loss: 0.013896 (0.013895) Loss: 0.11916 (0.11332) +2025-09-14,19:54:05 | INFO | Train Epoch: 13 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.054335 (0.099303) Boundary_loss: 0.013894 (0.013895) Loss: 0.068229 (0.11320) +2025-09-14,19:54:35 | INFO | Train Epoch: 13 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12213 (0.099367) Boundary_loss: 0.013895 (0.013895) Loss: 0.13603 (0.11326) +2025-09-14,19:55:06 | INFO | Train Epoch: 13 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.091412 (0.099344) Boundary_loss: 0.013896 (0.013895) Loss: 0.10531 (0.11324) +2025-09-14,19:55:37 | INFO | Train Epoch: 13 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.079844 (0.099290) Boundary_loss: 0.013895 (0.013895) Loss: 0.093739 (0.11318) +2025-09-14,19:56:08 | INFO | Train Epoch: 13 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.12985 (0.099375) Boundary_loss: 0.013894 (0.013895) Loss: 0.14375 (0.11327) +2025-09-14,19:56:38 | INFO | Train Epoch: 13 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10351 (0.099387) Boundary_loss: 0.013894 (0.013895) Loss: 0.11740 (0.11328) +2025-09-14,19:57:09 | INFO | Train Epoch: 13 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.13020 (0.099472) Boundary_loss: 0.013895 (0.013895) Loss: 0.14409 (0.11337) +2025-09-14,19:57:40 | INFO | Train Epoch: 13 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.061870 (0.099368) Boundary_loss: 0.013895 (0.013895) Loss: 0.075766 (0.11326) +2025-09-14,19:58:11 | INFO | Train Epoch: 13 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.11420 (0.099409) Boundary_loss: 0.013894 (0.013895) Loss: 0.12810 (0.11330) +2025-09-14,19:58:41 | INFO | Train Epoch: 13 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11459 (0.099451) Boundary_loss: 0.013894 (0.013895) Loss: 0.12848 (0.11335) +2025-09-14,19:59:12 | INFO | Train Epoch: 13 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10613 (0.099469) Boundary_loss: 0.013894 (0.013895) Loss: 0.12002 (0.11336) +2025-09-14,19:59:43 | INFO | Train Epoch: 13 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.093253 (0.099452) Boundary_loss: 0.013896 (0.013895) Loss: 0.10715 (0.11335) +2025-09-14,20:00:13 | INFO | Train Epoch: 13 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.12984 (0.099535) Boundary_loss: 0.013895 (0.013895) Loss: 0.14374 (0.11343) +2025-09-14,20:00:44 | INFO | Train Epoch: 13 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.067853 (0.099449) Boundary_loss: 0.013894 (0.013895) Loss: 0.081748 (0.11334) +2025-09-14,20:01:15 | INFO | Train Epoch: 13 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.085077 (0.099410) Boundary_loss: 0.013894 (0.013895) Loss: 0.098971 (0.11330) +2025-09-14,20:01:45 | INFO | Train Epoch: 13 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.080519 (0.099359) Boundary_loss: 0.013895 (0.013895) Loss: 0.094414 (0.11325) +2025-09-14,20:02:16 | INFO | Train Epoch: 13 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.089522 (0.099332) Boundary_loss: 0.013895 (0.013895) Loss: 0.10342 (0.11323) +2025-09-14,20:02:47 | INFO | Train Epoch: 13 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10471 (0.099347) Boundary_loss: 0.013895 (0.013895) Loss: 0.11860 (0.11324) +2025-09-14,20:03:18 | INFO | Train Epoch: 13 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10287 (0.099356) Boundary_loss: 0.013894 (0.013895) Loss: 0.11677 (0.11325) +2025-09-14,20:03:48 | INFO | Train Epoch: 13 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.093543 (0.099340) Boundary_loss: 0.013895 (0.013895) Loss: 0.10744 (0.11324) +2025-09-14,20:04:19 | INFO | Train Epoch: 13 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.087773 (0.099310) Boundary_loss: 0.013895 (0.013895) Loss: 0.10167 (0.11320) +2025-09-14,20:04:49 | INFO | Train Epoch: 13 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.076181 (0.099248) Boundary_loss: 0.013895 (0.013895) Loss: 0.090077 (0.11314) +2025-09-14,20:05:20 | INFO | Train Epoch: 13 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.065491 (0.099159) Boundary_loss: 0.013895 (0.013895) Loss: 0.079386 (0.11305) +2025-09-14,20:05:51 | INFO | Train Epoch: 13 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.080004 (0.099108) Boundary_loss: 0.013894 (0.013895) Loss: 0.093898 (0.11300) +2025-09-14,20:06:21 | INFO | Train Epoch: 13 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11701 (0.099155) Boundary_loss: 0.013895 (0.013895) Loss: 0.13090 (0.11305) +2025-09-14,20:06:52 | INFO | Train Epoch: 13 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.096257 (0.099147) Boundary_loss: 0.013895 (0.013895) Loss: 0.11015 (0.11304) +2025-09-14,20:07:23 | INFO | Train Epoch: 13 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.14401 (0.099265) Boundary_loss: 0.013894 (0.013895) Loss: 0.15791 (0.11316) +2025-09-14,20:07:54 | INFO | Train Epoch: 13 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.080599 (0.099216) Boundary_loss: 0.013894 (0.013895) Loss: 0.094493 (0.11311) +2025-09-14,20:08:24 | INFO | Train Epoch: 13 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10132 (0.099222) Boundary_loss: 0.013895 (0.013895) Loss: 0.11521 (0.11312) +2025-09-14,20:08:55 | INFO | Train Epoch: 13 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.096387 (0.099214) Boundary_loss: 0.013895 (0.013895) Loss: 0.11028 (0.11311) +2025-09-14,20:09:26 | INFO | Train Epoch: 13 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13496 (0.099307) Boundary_loss: 0.013894 (0.013895) Loss: 0.14885 (0.11320) +2025-09-14,20:09:56 | INFO | Train Epoch: 13 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.096819 (0.099301) Boundary_loss: 0.013895 (0.013895) Loss: 0.11071 (0.11320) +2025-09-14,20:10:27 | INFO | Train Epoch: 13 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.096315 (0.099293) Boundary_loss: 0.013895 (0.013895) Loss: 0.11021 (0.11319) +2025-09-14,20:10:58 | INFO | Train Epoch: 13 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.095328 (0.099283) Boundary_loss: 0.013894 (0.013895) Loss: 0.10922 (0.11318) +2025-09-14,20:11:28 | INFO | Train Epoch: 13 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.089814 (0.099259) Boundary_loss: 0.013894 (0.013895) Loss: 0.10371 (0.11315) +2025-09-14,20:11:59 | INFO | Train Epoch: 13 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.098055 (0.099256) Boundary_loss: 0.013895 (0.013895) Loss: 0.11195 (0.11315) +2025-09-14,20:12:30 | INFO | Train Epoch: 13 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10056 (0.099259) Boundary_loss: 0.013895 (0.013895) Loss: 0.11445 (0.11315) +2025-09-14,20:13:01 | INFO | Train Epoch: 13 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.10233 (0.099267) Boundary_loss: 0.013894 (0.013895) Loss: 0.11622 (0.11316) +2025-09-14,20:13:31 | INFO | Train Epoch: 13 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.081727 (0.099222) Boundary_loss: 0.013895 (0.013895) Loss: 0.095623 (0.11312) +2025-09-14,20:14:02 | INFO | Train Epoch: 13 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.077648 (0.099167) Boundary_loss: 0.013894 (0.013895) Loss: 0.091542 (0.11306) +2025-09-14,20:14:32 | INFO | Train Epoch: 13 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10078 (0.099171) Boundary_loss: 0.013894 (0.013895) Loss: 0.11467 (0.11307) +2025-09-14,20:15:03 | INFO | Train Epoch: 13 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.087376 (0.099142) Boundary_loss: 0.013895 (0.013895) Loss: 0.10127 (0.11304) +2025-09-14,20:15:34 | INFO | Train Epoch: 13 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.079608 (0.099092) Boundary_loss: 0.013895 (0.013895) Loss: 0.093503 (0.11299) +2025-09-14,20:16:04 | INFO | Train Epoch: 13 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.088712 (0.099066) Boundary_loss: 0.013894 (0.013895) Loss: 0.10261 (0.11296) +2025-09-14,20:16:35 | INFO | Train Epoch: 13 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10345 (0.099077) Boundary_loss: 0.013895 (0.013895) Loss: 0.11735 (0.11297) +2025-09-14,20:17:05 | INFO | Train Epoch: 13 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.079134 (0.099027) Boundary_loss: 0.013894 (0.013895) Loss: 0.093029 (0.11292) +2025-09-14,20:17:36 | INFO | Train Epoch: 13 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.10596 (0.099045) Boundary_loss: 0.013894 (0.013895) Loss: 0.11985 (0.11294) +2025-09-14,20:18:07 | INFO | Train Epoch: 13 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.092324 (0.099028) Boundary_loss: 0.013895 (0.013895) Loss: 0.10622 (0.11292) +2025-09-14,20:18:38 | INFO | Train Epoch: 13 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.088593 (0.099002) Boundary_loss: 0.013895 (0.013895) Loss: 0.10249 (0.11290) +2025-09-14,20:19:08 | INFO | Train Epoch: 13 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.062768 (0.098912) Boundary_loss: 0.013895 (0.013895) Loss: 0.076663 (0.11281) +2025-09-14,20:19:39 | INFO | Train Epoch: 13 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.086742 (0.098882) Boundary_loss: 0.013895 (0.013895) Loss: 0.10064 (0.11278) +2025-09-14,20:20:10 | INFO | Train Epoch: 13 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.084085 (0.098846) Boundary_loss: 0.013896 (0.013895) Loss: 0.097981 (0.11274) +2025-09-14,20:20:40 | INFO | Train Epoch: 13 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10805 (0.098869) Boundary_loss: 0.013895 (0.013895) Loss: 0.12194 (0.11276) +2025-09-14,20:21:11 | INFO | Train Epoch: 13 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.084720 (0.098834) Boundary_loss: 0.013896 (0.013895) Loss: 0.098615 (0.11273) +2025-09-14,20:21:42 | INFO | Train Epoch: 13 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10824 (0.098857) Boundary_loss: 0.013894 (0.013895) Loss: 0.12213 (0.11275) +2025-09-14,20:22:13 | INFO | Train Epoch: 13 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.068569 (0.098783) Boundary_loss: 0.013895 (0.013895) Loss: 0.082464 (0.11268) +2025-09-14,20:22:43 | INFO | Train Epoch: 13 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.075134 (0.098725) Boundary_loss: 0.013895 (0.013895) Loss: 0.089029 (0.11262) +2025-09-14,20:23:14 | INFO | Train Epoch: 13 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.093130 (0.098712) Boundary_loss: 0.013894 (0.013895) Loss: 0.10702 (0.11261) +2025-09-14,20:23:45 | INFO | Train Epoch: 13 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11256 (0.098745) Boundary_loss: 0.013894 (0.013895) Loss: 0.12646 (0.11264) +2025-09-14,20:24:16 | INFO | Train Epoch: 13 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.092248 (0.098730) Boundary_loss: 0.013894 (0.013895) Loss: 0.10614 (0.11262) +2025-09-14,20:24:46 | INFO | Train Epoch: 13 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.11249 (0.098763) Boundary_loss: 0.013895 (0.013895) Loss: 0.12639 (0.11266) +2025-09-14,20:25:17 | INFO | Train Epoch: 13 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.089723 (0.098741) Boundary_loss: 0.013895 (0.013895) Loss: 0.10362 (0.11264) +2025-09-14,20:25:48 | INFO | Train Epoch: 13 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.087033 (0.098713) Boundary_loss: 0.013894 (0.013895) Loss: 0.10093 (0.11261) +2025-09-14,20:26:18 | INFO | Train Epoch: 13 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.095320 (0.098705) Boundary_loss: 0.013895 (0.013895) Loss: 0.10922 (0.11260) +2025-09-14,20:26:49 | INFO | Train Epoch: 13 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10796 (0.098727) Boundary_loss: 0.013895 (0.013895) Loss: 0.12185 (0.11262) +2025-09-14,20:27:20 | INFO | Train Epoch: 13 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10868 (0.098751) Boundary_loss: 0.013894 (0.013895) Loss: 0.12258 (0.11265) +2025-09-14,20:27:50 | INFO | Train Epoch: 13 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.092905 (0.098737) Boundary_loss: 0.013895 (0.013895) Loss: 0.10680 (0.11263) +2025-09-14,20:28:21 | INFO | Train Epoch: 13 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10839 (0.098760) Boundary_loss: 0.013895 (0.013895) Loss: 0.12228 (0.11265) +2025-09-14,20:28:51 | INFO | Train Epoch: 13 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.078273 (0.098711) Boundary_loss: 0.013894 (0.013895) Loss: 0.092167 (0.11261) +2025-09-14,20:29:22 | INFO | Train Epoch: 13 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.097574 (0.098709) Boundary_loss: 0.013895 (0.013895) Loss: 0.11147 (0.11260) +2025-09-14,20:29:52 | INFO | Train Epoch: 13 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.082991 (0.098672) Boundary_loss: 0.013895 (0.013895) Loss: 0.096885 (0.11257) +2025-09-14,20:30:23 | INFO | Train Epoch: 13 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11214 (0.098703) Boundary_loss: 0.013895 (0.013895) Loss: 0.12603 (0.11260) +2025-09-14,20:30:53 | INFO | Train Epoch: 13 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.079503 (0.098658) Boundary_loss: 0.013895 (0.013895) Loss: 0.093398 (0.11255) +2025-09-14,20:31:24 | INFO | Train Epoch: 13 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.091589 (0.098642) Boundary_loss: 0.013895 (0.013895) Loss: 0.10548 (0.11254) +2025-09-14,20:31:55 | INFO | Train Epoch: 13 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11000 (0.098668) Boundary_loss: 0.013895 (0.013895) Loss: 0.12389 (0.11256) +2025-09-14,20:32:25 | INFO | Train Epoch: 13 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10411 (0.098681) Boundary_loss: 0.013894 (0.013895) Loss: 0.11800 (0.11258) +2025-09-14,20:32:56 | INFO | Train Epoch: 13 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12969 (0.098753) Boundary_loss: 0.013894 (0.013895) Loss: 0.14359 (0.11265) +2025-09-14,20:33:26 | INFO | Train Epoch: 13 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.071082 (0.098689) Boundary_loss: 0.013896 (0.013895) Loss: 0.084977 (0.11258) +2025-09-14,20:33:57 | INFO | Train Epoch: 13 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.095156 (0.098681) Boundary_loss: 0.013894 (0.013895) Loss: 0.10905 (0.11258) +2025-09-14,20:34:27 | INFO | Train Epoch: 13 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.087648 (0.098655) Boundary_loss: 0.013895 (0.013895) Loss: 0.10154 (0.11255) +2025-09-14,20:34:58 | INFO | Train Epoch: 13 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.089945 (0.098635) Boundary_loss: 0.013895 (0.013895) Loss: 0.10384 (0.11253) +2025-09-14,20:35:29 | INFO | Train Epoch: 13 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10491 (0.098650) Boundary_loss: 0.013894 (0.013895) Loss: 0.11881 (0.11254) +2025-09-14,20:35:59 | INFO | Train Epoch: 13 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.13125 (0.098724) Boundary_loss: 0.013894 (0.013895) Loss: 0.14514 (0.11262) +2025-09-14,20:36:30 | INFO | Train Epoch: 13 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.077552 (0.098676) Boundary_loss: 0.013894 (0.013895) Loss: 0.091446 (0.11257) +2025-09-14,20:37:01 | INFO | Train Epoch: 13 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.092755 (0.098662) Boundary_loss: 0.013894 (0.013895) Loss: 0.10665 (0.11256) +2025-09-14,20:37:31 | INFO | Train Epoch: 13 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.069918 (0.098597) Boundary_loss: 0.013896 (0.013895) Loss: 0.083814 (0.11249) +2025-09-14,20:38:02 | INFO | Train Epoch: 13 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.092290 (0.098583) Boundary_loss: 0.013895 (0.013895) Loss: 0.10619 (0.11248) +2025-09-14,20:38:33 | INFO | Train Epoch: 13 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.083486 (0.098549) Boundary_loss: 0.013895 (0.013895) Loss: 0.097381 (0.11244) +2025-09-14,20:39:04 | INFO | Train Epoch: 13 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.074097 (0.098493) Boundary_loss: 0.013894 (0.013895) Loss: 0.087991 (0.11239) +2025-09-14,20:39:34 | INFO | Train Epoch: 13 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.099870 (0.098496) Boundary_loss: 0.013895 (0.013895) Loss: 0.11376 (0.11239) +2025-09-14,20:40:05 | INFO | Train Epoch: 13 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.083219 (0.098462) Boundary_loss: 0.013894 (0.013895) Loss: 0.097114 (0.11236) +2025-09-14,20:40:36 | INFO | Train Epoch: 13 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12232 (0.098516) Boundary_loss: 0.013895 (0.013895) Loss: 0.13621 (0.11241) +2025-09-14,20:41:06 | INFO | Train Epoch: 13 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12034 (0.098564) Boundary_loss: 0.013895 (0.013895) Loss: 0.13424 (0.11246) +2025-09-14,20:41:37 | INFO | Train Epoch: 13 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10705 (0.098583) Boundary_loss: 0.013894 (0.013895) Loss: 0.12094 (0.11248) +2025-09-14,20:42:08 | INFO | Train Epoch: 13 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.073999 (0.098529) Boundary_loss: 0.013895 (0.013895) Loss: 0.087894 (0.11242) +2025-09-14,20:42:39 | INFO | Train Epoch: 13 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12857 (0.098595) Boundary_loss: 0.013896 (0.013895) Loss: 0.14247 (0.11249) +2025-09-14,20:43:10 | INFO | Train Epoch: 13 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.11239 (0.098626) Boundary_loss: 0.013894 (0.013895) Loss: 0.12628 (0.11252) +2025-09-14,20:43:40 | INFO | Train Epoch: 13 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.084915 (0.098596) Boundary_loss: 0.013894 (0.013895) Loss: 0.098809 (0.11249) +2025-09-14,20:44:11 | INFO | Train Epoch: 13 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.084704 (0.098565) Boundary_loss: 0.013895 (0.013895) Loss: 0.098599 (0.11246) +2025-09-14,20:44:42 | INFO | Train Epoch: 13 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.086833 (0.098539) Boundary_loss: 0.013895 (0.013895) Loss: 0.10073 (0.11243) +2025-09-14,20:45:12 | INFO | Train Epoch: 13 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.084271 (0.098508) Boundary_loss: 0.013894 (0.013895) Loss: 0.098166 (0.11240) +2025-09-14,20:45:43 | INFO | Train Epoch: 13 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.073972 (0.098454) Boundary_loss: 0.013894 (0.013895) Loss: 0.087866 (0.11235) +2025-09-14,20:46:14 | INFO | Train Epoch: 13 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.11197 (0.098484) Boundary_loss: 0.013895 (0.013895) Loss: 0.12586 (0.11238) +2025-09-14,20:46:44 | INFO | Train Epoch: 13 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.085737 (0.098456) Boundary_loss: 0.013895 (0.013895) Loss: 0.099632 (0.11235) +2025-09-14,20:47:15 | INFO | Train Epoch: 13 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.096289 (0.098451) Boundary_loss: 0.013894 (0.013895) Loss: 0.11018 (0.11235) +2025-09-14,20:47:46 | INFO | Train Epoch: 13 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.073496 (0.098397) Boundary_loss: 0.013895 (0.013895) Loss: 0.087390 (0.11229) +2025-09-14,20:48:16 | INFO | Train Epoch: 13 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.080107 (0.098357) Boundary_loss: 0.013894 (0.013895) Loss: 0.094002 (0.11225) +2025-09-14,20:48:47 | INFO | Train Epoch: 13 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.091360 (0.098342) Boundary_loss: 0.013895 (0.013895) Loss: 0.10525 (0.11224) +2025-09-14,20:49:18 | INFO | Train Epoch: 13 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12044 (0.098390) Boundary_loss: 0.013895 (0.013895) Loss: 0.13433 (0.11228) +2025-09-14,20:49:49 | INFO | Train Epoch: 13 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11275 (0.098421) Boundary_loss: 0.013894 (0.013895) Loss: 0.12665 (0.11232) +2025-09-14,20:50:19 | INFO | Train Epoch: 13 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10257 (0.098430) Boundary_loss: 0.013895 (0.013895) Loss: 0.11647 (0.11232) +2025-09-14,20:50:50 | INFO | Train Epoch: 13 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.095840 (0.098424) Boundary_loss: 0.013895 (0.013895) Loss: 0.10973 (0.11232) +2025-09-14,20:51:21 | INFO | Train Epoch: 13 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.096711 (0.098420) Boundary_loss: 0.013895 (0.013895) Loss: 0.11061 (0.11232) +2025-09-14,20:51:52 | INFO | Train Epoch: 13 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.095186 (0.098413) Boundary_loss: 0.013896 (0.013895) Loss: 0.10908 (0.11231) +2025-09-14,20:52:23 | INFO | Train Epoch: 13 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.098447 (0.098413) Boundary_loss: 0.013894 (0.013895) Loss: 0.11234 (0.11231) +2025-09-14,20:52:53 | INFO | Train Epoch: 13 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12993 (0.098481) Boundary_loss: 0.013895 (0.013895) Loss: 0.14382 (0.11238) +2025-09-14,20:53:24 | INFO | Train Epoch: 13 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11487 (0.098515) Boundary_loss: 0.013894 (0.013895) Loss: 0.12876 (0.11241) +2025-09-14,20:53:55 | INFO | Train Epoch: 13 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.084888 (0.098486) Boundary_loss: 0.013895 (0.013895) Loss: 0.098783 (0.11238) +2025-09-14,20:54:25 | INFO | Train Epoch: 13 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11283 (0.098517) Boundary_loss: 0.013895 (0.013895) Loss: 0.12672 (0.11241) +2025-09-14,20:54:56 | INFO | Train Epoch: 13 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.075787 (0.098469) Boundary_loss: 0.013894 (0.013895) Loss: 0.089681 (0.11236) +2025-09-14,20:55:27 | INFO | Train Epoch: 13 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.12151 (0.098517) Boundary_loss: 0.013894 (0.013895) Loss: 0.13541 (0.11241) +2025-09-14,20:55:58 | INFO | Train Epoch: 13 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.062874 (0.098442) Boundary_loss: 0.013896 (0.013895) Loss: 0.076769 (0.11234) +2025-09-14,20:56:28 | INFO | Train Epoch: 13 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.093997 (0.098433) Boundary_loss: 0.013895 (0.013895) Loss: 0.10789 (0.11233) +2025-09-14,20:56:59 | INFO | Train Epoch: 13 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.098744 (0.098434) Boundary_loss: 0.013894 (0.013895) Loss: 0.11264 (0.11233) +2025-09-14,20:57:29 | INFO | Train Epoch: 13 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10478 (0.098447) Boundary_loss: 0.013894 (0.013895) Loss: 0.11867 (0.11234) +2025-09-14,20:58:00 | INFO | Train Epoch: 13 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.13241 (0.098518) Boundary_loss: 0.013894 (0.013895) Loss: 0.14631 (0.11241) +2025-09-14,20:58:30 | INFO | Train Epoch: 13 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.14649 (0.098617) Boundary_loss: 0.013895 (0.013895) Loss: 0.16038 (0.11251) +2025-09-14,20:59:01 | INFO | Train Epoch: 13 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.098344 (0.098617) Boundary_loss: 0.013896 (0.013895) Loss: 0.11224 (0.11251) +2025-09-14,20:59:32 | INFO | Train Epoch: 13 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10312 (0.098626) Boundary_loss: 0.013895 (0.013895) Loss: 0.11702 (0.11252) +2025-09-14,21:00:03 | INFO | Train Epoch: 13 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11913 (0.098669) Boundary_loss: 0.013895 (0.013895) Loss: 0.13303 (0.11256) +2025-09-14,21:00:34 | INFO | Train Epoch: 13 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.063804 (0.098597) Boundary_loss: 0.013894 (0.013895) Loss: 0.077698 (0.11249) +2025-09-14,21:01:04 | INFO | Train Epoch: 13 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.069659 (0.098537) Boundary_loss: 0.013894 (0.013895) Loss: 0.083553 (0.11243) +2025-09-14,21:01:35 | INFO | Train Epoch: 13 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.12407 (0.098590) Boundary_loss: 0.013896 (0.013895) Loss: 0.13797 (0.11248) +2025-09-14,21:02:06 | INFO | Train Epoch: 13 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.084027 (0.098560) Boundary_loss: 0.013896 (0.013895) Loss: 0.097922 (0.11245) +2025-09-14,21:02:37 | INFO | Train Epoch: 13 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.079481 (0.098521) Boundary_loss: 0.013894 (0.013895) Loss: 0.093375 (0.11242) +2025-09-14,21:03:08 | INFO | Train Epoch: 13 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.061543 (0.098445) Boundary_loss: 0.013895 (0.013895) Loss: 0.075437 (0.11234) +2025-09-14,21:03:38 | INFO | Train Epoch: 13 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.085531 (0.098419) Boundary_loss: 0.013894 (0.013895) Loss: 0.099425 (0.11231) +2025-09-14,21:04:09 | INFO | Train Epoch: 13 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12777 (0.098479) Boundary_loss: 0.013895 (0.013895) Loss: 0.14166 (0.11237) +2025-09-14,21:04:40 | INFO | Train Epoch: 13 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.089720 (0.098461) Boundary_loss: 0.013894 (0.013895) Loss: 0.10361 (0.11236) +2025-09-14,21:05:10 | INFO | Train Epoch: 13 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.093366 (0.098451) Boundary_loss: 0.013894 (0.013895) Loss: 0.10726 (0.11235) +2025-09-14,21:05:41 | INFO | Train Epoch: 13 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.089801 (0.098433) Boundary_loss: 0.013895 (0.013895) Loss: 0.10370 (0.11233) +2025-09-14,21:06:12 | INFO | Train Epoch: 13 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.084576 (0.098405) Boundary_loss: 0.013895 (0.013895) Loss: 0.098472 (0.11230) +2025-09-14,21:06:42 | INFO | Train Epoch: 13 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12776 (0.098464) Boundary_loss: 0.013895 (0.013895) Loss: 0.14166 (0.11236) +2025-09-14,21:07:13 | INFO | Train Epoch: 13 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.094330 (0.098456) Boundary_loss: 0.013894 (0.013895) Loss: 0.10822 (0.11235) +2025-09-14,21:07:44 | INFO | Train Epoch: 13 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.082817 (0.098425) Boundary_loss: 0.013894 (0.013895) Loss: 0.096711 (0.11232) +2025-09-14,21:08:15 | INFO | Train Epoch: 13 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.083241 (0.098394) Boundary_loss: 0.013895 (0.013895) Loss: 0.097135 (0.11229) +2025-09-14,21:08:46 | INFO | Train Epoch: 13 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.099371 (0.098396) Boundary_loss: 0.013894 (0.013895) Loss: 0.11327 (0.11229) +2025-09-14,21:09:16 | INFO | Train Epoch: 13 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.089011 (0.098377) Boundary_loss: 0.013895 (0.013895) Loss: 0.10291 (0.11227) +2025-09-14,21:09:47 | INFO | Train Epoch: 13 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10346 (0.098388) Boundary_loss: 0.013896 (0.013895) Loss: 0.11736 (0.11228) +2025-09-14,21:10:18 | INFO | Train Epoch: 13 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10830 (0.098407) Boundary_loss: 0.013896 (0.013895) Loss: 0.12220 (0.11230) +2025-09-14,21:10:49 | INFO | Train Epoch: 13 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.080690 (0.098372) Boundary_loss: 0.013896 (0.013895) Loss: 0.094586 (0.11227) +2025-09-14,21:11:19 | INFO | Train Epoch: 13 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.084845 (0.098345) Boundary_loss: 0.013895 (0.013895) Loss: 0.098740 (0.11224) +2025-09-14,21:11:50 | INFO | Train Epoch: 13 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.099494 (0.098348) Boundary_loss: 0.013895 (0.013895) Loss: 0.11339 (0.11224) +2025-09-14,21:12:21 | INFO | Train Epoch: 13 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.081826 (0.098315) Boundary_loss: 0.013896 (0.013895) Loss: 0.095721 (0.11221) +2025-09-14,21:12:52 | INFO | Train Epoch: 13 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10060 (0.098320) Boundary_loss: 0.013894 (0.013895) Loss: 0.11449 (0.11221) +2025-09-14,21:13:22 | INFO | Train Epoch: 13 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12495 (0.098372) Boundary_loss: 0.013895 (0.013895) Loss: 0.13884 (0.11227) +2025-09-14,21:13:53 | INFO | Train Epoch: 13 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.069942 (0.098316) Boundary_loss: 0.013895 (0.013895) Loss: 0.083837 (0.11221) +2025-09-14,21:14:24 | INFO | Train Epoch: 13 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10011 (0.098320) Boundary_loss: 0.013895 (0.013895) Loss: 0.11401 (0.11221) +2025-09-14,21:14:55 | INFO | Train Epoch: 13 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.092673 (0.098309) Boundary_loss: 0.013894 (0.013895) Loss: 0.10657 (0.11220) +2025-09-14,21:15:25 | INFO | Train Epoch: 13 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.077247 (0.098268) Boundary_loss: 0.013895 (0.013895) Loss: 0.091142 (0.11216) +2025-09-14,21:15:56 | INFO | Train Epoch: 13 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.085400 (0.098243) Boundary_loss: 0.013895 (0.013895) Loss: 0.099295 (0.11214) +2025-09-14,21:16:25 | INFO | Train Epoch: 13 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10309 (0.098252) Boundary_loss: 0.013894 (0.013895) Loss: 0.11699 (0.11215) +2025-09-14,21:16:25 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,21:16:25 | INFO | [Epoch 13] Average Step Time: 0.310s | Average GPU Memory: 25.2 GB +2025-09-14,21:16:25 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-14,21:16:25 | INFO | Starting zero-shot imagenet. +2025-09-14,21:16:25 | INFO | Building zero-shot classifier +2025-09-14,21:16:31 | INFO | Using classifier +2025-09-14,21:17:07 | INFO | Finished zero-shot imagenet. +2025-09-14,21:17:07 | INFO | Eval Epoch: 14 imagenet-zeroshot-val-top1: 0.3071 imagenet-zeroshot-val-top5: 0.5755 +2025-09-14,21:17:08 | INFO | Start epoch 14 +2025-09-14,21:17:10 | INFO | Train Epoch: 14 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.072097 (0.072097) Boundary_loss: 0.013895 (0.013895) Loss: 0.085992 (0.085992) +2025-09-14,21:17:40 | INFO | Train Epoch: 14 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.093432 (0.082764) Boundary_loss: 0.013895 (0.013895) Loss: 0.10733 (0.096659) +2025-09-14,21:18:11 | INFO | Train Epoch: 14 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.096739 (0.087422) Boundary_loss: 0.013894 (0.013895) Loss: 0.11063 (0.10132) +2025-09-14,21:18:41 | INFO | Train Epoch: 14 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.12406 (0.096582) Boundary_loss: 0.013895 (0.013895) Loss: 0.13796 (0.11048) +2025-09-14,21:19:12 | INFO | Train Epoch: 14 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11467 (0.10020) Boundary_loss: 0.013894 (0.013895) Loss: 0.12856 (0.11409) +2025-09-14,21:19:43 | INFO | Train Epoch: 14 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.11230 (0.10222) Boundary_loss: 0.013895 (0.013895) Loss: 0.12620 (0.11611) +2025-09-14,21:20:13 | INFO | Train Epoch: 14 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.093472 (0.10097) Boundary_loss: 0.013895 (0.013895) Loss: 0.10737 (0.11486) +2025-09-14,21:20:44 | INFO | Train Epoch: 14 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.076394 (0.097896) Boundary_loss: 0.013894 (0.013895) Loss: 0.090288 (0.11179) +2025-09-14,21:21:15 | INFO | Train Epoch: 14 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.071559 (0.094970) Boundary_loss: 0.013894 (0.013895) Loss: 0.085454 (0.10886) +2025-09-14,21:21:46 | INFO | Train Epoch: 14 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.077087 (0.093181) Boundary_loss: 0.013894 (0.013895) Loss: 0.090981 (0.10708) +2025-09-14,21:22:16 | INFO | Train Epoch: 14 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11113 (0.094813) Boundary_loss: 0.013895 (0.013895) Loss: 0.12503 (0.10871) +2025-09-14,21:22:47 | INFO | Train Epoch: 14 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10830 (0.095937) Boundary_loss: 0.013895 (0.013895) Loss: 0.12219 (0.10983) +2025-09-14,21:23:18 | INFO | Train Epoch: 14 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10429 (0.096579) Boundary_loss: 0.013895 (0.013895) Loss: 0.11818 (0.11047) +2025-09-14,21:23:49 | INFO | Train Epoch: 14 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.10055 (0.096863) Boundary_loss: 0.013894 (0.013895) Loss: 0.11444 (0.11076) +2025-09-14,21:24:19 | INFO | Train Epoch: 14 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.13529 (0.099425) Boundary_loss: 0.013895 (0.013895) Loss: 0.14919 (0.11332) +2025-09-14,21:24:50 | INFO | Train Epoch: 14 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.075449 (0.097926) Boundary_loss: 0.013894 (0.013895) Loss: 0.089343 (0.11182) +2025-09-14,21:25:21 | INFO | Train Epoch: 14 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.087336 (0.097303) Boundary_loss: 0.013895 (0.013895) Loss: 0.10123 (0.11120) +2025-09-14,21:25:51 | INFO | Train Epoch: 14 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.080932 (0.096394) Boundary_loss: 0.013895 (0.013895) Loss: 0.094827 (0.11029) +2025-09-14,21:26:22 | INFO | Train Epoch: 14 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.099243 (0.096544) Boundary_loss: 0.013894 (0.013895) Loss: 0.11314 (0.11044) +2025-09-14,21:26:53 | INFO | Train Epoch: 14 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.076309 (0.095532) Boundary_loss: 0.013896 (0.013895) Loss: 0.090205 (0.10943) +2025-09-14,21:27:23 | INFO | Train Epoch: 14 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10181 (0.095831) Boundary_loss: 0.013894 (0.013895) Loss: 0.11571 (0.10973) +2025-09-14,21:27:54 | INFO | Train Epoch: 14 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.060334 (0.094218) Boundary_loss: 0.013894 (0.013895) Loss: 0.074229 (0.10811) +2025-09-14,21:28:25 | INFO | Train Epoch: 14 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.069639 (0.093149) Boundary_loss: 0.013895 (0.013895) Loss: 0.083534 (0.10704) +2025-09-14,21:28:56 | INFO | Train Epoch: 14 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.13617 (0.094942) Boundary_loss: 0.013896 (0.013895) Loss: 0.15007 (0.10884) +2025-09-14,21:29:26 | INFO | Train Epoch: 14 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.091182 (0.094791) Boundary_loss: 0.013895 (0.013895) Loss: 0.10508 (0.10869) +2025-09-14,21:29:57 | INFO | Train Epoch: 14 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.096706 (0.094865) Boundary_loss: 0.013894 (0.013895) Loss: 0.11060 (0.10876) +2025-09-14,21:30:28 | INFO | Train Epoch: 14 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.042453 (0.092924) Boundary_loss: 0.013895 (0.013895) Loss: 0.056348 (0.10682) +2025-09-14,21:30:58 | INFO | Train Epoch: 14 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11810 (0.093823) Boundary_loss: 0.013895 (0.013895) Loss: 0.13200 (0.10772) +2025-09-14,21:31:29 | INFO | Train Epoch: 14 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10598 (0.094242) Boundary_loss: 0.013895 (0.013895) Loss: 0.11988 (0.10814) +2025-09-14,21:32:00 | INFO | Train Epoch: 14 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.085225 (0.093942) Boundary_loss: 0.013895 (0.013895) Loss: 0.099120 (0.10784) +2025-09-14,21:32:31 | INFO | Train Epoch: 14 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.080948 (0.093522) Boundary_loss: 0.013895 (0.013895) Loss: 0.094844 (0.10742) +2025-09-14,21:33:01 | INFO | Train Epoch: 14 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.093420 (0.093519) Boundary_loss: 0.013894 (0.013895) Loss: 0.10731 (0.10741) +2025-09-14,21:33:32 | INFO | Train Epoch: 14 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.074231 (0.092935) Boundary_loss: 0.013895 (0.013895) Loss: 0.088126 (0.10683) +2025-09-14,21:34:03 | INFO | Train Epoch: 14 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.14241 (0.094390) Boundary_loss: 0.013894 (0.013895) Loss: 0.15630 (0.10828) +2025-09-14,21:34:34 | INFO | Train Epoch: 14 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.068770 (0.093658) Boundary_loss: 0.013895 (0.013895) Loss: 0.082665 (0.10755) +2025-09-14,21:35:04 | INFO | Train Epoch: 14 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.078453 (0.093235) Boundary_loss: 0.013895 (0.013895) Loss: 0.092348 (0.10713) +2025-09-14,21:35:35 | INFO | Train Epoch: 14 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.068840 (0.092576) Boundary_loss: 0.013895 (0.013895) Loss: 0.082734 (0.10647) +2025-09-14,21:36:06 | INFO | Train Epoch: 14 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.081052 (0.092273) Boundary_loss: 0.013895 (0.013895) Loss: 0.094947 (0.10617) +2025-09-14,21:36:36 | INFO | Train Epoch: 14 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.093691 (0.092309) Boundary_loss: 0.013894 (0.013895) Loss: 0.10758 (0.10620) +2025-09-14,21:37:07 | INFO | Train Epoch: 14 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11011 (0.092754) Boundary_loss: 0.013895 (0.013895) Loss: 0.12400 (0.10665) +2025-09-14,21:37:38 | INFO | Train Epoch: 14 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11674 (0.093339) Boundary_loss: 0.013894 (0.013895) Loss: 0.13064 (0.10723) +2025-09-14,21:38:08 | INFO | Train Epoch: 14 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10557 (0.093630) Boundary_loss: 0.013895 (0.013895) Loss: 0.11946 (0.10753) +2025-09-14,21:38:39 | INFO | Train Epoch: 14 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12132 (0.094274) Boundary_loss: 0.013895 (0.013895) Loss: 0.13521 (0.10817) +2025-09-14,21:39:10 | INFO | Train Epoch: 14 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.11197 (0.094676) Boundary_loss: 0.013894 (0.013895) Loss: 0.12586 (0.10857) +2025-09-14,21:39:40 | INFO | Train Epoch: 14 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.087198 (0.094510) Boundary_loss: 0.013895 (0.013895) Loss: 0.10109 (0.10840) +2025-09-14,21:40:11 | INFO | Train Epoch: 14 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11461 (0.094947) Boundary_loss: 0.013895 (0.013895) Loss: 0.12851 (0.10884) +2025-09-14,21:40:42 | INFO | Train Epoch: 14 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.11941 (0.095468) Boundary_loss: 0.013895 (0.013895) Loss: 0.13330 (0.10936) +2025-09-14,21:41:12 | INFO | Train Epoch: 14 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.12013 (0.095981) Boundary_loss: 0.013895 (0.013895) Loss: 0.13402 (0.10988) +2025-09-14,21:41:43 | INFO | Train Epoch: 14 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.095831 (0.095978) Boundary_loss: 0.013895 (0.013895) Loss: 0.10973 (0.10987) +2025-09-14,21:42:13 | INFO | Train Epoch: 14 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.093569 (0.095930) Boundary_loss: 0.013895 (0.013895) Loss: 0.10746 (0.10982) +2025-09-14,21:42:44 | INFO | Train Epoch: 14 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.087838 (0.095772) Boundary_loss: 0.013895 (0.013895) Loss: 0.10173 (0.10967) +2025-09-14,21:43:15 | INFO | Train Epoch: 14 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.070865 (0.095293) Boundary_loss: 0.013894 (0.013895) Loss: 0.084759 (0.10919) +2025-09-14,21:43:45 | INFO | Train Epoch: 14 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.10915 (0.095554) Boundary_loss: 0.013894 (0.013895) Loss: 0.12304 (0.10945) +2025-09-14,21:44:16 | INFO | Train Epoch: 14 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.061721 (0.094927) Boundary_loss: 0.013895 (0.013895) Loss: 0.075616 (0.10882) +2025-09-14,21:44:47 | INFO | Train Epoch: 14 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10856 (0.095175) Boundary_loss: 0.013895 (0.013895) Loss: 0.12246 (0.10907) +2025-09-14,21:45:17 | INFO | Train Epoch: 14 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12202 (0.095655) Boundary_loss: 0.013894 (0.013895) Loss: 0.13591 (0.10955) +2025-09-14,21:45:48 | INFO | Train Epoch: 14 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.092533 (0.095600) Boundary_loss: 0.013894 (0.013895) Loss: 0.10643 (0.10949) +2025-09-14,21:46:19 | INFO | Train Epoch: 14 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.078324 (0.095302) Boundary_loss: 0.013895 (0.013895) Loss: 0.092219 (0.10920) +2025-09-14,21:46:49 | INFO | Train Epoch: 14 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.092811 (0.095260) Boundary_loss: 0.013894 (0.013895) Loss: 0.10671 (0.10915) +2025-09-14,21:47:20 | INFO | Train Epoch: 14 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.10694 (0.095454) Boundary_loss: 0.013897 (0.013895) Loss: 0.12084 (0.10935) +2025-09-14,21:47:51 | INFO | Train Epoch: 14 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.066815 (0.094985) Boundary_loss: 0.013895 (0.013895) Loss: 0.080710 (0.10888) +2025-09-14,21:48:21 | INFO | Train Epoch: 14 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.098960 (0.095049) Boundary_loss: 0.013894 (0.013895) Loss: 0.11285 (0.10894) +2025-09-14,21:48:52 | INFO | Train Epoch: 14 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.071858 (0.094681) Boundary_loss: 0.013894 (0.013895) Loss: 0.085752 (0.10858) +2025-09-14,21:49:22 | INFO | Train Epoch: 14 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.094317 (0.094675) Boundary_loss: 0.013895 (0.013895) Loss: 0.10821 (0.10857) +2025-09-14,21:49:53 | INFO | Train Epoch: 14 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.065762 (0.094230) Boundary_loss: 0.013894 (0.013895) Loss: 0.079657 (0.10813) +2025-09-14,21:50:24 | INFO | Train Epoch: 14 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10219 (0.094351) Boundary_loss: 0.013896 (0.013895) Loss: 0.11609 (0.10825) +2025-09-14,21:50:55 | INFO | Train Epoch: 14 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.079279 (0.094126) Boundary_loss: 0.013895 (0.013895) Loss: 0.093174 (0.10802) +2025-09-14,21:51:26 | INFO | Train Epoch: 14 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.058230 (0.093598) Boundary_loss: 0.013895 (0.013895) Loss: 0.072125 (0.10749) +2025-09-14,21:51:56 | INFO | Train Epoch: 14 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10830 (0.093811) Boundary_loss: 0.013894 (0.013895) Loss: 0.12220 (0.10771) +2025-09-14,21:52:27 | INFO | Train Epoch: 14 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.098876 (0.093884) Boundary_loss: 0.013894 (0.013895) Loss: 0.11277 (0.10778) +2025-09-14,21:52:58 | INFO | Train Epoch: 14 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.071621 (0.093570) Boundary_loss: 0.013894 (0.013895) Loss: 0.085515 (0.10746) +2025-09-14,21:53:28 | INFO | Train Epoch: 14 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.093911 (0.093575) Boundary_loss: 0.013895 (0.013895) Loss: 0.10781 (0.10747) +2025-09-14,21:53:59 | INFO | Train Epoch: 14 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11916 (0.093925) Boundary_loss: 0.013895 (0.013895) Loss: 0.13306 (0.10782) +2025-09-14,21:54:30 | INFO | Train Epoch: 14 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.083545 (0.093785) Boundary_loss: 0.013896 (0.013895) Loss: 0.097441 (0.10768) +2025-09-14,21:55:01 | INFO | Train Epoch: 14 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.093163 (0.093777) Boundary_loss: 0.013894 (0.013895) Loss: 0.10706 (0.10767) +2025-09-14,21:55:31 | INFO | Train Epoch: 14 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.083787 (0.093645) Boundary_loss: 0.013894 (0.013895) Loss: 0.097681 (0.10754) +2025-09-14,21:56:02 | INFO | Train Epoch: 14 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10638 (0.093811) Boundary_loss: 0.013895 (0.013895) Loss: 0.12027 (0.10771) +2025-09-14,21:56:33 | INFO | Train Epoch: 14 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.057436 (0.093344) Boundary_loss: 0.013895 (0.013895) Loss: 0.071332 (0.10724) +2025-09-14,21:57:03 | INFO | Train Epoch: 14 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10897 (0.093542) Boundary_loss: 0.013895 (0.013895) Loss: 0.12286 (0.10744) +2025-09-14,21:57:34 | INFO | Train Epoch: 14 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.067523 (0.093217) Boundary_loss: 0.013895 (0.013895) Loss: 0.081417 (0.10711) +2025-09-14,21:58:05 | INFO | Train Epoch: 14 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.096382 (0.093256) Boundary_loss: 0.013894 (0.013895) Loss: 0.11028 (0.10715) +2025-09-14,21:58:36 | INFO | Train Epoch: 14 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.066706 (0.092932) Boundary_loss: 0.013895 (0.013895) Loss: 0.080601 (0.10683) +2025-09-14,21:59:06 | INFO | Train Epoch: 14 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.095682 (0.092965) Boundary_loss: 0.013894 (0.013895) Loss: 0.10958 (0.10686) +2025-09-14,21:59:37 | INFO | Train Epoch: 14 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.087926 (0.092905) Boundary_loss: 0.013894 (0.013895) Loss: 0.10182 (0.10680) +2025-09-14,22:00:07 | INFO | Train Epoch: 14 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.069354 (0.092628) Boundary_loss: 0.013894 (0.013895) Loss: 0.083248 (0.10652) +2025-09-14,22:00:38 | INFO | Train Epoch: 14 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10016 (0.092716) Boundary_loss: 0.013895 (0.013895) Loss: 0.11406 (0.10661) +2025-09-14,22:01:08 | INFO | Train Epoch: 14 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.074891 (0.092511) Boundary_loss: 0.013895 (0.013895) Loss: 0.088787 (0.10641) +2025-09-14,22:01:39 | INFO | Train Epoch: 14 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12557 (0.092887) Boundary_loss: 0.013895 (0.013895) Loss: 0.13946 (0.10678) +2025-09-14,22:02:10 | INFO | Train Epoch: 14 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.086490 (0.092815) Boundary_loss: 0.013895 (0.013895) Loss: 0.10038 (0.10671) +2025-09-14,22:02:40 | INFO | Train Epoch: 14 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10407 (0.092940) Boundary_loss: 0.013895 (0.013895) Loss: 0.11796 (0.10683) +2025-09-14,22:03:11 | INFO | Train Epoch: 14 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.081793 (0.092817) Boundary_loss: 0.013896 (0.013895) Loss: 0.095689 (0.10671) +2025-09-14,22:03:42 | INFO | Train Epoch: 14 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.093514 (0.092825) Boundary_loss: 0.013894 (0.013895) Loss: 0.10741 (0.10672) +2025-09-14,22:04:13 | INFO | Train Epoch: 14 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.093477 (0.092832) Boundary_loss: 0.013895 (0.013895) Loss: 0.10737 (0.10673) +2025-09-14,22:04:43 | INFO | Train Epoch: 14 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.061381 (0.092497) Boundary_loss: 0.013895 (0.013895) Loss: 0.075276 (0.10639) +2025-09-14,22:05:14 | INFO | Train Epoch: 14 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.068318 (0.092243) Boundary_loss: 0.013895 (0.013895) Loss: 0.082213 (0.10614) +2025-09-14,22:05:45 | INFO | Train Epoch: 14 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.066850 (0.091978) Boundary_loss: 0.013894 (0.013895) Loss: 0.080744 (0.10587) +2025-09-14,22:06:16 | INFO | Train Epoch: 14 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11185 (0.092183) Boundary_loss: 0.013894 (0.013895) Loss: 0.12574 (0.10608) +2025-09-14,22:06:46 | INFO | Train Epoch: 14 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.079766 (0.092056) Boundary_loss: 0.013895 (0.013895) Loss: 0.093661 (0.10595) +2025-09-14,22:07:17 | INFO | Train Epoch: 14 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10954 (0.092233) Boundary_loss: 0.013895 (0.013895) Loss: 0.12343 (0.10613) +2025-09-14,22:07:48 | INFO | Train Epoch: 14 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10428 (0.092354) Boundary_loss: 0.013894 (0.013895) Loss: 0.11818 (0.10625) +2025-09-14,22:08:19 | INFO | Train Epoch: 14 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10282 (0.092457) Boundary_loss: 0.013895 (0.013895) Loss: 0.11672 (0.10635) +2025-09-14,22:08:50 | INFO | Train Epoch: 14 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.084461 (0.092379) Boundary_loss: 0.013895 (0.013895) Loss: 0.098355 (0.10627) +2025-09-14,22:09:20 | INFO | Train Epoch: 14 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.068277 (0.092145) Boundary_loss: 0.013895 (0.013895) Loss: 0.082172 (0.10604) +2025-09-14,22:09:51 | INFO | Train Epoch: 14 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11223 (0.092338) Boundary_loss: 0.013895 (0.013895) Loss: 0.12613 (0.10623) +2025-09-14,22:10:22 | INFO | Train Epoch: 14 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.14917 (0.092879) Boundary_loss: 0.013894 (0.013895) Loss: 0.16307 (0.10677) +2025-09-14,22:10:53 | INFO | Train Epoch: 14 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.072335 (0.092685) Boundary_loss: 0.013894 (0.013895) Loss: 0.086229 (0.10658) +2025-09-14,22:11:23 | INFO | Train Epoch: 14 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.098856 (0.092743) Boundary_loss: 0.013895 (0.013895) Loss: 0.11275 (0.10664) +2025-09-14,22:11:54 | INFO | Train Epoch: 14 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11074 (0.092910) Boundary_loss: 0.013894 (0.013895) Loss: 0.12464 (0.10680) +2025-09-14,22:12:25 | INFO | Train Epoch: 14 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.094664 (0.092926) Boundary_loss: 0.013894 (0.013895) Loss: 0.10856 (0.10682) +2025-09-14,22:12:55 | INFO | Train Epoch: 14 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.071992 (0.092735) Boundary_loss: 0.013894 (0.013895) Loss: 0.085886 (0.10663) +2025-09-14,22:13:26 | INFO | Train Epoch: 14 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.082911 (0.092647) Boundary_loss: 0.013895 (0.013895) Loss: 0.096806 (0.10654) +2025-09-14,22:13:57 | INFO | Train Epoch: 14 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10170 (0.092728) Boundary_loss: 0.013894 (0.013895) Loss: 0.11559 (0.10662) +2025-09-14,22:14:27 | INFO | Train Epoch: 14 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.068070 (0.092510) Boundary_loss: 0.013896 (0.013895) Loss: 0.081965 (0.10640) +2025-09-14,22:14:58 | INFO | Train Epoch: 14 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.095563 (0.092536) Boundary_loss: 0.013894 (0.013895) Loss: 0.10946 (0.10643) +2025-09-14,22:15:29 | INFO | Train Epoch: 14 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.090130 (0.092515) Boundary_loss: 0.013895 (0.013895) Loss: 0.10403 (0.10641) +2025-09-14,22:16:00 | INFO | Train Epoch: 14 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10006 (0.092580) Boundary_loss: 0.013896 (0.013895) Loss: 0.11396 (0.10648) +2025-09-14,22:16:31 | INFO | Train Epoch: 14 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.079955 (0.092473) Boundary_loss: 0.013895 (0.013895) Loss: 0.093849 (0.10637) +2025-09-14,22:17:02 | INFO | Train Epoch: 14 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.060663 (0.092203) Boundary_loss: 0.013894 (0.013895) Loss: 0.074558 (0.10610) +2025-09-14,22:17:32 | INFO | Train Epoch: 14 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10644 (0.092323) Boundary_loss: 0.013895 (0.013895) Loss: 0.12033 (0.10622) +2025-09-14,22:18:03 | INFO | Train Epoch: 14 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.053289 (0.091997) Boundary_loss: 0.013894 (0.013895) Loss: 0.067183 (0.10589) +2025-09-14,22:18:34 | INFO | Train Epoch: 14 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.080331 (0.091901) Boundary_loss: 0.013894 (0.013895) Loss: 0.094225 (0.10580) +2025-09-14,22:19:05 | INFO | Train Epoch: 14 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.071526 (0.091734) Boundary_loss: 0.013894 (0.013895) Loss: 0.085420 (0.10563) +2025-09-14,22:19:35 | INFO | Train Epoch: 14 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.064516 (0.091513) Boundary_loss: 0.013894 (0.013895) Loss: 0.078410 (0.10541) +2025-09-14,22:20:06 | INFO | Train Epoch: 14 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10234 (0.091600) Boundary_loss: 0.013895 (0.013895) Loss: 0.11624 (0.10549) +2025-09-14,22:20:37 | INFO | Train Epoch: 14 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.054201 (0.091301) Boundary_loss: 0.013895 (0.013895) Loss: 0.068096 (0.10520) +2025-09-14,22:21:07 | INFO | Train Epoch: 14 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.074839 (0.091170) Boundary_loss: 0.013894 (0.013895) Loss: 0.088733 (0.10506) +2025-09-14,22:21:38 | INFO | Train Epoch: 14 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.093361 (0.091187) Boundary_loss: 0.013895 (0.013895) Loss: 0.10726 (0.10508) +2025-09-14,22:22:09 | INFO | Train Epoch: 14 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.094623 (0.091214) Boundary_loss: 0.013894 (0.013895) Loss: 0.10852 (0.10511) +2025-09-14,22:22:39 | INFO | Train Epoch: 14 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.063914 (0.091003) Boundary_loss: 0.013895 (0.013895) Loss: 0.077809 (0.10490) +2025-09-14,22:23:10 | INFO | Train Epoch: 14 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.082748 (0.090939) Boundary_loss: 0.013895 (0.013895) Loss: 0.096643 (0.10483) +2025-09-14,22:23:40 | INFO | Train Epoch: 14 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.082413 (0.090874) Boundary_loss: 0.013894 (0.013895) Loss: 0.096307 (0.10477) +2025-09-14,22:24:11 | INFO | Train Epoch: 14 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.098592 (0.090932) Boundary_loss: 0.013894 (0.013895) Loss: 0.11249 (0.10483) +2025-09-14,22:24:42 | INFO | Train Epoch: 14 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.087038 (0.090903) Boundary_loss: 0.013895 (0.013895) Loss: 0.10093 (0.10480) +2025-09-14,22:25:12 | INFO | Train Epoch: 14 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.077299 (0.090802) Boundary_loss: 0.013895 (0.013895) Loss: 0.091194 (0.10470) +2025-09-14,22:25:43 | INFO | Train Epoch: 14 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.089242 (0.090790) Boundary_loss: 0.013894 (0.013895) Loss: 0.10314 (0.10468) +2025-09-14,22:26:14 | INFO | Train Epoch: 14 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.099863 (0.090857) Boundary_loss: 0.013894 (0.013895) Loss: 0.11376 (0.10475) +2025-09-14,22:26:44 | INFO | Train Epoch: 14 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.097020 (0.090902) Boundary_loss: 0.013894 (0.013895) Loss: 0.11091 (0.10480) +2025-09-14,22:27:15 | INFO | Train Epoch: 14 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.095630 (0.090936) Boundary_loss: 0.013895 (0.013895) Loss: 0.10952 (0.10483) +2025-09-14,22:27:46 | INFO | Train Epoch: 14 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10329 (0.091025) Boundary_loss: 0.013895 (0.013895) Loss: 0.11719 (0.10492) +2025-09-14,22:28:16 | INFO | Train Epoch: 14 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.080304 (0.090948) Boundary_loss: 0.013894 (0.013895) Loss: 0.094199 (0.10484) +2025-09-14,22:28:47 | INFO | Train Epoch: 14 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.061949 (0.090743) Boundary_loss: 0.013895 (0.013895) Loss: 0.075844 (0.10464) +2025-09-14,22:29:18 | INFO | Train Epoch: 14 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.060494 (0.090530) Boundary_loss: 0.013895 (0.013895) Loss: 0.074389 (0.10442) +2025-09-14,22:29:48 | INFO | Train Epoch: 14 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.067260 (0.090367) Boundary_loss: 0.013895 (0.013895) Loss: 0.081155 (0.10426) +2025-09-14,22:30:19 | INFO | Train Epoch: 14 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.079218 (0.090290) Boundary_loss: 0.013895 (0.013895) Loss: 0.093112 (0.10418) +2025-09-14,22:30:50 | INFO | Train Epoch: 14 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10067 (0.090361) Boundary_loss: 0.013894 (0.013895) Loss: 0.11456 (0.10426) +2025-09-14,22:31:20 | INFO | Train Epoch: 14 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11734 (0.090546) Boundary_loss: 0.013894 (0.013895) Loss: 0.13124 (0.10444) +2025-09-14,22:31:51 | INFO | Train Epoch: 14 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10416 (0.090639) Boundary_loss: 0.013894 (0.013895) Loss: 0.11805 (0.10453) +2025-09-14,22:32:22 | INFO | Train Epoch: 14 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.10571 (0.090740) Boundary_loss: 0.013893 (0.013895) Loss: 0.11960 (0.10464) +2025-09-14,22:32:52 | INFO | Train Epoch: 14 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.091424 (0.090745) Boundary_loss: 0.013895 (0.013895) Loss: 0.10532 (0.10464) +2025-09-14,22:33:23 | INFO | Train Epoch: 14 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.075104 (0.090641) Boundary_loss: 0.013895 (0.013895) Loss: 0.089000 (0.10454) +2025-09-14,22:33:54 | INFO | Train Epoch: 14 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10709 (0.090750) Boundary_loss: 0.013895 (0.013895) Loss: 0.12099 (0.10464) +2025-09-14,22:34:25 | INFO | Train Epoch: 14 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11258 (0.090893) Boundary_loss: 0.013895 (0.013895) Loss: 0.12647 (0.10479) +2025-09-14,22:34:55 | INFO | Train Epoch: 14 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10092 (0.090959) Boundary_loss: 0.013895 (0.013895) Loss: 0.11481 (0.10485) +2025-09-14,22:35:26 | INFO | Train Epoch: 14 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.094196 (0.090980) Boundary_loss: 0.013894 (0.013895) Loss: 0.10809 (0.10487) +2025-09-14,22:35:57 | INFO | Train Epoch: 14 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.097588 (0.091022) Boundary_loss: 0.013895 (0.013895) Loss: 0.11148 (0.10492) +2025-09-14,22:36:27 | INFO | Train Epoch: 14 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.056417 (0.090801) Boundary_loss: 0.013895 (0.013895) Loss: 0.070312 (0.10470) +2025-09-14,22:36:58 | INFO | Train Epoch: 14 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.077579 (0.090716) Boundary_loss: 0.013894 (0.013895) Loss: 0.091473 (0.10461) +2025-09-14,22:37:28 | INFO | Train Epoch: 14 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.082260 (0.090663) Boundary_loss: 0.013895 (0.013895) Loss: 0.096155 (0.10456) +2025-09-14,22:37:59 | INFO | Train Epoch: 14 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10422 (0.090748) Boundary_loss: 0.013895 (0.013895) Loss: 0.11811 (0.10464) +2025-09-14,22:38:30 | INFO | Train Epoch: 14 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11722 (0.090914) Boundary_loss: 0.013895 (0.013895) Loss: 0.13111 (0.10481) +2025-09-14,22:39:00 | INFO | Train Epoch: 14 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.096918 (0.090951) Boundary_loss: 0.013895 (0.013895) Loss: 0.11081 (0.10485) +2025-09-14,22:39:30 | INFO | Train Epoch: 14 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.044920 (0.090667) Boundary_loss: 0.013895 (0.013895) Loss: 0.058815 (0.10456) +2025-09-14,22:40:01 | INFO | Train Epoch: 14 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.063245 (0.090498) Boundary_loss: 0.013895 (0.013895) Loss: 0.077139 (0.10439) +2025-09-14,22:40:32 | INFO | Train Epoch: 14 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.086309 (0.090473) Boundary_loss: 0.013894 (0.013895) Loss: 0.10020 (0.10437) +2025-09-14,22:41:03 | INFO | Train Epoch: 14 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.069763 (0.090347) Boundary_loss: 0.013894 (0.013895) Loss: 0.083657 (0.10424) +2025-09-14,22:41:33 | INFO | Train Epoch: 14 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.083037 (0.090303) Boundary_loss: 0.013895 (0.013895) Loss: 0.096932 (0.10420) +2025-09-14,22:42:04 | INFO | Train Epoch: 14 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.066460 (0.090161) Boundary_loss: 0.013894 (0.013895) Loss: 0.080354 (0.10406) +2025-09-14,22:42:35 | INFO | Train Epoch: 14 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.080431 (0.090103) Boundary_loss: 0.013893 (0.013895) Loss: 0.094324 (0.10400) +2025-09-14,22:43:05 | INFO | Train Epoch: 14 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.049097 (0.089860) Boundary_loss: 0.013895 (0.013895) Loss: 0.062992 (0.10375) +2025-09-14,22:43:36 | INFO | Train Epoch: 14 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.055192 (0.089656) Boundary_loss: 0.013894 (0.013895) Loss: 0.069087 (0.10355) +2025-09-14,22:44:07 | INFO | Train Epoch: 14 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10846 (0.089766) Boundary_loss: 0.013894 (0.013895) Loss: 0.12235 (0.10366) +2025-09-14,22:44:37 | INFO | Train Epoch: 14 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.086963 (0.089750) Boundary_loss: 0.013895 (0.013895) Loss: 0.10086 (0.10364) +2025-09-14,22:45:08 | INFO | Train Epoch: 14 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.079658 (0.089691) Boundary_loss: 0.013894 (0.013895) Loss: 0.093552 (0.10359) +2025-09-14,22:45:39 | INFO | Train Epoch: 14 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.083878 (0.089658) Boundary_loss: 0.013894 (0.013895) Loss: 0.097772 (0.10355) +2025-09-14,22:46:09 | INFO | Train Epoch: 14 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.088928 (0.089654) Boundary_loss: 0.013895 (0.013895) Loss: 0.10282 (0.10355) +2025-09-14,22:46:40 | INFO | Train Epoch: 14 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.091118 (0.089662) Boundary_loss: 0.013895 (0.013895) Loss: 0.10501 (0.10356) +2025-09-14,22:47:11 | INFO | Train Epoch: 14 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.098174 (0.089710) Boundary_loss: 0.013895 (0.013895) Loss: 0.11207 (0.10360) +2025-09-14,22:47:41 | INFO | Train Epoch: 14 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.067926 (0.089588) Boundary_loss: 0.013894 (0.013895) Loss: 0.081820 (0.10348) +2025-09-14,22:48:12 | INFO | Train Epoch: 14 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.080455 (0.089537) Boundary_loss: 0.013896 (0.013895) Loss: 0.094351 (0.10343) +2025-09-14,22:48:42 | INFO | Train Epoch: 14 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12199 (0.089717) Boundary_loss: 0.013894 (0.013895) Loss: 0.13588 (0.10361) +2025-09-14,22:49:13 | INFO | Train Epoch: 14 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10184 (0.089784) Boundary_loss: 0.013895 (0.013895) Loss: 0.11574 (0.10368) +2025-09-14,22:49:43 | INFO | Train Epoch: 14 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.095821 (0.089817) Boundary_loss: 0.013895 (0.013895) Loss: 0.10972 (0.10371) +2025-09-14,22:50:14 | INFO | Train Epoch: 14 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.063950 (0.089676) Boundary_loss: 0.013896 (0.013895) Loss: 0.077846 (0.10357) +2025-09-14,22:50:45 | INFO | Train Epoch: 14 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.062338 (0.089527) Boundary_loss: 0.013895 (0.013895) Loss: 0.076233 (0.10342) +2025-09-14,22:51:15 | INFO | Train Epoch: 14 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.086017 (0.089508) Boundary_loss: 0.013895 (0.013895) Loss: 0.099912 (0.10340) +2025-09-14,22:51:46 | INFO | Train Epoch: 14 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.074167 (0.089426) Boundary_loss: 0.013895 (0.013895) Loss: 0.088062 (0.10332) +2025-09-14,22:52:17 | INFO | Train Epoch: 14 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11652 (0.089571) Boundary_loss: 0.013894 (0.013895) Loss: 0.13041 (0.10347) +2025-09-14,22:52:47 | INFO | Train Epoch: 14 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.085155 (0.089547) Boundary_loss: 0.013895 (0.013895) Loss: 0.099050 (0.10344) +2025-09-14,22:53:18 | INFO | Train Epoch: 14 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10908 (0.089651) Boundary_loss: 0.013894 (0.013895) Loss: 0.12298 (0.10355) +2025-09-14,22:53:49 | INFO | Train Epoch: 14 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10069 (0.089709) Boundary_loss: 0.013894 (0.013895) Loss: 0.11458 (0.10360) +2025-09-14,22:54:19 | INFO | Train Epoch: 14 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.075961 (0.089637) Boundary_loss: 0.013894 (0.013895) Loss: 0.089855 (0.10353) +2025-09-14,22:54:50 | INFO | Train Epoch: 14 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.091533 (0.089647) Boundary_loss: 0.013894 (0.013895) Loss: 0.10543 (0.10354) +2025-09-14,22:55:21 | INFO | Train Epoch: 14 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.066760 (0.089528) Boundary_loss: 0.013895 (0.013895) Loss: 0.080655 (0.10342) +2025-09-14,22:55:51 | INFO | Train Epoch: 14 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.083986 (0.089499) Boundary_loss: 0.013895 (0.013895) Loss: 0.097881 (0.10339) +2025-09-14,22:56:22 | INFO | Train Epoch: 14 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.090161 (0.089503) Boundary_loss: 0.013894 (0.013895) Loss: 0.10405 (0.10340) +2025-09-14,22:56:53 | INFO | Train Epoch: 14 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.14281 (0.089775) Boundary_loss: 0.013894 (0.013895) Loss: 0.15670 (0.10367) +2025-09-14,22:57:24 | INFO | Train Epoch: 14 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.067667 (0.089663) Boundary_loss: 0.013895 (0.013895) Loss: 0.081562 (0.10356) +2025-09-14,22:57:54 | INFO | Train Epoch: 14 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.096030 (0.089695) Boundary_loss: 0.013895 (0.013895) Loss: 0.10993 (0.10359) +2025-09-14,22:58:25 | INFO | Train Epoch: 14 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.097240 (0.089733) Boundary_loss: 0.013895 (0.013895) Loss: 0.11113 (0.10363) +2025-09-14,22:58:55 | INFO | Train Epoch: 14 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.056724 (0.089568) Boundary_loss: 0.013895 (0.013895) Loss: 0.070619 (0.10346) +2025-09-14,22:59:26 | INFO | Train Epoch: 14 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.073372 (0.089487) Boundary_loss: 0.013894 (0.013895) Loss: 0.087266 (0.10338) +2025-09-14,22:59:57 | INFO | Train Epoch: 14 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.087821 (0.089479) Boundary_loss: 0.013896 (0.013895) Loss: 0.10172 (0.10337) +2025-09-14,23:00:27 | INFO | Train Epoch: 14 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.078896 (0.089427) Boundary_loss: 0.013896 (0.013895) Loss: 0.092792 (0.10332) +2025-09-14,23:00:58 | INFO | Train Epoch: 14 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.088672 (0.089423) Boundary_loss: 0.013894 (0.013895) Loss: 0.10257 (0.10332) +2025-09-14,23:01:29 | INFO | Train Epoch: 14 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.089113 (0.089422) Boundary_loss: 0.013896 (0.013895) Loss: 0.10301 (0.10332) +2025-09-14,23:02:00 | INFO | Train Epoch: 14 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.076384 (0.089358) Boundary_loss: 0.013895 (0.013895) Loss: 0.090279 (0.10325) +2025-09-14,23:02:30 | INFO | Train Epoch: 14 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.057527 (0.089204) Boundary_loss: 0.013895 (0.013895) Loss: 0.071421 (0.10310) +2025-09-14,23:03:01 | INFO | Train Epoch: 14 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.094056 (0.089228) Boundary_loss: 0.013895 (0.013895) Loss: 0.10795 (0.10312) +2025-09-14,23:03:32 | INFO | Train Epoch: 14 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.086316 (0.089214) Boundary_loss: 0.013894 (0.013895) Loss: 0.10021 (0.10311) +2025-09-14,23:04:03 | INFO | Train Epoch: 14 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10038 (0.089267) Boundary_loss: 0.013895 (0.013895) Loss: 0.11428 (0.10316) +2025-09-14,23:04:33 | INFO | Train Epoch: 14 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.11262 (0.089378) Boundary_loss: 0.013895 (0.013895) Loss: 0.12651 (0.10327) +2025-09-14,23:05:04 | INFO | Train Epoch: 14 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.10804 (0.089466) Boundary_loss: 0.013896 (0.013895) Loss: 0.12193 (0.10336) +2025-09-14,23:05:35 | INFO | Train Epoch: 14 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.069881 (0.089374) Boundary_loss: 0.013896 (0.013895) Loss: 0.083777 (0.10327) +2025-09-14,23:06:06 | INFO | Train Epoch: 14 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.064814 (0.089259) Boundary_loss: 0.013895 (0.013895) Loss: 0.078708 (0.10315) +2025-09-14,23:06:36 | INFO | Train Epoch: 14 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.095486 (0.089288) Boundary_loss: 0.013895 (0.013895) Loss: 0.10938 (0.10318) +2025-09-14,23:07:07 | INFO | Train Epoch: 14 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.080823 (0.089249) Boundary_loss: 0.013896 (0.013895) Loss: 0.094719 (0.10314) +2025-09-14,23:07:38 | INFO | Train Epoch: 14 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.095917 (0.089279) Boundary_loss: 0.013895 (0.013895) Loss: 0.10981 (0.10317) +2025-09-14,23:08:09 | INFO | Train Epoch: 14 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10526 (0.089353) Boundary_loss: 0.013894 (0.013895) Loss: 0.11916 (0.10325) +2025-09-14,23:08:39 | INFO | Train Epoch: 14 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.080461 (0.089312) Boundary_loss: 0.013895 (0.013895) Loss: 0.094356 (0.10321) +2025-09-14,23:09:10 | INFO | Train Epoch: 14 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10735 (0.089394) Boundary_loss: 0.013895 (0.013895) Loss: 0.12124 (0.10329) +2025-09-14,23:09:41 | INFO | Train Epoch: 14 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.094243 (0.089416) Boundary_loss: 0.013895 (0.013895) Loss: 0.10814 (0.10331) +2025-09-14,23:10:11 | INFO | Train Epoch: 14 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.080587 (0.089376) Boundary_loss: 0.013895 (0.013895) Loss: 0.094482 (0.10327) +2025-09-14,23:10:42 | INFO | Train Epoch: 14 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.064248 (0.089264) Boundary_loss: 0.013895 (0.013895) Loss: 0.078144 (0.10316) +2025-09-14,23:11:13 | INFO | Train Epoch: 14 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.070777 (0.089181) Boundary_loss: 0.013895 (0.013895) Loss: 0.084672 (0.10308) +2025-09-14,23:11:43 | INFO | Train Epoch: 14 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.083873 (0.089158) Boundary_loss: 0.013895 (0.013895) Loss: 0.097768 (0.10305) +2025-09-14,23:12:14 | INFO | Train Epoch: 14 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.088812 (0.089156) Boundary_loss: 0.013894 (0.013895) Loss: 0.10271 (0.10305) +2025-09-14,23:12:45 | INFO | Train Epoch: 14 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.090599 (0.089162) Boundary_loss: 0.013894 (0.013895) Loss: 0.10449 (0.10306) +2025-09-14,23:13:15 | INFO | Train Epoch: 14 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.093126 (0.089180) Boundary_loss: 0.013895 (0.013895) Loss: 0.10702 (0.10307) +2025-09-14,23:13:46 | INFO | Train Epoch: 14 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10896 (0.089266) Boundary_loss: 0.013895 (0.013895) Loss: 0.12285 (0.10316) +2025-09-14,23:14:17 | INFO | Train Epoch: 14 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.054440 (0.089115) Boundary_loss: 0.013895 (0.013895) Loss: 0.068335 (0.10301) +2025-09-14,23:14:48 | INFO | Train Epoch: 14 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12421 (0.089267) Boundary_loss: 0.013895 (0.013895) Loss: 0.13810 (0.10316) +2025-09-14,23:15:18 | INFO | Train Epoch: 14 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.065549 (0.089164) Boundary_loss: 0.013896 (0.013895) Loss: 0.079445 (0.10306) +2025-09-14,23:15:49 | INFO | Train Epoch: 14 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12482 (0.089317) Boundary_loss: 0.013895 (0.013895) Loss: 0.13871 (0.10321) +2025-09-14,23:16:20 | INFO | Train Epoch: 14 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.12673 (0.089477) Boundary_loss: 0.013895 (0.013895) Loss: 0.14062 (0.10337) +2025-09-14,23:16:51 | INFO | Train Epoch: 14 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.096339 (0.089506) Boundary_loss: 0.013895 (0.013895) Loss: 0.11023 (0.10340) +2025-09-14,23:17:21 | INFO | Train Epoch: 14 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.10024 (0.089552) Boundary_loss: 0.013894 (0.013895) Loss: 0.11413 (0.10345) +2025-09-14,23:17:52 | INFO | Train Epoch: 14 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.088313 (0.089547) Boundary_loss: 0.013895 (0.013895) Loss: 0.10221 (0.10344) +2025-09-14,23:18:23 | INFO | Train Epoch: 14 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.071876 (0.089472) Boundary_loss: 0.013895 (0.013895) Loss: 0.085771 (0.10337) +2025-09-14,23:18:53 | INFO | Train Epoch: 14 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.071331 (0.089397) Boundary_loss: 0.013896 (0.013895) Loss: 0.085227 (0.10329) +2025-09-14,23:19:24 | INFO | Train Epoch: 14 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.096589 (0.089427) Boundary_loss: 0.013895 (0.013895) Loss: 0.11048 (0.10332) +2025-09-14,23:19:55 | INFO | Train Epoch: 14 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.12578 (0.089577) Boundary_loss: 0.013894 (0.013895) Loss: 0.13968 (0.10347) +2025-09-14,23:20:26 | INFO | Train Epoch: 14 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.065451 (0.089478) Boundary_loss: 0.013894 (0.013895) Loss: 0.079345 (0.10337) +2025-09-14,23:20:56 | INFO | Train Epoch: 14 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.088752 (0.089475) Boundary_loss: 0.013896 (0.013895) Loss: 0.10265 (0.10337) +2025-09-14,23:21:26 | INFO | Train Epoch: 14 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.092580 (0.089487) Boundary_loss: 0.013894 (0.013895) Loss: 0.10647 (0.10338) +2025-09-14,23:21:57 | INFO | Train Epoch: 14 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.058431 (0.089361) Boundary_loss: 0.013894 (0.013895) Loss: 0.072325 (0.10326) +2025-09-14,23:22:28 | INFO | Train Epoch: 14 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.084491 (0.089341) Boundary_loss: 0.013893 (0.013895) Loss: 0.098384 (0.10324) +2025-09-14,23:22:58 | INFO | Train Epoch: 14 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.080331 (0.089304) Boundary_loss: 0.013895 (0.013895) Loss: 0.094226 (0.10320) +2025-09-14,23:23:29 | INFO | Train Epoch: 14 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.080015 (0.089267) Boundary_loss: 0.013896 (0.013895) Loss: 0.093911 (0.10316) +2025-09-14,23:24:00 | INFO | Train Epoch: 14 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.069862 (0.089189) Boundary_loss: 0.013897 (0.013895) Loss: 0.083758 (0.10308) +2025-09-14,23:24:30 | INFO | Train Epoch: 14 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.096204 (0.089217) Boundary_loss: 0.013895 (0.013895) Loss: 0.11010 (0.10311) +2025-09-14,23:25:01 | INFO | Train Epoch: 14 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.094858 (0.089240) Boundary_loss: 0.013895 (0.013895) Loss: 0.10875 (0.10313) +2025-09-14,23:25:31 | INFO | Train Epoch: 14 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.085788 (0.089226) Boundary_loss: 0.013895 (0.013895) Loss: 0.099683 (0.10312) +2025-09-14,23:26:02 | INFO | Train Epoch: 14 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.089534 (0.089227) Boundary_loss: 0.013895 (0.013895) Loss: 0.10343 (0.10312) +2025-09-14,23:26:33 | INFO | Train Epoch: 14 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.086389 (0.089216) Boundary_loss: 0.013895 (0.013895) Loss: 0.10028 (0.10311) +2025-09-14,23:27:04 | INFO | Train Epoch: 14 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.094708 (0.089237) Boundary_loss: 0.013895 (0.013895) Loss: 0.10860 (0.10313) +2025-09-14,23:27:34 | INFO | Train Epoch: 14 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.075039 (0.089182) Boundary_loss: 0.013895 (0.013895) Loss: 0.088934 (0.10308) +2025-09-14,23:28:05 | INFO | Train Epoch: 14 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10645 (0.089249) Boundary_loss: 0.013894 (0.013895) Loss: 0.12035 (0.10314) +2025-09-14,23:28:36 | INFO | Train Epoch: 14 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10854 (0.089324) Boundary_loss: 0.013894 (0.013895) Loss: 0.12243 (0.10322) +2025-09-14,23:29:07 | INFO | Train Epoch: 14 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10598 (0.089388) Boundary_loss: 0.013895 (0.013895) Loss: 0.11988 (0.10328) +2025-09-14,23:29:37 | INFO | Train Epoch: 14 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12752 (0.089535) Boundary_loss: 0.013895 (0.013895) Loss: 0.14142 (0.10343) +2025-09-14,23:30:08 | INFO | Train Epoch: 14 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.068937 (0.089456) Boundary_loss: 0.013894 (0.013895) Loss: 0.082831 (0.10335) +2025-09-14,23:30:39 | INFO | Train Epoch: 14 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.076316 (0.089406) Boundary_loss: 0.013895 (0.013895) Loss: 0.090211 (0.10330) +2025-09-14,23:31:10 | INFO | Train Epoch: 14 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.083922 (0.089385) Boundary_loss: 0.013895 (0.013895) Loss: 0.097817 (0.10328) +2025-09-14,23:31:40 | INFO | Train Epoch: 14 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.094353 (0.089404) Boundary_loss: 0.013895 (0.013895) Loss: 0.10825 (0.10330) +2025-09-14,23:32:11 | INFO | Train Epoch: 14 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10713 (0.089471) Boundary_loss: 0.013896 (0.013895) Loss: 0.12102 (0.10337) +2025-09-14,23:32:42 | INFO | Train Epoch: 14 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.070020 (0.089398) Boundary_loss: 0.013895 (0.013895) Loss: 0.083914 (0.10329) +2025-09-14,23:33:13 | INFO | Train Epoch: 14 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.078431 (0.089357) Boundary_loss: 0.013895 (0.013895) Loss: 0.092327 (0.10325) +2025-09-14,23:33:43 | INFO | Train Epoch: 14 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.070000 (0.089284) Boundary_loss: 0.013894 (0.013895) Loss: 0.083894 (0.10318) +2025-09-14,23:34:14 | INFO | Train Epoch: 14 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.095475 (0.089307) Boundary_loss: 0.013895 (0.013895) Loss: 0.10937 (0.10320) +2025-09-14,23:34:45 | INFO | Train Epoch: 14 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.11199 (0.089391) Boundary_loss: 0.013894 (0.013895) Loss: 0.12589 (0.10329) +2025-09-14,23:35:16 | INFO | Train Epoch: 14 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.076227 (0.089343) Boundary_loss: 0.013894 (0.013895) Loss: 0.090121 (0.10324) +2025-09-14,23:35:47 | INFO | Train Epoch: 14 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11013 (0.089419) Boundary_loss: 0.013894 (0.013895) Loss: 0.12402 (0.10331) +2025-09-14,23:36:18 | INFO | Train Epoch: 14 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11069 (0.089497) Boundary_loss: 0.013894 (0.013895) Loss: 0.12458 (0.10339) +2025-09-14,23:36:48 | INFO | Train Epoch: 14 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10585 (0.089557) Boundary_loss: 0.013895 (0.013895) Loss: 0.11974 (0.10345) +2025-09-14,23:37:19 | INFO | Train Epoch: 14 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.077447 (0.089513) Boundary_loss: 0.013895 (0.013895) Loss: 0.091342 (0.10341) +2025-09-14,23:37:50 | INFO | Train Epoch: 14 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.078473 (0.089473) Boundary_loss: 0.013894 (0.013895) Loss: 0.092368 (0.10337) +2025-09-14,23:38:20 | INFO | Train Epoch: 14 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.084622 (0.089455) Boundary_loss: 0.013895 (0.013895) Loss: 0.098517 (0.10335) +2025-09-14,23:38:51 | INFO | Train Epoch: 14 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11421 (0.089544) Boundary_loss: 0.013894 (0.013895) Loss: 0.12810 (0.10344) +2025-09-14,23:39:22 | INFO | Train Epoch: 14 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.071689 (0.089480) Boundary_loss: 0.013894 (0.013895) Loss: 0.085583 (0.10337) +2025-09-14,23:39:52 | INFO | Train Epoch: 14 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.057407 (0.089366) Boundary_loss: 0.013894 (0.013895) Loss: 0.071301 (0.10326) +2025-09-14,23:40:23 | INFO | Train Epoch: 14 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.070350 (0.089298) Boundary_loss: 0.013894 (0.013895) Loss: 0.084244 (0.10319) +2025-09-14,23:40:54 | INFO | Train Epoch: 14 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.077313 (0.089256) Boundary_loss: 0.013895 (0.013895) Loss: 0.091209 (0.10315) +2025-09-14,23:41:25 | INFO | Train Epoch: 14 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.060318 (0.089153) Boundary_loss: 0.013895 (0.013895) Loss: 0.074213 (0.10305) +2025-09-14,23:41:55 | INFO | Train Epoch: 14 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.086142 (0.089143) Boundary_loss: 0.013895 (0.013895) Loss: 0.10004 (0.10304) +2025-09-14,23:42:26 | INFO | Train Epoch: 14 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.076168 (0.089097) Boundary_loss: 0.013895 (0.013895) Loss: 0.090063 (0.10299) +2025-09-14,23:42:56 | INFO | Train Epoch: 14 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.078733 (0.089061) Boundary_loss: 0.013894 (0.013895) Loss: 0.092627 (0.10296) +2025-09-14,23:43:27 | INFO | Train Epoch: 14 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11204 (0.089141) Boundary_loss: 0.013895 (0.013895) Loss: 0.12593 (0.10304) +2025-09-14,23:43:58 | INFO | Train Epoch: 14 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.064007 (0.089054) Boundary_loss: 0.013895 (0.013895) Loss: 0.077902 (0.10295) +2025-09-14,23:44:28 | INFO | Train Epoch: 14 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.13909 (0.089227) Boundary_loss: 0.013896 (0.013895) Loss: 0.15299 (0.10312) +2025-09-14,23:44:58 | INFO | Train Epoch: 14 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.065539 (0.089145) Boundary_loss: 0.013895 (0.013895) Loss: 0.079434 (0.10304) +2025-09-14,23:45:29 | INFO | Train Epoch: 14 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.074612 (0.089095) Boundary_loss: 0.013896 (0.013895) Loss: 0.088508 (0.10299) +2025-09-14,23:46:00 | INFO | Train Epoch: 14 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.10623 (0.089154) Boundary_loss: 0.013894 (0.013895) Loss: 0.12013 (0.10305) +2025-09-14,23:46:30 | INFO | Train Epoch: 14 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10023 (0.089192) Boundary_loss: 0.013894 (0.013895) Loss: 0.11412 (0.10309) +2025-09-14,23:47:01 | INFO | Train Epoch: 14 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.091995 (0.089201) Boundary_loss: 0.013895 (0.013895) Loss: 0.10589 (0.10310) +2025-09-14,23:47:32 | INFO | Train Epoch: 14 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.066605 (0.089125) Boundary_loss: 0.013895 (0.013895) Loss: 0.080500 (0.10302) +2025-09-14,23:48:03 | INFO | Train Epoch: 14 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.070201 (0.089061) Boundary_loss: 0.013895 (0.013895) Loss: 0.084095 (0.10296) +2025-09-14,23:48:34 | INFO | Train Epoch: 14 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.067118 (0.088987) Boundary_loss: 0.013895 (0.013895) Loss: 0.081013 (0.10288) +2025-09-14,23:49:04 | INFO | Train Epoch: 14 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.097762 (0.089016) Boundary_loss: 0.013894 (0.013895) Loss: 0.11166 (0.10291) +2025-09-14,23:49:35 | INFO | Train Epoch: 14 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10989 (0.089086) Boundary_loss: 0.013895 (0.013895) Loss: 0.12378 (0.10298) +2025-09-14,23:50:06 | INFO | Train Epoch: 14 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.071302 (0.089027) Boundary_loss: 0.013894 (0.013895) Loss: 0.085196 (0.10292) +2025-09-14,23:50:36 | INFO | Train Epoch: 14 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.079895 (0.088996) Boundary_loss: 0.013895 (0.013895) Loss: 0.093790 (0.10289) +2025-09-14,23:51:07 | INFO | Train Epoch: 14 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.076940 (0.088957) Boundary_loss: 0.013895 (0.013895) Loss: 0.090835 (0.10285) +2025-09-14,23:51:37 | INFO | Train Epoch: 14 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.080197 (0.088928) Boundary_loss: 0.013895 (0.013895) Loss: 0.094092 (0.10282) +2025-09-14,23:52:08 | INFO | Train Epoch: 14 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.089295 (0.088929) Boundary_loss: 0.013895 (0.013895) Loss: 0.10319 (0.10282) +2025-09-14,23:52:38 | INFO | Train Epoch: 14 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11723 (0.089022) Boundary_loss: 0.013894 (0.013895) Loss: 0.13112 (0.10292) +2025-09-14,23:53:09 | INFO | Train Epoch: 14 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.073464 (0.088971) Boundary_loss: 0.013895 (0.013895) Loss: 0.087359 (0.10287) +2025-09-14,23:53:39 | INFO | Train Epoch: 14 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.083486 (0.088953) Boundary_loss: 0.013895 (0.013895) Loss: 0.097380 (0.10285) +2025-09-14,23:54:10 | INFO | Train Epoch: 14 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.083313 (0.088935) Boundary_loss: 0.013895 (0.013895) Loss: 0.097208 (0.10283) +2025-09-14,23:54:41 | INFO | Train Epoch: 14 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.12057 (0.089037) Boundary_loss: 0.013895 (0.013895) Loss: 0.13447 (0.10293) +2025-09-14,23:55:11 | INFO | Train Epoch: 14 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.097952 (0.089066) Boundary_loss: 0.013896 (0.013895) Loss: 0.11185 (0.10296) +2025-09-14,23:55:42 | INFO | Train Epoch: 14 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.068236 (0.088999) Boundary_loss: 0.013895 (0.013895) Loss: 0.082131 (0.10289) +2025-09-14,23:56:13 | INFO | Train Epoch: 14 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10513 (0.089050) Boundary_loss: 0.013895 (0.013895) Loss: 0.11902 (0.10295) +2025-09-14,23:56:43 | INFO | Train Epoch: 14 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.096341 (0.089074) Boundary_loss: 0.013895 (0.013895) Loss: 0.11024 (0.10297) +2025-09-14,23:57:14 | INFO | Train Epoch: 14 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11594 (0.089159) Boundary_loss: 0.013895 (0.013895) Loss: 0.12984 (0.10305) +2025-09-14,23:57:44 | INFO | Train Epoch: 14 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.083812 (0.089142) Boundary_loss: 0.013895 (0.013895) Loss: 0.097707 (0.10304) +2025-09-14,23:58:15 | INFO | Train Epoch: 14 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.084232 (0.089127) Boundary_loss: 0.013894 (0.013895) Loss: 0.098127 (0.10302) +2025-09-14,23:58:46 | INFO | Train Epoch: 14 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.086592 (0.089119) Boundary_loss: 0.013894 (0.013895) Loss: 0.10049 (0.10301) +2025-09-14,23:59:17 | INFO | Train Epoch: 14 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.054235 (0.089009) Boundary_loss: 0.013895 (0.013895) Loss: 0.068130 (0.10290) +2025-09-14,23:59:47 | INFO | Train Epoch: 14 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.062528 (0.088926) Boundary_loss: 0.013895 (0.013895) Loss: 0.076423 (0.10282) +2025-09-15,00:00:18 | INFO | Train Epoch: 14 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.12110 (0.089027) Boundary_loss: 0.013895 (0.013895) Loss: 0.13500 (0.10292) +2025-09-15,00:00:49 | INFO | Train Epoch: 14 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10164 (0.089066) Boundary_loss: 0.013894 (0.013895) Loss: 0.11554 (0.10296) +2025-09-15,00:01:20 | INFO | Train Epoch: 14 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.057570 (0.088968) Boundary_loss: 0.013896 (0.013895) Loss: 0.071466 (0.10286) +2025-09-15,00:01:50 | INFO | Train Epoch: 14 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.086373 (0.088960) Boundary_loss: 0.013895 (0.013895) Loss: 0.10027 (0.10285) +2025-09-15,00:02:21 | INFO | Train Epoch: 14 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.086230 (0.088952) Boundary_loss: 0.013895 (0.013895) Loss: 0.10013 (0.10285) +2025-09-15,00:02:52 | INFO | Train Epoch: 14 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10750 (0.089009) Boundary_loss: 0.013895 (0.013895) Loss: 0.12140 (0.10290) +2025-09-15,00:03:22 | INFO | Train Epoch: 14 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.070030 (0.088951) Boundary_loss: 0.013895 (0.013895) Loss: 0.083925 (0.10285) +2025-09-15,00:03:53 | INFO | Train Epoch: 14 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.061996 (0.088868) Boundary_loss: 0.013895 (0.013895) Loss: 0.075891 (0.10276) +2025-09-15,00:04:24 | INFO | Train Epoch: 14 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.10804 (0.088927) Boundary_loss: 0.013894 (0.013895) Loss: 0.12194 (0.10282) +2025-09-15,00:04:54 | INFO | Train Epoch: 14 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10123 (0.088964) Boundary_loss: 0.013895 (0.013895) Loss: 0.11513 (0.10286) +2025-09-15,00:05:25 | INFO | Train Epoch: 14 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10711 (0.089019) Boundary_loss: 0.013896 (0.013895) Loss: 0.12100 (0.10291) +2025-09-15,00:05:56 | INFO | Train Epoch: 14 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.068667 (0.088957) Boundary_loss: 0.013895 (0.013895) Loss: 0.082562 (0.10285) +2025-09-15,00:06:26 | INFO | Train Epoch: 14 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10007 (0.088991) Boundary_loss: 0.013894 (0.013895) Loss: 0.11397 (0.10289) +2025-09-15,00:06:57 | INFO | Train Epoch: 14 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.091026 (0.088997) Boundary_loss: 0.013894 (0.013895) Loss: 0.10492 (0.10289) +2025-09-15,00:07:27 | INFO | Train Epoch: 14 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.11446 (0.089073) Boundary_loss: 0.013894 (0.013895) Loss: 0.12835 (0.10297) +2025-09-15,00:07:58 | INFO | Train Epoch: 14 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10204 (0.089112) Boundary_loss: 0.013895 (0.013895) Loss: 0.11594 (0.10301) +2025-09-15,00:08:29 | INFO | Train Epoch: 14 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14346 (0.089274) Boundary_loss: 0.013896 (0.013895) Loss: 0.15735 (0.10317) +2025-09-15,00:08:59 | INFO | Train Epoch: 14 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.054709 (0.089171) Boundary_loss: 0.013894 (0.013895) Loss: 0.068603 (0.10307) +2025-09-15,00:09:30 | INFO | Train Epoch: 14 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.12768 (0.089285) Boundary_loss: 0.013894 (0.013895) Loss: 0.14158 (0.10318) +2025-09-15,00:10:00 | INFO | Train Epoch: 14 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.079340 (0.089256) Boundary_loss: 0.013895 (0.013895) Loss: 0.093235 (0.10315) +2025-09-15,00:10:31 | INFO | Train Epoch: 14 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.098666 (0.089283) Boundary_loss: 0.013895 (0.013895) Loss: 0.11256 (0.10318) +2025-09-15,00:11:02 | INFO | Train Epoch: 14 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.074339 (0.089240) Boundary_loss: 0.013896 (0.013895) Loss: 0.088235 (0.10313) +2025-09-15,00:11:32 | INFO | Train Epoch: 14 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.098888 (0.089268) Boundary_loss: 0.013895 (0.013895) Loss: 0.11278 (0.10316) +2025-09-15,00:12:03 | INFO | Train Epoch: 14 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.096877 (0.089290) Boundary_loss: 0.013895 (0.013895) Loss: 0.11077 (0.10318) +2025-09-15,00:12:34 | INFO | Train Epoch: 14 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.083716 (0.089274) Boundary_loss: 0.013895 (0.013895) Loss: 0.097611 (0.10317) +2025-09-15,00:13:05 | INFO | Train Epoch: 14 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.069917 (0.089218) Boundary_loss: 0.013894 (0.013895) Loss: 0.083812 (0.10311) +2025-09-15,00:13:35 | INFO | Train Epoch: 14 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.082375 (0.089198) Boundary_loss: 0.013895 (0.013895) Loss: 0.096270 (0.10309) +2025-09-15,00:14:06 | INFO | Train Epoch: 14 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.052971 (0.089094) Boundary_loss: 0.013895 (0.013895) Loss: 0.066866 (0.10299) +2025-09-15,00:14:37 | INFO | Train Epoch: 14 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.087072 (0.089088) Boundary_loss: 0.013895 (0.013895) Loss: 0.10097 (0.10298) +2025-09-15,00:15:08 | INFO | Train Epoch: 14 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.095780 (0.089107) Boundary_loss: 0.013895 (0.013895) Loss: 0.10968 (0.10300) +2025-09-15,00:15:38 | INFO | Train Epoch: 14 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.056962 (0.089015) Boundary_loss: 0.013894 (0.013895) Loss: 0.070856 (0.10291) +2025-09-15,00:16:09 | INFO | Train Epoch: 14 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10400 (0.089058) Boundary_loss: 0.013894 (0.013895) Loss: 0.11789 (0.10295) +2025-09-15,00:16:40 | INFO | Train Epoch: 14 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10235 (0.089096) Boundary_loss: 0.013894 (0.013895) Loss: 0.11624 (0.10299) +2025-09-15,00:17:11 | INFO | Train Epoch: 14 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.076586 (0.089060) Boundary_loss: 0.013894 (0.013895) Loss: 0.090480 (0.10295) +2025-09-15,00:17:41 | INFO | Train Epoch: 14 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10240 (0.089098) Boundary_loss: 0.013895 (0.013895) Loss: 0.11630 (0.10299) +2025-09-15,00:18:12 | INFO | Train Epoch: 14 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.085454 (0.089088) Boundary_loss: 0.013895 (0.013895) Loss: 0.099349 (0.10298) +2025-09-15,00:18:43 | INFO | Train Epoch: 14 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.096157 (0.089107) Boundary_loss: 0.013895 (0.013895) Loss: 0.11005 (0.10300) +2025-09-15,00:19:13 | INFO | Train Epoch: 14 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10182 (0.089143) Boundary_loss: 0.013896 (0.013895) Loss: 0.11571 (0.10304) +2025-09-15,00:19:44 | INFO | Train Epoch: 14 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.10260 (0.089181) Boundary_loss: 0.013894 (0.013895) Loss: 0.11649 (0.10308) +2025-09-15,00:20:15 | INFO | Train Epoch: 14 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.077177 (0.089147) Boundary_loss: 0.013895 (0.013895) Loss: 0.091072 (0.10304) +2025-09-15,00:20:46 | INFO | Train Epoch: 14 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.077215 (0.089114) Boundary_loss: 0.013894 (0.013895) Loss: 0.091110 (0.10301) +2025-09-15,00:21:16 | INFO | Train Epoch: 14 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.088920 (0.089113) Boundary_loss: 0.013895 (0.013895) Loss: 0.10282 (0.10301) +2025-09-15,00:21:46 | INFO | Train Epoch: 14 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.076182 (0.089078) Boundary_loss: 0.013895 (0.013895) Loss: 0.090077 (0.10297) +2025-09-15,00:22:17 | INFO | Train Epoch: 14 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.13593 (0.089207) Boundary_loss: 0.013894 (0.013895) Loss: 0.14982 (0.10310) +2025-09-15,00:22:48 | INFO | Train Epoch: 14 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.089773 (0.089208) Boundary_loss: 0.013895 (0.013895) Loss: 0.10367 (0.10310) +2025-09-15,00:23:19 | INFO | Train Epoch: 14 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10676 (0.089256) Boundary_loss: 0.013897 (0.013895) Loss: 0.12066 (0.10315) +2025-09-15,00:23:49 | INFO | Train Epoch: 14 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.069560 (0.089203) Boundary_loss: 0.013895 (0.013895) Loss: 0.083456 (0.10310) +2025-09-15,00:24:20 | INFO | Train Epoch: 14 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.071699 (0.089155) Boundary_loss: 0.013895 (0.013895) Loss: 0.085594 (0.10305) +2025-09-15,00:24:51 | INFO | Train Epoch: 14 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.064377 (0.089088) Boundary_loss: 0.013894 (0.013895) Loss: 0.078271 (0.10298) +2025-09-15,00:25:21 | INFO | Train Epoch: 14 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.083005 (0.089071) Boundary_loss: 0.013895 (0.013895) Loss: 0.096900 (0.10297) +2025-09-15,00:25:52 | INFO | Train Epoch: 14 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.090497 (0.089075) Boundary_loss: 0.013895 (0.013895) Loss: 0.10439 (0.10297) +2025-09-15,00:26:23 | INFO | Train Epoch: 14 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.095840 (0.089093) Boundary_loss: 0.013894 (0.013895) Loss: 0.10973 (0.10299) +2025-09-15,00:26:53 | INFO | Train Epoch: 14 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.078687 (0.089065) Boundary_loss: 0.013894 (0.013895) Loss: 0.092581 (0.10296) +2025-09-15,00:27:24 | INFO | Train Epoch: 14 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.074157 (0.089025) Boundary_loss: 0.013894 (0.013895) Loss: 0.088051 (0.10292) +2025-09-15,00:27:55 | INFO | Train Epoch: 14 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.077800 (0.088995) Boundary_loss: 0.013895 (0.013895) Loss: 0.091695 (0.10289) +2025-09-15,00:28:26 | INFO | Train Epoch: 14 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.046448 (0.088882) Boundary_loss: 0.013895 (0.013895) Loss: 0.060343 (0.10278) +2025-09-15,00:28:57 | INFO | Train Epoch: 14 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.10384 (0.088922) Boundary_loss: 0.013895 (0.013895) Loss: 0.11774 (0.10282) +2025-09-15,00:29:28 | INFO | Train Epoch: 14 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.093428 (0.088934) Boundary_loss: 0.013894 (0.013895) Loss: 0.10732 (0.10283) +2025-09-15,00:29:59 | INFO | Train Epoch: 14 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.098652 (0.088959) Boundary_loss: 0.013895 (0.013895) Loss: 0.11255 (0.10285) +2025-09-15,00:30:30 | INFO | Train Epoch: 14 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10113 (0.088991) Boundary_loss: 0.013895 (0.013895) Loss: 0.11502 (0.10289) +2025-09-15,00:31:01 | INFO | Train Epoch: 14 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.10277 (0.089028) Boundary_loss: 0.013896 (0.013895) Loss: 0.11666 (0.10292) +2025-09-15,00:31:32 | INFO | Train Epoch: 14 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.066168 (0.088968) Boundary_loss: 0.013895 (0.013895) Loss: 0.080063 (0.10286) +2025-09-15,00:32:02 | INFO | Train Epoch: 14 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.082647 (0.088951) Boundary_loss: 0.013893 (0.013895) Loss: 0.096540 (0.10285) +2025-09-15,00:32:33 | INFO | Train Epoch: 14 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.053473 (0.088858) Boundary_loss: 0.013895 (0.013895) Loss: 0.067369 (0.10275) +2025-09-15,00:33:04 | INFO | Train Epoch: 14 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.088367 (0.088857) Boundary_loss: 0.013895 (0.013895) Loss: 0.10226 (0.10275) +2025-09-15,00:33:34 | INFO | Train Epoch: 14 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.078232 (0.088830) Boundary_loss: 0.013895 (0.013895) Loss: 0.092127 (0.10272) +2025-09-15,00:34:05 | INFO | Train Epoch: 14 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.083369 (0.088815) Boundary_loss: 0.013894 (0.013895) Loss: 0.097263 (0.10271) +2025-09-15,00:34:36 | INFO | Train Epoch: 14 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.087914 (0.088813) Boundary_loss: 0.013897 (0.013895) Loss: 0.10181 (0.10271) +2025-09-15,00:35:06 | INFO | Train Epoch: 14 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.087135 (0.088809) Boundary_loss: 0.013894 (0.013895) Loss: 0.10103 (0.10270) +2025-09-15,00:35:37 | INFO | Train Epoch: 14 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.066373 (0.088751) Boundary_loss: 0.013895 (0.013895) Loss: 0.080268 (0.10265) +2025-09-15,00:36:08 | INFO | Train Epoch: 14 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.060203 (0.088678) Boundary_loss: 0.013894 (0.013895) Loss: 0.074097 (0.10257) +2025-09-15,00:36:39 | INFO | Train Epoch: 14 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.064609 (0.088616) Boundary_loss: 0.013896 (0.013895) Loss: 0.078504 (0.10251) +2025-09-15,00:37:09 | INFO | Train Epoch: 14 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.078006 (0.088589) Boundary_loss: 0.013894 (0.013895) Loss: 0.091901 (0.10248) +2025-09-15,00:37:40 | INFO | Train Epoch: 14 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13065 (0.088696) Boundary_loss: 0.013894 (0.013895) Loss: 0.14454 (0.10259) +2025-09-15,00:38:11 | INFO | Train Epoch: 14 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.083214 (0.088682) Boundary_loss: 0.013894 (0.013895) Loss: 0.097108 (0.10258) +2025-09-15,00:38:42 | INFO | Train Epoch: 14 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.091011 (0.088688) Boundary_loss: 0.013895 (0.013895) Loss: 0.10491 (0.10258) +2025-09-15,00:39:12 | INFO | Train Epoch: 14 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.081303 (0.088670) Boundary_loss: 0.013894 (0.013895) Loss: 0.095197 (0.10256) +2025-09-15,00:39:43 | INFO | Train Epoch: 14 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10367 (0.088707) Boundary_loss: 0.013897 (0.013895) Loss: 0.11757 (0.10260) +2025-09-15,00:40:14 | INFO | Train Epoch: 14 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11654 (0.088777) Boundary_loss: 0.013895 (0.013895) Loss: 0.13043 (0.10267) +2025-09-15,00:40:44 | INFO | Train Epoch: 14 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11719 (0.088849) Boundary_loss: 0.013895 (0.013895) Loss: 0.13108 (0.10274) +2025-09-15,00:41:15 | INFO | Train Epoch: 14 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.076504 (0.088818) Boundary_loss: 0.013894 (0.013895) Loss: 0.090398 (0.10271) +2025-09-15,00:41:46 | INFO | Train Epoch: 14 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.10337 (0.088854) Boundary_loss: 0.013894 (0.013895) Loss: 0.11727 (0.10275) +2025-09-15,00:42:17 | INFO | Train Epoch: 14 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.067068 (0.088800) Boundary_loss: 0.013895 (0.013895) Loss: 0.080963 (0.10269) +2025-09-15,00:42:47 | INFO | Train Epoch: 14 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.083143 (0.088786) Boundary_loss: 0.013895 (0.013895) Loss: 0.097038 (0.10268) +2025-09-15,00:43:18 | INFO | Train Epoch: 14 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.075946 (0.088754) Boundary_loss: 0.013895 (0.013895) Loss: 0.089841 (0.10265) +2025-09-15,00:43:49 | INFO | Train Epoch: 14 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.11912 (0.088829) Boundary_loss: 0.013894 (0.013895) Loss: 0.13301 (0.10272) +2025-09-15,00:44:20 | INFO | Train Epoch: 14 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.12554 (0.088919) Boundary_loss: 0.013895 (0.013895) Loss: 0.13944 (0.10281) +2025-09-15,00:44:50 | INFO | Train Epoch: 14 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10544 (0.088960) Boundary_loss: 0.013895 (0.013895) Loss: 0.11934 (0.10285) +2025-09-15,00:45:21 | INFO | Train Epoch: 14 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.098346 (0.088983) Boundary_loss: 0.013894 (0.013895) Loss: 0.11224 (0.10288) +2025-09-15,00:45:52 | INFO | Train Epoch: 14 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.051628 (0.088892) Boundary_loss: 0.013894 (0.013895) Loss: 0.065523 (0.10279) +2025-09-15,00:46:23 | INFO | Train Epoch: 14 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.10034 (0.088920) Boundary_loss: 0.013894 (0.013895) Loss: 0.11423 (0.10281) +2025-09-15,00:46:54 | INFO | Train Epoch: 14 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.077286 (0.088891) Boundary_loss: 0.013895 (0.013895) Loss: 0.091181 (0.10279) +2025-09-15,00:47:24 | INFO | Train Epoch: 14 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11869 (0.088964) Boundary_loss: 0.013894 (0.013895) Loss: 0.13259 (0.10286) +2025-09-15,00:47:55 | INFO | Train Epoch: 14 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.076895 (0.088934) Boundary_loss: 0.013895 (0.013895) Loss: 0.090790 (0.10283) +2025-09-15,00:48:26 | INFO | Train Epoch: 14 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.13348 (0.089042) Boundary_loss: 0.013894 (0.013895) Loss: 0.14737 (0.10294) +2025-09-15,00:48:56 | INFO | Train Epoch: 14 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.065799 (0.088986) Boundary_loss: 0.013895 (0.013895) Loss: 0.079694 (0.10288) +2025-09-15,00:49:27 | INFO | Train Epoch: 14 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10136 (0.089016) Boundary_loss: 0.013895 (0.013895) Loss: 0.11526 (0.10291) +2025-09-15,00:49:57 | INFO | Train Epoch: 14 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.063464 (0.088954) Boundary_loss: 0.013894 (0.013895) Loss: 0.077358 (0.10285) +2025-09-15,00:50:28 | INFO | Train Epoch: 14 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.079982 (0.088933) Boundary_loss: 0.013894 (0.013895) Loss: 0.093875 (0.10283) +2025-09-15,00:50:59 | INFO | Train Epoch: 14 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10336 (0.088967) Boundary_loss: 0.013896 (0.013895) Loss: 0.11726 (0.10286) +2025-09-15,00:51:30 | INFO | Train Epoch: 14 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.10772 (0.089012) Boundary_loss: 0.013894 (0.013895) Loss: 0.12161 (0.10291) +2025-09-15,00:52:01 | INFO | Train Epoch: 14 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.063829 (0.088952) Boundary_loss: 0.013895 (0.013895) Loss: 0.077724 (0.10285) +2025-09-15,00:52:31 | INFO | Train Epoch: 14 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.066604 (0.088899) Boundary_loss: 0.013894 (0.013895) Loss: 0.080498 (0.10279) +2025-09-15,00:53:02 | INFO | Train Epoch: 14 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.084884 (0.088890) Boundary_loss: 0.013895 (0.013895) Loss: 0.098779 (0.10278) +2025-09-15,00:53:32 | INFO | Train Epoch: 14 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.097411 (0.088910) Boundary_loss: 0.013895 (0.013895) Loss: 0.11131 (0.10280) +2025-09-15,00:54:03 | INFO | Train Epoch: 14 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.087084 (0.088906) Boundary_loss: 0.013895 (0.013895) Loss: 0.10098 (0.10280) +2025-09-15,00:54:34 | INFO | Train Epoch: 14 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.071031 (0.088864) Boundary_loss: 0.013895 (0.013895) Loss: 0.084926 (0.10276) +2025-09-15,00:55:05 | INFO | Train Epoch: 14 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.080248 (0.088843) Boundary_loss: 0.013895 (0.013895) Loss: 0.094143 (0.10274) +2025-09-15,00:55:35 | INFO | Train Epoch: 14 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.080526 (0.088824) Boundary_loss: 0.013895 (0.013895) Loss: 0.094421 (0.10272) +2025-09-15,00:56:06 | INFO | Train Epoch: 14 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.079607 (0.088803) Boundary_loss: 0.013895 (0.013895) Loss: 0.093502 (0.10270) +2025-09-15,00:56:37 | INFO | Train Epoch: 14 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10848 (0.088848) Boundary_loss: 0.013895 (0.013895) Loss: 0.12238 (0.10274) +2025-09-15,00:57:08 | INFO | Train Epoch: 14 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.065087 (0.088793) Boundary_loss: 0.013894 (0.013895) Loss: 0.078982 (0.10269) +2025-09-15,00:57:39 | INFO | Train Epoch: 14 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10359 (0.088827) Boundary_loss: 0.013895 (0.013895) Loss: 0.11748 (0.10272) +2025-09-15,00:58:09 | INFO | Train Epoch: 14 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.091762 (0.088834) Boundary_loss: 0.013895 (0.013895) Loss: 0.10566 (0.10273) +2025-09-15,00:58:40 | INFO | Train Epoch: 14 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.051150 (0.088747) Boundary_loss: 0.013895 (0.013895) Loss: 0.065046 (0.10264) +2025-09-15,00:59:11 | INFO | Train Epoch: 14 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.061405 (0.088684) Boundary_loss: 0.013895 (0.013895) Loss: 0.075300 (0.10258) +2025-09-15,00:59:42 | INFO | Train Epoch: 14 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.093494 (0.088696) Boundary_loss: 0.013894 (0.013895) Loss: 0.10739 (0.10259) +2025-09-15,01:00:12 | INFO | Train Epoch: 14 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.098455 (0.088718) Boundary_loss: 0.013894 (0.013895) Loss: 0.11235 (0.10261) +2025-09-15,01:00:43 | INFO | Train Epoch: 14 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.066180 (0.088666) Boundary_loss: 0.013895 (0.013895) Loss: 0.080075 (0.10256) +2025-09-15,01:01:13 | INFO | Train Epoch: 14 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.091775 (0.088673) Boundary_loss: 0.013894 (0.013895) Loss: 0.10567 (0.10257) +2025-09-15,01:01:44 | INFO | Train Epoch: 14 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.093851 (0.088685) Boundary_loss: 0.013895 (0.013895) Loss: 0.10775 (0.10258) +2025-09-15,01:02:14 | INFO | Train Epoch: 14 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11601 (0.088747) Boundary_loss: 0.013894 (0.013895) Loss: 0.12990 (0.10264) +2025-09-15,01:02:44 | INFO | Train Epoch: 14 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.086994 (0.088743) Boundary_loss: 0.013894 (0.013895) Loss: 0.10089 (0.10264) +2025-09-15,01:03:14 | INFO | Train Epoch: 14 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.089423 (0.088745) Boundary_loss: 0.013896 (0.013895) Loss: 0.10332 (0.10264) +2025-09-15,01:03:45 | INFO | Train Epoch: 14 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.092982 (0.088754) Boundary_loss: 0.013895 (0.013895) Loss: 0.10688 (0.10265) +2025-09-15,01:04:15 | INFO | Train Epoch: 14 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.069346 (0.088711) Boundary_loss: 0.013896 (0.013895) Loss: 0.083242 (0.10261) +2025-09-15,01:04:45 | INFO | Train Epoch: 14 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11513 (0.088770) Boundary_loss: 0.013895 (0.013895) Loss: 0.12903 (0.10266) +2025-09-15,01:05:15 | INFO | Train Epoch: 14 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.075119 (0.088739) Boundary_loss: 0.013895 (0.013895) Loss: 0.089015 (0.10263) +2025-09-15,01:05:45 | INFO | Train Epoch: 14 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.13417 (0.088841) Boundary_loss: 0.013896 (0.013895) Loss: 0.14807 (0.10274) +2025-09-15,01:06:16 | INFO | Train Epoch: 14 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.094487 (0.088853) Boundary_loss: 0.013895 (0.013895) Loss: 0.10838 (0.10275) +2025-09-15,01:06:46 | INFO | Train Epoch: 14 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11358 (0.088908) Boundary_loss: 0.013895 (0.013895) Loss: 0.12748 (0.10280) +2025-09-15,01:07:16 | INFO | Train Epoch: 14 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.086614 (0.088903) Boundary_loss: 0.013894 (0.013895) Loss: 0.10051 (0.10280) +2025-09-15,01:07:47 | INFO | Train Epoch: 14 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.12359 (0.088980) Boundary_loss: 0.013894 (0.013895) Loss: 0.13749 (0.10287) +2025-09-15,01:08:18 | INFO | Train Epoch: 14 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.097486 (0.088999) Boundary_loss: 0.013894 (0.013895) Loss: 0.11138 (0.10289) +2025-09-15,01:08:49 | INFO | Train Epoch: 14 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.081010 (0.088981) Boundary_loss: 0.013894 (0.013895) Loss: 0.094904 (0.10288) +2025-09-15,01:09:20 | INFO | Train Epoch: 14 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.12604 (0.089063) Boundary_loss: 0.013895 (0.013895) Loss: 0.13994 (0.10296) +2025-09-15,01:09:51 | INFO | Train Epoch: 14 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.098376 (0.089083) Boundary_loss: 0.013894 (0.013895) Loss: 0.11227 (0.10298) +2025-09-15,01:10:22 | INFO | Train Epoch: 14 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.054813 (0.089008) Boundary_loss: 0.013894 (0.013895) Loss: 0.068708 (0.10290) +2025-09-15,01:10:53 | INFO | Train Epoch: 14 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.078029 (0.088984) Boundary_loss: 0.013896 (0.013895) Loss: 0.091925 (0.10288) +2025-09-15,01:11:24 | INFO | Train Epoch: 14 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.068319 (0.088939) Boundary_loss: 0.013896 (0.013895) Loss: 0.082215 (0.10283) +2025-09-15,01:11:55 | INFO | Train Epoch: 14 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.081257 (0.088922) Boundary_loss: 0.013894 (0.013895) Loss: 0.095152 (0.10282) +2025-09-15,01:12:25 | INFO | Train Epoch: 14 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.047403 (0.088832) Boundary_loss: 0.013895 (0.013895) Loss: 0.061298 (0.10273) +2025-09-15,01:12:56 | INFO | Train Epoch: 14 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.063619 (0.088778) Boundary_loss: 0.013895 (0.013895) Loss: 0.077515 (0.10267) +2025-09-15,01:13:27 | INFO | Train Epoch: 14 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.083512 (0.088766) Boundary_loss: 0.013895 (0.013895) Loss: 0.097407 (0.10266) +2025-09-15,01:13:58 | INFO | Train Epoch: 14 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.089758 (0.088768) Boundary_loss: 0.013894 (0.013895) Loss: 0.10365 (0.10266) +2025-09-15,01:14:29 | INFO | Train Epoch: 14 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.099805 (0.088792) Boundary_loss: 0.013894 (0.013895) Loss: 0.11370 (0.10269) +2025-09-15,01:14:59 | INFO | Train Epoch: 14 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.067085 (0.088746) Boundary_loss: 0.013894 (0.013895) Loss: 0.080979 (0.10264) +2025-09-15,01:15:30 | INFO | Train Epoch: 14 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.062965 (0.088690) Boundary_loss: 0.013895 (0.013895) Loss: 0.076859 (0.10259) +2025-09-15,01:16:01 | INFO | Train Epoch: 14 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.097611 (0.088709) Boundary_loss: 0.013894 (0.013895) Loss: 0.11151 (0.10260) +2025-09-15,01:16:31 | INFO | Train Epoch: 14 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11718 (0.088770) Boundary_loss: 0.013895 (0.013895) Loss: 0.13108 (0.10266) +2025-09-15,01:17:02 | INFO | Train Epoch: 14 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.10001 (0.088794) Boundary_loss: 0.013895 (0.013895) Loss: 0.11390 (0.10269) +2025-09-15,01:17:32 | INFO | Train Epoch: 14 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.085546 (0.088787) Boundary_loss: 0.013895 (0.013895) Loss: 0.099441 (0.10268) +2025-09-15,01:18:03 | INFO | Train Epoch: 14 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.097292 (0.088805) Boundary_loss: 0.013894 (0.013895) Loss: 0.11119 (0.10270) +2025-09-15,01:18:34 | INFO | Train Epoch: 14 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.091153 (0.088810) Boundary_loss: 0.013897 (0.013895) Loss: 0.10505 (0.10270) +2025-09-15,01:19:04 | INFO | Train Epoch: 14 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.083494 (0.088799) Boundary_loss: 0.013894 (0.013895) Loss: 0.097389 (0.10269) +2025-09-15,01:19:35 | INFO | Train Epoch: 14 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.067151 (0.088753) Boundary_loss: 0.013895 (0.013895) Loss: 0.081046 (0.10265) +2025-09-15,01:20:06 | INFO | Train Epoch: 14 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.089873 (0.088756) Boundary_loss: 0.013895 (0.013895) Loss: 0.10377 (0.10265) +2025-09-15,01:20:37 | INFO | Train Epoch: 14 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.068949 (0.088714) Boundary_loss: 0.013894 (0.013895) Loss: 0.082844 (0.10261) +2025-09-15,01:21:07 | INFO | Train Epoch: 14 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.078405 (0.088693) Boundary_loss: 0.013895 (0.013895) Loss: 0.092300 (0.10259) +2025-09-15,01:21:38 | INFO | Train Epoch: 14 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.076256 (0.088667) Boundary_loss: 0.013895 (0.013895) Loss: 0.090152 (0.10256) +2025-09-15,01:22:09 | INFO | Train Epoch: 14 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.079669 (0.088648) Boundary_loss: 0.013894 (0.013895) Loss: 0.093563 (0.10254) +2025-09-15,01:22:40 | INFO | Train Epoch: 14 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.10305 (0.088678) Boundary_loss: 0.013895 (0.013895) Loss: 0.11695 (0.10257) +2025-09-15,01:23:10 | INFO | Train Epoch: 14 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.077087 (0.088654) Boundary_loss: 0.013894 (0.013895) Loss: 0.090981 (0.10255) +2025-09-15,01:23:41 | INFO | Train Epoch: 14 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.082940 (0.088642) Boundary_loss: 0.013894 (0.013895) Loss: 0.096835 (0.10254) +2025-09-15,01:24:12 | INFO | Train Epoch: 14 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.092037 (0.088649) Boundary_loss: 0.013894 (0.013895) Loss: 0.10593 (0.10254) +2025-09-15,01:24:42 | INFO | Train Epoch: 14 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.089659 (0.088651) Boundary_loss: 0.013895 (0.013895) Loss: 0.10355 (0.10255) +2025-09-15,01:25:13 | INFO | Train Epoch: 14 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.064533 (0.088602) Boundary_loss: 0.013894 (0.013895) Loss: 0.078427 (0.10250) +2025-09-15,01:25:43 | INFO | Train Epoch: 14 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.081497 (0.088587) Boundary_loss: 0.013895 (0.013895) Loss: 0.095391 (0.10248) +2025-09-15,01:26:14 | INFO | Train Epoch: 14 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.089025 (0.088588) Boundary_loss: 0.013896 (0.013895) Loss: 0.10292 (0.10248) +2025-09-15,01:26:44 | INFO | Train Epoch: 14 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.068500 (0.088547) Boundary_loss: 0.013894 (0.013895) Loss: 0.082395 (0.10244) +2025-09-15,01:27:14 | INFO | Train Epoch: 14 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.096792 (0.088564) Boundary_loss: 0.013894 (0.013895) Loss: 0.11069 (0.10246) +2025-09-15,01:27:45 | INFO | Train Epoch: 14 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.093864 (0.088574) Boundary_loss: 0.013895 (0.013895) Loss: 0.10776 (0.10247) +2025-09-15,01:28:15 | INFO | Train Epoch: 14 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.062567 (0.088521) Boundary_loss: 0.013895 (0.013895) Loss: 0.076462 (0.10242) +2025-09-15,01:28:46 | INFO | Train Epoch: 14 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11498 (0.088575) Boundary_loss: 0.013895 (0.013895) Loss: 0.12887 (0.10247) +2025-09-15,01:29:16 | INFO | Train Epoch: 14 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.067084 (0.088532) Boundary_loss: 0.013894 (0.013895) Loss: 0.080979 (0.10243) +2025-09-15,01:29:47 | INFO | Train Epoch: 14 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.078692 (0.088512) Boundary_loss: 0.013895 (0.013895) Loss: 0.092586 (0.10241) +2025-09-15,01:30:17 | INFO | Train Epoch: 14 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.097482 (0.088530) Boundary_loss: 0.013896 (0.013895) Loss: 0.11138 (0.10242) +2025-09-15,01:30:48 | INFO | Train Epoch: 14 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.088432 (0.088530) Boundary_loss: 0.013896 (0.013895) Loss: 0.10233 (0.10242) +2025-09-15,01:31:18 | INFO | Train Epoch: 14 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.094925 (0.088543) Boundary_loss: 0.013895 (0.013895) Loss: 0.10882 (0.10244) +2025-09-15,01:31:49 | INFO | Train Epoch: 14 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.073663 (0.088513) Boundary_loss: 0.013894 (0.013895) Loss: 0.087557 (0.10241) +2025-09-15,01:32:19 | INFO | Train Epoch: 14 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.088874 (0.088513) Boundary_loss: 0.013895 (0.013895) Loss: 0.10277 (0.10241) +2025-09-15,01:32:50 | INFO | Train Epoch: 14 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.10195 (0.088540) Boundary_loss: 0.013894 (0.013895) Loss: 0.11585 (0.10243) +2025-09-15,01:33:21 | INFO | Train Epoch: 14 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.11282 (0.088589) Boundary_loss: 0.013894 (0.013895) Loss: 0.12672 (0.10248) +2025-09-15,01:33:51 | INFO | Train Epoch: 14 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.086381 (0.088584) Boundary_loss: 0.013896 (0.013895) Loss: 0.10028 (0.10248) +2025-09-15,01:34:21 | INFO | Train Epoch: 14 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.071700 (0.088551) Boundary_loss: 0.013895 (0.013895) Loss: 0.085595 (0.10245) +2025-09-15,01:34:52 | INFO | Train Epoch: 14 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10772 (0.088589) Boundary_loss: 0.013895 (0.013895) Loss: 0.12161 (0.10248) +2025-09-15,01:35:22 | INFO | Train Epoch: 14 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.078707 (0.088569) Boundary_loss: 0.013895 (0.013895) Loss: 0.092602 (0.10246) +2025-09-15,01:35:53 | INFO | Train Epoch: 14 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.094147 (0.088580) Boundary_loss: 0.013895 (0.013895) Loss: 0.10804 (0.10247) +2025-09-15,01:36:23 | INFO | Train Epoch: 14 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.056472 (0.088517) Boundary_loss: 0.013895 (0.013895) Loss: 0.070367 (0.10241) +2025-09-15,01:36:54 | INFO | Train Epoch: 14 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.092236 (0.088524) Boundary_loss: 0.013896 (0.013895) Loss: 0.10613 (0.10242) +2025-09-15,01:37:24 | INFO | Train Epoch: 14 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.060821 (0.088470) Boundary_loss: 0.013894 (0.013895) Loss: 0.074715 (0.10236) +2025-09-15,01:37:55 | INFO | Train Epoch: 14 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.070060 (0.088434) Boundary_loss: 0.013895 (0.013895) Loss: 0.083955 (0.10233) +2025-09-15,01:38:25 | INFO | Train Epoch: 14 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.089710 (0.088436) Boundary_loss: 0.013895 (0.013895) Loss: 0.10360 (0.10233) +2025-09-15,01:38:56 | INFO | Train Epoch: 14 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.076628 (0.088413) Boundary_loss: 0.013895 (0.013895) Loss: 0.090523 (0.10231) +2025-09-15,01:39:26 | INFO | Train Epoch: 14 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.053240 (0.088345) Boundary_loss: 0.013896 (0.013895) Loss: 0.067136 (0.10224) +2025-09-15,01:39:57 | INFO | Train Epoch: 14 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.059166 (0.088288) Boundary_loss: 0.013896 (0.013895) Loss: 0.073062 (0.10218) +2025-09-15,01:40:26 | INFO | Train Epoch: 14 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.089680 (0.088291) Boundary_loss: 0.013895 (0.013895) Loss: 0.10357 (0.10219) +2025-09-15,01:40:26 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-15,01:40:26 | INFO | [Epoch 14] Average Step Time: 0.310s | Average GPU Memory: 25.1 GB +2025-09-15,01:40:26 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-09-15,01:40:26 | INFO | Starting zero-shot imagenet. +2025-09-15,01:40:26 | INFO | Building zero-shot classifier +2025-09-15,01:40:32 | INFO | Using classifier +2025-09-15,01:41:09 | INFO | Finished zero-shot imagenet. +2025-09-15,01:41:09 | INFO | Eval Epoch: 15 imagenet-zeroshot-val-top1: 0.3083 imagenet-zeroshot-val-top5: 0.5763