diff --git "a/DRIP_4x_16_XL_2_10/out.log" "b/DRIP_4x_16_XL_2_10/out.log" new file mode 100644--- /dev/null +++ "b/DRIP_4x_16_XL_2_10/out.log" @@ -0,0 +1,8062 @@ +2025-08-20,15:58:21 | INFO | Running with a single process. Device cuda. +2025-08-20,15:58:21 | INFO | Loaded ViT-B-16 model config. +2025-08-20,15:58:23 | INFO | Model: +2025-08-20,15:58:23 | INFO | CLIP( + (visual): DTPViT( + (patch_embed): Conv2d(3, 768, kernel_size=(16, 16), stride=(16, 16)) + (dropout): Dropout(p=0.0, inplace=False) + (pos_emb): PositionalEmbedding() + (pre_blocks): ModuleList( + (0-1): 2 x RelPartialLearnableDecoderLayer( + (dec_attn): RelPartialLearnableMultiHeadAttn( + (qkv_net): Linear(in_features=768, out_features=2304, bias=True) + (r_net): Linear(in_features=768, out_features=768, bias=True) + (drop): Dropout(p=0.0, inplace=False) + (dropatt): Dropout(p=0.1, inplace=False) + (o_net): Linear(in_features=768, out_features=768, bias=True) + (layer_norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + ) + (pos_ff): PositionwiseFF( + (CoreNet): Sequential( + (0): Linear(in_features=768, out_features=3072, bias=True) + (1): GELU(approximate='none') + (2): Dropout(p=0.0, inplace=False) + (3): Linear(in_features=3072, out_features=768, bias=True) + (4): Dropout(p=0.0, inplace=False) + ) + (layer_norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + ) + ) + ) + (short_blocks): ModuleList( + (0-9): 10 x RelPartialLearnableDecoderLayer( + (dec_attn): RelPartialLearnableMultiHeadAttn( + (qkv_net): Linear(in_features=768, out_features=2304, bias=True) + (r_net): Linear(in_features=768, out_features=768, bias=True) + (drop): Dropout(p=0.0, inplace=False) + (dropatt): Dropout(p=0.1, inplace=False) + (o_net): Linear(in_features=768, out_features=768, bias=True) + (layer_norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + ) + (pos_ff): PositionwiseFF( + (CoreNet): Sequential( + (0): Linear(in_features=768, out_features=3072, bias=True) + (1): GELU(approximate='none') + (2): Dropout(p=0.0, inplace=False) + (3): Linear(in_features=3072, out_features=768, bias=True) + (4): Dropout(p=0.0, inplace=False) + ) + (layer_norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + ) + ) + ) + (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) +) +2025-08-20,15:58:23 | INFO | Params: +2025-08-20,15:58:23 | INFO | DTP: True +2025-08-20,15:58:23 | INFO | accum_freq: 1 +2025-08-20,15:58:23 | INFO | aug_cfg: {} +2025-08-20,15:58:23 | INFO | batch_size: 512 +2025-08-20,15:58:23 | INFO | beta1: 0.9 +2025-08-20,15:58:23 | INFO | beta2: 0.98 +2025-08-20,15:58:23 | INFO | cache_dir: None +2025-08-20,15:58:23 | INFO | checkpoint_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_08_20-15_58_21-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/checkpoints +2025-08-20,15:58:23 | INFO | coca_caption_loss_weight: 2.0 +2025-08-20,15:58:23 | INFO | coca_contrastive_loss_weight: 1.0 +2025-08-20,15:58:23 | INFO | copy_codebase: False +2025-08-20,15:58:23 | INFO | csv_caption_key: title +2025-08-20,15:58:23 | INFO | csv_img_key: filepath +2025-08-20,15:58:23 | INFO | csv_separator: +2025-08-20,15:58:23 | INFO | dataset_resampled: False +2025-08-20,15:58:23 | INFO | dataset_type: webdataset +2025-08-20,15:58:23 | INFO | ddp_static_graph: False +2025-08-20,15:58:23 | INFO | debug: False +2025-08-20,15:58:23 | INFO | delete_previous_checkpoint: False +2025-08-20,15:58:23 | INFO | device: cuda +2025-08-20,15:58:23 | INFO | dist_backend: None +2025-08-20,15:58:23 | INFO | dist_url: None +2025-08-20,15:58:23 | INFO | distill: False +2025-08-20,15:58:23 | INFO | distill_model: None +2025-08-20,15:58:23 | INFO | distill_pretrained: None +2025-08-20,15:58:23 | INFO | distributed: False +2025-08-20,15:58:23 | INFO | epochs: 15 +2025-08-20,15:58:23 | INFO | epochs_cooldown: None +2025-08-20,15:58:23 | INFO | eps: 1e-06 +2025-08-20,15:58:23 | INFO | force_custom_text: False +2025-08-20,15:58:23 | INFO | force_image_size: None +2025-08-20,15:58:23 | INFO | force_patch_dropout: None +2025-08-20,15:58:23 | INFO | force_quick_gelu: False +2025-08-20,15:58:23 | INFO | gather_with_grad: False +2025-08-20,15:58:23 | INFO | grad_checkpointing: False +2025-08-20,15:58:23 | INFO | grad_clip_norm: None +2025-08-20,15:58:23 | INFO | horovod: False +2025-08-20,15:58:23 | INFO | image_interpolation: None +2025-08-20,15:58:23 | INFO | image_mean: None +2025-08-20,15:58:23 | INFO | image_resize_mode: None +2025-08-20,15:58:23 | INFO | image_std: None +2025-08-20,15:58:23 | INFO | imagenet_v2: None +2025-08-20,15:58:23 | INFO | imagenet_val: /fs/scratch/PAS2836/yusenpeng_dataset/val +2025-08-20,15:58:23 | INFO | local_loss: False +2025-08-20,15:58:23 | INFO | local_rank: 0 +2025-08-20,15:58:23 | INFO | lock_image: False +2025-08-20,15:58:23 | INFO | lock_image_freeze_bn_stats: False +2025-08-20,15:58:23 | INFO | lock_image_unlocked_groups: 0 +2025-08-20,15:58:23 | INFO | lock_text: False +2025-08-20,15:58:23 | INFO | lock_text_freeze_layer_norm: False +2025-08-20,15:58:23 | INFO | lock_text_unlocked_layers: 0 +2025-08-20,15:58:23 | INFO | log_every_n_steps: 100 +2025-08-20,15:58:23 | INFO | log_level: 20 +2025-08-20,15:58:23 | INFO | log_local: False +2025-08-20,15:58:23 | INFO | log_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_08_20-15_58_21-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/out.log +2025-08-20,15:58:23 | INFO | logs: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/ +2025-08-20,15:58:23 | INFO | loss_dist_impl: None +2025-08-20,15:58:23 | INFO | lr: 5e-05 +2025-08-20,15:58:23 | INFO | lr_cooldown_end: 0.0 +2025-08-20,15:58:23 | INFO | lr_cooldown_power: 1.0 +2025-08-20,15:58:23 | INFO | lr_scheduler: cosine +2025-08-20,15:58:23 | INFO | model: ViT-B-16 +2025-08-20,15:58:23 | INFO | momentum: None +2025-08-20,15:58:23 | INFO | name: 2025_08_20-15_58_21-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp +2025-08-20,15:58:23 | INFO | no_set_device_rank: False +2025-08-20,15:58:23 | INFO | opt: adamw +2025-08-20,15:58:23 | INFO | precision: amp +2025-08-20,15:58:23 | INFO | pretrained: +2025-08-20,15:58:23 | INFO | pretrained_image: False +2025-08-20,15:58:23 | INFO | rank: 0 +2025-08-20,15:58:23 | INFO | remote_sync: None +2025-08-20,15:58:23 | INFO | remote_sync_frequency: 300 +2025-08-20,15:58:23 | INFO | remote_sync_protocol: s3 +2025-08-20,15:58:23 | INFO | report_to: tensorboard +2025-08-20,15:58:23 | INFO | resume: None +2025-08-20,15:58:23 | INFO | save_frequency: 1 +2025-08-20,15:58:23 | INFO | save_most_recent: False +2025-08-20,15:58:23 | INFO | seed: 0 +2025-08-20,15:58:23 | INFO | siglip: False +2025-08-20,15:58:23 | INFO | skip_scheduler: False +2025-08-20,15:58:23 | INFO | tensorboard: True +2025-08-20,15:58:23 | INFO | tensorboard_path: /fs/scratch/PAS2836/yusenpeng_checkpoint/CLIP/2025_08_20-15_58_21-model_ViT-B-16-lr_5e-05-b_512-j_8-p_amp/tensorboard +2025-08-20,15:58:23 | INFO | torchcompile: False +2025-08-20,15:58:23 | INFO | torchscript: False +2025-08-20,15:58:23 | INFO | trace: False +2025-08-20,15:58:23 | INFO | train_data: 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+2025-08-20,15:58:23 | INFO | train_data_upsampling_factors: None +2025-08-20,15:58:23 | INFO | train_num_samples: 26365716 +2025-08-20,15:58:23 | INFO | use_bn_sync: False +2025-08-20,15:58:23 | INFO | use_bnb_linear: None +2025-08-20,15:58:23 | INFO | val_data: None +2025-08-20,15:58:23 | INFO | val_frequency: 1 +2025-08-20,15:58:23 | INFO | val_num_samples: None +2025-08-20,15:58:23 | INFO | wandb: False +2025-08-20,15:58:23 | INFO | wandb_notes: +2025-08-20,15:58:23 | INFO | wandb_project_name: open-clip +2025-08-20,15:58:23 | INFO | warmup: 50 +2025-08-20,15:58:23 | INFO | wd: 0.1 +2025-08-20,15:58:23 | INFO | workers: 8 +2025-08-20,15:58:23 | INFO | world_size: 1 +2025-08-20,15:58:23 | INFO | zeroshot_frequency: 1 +2025-08-20,15:58:23 | 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 +2025-08-20,15:58:23 | INFO | Start epoch 0 +2025-08-20,15:58:27 | INFO | Train Epoch: 0 [ 512/26365952 (0%)] Avg Boundaries (per batch): 91.553 Boundary Ratio: 0.467 Contrastive_loss: 6.2993 (6.2993) Boundary_loss: 0.12720 (0.12720) Loss: 6.4265 (6.4265) +2025-08-20,15:59:30 | INFO | Train Epoch: 0 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 47.602 Boundary Ratio: 0.243 Contrastive_loss: 6.1217 (6.2105) Boundary_loss: 0.016587 (0.071894) Loss: 6.1383 (6.2824) +2025-08-20,16:00:29 | INFO | Train Epoch: 0 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 49.900 Boundary Ratio: 0.255 Contrastive_loss: 5.9628 (6.1279) Boundary_loss: 0.016744 (0.053510) Loss: 5.9796 (6.1815) +2025-08-20,16:01:28 | INFO | Train Epoch: 0 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 51.076 Boundary Ratio: 0.261 Contrastive_loss: 5.8902 (6.0685) Boundary_loss: 0.017152 (0.044421) Loss: 5.9073 (6.1129) +2025-08-20,16:02:27 | INFO | Train Epoch: 0 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 5.7108 (5.9970) Boundary_loss: 0.016421 (0.038821) Loss: 5.7272 (6.0358) +2025-08-20,16:03:26 | INFO | Train Epoch: 0 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 50.633 Boundary Ratio: 0.258 Contrastive_loss: 5.5808 (5.9276) Boundary_loss: 0.016784 (0.035148) Loss: 5.5975 (5.9627) +2025-08-20,16:04:25 | INFO | Train Epoch: 0 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 5.5097 (5.8679) Boundary_loss: 0.016648 (0.032505) Loss: 5.5263 (5.9004) +2025-08-20,16:05:24 | INFO | Train Epoch: 0 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.791 Boundary Ratio: 0.254 Contrastive_loss: 5.3256 (5.8001) Boundary_loss: 0.016638 (0.030522) Loss: 5.3422 (5.8306) +2025-08-20,16:06:24 | INFO | Train Epoch: 0 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 50.723 Boundary Ratio: 0.259 Contrastive_loss: 5.3431 (5.7493) Boundary_loss: 0.016706 (0.028987) Loss: 5.3598 (5.7783) +2025-08-20,16:07:23 | INFO | Train Epoch: 0 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 5.0870 (5.6831) Boundary_loss: 0.016451 (0.027733) Loss: 5.1034 (5.7108) +2025-08-20,16:08:22 | INFO | Train Epoch: 0 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 47.869 Boundary Ratio: 0.244 Contrastive_loss: 5.2296 (5.6419) Boundary_loss: 0.016634 (0.026724) Loss: 5.2462 (5.6686) +2025-08-20,16:09:21 | INFO | Train Epoch: 0 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 5.1209 (5.5984) Boundary_loss: 0.016228 (0.025849) Loss: 5.1371 (5.6243) +2025-08-20,16:10:20 | INFO | Train Epoch: 0 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 47.332 Boundary Ratio: 0.241 Contrastive_loss: 5.0784 (5.5584) Boundary_loss: 0.016594 (0.025137) Loss: 5.0950 (5.5836) +2025-08-20,16:11:19 | INFO | Train Epoch: 0 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 49.289 Boundary Ratio: 0.251 Contrastive_loss: 4.9038 (5.5117) Boundary_loss: 0.016269 (0.024504) Loss: 4.9201 (5.5362) +2025-08-20,16:12:18 | INFO | Train Epoch: 0 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.057 Boundary Ratio: 0.245 Contrastive_loss: 4.9970 (5.4774) Boundary_loss: 0.016798 (0.023990) Loss: 5.0138 (5.5014) +2025-08-20,16:13:17 | INFO | Train Epoch: 0 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 50.736 Boundary Ratio: 0.259 Contrastive_loss: 5.0131 (5.4484) Boundary_loss: 0.016892 (0.023546) Loss: 5.0300 (5.4719) +2025-08-20,16:14:16 | INFO | Train Epoch: 0 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 4.9378 (5.4183) Boundary_loss: 0.016239 (0.023117) Loss: 4.9541 (5.4414) +2025-08-20,16:15:15 | INFO | Train Epoch: 0 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 4.6659 (5.3765) Boundary_loss: 0.016201 (0.022732) Loss: 4.6821 (5.3993) +2025-08-20,16:16:14 | INFO | Train Epoch: 0 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 49.955 Boundary Ratio: 0.255 Contrastive_loss: 4.5686 (5.3340) Boundary_loss: 0.016605 (0.022410) Loss: 4.5852 (5.3564) +2025-08-20,16:17:13 | INFO | Train Epoch: 0 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 50.408 Boundary Ratio: 0.257 Contrastive_loss: 4.7165 (5.3031) Boundary_loss: 0.016644 (0.022122) Loss: 4.7331 (5.3252) +2025-08-20,16:18:12 | INFO | Train Epoch: 0 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.865 Boundary Ratio: 0.254 Contrastive_loss: 4.6696 (5.2729) Boundary_loss: 0.016332 (0.021846) Loss: 4.6859 (5.2948) +2025-08-20,16:19:11 | INFO | Train Epoch: 0 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 4.6428 (5.2443) Boundary_loss: 0.016516 (0.021604) Loss: 4.6593 (5.2659) +2025-08-20,16:20:10 | INFO | Train Epoch: 0 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 4.6003 (5.2163) Boundary_loss: 0.016180 (0.021368) Loss: 4.6165 (5.2377) +2025-08-20,16:21:09 | INFO | Train Epoch: 0 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 4.3936 (5.1820) Boundary_loss: 0.016323 (0.021158) Loss: 4.4099 (5.2032) +2025-08-20,16:22:08 | INFO | Train Epoch: 0 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 4.6409 (5.1604) Boundary_loss: 0.016421 (0.020968) Loss: 4.6573 (5.1813) +2025-08-20,16:23:07 | INFO | Train Epoch: 0 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 4.3597 (5.1296) Boundary_loss: 0.016342 (0.020790) Loss: 4.3760 (5.1504) +2025-08-20,16:24:06 | INFO | Train Epoch: 0 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 49.562 Boundary Ratio: 0.253 Contrastive_loss: 4.5329 (5.1075) Boundary_loss: 0.016498 (0.020631) Loss: 4.5494 (5.1281) +2025-08-20,16:25:05 | INFO | Train Epoch: 0 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 4.3476 (5.0803) Boundary_loss: 0.016666 (0.020490) Loss: 4.3642 (5.1008) +2025-08-20,16:26:04 | INFO | Train Epoch: 0 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.238 Boundary Ratio: 0.246 Contrastive_loss: 4.2969 (5.0533) Boundary_loss: 0.016439 (0.020350) Loss: 4.3133 (5.0737) +2025-08-20,16:27:03 | INFO | Train Epoch: 0 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 4.3606 (5.0302) Boundary_loss: 0.016274 (0.020214) Loss: 4.3769 (5.0505) +2025-08-20,16:28:02 | INFO | Train Epoch: 0 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 46.662 Boundary Ratio: 0.238 Contrastive_loss: 4.2931 (5.0065) Boundary_loss: 0.016868 (0.020106) Loss: 4.3100 (5.0266) +2025-08-20,16:29:00 | INFO | Train Epoch: 0 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 47.678 Boundary Ratio: 0.243 Contrastive_loss: 4.3362 (4.9855) Boundary_loss: 0.016515 (0.019994) Loss: 4.3527 (5.0055) +2025-08-20,16:29:59 | INFO | Train Epoch: 0 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 49.828 Boundary Ratio: 0.254 Contrastive_loss: 4.2814 (4.9642) Boundary_loss: 0.016263 (0.019881) Loss: 4.2977 (4.9841) +2025-08-20,16:30:58 | INFO | Train Epoch: 0 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 49.268 Boundary Ratio: 0.251 Contrastive_loss: 4.0535 (4.9374) Boundary_loss: 0.016383 (0.019778) Loss: 4.0699 (4.9572) +2025-08-20,16:31:57 | INFO | Train Epoch: 0 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.246 Boundary Ratio: 0.246 Contrastive_loss: 4.0868 (4.9131) Boundary_loss: 0.016170 (0.019675) Loss: 4.1029 (4.9328) +2025-08-20,16:32:56 | INFO | Train Epoch: 0 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 49.361 Boundary Ratio: 0.252 Contrastive_loss: 4.0316 (4.8886) Boundary_loss: 0.016314 (0.019582) Loss: 4.0479 (4.9082) +2025-08-20,16:33:55 | INFO | Train Epoch: 0 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 4.0634 (4.8663) Boundary_loss: 0.016077 (0.019487) Loss: 4.0795 (4.8858) +2025-08-20,16:34:54 | INFO | Train Epoch: 0 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 4.1297 (4.8469) Boundary_loss: 0.016311 (0.019403) Loss: 4.1460 (4.8663) +2025-08-20,16:35:53 | INFO | Train Epoch: 0 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 4.0060 (4.8254) Boundary_loss: 0.016421 (0.019327) Loss: 4.0224 (4.8447) +2025-08-20,16:36:51 | INFO | Train Epoch: 0 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 50.117 Boundary Ratio: 0.256 Contrastive_loss: 3.9155 (4.8026) Boundary_loss: 0.016295 (0.019251) Loss: 3.9318 (4.8219) +2025-08-20,16:37:50 | INFO | Train Epoch: 0 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 4.0014 (4.7831) Boundary_loss: 0.016171 (0.019176) Loss: 4.0175 (4.8022) +2025-08-20,16:38:49 | INFO | Train Epoch: 0 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 3.8197 (4.7601) Boundary_loss: 0.016196 (0.019105) Loss: 3.8359 (4.7792) +2025-08-20,16:39:48 | INFO | Train Epoch: 0 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 47.385 Boundary Ratio: 0.242 Contrastive_loss: 4.0151 (4.7428) Boundary_loss: 0.016300 (0.019040) Loss: 4.0314 (4.7618) +2025-08-20,16:40:47 | INFO | Train Epoch: 0 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 49.645 Boundary Ratio: 0.253 Contrastive_loss: 3.8538 (4.7226) Boundary_loss: 0.016332 (0.018978) Loss: 3.8702 (4.7416) +2025-08-20,16:41:46 | INFO | Train Epoch: 0 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 47.834 Boundary Ratio: 0.244 Contrastive_loss: 3.9407 (4.7052) Boundary_loss: 0.016626 (0.018926) Loss: 3.9573 (4.7241) +2025-08-20,16:42:44 | INFO | Train Epoch: 0 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.105 Boundary Ratio: 0.245 Contrastive_loss: 3.9631 (4.6891) Boundary_loss: 0.015974 (0.018862) Loss: 3.9790 (4.7080) +2025-08-20,16:43:43 | INFO | Train Epoch: 0 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 3.9132 (4.6726) Boundary_loss: 0.016305 (0.018807) Loss: 3.9296 (4.6914) +2025-08-20,16:44:42 | INFO | Train Epoch: 0 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 3.9398 (4.6573) Boundary_loss: 0.016326 (0.018756) Loss: 3.9561 (4.6761) +2025-08-20,16:45:41 | INFO | Train Epoch: 0 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.107 Boundary Ratio: 0.245 Contrastive_loss: 3.8419 (4.6407) Boundary_loss: 0.016420 (0.018708) Loss: 3.8583 (4.6594) +2025-08-20,16:46:39 | INFO | Train Epoch: 0 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 51.207 Boundary Ratio: 0.261 Contrastive_loss: 3.8135 (4.6241) Boundary_loss: 0.016793 (0.018670) Loss: 3.8303 (4.6428) +2025-08-20,16:47:38 | INFO | Train Epoch: 0 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 47.256 Boundary Ratio: 0.241 Contrastive_loss: 3.9919 (4.6117) Boundary_loss: 0.016377 (0.018625) Loss: 4.0083 (4.6304) +2025-08-20,16:48:37 | INFO | Train Epoch: 0 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 3.6988 (4.5942) Boundary_loss: 0.016224 (0.018579) Loss: 3.7150 (4.6128) +2025-08-20,16:49:35 | INFO | Train Epoch: 0 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 3.8433 (4.5800) Boundary_loss: 0.016153 (0.018533) Loss: 3.8594 (4.5985) +2025-08-20,16:50:34 | INFO | Train Epoch: 0 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 47.689 Boundary Ratio: 0.243 Contrastive_loss: 3.7470 (4.5646) Boundary_loss: 0.016551 (0.018496) Loss: 3.7635 (4.5831) +2025-08-20,16:51:33 | INFO | Train Epoch: 0 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 47.732 Boundary Ratio: 0.244 Contrastive_loss: 3.6778 (4.5485) Boundary_loss: 0.016460 (0.018459) Loss: 3.6943 (4.5669) +2025-08-20,16:52:31 | INFO | Train Epoch: 0 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 49.934 Boundary Ratio: 0.255 Contrastive_loss: 3.7574 (4.5343) Boundary_loss: 0.016286 (0.018420) Loss: 3.7737 (4.5528) +2025-08-20,16:53:30 | INFO | Train Epoch: 0 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 50.174 Boundary Ratio: 0.256 Contrastive_loss: 3.5172 (4.5165) Boundary_loss: 0.016281 (0.018383) Loss: 3.5335 (4.5349) +2025-08-20,16:54:28 | INFO | Train Epoch: 0 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 47.443 Boundary Ratio: 0.242 Contrastive_loss: 3.5412 (4.4997) Boundary_loss: 0.016321 (0.018347) Loss: 3.5576 (4.5180) +2025-08-20,16:55:27 | INFO | Train Epoch: 0 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 3.6621 (4.4855) Boundary_loss: 0.015972 (0.018307) Loss: 3.6781 (4.5038) +2025-08-20,16:56:26 | INFO | Train Epoch: 0 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 47.219 Boundary Ratio: 0.241 Contrastive_loss: 3.8050 (4.4741) Boundary_loss: 0.016680 (0.018280) Loss: 3.8217 (4.4924) +2025-08-20,16:57:24 | INFO | Train Epoch: 0 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 3.7097 (4.4616) Boundary_loss: 0.016146 (0.018245) Loss: 3.7259 (4.4799) +2025-08-20,16:58:23 | INFO | Train Epoch: 0 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 3.5014 (4.4461) Boundary_loss: 0.015996 (0.018209) Loss: 3.5174 (4.4643) +2025-08-20,16:59:21 | INFO | Train Epoch: 0 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 3.5739 (4.4323) Boundary_loss: 0.016044 (0.018174) Loss: 3.5900 (4.4504) +2025-08-20,17:00:20 | INFO | Train Epoch: 0 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 47.564 Boundary Ratio: 0.243 Contrastive_loss: 3.7098 (4.4210) Boundary_loss: 0.016318 (0.018145) Loss: 3.7261 (4.4391) +2025-08-20,17:01:19 | INFO | Train Epoch: 0 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.482 Boundary Ratio: 0.247 Contrastive_loss: 3.5706 (4.4079) Boundary_loss: 0.016292 (0.018117) Loss: 3.5869 (4.4260) +2025-08-20,17:02:17 | INFO | Train Epoch: 0 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 3.6947 (4.3971) Boundary_loss: 0.016399 (0.018091) Loss: 3.7111 (4.4152) +2025-08-20,17:03:16 | INFO | Train Epoch: 0 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 3.5721 (4.3848) Boundary_loss: 0.016062 (0.018060) Loss: 3.5882 (4.4028) +2025-08-20,17:04:15 | INFO | Train Epoch: 0 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 3.4222 (4.3706) Boundary_loss: 0.016199 (0.018033) Loss: 3.4384 (4.3887) +2025-08-20,17:05:13 | INFO | Train Epoch: 0 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 3.4617 (4.3575) Boundary_loss: 0.016003 (0.018004) Loss: 3.4777 (4.3755) +2025-08-20,17:06:11 | INFO | Train Epoch: 0 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 47.877 Boundary Ratio: 0.244 Contrastive_loss: 3.6148 (4.3468) Boundary_loss: 0.015957 (0.017974) Loss: 3.6308 (4.3648) +2025-08-20,17:07:10 | INFO | Train Epoch: 0 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 3.5186 (4.3352) Boundary_loss: 0.016017 (0.017947) Loss: 3.5346 (4.3531) +2025-08-20,17:08:08 | INFO | Train Epoch: 0 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 3.4817 (4.3233) Boundary_loss: 0.016116 (0.017921) Loss: 3.4978 (4.3412) +2025-08-20,17:09:07 | INFO | Train Epoch: 0 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 3.3534 (4.3100) Boundary_loss: 0.016283 (0.017899) Loss: 3.3697 (4.3279) +2025-08-20,17:10:05 | INFO | Train Epoch: 0 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 49.168 Boundary Ratio: 0.251 Contrastive_loss: 3.3331 (4.2968) Boundary_loss: 0.016198 (0.017876) Loss: 3.3493 (4.3147) +2025-08-20,17:11:04 | INFO | Train Epoch: 0 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.172 Boundary Ratio: 0.246 Contrastive_loss: 3.4274 (4.2852) Boundary_loss: 0.016013 (0.017851) Loss: 3.4435 (4.3031) +2025-08-20,17:12:02 | INFO | Train Epoch: 0 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.252 Boundary Ratio: 0.246 Contrastive_loss: 3.4289 (4.2740) Boundary_loss: 0.016052 (0.017827) Loss: 3.4450 (4.2918) +2025-08-20,17:13:01 | INFO | Train Epoch: 0 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 3.5057 (4.2640) Boundary_loss: 0.016051 (0.017804) Loss: 3.5218 (4.2818) +2025-08-20,17:13:59 | INFO | Train Epoch: 0 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 47.463 Boundary Ratio: 0.242 Contrastive_loss: 3.3197 (4.2519) Boundary_loss: 0.016324 (0.017785) Loss: 3.3360 (4.2697) +2025-08-20,17:14:58 | INFO | Train Epoch: 0 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 3.3884 (4.2410) Boundary_loss: 0.016102 (0.017764) Loss: 3.4045 (4.2587) +2025-08-20,17:15:56 | INFO | Train Epoch: 0 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 50.287 Boundary Ratio: 0.257 Contrastive_loss: 3.3877 (4.2303) Boundary_loss: 0.016125 (0.017744) Loss: 3.4038 (4.2480) +2025-08-20,17:16:55 | INFO | Train Epoch: 0 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 3.4166 (4.2203) Boundary_loss: 0.016148 (0.017724) Loss: 3.4327 (4.2380) +2025-08-20,17:17:53 | INFO | Train Epoch: 0 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 3.3474 (4.2096) Boundary_loss: 0.015918 (0.017702) Loss: 3.3633 (4.2273) +2025-08-20,17:18:52 | INFO | Train Epoch: 0 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 47.877 Boundary Ratio: 0.244 Contrastive_loss: 3.4164 (4.2001) Boundary_loss: 0.016135 (0.017683) Loss: 3.4325 (4.2177) +2025-08-20,17:19:50 | INFO | Train Epoch: 0 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 49.682 Boundary Ratio: 0.253 Contrastive_loss: 3.5032 (4.1918) Boundary_loss: 0.015963 (0.017663) Loss: 3.5192 (4.2094) +2025-08-20,17:20:49 | INFO | Train Epoch: 0 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 47.674 Boundary Ratio: 0.243 Contrastive_loss: 3.3714 (4.1821) Boundary_loss: 0.016169 (0.017645) Loss: 3.3876 (4.1997) +2025-08-20,17:21:47 | INFO | Train Epoch: 0 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 50.139 Boundary Ratio: 0.256 Contrastive_loss: 3.2903 (4.1717) Boundary_loss: 0.016040 (0.017626) Loss: 3.3063 (4.1894) +2025-08-20,17:22:45 | INFO | Train Epoch: 0 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.389 Boundary Ratio: 0.252 Contrastive_loss: 3.2186 (4.1608) Boundary_loss: 0.016276 (0.017611) Loss: 3.2349 (4.1784) +2025-08-20,17:23:44 | INFO | Train Epoch: 0 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 49.459 Boundary Ratio: 0.252 Contrastive_loss: 3.1738 (4.1496) Boundary_loss: 0.016021 (0.017593) Loss: 3.1899 (4.1672) +2025-08-20,17:24:43 | INFO | Train Epoch: 0 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 47.219 Boundary Ratio: 0.241 Contrastive_loss: 3.2867 (4.1399) Boundary_loss: 0.016145 (0.017576) Loss: 3.3028 (4.1574) +2025-08-20,17:25:41 | INFO | Train Epoch: 0 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 49.182 Boundary Ratio: 0.251 Contrastive_loss: 3.2310 (4.1298) Boundary_loss: 0.016315 (0.017562) Loss: 3.2473 (4.1473) +2025-08-20,17:26:40 | INFO | Train Epoch: 0 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 3.1600 (4.1191) Boundary_loss: 0.016223 (0.017548) Loss: 3.1762 (4.1367) +2025-08-20,17:27:38 | INFO | Train Epoch: 0 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 3.1162 (4.1082) Boundary_loss: 0.016174 (0.017533) Loss: 3.1324 (4.1257) +2025-08-20,17:28:37 | INFO | Train Epoch: 0 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 3.3492 (4.1000) Boundary_loss: 0.016006 (0.017516) Loss: 3.3652 (4.1176) +2025-08-20,17:29:35 | INFO | Train Epoch: 0 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 3.0093 (4.0884) Boundary_loss: 0.016434 (0.017505) Loss: 3.0257 (4.1060) +2025-08-20,17:30:34 | INFO | Train Epoch: 0 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 50.510 Boundary Ratio: 0.258 Contrastive_loss: 3.0573 (4.0776) Boundary_loss: 0.016195 (0.017491) Loss: 3.0735 (4.0951) +2025-08-20,17:31:32 | INFO | Train Epoch: 0 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 49.896 Boundary Ratio: 0.255 Contrastive_loss: 3.0798 (4.0672) Boundary_loss: 0.016133 (0.017477) Loss: 3.0960 (4.0847) +2025-08-20,17:32:31 | INFO | Train Epoch: 0 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 49.977 Boundary Ratio: 0.255 Contrastive_loss: 3.2848 (4.0591) Boundary_loss: 0.016378 (0.017466) Loss: 3.3012 (4.0766) +2025-08-20,17:33:29 | INFO | Train Epoch: 0 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 3.1931 (4.0503) Boundary_loss: 0.015958 (0.017450) Loss: 3.2090 (4.0677) +2025-08-20,17:34:28 | INFO | Train Epoch: 0 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.502 Boundary Ratio: 0.253 Contrastive_loss: 3.1141 (4.0408) Boundary_loss: 0.016085 (0.017436) Loss: 3.1302 (4.0583) +2025-08-20,17:35:26 | INFO | Train Epoch: 0 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 47.936 Boundary Ratio: 0.245 Contrastive_loss: 3.0720 (4.0311) Boundary_loss: 0.016016 (0.017422) Loss: 3.0880 (4.0486) +2025-08-20,17:36:25 | INFO | Train Epoch: 0 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 49.455 Boundary Ratio: 0.252 Contrastive_loss: 3.0865 (4.0218) Boundary_loss: 0.016076 (0.017409) Loss: 3.1026 (4.0392) +2025-08-20,17:37:23 | INFO | Train Epoch: 0 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 3.0984 (4.0127) Boundary_loss: 0.016046 (0.017396) Loss: 3.1145 (4.0301) +2025-08-20,17:38:21 | INFO | Train Epoch: 0 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.062 Boundary Ratio: 0.245 Contrastive_loss: 3.0183 (4.0031) Boundary_loss: 0.016125 (0.017383) Loss: 3.0344 (4.0205) +2025-08-20,17:39:20 | INFO | Train Epoch: 0 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 3.1631 (3.9950) Boundary_loss: 0.015989 (0.017370) Loss: 3.1791 (4.0124) +2025-08-20,17:40:18 | INFO | Train Epoch: 0 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 49.707 Boundary Ratio: 0.254 Contrastive_loss: 2.9666 (3.9852) Boundary_loss: 0.015968 (0.017356) Loss: 2.9826 (4.0026) +2025-08-20,17:41:17 | INFO | Train Epoch: 0 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 3.0350 (3.9763) Boundary_loss: 0.016040 (0.017344) Loss: 3.0510 (3.9936) +2025-08-20,17:42:15 | INFO | Train Epoch: 0 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 3.0385 (3.9675) Boundary_loss: 0.016074 (0.017332) Loss: 3.0545 (3.9848) +2025-08-20,17:43:13 | INFO | Train Epoch: 0 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.211 Boundary Ratio: 0.251 Contrastive_loss: 3.1540 (3.9600) Boundary_loss: 0.015833 (0.017318) Loss: 3.1698 (3.9773) +2025-08-20,17:44:12 | INFO | Train Epoch: 0 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 49.719 Boundary Ratio: 0.254 Contrastive_loss: 2.9931 (3.9511) Boundary_loss: 0.016032 (0.017306) Loss: 3.0091 (3.9684) +2025-08-20,17:45:10 | INFO | Train Epoch: 0 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 3.0713 (3.9431) Boundary_loss: 0.015791 (0.017293) Loss: 3.0871 (3.9604) +2025-08-20,17:46:08 | INFO | Train Epoch: 0 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.025 Boundary Ratio: 0.245 Contrastive_loss: 2.9530 (3.9342) Boundary_loss: 0.016149 (0.017282) Loss: 2.9692 (3.9515) +2025-08-20,17:47:07 | INFO | Train Epoch: 0 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.561 Boundary Ratio: 0.253 Contrastive_loss: 2.9360 (3.9253) Boundary_loss: 0.015733 (0.017269) Loss: 2.9518 (3.9425) +2025-08-20,17:48:05 | INFO | Train Epoch: 0 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 2.8576 (3.9158) Boundary_loss: 0.016175 (0.017259) Loss: 2.8738 (3.9331) +2025-08-20,17:49:04 | INFO | Train Epoch: 0 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 49.430 Boundary Ratio: 0.252 Contrastive_loss: 2.9490 (3.9073) Boundary_loss: 0.015919 (0.017247) Loss: 2.9649 (3.9246) +2025-08-20,17:50:02 | INFO | Train Epoch: 0 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 3.0042 (3.8995) Boundary_loss: 0.016007 (0.017236) Loss: 3.0202 (3.9167) +2025-08-20,17:51:00 | INFO | Train Epoch: 0 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 2.8665 (3.8906) Boundary_loss: 0.016017 (0.017226) Loss: 2.8825 (3.9078) +2025-08-20,17:51:59 | INFO | Train Epoch: 0 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 49.555 Boundary Ratio: 0.253 Contrastive_loss: 2.9156 (3.8822) Boundary_loss: 0.016162 (0.017217) Loss: 2.9317 (3.8995) +2025-08-20,17:52:57 | INFO | Train Epoch: 0 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.115 Boundary Ratio: 0.245 Contrastive_loss: 2.9730 (3.8745) Boundary_loss: 0.015943 (0.017206) Loss: 2.9890 (3.8917) +2025-08-20,17:53:55 | INFO | Train Epoch: 0 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.258 Boundary Ratio: 0.251 Contrastive_loss: 2.9761 (3.8670) Boundary_loss: 0.016079 (0.017196) Loss: 2.9921 (3.8842) +2025-08-20,17:54:54 | INFO | Train Epoch: 0 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 2.8417 (3.8584) Boundary_loss: 0.015907 (0.017186) Loss: 2.8576 (3.8756) +2025-08-20,17:55:52 | INFO | Train Epoch: 0 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 2.9073 (3.8506) Boundary_loss: 0.015787 (0.017174) Loss: 2.9231 (3.8677) +2025-08-20,17:56:50 | INFO | Train Epoch: 0 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 2.9012 (3.8428) Boundary_loss: 0.015906 (0.017164) Loss: 2.9171 (3.8600) +2025-08-20,17:57:48 | INFO | Train Epoch: 0 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 2.8997 (3.8351) Boundary_loss: 0.015818 (0.017153) Loss: 2.9155 (3.8523) +2025-08-20,17:58:47 | INFO | Train Epoch: 0 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 47.982 Boundary Ratio: 0.245 Contrastive_loss: 2.8715 (3.8274) Boundary_loss: 0.016129 (0.017145) Loss: 2.8876 (3.8445) +2025-08-20,17:59:45 | INFO | Train Epoch: 0 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 47.703 Boundary Ratio: 0.243 Contrastive_loss: 2.8542 (3.8196) Boundary_loss: 0.016013 (0.017136) Loss: 2.8702 (3.8367) +2025-08-20,18:00:43 | INFO | Train Epoch: 0 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 49.859 Boundary Ratio: 0.254 Contrastive_loss: 2.8320 (3.8117) Boundary_loss: 0.016046 (0.017127) Loss: 2.8480 (3.8289) +2025-08-20,18:01:42 | INFO | Train Epoch: 0 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 47.365 Boundary Ratio: 0.242 Contrastive_loss: 2.8855 (3.8044) Boundary_loss: 0.016021 (0.017118) Loss: 2.9015 (3.8216) +2025-08-20,18:02:40 | INFO | Train Epoch: 0 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 47.730 Boundary Ratio: 0.244 Contrastive_loss: 2.8172 (3.7967) Boundary_loss: 0.015899 (0.017109) Loss: 2.8331 (3.8138) +2025-08-20,18:03:38 | INFO | Train Epoch: 0 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 2.9339 (3.7900) Boundary_loss: 0.016042 (0.017100) Loss: 2.9500 (3.8071) +2025-08-20,18:04:36 | INFO | Train Epoch: 0 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 2.8270 (3.7826) Boundary_loss: 0.015719 (0.017090) Loss: 2.8427 (3.7997) +2025-08-20,18:05:34 | INFO | Train Epoch: 0 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 2.8369 (3.7754) Boundary_loss: 0.015653 (0.017079) Loss: 2.8526 (3.7925) +2025-08-20,18:06:33 | INFO | Train Epoch: 0 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 2.7316 (3.7675) Boundary_loss: 0.015853 (0.017069) Loss: 2.7474 (3.7846) +2025-08-20,18:07:31 | INFO | Train Epoch: 0 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.719 Boundary Ratio: 0.254 Contrastive_loss: 2.8139 (3.7603) Boundary_loss: 0.016150 (0.017063) Loss: 2.8300 (3.7774) +2025-08-20,18:08:29 | INFO | Train Epoch: 0 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 50.010 Boundary Ratio: 0.255 Contrastive_loss: 2.7471 (3.7528) Boundary_loss: 0.016157 (0.017056) Loss: 2.7632 (3.7698) +2025-08-20,18:09:27 | INFO | Train Epoch: 0 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 47.109 Boundary Ratio: 0.240 Contrastive_loss: 2.7286 (3.7452) Boundary_loss: 0.015852 (0.017047) Loss: 2.7444 (3.7622) +2025-08-20,18:10:26 | INFO | Train Epoch: 0 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 49.580 Boundary Ratio: 0.253 Contrastive_loss: 2.7324 (3.7377) Boundary_loss: 0.015870 (0.017038) Loss: 2.7483 (3.7548) +2025-08-20,18:11:23 | INFO | Train Epoch: 0 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 2.7366 (3.7304) Boundary_loss: 0.015797 (0.017029) Loss: 2.7524 (3.7475) +2025-08-20,18:12:22 | INFO | Train Epoch: 0 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.725 Boundary Ratio: 0.254 Contrastive_loss: 2.7577 (3.7234) Boundary_loss: 0.015820 (0.017020) Loss: 2.7735 (3.7404) +2025-08-20,18:13:20 | INFO | Train Epoch: 0 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 2.6784 (3.7159) Boundary_loss: 0.015944 (0.017013) Loss: 2.6943 (3.7329) +2025-08-20,18:14:18 | INFO | Train Epoch: 0 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 2.7957 (3.7093) Boundary_loss: 0.015884 (0.017005) Loss: 2.8116 (3.7263) +2025-08-20,18:15:16 | INFO | Train Epoch: 0 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 47.342 Boundary Ratio: 0.242 Contrastive_loss: 2.7784 (3.7027) Boundary_loss: 0.016300 (0.017000) Loss: 2.7947 (3.7197) +2025-08-20,18:16:15 | INFO | Train Epoch: 0 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 2.7491 (3.6960) Boundary_loss: 0.015809 (0.016991) Loss: 2.7649 (3.7130) +2025-08-20,18:17:13 | INFO | Train Epoch: 0 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 2.7617 (3.6894) Boundary_loss: 0.015853 (0.016983) Loss: 2.7776 (3.7064) +2025-08-20,18:18:11 | INFO | Train Epoch: 0 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.025 Boundary Ratio: 0.245 Contrastive_loss: 2.6541 (3.6822) Boundary_loss: 0.016128 (0.016977) Loss: 2.6703 (3.6992) +2025-08-20,18:19:09 | INFO | Train Epoch: 0 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 2.7898 (3.6761) Boundary_loss: 0.016056 (0.016971) Loss: 2.8058 (3.6931) +2025-08-20,18:20:07 | INFO | Train Epoch: 0 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.713 Boundary Ratio: 0.254 Contrastive_loss: 2.7002 (3.6694) Boundary_loss: 0.015870 (0.016963) Loss: 2.7161 (3.6864) +2025-08-20,18:21:05 | INFO | Train Epoch: 0 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 2.6042 (3.6622) Boundary_loss: 0.015600 (0.016954) Loss: 2.6198 (3.6791) +2025-08-20,18:22:03 | INFO | Train Epoch: 0 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 2.7777 (3.6562) Boundary_loss: 0.015677 (0.016946) Loss: 2.7934 (3.6731) +2025-08-20,18:23:01 | INFO | Train Epoch: 0 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 2.7529 (3.6501) Boundary_loss: 0.015964 (0.016939) Loss: 2.7689 (3.6671) +2025-08-20,18:23:59 | INFO | Train Epoch: 0 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 2.7041 (3.6438) Boundary_loss: 0.015876 (0.016932) Loss: 2.7200 (3.6608) +2025-08-20,18:24:58 | INFO | Train Epoch: 0 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 50.098 Boundary Ratio: 0.256 Contrastive_loss: 2.6042 (3.6369) Boundary_loss: 0.015841 (0.016925) Loss: 2.6200 (3.6539) +2025-08-20,18:25:56 | INFO | Train Epoch: 0 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 47.949 Boundary Ratio: 0.245 Contrastive_loss: 2.6179 (3.6302) Boundary_loss: 0.015822 (0.016917) Loss: 2.6337 (3.6471) +2025-08-20,18:26:54 | INFO | Train Epoch: 0 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 49.861 Boundary Ratio: 0.254 Contrastive_loss: 2.7914 (3.6247) Boundary_loss: 0.016081 (0.016912) Loss: 2.8075 (3.6417) +2025-08-20,18:27:52 | INFO | Train Epoch: 0 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 2.7876 (3.6193) Boundary_loss: 0.016021 (0.016906) Loss: 2.8036 (3.6362) +2025-08-20,18:28:50 | INFO | Train Epoch: 0 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.059 Boundary Ratio: 0.245 Contrastive_loss: 2.7420 (3.6137) Boundary_loss: 0.016035 (0.016901) Loss: 2.7581 (3.6306) +2025-08-20,18:29:49 | INFO | Train Epoch: 0 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 49.764 Boundary Ratio: 0.254 Contrastive_loss: 2.5425 (3.6068) Boundary_loss: 0.015921 (0.016894) Loss: 2.5584 (3.6237) +2025-08-20,18:30:47 | INFO | Train Epoch: 0 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.482 Boundary Ratio: 0.247 Contrastive_loss: 2.7636 (3.6014) Boundary_loss: 0.015619 (0.016886) Loss: 2.7792 (3.6183) +2025-08-20,18:31:45 | INFO | Train Epoch: 0 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 2.4544 (3.5942) Boundary_loss: 0.015744 (0.016879) Loss: 2.4701 (3.6110) +2025-08-20,18:32:43 | INFO | Train Epoch: 0 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 47.074 Boundary Ratio: 0.240 Contrastive_loss: 2.6176 (3.5880) Boundary_loss: 0.015962 (0.016873) Loss: 2.6336 (3.6049) +2025-08-20,18:33:41 | INFO | Train Epoch: 0 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 49.305 Boundary Ratio: 0.252 Contrastive_loss: 2.5095 (3.5813) Boundary_loss: 0.015816 (0.016867) Loss: 2.5253 (3.5981) +2025-08-20,18:34:40 | INFO | Train Epoch: 0 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 2.5326 (3.5748) Boundary_loss: 0.015732 (0.016859) Loss: 2.5483 (3.5916) +2025-08-20,18:35:38 | INFO | Train Epoch: 0 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 2.5473 (3.5684) Boundary_loss: 0.015798 (0.016853) Loss: 2.5631 (3.5853) +2025-08-20,18:36:36 | INFO | Train Epoch: 0 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.014 Boundary Ratio: 0.245 Contrastive_loss: 2.6090 (3.5625) Boundary_loss: 0.015878 (0.016847) Loss: 2.6249 (3.5794) +2025-08-20,18:37:34 | INFO | Train Epoch: 0 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 2.5860 (3.5566) Boundary_loss: 0.015952 (0.016841) Loss: 2.6020 (3.5734) +2025-08-20,18:38:32 | INFO | Train Epoch: 0 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.049 Boundary Ratio: 0.245 Contrastive_loss: 2.4774 (3.5500) Boundary_loss: 0.015924 (0.016836) Loss: 2.4933 (3.5669) +2025-08-20,18:39:31 | INFO | Train Epoch: 0 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 2.5787 (3.5442) Boundary_loss: 0.015749 (0.016829) Loss: 2.5945 (3.5610) +2025-08-20,18:40:29 | INFO | Train Epoch: 0 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 49.352 Boundary Ratio: 0.252 Contrastive_loss: 2.5817 (3.5384) Boundary_loss: 0.015788 (0.016823) Loss: 2.5975 (3.5552) +2025-08-20,18:41:27 | INFO | Train Epoch: 0 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 2.6268 (3.5330) Boundary_loss: 0.016007 (0.016818) Loss: 2.6428 (3.5498) +2025-08-20,18:42:25 | INFO | Train Epoch: 0 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 50.658 Boundary Ratio: 0.258 Contrastive_loss: 2.6092 (3.5275) Boundary_loss: 0.016281 (0.016815) Loss: 2.6255 (3.5443) +2025-08-20,18:43:24 | INFO | Train Epoch: 0 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 47.969 Boundary Ratio: 0.245 Contrastive_loss: 2.5488 (3.5218) Boundary_loss: 0.015819 (0.016809) Loss: 2.5646 (3.5386) +2025-08-20,18:44:22 | INFO | Train Epoch: 0 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 2.5474 (3.5161) Boundary_loss: 0.015951 (0.016804) Loss: 2.5634 (3.5329) +2025-08-20,18:45:20 | INFO | Train Epoch: 0 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 50.941 Boundary Ratio: 0.260 Contrastive_loss: 2.5808 (3.5106) Boundary_loss: 0.016246 (0.016801) Loss: 2.5971 (3.5274) +2025-08-20,18:46:18 | INFO | Train Epoch: 0 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 2.6268 (3.5055) Boundary_loss: 0.015870 (0.016796) Loss: 2.6427 (3.5223) +2025-08-20,18:47:16 | INFO | Train Epoch: 0 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 2.6574 (3.5007) Boundary_loss: 0.015877 (0.016790) Loss: 2.6733 (3.5174) +2025-08-20,18:48:15 | INFO | Train Epoch: 0 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.439 Boundary Ratio: 0.252 Contrastive_loss: 2.5682 (3.4953) Boundary_loss: 0.015991 (0.016786) Loss: 2.5842 (3.5121) +2025-08-20,18:49:13 | INFO | Train Epoch: 0 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 2.4859 (3.4896) Boundary_loss: 0.016186 (0.016782) Loss: 2.5021 (3.5064) +2025-08-20,18:50:11 | INFO | Train Epoch: 0 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 49.506 Boundary Ratio: 0.253 Contrastive_loss: 2.6376 (3.4848) Boundary_loss: 0.015949 (0.016778) Loss: 2.6536 (3.5016) +2025-08-20,18:51:09 | INFO | Train Epoch: 0 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 2.3930 (3.4786) Boundary_loss: 0.015868 (0.016773) Loss: 2.4088 (3.4954) +2025-08-20,18:52:07 | INFO | Train Epoch: 0 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 2.4357 (3.4728) Boundary_loss: 0.015535 (0.016766) Loss: 2.4513 (3.4896) +2025-08-20,18:53:06 | INFO | Train Epoch: 0 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 50.658 Boundary Ratio: 0.258 Contrastive_loss: 2.5040 (3.4674) Boundary_loss: 0.016084 (0.016762) Loss: 2.5201 (3.4842) +2025-08-20,18:54:04 | INFO | Train Epoch: 0 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 2.5211 (3.4622) Boundary_loss: 0.015693 (0.016756) Loss: 2.5368 (3.4790) +2025-08-20,18:55:02 | INFO | Train Epoch: 0 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.406 Boundary Ratio: 0.247 Contrastive_loss: 2.4389 (3.4566) Boundary_loss: 0.015886 (0.016751) Loss: 2.4548 (3.4733) +2025-08-20,18:56:00 | INFO | Train Epoch: 0 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 2.3496 (3.4505) Boundary_loss: 0.015796 (0.016746) Loss: 2.3654 (3.4673) +2025-08-20,18:56:58 | INFO | Train Epoch: 0 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 2.4677 (3.4452) Boundary_loss: 0.015706 (0.016740) Loss: 2.4834 (3.4619) +2025-08-20,18:57:56 | INFO | Train Epoch: 0 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 2.5380 (3.4403) Boundary_loss: 0.015975 (0.016736) Loss: 2.5540 (3.4570) +2025-08-20,18:58:54 | INFO | Train Epoch: 0 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 50.102 Boundary Ratio: 0.256 Contrastive_loss: 2.5094 (3.4353) Boundary_loss: 0.015952 (0.016732) Loss: 2.5253 (3.4520) +2025-08-20,18:59:52 | INFO | Train Epoch: 0 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.223 Boundary Ratio: 0.246 Contrastive_loss: 2.2726 (3.4291) Boundary_loss: 0.015900 (0.016727) Loss: 2.2885 (3.4458) +2025-08-20,19:00:50 | INFO | Train Epoch: 0 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.191 Boundary Ratio: 0.246 Contrastive_loss: 2.5943 (3.4246) Boundary_loss: 0.015826 (0.016723) Loss: 2.6101 (3.4413) +2025-08-20,19:01:48 | INFO | Train Epoch: 0 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.129 Boundary Ratio: 0.246 Contrastive_loss: 2.4667 (3.4196) Boundary_loss: 0.015727 (0.016717) Loss: 2.4824 (3.4363) +2025-08-20,19:02:47 | INFO | Train Epoch: 0 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.346 Boundary Ratio: 0.247 Contrastive_loss: 2.4038 (3.4142) Boundary_loss: 0.015854 (0.016713) Loss: 2.4196 (3.4309) +2025-08-20,19:03:45 | INFO | Train Epoch: 0 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 2.2355 (3.4080) Boundary_loss: 0.015823 (0.016708) Loss: 2.2513 (3.4247) +2025-08-20,19:04:43 | INFO | Train Epoch: 0 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 47.516 Boundary Ratio: 0.242 Contrastive_loss: 2.5308 (3.4035) Boundary_loss: 0.015992 (0.016704) Loss: 2.5467 (3.4202) +2025-08-20,19:05:41 | INFO | Train Epoch: 0 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 2.5126 (3.3989) Boundary_loss: 0.015907 (0.016700) Loss: 2.5285 (3.4156) +2025-08-20,19:06:39 | INFO | Train Epoch: 0 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 2.2050 (3.3927) Boundary_loss: 0.015688 (0.016695) Loss: 2.2207 (3.4094) +2025-08-20,19:07:37 | INFO | Train Epoch: 0 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.395 Boundary Ratio: 0.252 Contrastive_loss: 2.3816 (3.3875) Boundary_loss: 0.015743 (0.016690) Loss: 2.3973 (3.4042) +2025-08-20,19:08:35 | INFO | Train Epoch: 0 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 2.4033 (3.3825) Boundary_loss: 0.015635 (0.016685) Loss: 2.4190 (3.3992) +2025-08-20,19:09:33 | INFO | Train Epoch: 0 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.072 Boundary Ratio: 0.245 Contrastive_loss: 2.3348 (3.3772) Boundary_loss: 0.015749 (0.016680) Loss: 2.3505 (3.3939) +2025-08-20,19:10:31 | INFO | Train Epoch: 0 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 2.3082 (3.3718) Boundary_loss: 0.015863 (0.016676) Loss: 2.3240 (3.3885) +2025-08-20,19:11:29 | INFO | Train Epoch: 0 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 2.3387 (3.3666) Boundary_loss: 0.015764 (0.016671) Loss: 2.3544 (3.3833) +2025-08-20,19:12:27 | INFO | Train Epoch: 0 [10189312/26365952 (39%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 2.4197 (3.3619) Boundary_loss: 0.015860 (0.016667) Loss: 2.4356 (3.3785) +2025-08-20,19:13:26 | INFO | Train Epoch: 0 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 2.2590 (3.3564) Boundary_loss: 0.015909 (0.016664) Loss: 2.2749 (3.3730) +2025-08-20,19:14:23 | INFO | Train Epoch: 0 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 2.4301 (3.3518) Boundary_loss: 0.015667 (0.016659) Loss: 2.4458 (3.3684) +2025-08-20,19:15:22 | INFO | Train Epoch: 0 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 2.4316 (3.3472) Boundary_loss: 0.015640 (0.016654) Loss: 2.4472 (3.3639) +2025-08-20,19:16:20 | INFO | Train Epoch: 0 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 2.3969 (3.3426) Boundary_loss: 0.015773 (0.016649) Loss: 2.4127 (3.3592) +2025-08-20,19:17:18 | INFO | Train Epoch: 0 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 2.4631 (3.3383) Boundary_loss: 0.015784 (0.016645) Loss: 2.4789 (3.3549) +2025-08-20,19:18:16 | INFO | Train Epoch: 0 [10496512/26365952 (40%)] Avg Boundaries (per batch): 49.707 Boundary Ratio: 0.254 Contrastive_loss: 2.3403 (3.3335) Boundary_loss: 0.015738 (0.016641) Loss: 2.3560 (3.3501) +2025-08-20,19:19:14 | INFO | Train Epoch: 0 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 2.4763 (3.3293) Boundary_loss: 0.016048 (0.016638) Loss: 2.4923 (3.3459) +2025-08-20,19:20:11 | INFO | Train Epoch: 0 [10598912/26365952 (40%)] Avg Boundaries (per batch): 49.789 Boundary Ratio: 0.254 Contrastive_loss: 2.4426 (3.3250) Boundary_loss: 0.016005 (0.016635) Loss: 2.4586 (3.3417) +2025-08-20,19:21:10 | INFO | Train Epoch: 0 [10650112/26365952 (40%)] Avg Boundaries (per batch): 50.197 Boundary Ratio: 0.256 Contrastive_loss: 2.4305 (3.3208) Boundary_loss: 0.015912 (0.016631) Loss: 2.4464 (3.3374) +2025-08-20,19:22:08 | INFO | Train Epoch: 0 [10701312/26365952 (41%)] Avg Boundaries (per batch): 47.385 Boundary Ratio: 0.242 Contrastive_loss: 2.1868 (3.3154) Boundary_loss: 0.015798 (0.016627) Loss: 2.2026 (3.3320) +2025-08-20,19:23:06 | INFO | Train Epoch: 0 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 2.3868 (3.3110) Boundary_loss: 0.015677 (0.016623) Loss: 2.4025 (3.3276) +2025-08-20,19:24:03 | INFO | Train Epoch: 0 [10803712/26365952 (41%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 2.2413 (3.3059) Boundary_loss: 0.015661 (0.016618) Loss: 2.2570 (3.3225) +2025-08-20,19:25:01 | INFO | Train Epoch: 0 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 2.3845 (3.3016) Boundary_loss: 0.015818 (0.016615) Loss: 2.4004 (3.3182) +2025-08-20,19:25:59 | INFO | Train Epoch: 0 [10906112/26365952 (41%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 2.1926 (3.2964) Boundary_loss: 0.015872 (0.016611) Loss: 2.2085 (3.3130) +2025-08-20,19:26:57 | INFO | Train Epoch: 0 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 2.4353 (3.2924) Boundary_loss: 0.015725 (0.016607) Loss: 2.4510 (3.3090) +2025-08-20,19:27:55 | INFO | Train Epoch: 0 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 2.1719 (3.2872) Boundary_loss: 0.015822 (0.016603) Loss: 2.1878 (3.3038) +2025-08-20,19:28:54 | INFO | Train Epoch: 0 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 2.1512 (3.2820) Boundary_loss: 0.015796 (0.016600) Loss: 2.1670 (3.2986) +2025-08-20,19:29:52 | INFO | Train Epoch: 0 [11110912/26365952 (42%)] Avg Boundaries (per batch): 49.791 Boundary Ratio: 0.254 Contrastive_loss: 2.3718 (3.2778) Boundary_loss: 0.015597 (0.016595) Loss: 2.3874 (3.2944) +2025-08-20,19:30:50 | INFO | Train Epoch: 0 [11162112/26365952 (42%)] Avg Boundaries (per batch): 49.211 Boundary Ratio: 0.251 Contrastive_loss: 2.3962 (3.2738) Boundary_loss: 0.015736 (0.016591) Loss: 2.4120 (3.2904) +2025-08-20,19:31:48 | INFO | Train Epoch: 0 [11213312/26365952 (43%)] Avg Boundaries (per batch): 49.451 Boundary Ratio: 0.252 Contrastive_loss: 2.2594 (3.2692) Boundary_loss: 0.015646 (0.016587) Loss: 2.2751 (3.2858) +2025-08-20,19:32:46 | INFO | Train Epoch: 0 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.123 Boundary Ratio: 0.246 Contrastive_loss: 2.5024 (3.2657) Boundary_loss: 0.015732 (0.016583) Loss: 2.5182 (3.2823) +2025-08-20,19:33:44 | INFO | Train Epoch: 0 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.219 Boundary Ratio: 0.246 Contrastive_loss: 2.2473 (3.2611) Boundary_loss: 0.015558 (0.016578) Loss: 2.2628 (3.2777) +2025-08-20,19:34:42 | INFO | Train Epoch: 0 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 2.1834 (3.2563) Boundary_loss: 0.015852 (0.016575) Loss: 2.1992 (3.2729) +2025-08-20,19:35:40 | INFO | Train Epoch: 0 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 2.3747 (3.2523) Boundary_loss: 0.015611 (0.016571) Loss: 2.3903 (3.2689) +2025-08-20,19:36:38 | INFO | Train Epoch: 0 [11469312/26365952 (44%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 2.1588 (3.2475) Boundary_loss: 0.015657 (0.016567) Loss: 2.1745 (3.2641) +2025-08-20,19:37:36 | INFO | Train Epoch: 0 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 2.3606 (3.2436) Boundary_loss: 0.015820 (0.016563) Loss: 2.3764 (3.2601) +2025-08-20,19:38:34 | INFO | Train Epoch: 0 [11571712/26365952 (44%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 2.2255 (3.2391) Boundary_loss: 0.015993 (0.016561) Loss: 2.2415 (3.2556) +2025-08-20,19:39:31 | INFO | Train Epoch: 0 [11622912/26365952 (44%)] Avg Boundaries (per batch): 47.477 Boundary Ratio: 0.242 Contrastive_loss: 2.4160 (3.2355) Boundary_loss: 0.015746 (0.016557) Loss: 2.4318 (3.2520) +2025-08-20,19:40:29 | INFO | Train Epoch: 0 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.451 Boundary Ratio: 0.252 Contrastive_loss: 2.3703 (3.2317) Boundary_loss: 0.015687 (0.016553) Loss: 2.3860 (3.2482) +2025-08-20,19:41:27 | INFO | Train Epoch: 0 [11725312/26365952 (44%)] Avg Boundaries (per batch): 49.801 Boundary Ratio: 0.254 Contrastive_loss: 2.0971 (3.2268) Boundary_loss: 0.015815 (0.016550) Loss: 2.1129 (3.2433) +2025-08-20,19:42:25 | INFO | Train Epoch: 0 [11776512/26365952 (45%)] Avg Boundaries (per batch): 49.691 Boundary Ratio: 0.254 Contrastive_loss: 2.2775 (3.2226) Boundary_loss: 0.015752 (0.016547) Loss: 2.2933 (3.2392) +2025-08-20,19:43:23 | INFO | Train Epoch: 0 [11827712/26365952 (45%)] Avg Boundaries (per batch): 50.004 Boundary Ratio: 0.255 Contrastive_loss: 2.2070 (3.2183) Boundary_loss: 0.016124 (0.016545) Loss: 2.2231 (3.2348) +2025-08-20,19:44:21 | INFO | Train Epoch: 0 [11878912/26365952 (45%)] Avg Boundaries (per batch): 49.479 Boundary Ratio: 0.252 Contrastive_loss: 2.0716 (3.2134) Boundary_loss: 0.015781 (0.016542) Loss: 2.0874 (3.2299) +2025-08-20,19:45:19 | INFO | Train Epoch: 0 [11930112/26365952 (45%)] Avg Boundaries (per batch): 49.480 Boundary Ratio: 0.252 Contrastive_loss: 2.1752 (3.2089) Boundary_loss: 0.015827 (0.016539) Loss: 2.1911 (3.2255) +2025-08-20,19:46:17 | INFO | Train Epoch: 0 [11981312/26365952 (45%)] Avg Boundaries (per batch): 47.648 Boundary Ratio: 0.243 Contrastive_loss: 2.2576 (3.2049) Boundary_loss: 0.015809 (0.016536) Loss: 2.2734 (3.2214) +2025-08-20,19:47:15 | INFO | Train Epoch: 0 [12032512/26365952 (46%)] Avg Boundaries (per batch): 49.633 Boundary Ratio: 0.253 Contrastive_loss: 2.2181 (3.2007) Boundary_loss: 0.015746 (0.016532) Loss: 2.2339 (3.2172) +2025-08-20,19:48:13 | INFO | Train Epoch: 0 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 2.1116 (3.1961) Boundary_loss: 0.015655 (0.016528) Loss: 2.1273 (3.2126) +2025-08-20,19:49:10 | INFO | Train Epoch: 0 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.020 Boundary Ratio: 0.245 Contrastive_loss: 2.3478 (3.1925) Boundary_loss: 0.015710 (0.016525) Loss: 2.3635 (3.2091) +2025-08-20,19:50:08 | INFO | Train Epoch: 0 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.225 Boundary Ratio: 0.246 Contrastive_loss: 2.3780 (3.1891) Boundary_loss: 0.015706 (0.016522) Loss: 2.3937 (3.2056) +2025-08-20,19:51:06 | INFO | Train Epoch: 0 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 2.0865 (3.1845) Boundary_loss: 0.015672 (0.016518) Loss: 2.1021 (3.2010) +2025-08-20,19:52:04 | INFO | Train Epoch: 0 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.152 Boundary Ratio: 0.246 Contrastive_loss: 2.1857 (3.1804) Boundary_loss: 0.015898 (0.016516) Loss: 2.2016 (3.1969) +2025-08-20,19:53:02 | INFO | Train Epoch: 0 [12339712/26365952 (47%)] Avg Boundaries (per batch): 50.188 Boundary Ratio: 0.256 Contrastive_loss: 2.1379 (3.1761) Boundary_loss: 0.016021 (0.016513) Loss: 2.1539 (3.1926) +2025-08-20,19:54:00 | INFO | Train Epoch: 0 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.043 Boundary Ratio: 0.245 Contrastive_loss: 2.0646 (3.1715) Boundary_loss: 0.015897 (0.016511) Loss: 2.0805 (3.1880) +2025-08-20,19:54:58 | INFO | Train Epoch: 0 [12442112/26365952 (47%)] Avg Boundaries (per batch): 49.869 Boundary Ratio: 0.254 Contrastive_loss: 2.1719 (3.1674) Boundary_loss: 0.015738 (0.016508) Loss: 2.1876 (3.1839) +2025-08-20,19:55:55 | INFO | Train Epoch: 0 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 2.2131 (3.1635) Boundary_loss: 0.015747 (0.016505) Loss: 2.2289 (3.1800) +2025-08-20,19:56:53 | INFO | Train Epoch: 0 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 2.1901 (3.1595) Boundary_loss: 0.015818 (0.016502) Loss: 2.2059 (3.1760) +2025-08-20,19:57:51 | INFO | Train Epoch: 0 [12595712/26365952 (48%)] Avg Boundaries (per batch): 49.934 Boundary Ratio: 0.255 Contrastive_loss: 2.2297 (3.1558) Boundary_loss: 0.015762 (0.016499) Loss: 2.2454 (3.1723) +2025-08-20,19:58:49 | INFO | Train Epoch: 0 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.111 Boundary Ratio: 0.245 Contrastive_loss: 2.0024 (3.1511) Boundary_loss: 0.015799 (0.016496) Loss: 2.0182 (3.1676) +2025-08-20,19:59:46 | INFO | Train Epoch: 0 [12698112/26365952 (48%)] Avg Boundaries (per batch): 49.852 Boundary Ratio: 0.254 Contrastive_loss: 2.2566 (3.1475) Boundary_loss: 0.016240 (0.016495) Loss: 2.2728 (3.1640) +2025-08-20,20:00:44 | INFO | Train Epoch: 0 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 2.0990 (3.1433) Boundary_loss: 0.015754 (0.016492) Loss: 2.1148 (3.1598) +2025-08-20,20:01:42 | INFO | Train Epoch: 0 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 2.0908 (3.1392) Boundary_loss: 0.015698 (0.016489) Loss: 2.1065 (3.1556) +2025-08-20,20:02:39 | INFO | Train Epoch: 0 [12851712/26365952 (49%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 2.1467 (3.1352) Boundary_loss: 0.015750 (0.016486) Loss: 2.1624 (3.1517) +2025-08-20,20:03:37 | INFO | Train Epoch: 0 [12902912/26365952 (49%)] Avg Boundaries (per batch): 49.311 Boundary Ratio: 0.252 Contrastive_loss: 2.3292 (3.1320) Boundary_loss: 0.015580 (0.016482) Loss: 2.3448 (3.1485) +2025-08-20,20:04:35 | INFO | Train Epoch: 0 [12954112/26365952 (49%)] Avg Boundaries (per batch): 47.867 Boundary Ratio: 0.244 Contrastive_loss: 2.1642 (3.1282) Boundary_loss: 0.015746 (0.016479) Loss: 2.1800 (3.1447) +2025-08-20,20:05:33 | INFO | Train Epoch: 0 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 2.0959 (3.1242) Boundary_loss: 0.015590 (0.016476) Loss: 2.1115 (3.1406) +2025-08-20,20:06:30 | INFO | Train Epoch: 0 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 2.1664 (3.1204) Boundary_loss: 0.015613 (0.016473) Loss: 2.1820 (3.1369) +2025-08-20,20:07:28 | INFO | Train Epoch: 0 [13107712/26365952 (50%)] Avg Boundaries (per batch): 47.818 Boundary Ratio: 0.244 Contrastive_loss: 2.2276 (3.1170) Boundary_loss: 0.015935 (0.016471) Loss: 2.2435 (3.1334) +2025-08-20,20:08:26 | INFO | Train Epoch: 0 [13158912/26365952 (50%)] Avg Boundaries (per batch): 49.307 Boundary Ratio: 0.252 Contrastive_loss: 2.0749 (3.1129) Boundary_loss: 0.015937 (0.016468) Loss: 2.0908 (3.1294) +2025-08-20,20:09:24 | INFO | Train Epoch: 0 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.570 Boundary Ratio: 0.253 Contrastive_loss: 2.2993 (3.1098) Boundary_loss: 0.015953 (0.016466) Loss: 2.3152 (3.1262) +2025-08-20,20:10:22 | INFO | Train Epoch: 0 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 2.0544 (3.1057) Boundary_loss: 0.015576 (0.016463) Loss: 2.0699 (3.1222) +2025-08-20,20:11:20 | INFO | Train Epoch: 0 [13312512/26365952 (50%)] Avg Boundaries (per batch): 47.924 Boundary Ratio: 0.245 Contrastive_loss: 2.0332 (3.1016) Boundary_loss: 0.015706 (0.016460) Loss: 2.0489 (3.1181) +2025-08-20,20:12:18 | INFO | Train Epoch: 0 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 2.2580 (3.0984) Boundary_loss: 0.015785 (0.016458) Loss: 2.2738 (3.1148) +2025-08-20,20:13:15 | INFO | Train Epoch: 0 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.947 Boundary Ratio: 0.255 Contrastive_loss: 2.1819 (3.0949) Boundary_loss: 0.015539 (0.016454) Loss: 2.1974 (3.1114) +2025-08-20,20:14:13 | INFO | Train Epoch: 0 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 2.1957 (3.0915) Boundary_loss: 0.015641 (0.016451) Loss: 2.2113 (3.1079) +2025-08-20,20:15:11 | INFO | Train Epoch: 0 [13517312/26365952 (51%)] Avg Boundaries (per batch): 47.756 Boundary Ratio: 0.244 Contrastive_loss: 2.0912 (3.0877) Boundary_loss: 0.015846 (0.016449) Loss: 2.1070 (3.1042) +2025-08-20,20:16:08 | INFO | Train Epoch: 0 [13568512/26365952 (51%)] Avg Boundaries (per batch): 47.471 Boundary Ratio: 0.242 Contrastive_loss: 1.9545 (3.0835) Boundary_loss: 0.015716 (0.016446) Loss: 1.9702 (3.0999) +2025-08-20,20:17:06 | INFO | Train Epoch: 0 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 2.2684 (3.0804) Boundary_loss: 0.015590 (0.016443) Loss: 2.2840 (3.0968) +2025-08-20,20:18:04 | INFO | Train Epoch: 0 [13670912/26365952 (52%)] Avg Boundaries (per batch): 49.779 Boundary Ratio: 0.254 Contrastive_loss: 2.0390 (3.0765) Boundary_loss: 0.015760 (0.016440) Loss: 2.0548 (3.0930) +2025-08-20,20:19:02 | INFO | Train Epoch: 0 [13722112/26365952 (52%)] Avg Boundaries (per batch): 49.406 Boundary Ratio: 0.252 Contrastive_loss: 2.1761 (3.0732) Boundary_loss: 0.015854 (0.016438) Loss: 2.1919 (3.0896) +2025-08-20,20:20:00 | INFO | Train Epoch: 0 [13773312/26365952 (52%)] Avg Boundaries (per batch): 47.758 Boundary Ratio: 0.244 Contrastive_loss: 1.9653 (3.0691) Boundary_loss: 0.015981 (0.016436) Loss: 1.9813 (3.0855) +2025-08-20,20:20:57 | INFO | Train Epoch: 0 [13824512/26365952 (52%)] Avg Boundaries (per batch): 47.822 Boundary Ratio: 0.244 Contrastive_loss: 2.0593 (3.0653) Boundary_loss: 0.015782 (0.016434) Loss: 2.0750 (3.0818) +2025-08-20,20:21:55 | INFO | Train Epoch: 0 [13875712/26365952 (53%)] Avg Boundaries (per batch): 50.277 Boundary Ratio: 0.257 Contrastive_loss: 2.0647 (3.0617) Boundary_loss: 0.015789 (0.016432) Loss: 2.0805 (3.0781) +2025-08-20,20:22:53 | INFO | Train Epoch: 0 [13926912/26365952 (53%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 2.2181 (3.0586) Boundary_loss: 0.015844 (0.016429) Loss: 2.2339 (3.0750) +2025-08-20,20:23:51 | INFO | Train Epoch: 0 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 2.0438 (3.0549) Boundary_loss: 0.015815 (0.016427) Loss: 2.0596 (3.0713) +2025-08-20,20:24:49 | INFO | Train Epoch: 0 [14029312/26365952 (53%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 2.2082 (3.0518) Boundary_loss: 0.015627 (0.016424) Loss: 2.2238 (3.0682) +2025-08-20,20:25:46 | INFO | Train Epoch: 0 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 2.1433 (3.0485) Boundary_loss: 0.015703 (0.016422) Loss: 2.1590 (3.0649) +2025-08-20,20:26:44 | INFO | Train Epoch: 0 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 2.0838 (3.0450) Boundary_loss: 0.015674 (0.016419) Loss: 2.0995 (3.0614) +2025-08-20,20:27:42 | INFO | Train Epoch: 0 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 2.0796 (3.0415) Boundary_loss: 0.015588 (0.016416) Loss: 2.0952 (3.0580) +2025-08-20,20:28:40 | INFO | Train Epoch: 0 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 2.0506 (3.0380) Boundary_loss: 0.015970 (0.016414) Loss: 2.0666 (3.0544) +2025-08-20,20:29:37 | INFO | Train Epoch: 0 [14285312/26365952 (54%)] Avg Boundaries (per batch): 49.871 Boundary Ratio: 0.254 Contrastive_loss: 2.0708 (3.0345) Boundary_loss: 0.015732 (0.016412) Loss: 2.0866 (3.0510) +2025-08-20,20:30:35 | INFO | Train Epoch: 0 [14336512/26365952 (54%)] Avg Boundaries (per batch): 47.924 Boundary Ratio: 0.245 Contrastive_loss: 2.1179 (3.0313) Boundary_loss: 0.015636 (0.016409) Loss: 2.1335 (3.0477) +2025-08-20,20:31:33 | INFO | Train Epoch: 0 [14387712/26365952 (55%)] Avg Boundaries (per batch): 49.838 Boundary Ratio: 0.254 Contrastive_loss: 2.0951 (3.0280) Boundary_loss: 0.015633 (0.016406) Loss: 2.1107 (3.0444) +2025-08-20,20:32:31 | INFO | Train Epoch: 0 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.096 Boundary Ratio: 0.245 Contrastive_loss: 2.1008 (3.0247) Boundary_loss: 0.015532 (0.016403) Loss: 2.1163 (3.0411) +2025-08-20,20:33:29 | INFO | Train Epoch: 0 [14490112/26365952 (55%)] Avg Boundaries (per batch): 49.805 Boundary Ratio: 0.254 Contrastive_loss: 2.0017 (3.0211) Boundary_loss: 0.015779 (0.016401) Loss: 2.0175 (3.0375) +2025-08-20,20:34:27 | INFO | Train Epoch: 0 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 1.9593 (3.0174) Boundary_loss: 0.015795 (0.016399) Loss: 1.9751 (3.0338) +2025-08-20,20:35:24 | INFO | Train Epoch: 0 [14592512/26365952 (55%)] Avg Boundaries (per batch): 47.639 Boundary Ratio: 0.243 Contrastive_loss: 1.9691 (3.0137) Boundary_loss: 0.015852 (0.016397) Loss: 1.9850 (3.0301) +2025-08-20,20:36:22 | INFO | Train Epoch: 0 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.170 Boundary Ratio: 0.246 Contrastive_loss: 1.9983 (3.0102) Boundary_loss: 0.015647 (0.016394) Loss: 2.0139 (3.0265) +2025-08-20,20:37:20 | INFO | Train Epoch: 0 [14694912/26365952 (56%)] Avg Boundaries (per batch): 50.035 Boundary Ratio: 0.255 Contrastive_loss: 2.0352 (3.0068) Boundary_loss: 0.015749 (0.016392) Loss: 2.0509 (3.0232) +2025-08-20,20:38:17 | INFO | Train Epoch: 0 [14746112/26365952 (56%)] Avg Boundaries (per batch): 50.559 Boundary Ratio: 0.258 Contrastive_loss: 1.9976 (3.0033) Boundary_loss: 0.015783 (0.016390) Loss: 2.0133 (3.0197) +2025-08-20,20:39:15 | INFO | Train Epoch: 0 [14797312/26365952 (56%)] Avg Boundaries (per batch): 49.783 Boundary Ratio: 0.254 Contrastive_loss: 2.0001 (2.9998) Boundary_loss: 0.015793 (0.016388) Loss: 2.0159 (3.0162) +2025-08-20,20:40:13 | INFO | Train Epoch: 0 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.242 Boundary Ratio: 0.246 Contrastive_loss: 2.1763 (2.9970) Boundary_loss: 0.015783 (0.016386) Loss: 2.1921 (3.0134) +2025-08-20,20:41:11 | INFO | Train Epoch: 0 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 2.0317 (2.9937) Boundary_loss: 0.015689 (0.016384) Loss: 2.0474 (3.0101) +2025-08-20,20:42:08 | INFO | Train Epoch: 0 [14950912/26365952 (57%)] Avg Boundaries (per batch): 49.359 Boundary Ratio: 0.252 Contrastive_loss: 2.3081 (2.9913) Boundary_loss: 0.015485 (0.016381) Loss: 2.3236 (3.0077) +2025-08-20,20:43:06 | INFO | Train Epoch: 0 [15002112/26365952 (57%)] Avg Boundaries (per batch): 49.373 Boundary Ratio: 0.252 Contrastive_loss: 1.9370 (2.9878) Boundary_loss: 0.015585 (0.016378) Loss: 1.9526 (3.0041) +2025-08-20,20:44:04 | INFO | Train Epoch: 0 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 2.1073 (2.9848) Boundary_loss: 0.015613 (0.016375) Loss: 2.1229 (3.0011) +2025-08-20,20:45:01 | INFO | Train Epoch: 0 [15104512/26365952 (57%)] Avg Boundaries (per batch): 50.504 Boundary Ratio: 0.258 Contrastive_loss: 1.9612 (2.9813) Boundary_loss: 0.016075 (0.016374) Loss: 1.9773 (2.9977) +2025-08-20,20:45:59 | INFO | Train Epoch: 0 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.943 Boundary Ratio: 0.255 Contrastive_loss: 1.9784 (2.9779) Boundary_loss: 0.015464 (0.016371) Loss: 1.9939 (2.9943) +2025-08-20,20:46:57 | INFO | Train Epoch: 0 [15206912/26365952 (58%)] Avg Boundaries (per batch): 49.443 Boundary Ratio: 0.252 Contrastive_loss: 2.1796 (2.9753) Boundary_loss: 0.015631 (0.016369) Loss: 2.1952 (2.9916) +2025-08-20,20:47:54 | INFO | Train Epoch: 0 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 2.0904 (2.9723) Boundary_loss: 0.015620 (0.016366) Loss: 2.1061 (2.9887) +2025-08-20,20:48:52 | INFO | Train Epoch: 0 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 2.1385 (2.9695) Boundary_loss: 0.015658 (0.016364) Loss: 2.1542 (2.9859) +2025-08-20,20:49:49 | INFO | Train Epoch: 0 [15360512/26365952 (58%)] Avg Boundaries (per batch): 47.066 Boundary Ratio: 0.240 Contrastive_loss: 1.9260 (2.9660) Boundary_loss: 0.015807 (0.016362) Loss: 1.9419 (2.9824) +2025-08-20,20:50:47 | INFO | Train Epoch: 0 [15411712/26365952 (58%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 2.0335 (2.9630) Boundary_loss: 0.015581 (0.016359) Loss: 2.0491 (2.9793) +2025-08-20,20:51:45 | INFO | Train Epoch: 0 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 2.0984 (2.9601) Boundary_loss: 0.015688 (0.016357) Loss: 2.1141 (2.9765) +2025-08-20,20:52:43 | INFO | Train Epoch: 0 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 2.0028 (2.9570) Boundary_loss: 0.015568 (0.016355) Loss: 2.0183 (2.9733) +2025-08-20,20:53:40 | INFO | Train Epoch: 0 [15565312/26365952 (59%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 2.1232 (2.9542) Boundary_loss: 0.015868 (0.016353) Loss: 2.1390 (2.9706) +2025-08-20,20:54:38 | INFO | Train Epoch: 0 [15616512/26365952 (59%)] Avg Boundaries (per batch): 50.197 Boundary Ratio: 0.256 Contrastive_loss: 1.9615 (2.9510) Boundary_loss: 0.015804 (0.016351) Loss: 1.9773 (2.9673) +2025-08-20,20:55:36 | INFO | Train Epoch: 0 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 1.9015 (2.9476) Boundary_loss: 0.015725 (0.016349) Loss: 1.9173 (2.9639) +2025-08-20,20:56:34 | INFO | Train Epoch: 0 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 2.0547 (2.9447) Boundary_loss: 0.015799 (0.016347) Loss: 2.0705 (2.9610) +2025-08-20,20:57:31 | INFO | Train Epoch: 0 [15770112/26365952 (60%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 1.8356 (2.9411) Boundary_loss: 0.015714 (0.016345) Loss: 1.8513 (2.9574) +2025-08-20,20:58:29 | INFO | Train Epoch: 0 [15821312/26365952 (60%)] Avg Boundaries (per batch): 50.088 Boundary Ratio: 0.256 Contrastive_loss: 2.0917 (2.9383) Boundary_loss: 0.015666 (0.016343) Loss: 2.1074 (2.9547) +2025-08-20,20:59:27 | INFO | Train Epoch: 0 [15872512/26365952 (60%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 1.9606 (2.9352) Boundary_loss: 0.015705 (0.016341) Loss: 1.9763 (2.9515) +2025-08-20,21:00:24 | INFO | Train Epoch: 0 [15923712/26365952 (60%)] Avg Boundaries (per batch): 47.322 Boundary Ratio: 0.241 Contrastive_loss: 2.2260 (2.9329) Boundary_loss: 0.015568 (0.016339) Loss: 2.2415 (2.9493) +2025-08-20,21:01:22 | INFO | Train Epoch: 0 [15974912/26365952 (61%)] Avg Boundaries (per batch): 47.881 Boundary Ratio: 0.244 Contrastive_loss: 1.9140 (2.9297) Boundary_loss: 0.015765 (0.016337) Loss: 1.9298 (2.9460) +2025-08-20,21:02:19 | INFO | Train Epoch: 0 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.059 Boundary Ratio: 0.245 Contrastive_loss: 2.1435 (2.9272) Boundary_loss: 0.015585 (0.016334) Loss: 2.1591 (2.9435) +2025-08-20,21:03:17 | INFO | Train Epoch: 0 [16077312/26365952 (61%)] Avg Boundaries (per batch): 47.664 Boundary Ratio: 0.243 Contrastive_loss: 2.0230 (2.9243) Boundary_loss: 0.015733 (0.016332) Loss: 2.0387 (2.9406) +2025-08-20,21:04:14 | INFO | Train Epoch: 0 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.324 Boundary Ratio: 0.247 Contrastive_loss: 2.0155 (2.9214) Boundary_loss: 0.015697 (0.016330) Loss: 2.0312 (2.9377) +2025-08-20,21:05:12 | INFO | Train Epoch: 0 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 1.8951 (2.9182) Boundary_loss: 0.015580 (0.016328) Loss: 1.9107 (2.9345) +2025-08-20,21:06:10 | INFO | Train Epoch: 0 [16230912/26365952 (62%)] Avg Boundaries (per batch): 49.852 Boundary Ratio: 0.254 Contrastive_loss: 1.9780 (2.9152) Boundary_loss: 0.015794 (0.016326) Loss: 1.9938 (2.9315) +2025-08-20,21:07:07 | INFO | Train Epoch: 0 [16282112/26365952 (62%)] Avg Boundaries (per batch): 47.602 Boundary Ratio: 0.243 Contrastive_loss: 1.8603 (2.9119) Boundary_loss: 0.015537 (0.016324) Loss: 1.8759 (2.9282) +2025-08-20,21:08:05 | INFO | Train Epoch: 0 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 1.8205 (2.9085) Boundary_loss: 0.015552 (0.016321) Loss: 1.8360 (2.9248) +2025-08-20,21:09:02 | INFO | Train Epoch: 0 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 2.0472 (2.9058) Boundary_loss: 0.015573 (0.016319) Loss: 2.0628 (2.9221) +2025-08-20,21:10:00 | INFO | Train Epoch: 0 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 1.8889 (2.9027) Boundary_loss: 0.015843 (0.016318) Loss: 1.9047 (2.9190) +2025-08-20,21:10:58 | INFO | Train Epoch: 0 [16486912/26365952 (63%)] Avg Boundaries (per batch): 46.975 Boundary Ratio: 0.240 Contrastive_loss: 2.0499 (2.9000) Boundary_loss: 0.015808 (0.016316) Loss: 2.0657 (2.9163) +2025-08-20,21:11:55 | INFO | Train Epoch: 0 [16538112/26365952 (63%)] Avg Boundaries (per batch): 47.727 Boundary Ratio: 0.244 Contrastive_loss: 2.0255 (2.8973) Boundary_loss: 0.015635 (0.016314) Loss: 2.0411 (2.9136) +2025-08-20,21:12:53 | INFO | Train Epoch: 0 [16589312/26365952 (63%)] Avg Boundaries (per batch): 49.338 Boundary Ratio: 0.252 Contrastive_loss: 1.7348 (2.8937) Boundary_loss: 0.015806 (0.016312) Loss: 1.7506 (2.9101) +2025-08-20,21:13:51 | INFO | Train Epoch: 0 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 1.8430 (2.8905) Boundary_loss: 0.015522 (0.016310) Loss: 1.8585 (2.9068) +2025-08-20,21:14:48 | INFO | Train Epoch: 0 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 2.0096 (2.8878) Boundary_loss: 0.015780 (0.016308) Loss: 2.0254 (2.9041) +2025-08-20,21:15:46 | INFO | Train Epoch: 0 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 2.0846 (2.8854) Boundary_loss: 0.015683 (0.016306) Loss: 2.1002 (2.9017) +2025-08-20,21:16:44 | INFO | Train Epoch: 0 [16794112/26365952 (64%)] Avg Boundaries (per batch): 49.854 Boundary Ratio: 0.254 Contrastive_loss: 1.8666 (2.8823) Boundary_loss: 0.015987 (0.016305) Loss: 1.8826 (2.8986) +2025-08-20,21:17:41 | INFO | Train Epoch: 0 [16845312/26365952 (64%)] Avg Boundaries (per batch): 49.928 Boundary Ratio: 0.255 Contrastive_loss: 1.8402 (2.8791) Boundary_loss: 0.015735 (0.016304) Loss: 1.8559 (2.8954) +2025-08-20,21:18:39 | INFO | Train Epoch: 0 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 1.8023 (2.8759) Boundary_loss: 0.015601 (0.016302) Loss: 1.8179 (2.8922) +2025-08-20,21:19:37 | INFO | Train Epoch: 0 [16947712/26365952 (64%)] Avg Boundaries (per batch): 47.965 Boundary Ratio: 0.245 Contrastive_loss: 1.8699 (2.8728) Boundary_loss: 0.015815 (0.016300) Loss: 1.8857 (2.8891) +2025-08-20,21:20:34 | INFO | Train Epoch: 0 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 1.7301 (2.8694) Boundary_loss: 0.015664 (0.016298) Loss: 1.7458 (2.8857) +2025-08-20,21:21:32 | INFO | Train Epoch: 0 [17050112/26365952 (65%)] Avg Boundaries (per batch): 49.385 Boundary Ratio: 0.252 Contrastive_loss: 1.8631 (2.8664) Boundary_loss: 0.015694 (0.016296) Loss: 1.8788 (2.8827) +2025-08-20,21:22:29 | INFO | Train Epoch: 0 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.254 Boundary Ratio: 0.246 Contrastive_loss: 1.8904 (2.8635) Boundary_loss: 0.015626 (0.016294) Loss: 1.9060 (2.8798) +2025-08-20,21:23:27 | INFO | Train Epoch: 0 [17152512/26365952 (65%)] Avg Boundaries (per batch): 49.352 Boundary Ratio: 0.252 Contrastive_loss: 1.9633 (2.8608) Boundary_loss: 0.015670 (0.016293) Loss: 1.9789 (2.8771) +2025-08-20,21:24:25 | INFO | Train Epoch: 0 [17203712/26365952 (65%)] Avg Boundaries (per batch): 49.684 Boundary Ratio: 0.253 Contrastive_loss: 1.7562 (2.8575) Boundary_loss: 0.015677 (0.016291) Loss: 1.7718 (2.8738) +2025-08-20,21:25:23 | INFO | Train Epoch: 0 [17254912/26365952 (65%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 1.8217 (2.8545) Boundary_loss: 0.015665 (0.016289) Loss: 1.8374 (2.8707) +2025-08-20,21:26:20 | INFO | Train Epoch: 0 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 1.8852 (2.8516) Boundary_loss: 0.015524 (0.016287) Loss: 1.9007 (2.8679) +2025-08-20,21:27:18 | INFO | Train Epoch: 0 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 1.8071 (2.8485) Boundary_loss: 0.015526 (0.016284) Loss: 1.8226 (2.8648) +2025-08-20,21:28:15 | INFO | Train Epoch: 0 [17408512/26365952 (66%)] Avg Boundaries (per batch): 47.875 Boundary Ratio: 0.244 Contrastive_loss: 2.0749 (2.8463) Boundary_loss: 0.015484 (0.016282) Loss: 2.0903 (2.8625) +2025-08-20,21:29:13 | INFO | Train Epoch: 0 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.391 Boundary Ratio: 0.247 Contrastive_loss: 1.8461 (2.8433) Boundary_loss: 0.015512 (0.016280) Loss: 1.8616 (2.8596) +2025-08-20,21:30:11 | INFO | Train Epoch: 0 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 1.8946 (2.8406) Boundary_loss: 0.015685 (0.016278) Loss: 1.9103 (2.8568) +2025-08-20,21:31:09 | INFO | Train Epoch: 0 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.596 Boundary Ratio: 0.253 Contrastive_loss: 1.7795 (2.8375) Boundary_loss: 0.015611 (0.016276) Loss: 1.7951 (2.8538) +2025-08-20,21:32:06 | INFO | Train Epoch: 0 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 1.9754 (2.8350) Boundary_loss: 0.015565 (0.016274) Loss: 1.9909 (2.8513) +2025-08-20,21:33:04 | INFO | Train Epoch: 0 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 1.9535 (2.8324) Boundary_loss: 0.015568 (0.016272) Loss: 1.9691 (2.8487) +2025-08-20,21:34:02 | INFO | Train Epoch: 0 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.375 Boundary Ratio: 0.252 Contrastive_loss: 1.7158 (2.8292) Boundary_loss: 0.015689 (0.016270) Loss: 1.7315 (2.8455) +2025-08-20,21:35:00 | INFO | Train Epoch: 0 [17766912/26365952 (67%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 1.8672 (2.8265) Boundary_loss: 0.015477 (0.016268) Loss: 1.8827 (2.8427) +2025-08-20,21:35:57 | INFO | Train Epoch: 0 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 1.8500 (2.8237) Boundary_loss: 0.015732 (0.016267) Loss: 1.8657 (2.8399) +2025-08-20,21:36:55 | INFO | Train Epoch: 0 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.719 Boundary Ratio: 0.254 Contrastive_loss: 1.8708 (2.8209) Boundary_loss: 0.015663 (0.016265) Loss: 1.8864 (2.8372) +2025-08-20,21:37:53 | INFO | Train Epoch: 0 [17920512/26365952 (68%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 1.9770 (2.8185) Boundary_loss: 0.015531 (0.016263) Loss: 1.9925 (2.8348) +2025-08-20,21:38:50 | INFO | Train Epoch: 0 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.111 Boundary Ratio: 0.245 Contrastive_loss: 1.9263 (2.8160) Boundary_loss: 0.015541 (0.016261) Loss: 1.9419 (2.8323) +2025-08-20,21:39:48 | INFO | Train Epoch: 0 [18022912/26365952 (68%)] Avg Boundaries (per batch): 49.520 Boundary Ratio: 0.253 Contrastive_loss: 1.8424 (2.8132) Boundary_loss: 0.015721 (0.016259) Loss: 1.8581 (2.8295) +2025-08-20,21:40:46 | INFO | Train Epoch: 0 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.7740 (2.8103) Boundary_loss: 0.015794 (0.016258) Loss: 1.7898 (2.8266) +2025-08-20,21:41:43 | INFO | Train Epoch: 0 [18125312/26365952 (69%)] Avg Boundaries (per batch): 49.279 Boundary Ratio: 0.251 Contrastive_loss: 1.7756 (2.8074) Boundary_loss: 0.015519 (0.016256) Loss: 1.7911 (2.8236) +2025-08-20,21:42:40 | INFO | Train Epoch: 0 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 1.7244 (2.8043) Boundary_loss: 0.015732 (0.016254) Loss: 1.7401 (2.8206) +2025-08-20,21:43:38 | INFO | Train Epoch: 0 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 1.6852 (2.8012) Boundary_loss: 0.015790 (0.016253) Loss: 1.7010 (2.8175) +2025-08-20,21:44:36 | INFO | Train Epoch: 0 [18278912/26365952 (69%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 1.9271 (2.7988) Boundary_loss: 0.015612 (0.016251) Loss: 1.9427 (2.8150) +2025-08-20,21:45:34 | INFO | Train Epoch: 0 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.396 Boundary Ratio: 0.252 Contrastive_loss: 1.8789 (2.7962) Boundary_loss: 0.015563 (0.016249) Loss: 1.8945 (2.8125) +2025-08-20,21:46:31 | INFO | Train Epoch: 0 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 1.8971 (2.7937) Boundary_loss: 0.015473 (0.016247) Loss: 1.9125 (2.8100) +2025-08-20,21:47:29 | INFO | Train Epoch: 0 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 1.7298 (2.7908) Boundary_loss: 0.015422 (0.016245) Loss: 1.7453 (2.8070) +2025-08-20,21:48:27 | INFO | Train Epoch: 0 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.8429 (2.7881) Boundary_loss: 0.015487 (0.016243) Loss: 1.8584 (2.8044) +2025-08-20,21:49:24 | INFO | Train Epoch: 0 [18534912/26365952 (70%)] Avg Boundaries (per batch): 49.516 Boundary Ratio: 0.253 Contrastive_loss: 1.8547 (2.7856) Boundary_loss: 0.015610 (0.016241) Loss: 1.8703 (2.8018) +2025-08-20,21:50:22 | INFO | Train Epoch: 0 [18586112/26365952 (70%)] Avg Boundaries (per batch): 50.312 Boundary Ratio: 0.257 Contrastive_loss: 1.9599 (2.7833) Boundary_loss: 0.015657 (0.016239) Loss: 1.9756 (2.7995) +2025-08-20,21:51:19 | INFO | Train Epoch: 0 [18637312/26365952 (71%)] Avg Boundaries (per batch): 47.744 Boundary Ratio: 0.244 Contrastive_loss: 1.8048 (2.7806) Boundary_loss: 0.015572 (0.016238) Loss: 1.8204 (2.7969) +2025-08-20,21:52:17 | INFO | Train Epoch: 0 [18688512/26365952 (71%)] Avg Boundaries (per batch): 49.975 Boundary Ratio: 0.255 Contrastive_loss: 1.8253 (2.7780) Boundary_loss: 0.015871 (0.016237) Loss: 1.8412 (2.7942) +2025-08-20,21:53:15 | INFO | Train Epoch: 0 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 2.0196 (2.7759) Boundary_loss: 0.015483 (0.016235) Loss: 2.0351 (2.7922) +2025-08-20,21:54:13 | INFO | Train Epoch: 0 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 1.9080 (2.7736) Boundary_loss: 0.015550 (0.016233) Loss: 1.9236 (2.7898) +2025-08-20,21:55:11 | INFO | Train Epoch: 0 [18842112/26365952 (71%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 1.8187 (2.7710) Boundary_loss: 0.015695 (0.016231) Loss: 1.8343 (2.7872) +2025-08-20,21:56:08 | INFO | Train Epoch: 0 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 1.8370 (2.7685) Boundary_loss: 0.015451 (0.016229) Loss: 1.8525 (2.7847) +2025-08-20,21:57:06 | INFO | Train Epoch: 0 [18944512/26365952 (72%)] Avg Boundaries (per batch): 49.527 Boundary Ratio: 0.253 Contrastive_loss: 1.9850 (2.7664) Boundary_loss: 0.015563 (0.016227) Loss: 2.0005 (2.7826) +2025-08-20,21:58:04 | INFO | Train Epoch: 0 [18995712/26365952 (72%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 1.8425 (2.7639) Boundary_loss: 0.015429 (0.016225) Loss: 1.8579 (2.7801) +2025-08-20,21:59:01 | INFO | Train Epoch: 0 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.566 Boundary Ratio: 0.253 Contrastive_loss: 2.0192 (2.7619) Boundary_loss: 0.015492 (0.016223) Loss: 2.0347 (2.7781) +2025-08-20,21:59:59 | INFO | Train Epoch: 0 [19098112/26365952 (72%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 1.7723 (2.7592) Boundary_loss: 0.015611 (0.016222) Loss: 1.7879 (2.7755) +2025-08-20,22:00:57 | INFO | Train Epoch: 0 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 1.8066 (2.7567) Boundary_loss: 0.015617 (0.016220) Loss: 1.8222 (2.7729) +2025-08-20,22:01:54 | INFO | Train Epoch: 0 [19200512/26365952 (73%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 1.8059 (2.7542) Boundary_loss: 0.015442 (0.016218) Loss: 1.8214 (2.7704) +2025-08-20,22:02:52 | INFO | Train Epoch: 0 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 1.8489 (2.7518) Boundary_loss: 0.015511 (0.016216) Loss: 1.8644 (2.7680) +2025-08-20,22:03:50 | INFO | Train Epoch: 0 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.492 Boundary Ratio: 0.247 Contrastive_loss: 1.8420 (2.7494) Boundary_loss: 0.015624 (0.016214) Loss: 1.8576 (2.7656) +2025-08-20,22:04:48 | INFO | Train Epoch: 0 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.7205 (2.7466) Boundary_loss: 0.015560 (0.016213) Loss: 1.7360 (2.7629) +2025-08-20,22:05:45 | INFO | Train Epoch: 0 [19405312/26365952 (74%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 1.8734 (2.7443) Boundary_loss: 0.015522 (0.016211) Loss: 1.8889 (2.7606) +2025-08-20,22:06:43 | INFO | Train Epoch: 0 [19456512/26365952 (74%)] Avg Boundaries (per batch): 46.953 Boundary Ratio: 0.240 Contrastive_loss: 1.8540 (2.7420) Boundary_loss: 0.015671 (0.016209) Loss: 1.8697 (2.7582) +2025-08-20,22:07:41 | INFO | Train Epoch: 0 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 1.8271 (2.7396) Boundary_loss: 0.015655 (0.016208) Loss: 1.8428 (2.7558) +2025-08-20,22:08:38 | INFO | Train Epoch: 0 [19558912/26365952 (74%)] Avg Boundaries (per batch): 47.268 Boundary Ratio: 0.241 Contrastive_loss: 1.6700 (2.7368) Boundary_loss: 0.015465 (0.016206) Loss: 1.6855 (2.7530) +2025-08-20,22:09:36 | INFO | Train Epoch: 0 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 1.7503 (2.7343) Boundary_loss: 0.015623 (0.016205) Loss: 1.7659 (2.7505) +2025-08-20,22:10:34 | INFO | Train Epoch: 0 [19661312/26365952 (75%)] Avg Boundaries (per batch): 49.703 Boundary Ratio: 0.254 Contrastive_loss: 1.7088 (2.7316) Boundary_loss: 0.015813 (0.016204) Loss: 1.7246 (2.7478) +2025-08-20,22:11:32 | INFO | Train Epoch: 0 [19712512/26365952 (75%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 1.8708 (2.7294) Boundary_loss: 0.015667 (0.016202) Loss: 1.8864 (2.7456) +2025-08-20,22:12:30 | INFO | Train Epoch: 0 [19763712/26365952 (75%)] Avg Boundaries (per batch): 50.381 Boundary Ratio: 0.257 Contrastive_loss: 1.6872 (2.7267) Boundary_loss: 0.015750 (0.016201) Loss: 1.7030 (2.7429) +2025-08-20,22:13:27 | INFO | Train Epoch: 0 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 1.7392 (2.7241) Boundary_loss: 0.015575 (0.016199) Loss: 1.7548 (2.7403) +2025-08-20,22:14:25 | INFO | Train Epoch: 0 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 1.8918 (2.7220) Boundary_loss: 0.015501 (0.016198) Loss: 1.9073 (2.7382) +2025-08-20,22:15:22 | INFO | Train Epoch: 0 [19917312/26365952 (76%)] Avg Boundaries (per batch): 49.707 Boundary Ratio: 0.254 Contrastive_loss: 1.9818 (2.7201) Boundary_loss: 0.015460 (0.016196) Loss: 1.9973 (2.7363) +2025-08-20,22:16:20 | INFO | Train Epoch: 0 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 1.7160 (2.7175) Boundary_loss: 0.015642 (0.016194) Loss: 1.7316 (2.7337) +2025-08-20,22:17:17 | INFO | Train Epoch: 0 [20019712/26365952 (76%)] Avg Boundaries (per batch): 47.990 Boundary Ratio: 0.245 Contrastive_loss: 1.8313 (2.7153) Boundary_loss: 0.015704 (0.016193) Loss: 1.8470 (2.7314) +2025-08-20,22:18:15 | INFO | Train Epoch: 0 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 1.8534 (2.7131) Boundary_loss: 0.015522 (0.016191) Loss: 1.8689 (2.7293) +2025-08-20,22:19:13 | INFO | Train Epoch: 0 [20122112/26365952 (76%)] Avg Boundaries (per batch): 50.551 Boundary Ratio: 0.258 Contrastive_loss: 1.7468 (2.7106) Boundary_loss: 0.015866 (0.016190) Loss: 1.7626 (2.7268) +2025-08-20,22:20:10 | INFO | Train Epoch: 0 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 1.8220 (2.7084) Boundary_loss: 0.015525 (0.016189) Loss: 1.8375 (2.7245) +2025-08-20,22:21:08 | INFO | Train Epoch: 0 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.248 Boundary Ratio: 0.246 Contrastive_loss: 1.6791 (2.7058) Boundary_loss: 0.015535 (0.016187) Loss: 1.6946 (2.7219) +2025-08-20,22:22:06 | INFO | Train Epoch: 0 [20275712/26365952 (77%)] Avg Boundaries (per batch): 47.555 Boundary Ratio: 0.243 Contrastive_loss: 1.8322 (2.7036) Boundary_loss: 0.015739 (0.016186) Loss: 1.8479 (2.7197) +2025-08-20,22:23:03 | INFO | Train Epoch: 0 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 1.7188 (2.7011) Boundary_loss: 0.015503 (0.016184) Loss: 1.7343 (2.7173) +2025-08-20,22:24:01 | INFO | Train Epoch: 0 [20378112/26365952 (77%)] Avg Boundaries (per batch): 49.777 Boundary Ratio: 0.254 Contrastive_loss: 1.6835 (2.6985) Boundary_loss: 0.015607 (0.016183) Loss: 1.6991 (2.7147) +2025-08-20,22:24:58 | INFO | Train Epoch: 0 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 1.6775 (2.6960) Boundary_loss: 0.015536 (0.016181) Loss: 1.6931 (2.7122) +2025-08-20,22:25:56 | INFO | Train Epoch: 0 [20480512/26365952 (78%)] Avg Boundaries (per batch): 50.260 Boundary Ratio: 0.256 Contrastive_loss: 1.6863 (2.6935) Boundary_loss: 0.015724 (0.016180) Loss: 1.7020 (2.7096) +2025-08-20,22:26:53 | INFO | Train Epoch: 0 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.516 Boundary Ratio: 0.253 Contrastive_loss: 1.8687 (2.6914) Boundary_loss: 0.015561 (0.016179) Loss: 1.8842 (2.7076) +2025-08-20,22:27:51 | INFO | Train Epoch: 0 [20582912/26365952 (78%)] Avg Boundaries (per batch): 49.639 Boundary Ratio: 0.253 Contrastive_loss: 1.8047 (2.6892) Boundary_loss: 0.015693 (0.016177) Loss: 1.8204 (2.7054) +2025-08-20,22:28:49 | INFO | Train Epoch: 0 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 1.9223 (2.6873) Boundary_loss: 0.015534 (0.016176) Loss: 1.9378 (2.7035) +2025-08-20,22:29:46 | INFO | Train Epoch: 0 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.049 Boundary Ratio: 0.245 Contrastive_loss: 1.7947 (2.6851) Boundary_loss: 0.015782 (0.016175) Loss: 1.8104 (2.7013) +2025-08-20,22:30:44 | INFO | Train Epoch: 0 [20736512/26365952 (79%)] Avg Boundaries (per batch): 49.627 Boundary Ratio: 0.253 Contrastive_loss: 1.8122 (2.6830) Boundary_loss: 0.015698 (0.016174) Loss: 1.8279 (2.6991) +2025-08-20,22:31:41 | INFO | Train Epoch: 0 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 1.7357 (2.6806) Boundary_loss: 0.015650 (0.016172) Loss: 1.7513 (2.6968) +2025-08-20,22:32:39 | INFO | Train Epoch: 0 [20838912/26365952 (79%)] Avg Boundaries (per batch): 47.867 Boundary Ratio: 0.244 Contrastive_loss: 1.6769 (2.6782) Boundary_loss: 0.015615 (0.016171) Loss: 1.6925 (2.6943) +2025-08-20,22:33:37 | INFO | Train Epoch: 0 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.285 Boundary Ratio: 0.246 Contrastive_loss: 1.8435 (2.6761) Boundary_loss: 0.015445 (0.016169) Loss: 1.8590 (2.6923) +2025-08-20,22:34:34 | INFO | Train Epoch: 0 [20941312/26365952 (79%)] Avg Boundaries (per batch): 47.523 Boundary Ratio: 0.242 Contrastive_loss: 1.7085 (2.6738) Boundary_loss: 0.015666 (0.016168) Loss: 1.7242 (2.6899) +2025-08-20,22:35:32 | INFO | Train Epoch: 0 [20992512/26365952 (80%)] Avg Boundaries (per batch): 47.707 Boundary Ratio: 0.243 Contrastive_loss: 1.6796 (2.6714) Boundary_loss: 0.015775 (0.016167) Loss: 1.6954 (2.6875) +2025-08-20,22:36:30 | INFO | Train Epoch: 0 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 1.5965 (2.6687) Boundary_loss: 0.015508 (0.016165) Loss: 1.6120 (2.6849) +2025-08-20,22:37:27 | INFO | Train Epoch: 0 [21094912/26365952 (80%)] Avg Boundaries (per batch): 50.143 Boundary Ratio: 0.256 Contrastive_loss: 1.7555 (2.6665) Boundary_loss: 0.015653 (0.016164) Loss: 1.7711 (2.6827) +2025-08-20,22:38:25 | INFO | Train Epoch: 0 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 1.7198 (2.6642) Boundary_loss: 0.015576 (0.016163) Loss: 1.7354 (2.6804) +2025-08-20,22:39:23 | INFO | Train Epoch: 0 [21197312/26365952 (80%)] Avg Boundaries (per batch): 47.898 Boundary Ratio: 0.244 Contrastive_loss: 1.7491 (2.6620) Boundary_loss: 0.015588 (0.016161) Loss: 1.7647 (2.6782) +2025-08-20,22:40:20 | INFO | Train Epoch: 0 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.328 Boundary Ratio: 0.247 Contrastive_loss: 1.6091 (2.6595) Boundary_loss: 0.015307 (0.016159) Loss: 1.6244 (2.6757) +2025-08-20,22:41:18 | INFO | Train Epoch: 0 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 1.8158 (2.6575) Boundary_loss: 0.015615 (0.016158) Loss: 1.8314 (2.6736) +2025-08-20,22:42:16 | INFO | Train Epoch: 0 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.979 Boundary Ratio: 0.255 Contrastive_loss: 1.8443 (2.6555) Boundary_loss: 0.015542 (0.016157) Loss: 1.8599 (2.6717) +2025-08-20,22:43:13 | INFO | Train Epoch: 0 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 1.7112 (2.6533) Boundary_loss: 0.015485 (0.016155) Loss: 1.7267 (2.6694) +2025-08-20,22:44:11 | INFO | Train Epoch: 0 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 1.8781 (2.6514) Boundary_loss: 0.015518 (0.016153) Loss: 1.8936 (2.6676) +2025-08-20,22:45:08 | INFO | Train Epoch: 0 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 1.6851 (2.6491) Boundary_loss: 0.015581 (0.016152) Loss: 1.7007 (2.6653) +2025-08-20,22:46:06 | INFO | Train Epoch: 0 [21555712/26365952 (82%)] Avg Boundaries (per batch): 50.154 Boundary Ratio: 0.256 Contrastive_loss: 1.6967 (2.6469) Boundary_loss: 0.015582 (0.016151) Loss: 1.7123 (2.6630) +2025-08-20,22:47:04 | INFO | Train Epoch: 0 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 1.6729 (2.6446) Boundary_loss: 0.015600 (0.016149) Loss: 1.6885 (2.6607) +2025-08-20,22:48:01 | INFO | Train Epoch: 0 [21658112/26365952 (82%)] Avg Boundaries (per batch): 49.865 Boundary Ratio: 0.254 Contrastive_loss: 1.6222 (2.6422) Boundary_loss: 0.015660 (0.016148) Loss: 1.6379 (2.6583) +2025-08-20,22:48:59 | INFO | Train Epoch: 0 [21709312/26365952 (82%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 1.8108 (2.6402) Boundary_loss: 0.015637 (0.016147) Loss: 1.8264 (2.6564) +2025-08-20,22:49:57 | INFO | Train Epoch: 0 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 1.8401 (2.6383) Boundary_loss: 0.015550 (0.016146) Loss: 1.8557 (2.6545) +2025-08-20,22:50:54 | INFO | Train Epoch: 0 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.270 Boundary Ratio: 0.246 Contrastive_loss: 1.7224 (2.6362) Boundary_loss: 0.015420 (0.016144) Loss: 1.7379 (2.6523) +2025-08-20,22:51:52 | INFO | Train Epoch: 0 [21862912/26365952 (83%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 1.5962 (2.6338) Boundary_loss: 0.015596 (0.016143) Loss: 1.6118 (2.6499) +2025-08-20,22:52:49 | INFO | Train Epoch: 0 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.375 Boundary Ratio: 0.252 Contrastive_loss: 1.7457 (2.6317) Boundary_loss: 0.015534 (0.016141) Loss: 1.7612 (2.6478) +2025-08-20,22:53:47 | INFO | Train Epoch: 0 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 1.7619 (2.6297) Boundary_loss: 0.015483 (0.016140) Loss: 1.7774 (2.6458) +2025-08-20,22:54:44 | INFO | Train Epoch: 0 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 1.8115 (2.6278) Boundary_loss: 0.015721 (0.016139) Loss: 1.8272 (2.6439) +2025-08-20,22:55:42 | INFO | Train Epoch: 0 [22067712/26365952 (84%)] Avg Boundaries (per batch): 47.967 Boundary Ratio: 0.245 Contrastive_loss: 1.7787 (2.6258) Boundary_loss: 0.015505 (0.016137) Loss: 1.7943 (2.6419) +2025-08-20,22:56:39 | INFO | Train Epoch: 0 [22118912/26365952 (84%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 1.7536 (2.6238) Boundary_loss: 0.015528 (0.016136) Loss: 1.7691 (2.6399) +2025-08-20,22:57:37 | INFO | Train Epoch: 0 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 1.7892 (2.6219) Boundary_loss: 0.015451 (0.016134) Loss: 1.8046 (2.6380) +2025-08-20,22:58:34 | INFO | Train Epoch: 0 [22221312/26365952 (84%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 1.7632 (2.6199) Boundary_loss: 0.015463 (0.016133) Loss: 1.7787 (2.6360) +2025-08-20,22:59:32 | INFO | Train Epoch: 0 [22272512/26365952 (84%)] Avg Boundaries (per batch): 50.756 Boundary Ratio: 0.259 Contrastive_loss: 1.6341 (2.6176) Boundary_loss: 0.015738 (0.016132) Loss: 1.6498 (2.6338) +2025-08-20,23:00:30 | INFO | Train Epoch: 0 [22323712/26365952 (85%)] Avg Boundaries (per batch): 49.744 Boundary Ratio: 0.254 Contrastive_loss: 1.6355 (2.6154) Boundary_loss: 0.015887 (0.016131) Loss: 1.6514 (2.6315) +2025-08-20,23:01:27 | INFO | Train Epoch: 0 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 1.6669 (2.6132) Boundary_loss: 0.015409 (0.016130) Loss: 1.6823 (2.6294) +2025-08-20,23:02:25 | INFO | Train Epoch: 0 [22426112/26365952 (85%)] Avg Boundaries (per batch): 50.105 Boundary Ratio: 0.256 Contrastive_loss: 1.6587 (2.6111) Boundary_loss: 0.015723 (0.016129) Loss: 1.6744 (2.6272) +2025-08-20,23:03:22 | INFO | Train Epoch: 0 [22477312/26365952 (85%)] Avg Boundaries (per batch): 49.412 Boundary Ratio: 0.252 Contrastive_loss: 1.5838 (2.6087) Boundary_loss: 0.015599 (0.016127) Loss: 1.5994 (2.6248) +2025-08-20,23:04:20 | INFO | Train Epoch: 0 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.6598 (2.6066) Boundary_loss: 0.015520 (0.016126) Loss: 1.6754 (2.6227) +2025-08-20,23:05:17 | INFO | Train Epoch: 0 [22579712/26365952 (86%)] Avg Boundaries (per batch): 47.414 Boundary Ratio: 0.242 Contrastive_loss: 1.7733 (2.6047) Boundary_loss: 0.015669 (0.016125) Loss: 1.7890 (2.6208) +2025-08-20,23:06:15 | INFO | Train Epoch: 0 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 1.7101 (2.6027) Boundary_loss: 0.015486 (0.016124) Loss: 1.7256 (2.6188) +2025-08-20,23:07:12 | INFO | Train Epoch: 0 [22682112/26365952 (86%)] Avg Boundaries (per batch): 47.949 Boundary Ratio: 0.245 Contrastive_loss: 1.5713 (2.6003) Boundary_loss: 0.015444 (0.016122) Loss: 1.5867 (2.6165) +2025-08-20,23:08:10 | INFO | Train Epoch: 0 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 1.6513 (2.5982) Boundary_loss: 0.015463 (0.016121) Loss: 1.6668 (2.6143) +2025-08-20,23:09:07 | INFO | Train Epoch: 0 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 1.6932 (2.5962) Boundary_loss: 0.015488 (0.016119) Loss: 1.7087 (2.6123) +2025-08-20,23:10:05 | INFO | Train Epoch: 0 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 1.7729 (2.5943) Boundary_loss: 0.015537 (0.016118) Loss: 1.7885 (2.6105) +2025-08-20,23:11:03 | INFO | Train Epoch: 0 [22886912/26365952 (87%)] Avg Boundaries (per batch): 47.988 Boundary Ratio: 0.245 Contrastive_loss: 1.6619 (2.5923) Boundary_loss: 0.015673 (0.016117) Loss: 1.6776 (2.6084) +2025-08-20,23:12:00 | INFO | Train Epoch: 0 [22938112/26365952 (87%)] Avg Boundaries (per batch): 47.271 Boundary Ratio: 0.241 Contrastive_loss: 1.6310 (2.5901) Boundary_loss: 0.015747 (0.016116) Loss: 1.6467 (2.6062) +2025-08-20,23:12:58 | INFO | Train Epoch: 0 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.000 Boundary Ratio: 0.245 Contrastive_loss: 1.5009 (2.5877) Boundary_loss: 0.015500 (0.016115) Loss: 1.5164 (2.6038) +2025-08-20,23:13:55 | INFO | Train Epoch: 0 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.7527 (2.5858) Boundary_loss: 0.015589 (0.016114) Loss: 1.7683 (2.6020) +2025-08-20,23:14:53 | INFO | Train Epoch: 0 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 1.7048 (2.5839) Boundary_loss: 0.015793 (0.016113) Loss: 1.7206 (2.6000) +2025-08-20,23:15:50 | INFO | Train Epoch: 0 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.375 Boundary Ratio: 0.247 Contrastive_loss: 1.7532 (2.5821) Boundary_loss: 0.015416 (0.016111) Loss: 1.7686 (2.5982) +2025-08-20,23:16:48 | INFO | Train Epoch: 0 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 1.6567 (2.5800) Boundary_loss: 0.015457 (0.016110) Loss: 1.6722 (2.5961) +2025-08-20,23:17:45 | INFO | Train Epoch: 0 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.291 Boundary Ratio: 0.246 Contrastive_loss: 1.7129 (2.5781) Boundary_loss: 0.015446 (0.016108) Loss: 1.7283 (2.5942) +2025-08-20,23:18:43 | INFO | Train Epoch: 0 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 1.6570 (2.5761) Boundary_loss: 0.015462 (0.016107) Loss: 1.6725 (2.5922) +2025-08-20,23:19:41 | INFO | Train Epoch: 0 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 1.6773 (2.5741) Boundary_loss: 0.015607 (0.016106) Loss: 1.6929 (2.5902) +2025-08-20,23:20:38 | INFO | Train Epoch: 0 [23398912/26365952 (89%)] Avg Boundaries (per batch): 47.840 Boundary Ratio: 0.244 Contrastive_loss: 1.6734 (2.5722) Boundary_loss: 0.015701 (0.016105) Loss: 1.6891 (2.5883) +2025-08-20,23:21:36 | INFO | Train Epoch: 0 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.734 Boundary Ratio: 0.254 Contrastive_loss: 1.6327 (2.5701) Boundary_loss: 0.015596 (0.016104) Loss: 1.6483 (2.5862) +2025-08-20,23:22:33 | INFO | Train Epoch: 0 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 1.6037 (2.5680) Boundary_loss: 0.015446 (0.016102) Loss: 1.6192 (2.5841) +2025-08-20,23:23:31 | INFO | Train Epoch: 0 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 1.6900 (2.5661) Boundary_loss: 0.015426 (0.016101) Loss: 1.7054 (2.5822) +2025-08-20,23:24:28 | INFO | Train Epoch: 0 [23603712/26365952 (90%)] Avg Boundaries (per batch): 49.902 Boundary Ratio: 0.255 Contrastive_loss: 1.6236 (2.5641) Boundary_loss: 0.015673 (0.016100) Loss: 1.6392 (2.5802) +2025-08-20,23:25:26 | INFO | Train Epoch: 0 [23654912/26365952 (90%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 1.6419 (2.5621) Boundary_loss: 0.015554 (0.016099) Loss: 1.6575 (2.5782) +2025-08-20,23:26:23 | INFO | Train Epoch: 0 [23706112/26365952 (90%)] Avg Boundaries (per batch): 47.770 Boundary Ratio: 0.244 Contrastive_loss: 1.5145 (2.5598) Boundary_loss: 0.015576 (0.016098) Loss: 1.5300 (2.5759) +2025-08-20,23:27:20 | INFO | Train Epoch: 0 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 1.8797 (2.5584) Boundary_loss: 0.015370 (0.016096) Loss: 1.8951 (2.5745) +2025-08-20,23:28:18 | INFO | Train Epoch: 0 [23808512/26365952 (90%)] Avg Boundaries (per batch): 49.635 Boundary Ratio: 0.253 Contrastive_loss: 1.6741 (2.5565) Boundary_loss: 0.015517 (0.016095) Loss: 1.6896 (2.5726) +2025-08-20,23:29:15 | INFO | Train Epoch: 0 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.7188 (2.5547) Boundary_loss: 0.015583 (0.016094) Loss: 1.7344 (2.5708) +2025-08-20,23:30:13 | INFO | Train Epoch: 0 [23910912/26365952 (91%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 1.6813 (2.5528) Boundary_loss: 0.015481 (0.016093) Loss: 1.6968 (2.5689) +2025-08-20,23:31:11 | INFO | Train Epoch: 0 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 1.5664 (2.5507) Boundary_loss: 0.015665 (0.016092) Loss: 1.5821 (2.5668) +2025-08-20,23:32:08 | INFO | Train Epoch: 0 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.977 Boundary Ratio: 0.255 Contrastive_loss: 1.7065 (2.5489) Boundary_loss: 0.015827 (0.016091) Loss: 1.7224 (2.5650) +2025-08-20,23:33:06 | INFO | Train Epoch: 0 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 1.5473 (2.5468) Boundary_loss: 0.015311 (0.016089) Loss: 1.5626 (2.5629) +2025-08-20,23:34:03 | INFO | Train Epoch: 0 [24115712/26365952 (91%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 1.4630 (2.5445) Boundary_loss: 0.015647 (0.016088) Loss: 1.4786 (2.5606) +2025-08-20,23:35:00 | INFO | Train Epoch: 0 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 1.6638 (2.5426) Boundary_loss: 0.015556 (0.016087) Loss: 1.6794 (2.5587) +2025-08-20,23:35:58 | INFO | Train Epoch: 0 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.6420 (2.5407) Boundary_loss: 0.015565 (0.016086) Loss: 1.6576 (2.5568) +2025-08-20,23:36:55 | INFO | Train Epoch: 0 [24269312/26365952 (92%)] Avg Boundaries (per batch): 49.596 Boundary Ratio: 0.253 Contrastive_loss: 1.7388 (2.5390) Boundary_loss: 0.015423 (0.016085) Loss: 1.7542 (2.5551) +2025-08-20,23:37:53 | INFO | Train Epoch: 0 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.109 Boundary Ratio: 0.245 Contrastive_loss: 1.5928 (2.5370) Boundary_loss: 0.015655 (0.016084) Loss: 1.6085 (2.5531) +2025-08-20,23:38:50 | INFO | Train Epoch: 0 [24371712/26365952 (92%)] Avg Boundaries (per batch): 49.992 Boundary Ratio: 0.255 Contrastive_loss: 1.6454 (2.5352) Boundary_loss: 0.015605 (0.016083) Loss: 1.6610 (2.5513) +2025-08-20,23:39:48 | INFO | Train Epoch: 0 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 1.6218 (2.5333) Boundary_loss: 0.015411 (0.016082) Loss: 1.6372 (2.5493) +2025-08-20,23:40:46 | INFO | Train Epoch: 0 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 1.7412 (2.5316) Boundary_loss: 0.015650 (0.016081) Loss: 1.7569 (2.5477) +2025-08-20,23:41:43 | INFO | Train Epoch: 0 [24525312/26365952 (93%)] Avg Boundaries (per batch): 49.416 Boundary Ratio: 0.252 Contrastive_loss: 1.5671 (2.5296) Boundary_loss: 0.015616 (0.016080) Loss: 1.5827 (2.5457) +2025-08-20,23:42:41 | INFO | Train Epoch: 0 [24576512/26365952 (93%)] Avg Boundaries (per batch): 47.490 Boundary Ratio: 0.242 Contrastive_loss: 1.4353 (2.5273) Boundary_loss: 0.015657 (0.016079) Loss: 1.4509 (2.5434) +2025-08-20,23:43:38 | INFO | Train Epoch: 0 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.197 Boundary Ratio: 0.246 Contrastive_loss: 1.6652 (2.5255) Boundary_loss: 0.015614 (0.016078) Loss: 1.6808 (2.5416) +2025-08-20,23:44:36 | INFO | Train Epoch: 0 [24678912/26365952 (94%)] Avg Boundaries (per batch): 49.676 Boundary Ratio: 0.253 Contrastive_loss: 1.7337 (2.5239) Boundary_loss: 0.015496 (0.016077) Loss: 1.7492 (2.5400) +2025-08-20,23:45:33 | INFO | Train Epoch: 0 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 1.6477 (2.5221) Boundary_loss: 0.015660 (0.016076) Loss: 1.6634 (2.5382) +2025-08-20,23:46:31 | INFO | Train Epoch: 0 [24781312/26365952 (94%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 1.7001 (2.5204) Boundary_loss: 0.015554 (0.016075) Loss: 1.7157 (2.5365) +2025-08-20,23:47:28 | INFO | Train Epoch: 0 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 1.7330 (2.5188) Boundary_loss: 0.015608 (0.016074) Loss: 1.7486 (2.5348) +2025-08-20,23:48:26 | INFO | Train Epoch: 0 [24883712/26365952 (94%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 1.4477 (2.5166) Boundary_loss: 0.015407 (0.016072) Loss: 1.4631 (2.5326) +2025-08-20,23:49:24 | INFO | Train Epoch: 0 [24934912/26365952 (95%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 1.5774 (2.5146) Boundary_loss: 0.015464 (0.016071) Loss: 1.5928 (2.5307) +2025-08-20,23:50:21 | INFO | Train Epoch: 0 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.6808 (2.5129) Boundary_loss: 0.015535 (0.016070) Loss: 1.6964 (2.5290) +2025-08-20,23:51:19 | INFO | Train Epoch: 0 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.6128 (2.5111) Boundary_loss: 0.015302 (0.016068) Loss: 1.6281 (2.5272) +2025-08-20,23:52:16 | INFO | Train Epoch: 0 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 1.5527 (2.5091) Boundary_loss: 0.015467 (0.016067) Loss: 1.5681 (2.5252) +2025-08-20,23:53:14 | INFO | Train Epoch: 0 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 1.6091 (2.5073) Boundary_loss: 0.015423 (0.016066) Loss: 1.6246 (2.5234) +2025-08-20,23:54:11 | INFO | Train Epoch: 0 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.4213 (2.5051) Boundary_loss: 0.015431 (0.016065) Loss: 1.4368 (2.5212) +2025-08-20,23:55:09 | INFO | Train Epoch: 0 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 1.7068 (2.5035) Boundary_loss: 0.015234 (0.016063) Loss: 1.7220 (2.5196) +2025-08-20,23:56:06 | INFO | Train Epoch: 0 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 1.5781 (2.5016) Boundary_loss: 0.015642 (0.016062) Loss: 1.5937 (2.5177) +2025-08-20,23:57:04 | INFO | Train Epoch: 0 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.496 Boundary Ratio: 0.253 Contrastive_loss: 1.5325 (2.4997) Boundary_loss: 0.015541 (0.016061) Loss: 1.5481 (2.5157) +2025-08-20,23:58:01 | INFO | Train Epoch: 0 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.596 Boundary Ratio: 0.253 Contrastive_loss: 1.5752 (2.4978) Boundary_loss: 0.015564 (0.016060) Loss: 1.5908 (2.5139) +2025-08-20,23:58:59 | INFO | Train Epoch: 0 [25446912/26365952 (97%)] Avg Boundaries (per batch): 47.811 Boundary Ratio: 0.244 Contrastive_loss: 1.6234 (2.4961) Boundary_loss: 0.015613 (0.016059) Loss: 1.6390 (2.5121) +2025-08-20,23:59:56 | INFO | Train Epoch: 0 [25498112/26365952 (97%)] Avg Boundaries (per batch): 47.441 Boundary Ratio: 0.242 Contrastive_loss: 1.6770 (2.4944) Boundary_loss: 0.015673 (0.016058) Loss: 1.6927 (2.5105) +2025-08-21,00:00:54 | INFO | Train Epoch: 0 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 1.6651 (2.4928) Boundary_loss: 0.015487 (0.016057) Loss: 1.6806 (2.5088) +2025-08-21,00:01:51 | INFO | Train Epoch: 0 [25600512/26365952 (97%)] Avg Boundaries (per batch): 49.420 Boundary Ratio: 0.252 Contrastive_loss: 1.7037 (2.4912) Boundary_loss: 0.015586 (0.016056) Loss: 1.7193 (2.5072) +2025-08-21,00:02:49 | INFO | Train Epoch: 0 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.100 Boundary Ratio: 0.245 Contrastive_loss: 1.5647 (2.4893) Boundary_loss: 0.015482 (0.016055) Loss: 1.5802 (2.5054) +2025-08-21,00:03:46 | INFO | Train Epoch: 0 [25702912/26365952 (97%)] Avg Boundaries (per batch): 47.678 Boundary Ratio: 0.243 Contrastive_loss: 1.5810 (2.4875) Boundary_loss: 0.015602 (0.016054) Loss: 1.5966 (2.5036) +2025-08-21,00:04:44 | INFO | Train Epoch: 0 [25754112/26365952 (98%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 1.7880 (2.4861) Boundary_loss: 0.015476 (0.016053) Loss: 1.8034 (2.5022) +2025-08-21,00:05:41 | INFO | Train Epoch: 0 [25805312/26365952 (98%)] Avg Boundaries (per batch): 49.908 Boundary Ratio: 0.255 Contrastive_loss: 1.5119 (2.4842) Boundary_loss: 0.015396 (0.016052) Loss: 1.5273 (2.5003) +2025-08-21,00:06:39 | INFO | Train Epoch: 0 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.6370 (2.4825) Boundary_loss: 0.015500 (0.016051) Loss: 1.6525 (2.4986) +2025-08-21,00:07:36 | INFO | Train Epoch: 0 [25907712/26365952 (98%)] Avg Boundaries (per batch): 47.971 Boundary Ratio: 0.245 Contrastive_loss: 1.4691 (2.4805) Boundary_loss: 0.015666 (0.016050) Loss: 1.4848 (2.4966) +2025-08-21,00:08:34 | INFO | Train Epoch: 0 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 1.4638 (2.4785) Boundary_loss: 0.015479 (0.016049) Loss: 1.4792 (2.4946) +2025-08-21,00:09:31 | INFO | Train Epoch: 0 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 1.6783 (2.4770) Boundary_loss: 0.015444 (0.016048) Loss: 1.6938 (2.4930) +2025-08-21,00:10:29 | INFO | Train Epoch: 0 [26061312/26365952 (99%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 1.5066 (2.4751) Boundary_loss: 0.015438 (0.016046) Loss: 1.5220 (2.4911) +2025-08-21,00:11:26 | INFO | Train Epoch: 0 [26112512/26365952 (99%)] Avg Boundaries (per batch): 49.404 Boundary Ratio: 0.252 Contrastive_loss: 1.6487 (2.4735) Boundary_loss: 0.015480 (0.016045) Loss: 1.6641 (2.4895) +2025-08-21,00:12:24 | INFO | Train Epoch: 0 [26163712/26365952 (99%)] Avg Boundaries (per batch): 49.410 Boundary Ratio: 0.252 Contrastive_loss: 1.7859 (2.4721) Boundary_loss: 0.015335 (0.016044) Loss: 1.8013 (2.4882) +2025-08-21,00:13:21 | INFO | Train Epoch: 0 [26214912/26365952 (99%)] Avg Boundaries (per batch): 47.502 Boundary Ratio: 0.242 Contrastive_loss: 1.4045 (2.4700) Boundary_loss: 0.015657 (0.016043) Loss: 1.4202 (2.4861) +2025-08-21,00:14:19 | INFO | Train Epoch: 0 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 1.5540 (2.4682) Boundary_loss: 0.015470 (0.016042) Loss: 1.5694 (2.4843) +2025-08-21,00:15:16 | INFO | Train Epoch: 0 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 1.7507 (2.4669) Boundary_loss: 0.015653 (0.016041) Loss: 1.7663 (2.4829) +2025-08-21,00:16:11 | INFO | Train Epoch: 0 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 1.7108 (2.4654) Boundary_loss: 0.015484 (0.016040) Loss: 1.7263 (2.4814) +2025-08-21,00:16:11 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-21,00:16:11 | INFO | [Epoch 0] Average Step Time: 0.586s | Average GPU Memory: 32.5 GB +2025-08-21,00:16:11 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-21,00:16:11 | INFO | Starting zero-shot imagenet. +2025-08-21,00:16:11 | INFO | Building zero-shot classifier +2025-08-21,00:16:20 | INFO | Using classifier +2025-08-21,00:17:23 | INFO | Finished zero-shot imagenet. +2025-08-21,00:17:23 | INFO | Eval Epoch: 1 imagenet-zeroshot-val-top1: 0.1249 imagenet-zeroshot-val-top5: 0.2972 +2025-08-21,00:17:24 | INFO | Start epoch 1 +2025-08-21,00:17:26 | INFO | Train Epoch: 1 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 1.4559 (1.4559) Boundary_loss: 0.015410 (0.015410) Loss: 1.4714 (1.4714) +2025-08-21,00:18:23 | INFO | Train Epoch: 1 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.5512 (1.5036) Boundary_loss: 0.015612 (0.015511) Loss: 1.5668 (1.5191) +2025-08-21,00:19:21 | INFO | Train Epoch: 1 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 1.3595 (1.4556) Boundary_loss: 0.015544 (0.015522) Loss: 1.3751 (1.4711) +2025-08-21,00:20:18 | INFO | Train Epoch: 1 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.572 Boundary Ratio: 0.253 Contrastive_loss: 1.5798 (1.4866) Boundary_loss: 0.015553 (0.015530) Loss: 1.5954 (1.5021) +2025-08-21,00:21:15 | INFO | Train Epoch: 1 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.229 Boundary Ratio: 0.246 Contrastive_loss: 1.5023 (1.4898) Boundary_loss: 0.015483 (0.015520) Loss: 1.5178 (1.5053) +2025-08-21,00:22:13 | INFO | Train Epoch: 1 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 1.4902 (1.4898) Boundary_loss: 0.015586 (0.015531) Loss: 1.5058 (1.5054) +2025-08-21,00:23:10 | INFO | Train Epoch: 1 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 49.400 Boundary Ratio: 0.252 Contrastive_loss: 1.6601 (1.5141) Boundary_loss: 0.015649 (0.015548) Loss: 1.6757 (1.5297) +2025-08-21,00:24:08 | INFO | Train Epoch: 1 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 1.5250 (1.5155) Boundary_loss: 0.015446 (0.015535) Loss: 1.5404 (1.5310) +2025-08-21,00:25:05 | INFO | Train Epoch: 1 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 1.4663 (1.5100) Boundary_loss: 0.015613 (0.015544) Loss: 1.4819 (1.5256) +2025-08-21,00:26:03 | INFO | Train Epoch: 1 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 49.424 Boundary Ratio: 0.252 Contrastive_loss: 1.6107 (1.5201) Boundary_loss: 0.015521 (0.015542) Loss: 1.6262 (1.5356) +2025-08-21,00:27:00 | INFO | Train Epoch: 1 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 49.898 Boundary Ratio: 0.255 Contrastive_loss: 1.6659 (1.5334) Boundary_loss: 0.015726 (0.015559) Loss: 1.6817 (1.5489) +2025-08-21,00:27:57 | INFO | Train Epoch: 1 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 49.598 Boundary Ratio: 0.253 Contrastive_loss: 1.4750 (1.5285) Boundary_loss: 0.015550 (0.015558) Loss: 1.4905 (1.5441) +2025-08-21,00:28:55 | INFO | Train Epoch: 1 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 1.4331 (1.5212) Boundary_loss: 0.015420 (0.015547) Loss: 1.4485 (1.5367) +2025-08-21,00:29:52 | INFO | Train Epoch: 1 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 49.668 Boundary Ratio: 0.253 Contrastive_loss: 1.5026 (1.5198) Boundary_loss: 0.015481 (0.015543) Loss: 1.5181 (1.5354) +2025-08-21,00:30:49 | INFO | Train Epoch: 1 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 49.723 Boundary Ratio: 0.254 Contrastive_loss: 1.3727 (1.5100) Boundary_loss: 0.015522 (0.015541) Loss: 1.3882 (1.5256) +2025-08-21,00:31:47 | INFO | Train Epoch: 1 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 1.4918 (1.5089) Boundary_loss: 0.015361 (0.015530) Loss: 1.5071 (1.5244) +2025-08-21,00:32:44 | INFO | Train Epoch: 1 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 49.537 Boundary Ratio: 0.253 Contrastive_loss: 1.4963 (1.5081) Boundary_loss: 0.015557 (0.015532) Loss: 1.5118 (1.5237) +2025-08-21,00:33:41 | INFO | Train Epoch: 1 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.170 Boundary Ratio: 0.246 Contrastive_loss: 1.4877 (1.5070) Boundary_loss: 0.015560 (0.015533) Loss: 1.5033 (1.5225) +2025-08-21,00:34:39 | INFO | Train Epoch: 1 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.092 Boundary Ratio: 0.245 Contrastive_loss: 1.5827 (1.5110) Boundary_loss: 0.015719 (0.015543) Loss: 1.5984 (1.5265) +2025-08-21,00:35:36 | INFO | Train Epoch: 1 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 1.4933 (1.5101) Boundary_loss: 0.015527 (0.015542) Loss: 1.5088 (1.5256) +2025-08-21,00:36:33 | INFO | Train Epoch: 1 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 1.5070 (1.5100) Boundary_loss: 0.015468 (0.015539) Loss: 1.5225 (1.5255) +2025-08-21,00:37:31 | INFO | Train Epoch: 1 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 1.4126 (1.5055) Boundary_loss: 0.015526 (0.015538) Loss: 1.4281 (1.5211) +2025-08-21,00:38:28 | INFO | Train Epoch: 1 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 1.5186 (1.5061) Boundary_loss: 0.015523 (0.015537) Loss: 1.5341 (1.5216) +2025-08-21,00:39:26 | INFO | Train Epoch: 1 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.316 Boundary Ratio: 0.247 Contrastive_loss: 1.6945 (1.5140) Boundary_loss: 0.015616 (0.015541) Loss: 1.7101 (1.5295) +2025-08-21,00:40:23 | INFO | Train Epoch: 1 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 47.900 Boundary Ratio: 0.244 Contrastive_loss: 1.6554 (1.5196) Boundary_loss: 0.015380 (0.015534) Loss: 1.6708 (1.5351) +2025-08-21,00:41:21 | INFO | Train Epoch: 1 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 1.6276 (1.5238) Boundary_loss: 0.015423 (0.015530) Loss: 1.6430 (1.5393) +2025-08-21,00:42:18 | INFO | Train Epoch: 1 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 47.600 Boundary Ratio: 0.243 Contrastive_loss: 1.5008 (1.5229) Boundary_loss: 0.015436 (0.015526) Loss: 1.5162 (1.5384) +2025-08-21,00:43:16 | INFO | Train Epoch: 1 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 47.705 Boundary Ratio: 0.243 Contrastive_loss: 1.5058 (1.5223) Boundary_loss: 0.015610 (0.015529) Loss: 1.5214 (1.5378) +2025-08-21,00:44:14 | INFO | Train Epoch: 1 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 1.5119 (1.5219) Boundary_loss: 0.015342 (0.015523) Loss: 1.5273 (1.5375) +2025-08-21,00:45:11 | INFO | Train Epoch: 1 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.4926 (1.5210) Boundary_loss: 0.015512 (0.015523) Loss: 1.5081 (1.5365) +2025-08-21,00:46:08 | INFO | Train Epoch: 1 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.5851 (1.5230) Boundary_loss: 0.015555 (0.015524) Loss: 1.6007 (1.5386) +2025-08-21,00:47:06 | INFO | Train Epoch: 1 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.068 Boundary Ratio: 0.245 Contrastive_loss: 1.5314 (1.5233) Boundary_loss: 0.015617 (0.015527) Loss: 1.5470 (1.5388) +2025-08-21,00:48:04 | INFO | Train Epoch: 1 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 1.6107 (1.5259) Boundary_loss: 0.015436 (0.015524) Loss: 1.6261 (1.5415) +2025-08-21,00:49:01 | INFO | Train Epoch: 1 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.174 Boundary Ratio: 0.246 Contrastive_loss: 1.5211 (1.5258) Boundary_loss: 0.015833 (0.015533) Loss: 1.5369 (1.5413) +2025-08-21,00:49:59 | INFO | Train Epoch: 1 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 1.5936 (1.5277) Boundary_loss: 0.015607 (0.015535) Loss: 1.6093 (1.5433) +2025-08-21,00:50:56 | INFO | Train Epoch: 1 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 1.4263 (1.5249) Boundary_loss: 0.015499 (0.015534) Loss: 1.4418 (1.5405) +2025-08-21,00:51:54 | INFO | Train Epoch: 1 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 49.604 Boundary Ratio: 0.253 Contrastive_loss: 1.4515 (1.5229) Boundary_loss: 0.015746 (0.015540) Loss: 1.4673 (1.5385) +2025-08-21,00:52:51 | INFO | Train Epoch: 1 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 49.574 Boundary Ratio: 0.253 Contrastive_loss: 1.5182 (1.5228) Boundary_loss: 0.015612 (0.015542) Loss: 1.5339 (1.5384) +2025-08-21,00:53:49 | INFO | Train Epoch: 1 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 1.4830 (1.5218) Boundary_loss: 0.015382 (0.015538) Loss: 1.4984 (1.5373) +2025-08-21,00:54:46 | INFO | Train Epoch: 1 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 49.742 Boundary Ratio: 0.254 Contrastive_loss: 1.6283 (1.5245) Boundary_loss: 0.015492 (0.015536) Loss: 1.6438 (1.5400) +2025-08-21,00:55:44 | INFO | Train Epoch: 1 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 47.848 Boundary Ratio: 0.244 Contrastive_loss: 1.5098 (1.5241) Boundary_loss: 0.015295 (0.015531) Loss: 1.5251 (1.5396) +2025-08-21,00:56:42 | INFO | Train Epoch: 1 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 49.689 Boundary Ratio: 0.254 Contrastive_loss: 1.5642 (1.5251) Boundary_loss: 0.015474 (0.015529) Loss: 1.5797 (1.5406) +2025-08-21,00:57:39 | INFO | Train Epoch: 1 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 1.4359 (1.5230) Boundary_loss: 0.015518 (0.015529) Loss: 1.4514 (1.5385) +2025-08-21,00:58:37 | INFO | Train Epoch: 1 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 49.691 Boundary Ratio: 0.254 Contrastive_loss: 1.4643 (1.5216) Boundary_loss: 0.015563 (0.015530) Loss: 1.4799 (1.5372) +2025-08-21,00:59:34 | INFO | Train Epoch: 1 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 49.467 Boundary Ratio: 0.252 Contrastive_loss: 1.4209 (1.5194) Boundary_loss: 0.015435 (0.015528) Loss: 1.4364 (1.5349) +2025-08-21,01:00:32 | INFO | Train Epoch: 1 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 47.639 Boundary Ratio: 0.243 Contrastive_loss: 1.6330 (1.5219) Boundary_loss: 0.015579 (0.015529) Loss: 1.6486 (1.5374) +2025-08-21,01:01:29 | INFO | Train Epoch: 1 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 1.4854 (1.5211) Boundary_loss: 0.015434 (0.015527) Loss: 1.5008 (1.5366) +2025-08-21,01:02:27 | INFO | Train Epoch: 1 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 49.357 Boundary Ratio: 0.252 Contrastive_loss: 1.3546 (1.5176) Boundary_loss: 0.015503 (0.015526) Loss: 1.3702 (1.5332) +2025-08-21,01:03:24 | INFO | Train Epoch: 1 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 1.4261 (1.5158) Boundary_loss: 0.015525 (0.015526) Loss: 1.4417 (1.5313) +2025-08-21,01:04:22 | INFO | Train Epoch: 1 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 1.6434 (1.5183) Boundary_loss: 0.015212 (0.015520) Loss: 1.6587 (1.5338) +2025-08-21,01:05:20 | INFO | Train Epoch: 1 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 1.6195 (1.5203) Boundary_loss: 0.015500 (0.015520) Loss: 1.6350 (1.5358) +2025-08-21,01:06:17 | INFO | Train Epoch: 1 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 1.4880 (1.5197) Boundary_loss: 0.015357 (0.015516) Loss: 1.5034 (1.5352) +2025-08-21,01:07:14 | INFO | Train Epoch: 1 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 49.295 Boundary Ratio: 0.252 Contrastive_loss: 1.4680 (1.5187) Boundary_loss: 0.015419 (0.015515) Loss: 1.4834 (1.5342) +2025-08-21,01:08:12 | INFO | Train Epoch: 1 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 1.5084 (1.5185) Boundary_loss: 0.015506 (0.015514) Loss: 1.5240 (1.5340) +2025-08-21,01:09:09 | INFO | Train Epoch: 1 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 1.5182 (1.5185) Boundary_loss: 0.015552 (0.015515) Loss: 1.5338 (1.5340) +2025-08-21,01:10:07 | INFO | Train Epoch: 1 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 47.422 Boundary Ratio: 0.242 Contrastive_loss: 1.4873 (1.5180) Boundary_loss: 0.015566 (0.015516) Loss: 1.5029 (1.5335) +2025-08-21,01:11:04 | INFO | Train Epoch: 1 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 1.4514 (1.5168) Boundary_loss: 0.015352 (0.015513) Loss: 1.4667 (1.5323) +2025-08-21,01:12:02 | INFO | Train Epoch: 1 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.158 Boundary Ratio: 0.246 Contrastive_loss: 1.5622 (1.5176) Boundary_loss: 0.015606 (0.015515) Loss: 1.5778 (1.5331) +2025-08-21,01:12:59 | INFO | Train Epoch: 1 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 1.5848 (1.5187) Boundary_loss: 0.015500 (0.015515) Loss: 1.6003 (1.5342) +2025-08-21,01:13:57 | INFO | Train Epoch: 1 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 1.4199 (1.5171) Boundary_loss: 0.015358 (0.015512) Loss: 1.4353 (1.5326) +2025-08-21,01:14:54 | INFO | Train Epoch: 1 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 1.3237 (1.5139) Boundary_loss: 0.015431 (0.015511) Loss: 1.3392 (1.5294) +2025-08-21,01:15:52 | INFO | Train Epoch: 1 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 47.727 Boundary Ratio: 0.244 Contrastive_loss: 1.3818 (1.5118) Boundary_loss: 0.015367 (0.015508) Loss: 1.3972 (1.5273) +2025-08-21,01:16:49 | INFO | Train Epoch: 1 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 1.4827 (1.5113) Boundary_loss: 0.015474 (0.015508) Loss: 1.4982 (1.5268) +2025-08-21,01:17:46 | INFO | Train Epoch: 1 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 1.4418 (1.5102) Boundary_loss: 0.015278 (0.015504) Loss: 1.4571 (1.5257) +2025-08-21,01:18:44 | INFO | Train Epoch: 1 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 1.4254 (1.5089) Boundary_loss: 0.015369 (0.015502) Loss: 1.4408 (1.5244) +2025-08-21,01:19:41 | INFO | Train Epoch: 1 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 47.842 Boundary Ratio: 0.244 Contrastive_loss: 1.3446 (1.5064) Boundary_loss: 0.015617 (0.015504) Loss: 1.3602 (1.5219) +2025-08-21,01:20:38 | INFO | Train Epoch: 1 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.221 Boundary Ratio: 0.246 Contrastive_loss: 1.5148 (1.5065) Boundary_loss: 0.015447 (0.015503) Loss: 1.5303 (1.5220) +2025-08-21,01:21:36 | INFO | Train Epoch: 1 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.600 Boundary Ratio: 0.253 Contrastive_loss: 1.3947 (1.5049) Boundary_loss: 0.015619 (0.015505) Loss: 1.4103 (1.5204) +2025-08-21,01:22:34 | INFO | Train Epoch: 1 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 1.3203 (1.5022) Boundary_loss: 0.015520 (0.015505) Loss: 1.3358 (1.5177) +2025-08-21,01:23:31 | INFO | Train Epoch: 1 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 49.580 Boundary Ratio: 0.253 Contrastive_loss: 1.4007 (1.5008) Boundary_loss: 0.015444 (0.015504) Loss: 1.4161 (1.5163) +2025-08-21,01:24:29 | INFO | Train Epoch: 1 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 47.953 Boundary Ratio: 0.245 Contrastive_loss: 1.4378 (1.4999) Boundary_loss: 0.015450 (0.015503) Loss: 1.4533 (1.5154) +2025-08-21,01:25:26 | INFO | Train Epoch: 1 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 1.4441 (1.4991) Boundary_loss: 0.015431 (0.015502) Loss: 1.4595 (1.5146) +2025-08-21,01:26:24 | INFO | Train Epoch: 1 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.375 Boundary Ratio: 0.247 Contrastive_loss: 1.5214 (1.4994) Boundary_loss: 0.015557 (0.015503) Loss: 1.5369 (1.5149) +2025-08-21,01:27:22 | INFO | Train Epoch: 1 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 1.4515 (1.4988) Boundary_loss: 0.015370 (0.015501) Loss: 1.4668 (1.5143) +2025-08-21,01:28:19 | INFO | Train Epoch: 1 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 1.3780 (1.4972) Boundary_loss: 0.015405 (0.015500) Loss: 1.3934 (1.5127) +2025-08-21,01:29:16 | INFO | Train Epoch: 1 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 1.3344 (1.4950) Boundary_loss: 0.015348 (0.015498) Loss: 1.3497 (1.5105) +2025-08-21,01:30:14 | INFO | Train Epoch: 1 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 1.3537 (1.4932) Boundary_loss: 0.015712 (0.015501) Loss: 1.3694 (1.5087) +2025-08-21,01:31:12 | INFO | Train Epoch: 1 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 1.4056 (1.4921) Boundary_loss: 0.015481 (0.015500) Loss: 1.4211 (1.5076) +2025-08-21,01:32:09 | INFO | Train Epoch: 1 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.217 Boundary Ratio: 0.246 Contrastive_loss: 1.3520 (1.4903) Boundary_loss: 0.015412 (0.015499) Loss: 1.3674 (1.5058) +2025-08-21,01:33:07 | INFO | Train Epoch: 1 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 49.863 Boundary Ratio: 0.254 Contrastive_loss: 1.3381 (1.4884) Boundary_loss: 0.015620 (0.015501) Loss: 1.3537 (1.5039) +2025-08-21,01:34:04 | INFO | Train Epoch: 1 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 47.355 Boundary Ratio: 0.242 Contrastive_loss: 1.4475 (1.4879) Boundary_loss: 0.015370 (0.015499) Loss: 1.4629 (1.5034) +2025-08-21,01:35:02 | INFO | Train Epoch: 1 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 1.4713 (1.4877) Boundary_loss: 0.015290 (0.015497) Loss: 1.4865 (1.5032) +2025-08-21,01:35:59 | INFO | Train Epoch: 1 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 49.277 Boundary Ratio: 0.251 Contrastive_loss: 1.4540 (1.4873) Boundary_loss: 0.015509 (0.015497) Loss: 1.4695 (1.5028) +2025-08-21,01:36:57 | INFO | Train Epoch: 1 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.154 Boundary Ratio: 0.246 Contrastive_loss: 1.3394 (1.4855) Boundary_loss: 0.015323 (0.015495) Loss: 1.3547 (1.5010) +2025-08-21,01:37:54 | INFO | Train Epoch: 1 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 49.555 Boundary Ratio: 0.253 Contrastive_loss: 1.5054 (1.4857) Boundary_loss: 0.015711 (0.015497) Loss: 1.5211 (1.5012) +2025-08-21,01:38:52 | INFO | Train Epoch: 1 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 1.3604 (1.4843) Boundary_loss: 0.015529 (0.015498) Loss: 1.3759 (1.4998) +2025-08-21,01:39:49 | INFO | Train Epoch: 1 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.883 Boundary Ratio: 0.255 Contrastive_loss: 1.5248 (1.4848) Boundary_loss: 0.015589 (0.015499) Loss: 1.5404 (1.5003) +2025-08-21,01:40:47 | INFO | Train Epoch: 1 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 1.4830 (1.4847) Boundary_loss: 0.015339 (0.015497) Loss: 1.4984 (1.5002) +2025-08-21,01:41:44 | INFO | Train Epoch: 1 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.000 Boundary Ratio: 0.245 Contrastive_loss: 1.3114 (1.4828) Boundary_loss: 0.015450 (0.015496) Loss: 1.3268 (1.4983) +2025-08-21,01:42:41 | INFO | Train Epoch: 1 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 1.4965 (1.4829) Boundary_loss: 0.015650 (0.015498) Loss: 1.5121 (1.4984) +2025-08-21,01:43:39 | INFO | Train Epoch: 1 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 47.898 Boundary Ratio: 0.244 Contrastive_loss: 1.3962 (1.4820) Boundary_loss: 0.015529 (0.015498) Loss: 1.4118 (1.4975) +2025-08-21,01:44:36 | INFO | Train Epoch: 1 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.068 Boundary Ratio: 0.245 Contrastive_loss: 1.3178 (1.4802) Boundary_loss: 0.015471 (0.015498) Loss: 1.3333 (1.4957) +2025-08-21,01:45:33 | INFO | Train Epoch: 1 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 1.3754 (1.4791) Boundary_loss: 0.015669 (0.015500) Loss: 1.3911 (1.4946) +2025-08-21,01:46:31 | INFO | Train Epoch: 1 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 47.533 Boundary Ratio: 0.243 Contrastive_loss: 1.3983 (1.4782) Boundary_loss: 0.015764 (0.015503) Loss: 1.4141 (1.4937) +2025-08-21,01:47:29 | INFO | Train Epoch: 1 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 1.3911 (1.4773) Boundary_loss: 0.015487 (0.015503) Loss: 1.4066 (1.4928) +2025-08-21,01:48:26 | INFO | Train Epoch: 1 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 1.3280 (1.4757) Boundary_loss: 0.015490 (0.015502) Loss: 1.3435 (1.4912) +2025-08-21,01:49:24 | INFO | Train Epoch: 1 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 1.4731 (1.4757) Boundary_loss: 0.015387 (0.015501) Loss: 1.4885 (1.4912) +2025-08-21,01:50:21 | INFO | Train Epoch: 1 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 1.4865 (1.4758) Boundary_loss: 0.015470 (0.015501) Loss: 1.5020 (1.4913) +2025-08-21,01:51:18 | INFO | Train Epoch: 1 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 1.2671 (1.4737) Boundary_loss: 0.015386 (0.015500) Loss: 1.2824 (1.4892) +2025-08-21,01:52:16 | INFO | Train Epoch: 1 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 1.3260 (1.4722) Boundary_loss: 0.015370 (0.015498) Loss: 1.3414 (1.4877) +2025-08-21,01:53:13 | INFO | Train Epoch: 1 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 1.4725 (1.4722) Boundary_loss: 0.015290 (0.015496) Loss: 1.4878 (1.4877) +2025-08-21,01:54:11 | INFO | Train Epoch: 1 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.115 Boundary Ratio: 0.245 Contrastive_loss: 1.4966 (1.4725) Boundary_loss: 0.015325 (0.015495) Loss: 1.5119 (1.4880) +2025-08-21,01:55:08 | INFO | Train Epoch: 1 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 1.2753 (1.4706) Boundary_loss: 0.015340 (0.015493) Loss: 1.2906 (1.4861) +2025-08-21,01:56:05 | INFO | Train Epoch: 1 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 49.578 Boundary Ratio: 0.253 Contrastive_loss: 1.4099 (1.4700) Boundary_loss: 0.015616 (0.015494) Loss: 1.4255 (1.4855) +2025-08-21,01:57:03 | INFO | Train Epoch: 1 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.2715 (1.4681) Boundary_loss: 0.015362 (0.015493) Loss: 1.2868 (1.4836) +2025-08-21,01:58:00 | INFO | Train Epoch: 1 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.3760 (1.4672) Boundary_loss: 0.015490 (0.015493) Loss: 1.3914 (1.4827) +2025-08-21,01:58:58 | INFO | Train Epoch: 1 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.133 Boundary Ratio: 0.246 Contrastive_loss: 1.3741 (1.4664) Boundary_loss: 0.015619 (0.015494) Loss: 1.3897 (1.4818) +2025-08-21,01:59:55 | INFO | Train Epoch: 1 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.3807 (1.4656) Boundary_loss: 0.015591 (0.015495) Loss: 1.3963 (1.4811) +2025-08-21,02:00:53 | INFO | Train Epoch: 1 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.080 Boundary Ratio: 0.245 Contrastive_loss: 1.2668 (1.4637) Boundary_loss: 0.015474 (0.015495) Loss: 1.2823 (1.4792) +2025-08-21,02:01:50 | INFO | Train Epoch: 1 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.053 Boundary Ratio: 0.245 Contrastive_loss: 1.4146 (1.4633) Boundary_loss: 0.015567 (0.015496) Loss: 1.4302 (1.4788) +2025-08-21,02:02:47 | INFO | Train Epoch: 1 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.3399 (1.4622) Boundary_loss: 0.015388 (0.015495) Loss: 1.3553 (1.4777) +2025-08-21,02:03:45 | INFO | Train Epoch: 1 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 1.5415 (1.4629) Boundary_loss: 0.015600 (0.015496) Loss: 1.5571 (1.4784) +2025-08-21,02:04:42 | INFO | Train Epoch: 1 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 1.2003 (1.4606) Boundary_loss: 0.015297 (0.015494) Loss: 1.2156 (1.4761) +2025-08-21,02:05:40 | INFO | Train Epoch: 1 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 1.3611 (1.4597) Boundary_loss: 0.015481 (0.015494) Loss: 1.3766 (1.4752) +2025-08-21,02:06:38 | INFO | Train Epoch: 1 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 1.3755 (1.4590) Boundary_loss: 0.015604 (0.015495) Loss: 1.3911 (1.4744) +2025-08-21,02:07:35 | INFO | Train Epoch: 1 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 1.3319 (1.4579) Boundary_loss: 0.015608 (0.015496) Loss: 1.3475 (1.4734) +2025-08-21,02:08:33 | INFO | Train Epoch: 1 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 1.4595 (1.4579) Boundary_loss: 0.015587 (0.015496) Loss: 1.4751 (1.4734) +2025-08-21,02:09:30 | INFO | Train Epoch: 1 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 1.4522 (1.4578) Boundary_loss: 0.015469 (0.015496) Loss: 1.4676 (1.4733) +2025-08-21,02:10:28 | INFO | Train Epoch: 1 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.3335 (1.4568) Boundary_loss: 0.015416 (0.015496) Loss: 1.3489 (1.4723) +2025-08-21,02:11:25 | INFO | Train Epoch: 1 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.018 Boundary Ratio: 0.245 Contrastive_loss: 1.4856 (1.4570) Boundary_loss: 0.015515 (0.015496) Loss: 1.5011 (1.4725) +2025-08-21,02:12:23 | INFO | Train Epoch: 1 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 49.723 Boundary Ratio: 0.254 Contrastive_loss: 1.2946 (1.4557) Boundary_loss: 0.015603 (0.015497) Loss: 1.3102 (1.4712) +2025-08-21,02:13:20 | INFO | Train Epoch: 1 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 1.3356 (1.4547) Boundary_loss: 0.015723 (0.015498) Loss: 1.3513 (1.4702) +2025-08-21,02:14:17 | INFO | Train Epoch: 1 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.389 Boundary Ratio: 0.247 Contrastive_loss: 1.3917 (1.4542) Boundary_loss: 0.015429 (0.015498) Loss: 1.4071 (1.4697) +2025-08-21,02:15:15 | INFO | Train Epoch: 1 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.268 Boundary Ratio: 0.246 Contrastive_loss: 1.4228 (1.4539) Boundary_loss: 0.015681 (0.015499) Loss: 1.4385 (1.4694) +2025-08-21,02:16:12 | INFO | Train Epoch: 1 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 1.4554 (1.4539) Boundary_loss: 0.015523 (0.015500) Loss: 1.4709 (1.4694) +2025-08-21,02:17:10 | INFO | Train Epoch: 1 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 1.3181 (1.4529) Boundary_loss: 0.015450 (0.015499) Loss: 1.3336 (1.4684) +2025-08-21,02:18:07 | INFO | Train Epoch: 1 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.152 Boundary Ratio: 0.246 Contrastive_loss: 1.3597 (1.4521) Boundary_loss: 0.015442 (0.015499) Loss: 1.3751 (1.4676) +2025-08-21,02:19:05 | INFO | Train Epoch: 1 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 1.3429 (1.4513) Boundary_loss: 0.015390 (0.015498) Loss: 1.3583 (1.4668) +2025-08-21,02:20:02 | INFO | Train Epoch: 1 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 1.3884 (1.4508) Boundary_loss: 0.015544 (0.015498) Loss: 1.4040 (1.4663) +2025-08-21,02:21:00 | INFO | Train Epoch: 1 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 1.3988 (1.4504) Boundary_loss: 0.015361 (0.015497) Loss: 1.4141 (1.4659) +2025-08-21,02:21:57 | INFO | Train Epoch: 1 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 1.2102 (1.4486) Boundary_loss: 0.015628 (0.015498) Loss: 1.2259 (1.4641) +2025-08-21,02:22:55 | INFO | Train Epoch: 1 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 47.295 Boundary Ratio: 0.241 Contrastive_loss: 1.2770 (1.4473) Boundary_loss: 0.015553 (0.015499) Loss: 1.2926 (1.4628) +2025-08-21,02:23:52 | INFO | Train Epoch: 1 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 1.3649 (1.4466) Boundary_loss: 0.015505 (0.015499) Loss: 1.3804 (1.4621) +2025-08-21,02:24:49 | INFO | Train Epoch: 1 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 1.4741 (1.4468) Boundary_loss: 0.015517 (0.015499) Loss: 1.4896 (1.4623) +2025-08-21,02:25:47 | INFO | Train Epoch: 1 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.3278 (1.4460) Boundary_loss: 0.015541 (0.015499) Loss: 1.3434 (1.4615) +2025-08-21,02:26:44 | INFO | Train Epoch: 1 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 49.209 Boundary Ratio: 0.251 Contrastive_loss: 1.3987 (1.4456) Boundary_loss: 0.015668 (0.015500) Loss: 1.4144 (1.4611) +2025-08-21,02:27:42 | INFO | Train Epoch: 1 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 50.100 Boundary Ratio: 0.256 Contrastive_loss: 1.3190 (1.4447) Boundary_loss: 0.015547 (0.015501) Loss: 1.3346 (1.4602) +2025-08-21,02:28:39 | INFO | Train Epoch: 1 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.621 Boundary Ratio: 0.253 Contrastive_loss: 1.4098 (1.4444) Boundary_loss: 0.015551 (0.015501) Loss: 1.4254 (1.4599) +2025-08-21,02:29:37 | INFO | Train Epoch: 1 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 1.2068 (1.4427) Boundary_loss: 0.015416 (0.015500) Loss: 1.2222 (1.4582) +2025-08-21,02:30:34 | INFO | Train Epoch: 1 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 1.2713 (1.4415) Boundary_loss: 0.015514 (0.015501) Loss: 1.2868 (1.4570) +2025-08-21,02:31:31 | INFO | Train Epoch: 1 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 47.332 Boundary Ratio: 0.241 Contrastive_loss: 1.4162 (1.4413) Boundary_loss: 0.015564 (0.015501) Loss: 1.4318 (1.4568) +2025-08-21,02:32:29 | INFO | Train Epoch: 1 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 1.3495 (1.4407) Boundary_loss: 0.015399 (0.015500) Loss: 1.3649 (1.4562) +2025-08-21,02:33:26 | INFO | Train Epoch: 1 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 1.2375 (1.4393) Boundary_loss: 0.015494 (0.015500) Loss: 1.2530 (1.4548) +2025-08-21,02:34:24 | INFO | Train Epoch: 1 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 1.2952 (1.4383) Boundary_loss: 0.015506 (0.015500) Loss: 1.3107 (1.4538) +2025-08-21,02:35:21 | INFO | Train Epoch: 1 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 1.3934 (1.4379) Boundary_loss: 0.015378 (0.015499) Loss: 1.4088 (1.4534) +2025-08-21,02:36:19 | INFO | Train Epoch: 1 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 1.4173 (1.4378) Boundary_loss: 0.015398 (0.015499) Loss: 1.4327 (1.4533) +2025-08-21,02:37:16 | INFO | Train Epoch: 1 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.457 Boundary Ratio: 0.247 Contrastive_loss: 1.1717 (1.4360) Boundary_loss: 0.015638 (0.015500) Loss: 1.1873 (1.4515) +2025-08-21,02:38:13 | INFO | Train Epoch: 1 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 1.4206 (1.4359) Boundary_loss: 0.015412 (0.015499) Loss: 1.4360 (1.4514) +2025-08-21,02:39:11 | INFO | Train Epoch: 1 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.883 Boundary Ratio: 0.255 Contrastive_loss: 1.4065 (1.4357) Boundary_loss: 0.015642 (0.015500) Loss: 1.4221 (1.4512) +2025-08-21,02:40:08 | INFO | Train Epoch: 1 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.4218 (1.4356) Boundary_loss: 0.015331 (0.015499) Loss: 1.4371 (1.4511) +2025-08-21,02:41:06 | INFO | Train Epoch: 1 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 1.2748 (1.4345) Boundary_loss: 0.015468 (0.015499) Loss: 1.2902 (1.4500) +2025-08-21,02:42:03 | INFO | Train Epoch: 1 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 1.2069 (1.4330) Boundary_loss: 0.015284 (0.015497) Loss: 1.2222 (1.4485) +2025-08-21,02:43:01 | INFO | Train Epoch: 1 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 49.736 Boundary Ratio: 0.254 Contrastive_loss: 1.3334 (1.4324) Boundary_loss: 0.015430 (0.015497) Loss: 1.3488 (1.4479) +2025-08-21,02:43:58 | INFO | Train Epoch: 1 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 1.3665 (1.4320) Boundary_loss: 0.015492 (0.015497) Loss: 1.3820 (1.4475) +2025-08-21,02:44:56 | INFO | Train Epoch: 1 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 49.777 Boundary Ratio: 0.254 Contrastive_loss: 1.3409 (1.4314) Boundary_loss: 0.015523 (0.015497) Loss: 1.3565 (1.4469) +2025-08-21,02:45:53 | INFO | Train Epoch: 1 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.203 Boundary Ratio: 0.246 Contrastive_loss: 1.4792 (1.4317) Boundary_loss: 0.015345 (0.015496) Loss: 1.4946 (1.4472) +2025-08-21,02:46:51 | INFO | Train Epoch: 1 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 49.879 Boundary Ratio: 0.254 Contrastive_loss: 1.3720 (1.4313) Boundary_loss: 0.015572 (0.015496) Loss: 1.3875 (1.4468) +2025-08-21,02:47:48 | INFO | Train Epoch: 1 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 49.414 Boundary Ratio: 0.252 Contrastive_loss: 1.2736 (1.4303) Boundary_loss: 0.015370 (0.015496) Loss: 1.2890 (1.4458) +2025-08-21,02:48:45 | INFO | Train Epoch: 1 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 1.4016 (1.4301) Boundary_loss: 0.015409 (0.015495) Loss: 1.4170 (1.4456) +2025-08-21,02:49:43 | INFO | Train Epoch: 1 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 1.2879 (1.4292) Boundary_loss: 0.015380 (0.015494) Loss: 1.3033 (1.4447) +2025-08-21,02:50:40 | INFO | Train Epoch: 1 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 1.3546 (1.4288) Boundary_loss: 0.015531 (0.015495) Loss: 1.3701 (1.4443) +2025-08-21,02:51:38 | INFO | Train Epoch: 1 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.504 Boundary Ratio: 0.253 Contrastive_loss: 1.3719 (1.4284) Boundary_loss: 0.015350 (0.015494) Loss: 1.3873 (1.4439) +2025-08-21,02:52:35 | INFO | Train Epoch: 1 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 47.463 Boundary Ratio: 0.242 Contrastive_loss: 1.2299 (1.4272) Boundary_loss: 0.015528 (0.015494) Loss: 1.2455 (1.4427) +2025-08-21,02:53:33 | INFO | Train Epoch: 1 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 1.4664 (1.4274) Boundary_loss: 0.015622 (0.015495) Loss: 1.4820 (1.4429) +2025-08-21,02:54:30 | INFO | Train Epoch: 1 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.219 Boundary Ratio: 0.246 Contrastive_loss: 1.3107 (1.4267) Boundary_loss: 0.015512 (0.015495) Loss: 1.3262 (1.4422) +2025-08-21,02:55:27 | INFO | Train Epoch: 1 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 1.3977 (1.4266) Boundary_loss: 0.015448 (0.015495) Loss: 1.4132 (1.4420) +2025-08-21,02:56:25 | INFO | Train Epoch: 1 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 50.031 Boundary Ratio: 0.255 Contrastive_loss: 1.3628 (1.4262) Boundary_loss: 0.015510 (0.015495) Loss: 1.3783 (1.4417) +2025-08-21,02:57:22 | INFO | Train Epoch: 1 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 47.580 Boundary Ratio: 0.243 Contrastive_loss: 1.1989 (1.4248) Boundary_loss: 0.015556 (0.015495) Loss: 1.2145 (1.4403) +2025-08-21,02:58:20 | INFO | Train Epoch: 1 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 1.2053 (1.4235) Boundary_loss: 0.015557 (0.015495) Loss: 1.2209 (1.4390) +2025-08-21,02:59:17 | INFO | Train Epoch: 1 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 1.3496 (1.4231) Boundary_loss: 0.015439 (0.015495) Loss: 1.3651 (1.4386) +2025-08-21,03:00:14 | INFO | Train Epoch: 1 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 1.3080 (1.4224) Boundary_loss: 0.015281 (0.015494) Loss: 1.3233 (1.4379) +2025-08-21,03:01:11 | INFO | Train Epoch: 1 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 1.3562 (1.4220) Boundary_loss: 0.015725 (0.015495) Loss: 1.3719 (1.4375) +2025-08-21,03:02:09 | INFO | Train Epoch: 1 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 1.2784 (1.4212) Boundary_loss: 0.015540 (0.015495) Loss: 1.2939 (1.4367) +2025-08-21,03:03:06 | INFO | Train Epoch: 1 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.3701 (1.4209) Boundary_loss: 0.015650 (0.015496) Loss: 1.3858 (1.4364) +2025-08-21,03:04:03 | INFO | Train Epoch: 1 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 1.3743 (1.4206) Boundary_loss: 0.015462 (0.015496) Loss: 1.3897 (1.4361) +2025-08-21,03:05:01 | INFO | Train Epoch: 1 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 1.4164 (1.4206) Boundary_loss: 0.015467 (0.015496) Loss: 1.4319 (1.4361) +2025-08-21,03:05:58 | INFO | Train Epoch: 1 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 1.3200 (1.4200) Boundary_loss: 0.015345 (0.015495) Loss: 1.3353 (1.4355) +2025-08-21,03:06:55 | INFO | Train Epoch: 1 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 1.2983 (1.4194) Boundary_loss: 0.015388 (0.015494) Loss: 1.3137 (1.4349) +2025-08-21,03:07:52 | INFO | Train Epoch: 1 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.457 Boundary Ratio: 0.247 Contrastive_loss: 1.2642 (1.4185) Boundary_loss: 0.015386 (0.015494) Loss: 1.2796 (1.4340) +2025-08-21,03:08:50 | INFO | Train Epoch: 1 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 1.3602 (1.4182) Boundary_loss: 0.015541 (0.015494) Loss: 1.3758 (1.4337) +2025-08-21,03:09:47 | INFO | Train Epoch: 1 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 1.3416 (1.4177) Boundary_loss: 0.015519 (0.015494) Loss: 1.3571 (1.4332) +2025-08-21,03:10:45 | INFO | Train Epoch: 1 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 1.4332 (1.4178) Boundary_loss: 0.015698 (0.015495) Loss: 1.4489 (1.4333) +2025-08-21,03:11:42 | INFO | Train Epoch: 1 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 49.623 Boundary Ratio: 0.253 Contrastive_loss: 1.3921 (1.4177) Boundary_loss: 0.015477 (0.015495) Loss: 1.4075 (1.4332) +2025-08-21,03:12:39 | INFO | Train Epoch: 1 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 1.0361 (1.4156) Boundary_loss: 0.015447 (0.015495) Loss: 1.0515 (1.4311) +2025-08-21,03:13:37 | INFO | Train Epoch: 1 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 1.3992 (1.4155) Boundary_loss: 0.015613 (0.015496) Loss: 1.4148 (1.4310) +2025-08-21,03:14:34 | INFO | Train Epoch: 1 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 1.3813 (1.4153) Boundary_loss: 0.015583 (0.015496) Loss: 1.3969 (1.4308) +2025-08-21,03:15:32 | INFO | Train Epoch: 1 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 1.3691 (1.4151) Boundary_loss: 0.015412 (0.015496) Loss: 1.3845 (1.4306) +2025-08-21,03:16:29 | INFO | Train Epoch: 1 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 1.0697 (1.4133) Boundary_loss: 0.015335 (0.015495) Loss: 1.0850 (1.4288) +2025-08-21,03:17:26 | INFO | Train Epoch: 1 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 49.355 Boundary Ratio: 0.252 Contrastive_loss: 1.3235 (1.4128) Boundary_loss: 0.015427 (0.015494) Loss: 1.3390 (1.4283) +2025-08-21,03:18:24 | INFO | Train Epoch: 1 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 1.3402 (1.4124) Boundary_loss: 0.015443 (0.015494) Loss: 1.3557 (1.4279) +2025-08-21,03:19:22 | INFO | Train Epoch: 1 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.619 Boundary Ratio: 0.253 Contrastive_loss: 1.2311 (1.4115) Boundary_loss: 0.015401 (0.015494) Loss: 1.2465 (1.4269) +2025-08-21,03:20:19 | INFO | Train Epoch: 1 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 49.680 Boundary Ratio: 0.253 Contrastive_loss: 1.3322 (1.4110) Boundary_loss: 0.015599 (0.015494) Loss: 1.3478 (1.4265) +2025-08-21,03:21:17 | INFO | Train Epoch: 1 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 47.713 Boundary Ratio: 0.243 Contrastive_loss: 1.2268 (1.4101) Boundary_loss: 0.015497 (0.015494) Loss: 1.2423 (1.4256) +2025-08-21,03:22:14 | INFO | Train Epoch: 1 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 1.4439 (1.4103) Boundary_loss: 0.015407 (0.015494) Loss: 1.4593 (1.4258) +2025-08-21,03:23:12 | INFO | Train Epoch: 1 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 1.4114 (1.4103) Boundary_loss: 0.015354 (0.015493) Loss: 1.4268 (1.4258) +2025-08-21,03:24:09 | INFO | Train Epoch: 1 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 1.4516 (1.4105) Boundary_loss: 0.015457 (0.015493) Loss: 1.4671 (1.4260) +2025-08-21,03:25:07 | INFO | Train Epoch: 1 [10035712/26365952 (38%)] Avg Boundaries (per batch): 47.744 Boundary Ratio: 0.244 Contrastive_loss: 1.1431 (1.4091) Boundary_loss: 0.015498 (0.015493) Loss: 1.1586 (1.4246) +2025-08-21,03:26:04 | INFO | Train Epoch: 1 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 1.4807 (1.4095) Boundary_loss: 0.015385 (0.015492) Loss: 1.4961 (1.4250) +2025-08-21,03:27:02 | INFO | Train Epoch: 1 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.393 Boundary Ratio: 0.247 Contrastive_loss: 1.2810 (1.4088) Boundary_loss: 0.015452 (0.015492) Loss: 1.2965 (1.4243) +2025-08-21,03:27:59 | INFO | Train Epoch: 1 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 1.1848 (1.4077) Boundary_loss: 0.015431 (0.015492) Loss: 1.2002 (1.4232) +2025-08-21,03:28:56 | INFO | Train Epoch: 1 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 1.2380 (1.4069) Boundary_loss: 0.015429 (0.015492) Loss: 1.2534 (1.4224) +2025-08-21,03:29:54 | INFO | Train Epoch: 1 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 1.2667 (1.4062) Boundary_loss: 0.015576 (0.015492) Loss: 1.2823 (1.4217) +2025-08-21,03:30:51 | INFO | Train Epoch: 1 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 1.4509 (1.4064) Boundary_loss: 0.015485 (0.015492) Loss: 1.4664 (1.4219) +2025-08-21,03:31:49 | INFO | Train Epoch: 1 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.162 Boundary Ratio: 0.246 Contrastive_loss: 1.2392 (1.4056) Boundary_loss: 0.015317 (0.015491) Loss: 1.2546 (1.4211) +2025-08-21,03:32:46 | INFO | Train Epoch: 1 [10445312/26365952 (40%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 1.2774 (1.4050) Boundary_loss: 0.015332 (0.015490) Loss: 1.2927 (1.4204) +2025-08-21,03:33:44 | INFO | Train Epoch: 1 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 1.4294 (1.4051) Boundary_loss: 0.015466 (0.015490) Loss: 1.4448 (1.4206) +2025-08-21,03:34:41 | INFO | Train Epoch: 1 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.285 Boundary Ratio: 0.246 Contrastive_loss: 1.2329 (1.4042) Boundary_loss: 0.015706 (0.015491) Loss: 1.2486 (1.4197) +2025-08-21,03:35:39 | INFO | Train Epoch: 1 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.273 Boundary Ratio: 0.246 Contrastive_loss: 1.3859 (1.4042) Boundary_loss: 0.015286 (0.015490) Loss: 1.4012 (1.4196) +2025-08-21,03:36:36 | INFO | Train Epoch: 1 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 1.2491 (1.4034) Boundary_loss: 0.015355 (0.015490) Loss: 1.2645 (1.4189) +2025-08-21,03:37:34 | INFO | Train Epoch: 1 [10701312/26365952 (41%)] Avg Boundaries (per batch): 49.314 Boundary Ratio: 0.252 Contrastive_loss: 1.2159 (1.4025) Boundary_loss: 0.015400 (0.015489) Loss: 1.2313 (1.4180) +2025-08-21,03:38:31 | INFO | Train Epoch: 1 [10752512/26365952 (41%)] Avg Boundaries (per batch): 50.172 Boundary Ratio: 0.256 Contrastive_loss: 1.3440 (1.4022) Boundary_loss: 0.015597 (0.015490) Loss: 1.3596 (1.4177) +2025-08-21,03:39:28 | INFO | Train Epoch: 1 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 1.2594 (1.4016) Boundary_loss: 0.015441 (0.015489) Loss: 1.2748 (1.4171) +2025-08-21,03:40:26 | INFO | Train Epoch: 1 [10854912/26365952 (41%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 1.3006 (1.4011) Boundary_loss: 0.015350 (0.015489) Loss: 1.3159 (1.4166) +2025-08-21,03:41:23 | INFO | Train Epoch: 1 [10906112/26365952 (41%)] Avg Boundaries (per batch): 49.631 Boundary Ratio: 0.253 Contrastive_loss: 1.2740 (1.4005) Boundary_loss: 0.015569 (0.015489) Loss: 1.2895 (1.4160) +2025-08-21,03:42:21 | INFO | Train Epoch: 1 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 1.2258 (1.3997) Boundary_loss: 0.015333 (0.015488) Loss: 1.2412 (1.4152) +2025-08-21,03:43:18 | INFO | Train Epoch: 1 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.684 Boundary Ratio: 0.253 Contrastive_loss: 1.2010 (1.3988) Boundary_loss: 0.015645 (0.015489) Loss: 1.2166 (1.4143) +2025-08-21,03:44:15 | INFO | Train Epoch: 1 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.264 Boundary Ratio: 0.251 Contrastive_loss: 1.2741 (1.3982) Boundary_loss: 0.015444 (0.015489) Loss: 1.2896 (1.4137) +2025-08-21,03:45:13 | INFO | Train Epoch: 1 [11110912/26365952 (42%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 1.4306 (1.3983) Boundary_loss: 0.015478 (0.015489) Loss: 1.4461 (1.4138) +2025-08-21,03:46:10 | INFO | Train Epoch: 1 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.330 Boundary Ratio: 0.247 Contrastive_loss: 1.2322 (1.3976) Boundary_loss: 0.015312 (0.015488) Loss: 1.2475 (1.4131) +2025-08-21,03:47:07 | INFO | Train Epoch: 1 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.275 Boundary Ratio: 0.246 Contrastive_loss: 1.2212 (1.3968) Boundary_loss: 0.015576 (0.015489) Loss: 1.2368 (1.4123) +2025-08-21,03:48:04 | INFO | Train Epoch: 1 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 1.2146 (1.3960) Boundary_loss: 0.015221 (0.015487) Loss: 1.2298 (1.4114) +2025-08-21,03:49:02 | INFO | Train Epoch: 1 [11315712/26365952 (43%)] Avg Boundaries (per batch): 47.918 Boundary Ratio: 0.244 Contrastive_loss: 1.3452 (1.3957) Boundary_loss: 0.015518 (0.015487) Loss: 1.3607 (1.4112) +2025-08-21,03:49:59 | INFO | Train Epoch: 1 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 1.3440 (1.3955) Boundary_loss: 0.015614 (0.015488) Loss: 1.3596 (1.4110) +2025-08-21,03:50:57 | INFO | Train Epoch: 1 [11418112/26365952 (43%)] Avg Boundaries (per batch): 49.871 Boundary Ratio: 0.254 Contrastive_loss: 1.2090 (1.3947) Boundary_loss: 0.015443 (0.015488) Loss: 1.2245 (1.4102) +2025-08-21,03:51:54 | INFO | Train Epoch: 1 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 1.0996 (1.3934) Boundary_loss: 0.015588 (0.015488) Loss: 1.1152 (1.4088) +2025-08-21,03:52:52 | INFO | Train Epoch: 1 [11520512/26365952 (44%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 1.3230 (1.3930) Boundary_loss: 0.015463 (0.015488) Loss: 1.3385 (1.4085) +2025-08-21,03:53:49 | INFO | Train Epoch: 1 [11571712/26365952 (44%)] Avg Boundaries (per batch): 47.432 Boundary Ratio: 0.242 Contrastive_loss: 1.2552 (1.3924) Boundary_loss: 0.015676 (0.015489) Loss: 1.2709 (1.4079) +2025-08-21,03:54:47 | INFO | Train Epoch: 1 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 1.3577 (1.3923) Boundary_loss: 0.015485 (0.015489) Loss: 1.3732 (1.4078) +2025-08-21,03:55:44 | INFO | Train Epoch: 1 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.418 Boundary Ratio: 0.252 Contrastive_loss: 1.2953 (1.3919) Boundary_loss: 0.015385 (0.015489) Loss: 1.3107 (1.4073) +2025-08-21,03:56:41 | INFO | Train Epoch: 1 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.201 Boundary Ratio: 0.246 Contrastive_loss: 1.2368 (1.3912) Boundary_loss: 0.015600 (0.015489) Loss: 1.2524 (1.4067) +2025-08-21,03:57:39 | INFO | Train Epoch: 1 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 1.1743 (1.3902) Boundary_loss: 0.015441 (0.015489) Loss: 1.1898 (1.4057) +2025-08-21,03:58:36 | INFO | Train Epoch: 1 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.109 Boundary Ratio: 0.245 Contrastive_loss: 1.3721 (1.3902) Boundary_loss: 0.015394 (0.015488) Loss: 1.3875 (1.4057) +2025-08-21,03:59:34 | INFO | Train Epoch: 1 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 1.2536 (1.3896) Boundary_loss: 0.015485 (0.015488) Loss: 1.2691 (1.4051) +2025-08-21,04:00:31 | INFO | Train Epoch: 1 [11930112/26365952 (45%)] Avg Boundaries (per batch): 49.512 Boundary Ratio: 0.253 Contrastive_loss: 1.2934 (1.3892) Boundary_loss: 0.015416 (0.015488) Loss: 1.3088 (1.4047) +2025-08-21,04:01:28 | INFO | Train Epoch: 1 [11981312/26365952 (45%)] Avg Boundaries (per batch): 49.324 Boundary Ratio: 0.252 Contrastive_loss: 1.3170 (1.3889) Boundary_loss: 0.015513 (0.015488) Loss: 1.3325 (1.4043) +2025-08-21,04:02:26 | INFO | Train Epoch: 1 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 1.1933 (1.3880) Boundary_loss: 0.015340 (0.015488) Loss: 1.2086 (1.4035) +2025-08-21,04:03:23 | INFO | Train Epoch: 1 [12083712/26365952 (46%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 1.1817 (1.3872) Boundary_loss: 0.015229 (0.015486) Loss: 1.1969 (1.4026) +2025-08-21,04:04:21 | INFO | Train Epoch: 1 [12134912/26365952 (46%)] Avg Boundaries (per batch): 49.283 Boundary Ratio: 0.251 Contrastive_loss: 1.2973 (1.3868) Boundary_loss: 0.015410 (0.015486) Loss: 1.3127 (1.4023) +2025-08-21,04:05:18 | INFO | Train Epoch: 1 [12186112/26365952 (46%)] Avg Boundaries (per batch): 49.654 Boundary Ratio: 0.253 Contrastive_loss: 1.2124 (1.3861) Boundary_loss: 0.015345 (0.015486) Loss: 1.2278 (1.4015) +2025-08-21,04:06:16 | INFO | Train Epoch: 1 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.227 Boundary Ratio: 0.246 Contrastive_loss: 1.2010 (1.3853) Boundary_loss: 0.015411 (0.015485) Loss: 1.2164 (1.4008) +2025-08-21,04:07:13 | INFO | Train Epoch: 1 [12288512/26365952 (47%)] Avg Boundaries (per batch): 49.244 Boundary Ratio: 0.251 Contrastive_loss: 1.1787 (1.3844) Boundary_loss: 0.015568 (0.015486) Loss: 1.1942 (1.3999) +2025-08-21,04:08:11 | INFO | Train Epoch: 1 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 1.2102 (1.3837) Boundary_loss: 0.015351 (0.015485) Loss: 1.2255 (1.3992) +2025-08-21,04:09:08 | INFO | Train Epoch: 1 [12390912/26365952 (47%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 1.1345 (1.3827) Boundary_loss: 0.015357 (0.015484) Loss: 1.1499 (1.3982) +2025-08-21,04:10:05 | INFO | Train Epoch: 1 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 1.1221 (1.3816) Boundary_loss: 0.015349 (0.015484) Loss: 1.1375 (1.3971) +2025-08-21,04:11:03 | INFO | Train Epoch: 1 [12493312/26365952 (47%)] Avg Boundaries (per batch): 49.379 Boundary Ratio: 0.252 Contrastive_loss: 1.1949 (1.3809) Boundary_loss: 0.015521 (0.015484) Loss: 1.2104 (1.3963) +2025-08-21,04:12:00 | INFO | Train Epoch: 1 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.389 Boundary Ratio: 0.247 Contrastive_loss: 1.2023 (1.3801) Boundary_loss: 0.015378 (0.015484) Loss: 1.2177 (1.3956) +2025-08-21,04:12:57 | INFO | Train Epoch: 1 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 1.4033 (1.3802) Boundary_loss: 0.015337 (0.015483) Loss: 1.4187 (1.3957) +2025-08-21,04:13:55 | INFO | Train Epoch: 1 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 1.2646 (1.3798) Boundary_loss: 0.015352 (0.015483) Loss: 1.2799 (1.3952) +2025-08-21,04:14:52 | INFO | Train Epoch: 1 [12698112/26365952 (48%)] Avg Boundaries (per batch): 47.783 Boundary Ratio: 0.244 Contrastive_loss: 1.3219 (1.3795) Boundary_loss: 0.015529 (0.015483) Loss: 1.3375 (1.3950) +2025-08-21,04:15:49 | INFO | Train Epoch: 1 [12749312/26365952 (48%)] Avg Boundaries (per batch): 49.643 Boundary Ratio: 0.253 Contrastive_loss: 1.1860 (1.3787) Boundary_loss: 0.015365 (0.015482) Loss: 1.2013 (1.3942) +2025-08-21,04:16:47 | INFO | Train Epoch: 1 [12800512/26365952 (49%)] Avg Boundaries (per batch): 49.738 Boundary Ratio: 0.254 Contrastive_loss: 1.2495 (1.3782) Boundary_loss: 0.015526 (0.015482) Loss: 1.2650 (1.3937) +2025-08-21,04:17:44 | INFO | Train Epoch: 1 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 1.1380 (1.3773) Boundary_loss: 0.015453 (0.015482) Loss: 1.1535 (1.3928) +2025-08-21,04:18:41 | INFO | Train Epoch: 1 [12902912/26365952 (49%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 1.2524 (1.3768) Boundary_loss: 0.015438 (0.015482) Loss: 1.2679 (1.3923) +2025-08-21,04:19:39 | INFO | Train Epoch: 1 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 1.2426 (1.3763) Boundary_loss: 0.015535 (0.015482) Loss: 1.2582 (1.3917) +2025-08-21,04:20:36 | INFO | Train Epoch: 1 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 1.2479 (1.3758) Boundary_loss: 0.015328 (0.015482) Loss: 1.2632 (1.3912) +2025-08-21,04:21:34 | INFO | Train Epoch: 1 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 1.2727 (1.3754) Boundary_loss: 0.015342 (0.015481) Loss: 1.2880 (1.3908) +2025-08-21,04:22:31 | INFO | Train Epoch: 1 [13107712/26365952 (50%)] Avg Boundaries (per batch): 49.627 Boundary Ratio: 0.253 Contrastive_loss: 1.1857 (1.3746) Boundary_loss: 0.015437 (0.015481) Loss: 1.2011 (1.3901) +2025-08-21,04:23:28 | INFO | Train Epoch: 1 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 1.3258 (1.3744) Boundary_loss: 0.015451 (0.015481) Loss: 1.3413 (1.3899) +2025-08-21,04:24:26 | INFO | Train Epoch: 1 [13210112/26365952 (50%)] Avg Boundaries (per batch): 47.553 Boundary Ratio: 0.243 Contrastive_loss: 1.1847 (1.3737) Boundary_loss: 0.015492 (0.015481) Loss: 1.2002 (1.3892) +2025-08-21,04:25:23 | INFO | Train Epoch: 1 [13261312/26365952 (50%)] Avg Boundaries (per batch): 49.613 Boundary Ratio: 0.253 Contrastive_loss: 1.2284 (1.3731) Boundary_loss: 0.015396 (0.015481) Loss: 1.2438 (1.3886) +2025-08-21,04:26:21 | INFO | Train Epoch: 1 [13312512/26365952 (50%)] Avg Boundaries (per batch): 47.930 Boundary Ratio: 0.245 Contrastive_loss: 1.2759 (1.3728) Boundary_loss: 0.015486 (0.015481) Loss: 1.2914 (1.3882) +2025-08-21,04:27:18 | INFO | Train Epoch: 1 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 1.0772 (1.3716) Boundary_loss: 0.015423 (0.015480) Loss: 1.0927 (1.3871) +2025-08-21,04:28:15 | INFO | Train Epoch: 1 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 1.0936 (1.3706) Boundary_loss: 0.015305 (0.015480) Loss: 1.1089 (1.3861) +2025-08-21,04:29:13 | INFO | Train Epoch: 1 [13466112/26365952 (51%)] Avg Boundaries (per batch): 49.367 Boundary Ratio: 0.252 Contrastive_loss: 1.2434 (1.3701) Boundary_loss: 0.015362 (0.015479) Loss: 1.2587 (1.3856) +2025-08-21,04:30:10 | INFO | Train Epoch: 1 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 1.1214 (1.3692) Boundary_loss: 0.015404 (0.015479) Loss: 1.1368 (1.3846) +2025-08-21,04:31:07 | INFO | Train Epoch: 1 [13568512/26365952 (51%)] Avg Boundaries (per batch): 49.742 Boundary Ratio: 0.254 Contrastive_loss: 1.3529 (1.3691) Boundary_loss: 0.015317 (0.015478) Loss: 1.3682 (1.3846) +2025-08-21,04:32:05 | INFO | Train Epoch: 1 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.2135 (1.3685) Boundary_loss: 0.015507 (0.015479) Loss: 1.2290 (1.3840) +2025-08-21,04:33:02 | INFO | Train Epoch: 1 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 1.2582 (1.3681) Boundary_loss: 0.015432 (0.015478) Loss: 1.2736 (1.3836) +2025-08-21,04:34:00 | INFO | Train Epoch: 1 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 1.2057 (1.3675) Boundary_loss: 0.015425 (0.015478) Loss: 1.2211 (1.3830) +2025-08-21,04:34:57 | INFO | Train Epoch: 1 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 1.4362 (1.3677) Boundary_loss: 0.015430 (0.015478) Loss: 1.4516 (1.3832) +2025-08-21,04:35:55 | INFO | Train Epoch: 1 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 1.2225 (1.3672) Boundary_loss: 0.015734 (0.015479) Loss: 1.2382 (1.3827) +2025-08-21,04:36:52 | INFO | Train Epoch: 1 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.199 Boundary Ratio: 0.246 Contrastive_loss: 1.1325 (1.3664) Boundary_loss: 0.015418 (0.015479) Loss: 1.1479 (1.3818) +2025-08-21,04:37:50 | INFO | Train Epoch: 1 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 1.3723 (1.3664) Boundary_loss: 0.015363 (0.015478) Loss: 1.3876 (1.3819) +2025-08-21,04:38:47 | INFO | Train Epoch: 1 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 1.1976 (1.3658) Boundary_loss: 0.015760 (0.015479) Loss: 1.2133 (1.3812) +2025-08-21,04:39:44 | INFO | Train Epoch: 1 [14029312/26365952 (53%)] Avg Boundaries (per batch): 49.572 Boundary Ratio: 0.253 Contrastive_loss: 1.2020 (1.3652) Boundary_loss: 0.015451 (0.015479) Loss: 1.2174 (1.3806) +2025-08-21,04:40:42 | INFO | Train Epoch: 1 [14080512/26365952 (53%)] Avg Boundaries (per batch): 47.943 Boundary Ratio: 0.245 Contrastive_loss: 1.1631 (1.3644) Boundary_loss: 0.015695 (0.015480) Loss: 1.1788 (1.3799) +2025-08-21,04:41:39 | INFO | Train Epoch: 1 [14131712/26365952 (54%)] Avg Boundaries (per batch): 47.902 Boundary Ratio: 0.244 Contrastive_loss: 1.2140 (1.3639) Boundary_loss: 0.015529 (0.015480) Loss: 1.2295 (1.3794) +2025-08-21,04:42:36 | INFO | Train Epoch: 1 [14182912/26365952 (54%)] Avg Boundaries (per batch): 49.807 Boundary Ratio: 0.254 Contrastive_loss: 1.2446 (1.3635) Boundary_loss: 0.015423 (0.015480) Loss: 1.2600 (1.3789) +2025-08-21,04:43:34 | INFO | Train Epoch: 1 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 1.3016 (1.3632) Boundary_loss: 0.015415 (0.015480) Loss: 1.3170 (1.3787) +2025-08-21,04:44:31 | INFO | Train Epoch: 1 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 1.2765 (1.3629) Boundary_loss: 0.015521 (0.015480) Loss: 1.2920 (1.3784) +2025-08-21,04:45:28 | INFO | Train Epoch: 1 [14336512/26365952 (54%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 1.1165 (1.3620) Boundary_loss: 0.015451 (0.015480) Loss: 1.1319 (1.3775) +2025-08-21,04:46:26 | INFO | Train Epoch: 1 [14387712/26365952 (55%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 1.2936 (1.3618) Boundary_loss: 0.015446 (0.015480) Loss: 1.3091 (1.3773) +2025-08-21,04:47:23 | INFO | Train Epoch: 1 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 1.2117 (1.3613) Boundary_loss: 0.015512 (0.015480) Loss: 1.2272 (1.3768) +2025-08-21,04:48:20 | INFO | Train Epoch: 1 [14490112/26365952 (55%)] Avg Boundaries (per batch): 49.781 Boundary Ratio: 0.254 Contrastive_loss: 1.2675 (1.3609) Boundary_loss: 0.015465 (0.015480) Loss: 1.2830 (1.3764) +2025-08-21,04:49:18 | INFO | Train Epoch: 1 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 1.1022 (1.3600) Boundary_loss: 0.015205 (0.015479) Loss: 1.1174 (1.3755) +2025-08-21,04:50:15 | INFO | Train Epoch: 1 [14592512/26365952 (55%)] Avg Boundaries (per batch): 49.422 Boundary Ratio: 0.252 Contrastive_loss: 1.1933 (1.3595) Boundary_loss: 0.015250 (0.015478) Loss: 1.2085 (1.3749) +2025-08-21,04:51:12 | INFO | Train Epoch: 1 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 1.2028 (1.3589) Boundary_loss: 0.015512 (0.015478) Loss: 1.2183 (1.3744) +2025-08-21,04:52:10 | INFO | Train Epoch: 1 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.275 Boundary Ratio: 0.246 Contrastive_loss: 1.1538 (1.3582) Boundary_loss: 0.015365 (0.015478) Loss: 1.1692 (1.3737) +2025-08-21,04:53:07 | INFO | Train Epoch: 1 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 1.0924 (1.3573) Boundary_loss: 0.015399 (0.015477) Loss: 1.1078 (1.3728) +2025-08-21,04:54:04 | INFO | Train Epoch: 1 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.2204 (1.3568) Boundary_loss: 0.015603 (0.015478) Loss: 1.2361 (1.3723) +2025-08-21,04:55:02 | INFO | Train Epoch: 1 [14848512/26365952 (56%)] Avg Boundaries (per batch): 47.953 Boundary Ratio: 0.245 Contrastive_loss: 1.2149 (1.3563) Boundary_loss: 0.015431 (0.015478) Loss: 1.2304 (1.3718) +2025-08-21,04:55:59 | INFO | Train Epoch: 1 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 1.2092 (1.3558) Boundary_loss: 0.015411 (0.015477) Loss: 1.2246 (1.3713) +2025-08-21,04:56:56 | INFO | Train Epoch: 1 [14950912/26365952 (57%)] Avg Boundaries (per batch): 49.836 Boundary Ratio: 0.254 Contrastive_loss: 1.2085 (1.3553) Boundary_loss: 0.015620 (0.015478) Loss: 1.2241 (1.3708) +2025-08-21,04:57:53 | INFO | Train Epoch: 1 [15002112/26365952 (57%)] Avg Boundaries (per batch): 49.521 Boundary Ratio: 0.253 Contrastive_loss: 1.3483 (1.3553) Boundary_loss: 0.015399 (0.015478) Loss: 1.3637 (1.3708) +2025-08-21,04:58:51 | INFO | Train Epoch: 1 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 1.1018 (1.3544) Boundary_loss: 0.015298 (0.015477) Loss: 1.1171 (1.3699) +2025-08-21,04:59:48 | INFO | Train Epoch: 1 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 1.0710 (1.3535) Boundary_loss: 0.015375 (0.015477) Loss: 1.0863 (1.3689) +2025-08-21,05:00:46 | INFO | Train Epoch: 1 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 1.2639 (1.3532) Boundary_loss: 0.015287 (0.015476) Loss: 1.2792 (1.3686) +2025-08-21,05:01:43 | INFO | Train Epoch: 1 [15206912/26365952 (58%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 1.1381 (1.3524) Boundary_loss: 0.015426 (0.015476) Loss: 1.1535 (1.3679) +2025-08-21,05:02:40 | INFO | Train Epoch: 1 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 1.1671 (1.3518) Boundary_loss: 0.015417 (0.015476) Loss: 1.1825 (1.3673) +2025-08-21,05:03:37 | INFO | Train Epoch: 1 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.1766 (1.3512) Boundary_loss: 0.015431 (0.015476) Loss: 1.1920 (1.3667) +2025-08-21,05:04:34 | INFO | Train Epoch: 1 [15360512/26365952 (58%)] Avg Boundaries (per batch): 47.072 Boundary Ratio: 0.240 Contrastive_loss: 1.2546 (1.3509) Boundary_loss: 0.015486 (0.015476) Loss: 1.2701 (1.3664) +2025-08-21,05:05:32 | INFO | Train Epoch: 1 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.094 Boundary Ratio: 0.245 Contrastive_loss: 1.0785 (1.3500) Boundary_loss: 0.015565 (0.015476) Loss: 1.0940 (1.3655) +2025-08-21,05:06:29 | INFO | Train Epoch: 1 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.107 Boundary Ratio: 0.245 Contrastive_loss: 1.2628 (1.3497) Boundary_loss: 0.015462 (0.015476) Loss: 1.2782 (1.3652) +2025-08-21,05:07:26 | INFO | Train Epoch: 1 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 1.1197 (1.3490) Boundary_loss: 0.015222 (0.015475) Loss: 1.1350 (1.3644) +2025-08-21,05:08:24 | INFO | Train Epoch: 1 [15565312/26365952 (59%)] Avg Boundaries (per batch): 49.469 Boundary Ratio: 0.252 Contrastive_loss: 1.2027 (1.3485) Boundary_loss: 0.015380 (0.015475) Loss: 1.2180 (1.3640) +2025-08-21,05:09:21 | INFO | Train Epoch: 1 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.221 Boundary Ratio: 0.246 Contrastive_loss: 1.0811 (1.3476) Boundary_loss: 0.015494 (0.015475) Loss: 1.0966 (1.3631) +2025-08-21,05:10:19 | INFO | Train Epoch: 1 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 1.2135 (1.3472) Boundary_loss: 0.015299 (0.015474) Loss: 1.2288 (1.3627) +2025-08-21,05:11:16 | INFO | Train Epoch: 1 [15718912/26365952 (60%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 1.2443 (1.3468) Boundary_loss: 0.015447 (0.015474) Loss: 1.2597 (1.3623) +2025-08-21,05:12:13 | INFO | Train Epoch: 1 [15770112/26365952 (60%)] Avg Boundaries (per batch): 47.664 Boundary Ratio: 0.243 Contrastive_loss: 1.2424 (1.3465) Boundary_loss: 0.015583 (0.015474) Loss: 1.2580 (1.3620) +2025-08-21,05:13:11 | INFO | Train Epoch: 1 [15821312/26365952 (60%)] Avg Boundaries (per batch): 49.889 Boundary Ratio: 0.255 Contrastive_loss: 1.2654 (1.3462) Boundary_loss: 0.015341 (0.015474) Loss: 1.2807 (1.3617) +2025-08-21,05:14:08 | INFO | Train Epoch: 1 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 1.3011 (1.3461) Boundary_loss: 0.015239 (0.015473) Loss: 1.3163 (1.3616) +2025-08-21,05:15:05 | INFO | Train Epoch: 1 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 1.1706 (1.3455) Boundary_loss: 0.015418 (0.015473) Loss: 1.1860 (1.3610) +2025-08-21,05:16:02 | INFO | Train Epoch: 1 [15974912/26365952 (61%)] Avg Boundaries (per batch): 50.014 Boundary Ratio: 0.255 Contrastive_loss: 1.2026 (1.3451) Boundary_loss: 0.015581 (0.015473) Loss: 1.2182 (1.3606) +2025-08-21,05:17:00 | INFO | Train Epoch: 1 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 1.2922 (1.3449) Boundary_loss: 0.015371 (0.015473) Loss: 1.3076 (1.3604) +2025-08-21,05:17:57 | INFO | Train Epoch: 1 [16077312/26365952 (61%)] Avg Boundaries (per batch): 49.859 Boundary Ratio: 0.254 Contrastive_loss: 1.1265 (1.3442) Boundary_loss: 0.015490 (0.015473) Loss: 1.1419 (1.3597) +2025-08-21,05:18:54 | INFO | Train Epoch: 1 [16128512/26365952 (61%)] Avg Boundaries (per batch): 50.043 Boundary Ratio: 0.255 Contrastive_loss: 1.2343 (1.3439) Boundary_loss: 0.015469 (0.015473) Loss: 1.2498 (1.3593) +2025-08-21,05:19:52 | INFO | Train Epoch: 1 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 1.1629 (1.3433) Boundary_loss: 0.015672 (0.015474) Loss: 1.1786 (1.3588) +2025-08-21,05:20:49 | INFO | Train Epoch: 1 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 1.2290 (1.3429) Boundary_loss: 0.015426 (0.015474) Loss: 1.2444 (1.3584) +2025-08-21,05:21:46 | INFO | Train Epoch: 1 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 1.2051 (1.3425) Boundary_loss: 0.015272 (0.015473) Loss: 1.2204 (1.3580) +2025-08-21,05:22:43 | INFO | Train Epoch: 1 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 1.1740 (1.3420) Boundary_loss: 0.015390 (0.015473) Loss: 1.1894 (1.3575) +2025-08-21,05:23:41 | INFO | Train Epoch: 1 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 1.1777 (1.3415) Boundary_loss: 0.015563 (0.015473) Loss: 1.1933 (1.3569) +2025-08-21,05:24:38 | INFO | Train Epoch: 1 [16435712/26365952 (62%)] Avg Boundaries (per batch): 49.783 Boundary Ratio: 0.254 Contrastive_loss: 1.2409 (1.3412) Boundary_loss: 0.015364 (0.015473) Loss: 1.2562 (1.3566) +2025-08-21,05:25:36 | INFO | Train Epoch: 1 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.287 Boundary Ratio: 0.246 Contrastive_loss: 1.3396 (1.3412) Boundary_loss: 0.015351 (0.015472) Loss: 1.3550 (1.3566) +2025-08-21,05:26:33 | INFO | Train Epoch: 1 [16538112/26365952 (63%)] Avg Boundaries (per batch): 47.928 Boundary Ratio: 0.245 Contrastive_loss: 1.1676 (1.3406) Boundary_loss: 0.015565 (0.015473) Loss: 1.1832 (1.3561) +2025-08-21,05:27:30 | INFO | Train Epoch: 1 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.170 Boundary Ratio: 0.246 Contrastive_loss: 1.2190 (1.3402) Boundary_loss: 0.015469 (0.015473) Loss: 1.2345 (1.3557) +2025-08-21,05:28:28 | INFO | Train Epoch: 1 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.309 Boundary Ratio: 0.252 Contrastive_loss: 1.1182 (1.3396) Boundary_loss: 0.015477 (0.015473) Loss: 1.1337 (1.3550) +2025-08-21,05:29:25 | INFO | Train Epoch: 1 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 1.1119 (1.3389) Boundary_loss: 0.015484 (0.015473) Loss: 1.1274 (1.3543) +2025-08-21,05:30:23 | INFO | Train Epoch: 1 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 1.0920 (1.3381) Boundary_loss: 0.015305 (0.015472) Loss: 1.1073 (1.3536) +2025-08-21,05:31:20 | INFO | Train Epoch: 1 [16794112/26365952 (64%)] Avg Boundaries (per batch): 47.871 Boundary Ratio: 0.244 Contrastive_loss: 1.1441 (1.3375) Boundary_loss: 0.015446 (0.015472) Loss: 1.1596 (1.3530) +2025-08-21,05:32:17 | INFO | Train Epoch: 1 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.100 Boundary Ratio: 0.245 Contrastive_loss: 1.2241 (1.3372) Boundary_loss: 0.015555 (0.015472) Loss: 1.2396 (1.3527) +2025-08-21,05:33:15 | INFO | Train Epoch: 1 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 1.1915 (1.3367) Boundary_loss: 0.015547 (0.015472) Loss: 1.2071 (1.3522) +2025-08-21,05:34:12 | INFO | Train Epoch: 1 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 1.1639 (1.3362) Boundary_loss: 0.015316 (0.015472) Loss: 1.1793 (1.3517) +2025-08-21,05:35:09 | INFO | Train Epoch: 1 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 1.2896 (1.3361) Boundary_loss: 0.015318 (0.015472) Loss: 1.3049 (1.3516) +2025-08-21,05:36:07 | INFO | Train Epoch: 1 [17050112/26365952 (65%)] Avg Boundaries (per batch): 47.658 Boundary Ratio: 0.243 Contrastive_loss: 1.0794 (1.3353) Boundary_loss: 0.015376 (0.015471) Loss: 1.0948 (1.3508) +2025-08-21,05:37:04 | INFO | Train Epoch: 1 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 1.2380 (1.3350) Boundary_loss: 0.015332 (0.015471) Loss: 1.2533 (1.3505) +2025-08-21,05:38:01 | INFO | Train Epoch: 1 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.078 Boundary Ratio: 0.245 Contrastive_loss: 1.1139 (1.3344) Boundary_loss: 0.015398 (0.015471) Loss: 1.1293 (1.3498) +2025-08-21,05:38:58 | INFO | Train Epoch: 1 [17203712/26365952 (65%)] Avg Boundaries (per batch): 47.545 Boundary Ratio: 0.243 Contrastive_loss: 1.2381 (1.3341) Boundary_loss: 0.015341 (0.015470) Loss: 1.2535 (1.3496) +2025-08-21,05:39:56 | INFO | Train Epoch: 1 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.230 Boundary Ratio: 0.246 Contrastive_loss: 1.1126 (1.3334) Boundary_loss: 0.015413 (0.015470) Loss: 1.1280 (1.3489) +2025-08-21,05:40:53 | INFO | Train Epoch: 1 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.744 Boundary Ratio: 0.254 Contrastive_loss: 1.2222 (1.3331) Boundary_loss: 0.015287 (0.015470) Loss: 1.2375 (1.3486) +2025-08-21,05:41:50 | INFO | Train Epoch: 1 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 1.1999 (1.3327) Boundary_loss: 0.015353 (0.015469) Loss: 1.2153 (1.3482) +2025-08-21,05:42:48 | INFO | Train Epoch: 1 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 1.2477 (1.3325) Boundary_loss: 0.015317 (0.015469) Loss: 1.2630 (1.3479) +2025-08-21,05:43:45 | INFO | Train Epoch: 1 [17459712/26365952 (66%)] Avg Boundaries (per batch): 49.811 Boundary Ratio: 0.254 Contrastive_loss: 1.0839 (1.3317) Boundary_loss: 0.015472 (0.015469) Loss: 1.0994 (1.3472) +2025-08-21,05:44:43 | INFO | Train Epoch: 1 [17510912/26365952 (66%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 1.1492 (1.3312) Boundary_loss: 0.015425 (0.015469) Loss: 1.1646 (1.3467) +2025-08-21,05:45:40 | INFO | Train Epoch: 1 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 1.3285 (1.3312) Boundary_loss: 0.015322 (0.015468) Loss: 1.3438 (1.3467) +2025-08-21,05:46:37 | INFO | Train Epoch: 1 [17613312/26365952 (67%)] Avg Boundaries (per batch): 49.711 Boundary Ratio: 0.254 Contrastive_loss: 1.2505 (1.3310) Boundary_loss: 0.015542 (0.015468) Loss: 1.2660 (1.3464) +2025-08-21,05:47:35 | INFO | Train Epoch: 1 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 1.0775 (1.3302) Boundary_loss: 0.015507 (0.015469) Loss: 1.0930 (1.3457) +2025-08-21,05:48:32 | INFO | Train Epoch: 1 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 1.2656 (1.3300) Boundary_loss: 0.015476 (0.015469) Loss: 1.2811 (1.3455) +2025-08-21,05:49:29 | INFO | Train Epoch: 1 [17766912/26365952 (67%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 1.0491 (1.3292) Boundary_loss: 0.015304 (0.015468) Loss: 1.0644 (1.3447) +2025-08-21,05:50:27 | INFO | Train Epoch: 1 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.877 Boundary Ratio: 0.254 Contrastive_loss: 1.1152 (1.3286) Boundary_loss: 0.015701 (0.015469) Loss: 1.1309 (1.3441) +2025-08-21,05:51:24 | INFO | Train Epoch: 1 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.242 Boundary Ratio: 0.246 Contrastive_loss: 1.1180 (1.3280) Boundary_loss: 0.015421 (0.015469) Loss: 1.1334 (1.3435) +2025-08-21,05:52:21 | INFO | Train Epoch: 1 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.244 Boundary Ratio: 0.246 Contrastive_loss: 1.0694 (1.3273) Boundary_loss: 0.015463 (0.015469) Loss: 1.0849 (1.3427) +2025-08-21,05:53:19 | INFO | Train Epoch: 1 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 1.2249 (1.3270) Boundary_loss: 0.015448 (0.015469) Loss: 1.2404 (1.3425) +2025-08-21,05:54:16 | INFO | Train Epoch: 1 [18022912/26365952 (68%)] Avg Boundaries (per batch): 47.645 Boundary Ratio: 0.243 Contrastive_loss: 1.0327 (1.3262) Boundary_loss: 0.015675 (0.015469) Loss: 1.0484 (1.3416) +2025-08-21,05:55:14 | INFO | Train Epoch: 1 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 1.0714 (1.3254) Boundary_loss: 0.015464 (0.015469) Loss: 1.0868 (1.3409) +2025-08-21,05:56:11 | INFO | Train Epoch: 1 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 1.0824 (1.3247) Boundary_loss: 0.015510 (0.015469) Loss: 1.0979 (1.3402) +2025-08-21,05:57:08 | INFO | Train Epoch: 1 [18176512/26365952 (69%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 1.2552 (1.3246) Boundary_loss: 0.015523 (0.015469) Loss: 1.2708 (1.3400) +2025-08-21,05:58:06 | INFO | Train Epoch: 1 [18227712/26365952 (69%)] Avg Boundaries (per batch): 49.168 Boundary Ratio: 0.251 Contrastive_loss: 1.1315 (1.3240) Boundary_loss: 0.015378 (0.015469) Loss: 1.1469 (1.3395) +2025-08-21,05:59:03 | INFO | Train Epoch: 1 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 1.0163 (1.3232) Boundary_loss: 0.015357 (0.015469) Loss: 1.0316 (1.3386) +2025-08-21,06:00:00 | INFO | Train Epoch: 1 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.219 Boundary Ratio: 0.251 Contrastive_loss: 1.2352 (1.3229) Boundary_loss: 0.015458 (0.015469) Loss: 1.2506 (1.3384) +2025-08-21,06:00:58 | INFO | Train Epoch: 1 [18381312/26365952 (70%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 1.3450 (1.3230) Boundary_loss: 0.015364 (0.015468) Loss: 1.3604 (1.3384) +2025-08-21,06:01:55 | INFO | Train Epoch: 1 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.211 Boundary Ratio: 0.246 Contrastive_loss: 1.0779 (1.3223) Boundary_loss: 0.015390 (0.015468) Loss: 1.0933 (1.3378) +2025-08-21,06:02:52 | INFO | Train Epoch: 1 [18483712/26365952 (70%)] Avg Boundaries (per batch): 49.531 Boundary Ratio: 0.253 Contrastive_loss: 1.2600 (1.3221) Boundary_loss: 0.015419 (0.015468) Loss: 1.2754 (1.3376) +2025-08-21,06:03:50 | INFO | Train Epoch: 1 [18534912/26365952 (70%)] Avg Boundaries (per batch): 47.635 Boundary Ratio: 0.243 Contrastive_loss: 1.1215 (1.3216) Boundary_loss: 0.015587 (0.015468) Loss: 1.1371 (1.3370) +2025-08-21,06:04:47 | INFO | Train Epoch: 1 [18586112/26365952 (70%)] Avg Boundaries (per batch): 49.887 Boundary Ratio: 0.255 Contrastive_loss: 1.0946 (1.3209) Boundary_loss: 0.015407 (0.015468) Loss: 1.1100 (1.3364) +2025-08-21,06:05:44 | INFO | Train Epoch: 1 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 1.1811 (1.3206) Boundary_loss: 0.015339 (0.015468) Loss: 1.1964 (1.3360) +2025-08-21,06:06:41 | INFO | Train Epoch: 1 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 1.1519 (1.3201) Boundary_loss: 0.015471 (0.015468) Loss: 1.1673 (1.3356) +2025-08-21,06:07:39 | INFO | Train Epoch: 1 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 1.2284 (1.3198) Boundary_loss: 0.015519 (0.015468) Loss: 1.2440 (1.3353) +2025-08-21,06:08:36 | INFO | Train Epoch: 1 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.391 Boundary Ratio: 0.247 Contrastive_loss: 1.1494 (1.3194) Boundary_loss: 0.015534 (0.015468) Loss: 1.1649 (1.3349) +2025-08-21,06:09:33 | INFO | Train Epoch: 1 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.516 Boundary Ratio: 0.248 Contrastive_loss: 1.2833 (1.3193) Boundary_loss: 0.015316 (0.015468) Loss: 1.2986 (1.3348) +2025-08-21,06:10:31 | INFO | Train Epoch: 1 [18893312/26365952 (72%)] Avg Boundaries (per batch): 47.512 Boundary Ratio: 0.242 Contrastive_loss: 1.2358 (1.3191) Boundary_loss: 0.015585 (0.015468) Loss: 1.2514 (1.3345) +2025-08-21,06:11:28 | INFO | Train Epoch: 1 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 1.1728 (1.3187) Boundary_loss: 0.015348 (0.015468) Loss: 1.1881 (1.3341) +2025-08-21,06:12:26 | INFO | Train Epoch: 1 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.252 Boundary Ratio: 0.246 Contrastive_loss: 1.0917 (1.3181) Boundary_loss: 0.015263 (0.015467) Loss: 1.1069 (1.3335) +2025-08-21,06:13:23 | INFO | Train Epoch: 1 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.545 Boundary Ratio: 0.253 Contrastive_loss: 1.0809 (1.3174) Boundary_loss: 0.015440 (0.015467) Loss: 1.0964 (1.3329) +2025-08-21,06:14:20 | INFO | Train Epoch: 1 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 1.0272 (1.3166) Boundary_loss: 0.015257 (0.015467) Loss: 1.0424 (1.3321) +2025-08-21,06:15:18 | INFO | Train Epoch: 1 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 1.1083 (1.3161) Boundary_loss: 0.015393 (0.015466) Loss: 1.1237 (1.3316) +2025-08-21,06:16:15 | INFO | Train Epoch: 1 [19200512/26365952 (73%)] Avg Boundaries (per batch): 49.209 Boundary Ratio: 0.251 Contrastive_loss: 1.0570 (1.3154) Boundary_loss: 0.015413 (0.015466) Loss: 1.0724 (1.3309) +2025-08-21,06:17:12 | INFO | Train Epoch: 1 [19251712/26365952 (73%)] Avg Boundaries (per batch): 47.635 Boundary Ratio: 0.243 Contrastive_loss: 1.2089 (1.3151) Boundary_loss: 0.015568 (0.015467) Loss: 1.2244 (1.3306) +2025-08-21,06:18:10 | INFO | Train Epoch: 1 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 1.0515 (1.3144) Boundary_loss: 0.015446 (0.015467) Loss: 1.0669 (1.3299) +2025-08-21,06:19:07 | INFO | Train Epoch: 1 [19354112/26365952 (73%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 1.2233 (1.3142) Boundary_loss: 0.015420 (0.015466) Loss: 1.2387 (1.3296) +2025-08-21,06:20:04 | INFO | Train Epoch: 1 [19405312/26365952 (74%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 1.1696 (1.3138) Boundary_loss: 0.015461 (0.015466) Loss: 1.1851 (1.3293) +2025-08-21,06:21:02 | INFO | Train Epoch: 1 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 1.1917 (1.3135) Boundary_loss: 0.015415 (0.015466) Loss: 1.2071 (1.3289) +2025-08-21,06:21:59 | INFO | Train Epoch: 1 [19507712/26365952 (74%)] Avg Boundaries (per batch): 50.121 Boundary Ratio: 0.256 Contrastive_loss: 1.0753 (1.3129) Boundary_loss: 0.015576 (0.015467) Loss: 1.0909 (1.3283) +2025-08-21,06:22:56 | INFO | Train Epoch: 1 [19558912/26365952 (74%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 1.0750 (1.3122) Boundary_loss: 0.015480 (0.015467) Loss: 1.0905 (1.3277) +2025-08-21,06:23:54 | INFO | Train Epoch: 1 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.98815 (1.3114) Boundary_loss: 0.015436 (0.015467) Loss: 1.0036 (1.3269) +2025-08-21,06:24:51 | INFO | Train Epoch: 1 [19661312/26365952 (75%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 1.1817 (1.3111) Boundary_loss: 0.015411 (0.015466) Loss: 1.1971 (1.3265) +2025-08-21,06:25:48 | INFO | Train Epoch: 1 [19712512/26365952 (75%)] Avg Boundaries (per batch): 47.658 Boundary Ratio: 0.243 Contrastive_loss: 1.1749 (1.3107) Boundary_loss: 0.015271 (0.015466) Loss: 1.1902 (1.3262) +2025-08-21,06:26:46 | INFO | Train Epoch: 1 [19763712/26365952 (75%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 1.2093 (1.3104) Boundary_loss: 0.015265 (0.015465) Loss: 1.2245 (1.3259) +2025-08-21,06:27:43 | INFO | Train Epoch: 1 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 1.1197 (1.3099) Boundary_loss: 0.015408 (0.015465) Loss: 1.1351 (1.3254) +2025-08-21,06:28:41 | INFO | Train Epoch: 1 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 1.1754 (1.3096) Boundary_loss: 0.015375 (0.015465) Loss: 1.1908 (1.3251) +2025-08-21,06:29:38 | INFO | Train Epoch: 1 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 1.2167 (1.3094) Boundary_loss: 0.015387 (0.015465) Loss: 1.2321 (1.3248) +2025-08-21,06:30:35 | INFO | Train Epoch: 1 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 1.1086 (1.3089) Boundary_loss: 0.015375 (0.015465) Loss: 1.1240 (1.3243) +2025-08-21,06:31:33 | INFO | Train Epoch: 1 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 1.1317 (1.3084) Boundary_loss: 0.015397 (0.015464) Loss: 1.1471 (1.3239) +2025-08-21,06:32:30 | INFO | Train Epoch: 1 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 1.0466 (1.3077) Boundary_loss: 0.015399 (0.015464) Loss: 1.0620 (1.3232) +2025-08-21,06:33:27 | INFO | Train Epoch: 1 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 1.0975 (1.3072) Boundary_loss: 0.015399 (0.015464) Loss: 1.1129 (1.3227) +2025-08-21,06:34:25 | INFO | Train Epoch: 1 [20173312/26365952 (77%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 1.2731 (1.3071) Boundary_loss: 0.015520 (0.015464) Loss: 1.2886 (1.3226) +2025-08-21,06:35:22 | INFO | Train Epoch: 1 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 1.2788 (1.3070) Boundary_loss: 0.015511 (0.015464) Loss: 1.2943 (1.3225) +2025-08-21,06:36:20 | INFO | Train Epoch: 1 [20275712/26365952 (77%)] Avg Boundaries (per batch): 47.736 Boundary Ratio: 0.244 Contrastive_loss: 1.0565 (1.3064) Boundary_loss: 0.015439 (0.015464) Loss: 1.0720 (1.3219) +2025-08-21,06:37:17 | INFO | Train Epoch: 1 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 1.0619 (1.3058) Boundary_loss: 0.015395 (0.015464) Loss: 1.0773 (1.3213) +2025-08-21,06:38:15 | INFO | Train Epoch: 1 [20378112/26365952 (77%)] Avg Boundaries (per batch): 50.020 Boundary Ratio: 0.255 Contrastive_loss: 1.0663 (1.3052) Boundary_loss: 0.015377 (0.015464) Loss: 1.0816 (1.3207) +2025-08-21,06:39:12 | INFO | Train Epoch: 1 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.059 Boundary Ratio: 0.245 Contrastive_loss: 1.1451 (1.3048) Boundary_loss: 0.015355 (0.015464) Loss: 1.1605 (1.3203) +2025-08-21,06:40:09 | INFO | Train Epoch: 1 [20480512/26365952 (78%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 1.0674 (1.3042) Boundary_loss: 0.015428 (0.015463) Loss: 1.0829 (1.3197) +2025-08-21,06:41:07 | INFO | Train Epoch: 1 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.248 Boundary Ratio: 0.246 Contrastive_loss: 1.0665 (1.3036) Boundary_loss: 0.015483 (0.015464) Loss: 1.0820 (1.3191) +2025-08-21,06:42:04 | INFO | Train Epoch: 1 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 1.1021 (1.3031) Boundary_loss: 0.015327 (0.015463) Loss: 1.1174 (1.3186) +2025-08-21,06:43:01 | INFO | Train Epoch: 1 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.135 Boundary Ratio: 0.246 Contrastive_loss: 1.0382 (1.3025) Boundary_loss: 0.015425 (0.015463) Loss: 1.0536 (1.3179) +2025-08-21,06:43:59 | INFO | Train Epoch: 1 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 1.2625 (1.3024) Boundary_loss: 0.015494 (0.015463) Loss: 1.2780 (1.3178) +2025-08-21,06:44:56 | INFO | Train Epoch: 1 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 1.0992 (1.3019) Boundary_loss: 0.015394 (0.015463) Loss: 1.1146 (1.3173) +2025-08-21,06:45:53 | INFO | Train Epoch: 1 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.338 Boundary Ratio: 0.252 Contrastive_loss: 1.1892 (1.3016) Boundary_loss: 0.015485 (0.015463) Loss: 1.2047 (1.3170) +2025-08-21,06:46:51 | INFO | Train Epoch: 1 [20838912/26365952 (79%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 1.1372 (1.3012) Boundary_loss: 0.015331 (0.015463) Loss: 1.1525 (1.3166) +2025-08-21,06:47:48 | INFO | Train Epoch: 1 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 1.0636 (1.3006) Boundary_loss: 0.015479 (0.015463) Loss: 1.0791 (1.3161) +2025-08-21,06:48:45 | INFO | Train Epoch: 1 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.90897 (1.2996) Boundary_loss: 0.015380 (0.015463) Loss: 0.92435 (1.3151) +2025-08-21,06:49:42 | INFO | Train Epoch: 1 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.146 Boundary Ratio: 0.246 Contrastive_loss: 1.0872 (1.2991) Boundary_loss: 0.015521 (0.015463) Loss: 1.1028 (1.3146) +2025-08-21,06:50:40 | INFO | Train Epoch: 1 [21043712/26365952 (80%)] Avg Boundaries (per batch): 49.318 Boundary Ratio: 0.252 Contrastive_loss: 1.1046 (1.2987) Boundary_loss: 0.015402 (0.015463) Loss: 1.1200 (1.3141) +2025-08-21,06:51:37 | INFO | Train Epoch: 1 [21094912/26365952 (80%)] Avg Boundaries (per batch): 49.373 Boundary Ratio: 0.252 Contrastive_loss: 1.1887 (1.2984) Boundary_loss: 0.015336 (0.015462) Loss: 1.2040 (1.3138) +2025-08-21,06:52:34 | INFO | Train Epoch: 1 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 1.0550 (1.2978) Boundary_loss: 0.015453 (0.015462) Loss: 1.0705 (1.3133) +2025-08-21,06:53:31 | INFO | Train Epoch: 1 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.99015 (1.2971) Boundary_loss: 0.015365 (0.015462) Loss: 1.0055 (1.3125) +2025-08-21,06:54:29 | INFO | Train Epoch: 1 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 1.0734 (1.2965) Boundary_loss: 0.015368 (0.015462) Loss: 1.0888 (1.3120) +2025-08-21,06:55:26 | INFO | Train Epoch: 1 [21299712/26365952 (81%)] Avg Boundaries (per batch): 49.619 Boundary Ratio: 0.253 Contrastive_loss: 0.94666 (1.2957) Boundary_loss: 0.015357 (0.015462) Loss: 0.96202 (1.3111) +2025-08-21,06:56:23 | INFO | Train Epoch: 1 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 1.2427 (1.2956) Boundary_loss: 0.015449 (0.015461) Loss: 1.2581 (1.3110) +2025-08-21,06:57:21 | INFO | Train Epoch: 1 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 1.0576 (1.2950) Boundary_loss: 0.015306 (0.015461) Loss: 1.0729 (1.3104) +2025-08-21,06:58:18 | INFO | Train Epoch: 1 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 1.1341 (1.2946) Boundary_loss: 0.015394 (0.015461) Loss: 1.1495 (1.3101) +2025-08-21,06:59:15 | INFO | Train Epoch: 1 [21504512/26365952 (82%)] Avg Boundaries (per batch): 49.387 Boundary Ratio: 0.252 Contrastive_loss: 1.1312 (1.2942) Boundary_loss: 0.015425 (0.015461) Loss: 1.1466 (1.3097) +2025-08-21,07:00:13 | INFO | Train Epoch: 1 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 1.0407 (1.2936) Boundary_loss: 0.015393 (0.015461) Loss: 1.0561 (1.3091) +2025-08-21,07:01:10 | INFO | Train Epoch: 1 [21606912/26365952 (82%)] Avg Boundaries (per batch): 49.750 Boundary Ratio: 0.254 Contrastive_loss: 1.2126 (1.2934) Boundary_loss: 0.015383 (0.015461) Loss: 1.2280 (1.3089) +2025-08-21,07:02:07 | INFO | Train Epoch: 1 [21658112/26365952 (82%)] Avg Boundaries (per batch): 49.594 Boundary Ratio: 0.253 Contrastive_loss: 1.0475 (1.2928) Boundary_loss: 0.015293 (0.015460) Loss: 1.0628 (1.3083) +2025-08-21,07:03:05 | INFO | Train Epoch: 1 [21709312/26365952 (82%)] Avg Boundaries (per batch): 49.693 Boundary Ratio: 0.254 Contrastive_loss: 1.0946 (1.2924) Boundary_loss: 0.015394 (0.015460) Loss: 1.1100 (1.3078) +2025-08-21,07:04:03 | INFO | Train Epoch: 1 [21760512/26365952 (83%)] Avg Boundaries (per batch): 47.914 Boundary Ratio: 0.244 Contrastive_loss: 1.1761 (1.2921) Boundary_loss: 0.015507 (0.015460) Loss: 1.1916 (1.3076) +2025-08-21,07:05:00 | INFO | Train Epoch: 1 [21811712/26365952 (83%)] Avg Boundaries (per batch): 49.949 Boundary Ratio: 0.255 Contrastive_loss: 1.1608 (1.2918) Boundary_loss: 0.015463 (0.015460) Loss: 1.1763 (1.3073) +2025-08-21,07:05:57 | INFO | Train Epoch: 1 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 1.1036 (1.2914) Boundary_loss: 0.015434 (0.015460) Loss: 1.1191 (1.3068) +2025-08-21,07:06:55 | INFO | Train Epoch: 1 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 1.0703 (1.2908) Boundary_loss: 0.015422 (0.015460) Loss: 1.0857 (1.3063) +2025-08-21,07:07:52 | INFO | Train Epoch: 1 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.748 Boundary Ratio: 0.254 Contrastive_loss: 1.0244 (1.2902) Boundary_loss: 0.015418 (0.015460) Loss: 1.0398 (1.3057) +2025-08-21,07:08:50 | INFO | Train Epoch: 1 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 1.0449 (1.2897) Boundary_loss: 0.015444 (0.015460) Loss: 1.0604 (1.3051) +2025-08-21,07:09:47 | INFO | Train Epoch: 1 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.0795 (1.2892) Boundary_loss: 0.015452 (0.015460) Loss: 1.0949 (1.3046) +2025-08-21,07:10:44 | INFO | Train Epoch: 1 [22118912/26365952 (84%)] Avg Boundaries (per batch): 47.381 Boundary Ratio: 0.242 Contrastive_loss: 1.2718 (1.2891) Boundary_loss: 0.015432 (0.015460) Loss: 1.2872 (1.3046) +2025-08-21,07:11:42 | INFO | Train Epoch: 1 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.482 Boundary Ratio: 0.247 Contrastive_loss: 1.0300 (1.2885) Boundary_loss: 0.015422 (0.015460) Loss: 1.0454 (1.3040) +2025-08-21,07:12:39 | INFO | Train Epoch: 1 [22221312/26365952 (84%)] Avg Boundaries (per batch): 49.662 Boundary Ratio: 0.253 Contrastive_loss: 1.1125 (1.2881) Boundary_loss: 0.015456 (0.015460) Loss: 1.1280 (1.3036) +2025-08-21,07:13:36 | INFO | Train Epoch: 1 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.447 Boundary Ratio: 0.252 Contrastive_loss: 0.98320 (1.2874) Boundary_loss: 0.015511 (0.015460) Loss: 0.99871 (1.3029) +2025-08-21,07:14:34 | INFO | Train Epoch: 1 [22323712/26365952 (85%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 1.0714 (1.2869) Boundary_loss: 0.015426 (0.015460) Loss: 1.0869 (1.3024) +2025-08-21,07:15:31 | INFO | Train Epoch: 1 [22374912/26365952 (85%)] Avg Boundaries (per batch): 49.420 Boundary Ratio: 0.252 Contrastive_loss: 1.0558 (1.2864) Boundary_loss: 0.015508 (0.015460) Loss: 1.0713 (1.3019) +2025-08-21,07:16:29 | INFO | Train Epoch: 1 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.508 Boundary Ratio: 0.247 Contrastive_loss: 1.0958 (1.2860) Boundary_loss: 0.015336 (0.015459) Loss: 1.1111 (1.3014) +2025-08-21,07:17:26 | INFO | Train Epoch: 1 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.0463 (1.2854) Boundary_loss: 0.015500 (0.015460) Loss: 1.0618 (1.3009) +2025-08-21,07:18:23 | INFO | Train Epoch: 1 [22528512/26365952 (85%)] Avg Boundaries (per batch): 47.893 Boundary Ratio: 0.244 Contrastive_loss: 1.1647 (1.2851) Boundary_loss: 0.015510 (0.015460) Loss: 1.1802 (1.3006) +2025-08-21,07:19:21 | INFO | Train Epoch: 1 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.0283 (1.2846) Boundary_loss: 0.015377 (0.015460) Loss: 1.0437 (1.3000) +2025-08-21,07:20:18 | INFO | Train Epoch: 1 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 1.1514 (1.2843) Boundary_loss: 0.015339 (0.015459) Loss: 1.1668 (1.2997) +2025-08-21,07:21:16 | INFO | Train Epoch: 1 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.230 Boundary Ratio: 0.246 Contrastive_loss: 1.1016 (1.2839) Boundary_loss: 0.015471 (0.015459) Loss: 1.1170 (1.2993) +2025-08-21,07:22:13 | INFO | Train Epoch: 1 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 1.0063 (1.2832) Boundary_loss: 0.015499 (0.015459) Loss: 1.0218 (1.2987) +2025-08-21,07:23:11 | INFO | Train Epoch: 1 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.363 Boundary Ratio: 0.247 Contrastive_loss: 1.0693 (1.2828) Boundary_loss: 0.015359 (0.015459) Loss: 1.0847 (1.2982) +2025-08-21,07:24:08 | INFO | Train Epoch: 1 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.080 Boundary Ratio: 0.245 Contrastive_loss: 1.1776 (1.2825) Boundary_loss: 0.015352 (0.015459) Loss: 1.1930 (1.2980) +2025-08-21,07:25:05 | INFO | Train Epoch: 1 [22886912/26365952 (87%)] Avg Boundaries (per batch): 49.465 Boundary Ratio: 0.252 Contrastive_loss: 1.3016 (1.2826) Boundary_loss: 0.015548 (0.015459) Loss: 1.3171 (1.2980) +2025-08-21,07:26:02 | INFO | Train Epoch: 1 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 1.1395 (1.2822) Boundary_loss: 0.015336 (0.015459) Loss: 1.1548 (1.2977) +2025-08-21,07:27:00 | INFO | Train Epoch: 1 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 1.1861 (1.2820) Boundary_loss: 0.015330 (0.015459) Loss: 1.2014 (1.2975) +2025-08-21,07:27:57 | INFO | Train Epoch: 1 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 1.1837 (1.2818) Boundary_loss: 0.015493 (0.015459) Loss: 1.1992 (1.2973) +2025-08-21,07:28:55 | INFO | Train Epoch: 1 [23091712/26365952 (88%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 1.0850 (1.2814) Boundary_loss: 0.015336 (0.015458) Loss: 1.1004 (1.2968) +2025-08-21,07:29:52 | INFO | Train Epoch: 1 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 1.1524 (1.2811) Boundary_loss: 0.015263 (0.015458) Loss: 1.1677 (1.2965) +2025-08-21,07:30:49 | INFO | Train Epoch: 1 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.270 Boundary Ratio: 0.246 Contrastive_loss: 1.2091 (1.2809) Boundary_loss: 0.015288 (0.015458) Loss: 1.2244 (1.2964) +2025-08-21,07:31:46 | INFO | Train Epoch: 1 [23245312/26365952 (88%)] Avg Boundaries (per batch): 49.988 Boundary Ratio: 0.255 Contrastive_loss: 1.0690 (1.2805) Boundary_loss: 0.015587 (0.015458) Loss: 1.0846 (1.2959) +2025-08-21,07:32:44 | INFO | Train Epoch: 1 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.209 Boundary Ratio: 0.246 Contrastive_loss: 1.1178 (1.2801) Boundary_loss: 0.015499 (0.015458) Loss: 1.1333 (1.2956) +2025-08-21,07:33:41 | INFO | Train Epoch: 1 [23347712/26365952 (89%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 1.0686 (1.2796) Boundary_loss: 0.015475 (0.015458) Loss: 1.0841 (1.2951) +2025-08-21,07:34:38 | INFO | Train Epoch: 1 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.363 Boundary Ratio: 0.247 Contrastive_loss: 1.1487 (1.2794) Boundary_loss: 0.015413 (0.015458) Loss: 1.1641 (1.2948) +2025-08-21,07:35:36 | INFO | Train Epoch: 1 [23450112/26365952 (89%)] Avg Boundaries (per batch): 47.438 Boundary Ratio: 0.242 Contrastive_loss: 1.0383 (1.2788) Boundary_loss: 0.015408 (0.015458) Loss: 1.0537 (1.2943) +2025-08-21,07:36:33 | INFO | Train Epoch: 1 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.363 Boundary Ratio: 0.247 Contrastive_loss: 1.1419 (1.2785) Boundary_loss: 0.015204 (0.015457) Loss: 1.1571 (1.2940) +2025-08-21,07:37:30 | INFO | Train Epoch: 1 [23552512/26365952 (89%)] Avg Boundaries (per batch): 49.717 Boundary Ratio: 0.254 Contrastive_loss: 1.1057 (1.2782) Boundary_loss: 0.015524 (0.015457) Loss: 1.1212 (1.2936) +2025-08-21,07:38:28 | INFO | Train Epoch: 1 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 1.0696 (1.2777) Boundary_loss: 0.015485 (0.015457) Loss: 1.0851 (1.2932) +2025-08-21,07:39:25 | INFO | Train Epoch: 1 [23654912/26365952 (90%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.96419 (1.2770) Boundary_loss: 0.015338 (0.015457) Loss: 0.97953 (1.2925) +2025-08-21,07:40:22 | INFO | Train Epoch: 1 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.252 Boundary Ratio: 0.246 Contrastive_loss: 1.1759 (1.2768) Boundary_loss: 0.015300 (0.015457) Loss: 1.1912 (1.2923) +2025-08-21,07:41:20 | INFO | Train Epoch: 1 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 1.0718 (1.2764) Boundary_loss: 0.015470 (0.015457) Loss: 1.0872 (1.2918) +2025-08-21,07:42:17 | INFO | Train Epoch: 1 [23808512/26365952 (90%)] Avg Boundaries (per batch): 49.328 Boundary Ratio: 0.252 Contrastive_loss: 1.2196 (1.2763) Boundary_loss: 0.015379 (0.015457) Loss: 1.2349 (1.2917) +2025-08-21,07:43:14 | INFO | Train Epoch: 1 [23859712/26365952 (90%)] Avg Boundaries (per batch): 49.637 Boundary Ratio: 0.253 Contrastive_loss: 1.1188 (1.2759) Boundary_loss: 0.015246 (0.015456) Loss: 1.1340 (1.2914) +2025-08-21,07:44:11 | INFO | Train Epoch: 1 [23910912/26365952 (91%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 1.2460 (1.2759) Boundary_loss: 0.015266 (0.015456) Loss: 1.2613 (1.2913) +2025-08-21,07:45:09 | INFO | Train Epoch: 1 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.242 Boundary Ratio: 0.246 Contrastive_loss: 1.2125 (1.2757) Boundary_loss: 0.015423 (0.015456) Loss: 1.2279 (1.2912) +2025-08-21,07:46:06 | INFO | Train Epoch: 1 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.92243 (1.2750) Boundary_loss: 0.015420 (0.015456) Loss: 0.93785 (1.2904) +2025-08-21,07:47:03 | INFO | Train Epoch: 1 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.131 Boundary Ratio: 0.246 Contrastive_loss: 1.1719 (1.2747) Boundary_loss: 0.015396 (0.015456) Loss: 1.1873 (1.2902) +2025-08-21,07:48:01 | INFO | Train Epoch: 1 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 1.1535 (1.2745) Boundary_loss: 0.015604 (0.015456) Loss: 1.1691 (1.2899) +2025-08-21,07:48:58 | INFO | Train Epoch: 1 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.92915 (1.2738) Boundary_loss: 0.015415 (0.015456) Loss: 0.94457 (1.2892) +2025-08-21,07:49:55 | INFO | Train Epoch: 1 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.92336 (1.2730) Boundary_loss: 0.015368 (0.015456) Loss: 0.93873 (1.2885) +2025-08-21,07:50:52 | INFO | Train Epoch: 1 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.389 Boundary Ratio: 0.247 Contrastive_loss: 1.0602 (1.2726) Boundary_loss: 0.015500 (0.015456) Loss: 1.0757 (1.2880) +2025-08-21,07:51:50 | INFO | Train Epoch: 1 [24320512/26365952 (92%)] Avg Boundaries (per batch): 47.793 Boundary Ratio: 0.244 Contrastive_loss: 1.0564 (1.2721) Boundary_loss: 0.015289 (0.015455) Loss: 1.0717 (1.2876) +2025-08-21,07:52:47 | INFO | Train Epoch: 1 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.189 Boundary Ratio: 0.246 Contrastive_loss: 1.1481 (1.2719) Boundary_loss: 0.015280 (0.015455) Loss: 1.1634 (1.2873) +2025-08-21,07:53:44 | INFO | Train Epoch: 1 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 1.0594 (1.2714) Boundary_loss: 0.015499 (0.015455) Loss: 1.0749 (1.2869) +2025-08-21,07:54:42 | INFO | Train Epoch: 1 [24474112/26365952 (93%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 1.1308 (1.2711) Boundary_loss: 0.015487 (0.015455) Loss: 1.1463 (1.2866) +2025-08-21,07:55:39 | INFO | Train Epoch: 1 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 1.0502 (1.2707) Boundary_loss: 0.015347 (0.015455) Loss: 1.0655 (1.2861) +2025-08-21,07:56:36 | INFO | Train Epoch: 1 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 0.93172 (1.2700) Boundary_loss: 0.015459 (0.015455) Loss: 0.94717 (1.2854) +2025-08-21,07:57:33 | INFO | Train Epoch: 1 [24627712/26365952 (93%)] Avg Boundaries (per batch): 47.783 Boundary Ratio: 0.244 Contrastive_loss: 1.0435 (1.2695) Boundary_loss: 0.015262 (0.015454) Loss: 1.0588 (1.2849) +2025-08-21,07:58:31 | INFO | Train Epoch: 1 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.99964 (1.2689) Boundary_loss: 0.015529 (0.015455) Loss: 1.0152 (1.2844) +2025-08-21,07:59:28 | INFO | Train Epoch: 1 [24730112/26365952 (94%)] Avg Boundaries (per batch): 49.633 Boundary Ratio: 0.253 Contrastive_loss: 0.89955 (1.2682) Boundary_loss: 0.015447 (0.015455) Loss: 0.91499 (1.2836) +2025-08-21,08:00:25 | INFO | Train Epoch: 1 [24781312/26365952 (94%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 1.1137 (1.2678) Boundary_loss: 0.015499 (0.015455) Loss: 1.1292 (1.2833) +2025-08-21,08:01:23 | INFO | Train Epoch: 1 [24832512/26365952 (94%)] Avg Boundaries (per batch): 50.043 Boundary Ratio: 0.255 Contrastive_loss: 1.0284 (1.2674) Boundary_loss: 0.015541 (0.015455) Loss: 1.0439 (1.2828) +2025-08-21,08:02:20 | INFO | Train Epoch: 1 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 1.0809 (1.2670) Boundary_loss: 0.015450 (0.015455) Loss: 1.0964 (1.2824) +2025-08-21,08:03:17 | INFO | Train Epoch: 1 [24934912/26365952 (95%)] Avg Boundaries (per batch): 49.330 Boundary Ratio: 0.252 Contrastive_loss: 1.0938 (1.2666) Boundary_loss: 0.015286 (0.015455) Loss: 1.1091 (1.2821) +2025-08-21,08:04:15 | INFO | Train Epoch: 1 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.475 Boundary Ratio: 0.252 Contrastive_loss: 1.1578 (1.2664) Boundary_loss: 0.015419 (0.015454) Loss: 1.1732 (1.2818) +2025-08-21,08:05:12 | INFO | Train Epoch: 1 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 1.1879 (1.2662) Boundary_loss: 0.015437 (0.015454) Loss: 1.2034 (1.2817) +2025-08-21,08:06:10 | INFO | Train Epoch: 1 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 0.84815 (1.2654) Boundary_loss: 0.015284 (0.015454) Loss: 0.86343 (1.2808) +2025-08-21,08:07:07 | INFO | Train Epoch: 1 [25139712/26365952 (95%)] Avg Boundaries (per batch): 47.992 Boundary Ratio: 0.245 Contrastive_loss: 1.1833 (1.2652) Boundary_loss: 0.015504 (0.015454) Loss: 1.1988 (1.2807) +2025-08-21,08:08:04 | INFO | Train Epoch: 1 [25190912/26365952 (96%)] Avg Boundaries (per batch): 50.412 Boundary Ratio: 0.257 Contrastive_loss: 1.1447 (1.2650) Boundary_loss: 0.015360 (0.015454) Loss: 1.1601 (1.2804) +2025-08-21,08:09:02 | INFO | Train Epoch: 1 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.049 Boundary Ratio: 0.245 Contrastive_loss: 1.1480 (1.2647) Boundary_loss: 0.015394 (0.015454) Loss: 1.1634 (1.2802) +2025-08-21,08:09:59 | INFO | Train Epoch: 1 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 1.1062 (1.2644) Boundary_loss: 0.015515 (0.015454) Loss: 1.1217 (1.2799) +2025-08-21,08:10:57 | INFO | Train Epoch: 1 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 1.0868 (1.2641) Boundary_loss: 0.015418 (0.015454) Loss: 1.1022 (1.2795) +2025-08-21,08:11:54 | INFO | Train Epoch: 1 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 1.0933 (1.2637) Boundary_loss: 0.015258 (0.015454) Loss: 1.1085 (1.2792) +2025-08-21,08:12:52 | INFO | Train Epoch: 1 [25446912/26365952 (97%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.97953 (1.2631) Boundary_loss: 0.015344 (0.015453) Loss: 0.99488 (1.2786) +2025-08-21,08:13:49 | INFO | Train Epoch: 1 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 1.1081 (1.2628) Boundary_loss: 0.015408 (0.015453) Loss: 1.1235 (1.2783) +2025-08-21,08:14:46 | INFO | Train Epoch: 1 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 1.0601 (1.2624) Boundary_loss: 0.015299 (0.015453) Loss: 1.0754 (1.2779) +2025-08-21,08:15:44 | INFO | Train Epoch: 1 [25600512/26365952 (97%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 1.0673 (1.2620) Boundary_loss: 0.015360 (0.015453) Loss: 1.0827 (1.2775) +2025-08-21,08:16:41 | INFO | Train Epoch: 1 [25651712/26365952 (97%)] Avg Boundaries (per batch): 49.506 Boundary Ratio: 0.253 Contrastive_loss: 1.0148 (1.2615) Boundary_loss: 0.015284 (0.015452) Loss: 1.0301 (1.2770) +2025-08-21,08:17:38 | INFO | Train Epoch: 1 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.145 Boundary Ratio: 0.246 Contrastive_loss: 1.0400 (1.2611) Boundary_loss: 0.015577 (0.015453) Loss: 1.0556 (1.2766) +2025-08-21,08:18:36 | INFO | Train Epoch: 1 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.033 Boundary Ratio: 0.245 Contrastive_loss: 1.1924 (1.2610) Boundary_loss: 0.015485 (0.015453) Loss: 1.2079 (1.2764) +2025-08-21,08:19:33 | INFO | Train Epoch: 1 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 1.1104 (1.2607) Boundary_loss: 0.015316 (0.015452) Loss: 1.1257 (1.2761) +2025-08-21,08:20:30 | INFO | Train Epoch: 1 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.043 Boundary Ratio: 0.245 Contrastive_loss: 1.2049 (1.2606) Boundary_loss: 0.015456 (0.015452) Loss: 1.2203 (1.2760) +2025-08-21,08:21:27 | INFO | Train Epoch: 1 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 1.1039 (1.2602) Boundary_loss: 0.015383 (0.015452) Loss: 1.1193 (1.2757) +2025-08-21,08:22:25 | INFO | Train Epoch: 1 [25958912/26365952 (98%)] Avg Boundaries (per batch): 47.928 Boundary Ratio: 0.245 Contrastive_loss: 0.93377 (1.2596) Boundary_loss: 0.015268 (0.015452) Loss: 0.94903 (1.2751) +2025-08-21,08:23:22 | INFO | Train Epoch: 1 [26010112/26365952 (99%)] Avg Boundaries (per batch): 47.672 Boundary Ratio: 0.243 Contrastive_loss: 1.1087 (1.2593) Boundary_loss: 0.015523 (0.015452) Loss: 1.1242 (1.2748) +2025-08-21,08:24:20 | INFO | Train Epoch: 1 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.209 Boundary Ratio: 0.246 Contrastive_loss: 0.98349 (1.2588) Boundary_loss: 0.015262 (0.015452) Loss: 0.99875 (1.2742) +2025-08-21,08:25:17 | INFO | Train Epoch: 1 [26112512/26365952 (99%)] Avg Boundaries (per batch): 49.500 Boundary Ratio: 0.253 Contrastive_loss: 1.0545 (1.2584) Boundary_loss: 0.015223 (0.015451) Loss: 1.0697 (1.2738) +2025-08-21,08:26:14 | INFO | Train Epoch: 1 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 1.1382 (1.2581) Boundary_loss: 0.015471 (0.015451) Loss: 1.1537 (1.2736) +2025-08-21,08:27:11 | INFO | Train Epoch: 1 [26214912/26365952 (99%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.99207 (1.2576) Boundary_loss: 0.015447 (0.015451) Loss: 1.0075 (1.2731) +2025-08-21,08:28:09 | INFO | Train Epoch: 1 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 1.1362 (1.2574) Boundary_loss: 0.015473 (0.015451) Loss: 1.1516 (1.2728) +2025-08-21,08:29:06 | INFO | Train Epoch: 1 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.92999 (1.2567) Boundary_loss: 0.015385 (0.015451) Loss: 0.94537 (1.2722) +2025-08-21,08:30:01 | INFO | Train Epoch: 1 [26365952/26365952 (100%)] Avg Boundaries (per batch): 49.309 Boundary Ratio: 0.252 Contrastive_loss: 0.86563 (1.2560) Boundary_loss: 0.015453 (0.015451) Loss: 0.88109 (1.2714) +2025-08-21,08:30:01 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-21,08:30:01 | INFO | [Epoch 1] Average Step Time: 0.576s | Average GPU Memory: 32.1 GB +2025-08-21,08:30:01 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-21,08:30:01 | INFO | Starting zero-shot imagenet. +2025-08-21,08:30:01 | INFO | Building zero-shot classifier +2025-08-21,08:30:10 | INFO | Using classifier +2025-08-21,08:30:57 | INFO | Finished zero-shot imagenet. +2025-08-21,08:30:57 | INFO | Eval Epoch: 2 imagenet-zeroshot-val-top1: 0.1744 imagenet-zeroshot-val-top5: 0.3806 +2025-08-21,08:30:58 | INFO | Start epoch 2 +2025-08-21,08:31:00 | INFO | Train Epoch: 2 [ 512/26365952 (0%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 1.0699 (1.0699) Boundary_loss: 0.015368 (0.015368) Loss: 1.0853 (1.0853) +2025-08-21,08:31:58 | INFO | Train Epoch: 2 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.035 Boundary Ratio: 0.245 Contrastive_loss: 1.1467 (1.1083) Boundary_loss: 0.015531 (0.015449) Loss: 1.1623 (1.1238) +2025-08-21,08:32:55 | INFO | Train Epoch: 2 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.070 Boundary Ratio: 0.245 Contrastive_loss: 1.1431 (1.1199) Boundary_loss: 0.015345 (0.015414) Loss: 1.1585 (1.1353) +2025-08-21,08:33:52 | INFO | Train Epoch: 2 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 1.1334 (1.1233) Boundary_loss: 0.015495 (0.015435) Loss: 1.1489 (1.1387) +2025-08-21,08:34:49 | INFO | Train Epoch: 2 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.262 Boundary Ratio: 0.246 Contrastive_loss: 1.0352 (1.1057) Boundary_loss: 0.015294 (0.015407) Loss: 1.0505 (1.1211) +2025-08-21,08:35:46 | INFO | Train Epoch: 2 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.270 Boundary Ratio: 0.246 Contrastive_loss: 0.99854 (1.0878) Boundary_loss: 0.015446 (0.015413) Loss: 1.0140 (1.1032) +2025-08-21,08:36:43 | INFO | Train Epoch: 2 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.95626 (1.0690) Boundary_loss: 0.015417 (0.015414) Loss: 0.97168 (1.0844) +2025-08-21,08:37:40 | INFO | Train Epoch: 2 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.99415 (1.0597) Boundary_loss: 0.015585 (0.015435) Loss: 1.0097 (1.0751) +2025-08-21,08:38:38 | INFO | Train Epoch: 2 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 0.97267 (1.0500) Boundary_loss: 0.015393 (0.015430) Loss: 0.98806 (1.0654) +2025-08-21,08:39:35 | INFO | Train Epoch: 2 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 0.96548 (1.0415) Boundary_loss: 0.015315 (0.015419) Loss: 0.98080 (1.0570) +2025-08-21,08:40:32 | INFO | Train Epoch: 2 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.96351 (1.0345) Boundary_loss: 0.015360 (0.015414) Loss: 0.97887 (1.0499) +2025-08-21,08:41:29 | INFO | Train Epoch: 2 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.96934 (1.0290) Boundary_loss: 0.015509 (0.015421) Loss: 0.98485 (1.0444) +2025-08-21,08:42:26 | INFO | Train Epoch: 2 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 1.0280 (1.0289) Boundary_loss: 0.015298 (0.015412) Loss: 1.0432 (1.0444) +2025-08-21,08:43:23 | INFO | Train Epoch: 2 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.90587 (1.0202) Boundary_loss: 0.015330 (0.015406) Loss: 0.92120 (1.0356) +2025-08-21,08:44:21 | INFO | Train Epoch: 2 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 47.930 Boundary Ratio: 0.245 Contrastive_loss: 1.1951 (1.0318) Boundary_loss: 0.015397 (0.015406) Loss: 1.2105 (1.0472) +2025-08-21,08:45:18 | INFO | Train Epoch: 2 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.99839 (1.0297) Boundary_loss: 0.015636 (0.015420) Loss: 1.0140 (1.0451) +2025-08-21,08:46:15 | INFO | Train Epoch: 2 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 49.301 Boundary Ratio: 0.252 Contrastive_loss: 1.1647 (1.0377) Boundary_loss: 0.015569 (0.015429) Loss: 1.1802 (1.0531) +2025-08-21,08:47:12 | INFO | Train Epoch: 2 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.96874 (1.0338) Boundary_loss: 0.015537 (0.015435) Loss: 0.98428 (1.0493) +2025-08-21,08:48:09 | INFO | Train Epoch: 2 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 1.1126 (1.0380) Boundary_loss: 0.015183 (0.015421) Loss: 1.1278 (1.0534) +2025-08-21,08:49:07 | INFO | Train Epoch: 2 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 1.0153 (1.0368) Boundary_loss: 0.015232 (0.015412) Loss: 1.0305 (1.0523) +2025-08-21,08:50:04 | INFO | Train Epoch: 2 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 1.0551 (1.0377) Boundary_loss: 0.015243 (0.015404) Loss: 1.0704 (1.0531) +2025-08-21,08:51:01 | INFO | Train Epoch: 2 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.84036 (1.0287) Boundary_loss: 0.015498 (0.015408) Loss: 0.85586 (1.0442) +2025-08-21,08:51:58 | INFO | Train Epoch: 2 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 49.367 Boundary Ratio: 0.252 Contrastive_loss: 0.93920 (1.0249) Boundary_loss: 0.015366 (0.015406) Loss: 0.95456 (1.0403) +2025-08-21,08:52:55 | INFO | Train Epoch: 2 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 1.0066 (1.0241) Boundary_loss: 0.015447 (0.015408) Loss: 1.0221 (1.0395) +2025-08-21,08:53:52 | INFO | Train Epoch: 2 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 50.115 Boundary Ratio: 0.256 Contrastive_loss: 0.91848 (1.0199) Boundary_loss: 0.015439 (0.015409) Loss: 0.93391 (1.0353) +2025-08-21,08:54:49 | INFO | Train Epoch: 2 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 1.0061 (1.0193) Boundary_loss: 0.015340 (0.015407) Loss: 1.0214 (1.0347) +2025-08-21,08:55:46 | INFO | Train Epoch: 2 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 1.0162 (1.0192) Boundary_loss: 0.015360 (0.015405) Loss: 1.0316 (1.0346) +2025-08-21,08:56:43 | INFO | Train Epoch: 2 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.205 Boundary Ratio: 0.246 Contrastive_loss: 1.0802 (1.0214) Boundary_loss: 0.015331 (0.015402) Loss: 1.0956 (1.0368) +2025-08-21,08:57:40 | INFO | Train Epoch: 2 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 1.0102 (1.0210) Boundary_loss: 0.015284 (0.015398) Loss: 1.0255 (1.0364) +2025-08-21,08:58:37 | INFO | Train Epoch: 2 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 0.92725 (1.0179) Boundary_loss: 0.015429 (0.015399) Loss: 0.94268 (1.0333) +2025-08-21,08:59:35 | INFO | Train Epoch: 2 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.695 Boundary Ratio: 0.254 Contrastive_loss: 0.99570 (1.0172) Boundary_loss: 0.015565 (0.015405) Loss: 1.0113 (1.0326) +2025-08-21,09:00:32 | INFO | Train Epoch: 2 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.141 Boundary Ratio: 0.246 Contrastive_loss: 0.97603 (1.0159) Boundary_loss: 0.015319 (0.015402) Loss: 0.99135 (1.0313) +2025-08-21,09:01:29 | INFO | Train Epoch: 2 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.94671 (1.0138) Boundary_loss: 0.015290 (0.015398) Loss: 0.96200 (1.0292) +2025-08-21,09:02:26 | INFO | Train Epoch: 2 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 1.1070 (1.0165) Boundary_loss: 0.015459 (0.015400) Loss: 1.1224 (1.0319) +2025-08-21,09:03:23 | INFO | Train Epoch: 2 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.90181 (1.0133) Boundary_loss: 0.015314 (0.015398) Loss: 0.91712 (1.0287) +2025-08-21,09:04:20 | INFO | Train Epoch: 2 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.97246 (1.0121) Boundary_loss: 0.015515 (0.015401) Loss: 0.98798 (1.0275) +2025-08-21,09:05:17 | INFO | Train Epoch: 2 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 1.1210 (1.0151) Boundary_loss: 0.015641 (0.015408) Loss: 1.1367 (1.0305) +2025-08-21,09:06:14 | INFO | Train Epoch: 2 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.92274 (1.0126) Boundary_loss: 0.015389 (0.015407) Loss: 0.93812 (1.0280) +2025-08-21,09:07:12 | INFO | Train Epoch: 2 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.96734 (1.0115) Boundary_loss: 0.015466 (0.015409) Loss: 0.98281 (1.0269) +2025-08-21,09:08:09 | INFO | Train Epoch: 2 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.307 Boundary Ratio: 0.246 Contrastive_loss: 0.99035 (1.0109) Boundary_loss: 0.015317 (0.015406) Loss: 1.0057 (1.0264) +2025-08-21,09:09:06 | INFO | Train Epoch: 2 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.92608 (1.0089) Boundary_loss: 0.015445 (0.015407) Loss: 0.94152 (1.0243) +2025-08-21,09:10:03 | INFO | Train Epoch: 2 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.033 Boundary Ratio: 0.245 Contrastive_loss: 0.97114 (1.0080) Boundary_loss: 0.015276 (0.015404) Loss: 0.98641 (1.0234) +2025-08-21,09:11:00 | INFO | Train Epoch: 2 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.100 Boundary Ratio: 0.245 Contrastive_loss: 0.93431 (1.0063) Boundary_loss: 0.015285 (0.015401) Loss: 0.94960 (1.0217) +2025-08-21,09:11:57 | INFO | Train Epoch: 2 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 47.586 Boundary Ratio: 0.243 Contrastive_loss: 0.87294 (1.0032) Boundary_loss: 0.015492 (0.015403) Loss: 0.88844 (1.0186) +2025-08-21,09:12:54 | INFO | Train Epoch: 2 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.90486 (1.0010) Boundary_loss: 0.015343 (0.015402) Loss: 0.92020 (1.0165) +2025-08-21,09:13:52 | INFO | Train Epoch: 2 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 49.326 Boundary Ratio: 0.252 Contrastive_loss: 0.92893 (0.99948) Boundary_loss: 0.015395 (0.015402) Loss: 0.94433 (1.0149) +2025-08-21,09:14:49 | INFO | Train Epoch: 2 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.98922 (0.99926) Boundary_loss: 0.015357 (0.015401) Loss: 1.0046 (1.0147) +2025-08-21,09:15:46 | INFO | Train Epoch: 2 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.385 Boundary Ratio: 0.247 Contrastive_loss: 1.0071 (0.99943) Boundary_loss: 0.015326 (0.015399) Loss: 1.0224 (1.0148) +2025-08-21,09:16:43 | INFO | Train Epoch: 2 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 47.701 Boundary Ratio: 0.243 Contrastive_loss: 1.0657 (1.0008) Boundary_loss: 0.015456 (0.015401) Loss: 1.0811 (1.0162) +2025-08-21,09:17:40 | INFO | Train Epoch: 2 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.97906 (1.0003) Boundary_loss: 0.015361 (0.015400) Loss: 0.99442 (1.0157) +2025-08-21,09:18:37 | INFO | Train Epoch: 2 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 1.0977 (1.0023) Boundary_loss: 0.015389 (0.015400) Loss: 1.1131 (1.0177) +2025-08-21,09:19:34 | INFO | Train Epoch: 2 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 1.0521 (1.0032) Boundary_loss: 0.015254 (0.015397) Loss: 1.0673 (1.0186) +2025-08-21,09:20:32 | INFO | Train Epoch: 2 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.92625 (1.0018) Boundary_loss: 0.015444 (0.015398) Loss: 0.94169 (1.0172) +2025-08-21,09:21:29 | INFO | Train Epoch: 2 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 1.0763 (1.0031) Boundary_loss: 0.015391 (0.015397) Loss: 1.0916 (1.0185) +2025-08-21,09:22:26 | INFO | Train Epoch: 2 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.95814 (1.0023) Boundary_loss: 0.015208 (0.015394) Loss: 0.97334 (1.0177) +2025-08-21,09:23:23 | INFO | Train Epoch: 2 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.88035 (1.0001) Boundary_loss: 0.015269 (0.015392) Loss: 0.89562 (1.0155) +2025-08-21,09:24:20 | INFO | Train Epoch: 2 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 0.94782 (0.99922) Boundary_loss: 0.015280 (0.015390) Loss: 0.96310 (1.0146) +2025-08-21,09:25:17 | INFO | Train Epoch: 2 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 0.97222 (0.99876) Boundary_loss: 0.015519 (0.015392) Loss: 0.98774 (1.0142) +2025-08-21,09:26:14 | INFO | Train Epoch: 2 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.94670 (0.99788) Boundary_loss: 0.015361 (0.015392) Loss: 0.96206 (1.0133) +2025-08-21,09:27:11 | INFO | Train Epoch: 2 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.400 Boundary Ratio: 0.252 Contrastive_loss: 1.0572 (0.99887) Boundary_loss: 0.015380 (0.015391) Loss: 1.0726 (1.0143) +2025-08-21,09:28:08 | INFO | Train Epoch: 2 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 1.0051 (0.99897) Boundary_loss: 0.015277 (0.015389) Loss: 1.0204 (1.0144) +2025-08-21,09:29:06 | INFO | Train Epoch: 2 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.94208 (0.99805) Boundary_loss: 0.015365 (0.015389) Loss: 0.95745 (1.0134) +2025-08-21,09:30:03 | INFO | Train Epoch: 2 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.96740 (0.99756) Boundary_loss: 0.015367 (0.015389) Loss: 0.98277 (1.0130) +2025-08-21,09:31:00 | INFO | Train Epoch: 2 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 47.998 Boundary Ratio: 0.245 Contrastive_loss: 1.0734 (0.99875) Boundary_loss: 0.015246 (0.015387) Loss: 1.0887 (1.0141) +2025-08-21,09:31:57 | INFO | Train Epoch: 2 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.96392 (0.99821) Boundary_loss: 0.015355 (0.015386) Loss: 0.97927 (1.0136) +2025-08-21,09:32:54 | INFO | Train Epoch: 2 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 1.0707 (0.99931) Boundary_loss: 0.015321 (0.015385) Loss: 1.0860 (1.0147) +2025-08-21,09:33:52 | INFO | Train Epoch: 2 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 47.887 Boundary Ratio: 0.244 Contrastive_loss: 0.99537 (0.99925) Boundary_loss: 0.015258 (0.015383) Loss: 1.0106 (1.0146) +2025-08-21,09:34:49 | INFO | Train Epoch: 2 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.295 Boundary Ratio: 0.252 Contrastive_loss: 0.95672 (0.99863) Boundary_loss: 0.015201 (0.015380) Loss: 0.97192 (1.0140) +2025-08-21,09:35:46 | INFO | Train Epoch: 2 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 47.428 Boundary Ratio: 0.242 Contrastive_loss: 0.92968 (0.99763) Boundary_loss: 0.015339 (0.015380) Loss: 0.94502 (1.0130) +2025-08-21,09:36:43 | INFO | Train Epoch: 2 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 49.311 Boundary Ratio: 0.252 Contrastive_loss: 1.0497 (0.99837) Boundary_loss: 0.015243 (0.015378) Loss: 1.0650 (1.0137) +2025-08-21,09:37:40 | INFO | Train Epoch: 2 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.91384 (0.99718) Boundary_loss: 0.015331 (0.015377) Loss: 0.92917 (1.0126) +2025-08-21,09:38:38 | INFO | Train Epoch: 2 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 1.0418 (0.99780) Boundary_loss: 0.015343 (0.015377) Loss: 1.0572 (1.0132) +2025-08-21,09:39:35 | INFO | Train Epoch: 2 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 0.94461 (0.99707) Boundary_loss: 0.015347 (0.015376) Loss: 0.95995 (1.0124) +2025-08-21,09:40:32 | INFO | Train Epoch: 2 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 1.0500 (0.99779) Boundary_loss: 0.015428 (0.015377) Loss: 1.0654 (1.0132) +2025-08-21,09:41:29 | INFO | Train Epoch: 2 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 1.1448 (0.99975) Boundary_loss: 0.015292 (0.015376) Loss: 1.1601 (1.0151) +2025-08-21,09:42:27 | INFO | Train Epoch: 2 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 1.0794 (1.0008) Boundary_loss: 0.015307 (0.015375) Loss: 1.0947 (1.0162) +2025-08-21,09:43:24 | INFO | Train Epoch: 2 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 1.0033 (1.0008) Boundary_loss: 0.015362 (0.015375) Loss: 1.0187 (1.0162) +2025-08-21,09:44:21 | INFO | Train Epoch: 2 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.96277 (1.0003) Boundary_loss: 0.015394 (0.015375) Loss: 0.97816 (1.0157) +2025-08-21,09:45:18 | INFO | Train Epoch: 2 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.941 Boundary Ratio: 0.255 Contrastive_loss: 1.0464 (1.0009) Boundary_loss: 0.015557 (0.015377) Loss: 1.0619 (1.0163) +2025-08-21,09:46:15 | INFO | Train Epoch: 2 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.89810 (0.99964) Boundary_loss: 0.015593 (0.015380) Loss: 0.91369 (1.0150) +2025-08-21,09:47:12 | INFO | Train Epoch: 2 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.97375 (0.99932) Boundary_loss: 0.015341 (0.015380) Loss: 0.98909 (1.0147) +2025-08-21,09:48:10 | INFO | Train Epoch: 2 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.424 Boundary Ratio: 0.252 Contrastive_loss: 0.91830 (0.99833) Boundary_loss: 0.015458 (0.015381) Loss: 0.93376 (1.0137) +2025-08-21,09:49:07 | INFO | Train Epoch: 2 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 1.0143 (0.99852) Boundary_loss: 0.015324 (0.015380) Loss: 1.0296 (1.0139) +2025-08-21,09:50:04 | INFO | Train Epoch: 2 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.95928 (0.99806) Boundary_loss: 0.015402 (0.015380) Loss: 0.97468 (1.0134) +2025-08-21,09:51:01 | INFO | Train Epoch: 2 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 1.0142 (0.99825) Boundary_loss: 0.015493 (0.015381) Loss: 1.0297 (1.0136) +2025-08-21,09:51:58 | INFO | Train Epoch: 2 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 47.758 Boundary Ratio: 0.244 Contrastive_loss: 0.86738 (0.99672) Boundary_loss: 0.015387 (0.015382) Loss: 0.88277 (1.0121) +2025-08-21,09:52:56 | INFO | Train Epoch: 2 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.91143 (0.99574) Boundary_loss: 0.015308 (0.015381) Loss: 0.92674 (1.0111) +2025-08-21,09:53:53 | INFO | Train Epoch: 2 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 49.279 Boundary Ratio: 0.251 Contrastive_loss: 1.0021 (0.99582) Boundary_loss: 0.015278 (0.015380) Loss: 1.0174 (1.0112) +2025-08-21,09:54:50 | INFO | Train Epoch: 2 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 49.525 Boundary Ratio: 0.253 Contrastive_loss: 1.0533 (0.99646) Boundary_loss: 0.015265 (0.015378) Loss: 1.0686 (1.0118) +2025-08-21,09:55:47 | INFO | Train Epoch: 2 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 49.592 Boundary Ratio: 0.253 Contrastive_loss: 0.97266 (0.99620) Boundary_loss: 0.015454 (0.015379) Loss: 0.98812 (1.0116) +2025-08-21,09:56:44 | INFO | Train Epoch: 2 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 0.93889 (0.99557) Boundary_loss: 0.015288 (0.015378) Loss: 0.95418 (1.0109) +2025-08-21,09:57:42 | INFO | Train Epoch: 2 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.97104 (0.99530) Boundary_loss: 0.015335 (0.015378) Loss: 0.98637 (1.0107) +2025-08-21,09:58:39 | INFO | Train Epoch: 2 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.95487 (0.99487) Boundary_loss: 0.015262 (0.015376) Loss: 0.97013 (1.0102) +2025-08-21,09:59:36 | INFO | Train Epoch: 2 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.98841 (0.99480) Boundary_loss: 0.015287 (0.015375) Loss: 1.0037 (1.0102) +2025-08-21,10:00:33 | INFO | Train Epoch: 2 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 49.344 Boundary Ratio: 0.252 Contrastive_loss: 0.98252 (0.99467) Boundary_loss: 0.015489 (0.015377) Loss: 0.99801 (1.0100) +2025-08-21,10:01:31 | INFO | Train Epoch: 2 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.88315 (0.99351) Boundary_loss: 0.015373 (0.015377) Loss: 0.89853 (1.0089) +2025-08-21,10:02:28 | INFO | Train Epoch: 2 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.97747 (0.99334) Boundary_loss: 0.015300 (0.015376) Loss: 0.99277 (1.0087) +2025-08-21,10:03:25 | INFO | Train Epoch: 2 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 47.588 Boundary Ratio: 0.243 Contrastive_loss: 0.87795 (0.99216) Boundary_loss: 0.015366 (0.015376) Loss: 0.89332 (1.0075) +2025-08-21,10:04:22 | INFO | Train Epoch: 2 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.307 Boundary Ratio: 0.252 Contrastive_loss: 0.95277 (0.99177) Boundary_loss: 0.015375 (0.015376) Loss: 0.96814 (1.0071) +2025-08-21,10:05:19 | INFO | Train Epoch: 2 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.98459 (0.99169) Boundary_loss: 0.015321 (0.015375) Loss: 0.99991 (1.0071) +2025-08-21,10:06:17 | INFO | Train Epoch: 2 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 1.0165 (0.99194) Boundary_loss: 0.015190 (0.015373) Loss: 1.0317 (1.0073) +2025-08-21,10:07:14 | INFO | Train Epoch: 2 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 1.0061 (0.99208) Boundary_loss: 0.015348 (0.015373) Loss: 1.0215 (1.0075) +2025-08-21,10:08:11 | INFO | Train Epoch: 2 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 47.658 Boundary Ratio: 0.243 Contrastive_loss: 0.89981 (0.99118) Boundary_loss: 0.015398 (0.015373) Loss: 0.91520 (1.0066) +2025-08-21,10:09:08 | INFO | Train Epoch: 2 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 0.83096 (0.98964) Boundary_loss: 0.015331 (0.015373) Loss: 0.84629 (1.0050) +2025-08-21,10:10:05 | INFO | Train Epoch: 2 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 0.96797 (0.98944) Boundary_loss: 0.015336 (0.015373) Loss: 0.98330 (1.0048) +2025-08-21,10:11:03 | INFO | Train Epoch: 2 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.170 Boundary Ratio: 0.246 Contrastive_loss: 0.83980 (0.98802) Boundary_loss: 0.015352 (0.015372) Loss: 0.85515 (1.0034) +2025-08-21,10:12:00 | INFO | Train Epoch: 2 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.82159 (0.98647) Boundary_loss: 0.015273 (0.015371) Loss: 0.83686 (1.0018) +2025-08-21,10:12:57 | INFO | Train Epoch: 2 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.98625 (0.98647) Boundary_loss: 0.015417 (0.015372) Loss: 1.0017 (1.0018) +2025-08-21,10:13:54 | INFO | Train Epoch: 2 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 1.0100 (0.98668) Boundary_loss: 0.015273 (0.015371) Loss: 1.0253 (1.0021) +2025-08-21,10:14:51 | INFO | Train Epoch: 2 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.90200 (0.98591) Boundary_loss: 0.015416 (0.015371) Loss: 0.91741 (1.0013) +2025-08-21,10:15:48 | INFO | Train Epoch: 2 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.96984 (0.98577) Boundary_loss: 0.015324 (0.015371) Loss: 0.98516 (1.0011) +2025-08-21,10:16:45 | INFO | Train Epoch: 2 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.94084 (0.98537) Boundary_loss: 0.015159 (0.015369) Loss: 0.95600 (1.0007) +2025-08-21,10:17:42 | INFO | Train Epoch: 2 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.79480 (0.98368) Boundary_loss: 0.015368 (0.015369) Loss: 0.81016 (0.99905) +2025-08-21,10:18:39 | INFO | Train Epoch: 2 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 47.816 Boundary Ratio: 0.244 Contrastive_loss: 0.85579 (0.98256) Boundary_loss: 0.015346 (0.015369) Loss: 0.87114 (0.99793) +2025-08-21,10:19:37 | INFO | Train Epoch: 2 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 49.633 Boundary Ratio: 0.253 Contrastive_loss: 0.94793 (0.98226) Boundary_loss: 0.015473 (0.015370) Loss: 0.96340 (0.99763) +2025-08-21,10:20:34 | INFO | Train Epoch: 2 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 0.81012 (0.98077) Boundary_loss: 0.015368 (0.015370) Loss: 0.82549 (0.99614) +2025-08-21,10:21:31 | INFO | Train Epoch: 2 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 1.0132 (0.98105) Boundary_loss: 0.015427 (0.015370) Loss: 1.0286 (0.99642) +2025-08-21,10:22:28 | INFO | Train Epoch: 2 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 1.0744 (0.98184) Boundary_loss: 0.015330 (0.015370) Loss: 1.0897 (0.99721) +2025-08-21,10:23:25 | INFO | Train Epoch: 2 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.354 Boundary Ratio: 0.247 Contrastive_loss: 1.0142 (0.98211) Boundary_loss: 0.015349 (0.015370) Loss: 1.0295 (0.99748) +2025-08-21,10:24:23 | INFO | Train Epoch: 2 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 49.381 Boundary Ratio: 0.252 Contrastive_loss: 0.95188 (0.98186) Boundary_loss: 0.015173 (0.015368) Loss: 0.96705 (0.99723) +2025-08-21,10:25:20 | INFO | Train Epoch: 2 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 1.0466 (0.98240) Boundary_loss: 0.015307 (0.015368) Loss: 1.0619 (0.99776) +2025-08-21,10:26:17 | INFO | Train Epoch: 2 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.85458 (0.98135) Boundary_loss: 0.015348 (0.015367) Loss: 0.86993 (0.99672) +2025-08-21,10:27:14 | INFO | Train Epoch: 2 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.89874 (0.98068) Boundary_loss: 0.015465 (0.015368) Loss: 0.91420 (0.99604) +2025-08-21,10:28:11 | INFO | Train Epoch: 2 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 49.809 Boundary Ratio: 0.254 Contrastive_loss: 0.92127 (0.98020) Boundary_loss: 0.015409 (0.015369) Loss: 0.93668 (0.99557) +2025-08-21,10:29:09 | INFO | Train Epoch: 2 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 0.93233 (0.97981) Boundary_loss: 0.015346 (0.015368) Loss: 0.94768 (0.99518) +2025-08-21,10:30:06 | INFO | Train Epoch: 2 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.98556 (0.97986) Boundary_loss: 0.015300 (0.015368) Loss: 1.0009 (0.99523) +2025-08-21,10:31:03 | INFO | Train Epoch: 2 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.506 Boundary Ratio: 0.253 Contrastive_loss: 0.87100 (0.97900) Boundary_loss: 0.015398 (0.015368) Loss: 0.88639 (0.99437) +2025-08-21,10:32:00 | INFO | Train Epoch: 2 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 47.850 Boundary Ratio: 0.244 Contrastive_loss: 1.0133 (0.97927) Boundary_loss: 0.015330 (0.015368) Loss: 1.0286 (0.99464) +2025-08-21,10:32:57 | INFO | Train Epoch: 2 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.99422 (0.97939) Boundary_loss: 0.015310 (0.015367) Loss: 1.0095 (0.99475) +2025-08-21,10:33:54 | INFO | Train Epoch: 2 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.94878 (0.97915) Boundary_loss: 0.015375 (0.015367) Loss: 0.96415 (0.99452) +2025-08-21,10:34:51 | INFO | Train Epoch: 2 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 47.844 Boundary Ratio: 0.244 Contrastive_loss: 0.86029 (0.97824) Boundary_loss: 0.015403 (0.015368) Loss: 0.87569 (0.99361) +2025-08-21,10:35:48 | INFO | Train Epoch: 2 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.97239 (0.97820) Boundary_loss: 0.015299 (0.015367) Loss: 0.98769 (0.99357) +2025-08-21,10:36:45 | INFO | Train Epoch: 2 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.553 Boundary Ratio: 0.253 Contrastive_loss: 0.98376 (0.97824) Boundary_loss: 0.015416 (0.015367) Loss: 0.99917 (0.99361) +2025-08-21,10:37:42 | INFO | Train Epoch: 2 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.375 Boundary Ratio: 0.252 Contrastive_loss: 0.93600 (0.97793) Boundary_loss: 0.015447 (0.015368) Loss: 0.95144 (0.99329) +2025-08-21,10:38:40 | INFO | Train Epoch: 2 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.97351 (0.97789) Boundary_loss: 0.015379 (0.015368) Loss: 0.98889 (0.99326) +2025-08-21,10:39:37 | INFO | Train Epoch: 2 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.97864 (0.97790) Boundary_loss: 0.015302 (0.015368) Loss: 0.99394 (0.99327) +2025-08-21,10:40:34 | INFO | Train Epoch: 2 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.277 Boundary Ratio: 0.246 Contrastive_loss: 0.99748 (0.97804) Boundary_loss: 0.015270 (0.015367) Loss: 1.0127 (0.99341) +2025-08-21,10:41:31 | INFO | Train Epoch: 2 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 1.0055 (0.97824) Boundary_loss: 0.015359 (0.015367) Loss: 1.0209 (0.99361) +2025-08-21,10:42:29 | INFO | Train Epoch: 2 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.96489 (0.97815) Boundary_loss: 0.015458 (0.015368) Loss: 0.98035 (0.99351) +2025-08-21,10:43:26 | INFO | Train Epoch: 2 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 49.387 Boundary Ratio: 0.252 Contrastive_loss: 0.91668 (0.97771) Boundary_loss: 0.015119 (0.015366) Loss: 0.93179 (0.99307) +2025-08-21,10:44:23 | INFO | Train Epoch: 2 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.061 Boundary Ratio: 0.245 Contrastive_loss: 0.91336 (0.97725) Boundary_loss: 0.015275 (0.015365) Loss: 0.92864 (0.99261) +2025-08-21,10:45:20 | INFO | Train Epoch: 2 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 49.635 Boundary Ratio: 0.253 Contrastive_loss: 0.92111 (0.97685) Boundary_loss: 0.015197 (0.015364) Loss: 0.93631 (0.99222) +2025-08-21,10:46:17 | INFO | Train Epoch: 2 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 0.97436 (0.97684) Boundary_loss: 0.015348 (0.015364) Loss: 0.98971 (0.99220) +2025-08-21,10:47:15 | INFO | Train Epoch: 2 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.521 Boundary Ratio: 0.253 Contrastive_loss: 1.0116 (0.97708) Boundary_loss: 0.015333 (0.015364) Loss: 1.0269 (0.99244) +2025-08-21,10:48:12 | INFO | Train Epoch: 2 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 1.0184 (0.97736) Boundary_loss: 0.015511 (0.015365) Loss: 1.0339 (0.99273) +2025-08-21,10:49:09 | INFO | Train Epoch: 2 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.86582 (0.97660) Boundary_loss: 0.015298 (0.015364) Loss: 0.88111 (0.99196) +2025-08-21,10:50:06 | INFO | Train Epoch: 2 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 49.471 Boundary Ratio: 0.252 Contrastive_loss: 0.85104 (0.97574) Boundary_loss: 0.015538 (0.015365) Loss: 0.86658 (0.99111) +2025-08-21,10:51:03 | INFO | Train Epoch: 2 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 0.95838 (0.97563) Boundary_loss: 0.015310 (0.015365) Loss: 0.97369 (0.99099) +2025-08-21,10:52:01 | INFO | Train Epoch: 2 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 0.84683 (0.97476) Boundary_loss: 0.015244 (0.015364) Loss: 0.86207 (0.99013) +2025-08-21,10:52:58 | INFO | Train Epoch: 2 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.77672 (0.97344) Boundary_loss: 0.015328 (0.015364) Loss: 0.79205 (0.98881) +2025-08-21,10:53:55 | INFO | Train Epoch: 2 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 47.713 Boundary Ratio: 0.243 Contrastive_loss: 0.95511 (0.97332) Boundary_loss: 0.015473 (0.015365) Loss: 0.97058 (0.98869) +2025-08-21,10:54:52 | INFO | Train Epoch: 2 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.92613 (0.97301) Boundary_loss: 0.015379 (0.015365) Loss: 0.94151 (0.98838) +2025-08-21,10:55:49 | INFO | Train Epoch: 2 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.97198 (0.97300) Boundary_loss: 0.015448 (0.015365) Loss: 0.98743 (0.98837) +2025-08-21,10:56:46 | INFO | Train Epoch: 2 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 49.768 Boundary Ratio: 0.254 Contrastive_loss: 0.95775 (0.97291) Boundary_loss: 0.015461 (0.015366) Loss: 0.97322 (0.98827) +2025-08-21,10:57:43 | INFO | Train Epoch: 2 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 1.0311 (0.97328) Boundary_loss: 0.015291 (0.015365) Loss: 1.0464 (0.98865) +2025-08-21,10:58:41 | INFO | Train Epoch: 2 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 47.680 Boundary Ratio: 0.243 Contrastive_loss: 0.92152 (0.97295) Boundary_loss: 0.015395 (0.015366) Loss: 0.93691 (0.98831) +2025-08-21,10:59:38 | INFO | Train Epoch: 2 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 49.510 Boundary Ratio: 0.253 Contrastive_loss: 0.81082 (0.97192) Boundary_loss: 0.015374 (0.015366) Loss: 0.82619 (0.98728) +2025-08-21,11:00:35 | INFO | Train Epoch: 2 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.83558 (0.97105) Boundary_loss: 0.015236 (0.015365) Loss: 0.85082 (0.98642) +2025-08-21,11:01:32 | INFO | Train Epoch: 2 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.436 Boundary Ratio: 0.252 Contrastive_loss: 0.95021 (0.97092) Boundary_loss: 0.015303 (0.015364) Loss: 0.96552 (0.98629) +2025-08-21,11:02:29 | INFO | Train Epoch: 2 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.088 Boundary Ratio: 0.245 Contrastive_loss: 1.0200 (0.97123) Boundary_loss: 0.015565 (0.015366) Loss: 1.0355 (0.98659) +2025-08-21,11:03:26 | INFO | Train Epoch: 2 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 49.611 Boundary Ratio: 0.253 Contrastive_loss: 0.98618 (0.97132) Boundary_loss: 0.015357 (0.015366) Loss: 1.0015 (0.98669) +2025-08-21,11:04:23 | INFO | Train Epoch: 2 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.86327 (0.97065) Boundary_loss: 0.015242 (0.015365) Loss: 0.87851 (0.98602) +2025-08-21,11:05:20 | INFO | Train Epoch: 2 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.289 Boundary Ratio: 0.246 Contrastive_loss: 0.87500 (0.97007) Boundary_loss: 0.015282 (0.015364) Loss: 0.89028 (0.98543) +2025-08-21,11:06:18 | INFO | Train Epoch: 2 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 0.96293 (0.97002) Boundary_loss: 0.015508 (0.015365) Loss: 0.97844 (0.98539) +2025-08-21,11:07:15 | INFO | Train Epoch: 2 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 0.78831 (0.96892) Boundary_loss: 0.015335 (0.015365) Loss: 0.80365 (0.98429) +2025-08-21,11:08:12 | INFO | Train Epoch: 2 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.91863 (0.96862) Boundary_loss: 0.015386 (0.015365) Loss: 0.93401 (0.98399) +2025-08-21,11:09:09 | INFO | Train Epoch: 2 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 49.365 Boundary Ratio: 0.252 Contrastive_loss: 0.88471 (0.96812) Boundary_loss: 0.015379 (0.015365) Loss: 0.90009 (0.98348) +2025-08-21,11:10:06 | INFO | Train Epoch: 2 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 0.79932 (0.96711) Boundary_loss: 0.015203 (0.015364) Loss: 0.81452 (0.98248) +2025-08-21,11:11:03 | INFO | Train Epoch: 2 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.86560 (0.96651) Boundary_loss: 0.015352 (0.015364) Loss: 0.88095 (0.98188) +2025-08-21,11:12:00 | INFO | Train Epoch: 2 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.92872 (0.96629) Boundary_loss: 0.015321 (0.015364) Loss: 0.94404 (0.98165) +2025-08-21,11:12:57 | INFO | Train Epoch: 2 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 47.514 Boundary Ratio: 0.242 Contrastive_loss: 0.97773 (0.96636) Boundary_loss: 0.015147 (0.015363) Loss: 0.99288 (0.98172) +2025-08-21,11:13:54 | INFO | Train Epoch: 2 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.88834 (0.96590) Boundary_loss: 0.015297 (0.015362) Loss: 0.90363 (0.98127) +2025-08-21,11:14:51 | INFO | Train Epoch: 2 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 50.031 Boundary Ratio: 0.255 Contrastive_loss: 0.85385 (0.96526) Boundary_loss: 0.015506 (0.015363) Loss: 0.86935 (0.98062) +2025-08-21,11:15:48 | INFO | Train Epoch: 2 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.189 Boundary Ratio: 0.246 Contrastive_loss: 0.83984 (0.96453) Boundary_loss: 0.015339 (0.015363) Loss: 0.85518 (0.97990) +2025-08-21,11:16:46 | INFO | Train Epoch: 2 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.95200 (0.96446) Boundary_loss: 0.015290 (0.015363) Loss: 0.96729 (0.97983) +2025-08-21,11:17:43 | INFO | Train Epoch: 2 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.92016 (0.96421) Boundary_loss: 0.015285 (0.015362) Loss: 0.93544 (0.97957) +2025-08-21,11:18:40 | INFO | Train Epoch: 2 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 46.828 Boundary Ratio: 0.239 Contrastive_loss: 0.89652 (0.96383) Boundary_loss: 0.015564 (0.015363) Loss: 0.91209 (0.97919) +2025-08-21,11:19:37 | INFO | Train Epoch: 2 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 49.668 Boundary Ratio: 0.253 Contrastive_loss: 0.96928 (0.96386) Boundary_loss: 0.015469 (0.015364) Loss: 0.98475 (0.97922) +2025-08-21,11:20:34 | INFO | Train Epoch: 2 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.191 Boundary Ratio: 0.246 Contrastive_loss: 0.92737 (0.96366) Boundary_loss: 0.015374 (0.015364) Loss: 0.94274 (0.97902) +2025-08-21,11:21:32 | INFO | Train Epoch: 2 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.89164 (0.96326) Boundary_loss: 0.015389 (0.015364) Loss: 0.90703 (0.97862) +2025-08-21,11:22:29 | INFO | Train Epoch: 2 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 47.744 Boundary Ratio: 0.244 Contrastive_loss: 0.94468 (0.96315) Boundary_loss: 0.015384 (0.015364) Loss: 0.96006 (0.97852) +2025-08-21,11:23:26 | INFO | Train Epoch: 2 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.80213 (0.96227) Boundary_loss: 0.015389 (0.015364) Loss: 0.81752 (0.97763) +2025-08-21,11:24:23 | INFO | Train Epoch: 2 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.91424 (0.96201) Boundary_loss: 0.015414 (0.015365) Loss: 0.92966 (0.97737) +2025-08-21,11:25:20 | INFO | Train Epoch: 2 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.96753 (0.96204) Boundary_loss: 0.015367 (0.015365) Loss: 0.98290 (0.97740) +2025-08-21,11:26:17 | INFO | Train Epoch: 2 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.86750 (0.96152) Boundary_loss: 0.015327 (0.015364) Loss: 0.88283 (0.97689) +2025-08-21,11:27:14 | INFO | Train Epoch: 2 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.99438 (0.96170) Boundary_loss: 0.015231 (0.015364) Loss: 1.0096 (0.97707) +2025-08-21,11:28:12 | INFO | Train Epoch: 2 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 0.89454 (0.96134) Boundary_loss: 0.015294 (0.015363) Loss: 0.90983 (0.97671) +2025-08-21,11:29:09 | INFO | Train Epoch: 2 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.86933 (0.96085) Boundary_loss: 0.015466 (0.015364) Loss: 0.88480 (0.97622) +2025-08-21,11:30:06 | INFO | Train Epoch: 2 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.174 Boundary Ratio: 0.246 Contrastive_loss: 0.88056 (0.96043) Boundary_loss: 0.015160 (0.015363) Loss: 0.89572 (0.97579) +2025-08-21,11:31:03 | INFO | Train Epoch: 2 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.199 Boundary Ratio: 0.246 Contrastive_loss: 0.93594 (0.96030) Boundary_loss: 0.015459 (0.015363) Loss: 0.95140 (0.97566) +2025-08-21,11:32:00 | INFO | Train Epoch: 2 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.89707 (0.95997) Boundary_loss: 0.015230 (0.015363) Loss: 0.91230 (0.97533) +2025-08-21,11:32:58 | INFO | Train Epoch: 2 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 1.0139 (0.96025) Boundary_loss: 0.015398 (0.015363) Loss: 1.0293 (0.97561) +2025-08-21,11:33:54 | INFO | Train Epoch: 2 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 47.391 Boundary Ratio: 0.242 Contrastive_loss: 1.0090 (0.96050) Boundary_loss: 0.015388 (0.015363) Loss: 1.0244 (0.97586) +2025-08-21,11:34:52 | INFO | Train Epoch: 2 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 0.89715 (0.96017) Boundary_loss: 0.015317 (0.015363) Loss: 0.91247 (0.97554) +2025-08-21,11:35:49 | INFO | Train Epoch: 2 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.81122 (0.95941) Boundary_loss: 0.015582 (0.015364) Loss: 0.82680 (0.97477) +2025-08-21,11:36:46 | INFO | Train Epoch: 2 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 49.373 Boundary Ratio: 0.252 Contrastive_loss: 0.98064 (0.95952) Boundary_loss: 0.015299 (0.015363) Loss: 0.99594 (0.97488) +2025-08-21,11:37:43 | INFO | Train Epoch: 2 [10035712/26365952 (38%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 0.98744 (0.95966) Boundary_loss: 0.015211 (0.015363) Loss: 1.0026 (0.97502) +2025-08-21,11:38:40 | INFO | Train Epoch: 2 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.459 Boundary Ratio: 0.252 Contrastive_loss: 0.82643 (0.95899) Boundary_loss: 0.015455 (0.015363) Loss: 0.84188 (0.97435) +2025-08-21,11:39:37 | INFO | Train Epoch: 2 [10138112/26365952 (38%)] Avg Boundaries (per batch): 47.750 Boundary Ratio: 0.244 Contrastive_loss: 0.85913 (0.95849) Boundary_loss: 0.015618 (0.015364) Loss: 0.87474 (0.97385) +2025-08-21,11:40:35 | INFO | Train Epoch: 2 [10189312/26365952 (39%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.96874 (0.95854) Boundary_loss: 0.015566 (0.015365) Loss: 0.98431 (0.97390) +2025-08-21,11:41:32 | INFO | Train Epoch: 2 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.688 Boundary Ratio: 0.254 Contrastive_loss: 1.0412 (0.95895) Boundary_loss: 0.015443 (0.015366) Loss: 1.0566 (0.97431) +2025-08-21,11:42:29 | INFO | Train Epoch: 2 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.79282 (0.95813) Boundary_loss: 0.015229 (0.015365) Loss: 0.80805 (0.97349) +2025-08-21,11:43:26 | INFO | Train Epoch: 2 [10342912/26365952 (39%)] Avg Boundaries (per batch): 50.057 Boundary Ratio: 0.255 Contrastive_loss: 0.94234 (0.95805) Boundary_loss: 0.015426 (0.015365) Loss: 0.95776 (0.97341) +2025-08-21,11:44:24 | INFO | Train Epoch: 2 [10394112/26365952 (39%)] Avg Boundaries (per batch): 49.436 Boundary Ratio: 0.252 Contrastive_loss: 0.81570 (0.95735) Boundary_loss: 0.015379 (0.015366) Loss: 0.83108 (0.97272) +2025-08-21,11:45:21 | INFO | Train Epoch: 2 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.88143 (0.95698) Boundary_loss: 0.015395 (0.015366) Loss: 0.89683 (0.97235) +2025-08-21,11:46:18 | INFO | Train Epoch: 2 [10496512/26365952 (40%)] Avg Boundaries (per batch): 47.744 Boundary Ratio: 0.244 Contrastive_loss: 0.91396 (0.95677) Boundary_loss: 0.015357 (0.015366) Loss: 0.92932 (0.97214) +2025-08-21,11:47:15 | INFO | Train Epoch: 2 [10547712/26365952 (40%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.98315 (0.95690) Boundary_loss: 0.015445 (0.015366) Loss: 0.99859 (0.97226) +2025-08-21,11:48:12 | INFO | Train Epoch: 2 [10598912/26365952 (40%)] Avg Boundaries (per batch): 49.424 Boundary Ratio: 0.252 Contrastive_loss: 0.87247 (0.95649) Boundary_loss: 0.015406 (0.015366) Loss: 0.88787 (0.97186) +2025-08-21,11:49:10 | INFO | Train Epoch: 2 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.83945 (0.95593) Boundary_loss: 0.015346 (0.015366) Loss: 0.85480 (0.97130) +2025-08-21,11:50:07 | INFO | Train Epoch: 2 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 1.0029 (0.95616) Boundary_loss: 0.015282 (0.015366) Loss: 1.0182 (0.97152) +2025-08-21,11:51:04 | INFO | Train Epoch: 2 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.309 Boundary Ratio: 0.252 Contrastive_loss: 0.95665 (0.95616) Boundary_loss: 0.015513 (0.015366) Loss: 0.97217 (0.97153) +2025-08-21,11:52:01 | INFO | Train Epoch: 2 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.084 Boundary Ratio: 0.245 Contrastive_loss: 0.80561 (0.95545) Boundary_loss: 0.015431 (0.015367) Loss: 0.82104 (0.97082) +2025-08-21,11:52:58 | INFO | Train Epoch: 2 [10854912/26365952 (41%)] Avg Boundaries (per batch): 49.357 Boundary Ratio: 0.252 Contrastive_loss: 0.85089 (0.95496) Boundary_loss: 0.015415 (0.015367) Loss: 0.86630 (0.97032) +2025-08-21,11:53:55 | INFO | Train Epoch: 2 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.201 Boundary Ratio: 0.246 Contrastive_loss: 0.83793 (0.95441) Boundary_loss: 0.015461 (0.015367) Loss: 0.85339 (0.96978) +2025-08-21,11:54:53 | INFO | Train Epoch: 2 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.87701 (0.95405) Boundary_loss: 0.015338 (0.015367) Loss: 0.89234 (0.96942) +2025-08-21,11:55:49 | INFO | Train Epoch: 2 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.811 Boundary Ratio: 0.254 Contrastive_loss: 0.89331 (0.95377) Boundary_loss: 0.015324 (0.015367) Loss: 0.90864 (0.96914) +2025-08-21,11:56:47 | INFO | Train Epoch: 2 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.410 Boundary Ratio: 0.252 Contrastive_loss: 1.0066 (0.95401) Boundary_loss: 0.015214 (0.015366) Loss: 1.0219 (0.96938) +2025-08-21,11:57:44 | INFO | Train Epoch: 2 [11110912/26365952 (42%)] Avg Boundaries (per batch): 47.893 Boundary Ratio: 0.244 Contrastive_loss: 0.83182 (0.95345) Boundary_loss: 0.015328 (0.015366) Loss: 0.84715 (0.96882) +2025-08-21,11:58:41 | INFO | Train Epoch: 2 [11162112/26365952 (42%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 0.94552 (0.95342) Boundary_loss: 0.015248 (0.015366) Loss: 0.96076 (0.96878) +2025-08-21,11:59:38 | INFO | Train Epoch: 2 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 1.0026 (0.95364) Boundary_loss: 0.015381 (0.015366) Loss: 1.0180 (0.96901) +2025-08-21,12:00:36 | INFO | Train Epoch: 2 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.80866 (0.95298) Boundary_loss: 0.015369 (0.015366) Loss: 0.82403 (0.96835) +2025-08-21,12:01:33 | INFO | Train Epoch: 2 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.289 Boundary Ratio: 0.246 Contrastive_loss: 0.93106 (0.95289) Boundary_loss: 0.015384 (0.015366) Loss: 0.94644 (0.96825) +2025-08-21,12:02:30 | INFO | Train Epoch: 2 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 0.88030 (0.95256) Boundary_loss: 0.015249 (0.015365) Loss: 0.89555 (0.96793) +2025-08-21,12:03:27 | INFO | Train Epoch: 2 [11418112/26365952 (43%)] Avg Boundaries (per batch): 47.775 Boundary Ratio: 0.244 Contrastive_loss: 1.0407 (0.95295) Boundary_loss: 0.015286 (0.015365) Loss: 1.0560 (0.96832) +2025-08-21,12:04:24 | INFO | Train Epoch: 2 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.131 Boundary Ratio: 0.246 Contrastive_loss: 0.98236 (0.95308) Boundary_loss: 0.015355 (0.015365) Loss: 0.99772 (0.96845) +2025-08-21,12:05:21 | INFO | Train Epoch: 2 [11520512/26365952 (44%)] Avg Boundaries (per batch): 50.033 Boundary Ratio: 0.255 Contrastive_loss: 1.0882 (0.95368) Boundary_loss: 0.015449 (0.015365) Loss: 1.1036 (0.96905) +2025-08-21,12:06:18 | INFO | Train Epoch: 2 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.91555 (0.95351) Boundary_loss: 0.015251 (0.015365) Loss: 0.93080 (0.96888) +2025-08-21,12:07:16 | INFO | Train Epoch: 2 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.328 Boundary Ratio: 0.247 Contrastive_loss: 0.85337 (0.95307) Boundary_loss: 0.015302 (0.015364) Loss: 0.86867 (0.96844) +2025-08-21,12:08:13 | INFO | Train Epoch: 2 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.684 Boundary Ratio: 0.253 Contrastive_loss: 0.86363 (0.95268) Boundary_loss: 0.015286 (0.015364) Loss: 0.87891 (0.96805) +2025-08-21,12:09:10 | INFO | Train Epoch: 2 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.92391 (0.95256) Boundary_loss: 0.015291 (0.015364) Loss: 0.93920 (0.96792) +2025-08-21,12:10:07 | INFO | Train Epoch: 2 [11776512/26365952 (45%)] Avg Boundaries (per batch): 49.404 Boundary Ratio: 0.252 Contrastive_loss: 0.79040 (0.95186) Boundary_loss: 0.015417 (0.015364) Loss: 0.80582 (0.96722) +2025-08-21,12:11:04 | INFO | Train Epoch: 2 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 0.78832 (0.95115) Boundary_loss: 0.015456 (0.015364) Loss: 0.80377 (0.96652) +2025-08-21,12:12:02 | INFO | Train Epoch: 2 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.94195 (0.95111) Boundary_loss: 0.015407 (0.015365) Loss: 0.95736 (0.96648) +2025-08-21,12:12:59 | INFO | Train Epoch: 2 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.93031 (0.95102) Boundary_loss: 0.015422 (0.015365) Loss: 0.94573 (0.96639) +2025-08-21,12:13:56 | INFO | Train Epoch: 2 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.86269 (0.95065) Boundary_loss: 0.015177 (0.015364) Loss: 0.87787 (0.96601) +2025-08-21,12:14:53 | INFO | Train Epoch: 2 [12032512/26365952 (46%)] Avg Boundaries (per batch): 49.311 Boundary Ratio: 0.252 Contrastive_loss: 0.86262 (0.95027) Boundary_loss: 0.015528 (0.015365) Loss: 0.87814 (0.96564) +2025-08-21,12:15:50 | INFO | Train Epoch: 2 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.95464 (0.95029) Boundary_loss: 0.015179 (0.015364) Loss: 0.96982 (0.96566) +2025-08-21,12:16:47 | INFO | Train Epoch: 2 [12134912/26365952 (46%)] Avg Boundaries (per batch): 49.688 Boundary Ratio: 0.254 Contrastive_loss: 0.89326 (0.95005) Boundary_loss: 0.015614 (0.015365) Loss: 0.90887 (0.96542) +2025-08-21,12:17:45 | INFO | Train Epoch: 2 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.141 Boundary Ratio: 0.246 Contrastive_loss: 0.87928 (0.94976) Boundary_loss: 0.015397 (0.015365) Loss: 0.89468 (0.96512) +2025-08-21,12:18:42 | INFO | Train Epoch: 2 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.75026 (0.94893) Boundary_loss: 0.015258 (0.015365) Loss: 0.76552 (0.96429) +2025-08-21,12:19:39 | INFO | Train Epoch: 2 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.330 Boundary Ratio: 0.247 Contrastive_loss: 0.91015 (0.94877) Boundary_loss: 0.015289 (0.015364) Loss: 0.92544 (0.96413) +2025-08-21,12:20:36 | INFO | Train Epoch: 2 [12339712/26365952 (47%)] Avg Boundaries (per batch): 49.494 Boundary Ratio: 0.253 Contrastive_loss: 0.87320 (0.94845) Boundary_loss: 0.015564 (0.015365) Loss: 0.88876 (0.96382) +2025-08-21,12:21:33 | INFO | Train Epoch: 2 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.99447 (0.94864) Boundary_loss: 0.015324 (0.015365) Loss: 1.0098 (0.96401) +2025-08-21,12:22:31 | INFO | Train Epoch: 2 [12442112/26365952 (47%)] Avg Boundaries (per batch): 49.400 Boundary Ratio: 0.252 Contrastive_loss: 0.99723 (0.94884) Boundary_loss: 0.015470 (0.015365) Loss: 1.0127 (0.96421) +2025-08-21,12:23:28 | INFO | Train Epoch: 2 [12493312/26365952 (47%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.81548 (0.94830) Boundary_loss: 0.015227 (0.015365) Loss: 0.83071 (0.96366) +2025-08-21,12:24:25 | INFO | Train Epoch: 2 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.322 Boundary Ratio: 0.247 Contrastive_loss: 0.76226 (0.94754) Boundary_loss: 0.015461 (0.015365) Loss: 0.77772 (0.96291) +2025-08-21,12:25:22 | INFO | Train Epoch: 2 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.92872 (0.94746) Boundary_loss: 0.015328 (0.015365) Loss: 0.94405 (0.96283) +2025-08-21,12:26:19 | INFO | Train Epoch: 2 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 1.0428 (0.94785) Boundary_loss: 0.015267 (0.015365) Loss: 1.0581 (0.96321) +2025-08-21,12:27:16 | INFO | Train Epoch: 2 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.139 Boundary Ratio: 0.246 Contrastive_loss: 0.92080 (0.94774) Boundary_loss: 0.015382 (0.015365) Loss: 0.93618 (0.96311) +2025-08-21,12:28:13 | INFO | Train Epoch: 2 [12749312/26365952 (48%)] Avg Boundaries (per batch): 49.896 Boundary Ratio: 0.255 Contrastive_loss: 0.87160 (0.94744) Boundary_loss: 0.015271 (0.015364) Loss: 0.88687 (0.96280) +2025-08-21,12:29:10 | INFO | Train Epoch: 2 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.82777 (0.94696) Boundary_loss: 0.015477 (0.015365) Loss: 0.84324 (0.96232) +2025-08-21,12:30:08 | INFO | Train Epoch: 2 [12851712/26365952 (49%)] Avg Boundaries (per batch): 47.998 Boundary Ratio: 0.245 Contrastive_loss: 0.82944 (0.94649) Boundary_loss: 0.015532 (0.015366) Loss: 0.84497 (0.96186) +2025-08-21,12:31:05 | INFO | Train Epoch: 2 [12902912/26365952 (49%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.89155 (0.94628) Boundary_loss: 0.015491 (0.015366) Loss: 0.90704 (0.96164) +2025-08-21,12:32:02 | INFO | Train Epoch: 2 [12954112/26365952 (49%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.99398 (0.94646) Boundary_loss: 0.015425 (0.015366) Loss: 1.0094 (0.96183) +2025-08-21,12:32:59 | INFO | Train Epoch: 2 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.87805 (0.94620) Boundary_loss: 0.015241 (0.015366) Loss: 0.89329 (0.96156) +2025-08-21,12:33:57 | INFO | Train Epoch: 2 [13056512/26365952 (50%)] Avg Boundaries (per batch): 49.303 Boundary Ratio: 0.252 Contrastive_loss: 0.91643 (0.94608) Boundary_loss: 0.015266 (0.015365) Loss: 0.93169 (0.96144) +2025-08-21,12:34:54 | INFO | Train Epoch: 2 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.89206 (0.94587) Boundary_loss: 0.015401 (0.015366) Loss: 0.90746 (0.96123) +2025-08-21,12:35:51 | INFO | Train Epoch: 2 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.84824 (0.94549) Boundary_loss: 0.015379 (0.015366) Loss: 0.86361 (0.96086) +2025-08-21,12:36:48 | INFO | Train Epoch: 2 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.279 Boundary Ratio: 0.251 Contrastive_loss: 0.85139 (0.94513) Boundary_loss: 0.015252 (0.015365) Loss: 0.86665 (0.96049) +2025-08-21,12:37:45 | INFO | Train Epoch: 2 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.375 Boundary Ratio: 0.247 Contrastive_loss: 0.83170 (0.94469) Boundary_loss: 0.015380 (0.015365) Loss: 0.84708 (0.96006) +2025-08-21,12:38:42 | INFO | Train Epoch: 2 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.145 Boundary Ratio: 0.246 Contrastive_loss: 0.86212 (0.94437) Boundary_loss: 0.015371 (0.015365) Loss: 0.87749 (0.95974) +2025-08-21,12:39:40 | INFO | Train Epoch: 2 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.328 Boundary Ratio: 0.247 Contrastive_loss: 0.91502 (0.94426) Boundary_loss: 0.015320 (0.015365) Loss: 0.93034 (0.95963) +2025-08-21,12:40:37 | INFO | Train Epoch: 2 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.94683 (0.94427) Boundary_loss: 0.015410 (0.015365) Loss: 0.96224 (0.95964) +2025-08-21,12:41:34 | INFO | Train Epoch: 2 [13466112/26365952 (51%)] Avg Boundaries (per batch): 47.576 Boundary Ratio: 0.243 Contrastive_loss: 0.88860 (0.94406) Boundary_loss: 0.015347 (0.015365) Loss: 0.90395 (0.95943) +2025-08-21,12:42:31 | INFO | Train Epoch: 2 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.229 Boundary Ratio: 0.246 Contrastive_loss: 0.93458 (0.94403) Boundary_loss: 0.015388 (0.015365) Loss: 0.94997 (0.95939) +2025-08-21,12:43:28 | INFO | Train Epoch: 2 [13568512/26365952 (51%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.90910 (0.94389) Boundary_loss: 0.015460 (0.015366) Loss: 0.92456 (0.95926) +2025-08-21,12:44:26 | INFO | Train Epoch: 2 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.86379 (0.94359) Boundary_loss: 0.015155 (0.015365) Loss: 0.87895 (0.95896) +2025-08-21,12:45:23 | INFO | Train Epoch: 2 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.85027 (0.94325) Boundary_loss: 0.015296 (0.015365) Loss: 0.86557 (0.95861) +2025-08-21,12:46:20 | INFO | Train Epoch: 2 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.99648 (0.94344) Boundary_loss: 0.015195 (0.015364) Loss: 1.0117 (0.95881) +2025-08-21,12:47:17 | INFO | Train Epoch: 2 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.95418 (0.94348) Boundary_loss: 0.015289 (0.015364) Loss: 0.96947 (0.95885) +2025-08-21,12:48:15 | INFO | Train Epoch: 2 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 0.88400 (0.94326) Boundary_loss: 0.015306 (0.015363) Loss: 0.89931 (0.95863) +2025-08-21,12:49:12 | INFO | Train Epoch: 2 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.77558 (0.94265) Boundary_loss: 0.015331 (0.015363) Loss: 0.79091 (0.95801) +2025-08-21,12:50:09 | INFO | Train Epoch: 2 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.176 Boundary Ratio: 0.246 Contrastive_loss: 0.80102 (0.94213) Boundary_loss: 0.015312 (0.015363) Loss: 0.81633 (0.95749) +2025-08-21,12:51:06 | INFO | Train Epoch: 2 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.89007 (0.94194) Boundary_loss: 0.015393 (0.015363) Loss: 0.90546 (0.95730) +2025-08-21,12:52:03 | INFO | Train Epoch: 2 [14029312/26365952 (53%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 1.0540 (0.94235) Boundary_loss: 0.015308 (0.015363) Loss: 1.0693 (0.95771) +2025-08-21,12:53:00 | INFO | Train Epoch: 2 [14080512/26365952 (53%)] Avg Boundaries (per batch): 47.904 Boundary Ratio: 0.244 Contrastive_loss: 0.87445 (0.94210) Boundary_loss: 0.015402 (0.015363) Loss: 0.88985 (0.95746) +2025-08-21,12:53:57 | INFO | Train Epoch: 2 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.95000 (0.94213) Boundary_loss: 0.015364 (0.015363) Loss: 0.96536 (0.95749) +2025-08-21,12:54:55 | INFO | Train Epoch: 2 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.053 Boundary Ratio: 0.245 Contrastive_loss: 0.85491 (0.94182) Boundary_loss: 0.015410 (0.015363) Loss: 0.87033 (0.95718) +2025-08-21,12:55:52 | INFO | Train Epoch: 2 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.85051 (0.94149) Boundary_loss: 0.015358 (0.015363) Loss: 0.86587 (0.95685) +2025-08-21,12:56:49 | INFO | Train Epoch: 2 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.191 Boundary Ratio: 0.246 Contrastive_loss: 0.85651 (0.94118) Boundary_loss: 0.015362 (0.015363) Loss: 0.87187 (0.95655) +2025-08-21,12:57:46 | INFO | Train Epoch: 2 [14336512/26365952 (54%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.96070 (0.94125) Boundary_loss: 0.015307 (0.015363) Loss: 0.97601 (0.95662) +2025-08-21,12:58:43 | INFO | Train Epoch: 2 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 1.0453 (0.94162) Boundary_loss: 0.015394 (0.015363) Loss: 1.0607 (0.95699) +2025-08-21,12:59:40 | INFO | Train Epoch: 2 [14438912/26365952 (55%)] Avg Boundaries (per batch): 49.512 Boundary Ratio: 0.253 Contrastive_loss: 0.89066 (0.94144) Boundary_loss: 0.015433 (0.015364) Loss: 0.90609 (0.95681) +2025-08-21,13:00:37 | INFO | Train Epoch: 2 [14490112/26365952 (55%)] Avg Boundaries (per batch): 49.438 Boundary Ratio: 0.252 Contrastive_loss: 0.93842 (0.94143) Boundary_loss: 0.015405 (0.015364) Loss: 0.95382 (0.95680) +2025-08-21,13:01:35 | INFO | Train Epoch: 2 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.189 Boundary Ratio: 0.246 Contrastive_loss: 0.93971 (0.94143) Boundary_loss: 0.015297 (0.015363) Loss: 0.95500 (0.95679) +2025-08-21,13:02:32 | INFO | Train Epoch: 2 [14592512/26365952 (55%)] Avg Boundaries (per batch): 47.805 Boundary Ratio: 0.244 Contrastive_loss: 0.97261 (0.94153) Boundary_loss: 0.015164 (0.015363) Loss: 0.98777 (0.95690) +2025-08-21,13:03:29 | INFO | Train Epoch: 2 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.80536 (0.94106) Boundary_loss: 0.015428 (0.015363) Loss: 0.82079 (0.95642) +2025-08-21,13:04:26 | INFO | Train Epoch: 2 [14694912/26365952 (56%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.78268 (0.94051) Boundary_loss: 0.015349 (0.015363) Loss: 0.79803 (0.95587) +2025-08-21,13:05:23 | INFO | Train Epoch: 2 [14746112/26365952 (56%)] Avg Boundaries (per batch): 50.311 Boundary Ratio: 0.257 Contrastive_loss: 0.97299 (0.94062) Boundary_loss: 0.015552 (0.015364) Loss: 0.98854 (0.95599) +2025-08-21,13:06:20 | INFO | Train Epoch: 2 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.219 Boundary Ratio: 0.246 Contrastive_loss: 0.81894 (0.94020) Boundary_loss: 0.015399 (0.015364) Loss: 0.83434 (0.95557) +2025-08-21,13:07:17 | INFO | Train Epoch: 2 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.094 Boundary Ratio: 0.245 Contrastive_loss: 0.94938 (0.94023) Boundary_loss: 0.015348 (0.015364) Loss: 0.96473 (0.95560) +2025-08-21,13:08:15 | INFO | Train Epoch: 2 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.086 Boundary Ratio: 0.245 Contrastive_loss: 1.0109 (0.94048) Boundary_loss: 0.015368 (0.015364) Loss: 1.0263 (0.95584) +2025-08-21,13:09:12 | INFO | Train Epoch: 2 [14950912/26365952 (57%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.81624 (0.94005) Boundary_loss: 0.015378 (0.015364) Loss: 0.83162 (0.95542) +2025-08-21,13:10:09 | INFO | Train Epoch: 2 [15002112/26365952 (57%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 1.0865 (0.94055) Boundary_loss: 0.015209 (0.015363) Loss: 1.1017 (0.95591) +2025-08-21,13:11:06 | INFO | Train Epoch: 2 [15053312/26365952 (57%)] Avg Boundaries (per batch): 47.512 Boundary Ratio: 0.242 Contrastive_loss: 0.80910 (0.94011) Boundary_loss: 0.015462 (0.015363) Loss: 0.82456 (0.95547) +2025-08-21,13:12:03 | INFO | Train Epoch: 2 [15104512/26365952 (57%)] Avg Boundaries (per batch): 49.348 Boundary Ratio: 0.252 Contrastive_loss: 0.96404 (0.94019) Boundary_loss: 0.015248 (0.015363) Loss: 0.97929 (0.95555) +2025-08-21,13:13:00 | INFO | Train Epoch: 2 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.85234 (0.93989) Boundary_loss: 0.015274 (0.015363) Loss: 0.86762 (0.95525) +2025-08-21,13:13:57 | INFO | Train Epoch: 2 [15206912/26365952 (58%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 0.82798 (0.93951) Boundary_loss: 0.015370 (0.015363) Loss: 0.84335 (0.95488) +2025-08-21,13:14:54 | INFO | Train Epoch: 2 [15258112/26365952 (58%)] Avg Boundaries (per batch): 49.779 Boundary Ratio: 0.254 Contrastive_loss: 0.77131 (0.93895) Boundary_loss: 0.015289 (0.015363) Loss: 0.78660 (0.95431) +2025-08-21,13:15:51 | INFO | Train Epoch: 2 [15309312/26365952 (58%)] Avg Boundaries (per batch): 47.830 Boundary Ratio: 0.244 Contrastive_loss: 0.94345 (0.93897) Boundary_loss: 0.015304 (0.015362) Loss: 0.95875 (0.95433) +2025-08-21,13:16:49 | INFO | Train Epoch: 2 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.88973 (0.93880) Boundary_loss: 0.015345 (0.015362) Loss: 0.90507 (0.95417) +2025-08-21,13:17:46 | INFO | Train Epoch: 2 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.85040 (0.93851) Boundary_loss: 0.015212 (0.015362) Loss: 0.86561 (0.95387) +2025-08-21,13:18:43 | INFO | Train Epoch: 2 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.93971 (0.93852) Boundary_loss: 0.015305 (0.015362) Loss: 0.95502 (0.95388) +2025-08-21,13:19:40 | INFO | Train Epoch: 2 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.88685 (0.93835) Boundary_loss: 0.015230 (0.015361) Loss: 0.90208 (0.95371) +2025-08-21,13:20:38 | INFO | Train Epoch: 2 [15565312/26365952 (59%)] Avg Boundaries (per batch): 47.555 Boundary Ratio: 0.243 Contrastive_loss: 0.93127 (0.93832) Boundary_loss: 0.015466 (0.015362) Loss: 0.94674 (0.95368) +2025-08-21,13:21:35 | INFO | Train Epoch: 2 [15616512/26365952 (59%)] Avg Boundaries (per batch): 47.641 Boundary Ratio: 0.243 Contrastive_loss: 0.77968 (0.93780) Boundary_loss: 0.015427 (0.015362) Loss: 0.79510 (0.95317) +2025-08-21,13:22:32 | INFO | Train Epoch: 2 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 0.91450 (0.93773) Boundary_loss: 0.015289 (0.015362) Loss: 0.92979 (0.95309) +2025-08-21,13:23:29 | INFO | Train Epoch: 2 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.91284 (0.93765) Boundary_loss: 0.015384 (0.015362) Loss: 0.92822 (0.95301) +2025-08-21,13:24:26 | INFO | Train Epoch: 2 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.82600 (0.93729) Boundary_loss: 0.015206 (0.015361) Loss: 0.84120 (0.95265) +2025-08-21,13:25:23 | INFO | Train Epoch: 2 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.76085 (0.93672) Boundary_loss: 0.015324 (0.015361) Loss: 0.77617 (0.95208) +2025-08-21,13:26:20 | INFO | Train Epoch: 2 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 1.0135 (0.93696) Boundary_loss: 0.015557 (0.015362) Loss: 1.0290 (0.95232) +2025-08-21,13:27:17 | INFO | Train Epoch: 2 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.93145 (0.93695) Boundary_loss: 0.015301 (0.015361) Loss: 0.94675 (0.95231) +2025-08-21,13:28:14 | INFO | Train Epoch: 2 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.92590 (0.93691) Boundary_loss: 0.015438 (0.015362) Loss: 0.94134 (0.95227) +2025-08-21,13:29:12 | INFO | Train Epoch: 2 [16026112/26365952 (61%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.78024 (0.93641) Boundary_loss: 0.015377 (0.015362) Loss: 0.79561 (0.95177) +2025-08-21,13:30:09 | INFO | Train Epoch: 2 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.78850 (0.93594) Boundary_loss: 0.015282 (0.015361) Loss: 0.80378 (0.95130) +2025-08-21,13:31:06 | INFO | Train Epoch: 2 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.83121 (0.93561) Boundary_loss: 0.015254 (0.015361) Loss: 0.84646 (0.95097) +2025-08-21,13:32:03 | INFO | Train Epoch: 2 [16179712/26365952 (61%)] Avg Boundaries (per batch): 49.447 Boundary Ratio: 0.252 Contrastive_loss: 0.86317 (0.93538) Boundary_loss: 0.015288 (0.015361) Loss: 0.87846 (0.95074) +2025-08-21,13:33:00 | INFO | Train Epoch: 2 [16230912/26365952 (62%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.89726 (0.93526) Boundary_loss: 0.015310 (0.015361) Loss: 0.91257 (0.95062) +2025-08-21,13:33:57 | INFO | Train Epoch: 2 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.82161 (0.93491) Boundary_loss: 0.015172 (0.015360) Loss: 0.83679 (0.95027) +2025-08-21,13:34:54 | INFO | Train Epoch: 2 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.86453 (0.93469) Boundary_loss: 0.015336 (0.015360) Loss: 0.87987 (0.95005) +2025-08-21,13:35:51 | INFO | Train Epoch: 2 [16384512/26365952 (62%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.93488 (0.93469) Boundary_loss: 0.015255 (0.015360) Loss: 0.95014 (0.95005) +2025-08-21,13:36:48 | INFO | Train Epoch: 2 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.93271 (0.93468) Boundary_loss: 0.015346 (0.015360) Loss: 0.94805 (0.95004) +2025-08-21,13:37:45 | INFO | Train Epoch: 2 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.78170 (0.93421) Boundary_loss: 0.015312 (0.015360) Loss: 0.79701 (0.94957) +2025-08-21,13:38:42 | INFO | Train Epoch: 2 [16538112/26365952 (63%)] Avg Boundaries (per batch): 49.543 Boundary Ratio: 0.253 Contrastive_loss: 0.96529 (0.93430) Boundary_loss: 0.015293 (0.015359) Loss: 0.98058 (0.94966) +2025-08-21,13:39:39 | INFO | Train Epoch: 2 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.81381 (0.93393) Boundary_loss: 0.015188 (0.015359) Loss: 0.82900 (0.94929) +2025-08-21,13:40:37 | INFO | Train Epoch: 2 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.705 Boundary Ratio: 0.254 Contrastive_loss: 0.85550 (0.93369) Boundary_loss: 0.015497 (0.015359) Loss: 0.87099 (0.94905) +2025-08-21,13:41:34 | INFO | Train Epoch: 2 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.96897 (0.93380) Boundary_loss: 0.015371 (0.015359) Loss: 0.98434 (0.94916) +2025-08-21,13:42:31 | INFO | Train Epoch: 2 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.88390 (0.93365) Boundary_loss: 0.015220 (0.015359) Loss: 0.89912 (0.94901) +2025-08-21,13:43:28 | INFO | Train Epoch: 2 [16794112/26365952 (64%)] Avg Boundaries (per batch): 49.635 Boundary Ratio: 0.253 Contrastive_loss: 0.96030 (0.93373) Boundary_loss: 0.015477 (0.015359) Loss: 0.97578 (0.94909) +2025-08-21,13:44:25 | INFO | Train Epoch: 2 [16845312/26365952 (64%)] Avg Boundaries (per batch): 49.416 Boundary Ratio: 0.252 Contrastive_loss: 0.86204 (0.93351) Boundary_loss: 0.015309 (0.015359) Loss: 0.87735 (0.94887) +2025-08-21,13:45:22 | INFO | Train Epoch: 2 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.348 Boundary Ratio: 0.247 Contrastive_loss: 0.85286 (0.93327) Boundary_loss: 0.015298 (0.015359) Loss: 0.86816 (0.94863) +2025-08-21,13:46:19 | INFO | Train Epoch: 2 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.86341 (0.93306) Boundary_loss: 0.015279 (0.015359) Loss: 0.87869 (0.94842) +2025-08-21,13:47:16 | INFO | Train Epoch: 2 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.275 Boundary Ratio: 0.246 Contrastive_loss: 0.81749 (0.93271) Boundary_loss: 0.015350 (0.015359) Loss: 0.83284 (0.94807) +2025-08-21,13:48:14 | INFO | Train Epoch: 2 [17050112/26365952 (65%)] Avg Boundaries (per batch): 49.494 Boundary Ratio: 0.253 Contrastive_loss: 1.0834 (0.93316) Boundary_loss: 0.015476 (0.015359) Loss: 1.0989 (0.94852) +2025-08-21,13:49:11 | INFO | Train Epoch: 2 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.69841 (0.93246) Boundary_loss: 0.015315 (0.015359) Loss: 0.71372 (0.94782) +2025-08-21,13:50:08 | INFO | Train Epoch: 2 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.80515 (0.93208) Boundary_loss: 0.015327 (0.015359) Loss: 0.82047 (0.94744) +2025-08-21,13:51:05 | INFO | Train Epoch: 2 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.215 Boundary Ratio: 0.246 Contrastive_loss: 0.92648 (0.93206) Boundary_loss: 0.015416 (0.015359) Loss: 0.94189 (0.94742) +2025-08-21,13:52:02 | INFO | Train Epoch: 2 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 0.86896 (0.93188) Boundary_loss: 0.015528 (0.015359) Loss: 0.88448 (0.94724) +2025-08-21,13:52:59 | INFO | Train Epoch: 2 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.92503 (0.93186) Boundary_loss: 0.015419 (0.015360) Loss: 0.94045 (0.94722) +2025-08-21,13:53:56 | INFO | Train Epoch: 2 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 0.78204 (0.93142) Boundary_loss: 0.015400 (0.015360) Loss: 0.79744 (0.94678) +2025-08-21,13:54:53 | INFO | Train Epoch: 2 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.80391 (0.93104) Boundary_loss: 0.015289 (0.015359) Loss: 0.81920 (0.94640) +2025-08-21,13:55:50 | INFO | Train Epoch: 2 [17459712/26365952 (66%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.84516 (0.93079) Boundary_loss: 0.015155 (0.015359) Loss: 0.86031 (0.94615) +2025-08-21,13:56:47 | INFO | Train Epoch: 2 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.79138 (0.93039) Boundary_loss: 0.015228 (0.015359) Loss: 0.80661 (0.94574) +2025-08-21,13:57:44 | INFO | Train Epoch: 2 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.82830 (0.93009) Boundary_loss: 0.015377 (0.015359) Loss: 0.84367 (0.94545) +2025-08-21,13:58:41 | INFO | Train Epoch: 2 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 1.0356 (0.93039) Boundary_loss: 0.015357 (0.015359) Loss: 1.0509 (0.94575) +2025-08-21,13:59:39 | INFO | Train Epoch: 2 [17664512/26365952 (67%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 0.75261 (0.92988) Boundary_loss: 0.015140 (0.015358) Loss: 0.76775 (0.94524) +2025-08-21,14:00:36 | INFO | Train Epoch: 2 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.85613 (0.92967) Boundary_loss: 0.015114 (0.015357) Loss: 0.87124 (0.94503) +2025-08-21,14:01:33 | INFO | Train Epoch: 2 [17766912/26365952 (67%)] Avg Boundaries (per batch): 49.244 Boundary Ratio: 0.251 Contrastive_loss: 0.86770 (0.92949) Boundary_loss: 0.015192 (0.015357) Loss: 0.88289 (0.94485) +2025-08-21,14:02:30 | INFO | Train Epoch: 2 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.79137 (0.92909) Boundary_loss: 0.015201 (0.015356) Loss: 0.80657 (0.94445) +2025-08-21,14:03:27 | INFO | Train Epoch: 2 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.412 Boundary Ratio: 0.252 Contrastive_loss: 0.84287 (0.92885) Boundary_loss: 0.015265 (0.015356) Loss: 0.85814 (0.94420) +2025-08-21,14:04:24 | INFO | Train Epoch: 2 [17920512/26365952 (68%)] Avg Boundaries (per batch): 49.455 Boundary Ratio: 0.252 Contrastive_loss: 0.87315 (0.92869) Boundary_loss: 0.015221 (0.015356) Loss: 0.88837 (0.94404) +2025-08-21,14:05:21 | INFO | Train Epoch: 2 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.172 Boundary Ratio: 0.246 Contrastive_loss: 0.74350 (0.92816) Boundary_loss: 0.015333 (0.015356) Loss: 0.75883 (0.94352) +2025-08-21,14:06:18 | INFO | Train Epoch: 2 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.73770 (0.92762) Boundary_loss: 0.015102 (0.015355) Loss: 0.75280 (0.94298) +2025-08-21,14:07:15 | INFO | Train Epoch: 2 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.068 Boundary Ratio: 0.245 Contrastive_loss: 0.82530 (0.92733) Boundary_loss: 0.015191 (0.015354) Loss: 0.84049 (0.94269) +2025-08-21,14:08:12 | INFO | Train Epoch: 2 [18125312/26365952 (69%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 0.96331 (0.92744) Boundary_loss: 0.015415 (0.015355) Loss: 0.97873 (0.94279) +2025-08-21,14:09:10 | INFO | Train Epoch: 2 [18176512/26365952 (69%)] Avg Boundaries (per batch): 49.219 Boundary Ratio: 0.251 Contrastive_loss: 0.95333 (0.92751) Boundary_loss: 0.015414 (0.015355) Loss: 0.96874 (0.94286) +2025-08-21,14:10:07 | INFO | Train Epoch: 2 [18227712/26365952 (69%)] Avg Boundaries (per batch): 47.547 Boundary Ratio: 0.243 Contrastive_loss: 0.88299 (0.92738) Boundary_loss: 0.015484 (0.015355) Loss: 0.89848 (0.94274) +2025-08-21,14:11:04 | INFO | Train Epoch: 2 [18278912/26365952 (69%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 0.84648 (0.92716) Boundary_loss: 0.015133 (0.015354) Loss: 0.86161 (0.94251) +2025-08-21,14:12:01 | INFO | Train Epoch: 2 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.469 Boundary Ratio: 0.252 Contrastive_loss: 0.72927 (0.92661) Boundary_loss: 0.015236 (0.015354) Loss: 0.74451 (0.94196) +2025-08-21,14:12:58 | INFO | Train Epoch: 2 [18381312/26365952 (70%)] Avg Boundaries (per batch): 50.408 Boundary Ratio: 0.257 Contrastive_loss: 0.91897 (0.92659) Boundary_loss: 0.015583 (0.015355) Loss: 0.93455 (0.94194) +2025-08-21,14:13:55 | INFO | Train Epoch: 2 [18432512/26365952 (70%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.87583 (0.92644) Boundary_loss: 0.015382 (0.015355) Loss: 0.89121 (0.94180) +2025-08-21,14:14:52 | INFO | Train Epoch: 2 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.86274 (0.92627) Boundary_loss: 0.015204 (0.015354) Loss: 0.87794 (0.94162) +2025-08-21,14:15:49 | INFO | Train Epoch: 2 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.73577 (0.92574) Boundary_loss: 0.015248 (0.015354) Loss: 0.75102 (0.94110) +2025-08-21,14:16:46 | INFO | Train Epoch: 2 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.87709 (0.92561) Boundary_loss: 0.015176 (0.015354) Loss: 0.89227 (0.94096) +2025-08-21,14:17:43 | INFO | Train Epoch: 2 [18637312/26365952 (71%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.86122 (0.92543) Boundary_loss: 0.015191 (0.015353) Loss: 0.87641 (0.94079) +2025-08-21,14:18:40 | INFO | Train Epoch: 2 [18688512/26365952 (71%)] Avg Boundaries (per batch): 49.795 Boundary Ratio: 0.254 Contrastive_loss: 0.76034 (0.92498) Boundary_loss: 0.015271 (0.015353) Loss: 0.77561 (0.94034) +2025-08-21,14:19:38 | INFO | Train Epoch: 2 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.82833 (0.92472) Boundary_loss: 0.015276 (0.015353) Loss: 0.84361 (0.94007) +2025-08-21,14:20:35 | INFO | Train Epoch: 2 [18790912/26365952 (71%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.91799 (0.92470) Boundary_loss: 0.015311 (0.015353) Loss: 0.93330 (0.94005) +2025-08-21,14:21:32 | INFO | Train Epoch: 2 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.74833 (0.92422) Boundary_loss: 0.015307 (0.015353) Loss: 0.76364 (0.93958) +2025-08-21,14:22:29 | INFO | Train Epoch: 2 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.79294 (0.92387) Boundary_loss: 0.015201 (0.015352) Loss: 0.80815 (0.93922) +2025-08-21,14:23:26 | INFO | Train Epoch: 2 [18944512/26365952 (72%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.89169 (0.92378) Boundary_loss: 0.015235 (0.015352) Loss: 0.90692 (0.93913) +2025-08-21,14:24:23 | INFO | Train Epoch: 2 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.86631 (0.92363) Boundary_loss: 0.015248 (0.015352) Loss: 0.88156 (0.93898) +2025-08-21,14:25:20 | INFO | Train Epoch: 2 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.82979 (0.92338) Boundary_loss: 0.015258 (0.015351) Loss: 0.84505 (0.93873) +2025-08-21,14:26:18 | INFO | Train Epoch: 2 [19098112/26365952 (72%)] Avg Boundaries (per batch): 47.480 Boundary Ratio: 0.242 Contrastive_loss: 0.87442 (0.92324) Boundary_loss: 0.015417 (0.015351) Loss: 0.88983 (0.93860) +2025-08-21,14:27:15 | INFO | Train Epoch: 2 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.74626 (0.92277) Boundary_loss: 0.015273 (0.015351) Loss: 0.76153 (0.93812) +2025-08-21,14:28:12 | INFO | Train Epoch: 2 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.87731 (0.92265) Boundary_loss: 0.015272 (0.015351) Loss: 0.89258 (0.93800) +2025-08-21,14:29:09 | INFO | Train Epoch: 2 [19251712/26365952 (73%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 0.99513 (0.92284) Boundary_loss: 0.015305 (0.015351) Loss: 1.0104 (0.93819) +2025-08-21,14:30:06 | INFO | Train Epoch: 2 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.88931 (0.92276) Boundary_loss: 0.015284 (0.015351) Loss: 0.90460 (0.93811) +2025-08-21,14:31:04 | INFO | Train Epoch: 2 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.92174 (0.92275) Boundary_loss: 0.015195 (0.015350) Loss: 0.93693 (0.93810) +2025-08-21,14:32:01 | INFO | Train Epoch: 2 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.91489 (0.92273) Boundary_loss: 0.015305 (0.015350) Loss: 0.93020 (0.93808) +2025-08-21,14:32:58 | INFO | Train Epoch: 2 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.992 Boundary Ratio: 0.255 Contrastive_loss: 0.93747 (0.92277) Boundary_loss: 0.015443 (0.015350) Loss: 0.95291 (0.93812) +2025-08-21,14:33:55 | INFO | Train Epoch: 2 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.83773 (0.92255) Boundary_loss: 0.015322 (0.015350) Loss: 0.85305 (0.93790) +2025-08-21,14:34:53 | INFO | Train Epoch: 2 [19558912/26365952 (74%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.80708 (0.92225) Boundary_loss: 0.015268 (0.015350) Loss: 0.82234 (0.93760) +2025-08-21,14:35:50 | INFO | Train Epoch: 2 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.195 Boundary Ratio: 0.246 Contrastive_loss: 0.89822 (0.92218) Boundary_loss: 0.015374 (0.015350) Loss: 0.91360 (0.93753) +2025-08-21,14:36:47 | INFO | Train Epoch: 2 [19661312/26365952 (75%)] Avg Boundaries (per batch): 47.992 Boundary Ratio: 0.245 Contrastive_loss: 0.80478 (0.92188) Boundary_loss: 0.015335 (0.015350) Loss: 0.82011 (0.93723) +2025-08-21,14:37:44 | INFO | Train Epoch: 2 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.049 Boundary Ratio: 0.245 Contrastive_loss: 0.82540 (0.92163) Boundary_loss: 0.015357 (0.015350) Loss: 0.84076 (0.93698) +2025-08-21,14:38:41 | INFO | Train Epoch: 2 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.168 Boundary Ratio: 0.246 Contrastive_loss: 0.78443 (0.92127) Boundary_loss: 0.015282 (0.015350) Loss: 0.79971 (0.93662) +2025-08-21,14:39:38 | INFO | Train Epoch: 2 [19814912/26365952 (75%)] Avg Boundaries (per batch): 47.727 Boundary Ratio: 0.244 Contrastive_loss: 0.78645 (0.92093) Boundary_loss: 0.015309 (0.015350) Loss: 0.80176 (0.93628) +2025-08-21,14:40:35 | INFO | Train Epoch: 2 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.82242 (0.92067) Boundary_loss: 0.015142 (0.015349) Loss: 0.83757 (0.93602) +2025-08-21,14:41:33 | INFO | Train Epoch: 2 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.85899 (0.92052) Boundary_loss: 0.015264 (0.015349) Loss: 0.87426 (0.93586) +2025-08-21,14:42:30 | INFO | Train Epoch: 2 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.79627 (0.92020) Boundary_loss: 0.015223 (0.015349) Loss: 0.81149 (0.93555) +2025-08-21,14:43:27 | INFO | Train Epoch: 2 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 0.81976 (0.91994) Boundary_loss: 0.015306 (0.015349) Loss: 0.83507 (0.93529) +2025-08-21,14:44:24 | INFO | Train Epoch: 2 [20070912/26365952 (76%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.91796 (0.91994) Boundary_loss: 0.015401 (0.015349) Loss: 0.93337 (0.93529) +2025-08-21,14:45:21 | INFO | Train Epoch: 2 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.78586 (0.91960) Boundary_loss: 0.015303 (0.015349) Loss: 0.80116 (0.93495) +2025-08-21,14:46:18 | INFO | Train Epoch: 2 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.115 Boundary Ratio: 0.245 Contrastive_loss: 0.97615 (0.91974) Boundary_loss: 0.015228 (0.015348) Loss: 0.99138 (0.93509) +2025-08-21,14:47:15 | INFO | Train Epoch: 2 [20224512/26365952 (77%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.97518 (0.91988) Boundary_loss: 0.015265 (0.015348) Loss: 0.99045 (0.93523) +2025-08-21,14:48:12 | INFO | Train Epoch: 2 [20275712/26365952 (77%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.84567 (0.91969) Boundary_loss: 0.015528 (0.015349) Loss: 0.86120 (0.93504) +2025-08-21,14:49:10 | INFO | Train Epoch: 2 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.88611 (0.91961) Boundary_loss: 0.015214 (0.015348) Loss: 0.90132 (0.93496) +2025-08-21,14:50:07 | INFO | Train Epoch: 2 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.82713 (0.91938) Boundary_loss: 0.015432 (0.015349) Loss: 0.84256 (0.93473) +2025-08-21,14:51:04 | INFO | Train Epoch: 2 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.92552 (0.91939) Boundary_loss: 0.015211 (0.015348) Loss: 0.94074 (0.93474) +2025-08-21,14:52:01 | INFO | Train Epoch: 2 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.74973 (0.91897) Boundary_loss: 0.015384 (0.015348) Loss: 0.76511 (0.93432) +2025-08-21,14:52:58 | INFO | Train Epoch: 2 [20531712/26365952 (78%)] Avg Boundaries (per batch): 47.631 Boundary Ratio: 0.243 Contrastive_loss: 0.70562 (0.91844) Boundary_loss: 0.015337 (0.015348) Loss: 0.72095 (0.93379) +2025-08-21,14:53:55 | INFO | Train Epoch: 2 [20582912/26365952 (78%)] Avg Boundaries (per batch): 47.963 Boundary Ratio: 0.245 Contrastive_loss: 0.91084 (0.91842) Boundary_loss: 0.015461 (0.015349) Loss: 0.92630 (0.93377) +2025-08-21,14:54:52 | INFO | Train Epoch: 2 [20634112/26365952 (78%)] Avg Boundaries (per batch): 50.174 Boundary Ratio: 0.256 Contrastive_loss: 0.82734 (0.91819) Boundary_loss: 0.015530 (0.015349) Loss: 0.84287 (0.93354) +2025-08-21,14:55:49 | INFO | Train Epoch: 2 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.79184 (0.91788) Boundary_loss: 0.015130 (0.015348) Loss: 0.80697 (0.93323) +2025-08-21,14:56:46 | INFO | Train Epoch: 2 [20736512/26365952 (79%)] Avg Boundaries (per batch): 49.648 Boundary Ratio: 0.253 Contrastive_loss: 0.84944 (0.91771) Boundary_loss: 0.015489 (0.015349) Loss: 0.86493 (0.93306) +2025-08-21,14:57:43 | INFO | Train Epoch: 2 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.75997 (0.91733) Boundary_loss: 0.015380 (0.015349) Loss: 0.77535 (0.93267) +2025-08-21,14:58:40 | INFO | Train Epoch: 2 [20838912/26365952 (79%)] Avg Boundaries (per batch): 49.709 Boundary Ratio: 0.254 Contrastive_loss: 0.85731 (0.91718) Boundary_loss: 0.015495 (0.015349) Loss: 0.87280 (0.93253) +2025-08-21,14:59:37 | INFO | Train Epoch: 2 [20890112/26365952 (79%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.84843 (0.91701) Boundary_loss: 0.015178 (0.015349) Loss: 0.86361 (0.93236) +2025-08-21,15:00:34 | INFO | Train Epoch: 2 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.78086 (0.91668) Boundary_loss: 0.015313 (0.015349) Loss: 0.79617 (0.93203) +2025-08-21,15:01:31 | INFO | Train Epoch: 2 [20992512/26365952 (80%)] Avg Boundaries (per batch): 49.871 Boundary Ratio: 0.254 Contrastive_loss: 0.88919 (0.91661) Boundary_loss: 0.015262 (0.015349) Loss: 0.90445 (0.93196) +2025-08-21,15:02:28 | INFO | Train Epoch: 2 [21043712/26365952 (80%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.89769 (0.91657) Boundary_loss: 0.015233 (0.015348) Loss: 0.91292 (0.93191) +2025-08-21,15:03:26 | INFO | Train Epoch: 2 [21094912/26365952 (80%)] Avg Boundaries (per batch): 49.303 Boundary Ratio: 0.252 Contrastive_loss: 0.74224 (0.91614) Boundary_loss: 0.015226 (0.015348) Loss: 0.75746 (0.93149) +2025-08-21,15:04:23 | INFO | Train Epoch: 2 [21146112/26365952 (80%)] Avg Boundaries (per batch): 49.498 Boundary Ratio: 0.253 Contrastive_loss: 0.75882 (0.91576) Boundary_loss: 0.015443 (0.015348) Loss: 0.77426 (0.93111) +2025-08-21,15:05:20 | INFO | Train Epoch: 2 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.77266 (0.91542) Boundary_loss: 0.015116 (0.015348) Loss: 0.78777 (0.93077) +2025-08-21,15:06:17 | INFO | Train Epoch: 2 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.91170 (0.91541) Boundary_loss: 0.015420 (0.015348) Loss: 0.92712 (0.93076) +2025-08-21,15:07:14 | INFO | Train Epoch: 2 [21299712/26365952 (81%)] Avg Boundaries (per batch): 49.977 Boundary Ratio: 0.255 Contrastive_loss: 0.79873 (0.91513) Boundary_loss: 0.015492 (0.015348) Loss: 0.81422 (0.93048) +2025-08-21,15:08:11 | INFO | Train Epoch: 2 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.303 Boundary Ratio: 0.252 Contrastive_loss: 0.83485 (0.91494) Boundary_loss: 0.015243 (0.015348) Loss: 0.85010 (0.93029) +2025-08-21,15:09:08 | INFO | Train Epoch: 2 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.064 Boundary Ratio: 0.245 Contrastive_loss: 0.94246 (0.91500) Boundary_loss: 0.015314 (0.015348) Loss: 0.95778 (0.93035) +2025-08-21,15:10:05 | INFO | Train Epoch: 2 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.83331 (0.91481) Boundary_loss: 0.015172 (0.015347) Loss: 0.84848 (0.93016) +2025-08-21,15:11:02 | INFO | Train Epoch: 2 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.301 Boundary Ratio: 0.246 Contrastive_loss: 0.81629 (0.91457) Boundary_loss: 0.015369 (0.015347) Loss: 0.83166 (0.92992) +2025-08-21,15:11:59 | INFO | Train Epoch: 2 [21555712/26365952 (82%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 0.86749 (0.91446) Boundary_loss: 0.015289 (0.015347) Loss: 0.88278 (0.92981) +2025-08-21,15:12:56 | INFO | Train Epoch: 2 [21606912/26365952 (82%)] Avg Boundaries (per batch): 49.961 Boundary Ratio: 0.255 Contrastive_loss: 0.80893 (0.91421) Boundary_loss: 0.015597 (0.015348) Loss: 0.82453 (0.92956) +2025-08-21,15:13:53 | INFO | Train Epoch: 2 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.084 Boundary Ratio: 0.245 Contrastive_loss: 0.90168 (0.91418) Boundary_loss: 0.015312 (0.015348) Loss: 0.91699 (0.92953) +2025-08-21,15:14:50 | INFO | Train Epoch: 2 [21709312/26365952 (82%)] Avg Boundaries (per batch): 49.635 Boundary Ratio: 0.253 Contrastive_loss: 0.76914 (0.91384) Boundary_loss: 0.015359 (0.015348) Loss: 0.78450 (0.92919) +2025-08-21,15:15:47 | INFO | Train Epoch: 2 [21760512/26365952 (83%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 0.84232 (0.91368) Boundary_loss: 0.015174 (0.015347) Loss: 0.85749 (0.92902) +2025-08-21,15:16:44 | INFO | Train Epoch: 2 [21811712/26365952 (83%)] Avg Boundaries (per batch): 49.430 Boundary Ratio: 0.252 Contrastive_loss: 0.92520 (0.91370) Boundary_loss: 0.015225 (0.015347) Loss: 0.94043 (0.92905) +2025-08-21,15:17:41 | INFO | Train Epoch: 2 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 0.85330 (0.91356) Boundary_loss: 0.015361 (0.015347) Loss: 0.86866 (0.92891) +2025-08-21,15:18:38 | INFO | Train Epoch: 2 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.92085 (0.91358) Boundary_loss: 0.015182 (0.015347) Loss: 0.93603 (0.92892) +2025-08-21,15:19:35 | INFO | Train Epoch: 2 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.361 Boundary Ratio: 0.252 Contrastive_loss: 0.79910 (0.91331) Boundary_loss: 0.015190 (0.015346) Loss: 0.81429 (0.92866) +2025-08-21,15:20:32 | INFO | Train Epoch: 2 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.90381 (0.91329) Boundary_loss: 0.015341 (0.015346) Loss: 0.91915 (0.92864) +2025-08-21,15:21:30 | INFO | Train Epoch: 2 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.79931 (0.91303) Boundary_loss: 0.015362 (0.015346) Loss: 0.81467 (0.92837) +2025-08-21,15:22:27 | INFO | Train Epoch: 2 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.84186 (0.91286) Boundary_loss: 0.015406 (0.015347) Loss: 0.85726 (0.92821) +2025-08-21,15:23:24 | INFO | Train Epoch: 2 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.85221 (0.91272) Boundary_loss: 0.015202 (0.015346) Loss: 0.86741 (0.92807) +2025-08-21,15:24:21 | INFO | Train Epoch: 2 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.232 Boundary Ratio: 0.246 Contrastive_loss: 0.77230 (0.91240) Boundary_loss: 0.015029 (0.015346) Loss: 0.78733 (0.92774) +2025-08-21,15:25:18 | INFO | Train Epoch: 2 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.71213 (0.91194) Boundary_loss: 0.015355 (0.015346) Loss: 0.72749 (0.92729) +2025-08-21,15:26:15 | INFO | Train Epoch: 2 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.78997 (0.91166) Boundary_loss: 0.015116 (0.015345) Loss: 0.80508 (0.92701) +2025-08-21,15:27:12 | INFO | Train Epoch: 2 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.82941 (0.91147) Boundary_loss: 0.015204 (0.015345) Loss: 0.84461 (0.92682) +2025-08-21,15:28:09 | INFO | Train Epoch: 2 [22426112/26365952 (85%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.85083 (0.91133) Boundary_loss: 0.015314 (0.015345) Loss: 0.86615 (0.92668) +2025-08-21,15:29:06 | INFO | Train Epoch: 2 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.082 Boundary Ratio: 0.245 Contrastive_loss: 0.84049 (0.91117) Boundary_loss: 0.015475 (0.015345) Loss: 0.85596 (0.92652) +2025-08-21,15:30:03 | INFO | Train Epoch: 2 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.850 Boundary Ratio: 0.254 Contrastive_loss: 0.86821 (0.91108) Boundary_loss: 0.015462 (0.015345) Loss: 0.88367 (0.92642) +2025-08-21,15:31:00 | INFO | Train Epoch: 2 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.91041 (0.91107) Boundary_loss: 0.015352 (0.015345) Loss: 0.92576 (0.92642) +2025-08-21,15:31:57 | INFO | Train Epoch: 2 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.426 Boundary Ratio: 0.252 Contrastive_loss: 0.81144 (0.91085) Boundary_loss: 0.015231 (0.015345) Loss: 0.82667 (0.92619) +2025-08-21,15:32:55 | INFO | Train Epoch: 2 [22682112/26365952 (86%)] Avg Boundaries (per batch): 47.871 Boundary Ratio: 0.244 Contrastive_loss: 0.90142 (0.91083) Boundary_loss: 0.015282 (0.015345) Loss: 0.91670 (0.92617) +2025-08-21,15:33:52 | INFO | Train Epoch: 2 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.484 Boundary Ratio: 0.252 Contrastive_loss: 0.68408 (0.91032) Boundary_loss: 0.015333 (0.015345) Loss: 0.69941 (0.92566) +2025-08-21,15:34:49 | INFO | Train Epoch: 2 [22784512/26365952 (86%)] Avg Boundaries (per batch): 49.814 Boundary Ratio: 0.254 Contrastive_loss: 0.82920 (0.91014) Boundary_loss: 0.015312 (0.015345) Loss: 0.84451 (0.92548) +2025-08-21,15:35:46 | INFO | Train Epoch: 2 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.094 Boundary Ratio: 0.245 Contrastive_loss: 0.95468 (0.91024) Boundary_loss: 0.015276 (0.015345) Loss: 0.96996 (0.92558) +2025-08-21,15:36:43 | INFO | Train Epoch: 2 [22886912/26365952 (87%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.93952 (0.91030) Boundary_loss: 0.015315 (0.015344) Loss: 0.95483 (0.92565) +2025-08-21,15:37:40 | INFO | Train Epoch: 2 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 0.92111 (0.91033) Boundary_loss: 0.015341 (0.015344) Loss: 0.93645 (0.92567) +2025-08-21,15:38:37 | INFO | Train Epoch: 2 [22989312/26365952 (87%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.80972 (0.91010) Boundary_loss: 0.015284 (0.015344) Loss: 0.82500 (0.92545) +2025-08-21,15:39:35 | INFO | Train Epoch: 2 [23040512/26365952 (87%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.93407 (0.91016) Boundary_loss: 0.015144 (0.015344) Loss: 0.94922 (0.92550) +2025-08-21,15:40:32 | INFO | Train Epoch: 2 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.80336 (0.90992) Boundary_loss: 0.015360 (0.015344) Loss: 0.81872 (0.92526) +2025-08-21,15:41:29 | INFO | Train Epoch: 2 [23142912/26365952 (88%)] Avg Boundaries (per batch): 49.465 Boundary Ratio: 0.252 Contrastive_loss: 0.85702 (0.90980) Boundary_loss: 0.015371 (0.015344) Loss: 0.87239 (0.92515) +2025-08-21,15:42:26 | INFO | Train Epoch: 2 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.89115 (0.90976) Boundary_loss: 0.015266 (0.015344) Loss: 0.90642 (0.92511) +2025-08-21,15:43:23 | INFO | Train Epoch: 2 [23245312/26365952 (88%)] Avg Boundaries (per batch): 47.717 Boundary Ratio: 0.243 Contrastive_loss: 0.81173 (0.90955) Boundary_loss: 0.015444 (0.015344) Loss: 0.82717 (0.92489) +2025-08-21,15:44:20 | INFO | Train Epoch: 2 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.86229 (0.90944) Boundary_loss: 0.015466 (0.015344) Loss: 0.87775 (0.92479) +2025-08-21,15:45:17 | INFO | Train Epoch: 2 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.77883 (0.90916) Boundary_loss: 0.015450 (0.015345) Loss: 0.79428 (0.92450) +2025-08-21,15:46:14 | INFO | Train Epoch: 2 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.150 Boundary Ratio: 0.246 Contrastive_loss: 0.86110 (0.90905) Boundary_loss: 0.015328 (0.015345) Loss: 0.87643 (0.92440) +2025-08-21,15:47:12 | INFO | Train Epoch: 2 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.693 Boundary Ratio: 0.254 Contrastive_loss: 0.86515 (0.90896) Boundary_loss: 0.015442 (0.015345) Loss: 0.88060 (0.92430) +2025-08-21,15:48:09 | INFO | Train Epoch: 2 [23501312/26365952 (89%)] Avg Boundaries (per batch): 47.203 Boundary Ratio: 0.241 Contrastive_loss: 0.78617 (0.90869) Boundary_loss: 0.015601 (0.015345) Loss: 0.80177 (0.92403) +2025-08-21,15:49:06 | INFO | Train Epoch: 2 [23552512/26365952 (89%)] Avg Boundaries (per batch): 49.432 Boundary Ratio: 0.252 Contrastive_loss: 0.79050 (0.90843) Boundary_loss: 0.015303 (0.015345) Loss: 0.80580 (0.92378) +2025-08-21,15:50:03 | INFO | Train Epoch: 2 [23603712/26365952 (90%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.78376 (0.90816) Boundary_loss: 0.015308 (0.015345) Loss: 0.79907 (0.92351) +2025-08-21,15:51:00 | INFO | Train Epoch: 2 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.87264 (0.90809) Boundary_loss: 0.015250 (0.015345) Loss: 0.88789 (0.92343) +2025-08-21,15:51:57 | INFO | Train Epoch: 2 [23706112/26365952 (90%)] Avg Boundaries (per batch): 49.729 Boundary Ratio: 0.254 Contrastive_loss: 0.84410 (0.90795) Boundary_loss: 0.015506 (0.015345) Loss: 0.85961 (0.92329) +2025-08-21,15:52:54 | INFO | Train Epoch: 2 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.85017 (0.90782) Boundary_loss: 0.015262 (0.015345) Loss: 0.86543 (0.92317) +2025-08-21,15:53:51 | INFO | Train Epoch: 2 [23808512/26365952 (90%)] Avg Boundaries (per batch): 49.436 Boundary Ratio: 0.252 Contrastive_loss: 0.80154 (0.90760) Boundary_loss: 0.015316 (0.015345) Loss: 0.81686 (0.92294) +2025-08-21,15:54:49 | INFO | Train Epoch: 2 [23859712/26365952 (90%)] Avg Boundaries (per batch): 47.982 Boundary Ratio: 0.245 Contrastive_loss: 0.94076 (0.90767) Boundary_loss: 0.015495 (0.015345) Loss: 0.95626 (0.92301) +2025-08-21,15:55:46 | INFO | Train Epoch: 2 [23910912/26365952 (91%)] Avg Boundaries (per batch): 49.625 Boundary Ratio: 0.253 Contrastive_loss: 0.77854 (0.90739) Boundary_loss: 0.015489 (0.015346) Loss: 0.79402 (0.92274) +2025-08-21,15:56:43 | INFO | Train Epoch: 2 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.80161 (0.90717) Boundary_loss: 0.015358 (0.015346) Loss: 0.81696 (0.92251) +2025-08-21,15:57:40 | INFO | Train Epoch: 2 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.87986 (0.90711) Boundary_loss: 0.015452 (0.015346) Loss: 0.89532 (0.92245) +2025-08-21,15:58:37 | INFO | Train Epoch: 2 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.77855 (0.90683) Boundary_loss: 0.015294 (0.015346) Loss: 0.79385 (0.92218) +2025-08-21,15:59:34 | INFO | Train Epoch: 2 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.84946 (0.90671) Boundary_loss: 0.015262 (0.015346) Loss: 0.86472 (0.92206) +2025-08-21,16:00:31 | INFO | Train Epoch: 2 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.94093 (0.90679) Boundary_loss: 0.015224 (0.015345) Loss: 0.95615 (0.92213) +2025-08-21,16:01:28 | INFO | Train Epoch: 2 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.85630 (0.90668) Boundary_loss: 0.015172 (0.015345) Loss: 0.87147 (0.92202) +2025-08-21,16:02:25 | INFO | Train Epoch: 2 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.83855 (0.90654) Boundary_loss: 0.015428 (0.015345) Loss: 0.85398 (0.92188) +2025-08-21,16:03:22 | INFO | Train Epoch: 2 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.96180 (0.90665) Boundary_loss: 0.015204 (0.015345) Loss: 0.97701 (0.92200) +2025-08-21,16:04:19 | INFO | Train Epoch: 2 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.82298 (0.90648) Boundary_loss: 0.015305 (0.015345) Loss: 0.83828 (0.92182) +2025-08-21,16:05:16 | INFO | Train Epoch: 2 [24422912/26365952 (93%)] Avg Boundaries (per batch): 50.492 Boundary Ratio: 0.258 Contrastive_loss: 0.80735 (0.90627) Boundary_loss: 0.015499 (0.015345) Loss: 0.82285 (0.92161) +2025-08-21,16:06:13 | INFO | Train Epoch: 2 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.139 Boundary Ratio: 0.246 Contrastive_loss: 0.81081 (0.90607) Boundary_loss: 0.015262 (0.015345) Loss: 0.82607 (0.92141) +2025-08-21,16:07:10 | INFO | Train Epoch: 2 [24525312/26365952 (93%)] Avg Boundaries (per batch): 49.578 Boundary Ratio: 0.253 Contrastive_loss: 0.75584 (0.90576) Boundary_loss: 0.015317 (0.015345) Loss: 0.77115 (0.92110) +2025-08-21,16:08:07 | INFO | Train Epoch: 2 [24576512/26365952 (93%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 0.76572 (0.90547) Boundary_loss: 0.015282 (0.015345) Loss: 0.78100 (0.92081) +2025-08-21,16:09:05 | INFO | Train Epoch: 2 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.80007 (0.90525) Boundary_loss: 0.015210 (0.015344) Loss: 0.81528 (0.92059) +2025-08-21,16:10:02 | INFO | Train Epoch: 2 [24678912/26365952 (94%)] Avg Boundaries (per batch): 49.637 Boundary Ratio: 0.253 Contrastive_loss: 0.84896 (0.90513) Boundary_loss: 0.015321 (0.015344) Loss: 0.86428 (0.92047) +2025-08-21,16:10:59 | INFO | Train Epoch: 2 [24730112/26365952 (94%)] Avg Boundaries (per batch): 49.650 Boundary Ratio: 0.253 Contrastive_loss: 0.78709 (0.90489) Boundary_loss: 0.015377 (0.015344) Loss: 0.80246 (0.92023) +2025-08-21,16:11:56 | INFO | Train Epoch: 2 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.75960 (0.90459) Boundary_loss: 0.015272 (0.015344) Loss: 0.77487 (0.91993) +2025-08-21,16:12:53 | INFO | Train Epoch: 2 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 0.78188 (0.90433) Boundary_loss: 0.015450 (0.015345) Loss: 0.79733 (0.91968) +2025-08-21,16:13:50 | INFO | Train Epoch: 2 [24883712/26365952 (94%)] Avg Boundaries (per batch): 50.059 Boundary Ratio: 0.255 Contrastive_loss: 0.78820 (0.90410) Boundary_loss: 0.015352 (0.015345) Loss: 0.80355 (0.91944) +2025-08-21,16:14:47 | INFO | Train Epoch: 2 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.77670 (0.90383) Boundary_loss: 0.015211 (0.015344) Loss: 0.79191 (0.91918) +2025-08-21,16:15:44 | INFO | Train Epoch: 2 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.77017 (0.90356) Boundary_loss: 0.015260 (0.015344) Loss: 0.78543 (0.91891) +2025-08-21,16:16:41 | INFO | Train Epoch: 2 [25037312/26365952 (95%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 0.77036 (0.90329) Boundary_loss: 0.015382 (0.015344) Loss: 0.78575 (0.91863) +2025-08-21,16:17:38 | INFO | Train Epoch: 2 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 0.84800 (0.90318) Boundary_loss: 0.015352 (0.015344) Loss: 0.86335 (0.91852) +2025-08-21,16:18:35 | INFO | Train Epoch: 2 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.97184 (0.90332) Boundary_loss: 0.015532 (0.015345) Loss: 0.98737 (0.91866) +2025-08-21,16:19:33 | INFO | Train Epoch: 2 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.125 Boundary Ratio: 0.246 Contrastive_loss: 0.75161 (0.90301) Boundary_loss: 0.015206 (0.015344) Loss: 0.76682 (0.91835) +2025-08-21,16:20:30 | INFO | Train Epoch: 2 [25242112/26365952 (96%)] Avg Boundaries (per batch): 49.301 Boundary Ratio: 0.252 Contrastive_loss: 0.86257 (0.90293) Boundary_loss: 0.015350 (0.015344) Loss: 0.87792 (0.91827) +2025-08-21,16:21:27 | INFO | Train Epoch: 2 [25293312/26365952 (96%)] Avg Boundaries (per batch): 50.061 Boundary Ratio: 0.255 Contrastive_loss: 0.80540 (0.90273) Boundary_loss: 0.015444 (0.015345) Loss: 0.82084 (0.91807) +2025-08-21,16:22:24 | INFO | Train Epoch: 2 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.85539 (0.90263) Boundary_loss: 0.015214 (0.015344) Loss: 0.87061 (0.91798) +2025-08-21,16:23:22 | INFO | Train Epoch: 2 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.309 Boundary Ratio: 0.252 Contrastive_loss: 0.88116 (0.90259) Boundary_loss: 0.015357 (0.015344) Loss: 0.89651 (0.91794) +2025-08-21,16:24:19 | INFO | Train Epoch: 2 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.90472 (0.90260) Boundary_loss: 0.015450 (0.015344) Loss: 0.92017 (0.91794) +2025-08-21,16:25:16 | INFO | Train Epoch: 2 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.77984 (0.90235) Boundary_loss: 0.015301 (0.015344) Loss: 0.79514 (0.91769) +2025-08-21,16:26:13 | INFO | Train Epoch: 2 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.80265 (0.90215) Boundary_loss: 0.015364 (0.015344) Loss: 0.81801 (0.91749) +2025-08-21,16:27:10 | INFO | Train Epoch: 2 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 0.80369 (0.90195) Boundary_loss: 0.015224 (0.015344) Loss: 0.81891 (0.91730) +2025-08-21,16:28:06 | INFO | Train Epoch: 2 [25651712/26365952 (97%)] Avg Boundaries (per batch): 49.662 Boundary Ratio: 0.253 Contrastive_loss: 0.76040 (0.90167) Boundary_loss: 0.015377 (0.015344) Loss: 0.77578 (0.91702) +2025-08-21,16:29:04 | INFO | Train Epoch: 2 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 0.78781 (0.90145) Boundary_loss: 0.015158 (0.015344) Loss: 0.80297 (0.91679) +2025-08-21,16:30:01 | INFO | Train Epoch: 2 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.229 Boundary Ratio: 0.246 Contrastive_loss: 0.91060 (0.90146) Boundary_loss: 0.015262 (0.015344) Loss: 0.92586 (0.91681) +2025-08-21,16:30:58 | INFO | Train Epoch: 2 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.88742 (0.90144) Boundary_loss: 0.015246 (0.015344) Loss: 0.90266 (0.91678) +2025-08-21,16:31:55 | INFO | Train Epoch: 2 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.64226 (0.90092) Boundary_loss: 0.015274 (0.015343) Loss: 0.65753 (0.91627) +2025-08-21,16:32:52 | INFO | Train Epoch: 2 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.85244 (0.90083) Boundary_loss: 0.015289 (0.015343) Loss: 0.86773 (0.91617) +2025-08-21,16:33:49 | INFO | Train Epoch: 2 [25958912/26365952 (98%)] Avg Boundaries (per batch): 49.430 Boundary Ratio: 0.252 Contrastive_loss: 0.93515 (0.90090) Boundary_loss: 0.015310 (0.015343) Loss: 0.95046 (0.91624) +2025-08-21,16:34:46 | INFO | Train Epoch: 2 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.86023 (0.90082) Boundary_loss: 0.015301 (0.015343) Loss: 0.87553 (0.91616) +2025-08-21,16:35:43 | INFO | Train Epoch: 2 [26061312/26365952 (99%)] Avg Boundaries (per batch): 47.299 Boundary Ratio: 0.241 Contrastive_loss: 0.85465 (0.90072) Boundary_loss: 0.015433 (0.015343) Loss: 0.87009 (0.91607) +2025-08-21,16:36:40 | INFO | Train Epoch: 2 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.80715 (0.90054) Boundary_loss: 0.015505 (0.015344) Loss: 0.82266 (0.91589) +2025-08-21,16:37:37 | INFO | Train Epoch: 2 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.74964 (0.90025) Boundary_loss: 0.015394 (0.015344) Loss: 0.76503 (0.91559) +2025-08-21,16:38:35 | INFO | Train Epoch: 2 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.81620 (0.90008) Boundary_loss: 0.015311 (0.015344) Loss: 0.83152 (0.91543) +2025-08-21,16:39:32 | INFO | Train Epoch: 2 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.87283 (0.90003) Boundary_loss: 0.015257 (0.015343) Loss: 0.88808 (0.91537) +2025-08-21,16:40:29 | INFO | Train Epoch: 2 [26317312/26365952 (100%)] Avg Boundaries (per batch): 49.852 Boundary Ratio: 0.254 Contrastive_loss: 0.89418 (0.90002) Boundary_loss: 0.015362 (0.015344) Loss: 0.90954 (0.91536) +2025-08-21,16:41:23 | INFO | Train Epoch: 2 [26365952/26365952 (100%)] Avg Boundaries (per batch): 49.674 Boundary Ratio: 0.253 Contrastive_loss: 0.87046 (0.89996) Boundary_loss: 0.015239 (0.015343) Loss: 0.88569 (0.91530) +2025-08-21,16:41:23 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-21,16:41:23 | INFO | [Epoch 2] Average Step Time: 0.575s | Average GPU Memory: 32.1 GB +2025-08-21,16:41:23 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-21,16:41:23 | INFO | Starting zero-shot imagenet. +2025-08-21,16:41:23 | INFO | Building zero-shot classifier +2025-08-21,16:41:32 | INFO | Using classifier +2025-08-21,16:42:20 | INFO | Finished zero-shot imagenet. +2025-08-21,16:42:20 | INFO | Eval Epoch: 3 imagenet-zeroshot-val-top1: 0.2045 imagenet-zeroshot-val-top5: 0.4303 +2025-08-21,16:42:22 | INFO | Start epoch 3 +2025-08-21,16:42:24 | INFO | Train Epoch: 3 [ 512/26365952 (0%)] Avg Boundaries (per batch): 49.521 Boundary Ratio: 0.253 Contrastive_loss: 0.71508 (0.71508) Boundary_loss: 0.015403 (0.015403) Loss: 0.73048 (0.73048) +2025-08-21,16:43:21 | INFO | Train Epoch: 3 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.86782 (0.79145) Boundary_loss: 0.015448 (0.015425) Loss: 0.88327 (0.80688) +2025-08-21,16:44:18 | INFO | Train Epoch: 3 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.81824 (0.80038) Boundary_loss: 0.015108 (0.015320) Loss: 0.83335 (0.81570) +2025-08-21,16:45:15 | INFO | Train Epoch: 3 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.428 Boundary Ratio: 0.252 Contrastive_loss: 0.77914 (0.79507) Boundary_loss: 0.015289 (0.015312) Loss: 0.79443 (0.81038) +2025-08-21,16:46:12 | INFO | Train Epoch: 3 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 49.182 Boundary Ratio: 0.251 Contrastive_loss: 0.80531 (0.79712) Boundary_loss: 0.015268 (0.015303) Loss: 0.82057 (0.81242) +2025-08-21,16:47:09 | INFO | Train Epoch: 3 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 49.342 Boundary Ratio: 0.252 Contrastive_loss: 0.73703 (0.78710) Boundary_loss: 0.015202 (0.015286) Loss: 0.75224 (0.80239) +2025-08-21,16:48:06 | INFO | Train Epoch: 3 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.74002 (0.78038) Boundary_loss: 0.015298 (0.015288) Loss: 0.75532 (0.79567) +2025-08-21,16:49:03 | INFO | Train Epoch: 3 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.71193 (0.77182) Boundary_loss: 0.015305 (0.015290) Loss: 0.72724 (0.78711) +2025-08-21,16:50:00 | INFO | Train Epoch: 3 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.73323 (0.76753) Boundary_loss: 0.015558 (0.015320) Loss: 0.74879 (0.78285) +2025-08-21,16:50:56 | INFO | Train Epoch: 3 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.270 Boundary Ratio: 0.246 Contrastive_loss: 0.71609 (0.76239) Boundary_loss: 0.015313 (0.015319) Loss: 0.73140 (0.77771) +2025-08-21,16:51:54 | INFO | Train Epoch: 3 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.74688 (0.76098) Boundary_loss: 0.015233 (0.015311) Loss: 0.76211 (0.77629) +2025-08-21,16:52:51 | INFO | Train Epoch: 3 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.71038 (0.75676) Boundary_loss: 0.015435 (0.015322) Loss: 0.72581 (0.77208) +2025-08-21,16:53:48 | INFO | Train Epoch: 3 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.76176 (0.75715) Boundary_loss: 0.015216 (0.015314) Loss: 0.77697 (0.77246) +2025-08-21,16:54:45 | INFO | Train Epoch: 3 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.70061 (0.75311) Boundary_loss: 0.015562 (0.015331) Loss: 0.71618 (0.76844) +2025-08-21,16:55:42 | INFO | Train Epoch: 3 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.81033 (0.75692) Boundary_loss: 0.015319 (0.015331) Loss: 0.82564 (0.77225) +2025-08-21,16:56:39 | INFO | Train Epoch: 3 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 0.91435 (0.76676) Boundary_loss: 0.015312 (0.015329) Loss: 0.92966 (0.78209) +2025-08-21,16:57:36 | INFO | Train Epoch: 3 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.75871 (0.76629) Boundary_loss: 0.015203 (0.015322) Loss: 0.77391 (0.78161) +2025-08-21,16:58:33 | INFO | Train Epoch: 3 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 49.758 Boundary Ratio: 0.254 Contrastive_loss: 0.85229 (0.77107) Boundary_loss: 0.015195 (0.015315) Loss: 0.86749 (0.78638) +2025-08-21,16:59:30 | INFO | Train Epoch: 3 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 50.070 Boundary Ratio: 0.255 Contrastive_loss: 0.80862 (0.77304) Boundary_loss: 0.015392 (0.015319) Loss: 0.82402 (0.78836) +2025-08-21,17:00:27 | INFO | Train Epoch: 3 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.041 Boundary Ratio: 0.245 Contrastive_loss: 0.86625 (0.77770) Boundary_loss: 0.015280 (0.015317) Loss: 0.88153 (0.79302) +2025-08-21,17:01:24 | INFO | Train Epoch: 3 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.71236 (0.77459) Boundary_loss: 0.015058 (0.015305) Loss: 0.72742 (0.78990) +2025-08-21,17:02:22 | INFO | Train Epoch: 3 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.80362 (0.77591) Boundary_loss: 0.015321 (0.015305) Loss: 0.81894 (0.79122) +2025-08-21,17:03:18 | INFO | Train Epoch: 3 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.434 Boundary Ratio: 0.247 Contrastive_loss: 0.75326 (0.77493) Boundary_loss: 0.015184 (0.015300) Loss: 0.76844 (0.79023) +2025-08-21,17:04:16 | INFO | Train Epoch: 3 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.73418 (0.77323) Boundary_loss: 0.015273 (0.015299) Loss: 0.74946 (0.78853) +2025-08-21,17:05:13 | INFO | Train Epoch: 3 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.80124 (0.77435) Boundary_loss: 0.015336 (0.015301) Loss: 0.81658 (0.78965) +2025-08-21,17:06:10 | INFO | Train Epoch: 3 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.82542 (0.77631) Boundary_loss: 0.015290 (0.015300) Loss: 0.84071 (0.79161) +2025-08-21,17:07:07 | INFO | Train Epoch: 3 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.75913 (0.77568) Boundary_loss: 0.015239 (0.015298) Loss: 0.77437 (0.79097) +2025-08-21,17:08:04 | INFO | Train Epoch: 3 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 0.80715 (0.77680) Boundary_loss: 0.015276 (0.015297) Loss: 0.82243 (0.79210) +2025-08-21,17:09:01 | INFO | Train Epoch: 3 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.141 Boundary Ratio: 0.246 Contrastive_loss: 0.84663 (0.77921) Boundary_loss: 0.015310 (0.015297) Loss: 0.86194 (0.79451) +2025-08-21,17:09:58 | INFO | Train Epoch: 3 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 49.529 Boundary Ratio: 0.253 Contrastive_loss: 0.74972 (0.77823) Boundary_loss: 0.015446 (0.015302) Loss: 0.76517 (0.79353) +2025-08-21,17:10:55 | INFO | Train Epoch: 3 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.502 Boundary Ratio: 0.253 Contrastive_loss: 0.76554 (0.77782) Boundary_loss: 0.015305 (0.015303) Loss: 0.78085 (0.79312) +2025-08-21,17:11:52 | INFO | Train Epoch: 3 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 47.979 Boundary Ratio: 0.245 Contrastive_loss: 0.92641 (0.78246) Boundary_loss: 0.015252 (0.015301) Loss: 0.94166 (0.79776) +2025-08-21,17:12:49 | INFO | Train Epoch: 3 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.56820 (0.77597) Boundary_loss: 0.015102 (0.015295) Loss: 0.58330 (0.79126) +2025-08-21,17:13:46 | INFO | Train Epoch: 3 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.77825 (0.77604) Boundary_loss: 0.015273 (0.015294) Loss: 0.79353 (0.79133) +2025-08-21,17:14:43 | INFO | Train Epoch: 3 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.67755 (0.77322) Boundary_loss: 0.015284 (0.015294) Loss: 0.69283 (0.78852) +2025-08-21,17:15:39 | INFO | Train Epoch: 3 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 0.73340 (0.77211) Boundary_loss: 0.015153 (0.015290) Loss: 0.74855 (0.78740) +2025-08-21,17:16:36 | INFO | Train Epoch: 3 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 0.71209 (0.77049) Boundary_loss: 0.015260 (0.015289) Loss: 0.72735 (0.78578) +2025-08-21,17:17:33 | INFO | Train Epoch: 3 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.76724 (0.77041) Boundary_loss: 0.015255 (0.015288) Loss: 0.78250 (0.78570) +2025-08-21,17:18:30 | INFO | Train Epoch: 3 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.168 Boundary Ratio: 0.251 Contrastive_loss: 0.88198 (0.77327) Boundary_loss: 0.015318 (0.015289) Loss: 0.89730 (0.78856) +2025-08-21,17:19:27 | INFO | Train Epoch: 3 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 49.508 Boundary Ratio: 0.253 Contrastive_loss: 0.70366 (0.77153) Boundary_loss: 0.015432 (0.015293) Loss: 0.71909 (0.78682) +2025-08-21,17:20:24 | INFO | Train Epoch: 3 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.72888 (0.77049) Boundary_loss: 0.015390 (0.015295) Loss: 0.74427 (0.78578) +2025-08-21,17:21:21 | INFO | Train Epoch: 3 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.348 Boundary Ratio: 0.247 Contrastive_loss: 0.89162 (0.77337) Boundary_loss: 0.015365 (0.015297) Loss: 0.90699 (0.78867) +2025-08-21,17:22:18 | INFO | Train Epoch: 3 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.006 Boundary Ratio: 0.245 Contrastive_loss: 0.81275 (0.77429) Boundary_loss: 0.015301 (0.015297) Loss: 0.82805 (0.78958) +2025-08-21,17:23:15 | INFO | Train Epoch: 3 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.79346 (0.77472) Boundary_loss: 0.015350 (0.015298) Loss: 0.80881 (0.79002) +2025-08-21,17:24:12 | INFO | Train Epoch: 3 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.63532 (0.77163) Boundary_loss: 0.015193 (0.015296) Loss: 0.65051 (0.78692) +2025-08-21,17:25:09 | INFO | Train Epoch: 3 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.81557 (0.77258) Boundary_loss: 0.015168 (0.015293) Loss: 0.83074 (0.78787) +2025-08-21,17:26:07 | INFO | Train Epoch: 3 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.71318 (0.77132) Boundary_loss: 0.015390 (0.015295) Loss: 0.72857 (0.78661) +2025-08-21,17:27:04 | INFO | Train Epoch: 3 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.73945 (0.77065) Boundary_loss: 0.015270 (0.015294) Loss: 0.75472 (0.78595) +2025-08-21,17:28:01 | INFO | Train Epoch: 3 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 0.73637 (0.76995) Boundary_loss: 0.015355 (0.015296) Loss: 0.75173 (0.78525) +2025-08-21,17:28:57 | INFO | Train Epoch: 3 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.74589 (0.76947) Boundary_loss: 0.015139 (0.015293) Loss: 0.76103 (0.78476) +2025-08-21,17:29:54 | INFO | Train Epoch: 3 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.62027 (0.76655) Boundary_loss: 0.015319 (0.015293) Loss: 0.63559 (0.78184) +2025-08-21,17:30:52 | INFO | Train Epoch: 3 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.77185 (0.76665) Boundary_loss: 0.015319 (0.015294) Loss: 0.78717 (0.78194) +2025-08-21,17:31:49 | INFO | Train Epoch: 3 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.72294 (0.76582) Boundary_loss: 0.015264 (0.015293) Loss: 0.73820 (0.78112) +2025-08-21,17:32:46 | INFO | Train Epoch: 3 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.81747 (0.76678) Boundary_loss: 0.015054 (0.015289) Loss: 0.83252 (0.78207) +2025-08-21,17:33:42 | INFO | Train Epoch: 3 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 49.457 Boundary Ratio: 0.252 Contrastive_loss: 0.86805 (0.76862) Boundary_loss: 0.015156 (0.015286) Loss: 0.88321 (0.78391) +2025-08-21,17:34:39 | INFO | Train Epoch: 3 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.248 Boundary Ratio: 0.246 Contrastive_loss: 0.71525 (0.76767) Boundary_loss: 0.015344 (0.015287) Loss: 0.73059 (0.78296) +2025-08-21,17:35:36 | INFO | Train Epoch: 3 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.69893 (0.76646) Boundary_loss: 0.015223 (0.015286) Loss: 0.71415 (0.78175) +2025-08-21,17:36:33 | INFO | Train Epoch: 3 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.76468 (0.76643) Boundary_loss: 0.015257 (0.015286) Loss: 0.77994 (0.78172) +2025-08-21,17:37:30 | INFO | Train Epoch: 3 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.65545 (0.76455) Boundary_loss: 0.015085 (0.015282) Loss: 0.67053 (0.77983) +2025-08-21,17:38:27 | INFO | Train Epoch: 3 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.76458 (0.76455) Boundary_loss: 0.015290 (0.015282) Loss: 0.77987 (0.77983) +2025-08-21,17:39:24 | INFO | Train Epoch: 3 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 49.463 Boundary Ratio: 0.252 Contrastive_loss: 0.75299 (0.76436) Boundary_loss: 0.015253 (0.015282) Loss: 0.76824 (0.77964) +2025-08-21,17:40:21 | INFO | Train Epoch: 3 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.78441 (0.76469) Boundary_loss: 0.015118 (0.015279) Loss: 0.79953 (0.77996) +2025-08-21,17:41:19 | INFO | Train Epoch: 3 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.68948 (0.76349) Boundary_loss: 0.015141 (0.015277) Loss: 0.70463 (0.77877) +2025-08-21,17:42:16 | INFO | Train Epoch: 3 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 49.324 Boundary Ratio: 0.252 Contrastive_loss: 0.68967 (0.76234) Boundary_loss: 0.015289 (0.015277) Loss: 0.70496 (0.77762) +2025-08-21,17:43:13 | INFO | Train Epoch: 3 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.363 Boundary Ratio: 0.247 Contrastive_loss: 0.69197 (0.76126) Boundary_loss: 0.015305 (0.015278) Loss: 0.70727 (0.77653) +2025-08-21,17:44:10 | INFO | Train Epoch: 3 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.75477 (0.76116) Boundary_loss: 0.015300 (0.015278) Loss: 0.77007 (0.77644) +2025-08-21,17:45:07 | INFO | Train Epoch: 3 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 50.355 Boundary Ratio: 0.257 Contrastive_loss: 0.79248 (0.76162) Boundary_loss: 0.015391 (0.015280) Loss: 0.80787 (0.77690) +2025-08-21,17:46:04 | INFO | Train Epoch: 3 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.83239 (0.76267) Boundary_loss: 0.015106 (0.015277) Loss: 0.84750 (0.77794) +2025-08-21,17:47:01 | INFO | Train Epoch: 3 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.80598 (0.76329) Boundary_loss: 0.015355 (0.015278) Loss: 0.82134 (0.77857) +2025-08-21,17:47:58 | INFO | Train Epoch: 3 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 47.676 Boundary Ratio: 0.243 Contrastive_loss: 0.79580 (0.76376) Boundary_loss: 0.015407 (0.015280) Loss: 0.81121 (0.77904) +2025-08-21,17:48:55 | INFO | Train Epoch: 3 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.84964 (0.76497) Boundary_loss: 0.015178 (0.015279) Loss: 0.86481 (0.78025) +2025-08-21,17:49:52 | INFO | Train Epoch: 3 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.67056 (0.76366) Boundary_loss: 0.015217 (0.015278) Loss: 0.68578 (0.77893) +2025-08-21,17:50:49 | INFO | Train Epoch: 3 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.68409 (0.76257) Boundary_loss: 0.015379 (0.015279) Loss: 0.69947 (0.77784) +2025-08-21,17:51:46 | INFO | Train Epoch: 3 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.77068 (0.76268) Boundary_loss: 0.015187 (0.015278) Loss: 0.78587 (0.77795) +2025-08-21,17:52:43 | INFO | Train Epoch: 3 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 49.760 Boundary Ratio: 0.254 Contrastive_loss: 0.65279 (0.76121) Boundary_loss: 0.015473 (0.015280) Loss: 0.66827 (0.77649) +2025-08-21,17:53:40 | INFO | Train Epoch: 3 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.74521 (0.76100) Boundary_loss: 0.015289 (0.015281) Loss: 0.76049 (0.77628) +2025-08-21,17:54:37 | INFO | Train Epoch: 3 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 47.699 Boundary Ratio: 0.243 Contrastive_loss: 0.79011 (0.76138) Boundary_loss: 0.015276 (0.015281) Loss: 0.80539 (0.77666) +2025-08-21,17:55:34 | INFO | Train Epoch: 3 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 0.84551 (0.76246) Boundary_loss: 0.015162 (0.015279) Loss: 0.86067 (0.77774) +2025-08-21,17:56:31 | INFO | Train Epoch: 3 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.396 Boundary Ratio: 0.252 Contrastive_loss: 0.71127 (0.76181) Boundary_loss: 0.015299 (0.015279) Loss: 0.72657 (0.77709) +2025-08-21,17:57:28 | INFO | Train Epoch: 3 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.79775 (0.76226) Boundary_loss: 0.015317 (0.015280) Loss: 0.81307 (0.77754) +2025-08-21,17:58:26 | INFO | Train Epoch: 3 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.393 Boundary Ratio: 0.247 Contrastive_loss: 0.60881 (0.76036) Boundary_loss: 0.015194 (0.015279) Loss: 0.62400 (0.77564) +2025-08-21,17:59:23 | INFO | Train Epoch: 3 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.80614 (0.76092) Boundary_loss: 0.015143 (0.015277) Loss: 0.82129 (0.77620) +2025-08-21,18:00:20 | INFO | Train Epoch: 3 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 47.580 Boundary Ratio: 0.243 Contrastive_loss: 0.81779 (0.76161) Boundary_loss: 0.015414 (0.015279) Loss: 0.83321 (0.77689) +2025-08-21,18:01:17 | INFO | Train Epoch: 3 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.68536 (0.76070) Boundary_loss: 0.015259 (0.015278) Loss: 0.70061 (0.77598) +2025-08-21,18:02:14 | INFO | Train Epoch: 3 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.76426 (0.76074) Boundary_loss: 0.015340 (0.015279) Loss: 0.77960 (0.77602) +2025-08-21,18:03:11 | INFO | Train Epoch: 3 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.62401 (0.75915) Boundary_loss: 0.015334 (0.015280) Loss: 0.63934 (0.77443) +2025-08-21,18:04:08 | INFO | Train Epoch: 3 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.316 Boundary Ratio: 0.252 Contrastive_loss: 0.82155 (0.75987) Boundary_loss: 0.015295 (0.015280) Loss: 0.83685 (0.77515) +2025-08-21,18:05:05 | INFO | Train Epoch: 3 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.70640 (0.75926) Boundary_loss: 0.015206 (0.015279) Loss: 0.72161 (0.77454) +2025-08-21,18:06:02 | INFO | Train Epoch: 3 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.78287 (0.75953) Boundary_loss: 0.015175 (0.015278) Loss: 0.79805 (0.77480) +2025-08-21,18:06:59 | INFO | Train Epoch: 3 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.61961 (0.75797) Boundary_loss: 0.015234 (0.015277) Loss: 0.63484 (0.77325) +2025-08-21,18:07:56 | INFO | Train Epoch: 3 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.127 Boundary Ratio: 0.246 Contrastive_loss: 0.75681 (0.75796) Boundary_loss: 0.015419 (0.015279) Loss: 0.77223 (0.77324) +2025-08-21,18:08:53 | INFO | Train Epoch: 3 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.77930 (0.75819) Boundary_loss: 0.015290 (0.015279) Loss: 0.79459 (0.77347) +2025-08-21,18:09:50 | INFO | Train Epoch: 3 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.78111 (0.75844) Boundary_loss: 0.015285 (0.015279) Loss: 0.79639 (0.77372) +2025-08-21,18:10:46 | INFO | Train Epoch: 3 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.68365 (0.75764) Boundary_loss: 0.015044 (0.015277) Loss: 0.69870 (0.77292) +2025-08-21,18:11:43 | INFO | Train Epoch: 3 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.77391 (0.75781) Boundary_loss: 0.015300 (0.015277) Loss: 0.78921 (0.77309) +2025-08-21,18:12:41 | INFO | Train Epoch: 3 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.145 Boundary Ratio: 0.246 Contrastive_loss: 0.78930 (0.75814) Boundary_loss: 0.015375 (0.015278) Loss: 0.80468 (0.77342) +2025-08-21,18:13:38 | INFO | Train Epoch: 3 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.75896 (0.75815) Boundary_loss: 0.015309 (0.015278) Loss: 0.77427 (0.77343) +2025-08-21,18:14:35 | INFO | Train Epoch: 3 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.78067 (0.75838) Boundary_loss: 0.015515 (0.015281) Loss: 0.79619 (0.77366) +2025-08-21,18:15:32 | INFO | Train Epoch: 3 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.78669 (0.75866) Boundary_loss: 0.015333 (0.015281) Loss: 0.80203 (0.77395) +2025-08-21,18:16:29 | INFO | Train Epoch: 3 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.75784 (0.75866) Boundary_loss: 0.015247 (0.015281) Loss: 0.77309 (0.77394) +2025-08-21,18:17:25 | INFO | Train Epoch: 3 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.71681 (0.75824) Boundary_loss: 0.015346 (0.015282) Loss: 0.73216 (0.77352) +2025-08-21,18:18:22 | INFO | Train Epoch: 3 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.62485 (0.75693) Boundary_loss: 0.015090 (0.015280) Loss: 0.63994 (0.77221) +2025-08-21,18:19:20 | INFO | Train Epoch: 3 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.82518 (0.75760) Boundary_loss: 0.015180 (0.015279) Loss: 0.84036 (0.77288) +2025-08-21,18:20:17 | INFO | Train Epoch: 3 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 49.516 Boundary Ratio: 0.253 Contrastive_loss: 0.83737 (0.75836) Boundary_loss: 0.015356 (0.015279) Loss: 0.85273 (0.77364) +2025-08-21,18:21:14 | INFO | Train Epoch: 3 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.78257 (0.75859) Boundary_loss: 0.015155 (0.015278) Loss: 0.79773 (0.77387) +2025-08-21,18:22:11 | INFO | Train Epoch: 3 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.73462 (0.75837) Boundary_loss: 0.015321 (0.015279) Loss: 0.74994 (0.77365) +2025-08-21,18:23:08 | INFO | Train Epoch: 3 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.79140 (0.75868) Boundary_loss: 0.015228 (0.015278) Loss: 0.80663 (0.77396) +2025-08-21,18:24:05 | INFO | Train Epoch: 3 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 0.72968 (0.75841) Boundary_loss: 0.015338 (0.015279) Loss: 0.74502 (0.77369) +2025-08-21,18:25:02 | INFO | Train Epoch: 3 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.377 Boundary Ratio: 0.247 Contrastive_loss: 0.61949 (0.75713) Boundary_loss: 0.015297 (0.015279) Loss: 0.63478 (0.77241) +2025-08-21,18:25:59 | INFO | Train Epoch: 3 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.76955 (0.75725) Boundary_loss: 0.015243 (0.015279) Loss: 0.78479 (0.77253) +2025-08-21,18:26:56 | INFO | Train Epoch: 3 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.69540 (0.75669) Boundary_loss: 0.015351 (0.015279) Loss: 0.71075 (0.77197) +2025-08-21,18:27:53 | INFO | Train Epoch: 3 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.81502 (0.75721) Boundary_loss: 0.015429 (0.015281) Loss: 0.83045 (0.77249) +2025-08-21,18:28:51 | INFO | Train Epoch: 3 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.80578 (0.75764) Boundary_loss: 0.015267 (0.015280) Loss: 0.82104 (0.77292) +2025-08-21,18:29:48 | INFO | Train Epoch: 3 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 49.951 Boundary Ratio: 0.255 Contrastive_loss: 0.74592 (0.75754) Boundary_loss: 0.015569 (0.015283) Loss: 0.76149 (0.77282) +2025-08-21,18:30:45 | INFO | Train Epoch: 3 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 47.682 Boundary Ratio: 0.243 Contrastive_loss: 0.78637 (0.75779) Boundary_loss: 0.015177 (0.015282) Loss: 0.80155 (0.77307) +2025-08-21,18:31:42 | INFO | Train Epoch: 3 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 49.789 Boundary Ratio: 0.254 Contrastive_loss: 0.65057 (0.75686) Boundary_loss: 0.015436 (0.015283) Loss: 0.66601 (0.77215) +2025-08-21,18:32:39 | INFO | Train Epoch: 3 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.71344 (0.75649) Boundary_loss: 0.015252 (0.015283) Loss: 0.72869 (0.77178) +2025-08-21,18:33:36 | INFO | Train Epoch: 3 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.133 Boundary Ratio: 0.246 Contrastive_loss: 0.63966 (0.75550) Boundary_loss: 0.015237 (0.015283) Loss: 0.65490 (0.77079) +2025-08-21,18:34:33 | INFO | Train Epoch: 3 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.77490 (0.75567) Boundary_loss: 0.015280 (0.015283) Loss: 0.79018 (0.77095) +2025-08-21,18:35:30 | INFO | Train Epoch: 3 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.77136 (0.75580) Boundary_loss: 0.015387 (0.015284) Loss: 0.78674 (0.77108) +2025-08-21,18:36:27 | INFO | Train Epoch: 3 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.79970 (0.75616) Boundary_loss: 0.015210 (0.015283) Loss: 0.81491 (0.77144) +2025-08-21,18:37:24 | INFO | Train Epoch: 3 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.73205 (0.75596) Boundary_loss: 0.015017 (0.015281) Loss: 0.74707 (0.77124) +2025-08-21,18:38:21 | INFO | Train Epoch: 3 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.78170 (0.75617) Boundary_loss: 0.015171 (0.015280) Loss: 0.79688 (0.77145) +2025-08-21,18:39:18 | INFO | Train Epoch: 3 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.85078 (0.75693) Boundary_loss: 0.015514 (0.015282) Loss: 0.86629 (0.77222) +2025-08-21,18:40:16 | INFO | Train Epoch: 3 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.74995 (0.75688) Boundary_loss: 0.015327 (0.015282) Loss: 0.76528 (0.77216) +2025-08-21,18:41:12 | INFO | Train Epoch: 3 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.182 Boundary Ratio: 0.246 Contrastive_loss: 0.72703 (0.75664) Boundary_loss: 0.015314 (0.015282) Loss: 0.74234 (0.77192) +2025-08-21,18:42:10 | INFO | Train Epoch: 3 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.78707 (0.75688) Boundary_loss: 0.015218 (0.015282) Loss: 0.80229 (0.77216) +2025-08-21,18:43:07 | INFO | Train Epoch: 3 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.67384 (0.75623) Boundary_loss: 0.015311 (0.015282) Loss: 0.68915 (0.77151) +2025-08-21,18:44:04 | INFO | Train Epoch: 3 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.71080 (0.75588) Boundary_loss: 0.015147 (0.015281) Loss: 0.72595 (0.77116) +2025-08-21,18:45:01 | INFO | Train Epoch: 3 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 47.418 Boundary Ratio: 0.242 Contrastive_loss: 0.76514 (0.75595) Boundary_loss: 0.015490 (0.015283) Loss: 0.78063 (0.77123) +2025-08-21,18:45:58 | INFO | Train Epoch: 3 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.678 Boundary Ratio: 0.253 Contrastive_loss: 0.68524 (0.75541) Boundary_loss: 0.015201 (0.015282) Loss: 0.70044 (0.77069) +2025-08-21,18:46:55 | INFO | Train Epoch: 3 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.72163 (0.75516) Boundary_loss: 0.015225 (0.015282) Loss: 0.73686 (0.77044) +2025-08-21,18:47:52 | INFO | Train Epoch: 3 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.500 Boundary Ratio: 0.253 Contrastive_loss: 0.78483 (0.75538) Boundary_loss: 0.015245 (0.015281) Loss: 0.80008 (0.77066) +2025-08-21,18:48:49 | INFO | Train Epoch: 3 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 0.63338 (0.75447) Boundary_loss: 0.015387 (0.015282) Loss: 0.64877 (0.76975) +2025-08-21,18:49:46 | INFO | Train Epoch: 3 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.63055 (0.75355) Boundary_loss: 0.015352 (0.015283) Loss: 0.64590 (0.76883) +2025-08-21,18:50:43 | INFO | Train Epoch: 3 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.68649 (0.75306) Boundary_loss: 0.015457 (0.015284) Loss: 0.70194 (0.76834) +2025-08-21,18:51:41 | INFO | Train Epoch: 3 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.64844 (0.75229) Boundary_loss: 0.015097 (0.015283) Loss: 0.66354 (0.76758) +2025-08-21,18:52:38 | INFO | Train Epoch: 3 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 0.73452 (0.75216) Boundary_loss: 0.015221 (0.015282) Loss: 0.74974 (0.76745) +2025-08-21,18:53:35 | INFO | Train Epoch: 3 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 47.885 Boundary Ratio: 0.244 Contrastive_loss: 0.77346 (0.75232) Boundary_loss: 0.015349 (0.015283) Loss: 0.78881 (0.76760) +2025-08-21,18:54:32 | INFO | Train Epoch: 3 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.73402 (0.75219) Boundary_loss: 0.015142 (0.015282) Loss: 0.74916 (0.76747) +2025-08-21,18:55:29 | INFO | Train Epoch: 3 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.74675 (0.75215) Boundary_loss: 0.015224 (0.015281) Loss: 0.76198 (0.76743) +2025-08-21,18:56:26 | INFO | Train Epoch: 3 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 47.848 Boundary Ratio: 0.244 Contrastive_loss: 0.75080 (0.75214) Boundary_loss: 0.015222 (0.015281) Loss: 0.76602 (0.76742) +2025-08-21,18:57:23 | INFO | Train Epoch: 3 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.78600 (0.75238) Boundary_loss: 0.015231 (0.015280) Loss: 0.80123 (0.76766) +2025-08-21,18:58:20 | INFO | Train Epoch: 3 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.73641 (0.75227) Boundary_loss: 0.015433 (0.015281) Loss: 0.75185 (0.76755) +2025-08-21,18:59:17 | INFO | Train Epoch: 3 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.78665 (0.75250) Boundary_loss: 0.015352 (0.015282) Loss: 0.80200 (0.76778) +2025-08-21,19:00:14 | INFO | Train Epoch: 3 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.420 Boundary Ratio: 0.252 Contrastive_loss: 0.66758 (0.75192) Boundary_loss: 0.015327 (0.015282) Loss: 0.68291 (0.76720) +2025-08-21,19:01:12 | INFO | Train Epoch: 3 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.324 Boundary Ratio: 0.247 Contrastive_loss: 0.71880 (0.75170) Boundary_loss: 0.015303 (0.015282) Loss: 0.73410 (0.76698) +2025-08-21,19:02:09 | INFO | Train Epoch: 3 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 50.510 Boundary Ratio: 0.258 Contrastive_loss: 0.63373 (0.75090) Boundary_loss: 0.015453 (0.015284) Loss: 0.64919 (0.76618) +2025-08-21,19:03:06 | INFO | Train Epoch: 3 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 47.512 Boundary Ratio: 0.242 Contrastive_loss: 0.73954 (0.75082) Boundary_loss: 0.015427 (0.015285) Loss: 0.75497 (0.76611) +2025-08-21,19:04:03 | INFO | Train Epoch: 3 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.81615 (0.75126) Boundary_loss: 0.015256 (0.015284) Loss: 0.83141 (0.76654) +2025-08-21,19:05:00 | INFO | Train Epoch: 3 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 49.277 Boundary Ratio: 0.251 Contrastive_loss: 0.76717 (0.75136) Boundary_loss: 0.015248 (0.015284) Loss: 0.78242 (0.76665) +2025-08-21,19:05:57 | INFO | Train Epoch: 3 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.69560 (0.75100) Boundary_loss: 0.015139 (0.015283) Loss: 0.71074 (0.76628) +2025-08-21,19:06:54 | INFO | Train Epoch: 3 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.68217 (0.75055) Boundary_loss: 0.015416 (0.015284) Loss: 0.69759 (0.76583) +2025-08-21,19:07:51 | INFO | Train Epoch: 3 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.69479 (0.75018) Boundary_loss: 0.015187 (0.015283) Loss: 0.70998 (0.76547) +2025-08-21,19:08:48 | INFO | Train Epoch: 3 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.85638 (0.75087) Boundary_loss: 0.015310 (0.015284) Loss: 0.87169 (0.76615) +2025-08-21,19:09:45 | INFO | Train Epoch: 3 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 0.67888 (0.75041) Boundary_loss: 0.015464 (0.015285) Loss: 0.69435 (0.76569) +2025-08-21,19:10:42 | INFO | Train Epoch: 3 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 50.186 Boundary Ratio: 0.256 Contrastive_loss: 0.78103 (0.75060) Boundary_loss: 0.015557 (0.015286) Loss: 0.79658 (0.76589) +2025-08-21,19:11:39 | INFO | Train Epoch: 3 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 47.938 Boundary Ratio: 0.245 Contrastive_loss: 0.72835 (0.75046) Boundary_loss: 0.015290 (0.015286) Loss: 0.74364 (0.76575) +2025-08-21,19:12:36 | INFO | Train Epoch: 3 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.52160 (0.74902) Boundary_loss: 0.015355 (0.015287) Loss: 0.53695 (0.76431) +2025-08-21,19:13:33 | INFO | Train Epoch: 3 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.70049 (0.74872) Boundary_loss: 0.015250 (0.015287) Loss: 0.71574 (0.76401) +2025-08-21,19:14:30 | INFO | Train Epoch: 3 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.83051 (0.74923) Boundary_loss: 0.015189 (0.015286) Loss: 0.84570 (0.76451) +2025-08-21,19:15:28 | INFO | Train Epoch: 3 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.645 Boundary Ratio: 0.253 Contrastive_loss: 0.75189 (0.74924) Boundary_loss: 0.015215 (0.015286) Loss: 0.76711 (0.76453) +2025-08-21,19:16:25 | INFO | Train Epoch: 3 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.78864 (0.74949) Boundary_loss: 0.015159 (0.015285) Loss: 0.80380 (0.76477) +2025-08-21,19:17:22 | INFO | Train Epoch: 3 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 47.934 Boundary Ratio: 0.245 Contrastive_loss: 0.71444 (0.74927) Boundary_loss: 0.015222 (0.015284) Loss: 0.72966 (0.76456) +2025-08-21,19:18:19 | INFO | Train Epoch: 3 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.62226 (0.74850) Boundary_loss: 0.015083 (0.015283) Loss: 0.63735 (0.76379) +2025-08-21,19:19:16 | INFO | Train Epoch: 3 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.492 Boundary Ratio: 0.253 Contrastive_loss: 0.70001 (0.74821) Boundary_loss: 0.015275 (0.015283) Loss: 0.71529 (0.76349) +2025-08-21,19:20:13 | INFO | Train Epoch: 3 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 0.74117 (0.74817) Boundary_loss: 0.015283 (0.015283) Loss: 0.75645 (0.76345) +2025-08-21,19:21:10 | INFO | Train Epoch: 3 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 49.443 Boundary Ratio: 0.252 Contrastive_loss: 0.84060 (0.74872) Boundary_loss: 0.015234 (0.015283) Loss: 0.85584 (0.76400) +2025-08-21,19:22:07 | INFO | Train Epoch: 3 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 49.738 Boundary Ratio: 0.254 Contrastive_loss: 0.71535 (0.74852) Boundary_loss: 0.015217 (0.015283) Loss: 0.73057 (0.76380) +2025-08-21,19:23:04 | INFO | Train Epoch: 3 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.62064 (0.74777) Boundary_loss: 0.015245 (0.015282) Loss: 0.63589 (0.76305) +2025-08-21,19:24:01 | INFO | Train Epoch: 3 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.74127 (0.74773) Boundary_loss: 0.015438 (0.015283) Loss: 0.75671 (0.76301) +2025-08-21,19:24:58 | INFO | Train Epoch: 3 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.520 Boundary Ratio: 0.253 Contrastive_loss: 0.75960 (0.74780) Boundary_loss: 0.015198 (0.015283) Loss: 0.77480 (0.76308) +2025-08-21,19:25:55 | INFO | Train Epoch: 3 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.68364 (0.74743) Boundary_loss: 0.015105 (0.015282) Loss: 0.69874 (0.76271) +2025-08-21,19:26:52 | INFO | Train Epoch: 3 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.152 Boundary Ratio: 0.246 Contrastive_loss: 0.76270 (0.74752) Boundary_loss: 0.015346 (0.015282) Loss: 0.77804 (0.76280) +2025-08-21,19:27:49 | INFO | Train Epoch: 3 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 47.965 Boundary Ratio: 0.245 Contrastive_loss: 0.78293 (0.74772) Boundary_loss: 0.015252 (0.015282) Loss: 0.79819 (0.76300) +2025-08-21,19:28:46 | INFO | Train Epoch: 3 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.70630 (0.74748) Boundary_loss: 0.015258 (0.015282) Loss: 0.72155 (0.76277) +2025-08-21,19:29:43 | INFO | Train Epoch: 3 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 0.65844 (0.74698) Boundary_loss: 0.015394 (0.015282) Loss: 0.67383 (0.76226) +2025-08-21,19:30:41 | INFO | Train Epoch: 3 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.67931 (0.74660) Boundary_loss: 0.015305 (0.015282) Loss: 0.69461 (0.76188) +2025-08-21,19:31:38 | INFO | Train Epoch: 3 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.76531 (0.74670) Boundary_loss: 0.015407 (0.015283) Loss: 0.78072 (0.76199) +2025-08-21,19:32:35 | INFO | Train Epoch: 3 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.162 Boundary Ratio: 0.246 Contrastive_loss: 0.77984 (0.74689) Boundary_loss: 0.015303 (0.015283) Loss: 0.79514 (0.76217) +2025-08-21,19:33:32 | INFO | Train Epoch: 3 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.143 Boundary Ratio: 0.246 Contrastive_loss: 0.78458 (0.74710) Boundary_loss: 0.015348 (0.015284) Loss: 0.79993 (0.76238) +2025-08-21,19:34:29 | INFO | Train Epoch: 3 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 47.906 Boundary Ratio: 0.244 Contrastive_loss: 0.81300 (0.74746) Boundary_loss: 0.015350 (0.015284) Loss: 0.82835 (0.76274) +2025-08-21,19:35:26 | INFO | Train Epoch: 3 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 49.443 Boundary Ratio: 0.252 Contrastive_loss: 0.78711 (0.74768) Boundary_loss: 0.015165 (0.015283) Loss: 0.80227 (0.76296) +2025-08-21,19:36:23 | INFO | Train Epoch: 3 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 49.381 Boundary Ratio: 0.252 Contrastive_loss: 0.69368 (0.74738) Boundary_loss: 0.015106 (0.015282) Loss: 0.70879 (0.76266) +2025-08-21,19:37:20 | INFO | Train Epoch: 3 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.66876 (0.74696) Boundary_loss: 0.015271 (0.015282) Loss: 0.68403 (0.76224) +2025-08-21,19:38:17 | INFO | Train Epoch: 3 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.67724 (0.74658) Boundary_loss: 0.015371 (0.015283) Loss: 0.69261 (0.76187) +2025-08-21,19:39:14 | INFO | Train Epoch: 3 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.80187 (0.74688) Boundary_loss: 0.015350 (0.015283) Loss: 0.81722 (0.76216) +2025-08-21,19:40:11 | INFO | Train Epoch: 3 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 49.693 Boundary Ratio: 0.254 Contrastive_loss: 0.54399 (0.74580) Boundary_loss: 0.015237 (0.015283) Loss: 0.55923 (0.76108) +2025-08-21,19:41:08 | INFO | Train Epoch: 3 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.84675 (0.74633) Boundary_loss: 0.015113 (0.015282) Loss: 0.86186 (0.76161) +2025-08-21,19:42:05 | INFO | Train Epoch: 3 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.76605 (0.74644) Boundary_loss: 0.015237 (0.015282) Loss: 0.78129 (0.76172) +2025-08-21,19:43:02 | INFO | Train Epoch: 3 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.66951 (0.74603) Boundary_loss: 0.015270 (0.015282) Loss: 0.68478 (0.76132) +2025-08-21,19:43:59 | INFO | Train Epoch: 3 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 50.078 Boundary Ratio: 0.256 Contrastive_loss: 0.77026 (0.74616) Boundary_loss: 0.015322 (0.015282) Loss: 0.78558 (0.76144) +2025-08-21,19:44:55 | INFO | Train Epoch: 3 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.85239 (0.74671) Boundary_loss: 0.015197 (0.015282) Loss: 0.86759 (0.76199) +2025-08-21,19:45:52 | INFO | Train Epoch: 3 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.342 Boundary Ratio: 0.247 Contrastive_loss: 0.69709 (0.74645) Boundary_loss: 0.015175 (0.015281) Loss: 0.71226 (0.76174) +2025-08-21,19:46:50 | INFO | Train Epoch: 3 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.70615 (0.74625) Boundary_loss: 0.015423 (0.015282) Loss: 0.72157 (0.76153) +2025-08-21,19:47:46 | INFO | Train Epoch: 3 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 49.189 Boundary Ratio: 0.251 Contrastive_loss: 0.82749 (0.74666) Boundary_loss: 0.015325 (0.015282) Loss: 0.84281 (0.76194) +2025-08-21,19:48:44 | INFO | Train Epoch: 3 [10035712/26365952 (38%)] Avg Boundaries (per batch): 49.449 Boundary Ratio: 0.252 Contrastive_loss: 0.80898 (0.74698) Boundary_loss: 0.015317 (0.015282) Loss: 0.82429 (0.76226) +2025-08-21,19:49:41 | INFO | Train Epoch: 3 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 0.69698 (0.74673) Boundary_loss: 0.015203 (0.015282) Loss: 0.71219 (0.76201) +2025-08-21,19:50:38 | INFO | Train Epoch: 3 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.60162 (0.74600) Boundary_loss: 0.015295 (0.015282) Loss: 0.61691 (0.76128) +2025-08-21,19:51:35 | INFO | Train Epoch: 3 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.69637 (0.74575) Boundary_loss: 0.015272 (0.015282) Loss: 0.71164 (0.76103) +2025-08-21,19:52:32 | INFO | Train Epoch: 3 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.71501 (0.74560) Boundary_loss: 0.015158 (0.015281) Loss: 0.73017 (0.76088) +2025-08-21,19:53:29 | INFO | Train Epoch: 3 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.180 Boundary Ratio: 0.246 Contrastive_loss: 0.76026 (0.74567) Boundary_loss: 0.015378 (0.015282) Loss: 0.77564 (0.76095) +2025-08-21,19:54:26 | INFO | Train Epoch: 3 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.383 Boundary Ratio: 0.252 Contrastive_loss: 0.82932 (0.74608) Boundary_loss: 0.015290 (0.015282) Loss: 0.84461 (0.76136) +2025-08-21,19:55:23 | INFO | Train Epoch: 3 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.78368 (0.74627) Boundary_loss: 0.015229 (0.015281) Loss: 0.79890 (0.76155) +2025-08-21,19:56:20 | INFO | Train Epoch: 3 [10445312/26365952 (40%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.83179 (0.74668) Boundary_loss: 0.015207 (0.015281) Loss: 0.84700 (0.76196) +2025-08-21,19:57:17 | INFO | Train Epoch: 3 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.72467 (0.74658) Boundary_loss: 0.015178 (0.015280) Loss: 0.73985 (0.76186) +2025-08-21,19:58:14 | INFO | Train Epoch: 3 [10547712/26365952 (40%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.78173 (0.74675) Boundary_loss: 0.015356 (0.015281) Loss: 0.79708 (0.76203) +2025-08-21,19:59:11 | INFO | Train Epoch: 3 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 0.71384 (0.74659) Boundary_loss: 0.015244 (0.015281) Loss: 0.72909 (0.76187) +2025-08-21,20:00:08 | INFO | Train Epoch: 3 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.59406 (0.74586) Boundary_loss: 0.015143 (0.015280) Loss: 0.60920 (0.76114) +2025-08-21,20:01:05 | INFO | Train Epoch: 3 [10701312/26365952 (41%)] Avg Boundaries (per batch): 49.375 Boundary Ratio: 0.252 Contrastive_loss: 0.78476 (0.74604) Boundary_loss: 0.015456 (0.015281) Loss: 0.80022 (0.76132) +2025-08-21,20:02:02 | INFO | Train Epoch: 3 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.424 Boundary Ratio: 0.252 Contrastive_loss: 0.60849 (0.74539) Boundary_loss: 0.015311 (0.015281) Loss: 0.62380 (0.76067) +2025-08-21,20:02:59 | INFO | Train Epoch: 3 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.033 Boundary Ratio: 0.245 Contrastive_loss: 0.81223 (0.74571) Boundary_loss: 0.015373 (0.015281) Loss: 0.82760 (0.76099) +2025-08-21,20:03:57 | INFO | Train Epoch: 3 [10854912/26365952 (41%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.64315 (0.74522) Boundary_loss: 0.015271 (0.015281) Loss: 0.65842 (0.76051) +2025-08-21,20:04:54 | INFO | Train Epoch: 3 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.057 Boundary Ratio: 0.245 Contrastive_loss: 0.73930 (0.74520) Boundary_loss: 0.015196 (0.015281) Loss: 0.75450 (0.76048) +2025-08-21,20:05:51 | INFO | Train Epoch: 3 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.549 Boundary Ratio: 0.253 Contrastive_loss: 0.81367 (0.74552) Boundary_loss: 0.015128 (0.015280) Loss: 0.82880 (0.76080) +2025-08-21,20:06:48 | INFO | Train Epoch: 3 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.65949 (0.74512) Boundary_loss: 0.015250 (0.015280) Loss: 0.67474 (0.76040) +2025-08-21,20:07:45 | INFO | Train Epoch: 3 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.75801 (0.74518) Boundary_loss: 0.015329 (0.015280) Loss: 0.77334 (0.76046) +2025-08-21,20:08:41 | INFO | Train Epoch: 3 [11110912/26365952 (42%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.72112 (0.74507) Boundary_loss: 0.015248 (0.015280) Loss: 0.73637 (0.76035) +2025-08-21,20:09:38 | INFO | Train Epoch: 3 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.79871 (0.74531) Boundary_loss: 0.015243 (0.015280) Loss: 0.81395 (0.76059) +2025-08-21,20:10:35 | INFO | Train Epoch: 3 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.111 Boundary Ratio: 0.245 Contrastive_loss: 0.77817 (0.74546) Boundary_loss: 0.015309 (0.015280) Loss: 0.79348 (0.76074) +2025-08-21,20:11:32 | INFO | Train Epoch: 3 [11264512/26365952 (43%)] Avg Boundaries (per batch): 49.482 Boundary Ratio: 0.252 Contrastive_loss: 0.64914 (0.74502) Boundary_loss: 0.015179 (0.015280) Loss: 0.66432 (0.76030) +2025-08-21,20:12:29 | INFO | Train Epoch: 3 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.70202 (0.74483) Boundary_loss: 0.015351 (0.015280) Loss: 0.71737 (0.76011) +2025-08-21,20:13:26 | INFO | Train Epoch: 3 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.219 Boundary Ratio: 0.246 Contrastive_loss: 0.72487 (0.74474) Boundary_loss: 0.015172 (0.015280) Loss: 0.74004 (0.76002) +2025-08-21,20:14:23 | INFO | Train Epoch: 3 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.63417 (0.74425) Boundary_loss: 0.015267 (0.015280) Loss: 0.64943 (0.75953) +2025-08-21,20:15:20 | INFO | Train Epoch: 3 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.60815 (0.74364) Boundary_loss: 0.015037 (0.015278) Loss: 0.62319 (0.75892) +2025-08-21,20:16:17 | INFO | Train Epoch: 3 [11520512/26365952 (44%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.82885 (0.74402) Boundary_loss: 0.015306 (0.015279) Loss: 0.84415 (0.75930) +2025-08-21,20:17:14 | INFO | Train Epoch: 3 [11571712/26365952 (44%)] Avg Boundaries (per batch): 49.385 Boundary Ratio: 0.252 Contrastive_loss: 0.74885 (0.74404) Boundary_loss: 0.015274 (0.015279) Loss: 0.76413 (0.75932) +2025-08-21,20:18:11 | INFO | Train Epoch: 3 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.77728 (0.74419) Boundary_loss: 0.015279 (0.015279) Loss: 0.79256 (0.75947) +2025-08-21,20:19:08 | INFO | Train Epoch: 3 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.621 Boundary Ratio: 0.253 Contrastive_loss: 0.76193 (0.74426) Boundary_loss: 0.015381 (0.015279) Loss: 0.77731 (0.75954) +2025-08-21,20:20:05 | INFO | Train Epoch: 3 [11725312/26365952 (44%)] Avg Boundaries (per batch): 47.803 Boundary Ratio: 0.244 Contrastive_loss: 0.66210 (0.74391) Boundary_loss: 0.015403 (0.015280) Loss: 0.67751 (0.75919) +2025-08-21,20:21:02 | INFO | Train Epoch: 3 [11776512/26365952 (45%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.72856 (0.74384) Boundary_loss: 0.015274 (0.015280) Loss: 0.74384 (0.75912) +2025-08-21,20:21:59 | INFO | Train Epoch: 3 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 0.77891 (0.74399) Boundary_loss: 0.015237 (0.015279) Loss: 0.79414 (0.75927) +2025-08-21,20:22:56 | INFO | Train Epoch: 3 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.79086 (0.74419) Boundary_loss: 0.015310 (0.015279) Loss: 0.80617 (0.75947) +2025-08-21,20:23:53 | INFO | Train Epoch: 3 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.67920 (0.74392) Boundary_loss: 0.015304 (0.015280) Loss: 0.69450 (0.75919) +2025-08-21,20:24:50 | INFO | Train Epoch: 3 [11981312/26365952 (45%)] Avg Boundaries (per batch): 47.609 Boundary Ratio: 0.243 Contrastive_loss: 0.59733 (0.74329) Boundary_loss: 0.015168 (0.015279) Loss: 0.61250 (0.75857) +2025-08-21,20:25:47 | INFO | Train Epoch: 3 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.070 Boundary Ratio: 0.245 Contrastive_loss: 0.80763 (0.74356) Boundary_loss: 0.015293 (0.015279) Loss: 0.82292 (0.75884) +2025-08-21,20:26:44 | INFO | Train Epoch: 3 [12083712/26365952 (46%)] Avg Boundaries (per batch): 49.752 Boundary Ratio: 0.254 Contrastive_loss: 0.79343 (0.74377) Boundary_loss: 0.015341 (0.015279) Loss: 0.80877 (0.75905) +2025-08-21,20:27:41 | INFO | Train Epoch: 3 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.67902 (0.74350) Boundary_loss: 0.015211 (0.015279) Loss: 0.69423 (0.75878) +2025-08-21,20:28:38 | INFO | Train Epoch: 3 [12186112/26365952 (46%)] Avg Boundaries (per batch): 49.381 Boundary Ratio: 0.252 Contrastive_loss: 0.67071 (0.74320) Boundary_loss: 0.015231 (0.015279) Loss: 0.68594 (0.75848) +2025-08-21,20:29:35 | INFO | Train Epoch: 3 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.76861 (0.74330) Boundary_loss: 0.015362 (0.015279) Loss: 0.78397 (0.75858) +2025-08-21,20:30:33 | INFO | Train Epoch: 3 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.63085 (0.74284) Boundary_loss: 0.015208 (0.015279) Loss: 0.64605 (0.75812) +2025-08-21,20:31:30 | INFO | Train Epoch: 3 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.63676 (0.74240) Boundary_loss: 0.015380 (0.015279) Loss: 0.65214 (0.75768) +2025-08-21,20:32:27 | INFO | Train Epoch: 3 [12390912/26365952 (47%)] Avg Boundaries (per batch): 49.688 Boundary Ratio: 0.254 Contrastive_loss: 0.64409 (0.74199) Boundary_loss: 0.015275 (0.015279) Loss: 0.65937 (0.75727) +2025-08-21,20:33:24 | INFO | Train Epoch: 3 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.71750 (0.74189) Boundary_loss: 0.015245 (0.015279) Loss: 0.73274 (0.75717) +2025-08-21,20:34:21 | INFO | Train Epoch: 3 [12493312/26365952 (47%)] Avg Boundaries (per batch): 49.619 Boundary Ratio: 0.253 Contrastive_loss: 0.76128 (0.74197) Boundary_loss: 0.015288 (0.015279) Loss: 0.77657 (0.75725) +2025-08-21,20:35:18 | INFO | Train Epoch: 3 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.64881 (0.74159) Boundary_loss: 0.015243 (0.015279) Loss: 0.66406 (0.75687) +2025-08-21,20:36:15 | INFO | Train Epoch: 3 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.307 Boundary Ratio: 0.246 Contrastive_loss: 0.71974 (0.74151) Boundary_loss: 0.015217 (0.015279) Loss: 0.73496 (0.75678) +2025-08-21,20:37:12 | INFO | Train Epoch: 3 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.86147 (0.74199) Boundary_loss: 0.015232 (0.015279) Loss: 0.87670 (0.75727) +2025-08-21,20:38:09 | INFO | Train Epoch: 3 [12698112/26365952 (48%)] Avg Boundaries (per batch): 47.791 Boundary Ratio: 0.244 Contrastive_loss: 0.72683 (0.74193) Boundary_loss: 0.015318 (0.015279) Loss: 0.74214 (0.75721) +2025-08-21,20:39:06 | INFO | Train Epoch: 3 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.75034 (0.74196) Boundary_loss: 0.015260 (0.015279) Loss: 0.76560 (0.75724) +2025-08-21,20:40:03 | INFO | Train Epoch: 3 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.64843 (0.74159) Boundary_loss: 0.015181 (0.015278) Loss: 0.66361 (0.75687) +2025-08-21,20:41:00 | INFO | Train Epoch: 3 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.67623 (0.74133) Boundary_loss: 0.015236 (0.015278) Loss: 0.69147 (0.75661) +2025-08-21,20:41:57 | INFO | Train Epoch: 3 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.81659 (0.74163) Boundary_loss: 0.015256 (0.015278) Loss: 0.83185 (0.75691) +2025-08-21,20:42:54 | INFO | Train Epoch: 3 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 0.69487 (0.74144) Boundary_loss: 0.015276 (0.015278) Loss: 0.71014 (0.75672) +2025-08-21,20:43:51 | INFO | Train Epoch: 3 [13005312/26365952 (49%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.73323 (0.74141) Boundary_loss: 0.015075 (0.015277) Loss: 0.74830 (0.75669) +2025-08-21,20:44:48 | INFO | Train Epoch: 3 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.71023 (0.74129) Boundary_loss: 0.015095 (0.015277) Loss: 0.72532 (0.75657) +2025-08-21,20:45:45 | INFO | Train Epoch: 3 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.70908 (0.74116) Boundary_loss: 0.015263 (0.015277) Loss: 0.72434 (0.75644) +2025-08-21,20:46:42 | INFO | Train Epoch: 3 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.014 Boundary Ratio: 0.245 Contrastive_loss: 0.50784 (0.74026) Boundary_loss: 0.015419 (0.015277) Loss: 0.52325 (0.75554) +2025-08-21,20:47:39 | INFO | Train Epoch: 3 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.72194 (0.74019) Boundary_loss: 0.015362 (0.015277) Loss: 0.73730 (0.75547) +2025-08-21,20:48:36 | INFO | Train Epoch: 3 [13261312/26365952 (50%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.69262 (0.74001) Boundary_loss: 0.015228 (0.015277) Loss: 0.70784 (0.75528) +2025-08-21,20:49:33 | INFO | Train Epoch: 3 [13312512/26365952 (50%)] Avg Boundaries (per batch): 50.004 Boundary Ratio: 0.255 Contrastive_loss: 0.73716 (0.74000) Boundary_loss: 0.015528 (0.015278) Loss: 0.75268 (0.75527) +2025-08-21,20:50:30 | INFO | Train Epoch: 3 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.67704 (0.73975) Boundary_loss: 0.015209 (0.015278) Loss: 0.69225 (0.75503) +2025-08-21,20:51:27 | INFO | Train Epoch: 3 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.67745 (0.73952) Boundary_loss: 0.015437 (0.015279) Loss: 0.69288 (0.75480) +2025-08-21,20:52:24 | INFO | Train Epoch: 3 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.79703 (0.73974) Boundary_loss: 0.015219 (0.015278) Loss: 0.81224 (0.75501) +2025-08-21,20:53:21 | INFO | Train Epoch: 3 [13517312/26365952 (51%)] Avg Boundaries (per batch): 47.746 Boundary Ratio: 0.244 Contrastive_loss: 0.61962 (0.73928) Boundary_loss: 0.015361 (0.015279) Loss: 0.63498 (0.75456) +2025-08-21,20:54:18 | INFO | Train Epoch: 3 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.68974 (0.73910) Boundary_loss: 0.015057 (0.015278) Loss: 0.70480 (0.75437) +2025-08-21,20:55:15 | INFO | Train Epoch: 3 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.74682 (0.73913) Boundary_loss: 0.015277 (0.015278) Loss: 0.76210 (0.75440) +2025-08-21,20:56:12 | INFO | Train Epoch: 3 [13670912/26365952 (52%)] Avg Boundaries (per batch): 49.316 Boundary Ratio: 0.252 Contrastive_loss: 0.77621 (0.73926) Boundary_loss: 0.015320 (0.015278) Loss: 0.79153 (0.75454) +2025-08-21,20:57:09 | INFO | Train Epoch: 3 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.61222 (0.73879) Boundary_loss: 0.015322 (0.015278) Loss: 0.62754 (0.75407) +2025-08-21,20:58:06 | INFO | Train Epoch: 3 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.79908 (0.73901) Boundary_loss: 0.015117 (0.015278) Loss: 0.81419 (0.75429) +2025-08-21,20:59:04 | INFO | Train Epoch: 3 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.67459 (0.73878) Boundary_loss: 0.015407 (0.015278) Loss: 0.68999 (0.75405) +2025-08-21,21:00:01 | INFO | Train Epoch: 3 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.73824 (0.73877) Boundary_loss: 0.015217 (0.015278) Loss: 0.75345 (0.75405) +2025-08-21,21:00:58 | INFO | Train Epoch: 3 [13926912/26365952 (53%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.68206 (0.73857) Boundary_loss: 0.015304 (0.015278) Loss: 0.69737 (0.75385) +2025-08-21,21:01:55 | INFO | Train Epoch: 3 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 0.75086 (0.73861) Boundary_loss: 0.015387 (0.015278) Loss: 0.76624 (0.75389) +2025-08-21,21:02:52 | INFO | Train Epoch: 3 [14029312/26365952 (53%)] Avg Boundaries (per batch): 49.219 Boundary Ratio: 0.251 Contrastive_loss: 0.75131 (0.73866) Boundary_loss: 0.015317 (0.015278) Loss: 0.76662 (0.75394) +2025-08-21,21:03:49 | INFO | Train Epoch: 3 [14080512/26365952 (53%)] Avg Boundaries (per batch): 47.855 Boundary Ratio: 0.244 Contrastive_loss: 0.76088 (0.73874) Boundary_loss: 0.015291 (0.015278) Loss: 0.77618 (0.75402) +2025-08-21,21:04:46 | INFO | Train Epoch: 3 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.68668 (0.73855) Boundary_loss: 0.015271 (0.015278) Loss: 0.70195 (0.75383) +2025-08-21,21:05:43 | INFO | Train Epoch: 3 [14182912/26365952 (54%)] Avg Boundaries (per batch): 49.742 Boundary Ratio: 0.254 Contrastive_loss: 0.71247 (0.73846) Boundary_loss: 0.015401 (0.015279) Loss: 0.72787 (0.75374) +2025-08-21,21:06:40 | INFO | Train Epoch: 3 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 0.64830 (0.73813) Boundary_loss: 0.015305 (0.015279) Loss: 0.66360 (0.75341) +2025-08-21,21:07:37 | INFO | Train Epoch: 3 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.68693 (0.73795) Boundary_loss: 0.015135 (0.015278) Loss: 0.70207 (0.75323) +2025-08-21,21:08:34 | INFO | Train Epoch: 3 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.71515 (0.73787) Boundary_loss: 0.015131 (0.015278) Loss: 0.73028 (0.75315) +2025-08-21,21:09:31 | INFO | Train Epoch: 3 [14387712/26365952 (55%)] Avg Boundaries (per batch): 50.008 Boundary Ratio: 0.255 Contrastive_loss: 0.75212 (0.73792) Boundary_loss: 0.015480 (0.015279) Loss: 0.76760 (0.75320) +2025-08-21,21:10:28 | INFO | Train Epoch: 3 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.041 Boundary Ratio: 0.245 Contrastive_loss: 0.78961 (0.73810) Boundary_loss: 0.015124 (0.015278) Loss: 0.80473 (0.75338) +2025-08-21,21:11:25 | INFO | Train Epoch: 3 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.76074 (0.73818) Boundary_loss: 0.015145 (0.015278) Loss: 0.77589 (0.75346) +2025-08-21,21:12:22 | INFO | Train Epoch: 3 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.72179 (0.73813) Boundary_loss: 0.015321 (0.015278) Loss: 0.73711 (0.75340) +2025-08-21,21:13:19 | INFO | Train Epoch: 3 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.75406 (0.73818) Boundary_loss: 0.015054 (0.015277) Loss: 0.76912 (0.75346) +2025-08-21,21:14:16 | INFO | Train Epoch: 3 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.490 Boundary Ratio: 0.253 Contrastive_loss: 0.65783 (0.73790) Boundary_loss: 0.015190 (0.015277) Loss: 0.67303 (0.75318) +2025-08-21,21:15:13 | INFO | Train Epoch: 3 [14694912/26365952 (56%)] Avg Boundaries (per batch): 49.717 Boundary Ratio: 0.254 Contrastive_loss: 0.74599 (0.73793) Boundary_loss: 0.015474 (0.015277) Loss: 0.76146 (0.75321) +2025-08-21,21:16:10 | INFO | Train Epoch: 3 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.307 Boundary Ratio: 0.246 Contrastive_loss: 0.57093 (0.73735) Boundary_loss: 0.015222 (0.015277) Loss: 0.58615 (0.75263) +2025-08-21,21:17:07 | INFO | Train Epoch: 3 [14797312/26365952 (56%)] Avg Boundaries (per batch): 49.486 Boundary Ratio: 0.252 Contrastive_loss: 0.67199 (0.73713) Boundary_loss: 0.015318 (0.015277) Loss: 0.68731 (0.75240) +2025-08-21,21:18:04 | INFO | Train Epoch: 3 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.74518 (0.73715) Boundary_loss: 0.015184 (0.015277) Loss: 0.76036 (0.75243) +2025-08-21,21:19:01 | INFO | Train Epoch: 3 [14899712/26365952 (57%)] Avg Boundaries (per batch): 49.625 Boundary Ratio: 0.253 Contrastive_loss: 0.67873 (0.73695) Boundary_loss: 0.015240 (0.015277) Loss: 0.69397 (0.75223) +2025-08-21,21:19:58 | INFO | Train Epoch: 3 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.50413 (0.73616) Boundary_loss: 0.015195 (0.015277) Loss: 0.51933 (0.75144) +2025-08-21,21:20:55 | INFO | Train Epoch: 3 [15002112/26365952 (57%)] Avg Boundaries (per batch): 49.520 Boundary Ratio: 0.253 Contrastive_loss: 0.66087 (0.73590) Boundary_loss: 0.015382 (0.015277) Loss: 0.67625 (0.75118) +2025-08-21,21:21:52 | INFO | Train Epoch: 3 [15053312/26365952 (57%)] Avg Boundaries (per batch): 49.221 Boundary Ratio: 0.251 Contrastive_loss: 0.77655 (0.73604) Boundary_loss: 0.015263 (0.015277) Loss: 0.79181 (0.75132) +2025-08-21,21:22:49 | INFO | Train Epoch: 3 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.133 Boundary Ratio: 0.246 Contrastive_loss: 0.64423 (0.73573) Boundary_loss: 0.015243 (0.015277) Loss: 0.65947 (0.75101) +2025-08-21,21:23:47 | INFO | Train Epoch: 3 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.72348 (0.73569) Boundary_loss: 0.015273 (0.015277) Loss: 0.73875 (0.75097) +2025-08-21,21:24:44 | INFO | Train Epoch: 3 [15206912/26365952 (58%)] Avg Boundaries (per batch): 49.494 Boundary Ratio: 0.253 Contrastive_loss: 0.67707 (0.73549) Boundary_loss: 0.015225 (0.015277) Loss: 0.69230 (0.75077) +2025-08-21,21:25:41 | INFO | Train Epoch: 3 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.79520 (0.73569) Boundary_loss: 0.015088 (0.015276) Loss: 0.81029 (0.75097) +2025-08-21,21:26:38 | INFO | Train Epoch: 3 [15309312/26365952 (58%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.64581 (0.73539) Boundary_loss: 0.015261 (0.015276) Loss: 0.66107 (0.75067) +2025-08-21,21:27:35 | INFO | Train Epoch: 3 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.53081 (0.73471) Boundary_loss: 0.015328 (0.015276) Loss: 0.54614 (0.74999) +2025-08-21,21:28:32 | INFO | Train Epoch: 3 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.62396 (0.73435) Boundary_loss: 0.015216 (0.015276) Loss: 0.63917 (0.74962) +2025-08-21,21:29:29 | INFO | Train Epoch: 3 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.75339 (0.73441) Boundary_loss: 0.015341 (0.015276) Loss: 0.76873 (0.74968) +2025-08-21,21:30:26 | INFO | Train Epoch: 3 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.78472 (0.73457) Boundary_loss: 0.015308 (0.015276) Loss: 0.80002 (0.74985) +2025-08-21,21:31:23 | INFO | Train Epoch: 3 [15565312/26365952 (59%)] Avg Boundaries (per batch): 47.990 Boundary Ratio: 0.245 Contrastive_loss: 0.65128 (0.73430) Boundary_loss: 0.015190 (0.015276) Loss: 0.66647 (0.74958) +2025-08-21,21:32:20 | INFO | Train Epoch: 3 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.73506 (0.73430) Boundary_loss: 0.015162 (0.015276) Loss: 0.75022 (0.74958) +2025-08-21,21:33:17 | INFO | Train Epoch: 3 [15667712/26365952 (59%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 0.69496 (0.73418) Boundary_loss: 0.015159 (0.015275) Loss: 0.71012 (0.74945) +2025-08-21,21:34:13 | INFO | Train Epoch: 3 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.73664 (0.73418) Boundary_loss: 0.015266 (0.015275) Loss: 0.75191 (0.74946) +2025-08-21,21:35:10 | INFO | Train Epoch: 3 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.63153 (0.73385) Boundary_loss: 0.015291 (0.015275) Loss: 0.64682 (0.74913) +2025-08-21,21:36:07 | INFO | Train Epoch: 3 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.59959 (0.73342) Boundary_loss: 0.015132 (0.015275) Loss: 0.61473 (0.74869) +2025-08-21,21:37:04 | INFO | Train Epoch: 3 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.016 Boundary Ratio: 0.245 Contrastive_loss: 0.60326 (0.73300) Boundary_loss: 0.015314 (0.015275) Loss: 0.61857 (0.74827) +2025-08-21,21:38:01 | INFO | Train Epoch: 3 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.69761 (0.73289) Boundary_loss: 0.015193 (0.015275) Loss: 0.71280 (0.74816) +2025-08-21,21:38:58 | INFO | Train Epoch: 3 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.65881 (0.73265) Boundary_loss: 0.015088 (0.015274) Loss: 0.67390 (0.74792) +2025-08-21,21:39:55 | INFO | Train Epoch: 3 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.73740 (0.73266) Boundary_loss: 0.015350 (0.015274) Loss: 0.75275 (0.74794) +2025-08-21,21:40:51 | INFO | Train Epoch: 3 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.72368 (0.73264) Boundary_loss: 0.015276 (0.015274) Loss: 0.73895 (0.74791) +2025-08-21,21:41:48 | INFO | Train Epoch: 3 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.277 Boundary Ratio: 0.246 Contrastive_loss: 0.70786 (0.73256) Boundary_loss: 0.015237 (0.015274) Loss: 0.72310 (0.74783) +2025-08-21,21:42:45 | INFO | Train Epoch: 3 [16179712/26365952 (61%)] Avg Boundaries (per batch): 47.760 Boundary Ratio: 0.244 Contrastive_loss: 0.69867 (0.73245) Boundary_loss: 0.015310 (0.015274) Loss: 0.71398 (0.74773) +2025-08-21,21:43:42 | INFO | Train Epoch: 3 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.74183 (0.73248) Boundary_loss: 0.015248 (0.015274) Loss: 0.75707 (0.74775) +2025-08-21,21:44:39 | INFO | Train Epoch: 3 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.83020 (0.73279) Boundary_loss: 0.015365 (0.015274) Loss: 0.84557 (0.74806) +2025-08-21,21:45:36 | INFO | Train Epoch: 3 [16333312/26365952 (62%)] Avg Boundaries (per batch): 50.432 Boundary Ratio: 0.257 Contrastive_loss: 0.79664 (0.73299) Boundary_loss: 0.015385 (0.015275) Loss: 0.81203 (0.74826) +2025-08-21,21:46:33 | INFO | Train Epoch: 3 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.79926 (0.73319) Boundary_loss: 0.015270 (0.015275) Loss: 0.81453 (0.74847) +2025-08-21,21:47:30 | INFO | Train Epoch: 3 [16435712/26365952 (62%)] Avg Boundaries (per batch): 49.621 Boundary Ratio: 0.253 Contrastive_loss: 0.66511 (0.73298) Boundary_loss: 0.015576 (0.015276) Loss: 0.68068 (0.74826) +2025-08-21,21:48:27 | INFO | Train Epoch: 3 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.445 Boundary Ratio: 0.252 Contrastive_loss: 0.62780 (0.73266) Boundary_loss: 0.015317 (0.015276) Loss: 0.64312 (0.74793) +2025-08-21,21:49:24 | INFO | Train Epoch: 3 [16538112/26365952 (63%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.78125 (0.73281) Boundary_loss: 0.015128 (0.015275) Loss: 0.79638 (0.74808) +2025-08-21,21:50:21 | INFO | Train Epoch: 3 [16589312/26365952 (63%)] Avg Boundaries (per batch): 49.871 Boundary Ratio: 0.254 Contrastive_loss: 0.62851 (0.73248) Boundary_loss: 0.015403 (0.015276) Loss: 0.64392 (0.74776) +2025-08-21,21:51:18 | INFO | Train Epoch: 3 [16640512/26365952 (63%)] Avg Boundaries (per batch): 50.113 Boundary Ratio: 0.256 Contrastive_loss: 0.69080 (0.73236) Boundary_loss: 0.015328 (0.015276) Loss: 0.70613 (0.74763) +2025-08-21,21:52:15 | INFO | Train Epoch: 3 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 0.66646 (0.73216) Boundary_loss: 0.015476 (0.015277) Loss: 0.68193 (0.74743) +2025-08-21,21:53:12 | INFO | Train Epoch: 3 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.61602 (0.73180) Boundary_loss: 0.015313 (0.015277) Loss: 0.63133 (0.74708) +2025-08-21,21:54:09 | INFO | Train Epoch: 3 [16794112/26365952 (64%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.77056 (0.73192) Boundary_loss: 0.015259 (0.015277) Loss: 0.78582 (0.74720) +2025-08-21,21:55:06 | INFO | Train Epoch: 3 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.68135 (0.73177) Boundary_loss: 0.015253 (0.015277) Loss: 0.69660 (0.74704) +2025-08-21,21:56:03 | INFO | Train Epoch: 3 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 0.68285 (0.73162) Boundary_loss: 0.015369 (0.015277) Loss: 0.69822 (0.74689) +2025-08-21,21:57:00 | INFO | Train Epoch: 3 [16947712/26365952 (64%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.66666 (0.73142) Boundary_loss: 0.015374 (0.015277) Loss: 0.68204 (0.74670) +2025-08-21,21:57:57 | INFO | Train Epoch: 3 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.66741 (0.73123) Boundary_loss: 0.015200 (0.015277) Loss: 0.68261 (0.74651) +2025-08-21,21:58:54 | INFO | Train Epoch: 3 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.115 Boundary Ratio: 0.245 Contrastive_loss: 0.64369 (0.73097) Boundary_loss: 0.015339 (0.015277) Loss: 0.65903 (0.74625) +2025-08-21,21:59:52 | INFO | Train Epoch: 3 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 0.75868 (0.73105) Boundary_loss: 0.015167 (0.015277) Loss: 0.77384 (0.74633) +2025-08-21,22:00:49 | INFO | Train Epoch: 3 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.62549 (0.73074) Boundary_loss: 0.015241 (0.015277) Loss: 0.64073 (0.74601) +2025-08-21,22:01:46 | INFO | Train Epoch: 3 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.385 Boundary Ratio: 0.247 Contrastive_loss: 0.59578 (0.73034) Boundary_loss: 0.015159 (0.015276) Loss: 0.61094 (0.74561) +2025-08-21,22:02:43 | INFO | Train Epoch: 3 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.70313 (0.73026) Boundary_loss: 0.015194 (0.015276) Loss: 0.71832 (0.74553) +2025-08-21,22:03:40 | INFO | Train Epoch: 3 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.424 Boundary Ratio: 0.252 Contrastive_loss: 0.74443 (0.73030) Boundary_loss: 0.015292 (0.015276) Loss: 0.75972 (0.74557) +2025-08-21,22:04:37 | INFO | Train Epoch: 3 [17357312/26365952 (66%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 0.74394 (0.73034) Boundary_loss: 0.015166 (0.015276) Loss: 0.75911 (0.74561) +2025-08-21,22:05:34 | INFO | Train Epoch: 3 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.71487 (0.73029) Boundary_loss: 0.015202 (0.015276) Loss: 0.73007 (0.74557) +2025-08-21,22:06:30 | INFO | Train Epoch: 3 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.63509 (0.73001) Boundary_loss: 0.015329 (0.015276) Loss: 0.65042 (0.74529) +2025-08-21,22:07:28 | INFO | Train Epoch: 3 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.79536 (0.73020) Boundary_loss: 0.015125 (0.015275) Loss: 0.81049 (0.74548) +2025-08-21,22:08:25 | INFO | Train Epoch: 3 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.520 Boundary Ratio: 0.253 Contrastive_loss: 0.67072 (0.73003) Boundary_loss: 0.015234 (0.015275) Loss: 0.68596 (0.74531) +2025-08-21,22:09:22 | INFO | Train Epoch: 3 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.63368 (0.72975) Boundary_loss: 0.015251 (0.015275) Loss: 0.64893 (0.74503) +2025-08-21,22:10:19 | INFO | Train Epoch: 3 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.63814 (0.72949) Boundary_loss: 0.015183 (0.015275) Loss: 0.65333 (0.74476) +2025-08-21,22:11:16 | INFO | Train Epoch: 3 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.64724 (0.72925) Boundary_loss: 0.015222 (0.015275) Loss: 0.66247 (0.74453) +2025-08-21,22:12:13 | INFO | Train Epoch: 3 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.64978 (0.72902) Boundary_loss: 0.015167 (0.015274) Loss: 0.66495 (0.74430) +2025-08-21,22:13:10 | INFO | Train Epoch: 3 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.70614 (0.72896) Boundary_loss: 0.015251 (0.015274) Loss: 0.72139 (0.74423) +2025-08-21,22:14:07 | INFO | Train Epoch: 3 [17869312/26365952 (68%)] Avg Boundaries (per batch): 47.996 Boundary Ratio: 0.245 Contrastive_loss: 0.81493 (0.72920) Boundary_loss: 0.015113 (0.015274) Loss: 0.83004 (0.74448) +2025-08-21,22:15:04 | INFO | Train Epoch: 3 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.66769 (0.72903) Boundary_loss: 0.015175 (0.015274) Loss: 0.68287 (0.74430) +2025-08-21,22:16:01 | INFO | Train Epoch: 3 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.77088 (0.72915) Boundary_loss: 0.015325 (0.015274) Loss: 0.78620 (0.74442) +2025-08-21,22:16:58 | INFO | Train Epoch: 3 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.137 Boundary Ratio: 0.246 Contrastive_loss: 0.61755 (0.72883) Boundary_loss: 0.015269 (0.015274) Loss: 0.63282 (0.74410) +2025-08-21,22:17:55 | INFO | Train Epoch: 3 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.79809 (0.72903) Boundary_loss: 0.015043 (0.015273) Loss: 0.81313 (0.74430) +2025-08-21,22:18:52 | INFO | Train Epoch: 3 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.72624 (0.72902) Boundary_loss: 0.015115 (0.015273) Loss: 0.74136 (0.74429) +2025-08-21,22:19:49 | INFO | Train Epoch: 3 [18176512/26365952 (69%)] Avg Boundaries (per batch): 49.527 Boundary Ratio: 0.253 Contrastive_loss: 0.74698 (0.72907) Boundary_loss: 0.015224 (0.015272) Loss: 0.76220 (0.74434) +2025-08-21,22:20:46 | INFO | Train Epoch: 3 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.61155 (0.72874) Boundary_loss: 0.015430 (0.015273) Loss: 0.62698 (0.74401) +2025-08-21,22:21:43 | INFO | Train Epoch: 3 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.73918 (0.72877) Boundary_loss: 0.015176 (0.015273) Loss: 0.75436 (0.74404) +2025-08-21,22:22:40 | INFO | Train Epoch: 3 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.73690 (0.72879) Boundary_loss: 0.015301 (0.015273) Loss: 0.75220 (0.74406) +2025-08-21,22:23:37 | INFO | Train Epoch: 3 [18381312/26365952 (70%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.63413 (0.72853) Boundary_loss: 0.015284 (0.015273) Loss: 0.64941 (0.74380) +2025-08-21,22:24:35 | INFO | Train Epoch: 3 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.74764 (0.72858) Boundary_loss: 0.015323 (0.015273) Loss: 0.76297 (0.74385) +2025-08-21,22:25:32 | INFO | Train Epoch: 3 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.262 Boundary Ratio: 0.246 Contrastive_loss: 0.81448 (0.72882) Boundary_loss: 0.015491 (0.015273) Loss: 0.82997 (0.74409) +2025-08-21,22:26:29 | INFO | Train Epoch: 3 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.70153 (0.72874) Boundary_loss: 0.015286 (0.015273) Loss: 0.71682 (0.74402) +2025-08-21,22:27:26 | INFO | Train Epoch: 3 [18586112/26365952 (70%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.67089 (0.72858) Boundary_loss: 0.015131 (0.015273) Loss: 0.68603 (0.74386) +2025-08-21,22:28:23 | INFO | Train Epoch: 3 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.69019 (0.72848) Boundary_loss: 0.015317 (0.015273) Loss: 0.70551 (0.74375) +2025-08-21,22:29:20 | INFO | Train Epoch: 3 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.63167 (0.72821) Boundary_loss: 0.015045 (0.015273) Loss: 0.64672 (0.74349) +2025-08-21,22:30:17 | INFO | Train Epoch: 3 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.67458 (0.72807) Boundary_loss: 0.015234 (0.015272) Loss: 0.68981 (0.74334) +2025-08-21,22:31:14 | INFO | Train Epoch: 3 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.57222 (0.72764) Boundary_loss: 0.015141 (0.015272) Loss: 0.58736 (0.74292) +2025-08-21,22:32:11 | INFO | Train Epoch: 3 [18842112/26365952 (71%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 0.65785 (0.72746) Boundary_loss: 0.015425 (0.015273) Loss: 0.67327 (0.74273) +2025-08-21,22:33:08 | INFO | Train Epoch: 3 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.75833 (0.72754) Boundary_loss: 0.015113 (0.015272) Loss: 0.77344 (0.74281) +2025-08-21,22:34:05 | INFO | Train Epoch: 3 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.332 Boundary Ratio: 0.247 Contrastive_loss: 0.67237 (0.72739) Boundary_loss: 0.015326 (0.015272) Loss: 0.68769 (0.74266) +2025-08-21,22:35:02 | INFO | Train Epoch: 3 [18995712/26365952 (72%)] Avg Boundaries (per batch): 49.359 Boundary Ratio: 0.252 Contrastive_loss: 0.72191 (0.72738) Boundary_loss: 0.015216 (0.015272) Loss: 0.73713 (0.74265) +2025-08-21,22:35:59 | INFO | Train Epoch: 3 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.781 Boundary Ratio: 0.254 Contrastive_loss: 0.68653 (0.72727) Boundary_loss: 0.015334 (0.015272) Loss: 0.70186 (0.74254) +2025-08-21,22:36:56 | INFO | Train Epoch: 3 [19098112/26365952 (72%)] Avg Boundaries (per batch): 49.900 Boundary Ratio: 0.255 Contrastive_loss: 0.65926 (0.72708) Boundary_loss: 0.015299 (0.015272) Loss: 0.67456 (0.74236) +2025-08-21,22:37:53 | INFO | Train Epoch: 3 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.61667 (0.72679) Boundary_loss: 0.015166 (0.015272) Loss: 0.63184 (0.74206) +2025-08-21,22:38:50 | INFO | Train Epoch: 3 [19200512/26365952 (73%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 0.64250 (0.72657) Boundary_loss: 0.015332 (0.015272) Loss: 0.65783 (0.74184) +2025-08-21,22:39:47 | INFO | Train Epoch: 3 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.70046 (0.72650) Boundary_loss: 0.015357 (0.015272) Loss: 0.71582 (0.74177) +2025-08-21,22:40:44 | INFO | Train Epoch: 3 [19302912/26365952 (73%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.72741 (0.72650) Boundary_loss: 0.015300 (0.015273) Loss: 0.74271 (0.74177) +2025-08-21,22:41:42 | INFO | Train Epoch: 3 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.62210 (0.72622) Boundary_loss: 0.015129 (0.015272) Loss: 0.63723 (0.74150) +2025-08-21,22:42:39 | INFO | Train Epoch: 3 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.270 Boundary Ratio: 0.246 Contrastive_loss: 0.63786 (0.72599) Boundary_loss: 0.015171 (0.015272) Loss: 0.65304 (0.74126) +2025-08-21,22:43:36 | INFO | Train Epoch: 3 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.64276 (0.72577) Boundary_loss: 0.015305 (0.015272) Loss: 0.65806 (0.74104) +2025-08-21,22:44:33 | INFO | Train Epoch: 3 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.72845 (0.72578) Boundary_loss: 0.015252 (0.015272) Loss: 0.74370 (0.74105) +2025-08-21,22:45:30 | INFO | Train Epoch: 3 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.207 Boundary Ratio: 0.246 Contrastive_loss: 0.66205 (0.72561) Boundary_loss: 0.015220 (0.015272) Loss: 0.67728 (0.74088) +2025-08-21,22:46:27 | INFO | Train Epoch: 3 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.69503 (0.72553) Boundary_loss: 0.015335 (0.015272) Loss: 0.71036 (0.74081) +2025-08-21,22:47:24 | INFO | Train Epoch: 3 [19661312/26365952 (75%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.62532 (0.72527) Boundary_loss: 0.015125 (0.015272) Loss: 0.64045 (0.74054) +2025-08-21,22:48:21 | INFO | Train Epoch: 3 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.79940 (0.72546) Boundary_loss: 0.015309 (0.015272) Loss: 0.81471 (0.74074) +2025-08-21,22:49:18 | INFO | Train Epoch: 3 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.66017 (0.72530) Boundary_loss: 0.015430 (0.015272) Loss: 0.67560 (0.74057) +2025-08-21,22:50:15 | INFO | Train Epoch: 3 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.879 Boundary Ratio: 0.254 Contrastive_loss: 0.67664 (0.72517) Boundary_loss: 0.015306 (0.015272) Loss: 0.69194 (0.74044) +2025-08-21,22:51:13 | INFO | Train Epoch: 3 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.67133 (0.72503) Boundary_loss: 0.015275 (0.015272) Loss: 0.68660 (0.74030) +2025-08-21,22:52:10 | INFO | Train Epoch: 3 [19917312/26365952 (76%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 0.72763 (0.72504) Boundary_loss: 0.015479 (0.015273) Loss: 0.74311 (0.74031) +2025-08-21,22:53:06 | INFO | Train Epoch: 3 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.547 Boundary Ratio: 0.253 Contrastive_loss: 0.65389 (0.72486) Boundary_loss: 0.015291 (0.015273) Loss: 0.66918 (0.74013) +2025-08-21,22:54:03 | INFO | Train Epoch: 3 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.71050 (0.72482) Boundary_loss: 0.015256 (0.015273) Loss: 0.72576 (0.74009) +2025-08-21,22:55:00 | INFO | Train Epoch: 3 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.088 Boundary Ratio: 0.245 Contrastive_loss: 0.61924 (0.72455) Boundary_loss: 0.015365 (0.015273) Loss: 0.63461 (0.73982) +2025-08-21,22:55:57 | INFO | Train Epoch: 3 [20122112/26365952 (76%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 0.59639 (0.72423) Boundary_loss: 0.015408 (0.015273) Loss: 0.61180 (0.73950) +2025-08-21,22:56:55 | INFO | Train Epoch: 3 [20173312/26365952 (77%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.69339 (0.72415) Boundary_loss: 0.015236 (0.015273) Loss: 0.70863 (0.73942) +2025-08-21,22:57:52 | INFO | Train Epoch: 3 [20224512/26365952 (77%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.63876 (0.72393) Boundary_loss: 0.015254 (0.015273) Loss: 0.65401 (0.73921) +2025-08-21,22:58:49 | INFO | Train Epoch: 3 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.73564 (0.72396) Boundary_loss: 0.015215 (0.015273) Loss: 0.75085 (0.73924) +2025-08-21,22:59:46 | INFO | Train Epoch: 3 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.061 Boundary Ratio: 0.245 Contrastive_loss: 0.61395 (0.72369) Boundary_loss: 0.015217 (0.015273) Loss: 0.62917 (0.73896) +2025-08-21,23:00:43 | INFO | Train Epoch: 3 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.148 Boundary Ratio: 0.246 Contrastive_loss: 0.72283 (0.72368) Boundary_loss: 0.015280 (0.015273) Loss: 0.73811 (0.73896) +2025-08-21,23:01:40 | INFO | Train Epoch: 3 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.54524 (0.72324) Boundary_loss: 0.015181 (0.015273) Loss: 0.56042 (0.73851) +2025-08-21,23:02:37 | INFO | Train Epoch: 3 [20480512/26365952 (78%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.66310 (0.72309) Boundary_loss: 0.015288 (0.015273) Loss: 0.67839 (0.73836) +2025-08-21,23:03:34 | INFO | Train Epoch: 3 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.77372 (0.72321) Boundary_loss: 0.015428 (0.015273) Loss: 0.78915 (0.73849) +2025-08-21,23:04:31 | INFO | Train Epoch: 3 [20582912/26365952 (78%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.68627 (0.72312) Boundary_loss: 0.015299 (0.015273) Loss: 0.70157 (0.73840) +2025-08-21,23:05:28 | INFO | Train Epoch: 3 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.66240 (0.72297) Boundary_loss: 0.015161 (0.015273) Loss: 0.67756 (0.73824) +2025-08-21,23:06:25 | INFO | Train Epoch: 3 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.72612 (0.72298) Boundary_loss: 0.015223 (0.015273) Loss: 0.74135 (0.73825) +2025-08-21,23:07:22 | INFO | Train Epoch: 3 [20736512/26365952 (79%)] Avg Boundaries (per batch): 49.412 Boundary Ratio: 0.252 Contrastive_loss: 0.69248 (0.72290) Boundary_loss: 0.015309 (0.015273) Loss: 0.70779 (0.73818) +2025-08-21,23:08:19 | INFO | Train Epoch: 3 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.293 Boundary Ratio: 0.251 Contrastive_loss: 0.72753 (0.72292) Boundary_loss: 0.015294 (0.015273) Loss: 0.74282 (0.73819) +2025-08-21,23:09:16 | INFO | Train Epoch: 3 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.67719 (0.72280) Boundary_loss: 0.015259 (0.015273) Loss: 0.69245 (0.73808) +2025-08-21,23:10:13 | INFO | Train Epoch: 3 [20890112/26365952 (79%)] Avg Boundaries (per batch): 49.570 Boundary Ratio: 0.253 Contrastive_loss: 0.77805 (0.72294) Boundary_loss: 0.015395 (0.015273) Loss: 0.79344 (0.73821) +2025-08-21,23:11:10 | INFO | Train Epoch: 3 [20941312/26365952 (79%)] Avg Boundaries (per batch): 47.057 Boundary Ratio: 0.240 Contrastive_loss: 0.59251 (0.72262) Boundary_loss: 0.015449 (0.015274) Loss: 0.60796 (0.73789) +2025-08-21,23:12:07 | INFO | Train Epoch: 3 [20992512/26365952 (80%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.62359 (0.72238) Boundary_loss: 0.015229 (0.015273) Loss: 0.63882 (0.73765) +2025-08-21,23:13:04 | INFO | Train Epoch: 3 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.68876 (0.72230) Boundary_loss: 0.015310 (0.015274) Loss: 0.70407 (0.73757) +2025-08-21,23:14:01 | INFO | Train Epoch: 3 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.69930 (0.72224) Boundary_loss: 0.015350 (0.015274) Loss: 0.71465 (0.73752) +2025-08-21,23:14:58 | INFO | Train Epoch: 3 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.221 Boundary Ratio: 0.246 Contrastive_loss: 0.55152 (0.72183) Boundary_loss: 0.015233 (0.015274) Loss: 0.56675 (0.73710) +2025-08-21,23:15:55 | INFO | Train Epoch: 3 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.66282 (0.72169) Boundary_loss: 0.015132 (0.015273) Loss: 0.67795 (0.73696) +2025-08-21,23:16:52 | INFO | Train Epoch: 3 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.65809 (0.72153) Boundary_loss: 0.015145 (0.015273) Loss: 0.67323 (0.73681) +2025-08-21,23:17:49 | INFO | Train Epoch: 3 [21299712/26365952 (81%)] Avg Boundaries (per batch): 47.682 Boundary Ratio: 0.243 Contrastive_loss: 0.71355 (0.72152) Boundary_loss: 0.015383 (0.015273) Loss: 0.72893 (0.73679) +2025-08-21,23:18:46 | INFO | Train Epoch: 3 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.61842 (0.72127) Boundary_loss: 0.015444 (0.015274) Loss: 0.63387 (0.73654) +2025-08-21,23:19:44 | INFO | Train Epoch: 3 [21402112/26365952 (81%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 0.69195 (0.72120) Boundary_loss: 0.015439 (0.015274) Loss: 0.70739 (0.73647) +2025-08-21,23:20:40 | INFO | Train Epoch: 3 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.596 Boundary Ratio: 0.253 Contrastive_loss: 0.73480 (0.72123) Boundary_loss: 0.015346 (0.015274) Loss: 0.75015 (0.73651) +2025-08-21,23:21:37 | INFO | Train Epoch: 3 [21504512/26365952 (82%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 0.69456 (0.72117) Boundary_loss: 0.015287 (0.015274) Loss: 0.70985 (0.73644) +2025-08-21,23:22:34 | INFO | Train Epoch: 3 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.65408 (0.72101) Boundary_loss: 0.015201 (0.015274) Loss: 0.66928 (0.73628) +2025-08-21,23:23:31 | INFO | Train Epoch: 3 [21606912/26365952 (82%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 0.65258 (0.72085) Boundary_loss: 0.015182 (0.015274) Loss: 0.66776 (0.73612) +2025-08-21,23:24:28 | INFO | Train Epoch: 3 [21658112/26365952 (82%)] Avg Boundaries (per batch): 47.721 Boundary Ratio: 0.243 Contrastive_loss: 0.90148 (0.72127) Boundary_loss: 0.015495 (0.015274) Loss: 0.91698 (0.73655) +2025-08-21,23:25:25 | INFO | Train Epoch: 3 [21709312/26365952 (82%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 0.61638 (0.72103) Boundary_loss: 0.015312 (0.015274) Loss: 0.63170 (0.73630) +2025-08-21,23:26:22 | INFO | Train Epoch: 3 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.62358 (0.72080) Boundary_loss: 0.015235 (0.015274) Loss: 0.63881 (0.73607) +2025-08-21,23:27:19 | INFO | Train Epoch: 3 [21811712/26365952 (83%)] Avg Boundaries (per batch): 47.891 Boundary Ratio: 0.244 Contrastive_loss: 0.72058 (0.72080) Boundary_loss: 0.015269 (0.015274) Loss: 0.73585 (0.73607) +2025-08-21,23:28:16 | INFO | Train Epoch: 3 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.59374 (0.72050) Boundary_loss: 0.015168 (0.015274) Loss: 0.60890 (0.73577) +2025-08-21,23:29:13 | INFO | Train Epoch: 3 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.648 Boundary Ratio: 0.253 Contrastive_loss: 0.69083 (0.72043) Boundary_loss: 0.015320 (0.015274) Loss: 0.70615 (0.73571) +2025-08-21,23:30:10 | INFO | Train Epoch: 3 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 0.65603 (0.72028) Boundary_loss: 0.015223 (0.015274) Loss: 0.67125 (0.73556) +2025-08-21,23:31:07 | INFO | Train Epoch: 3 [22016512/26365952 (84%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.64939 (0.72012) Boundary_loss: 0.015259 (0.015274) Loss: 0.66465 (0.73539) +2025-08-21,23:32:04 | INFO | Train Epoch: 3 [22067712/26365952 (84%)] Avg Boundaries (per batch): 47.826 Boundary Ratio: 0.244 Contrastive_loss: 0.75478 (0.72020) Boundary_loss: 0.015148 (0.015274) Loss: 0.76993 (0.73547) +2025-08-21,23:33:01 | INFO | Train Epoch: 3 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.80225 (0.72039) Boundary_loss: 0.015166 (0.015274) Loss: 0.81741 (0.73566) +2025-08-21,23:33:58 | INFO | Train Epoch: 3 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.375 Boundary Ratio: 0.247 Contrastive_loss: 0.70453 (0.72035) Boundary_loss: 0.015338 (0.015274) Loss: 0.71987 (0.73562) +2025-08-21,23:34:55 | INFO | Train Epoch: 3 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.75069 (0.72042) Boundary_loss: 0.015412 (0.015274) Loss: 0.76611 (0.73569) +2025-08-21,23:35:52 | INFO | Train Epoch: 3 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.63647 (0.72023) Boundary_loss: 0.015138 (0.015274) Loss: 0.65161 (0.73550) +2025-08-21,23:36:48 | INFO | Train Epoch: 3 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.64212 (0.72005) Boundary_loss: 0.015137 (0.015273) Loss: 0.65726 (0.73532) +2025-08-21,23:37:45 | INFO | Train Epoch: 3 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.69377 (0.71999) Boundary_loss: 0.015366 (0.015274) Loss: 0.70914 (0.73526) +2025-08-21,23:38:42 | INFO | Train Epoch: 3 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.58136 (0.71967) Boundary_loss: 0.015323 (0.015274) Loss: 0.59668 (0.73495) +2025-08-21,23:39:39 | INFO | Train Epoch: 3 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.71417 (0.71966) Boundary_loss: 0.015373 (0.015274) Loss: 0.72954 (0.73493) +2025-08-21,23:40:36 | INFO | Train Epoch: 3 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 0.69256 (0.71960) Boundary_loss: 0.015227 (0.015274) Loss: 0.70779 (0.73487) +2025-08-21,23:41:33 | INFO | Train Epoch: 3 [22579712/26365952 (86%)] Avg Boundaries (per batch): 49.676 Boundary Ratio: 0.253 Contrastive_loss: 0.58193 (0.71929) Boundary_loss: 0.015164 (0.015274) Loss: 0.59710 (0.73456) +2025-08-21,23:42:30 | INFO | Train Epoch: 3 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.551 Boundary Ratio: 0.253 Contrastive_loss: 0.60767 (0.71904) Boundary_loss: 0.015277 (0.015274) Loss: 0.62295 (0.73431) +2025-08-21,23:43:27 | INFO | Train Epoch: 3 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 0.65897 (0.71890) Boundary_loss: 0.015200 (0.015273) Loss: 0.67417 (0.73417) +2025-08-21,23:44:24 | INFO | Train Epoch: 3 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.420 Boundary Ratio: 0.252 Contrastive_loss: 0.60773 (0.71865) Boundary_loss: 0.015313 (0.015273) Loss: 0.62305 (0.73392) +2025-08-21,23:45:21 | INFO | Train Epoch: 3 [22784512/26365952 (86%)] Avg Boundaries (per batch): 47.742 Boundary Ratio: 0.244 Contrastive_loss: 0.67855 (0.71856) Boundary_loss: 0.015257 (0.015273) Loss: 0.69380 (0.73383) +2025-08-21,23:46:18 | INFO | Train Epoch: 3 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.70891 (0.71854) Boundary_loss: 0.015265 (0.015273) Loss: 0.72417 (0.73381) +2025-08-21,23:47:15 | INFO | Train Epoch: 3 [22886912/26365952 (87%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.65122 (0.71839) Boundary_loss: 0.015250 (0.015273) Loss: 0.66647 (0.73366) +2025-08-21,23:48:12 | INFO | Train Epoch: 3 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.67446 (0.71829) Boundary_loss: 0.015336 (0.015274) Loss: 0.68979 (0.73356) +2025-08-21,23:49:09 | INFO | Train Epoch: 3 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.68641 (0.71822) Boundary_loss: 0.015114 (0.015273) Loss: 0.70153 (0.73349) +2025-08-21,23:50:06 | INFO | Train Epoch: 3 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.65437 (0.71808) Boundary_loss: 0.015292 (0.015273) Loss: 0.66967 (0.73335) +2025-08-21,23:51:03 | INFO | Train Epoch: 3 [23091712/26365952 (88%)] Avg Boundaries (per batch): 47.619 Boundary Ratio: 0.243 Contrastive_loss: 0.65265 (0.71793) Boundary_loss: 0.015463 (0.015274) Loss: 0.66812 (0.73321) +2025-08-21,23:52:00 | INFO | Train Epoch: 3 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 0.60281 (0.71768) Boundary_loss: 0.015113 (0.015273) Loss: 0.61793 (0.73295) +2025-08-21,23:52:57 | INFO | Train Epoch: 3 [23194112/26365952 (88%)] Avg Boundaries (per batch): 49.557 Boundary Ratio: 0.253 Contrastive_loss: 0.68418 (0.71761) Boundary_loss: 0.015393 (0.015274) Loss: 0.69958 (0.73288) +2025-08-21,23:53:54 | INFO | Train Epoch: 3 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.330 Boundary Ratio: 0.247 Contrastive_loss: 0.74483 (0.71767) Boundary_loss: 0.015161 (0.015273) Loss: 0.75999 (0.73294) +2025-08-21,23:54:51 | INFO | Train Epoch: 3 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.62233 (0.71746) Boundary_loss: 0.015298 (0.015273) Loss: 0.63763 (0.73273) +2025-08-21,23:55:48 | INFO | Train Epoch: 3 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.119 Boundary Ratio: 0.246 Contrastive_loss: 0.66440 (0.71734) Boundary_loss: 0.015343 (0.015273) Loss: 0.67974 (0.73261) +2025-08-21,23:56:44 | INFO | Train Epoch: 3 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.76505 (0.71744) Boundary_loss: 0.015210 (0.015273) Loss: 0.78026 (0.73272) +2025-08-21,23:57:41 | INFO | Train Epoch: 3 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.62696 (0.71725) Boundary_loss: 0.015254 (0.015273) Loss: 0.64221 (0.73252) +2025-08-21,23:58:38 | INFO | Train Epoch: 3 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.63217 (0.71706) Boundary_loss: 0.015223 (0.015273) Loss: 0.64739 (0.73234) +2025-08-21,23:59:35 | INFO | Train Epoch: 3 [23552512/26365952 (89%)] Avg Boundaries (per batch): 49.828 Boundary Ratio: 0.254 Contrastive_loss: 0.65506 (0.71693) Boundary_loss: 0.015201 (0.015273) Loss: 0.67026 (0.73220) +2025-08-22,00:00:32 | INFO | Train Epoch: 3 [23603712/26365952 (90%)] Avg Boundaries (per batch): 49.824 Boundary Ratio: 0.254 Contrastive_loss: 0.62218 (0.71672) Boundary_loss: 0.015274 (0.015273) Loss: 0.63745 (0.73200) +2025-08-22,00:01:29 | INFO | Train Epoch: 3 [23654912/26365952 (90%)] Avg Boundaries (per batch): 47.898 Boundary Ratio: 0.244 Contrastive_loss: 0.81443 (0.71693) Boundary_loss: 0.015083 (0.015273) Loss: 0.82952 (0.73221) +2025-08-22,00:02:26 | INFO | Train Epoch: 3 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.64528 (0.71678) Boundary_loss: 0.015251 (0.015273) Loss: 0.66053 (0.73205) +2025-08-22,00:03:23 | INFO | Train Epoch: 3 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.60471 (0.71654) Boundary_loss: 0.015136 (0.015272) Loss: 0.61985 (0.73181) +2025-08-22,00:04:20 | INFO | Train Epoch: 3 [23808512/26365952 (90%)] Avg Boundaries (per batch): 49.385 Boundary Ratio: 0.252 Contrastive_loss: 0.65082 (0.71640) Boundary_loss: 0.015242 (0.015272) Loss: 0.66607 (0.73167) +2025-08-22,00:05:17 | INFO | Train Epoch: 3 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.67646 (0.71631) Boundary_loss: 0.015212 (0.015272) Loss: 0.69167 (0.73158) +2025-08-22,00:06:14 | INFO | Train Epoch: 3 [23910912/26365952 (91%)] Avg Boundaries (per batch): 49.109 Boundary Ratio: 0.251 Contrastive_loss: 0.70335 (0.71628) Boundary_loss: 0.015378 (0.015272) Loss: 0.71873 (0.73156) +2025-08-22,00:07:11 | INFO | Train Epoch: 3 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.60575 (0.71605) Boundary_loss: 0.015198 (0.015272) Loss: 0.62095 (0.73132) +2025-08-22,00:08:08 | INFO | Train Epoch: 3 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.62451 (0.71585) Boundary_loss: 0.015286 (0.015272) Loss: 0.63979 (0.73113) +2025-08-22,00:09:05 | INFO | Train Epoch: 3 [24064512/26365952 (91%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.68115 (0.71578) Boundary_loss: 0.015291 (0.015272) Loss: 0.69644 (0.73105) +2025-08-22,00:10:02 | INFO | Train Epoch: 3 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 0.63433 (0.71561) Boundary_loss: 0.015234 (0.015272) Loss: 0.64957 (0.73088) +2025-08-22,00:10:59 | INFO | Train Epoch: 3 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.58123 (0.71532) Boundary_loss: 0.015256 (0.015272) Loss: 0.59648 (0.73060) +2025-08-22,00:11:56 | INFO | Train Epoch: 3 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.69094 (0.71527) Boundary_loss: 0.015245 (0.015272) Loss: 0.70619 (0.73054) +2025-08-22,00:12:52 | INFO | Train Epoch: 3 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.64433 (0.71512) Boundary_loss: 0.015277 (0.015272) Loss: 0.65960 (0.73039) +2025-08-22,00:13:49 | INFO | Train Epoch: 3 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.80882 (0.71532) Boundary_loss: 0.015201 (0.015272) Loss: 0.82402 (0.73059) +2025-08-22,00:14:46 | INFO | Train Epoch: 3 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.77841 (0.71545) Boundary_loss: 0.015207 (0.015272) Loss: 0.79362 (0.73072) +2025-08-22,00:15:43 | INFO | Train Epoch: 3 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 0.62513 (0.71526) Boundary_loss: 0.015435 (0.015272) Loss: 0.64057 (0.73054) +2025-08-22,00:16:40 | INFO | Train Epoch: 3 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.76805 (0.71537) Boundary_loss: 0.015227 (0.015272) Loss: 0.78328 (0.73065) +2025-08-22,00:17:37 | INFO | Train Epoch: 3 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.67096 (0.71528) Boundary_loss: 0.015257 (0.015272) Loss: 0.68622 (0.73055) +2025-08-22,00:18:34 | INFO | Train Epoch: 3 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.66612 (0.71518) Boundary_loss: 0.015135 (0.015272) Loss: 0.68126 (0.73045) +2025-08-22,00:19:31 | INFO | Train Epoch: 3 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.148 Boundary Ratio: 0.246 Contrastive_loss: 0.74334 (0.71524) Boundary_loss: 0.015323 (0.015272) Loss: 0.75866 (0.73051) +2025-08-22,00:20:28 | INFO | Train Epoch: 3 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.63095 (0.71506) Boundary_loss: 0.015356 (0.015272) Loss: 0.64630 (0.73033) +2025-08-22,00:21:25 | INFO | Train Epoch: 3 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.69835 (0.71503) Boundary_loss: 0.015367 (0.015272) Loss: 0.71372 (0.73030) +2025-08-22,00:22:22 | INFO | Train Epoch: 3 [24781312/26365952 (94%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.70837 (0.71501) Boundary_loss: 0.015465 (0.015273) Loss: 0.72384 (0.73029) +2025-08-22,00:23:18 | INFO | Train Epoch: 3 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 0.74592 (0.71508) Boundary_loss: 0.015266 (0.015273) Loss: 0.76119 (0.73035) +2025-08-22,00:24:15 | INFO | Train Epoch: 3 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 0.63910 (0.71492) Boundary_loss: 0.015212 (0.015272) Loss: 0.65431 (0.73019) +2025-08-22,00:25:12 | INFO | Train Epoch: 3 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.62038 (0.71473) Boundary_loss: 0.015252 (0.015272) Loss: 0.63563 (0.73000) +2025-08-22,00:26:09 | INFO | Train Epoch: 3 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.65114 (0.71460) Boundary_loss: 0.015146 (0.015272) Loss: 0.66629 (0.72987) +2025-08-22,00:27:06 | INFO | Train Epoch: 3 [25037312/26365952 (95%)] Avg Boundaries (per batch): 47.545 Boundary Ratio: 0.243 Contrastive_loss: 0.69605 (0.71456) Boundary_loss: 0.015313 (0.015272) Loss: 0.71136 (0.72983) +2025-08-22,00:28:03 | INFO | Train Epoch: 3 [25088512/26365952 (95%)] Avg Boundaries (per batch): 49.424 Boundary Ratio: 0.252 Contrastive_loss: 0.67704 (0.71448) Boundary_loss: 0.015155 (0.015272) Loss: 0.69219 (0.72976) +2025-08-22,00:29:00 | INFO | Train Epoch: 3 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.73032 (0.71452) Boundary_loss: 0.015245 (0.015272) Loss: 0.74556 (0.72979) +2025-08-22,00:29:57 | INFO | Train Epoch: 3 [25190912/26365952 (96%)] Avg Boundaries (per batch): 49.383 Boundary Ratio: 0.252 Contrastive_loss: 0.70684 (0.71450) Boundary_loss: 0.015225 (0.015272) Loss: 0.72207 (0.72977) +2025-08-22,00:30:54 | INFO | Train Epoch: 3 [25242112/26365952 (96%)] Avg Boundaries (per batch): 47.967 Boundary Ratio: 0.245 Contrastive_loss: 0.68161 (0.71443) Boundary_loss: 0.015127 (0.015272) Loss: 0.69673 (0.72971) +2025-08-22,00:31:51 | INFO | Train Epoch: 3 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.385 Boundary Ratio: 0.247 Contrastive_loss: 0.64407 (0.71429) Boundary_loss: 0.015283 (0.015272) Loss: 0.65935 (0.72956) +2025-08-22,00:32:48 | INFO | Train Epoch: 3 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.277 Boundary Ratio: 0.251 Contrastive_loss: 0.61578 (0.71409) Boundary_loss: 0.015154 (0.015271) Loss: 0.63094 (0.72936) +2025-08-22,00:33:45 | INFO | Train Epoch: 3 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.438 Boundary Ratio: 0.252 Contrastive_loss: 0.62928 (0.71392) Boundary_loss: 0.015104 (0.015271) Loss: 0.64438 (0.72919) +2025-08-22,00:34:42 | INFO | Train Epoch: 3 [25446912/26365952 (97%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.67494 (0.71384) Boundary_loss: 0.015172 (0.015271) Loss: 0.69011 (0.72911) +2025-08-22,00:35:39 | INFO | Train Epoch: 3 [25498112/26365952 (97%)] Avg Boundaries (per batch): 50.000 Boundary Ratio: 0.255 Contrastive_loss: 0.58322 (0.71358) Boundary_loss: 0.015132 (0.015271) Loss: 0.59835 (0.72885) +2025-08-22,00:36:36 | INFO | Train Epoch: 3 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.62424 (0.71340) Boundary_loss: 0.015343 (0.015271) Loss: 0.63958 (0.72867) +2025-08-22,00:37:33 | INFO | Train Epoch: 3 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.021 Boundary Ratio: 0.245 Contrastive_loss: 0.64734 (0.71327) Boundary_loss: 0.015278 (0.015271) Loss: 0.66262 (0.72854) +2025-08-22,00:38:30 | INFO | Train Epoch: 3 [25651712/26365952 (97%)] Avg Boundaries (per batch): 49.562 Boundary Ratio: 0.253 Contrastive_loss: 0.67674 (0.71320) Boundary_loss: 0.015270 (0.015271) Loss: 0.69201 (0.72847) +2025-08-22,00:39:27 | INFO | Train Epoch: 3 [25702912/26365952 (97%)] Avg Boundaries (per batch): 49.881 Boundary Ratio: 0.254 Contrastive_loss: 0.76991 (0.71331) Boundary_loss: 0.015407 (0.015271) Loss: 0.78531 (0.72858) +2025-08-22,00:40:24 | INFO | Train Epoch: 3 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.63596 (0.71316) Boundary_loss: 0.015478 (0.015271) Loss: 0.65144 (0.72843) +2025-08-22,00:41:21 | INFO | Train Epoch: 3 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.62803 (0.71299) Boundary_loss: 0.015377 (0.015272) Loss: 0.64340 (0.72826) +2025-08-22,00:42:18 | INFO | Train Epoch: 3 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.71390 (0.71299) Boundary_loss: 0.015244 (0.015272) Loss: 0.72914 (0.72826) +2025-08-22,00:43:14 | INFO | Train Epoch: 3 [25907712/26365952 (98%)] Avg Boundaries (per batch): 49.467 Boundary Ratio: 0.252 Contrastive_loss: 0.60636 (0.71278) Boundary_loss: 0.015337 (0.015272) Loss: 0.62170 (0.72805) +2025-08-22,00:44:11 | INFO | Train Epoch: 3 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.62525 (0.71261) Boundary_loss: 0.015264 (0.015272) Loss: 0.64052 (0.72788) +2025-08-22,00:45:08 | INFO | Train Epoch: 3 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.57420 (0.71234) Boundary_loss: 0.015226 (0.015272) Loss: 0.58943 (0.72761) +2025-08-22,00:46:05 | INFO | Train Epoch: 3 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.68940 (0.71229) Boundary_loss: 0.015305 (0.015272) Loss: 0.70471 (0.72756) +2025-08-22,00:47:02 | INFO | Train Epoch: 3 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.69083 (0.71225) Boundary_loss: 0.015134 (0.015271) Loss: 0.70597 (0.72752) +2025-08-22,00:47:59 | INFO | Train Epoch: 3 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.65092 (0.71213) Boundary_loss: 0.015292 (0.015271) Loss: 0.66622 (0.72740) +2025-08-22,00:48:56 | INFO | Train Epoch: 3 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.135 Boundary Ratio: 0.246 Contrastive_loss: 0.65400 (0.71202) Boundary_loss: 0.015175 (0.015271) Loss: 0.66918 (0.72729) +2025-08-22,00:49:53 | INFO | Train Epoch: 3 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.72710 (0.71205) Boundary_loss: 0.015329 (0.015271) Loss: 0.74243 (0.72732) +2025-08-22,00:50:50 | INFO | Train Epoch: 3 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.438 Boundary Ratio: 0.247 Contrastive_loss: 0.67912 (0.71198) Boundary_loss: 0.015345 (0.015271) Loss: 0.69447 (0.72725) +2025-08-22,00:51:44 | INFO | Train Epoch: 3 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 0.57421 (0.71172) Boundary_loss: 0.015245 (0.015271) Loss: 0.58946 (0.72699) +2025-08-22,00:51:44 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-22,00:51:44 | INFO | [Epoch 3] Average Step Time: 0.574s | Average GPU Memory: 32.0 GB +2025-08-22,00:51:44 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-22,00:51:44 | INFO | Starting zero-shot imagenet. +2025-08-22,00:51:44 | INFO | Building zero-shot classifier +2025-08-22,00:51:53 | INFO | Using classifier +2025-08-22,00:52:38 | INFO | Finished zero-shot imagenet. +2025-08-22,00:52:38 | INFO | Eval Epoch: 4 imagenet-zeroshot-val-top1: 0.2255 imagenet-zeroshot-val-top5: 0.4531 +2025-08-22,00:52:39 | INFO | Start epoch 4 +2025-08-22,00:52:41 | INFO | Train Epoch: 4 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.025 Boundary Ratio: 0.245 Contrastive_loss: 0.44305 (0.44305) Boundary_loss: 0.015120 (0.015120) Loss: 0.45817 (0.45817) +2025-08-22,00:53:38 | INFO | Train Epoch: 4 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.59934 (0.52120) Boundary_loss: 0.015257 (0.015189) Loss: 0.61460 (0.53639) +2025-08-22,00:54:35 | INFO | Train Epoch: 4 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.55527 (0.53255) Boundary_loss: 0.015091 (0.015156) Loss: 0.57036 (0.54771) +2025-08-22,00:55:32 | INFO | Train Epoch: 4 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.691 Boundary Ratio: 0.254 Contrastive_loss: 0.65798 (0.56391) Boundary_loss: 0.015376 (0.015211) Loss: 0.67335 (0.57912) +2025-08-22,00:56:28 | INFO | Train Epoch: 4 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.55692 (0.56251) Boundary_loss: 0.015173 (0.015203) Loss: 0.57209 (0.57771) +2025-08-22,00:57:25 | INFO | Train Epoch: 4 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 49.318 Boundary Ratio: 0.252 Contrastive_loss: 0.60756 (0.57002) Boundary_loss: 0.015144 (0.015193) Loss: 0.62270 (0.58521) +2025-08-22,00:58:22 | INFO | Train Epoch: 4 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 50.035 Boundary Ratio: 0.255 Contrastive_loss: 0.54360 (0.56624) Boundary_loss: 0.015296 (0.015208) Loss: 0.55890 (0.58145) +2025-08-22,00:59:19 | INFO | Train Epoch: 4 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.236 Boundary Ratio: 0.246 Contrastive_loss: 0.64033 (0.57550) Boundary_loss: 0.015415 (0.015234) Loss: 0.65574 (0.59074) +2025-08-22,01:00:16 | INFO | Train Epoch: 4 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 0.54050 (0.57161) Boundary_loss: 0.015401 (0.015252) Loss: 0.55590 (0.58687) +2025-08-22,01:01:13 | INFO | Train Epoch: 4 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.72493 (0.58695) Boundary_loss: 0.015200 (0.015247) Loss: 0.74013 (0.60219) +2025-08-22,01:02:09 | INFO | Train Epoch: 4 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 0.70659 (0.59782) Boundary_loss: 0.015173 (0.015241) Loss: 0.72176 (0.61306) +2025-08-22,01:03:06 | INFO | Train Epoch: 4 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 50.100 Boundary Ratio: 0.256 Contrastive_loss: 0.52194 (0.59150) Boundary_loss: 0.015379 (0.015252) Loss: 0.53731 (0.60675) +2025-08-22,01:04:03 | INFO | Train Epoch: 4 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 0.66345 (0.59703) Boundary_loss: 0.015310 (0.015257) Loss: 0.67876 (0.61229) +2025-08-22,01:05:00 | INFO | Train Epoch: 4 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.332 Boundary Ratio: 0.247 Contrastive_loss: 0.59363 (0.59679) Boundary_loss: 0.015230 (0.015255) Loss: 0.60886 (0.61205) +2025-08-22,01:05:56 | INFO | Train Epoch: 4 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.68250 (0.60250) Boundary_loss: 0.015288 (0.015257) Loss: 0.69779 (0.61776) +2025-08-22,01:06:53 | INFO | Train Epoch: 4 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.56872 (0.60039) Boundary_loss: 0.015328 (0.015261) Loss: 0.58405 (0.61565) +2025-08-22,01:07:50 | INFO | Train Epoch: 4 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.60242 (0.60051) Boundary_loss: 0.015189 (0.015257) Loss: 0.61761 (0.61577) +2025-08-22,01:08:47 | INFO | Train Epoch: 4 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 47.941 Boundary Ratio: 0.245 Contrastive_loss: 0.55860 (0.59818) Boundary_loss: 0.015373 (0.015263) Loss: 0.57398 (0.61345) +2025-08-22,01:09:44 | INFO | Train Epoch: 4 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.71912 (0.60455) Boundary_loss: 0.015386 (0.015270) Loss: 0.73450 (0.61982) +2025-08-22,01:10:40 | INFO | Train Epoch: 4 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.65100 (0.60687) Boundary_loss: 0.015221 (0.015267) Loss: 0.66622 (0.62214) +2025-08-22,01:11:37 | INFO | Train Epoch: 4 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.66313 (0.60955) Boundary_loss: 0.015256 (0.015267) Loss: 0.67838 (0.62482) +2025-08-22,01:12:34 | INFO | Train Epoch: 4 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 0.62913 (0.61044) Boundary_loss: 0.015069 (0.015258) Loss: 0.64420 (0.62570) +2025-08-22,01:13:31 | INFO | Train Epoch: 4 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 49.803 Boundary Ratio: 0.254 Contrastive_loss: 0.65336 (0.61231) Boundary_loss: 0.015282 (0.015259) Loss: 0.66865 (0.62757) +2025-08-22,01:14:28 | INFO | Train Epoch: 4 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.61321 (0.61234) Boundary_loss: 0.015344 (0.015262) Loss: 0.62856 (0.62761) +2025-08-22,01:15:24 | INFO | Train Epoch: 4 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.65060 (0.61388) Boundary_loss: 0.015339 (0.015266) Loss: 0.66594 (0.62914) +2025-08-22,01:16:21 | INFO | Train Epoch: 4 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.49032 (0.60912) Boundary_loss: 0.015111 (0.015260) Loss: 0.50543 (0.62438) +2025-08-22,01:17:18 | INFO | Train Epoch: 4 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.63135 (0.60995) Boundary_loss: 0.015223 (0.015258) Loss: 0.64657 (0.62520) +2025-08-22,01:18:15 | INFO | Train Epoch: 4 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 49.656 Boundary Ratio: 0.253 Contrastive_loss: 0.80688 (0.61698) Boundary_loss: 0.015351 (0.015262) Loss: 0.82223 (0.63224) +2025-08-22,01:19:12 | INFO | Train Epoch: 4 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.61796 (0.61701) Boundary_loss: 0.015216 (0.015260) Loss: 0.63318 (0.63227) +2025-08-22,01:20:09 | INFO | Train Epoch: 4 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.56984 (0.61544) Boundary_loss: 0.015092 (0.015254) Loss: 0.58493 (0.63070) +2025-08-22,01:21:06 | INFO | Train Epoch: 4 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.365 Boundary Ratio: 0.252 Contrastive_loss: 0.58167 (0.61435) Boundary_loss: 0.015172 (0.015252) Loss: 0.59684 (0.62960) +2025-08-22,01:22:03 | INFO | Train Epoch: 4 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 0.58024 (0.61329) Boundary_loss: 0.015318 (0.015254) Loss: 0.59556 (0.62854) +2025-08-22,01:22:59 | INFO | Train Epoch: 4 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 49.268 Boundary Ratio: 0.251 Contrastive_loss: 0.62821 (0.61374) Boundary_loss: 0.015137 (0.015250) Loss: 0.64334 (0.62899) +2025-08-22,01:23:56 | INFO | Train Epoch: 4 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 50.148 Boundary Ratio: 0.256 Contrastive_loss: 0.54604 (0.61175) Boundary_loss: 0.015418 (0.015255) Loss: 0.56146 (0.62700) +2025-08-22,01:24:53 | INFO | Train Epoch: 4 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 47.855 Boundary Ratio: 0.244 Contrastive_loss: 0.57326 (0.61065) Boundary_loss: 0.015203 (0.015254) Loss: 0.58847 (0.62590) +2025-08-22,01:25:50 | INFO | Train Epoch: 4 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.209 Boundary Ratio: 0.246 Contrastive_loss: 0.68257 (0.61265) Boundary_loss: 0.015258 (0.015254) Loss: 0.69782 (0.62790) +2025-08-22,01:26:47 | INFO | Train Epoch: 4 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.57028 (0.61150) Boundary_loss: 0.015145 (0.015251) Loss: 0.58543 (0.62675) +2025-08-22,01:27:44 | INFO | Train Epoch: 4 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 50.020 Boundary Ratio: 0.255 Contrastive_loss: 0.59786 (0.61114) Boundary_loss: 0.015341 (0.015253) Loss: 0.61320 (0.62639) +2025-08-22,01:28:41 | INFO | Train Epoch: 4 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 47.906 Boundary Ratio: 0.244 Contrastive_loss: 0.55281 (0.60965) Boundary_loss: 0.015187 (0.015252) Loss: 0.56799 (0.62490) +2025-08-22,01:29:37 | INFO | Train Epoch: 4 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.53831 (0.60786) Boundary_loss: 0.015330 (0.015254) Loss: 0.55364 (0.62312) +2025-08-22,01:30:34 | INFO | Train Epoch: 4 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 0.69589 (0.61001) Boundary_loss: 0.015154 (0.015251) Loss: 0.71104 (0.62526) +2025-08-22,01:31:31 | INFO | Train Epoch: 4 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.75825 (0.61354) Boundary_loss: 0.015180 (0.015249) Loss: 0.77343 (0.62879) +2025-08-22,01:32:28 | INFO | Train Epoch: 4 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 47.924 Boundary Ratio: 0.245 Contrastive_loss: 0.59625 (0.61314) Boundary_loss: 0.015138 (0.015247) Loss: 0.61138 (0.62838) +2025-08-22,01:33:25 | INFO | Train Epoch: 4 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.182 Boundary Ratio: 0.246 Contrastive_loss: 0.59434 (0.61271) Boundary_loss: 0.015332 (0.015249) Loss: 0.60967 (0.62796) +2025-08-22,01:34:22 | INFO | Train Epoch: 4 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.121 Boundary Ratio: 0.246 Contrastive_loss: 0.55137 (0.61135) Boundary_loss: 0.015238 (0.015249) Loss: 0.56661 (0.62659) +2025-08-22,01:35:19 | INFO | Train Epoch: 4 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.180 Boundary Ratio: 0.246 Contrastive_loss: 0.59296 (0.61095) Boundary_loss: 0.015152 (0.015246) Loss: 0.60812 (0.62619) +2025-08-22,01:36:16 | INFO | Train Epoch: 4 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.58027 (0.61029) Boundary_loss: 0.015268 (0.015247) Loss: 0.59554 (0.62554) +2025-08-22,01:37:13 | INFO | Train Epoch: 4 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.66395 (0.61141) Boundary_loss: 0.015228 (0.015246) Loss: 0.67918 (0.62666) +2025-08-22,01:38:10 | INFO | Train Epoch: 4 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.61988 (0.61158) Boundary_loss: 0.015152 (0.015245) Loss: 0.63503 (0.62683) +2025-08-22,01:39:06 | INFO | Train Epoch: 4 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.62142 (0.61178) Boundary_loss: 0.015297 (0.015246) Loss: 0.63672 (0.62703) +2025-08-22,01:40:03 | INFO | Train Epoch: 4 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.71677 (0.61384) Boundary_loss: 0.015412 (0.015249) Loss: 0.73218 (0.62909) +2025-08-22,01:41:00 | INFO | Train Epoch: 4 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.66583 (0.61484) Boundary_loss: 0.015190 (0.015248) Loss: 0.68102 (0.63009) +2025-08-22,01:41:57 | INFO | Train Epoch: 4 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 0.62112 (0.61496) Boundary_loss: 0.015298 (0.015249) Loss: 0.63642 (0.63021) +2025-08-22,01:42:53 | INFO | Train Epoch: 4 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.67184 (0.61601) Boundary_loss: 0.015221 (0.015248) Loss: 0.68706 (0.63126) +2025-08-22,01:43:50 | INFO | Train Epoch: 4 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 0.59579 (0.61564) Boundary_loss: 0.015166 (0.015247) Loss: 0.61096 (0.63089) +2025-08-22,01:44:47 | INFO | Train Epoch: 4 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.59901 (0.61535) Boundary_loss: 0.015138 (0.015245) Loss: 0.61415 (0.63059) +2025-08-22,01:45:44 | INFO | Train Epoch: 4 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.60647 (0.61519) Boundary_loss: 0.015259 (0.015245) Loss: 0.62172 (0.63044) +2025-08-22,01:46:41 | INFO | Train Epoch: 4 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 49.693 Boundary Ratio: 0.254 Contrastive_loss: 0.63857 (0.61559) Boundary_loss: 0.015332 (0.015246) Loss: 0.65390 (0.63084) +2025-08-22,01:47:38 | INFO | Train Epoch: 4 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.254 Boundary Ratio: 0.246 Contrastive_loss: 0.69132 (0.61688) Boundary_loss: 0.015097 (0.015244) Loss: 0.70642 (0.63212) +2025-08-22,01:48:35 | INFO | Train Epoch: 4 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.547 Boundary Ratio: 0.253 Contrastive_loss: 0.54512 (0.61568) Boundary_loss: 0.015247 (0.015244) Loss: 0.56037 (0.63093) +2025-08-22,01:49:32 | INFO | Train Epoch: 4 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.328 Boundary Ratio: 0.247 Contrastive_loss: 0.59114 (0.61528) Boundary_loss: 0.015191 (0.015243) Loss: 0.60633 (0.63052) +2025-08-22,01:50:29 | INFO | Train Epoch: 4 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.64423 (0.61575) Boundary_loss: 0.015272 (0.015244) Loss: 0.65950 (0.63099) +2025-08-22,01:51:25 | INFO | Train Epoch: 4 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.312 Boundary Ratio: 0.246 Contrastive_loss: 0.49777 (0.61387) Boundary_loss: 0.015123 (0.015242) Loss: 0.51289 (0.62912) +2025-08-22,01:52:22 | INFO | Train Epoch: 4 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.47038 (0.61163) Boundary_loss: 0.015279 (0.015242) Loss: 0.48566 (0.62687) +2025-08-22,01:53:19 | INFO | Train Epoch: 4 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.123 Boundary Ratio: 0.246 Contrastive_loss: 0.67561 (0.61262) Boundary_loss: 0.015147 (0.015241) Loss: 0.69076 (0.62786) +2025-08-22,01:54:16 | INFO | Train Epoch: 4 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 50.346 Boundary Ratio: 0.257 Contrastive_loss: 0.56722 (0.61193) Boundary_loss: 0.015512 (0.015245) Loss: 0.58273 (0.62717) +2025-08-22,01:55:13 | INFO | Train Epoch: 4 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 0.55436 (0.61107) Boundary_loss: 0.015094 (0.015243) Loss: 0.56946 (0.62631) +2025-08-22,01:56:10 | INFO | Train Epoch: 4 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.71726 (0.61263) Boundary_loss: 0.015105 (0.015241) Loss: 0.73237 (0.62787) +2025-08-22,01:57:06 | INFO | Train Epoch: 4 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 49.576 Boundary Ratio: 0.253 Contrastive_loss: 0.64787 (0.61314) Boundary_loss: 0.015262 (0.015241) Loss: 0.66313 (0.62838) +2025-08-22,01:58:03 | INFO | Train Epoch: 4 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.64218 (0.61356) Boundary_loss: 0.015122 (0.015239) Loss: 0.65730 (0.62880) +2025-08-22,01:59:00 | INFO | Train Epoch: 4 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 0.66721 (0.61431) Boundary_loss: 0.015179 (0.015238) Loss: 0.68239 (0.62955) +2025-08-22,01:59:57 | INFO | Train Epoch: 4 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 0.55243 (0.61345) Boundary_loss: 0.015312 (0.015239) Loss: 0.56775 (0.62869) +2025-08-22,02:00:54 | INFO | Train Epoch: 4 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 47.994 Boundary Ratio: 0.245 Contrastive_loss: 0.63323 (0.61372) Boundary_loss: 0.015286 (0.015240) Loss: 0.64852 (0.62896) +2025-08-22,02:01:51 | INFO | Train Epoch: 4 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 49.219 Boundary Ratio: 0.251 Contrastive_loss: 0.56290 (0.61304) Boundary_loss: 0.015276 (0.015241) Loss: 0.57818 (0.62828) +2025-08-22,02:02:48 | INFO | Train Epoch: 4 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.60725 (0.61296) Boundary_loss: 0.015446 (0.015243) Loss: 0.62269 (0.62820) +2025-08-22,02:03:45 | INFO | Train Epoch: 4 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.367 Boundary Ratio: 0.252 Contrastive_loss: 0.70680 (0.61419) Boundary_loss: 0.015252 (0.015243) Loss: 0.72206 (0.62944) +2025-08-22,02:04:42 | INFO | Train Epoch: 4 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.57764 (0.61372) Boundary_loss: 0.015090 (0.015241) Loss: 0.59273 (0.62896) +2025-08-22,02:05:38 | INFO | Train Epoch: 4 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 49.680 Boundary Ratio: 0.253 Contrastive_loss: 0.60244 (0.61357) Boundary_loss: 0.015407 (0.015244) Loss: 0.61784 (0.62882) +2025-08-22,02:06:36 | INFO | Train Epoch: 4 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.434 Boundary Ratio: 0.247 Contrastive_loss: 0.54923 (0.61276) Boundary_loss: 0.015273 (0.015244) Loss: 0.56451 (0.62800) +2025-08-22,02:07:32 | INFO | Train Epoch: 4 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.188 Boundary Ratio: 0.246 Contrastive_loss: 0.70832 (0.61395) Boundary_loss: 0.015141 (0.015243) Loss: 0.72346 (0.62920) +2025-08-22,02:08:29 | INFO | Train Epoch: 4 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.66686 (0.61461) Boundary_loss: 0.015238 (0.015243) Loss: 0.68210 (0.62985) +2025-08-22,02:09:26 | INFO | Train Epoch: 4 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.67545 (0.61535) Boundary_loss: 0.015206 (0.015242) Loss: 0.69066 (0.63059) +2025-08-22,02:10:23 | INFO | Train Epoch: 4 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.51760 (0.61417) Boundary_loss: 0.015322 (0.015243) Loss: 0.53292 (0.62942) +2025-08-22,02:11:20 | INFO | Train Epoch: 4 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 0.65840 (0.61470) Boundary_loss: 0.015144 (0.015242) Loss: 0.67354 (0.62994) +2025-08-22,02:12:17 | INFO | Train Epoch: 4 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.58167 (0.61431) Boundary_loss: 0.015324 (0.015243) Loss: 0.59699 (0.62955) +2025-08-22,02:13:13 | INFO | Train Epoch: 4 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.53911 (0.61344) Boundary_loss: 0.015195 (0.015242) Loss: 0.55430 (0.62868) +2025-08-22,02:14:10 | INFO | Train Epoch: 4 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.336 Boundary Ratio: 0.252 Contrastive_loss: 0.52310 (0.61240) Boundary_loss: 0.015258 (0.015243) Loss: 0.53836 (0.62764) +2025-08-22,02:15:07 | INFO | Train Epoch: 4 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.135 Boundary Ratio: 0.246 Contrastive_loss: 0.64021 (0.61271) Boundary_loss: 0.015268 (0.015243) Loss: 0.65548 (0.62796) +2025-08-22,02:16:04 | INFO | Train Epoch: 4 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.47450 (0.61116) Boundary_loss: 0.015386 (0.015244) Loss: 0.48989 (0.62640) +2025-08-22,02:17:01 | INFO | Train Epoch: 4 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 49.811 Boundary Ratio: 0.254 Contrastive_loss: 0.56710 (0.61067) Boundary_loss: 0.015384 (0.015246) Loss: 0.58249 (0.62592) +2025-08-22,02:17:58 | INFO | Train Epoch: 4 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.58934 (0.61044) Boundary_loss: 0.015220 (0.015246) Loss: 0.60457 (0.62568) +2025-08-22,02:18:55 | INFO | Train Epoch: 4 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.60028 (0.61033) Boundary_loss: 0.015118 (0.015244) Loss: 0.61540 (0.62557) +2025-08-22,02:19:52 | INFO | Train Epoch: 4 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.56234 (0.60981) Boundary_loss: 0.015131 (0.015243) Loss: 0.57747 (0.62505) +2025-08-22,02:20:49 | INFO | Train Epoch: 4 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.58073 (0.60950) Boundary_loss: 0.015144 (0.015242) Loss: 0.59588 (0.62474) +2025-08-22,02:21:46 | INFO | Train Epoch: 4 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.59396 (0.60934) Boundary_loss: 0.015223 (0.015242) Loss: 0.60918 (0.62458) +2025-08-22,02:22:43 | INFO | Train Epoch: 4 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.56702 (0.60890) Boundary_loss: 0.015137 (0.015241) Loss: 0.58215 (0.62414) +2025-08-22,02:23:40 | INFO | Train Epoch: 4 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.377 Boundary Ratio: 0.247 Contrastive_loss: 0.57998 (0.60860) Boundary_loss: 0.015340 (0.015242) Loss: 0.59532 (0.62384) +2025-08-22,02:24:37 | INFO | Train Epoch: 4 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.72018 (0.60974) Boundary_loss: 0.015145 (0.015241) Loss: 0.73532 (0.62498) +2025-08-22,02:25:33 | INFO | Train Epoch: 4 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.289 Boundary Ratio: 0.246 Contrastive_loss: 0.61216 (0.60976) Boundary_loss: 0.015270 (0.015241) Loss: 0.62743 (0.62500) +2025-08-22,02:26:30 | INFO | Train Epoch: 4 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.59484 (0.60961) Boundary_loss: 0.015214 (0.015241) Loss: 0.61006 (0.62485) +2025-08-22,02:27:27 | INFO | Train Epoch: 4 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 0.73084 (0.61081) Boundary_loss: 0.015191 (0.015240) Loss: 0.74603 (0.62605) +2025-08-22,02:28:24 | INFO | Train Epoch: 4 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.56483 (0.61036) Boundary_loss: 0.015324 (0.015241) Loss: 0.58015 (0.62560) +2025-08-22,02:29:21 | INFO | Train Epoch: 4 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 0.58140 (0.61008) Boundary_loss: 0.015196 (0.015241) Loss: 0.59659 (0.62532) +2025-08-22,02:30:17 | INFO | Train Epoch: 4 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.377 Boundary Ratio: 0.247 Contrastive_loss: 0.55414 (0.60954) Boundary_loss: 0.015162 (0.015240) Loss: 0.56931 (0.62478) +2025-08-22,02:31:14 | INFO | Train Epoch: 4 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.53948 (0.60888) Boundary_loss: 0.015165 (0.015239) Loss: 0.55465 (0.62411) +2025-08-22,02:32:11 | INFO | Train Epoch: 4 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 0.60722 (0.60886) Boundary_loss: 0.015313 (0.015240) Loss: 0.62254 (0.62410) +2025-08-22,02:33:08 | INFO | Train Epoch: 4 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.53108 (0.60813) Boundary_loss: 0.015132 (0.015239) Loss: 0.54621 (0.62337) +2025-08-22,02:34:05 | INFO | Train Epoch: 4 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.53000 (0.60741) Boundary_loss: 0.015129 (0.015238) Loss: 0.54513 (0.62265) +2025-08-22,02:35:01 | INFO | Train Epoch: 4 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.60230 (0.60736) Boundary_loss: 0.015159 (0.015237) Loss: 0.61746 (0.62260) +2025-08-22,02:35:58 | INFO | Train Epoch: 4 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 47.781 Boundary Ratio: 0.244 Contrastive_loss: 0.52403 (0.60660) Boundary_loss: 0.015135 (0.015236) Loss: 0.53917 (0.62184) +2025-08-22,02:36:55 | INFO | Train Epoch: 4 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.60256 (0.60657) Boundary_loss: 0.015200 (0.015236) Loss: 0.61776 (0.62180) +2025-08-22,02:37:52 | INFO | Train Epoch: 4 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.666 Boundary Ratio: 0.253 Contrastive_loss: 0.65388 (0.60699) Boundary_loss: 0.015214 (0.015236) Loss: 0.66910 (0.62223) +2025-08-22,02:38:48 | INFO | Train Epoch: 4 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.50924 (0.60613) Boundary_loss: 0.015194 (0.015235) Loss: 0.52443 (0.62136) +2025-08-22,02:39:45 | INFO | Train Epoch: 4 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.58233 (0.60592) Boundary_loss: 0.015223 (0.015235) Loss: 0.59756 (0.62115) +2025-08-22,02:40:42 | INFO | Train Epoch: 4 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 49.346 Boundary Ratio: 0.252 Contrastive_loss: 0.54205 (0.60536) Boundary_loss: 0.015237 (0.015235) Loss: 0.55729 (0.62060) +2025-08-22,02:41:39 | INFO | Train Epoch: 4 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.57254 (0.60508) Boundary_loss: 0.015395 (0.015237) Loss: 0.58793 (0.62032) +2025-08-22,02:42:36 | INFO | Train Epoch: 4 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.51832 (0.60434) Boundary_loss: 0.015206 (0.015236) Loss: 0.53353 (0.61957) +2025-08-22,02:43:32 | INFO | Train Epoch: 4 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.67490 (0.60494) Boundary_loss: 0.015093 (0.015235) Loss: 0.68999 (0.62017) +2025-08-22,02:44:29 | INFO | Train Epoch: 4 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.63192 (0.60516) Boundary_loss: 0.015173 (0.015235) Loss: 0.64709 (0.62040) +2025-08-22,02:45:26 | INFO | Train Epoch: 4 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.60216 (0.60514) Boundary_loss: 0.015265 (0.015235) Loss: 0.61742 (0.62037) +2025-08-22,02:46:23 | INFO | Train Epoch: 4 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.67377 (0.60570) Boundary_loss: 0.015288 (0.015235) Loss: 0.68906 (0.62094) +2025-08-22,02:47:20 | INFO | Train Epoch: 4 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.57076 (0.60542) Boundary_loss: 0.015331 (0.015236) Loss: 0.58609 (0.62065) +2025-08-22,02:48:17 | INFO | Train Epoch: 4 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.58034 (0.60521) Boundary_loss: 0.015212 (0.015236) Loss: 0.59555 (0.62045) +2025-08-22,02:49:14 | INFO | Train Epoch: 4 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.63767 (0.60548) Boundary_loss: 0.015182 (0.015235) Loss: 0.65285 (0.62071) +2025-08-22,02:50:10 | INFO | Train Epoch: 4 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.061 Boundary Ratio: 0.245 Contrastive_loss: 0.59123 (0.60536) Boundary_loss: 0.015172 (0.015235) Loss: 0.60640 (0.62060) +2025-08-22,02:51:07 | INFO | Train Epoch: 4 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.57451 (0.60512) Boundary_loss: 0.015166 (0.015234) Loss: 0.58968 (0.62035) +2025-08-22,02:52:04 | INFO | Train Epoch: 4 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 47.812 Boundary Ratio: 0.244 Contrastive_loss: 0.51330 (0.60439) Boundary_loss: 0.015244 (0.015234) Loss: 0.52855 (0.61963) +2025-08-22,02:53:01 | INFO | Train Epoch: 4 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.61254 (0.60446) Boundary_loss: 0.015264 (0.015235) Loss: 0.62780 (0.61969) +2025-08-22,02:53:58 | INFO | Train Epoch: 4 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.67331 (0.60499) Boundary_loss: 0.015151 (0.015234) Loss: 0.68846 (0.62023) +2025-08-22,02:54:55 | INFO | Train Epoch: 4 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.773 Boundary Ratio: 0.254 Contrastive_loss: 0.61005 (0.60503) Boundary_loss: 0.015241 (0.015234) Loss: 0.62529 (0.62026) +2025-08-22,02:55:52 | INFO | Train Epoch: 4 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.395 Boundary Ratio: 0.252 Contrastive_loss: 0.59662 (0.60497) Boundary_loss: 0.015320 (0.015235) Loss: 0.61194 (0.62020) +2025-08-22,02:56:49 | INFO | Train Epoch: 4 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.54664 (0.60452) Boundary_loss: 0.015047 (0.015233) Loss: 0.56169 (0.61976) +2025-08-22,02:57:46 | INFO | Train Epoch: 4 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.59398 (0.60444) Boundary_loss: 0.015294 (0.015234) Loss: 0.60927 (0.61968) +2025-08-22,02:58:43 | INFO | Train Epoch: 4 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.54098 (0.60397) Boundary_loss: 0.015162 (0.015233) Loss: 0.55614 (0.61920) +2025-08-22,02:59:40 | INFO | Train Epoch: 4 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 49.344 Boundary Ratio: 0.252 Contrastive_loss: 0.57384 (0.60375) Boundary_loss: 0.015176 (0.015233) Loss: 0.58902 (0.61898) +2025-08-22,03:00:37 | INFO | Train Epoch: 4 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 0.57376 (0.60353) Boundary_loss: 0.015253 (0.015233) Loss: 0.58902 (0.61876) +2025-08-22,03:01:33 | INFO | Train Epoch: 4 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.57829 (0.60334) Boundary_loss: 0.015303 (0.015233) Loss: 0.59359 (0.61858) +2025-08-22,03:02:30 | INFO | Train Epoch: 4 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.53143 (0.60282) Boundary_loss: 0.015120 (0.015233) Loss: 0.54655 (0.61805) +2025-08-22,03:03:27 | INFO | Train Epoch: 4 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.55891 (0.60251) Boundary_loss: 0.015362 (0.015234) Loss: 0.57427 (0.61774) +2025-08-22,03:04:24 | INFO | Train Epoch: 4 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.64917 (0.60284) Boundary_loss: 0.015292 (0.015234) Loss: 0.66447 (0.61807) +2025-08-22,03:05:21 | INFO | Train Epoch: 4 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 49.225 Boundary Ratio: 0.251 Contrastive_loss: 0.46792 (0.60188) Boundary_loss: 0.015152 (0.015233) Loss: 0.48307 (0.61712) +2025-08-22,03:06:18 | INFO | Train Epoch: 4 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.66480 (0.60233) Boundary_loss: 0.015223 (0.015233) Loss: 0.68003 (0.61756) +2025-08-22,03:07:15 | INFO | Train Epoch: 4 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.63976 (0.60259) Boundary_loss: 0.015326 (0.015234) Loss: 0.65509 (0.61782) +2025-08-22,03:08:11 | INFO | Train Epoch: 4 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.51011 (0.60195) Boundary_loss: 0.015297 (0.015234) Loss: 0.52541 (0.61718) +2025-08-22,03:09:08 | INFO | Train Epoch: 4 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.69819 (0.60261) Boundary_loss: 0.015229 (0.015234) Loss: 0.71342 (0.61784) +2025-08-22,03:10:05 | INFO | Train Epoch: 4 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 0.43961 (0.60149) Boundary_loss: 0.015234 (0.015234) Loss: 0.45484 (0.61673) +2025-08-22,03:11:02 | INFO | Train Epoch: 4 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 49.264 Boundary Ratio: 0.251 Contrastive_loss: 0.63363 (0.60171) Boundary_loss: 0.015236 (0.015234) Loss: 0.64886 (0.61695) +2025-08-22,03:11:58 | INFO | Train Epoch: 4 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.59126 (0.60164) Boundary_loss: 0.015142 (0.015234) Loss: 0.60640 (0.61687) +2025-08-22,03:12:55 | INFO | Train Epoch: 4 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.66924 (0.60209) Boundary_loss: 0.015192 (0.015234) Loss: 0.68444 (0.61733) +2025-08-22,03:13:52 | INFO | Train Epoch: 4 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 49.318 Boundary Ratio: 0.252 Contrastive_loss: 0.50521 (0.60145) Boundary_loss: 0.015220 (0.015233) Loss: 0.52043 (0.61668) +2025-08-22,03:14:49 | INFO | Train Epoch: 4 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.168 Boundary Ratio: 0.246 Contrastive_loss: 0.49622 (0.60075) Boundary_loss: 0.015356 (0.015234) Loss: 0.51158 (0.61599) +2025-08-22,03:15:46 | INFO | Train Epoch: 4 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.54674 (0.60040) Boundary_loss: 0.015280 (0.015235) Loss: 0.56202 (0.61563) +2025-08-22,03:16:43 | INFO | Train Epoch: 4 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 47.938 Boundary Ratio: 0.245 Contrastive_loss: 0.58372 (0.60029) Boundary_loss: 0.015169 (0.015234) Loss: 0.59889 (0.61552) +2025-08-22,03:17:39 | INFO | Train Epoch: 4 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 49.307 Boundary Ratio: 0.252 Contrastive_loss: 0.53699 (0.59988) Boundary_loss: 0.015198 (0.015234) Loss: 0.55219 (0.61511) +2025-08-22,03:18:36 | INFO | Train Epoch: 4 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.338 Boundary Ratio: 0.247 Contrastive_loss: 0.57200 (0.59970) Boundary_loss: 0.015244 (0.015234) Loss: 0.58724 (0.61493) +2025-08-22,03:19:33 | INFO | Train Epoch: 4 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 47.746 Boundary Ratio: 0.244 Contrastive_loss: 0.58027 (0.59957) Boundary_loss: 0.015266 (0.015234) Loss: 0.59554 (0.61481) +2025-08-22,03:20:30 | INFO | Train Epoch: 4 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 47.680 Boundary Ratio: 0.243 Contrastive_loss: 0.58019 (0.59945) Boundary_loss: 0.015270 (0.015234) Loss: 0.59546 (0.61468) +2025-08-22,03:21:27 | INFO | Train Epoch: 4 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.56294 (0.59922) Boundary_loss: 0.015179 (0.015234) Loss: 0.57812 (0.61445) +2025-08-22,03:22:24 | INFO | Train Epoch: 4 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.535 Boundary Ratio: 0.253 Contrastive_loss: 0.66670 (0.59964) Boundary_loss: 0.015271 (0.015234) Loss: 0.68197 (0.61488) +2025-08-22,03:23:20 | INFO | Train Epoch: 4 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 49.301 Boundary Ratio: 0.252 Contrastive_loss: 0.56232 (0.59941) Boundary_loss: 0.015117 (0.015234) Loss: 0.57744 (0.61464) +2025-08-22,03:24:17 | INFO | Train Epoch: 4 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.51085 (0.59886) Boundary_loss: 0.015193 (0.015233) Loss: 0.52604 (0.61409) +2025-08-22,03:25:14 | INFO | Train Epoch: 4 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.57787 (0.59873) Boundary_loss: 0.015173 (0.015233) Loss: 0.59305 (0.61396) +2025-08-22,03:26:11 | INFO | Train Epoch: 4 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.52583 (0.59828) Boundary_loss: 0.015408 (0.015234) Loss: 0.54124 (0.61352) +2025-08-22,03:27:08 | INFO | Train Epoch: 4 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.721 Boundary Ratio: 0.254 Contrastive_loss: 0.63129 (0.59848) Boundary_loss: 0.015362 (0.015235) Loss: 0.64665 (0.61372) +2025-08-22,03:28:04 | INFO | Train Epoch: 4 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 49.607 Boundary Ratio: 0.253 Contrastive_loss: 0.56467 (0.59828) Boundary_loss: 0.015462 (0.015236) Loss: 0.58013 (0.61351) +2025-08-22,03:29:01 | INFO | Train Epoch: 4 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.58613 (0.59821) Boundary_loss: 0.015344 (0.015237) Loss: 0.60148 (0.61344) +2025-08-22,03:29:58 | INFO | Train Epoch: 4 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.58553 (0.59813) Boundary_loss: 0.015162 (0.015236) Loss: 0.60069 (0.61337) +2025-08-22,03:30:54 | INFO | Train Epoch: 4 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.57982 (0.59802) Boundary_loss: 0.015221 (0.015236) Loss: 0.59504 (0.61326) +2025-08-22,03:31:51 | INFO | Train Epoch: 4 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 49.541 Boundary Ratio: 0.253 Contrastive_loss: 0.70732 (0.59867) Boundary_loss: 0.015204 (0.015236) Loss: 0.72253 (0.61390) +2025-08-22,03:32:48 | INFO | Train Epoch: 4 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 49.619 Boundary Ratio: 0.253 Contrastive_loss: 0.65385 (0.59899) Boundary_loss: 0.015336 (0.015237) Loss: 0.66918 (0.61423) +2025-08-22,03:33:45 | INFO | Train Epoch: 4 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.59338 (0.59896) Boundary_loss: 0.015222 (0.015237) Loss: 0.60860 (0.61420) +2025-08-22,03:34:42 | INFO | Train Epoch: 4 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 0.70975 (0.59960) Boundary_loss: 0.015281 (0.015237) Loss: 0.72503 (0.61484) +2025-08-22,03:35:39 | INFO | Train Epoch: 4 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.64917 (0.59989) Boundary_loss: 0.015212 (0.015237) Loss: 0.66438 (0.61513) +2025-08-22,03:36:36 | INFO | Train Epoch: 4 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 47.748 Boundary Ratio: 0.244 Contrastive_loss: 0.57301 (0.59973) Boundary_loss: 0.015240 (0.015237) Loss: 0.58825 (0.61497) +2025-08-22,03:37:33 | INFO | Train Epoch: 4 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.50967 (0.59922) Boundary_loss: 0.015239 (0.015237) Loss: 0.52491 (0.61446) +2025-08-22,03:38:30 | INFO | Train Epoch: 4 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.54208 (0.59890) Boundary_loss: 0.015157 (0.015236) Loss: 0.55724 (0.61413) +2025-08-22,03:39:26 | INFO | Train Epoch: 4 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 0.50729 (0.59838) Boundary_loss: 0.015115 (0.015236) Loss: 0.52241 (0.61361) +2025-08-22,03:40:23 | INFO | Train Epoch: 4 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.57171 (0.59823) Boundary_loss: 0.015170 (0.015235) Loss: 0.58688 (0.61346) +2025-08-22,03:41:20 | INFO | Train Epoch: 4 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 49.674 Boundary Ratio: 0.253 Contrastive_loss: 0.47826 (0.59756) Boundary_loss: 0.015177 (0.015235) Loss: 0.49344 (0.61279) +2025-08-22,03:42:17 | INFO | Train Epoch: 4 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 49.697 Boundary Ratio: 0.254 Contrastive_loss: 0.55336 (0.59731) Boundary_loss: 0.015198 (0.015235) Loss: 0.56856 (0.61255) +2025-08-22,03:43:13 | INFO | Train Epoch: 4 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.64582 (0.59758) Boundary_loss: 0.015221 (0.015235) Loss: 0.66104 (0.61282) +2025-08-22,03:44:10 | INFO | Train Epoch: 4 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.66829 (0.59797) Boundary_loss: 0.015209 (0.015234) Loss: 0.68350 (0.61320) +2025-08-22,03:45:07 | INFO | Train Epoch: 4 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.60211 (0.59799) Boundary_loss: 0.015239 (0.015234) Loss: 0.61735 (0.61323) +2025-08-22,03:46:04 | INFO | Train Epoch: 4 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.084 Boundary Ratio: 0.245 Contrastive_loss: 0.64631 (0.59825) Boundary_loss: 0.015268 (0.015235) Loss: 0.66158 (0.61349) +2025-08-22,03:47:00 | INFO | Train Epoch: 4 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.57649 (0.59814) Boundary_loss: 0.015127 (0.015234) Loss: 0.59162 (0.61337) +2025-08-22,03:47:57 | INFO | Train Epoch: 4 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.51657 (0.59770) Boundary_loss: 0.015124 (0.015234) Loss: 0.53170 (0.61293) +2025-08-22,03:48:54 | INFO | Train Epoch: 4 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 49.426 Boundary Ratio: 0.252 Contrastive_loss: 0.62612 (0.59785) Boundary_loss: 0.015182 (0.015233) Loss: 0.64130 (0.61308) +2025-08-22,03:49:51 | INFO | Train Epoch: 4 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.61800 (0.59796) Boundary_loss: 0.015158 (0.015233) Loss: 0.63316 (0.61319) +2025-08-22,03:50:48 | INFO | Train Epoch: 4 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.49594 (0.59742) Boundary_loss: 0.015191 (0.015233) Loss: 0.51113 (0.61265) +2025-08-22,03:51:45 | INFO | Train Epoch: 4 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.61552 (0.59751) Boundary_loss: 0.015150 (0.015232) Loss: 0.63067 (0.61274) +2025-08-22,03:52:42 | INFO | Train Epoch: 4 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.50421 (0.59702) Boundary_loss: 0.015286 (0.015232) Loss: 0.51950 (0.61226) +2025-08-22,03:53:38 | INFO | Train Epoch: 4 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.55856 (0.59682) Boundary_loss: 0.015098 (0.015232) Loss: 0.57366 (0.61206) +2025-08-22,03:54:35 | INFO | Train Epoch: 4 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.53139 (0.59648) Boundary_loss: 0.015118 (0.015231) Loss: 0.54651 (0.61172) +2025-08-22,03:55:32 | INFO | Train Epoch: 4 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.65345 (0.59678) Boundary_loss: 0.015148 (0.015231) Loss: 0.66860 (0.61201) +2025-08-22,03:56:29 | INFO | Train Epoch: 4 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.58612 (0.59672) Boundary_loss: 0.015212 (0.015231) Loss: 0.60133 (0.61195) +2025-08-22,03:57:26 | INFO | Train Epoch: 4 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.270 Boundary Ratio: 0.246 Contrastive_loss: 0.54646 (0.59647) Boundary_loss: 0.015063 (0.015230) Loss: 0.56152 (0.61170) +2025-08-22,03:58:23 | INFO | Train Epoch: 4 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.56115 (0.59629) Boundary_loss: 0.015234 (0.015230) Loss: 0.57638 (0.61152) +2025-08-22,03:59:20 | INFO | Train Epoch: 4 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.529 Boundary Ratio: 0.253 Contrastive_loss: 0.55681 (0.59609) Boundary_loss: 0.015255 (0.015230) Loss: 0.57206 (0.61132) +2025-08-22,04:00:16 | INFO | Train Epoch: 4 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.018 Boundary Ratio: 0.245 Contrastive_loss: 0.66369 (0.59643) Boundary_loss: 0.015096 (0.015229) Loss: 0.67879 (0.61166) +2025-08-22,04:01:13 | INFO | Train Epoch: 4 [10189312/26365952 (39%)] Avg Boundaries (per batch): 47.854 Boundary Ratio: 0.244 Contrastive_loss: 0.64575 (0.59668) Boundary_loss: 0.015373 (0.015230) Loss: 0.66112 (0.61191) +2025-08-22,04:02:10 | INFO | Train Epoch: 4 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.584 Boundary Ratio: 0.253 Contrastive_loss: 0.53088 (0.59635) Boundary_loss: 0.015160 (0.015230) Loss: 0.54604 (0.61158) +2025-08-22,04:03:07 | INFO | Train Epoch: 4 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.57201 (0.59623) Boundary_loss: 0.015116 (0.015229) Loss: 0.58712 (0.61146) +2025-08-22,04:04:04 | INFO | Train Epoch: 4 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.64562 (0.59647) Boundary_loss: 0.015270 (0.015229) Loss: 0.66089 (0.61170) +2025-08-22,04:05:01 | INFO | Train Epoch: 4 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.48638 (0.59593) Boundary_loss: 0.015326 (0.015230) Loss: 0.50170 (0.61116) +2025-08-22,04:05:58 | INFO | Train Epoch: 4 [10445312/26365952 (40%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.63486 (0.59612) Boundary_loss: 0.015185 (0.015230) Loss: 0.65005 (0.61135) +2025-08-22,04:06:55 | INFO | Train Epoch: 4 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.64617 (0.59636) Boundary_loss: 0.015252 (0.015230) Loss: 0.66142 (0.61159) +2025-08-22,04:07:52 | INFO | Train Epoch: 4 [10547712/26365952 (40%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.70293 (0.59688) Boundary_loss: 0.015177 (0.015229) Loss: 0.71811 (0.61211) +2025-08-22,04:08:49 | INFO | Train Epoch: 4 [10598912/26365952 (40%)] Avg Boundaries (per batch): 49.631 Boundary Ratio: 0.253 Contrastive_loss: 0.63338 (0.59705) Boundary_loss: 0.015461 (0.015230) Loss: 0.64884 (0.61228) +2025-08-22,04:09:46 | INFO | Train Epoch: 4 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.49789 (0.59658) Boundary_loss: 0.015258 (0.015231) Loss: 0.51315 (0.61181) +2025-08-22,04:10:43 | INFO | Train Epoch: 4 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.393 Boundary Ratio: 0.247 Contrastive_loss: 0.59657 (0.59658) Boundary_loss: 0.015168 (0.015230) Loss: 0.61174 (0.61181) +2025-08-22,04:11:40 | INFO | Train Epoch: 4 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.742 Boundary Ratio: 0.254 Contrastive_loss: 0.53804 (0.59630) Boundary_loss: 0.015273 (0.015231) Loss: 0.55331 (0.61153) +2025-08-22,04:12:36 | INFO | Train Epoch: 4 [10803712/26365952 (41%)] Avg Boundaries (per batch): 49.477 Boundary Ratio: 0.252 Contrastive_loss: 0.64312 (0.59652) Boundary_loss: 0.015257 (0.015231) Loss: 0.65838 (0.61175) +2025-08-22,04:13:33 | INFO | Train Epoch: 4 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.54493 (0.59628) Boundary_loss: 0.015135 (0.015230) Loss: 0.56006 (0.61151) +2025-08-22,04:14:30 | INFO | Train Epoch: 4 [10906112/26365952 (41%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 0.50851 (0.59587) Boundary_loss: 0.015108 (0.015230) Loss: 0.52362 (0.61110) +2025-08-22,04:15:27 | INFO | Train Epoch: 4 [10957312/26365952 (42%)] Avg Boundaries (per batch): 47.713 Boundary Ratio: 0.243 Contrastive_loss: 0.53606 (0.59559) Boundary_loss: 0.015373 (0.015230) Loss: 0.55143 (0.61082) +2025-08-22,04:16:24 | INFO | Train Epoch: 4 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.076 Boundary Ratio: 0.245 Contrastive_loss: 0.60862 (0.59565) Boundary_loss: 0.015077 (0.015230) Loss: 0.62370 (0.61088) +2025-08-22,04:17:21 | INFO | Train Epoch: 4 [11059712/26365952 (42%)] Avg Boundaries (per batch): 47.986 Boundary Ratio: 0.245 Contrastive_loss: 0.56810 (0.59553) Boundary_loss: 0.015259 (0.015230) Loss: 0.58336 (0.61076) +2025-08-22,04:18:18 | INFO | Train Epoch: 4 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.164 Boundary Ratio: 0.246 Contrastive_loss: 0.57064 (0.59541) Boundary_loss: 0.015320 (0.015230) Loss: 0.58596 (0.61064) +2025-08-22,04:19:15 | INFO | Train Epoch: 4 [11162112/26365952 (42%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.52356 (0.59508) Boundary_loss: 0.015129 (0.015230) Loss: 0.53869 (0.61031) +2025-08-22,04:20:12 | INFO | Train Epoch: 4 [11213312/26365952 (43%)] Avg Boundaries (per batch): 47.699 Boundary Ratio: 0.243 Contrastive_loss: 0.71843 (0.59564) Boundary_loss: 0.015317 (0.015230) Loss: 0.73374 (0.61087) +2025-08-22,04:21:08 | INFO | Train Epoch: 4 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.54283 (0.59541) Boundary_loss: 0.015111 (0.015230) Loss: 0.55794 (0.61063) +2025-08-22,04:22:05 | INFO | Train Epoch: 4 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.54665 (0.59519) Boundary_loss: 0.015169 (0.015229) Loss: 0.56182 (0.61041) +2025-08-22,04:23:02 | INFO | Train Epoch: 4 [11366912/26365952 (43%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 0.60184 (0.59522) Boundary_loss: 0.015229 (0.015229) Loss: 0.61707 (0.61044) +2025-08-22,04:23:59 | INFO | Train Epoch: 4 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.57216 (0.59511) Boundary_loss: 0.015228 (0.015229) Loss: 0.58739 (0.61034) +2025-08-22,04:24:56 | INFO | Train Epoch: 4 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.369 Boundary Ratio: 0.247 Contrastive_loss: 0.60709 (0.59517) Boundary_loss: 0.015123 (0.015229) Loss: 0.62221 (0.61039) +2025-08-22,04:25:53 | INFO | Train Epoch: 4 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.60872 (0.59523) Boundary_loss: 0.015212 (0.015229) Loss: 0.62393 (0.61045) +2025-08-22,04:26:50 | INFO | Train Epoch: 4 [11571712/26365952 (44%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.55177 (0.59503) Boundary_loss: 0.015105 (0.015228) Loss: 0.56687 (0.61026) +2025-08-22,04:27:47 | INFO | Train Epoch: 4 [11622912/26365952 (44%)] Avg Boundaries (per batch): 49.484 Boundary Ratio: 0.252 Contrastive_loss: 0.57105 (0.59493) Boundary_loss: 0.015245 (0.015228) Loss: 0.58630 (0.61016) +2025-08-22,04:28:44 | INFO | Train Epoch: 4 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 0.63885 (0.59512) Boundary_loss: 0.015294 (0.015229) Loss: 0.65414 (0.61035) +2025-08-22,04:29:41 | INFO | Train Epoch: 4 [11725312/26365952 (44%)] Avg Boundaries (per batch): 49.773 Boundary Ratio: 0.254 Contrastive_loss: 0.54079 (0.59488) Boundary_loss: 0.015310 (0.015229) Loss: 0.55610 (0.61011) +2025-08-22,04:30:38 | INFO | Train Epoch: 4 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.59710 (0.59489) Boundary_loss: 0.015182 (0.015229) Loss: 0.61228 (0.61012) +2025-08-22,04:31:35 | INFO | Train Epoch: 4 [11827712/26365952 (45%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 0.53015 (0.59462) Boundary_loss: 0.015129 (0.015228) Loss: 0.54528 (0.60984) +2025-08-22,04:32:32 | INFO | Train Epoch: 4 [11878912/26365952 (45%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.55992 (0.59447) Boundary_loss: 0.015252 (0.015228) Loss: 0.57517 (0.60969) +2025-08-22,04:33:29 | INFO | Train Epoch: 4 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.48260 (0.59399) Boundary_loss: 0.015217 (0.015228) Loss: 0.49782 (0.60922) +2025-08-22,04:34:25 | INFO | Train Epoch: 4 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.254 Boundary Ratio: 0.246 Contrastive_loss: 0.54366 (0.59377) Boundary_loss: 0.015305 (0.015229) Loss: 0.55897 (0.60900) +2025-08-22,04:35:22 | INFO | Train Epoch: 4 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.057 Boundary Ratio: 0.245 Contrastive_loss: 0.57030 (0.59367) Boundary_loss: 0.015165 (0.015228) Loss: 0.58546 (0.60890) +2025-08-22,04:36:19 | INFO | Train Epoch: 4 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.65125 (0.59392) Boundary_loss: 0.015101 (0.015228) Loss: 0.66635 (0.60915) +2025-08-22,04:37:16 | INFO | Train Epoch: 4 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.55624 (0.59376) Boundary_loss: 0.015112 (0.015227) Loss: 0.57135 (0.60899) +2025-08-22,04:38:13 | INFO | Train Epoch: 4 [12186112/26365952 (46%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.70426 (0.59422) Boundary_loss: 0.015204 (0.015227) Loss: 0.71947 (0.60945) +2025-08-22,04:39:10 | INFO | Train Epoch: 4 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.625 Boundary Ratio: 0.253 Contrastive_loss: 0.51062 (0.59387) Boundary_loss: 0.015297 (0.015228) Loss: 0.52592 (0.60910) +2025-08-22,04:40:07 | INFO | Train Epoch: 4 [12288512/26365952 (47%)] Avg Boundaries (per batch): 47.469 Boundary Ratio: 0.242 Contrastive_loss: 0.68244 (0.59424) Boundary_loss: 0.015321 (0.015228) Loss: 0.69776 (0.60947) +2025-08-22,04:41:04 | INFO | Train Epoch: 4 [12339712/26365952 (47%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 0.62290 (0.59436) Boundary_loss: 0.015252 (0.015228) Loss: 0.63816 (0.60959) +2025-08-22,04:42:01 | INFO | Train Epoch: 4 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.58791 (0.59433) Boundary_loss: 0.015351 (0.015229) Loss: 0.60326 (0.60956) +2025-08-22,04:42:57 | INFO | Train Epoch: 4 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.52721 (0.59406) Boundary_loss: 0.015084 (0.015228) Loss: 0.54229 (0.60929) +2025-08-22,04:43:54 | INFO | Train Epoch: 4 [12493312/26365952 (47%)] Avg Boundaries (per batch): 49.576 Boundary Ratio: 0.253 Contrastive_loss: 0.61747 (0.59415) Boundary_loss: 0.015192 (0.015228) Loss: 0.63266 (0.60938) +2025-08-22,04:44:51 | INFO | Train Epoch: 4 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.55986 (0.59401) Boundary_loss: 0.015160 (0.015228) Loss: 0.57502 (0.60924) +2025-08-22,04:45:48 | INFO | Train Epoch: 4 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.52809 (0.59375) Boundary_loss: 0.015102 (0.015227) Loss: 0.54320 (0.60897) +2025-08-22,04:46:45 | INFO | Train Epoch: 4 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.105 Boundary Ratio: 0.245 Contrastive_loss: 0.71524 (0.59424) Boundary_loss: 0.015067 (0.015226) Loss: 0.73031 (0.60946) +2025-08-22,04:47:42 | INFO | Train Epoch: 4 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.52779 (0.59397) Boundary_loss: 0.015198 (0.015226) Loss: 0.54299 (0.60920) +2025-08-22,04:48:39 | INFO | Train Epoch: 4 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.45848 (0.59343) Boundary_loss: 0.015453 (0.015227) Loss: 0.47393 (0.60866) +2025-08-22,04:49:36 | INFO | Train Epoch: 4 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.64201 (0.59362) Boundary_loss: 0.015271 (0.015227) Loss: 0.65728 (0.60885) +2025-08-22,04:50:32 | INFO | Train Epoch: 4 [12851712/26365952 (49%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.61421 (0.59370) Boundary_loss: 0.015288 (0.015228) Loss: 0.62949 (0.60893) +2025-08-22,04:51:29 | INFO | Train Epoch: 4 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.47560 (0.59324) Boundary_loss: 0.015315 (0.015228) Loss: 0.49091 (0.60846) +2025-08-22,04:52:26 | INFO | Train Epoch: 4 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.59100 (0.59323) Boundary_loss: 0.015390 (0.015229) Loss: 0.60639 (0.60846) +2025-08-22,04:53:23 | INFO | Train Epoch: 4 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.59302 (0.59323) Boundary_loss: 0.015219 (0.015229) Loss: 0.60824 (0.60846) +2025-08-22,04:54:20 | INFO | Train Epoch: 4 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.098 Boundary Ratio: 0.245 Contrastive_loss: 0.57741 (0.59316) Boundary_loss: 0.015323 (0.015229) Loss: 0.59273 (0.60839) +2025-08-22,04:55:17 | INFO | Train Epoch: 4 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.057 Boundary Ratio: 0.245 Contrastive_loss: 0.65645 (0.59341) Boundary_loss: 0.015191 (0.015229) Loss: 0.67164 (0.60864) +2025-08-22,04:56:14 | INFO | Train Epoch: 4 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.59973 (0.59344) Boundary_loss: 0.015186 (0.015229) Loss: 0.61492 (0.60866) +2025-08-22,04:57:10 | INFO | Train Epoch: 4 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.59586 (0.59344) Boundary_loss: 0.015122 (0.015228) Loss: 0.61098 (0.60867) +2025-08-22,04:58:07 | INFO | Train Epoch: 4 [13261312/26365952 (50%)] Avg Boundaries (per batch): 50.129 Boundary Ratio: 0.256 Contrastive_loss: 0.60294 (0.59348) Boundary_loss: 0.015319 (0.015229) Loss: 0.61826 (0.60871) +2025-08-22,04:59:04 | INFO | Train Epoch: 4 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.176 Boundary Ratio: 0.246 Contrastive_loss: 0.56163 (0.59336) Boundary_loss: 0.015159 (0.015228) Loss: 0.57679 (0.60859) +2025-08-22,05:00:01 | INFO | Train Epoch: 4 [13363712/26365952 (51%)] Avg Boundaries (per batch): 49.619 Boundary Ratio: 0.253 Contrastive_loss: 0.53710 (0.59314) Boundary_loss: 0.015366 (0.015229) Loss: 0.55246 (0.60837) +2025-08-22,05:00:58 | INFO | Train Epoch: 4 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.52431 (0.59288) Boundary_loss: 0.015236 (0.015229) Loss: 0.53955 (0.60811) +2025-08-22,05:01:55 | INFO | Train Epoch: 4 [13466112/26365952 (51%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.62681 (0.59301) Boundary_loss: 0.015202 (0.015229) Loss: 0.64201 (0.60824) +2025-08-22,05:02:52 | INFO | Train Epoch: 4 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.328 Boundary Ratio: 0.247 Contrastive_loss: 0.57808 (0.59296) Boundary_loss: 0.015172 (0.015228) Loss: 0.59326 (0.60818) +2025-08-22,05:03:49 | INFO | Train Epoch: 4 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.297 Boundary Ratio: 0.246 Contrastive_loss: 0.49418 (0.59258) Boundary_loss: 0.015303 (0.015229) Loss: 0.50949 (0.60781) +2025-08-22,05:04:45 | INFO | Train Epoch: 4 [13619712/26365952 (52%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.60464 (0.59263) Boundary_loss: 0.015254 (0.015229) Loss: 0.61990 (0.60786) +2025-08-22,05:05:42 | INFO | Train Epoch: 4 [13670912/26365952 (52%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.56165 (0.59251) Boundary_loss: 0.015047 (0.015228) Loss: 0.57670 (0.60774) +2025-08-22,05:06:39 | INFO | Train Epoch: 4 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.57598 (0.59245) Boundary_loss: 0.015177 (0.015228) Loss: 0.59116 (0.60768) +2025-08-22,05:07:36 | INFO | Train Epoch: 4 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.107 Boundary Ratio: 0.245 Contrastive_loss: 0.50561 (0.59213) Boundary_loss: 0.015217 (0.015228) Loss: 0.52082 (0.60736) +2025-08-22,05:08:33 | INFO | Train Epoch: 4 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.246 Boundary Ratio: 0.251 Contrastive_loss: 0.62066 (0.59224) Boundary_loss: 0.015284 (0.015228) Loss: 0.63594 (0.60746) +2025-08-22,05:09:29 | INFO | Train Epoch: 4 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.60690 (0.59229) Boundary_loss: 0.015220 (0.015228) Loss: 0.62212 (0.60752) +2025-08-22,05:10:26 | INFO | Train Epoch: 4 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.58415 (0.59226) Boundary_loss: 0.015193 (0.015228) Loss: 0.59934 (0.60749) +2025-08-22,05:11:23 | INFO | Train Epoch: 4 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.406 Boundary Ratio: 0.247 Contrastive_loss: 0.67504 (0.59256) Boundary_loss: 0.015005 (0.015227) Loss: 0.69005 (0.60779) +2025-08-22,05:12:20 | INFO | Train Epoch: 4 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.61776 (0.59265) Boundary_loss: 0.015325 (0.015228) Loss: 0.63309 (0.60788) +2025-08-22,05:13:17 | INFO | Train Epoch: 4 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.59336 (0.59266) Boundary_loss: 0.015232 (0.015228) Loss: 0.60859 (0.60788) +2025-08-22,05:14:14 | INFO | Train Epoch: 4 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.64667 (0.59285) Boundary_loss: 0.015218 (0.015228) Loss: 0.66189 (0.60808) +2025-08-22,05:15:11 | INFO | Train Epoch: 4 [14182912/26365952 (54%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.54263 (0.59267) Boundary_loss: 0.015066 (0.015227) Loss: 0.55770 (0.60790) +2025-08-22,05:16:08 | INFO | Train Epoch: 4 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.61937 (0.59277) Boundary_loss: 0.015265 (0.015227) Loss: 0.63463 (0.60799) +2025-08-22,05:17:05 | INFO | Train Epoch: 4 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.63168 (0.59291) Boundary_loss: 0.015137 (0.015227) Loss: 0.64682 (0.60813) +2025-08-22,05:18:01 | INFO | Train Epoch: 4 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.40418 (0.59223) Boundary_loss: 0.015258 (0.015227) Loss: 0.41944 (0.60746) +2025-08-22,05:18:58 | INFO | Train Epoch: 4 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.68402 (0.59256) Boundary_loss: 0.015372 (0.015227) Loss: 0.69940 (0.60779) +2025-08-22,05:19:55 | INFO | Train Epoch: 4 [14438912/26365952 (55%)] Avg Boundaries (per batch): 47.734 Boundary Ratio: 0.244 Contrastive_loss: 0.56677 (0.59247) Boundary_loss: 0.015191 (0.015227) Loss: 0.58196 (0.60770) +2025-08-22,05:20:52 | INFO | Train Epoch: 4 [14490112/26365952 (55%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 0.63566 (0.59262) Boundary_loss: 0.015153 (0.015227) Loss: 0.65082 (0.60785) +2025-08-22,05:21:49 | INFO | Train Epoch: 4 [14541312/26365952 (55%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.49444 (0.59228) Boundary_loss: 0.015266 (0.015227) Loss: 0.50971 (0.60750) +2025-08-22,05:22:46 | INFO | Train Epoch: 4 [14592512/26365952 (55%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.48246 (0.59189) Boundary_loss: 0.015314 (0.015227) Loss: 0.49777 (0.60712) +2025-08-22,05:23:43 | INFO | Train Epoch: 4 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.297 Boundary Ratio: 0.246 Contrastive_loss: 0.51073 (0.59161) Boundary_loss: 0.015231 (0.015227) Loss: 0.52596 (0.60684) +2025-08-22,05:24:39 | INFO | Train Epoch: 4 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.66304 (0.59186) Boundary_loss: 0.015081 (0.015227) Loss: 0.67812 (0.60708) +2025-08-22,05:25:36 | INFO | Train Epoch: 4 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.61525 (0.59194) Boundary_loss: 0.015140 (0.015227) Loss: 0.63039 (0.60716) +2025-08-22,05:26:33 | INFO | Train Epoch: 4 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.62553 (0.59205) Boundary_loss: 0.015315 (0.015227) Loss: 0.64085 (0.60728) +2025-08-22,05:27:30 | INFO | Train Epoch: 4 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.68521 (0.59237) Boundary_loss: 0.015172 (0.015227) Loss: 0.70038 (0.60760) +2025-08-22,05:28:27 | INFO | Train Epoch: 4 [14899712/26365952 (57%)] Avg Boundaries (per batch): 49.465 Boundary Ratio: 0.252 Contrastive_loss: 0.56472 (0.59228) Boundary_loss: 0.015340 (0.015227) Loss: 0.58006 (0.60751) +2025-08-22,05:29:24 | INFO | Train Epoch: 4 [14950912/26365952 (57%)] Avg Boundaries (per batch): 47.693 Boundary Ratio: 0.243 Contrastive_loss: 0.57028 (0.59220) Boundary_loss: 0.015335 (0.015228) Loss: 0.58561 (0.60743) +2025-08-22,05:30:21 | INFO | Train Epoch: 4 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 0.63513 (0.59235) Boundary_loss: 0.015198 (0.015227) Loss: 0.65033 (0.60758) +2025-08-22,05:31:17 | INFO | Train Epoch: 4 [15053312/26365952 (57%)] Avg Boundaries (per batch): 47.945 Boundary Ratio: 0.245 Contrastive_loss: 0.61950 (0.59244) Boundary_loss: 0.015068 (0.015227) Loss: 0.63457 (0.60767) +2025-08-22,05:32:14 | INFO | Train Epoch: 4 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.203 Boundary Ratio: 0.246 Contrastive_loss: 0.65125 (0.59264) Boundary_loss: 0.015187 (0.015227) Loss: 0.66643 (0.60787) +2025-08-22,05:33:11 | INFO | Train Epoch: 4 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.574 Boundary Ratio: 0.253 Contrastive_loss: 0.53613 (0.59245) Boundary_loss: 0.015325 (0.015227) Loss: 0.55146 (0.60768) +2025-08-22,05:34:08 | INFO | Train Epoch: 4 [15206912/26365952 (58%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.56520 (0.59236) Boundary_loss: 0.015076 (0.015227) Loss: 0.58028 (0.60759) +2025-08-22,05:35:05 | INFO | Train Epoch: 4 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.55179 (0.59222) Boundary_loss: 0.015042 (0.015226) Loss: 0.56683 (0.60745) +2025-08-22,05:36:02 | INFO | Train Epoch: 4 [15309312/26365952 (58%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 0.64095 (0.59239) Boundary_loss: 0.015198 (0.015226) Loss: 0.65615 (0.60761) +2025-08-22,05:36:58 | INFO | Train Epoch: 4 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.58552 (0.59236) Boundary_loss: 0.015188 (0.015226) Loss: 0.60071 (0.60759) +2025-08-22,05:37:56 | INFO | Train Epoch: 4 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.58649 (0.59234) Boundary_loss: 0.015348 (0.015226) Loss: 0.60184 (0.60757) +2025-08-22,05:38:52 | INFO | Train Epoch: 4 [15462912/26365952 (59%)] Avg Boundaries (per batch): 47.572 Boundary Ratio: 0.243 Contrastive_loss: 0.47747 (0.59196) Boundary_loss: 0.015247 (0.015226) Loss: 0.49272 (0.60719) +2025-08-22,05:39:49 | INFO | Train Epoch: 4 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.57121 (0.59190) Boundary_loss: 0.015153 (0.015226) Loss: 0.58636 (0.60712) +2025-08-22,05:40:46 | INFO | Train Epoch: 4 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.55577 (0.59178) Boundary_loss: 0.015207 (0.015226) Loss: 0.57098 (0.60700) +2025-08-22,05:41:43 | INFO | Train Epoch: 4 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.57534 (0.59172) Boundary_loss: 0.015160 (0.015226) Loss: 0.59050 (0.60695) +2025-08-22,05:42:40 | INFO | Train Epoch: 4 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.303 Boundary Ratio: 0.246 Contrastive_loss: 0.60578 (0.59177) Boundary_loss: 0.015212 (0.015226) Loss: 0.62099 (0.60700) +2025-08-22,05:43:37 | INFO | Train Epoch: 4 [15718912/26365952 (60%)] Avg Boundaries (per batch): 49.629 Boundary Ratio: 0.253 Contrastive_loss: 0.61261 (0.59184) Boundary_loss: 0.015218 (0.015226) Loss: 0.62782 (0.60706) +2025-08-22,05:44:34 | INFO | Train Epoch: 4 [15770112/26365952 (60%)] Avg Boundaries (per batch): 47.779 Boundary Ratio: 0.244 Contrastive_loss: 0.53555 (0.59165) Boundary_loss: 0.015246 (0.015226) Loss: 0.55080 (0.60688) +2025-08-22,05:45:31 | INFO | Train Epoch: 4 [15821312/26365952 (60%)] Avg Boundaries (per batch): 47.963 Boundary Ratio: 0.245 Contrastive_loss: 0.54594 (0.59151) Boundary_loss: 0.015125 (0.015225) Loss: 0.56107 (0.60673) +2025-08-22,05:46:27 | INFO | Train Epoch: 4 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.59589 (0.59152) Boundary_loss: 0.015292 (0.015226) Loss: 0.61118 (0.60675) +2025-08-22,05:47:24 | INFO | Train Epoch: 4 [15923712/26365952 (60%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 0.66146 (0.59175) Boundary_loss: 0.015288 (0.015226) Loss: 0.67675 (0.60697) +2025-08-22,05:48:21 | INFO | Train Epoch: 4 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.63262 (0.59188) Boundary_loss: 0.015305 (0.015226) Loss: 0.64793 (0.60710) +2025-08-22,05:49:18 | INFO | Train Epoch: 4 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 0.60490 (0.59192) Boundary_loss: 0.015357 (0.015226) Loss: 0.62026 (0.60714) +2025-08-22,05:50:15 | INFO | Train Epoch: 4 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.066 Boundary Ratio: 0.245 Contrastive_loss: 0.63409 (0.59205) Boundary_loss: 0.015187 (0.015226) Loss: 0.64927 (0.60728) +2025-08-22,05:51:12 | INFO | Train Epoch: 4 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.70177 (0.59240) Boundary_loss: 0.015213 (0.015226) Loss: 0.71698 (0.60763) +2025-08-22,05:52:09 | INFO | Train Epoch: 4 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.182 Boundary Ratio: 0.246 Contrastive_loss: 0.49839 (0.59210) Boundary_loss: 0.015211 (0.015226) Loss: 0.51360 (0.60733) +2025-08-22,05:53:06 | INFO | Train Epoch: 4 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.391 Boundary Ratio: 0.247 Contrastive_loss: 0.49684 (0.59180) Boundary_loss: 0.015193 (0.015226) Loss: 0.51203 (0.60703) +2025-08-22,05:54:03 | INFO | Train Epoch: 4 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.64433 (0.59197) Boundary_loss: 0.015282 (0.015226) Loss: 0.65961 (0.60719) +2025-08-22,05:55:00 | INFO | Train Epoch: 4 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.64721 (0.59214) Boundary_loss: 0.015109 (0.015226) Loss: 0.66231 (0.60737) +2025-08-22,05:55:57 | INFO | Train Epoch: 4 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.65233 (0.59233) Boundary_loss: 0.015205 (0.015226) Loss: 0.66754 (0.60755) +2025-08-22,05:56:53 | INFO | Train Epoch: 4 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.64912 (0.59250) Boundary_loss: 0.015170 (0.015226) Loss: 0.66429 (0.60773) +2025-08-22,05:57:50 | INFO | Train Epoch: 4 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.332 Boundary Ratio: 0.252 Contrastive_loss: 0.58682 (0.59249) Boundary_loss: 0.015485 (0.015226) Loss: 0.60230 (0.60771) +2025-08-22,05:58:47 | INFO | Train Epoch: 4 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.195 Boundary Ratio: 0.246 Contrastive_loss: 0.56817 (0.59241) Boundary_loss: 0.015364 (0.015227) Loss: 0.58354 (0.60764) +2025-08-22,05:59:44 | INFO | Train Epoch: 4 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.52177 (0.59219) Boundary_loss: 0.015281 (0.015227) Loss: 0.53705 (0.60742) +2025-08-22,06:00:41 | INFO | Train Epoch: 4 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.64769 (0.59236) Boundary_loss: 0.015173 (0.015227) Loss: 0.66286 (0.60759) +2025-08-22,06:01:38 | INFO | Train Epoch: 4 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.287 Boundary Ratio: 0.246 Contrastive_loss: 0.55526 (0.59225) Boundary_loss: 0.015256 (0.015227) Loss: 0.57052 (0.60748) +2025-08-22,06:02:35 | INFO | Train Epoch: 4 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.127 Boundary Ratio: 0.246 Contrastive_loss: 0.66377 (0.59247) Boundary_loss: 0.015285 (0.015227) Loss: 0.67905 (0.60770) +2025-08-22,06:03:32 | INFO | Train Epoch: 4 [16794112/26365952 (64%)] Avg Boundaries (per batch): 49.686 Boundary Ratio: 0.253 Contrastive_loss: 0.62508 (0.59257) Boundary_loss: 0.015270 (0.015227) Loss: 0.64035 (0.60780) +2025-08-22,06:04:29 | INFO | Train Epoch: 4 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.57395 (0.59251) Boundary_loss: 0.015205 (0.015227) Loss: 0.58915 (0.60774) +2025-08-22,06:05:26 | INFO | Train Epoch: 4 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.56926 (0.59244) Boundary_loss: 0.015270 (0.015227) Loss: 0.58453 (0.60767) +2025-08-22,06:06:22 | INFO | Train Epoch: 4 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.51467 (0.59221) Boundary_loss: 0.015217 (0.015227) Loss: 0.52989 (0.60743) +2025-08-22,06:07:19 | INFO | Train Epoch: 4 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.55494 (0.59210) Boundary_loss: 0.015211 (0.015227) Loss: 0.57015 (0.60732) +2025-08-22,06:08:16 | INFO | Train Epoch: 4 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.57397 (0.59204) Boundary_loss: 0.015164 (0.015227) Loss: 0.58913 (0.60727) +2025-08-22,06:09:13 | INFO | Train Epoch: 4 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.264 Boundary Ratio: 0.251 Contrastive_loss: 0.58108 (0.59201) Boundary_loss: 0.015096 (0.015227) Loss: 0.59617 (0.60723) +2025-08-22,06:10:10 | INFO | Train Epoch: 4 [17152512/26365952 (65%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.52916 (0.59182) Boundary_loss: 0.015328 (0.015227) Loss: 0.54449 (0.60705) +2025-08-22,06:11:06 | INFO | Train Epoch: 4 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.55089 (0.59170) Boundary_loss: 0.015263 (0.015227) Loss: 0.56615 (0.60693) +2025-08-22,06:12:03 | INFO | Train Epoch: 4 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.52312 (0.59150) Boundary_loss: 0.015214 (0.015227) Loss: 0.53833 (0.60672) +2025-08-22,06:13:00 | INFO | Train Epoch: 4 [17306112/26365952 (66%)] Avg Boundaries (per batch): 50.250 Boundary Ratio: 0.256 Contrastive_loss: 0.71126 (0.59185) Boundary_loss: 0.015315 (0.015227) Loss: 0.72658 (0.60708) +2025-08-22,06:13:57 | INFO | Train Epoch: 4 [17357312/26365952 (66%)] Avg Boundaries (per batch): 49.543 Boundary Ratio: 0.253 Contrastive_loss: 0.53428 (0.59168) Boundary_loss: 0.015279 (0.015227) Loss: 0.54956 (0.60691) +2025-08-22,06:14:54 | INFO | Train Epoch: 4 [17408512/26365952 (66%)] Avg Boundaries (per batch): 47.900 Boundary Ratio: 0.244 Contrastive_loss: 0.46623 (0.59131) Boundary_loss: 0.015196 (0.015227) Loss: 0.48143 (0.60654) +2025-08-22,06:15:50 | INFO | Train Epoch: 4 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.60690 (0.59136) Boundary_loss: 0.015386 (0.015228) Loss: 0.62229 (0.60659) +2025-08-22,06:16:47 | INFO | Train Epoch: 4 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.59321 (0.59136) Boundary_loss: 0.015225 (0.015228) Loss: 0.60843 (0.60659) +2025-08-22,06:17:44 | INFO | Train Epoch: 4 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 0.50087 (0.59110) Boundary_loss: 0.015207 (0.015228) Loss: 0.51607 (0.60633) +2025-08-22,06:18:41 | INFO | Train Epoch: 4 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.57026 (0.59104) Boundary_loss: 0.015076 (0.015227) Loss: 0.58534 (0.60627) +2025-08-22,06:19:38 | INFO | Train Epoch: 4 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.58157 (0.59101) Boundary_loss: 0.015345 (0.015228) Loss: 0.59692 (0.60624) +2025-08-22,06:20:35 | INFO | Train Epoch: 4 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.439 Boundary Ratio: 0.252 Contrastive_loss: 0.51693 (0.59080) Boundary_loss: 0.015085 (0.015227) Loss: 0.53201 (0.60603) +2025-08-22,06:21:32 | INFO | Train Epoch: 4 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.56215 (0.59072) Boundary_loss: 0.015160 (0.015227) Loss: 0.57731 (0.60594) +2025-08-22,06:22:29 | INFO | Train Epoch: 4 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.59768 (0.59074) Boundary_loss: 0.015357 (0.015227) Loss: 0.61304 (0.60596) +2025-08-22,06:23:26 | INFO | Train Epoch: 4 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.256 Boundary Ratio: 0.246 Contrastive_loss: 0.65920 (0.59093) Boundary_loss: 0.015136 (0.015227) Loss: 0.67433 (0.60616) +2025-08-22,06:24:23 | INFO | Train Epoch: 4 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.57820 (0.59090) Boundary_loss: 0.015189 (0.015227) Loss: 0.59338 (0.60612) +2025-08-22,06:25:19 | INFO | Train Epoch: 4 [17971712/26365952 (68%)] Avg Boundaries (per batch): 49.373 Boundary Ratio: 0.252 Contrastive_loss: 0.48651 (0.59060) Boundary_loss: 0.015128 (0.015227) Loss: 0.50163 (0.60583) +2025-08-22,06:26:16 | INFO | Train Epoch: 4 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.57701 (0.59056) Boundary_loss: 0.015294 (0.015227) Loss: 0.59231 (0.60579) +2025-08-22,06:27:13 | INFO | Train Epoch: 4 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.49359 (0.59029) Boundary_loss: 0.015228 (0.015227) Loss: 0.50882 (0.60551) +2025-08-22,06:28:10 | INFO | Train Epoch: 4 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.53575 (0.59013) Boundary_loss: 0.015318 (0.015227) Loss: 0.55107 (0.60536) +2025-08-22,06:29:07 | INFO | Train Epoch: 4 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.57744 (0.59010) Boundary_loss: 0.015121 (0.015227) Loss: 0.59256 (0.60532) +2025-08-22,06:30:04 | INFO | Train Epoch: 4 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.56963 (0.59004) Boundary_loss: 0.015237 (0.015227) Loss: 0.58487 (0.60527) +2025-08-22,06:31:00 | INFO | Train Epoch: 4 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.64126 (0.59018) Boundary_loss: 0.015126 (0.015227) Loss: 0.65639 (0.60541) +2025-08-22,06:31:57 | INFO | Train Epoch: 4 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.59017 (0.59018) Boundary_loss: 0.015189 (0.015227) Loss: 0.60536 (0.60541) +2025-08-22,06:32:54 | INFO | Train Epoch: 4 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.129 Boundary Ratio: 0.246 Contrastive_loss: 0.60008 (0.59021) Boundary_loss: 0.015113 (0.015226) Loss: 0.61519 (0.60544) +2025-08-22,06:33:51 | INFO | Train Epoch: 4 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.369 Boundary Ratio: 0.247 Contrastive_loss: 0.64658 (0.59037) Boundary_loss: 0.015260 (0.015226) Loss: 0.66184 (0.60559) +2025-08-22,06:34:48 | INFO | Train Epoch: 4 [18483712/26365952 (70%)] Avg Boundaries (per batch): 47.689 Boundary Ratio: 0.243 Contrastive_loss: 0.50602 (0.59013) Boundary_loss: 0.015255 (0.015226) Loss: 0.52127 (0.60536) +2025-08-22,06:35:44 | INFO | Train Epoch: 4 [18534912/26365952 (70%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.59349 (0.59014) Boundary_loss: 0.015309 (0.015227) Loss: 0.60880 (0.60537) +2025-08-22,06:36:41 | INFO | Train Epoch: 4 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 0.53223 (0.58998) Boundary_loss: 0.015300 (0.015227) Loss: 0.54753 (0.60521) +2025-08-22,06:37:38 | INFO | Train Epoch: 4 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.51149 (0.58977) Boundary_loss: 0.015290 (0.015227) Loss: 0.52678 (0.60500) +2025-08-22,06:38:35 | INFO | Train Epoch: 4 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 0.64631 (0.58992) Boundary_loss: 0.015229 (0.015227) Loss: 0.66154 (0.60515) +2025-08-22,06:39:32 | INFO | Train Epoch: 4 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.55631 (0.58983) Boundary_loss: 0.015277 (0.015227) Loss: 0.57158 (0.60506) +2025-08-22,06:40:29 | INFO | Train Epoch: 4 [18790912/26365952 (71%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.57364 (0.58979) Boundary_loss: 0.015271 (0.015227) Loss: 0.58891 (0.60502) +2025-08-22,06:41:26 | INFO | Train Epoch: 4 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.43212 (0.58936) Boundary_loss: 0.015178 (0.015227) Loss: 0.44730 (0.60459) +2025-08-22,06:42:23 | INFO | Train Epoch: 4 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.49941 (0.58912) Boundary_loss: 0.015105 (0.015227) Loss: 0.51451 (0.60434) +2025-08-22,06:43:19 | INFO | Train Epoch: 4 [18944512/26365952 (72%)] Avg Boundaries (per batch): 49.500 Boundary Ratio: 0.253 Contrastive_loss: 0.59287 (0.58913) Boundary_loss: 0.015324 (0.015227) Loss: 0.60819 (0.60436) +2025-08-22,06:44:16 | INFO | Train Epoch: 4 [18995712/26365952 (72%)] Avg Boundaries (per batch): 50.035 Boundary Ratio: 0.255 Contrastive_loss: 0.58261 (0.58911) Boundary_loss: 0.015349 (0.015227) Loss: 0.59796 (0.60434) +2025-08-22,06:45:13 | INFO | Train Epoch: 4 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.48845 (0.58884) Boundary_loss: 0.015256 (0.015228) Loss: 0.50371 (0.60407) +2025-08-22,06:46:10 | INFO | Train Epoch: 4 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.60929 (0.58890) Boundary_loss: 0.015263 (0.015228) Loss: 0.62455 (0.60412) +2025-08-22,06:47:07 | INFO | Train Epoch: 4 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 0.56190 (0.58882) Boundary_loss: 0.015124 (0.015227) Loss: 0.57703 (0.60405) +2025-08-22,06:48:03 | INFO | Train Epoch: 4 [19200512/26365952 (73%)] Avg Boundaries (per batch): 47.949 Boundary Ratio: 0.245 Contrastive_loss: 0.53862 (0.58869) Boundary_loss: 0.015124 (0.015227) Loss: 0.55375 (0.60392) +2025-08-22,06:49:00 | INFO | Train Epoch: 4 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.54884 (0.58858) Boundary_loss: 0.015185 (0.015227) Loss: 0.56402 (0.60381) +2025-08-22,06:49:57 | INFO | Train Epoch: 4 [19302912/26365952 (73%)] Avg Boundaries (per batch): 49.318 Boundary Ratio: 0.252 Contrastive_loss: 0.55142 (0.58849) Boundary_loss: 0.015128 (0.015227) Loss: 0.56654 (0.60371) +2025-08-22,06:50:54 | INFO | Train Epoch: 4 [19354112/26365952 (73%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 0.56249 (0.58842) Boundary_loss: 0.015181 (0.015227) Loss: 0.57767 (0.60364) +2025-08-22,06:51:50 | INFO | Train Epoch: 4 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 0.52590 (0.58825) Boundary_loss: 0.015140 (0.015226) Loss: 0.54104 (0.60348) +2025-08-22,06:52:47 | INFO | Train Epoch: 4 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.59274 (0.58826) Boundary_loss: 0.015293 (0.015227) Loss: 0.60803 (0.60349) +2025-08-22,06:53:44 | INFO | Train Epoch: 4 [19507712/26365952 (74%)] Avg Boundaries (per batch): 49.328 Boundary Ratio: 0.252 Contrastive_loss: 0.62857 (0.58837) Boundary_loss: 0.015332 (0.015227) Loss: 0.64390 (0.60360) +2025-08-22,06:54:41 | INFO | Train Epoch: 4 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.096 Boundary Ratio: 0.245 Contrastive_loss: 0.70248 (0.58867) Boundary_loss: 0.015122 (0.015227) Loss: 0.71760 (0.60389) +2025-08-22,06:55:38 | INFO | Train Epoch: 4 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.59113 (0.58867) Boundary_loss: 0.015271 (0.015227) Loss: 0.60640 (0.60390) +2025-08-22,06:56:35 | INFO | Train Epoch: 4 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.301 Boundary Ratio: 0.246 Contrastive_loss: 0.56263 (0.58861) Boundary_loss: 0.015138 (0.015226) Loss: 0.57777 (0.60383) +2025-08-22,06:57:32 | INFO | Train Epoch: 4 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.56582 (0.58855) Boundary_loss: 0.015238 (0.015226) Loss: 0.58106 (0.60377) +2025-08-22,06:58:29 | INFO | Train Epoch: 4 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.59618 (0.58857) Boundary_loss: 0.015181 (0.015226) Loss: 0.61136 (0.60379) +2025-08-22,06:59:25 | INFO | Train Epoch: 4 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.46743 (0.58826) Boundary_loss: 0.015092 (0.015226) Loss: 0.48252 (0.60348) +2025-08-22,07:00:22 | INFO | Train Epoch: 4 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.076 Boundary Ratio: 0.245 Contrastive_loss: 0.65367 (0.58842) Boundary_loss: 0.015246 (0.015226) Loss: 0.66891 (0.60365) +2025-08-22,07:01:19 | INFO | Train Epoch: 4 [19917312/26365952 (76%)] Avg Boundaries (per batch): 49.539 Boundary Ratio: 0.253 Contrastive_loss: 0.56602 (0.58837) Boundary_loss: 0.015345 (0.015226) Loss: 0.58137 (0.60359) +2025-08-22,07:02:16 | INFO | Train Epoch: 4 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.66657 (0.58857) Boundary_loss: 0.015216 (0.015226) Loss: 0.68178 (0.60379) +2025-08-22,07:03:13 | INFO | Train Epoch: 4 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.57331 (0.58853) Boundary_loss: 0.015275 (0.015226) Loss: 0.58858 (0.60375) +2025-08-22,07:04:10 | INFO | Train Epoch: 4 [20070912/26365952 (76%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 0.50329 (0.58831) Boundary_loss: 0.015120 (0.015226) Loss: 0.51841 (0.60354) +2025-08-22,07:05:07 | INFO | Train Epoch: 4 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.57091 (0.58827) Boundary_loss: 0.015304 (0.015226) Loss: 0.58622 (0.60349) +2025-08-22,07:06:04 | INFO | Train Epoch: 4 [20173312/26365952 (77%)] Avg Boundaries (per batch): 49.938 Boundary Ratio: 0.255 Contrastive_loss: 0.67249 (0.58848) Boundary_loss: 0.015231 (0.015226) Loss: 0.68773 (0.60371) +2025-08-22,07:07:01 | INFO | Train Epoch: 4 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 0.58295 (0.58847) Boundary_loss: 0.015213 (0.015226) Loss: 0.59816 (0.60369) +2025-08-22,07:07:58 | INFO | Train Epoch: 4 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.56132 (0.58840) Boundary_loss: 0.015069 (0.015226) Loss: 0.57639 (0.60362) +2025-08-22,07:08:55 | INFO | Train Epoch: 4 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.49064 (0.58815) Boundary_loss: 0.015267 (0.015226) Loss: 0.50591 (0.60338) +2025-08-22,07:09:51 | INFO | Train Epoch: 4 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.62880 (0.58825) Boundary_loss: 0.015196 (0.015226) Loss: 0.64399 (0.60348) +2025-08-22,07:10:48 | INFO | Train Epoch: 4 [20429312/26365952 (77%)] Avg Boundaries (per batch): 49.668 Boundary Ratio: 0.253 Contrastive_loss: 0.55059 (0.58816) Boundary_loss: 0.015168 (0.015226) Loss: 0.56576 (0.60338) +2025-08-22,07:11:45 | INFO | Train Epoch: 4 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.61428 (0.58822) Boundary_loss: 0.014999 (0.015225) Loss: 0.62928 (0.60345) +2025-08-22,07:12:42 | INFO | Train Epoch: 4 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.54588 (0.58812) Boundary_loss: 0.015149 (0.015225) Loss: 0.56103 (0.60334) +2025-08-22,07:13:39 | INFO | Train Epoch: 4 [20582912/26365952 (78%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.56871 (0.58807) Boundary_loss: 0.015229 (0.015225) Loss: 0.58393 (0.60330) +2025-08-22,07:14:36 | INFO | Train Epoch: 4 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.48357 (0.58781) Boundary_loss: 0.015214 (0.015225) Loss: 0.49878 (0.60304) +2025-08-22,07:15:33 | INFO | Train Epoch: 4 [20685312/26365952 (78%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.59404 (0.58783) Boundary_loss: 0.015186 (0.015225) Loss: 0.60923 (0.60305) +2025-08-22,07:16:30 | INFO | Train Epoch: 4 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.60882 (0.58788) Boundary_loss: 0.015148 (0.015225) Loss: 0.62397 (0.60310) +2025-08-22,07:17:27 | INFO | Train Epoch: 4 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.59655 (0.58790) Boundary_loss: 0.015135 (0.015225) Loss: 0.61169 (0.60312) +2025-08-22,07:18:24 | INFO | Train Epoch: 4 [20838912/26365952 (79%)] Avg Boundaries (per batch): 49.695 Boundary Ratio: 0.254 Contrastive_loss: 0.66486 (0.58809) Boundary_loss: 0.015320 (0.015225) Loss: 0.68018 (0.60331) +2025-08-22,07:19:21 | INFO | Train Epoch: 4 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.53747 (0.58797) Boundary_loss: 0.015081 (0.015224) Loss: 0.55255 (0.60319) +2025-08-22,07:20:18 | INFO | Train Epoch: 4 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.54180 (0.58785) Boundary_loss: 0.015089 (0.015224) Loss: 0.55689 (0.60308) +2025-08-22,07:21:15 | INFO | Train Epoch: 4 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.51220 (0.58767) Boundary_loss: 0.015091 (0.015224) Loss: 0.52729 (0.60289) +2025-08-22,07:22:11 | INFO | Train Epoch: 4 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.457 Boundary Ratio: 0.247 Contrastive_loss: 0.59386 (0.58768) Boundary_loss: 0.015222 (0.015224) Loss: 0.60908 (0.60291) +2025-08-22,07:23:08 | INFO | Train Epoch: 4 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.50690 (0.58749) Boundary_loss: 0.015266 (0.015224) Loss: 0.52217 (0.60271) +2025-08-22,07:24:05 | INFO | Train Epoch: 4 [21146112/26365952 (80%)] Avg Boundaries (per batch): 49.309 Boundary Ratio: 0.252 Contrastive_loss: 0.50993 (0.58730) Boundary_loss: 0.015241 (0.015224) Loss: 0.52517 (0.60252) +2025-08-22,07:25:02 | INFO | Train Epoch: 4 [21197312/26365952 (80%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 0.49417 (0.58708) Boundary_loss: 0.015242 (0.015224) Loss: 0.50941 (0.60230) +2025-08-22,07:25:59 | INFO | Train Epoch: 4 [21248512/26365952 (81%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.48170 (0.58682) Boundary_loss: 0.015124 (0.015224) Loss: 0.49682 (0.60205) +2025-08-22,07:26:55 | INFO | Train Epoch: 4 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.059 Boundary Ratio: 0.245 Contrastive_loss: 0.51240 (0.58664) Boundary_loss: 0.015139 (0.015223) Loss: 0.52754 (0.60187) +2025-08-22,07:27:52 | INFO | Train Epoch: 4 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.53144 (0.58651) Boundary_loss: 0.015188 (0.015223) Loss: 0.54663 (0.60174) +2025-08-22,07:28:49 | INFO | Train Epoch: 4 [21402112/26365952 (81%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 0.62703 (0.58661) Boundary_loss: 0.015105 (0.015223) Loss: 0.64213 (0.60183) +2025-08-22,07:29:46 | INFO | Train Epoch: 4 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.50981 (0.58643) Boundary_loss: 0.015129 (0.015223) Loss: 0.52494 (0.60165) +2025-08-22,07:30:43 | INFO | Train Epoch: 4 [21504512/26365952 (82%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.70827 (0.58672) Boundary_loss: 0.015105 (0.015223) Loss: 0.72338 (0.60194) +2025-08-22,07:31:40 | INFO | Train Epoch: 4 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.56437 (0.58666) Boundary_loss: 0.015041 (0.015222) Loss: 0.57941 (0.60188) +2025-08-22,07:32:36 | INFO | Train Epoch: 4 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.338 Boundary Ratio: 0.247 Contrastive_loss: 0.58908 (0.58667) Boundary_loss: 0.015129 (0.015222) Loss: 0.60421 (0.60189) +2025-08-22,07:33:33 | INFO | Train Epoch: 4 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 0.55123 (0.58658) Boundary_loss: 0.015220 (0.015222) Loss: 0.56645 (0.60181) +2025-08-22,07:34:30 | INFO | Train Epoch: 4 [21709312/26365952 (82%)] Avg Boundaries (per batch): 49.199 Boundary Ratio: 0.251 Contrastive_loss: 0.51957 (0.58643) Boundary_loss: 0.015285 (0.015222) Loss: 0.53485 (0.60165) +2025-08-22,07:35:27 | INFO | Train Epoch: 4 [21760512/26365952 (83%)] Avg Boundaries (per batch): 49.314 Boundary Ratio: 0.252 Contrastive_loss: 0.66395 (0.58661) Boundary_loss: 0.015363 (0.015222) Loss: 0.67931 (0.60183) +2025-08-22,07:36:24 | INFO | Train Epoch: 4 [21811712/26365952 (83%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.51188 (0.58643) Boundary_loss: 0.015125 (0.015222) Loss: 0.52701 (0.60166) +2025-08-22,07:37:21 | INFO | Train Epoch: 4 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.62654 (0.58653) Boundary_loss: 0.015178 (0.015222) Loss: 0.64171 (0.60175) +2025-08-22,07:38:17 | INFO | Train Epoch: 4 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.52186 (0.58638) Boundary_loss: 0.015357 (0.015222) Loss: 0.53722 (0.60160) +2025-08-22,07:39:14 | INFO | Train Epoch: 4 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.572 Boundary Ratio: 0.253 Contrastive_loss: 0.54368 (0.58628) Boundary_loss: 0.015346 (0.015223) Loss: 0.55902 (0.60150) +2025-08-22,07:40:11 | INFO | Train Epoch: 4 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.45941 (0.58598) Boundary_loss: 0.015098 (0.015222) Loss: 0.47450 (0.60121) +2025-08-22,07:41:08 | INFO | Train Epoch: 4 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.246 Boundary Ratio: 0.246 Contrastive_loss: 0.59645 (0.58601) Boundary_loss: 0.015185 (0.015222) Loss: 0.61164 (0.60123) +2025-08-22,07:42:05 | INFO | Train Epoch: 4 [22118912/26365952 (84%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 0.56545 (0.58596) Boundary_loss: 0.015288 (0.015222) Loss: 0.58074 (0.60118) +2025-08-22,07:43:02 | INFO | Train Epoch: 4 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.54871 (0.58587) Boundary_loss: 0.015259 (0.015223) Loss: 0.56397 (0.60110) +2025-08-22,07:43:59 | INFO | Train Epoch: 4 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.52682 (0.58574) Boundary_loss: 0.015090 (0.015222) Loss: 0.54191 (0.60096) +2025-08-22,07:44:56 | INFO | Train Epoch: 4 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.199 Boundary Ratio: 0.251 Contrastive_loss: 0.48163 (0.58550) Boundary_loss: 0.015152 (0.015222) Loss: 0.49678 (0.60072) +2025-08-22,07:45:52 | INFO | Train Epoch: 4 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.338 Boundary Ratio: 0.247 Contrastive_loss: 0.54965 (0.58542) Boundary_loss: 0.015210 (0.015222) Loss: 0.56486 (0.60064) +2025-08-22,07:46:49 | INFO | Train Epoch: 4 [22374912/26365952 (85%)] Avg Boundaries (per batch): 49.900 Boundary Ratio: 0.255 Contrastive_loss: 0.58088 (0.58541) Boundary_loss: 0.015386 (0.015222) Loss: 0.59626 (0.60063) +2025-08-22,07:47:46 | INFO | Train Epoch: 4 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.322 Boundary Ratio: 0.247 Contrastive_loss: 0.67412 (0.58561) Boundary_loss: 0.015202 (0.015222) Loss: 0.68932 (0.60083) +2025-08-22,07:48:43 | INFO | Train Epoch: 4 [22477312/26365952 (85%)] Avg Boundaries (per batch): 47.953 Boundary Ratio: 0.245 Contrastive_loss: 0.56412 (0.58556) Boundary_loss: 0.015256 (0.015222) Loss: 0.57937 (0.60078) +2025-08-22,07:49:40 | INFO | Train Epoch: 4 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.463 Boundary Ratio: 0.252 Contrastive_loss: 0.60928 (0.58561) Boundary_loss: 0.015196 (0.015222) Loss: 0.62448 (0.60084) +2025-08-22,07:50:37 | INFO | Train Epoch: 4 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.61414 (0.58568) Boundary_loss: 0.015244 (0.015222) Loss: 0.62938 (0.60090) +2025-08-22,07:51:34 | INFO | Train Epoch: 4 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.148 Boundary Ratio: 0.251 Contrastive_loss: 0.62668 (0.58577) Boundary_loss: 0.015094 (0.015222) Loss: 0.64177 (0.60099) +2025-08-22,07:52:31 | INFO | Train Epoch: 4 [22682112/26365952 (86%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.60762 (0.58582) Boundary_loss: 0.015117 (0.015222) Loss: 0.62273 (0.60104) +2025-08-22,07:53:27 | INFO | Train Epoch: 4 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.479 Boundary Ratio: 0.252 Contrastive_loss: 0.57942 (0.58581) Boundary_loss: 0.015300 (0.015222) Loss: 0.59472 (0.60103) +2025-08-22,07:54:24 | INFO | Train Epoch: 4 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.57268 (0.58578) Boundary_loss: 0.015058 (0.015222) Loss: 0.58774 (0.60100) +2025-08-22,07:55:21 | INFO | Train Epoch: 4 [22835712/26365952 (87%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 0.58668 (0.58578) Boundary_loss: 0.015273 (0.015222) Loss: 0.60196 (0.60100) +2025-08-22,07:56:18 | INFO | Train Epoch: 4 [22886912/26365952 (87%)] Avg Boundaries (per batch): 49.682 Boundary Ratio: 0.253 Contrastive_loss: 0.54520 (0.58569) Boundary_loss: 0.015148 (0.015222) Loss: 0.56034 (0.60091) +2025-08-22,07:57:15 | INFO | Train Epoch: 4 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.65296 (0.58584) Boundary_loss: 0.015116 (0.015221) Loss: 0.66808 (0.60106) +2025-08-22,07:58:12 | INFO | Train Epoch: 4 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.60960 (0.58589) Boundary_loss: 0.015087 (0.015221) Loss: 0.62469 (0.60111) +2025-08-22,07:59:09 | INFO | Train Epoch: 4 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.50710 (0.58572) Boundary_loss: 0.015223 (0.015221) Loss: 0.52233 (0.60094) +2025-08-22,08:00:05 | INFO | Train Epoch: 4 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.56230 (0.58566) Boundary_loss: 0.015351 (0.015221) Loss: 0.57765 (0.60089) +2025-08-22,08:01:02 | INFO | Train Epoch: 4 [23142912/26365952 (88%)] Avg Boundaries (per batch): 49.459 Boundary Ratio: 0.252 Contrastive_loss: 0.41455 (0.58529) Boundary_loss: 0.015227 (0.015221) Loss: 0.42978 (0.60051) +2025-08-22,08:01:59 | INFO | Train Epoch: 4 [23194112/26365952 (88%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.60169 (0.58532) Boundary_loss: 0.015294 (0.015222) Loss: 0.61698 (0.60054) +2025-08-22,08:02:56 | INFO | Train Epoch: 4 [23245312/26365952 (88%)] Avg Boundaries (per batch): 50.109 Boundary Ratio: 0.256 Contrastive_loss: 0.70673 (0.58559) Boundary_loss: 0.015496 (0.015222) Loss: 0.72223 (0.60081) +2025-08-22,08:03:53 | INFO | Train Epoch: 4 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.363 Boundary Ratio: 0.247 Contrastive_loss: 0.45807 (0.58531) Boundary_loss: 0.015336 (0.015222) Loss: 0.47340 (0.60053) +2025-08-22,08:04:50 | INFO | Train Epoch: 4 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.72736 (0.58562) Boundary_loss: 0.015324 (0.015223) Loss: 0.74268 (0.60084) +2025-08-22,08:05:47 | INFO | Train Epoch: 4 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.63977 (0.58574) Boundary_loss: 0.015159 (0.015223) Loss: 0.65493 (0.60096) +2025-08-22,08:06:43 | INFO | Train Epoch: 4 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.44029 (0.58542) Boundary_loss: 0.015118 (0.015222) Loss: 0.45541 (0.60064) +2025-08-22,08:07:40 | INFO | Train Epoch: 4 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.56704 (0.58538) Boundary_loss: 0.015146 (0.015222) Loss: 0.58219 (0.60060) +2025-08-22,08:08:37 | INFO | Train Epoch: 4 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.307 Boundary Ratio: 0.246 Contrastive_loss: 0.52278 (0.58525) Boundary_loss: 0.015131 (0.015222) Loss: 0.53791 (0.60047) +2025-08-22,08:09:34 | INFO | Train Epoch: 4 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.45411 (0.58496) Boundary_loss: 0.015208 (0.015222) Loss: 0.46932 (0.60018) +2025-08-22,08:10:30 | INFO | Train Epoch: 4 [23654912/26365952 (90%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.52200 (0.58483) Boundary_loss: 0.015279 (0.015222) Loss: 0.53728 (0.60005) +2025-08-22,08:11:27 | INFO | Train Epoch: 4 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.60437 (0.58487) Boundary_loss: 0.015233 (0.015222) Loss: 0.61961 (0.60009) +2025-08-22,08:12:24 | INFO | Train Epoch: 4 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.50862 (0.58470) Boundary_loss: 0.015203 (0.015222) Loss: 0.52382 (0.59993) +2025-08-22,08:13:21 | INFO | Train Epoch: 4 [23808512/26365952 (90%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.62666 (0.58479) Boundary_loss: 0.015023 (0.015222) Loss: 0.64168 (0.60002) +2025-08-22,08:14:18 | INFO | Train Epoch: 4 [23859712/26365952 (90%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.51340 (0.58464) Boundary_loss: 0.015253 (0.015222) Loss: 0.52866 (0.59986) +2025-08-22,08:15:15 | INFO | Train Epoch: 4 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.65936 (0.58480) Boundary_loss: 0.015213 (0.015222) Loss: 0.67457 (0.60002) +2025-08-22,08:16:11 | INFO | Train Epoch: 4 [23962112/26365952 (91%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 0.54980 (0.58473) Boundary_loss: 0.015164 (0.015222) Loss: 0.56497 (0.59995) +2025-08-22,08:17:08 | INFO | Train Epoch: 4 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.55683 (0.58467) Boundary_loss: 0.015221 (0.015222) Loss: 0.57205 (0.59989) +2025-08-22,08:18:05 | INFO | Train Epoch: 4 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 0.59931 (0.58470) Boundary_loss: 0.015342 (0.015222) Loss: 0.61465 (0.59992) +2025-08-22,08:19:02 | INFO | Train Epoch: 4 [24115712/26365952 (91%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.59785 (0.58473) Boundary_loss: 0.015138 (0.015222) Loss: 0.61299 (0.59995) +2025-08-22,08:19:59 | INFO | Train Epoch: 4 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.64131 (0.58485) Boundary_loss: 0.015241 (0.015222) Loss: 0.65655 (0.60007) +2025-08-22,08:20:56 | INFO | Train Epoch: 4 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 0.56036 (0.58479) Boundary_loss: 0.015286 (0.015222) Loss: 0.57565 (0.60002) +2025-08-22,08:21:53 | INFO | Train Epoch: 4 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.60695 (0.58484) Boundary_loss: 0.015059 (0.015221) Loss: 0.62201 (0.60006) +2025-08-22,08:22:50 | INFO | Train Epoch: 4 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.63345 (0.58494) Boundary_loss: 0.015176 (0.015221) Loss: 0.64862 (0.60016) +2025-08-22,08:23:47 | INFO | Train Epoch: 4 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.61306 (0.58500) Boundary_loss: 0.015048 (0.015221) Loss: 0.62811 (0.60022) +2025-08-22,08:24:44 | INFO | Train Epoch: 4 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.56721 (0.58496) Boundary_loss: 0.015178 (0.015221) Loss: 0.58239 (0.60019) +2025-08-22,08:25:41 | INFO | Train Epoch: 4 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.55096 (0.58489) Boundary_loss: 0.015245 (0.015221) Loss: 0.56620 (0.60011) +2025-08-22,08:26:38 | INFO | Train Epoch: 4 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.64195 (0.58501) Boundary_loss: 0.015275 (0.015221) Loss: 0.65723 (0.60023) +2025-08-22,08:27:35 | INFO | Train Epoch: 4 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.52824 (0.58489) Boundary_loss: 0.015158 (0.015221) Loss: 0.54340 (0.60012) +2025-08-22,08:28:32 | INFO | Train Epoch: 4 [24627712/26365952 (93%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.53209 (0.58479) Boundary_loss: 0.015128 (0.015221) Loss: 0.54722 (0.60001) +2025-08-22,08:29:29 | INFO | Train Epoch: 4 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.61960 (0.58486) Boundary_loss: 0.015096 (0.015220) Loss: 0.63469 (0.60008) +2025-08-22,08:30:25 | INFO | Train Epoch: 4 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.71033 (0.58512) Boundary_loss: 0.015291 (0.015221) Loss: 0.72562 (0.60034) +2025-08-22,08:31:22 | INFO | Train Epoch: 4 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.54144 (0.58503) Boundary_loss: 0.015292 (0.015221) Loss: 0.55673 (0.60025) +2025-08-22,08:32:19 | INFO | Train Epoch: 4 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.62709 (0.58511) Boundary_loss: 0.015169 (0.015221) Loss: 0.64226 (0.60033) +2025-08-22,08:33:16 | INFO | Train Epoch: 4 [24883712/26365952 (94%)] Avg Boundaries (per batch): 49.617 Boundary Ratio: 0.253 Contrastive_loss: 0.53351 (0.58501) Boundary_loss: 0.015169 (0.015221) Loss: 0.54868 (0.60023) +2025-08-22,08:34:13 | INFO | Train Epoch: 4 [24934912/26365952 (95%)] Avg Boundaries (per batch): 49.414 Boundary Ratio: 0.252 Contrastive_loss: 0.54296 (0.58492) Boundary_loss: 0.015160 (0.015220) Loss: 0.55812 (0.60014) +2025-08-22,08:35:10 | INFO | Train Epoch: 4 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.127 Boundary Ratio: 0.246 Contrastive_loss: 0.52965 (0.58481) Boundary_loss: 0.015136 (0.015220) Loss: 0.54478 (0.60003) +2025-08-22,08:36:07 | INFO | Train Epoch: 4 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.57062 (0.58478) Boundary_loss: 0.015264 (0.015220) Loss: 0.58588 (0.60000) +2025-08-22,08:37:04 | INFO | Train Epoch: 4 [25088512/26365952 (95%)] Avg Boundaries (per batch): 47.584 Boundary Ratio: 0.243 Contrastive_loss: 0.52521 (0.58466) Boundary_loss: 0.015376 (0.015221) Loss: 0.54058 (0.59988) +2025-08-22,08:38:01 | INFO | Train Epoch: 4 [25139712/26365952 (95%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.59838 (0.58469) Boundary_loss: 0.015203 (0.015221) Loss: 0.61358 (0.59991) +2025-08-22,08:38:58 | INFO | Train Epoch: 4 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.57550 (0.58467) Boundary_loss: 0.015173 (0.015221) Loss: 0.59067 (0.59989) +2025-08-22,08:39:54 | INFO | Train Epoch: 4 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.46875 (0.58443) Boundary_loss: 0.015242 (0.015221) Loss: 0.48399 (0.59965) +2025-08-22,08:40:51 | INFO | Train Epoch: 4 [25293312/26365952 (96%)] Avg Boundaries (per batch): 49.260 Boundary Ratio: 0.251 Contrastive_loss: 0.56609 (0.58440) Boundary_loss: 0.015194 (0.015221) Loss: 0.58129 (0.59962) +2025-08-22,08:41:48 | INFO | Train Epoch: 4 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.451 Boundary Ratio: 0.252 Contrastive_loss: 0.50534 (0.58424) Boundary_loss: 0.015242 (0.015221) Loss: 0.52058 (0.59946) +2025-08-22,08:42:45 | INFO | Train Epoch: 4 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.859 Boundary Ratio: 0.254 Contrastive_loss: 0.61778 (0.58430) Boundary_loss: 0.015214 (0.015221) Loss: 0.63300 (0.59952) +2025-08-22,08:43:42 | INFO | Train Epoch: 4 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.66873 (0.58447) Boundary_loss: 0.015217 (0.015221) Loss: 0.68394 (0.59969) +2025-08-22,08:44:39 | INFO | Train Epoch: 4 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.49545 (0.58429) Boundary_loss: 0.015072 (0.015220) Loss: 0.51052 (0.59951) +2025-08-22,08:45:35 | INFO | Train Epoch: 4 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.57828 (0.58428) Boundary_loss: 0.015051 (0.015220) Loss: 0.59333 (0.59950) +2025-08-22,08:46:32 | INFO | Train Epoch: 4 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.44857 (0.58401) Boundary_loss: 0.015233 (0.015220) Loss: 0.46380 (0.59923) +2025-08-22,08:47:29 | INFO | Train Epoch: 4 [25651712/26365952 (97%)] Avg Boundaries (per batch): 47.877 Boundary Ratio: 0.244 Contrastive_loss: 0.57597 (0.58400) Boundary_loss: 0.015328 (0.015220) Loss: 0.59130 (0.59922) +2025-08-22,08:48:26 | INFO | Train Epoch: 4 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.59184 (0.58401) Boundary_loss: 0.015110 (0.015220) Loss: 0.60695 (0.59923) +2025-08-22,08:49:23 | INFO | Train Epoch: 4 [25754112/26365952 (98%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 0.56568 (0.58397) Boundary_loss: 0.015321 (0.015220) Loss: 0.58100 (0.59919) +2025-08-22,08:50:20 | INFO | Train Epoch: 4 [25805312/26365952 (98%)] Avg Boundaries (per batch): 47.740 Boundary Ratio: 0.244 Contrastive_loss: 0.59541 (0.58400) Boundary_loss: 0.015314 (0.015220) Loss: 0.61072 (0.59922) +2025-08-22,08:51:17 | INFO | Train Epoch: 4 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.52127 (0.58387) Boundary_loss: 0.015040 (0.015220) Loss: 0.53631 (0.59909) +2025-08-22,08:52:14 | INFO | Train Epoch: 4 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.46538 (0.58364) Boundary_loss: 0.015108 (0.015220) Loss: 0.48049 (0.59886) +2025-08-22,08:53:11 | INFO | Train Epoch: 4 [25958912/26365952 (98%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.54580 (0.58357) Boundary_loss: 0.015182 (0.015220) Loss: 0.56098 (0.59878) +2025-08-22,08:54:08 | INFO | Train Epoch: 4 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.57399 (0.58355) Boundary_loss: 0.015037 (0.015219) Loss: 0.58903 (0.59877) +2025-08-22,08:55:04 | INFO | Train Epoch: 4 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.47321 (0.58333) Boundary_loss: 0.015099 (0.015219) Loss: 0.48831 (0.59855) +2025-08-22,08:56:01 | INFO | Train Epoch: 4 [26112512/26365952 (99%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.53659 (0.58324) Boundary_loss: 0.015078 (0.015219) Loss: 0.55166 (0.59846) +2025-08-22,08:56:58 | INFO | Train Epoch: 4 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.365 Boundary Ratio: 0.247 Contrastive_loss: 0.59604 (0.58326) Boundary_loss: 0.015260 (0.015219) Loss: 0.61130 (0.59848) +2025-08-22,08:57:55 | INFO | Train Epoch: 4 [26214912/26365952 (99%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.60704 (0.58331) Boundary_loss: 0.015195 (0.015219) Loss: 0.62224 (0.59853) +2025-08-22,08:58:52 | INFO | Train Epoch: 4 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.50807 (0.58316) Boundary_loss: 0.015060 (0.015219) Loss: 0.52313 (0.59838) +2025-08-22,08:59:49 | INFO | Train Epoch: 4 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.45901 (0.58292) Boundary_loss: 0.015324 (0.015219) Loss: 0.47433 (0.59814) +2025-08-22,09:00:43 | INFO | Train Epoch: 4 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.434 Boundary Ratio: 0.247 Contrastive_loss: 0.55370 (0.58287) Boundary_loss: 0.015099 (0.015219) Loss: 0.56879 (0.59808) +2025-08-22,09:00:43 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-22,09:00:43 | INFO | [Epoch 4] Average Step Time: 0.572s | Average GPU Memory: 31.9 GB +2025-08-22,09:00:43 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-22,09:00:43 | INFO | Starting zero-shot imagenet. +2025-08-22,09:00:43 | INFO | Building zero-shot classifier +2025-08-22,09:00:52 | INFO | Using classifier +2025-08-22,09:01:38 | INFO | Finished zero-shot imagenet. +2025-08-22,09:01:38 | INFO | Eval Epoch: 5 imagenet-zeroshot-val-top1: 0.2402 imagenet-zeroshot-val-top5: 0.4850 +2025-08-22,09:01:39 | INFO | Start epoch 5 +2025-08-22,09:01:42 | INFO | Train Epoch: 5 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.56232 (0.56232) Boundary_loss: 0.015170 (0.015170) Loss: 0.57749 (0.57749) +2025-08-22,09:02:38 | INFO | Train Epoch: 5 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.016 Boundary Ratio: 0.245 Contrastive_loss: 0.52392 (0.54312) Boundary_loss: 0.014993 (0.015082) Loss: 0.53891 (0.55820) +2025-08-22,09:03:35 | INFO | Train Epoch: 5 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.46859 (0.51828) Boundary_loss: 0.015364 (0.015176) Loss: 0.48396 (0.53346) +2025-08-22,09:04:32 | INFO | Train Epoch: 5 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.50636 (0.51530) Boundary_loss: 0.015114 (0.015161) Loss: 0.52147 (0.53046) +2025-08-22,09:05:29 | INFO | Train Epoch: 5 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 49.445 Boundary Ratio: 0.252 Contrastive_loss: 0.56795 (0.52583) Boundary_loss: 0.015173 (0.015163) Loss: 0.58312 (0.54099) +2025-08-22,09:06:25 | INFO | Train Epoch: 5 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.56944 (0.53310) Boundary_loss: 0.015203 (0.015170) Loss: 0.58464 (0.54827) +2025-08-22,09:07:22 | INFO | Train Epoch: 5 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.44158 (0.52002) Boundary_loss: 0.015155 (0.015168) Loss: 0.45674 (0.53519) +2025-08-22,09:08:19 | INFO | Train Epoch: 5 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.59947 (0.52996) Boundary_loss: 0.015033 (0.015151) Loss: 0.61451 (0.54511) +2025-08-22,09:09:16 | INFO | Train Epoch: 5 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.113 Boundary Ratio: 0.245 Contrastive_loss: 0.48680 (0.52516) Boundary_loss: 0.015282 (0.015165) Loss: 0.50208 (0.54033) +2025-08-22,09:10:13 | INFO | Train Epoch: 5 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.49519 (0.52216) Boundary_loss: 0.015278 (0.015177) Loss: 0.51047 (0.53734) +2025-08-22,09:11:09 | INFO | Train Epoch: 5 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.56517 (0.52607) Boundary_loss: 0.015175 (0.015176) Loss: 0.58034 (0.54125) +2025-08-22,09:12:06 | INFO | Train Epoch: 5 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 47.969 Boundary Ratio: 0.245 Contrastive_loss: 0.56252 (0.52911) Boundary_loss: 0.015312 (0.015188) Loss: 0.57783 (0.54430) +2025-08-22,09:13:03 | INFO | Train Epoch: 5 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.59543 (0.53421) Boundary_loss: 0.015183 (0.015187) Loss: 0.61061 (0.54940) +2025-08-22,09:14:00 | INFO | Train Epoch: 5 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.47443 (0.52994) Boundary_loss: 0.015139 (0.015184) Loss: 0.48956 (0.54513) +2025-08-22,09:14:56 | INFO | Train Epoch: 5 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 0.56977 (0.53260) Boundary_loss: 0.015112 (0.015179) Loss: 0.58488 (0.54778) +2025-08-22,09:15:53 | INFO | Train Epoch: 5 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.49861 (0.53047) Boundary_loss: 0.015313 (0.015187) Loss: 0.51392 (0.54566) +2025-08-22,09:16:50 | INFO | Train Epoch: 5 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 49.148 Boundary Ratio: 0.251 Contrastive_loss: 0.52378 (0.53008) Boundary_loss: 0.015084 (0.015181) Loss: 0.53886 (0.54526) +2025-08-22,09:17:47 | INFO | Train Epoch: 5 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.45099 (0.52568) Boundary_loss: 0.015230 (0.015184) Loss: 0.46622 (0.54087) +2025-08-22,09:18:44 | INFO | Train Epoch: 5 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 0.57730 (0.52840) Boundary_loss: 0.015160 (0.015183) Loss: 0.59246 (0.54358) +2025-08-22,09:19:41 | INFO | Train Epoch: 5 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 0.53340 (0.52865) Boundary_loss: 0.015139 (0.015181) Loss: 0.54854 (0.54383) +2025-08-22,09:20:38 | INFO | Train Epoch: 5 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 0.43792 (0.52433) Boundary_loss: 0.015258 (0.015184) Loss: 0.45317 (0.53951) +2025-08-22,09:21:34 | INFO | Train Epoch: 5 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.57028 (0.52642) Boundary_loss: 0.015423 (0.015195) Loss: 0.58570 (0.54161) +2025-08-22,09:22:31 | INFO | Train Epoch: 5 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.43409 (0.52240) Boundary_loss: 0.015224 (0.015196) Loss: 0.44931 (0.53760) +2025-08-22,09:23:28 | INFO | Train Epoch: 5 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 0.59351 (0.52537) Boundary_loss: 0.015244 (0.015198) Loss: 0.60875 (0.54057) +2025-08-22,09:24:25 | INFO | Train Epoch: 5 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.361 Boundary Ratio: 0.247 Contrastive_loss: 0.57268 (0.52726) Boundary_loss: 0.015158 (0.015197) Loss: 0.58784 (0.54246) +2025-08-22,09:25:22 | INFO | Train Epoch: 5 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 49.297 Boundary Ratio: 0.252 Contrastive_loss: 0.48033 (0.52546) Boundary_loss: 0.015072 (0.015192) Loss: 0.49540 (0.54065) +2025-08-22,09:26:19 | INFO | Train Epoch: 5 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.48497 (0.52396) Boundary_loss: 0.015149 (0.015190) Loss: 0.50012 (0.53915) +2025-08-22,09:27:15 | INFO | Train Epoch: 5 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.48730 (0.52265) Boundary_loss: 0.015177 (0.015190) Loss: 0.50248 (0.53784) +2025-08-22,09:28:12 | INFO | Train Epoch: 5 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.55901 (0.52390) Boundary_loss: 0.015203 (0.015190) Loss: 0.57421 (0.53909) +2025-08-22,09:29:09 | INFO | Train Epoch: 5 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.45575 (0.52163) Boundary_loss: 0.015164 (0.015189) Loss: 0.47091 (0.53682) +2025-08-22,09:30:06 | INFO | Train Epoch: 5 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.51045 (0.52127) Boundary_loss: 0.015192 (0.015190) Loss: 0.52564 (0.53646) +2025-08-22,09:31:03 | INFO | Train Epoch: 5 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.51374 (0.52103) Boundary_loss: 0.015209 (0.015190) Loss: 0.52895 (0.53622) +2025-08-22,09:32:00 | INFO | Train Epoch: 5 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.273 Boundary Ratio: 0.246 Contrastive_loss: 0.50371 (0.52051) Boundary_loss: 0.015166 (0.015189) Loss: 0.51888 (0.53570) +2025-08-22,09:32:57 | INFO | Train Epoch: 5 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.52377 (0.52060) Boundary_loss: 0.015216 (0.015190) Loss: 0.53899 (0.53579) +2025-08-22,09:33:54 | INFO | Train Epoch: 5 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.51369 (0.52041) Boundary_loss: 0.015162 (0.015189) Loss: 0.52885 (0.53560) +2025-08-22,09:34:51 | INFO | Train Epoch: 5 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.62059 (0.52319) Boundary_loss: 0.015199 (0.015190) Loss: 0.63579 (0.53838) +2025-08-22,09:35:48 | INFO | Train Epoch: 5 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 47.377 Boundary Ratio: 0.242 Contrastive_loss: 0.60948 (0.52552) Boundary_loss: 0.015195 (0.015190) Loss: 0.62468 (0.54071) +2025-08-22,09:36:44 | INFO | Train Epoch: 5 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 0.42983 (0.52300) Boundary_loss: 0.015153 (0.015189) Loss: 0.44498 (0.53819) +2025-08-22,09:37:41 | INFO | Train Epoch: 5 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.283 Boundary Ratio: 0.251 Contrastive_loss: 0.55255 (0.52376) Boundary_loss: 0.015305 (0.015192) Loss: 0.56786 (0.53895) +2025-08-22,09:38:38 | INFO | Train Epoch: 5 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.46490 (0.52229) Boundary_loss: 0.015262 (0.015194) Loss: 0.48016 (0.53748) +2025-08-22,09:39:34 | INFO | Train Epoch: 5 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.348 Boundary Ratio: 0.252 Contrastive_loss: 0.45071 (0.52054) Boundary_loss: 0.015221 (0.015194) Loss: 0.46593 (0.53574) +2025-08-22,09:40:31 | INFO | Train Epoch: 5 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.48447 (0.51968) Boundary_loss: 0.015212 (0.015195) Loss: 0.49968 (0.53488) +2025-08-22,09:41:28 | INFO | Train Epoch: 5 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.314 Boundary Ratio: 0.247 Contrastive_loss: 0.46746 (0.51847) Boundary_loss: 0.015032 (0.015191) Loss: 0.48249 (0.53366) +2025-08-22,09:42:25 | INFO | Train Epoch: 5 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.48210 (0.51764) Boundary_loss: 0.015263 (0.015193) Loss: 0.49736 (0.53284) +2025-08-22,09:43:22 | INFO | Train Epoch: 5 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.44245 (0.51597) Boundary_loss: 0.014932 (0.015187) Loss: 0.45739 (0.53116) +2025-08-22,09:44:19 | INFO | Train Epoch: 5 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.42921 (0.51409) Boundary_loss: 0.015155 (0.015186) Loss: 0.44436 (0.52927) +2025-08-22,09:45:16 | INFO | Train Epoch: 5 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 0.52222 (0.51426) Boundary_loss: 0.015295 (0.015188) Loss: 0.53751 (0.52945) +2025-08-22,09:46:13 | INFO | Train Epoch: 5 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.52913 (0.51457) Boundary_loss: 0.015208 (0.015189) Loss: 0.54434 (0.52976) +2025-08-22,09:47:09 | INFO | Train Epoch: 5 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.54241 (0.51514) Boundary_loss: 0.015107 (0.015187) Loss: 0.55751 (0.53032) +2025-08-22,09:48:07 | INFO | Train Epoch: 5 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.52076 (0.51525) Boundary_loss: 0.015187 (0.015187) Loss: 0.53595 (0.53044) +2025-08-22,09:49:03 | INFO | Train Epoch: 5 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.53986 (0.51573) Boundary_loss: 0.015094 (0.015185) Loss: 0.55496 (0.53092) +2025-08-22,09:50:00 | INFO | Train Epoch: 5 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.48950 (0.51523) Boundary_loss: 0.015060 (0.015183) Loss: 0.50456 (0.53041) +2025-08-22,09:50:57 | INFO | Train Epoch: 5 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 49.258 Boundary Ratio: 0.251 Contrastive_loss: 0.46928 (0.51436) Boundary_loss: 0.015075 (0.015181) Loss: 0.48435 (0.52954) +2025-08-22,09:51:54 | INFO | Train Epoch: 5 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.48108 (0.51374) Boundary_loss: 0.015107 (0.015179) Loss: 0.49619 (0.52892) +2025-08-22,09:52:50 | INFO | Train Epoch: 5 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 49.484 Boundary Ratio: 0.252 Contrastive_loss: 0.47327 (0.51301) Boundary_loss: 0.015270 (0.015181) Loss: 0.48854 (0.52819) +2025-08-22,09:53:47 | INFO | Train Epoch: 5 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.51259 (0.51300) Boundary_loss: 0.015074 (0.015179) Loss: 0.52766 (0.52818) +2025-08-22,09:54:44 | INFO | Train Epoch: 5 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.51234 (0.51299) Boundary_loss: 0.015224 (0.015180) Loss: 0.52756 (0.52817) +2025-08-22,09:55:41 | INFO | Train Epoch: 5 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.53182 (0.51331) Boundary_loss: 0.015222 (0.015181) Loss: 0.54704 (0.52850) +2025-08-22,09:56:38 | INFO | Train Epoch: 5 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.48775 (0.51288) Boundary_loss: 0.015200 (0.015181) Loss: 0.50295 (0.52806) +2025-08-22,09:57:34 | INFO | Train Epoch: 5 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.795 Boundary Ratio: 0.254 Contrastive_loss: 0.56535 (0.51376) Boundary_loss: 0.015315 (0.015183) Loss: 0.58067 (0.52894) +2025-08-22,09:58:31 | INFO | Train Epoch: 5 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.45581 (0.51281) Boundary_loss: 0.015168 (0.015183) Loss: 0.47097 (0.52799) +2025-08-22,09:59:28 | INFO | Train Epoch: 5 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 49.309 Boundary Ratio: 0.252 Contrastive_loss: 0.53482 (0.51316) Boundary_loss: 0.015182 (0.015183) Loss: 0.55001 (0.52834) +2025-08-22,10:00:25 | INFO | Train Epoch: 5 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 49.416 Boundary Ratio: 0.252 Contrastive_loss: 0.52611 (0.51337) Boundary_loss: 0.015245 (0.015184) Loss: 0.54135 (0.52855) +2025-08-22,10:01:22 | INFO | Train Epoch: 5 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.088 Boundary Ratio: 0.245 Contrastive_loss: 0.53660 (0.51373) Boundary_loss: 0.015173 (0.015184) Loss: 0.55177 (0.52891) +2025-08-22,10:02:19 | INFO | Train Epoch: 5 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 0.44904 (0.51273) Boundary_loss: 0.015047 (0.015182) Loss: 0.46408 (0.52792) +2025-08-22,10:03:15 | INFO | Train Epoch: 5 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.44776 (0.51175) Boundary_loss: 0.015148 (0.015181) Loss: 0.46291 (0.52693) +2025-08-22,10:04:12 | INFO | Train Epoch: 5 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.60078 (0.51308) Boundary_loss: 0.015042 (0.015179) Loss: 0.61582 (0.52826) +2025-08-22,10:05:09 | INFO | Train Epoch: 5 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.50791 (0.51300) Boundary_loss: 0.015241 (0.015180) Loss: 0.52315 (0.52818) +2025-08-22,10:06:06 | INFO | Train Epoch: 5 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.42590 (0.51174) Boundary_loss: 0.015201 (0.015180) Loss: 0.44110 (0.52692) +2025-08-22,10:07:02 | INFO | Train Epoch: 5 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 49.609 Boundary Ratio: 0.253 Contrastive_loss: 0.45150 (0.51088) Boundary_loss: 0.015275 (0.015182) Loss: 0.46678 (0.52606) +2025-08-22,10:07:59 | INFO | Train Epoch: 5 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.53338 (0.51120) Boundary_loss: 0.015228 (0.015182) Loss: 0.54861 (0.52638) +2025-08-22,10:08:56 | INFO | Train Epoch: 5 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.41758 (0.50990) Boundary_loss: 0.015186 (0.015182) Loss: 0.43277 (0.52508) +2025-08-22,10:09:53 | INFO | Train Epoch: 5 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.48027 (0.50949) Boundary_loss: 0.015089 (0.015181) Loss: 0.49536 (0.52467) +2025-08-22,10:10:50 | INFO | Train Epoch: 5 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.62614 (0.51107) Boundary_loss: 0.015315 (0.015183) Loss: 0.64145 (0.52625) +2025-08-22,10:11:47 | INFO | Train Epoch: 5 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.50241 (0.51095) Boundary_loss: 0.015231 (0.015184) Loss: 0.51764 (0.52613) +2025-08-22,10:12:44 | INFO | Train Epoch: 5 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 0.42197 (0.50978) Boundary_loss: 0.015337 (0.015186) Loss: 0.43731 (0.52497) +2025-08-22,10:13:40 | INFO | Train Epoch: 5 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 0.50424 (0.50971) Boundary_loss: 0.015197 (0.015186) Loss: 0.51943 (0.52489) +2025-08-22,10:14:37 | INFO | Train Epoch: 5 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 0.57152 (0.51050) Boundary_loss: 0.015222 (0.015186) Loss: 0.58674 (0.52569) +2025-08-22,10:15:34 | INFO | Train Epoch: 5 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 0.50743 (0.51046) Boundary_loss: 0.015253 (0.015187) Loss: 0.52268 (0.52565) +2025-08-22,10:16:31 | INFO | Train Epoch: 5 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.55766 (0.51105) Boundary_loss: 0.015114 (0.015186) Loss: 0.57277 (0.52624) +2025-08-22,10:17:28 | INFO | Train Epoch: 5 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 47.961 Boundary Ratio: 0.245 Contrastive_loss: 0.50562 (0.51099) Boundary_loss: 0.015209 (0.015186) Loss: 0.52083 (0.52617) +2025-08-22,10:18:24 | INFO | Train Epoch: 5 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.486 Boundary Ratio: 0.252 Contrastive_loss: 0.52500 (0.51116) Boundary_loss: 0.015033 (0.015185) Loss: 0.54003 (0.52634) +2025-08-22,10:19:21 | INFO | Train Epoch: 5 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 49.729 Boundary Ratio: 0.254 Contrastive_loss: 0.47724 (0.51075) Boundary_loss: 0.015214 (0.015185) Loss: 0.49245 (0.52593) +2025-08-22,10:20:18 | INFO | Train Epoch: 5 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.225 Boundary Ratio: 0.246 Contrastive_loss: 0.46705 (0.51023) Boundary_loss: 0.015133 (0.015184) Loss: 0.48219 (0.52541) +2025-08-22,10:21:15 | INFO | Train Epoch: 5 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.54054 (0.51058) Boundary_loss: 0.015278 (0.015185) Loss: 0.55582 (0.52577) +2025-08-22,10:22:11 | INFO | Train Epoch: 5 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.45587 (0.50995) Boundary_loss: 0.015035 (0.015184) Loss: 0.47090 (0.52513) +2025-08-22,10:23:08 | INFO | Train Epoch: 5 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.47783 (0.50958) Boundary_loss: 0.015184 (0.015184) Loss: 0.49301 (0.52476) +2025-08-22,10:24:05 | INFO | Train Epoch: 5 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.55379 (0.51008) Boundary_loss: 0.015194 (0.015184) Loss: 0.56898 (0.52526) +2025-08-22,10:25:02 | INFO | Train Epoch: 5 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.54497 (0.51047) Boundary_loss: 0.015201 (0.015184) Loss: 0.56017 (0.52566) +2025-08-22,10:25:58 | INFO | Train Epoch: 5 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 0.50811 (0.51045) Boundary_loss: 0.015159 (0.015184) Loss: 0.52327 (0.52563) +2025-08-22,10:26:55 | INFO | Train Epoch: 5 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.48513 (0.51017) Boundary_loss: 0.015109 (0.015183) Loss: 0.50024 (0.52535) +2025-08-22,10:27:52 | INFO | Train Epoch: 5 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 0.53222 (0.51041) Boundary_loss: 0.015145 (0.015182) Loss: 0.54736 (0.52559) +2025-08-22,10:28:49 | INFO | Train Epoch: 5 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 0.49188 (0.51021) Boundary_loss: 0.015109 (0.015182) Loss: 0.50699 (0.52539) +2025-08-22,10:29:45 | INFO | Train Epoch: 5 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 0.44119 (0.50947) Boundary_loss: 0.015144 (0.015181) Loss: 0.45633 (0.52466) +2025-08-22,10:30:42 | INFO | Train Epoch: 5 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.44756 (0.50882) Boundary_loss: 0.015163 (0.015181) Loss: 0.46273 (0.52400) +2025-08-22,10:31:39 | INFO | Train Epoch: 5 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.43357 (0.50804) Boundary_loss: 0.015060 (0.015180) Loss: 0.44863 (0.52322) +2025-08-22,10:32:35 | INFO | Train Epoch: 5 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.48358 (0.50779) Boundary_loss: 0.015197 (0.015180) Loss: 0.49877 (0.52297) +2025-08-22,10:33:32 | INFO | Train Epoch: 5 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.125 Boundary Ratio: 0.246 Contrastive_loss: 0.44920 (0.50719) Boundary_loss: 0.015077 (0.015179) Loss: 0.46428 (0.52237) +2025-08-22,10:34:29 | INFO | Train Epoch: 5 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.59377 (0.50806) Boundary_loss: 0.015294 (0.015180) Loss: 0.60907 (0.52324) +2025-08-22,10:35:26 | INFO | Train Epoch: 5 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.182 Boundary Ratio: 0.246 Contrastive_loss: 0.55024 (0.50849) Boundary_loss: 0.015255 (0.015181) Loss: 0.56549 (0.52367) +2025-08-22,10:36:23 | INFO | Train Epoch: 5 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.56625 (0.50906) Boundary_loss: 0.015138 (0.015180) Loss: 0.58139 (0.52424) +2025-08-22,10:37:19 | INFO | Train Epoch: 5 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.54122 (0.50937) Boundary_loss: 0.015092 (0.015180) Loss: 0.55632 (0.52455) +2025-08-22,10:38:16 | INFO | Train Epoch: 5 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.48864 (0.50917) Boundary_loss: 0.015136 (0.015179) Loss: 0.50378 (0.52435) +2025-08-22,10:39:13 | INFO | Train Epoch: 5 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.58736 (0.50992) Boundary_loss: 0.015193 (0.015179) Loss: 0.60255 (0.52510) +2025-08-22,10:40:09 | INFO | Train Epoch: 5 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 47.818 Boundary Ratio: 0.244 Contrastive_loss: 0.43488 (0.50921) Boundary_loss: 0.015207 (0.015180) Loss: 0.45008 (0.52439) +2025-08-22,10:41:06 | INFO | Train Epoch: 5 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 49.355 Boundary Ratio: 0.252 Contrastive_loss: 0.51604 (0.50927) Boundary_loss: 0.015283 (0.015181) Loss: 0.53132 (0.52445) +2025-08-22,10:42:03 | INFO | Train Epoch: 5 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.285 Boundary Ratio: 0.246 Contrastive_loss: 0.53781 (0.50954) Boundary_loss: 0.015302 (0.015182) Loss: 0.55312 (0.52472) +2025-08-22,10:43:00 | INFO | Train Epoch: 5 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.48580 (0.50932) Boundary_loss: 0.015213 (0.015182) Loss: 0.50101 (0.52450) +2025-08-22,10:43:57 | INFO | Train Epoch: 5 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 49.475 Boundary Ratio: 0.252 Contrastive_loss: 0.50703 (0.50930) Boundary_loss: 0.015218 (0.015182) Loss: 0.52225 (0.52448) +2025-08-22,10:44:53 | INFO | Train Epoch: 5 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 49.389 Boundary Ratio: 0.252 Contrastive_loss: 0.63237 (0.51042) Boundary_loss: 0.015202 (0.015182) Loss: 0.64757 (0.52560) +2025-08-22,10:45:50 | INFO | Train Epoch: 5 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.57358 (0.51099) Boundary_loss: 0.015146 (0.015182) Loss: 0.58873 (0.52617) +2025-08-22,10:46:47 | INFO | Train Epoch: 5 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.63824 (0.51212) Boundary_loss: 0.015052 (0.015181) Loss: 0.65329 (0.52730) +2025-08-22,10:47:44 | INFO | Train Epoch: 5 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.64993 (0.51334) Boundary_loss: 0.015157 (0.015181) Loss: 0.66509 (0.52852) +2025-08-22,10:48:40 | INFO | Train Epoch: 5 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.63505 (0.51441) Boundary_loss: 0.015043 (0.015180) Loss: 0.65009 (0.52959) +2025-08-22,10:49:37 | INFO | Train Epoch: 5 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.45928 (0.51393) Boundary_loss: 0.015165 (0.015179) Loss: 0.47444 (0.52911) +2025-08-22,10:50:34 | INFO | Train Epoch: 5 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.49018 (0.51373) Boundary_loss: 0.015191 (0.015180) Loss: 0.50537 (0.52891) +2025-08-22,10:51:31 | INFO | Train Epoch: 5 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.58836 (0.51436) Boundary_loss: 0.015223 (0.015180) Loss: 0.60359 (0.52954) +2025-08-22,10:52:28 | INFO | Train Epoch: 5 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.55749 (0.51473) Boundary_loss: 0.015177 (0.015180) Loss: 0.57267 (0.52991) +2025-08-22,10:53:24 | INFO | Train Epoch: 5 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.56117 (0.51512) Boundary_loss: 0.015093 (0.015179) Loss: 0.57626 (0.53030) +2025-08-22,10:54:21 | INFO | Train Epoch: 5 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.44242 (0.51451) Boundary_loss: 0.015130 (0.015179) Loss: 0.45755 (0.52969) +2025-08-22,10:55:18 | INFO | Train Epoch: 5 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.021 Boundary Ratio: 0.245 Contrastive_loss: 0.49491 (0.51435) Boundary_loss: 0.015265 (0.015179) Loss: 0.51018 (0.52953) +2025-08-22,10:56:15 | INFO | Train Epoch: 5 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.52863 (0.51447) Boundary_loss: 0.015224 (0.015180) Loss: 0.54385 (0.52965) +2025-08-22,10:57:12 | INFO | Train Epoch: 5 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.44299 (0.51389) Boundary_loss: 0.015223 (0.015180) Loss: 0.45821 (0.52907) +2025-08-22,10:58:08 | INFO | Train Epoch: 5 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.47702 (0.51359) Boundary_loss: 0.015012 (0.015179) Loss: 0.49204 (0.52877) +2025-08-22,10:59:05 | INFO | Train Epoch: 5 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.50737 (0.51354) Boundary_loss: 0.015258 (0.015179) Loss: 0.52263 (0.52872) +2025-08-22,11:00:02 | INFO | Train Epoch: 5 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 0.49602 (0.51340) Boundary_loss: 0.015142 (0.015179) Loss: 0.51117 (0.52858) +2025-08-22,11:00:59 | INFO | Train Epoch: 5 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.45058 (0.51291) Boundary_loss: 0.015337 (0.015180) Loss: 0.46592 (0.52809) +2025-08-22,11:01:56 | INFO | Train Epoch: 5 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.48554 (0.51269) Boundary_loss: 0.014922 (0.015178) Loss: 0.50046 (0.52787) +2025-08-22,11:02:53 | INFO | Train Epoch: 5 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.39697 (0.51180) Boundary_loss: 0.015082 (0.015178) Loss: 0.41206 (0.52697) +2025-08-22,11:03:50 | INFO | Train Epoch: 5 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 0.48762 (0.51161) Boundary_loss: 0.015235 (0.015178) Loss: 0.50286 (0.52679) +2025-08-22,11:04:47 | INFO | Train Epoch: 5 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.51534 (0.51164) Boundary_loss: 0.015327 (0.015179) Loss: 0.53067 (0.52682) +2025-08-22,11:05:44 | INFO | Train Epoch: 5 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.55786 (0.51199) Boundary_loss: 0.015236 (0.015180) Loss: 0.57310 (0.52717) +2025-08-22,11:06:40 | INFO | Train Epoch: 5 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 47.326 Boundary Ratio: 0.241 Contrastive_loss: 0.37228 (0.51094) Boundary_loss: 0.015243 (0.015180) Loss: 0.38752 (0.52612) +2025-08-22,11:07:37 | INFO | Train Epoch: 5 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.51336 (0.51096) Boundary_loss: 0.015222 (0.015180) Loss: 0.52858 (0.52614) +2025-08-22,11:08:34 | INFO | Train Epoch: 5 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 49.705 Boundary Ratio: 0.254 Contrastive_loss: 0.45765 (0.51056) Boundary_loss: 0.015189 (0.015180) Loss: 0.47284 (0.52574) +2025-08-22,11:09:31 | INFO | Train Epoch: 5 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 0.42133 (0.50991) Boundary_loss: 0.015283 (0.015181) Loss: 0.43662 (0.52509) +2025-08-22,11:10:28 | INFO | Train Epoch: 5 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.59647 (0.51054) Boundary_loss: 0.015123 (0.015181) Loss: 0.61159 (0.52572) +2025-08-22,11:11:25 | INFO | Train Epoch: 5 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.57479 (0.51100) Boundary_loss: 0.015265 (0.015181) Loss: 0.59006 (0.52618) +2025-08-22,11:12:22 | INFO | Train Epoch: 5 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.57108 (0.51144) Boundary_loss: 0.015198 (0.015182) Loss: 0.58627 (0.52662) +2025-08-22,11:13:19 | INFO | Train Epoch: 5 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 47.832 Boundary Ratio: 0.244 Contrastive_loss: 0.44444 (0.51096) Boundary_loss: 0.015183 (0.015182) Loss: 0.45962 (0.52614) +2025-08-22,11:14:16 | INFO | Train Epoch: 5 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.516 Boundary Ratio: 0.248 Contrastive_loss: 0.46788 (0.51065) Boundary_loss: 0.015094 (0.015181) Loss: 0.48298 (0.52583) +2025-08-22,11:15:13 | INFO | Train Epoch: 5 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.45001 (0.51022) Boundary_loss: 0.015416 (0.015183) Loss: 0.46542 (0.52541) +2025-08-22,11:16:09 | INFO | Train Epoch: 5 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.47207 (0.50996) Boundary_loss: 0.015155 (0.015182) Loss: 0.48723 (0.52514) +2025-08-22,11:17:06 | INFO | Train Epoch: 5 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.779 Boundary Ratio: 0.254 Contrastive_loss: 0.49826 (0.50988) Boundary_loss: 0.015158 (0.015182) Loss: 0.51342 (0.52506) +2025-08-22,11:18:03 | INFO | Train Epoch: 5 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.44508 (0.50943) Boundary_loss: 0.015033 (0.015181) Loss: 0.46011 (0.52461) +2025-08-22,11:19:00 | INFO | Train Epoch: 5 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.904 Boundary Ratio: 0.255 Contrastive_loss: 0.49478 (0.50933) Boundary_loss: 0.015291 (0.015182) Loss: 0.51007 (0.52451) +2025-08-22,11:19:56 | INFO | Train Epoch: 5 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 0.51119 (0.50934) Boundary_loss: 0.015167 (0.015182) Loss: 0.52636 (0.52452) +2025-08-22,11:20:53 | INFO | Train Epoch: 5 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 49.428 Boundary Ratio: 0.252 Contrastive_loss: 0.45206 (0.50895) Boundary_loss: 0.015253 (0.015182) Loss: 0.46732 (0.52414) +2025-08-22,11:21:50 | INFO | Train Epoch: 5 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.287 Boundary Ratio: 0.246 Contrastive_loss: 0.48658 (0.50880) Boundary_loss: 0.015250 (0.015183) Loss: 0.50183 (0.52399) +2025-08-22,11:22:47 | INFO | Train Epoch: 5 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 0.48710 (0.50866) Boundary_loss: 0.015186 (0.015183) Loss: 0.50228 (0.52384) +2025-08-22,11:23:44 | INFO | Train Epoch: 5 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 0.40833 (0.50800) Boundary_loss: 0.015038 (0.015182) Loss: 0.42337 (0.52318) +2025-08-22,11:24:41 | INFO | Train Epoch: 5 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 0.56374 (0.50836) Boundary_loss: 0.015146 (0.015182) Loss: 0.57888 (0.52354) +2025-08-22,11:25:38 | INFO | Train Epoch: 5 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.51542 (0.50841) Boundary_loss: 0.015171 (0.015182) Loss: 0.53059 (0.52359) +2025-08-22,11:26:35 | INFO | Train Epoch: 5 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 47.840 Boundary Ratio: 0.244 Contrastive_loss: 0.39696 (0.50768) Boundary_loss: 0.015271 (0.015182) Loss: 0.41223 (0.52287) +2025-08-22,11:27:32 | INFO | Train Epoch: 5 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 0.59326 (0.50824) Boundary_loss: 0.015192 (0.015182) Loss: 0.60845 (0.52342) +2025-08-22,11:28:29 | INFO | Train Epoch: 5 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.55165 (0.50851) Boundary_loss: 0.015093 (0.015182) Loss: 0.56674 (0.52370) +2025-08-22,11:29:25 | INFO | Train Epoch: 5 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 49.342 Boundary Ratio: 0.252 Contrastive_loss: 0.47179 (0.50828) Boundary_loss: 0.015160 (0.015181) Loss: 0.48695 (0.52346) +2025-08-22,11:30:22 | INFO | Train Epoch: 5 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 47.982 Boundary Ratio: 0.245 Contrastive_loss: 0.48547 (0.50814) Boundary_loss: 0.015296 (0.015182) Loss: 0.50076 (0.52332) +2025-08-22,11:31:19 | INFO | Train Epoch: 5 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.303 Boundary Ratio: 0.246 Contrastive_loss: 0.52289 (0.50823) Boundary_loss: 0.015235 (0.015183) Loss: 0.53813 (0.52341) +2025-08-22,11:32:16 | INFO | Train Epoch: 5 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.52024 (0.50830) Boundary_loss: 0.015149 (0.015182) Loss: 0.53539 (0.52349) +2025-08-22,11:33:13 | INFO | Train Epoch: 5 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.51636 (0.50835) Boundary_loss: 0.015041 (0.015181) Loss: 0.53140 (0.52354) +2025-08-22,11:34:10 | INFO | Train Epoch: 5 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.45596 (0.50803) Boundary_loss: 0.014990 (0.015180) Loss: 0.47095 (0.52321) +2025-08-22,11:35:07 | INFO | Train Epoch: 5 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.51056 (0.50805) Boundary_loss: 0.015149 (0.015180) Loss: 0.52571 (0.52323) +2025-08-22,11:36:04 | INFO | Train Epoch: 5 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.586 Boundary Ratio: 0.253 Contrastive_loss: 0.56358 (0.50838) Boundary_loss: 0.015166 (0.015180) Loss: 0.57874 (0.52356) +2025-08-22,11:37:01 | INFO | Train Epoch: 5 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.45246 (0.50805) Boundary_loss: 0.015230 (0.015180) Loss: 0.46769 (0.52323) +2025-08-22,11:37:58 | INFO | Train Epoch: 5 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.869 Boundary Ratio: 0.254 Contrastive_loss: 0.52667 (0.50816) Boundary_loss: 0.015244 (0.015181) Loss: 0.54191 (0.52334) +2025-08-22,11:38:54 | INFO | Train Epoch: 5 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 0.56892 (0.50852) Boundary_loss: 0.015198 (0.015181) Loss: 0.58412 (0.52370) +2025-08-22,11:39:51 | INFO | Train Epoch: 5 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 0.46771 (0.50828) Boundary_loss: 0.015236 (0.015181) Loss: 0.48294 (0.52346) +2025-08-22,11:40:48 | INFO | Train Epoch: 5 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.48117 (0.50812) Boundary_loss: 0.015147 (0.015181) Loss: 0.49631 (0.52330) +2025-08-22,11:41:45 | INFO | Train Epoch: 5 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.42139 (0.50761) Boundary_loss: 0.015220 (0.015181) Loss: 0.43661 (0.52279) +2025-08-22,11:42:42 | INFO | Train Epoch: 5 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 49.391 Boundary Ratio: 0.252 Contrastive_loss: 0.48421 (0.50747) Boundary_loss: 0.015199 (0.015181) Loss: 0.49941 (0.52265) +2025-08-22,11:43:39 | INFO | Train Epoch: 5 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 0.54704 (0.50770) Boundary_loss: 0.015241 (0.015182) Loss: 0.56228 (0.52288) +2025-08-22,11:44:36 | INFO | Train Epoch: 5 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.56792 (0.50805) Boundary_loss: 0.015291 (0.015182) Loss: 0.58322 (0.52323) +2025-08-22,11:45:33 | INFO | Train Epoch: 5 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 0.52946 (0.50817) Boundary_loss: 0.015234 (0.015183) Loss: 0.54469 (0.52336) +2025-08-22,11:46:29 | INFO | Train Epoch: 5 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.44174 (0.50779) Boundary_loss: 0.015230 (0.015183) Loss: 0.45697 (0.52298) +2025-08-22,11:47:26 | INFO | Train Epoch: 5 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.48316 (0.50765) Boundary_loss: 0.015098 (0.015182) Loss: 0.49826 (0.52284) +2025-08-22,11:48:23 | INFO | Train Epoch: 5 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 0.58805 (0.50811) Boundary_loss: 0.015166 (0.015182) Loss: 0.60322 (0.52329) +2025-08-22,11:49:20 | INFO | Train Epoch: 5 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 49.781 Boundary Ratio: 0.254 Contrastive_loss: 0.44465 (0.50775) Boundary_loss: 0.015305 (0.015183) Loss: 0.45996 (0.52293) +2025-08-22,11:50:17 | INFO | Train Epoch: 5 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.51696 (0.50780) Boundary_loss: 0.015091 (0.015182) Loss: 0.53205 (0.52298) +2025-08-22,11:51:14 | INFO | Train Epoch: 5 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.47181 (0.50760) Boundary_loss: 0.015158 (0.015182) Loss: 0.48697 (0.52278) +2025-08-22,11:52:11 | INFO | Train Epoch: 5 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.53260 (0.50774) Boundary_loss: 0.015109 (0.015182) Loss: 0.54771 (0.52292) +2025-08-22,11:53:08 | INFO | Train Epoch: 5 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.53361 (0.50788) Boundary_loss: 0.015239 (0.015182) Loss: 0.54885 (0.52306) +2025-08-22,11:54:05 | INFO | Train Epoch: 5 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 0.48380 (0.50775) Boundary_loss: 0.015162 (0.015182) Loss: 0.49897 (0.52293) +2025-08-22,11:55:01 | INFO | Train Epoch: 5 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.119 Boundary Ratio: 0.246 Contrastive_loss: 0.52109 (0.50782) Boundary_loss: 0.015020 (0.015181) Loss: 0.53611 (0.52300) +2025-08-22,11:55:58 | INFO | Train Epoch: 5 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 0.50457 (0.50781) Boundary_loss: 0.015051 (0.015180) Loss: 0.51962 (0.52299) +2025-08-22,11:56:55 | INFO | Train Epoch: 5 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.56283 (0.50810) Boundary_loss: 0.015126 (0.015180) Loss: 0.57795 (0.52328) +2025-08-22,11:57:52 | INFO | Train Epoch: 5 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.47284 (0.50791) Boundary_loss: 0.015207 (0.015180) Loss: 0.48805 (0.52309) +2025-08-22,11:58:49 | INFO | Train Epoch: 5 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 47.801 Boundary Ratio: 0.244 Contrastive_loss: 0.55184 (0.50815) Boundary_loss: 0.015276 (0.015181) Loss: 0.56711 (0.52333) +2025-08-22,11:59:46 | INFO | Train Epoch: 5 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.44445 (0.50781) Boundary_loss: 0.015179 (0.015181) Loss: 0.45963 (0.52299) +2025-08-22,12:00:43 | INFO | Train Epoch: 5 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.324 Boundary Ratio: 0.247 Contrastive_loss: 0.47967 (0.50766) Boundary_loss: 0.015239 (0.015181) Loss: 0.49491 (0.52284) +2025-08-22,12:01:40 | INFO | Train Epoch: 5 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.57445 (0.50801) Boundary_loss: 0.015152 (0.015181) Loss: 0.58960 (0.52319) +2025-08-22,12:02:37 | INFO | Train Epoch: 5 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 0.47056 (0.50782) Boundary_loss: 0.015118 (0.015181) Loss: 0.48568 (0.52300) +2025-08-22,12:03:34 | INFO | Train Epoch: 5 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 47.990 Boundary Ratio: 0.245 Contrastive_loss: 0.48798 (0.50771) Boundary_loss: 0.015109 (0.015180) Loss: 0.50309 (0.52289) +2025-08-22,12:04:31 | INFO | Train Epoch: 5 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.109 Boundary Ratio: 0.245 Contrastive_loss: 0.52466 (0.50780) Boundary_loss: 0.015148 (0.015180) Loss: 0.53981 (0.52298) +2025-08-22,12:05:28 | INFO | Train Epoch: 5 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.53022 (0.50792) Boundary_loss: 0.015117 (0.015180) Loss: 0.54533 (0.52310) +2025-08-22,12:06:25 | INFO | Train Epoch: 5 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.38424 (0.50729) Boundary_loss: 0.015214 (0.015180) Loss: 0.39946 (0.52246) +2025-08-22,12:07:22 | INFO | Train Epoch: 5 [10035712/26365952 (38%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 0.45538 (0.50702) Boundary_loss: 0.015315 (0.015181) Loss: 0.47070 (0.52220) +2025-08-22,12:08:19 | INFO | Train Epoch: 5 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.47032 (0.50684) Boundary_loss: 0.015267 (0.015181) Loss: 0.48559 (0.52202) +2025-08-22,12:09:16 | INFO | Train Epoch: 5 [10138112/26365952 (38%)] Avg Boundaries (per batch): 47.893 Boundary Ratio: 0.244 Contrastive_loss: 0.50641 (0.50683) Boundary_loss: 0.015289 (0.015182) Loss: 0.52169 (0.52202) +2025-08-22,12:10:13 | INFO | Train Epoch: 5 [10189312/26365952 (39%)] Avg Boundaries (per batch): 49.641 Boundary Ratio: 0.253 Contrastive_loss: 0.40997 (0.50635) Boundary_loss: 0.015167 (0.015182) Loss: 0.42514 (0.52153) +2025-08-22,12:11:10 | INFO | Train Epoch: 5 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.53175 (0.50648) Boundary_loss: 0.015113 (0.015181) Loss: 0.54686 (0.52166) +2025-08-22,12:12:07 | INFO | Train Epoch: 5 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.50745 (0.50648) Boundary_loss: 0.015257 (0.015182) Loss: 0.52271 (0.52166) +2025-08-22,12:13:04 | INFO | Train Epoch: 5 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.316 Boundary Ratio: 0.247 Contrastive_loss: 0.47346 (0.50632) Boundary_loss: 0.015051 (0.015181) Loss: 0.48851 (0.52150) +2025-08-22,12:14:01 | INFO | Train Epoch: 5 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.50698 (0.50632) Boundary_loss: 0.015131 (0.015181) Loss: 0.52211 (0.52150) +2025-08-22,12:14:57 | INFO | Train Epoch: 5 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.54135 (0.50649) Boundary_loss: 0.015179 (0.015181) Loss: 0.55653 (0.52167) +2025-08-22,12:15:54 | INFO | Train Epoch: 5 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.53560 (0.50663) Boundary_loss: 0.015096 (0.015180) Loss: 0.55069 (0.52181) +2025-08-22,12:16:51 | INFO | Train Epoch: 5 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.59801 (0.50708) Boundary_loss: 0.015165 (0.015180) Loss: 0.61317 (0.52226) +2025-08-22,12:17:48 | INFO | Train Epoch: 5 [10598912/26365952 (40%)] Avg Boundaries (per batch): 49.367 Boundary Ratio: 0.252 Contrastive_loss: 0.56595 (0.50736) Boundary_loss: 0.015157 (0.015180) Loss: 0.58111 (0.52254) +2025-08-22,12:18:45 | INFO | Train Epoch: 5 [10650112/26365952 (40%)] Avg Boundaries (per batch): 47.980 Boundary Ratio: 0.245 Contrastive_loss: 0.56992 (0.50766) Boundary_loss: 0.015130 (0.015180) Loss: 0.58505 (0.52284) +2025-08-22,12:19:42 | INFO | Train Epoch: 5 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 0.49759 (0.50761) Boundary_loss: 0.015142 (0.015180) Loss: 0.51273 (0.52279) +2025-08-22,12:20:39 | INFO | Train Epoch: 5 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.49929 (0.50757) Boundary_loss: 0.015179 (0.015180) Loss: 0.51447 (0.52275) +2025-08-22,12:21:36 | INFO | Train Epoch: 5 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.48182 (0.50745) Boundary_loss: 0.014985 (0.015179) Loss: 0.49680 (0.52263) +2025-08-22,12:22:33 | INFO | Train Epoch: 5 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.55470 (0.50767) Boundary_loss: 0.015156 (0.015179) Loss: 0.56986 (0.52285) +2025-08-22,12:23:30 | INFO | Train Epoch: 5 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.162 Boundary Ratio: 0.246 Contrastive_loss: 0.47549 (0.50752) Boundary_loss: 0.015078 (0.015178) Loss: 0.49057 (0.52270) +2025-08-22,12:24:27 | INFO | Train Epoch: 5 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.320 Boundary Ratio: 0.252 Contrastive_loss: 0.49300 (0.50745) Boundary_loss: 0.015097 (0.015178) Loss: 0.50809 (0.52263) +2025-08-22,12:25:24 | INFO | Train Epoch: 5 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.47995 (0.50733) Boundary_loss: 0.015157 (0.015178) Loss: 0.49510 (0.52250) +2025-08-22,12:26:21 | INFO | Train Epoch: 5 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.277 Boundary Ratio: 0.251 Contrastive_loss: 0.52756 (0.50742) Boundary_loss: 0.015303 (0.015178) Loss: 0.54286 (0.52260) +2025-08-22,12:27:18 | INFO | Train Epoch: 5 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.53268 (0.50753) Boundary_loss: 0.015122 (0.015178) Loss: 0.54780 (0.52271) +2025-08-22,12:28:15 | INFO | Train Epoch: 5 [11162112/26365952 (42%)] Avg Boundaries (per batch): 49.564 Boundary Ratio: 0.253 Contrastive_loss: 0.45610 (0.50730) Boundary_loss: 0.015226 (0.015178) Loss: 0.47132 (0.52248) +2025-08-22,12:29:11 | INFO | Train Epoch: 5 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.46747 (0.50712) Boundary_loss: 0.015043 (0.015178) Loss: 0.48251 (0.52230) +2025-08-22,12:30:08 | INFO | Train Epoch: 5 [11264512/26365952 (43%)] Avg Boundaries (per batch): 47.770 Boundary Ratio: 0.244 Contrastive_loss: 0.47492 (0.50697) Boundary_loss: 0.015312 (0.015178) Loss: 0.49023 (0.52215) +2025-08-22,12:31:05 | INFO | Train Epoch: 5 [11315712/26365952 (43%)] Avg Boundaries (per batch): 49.492 Boundary Ratio: 0.253 Contrastive_loss: 0.43440 (0.50665) Boundary_loss: 0.015016 (0.015178) Loss: 0.44942 (0.52182) +2025-08-22,12:32:02 | INFO | Train Epoch: 5 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 0.54702 (0.50683) Boundary_loss: 0.015090 (0.015177) Loss: 0.56211 (0.52200) +2025-08-22,12:32:59 | INFO | Train Epoch: 5 [11418112/26365952 (43%)] Avg Boundaries (per batch): 49.621 Boundary Ratio: 0.253 Contrastive_loss: 0.40084 (0.50635) Boundary_loss: 0.015357 (0.015178) Loss: 0.41620 (0.52153) +2025-08-22,12:33:55 | INFO | Train Epoch: 5 [11469312/26365952 (44%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.51606 (0.50640) Boundary_loss: 0.015264 (0.015178) Loss: 0.53132 (0.52158) +2025-08-22,12:34:52 | INFO | Train Epoch: 5 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.51231 (0.50642) Boundary_loss: 0.015189 (0.015178) Loss: 0.52750 (0.52160) +2025-08-22,12:35:49 | INFO | Train Epoch: 5 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.56546 (0.50668) Boundary_loss: 0.015205 (0.015178) Loss: 0.58066 (0.52186) +2025-08-22,12:36:46 | INFO | Train Epoch: 5 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.51005 (0.50670) Boundary_loss: 0.015067 (0.015178) Loss: 0.52511 (0.52188) +2025-08-22,12:37:43 | INFO | Train Epoch: 5 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.41156 (0.50628) Boundary_loss: 0.015002 (0.015177) Loss: 0.42656 (0.52146) +2025-08-22,12:38:40 | INFO | Train Epoch: 5 [11725312/26365952 (44%)] Avg Boundaries (per batch): 47.967 Boundary Ratio: 0.245 Contrastive_loss: 0.51323 (0.50631) Boundary_loss: 0.015069 (0.015177) Loss: 0.52830 (0.52149) +2025-08-22,12:39:37 | INFO | Train Epoch: 5 [11776512/26365952 (45%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 0.46878 (0.50615) Boundary_loss: 0.015110 (0.015176) Loss: 0.48389 (0.52133) +2025-08-22,12:40:34 | INFO | Train Epoch: 5 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.48338 (0.50605) Boundary_loss: 0.015068 (0.015176) Loss: 0.49845 (0.52123) +2025-08-22,12:41:30 | INFO | Train Epoch: 5 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.43483 (0.50575) Boundary_loss: 0.015142 (0.015176) Loss: 0.44997 (0.52092) +2025-08-22,12:42:27 | INFO | Train Epoch: 5 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.54202 (0.50590) Boundary_loss: 0.015134 (0.015176) Loss: 0.55715 (0.52108) +2025-08-22,12:43:24 | INFO | Train Epoch: 5 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.033 Boundary Ratio: 0.245 Contrastive_loss: 0.41490 (0.50551) Boundary_loss: 0.015175 (0.015176) Loss: 0.43007 (0.52069) +2025-08-22,12:44:21 | INFO | Train Epoch: 5 [12032512/26365952 (46%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.41709 (0.50514) Boundary_loss: 0.015157 (0.015176) Loss: 0.43225 (0.52031) +2025-08-22,12:45:18 | INFO | Train Epoch: 5 [12083712/26365952 (46%)] Avg Boundaries (per batch): 47.914 Boundary Ratio: 0.244 Contrastive_loss: 0.42203 (0.50479) Boundary_loss: 0.015069 (0.015175) Loss: 0.43710 (0.51996) +2025-08-22,12:46:15 | INFO | Train Epoch: 5 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 0.47426 (0.50466) Boundary_loss: 0.015222 (0.015175) Loss: 0.48948 (0.51984) +2025-08-22,12:47:12 | INFO | Train Epoch: 5 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.39221 (0.50419) Boundary_loss: 0.015166 (0.015175) Loss: 0.40738 (0.51937) +2025-08-22,12:48:09 | INFO | Train Epoch: 5 [12237312/26365952 (46%)] Avg Boundaries (per batch): 47.928 Boundary Ratio: 0.245 Contrastive_loss: 0.38575 (0.50370) Boundary_loss: 0.015193 (0.015175) Loss: 0.40095 (0.51887) +2025-08-22,12:49:06 | INFO | Train Epoch: 5 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 0.49016 (0.50364) Boundary_loss: 0.015355 (0.015176) Loss: 0.50551 (0.51882) +2025-08-22,12:50:03 | INFO | Train Epoch: 5 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.070 Boundary Ratio: 0.245 Contrastive_loss: 0.48678 (0.50357) Boundary_loss: 0.015311 (0.015177) Loss: 0.50209 (0.51875) +2025-08-22,12:51:00 | INFO | Train Epoch: 5 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.50335 (0.50357) Boundary_loss: 0.015311 (0.015177) Loss: 0.51866 (0.51875) +2025-08-22,12:51:57 | INFO | Train Epoch: 5 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 0.54791 (0.50375) Boundary_loss: 0.015291 (0.015178) Loss: 0.56320 (0.51893) +2025-08-22,12:52:53 | INFO | Train Epoch: 5 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.47741 (0.50364) Boundary_loss: 0.015135 (0.015178) Loss: 0.49255 (0.51882) +2025-08-22,12:53:50 | INFO | Train Epoch: 5 [12544512/26365952 (48%)] Avg Boundaries (per batch): 49.352 Boundary Ratio: 0.252 Contrastive_loss: 0.54368 (0.50381) Boundary_loss: 0.015164 (0.015177) Loss: 0.55885 (0.51898) +2025-08-22,12:54:47 | INFO | Train Epoch: 5 [12595712/26365952 (48%)] Avg Boundaries (per batch): 49.477 Boundary Ratio: 0.252 Contrastive_loss: 0.47338 (0.50368) Boundary_loss: 0.015307 (0.015178) Loss: 0.48869 (0.51886) +2025-08-22,12:55:44 | INFO | Train Epoch: 5 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.50388 (0.50368) Boundary_loss: 0.015264 (0.015178) Loss: 0.51915 (0.51886) +2025-08-22,12:56:41 | INFO | Train Epoch: 5 [12698112/26365952 (48%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 0.50845 (0.50370) Boundary_loss: 0.015220 (0.015178) Loss: 0.52366 (0.51888) +2025-08-22,12:57:38 | INFO | Train Epoch: 5 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.57064 (0.50397) Boundary_loss: 0.015133 (0.015178) Loss: 0.58577 (0.51915) +2025-08-22,12:58:35 | INFO | Train Epoch: 5 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.104 Boundary Ratio: 0.245 Contrastive_loss: 0.49590 (0.50394) Boundary_loss: 0.015116 (0.015178) Loss: 0.51101 (0.51912) +2025-08-22,12:59:32 | INFO | Train Epoch: 5 [12851712/26365952 (49%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.46116 (0.50377) Boundary_loss: 0.015189 (0.015178) Loss: 0.47635 (0.51895) +2025-08-22,13:00:29 | INFO | Train Epoch: 5 [12902912/26365952 (49%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.40757 (0.50339) Boundary_loss: 0.015071 (0.015178) Loss: 0.42264 (0.51857) +2025-08-22,13:01:26 | INFO | Train Epoch: 5 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.43108 (0.50310) Boundary_loss: 0.015185 (0.015178) Loss: 0.44626 (0.51828) +2025-08-22,13:02:23 | INFO | Train Epoch: 5 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.54223 (0.50326) Boundary_loss: 0.015173 (0.015178) Loss: 0.55741 (0.51844) +2025-08-22,13:03:20 | INFO | Train Epoch: 5 [13056512/26365952 (50%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 0.46452 (0.50311) Boundary_loss: 0.015273 (0.015178) Loss: 0.47979 (0.51828) +2025-08-22,13:04:17 | INFO | Train Epoch: 5 [13107712/26365952 (50%)] Avg Boundaries (per batch): 49.547 Boundary Ratio: 0.253 Contrastive_loss: 0.46750 (0.50297) Boundary_loss: 0.015203 (0.015178) Loss: 0.48270 (0.51815) +2025-08-22,13:05:14 | INFO | Train Epoch: 5 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.47552 (0.50286) Boundary_loss: 0.015108 (0.015178) Loss: 0.49063 (0.51804) +2025-08-22,13:06:11 | INFO | Train Epoch: 5 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.572 Boundary Ratio: 0.253 Contrastive_loss: 0.57202 (0.50313) Boundary_loss: 0.015274 (0.015178) Loss: 0.58730 (0.51831) +2025-08-22,13:07:07 | INFO | Train Epoch: 5 [13261312/26365952 (50%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.46685 (0.50299) Boundary_loss: 0.015342 (0.015179) Loss: 0.48219 (0.51817) +2025-08-22,13:08:04 | INFO | Train Epoch: 5 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.53654 (0.50312) Boundary_loss: 0.015253 (0.015179) Loss: 0.55180 (0.51830) +2025-08-22,13:09:01 | INFO | Train Epoch: 5 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.223 Boundary Ratio: 0.246 Contrastive_loss: 0.48316 (0.50304) Boundary_loss: 0.015251 (0.015179) Loss: 0.49841 (0.51822) +2025-08-22,13:09:58 | INFO | Train Epoch: 5 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.59367 (0.50339) Boundary_loss: 0.015047 (0.015179) Loss: 0.60872 (0.51856) +2025-08-22,13:10:55 | INFO | Train Epoch: 5 [13466112/26365952 (51%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.55952 (0.50360) Boundary_loss: 0.015156 (0.015179) Loss: 0.57468 (0.51878) +2025-08-22,13:11:52 | INFO | Train Epoch: 5 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.51447 (0.50364) Boundary_loss: 0.015111 (0.015179) Loss: 0.52958 (0.51882) +2025-08-22,13:12:49 | INFO | Train Epoch: 5 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.211 Boundary Ratio: 0.246 Contrastive_loss: 0.52097 (0.50370) Boundary_loss: 0.015253 (0.015179) Loss: 0.53622 (0.51888) +2025-08-22,13:13:46 | INFO | Train Epoch: 5 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.50852 (0.50372) Boundary_loss: 0.015028 (0.015178) Loss: 0.52355 (0.51890) +2025-08-22,13:14:42 | INFO | Train Epoch: 5 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.262 Boundary Ratio: 0.246 Contrastive_loss: 0.54928 (0.50389) Boundary_loss: 0.015297 (0.015179) Loss: 0.56457 (0.51907) +2025-08-22,13:15:39 | INFO | Train Epoch: 5 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.46031 (0.50373) Boundary_loss: 0.015145 (0.015179) Loss: 0.47545 (0.51891) +2025-08-22,13:16:36 | INFO | Train Epoch: 5 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.50316 (0.50373) Boundary_loss: 0.015183 (0.015179) Loss: 0.51835 (0.51891) +2025-08-22,13:17:33 | INFO | Train Epoch: 5 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.47129 (0.50361) Boundary_loss: 0.015105 (0.015178) Loss: 0.48639 (0.51879) +2025-08-22,13:18:29 | INFO | Train Epoch: 5 [13875712/26365952 (53%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 0.45257 (0.50342) Boundary_loss: 0.015094 (0.015178) Loss: 0.46767 (0.51860) +2025-08-22,13:19:26 | INFO | Train Epoch: 5 [13926912/26365952 (53%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.55788 (0.50362) Boundary_loss: 0.015301 (0.015179) Loss: 0.57318 (0.51880) +2025-08-22,13:20:23 | INFO | Train Epoch: 5 [13978112/26365952 (53%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.53106 (0.50372) Boundary_loss: 0.015202 (0.015179) Loss: 0.54626 (0.51890) +2025-08-22,13:21:20 | INFO | Train Epoch: 5 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.50140 (0.50371) Boundary_loss: 0.015207 (0.015179) Loss: 0.51661 (0.51889) +2025-08-22,13:22:17 | INFO | Train Epoch: 5 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.49872 (0.50369) Boundary_loss: 0.015212 (0.015179) Loss: 0.51394 (0.51887) +2025-08-22,13:23:14 | INFO | Train Epoch: 5 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.42042 (0.50339) Boundary_loss: 0.015161 (0.015179) Loss: 0.43558 (0.51857) +2025-08-22,13:24:11 | INFO | Train Epoch: 5 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.52991 (0.50349) Boundary_loss: 0.015107 (0.015179) Loss: 0.54502 (0.51867) +2025-08-22,13:25:07 | INFO | Train Epoch: 5 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.38655 (0.50307) Boundary_loss: 0.015203 (0.015179) Loss: 0.40175 (0.51825) +2025-08-22,13:26:04 | INFO | Train Epoch: 5 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.56826 (0.50330) Boundary_loss: 0.015188 (0.015179) Loss: 0.58345 (0.51848) +2025-08-22,13:27:01 | INFO | Train Epoch: 5 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.44200 (0.50308) Boundary_loss: 0.015095 (0.015178) Loss: 0.45709 (0.51826) +2025-08-22,13:27:58 | INFO | Train Epoch: 5 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.369 Boundary Ratio: 0.247 Contrastive_loss: 0.50239 (0.50308) Boundary_loss: 0.015099 (0.015178) Loss: 0.51749 (0.51826) +2025-08-22,13:28:55 | INFO | Train Epoch: 5 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.47382 (0.50298) Boundary_loss: 0.015138 (0.015178) Loss: 0.48895 (0.51816) +2025-08-22,13:29:51 | INFO | Train Epoch: 5 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.54101 (0.50311) Boundary_loss: 0.015077 (0.015178) Loss: 0.55609 (0.51829) +2025-08-22,13:30:48 | INFO | Train Epoch: 5 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.46699 (0.50299) Boundary_loss: 0.015175 (0.015178) Loss: 0.48217 (0.51816) +2025-08-22,13:31:45 | INFO | Train Epoch: 5 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.40645 (0.50265) Boundary_loss: 0.015094 (0.015177) Loss: 0.42154 (0.51783) +2025-08-22,13:32:42 | INFO | Train Epoch: 5 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.50136 (0.50264) Boundary_loss: 0.015328 (0.015178) Loss: 0.51669 (0.51782) +2025-08-22,13:33:39 | INFO | Train Epoch: 5 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.44814 (0.50245) Boundary_loss: 0.015244 (0.015178) Loss: 0.46339 (0.51763) +2025-08-22,13:34:36 | INFO | Train Epoch: 5 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.48671 (0.50240) Boundary_loss: 0.015125 (0.015178) Loss: 0.50184 (0.51758) +2025-08-22,13:35:33 | INFO | Train Epoch: 5 [14797312/26365952 (56%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.53725 (0.50252) Boundary_loss: 0.015226 (0.015178) Loss: 0.55247 (0.51770) +2025-08-22,13:36:29 | INFO | Train Epoch: 5 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.53209 (0.50262) Boundary_loss: 0.015119 (0.015178) Loss: 0.54721 (0.51780) +2025-08-22,13:37:26 | INFO | Train Epoch: 5 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.51859 (0.50268) Boundary_loss: 0.015103 (0.015178) Loss: 0.53369 (0.51785) +2025-08-22,13:38:23 | INFO | Train Epoch: 5 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.41519 (0.50238) Boundary_loss: 0.015038 (0.015177) Loss: 0.43023 (0.51756) +2025-08-22,13:39:20 | INFO | Train Epoch: 5 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.45725 (0.50222) Boundary_loss: 0.015220 (0.015177) Loss: 0.47247 (0.51740) +2025-08-22,13:40:17 | INFO | Train Epoch: 5 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.51941 (0.50228) Boundary_loss: 0.015185 (0.015177) Loss: 0.53459 (0.51746) +2025-08-22,13:41:14 | INFO | Train Epoch: 5 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 0.36887 (0.50183) Boundary_loss: 0.015232 (0.015177) Loss: 0.38410 (0.51701) +2025-08-22,13:42:10 | INFO | Train Epoch: 5 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.672 Boundary Ratio: 0.253 Contrastive_loss: 0.48620 (0.50178) Boundary_loss: 0.015206 (0.015178) Loss: 0.50141 (0.51696) +2025-08-22,13:43:07 | INFO | Train Epoch: 5 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 0.43912 (0.50157) Boundary_loss: 0.015114 (0.015177) Loss: 0.45424 (0.51675) +2025-08-22,13:44:04 | INFO | Train Epoch: 5 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 0.54178 (0.50170) Boundary_loss: 0.015172 (0.015177) Loss: 0.55695 (0.51688) +2025-08-22,13:45:01 | INFO | Train Epoch: 5 [15309312/26365952 (58%)] Avg Boundaries (per batch): 49.268 Boundary Ratio: 0.251 Contrastive_loss: 0.54373 (0.50184) Boundary_loss: 0.015255 (0.015178) Loss: 0.55898 (0.51702) +2025-08-22,13:45:58 | INFO | Train Epoch: 5 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.49330 (0.50182) Boundary_loss: 0.015138 (0.015177) Loss: 0.50844 (0.51699) +2025-08-22,13:46:55 | INFO | Train Epoch: 5 [15411712/26365952 (58%)] Avg Boundaries (per batch): 49.377 Boundary Ratio: 0.252 Contrastive_loss: 0.58248 (0.50208) Boundary_loss: 0.015196 (0.015177) Loss: 0.59768 (0.51726) +2025-08-22,13:47:52 | INFO | Train Epoch: 5 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.43309 (0.50185) Boundary_loss: 0.015014 (0.015177) Loss: 0.44810 (0.51703) +2025-08-22,13:48:49 | INFO | Train Epoch: 5 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 0.62256 (0.50225) Boundary_loss: 0.015236 (0.015177) Loss: 0.63779 (0.51743) +2025-08-22,13:49:45 | INFO | Train Epoch: 5 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 0.44699 (0.50207) Boundary_loss: 0.015083 (0.015177) Loss: 0.46207 (0.51725) +2025-08-22,13:50:42 | INFO | Train Epoch: 5 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.627 Boundary Ratio: 0.253 Contrastive_loss: 0.54246 (0.50220) Boundary_loss: 0.015269 (0.015177) Loss: 0.55773 (0.51738) +2025-08-22,13:51:39 | INFO | Train Epoch: 5 [15667712/26365952 (59%)] Avg Boundaries (per batch): 47.850 Boundary Ratio: 0.244 Contrastive_loss: 0.54803 (0.50235) Boundary_loss: 0.015246 (0.015177) Loss: 0.56328 (0.51753) +2025-08-22,13:52:36 | INFO | Train Epoch: 5 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.47238 (0.50225) Boundary_loss: 0.015109 (0.015177) Loss: 0.48749 (0.51743) +2025-08-22,13:53:33 | INFO | Train Epoch: 5 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 0.53643 (0.50237) Boundary_loss: 0.015141 (0.015177) Loss: 0.55157 (0.51754) +2025-08-22,13:54:30 | INFO | Train Epoch: 5 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.148 Boundary Ratio: 0.246 Contrastive_loss: 0.47984 (0.50229) Boundary_loss: 0.015272 (0.015177) Loss: 0.49511 (0.51747) +2025-08-22,13:55:27 | INFO | Train Epoch: 5 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.50913 (0.50231) Boundary_loss: 0.015076 (0.015177) Loss: 0.52420 (0.51749) +2025-08-22,13:56:23 | INFO | Train Epoch: 5 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.51675 (0.50236) Boundary_loss: 0.015111 (0.015177) Loss: 0.53186 (0.51754) +2025-08-22,13:57:20 | INFO | Train Epoch: 5 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.020 Boundary Ratio: 0.245 Contrastive_loss: 0.50151 (0.50236) Boundary_loss: 0.015323 (0.015177) Loss: 0.51683 (0.51754) +2025-08-22,13:58:17 | INFO | Train Epoch: 5 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.48740 (0.50231) Boundary_loss: 0.015152 (0.015177) Loss: 0.50255 (0.51749) +2025-08-22,13:59:14 | INFO | Train Epoch: 5 [16077312/26365952 (61%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.47446 (0.50222) Boundary_loss: 0.015133 (0.015177) Loss: 0.48959 (0.51740) +2025-08-22,14:00:11 | INFO | Train Epoch: 5 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.47848 (0.50215) Boundary_loss: 0.015201 (0.015177) Loss: 0.49368 (0.51732) +2025-08-22,14:01:08 | INFO | Train Epoch: 5 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 0.41250 (0.50186) Boundary_loss: 0.015243 (0.015177) Loss: 0.42774 (0.51704) +2025-08-22,14:02:04 | INFO | Train Epoch: 5 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.48311 (0.50181) Boundary_loss: 0.015187 (0.015177) Loss: 0.49830 (0.51698) +2025-08-22,14:03:01 | INFO | Train Epoch: 5 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.46168 (0.50168) Boundary_loss: 0.015005 (0.015177) Loss: 0.47669 (0.51686) +2025-08-22,14:03:58 | INFO | Train Epoch: 5 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.58555 (0.50194) Boundary_loss: 0.015065 (0.015176) Loss: 0.60061 (0.51712) +2025-08-22,14:04:55 | INFO | Train Epoch: 5 [16384512/26365952 (62%)] Avg Boundaries (per batch): 49.529 Boundary Ratio: 0.253 Contrastive_loss: 0.41383 (0.50167) Boundary_loss: 0.015286 (0.015177) Loss: 0.42912 (0.51684) +2025-08-22,14:05:52 | INFO | Train Epoch: 5 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.50857 (0.50169) Boundary_loss: 0.015220 (0.015177) Loss: 0.52379 (0.51687) +2025-08-22,14:06:48 | INFO | Train Epoch: 5 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.52987 (0.50178) Boundary_loss: 0.015213 (0.015177) Loss: 0.54508 (0.51695) +2025-08-22,14:07:45 | INFO | Train Epoch: 5 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.385 Boundary Ratio: 0.247 Contrastive_loss: 0.49183 (0.50174) Boundary_loss: 0.015155 (0.015177) Loss: 0.50698 (0.51692) +2025-08-22,14:08:42 | INFO | Train Epoch: 5 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.54054 (0.50186) Boundary_loss: 0.015066 (0.015177) Loss: 0.55561 (0.51704) +2025-08-22,14:09:39 | INFO | Train Epoch: 5 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 0.46970 (0.50177) Boundary_loss: 0.015174 (0.015177) Loss: 0.48488 (0.51694) +2025-08-22,14:10:35 | INFO | Train Epoch: 5 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.56308 (0.50195) Boundary_loss: 0.015318 (0.015177) Loss: 0.57840 (0.51713) +2025-08-22,14:11:32 | INFO | Train Epoch: 5 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.44270 (0.50177) Boundary_loss: 0.015124 (0.015177) Loss: 0.45782 (0.51695) +2025-08-22,14:12:29 | INFO | Train Epoch: 5 [16794112/26365952 (64%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.52146 (0.50183) Boundary_loss: 0.015197 (0.015177) Loss: 0.53666 (0.51701) +2025-08-22,14:13:26 | INFO | Train Epoch: 5 [16845312/26365952 (64%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.40912 (0.50155) Boundary_loss: 0.015264 (0.015177) Loss: 0.42438 (0.51673) +2025-08-22,14:14:23 | INFO | Train Epoch: 5 [16896512/26365952 (64%)] Avg Boundaries (per batch): 49.412 Boundary Ratio: 0.252 Contrastive_loss: 0.50876 (0.50157) Boundary_loss: 0.015020 (0.015177) Loss: 0.52378 (0.51675) +2025-08-22,14:15:20 | INFO | Train Epoch: 5 [16947712/26365952 (64%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.51852 (0.50162) Boundary_loss: 0.015191 (0.015177) Loss: 0.53371 (0.51680) +2025-08-22,14:16:16 | INFO | Train Epoch: 5 [16998912/26365952 (64%)] Avg Boundaries (per batch): 49.773 Boundary Ratio: 0.254 Contrastive_loss: 0.45470 (0.50148) Boundary_loss: 0.015197 (0.015177) Loss: 0.46989 (0.51666) +2025-08-22,14:17:13 | INFO | Train Epoch: 5 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.45270 (0.50134) Boundary_loss: 0.015263 (0.015177) Loss: 0.46796 (0.51651) +2025-08-22,14:18:10 | INFO | Train Epoch: 5 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 0.46086 (0.50122) Boundary_loss: 0.015062 (0.015177) Loss: 0.47592 (0.51639) +2025-08-22,14:19:07 | INFO | Train Epoch: 5 [17152512/26365952 (65%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.48691 (0.50117) Boundary_loss: 0.015035 (0.015176) Loss: 0.50195 (0.51635) +2025-08-22,14:20:04 | INFO | Train Epoch: 5 [17203712/26365952 (65%)] Avg Boundaries (per batch): 49.949 Boundary Ratio: 0.255 Contrastive_loss: 0.51686 (0.50122) Boundary_loss: 0.015406 (0.015177) Loss: 0.53227 (0.51640) +2025-08-22,14:21:00 | INFO | Train Epoch: 5 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.45788 (0.50109) Boundary_loss: 0.015194 (0.015177) Loss: 0.47307 (0.51627) +2025-08-22,14:21:57 | INFO | Train Epoch: 5 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.305 Boundary Ratio: 0.252 Contrastive_loss: 0.44958 (0.50094) Boundary_loss: 0.015319 (0.015177) Loss: 0.46490 (0.51612) +2025-08-22,14:22:54 | INFO | Train Epoch: 5 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.43431 (0.50074) Boundary_loss: 0.015111 (0.015177) Loss: 0.44942 (0.51592) +2025-08-22,14:23:51 | INFO | Train Epoch: 5 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.54442 (0.50087) Boundary_loss: 0.015100 (0.015177) Loss: 0.55952 (0.51605) +2025-08-22,14:24:48 | INFO | Train Epoch: 5 [17459712/26365952 (66%)] Avg Boundaries (per batch): 49.570 Boundary Ratio: 0.253 Contrastive_loss: 0.50772 (0.50089) Boundary_loss: 0.015159 (0.015177) Loss: 0.52287 (0.51607) +2025-08-22,14:25:45 | INFO | Train Epoch: 5 [17510912/26365952 (66%)] Avg Boundaries (per batch): 47.809 Boundary Ratio: 0.244 Contrastive_loss: 0.44692 (0.50073) Boundary_loss: 0.015204 (0.015177) Loss: 0.46213 (0.51591) +2025-08-22,14:26:42 | INFO | Train Epoch: 5 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.43524 (0.50054) Boundary_loss: 0.015220 (0.015177) Loss: 0.45046 (0.51572) +2025-08-22,14:27:38 | INFO | Train Epoch: 5 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.42037 (0.50031) Boundary_loss: 0.015213 (0.015177) Loss: 0.43558 (0.51549) +2025-08-22,14:28:35 | INFO | Train Epoch: 5 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.48669 (0.50027) Boundary_loss: 0.015287 (0.015178) Loss: 0.50198 (0.51545) +2025-08-22,14:29:32 | INFO | Train Epoch: 5 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.352 Boundary Ratio: 0.252 Contrastive_loss: 0.49866 (0.50027) Boundary_loss: 0.015239 (0.015178) Loss: 0.51389 (0.51545) +2025-08-22,14:30:29 | INFO | Train Epoch: 5 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.48749 (0.50023) Boundary_loss: 0.015253 (0.015178) Loss: 0.50275 (0.51541) +2025-08-22,14:31:25 | INFO | Train Epoch: 5 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.48411 (0.50019) Boundary_loss: 0.015217 (0.015178) Loss: 0.49933 (0.51536) +2025-08-22,14:32:22 | INFO | Train Epoch: 5 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.49392 (0.50017) Boundary_loss: 0.015144 (0.015178) Loss: 0.50906 (0.51535) +2025-08-22,14:33:19 | INFO | Train Epoch: 5 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.52091 (0.50023) Boundary_loss: 0.015125 (0.015178) Loss: 0.53603 (0.51540) +2025-08-22,14:34:16 | INFO | Train Epoch: 5 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.47855 (0.50016) Boundary_loss: 0.015077 (0.015178) Loss: 0.49363 (0.51534) +2025-08-22,14:35:13 | INFO | Train Epoch: 5 [18022912/26365952 (68%)] Avg Boundaries (per batch): 49.393 Boundary Ratio: 0.252 Contrastive_loss: 0.53309 (0.50026) Boundary_loss: 0.015120 (0.015177) Loss: 0.54821 (0.51544) +2025-08-22,14:36:09 | INFO | Train Epoch: 5 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.508 Boundary Ratio: 0.247 Contrastive_loss: 0.53548 (0.50036) Boundary_loss: 0.015047 (0.015177) Loss: 0.55053 (0.51553) +2025-08-22,14:37:06 | INFO | Train Epoch: 5 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.44206 (0.50019) Boundary_loss: 0.015253 (0.015177) Loss: 0.45732 (0.51537) +2025-08-22,14:38:03 | INFO | Train Epoch: 5 [18176512/26365952 (69%)] Avg Boundaries (per batch): 49.676 Boundary Ratio: 0.253 Contrastive_loss: 0.68370 (0.50071) Boundary_loss: 0.015217 (0.015177) Loss: 0.69891 (0.51589) +2025-08-22,14:39:00 | INFO | Train Epoch: 5 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 0.53999 (0.50082) Boundary_loss: 0.015191 (0.015177) Loss: 0.55518 (0.51600) +2025-08-22,14:39:57 | INFO | Train Epoch: 5 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.51467 (0.50086) Boundary_loss: 0.015122 (0.015177) Loss: 0.52980 (0.51603) +2025-08-22,14:40:53 | INFO | Train Epoch: 5 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.465 Boundary Ratio: 0.252 Contrastive_loss: 0.46913 (0.50077) Boundary_loss: 0.015124 (0.015177) Loss: 0.48425 (0.51595) +2025-08-22,14:41:50 | INFO | Train Epoch: 5 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.47589 (0.50070) Boundary_loss: 0.015109 (0.015177) Loss: 0.49100 (0.51588) +2025-08-22,14:42:47 | INFO | Train Epoch: 5 [18432512/26365952 (70%)] Avg Boundaries (per batch): 47.975 Boundary Ratio: 0.245 Contrastive_loss: 0.46113 (0.50059) Boundary_loss: 0.015251 (0.015177) Loss: 0.47638 (0.51577) +2025-08-22,14:43:44 | INFO | Train Epoch: 5 [18483712/26365952 (70%)] Avg Boundaries (per batch): 49.955 Boundary Ratio: 0.255 Contrastive_loss: 0.51710 (0.50064) Boundary_loss: 0.015249 (0.015177) Loss: 0.53235 (0.51581) +2025-08-22,14:44:41 | INFO | Train Epoch: 5 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.52623 (0.50071) Boundary_loss: 0.015156 (0.015177) Loss: 0.54139 (0.51588) +2025-08-22,14:45:38 | INFO | Train Epoch: 5 [18586112/26365952 (70%)] Avg Boundaries (per batch): 49.383 Boundary Ratio: 0.252 Contrastive_loss: 0.51692 (0.50075) Boundary_loss: 0.015185 (0.015177) Loss: 0.53211 (0.51593) +2025-08-22,14:46:34 | INFO | Train Epoch: 5 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.49742 (0.50074) Boundary_loss: 0.015087 (0.015177) Loss: 0.51251 (0.51592) +2025-08-22,14:47:31 | INFO | Train Epoch: 5 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.37779 (0.50041) Boundary_loss: 0.015260 (0.015177) Loss: 0.39305 (0.51558) +2025-08-22,14:48:28 | INFO | Train Epoch: 5 [18739712/26365952 (71%)] Avg Boundaries (per batch): 47.898 Boundary Ratio: 0.244 Contrastive_loss: 0.44856 (0.50026) Boundary_loss: 0.015226 (0.015177) Loss: 0.46378 (0.51544) +2025-08-22,14:49:25 | INFO | Train Epoch: 5 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.58446 (0.50049) Boundary_loss: 0.015114 (0.015177) Loss: 0.59958 (0.51567) +2025-08-22,14:50:21 | INFO | Train Epoch: 5 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.48571 (0.50045) Boundary_loss: 0.015049 (0.015177) Loss: 0.50076 (0.51563) +2025-08-22,14:51:18 | INFO | Train Epoch: 5 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.51778 (0.50050) Boundary_loss: 0.015107 (0.015177) Loss: 0.53289 (0.51568) +2025-08-22,14:52:15 | INFO | Train Epoch: 5 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.46849 (0.50041) Boundary_loss: 0.015330 (0.015177) Loss: 0.48382 (0.51559) +2025-08-22,14:53:12 | INFO | Train Epoch: 5 [18995712/26365952 (72%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.55474 (0.50056) Boundary_loss: 0.015139 (0.015177) Loss: 0.56988 (0.51574) +2025-08-22,14:54:09 | INFO | Train Epoch: 5 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.47363 (0.50049) Boundary_loss: 0.015067 (0.015177) Loss: 0.48869 (0.51566) +2025-08-22,14:55:05 | INFO | Train Epoch: 5 [19098112/26365952 (72%)] Avg Boundaries (per batch): 47.650 Boundary Ratio: 0.243 Contrastive_loss: 0.46923 (0.50040) Boundary_loss: 0.015243 (0.015177) Loss: 0.48447 (0.51558) +2025-08-22,14:56:03 | INFO | Train Epoch: 5 [19149312/26365952 (73%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.46185 (0.50030) Boundary_loss: 0.015230 (0.015177) Loss: 0.47708 (0.51548) +2025-08-22,14:56:59 | INFO | Train Epoch: 5 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 0.48720 (0.50027) Boundary_loss: 0.015100 (0.015177) Loss: 0.50230 (0.51544) +2025-08-22,14:57:56 | INFO | Train Epoch: 5 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.49279 (0.50025) Boundary_loss: 0.015124 (0.015177) Loss: 0.50791 (0.51542) +2025-08-22,14:58:53 | INFO | Train Epoch: 5 [19302912/26365952 (73%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 0.50664 (0.50026) Boundary_loss: 0.015221 (0.015177) Loss: 0.52187 (0.51544) +2025-08-22,14:59:50 | INFO | Train Epoch: 5 [19354112/26365952 (73%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.48849 (0.50023) Boundary_loss: 0.015200 (0.015177) Loss: 0.50369 (0.51541) +2025-08-22,15:00:47 | INFO | Train Epoch: 5 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.064 Boundary Ratio: 0.245 Contrastive_loss: 0.46874 (0.50015) Boundary_loss: 0.015153 (0.015177) Loss: 0.48389 (0.51533) +2025-08-22,15:01:44 | INFO | Train Epoch: 5 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.33546 (0.49972) Boundary_loss: 0.015211 (0.015177) Loss: 0.35067 (0.51489) +2025-08-22,15:02:41 | INFO | Train Epoch: 5 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.55222 (0.49986) Boundary_loss: 0.015123 (0.015177) Loss: 0.56734 (0.51503) +2025-08-22,15:03:38 | INFO | Train Epoch: 5 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.58216 (0.50007) Boundary_loss: 0.015158 (0.015177) Loss: 0.59732 (0.51525) +2025-08-22,15:04:34 | INFO | Train Epoch: 5 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.44999 (0.49994) Boundary_loss: 0.015087 (0.015176) Loss: 0.46508 (0.51512) +2025-08-22,15:05:31 | INFO | Train Epoch: 5 [19661312/26365952 (75%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 0.52739 (0.50001) Boundary_loss: 0.015170 (0.015176) Loss: 0.54256 (0.51519) +2025-08-22,15:06:28 | INFO | Train Epoch: 5 [19712512/26365952 (75%)] Avg Boundaries (per batch): 49.586 Boundary Ratio: 0.253 Contrastive_loss: 0.60919 (0.50029) Boundary_loss: 0.015194 (0.015177) Loss: 0.62439 (0.51547) +2025-08-22,15:07:25 | INFO | Train Epoch: 5 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.58510 (0.50051) Boundary_loss: 0.015160 (0.015176) Loss: 0.60026 (0.51569) +2025-08-22,15:08:22 | INFO | Train Epoch: 5 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.45582 (0.50040) Boundary_loss: 0.015083 (0.015176) Loss: 0.47090 (0.51557) +2025-08-22,15:09:19 | INFO | Train Epoch: 5 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.50392 (0.50041) Boundary_loss: 0.015160 (0.015176) Loss: 0.51908 (0.51558) +2025-08-22,15:10:16 | INFO | Train Epoch: 5 [19917312/26365952 (76%)] Avg Boundaries (per batch): 49.525 Boundary Ratio: 0.253 Contrastive_loss: 0.41543 (0.50019) Boundary_loss: 0.015105 (0.015176) Loss: 0.43054 (0.51536) +2025-08-22,15:11:13 | INFO | Train Epoch: 5 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.492 Boundary Ratio: 0.247 Contrastive_loss: 0.57744 (0.50039) Boundary_loss: 0.015112 (0.015176) Loss: 0.59256 (0.51556) +2025-08-22,15:12:09 | INFO | Train Epoch: 5 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.238 Boundary Ratio: 0.246 Contrastive_loss: 0.51274 (0.50042) Boundary_loss: 0.015253 (0.015176) Loss: 0.52799 (0.51559) +2025-08-22,15:13:06 | INFO | Train Epoch: 5 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 0.51356 (0.50045) Boundary_loss: 0.015239 (0.015176) Loss: 0.52880 (0.51563) +2025-08-22,15:14:03 | INFO | Train Epoch: 5 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 0.65333 (0.50084) Boundary_loss: 0.015302 (0.015177) Loss: 0.66863 (0.51602) +2025-08-22,15:15:00 | INFO | Train Epoch: 5 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.44860 (0.50071) Boundary_loss: 0.015109 (0.015176) Loss: 0.46371 (0.51588) +2025-08-22,15:15:57 | INFO | Train Epoch: 5 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.54562 (0.50082) Boundary_loss: 0.015151 (0.015176) Loss: 0.56077 (0.51600) +2025-08-22,15:16:54 | INFO | Train Epoch: 5 [20275712/26365952 (77%)] Avg Boundaries (per batch): 49.426 Boundary Ratio: 0.252 Contrastive_loss: 0.42210 (0.50062) Boundary_loss: 0.015107 (0.015176) Loss: 0.43721 (0.51580) +2025-08-22,15:17:51 | INFO | Train Epoch: 5 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.40525 (0.50038) Boundary_loss: 0.015133 (0.015176) Loss: 0.42039 (0.51556) +2025-08-22,15:18:48 | INFO | Train Epoch: 5 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.56668 (0.50055) Boundary_loss: 0.015091 (0.015176) Loss: 0.58177 (0.51572) +2025-08-22,15:19:44 | INFO | Train Epoch: 5 [20429312/26365952 (77%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 0.56331 (0.50071) Boundary_loss: 0.015255 (0.015176) Loss: 0.57856 (0.51588) +2025-08-22,15:20:41 | INFO | Train Epoch: 5 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.172 Boundary Ratio: 0.246 Contrastive_loss: 0.50451 (0.50072) Boundary_loss: 0.015250 (0.015176) Loss: 0.51976 (0.51589) +2025-08-22,15:21:38 | INFO | Train Epoch: 5 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.50602 (0.50073) Boundary_loss: 0.015209 (0.015176) Loss: 0.52122 (0.51590) +2025-08-22,15:22:34 | INFO | Train Epoch: 5 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 0.59300 (0.50096) Boundary_loss: 0.015262 (0.015176) Loss: 0.60826 (0.51613) +2025-08-22,15:23:31 | INFO | Train Epoch: 5 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.48354 (0.50091) Boundary_loss: 0.015119 (0.015176) Loss: 0.49866 (0.51609) +2025-08-22,15:24:28 | INFO | Train Epoch: 5 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.47721 (0.50086) Boundary_loss: 0.015180 (0.015176) Loss: 0.49239 (0.51603) +2025-08-22,15:25:25 | INFO | Train Epoch: 5 [20736512/26365952 (79%)] Avg Boundaries (per batch): 49.211 Boundary Ratio: 0.251 Contrastive_loss: 0.53148 (0.50093) Boundary_loss: 0.015166 (0.015176) Loss: 0.54664 (0.51611) +2025-08-22,15:26:22 | INFO | Train Epoch: 5 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.45791 (0.50083) Boundary_loss: 0.015245 (0.015176) Loss: 0.47316 (0.51600) +2025-08-22,15:27:19 | INFO | Train Epoch: 5 [20838912/26365952 (79%)] Avg Boundaries (per batch): 49.656 Boundary Ratio: 0.253 Contrastive_loss: 0.57641 (0.50101) Boundary_loss: 0.015321 (0.015177) Loss: 0.59173 (0.51619) +2025-08-22,15:28:16 | INFO | Train Epoch: 5 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.52195 (0.50106) Boundary_loss: 0.015170 (0.015177) Loss: 0.53712 (0.51624) +2025-08-22,15:29:12 | INFO | Train Epoch: 5 [20941312/26365952 (79%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.57657 (0.50125) Boundary_loss: 0.015097 (0.015177) Loss: 0.59167 (0.51642) +2025-08-22,15:30:09 | INFO | Train Epoch: 5 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.51273 (0.50127) Boundary_loss: 0.015159 (0.015177) Loss: 0.52789 (0.51645) +2025-08-22,15:31:06 | INFO | Train Epoch: 5 [21043712/26365952 (80%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.42346 (0.50109) Boundary_loss: 0.015218 (0.015177) Loss: 0.43867 (0.51626) +2025-08-22,15:32:03 | INFO | Train Epoch: 5 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.264 Boundary Ratio: 0.246 Contrastive_loss: 0.59624 (0.50132) Boundary_loss: 0.015052 (0.015176) Loss: 0.61129 (0.51649) +2025-08-22,15:33:00 | INFO | Train Epoch: 5 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 0.44329 (0.50118) Boundary_loss: 0.014957 (0.015176) Loss: 0.45825 (0.51635) +2025-08-22,15:33:56 | INFO | Train Epoch: 5 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.59098 (0.50139) Boundary_loss: 0.015122 (0.015176) Loss: 0.60610 (0.51657) +2025-08-22,15:34:53 | INFO | Train Epoch: 5 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.42731 (0.50121) Boundary_loss: 0.015069 (0.015175) Loss: 0.44238 (0.51639) +2025-08-22,15:35:50 | INFO | Train Epoch: 5 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.338 Boundary Ratio: 0.247 Contrastive_loss: 0.49591 (0.50120) Boundary_loss: 0.015168 (0.015175) Loss: 0.51108 (0.51638) +2025-08-22,15:36:47 | INFO | Train Epoch: 5 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.43807 (0.50105) Boundary_loss: 0.015111 (0.015175) Loss: 0.45318 (0.51623) +2025-08-22,15:37:44 | INFO | Train Epoch: 5 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.434 Boundary Ratio: 0.247 Contrastive_loss: 0.42395 (0.50087) Boundary_loss: 0.015185 (0.015175) Loss: 0.43913 (0.51604) +2025-08-22,15:38:41 | INFO | Train Epoch: 5 [21453312/26365952 (81%)] Avg Boundaries (per batch): 47.891 Boundary Ratio: 0.244 Contrastive_loss: 0.46500 (0.50078) Boundary_loss: 0.015084 (0.015175) Loss: 0.48008 (0.51596) +2025-08-22,15:39:38 | INFO | Train Epoch: 5 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.44926 (0.50066) Boundary_loss: 0.015022 (0.015175) Loss: 0.46428 (0.51583) +2025-08-22,15:40:35 | INFO | Train Epoch: 5 [21555712/26365952 (82%)] Avg Boundaries (per batch): 49.408 Boundary Ratio: 0.252 Contrastive_loss: 0.46064 (0.50056) Boundary_loss: 0.014936 (0.015174) Loss: 0.47558 (0.51574) +2025-08-22,15:41:32 | INFO | Train Epoch: 5 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.244 Boundary Ratio: 0.246 Contrastive_loss: 0.48947 (0.50054) Boundary_loss: 0.015140 (0.015174) Loss: 0.50461 (0.51571) +2025-08-22,15:42:28 | INFO | Train Epoch: 5 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.336 Boundary Ratio: 0.247 Contrastive_loss: 0.44654 (0.50041) Boundary_loss: 0.015177 (0.015174) Loss: 0.46172 (0.51558) +2025-08-22,15:43:25 | INFO | Train Epoch: 5 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.40332 (0.50018) Boundary_loss: 0.015123 (0.015174) Loss: 0.41844 (0.51536) +2025-08-22,15:44:22 | INFO | Train Epoch: 5 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.52166 (0.50023) Boundary_loss: 0.015027 (0.015174) Loss: 0.53669 (0.51541) +2025-08-22,15:45:19 | INFO | Train Epoch: 5 [21811712/26365952 (83%)] Avg Boundaries (per batch): 49.326 Boundary Ratio: 0.252 Contrastive_loss: 0.46420 (0.50015) Boundary_loss: 0.015246 (0.015174) Loss: 0.47944 (0.51532) +2025-08-22,15:46:16 | INFO | Train Epoch: 5 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.45429 (0.50004) Boundary_loss: 0.015167 (0.015174) Loss: 0.46946 (0.51521) +2025-08-22,15:47:13 | INFO | Train Epoch: 5 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.152 Boundary Ratio: 0.246 Contrastive_loss: 0.43410 (0.49989) Boundary_loss: 0.015180 (0.015174) Loss: 0.44928 (0.51506) +2025-08-22,15:48:09 | INFO | Train Epoch: 5 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.48072 (0.49984) Boundary_loss: 0.015239 (0.015174) Loss: 0.49596 (0.51502) +2025-08-22,15:49:06 | INFO | Train Epoch: 5 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.44309 (0.49971) Boundary_loss: 0.015127 (0.015174) Loss: 0.45822 (0.51488) +2025-08-22,15:50:03 | INFO | Train Epoch: 5 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.51397 (0.49974) Boundary_loss: 0.015064 (0.015174) Loss: 0.52903 (0.51492) +2025-08-22,15:51:00 | INFO | Train Epoch: 5 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.53989 (0.49984) Boundary_loss: 0.015128 (0.015173) Loss: 0.55502 (0.51501) +2025-08-22,15:51:57 | INFO | Train Epoch: 5 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 0.56104 (0.49998) Boundary_loss: 0.015110 (0.015173) Loss: 0.57615 (0.51515) +2025-08-22,15:52:53 | INFO | Train Epoch: 5 [22221312/26365952 (84%)] Avg Boundaries (per batch): 47.744 Boundary Ratio: 0.244 Contrastive_loss: 0.44649 (0.49985) Boundary_loss: 0.015221 (0.015173) Loss: 0.46171 (0.51503) +2025-08-22,15:53:50 | INFO | Train Epoch: 5 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.48642 (0.49982) Boundary_loss: 0.015065 (0.015173) Loss: 0.50148 (0.51500) +2025-08-22,15:54:47 | INFO | Train Epoch: 5 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.50887 (0.49984) Boundary_loss: 0.015128 (0.015173) Loss: 0.52400 (0.51502) +2025-08-22,15:55:44 | INFO | Train Epoch: 5 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.50921 (0.49987) Boundary_loss: 0.015188 (0.015173) Loss: 0.52440 (0.51504) +2025-08-22,15:56:41 | INFO | Train Epoch: 5 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.55832 (0.50000) Boundary_loss: 0.015077 (0.015173) Loss: 0.57339 (0.51517) +2025-08-22,15:57:38 | INFO | Train Epoch: 5 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.45096 (0.49989) Boundary_loss: 0.015191 (0.015173) Loss: 0.46615 (0.51506) +2025-08-22,15:58:35 | INFO | Train Epoch: 5 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.54291 (0.49998) Boundary_loss: 0.015108 (0.015173) Loss: 0.55802 (0.51516) +2025-08-22,15:59:31 | INFO | Train Epoch: 5 [22579712/26365952 (86%)] Avg Boundaries (per batch): 49.367 Boundary Ratio: 0.252 Contrastive_loss: 0.50080 (0.49999) Boundary_loss: 0.015197 (0.015173) Loss: 0.51599 (0.51516) +2025-08-22,16:00:28 | INFO | Train Epoch: 5 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.44746 (0.49987) Boundary_loss: 0.015071 (0.015173) Loss: 0.46253 (0.51504) +2025-08-22,16:01:25 | INFO | Train Epoch: 5 [22682112/26365952 (86%)] Avg Boundaries (per batch): 49.615 Boundary Ratio: 0.253 Contrastive_loss: 0.54936 (0.49998) Boundary_loss: 0.015212 (0.015173) Loss: 0.56457 (0.51515) +2025-08-22,16:02:22 | INFO | Train Epoch: 5 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.42479 (0.49981) Boundary_loss: 0.015064 (0.015172) Loss: 0.43985 (0.51498) +2025-08-22,16:03:19 | INFO | Train Epoch: 5 [22784512/26365952 (86%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.47491 (0.49975) Boundary_loss: 0.015156 (0.015172) Loss: 0.49007 (0.51493) +2025-08-22,16:04:15 | INFO | Train Epoch: 5 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.50199 (0.49976) Boundary_loss: 0.015104 (0.015172) Loss: 0.51709 (0.51493) +2025-08-22,16:05:12 | INFO | Train Epoch: 5 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.53194 (0.49983) Boundary_loss: 0.015046 (0.015172) Loss: 0.54699 (0.51500) +2025-08-22,16:06:09 | INFO | Train Epoch: 5 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.49680 (0.49982) Boundary_loss: 0.015212 (0.015172) Loss: 0.51201 (0.51500) +2025-08-22,16:07:06 | INFO | Train Epoch: 5 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.45444 (0.49972) Boundary_loss: 0.015044 (0.015172) Loss: 0.46949 (0.51490) +2025-08-22,16:08:03 | INFO | Train Epoch: 5 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.47638 (0.49967) Boundary_loss: 0.015132 (0.015172) Loss: 0.49152 (0.51484) +2025-08-22,16:09:00 | INFO | Train Epoch: 5 [23091712/26365952 (88%)] Avg Boundaries (per batch): 49.684 Boundary Ratio: 0.253 Contrastive_loss: 0.50443 (0.49968) Boundary_loss: 0.015168 (0.015172) Loss: 0.51960 (0.51485) +2025-08-22,16:09:57 | INFO | Train Epoch: 5 [23142912/26365952 (88%)] Avg Boundaries (per batch): 49.793 Boundary Ratio: 0.254 Contrastive_loss: 0.46105 (0.49960) Boundary_loss: 0.015091 (0.015172) Loss: 0.47614 (0.51477) +2025-08-22,16:10:53 | INFO | Train Epoch: 5 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 0.49069 (0.49958) Boundary_loss: 0.015058 (0.015171) Loss: 0.50575 (0.51475) +2025-08-22,16:11:50 | INFO | Train Epoch: 5 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.53259 (0.49965) Boundary_loss: 0.014994 (0.015171) Loss: 0.54759 (0.51482) +2025-08-22,16:12:47 | INFO | Train Epoch: 5 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.182 Boundary Ratio: 0.246 Contrastive_loss: 0.46036 (0.49956) Boundary_loss: 0.015166 (0.015171) Loss: 0.47552 (0.51473) +2025-08-22,16:13:44 | INFO | Train Epoch: 5 [23347712/26365952 (89%)] Avg Boundaries (per batch): 49.576 Boundary Ratio: 0.253 Contrastive_loss: 0.49320 (0.49955) Boundary_loss: 0.015198 (0.015171) Loss: 0.50840 (0.51472) +2025-08-22,16:14:41 | INFO | Train Epoch: 5 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.047 Boundary Ratio: 0.245 Contrastive_loss: 0.44693 (0.49944) Boundary_loss: 0.015092 (0.015171) Loss: 0.46202 (0.51461) +2025-08-22,16:15:37 | INFO | Train Epoch: 5 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.471 Boundary Ratio: 0.252 Contrastive_loss: 0.51660 (0.49947) Boundary_loss: 0.015226 (0.015171) Loss: 0.53183 (0.51464) +2025-08-22,16:16:34 | INFO | Train Epoch: 5 [23501312/26365952 (89%)] Avg Boundaries (per batch): 49.479 Boundary Ratio: 0.252 Contrastive_loss: 0.42018 (0.49930) Boundary_loss: 0.015127 (0.015171) Loss: 0.43530 (0.51447) +2025-08-22,16:17:31 | INFO | Train Epoch: 5 [23552512/26365952 (89%)] Avg Boundaries (per batch): 49.641 Boundary Ratio: 0.253 Contrastive_loss: 0.50178 (0.49931) Boundary_loss: 0.015372 (0.015171) Loss: 0.51715 (0.51448) +2025-08-22,16:18:28 | INFO | Train Epoch: 5 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.46914 (0.49924) Boundary_loss: 0.015164 (0.015171) Loss: 0.48431 (0.51441) +2025-08-22,16:19:24 | INFO | Train Epoch: 5 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.55533 (0.49936) Boundary_loss: 0.015299 (0.015171) Loss: 0.57063 (0.51453) +2025-08-22,16:20:21 | INFO | Train Epoch: 5 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.141 Boundary Ratio: 0.246 Contrastive_loss: 0.40448 (0.49916) Boundary_loss: 0.015093 (0.015171) Loss: 0.41957 (0.51433) +2025-08-22,16:21:18 | INFO | Train Epoch: 5 [23757312/26365952 (90%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 0.48107 (0.49912) Boundary_loss: 0.015106 (0.015171) Loss: 0.49617 (0.51429) +2025-08-22,16:22:15 | INFO | Train Epoch: 5 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.40129 (0.49891) Boundary_loss: 0.015042 (0.015171) Loss: 0.41634 (0.51408) +2025-08-22,16:23:12 | INFO | Train Epoch: 5 [23859712/26365952 (90%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.41457 (0.49873) Boundary_loss: 0.015180 (0.015171) Loss: 0.42975 (0.51390) +2025-08-22,16:24:08 | INFO | Train Epoch: 5 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.56802 (0.49888) Boundary_loss: 0.015092 (0.015171) Loss: 0.58311 (0.51405) +2025-08-22,16:25:05 | INFO | Train Epoch: 5 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.39670 (0.49866) Boundary_loss: 0.015207 (0.015171) Loss: 0.41191 (0.51383) +2025-08-22,16:26:02 | INFO | Train Epoch: 5 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 0.45345 (0.49856) Boundary_loss: 0.015304 (0.015171) Loss: 0.46875 (0.51373) +2025-08-22,16:26:59 | INFO | Train Epoch: 5 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.47528 (0.49851) Boundary_loss: 0.015036 (0.015171) Loss: 0.49031 (0.51368) +2025-08-22,16:27:56 | INFO | Train Epoch: 5 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.131 Boundary Ratio: 0.246 Contrastive_loss: 0.44665 (0.49840) Boundary_loss: 0.015013 (0.015170) Loss: 0.46166 (0.51357) +2025-08-22,16:28:52 | INFO | Train Epoch: 5 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.44017 (0.49828) Boundary_loss: 0.015015 (0.015170) Loss: 0.45519 (0.51345) +2025-08-22,16:29:49 | INFO | Train Epoch: 5 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.699 Boundary Ratio: 0.254 Contrastive_loss: 0.46834 (0.49822) Boundary_loss: 0.015160 (0.015170) Loss: 0.48350 (0.51339) +2025-08-22,16:30:46 | INFO | Train Epoch: 5 [24269312/26365952 (92%)] Avg Boundaries (per batch): 47.736 Boundary Ratio: 0.244 Contrastive_loss: 0.49602 (0.49821) Boundary_loss: 0.015299 (0.015170) Loss: 0.51132 (0.51338) +2025-08-22,16:31:43 | INFO | Train Epoch: 5 [24320512/26365952 (92%)] Avg Boundaries (per batch): 49.367 Boundary Ratio: 0.252 Contrastive_loss: 0.49034 (0.49819) Boundary_loss: 0.015100 (0.015170) Loss: 0.50544 (0.51336) +2025-08-22,16:32:40 | INFO | Train Epoch: 5 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 0.52402 (0.49825) Boundary_loss: 0.015275 (0.015170) Loss: 0.53930 (0.51342) +2025-08-22,16:33:36 | INFO | Train Epoch: 5 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 0.60064 (0.49846) Boundary_loss: 0.015194 (0.015171) Loss: 0.61584 (0.51363) +2025-08-22,16:34:33 | INFO | Train Epoch: 5 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.58032 (0.49863) Boundary_loss: 0.015272 (0.015171) Loss: 0.59559 (0.51380) +2025-08-22,16:35:30 | INFO | Train Epoch: 5 [24525312/26365952 (93%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.47446 (0.49858) Boundary_loss: 0.015149 (0.015171) Loss: 0.48961 (0.51375) +2025-08-22,16:36:27 | INFO | Train Epoch: 5 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 0.52740 (0.49864) Boundary_loss: 0.015268 (0.015171) Loss: 0.54267 (0.51381) +2025-08-22,16:37:24 | INFO | Train Epoch: 5 [24627712/26365952 (93%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 0.44679 (0.49854) Boundary_loss: 0.015126 (0.015171) Loss: 0.46191 (0.51371) +2025-08-22,16:38:21 | INFO | Train Epoch: 5 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.46520 (0.49847) Boundary_loss: 0.015062 (0.015171) Loss: 0.48027 (0.51364) +2025-08-22,16:39:17 | INFO | Train Epoch: 5 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.36113 (0.49818) Boundary_loss: 0.015119 (0.015170) Loss: 0.37625 (0.51335) +2025-08-22,16:40:14 | INFO | Train Epoch: 5 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.47241 (0.49813) Boundary_loss: 0.015164 (0.015170) Loss: 0.48757 (0.51330) +2025-08-22,16:41:11 | INFO | Train Epoch: 5 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 0.47029 (0.49807) Boundary_loss: 0.015095 (0.015170) Loss: 0.48539 (0.51324) +2025-08-22,16:42:08 | INFO | Train Epoch: 5 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.47386 (0.49802) Boundary_loss: 0.015036 (0.015170) Loss: 0.48890 (0.51319) +2025-08-22,16:43:04 | INFO | Train Epoch: 5 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.43764 (0.49790) Boundary_loss: 0.015132 (0.015170) Loss: 0.45277 (0.51307) +2025-08-22,16:44:01 | INFO | Train Epoch: 5 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 0.44716 (0.49780) Boundary_loss: 0.015138 (0.015170) Loss: 0.46230 (0.51297) +2025-08-22,16:44:58 | INFO | Train Epoch: 5 [25037312/26365952 (95%)] Avg Boundaries (per batch): 49.750 Boundary Ratio: 0.254 Contrastive_loss: 0.47435 (0.49775) Boundary_loss: 0.015293 (0.015170) Loss: 0.48964 (0.51292) +2025-08-22,16:45:55 | INFO | Train Epoch: 5 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.56537 (0.49789) Boundary_loss: 0.015148 (0.015170) Loss: 0.58052 (0.51306) +2025-08-22,16:46:51 | INFO | Train Epoch: 5 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.40400 (0.49769) Boundary_loss: 0.015076 (0.015170) Loss: 0.41908 (0.51286) +2025-08-22,16:47:48 | INFO | Train Epoch: 5 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.43683 (0.49757) Boundary_loss: 0.015089 (0.015170) Loss: 0.45192 (0.51274) +2025-08-22,16:48:45 | INFO | Train Epoch: 5 [25242112/26365952 (96%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.44853 (0.49747) Boundary_loss: 0.015150 (0.015170) Loss: 0.46368 (0.51264) +2025-08-22,16:49:42 | INFO | Train Epoch: 5 [25293312/26365952 (96%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.45585 (0.49739) Boundary_loss: 0.015149 (0.015170) Loss: 0.47100 (0.51256) +2025-08-22,16:50:39 | INFO | Train Epoch: 5 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.387 Boundary Ratio: 0.252 Contrastive_loss: 0.51424 (0.49742) Boundary_loss: 0.015195 (0.015170) Loss: 0.52944 (0.51259) +2025-08-22,16:51:35 | INFO | Train Epoch: 5 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.56526 (0.49756) Boundary_loss: 0.015126 (0.015170) Loss: 0.58038 (0.51273) +2025-08-22,16:52:32 | INFO | Train Epoch: 5 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.47462 (0.49751) Boundary_loss: 0.015236 (0.015170) Loss: 0.48985 (0.51268) +2025-08-22,16:53:29 | INFO | Train Epoch: 5 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.375 Boundary Ratio: 0.252 Contrastive_loss: 0.46630 (0.49745) Boundary_loss: 0.015126 (0.015170) Loss: 0.48143 (0.51262) +2025-08-22,16:54:26 | INFO | Train Epoch: 5 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.42018 (0.49730) Boundary_loss: 0.015216 (0.015170) Loss: 0.43539 (0.51246) +2025-08-22,16:55:23 | INFO | Train Epoch: 5 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.43972 (0.49718) Boundary_loss: 0.015173 (0.015170) Loss: 0.45489 (0.51235) +2025-08-22,16:56:20 | INFO | Train Epoch: 5 [25651712/26365952 (97%)] Avg Boundaries (per batch): 49.211 Boundary Ratio: 0.251 Contrastive_loss: 0.51014 (0.49721) Boundary_loss: 0.015390 (0.015170) Loss: 0.52553 (0.51238) +2025-08-22,16:57:16 | INFO | Train Epoch: 5 [25702912/26365952 (97%)] Avg Boundaries (per batch): 49.381 Boundary Ratio: 0.252 Contrastive_loss: 0.40040 (0.49701) Boundary_loss: 0.015330 (0.015171) Loss: 0.41573 (0.51218) +2025-08-22,16:58:13 | INFO | Train Epoch: 5 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.57710 (0.49717) Boundary_loss: 0.015264 (0.015171) Loss: 0.59237 (0.51234) +2025-08-22,16:59:10 | INFO | Train Epoch: 5 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.43964 (0.49706) Boundary_loss: 0.015109 (0.015171) Loss: 0.45475 (0.51223) +2025-08-22,17:00:07 | INFO | Train Epoch: 5 [25856512/26365952 (98%)] Avg Boundaries (per batch): 49.512 Boundary Ratio: 0.253 Contrastive_loss: 0.49074 (0.49705) Boundary_loss: 0.015198 (0.015171) Loss: 0.50593 (0.51222) +2025-08-22,17:01:04 | INFO | Train Epoch: 5 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.42126 (0.49690) Boundary_loss: 0.015050 (0.015170) Loss: 0.43631 (0.51207) +2025-08-22,17:02:00 | INFO | Train Epoch: 5 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 0.42267 (0.49675) Boundary_loss: 0.015133 (0.015170) Loss: 0.43780 (0.51192) +2025-08-22,17:02:57 | INFO | Train Epoch: 5 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.52976 (0.49682) Boundary_loss: 0.015277 (0.015171) Loss: 0.54503 (0.51199) +2025-08-22,17:03:54 | INFO | Train Epoch: 5 [26061312/26365952 (99%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.56313 (0.49695) Boundary_loss: 0.015208 (0.015171) Loss: 0.57834 (0.51212) +2025-08-22,17:04:51 | INFO | Train Epoch: 5 [26112512/26365952 (99%)] Avg Boundaries (per batch): 49.525 Boundary Ratio: 0.253 Contrastive_loss: 0.46743 (0.49689) Boundary_loss: 0.015104 (0.015170) Loss: 0.48253 (0.51206) +2025-08-22,17:05:48 | INFO | Train Epoch: 5 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.58388 (0.49706) Boundary_loss: 0.015125 (0.015170) Loss: 0.59900 (0.51223) +2025-08-22,17:06:44 | INFO | Train Epoch: 5 [26214912/26365952 (99%)] Avg Boundaries (per batch): 49.281 Boundary Ratio: 0.251 Contrastive_loss: 0.51365 (0.49709) Boundary_loss: 0.015337 (0.015171) Loss: 0.52898 (0.51226) +2025-08-22,17:07:41 | INFO | Train Epoch: 5 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.463 Boundary Ratio: 0.252 Contrastive_loss: 0.55016 (0.49719) Boundary_loss: 0.015105 (0.015171) Loss: 0.56526 (0.51236) +2025-08-22,17:08:38 | INFO | Train Epoch: 5 [26317312/26365952 (100%)] Avg Boundaries (per batch): 47.961 Boundary Ratio: 0.245 Contrastive_loss: 0.41021 (0.49702) Boundary_loss: 0.015278 (0.015171) Loss: 0.42549 (0.51219) +2025-08-22,17:09:31 | INFO | Train Epoch: 5 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.43111 (0.49690) Boundary_loss: 0.015231 (0.015171) Loss: 0.44634 (0.51207) +2025-08-22,17:09:31 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-22,17:09:31 | INFO | [Epoch 5] Average Step Time: 0.571s | Average GPU Memory: 31.9 GB +2025-08-22,17:09:31 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-22,17:09:31 | INFO | Starting zero-shot imagenet. +2025-08-22,17:09:31 | INFO | Building zero-shot classifier +2025-08-22,17:09:41 | INFO | Using classifier +2025-08-22,17:10:23 | INFO | Finished zero-shot imagenet. +2025-08-22,17:10:23 | INFO | Eval Epoch: 6 imagenet-zeroshot-val-top1: 0.2502 imagenet-zeroshot-val-top5: 0.5000 +2025-08-22,17:10:24 | INFO | Start epoch 6 +2025-08-22,17:10:27 | INFO | Train Epoch: 6 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 0.40813 (0.40813) Boundary_loss: 0.015203 (0.015203) Loss: 0.42333 (0.42333) +2025-08-22,17:11:23 | INFO | Train Epoch: 6 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.46461 (0.43637) Boundary_loss: 0.015298 (0.015250) Loss: 0.47991 (0.45162) +2025-08-22,17:12:20 | INFO | Train Epoch: 6 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.43580 (0.43618) Boundary_loss: 0.015136 (0.015212) Loss: 0.45094 (0.45139) +2025-08-22,17:13:17 | INFO | Train Epoch: 6 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.158 Boundary Ratio: 0.246 Contrastive_loss: 0.44029 (0.43721) Boundary_loss: 0.015124 (0.015190) Loss: 0.45542 (0.45240) +2025-08-22,17:14:13 | INFO | Train Epoch: 6 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.45459 (0.44068) Boundary_loss: 0.015217 (0.015196) Loss: 0.46981 (0.45588) +2025-08-22,17:15:10 | INFO | Train Epoch: 6 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 47.865 Boundary Ratio: 0.244 Contrastive_loss: 0.32615 (0.42160) Boundary_loss: 0.015220 (0.015200) Loss: 0.34137 (0.43679) +2025-08-22,17:16:07 | INFO | Train Epoch: 6 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 0.46647 (0.42801) Boundary_loss: 0.015214 (0.015202) Loss: 0.48168 (0.44321) +2025-08-22,17:17:03 | INFO | Train Epoch: 6 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.49162 (0.43596) Boundary_loss: 0.015054 (0.015183) Loss: 0.50667 (0.45114) +2025-08-22,17:18:00 | INFO | Train Epoch: 6 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.39634 (0.43156) Boundary_loss: 0.015121 (0.015176) Loss: 0.41146 (0.44673) +2025-08-22,17:18:57 | INFO | Train Epoch: 6 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.174 Boundary Ratio: 0.246 Contrastive_loss: 0.49165 (0.43757) Boundary_loss: 0.015175 (0.015176) Loss: 0.50683 (0.45274) +2025-08-22,17:19:54 | INFO | Train Epoch: 6 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.42899 (0.43679) Boundary_loss: 0.015092 (0.015169) Loss: 0.44409 (0.45195) +2025-08-22,17:20:50 | INFO | Train Epoch: 6 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.47603 (0.44006) Boundary_loss: 0.014992 (0.015154) Loss: 0.49102 (0.45521) +2025-08-22,17:21:47 | INFO | Train Epoch: 6 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 0.40823 (0.43761) Boundary_loss: 0.015188 (0.015157) Loss: 0.42341 (0.45276) +2025-08-22,17:22:44 | INFO | Train Epoch: 6 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.55540 (0.44602) Boundary_loss: 0.014996 (0.015145) Loss: 0.57039 (0.46117) +2025-08-22,17:23:40 | INFO | Train Epoch: 6 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.39294 (0.44248) Boundary_loss: 0.015133 (0.015144) Loss: 0.40808 (0.45763) +2025-08-22,17:24:37 | INFO | Train Epoch: 6 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.45236 (0.44310) Boundary_loss: 0.015205 (0.015148) Loss: 0.46756 (0.45825) +2025-08-22,17:25:34 | INFO | Train Epoch: 6 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.38566 (0.43972) Boundary_loss: 0.015268 (0.015155) Loss: 0.40093 (0.45488) +2025-08-22,17:26:31 | INFO | Train Epoch: 6 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.361 Boundary Ratio: 0.247 Contrastive_loss: 0.51002 (0.44363) Boundary_loss: 0.015186 (0.015157) Loss: 0.52520 (0.45878) +2025-08-22,17:27:28 | INFO | Train Epoch: 6 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.33675 (0.43800) Boundary_loss: 0.015194 (0.015159) Loss: 0.35195 (0.45316) +2025-08-22,17:28:24 | INFO | Train Epoch: 6 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.39926 (0.43606) Boundary_loss: 0.015113 (0.015157) Loss: 0.41438 (0.45122) +2025-08-22,17:29:21 | INFO | Train Epoch: 6 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.41418 (0.43502) Boundary_loss: 0.015175 (0.015157) Loss: 0.42936 (0.45018) +2025-08-22,17:30:18 | INFO | Train Epoch: 6 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 0.44010 (0.43525) Boundary_loss: 0.015301 (0.015164) Loss: 0.45540 (0.45042) +2025-08-22,17:31:15 | INFO | Train Epoch: 6 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.41983 (0.43458) Boundary_loss: 0.015308 (0.015170) Loss: 0.43514 (0.44975) +2025-08-22,17:32:12 | INFO | Train Epoch: 6 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.41543 (0.43378) Boundary_loss: 0.015208 (0.015172) Loss: 0.43064 (0.44896) +2025-08-22,17:33:08 | INFO | Train Epoch: 6 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.42143 (0.43329) Boundary_loss: 0.015156 (0.015171) Loss: 0.43659 (0.44846) +2025-08-22,17:34:05 | INFO | Train Epoch: 6 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 0.35634 (0.43033) Boundary_loss: 0.015253 (0.015174) Loss: 0.37160 (0.44551) +2025-08-22,17:35:02 | INFO | Train Epoch: 6 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.057 Boundary Ratio: 0.245 Contrastive_loss: 0.44133 (0.43074) Boundary_loss: 0.015052 (0.015170) Loss: 0.45639 (0.44591) +2025-08-22,17:35:59 | INFO | Train Epoch: 6 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.40088 (0.42967) Boundary_loss: 0.015142 (0.015169) Loss: 0.41602 (0.44484) +2025-08-22,17:36:56 | INFO | Train Epoch: 6 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.41458 (0.42915) Boundary_loss: 0.015124 (0.015167) Loss: 0.42970 (0.44432) +2025-08-22,17:37:52 | INFO | Train Epoch: 6 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.35859 (0.42680) Boundary_loss: 0.015212 (0.015169) Loss: 0.37381 (0.44197) +2025-08-22,17:38:49 | INFO | Train Epoch: 6 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.47746 (0.42843) Boundary_loss: 0.015155 (0.015168) Loss: 0.49261 (0.44360) +2025-08-22,17:39:46 | INFO | Train Epoch: 6 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.37627 (0.42680) Boundary_loss: 0.015128 (0.015167) Loss: 0.39140 (0.44197) +2025-08-22,17:40:43 | INFO | Train Epoch: 6 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.38342 (0.42549) Boundary_loss: 0.015095 (0.015165) Loss: 0.39852 (0.44065) +2025-08-22,17:41:40 | INFO | Train Epoch: 6 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 47.889 Boundary Ratio: 0.244 Contrastive_loss: 0.48832 (0.42734) Boundary_loss: 0.015231 (0.015167) Loss: 0.50355 (0.44250) +2025-08-22,17:42:37 | INFO | Train Epoch: 6 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 0.39049 (0.42628) Boundary_loss: 0.015145 (0.015166) Loss: 0.40563 (0.44145) +2025-08-22,17:43:33 | INFO | Train Epoch: 6 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 49.451 Boundary Ratio: 0.252 Contrastive_loss: 0.37137 (0.42476) Boundary_loss: 0.015234 (0.015168) Loss: 0.38660 (0.43993) +2025-08-22,17:44:30 | INFO | Train Epoch: 6 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.42708 (0.42482) Boundary_loss: 0.015271 (0.015171) Loss: 0.44235 (0.43999) +2025-08-22,17:45:27 | INFO | Train Epoch: 6 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 0.40466 (0.42429) Boundary_loss: 0.015026 (0.015167) Loss: 0.41968 (0.43946) +2025-08-22,17:46:24 | INFO | Train Epoch: 6 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 0.29380 (0.42095) Boundary_loss: 0.015292 (0.015170) Loss: 0.30909 (0.43612) +2025-08-22,17:47:20 | INFO | Train Epoch: 6 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.42227 (0.42098) Boundary_loss: 0.015227 (0.015172) Loss: 0.43750 (0.43615) +2025-08-22,17:48:17 | INFO | Train Epoch: 6 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.54825 (0.42408) Boundary_loss: 0.015120 (0.015170) Loss: 0.56337 (0.43925) +2025-08-22,17:49:14 | INFO | Train Epoch: 6 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.289 Boundary Ratio: 0.246 Contrastive_loss: 0.40558 (0.42364) Boundary_loss: 0.015263 (0.015173) Loss: 0.42084 (0.43881) +2025-08-22,17:50:10 | INFO | Train Epoch: 6 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.51106 (0.42567) Boundary_loss: 0.015130 (0.015172) Loss: 0.52619 (0.44085) +2025-08-22,17:51:07 | INFO | Train Epoch: 6 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.46358 (0.42654) Boundary_loss: 0.015117 (0.015170) Loss: 0.47869 (0.44171) +2025-08-22,17:52:04 | INFO | Train Epoch: 6 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 49.514 Boundary Ratio: 0.253 Contrastive_loss: 0.45157 (0.42709) Boundary_loss: 0.015334 (0.015174) Loss: 0.46690 (0.44227) +2025-08-22,17:53:00 | INFO | Train Epoch: 6 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.45422 (0.42768) Boundary_loss: 0.015146 (0.015173) Loss: 0.46936 (0.44286) +2025-08-22,17:53:57 | INFO | Train Epoch: 6 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 0.43669 (0.42787) Boundary_loss: 0.015174 (0.015173) Loss: 0.45186 (0.44305) +2025-08-22,17:54:54 | INFO | Train Epoch: 6 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.47138 (0.42878) Boundary_loss: 0.015251 (0.015175) Loss: 0.48663 (0.44396) +2025-08-22,17:55:51 | INFO | Train Epoch: 6 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.38587 (0.42790) Boundary_loss: 0.015249 (0.015177) Loss: 0.40112 (0.44308) +2025-08-22,17:56:47 | INFO | Train Epoch: 6 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.45816 (0.42851) Boundary_loss: 0.015201 (0.015177) Loss: 0.47336 (0.44369) +2025-08-22,17:57:44 | INFO | Train Epoch: 6 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.44265 (0.42879) Boundary_loss: 0.015153 (0.015177) Loss: 0.45781 (0.44396) +2025-08-22,17:58:41 | INFO | Train Epoch: 6 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 49.465 Boundary Ratio: 0.252 Contrastive_loss: 0.42571 (0.42873) Boundary_loss: 0.015027 (0.015174) Loss: 0.44074 (0.44390) +2025-08-22,17:59:38 | INFO | Train Epoch: 6 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.41226 (0.42842) Boundary_loss: 0.015055 (0.015171) Loss: 0.42731 (0.44359) +2025-08-22,18:00:34 | INFO | Train Epoch: 6 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 47.994 Boundary Ratio: 0.245 Contrastive_loss: 0.36889 (0.42731) Boundary_loss: 0.015161 (0.015171) Loss: 0.38406 (0.44249) +2025-08-22,18:01:31 | INFO | Train Epoch: 6 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 49.324 Boundary Ratio: 0.252 Contrastive_loss: 0.40356 (0.42688) Boundary_loss: 0.015203 (0.015172) Loss: 0.41876 (0.44205) +2025-08-22,18:02:28 | INFO | Train Epoch: 6 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.40416 (0.42648) Boundary_loss: 0.015179 (0.015172) Loss: 0.41934 (0.44165) +2025-08-22,18:03:25 | INFO | Train Epoch: 6 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.029 Boundary Ratio: 0.245 Contrastive_loss: 0.47944 (0.42741) Boundary_loss: 0.015158 (0.015172) Loss: 0.49460 (0.44258) +2025-08-22,18:04:21 | INFO | Train Epoch: 6 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.50049 (0.42867) Boundary_loss: 0.015241 (0.015173) Loss: 0.51573 (0.44384) +2025-08-22,18:05:18 | INFO | Train Epoch: 6 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 47.725 Boundary Ratio: 0.243 Contrastive_loss: 0.36503 (0.42759) Boundary_loss: 0.015161 (0.015173) Loss: 0.38019 (0.44276) +2025-08-22,18:06:15 | INFO | Train Epoch: 6 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.39687 (0.42708) Boundary_loss: 0.015041 (0.015170) Loss: 0.41191 (0.44225) +2025-08-22,18:07:12 | INFO | Train Epoch: 6 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.46440 (0.42769) Boundary_loss: 0.015121 (0.015170) Loss: 0.47952 (0.44286) +2025-08-22,18:08:09 | INFO | Train Epoch: 6 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.51781 (0.42914) Boundary_loss: 0.015123 (0.015169) Loss: 0.53293 (0.44431) +2025-08-22,18:09:05 | INFO | Train Epoch: 6 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.39852 (0.42865) Boundary_loss: 0.015257 (0.015170) Loss: 0.41378 (0.44383) +2025-08-22,18:10:02 | INFO | Train Epoch: 6 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.33961 (0.42726) Boundary_loss: 0.014938 (0.015167) Loss: 0.35455 (0.44243) +2025-08-22,18:10:59 | INFO | Train Epoch: 6 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 49.482 Boundary Ratio: 0.252 Contrastive_loss: 0.42510 (0.42723) Boundary_loss: 0.015069 (0.015165) Loss: 0.44017 (0.44240) +2025-08-22,18:11:55 | INFO | Train Epoch: 6 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.35868 (0.42619) Boundary_loss: 0.015093 (0.015164) Loss: 0.37377 (0.44136) +2025-08-22,18:12:52 | INFO | Train Epoch: 6 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.40127 (0.42582) Boundary_loss: 0.015169 (0.015164) Loss: 0.41644 (0.44098) +2025-08-22,18:13:49 | INFO | Train Epoch: 6 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 47.941 Boundary Ratio: 0.245 Contrastive_loss: 0.43912 (0.42602) Boundary_loss: 0.015135 (0.015164) Loss: 0.45425 (0.44118) +2025-08-22,18:14:45 | INFO | Train Epoch: 6 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.150 Boundary Ratio: 0.246 Contrastive_loss: 0.50049 (0.42709) Boundary_loss: 0.015160 (0.015164) Loss: 0.51565 (0.44226) +2025-08-22,18:15:42 | INFO | Train Epoch: 6 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.176 Boundary Ratio: 0.246 Contrastive_loss: 0.41396 (0.42691) Boundary_loss: 0.015179 (0.015164) Loss: 0.42914 (0.44207) +2025-08-22,18:16:39 | INFO | Train Epoch: 6 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.38784 (0.42636) Boundary_loss: 0.015070 (0.015163) Loss: 0.40291 (0.44152) +2025-08-22,18:17:35 | INFO | Train Epoch: 6 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.951 Boundary Ratio: 0.255 Contrastive_loss: 0.43645 (0.42650) Boundary_loss: 0.015313 (0.015165) Loss: 0.45176 (0.44166) +2025-08-22,18:18:32 | INFO | Train Epoch: 6 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 0.39033 (0.42600) Boundary_loss: 0.015202 (0.015165) Loss: 0.40553 (0.44117) +2025-08-22,18:19:29 | INFO | Train Epoch: 6 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.34379 (0.42489) Boundary_loss: 0.015205 (0.015166) Loss: 0.35899 (0.44006) +2025-08-22,18:20:25 | INFO | Train Epoch: 6 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 49.562 Boundary Ratio: 0.253 Contrastive_loss: 0.54251 (0.42646) Boundary_loss: 0.015123 (0.015165) Loss: 0.55764 (0.44162) +2025-08-22,18:21:22 | INFO | Train Epoch: 6 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.39317 (0.42602) Boundary_loss: 0.015132 (0.015165) Loss: 0.40830 (0.44119) +2025-08-22,18:22:19 | INFO | Train Epoch: 6 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.41365 (0.42586) Boundary_loss: 0.015328 (0.015167) Loss: 0.42898 (0.44103) +2025-08-22,18:23:16 | INFO | Train Epoch: 6 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.35988 (0.42501) Boundary_loss: 0.015241 (0.015168) Loss: 0.37512 (0.44018) +2025-08-22,18:24:12 | INFO | Train Epoch: 6 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 0.40336 (0.42474) Boundary_loss: 0.015175 (0.015168) Loss: 0.41854 (0.43991) +2025-08-22,18:25:09 | INFO | Train Epoch: 6 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 47.877 Boundary Ratio: 0.244 Contrastive_loss: 0.41039 (0.42456) Boundary_loss: 0.015088 (0.015167) Loss: 0.42548 (0.43973) +2025-08-22,18:26:06 | INFO | Train Epoch: 6 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.39547 (0.42420) Boundary_loss: 0.015116 (0.015166) Loss: 0.41058 (0.43937) +2025-08-22,18:27:03 | INFO | Train Epoch: 6 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.252 Boundary Ratio: 0.246 Contrastive_loss: 0.44388 (0.42444) Boundary_loss: 0.015121 (0.015166) Loss: 0.45901 (0.43961) +2025-08-22,18:28:00 | INFO | Train Epoch: 6 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.34326 (0.42346) Boundary_loss: 0.015216 (0.015166) Loss: 0.35848 (0.43863) +2025-08-22,18:28:56 | INFO | Train Epoch: 6 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.37238 (0.42286) Boundary_loss: 0.015203 (0.015167) Loss: 0.38758 (0.43802) +2025-08-22,18:29:53 | INFO | Train Epoch: 6 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.38013 (0.42235) Boundary_loss: 0.015348 (0.015169) Loss: 0.39548 (0.43752) +2025-08-22,18:30:50 | INFO | Train Epoch: 6 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.42773 (0.42242) Boundary_loss: 0.015034 (0.015167) Loss: 0.44276 (0.43758) +2025-08-22,18:31:47 | INFO | Train Epoch: 6 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.38278 (0.42196) Boundary_loss: 0.015230 (0.015168) Loss: 0.39801 (0.43713) +2025-08-22,18:32:43 | INFO | Train Epoch: 6 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.37114 (0.42138) Boundary_loss: 0.015213 (0.015169) Loss: 0.38635 (0.43655) +2025-08-22,18:33:40 | INFO | Train Epoch: 6 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 0.47446 (0.42198) Boundary_loss: 0.015136 (0.015168) Loss: 0.48960 (0.43715) +2025-08-22,18:34:37 | INFO | Train Epoch: 6 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.47864 (0.42261) Boundary_loss: 0.015052 (0.015167) Loss: 0.49369 (0.43778) +2025-08-22,18:35:34 | INFO | Train Epoch: 6 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 47.930 Boundary Ratio: 0.245 Contrastive_loss: 0.41043 (0.42247) Boundary_loss: 0.015286 (0.015168) Loss: 0.42572 (0.43764) +2025-08-22,18:36:31 | INFO | Train Epoch: 6 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.47408 (0.42304) Boundary_loss: 0.015242 (0.015169) Loss: 0.48932 (0.43820) +2025-08-22,18:37:27 | INFO | Train Epoch: 6 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.41076 (0.42290) Boundary_loss: 0.015087 (0.015168) Loss: 0.42585 (0.43807) +2025-08-22,18:38:24 | INFO | Train Epoch: 6 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 0.44102 (0.42310) Boundary_loss: 0.015003 (0.015166) Loss: 0.45603 (0.43826) +2025-08-22,18:39:21 | INFO | Train Epoch: 6 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 0.48327 (0.42373) Boundary_loss: 0.015182 (0.015167) Loss: 0.49845 (0.43890) +2025-08-22,18:40:18 | INFO | Train Epoch: 6 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.47014 (0.42421) Boundary_loss: 0.015245 (0.015167) Loss: 0.48539 (0.43938) +2025-08-22,18:41:15 | INFO | Train Epoch: 6 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.35473 (0.42350) Boundary_loss: 0.015142 (0.015167) Loss: 0.36987 (0.43866) +2025-08-22,18:42:11 | INFO | Train Epoch: 6 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.38940 (0.42315) Boundary_loss: 0.015095 (0.015166) Loss: 0.40449 (0.43832) +2025-08-22,18:43:08 | INFO | Train Epoch: 6 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 0.39804 (0.42290) Boundary_loss: 0.015073 (0.015165) Loss: 0.41311 (0.43806) +2025-08-22,18:44:05 | INFO | Train Epoch: 6 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.37364 (0.42240) Boundary_loss: 0.014975 (0.015163) Loss: 0.38862 (0.43757) +2025-08-22,18:45:02 | INFO | Train Epoch: 6 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.33877 (0.42157) Boundary_loss: 0.015083 (0.015163) Loss: 0.35385 (0.43674) +2025-08-22,18:45:59 | INFO | Train Epoch: 6 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.41974 (0.42156) Boundary_loss: 0.015146 (0.015163) Loss: 0.43488 (0.43672) +2025-08-22,18:46:55 | INFO | Train Epoch: 6 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.38058 (0.42116) Boundary_loss: 0.015105 (0.015162) Loss: 0.39568 (0.43632) +2025-08-22,18:47:52 | INFO | Train Epoch: 6 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.207 Boundary Ratio: 0.246 Contrastive_loss: 0.40708 (0.42102) Boundary_loss: 0.015224 (0.015163) Loss: 0.42231 (0.43619) +2025-08-22,18:48:49 | INFO | Train Epoch: 6 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.37552 (0.42059) Boundary_loss: 0.015080 (0.015162) Loss: 0.39060 (0.43575) +2025-08-22,18:49:46 | INFO | Train Epoch: 6 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.41950 (0.42058) Boundary_loss: 0.015008 (0.015160) Loss: 0.43451 (0.43574) +2025-08-22,18:50:43 | INFO | Train Epoch: 6 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.39790 (0.42037) Boundary_loss: 0.015106 (0.015160) Loss: 0.41301 (0.43553) +2025-08-22,18:51:39 | INFO | Train Epoch: 6 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.38330 (0.42002) Boundary_loss: 0.015146 (0.015160) Loss: 0.39845 (0.43518) +2025-08-22,18:52:36 | INFO | Train Epoch: 6 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.46060 (0.42040) Boundary_loss: 0.015030 (0.015159) Loss: 0.47563 (0.43556) +2025-08-22,18:53:33 | INFO | Train Epoch: 6 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.242 Boundary Ratio: 0.246 Contrastive_loss: 0.35563 (0.41981) Boundary_loss: 0.015011 (0.015157) Loss: 0.37064 (0.43497) +2025-08-22,18:54:30 | INFO | Train Epoch: 6 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.48985 (0.42044) Boundary_loss: 0.015126 (0.015157) Loss: 0.50498 (0.43560) +2025-08-22,18:55:27 | INFO | Train Epoch: 6 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.41205 (0.42036) Boundary_loss: 0.015185 (0.015157) Loss: 0.42724 (0.43552) +2025-08-22,18:56:23 | INFO | Train Epoch: 6 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.56347 (0.42163) Boundary_loss: 0.015104 (0.015157) Loss: 0.57858 (0.43679) +2025-08-22,18:57:20 | INFO | Train Epoch: 6 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.41403 (0.42156) Boundary_loss: 0.015075 (0.015156) Loss: 0.42911 (0.43672) +2025-08-22,18:58:17 | INFO | Train Epoch: 6 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.47427 (0.42202) Boundary_loss: 0.015157 (0.015156) Loss: 0.48943 (0.43718) +2025-08-22,18:59:13 | INFO | Train Epoch: 6 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.35889 (0.42148) Boundary_loss: 0.015121 (0.015156) Loss: 0.37401 (0.43663) +2025-08-22,19:00:10 | INFO | Train Epoch: 6 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.45742 (0.42179) Boundary_loss: 0.015092 (0.015155) Loss: 0.47251 (0.43694) +2025-08-22,19:01:07 | INFO | Train Epoch: 6 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.332 Boundary Ratio: 0.247 Contrastive_loss: 0.44897 (0.42202) Boundary_loss: 0.015203 (0.015156) Loss: 0.46417 (0.43717) +2025-08-22,19:02:04 | INFO | Train Epoch: 6 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.40783 (0.42190) Boundary_loss: 0.015142 (0.015155) Loss: 0.42297 (0.43705) +2025-08-22,19:03:00 | INFO | Train Epoch: 6 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.37863 (0.42154) Boundary_loss: 0.015062 (0.015155) Loss: 0.39369 (0.43669) +2025-08-22,19:03:57 | INFO | Train Epoch: 6 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.41495 (0.42148) Boundary_loss: 0.015035 (0.015154) Loss: 0.42998 (0.43664) +2025-08-22,19:04:54 | INFO | Train Epoch: 6 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 47.846 Boundary Ratio: 0.244 Contrastive_loss: 0.49062 (0.42205) Boundary_loss: 0.015236 (0.015154) Loss: 0.50586 (0.43720) +2025-08-22,19:05:51 | INFO | Train Epoch: 6 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.41961 (0.42203) Boundary_loss: 0.015173 (0.015154) Loss: 0.43479 (0.43718) +2025-08-22,19:06:48 | INFO | Train Epoch: 6 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 49.537 Boundary Ratio: 0.253 Contrastive_loss: 0.40221 (0.42187) Boundary_loss: 0.015132 (0.015154) Loss: 0.41735 (0.43702) +2025-08-22,19:07:44 | INFO | Train Epoch: 6 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.42694 (0.42191) Boundary_loss: 0.015263 (0.015155) Loss: 0.44220 (0.43706) +2025-08-22,19:08:41 | INFO | Train Epoch: 6 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.32386 (0.42113) Boundary_loss: 0.015123 (0.015155) Loss: 0.33898 (0.43629) +2025-08-22,19:09:38 | INFO | Train Epoch: 6 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.41697 (0.42110) Boundary_loss: 0.015106 (0.015154) Loss: 0.43207 (0.43625) +2025-08-22,19:10:35 | INFO | Train Epoch: 6 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.43661 (0.42122) Boundary_loss: 0.015076 (0.015154) Loss: 0.45169 (0.43637) +2025-08-22,19:11:32 | INFO | Train Epoch: 6 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.41632 (0.42118) Boundary_loss: 0.014936 (0.015152) Loss: 0.43126 (0.43633) +2025-08-22,19:12:29 | INFO | Train Epoch: 6 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.42662 (0.42122) Boundary_loss: 0.015182 (0.015152) Loss: 0.44180 (0.43638) +2025-08-22,19:13:26 | INFO | Train Epoch: 6 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.39461 (0.42102) Boundary_loss: 0.015174 (0.015153) Loss: 0.40978 (0.43617) +2025-08-22,19:14:22 | INFO | Train Epoch: 6 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.37760 (0.42069) Boundary_loss: 0.015055 (0.015152) Loss: 0.39265 (0.43584) +2025-08-22,19:15:19 | INFO | Train Epoch: 6 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.39015 (0.42046) Boundary_loss: 0.015074 (0.015151) Loss: 0.40522 (0.43561) +2025-08-22,19:16:16 | INFO | Train Epoch: 6 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 0.51069 (0.42113) Boundary_loss: 0.015156 (0.015151) Loss: 0.52585 (0.43629) +2025-08-22,19:17:13 | INFO | Train Epoch: 6 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.38815 (0.42089) Boundary_loss: 0.015087 (0.015151) Loss: 0.40323 (0.43604) +2025-08-22,19:18:10 | INFO | Train Epoch: 6 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.184 Boundary Ratio: 0.246 Contrastive_loss: 0.44532 (0.42107) Boundary_loss: 0.015090 (0.015150) Loss: 0.46041 (0.43622) +2025-08-22,19:19:06 | INFO | Train Epoch: 6 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.44700 (0.42126) Boundary_loss: 0.015074 (0.015150) Loss: 0.46207 (0.43641) +2025-08-22,19:20:03 | INFO | Train Epoch: 6 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.48823 (0.42174) Boundary_loss: 0.015074 (0.015149) Loss: 0.50330 (0.43689) +2025-08-22,19:21:00 | INFO | Train Epoch: 6 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.44440 (0.42191) Boundary_loss: 0.015197 (0.015150) Loss: 0.45959 (0.43706) +2025-08-22,19:21:57 | INFO | Train Epoch: 6 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.34567 (0.42136) Boundary_loss: 0.015155 (0.015150) Loss: 0.36082 (0.43651) +2025-08-22,19:22:54 | INFO | Train Epoch: 6 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.46168 (0.42165) Boundary_loss: 0.015368 (0.015151) Loss: 0.47705 (0.43680) +2025-08-22,19:23:51 | INFO | Train Epoch: 6 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.40743 (0.42155) Boundary_loss: 0.015155 (0.015151) Loss: 0.42259 (0.43670) +2025-08-22,19:24:47 | INFO | Train Epoch: 6 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.42007 (0.42154) Boundary_loss: 0.015117 (0.015151) Loss: 0.43519 (0.43669) +2025-08-22,19:25:44 | INFO | Train Epoch: 6 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.34521 (0.42101) Boundary_loss: 0.015029 (0.015150) Loss: 0.36024 (0.43616) +2025-08-22,19:26:41 | INFO | Train Epoch: 6 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.33388 (0.42041) Boundary_loss: 0.015098 (0.015150) Loss: 0.34898 (0.43556) +2025-08-22,19:27:37 | INFO | Train Epoch: 6 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.699 Boundary Ratio: 0.254 Contrastive_loss: 0.43045 (0.42048) Boundary_loss: 0.015300 (0.015151) Loss: 0.44575 (0.43563) +2025-08-22,19:28:34 | INFO | Train Epoch: 6 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.41074 (0.42041) Boundary_loss: 0.015076 (0.015150) Loss: 0.42581 (0.43556) +2025-08-22,19:29:31 | INFO | Train Epoch: 6 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 0.46849 (0.42073) Boundary_loss: 0.015109 (0.015150) Loss: 0.48360 (0.43588) +2025-08-22,19:30:28 | INFO | Train Epoch: 6 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 47.912 Boundary Ratio: 0.244 Contrastive_loss: 0.41546 (0.42070) Boundary_loss: 0.015148 (0.015150) Loss: 0.43060 (0.43585) +2025-08-22,19:31:25 | INFO | Train Epoch: 6 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.072 Boundary Ratio: 0.245 Contrastive_loss: 0.33908 (0.42016) Boundary_loss: 0.015291 (0.015151) Loss: 0.35437 (0.43531) +2025-08-22,19:32:21 | INFO | Train Epoch: 6 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 49.477 Boundary Ratio: 0.252 Contrastive_loss: 0.40758 (0.42007) Boundary_loss: 0.015180 (0.015151) Loss: 0.42276 (0.43522) +2025-08-22,19:33:18 | INFO | Train Epoch: 6 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.43247 (0.42015) Boundary_loss: 0.015095 (0.015151) Loss: 0.44756 (0.43530) +2025-08-22,19:34:15 | INFO | Train Epoch: 6 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.33905 (0.41962) Boundary_loss: 0.015164 (0.015151) Loss: 0.35421 (0.43477) +2025-08-22,19:35:12 | INFO | Train Epoch: 6 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.44931 (0.41982) Boundary_loss: 0.015141 (0.015151) Loss: 0.46445 (0.43497) +2025-08-22,19:36:09 | INFO | Train Epoch: 6 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.41680 (0.41980) Boundary_loss: 0.015180 (0.015151) Loss: 0.43198 (0.43495) +2025-08-22,19:37:05 | INFO | Train Epoch: 6 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.38038 (0.41954) Boundary_loss: 0.015139 (0.015151) Loss: 0.39552 (0.43470) +2025-08-22,19:38:02 | INFO | Train Epoch: 6 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.39027 (0.41936) Boundary_loss: 0.015087 (0.015151) Loss: 0.40536 (0.43451) +2025-08-22,19:38:59 | INFO | Train Epoch: 6 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.000 Boundary Ratio: 0.245 Contrastive_loss: 0.41379 (0.41932) Boundary_loss: 0.015235 (0.015151) Loss: 0.42903 (0.43447) +2025-08-22,19:39:56 | INFO | Train Epoch: 6 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.45102 (0.41952) Boundary_loss: 0.015005 (0.015150) Loss: 0.46602 (0.43467) +2025-08-22,19:40:53 | INFO | Train Epoch: 6 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.40603 (0.41944) Boundary_loss: 0.015161 (0.015150) Loss: 0.42119 (0.43459) +2025-08-22,19:41:50 | INFO | Train Epoch: 6 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 0.41266 (0.41940) Boundary_loss: 0.015148 (0.015150) Loss: 0.42781 (0.43455) +2025-08-22,19:42:46 | INFO | Train Epoch: 6 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.54782 (0.42019) Boundary_loss: 0.015278 (0.015151) Loss: 0.56310 (0.43534) +2025-08-22,19:43:43 | INFO | Train Epoch: 6 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.348 Boundary Ratio: 0.247 Contrastive_loss: 0.42763 (0.42023) Boundary_loss: 0.015174 (0.015151) Loss: 0.44281 (0.43538) +2025-08-22,19:44:40 | INFO | Train Epoch: 6 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 47.994 Boundary Ratio: 0.245 Contrastive_loss: 0.49051 (0.42066) Boundary_loss: 0.015265 (0.015152) Loss: 0.50577 (0.43581) +2025-08-22,19:45:37 | INFO | Train Epoch: 6 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.40521 (0.42057) Boundary_loss: 0.014958 (0.015151) Loss: 0.42017 (0.43572) +2025-08-22,19:46:34 | INFO | Train Epoch: 6 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.322 Boundary Ratio: 0.247 Contrastive_loss: 0.48016 (0.42093) Boundary_loss: 0.015172 (0.015151) Loss: 0.49533 (0.43608) +2025-08-22,19:47:31 | INFO | Train Epoch: 6 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.43551 (0.42101) Boundary_loss: 0.015079 (0.015150) Loss: 0.45059 (0.43617) +2025-08-22,19:48:27 | INFO | Train Epoch: 6 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.43314 (0.42109) Boundary_loss: 0.015115 (0.015150) Loss: 0.44826 (0.43624) +2025-08-22,19:49:24 | INFO | Train Epoch: 6 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 49.496 Boundary Ratio: 0.253 Contrastive_loss: 0.44014 (0.42120) Boundary_loss: 0.015025 (0.015149) Loss: 0.45517 (0.43635) +2025-08-22,19:50:21 | INFO | Train Epoch: 6 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.43625 (0.42129) Boundary_loss: 0.015072 (0.015149) Loss: 0.45132 (0.43644) +2025-08-22,19:51:18 | INFO | Train Epoch: 6 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.46614 (0.42155) Boundary_loss: 0.014993 (0.015148) Loss: 0.48113 (0.43670) +2025-08-22,19:52:15 | INFO | Train Epoch: 6 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.45767 (0.42176) Boundary_loss: 0.015136 (0.015148) Loss: 0.47281 (0.43691) +2025-08-22,19:53:11 | INFO | Train Epoch: 6 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 0.37903 (0.42151) Boundary_loss: 0.015181 (0.015148) Loss: 0.39421 (0.43666) +2025-08-22,19:54:08 | INFO | Train Epoch: 6 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 49.531 Boundary Ratio: 0.253 Contrastive_loss: 0.45628 (0.42171) Boundary_loss: 0.015251 (0.015149) Loss: 0.47154 (0.43686) +2025-08-22,19:55:05 | INFO | Train Epoch: 6 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.48872 (0.42210) Boundary_loss: 0.015115 (0.015149) Loss: 0.50384 (0.43724) +2025-08-22,19:56:02 | INFO | Train Epoch: 6 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.39270 (0.42193) Boundary_loss: 0.015166 (0.015149) Loss: 0.40787 (0.43708) +2025-08-22,19:56:59 | INFO | Train Epoch: 6 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.197 Boundary Ratio: 0.246 Contrastive_loss: 0.43046 (0.42198) Boundary_loss: 0.014996 (0.015148) Loss: 0.44546 (0.43713) +2025-08-22,19:57:56 | INFO | Train Epoch: 6 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.41947 (0.42196) Boundary_loss: 0.015104 (0.015148) Loss: 0.43457 (0.43711) +2025-08-22,19:58:52 | INFO | Train Epoch: 6 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.32395 (0.42142) Boundary_loss: 0.015286 (0.015148) Loss: 0.33923 (0.43656) +2025-08-22,19:59:49 | INFO | Train Epoch: 6 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.42396 (0.42143) Boundary_loss: 0.015240 (0.015149) Loss: 0.43920 (0.43658) +2025-08-22,20:00:46 | INFO | Train Epoch: 6 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.43096 (0.42148) Boundary_loss: 0.015001 (0.015148) Loss: 0.44596 (0.43663) +2025-08-22,20:01:43 | INFO | Train Epoch: 6 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.551 Boundary Ratio: 0.253 Contrastive_loss: 0.40906 (0.42141) Boundary_loss: 0.015139 (0.015148) Loss: 0.42420 (0.43656) +2025-08-22,20:02:40 | INFO | Train Epoch: 6 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.42288 (0.42142) Boundary_loss: 0.015208 (0.015148) Loss: 0.43809 (0.43657) +2025-08-22,20:03:36 | INFO | Train Epoch: 6 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.41329 (0.42138) Boundary_loss: 0.015044 (0.015148) Loss: 0.42833 (0.43653) +2025-08-22,20:04:33 | INFO | Train Epoch: 6 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.38618 (0.42119) Boundary_loss: 0.015130 (0.015148) Loss: 0.40131 (0.43634) +2025-08-22,20:05:30 | INFO | Train Epoch: 6 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.514 Boundary Ratio: 0.253 Contrastive_loss: 0.40588 (0.42111) Boundary_loss: 0.015136 (0.015148) Loss: 0.42101 (0.43625) +2025-08-22,20:06:27 | INFO | Train Epoch: 6 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.40429 (0.42102) Boundary_loss: 0.015181 (0.015148) Loss: 0.41947 (0.43616) +2025-08-22,20:07:24 | INFO | Train Epoch: 6 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 47.918 Boundary Ratio: 0.244 Contrastive_loss: 0.40902 (0.42095) Boundary_loss: 0.015078 (0.015147) Loss: 0.42410 (0.43610) +2025-08-22,20:08:20 | INFO | Train Epoch: 6 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.41039 (0.42090) Boundary_loss: 0.015247 (0.015148) Loss: 0.42564 (0.43604) +2025-08-22,20:09:17 | INFO | Train Epoch: 6 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.42469 (0.42092) Boundary_loss: 0.015176 (0.015148) Loss: 0.43986 (0.43606) +2025-08-22,20:10:14 | INFO | Train Epoch: 6 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.371 Boundary Ratio: 0.252 Contrastive_loss: 0.47244 (0.42119) Boundary_loss: 0.015212 (0.015148) Loss: 0.48765 (0.43633) +2025-08-22,20:11:11 | INFO | Train Epoch: 6 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.38836 (0.42101) Boundary_loss: 0.015011 (0.015148) Loss: 0.40337 (0.43616) +2025-08-22,20:12:07 | INFO | Train Epoch: 6 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 0.41588 (0.42099) Boundary_loss: 0.015129 (0.015148) Loss: 0.43101 (0.43614) +2025-08-22,20:13:04 | INFO | Train Epoch: 6 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.45181 (0.42115) Boundary_loss: 0.015183 (0.015148) Loss: 0.46699 (0.43629) +2025-08-22,20:14:01 | INFO | Train Epoch: 6 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 47.975 Boundary Ratio: 0.245 Contrastive_loss: 0.51080 (0.42161) Boundary_loss: 0.015144 (0.015148) Loss: 0.52594 (0.43675) +2025-08-22,20:14:58 | INFO | Train Epoch: 6 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.31208 (0.42105) Boundary_loss: 0.014997 (0.015147) Loss: 0.32708 (0.43619) +2025-08-22,20:15:54 | INFO | Train Epoch: 6 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.38010 (0.42084) Boundary_loss: 0.015110 (0.015147) Loss: 0.39521 (0.43599) +2025-08-22,20:16:51 | INFO | Train Epoch: 6 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.38208 (0.42064) Boundary_loss: 0.015065 (0.015146) Loss: 0.39715 (0.43579) +2025-08-22,20:17:48 | INFO | Train Epoch: 6 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.41435 (0.42061) Boundary_loss: 0.015106 (0.015146) Loss: 0.42946 (0.43576) +2025-08-22,20:18:45 | INFO | Train Epoch: 6 [10189312/26365952 (39%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 0.42627 (0.42064) Boundary_loss: 0.015069 (0.015146) Loss: 0.44134 (0.43579) +2025-08-22,20:19:42 | INFO | Train Epoch: 6 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.328 Boundary Ratio: 0.252 Contrastive_loss: 0.42073 (0.42064) Boundary_loss: 0.015227 (0.015146) Loss: 0.43596 (0.43579) +2025-08-22,20:20:39 | INFO | Train Epoch: 6 [10291712/26365952 (39%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.53825 (0.42122) Boundary_loss: 0.015127 (0.015146) Loss: 0.55337 (0.43637) +2025-08-22,20:21:35 | INFO | Train Epoch: 6 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.40486 (0.42114) Boundary_loss: 0.014910 (0.015145) Loss: 0.41977 (0.43629) +2025-08-22,20:22:32 | INFO | Train Epoch: 6 [10394112/26365952 (39%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.39910 (0.42104) Boundary_loss: 0.015296 (0.015146) Loss: 0.41440 (0.43618) +2025-08-22,20:23:29 | INFO | Train Epoch: 6 [10445312/26365952 (40%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 0.42108 (0.42104) Boundary_loss: 0.015030 (0.015145) Loss: 0.43611 (0.43618) +2025-08-22,20:24:26 | INFO | Train Epoch: 6 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.38331 (0.42085) Boundary_loss: 0.015101 (0.015145) Loss: 0.39841 (0.43600) +2025-08-22,20:25:23 | INFO | Train Epoch: 6 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.211 Boundary Ratio: 0.246 Contrastive_loss: 0.47902 (0.42113) Boundary_loss: 0.015298 (0.015146) Loss: 0.49432 (0.43628) +2025-08-22,20:26:20 | INFO | Train Epoch: 6 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.41677 (0.42111) Boundary_loss: 0.015189 (0.015146) Loss: 0.43196 (0.43626) +2025-08-22,20:27:16 | INFO | Train Epoch: 6 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.45805 (0.42129) Boundary_loss: 0.015157 (0.015146) Loss: 0.47321 (0.43643) +2025-08-22,20:28:13 | INFO | Train Epoch: 6 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.36245 (0.42101) Boundary_loss: 0.015233 (0.015146) Loss: 0.37768 (0.43616) +2025-08-22,20:29:10 | INFO | Train Epoch: 6 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.48215 (0.42130) Boundary_loss: 0.015081 (0.015146) Loss: 0.49723 (0.43644) +2025-08-22,20:30:07 | INFO | Train Epoch: 6 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.389 Boundary Ratio: 0.247 Contrastive_loss: 0.41630 (0.42127) Boundary_loss: 0.015083 (0.015146) Loss: 0.43138 (0.43642) +2025-08-22,20:31:04 | INFO | Train Epoch: 6 [10854912/26365952 (41%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.44003 (0.42136) Boundary_loss: 0.015169 (0.015146) Loss: 0.45520 (0.43651) +2025-08-22,20:32:01 | INFO | Train Epoch: 6 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.42549 (0.42138) Boundary_loss: 0.015269 (0.015146) Loss: 0.44076 (0.43653) +2025-08-22,20:32:58 | INFO | Train Epoch: 6 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.50628 (0.42178) Boundary_loss: 0.015115 (0.015146) Loss: 0.52139 (0.43692) +2025-08-22,20:33:54 | INFO | Train Epoch: 6 [11008512/26365952 (42%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 0.42733 (0.42180) Boundary_loss: 0.015089 (0.015146) Loss: 0.44242 (0.43695) +2025-08-22,20:34:51 | INFO | Train Epoch: 6 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.46474 (0.42200) Boundary_loss: 0.015150 (0.015146) Loss: 0.47989 (0.43715) +2025-08-22,20:35:48 | INFO | Train Epoch: 6 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.270 Boundary Ratio: 0.246 Contrastive_loss: 0.40374 (0.42192) Boundary_loss: 0.015269 (0.015147) Loss: 0.41901 (0.43706) +2025-08-22,20:36:45 | INFO | Train Epoch: 6 [11162112/26365952 (42%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.50671 (0.42230) Boundary_loss: 0.015123 (0.015146) Loss: 0.52183 (0.43745) +2025-08-22,20:37:42 | INFO | Train Epoch: 6 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.48178 (0.42257) Boundary_loss: 0.015025 (0.015146) Loss: 0.49681 (0.43772) +2025-08-22,20:38:38 | INFO | Train Epoch: 6 [11264512/26365952 (43%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 0.43034 (0.42261) Boundary_loss: 0.015278 (0.015146) Loss: 0.44562 (0.43776) +2025-08-22,20:39:35 | INFO | Train Epoch: 6 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.43264 (0.42265) Boundary_loss: 0.015199 (0.015147) Loss: 0.44784 (0.43780) +2025-08-22,20:40:31 | INFO | Train Epoch: 6 [11366912/26365952 (43%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.41776 (0.42263) Boundary_loss: 0.015011 (0.015146) Loss: 0.43277 (0.43778) +2025-08-22,20:41:28 | INFO | Train Epoch: 6 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.34846 (0.42230) Boundary_loss: 0.015263 (0.015147) Loss: 0.36372 (0.43745) +2025-08-22,20:42:25 | INFO | Train Epoch: 6 [11469312/26365952 (44%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.39421 (0.42218) Boundary_loss: 0.015282 (0.015147) Loss: 0.40950 (0.43732) +2025-08-22,20:43:21 | INFO | Train Epoch: 6 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.47485 (0.42241) Boundary_loss: 0.015135 (0.015147) Loss: 0.48999 (0.43756) +2025-08-22,20:44:18 | INFO | Train Epoch: 6 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.057 Boundary Ratio: 0.245 Contrastive_loss: 0.40399 (0.42233) Boundary_loss: 0.015297 (0.015148) Loss: 0.41928 (0.43748) +2025-08-22,20:45:15 | INFO | Train Epoch: 6 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.37422 (0.42212) Boundary_loss: 0.015052 (0.015147) Loss: 0.38927 (0.43727) +2025-08-22,20:46:11 | INFO | Train Epoch: 6 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.33269 (0.42173) Boundary_loss: 0.015098 (0.015147) Loss: 0.34779 (0.43687) +2025-08-22,20:47:08 | INFO | Train Epoch: 6 [11725312/26365952 (44%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 0.35142 (0.42142) Boundary_loss: 0.015168 (0.015147) Loss: 0.36659 (0.43657) +2025-08-22,20:48:05 | INFO | Train Epoch: 6 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.35684 (0.42114) Boundary_loss: 0.015275 (0.015148) Loss: 0.37212 (0.43629) +2025-08-22,20:49:02 | INFO | Train Epoch: 6 [11827712/26365952 (45%)] Avg Boundaries (per batch): 49.277 Boundary Ratio: 0.251 Contrastive_loss: 0.38799 (0.42100) Boundary_loss: 0.015015 (0.015147) Loss: 0.40301 (0.43615) +2025-08-22,20:49:59 | INFO | Train Epoch: 6 [11878912/26365952 (45%)] Avg Boundaries (per batch): 49.406 Boundary Ratio: 0.252 Contrastive_loss: 0.36634 (0.42076) Boundary_loss: 0.015131 (0.015147) Loss: 0.38147 (0.43591) +2025-08-22,20:50:56 | INFO | Train Epoch: 6 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.35445 (0.42048) Boundary_loss: 0.015125 (0.015147) Loss: 0.36957 (0.43563) +2025-08-22,20:51:52 | INFO | Train Epoch: 6 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.037 Boundary Ratio: 0.245 Contrastive_loss: 0.43264 (0.42053) Boundary_loss: 0.015184 (0.015147) Loss: 0.44783 (0.43568) +2025-08-22,20:52:49 | INFO | Train Epoch: 6 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.43291 (0.42059) Boundary_loss: 0.015082 (0.015147) Loss: 0.44800 (0.43573) +2025-08-22,20:53:46 | INFO | Train Epoch: 6 [12083712/26365952 (46%)] Avg Boundaries (per batch): 47.955 Boundary Ratio: 0.245 Contrastive_loss: 0.42022 (0.42058) Boundary_loss: 0.015164 (0.015147) Loss: 0.43539 (0.43573) +2025-08-22,20:54:42 | INFO | Train Epoch: 6 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.072 Boundary Ratio: 0.245 Contrastive_loss: 0.40619 (0.42052) Boundary_loss: 0.015155 (0.015147) Loss: 0.42135 (0.43567) +2025-08-22,20:55:39 | INFO | Train Epoch: 6 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.46174 (0.42070) Boundary_loss: 0.015118 (0.015147) Loss: 0.47686 (0.43584) +2025-08-22,20:56:36 | INFO | Train Epoch: 6 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.41863 (0.42069) Boundary_loss: 0.015136 (0.015147) Loss: 0.43376 (0.43583) +2025-08-22,20:57:33 | INFO | Train Epoch: 6 [12288512/26365952 (47%)] Avg Boundaries (per batch): 49.148 Boundary Ratio: 0.251 Contrastive_loss: 0.39126 (0.42057) Boundary_loss: 0.015260 (0.015147) Loss: 0.40652 (0.43571) +2025-08-22,20:58:30 | INFO | Train Epoch: 6 [12339712/26365952 (47%)] Avg Boundaries (per batch): 49.268 Boundary Ratio: 0.251 Contrastive_loss: 0.41657 (0.42055) Boundary_loss: 0.015189 (0.015148) Loss: 0.43176 (0.43570) +2025-08-22,20:59:26 | INFO | Train Epoch: 6 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 0.49988 (0.42088) Boundary_loss: 0.015157 (0.015148) Loss: 0.51504 (0.43602) +2025-08-22,21:00:23 | INFO | Train Epoch: 6 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.50064 (0.42120) Boundary_loss: 0.015019 (0.015147) Loss: 0.51566 (0.43635) +2025-08-22,21:01:20 | INFO | Train Epoch: 6 [12493312/26365952 (47%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 0.47269 (0.42141) Boundary_loss: 0.015275 (0.015148) Loss: 0.48797 (0.43656) +2025-08-22,21:02:17 | INFO | Train Epoch: 6 [12544512/26365952 (48%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.35075 (0.42112) Boundary_loss: 0.015335 (0.015148) Loss: 0.36608 (0.43627) +2025-08-22,21:03:14 | INFO | Train Epoch: 6 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.391 Boundary Ratio: 0.247 Contrastive_loss: 0.48777 (0.42139) Boundary_loss: 0.015099 (0.015148) Loss: 0.50287 (0.43654) +2025-08-22,21:04:11 | INFO | Train Epoch: 6 [12646912/26365952 (48%)] Avg Boundaries (per batch): 49.303 Boundary Ratio: 0.252 Contrastive_loss: 0.40630 (0.42133) Boundary_loss: 0.015103 (0.015148) Loss: 0.42140 (0.43648) +2025-08-22,21:05:07 | INFO | Train Epoch: 6 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.34494 (0.42103) Boundary_loss: 0.015169 (0.015148) Loss: 0.36010 (0.43618) +2025-08-22,21:06:04 | INFO | Train Epoch: 6 [12749312/26365952 (48%)] Avg Boundaries (per batch): 49.615 Boundary Ratio: 0.253 Contrastive_loss: 0.45356 (0.42116) Boundary_loss: 0.015207 (0.015148) Loss: 0.46876 (0.43631) +2025-08-22,21:07:01 | INFO | Train Epoch: 6 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.37732 (0.42098) Boundary_loss: 0.015151 (0.015148) Loss: 0.39247 (0.43613) +2025-08-22,21:07:58 | INFO | Train Epoch: 6 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.42503 (0.42100) Boundary_loss: 0.015172 (0.015148) Loss: 0.44020 (0.43615) +2025-08-22,21:08:55 | INFO | Train Epoch: 6 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 0.40903 (0.42095) Boundary_loss: 0.015137 (0.015148) Loss: 0.42417 (0.43610) +2025-08-22,21:09:51 | INFO | Train Epoch: 6 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.40121 (0.42087) Boundary_loss: 0.015077 (0.015148) Loss: 0.41629 (0.43602) +2025-08-22,21:10:48 | INFO | Train Epoch: 6 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.36615 (0.42066) Boundary_loss: 0.015020 (0.015148) Loss: 0.38117 (0.43581) +2025-08-22,21:11:45 | INFO | Train Epoch: 6 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.42689 (0.42068) Boundary_loss: 0.015176 (0.015148) Loss: 0.44207 (0.43583) +2025-08-22,21:12:42 | INFO | Train Epoch: 6 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.203 Boundary Ratio: 0.246 Contrastive_loss: 0.36593 (0.42047) Boundary_loss: 0.015143 (0.015148) Loss: 0.38107 (0.43562) +2025-08-22,21:13:39 | INFO | Train Epoch: 6 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.38930 (0.42035) Boundary_loss: 0.014981 (0.015147) Loss: 0.40428 (0.43550) +2025-08-22,21:14:35 | INFO | Train Epoch: 6 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 0.41882 (0.42034) Boundary_loss: 0.015219 (0.015147) Loss: 0.43404 (0.43549) +2025-08-22,21:15:32 | INFO | Train Epoch: 6 [13261312/26365952 (50%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.37016 (0.42015) Boundary_loss: 0.015143 (0.015147) Loss: 0.38530 (0.43530) +2025-08-22,21:16:29 | INFO | Train Epoch: 6 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.33986 (0.41984) Boundary_loss: 0.015052 (0.015147) Loss: 0.35491 (0.43499) +2025-08-22,21:17:26 | INFO | Train Epoch: 6 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 0.35386 (0.41959) Boundary_loss: 0.015054 (0.015147) Loss: 0.36891 (0.43474) +2025-08-22,21:18:22 | INFO | Train Epoch: 6 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.420 Boundary Ratio: 0.252 Contrastive_loss: 0.41221 (0.41956) Boundary_loss: 0.015055 (0.015146) Loss: 0.42726 (0.43471) +2025-08-22,21:19:19 | INFO | Train Epoch: 6 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.45529 (0.41970) Boundary_loss: 0.015072 (0.015146) Loss: 0.47036 (0.43484) +2025-08-22,21:20:16 | INFO | Train Epoch: 6 [13517312/26365952 (51%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.34361 (0.41941) Boundary_loss: 0.015109 (0.015146) Loss: 0.35872 (0.43456) +2025-08-22,21:21:13 | INFO | Train Epoch: 6 [13568512/26365952 (51%)] Avg Boundaries (per batch): 49.605 Boundary Ratio: 0.253 Contrastive_loss: 0.41271 (0.41939) Boundary_loss: 0.015220 (0.015146) Loss: 0.42793 (0.43453) +2025-08-22,21:22:09 | INFO | Train Epoch: 6 [13619712/26365952 (52%)] Avg Boundaries (per batch): 47.656 Boundary Ratio: 0.243 Contrastive_loss: 0.38134 (0.41924) Boundary_loss: 0.015101 (0.015146) Loss: 0.39644 (0.43439) +2025-08-22,21:23:06 | INFO | Train Epoch: 6 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.37313 (0.41907) Boundary_loss: 0.014994 (0.015145) Loss: 0.38813 (0.43422) +2025-08-22,21:24:03 | INFO | Train Epoch: 6 [13722112/26365952 (52%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.36687 (0.41888) Boundary_loss: 0.015083 (0.015145) Loss: 0.38195 (0.43402) +2025-08-22,21:25:00 | INFO | Train Epoch: 6 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.40405 (0.41882) Boundary_loss: 0.015137 (0.015145) Loss: 0.41919 (0.43397) +2025-08-22,21:25:56 | INFO | Train Epoch: 6 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 0.48241 (0.41906) Boundary_loss: 0.015078 (0.015145) Loss: 0.49749 (0.43420) +2025-08-22,21:26:53 | INFO | Train Epoch: 6 [13875712/26365952 (53%)] Avg Boundaries (per batch): 49.232 Boundary Ratio: 0.251 Contrastive_loss: 0.49653 (0.41934) Boundary_loss: 0.015037 (0.015144) Loss: 0.51156 (0.43449) +2025-08-22,21:27:50 | INFO | Train Epoch: 6 [13926912/26365952 (53%)] Avg Boundaries (per batch): 49.615 Boundary Ratio: 0.253 Contrastive_loss: 0.47292 (0.41954) Boundary_loss: 0.015178 (0.015145) Loss: 0.48809 (0.43468) +2025-08-22,21:28:47 | INFO | Train Epoch: 6 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.47272 (0.41973) Boundary_loss: 0.015109 (0.015144) Loss: 0.48783 (0.43488) +2025-08-22,21:29:44 | INFO | Train Epoch: 6 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.40873 (0.41969) Boundary_loss: 0.015167 (0.015145) Loss: 0.42390 (0.43484) +2025-08-22,21:30:41 | INFO | Train Epoch: 6 [14080512/26365952 (53%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.44345 (0.41978) Boundary_loss: 0.015158 (0.015145) Loss: 0.45861 (0.43492) +2025-08-22,21:31:38 | INFO | Train Epoch: 6 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.027 Boundary Ratio: 0.245 Contrastive_loss: 0.33070 (0.41946) Boundary_loss: 0.015137 (0.015145) Loss: 0.34584 (0.43460) +2025-08-22,21:32:35 | INFO | Train Epoch: 6 [14182912/26365952 (54%)] Avg Boundaries (per batch): 49.734 Boundary Ratio: 0.254 Contrastive_loss: 0.45596 (0.41959) Boundary_loss: 0.015317 (0.015145) Loss: 0.47128 (0.43473) +2025-08-22,21:33:31 | INFO | Train Epoch: 6 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.44506 (0.41968) Boundary_loss: 0.014991 (0.015145) Loss: 0.46005 (0.43482) +2025-08-22,21:34:28 | INFO | Train Epoch: 6 [14285312/26365952 (54%)] Avg Boundaries (per batch): 49.168 Boundary Ratio: 0.251 Contrastive_loss: 0.38877 (0.41957) Boundary_loss: 0.015201 (0.015145) Loss: 0.40397 (0.43471) +2025-08-22,21:35:25 | INFO | Train Epoch: 6 [14336512/26365952 (54%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.49021 (0.41982) Boundary_loss: 0.015128 (0.015145) Loss: 0.50534 (0.43496) +2025-08-22,21:36:22 | INFO | Train Epoch: 6 [14387712/26365952 (55%)] Avg Boundaries (per batch): 49.717 Boundary Ratio: 0.254 Contrastive_loss: 0.38939 (0.41971) Boundary_loss: 0.015227 (0.015145) Loss: 0.40461 (0.43486) +2025-08-22,21:37:18 | INFO | Train Epoch: 6 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.102 Boundary Ratio: 0.245 Contrastive_loss: 0.47378 (0.41990) Boundary_loss: 0.015246 (0.015145) Loss: 0.48903 (0.43505) +2025-08-22,21:38:15 | INFO | Train Epoch: 6 [14490112/26365952 (55%)] Avg Boundaries (per batch): 49.473 Boundary Ratio: 0.252 Contrastive_loss: 0.45770 (0.42004) Boundary_loss: 0.015238 (0.015146) Loss: 0.47294 (0.43518) +2025-08-22,21:39:12 | INFO | Train Epoch: 6 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.42551 (0.42006) Boundary_loss: 0.015041 (0.015145) Loss: 0.44055 (0.43520) +2025-08-22,21:40:09 | INFO | Train Epoch: 6 [14592512/26365952 (55%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 0.36163 (0.41985) Boundary_loss: 0.015034 (0.015145) Loss: 0.37666 (0.43500) +2025-08-22,21:41:06 | INFO | Train Epoch: 6 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.44161 (0.41993) Boundary_loss: 0.015127 (0.015145) Loss: 0.45674 (0.43507) +2025-08-22,21:42:03 | INFO | Train Epoch: 6 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.41347 (0.41990) Boundary_loss: 0.015263 (0.015145) Loss: 0.42873 (0.43505) +2025-08-22,21:43:00 | INFO | Train Epoch: 6 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.44409 (0.41999) Boundary_loss: 0.015212 (0.015146) Loss: 0.45930 (0.43513) +2025-08-22,21:43:57 | INFO | Train Epoch: 6 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.45340 (0.42010) Boundary_loss: 0.015145 (0.015146) Loss: 0.46854 (0.43525) +2025-08-22,21:44:53 | INFO | Train Epoch: 6 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.36868 (0.41993) Boundary_loss: 0.015225 (0.015146) Loss: 0.38390 (0.43507) +2025-08-22,21:45:50 | INFO | Train Epoch: 6 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.44460 (0.42001) Boundary_loss: 0.015021 (0.015145) Loss: 0.45962 (0.43516) +2025-08-22,21:46:47 | INFO | Train Epoch: 6 [14950912/26365952 (57%)] Avg Boundaries (per batch): 49.350 Boundary Ratio: 0.252 Contrastive_loss: 0.42657 (0.42003) Boundary_loss: 0.015185 (0.015146) Loss: 0.44176 (0.43518) +2025-08-22,21:47:44 | INFO | Train Epoch: 6 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 0.41734 (0.42002) Boundary_loss: 0.015247 (0.015146) Loss: 0.43259 (0.43517) +2025-08-22,21:48:40 | INFO | Train Epoch: 6 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 0.38732 (0.41991) Boundary_loss: 0.015039 (0.015146) Loss: 0.40236 (0.43506) +2025-08-22,21:49:37 | INFO | Train Epoch: 6 [15104512/26365952 (57%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.43992 (0.41998) Boundary_loss: 0.015202 (0.015146) Loss: 0.45512 (0.43513) +2025-08-22,21:50:34 | INFO | Train Epoch: 6 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.471 Boundary Ratio: 0.252 Contrastive_loss: 0.37948 (0.41984) Boundary_loss: 0.015133 (0.015146) Loss: 0.39461 (0.43499) +2025-08-22,21:51:31 | INFO | Train Epoch: 6 [15206912/26365952 (58%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.43015 (0.41988) Boundary_loss: 0.015147 (0.015146) Loss: 0.44530 (0.43503) +2025-08-22,21:52:27 | INFO | Train Epoch: 6 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.42867 (0.41991) Boundary_loss: 0.015193 (0.015146) Loss: 0.44386 (0.43505) +2025-08-22,21:53:24 | INFO | Train Epoch: 6 [15309312/26365952 (58%)] Avg Boundaries (per batch): 49.961 Boundary Ratio: 0.255 Contrastive_loss: 0.35322 (0.41969) Boundary_loss: 0.015216 (0.015146) Loss: 0.36843 (0.43483) +2025-08-22,21:54:21 | INFO | Train Epoch: 6 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 0.48048 (0.41989) Boundary_loss: 0.015129 (0.015146) Loss: 0.49560 (0.43503) +2025-08-22,21:55:18 | INFO | Train Epoch: 6 [15411712/26365952 (58%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 0.41788 (0.41988) Boundary_loss: 0.015390 (0.015147) Loss: 0.43327 (0.43503) +2025-08-22,21:56:14 | INFO | Train Epoch: 6 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.42114 (0.41989) Boundary_loss: 0.015090 (0.015147) Loss: 0.43623 (0.43503) +2025-08-22,21:57:11 | INFO | Train Epoch: 6 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.44836 (0.41998) Boundary_loss: 0.015098 (0.015146) Loss: 0.46345 (0.43513) +2025-08-22,21:58:08 | INFO | Train Epoch: 6 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.43541 (0.42003) Boundary_loss: 0.014960 (0.015146) Loss: 0.45037 (0.43518) +2025-08-22,21:59:05 | INFO | Train Epoch: 6 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.45229 (0.42014) Boundary_loss: 0.014998 (0.015145) Loss: 0.46729 (0.43528) +2025-08-22,22:00:02 | INFO | Train Epoch: 6 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.44341 (0.42021) Boundary_loss: 0.015213 (0.015146) Loss: 0.45862 (0.43536) +2025-08-22,22:00:58 | INFO | Train Epoch: 6 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.41588 (0.42020) Boundary_loss: 0.015159 (0.015146) Loss: 0.43104 (0.43534) +2025-08-22,22:01:55 | INFO | Train Epoch: 6 [15770112/26365952 (60%)] Avg Boundaries (per batch): 49.605 Boundary Ratio: 0.253 Contrastive_loss: 0.41593 (0.42018) Boundary_loss: 0.015267 (0.015146) Loss: 0.43120 (0.43533) +2025-08-22,22:02:52 | INFO | Train Epoch: 6 [15821312/26365952 (60%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.45609 (0.42030) Boundary_loss: 0.015185 (0.015146) Loss: 0.47127 (0.43545) +2025-08-22,22:03:49 | INFO | Train Epoch: 6 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.33903 (0.42004) Boundary_loss: 0.015121 (0.015146) Loss: 0.35415 (0.43518) +2025-08-22,22:04:46 | INFO | Train Epoch: 6 [15923712/26365952 (60%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.44880 (0.42013) Boundary_loss: 0.015054 (0.015146) Loss: 0.46385 (0.43528) +2025-08-22,22:05:42 | INFO | Train Epoch: 6 [15974912/26365952 (61%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.30126 (0.41975) Boundary_loss: 0.015090 (0.015146) Loss: 0.31635 (0.43490) +2025-08-22,22:06:39 | INFO | Train Epoch: 6 [16026112/26365952 (61%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 0.43439 (0.41980) Boundary_loss: 0.015093 (0.015145) Loss: 0.44948 (0.43494) +2025-08-22,22:07:36 | INFO | Train Epoch: 6 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.38107 (0.41967) Boundary_loss: 0.015137 (0.015145) Loss: 0.39621 (0.43482) +2025-08-22,22:08:33 | INFO | Train Epoch: 6 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.35044 (0.41946) Boundary_loss: 0.015131 (0.015145) Loss: 0.36557 (0.43460) +2025-08-22,22:09:30 | INFO | Train Epoch: 6 [16179712/26365952 (61%)] Avg Boundaries (per batch): 49.490 Boundary Ratio: 0.253 Contrastive_loss: 0.39909 (0.41939) Boundary_loss: 0.015183 (0.015145) Loss: 0.41427 (0.43454) +2025-08-22,22:10:27 | INFO | Train Epoch: 6 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.40669 (0.41935) Boundary_loss: 0.015132 (0.015145) Loss: 0.42182 (0.43450) +2025-08-22,22:11:23 | INFO | Train Epoch: 6 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.41397 (0.41933) Boundary_loss: 0.015049 (0.015145) Loss: 0.42902 (0.43448) +2025-08-22,22:12:20 | INFO | Train Epoch: 6 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.42582 (0.41935) Boundary_loss: 0.015181 (0.015145) Loss: 0.44100 (0.43450) +2025-08-22,22:13:17 | INFO | Train Epoch: 6 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.35004 (0.41914) Boundary_loss: 0.015132 (0.015145) Loss: 0.36517 (0.43428) +2025-08-22,22:14:14 | INFO | Train Epoch: 6 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 0.46997 (0.41930) Boundary_loss: 0.015102 (0.015145) Loss: 0.48507 (0.43444) +2025-08-22,22:15:10 | INFO | Train Epoch: 6 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.41663 (0.41929) Boundary_loss: 0.015173 (0.015145) Loss: 0.43180 (0.43443) +2025-08-22,22:16:07 | INFO | Train Epoch: 6 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.35110 (0.41908) Boundary_loss: 0.015109 (0.015145) Loss: 0.36621 (0.43422) +2025-08-22,22:17:04 | INFO | Train Epoch: 6 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.34616 (0.41885) Boundary_loss: 0.015041 (0.015145) Loss: 0.36120 (0.43400) +2025-08-22,22:18:01 | INFO | Train Epoch: 6 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.42194 (0.41886) Boundary_loss: 0.015040 (0.015144) Loss: 0.43698 (0.43401) +2025-08-22,22:18:58 | INFO | Train Epoch: 6 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.178 Boundary Ratio: 0.246 Contrastive_loss: 0.38812 (0.41877) Boundary_loss: 0.015161 (0.015144) Loss: 0.40328 (0.43391) +2025-08-22,22:19:54 | INFO | Train Epoch: 6 [16742912/26365952 (64%)] Avg Boundaries (per batch): 47.979 Boundary Ratio: 0.245 Contrastive_loss: 0.42810 (0.41880) Boundary_loss: 0.015269 (0.015145) Loss: 0.44337 (0.43394) +2025-08-22,22:20:51 | INFO | Train Epoch: 6 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.38887 (0.41871) Boundary_loss: 0.015255 (0.015145) Loss: 0.40413 (0.43385) +2025-08-22,22:21:48 | INFO | Train Epoch: 6 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.039 Boundary Ratio: 0.245 Contrastive_loss: 0.50902 (0.41898) Boundary_loss: 0.015090 (0.015145) Loss: 0.52411 (0.43412) +2025-08-22,22:22:45 | INFO | Train Epoch: 6 [16896512/26365952 (64%)] Avg Boundaries (per batch): 47.977 Boundary Ratio: 0.245 Contrastive_loss: 0.42432 (0.41900) Boundary_loss: 0.015040 (0.015145) Loss: 0.43936 (0.43414) +2025-08-22,22:23:41 | INFO | Train Epoch: 6 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.38402 (0.41889) Boundary_loss: 0.015216 (0.015145) Loss: 0.39924 (0.43404) +2025-08-22,22:24:38 | INFO | Train Epoch: 6 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.39383 (0.41882) Boundary_loss: 0.015128 (0.015145) Loss: 0.40895 (0.43396) +2025-08-22,22:25:35 | INFO | Train Epoch: 6 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.40364 (0.41877) Boundary_loss: 0.015126 (0.015145) Loss: 0.41876 (0.43391) +2025-08-22,22:26:32 | INFO | Train Epoch: 6 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.44179 (0.41884) Boundary_loss: 0.015228 (0.015145) Loss: 0.45702 (0.43398) +2025-08-22,22:27:29 | INFO | Train Epoch: 6 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.42335 (0.41885) Boundary_loss: 0.015104 (0.015145) Loss: 0.43846 (0.43400) +2025-08-22,22:28:26 | INFO | Train Epoch: 6 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.45572 (0.41896) Boundary_loss: 0.015137 (0.015145) Loss: 0.47086 (0.43411) +2025-08-22,22:29:22 | INFO | Train Epoch: 6 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.45087 (0.41906) Boundary_loss: 0.015245 (0.015145) Loss: 0.46611 (0.43420) +2025-08-22,22:30:19 | INFO | Train Epoch: 6 [17306112/26365952 (66%)] Avg Boundaries (per batch): 47.988 Boundary Ratio: 0.245 Contrastive_loss: 0.44171 (0.41912) Boundary_loss: 0.015254 (0.015145) Loss: 0.45697 (0.43427) +2025-08-22,22:31:16 | INFO | Train Epoch: 6 [17357312/26365952 (66%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.44699 (0.41920) Boundary_loss: 0.015063 (0.015145) Loss: 0.46205 (0.43435) +2025-08-22,22:32:13 | INFO | Train Epoch: 6 [17408512/26365952 (66%)] Avg Boundaries (per batch): 49.404 Boundary Ratio: 0.252 Contrastive_loss: 0.39975 (0.41915) Boundary_loss: 0.015003 (0.015145) Loss: 0.41476 (0.43429) +2025-08-22,22:33:10 | INFO | Train Epoch: 6 [17459712/26365952 (66%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 0.43057 (0.41918) Boundary_loss: 0.015021 (0.015144) Loss: 0.44559 (0.43433) +2025-08-22,22:34:07 | INFO | Train Epoch: 6 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.46119 (0.41930) Boundary_loss: 0.015164 (0.015145) Loss: 0.47636 (0.43445) +2025-08-22,22:35:03 | INFO | Train Epoch: 6 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.44179 (0.41937) Boundary_loss: 0.015175 (0.015145) Loss: 0.45697 (0.43451) +2025-08-22,22:36:00 | INFO | Train Epoch: 6 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.46421 (0.41950) Boundary_loss: 0.015107 (0.015145) Loss: 0.47932 (0.43464) +2025-08-22,22:36:57 | INFO | Train Epoch: 6 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.41536 (0.41949) Boundary_loss: 0.015223 (0.015145) Loss: 0.43058 (0.43463) +2025-08-22,22:37:54 | INFO | Train Epoch: 6 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 0.50911 (0.41975) Boundary_loss: 0.015181 (0.015145) Loss: 0.52429 (0.43489) +2025-08-22,22:38:50 | INFO | Train Epoch: 6 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.44375 (0.41981) Boundary_loss: 0.015162 (0.015145) Loss: 0.45891 (0.43496) +2025-08-22,22:39:47 | INFO | Train Epoch: 6 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.45178 (0.41991) Boundary_loss: 0.015177 (0.015145) Loss: 0.46696 (0.43505) +2025-08-22,22:40:44 | INFO | Train Epoch: 6 [17869312/26365952 (68%)] Avg Boundaries (per batch): 50.211 Boundary Ratio: 0.256 Contrastive_loss: 0.46994 (0.42005) Boundary_loss: 0.015286 (0.015145) Loss: 0.48523 (0.43519) +2025-08-22,22:41:41 | INFO | Train Epoch: 6 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.34232 (0.41983) Boundary_loss: 0.015252 (0.015146) Loss: 0.35757 (0.43497) +2025-08-22,22:42:37 | INFO | Train Epoch: 6 [17971712/26365952 (68%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 0.39176 (0.41975) Boundary_loss: 0.015078 (0.015145) Loss: 0.40684 (0.43489) +2025-08-22,22:43:34 | INFO | Train Epoch: 6 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.39099 (0.41967) Boundary_loss: 0.015163 (0.015146) Loss: 0.40615 (0.43481) +2025-08-22,22:44:31 | INFO | Train Epoch: 6 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 0.44017 (0.41972) Boundary_loss: 0.015225 (0.015146) Loss: 0.45540 (0.43487) +2025-08-22,22:45:28 | INFO | Train Epoch: 6 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.43032 (0.41975) Boundary_loss: 0.015113 (0.015146) Loss: 0.44544 (0.43490) +2025-08-22,22:46:24 | INFO | Train Epoch: 6 [18176512/26365952 (69%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.46558 (0.41988) Boundary_loss: 0.015088 (0.015146) Loss: 0.48066 (0.43503) +2025-08-22,22:47:21 | INFO | Train Epoch: 6 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.39583 (0.41982) Boundary_loss: 0.015061 (0.015145) Loss: 0.41089 (0.43496) +2025-08-22,22:48:18 | INFO | Train Epoch: 6 [18278912/26365952 (69%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 0.39722 (0.41975) Boundary_loss: 0.015157 (0.015145) Loss: 0.41238 (0.43490) +2025-08-22,22:49:15 | INFO | Train Epoch: 6 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.39206 (0.41968) Boundary_loss: 0.015128 (0.015145) Loss: 0.40719 (0.43482) +2025-08-22,22:50:12 | INFO | Train Epoch: 6 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.39997 (0.41962) Boundary_loss: 0.015061 (0.015145) Loss: 0.41503 (0.43477) +2025-08-22,22:51:08 | INFO | Train Epoch: 6 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.35173 (0.41943) Boundary_loss: 0.015334 (0.015146) Loss: 0.36707 (0.43458) +2025-08-22,22:52:05 | INFO | Train Epoch: 6 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.31807 (0.41915) Boundary_loss: 0.015086 (0.015145) Loss: 0.33315 (0.43430) +2025-08-22,22:53:02 | INFO | Train Epoch: 6 [18534912/26365952 (70%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.36715 (0.41901) Boundary_loss: 0.014946 (0.015145) Loss: 0.38209 (0.43415) +2025-08-22,22:53:59 | INFO | Train Epoch: 6 [18586112/26365952 (70%)] Avg Boundaries (per batch): 50.068 Boundary Ratio: 0.255 Contrastive_loss: 0.39345 (0.41894) Boundary_loss: 0.015234 (0.015145) Loss: 0.40868 (0.43408) +2025-08-22,22:54:55 | INFO | Train Epoch: 6 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.43806 (0.41899) Boundary_loss: 0.014999 (0.015145) Loss: 0.45306 (0.43414) +2025-08-22,22:55:52 | INFO | Train Epoch: 6 [18688512/26365952 (71%)] Avg Boundaries (per batch): 49.420 Boundary Ratio: 0.252 Contrastive_loss: 0.43764 (0.41904) Boundary_loss: 0.015169 (0.015145) Loss: 0.45281 (0.43419) +2025-08-22,22:56:49 | INFO | Train Epoch: 6 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.40186 (0.41900) Boundary_loss: 0.015326 (0.015145) Loss: 0.41718 (0.43414) +2025-08-22,22:57:46 | INFO | Train Epoch: 6 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.46892 (0.41913) Boundary_loss: 0.015019 (0.015145) Loss: 0.48394 (0.43428) +2025-08-22,22:58:42 | INFO | Train Epoch: 6 [18842112/26365952 (71%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.39498 (0.41907) Boundary_loss: 0.015088 (0.015145) Loss: 0.41007 (0.43421) +2025-08-22,22:59:39 | INFO | Train Epoch: 6 [18893312/26365952 (72%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.39733 (0.41901) Boundary_loss: 0.015072 (0.015145) Loss: 0.41240 (0.43415) +2025-08-22,23:00:35 | INFO | Train Epoch: 6 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 0.37261 (0.41888) Boundary_loss: 0.015157 (0.015145) Loss: 0.38777 (0.43403) +2025-08-22,23:01:32 | INFO | Train Epoch: 6 [18995712/26365952 (72%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.48354 (0.41906) Boundary_loss: 0.015114 (0.015145) Loss: 0.49865 (0.43420) +2025-08-22,23:02:29 | INFO | Train Epoch: 6 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.45516 (0.41915) Boundary_loss: 0.015155 (0.015145) Loss: 0.47031 (0.43430) +2025-08-22,23:03:26 | INFO | Train Epoch: 6 [19098112/26365952 (72%)] Avg Boundaries (per batch): 49.494 Boundary Ratio: 0.253 Contrastive_loss: 0.37319 (0.41903) Boundary_loss: 0.015236 (0.015145) Loss: 0.38842 (0.43417) +2025-08-22,23:04:23 | INFO | Train Epoch: 6 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.44679 (0.41910) Boundary_loss: 0.015167 (0.015145) Loss: 0.46196 (0.43425) +2025-08-22,23:05:20 | INFO | Train Epoch: 6 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.256 Boundary Ratio: 0.246 Contrastive_loss: 0.41874 (0.41910) Boundary_loss: 0.015031 (0.015145) Loss: 0.43377 (0.43425) +2025-08-22,23:06:17 | INFO | Train Epoch: 6 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.44366 (0.41917) Boundary_loss: 0.015040 (0.015144) Loss: 0.45870 (0.43431) +2025-08-22,23:07:14 | INFO | Train Epoch: 6 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.46007 (0.41928) Boundary_loss: 0.014996 (0.015144) Loss: 0.47506 (0.43442) +2025-08-22,23:08:10 | INFO | Train Epoch: 6 [19354112/26365952 (73%)] Avg Boundaries (per batch): 49.457 Boundary Ratio: 0.252 Contrastive_loss: 0.41203 (0.41926) Boundary_loss: 0.015057 (0.015144) Loss: 0.42708 (0.43440) +2025-08-22,23:09:07 | INFO | Train Epoch: 6 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.36326 (0.41911) Boundary_loss: 0.015052 (0.015143) Loss: 0.37831 (0.43425) +2025-08-22,23:10:04 | INFO | Train Epoch: 6 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.44714 (0.41918) Boundary_loss: 0.015098 (0.015143) Loss: 0.46224 (0.43433) +2025-08-22,23:11:01 | INFO | Train Epoch: 6 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.46079 (0.41929) Boundary_loss: 0.015093 (0.015143) Loss: 0.47588 (0.43443) +2025-08-22,23:11:58 | INFO | Train Epoch: 6 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 0.37921 (0.41919) Boundary_loss: 0.015221 (0.015143) Loss: 0.39443 (0.43433) +2025-08-22,23:12:54 | INFO | Train Epoch: 6 [19610112/26365952 (74%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 0.31204 (0.41891) Boundary_loss: 0.015073 (0.015143) Loss: 0.32711 (0.43405) +2025-08-22,23:13:51 | INFO | Train Epoch: 6 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.35963 (0.41875) Boundary_loss: 0.015210 (0.015143) Loss: 0.37484 (0.43390) +2025-08-22,23:14:48 | INFO | Train Epoch: 6 [19712512/26365952 (75%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 0.35027 (0.41858) Boundary_loss: 0.015196 (0.015143) Loss: 0.36546 (0.43372) +2025-08-22,23:15:45 | INFO | Train Epoch: 6 [19763712/26365952 (75%)] Avg Boundaries (per batch): 49.775 Boundary Ratio: 0.254 Contrastive_loss: 0.38895 (0.41850) Boundary_loss: 0.015086 (0.015143) Loss: 0.40403 (0.43364) +2025-08-22,23:16:42 | INFO | Train Epoch: 6 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 0.36361 (0.41836) Boundary_loss: 0.015107 (0.015143) Loss: 0.37872 (0.43350) +2025-08-22,23:17:39 | INFO | Train Epoch: 6 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.41169 (0.41834) Boundary_loss: 0.015194 (0.015143) Loss: 0.42688 (0.43348) +2025-08-22,23:18:36 | INFO | Train Epoch: 6 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 0.35264 (0.41817) Boundary_loss: 0.015122 (0.015143) Loss: 0.36776 (0.43332) +2025-08-22,23:19:32 | INFO | Train Epoch: 6 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 0.40088 (0.41813) Boundary_loss: 0.015197 (0.015143) Loss: 0.41608 (0.43327) +2025-08-22,23:20:29 | INFO | Train Epoch: 6 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.45018 (0.41821) Boundary_loss: 0.015126 (0.015143) Loss: 0.46531 (0.43335) +2025-08-22,23:21:26 | INFO | Train Epoch: 6 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.40491 (0.41818) Boundary_loss: 0.015180 (0.015143) Loss: 0.42009 (0.43332) +2025-08-22,23:22:23 | INFO | Train Epoch: 6 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.39788 (0.41813) Boundary_loss: 0.015033 (0.015143) Loss: 0.41292 (0.43327) +2025-08-22,23:23:19 | INFO | Train Epoch: 6 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.50386 (0.41834) Boundary_loss: 0.015075 (0.015143) Loss: 0.51893 (0.43349) +2025-08-22,23:24:16 | INFO | Train Epoch: 6 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.41571 (0.41834) Boundary_loss: 0.015131 (0.015143) Loss: 0.43084 (0.43348) +2025-08-22,23:25:13 | INFO | Train Epoch: 6 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.43638 (0.41838) Boundary_loss: 0.015161 (0.015143) Loss: 0.45154 (0.43352) +2025-08-22,23:26:09 | INFO | Train Epoch: 6 [20326912/26365952 (77%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 0.43758 (0.41843) Boundary_loss: 0.015054 (0.015143) Loss: 0.45263 (0.43357) +2025-08-22,23:27:06 | INFO | Train Epoch: 6 [20378112/26365952 (77%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.45426 (0.41852) Boundary_loss: 0.015284 (0.015143) Loss: 0.46955 (0.43366) +2025-08-22,23:28:03 | INFO | Train Epoch: 6 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.195 Boundary Ratio: 0.246 Contrastive_loss: 0.40033 (0.41847) Boundary_loss: 0.015145 (0.015143) Loss: 0.41547 (0.43362) +2025-08-22,23:29:00 | INFO | Train Epoch: 6 [20480512/26365952 (78%)] Avg Boundaries (per batch): 49.344 Boundary Ratio: 0.252 Contrastive_loss: 0.34530 (0.41829) Boundary_loss: 0.015111 (0.015143) Loss: 0.36041 (0.43343) +2025-08-22,23:29:57 | INFO | Train Epoch: 6 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 0.47381 (0.41843) Boundary_loss: 0.015043 (0.015143) Loss: 0.48886 (0.43357) +2025-08-22,23:30:53 | INFO | Train Epoch: 6 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.47100 (0.41856) Boundary_loss: 0.014945 (0.015142) Loss: 0.48594 (0.43370) +2025-08-22,23:31:50 | INFO | Train Epoch: 6 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.350 Boundary Ratio: 0.247 Contrastive_loss: 0.39904 (0.41851) Boundary_loss: 0.015018 (0.015142) Loss: 0.41405 (0.43365) +2025-08-22,23:32:47 | INFO | Train Epoch: 6 [20685312/26365952 (78%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.44470 (0.41858) Boundary_loss: 0.015027 (0.015142) Loss: 0.45973 (0.43372) +2025-08-22,23:33:43 | INFO | Train Epoch: 6 [20736512/26365952 (79%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.36462 (0.41844) Boundary_loss: 0.015082 (0.015142) Loss: 0.37971 (0.43358) +2025-08-22,23:34:40 | INFO | Train Epoch: 6 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.44848 (0.41852) Boundary_loss: 0.014975 (0.015141) Loss: 0.46345 (0.43366) +2025-08-22,23:35:37 | INFO | Train Epoch: 6 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.40769 (0.41849) Boundary_loss: 0.015059 (0.015141) Loss: 0.42275 (0.43363) +2025-08-22,23:36:34 | INFO | Train Epoch: 6 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.44172 (0.41855) Boundary_loss: 0.015058 (0.015141) Loss: 0.45678 (0.43369) +2025-08-22,23:37:31 | INFO | Train Epoch: 6 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.40791 (0.41852) Boundary_loss: 0.015057 (0.015141) Loss: 0.42296 (0.43366) +2025-08-22,23:38:27 | INFO | Train Epoch: 6 [20992512/26365952 (80%)] Avg Boundaries (per batch): 49.527 Boundary Ratio: 0.253 Contrastive_loss: 0.42409 (0.41853) Boundary_loss: 0.015216 (0.015141) Loss: 0.43931 (0.43368) +2025-08-22,23:39:24 | INFO | Train Epoch: 6 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.45483 (0.41862) Boundary_loss: 0.015045 (0.015141) Loss: 0.46988 (0.43376) +2025-08-22,23:40:21 | INFO | Train Epoch: 6 [21094912/26365952 (80%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.37918 (0.41853) Boundary_loss: 0.015153 (0.015141) Loss: 0.39434 (0.43367) +2025-08-22,23:41:17 | INFO | Train Epoch: 6 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.42409 (0.41854) Boundary_loss: 0.015279 (0.015141) Loss: 0.43936 (0.43368) +2025-08-22,23:42:14 | INFO | Train Epoch: 6 [21197312/26365952 (80%)] Avg Boundaries (per batch): 49.363 Boundary Ratio: 0.252 Contrastive_loss: 0.46547 (0.41865) Boundary_loss: 0.015120 (0.015141) Loss: 0.48059 (0.43379) +2025-08-22,23:43:11 | INFO | Train Epoch: 6 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.47100 (0.41878) Boundary_loss: 0.015178 (0.015141) Loss: 0.48618 (0.43392) +2025-08-22,23:44:08 | INFO | Train Epoch: 6 [21299712/26365952 (81%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.44947 (0.41885) Boundary_loss: 0.015170 (0.015141) Loss: 0.46464 (0.43399) +2025-08-22,23:45:04 | INFO | Train Epoch: 6 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.43055 (0.41888) Boundary_loss: 0.015095 (0.015141) Loss: 0.44564 (0.43402) +2025-08-22,23:46:01 | INFO | Train Epoch: 6 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.39394 (0.41882) Boundary_loss: 0.015080 (0.015141) Loss: 0.40902 (0.43396) +2025-08-22,23:46:58 | INFO | Train Epoch: 6 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.40449 (0.41879) Boundary_loss: 0.015239 (0.015141) Loss: 0.41972 (0.43393) +2025-08-22,23:47:55 | INFO | Train Epoch: 6 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.45205 (0.41887) Boundary_loss: 0.015114 (0.015141) Loss: 0.46717 (0.43401) +2025-08-22,23:48:52 | INFO | Train Epoch: 6 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.39524 (0.41881) Boundary_loss: 0.015075 (0.015141) Loss: 0.41032 (0.43395) +2025-08-22,23:49:49 | INFO | Train Epoch: 6 [21606912/26365952 (82%)] Avg Boundaries (per batch): 49.486 Boundary Ratio: 0.252 Contrastive_loss: 0.40889 (0.41879) Boundary_loss: 0.015158 (0.015141) Loss: 0.42405 (0.43393) +2025-08-22,23:50:45 | INFO | Train Epoch: 6 [21658112/26365952 (82%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.53801 (0.41907) Boundary_loss: 0.015145 (0.015141) Loss: 0.55316 (0.43421) +2025-08-22,23:51:42 | INFO | Train Epoch: 6 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.43059 (0.41910) Boundary_loss: 0.015195 (0.015141) Loss: 0.44579 (0.43424) +2025-08-22,23:52:39 | INFO | Train Epoch: 6 [21760512/26365952 (83%)] Avg Boundaries (per batch): 49.295 Boundary Ratio: 0.252 Contrastive_loss: 0.44916 (0.41917) Boundary_loss: 0.015048 (0.015141) Loss: 0.46421 (0.43431) +2025-08-22,23:53:35 | INFO | Train Epoch: 6 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.44745 (0.41923) Boundary_loss: 0.015231 (0.015141) Loss: 0.46268 (0.43437) +2025-08-22,23:54:32 | INFO | Train Epoch: 6 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.31209 (0.41898) Boundary_loss: 0.015201 (0.015141) Loss: 0.32729 (0.43412) +2025-08-22,23:55:29 | INFO | Train Epoch: 6 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.38064 (0.41889) Boundary_loss: 0.015023 (0.015141) Loss: 0.39566 (0.43403) +2025-08-22,23:56:26 | INFO | Train Epoch: 6 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.258 Boundary Ratio: 0.251 Contrastive_loss: 0.39891 (0.41885) Boundary_loss: 0.015041 (0.015141) Loss: 0.41395 (0.43399) +2025-08-22,23:57:22 | INFO | Train Epoch: 6 [22016512/26365952 (84%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.34366 (0.41867) Boundary_loss: 0.014974 (0.015140) Loss: 0.35863 (0.43381) +2025-08-22,23:58:19 | INFO | Train Epoch: 6 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.053 Boundary Ratio: 0.245 Contrastive_loss: 0.43456 (0.41871) Boundary_loss: 0.015212 (0.015140) Loss: 0.44978 (0.43385) +2025-08-22,23:59:16 | INFO | Train Epoch: 6 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.52162 (0.41895) Boundary_loss: 0.015184 (0.015140) Loss: 0.53681 (0.43409) +2025-08-23,00:00:13 | INFO | Train Epoch: 6 [22170112/26365952 (84%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.39538 (0.41889) Boundary_loss: 0.015129 (0.015140) Loss: 0.41050 (0.43403) +2025-08-23,00:01:10 | INFO | Train Epoch: 6 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.43363 (0.41893) Boundary_loss: 0.015228 (0.015141) Loss: 0.44886 (0.43407) +2025-08-23,00:02:06 | INFO | Train Epoch: 6 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.35243 (0.41877) Boundary_loss: 0.015205 (0.015141) Loss: 0.36763 (0.43391) +2025-08-23,00:03:03 | INFO | Train Epoch: 6 [22323712/26365952 (85%)] Avg Boundaries (per batch): 49.602 Boundary Ratio: 0.253 Contrastive_loss: 0.42628 (0.41879) Boundary_loss: 0.015032 (0.015141) Loss: 0.44131 (0.43393) +2025-08-23,00:04:00 | INFO | Train Epoch: 6 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.39786 (0.41874) Boundary_loss: 0.015177 (0.015141) Loss: 0.41303 (0.43388) +2025-08-23,00:04:57 | INFO | Train Epoch: 6 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.35025 (0.41859) Boundary_loss: 0.015082 (0.015140) Loss: 0.36533 (0.43373) +2025-08-23,00:05:53 | INFO | Train Epoch: 6 [22477312/26365952 (85%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.41799 (0.41859) Boundary_loss: 0.015021 (0.015140) Loss: 0.43301 (0.43373) +2025-08-23,00:06:50 | INFO | Train Epoch: 6 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.34777 (0.41842) Boundary_loss: 0.015232 (0.015140) Loss: 0.36301 (0.43357) +2025-08-23,00:07:47 | INFO | Train Epoch: 6 [22579712/26365952 (86%)] Avg Boundaries (per batch): 49.381 Boundary Ratio: 0.252 Contrastive_loss: 0.43130 (0.41845) Boundary_loss: 0.015109 (0.015140) Loss: 0.44640 (0.43359) +2025-08-23,00:08:44 | INFO | Train Epoch: 6 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.39858 (0.41841) Boundary_loss: 0.015020 (0.015140) Loss: 0.41360 (0.43355) +2025-08-23,00:09:40 | INFO | Train Epoch: 6 [22682112/26365952 (86%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.55101 (0.41871) Boundary_loss: 0.015164 (0.015140) Loss: 0.56617 (0.43385) +2025-08-23,00:10:37 | INFO | Train Epoch: 6 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.305 Boundary Ratio: 0.252 Contrastive_loss: 0.44631 (0.41877) Boundary_loss: 0.015256 (0.015140) Loss: 0.46156 (0.43391) +2025-08-23,00:11:34 | INFO | Train Epoch: 6 [22784512/26365952 (86%)] Avg Boundaries (per batch): 47.945 Boundary Ratio: 0.245 Contrastive_loss: 0.39775 (0.41872) Boundary_loss: 0.015114 (0.015140) Loss: 0.41286 (0.43386) +2025-08-23,00:12:31 | INFO | Train Epoch: 6 [22835712/26365952 (87%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.44173 (0.41877) Boundary_loss: 0.015085 (0.015140) Loss: 0.45681 (0.43391) +2025-08-23,00:13:27 | INFO | Train Epoch: 6 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.41383 (0.41876) Boundary_loss: 0.015171 (0.015140) Loss: 0.42900 (0.43390) +2025-08-23,00:14:24 | INFO | Train Epoch: 6 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.43423 (0.41880) Boundary_loss: 0.015045 (0.015140) Loss: 0.44928 (0.43394) +2025-08-23,00:15:21 | INFO | Train Epoch: 6 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.34878 (0.41864) Boundary_loss: 0.015170 (0.015140) Loss: 0.36395 (0.43378) +2025-08-23,00:16:18 | INFO | Train Epoch: 6 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.43326 (0.41867) Boundary_loss: 0.015030 (0.015140) Loss: 0.44829 (0.43381) +2025-08-23,00:17:14 | INFO | Train Epoch: 6 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.44539 (0.41873) Boundary_loss: 0.015062 (0.015140) Loss: 0.46046 (0.43387) +2025-08-23,00:18:11 | INFO | Train Epoch: 6 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.37818 (0.41864) Boundary_loss: 0.015135 (0.015140) Loss: 0.39332 (0.43378) +2025-08-23,00:19:08 | INFO | Train Epoch: 6 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.41130 (0.41863) Boundary_loss: 0.014994 (0.015139) Loss: 0.42630 (0.43377) +2025-08-23,00:20:05 | INFO | Train Epoch: 6 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.39291 (0.41857) Boundary_loss: 0.015131 (0.015139) Loss: 0.40804 (0.43371) +2025-08-23,00:21:01 | INFO | Train Epoch: 6 [23296512/26365952 (88%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.42405 (0.41858) Boundary_loss: 0.015102 (0.015139) Loss: 0.43915 (0.43372) +2025-08-23,00:21:58 | INFO | Train Epoch: 6 [23347712/26365952 (89%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.48181 (0.41872) Boundary_loss: 0.015289 (0.015140) Loss: 0.49710 (0.43386) +2025-08-23,00:22:55 | INFO | Train Epoch: 6 [23398912/26365952 (89%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.38720 (0.41865) Boundary_loss: 0.015030 (0.015139) Loss: 0.40223 (0.43379) +2025-08-23,00:23:52 | INFO | Train Epoch: 6 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.529 Boundary Ratio: 0.253 Contrastive_loss: 0.40162 (0.41862) Boundary_loss: 0.015201 (0.015140) Loss: 0.41682 (0.43376) +2025-08-23,00:24:48 | INFO | Train Epoch: 6 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.34600 (0.41846) Boundary_loss: 0.015100 (0.015139) Loss: 0.36110 (0.43360) +2025-08-23,00:25:45 | INFO | Train Epoch: 6 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.32816 (0.41826) Boundary_loss: 0.015098 (0.015139) Loss: 0.34325 (0.43340) +2025-08-23,00:26:42 | INFO | Train Epoch: 6 [23603712/26365952 (90%)] Avg Boundaries (per batch): 47.469 Boundary Ratio: 0.242 Contrastive_loss: 0.28017 (0.41796) Boundary_loss: 0.015260 (0.015140) Loss: 0.29543 (0.43310) +2025-08-23,00:27:39 | INFO | Train Epoch: 6 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.38586 (0.41789) Boundary_loss: 0.015230 (0.015140) Loss: 0.40109 (0.43303) +2025-08-23,00:28:35 | INFO | Train Epoch: 6 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.39435 (0.41784) Boundary_loss: 0.015161 (0.015140) Loss: 0.40951 (0.43298) +2025-08-23,00:29:32 | INFO | Train Epoch: 6 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.41469 (0.41784) Boundary_loss: 0.015259 (0.015140) Loss: 0.42995 (0.43298) +2025-08-23,00:30:28 | INFO | Train Epoch: 6 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.41424 (0.41783) Boundary_loss: 0.015132 (0.015140) Loss: 0.42938 (0.43297) +2025-08-23,00:31:25 | INFO | Train Epoch: 6 [23859712/26365952 (90%)] Avg Boundaries (per batch): 49.908 Boundary Ratio: 0.255 Contrastive_loss: 0.36311 (0.41771) Boundary_loss: 0.015089 (0.015140) Loss: 0.37820 (0.43285) +2025-08-23,00:32:22 | INFO | Train Epoch: 6 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.39429 (0.41766) Boundary_loss: 0.015118 (0.015140) Loss: 0.40941 (0.43280) +2025-08-23,00:33:18 | INFO | Train Epoch: 6 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.34940 (0.41752) Boundary_loss: 0.015197 (0.015140) Loss: 0.36460 (0.43266) +2025-08-23,00:34:15 | INFO | Train Epoch: 6 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 0.40795 (0.41750) Boundary_loss: 0.015013 (0.015140) Loss: 0.42296 (0.43263) +2025-08-23,00:35:12 | INFO | Train Epoch: 6 [24064512/26365952 (91%)] Avg Boundaries (per batch): 49.293 Boundary Ratio: 0.251 Contrastive_loss: 0.41916 (0.41750) Boundary_loss: 0.015078 (0.015140) Loss: 0.43424 (0.43264) +2025-08-23,00:36:08 | INFO | Train Epoch: 6 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.43984 (0.41755) Boundary_loss: 0.015039 (0.015139) Loss: 0.45488 (0.43269) +2025-08-23,00:37:05 | INFO | Train Epoch: 6 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.744 Boundary Ratio: 0.254 Contrastive_loss: 0.33035 (0.41736) Boundary_loss: 0.015133 (0.015139) Loss: 0.34549 (0.43250) +2025-08-23,00:38:02 | INFO | Train Epoch: 6 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.34765 (0.41721) Boundary_loss: 0.015118 (0.015139) Loss: 0.36277 (0.43235) +2025-08-23,00:38:59 | INFO | Train Epoch: 6 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.39894 (0.41718) Boundary_loss: 0.015135 (0.015139) Loss: 0.41407 (0.43232) +2025-08-23,00:39:55 | INFO | Train Epoch: 6 [24320512/26365952 (92%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.43397 (0.41721) Boundary_loss: 0.015097 (0.015139) Loss: 0.44907 (0.43235) +2025-08-23,00:40:52 | INFO | Train Epoch: 6 [24371712/26365952 (92%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 0.36702 (0.41711) Boundary_loss: 0.015204 (0.015139) Loss: 0.38222 (0.43225) +2025-08-23,00:41:49 | INFO | Train Epoch: 6 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.26425 (0.41679) Boundary_loss: 0.015135 (0.015139) Loss: 0.27938 (0.43193) +2025-08-23,00:42:46 | INFO | Train Epoch: 6 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.38711 (0.41672) Boundary_loss: 0.015235 (0.015140) Loss: 0.40234 (0.43186) +2025-08-23,00:43:42 | INFO | Train Epoch: 6 [24525312/26365952 (93%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 0.34231 (0.41657) Boundary_loss: 0.015307 (0.015140) Loss: 0.35761 (0.43171) +2025-08-23,00:44:39 | INFO | Train Epoch: 6 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 0.47201 (0.41668) Boundary_loss: 0.015232 (0.015140) Loss: 0.48724 (0.43182) +2025-08-23,00:45:36 | INFO | Train Epoch: 6 [24627712/26365952 (93%)] Avg Boundaries (per batch): 49.506 Boundary Ratio: 0.253 Contrastive_loss: 0.40120 (0.41665) Boundary_loss: 0.015228 (0.015140) Loss: 0.41643 (0.43179) +2025-08-23,00:46:33 | INFO | Train Epoch: 6 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.42898 (0.41668) Boundary_loss: 0.015234 (0.015141) Loss: 0.44421 (0.43182) +2025-08-23,00:47:29 | INFO | Train Epoch: 6 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.39934 (0.41664) Boundary_loss: 0.015129 (0.015140) Loss: 0.41447 (0.43178) +2025-08-23,00:48:26 | INFO | Train Epoch: 6 [24781312/26365952 (94%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.43891 (0.41669) Boundary_loss: 0.015148 (0.015141) Loss: 0.45405 (0.43183) +2025-08-23,00:49:23 | INFO | Train Epoch: 6 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.42441 (0.41670) Boundary_loss: 0.015138 (0.015140) Loss: 0.43955 (0.43184) +2025-08-23,00:50:19 | INFO | Train Epoch: 6 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.40521 (0.41668) Boundary_loss: 0.015039 (0.015140) Loss: 0.42025 (0.43182) +2025-08-23,00:51:16 | INFO | Train Epoch: 6 [24934912/26365952 (95%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 0.43062 (0.41671) Boundary_loss: 0.015103 (0.015140) Loss: 0.44573 (0.43185) +2025-08-23,00:52:13 | INFO | Train Epoch: 6 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.43983 (0.41676) Boundary_loss: 0.015186 (0.015140) Loss: 0.45502 (0.43190) +2025-08-23,00:53:10 | INFO | Train Epoch: 6 [25037312/26365952 (95%)] Avg Boundaries (per batch): 49.400 Boundary Ratio: 0.252 Contrastive_loss: 0.39446 (0.41671) Boundary_loss: 0.015217 (0.015140) Loss: 0.40968 (0.43185) +2025-08-23,00:54:07 | INFO | Train Epoch: 6 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.38769 (0.41665) Boundary_loss: 0.015079 (0.015140) Loss: 0.40277 (0.43179) +2025-08-23,00:55:03 | INFO | Train Epoch: 6 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.50478 (0.41683) Boundary_loss: 0.014937 (0.015140) Loss: 0.51971 (0.43197) +2025-08-23,00:56:00 | INFO | Train Epoch: 6 [25190912/26365952 (96%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.44278 (0.41688) Boundary_loss: 0.015051 (0.015140) Loss: 0.45783 (0.43202) +2025-08-23,00:56:57 | INFO | Train Epoch: 6 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 0.53629 (0.41713) Boundary_loss: 0.015142 (0.015140) Loss: 0.55143 (0.43226) +2025-08-23,00:57:53 | INFO | Train Epoch: 6 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.37055 (0.41703) Boundary_loss: 0.015039 (0.015140) Loss: 0.38559 (0.43217) +2025-08-23,00:58:50 | INFO | Train Epoch: 6 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.43249 (0.41706) Boundary_loss: 0.015132 (0.015140) Loss: 0.44762 (0.43220) +2025-08-23,00:59:47 | INFO | Train Epoch: 6 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.40333 (0.41703) Boundary_loss: 0.015033 (0.015139) Loss: 0.41837 (0.43217) +2025-08-23,01:00:44 | INFO | Train Epoch: 6 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.41891 (0.41704) Boundary_loss: 0.015157 (0.015139) Loss: 0.43407 (0.43218) +2025-08-23,01:01:40 | INFO | Train Epoch: 6 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.49585 (0.41720) Boundary_loss: 0.015273 (0.015140) Loss: 0.51112 (0.43234) +2025-08-23,01:02:37 | INFO | Train Epoch: 6 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.40097 (0.41716) Boundary_loss: 0.015076 (0.015139) Loss: 0.41604 (0.43230) +2025-08-23,01:03:34 | INFO | Train Epoch: 6 [25600512/26365952 (97%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 0.48922 (0.41731) Boundary_loss: 0.015052 (0.015139) Loss: 0.50427 (0.43245) +2025-08-23,01:04:31 | INFO | Train Epoch: 6 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.38542 (0.41724) Boundary_loss: 0.015142 (0.015139) Loss: 0.40056 (0.43238) +2025-08-23,01:05:27 | INFO | Train Epoch: 6 [25702912/26365952 (97%)] Avg Boundaries (per batch): 47.854 Boundary Ratio: 0.244 Contrastive_loss: 0.41651 (0.41724) Boundary_loss: 0.015195 (0.015139) Loss: 0.43171 (0.43238) +2025-08-23,01:06:24 | INFO | Train Epoch: 6 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.47780 (0.41736) Boundary_loss: 0.015150 (0.015139) Loss: 0.49295 (0.43250) +2025-08-23,01:07:21 | INFO | Train Epoch: 6 [25805312/26365952 (98%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 0.49531 (0.41752) Boundary_loss: 0.015228 (0.015140) Loss: 0.51054 (0.43266) +2025-08-23,01:08:18 | INFO | Train Epoch: 6 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.41131 (0.41750) Boundary_loss: 0.015019 (0.015139) Loss: 0.42633 (0.43264) +2025-08-23,01:09:15 | INFO | Train Epoch: 6 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.336 Boundary Ratio: 0.247 Contrastive_loss: 0.34380 (0.41736) Boundary_loss: 0.015114 (0.015139) Loss: 0.35892 (0.43250) +2025-08-23,01:10:11 | INFO | Train Epoch: 6 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.264 Boundary Ratio: 0.246 Contrastive_loss: 0.40876 (0.41734) Boundary_loss: 0.015186 (0.015139) Loss: 0.42395 (0.43248) +2025-08-23,01:11:08 | INFO | Train Epoch: 6 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.41833 (0.41734) Boundary_loss: 0.015068 (0.015139) Loss: 0.43340 (0.43248) +2025-08-23,01:12:05 | INFO | Train Epoch: 6 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.41957 (0.41735) Boundary_loss: 0.015082 (0.015139) Loss: 0.43465 (0.43249) +2025-08-23,01:13:02 | INFO | Train Epoch: 6 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.43416 (0.41738) Boundary_loss: 0.015172 (0.015139) Loss: 0.44933 (0.43252) +2025-08-23,01:13:58 | INFO | Train Epoch: 6 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.38972 (0.41733) Boundary_loss: 0.015138 (0.015139) Loss: 0.40486 (0.43247) +2025-08-23,01:14:55 | INFO | Train Epoch: 6 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.42118 (0.41734) Boundary_loss: 0.015099 (0.015139) Loss: 0.43628 (0.43247) +2025-08-23,01:15:52 | INFO | Train Epoch: 6 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.506 Boundary Ratio: 0.253 Contrastive_loss: 0.45347 (0.41741) Boundary_loss: 0.015033 (0.015139) Loss: 0.46850 (0.43254) +2025-08-23,01:16:49 | INFO | Train Epoch: 6 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.277 Boundary Ratio: 0.246 Contrastive_loss: 0.36238 (0.41730) Boundary_loss: 0.015152 (0.015139) Loss: 0.37753 (0.43244) +2025-08-23,01:17:42 | INFO | Train Epoch: 6 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.43153 (0.41733) Boundary_loss: 0.015019 (0.015139) Loss: 0.44654 (0.43247) +2025-08-23,01:17:42 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-23,01:17:42 | INFO | [Epoch 6] Average Step Time: 0.571s | Average GPU Memory: 31.9 GB +2025-08-23,01:17:42 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-23,01:17:42 | INFO | Starting zero-shot imagenet. +2025-08-23,01:17:42 | INFO | Building zero-shot classifier +2025-08-23,01:17:51 | INFO | Using classifier +2025-08-23,01:18:34 | INFO | Finished zero-shot imagenet. +2025-08-23,01:18:34 | INFO | Eval Epoch: 7 imagenet-zeroshot-val-top1: 0.2629 imagenet-zeroshot-val-top5: 0.5145 +2025-08-23,01:18:35 | INFO | Start epoch 7 +2025-08-23,01:18:38 | INFO | Train Epoch: 7 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.30059 (0.30059) Boundary_loss: 0.015000 (0.015000) Loss: 0.31559 (0.31559) +2025-08-23,01:19:34 | INFO | Train Epoch: 7 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.40230 (0.35145) Boundary_loss: 0.015293 (0.015146) Loss: 0.41759 (0.36659) +2025-08-23,01:20:31 | INFO | Train Epoch: 7 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.40002 (0.36764) Boundary_loss: 0.015171 (0.015155) Loss: 0.41519 (0.38279) +2025-08-23,01:21:27 | INFO | Train Epoch: 7 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.44383 (0.38669) Boundary_loss: 0.014901 (0.015091) Loss: 0.45873 (0.40178) +2025-08-23,01:22:24 | INFO | Train Epoch: 7 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 0.37485 (0.38432) Boundary_loss: 0.015220 (0.015117) Loss: 0.39007 (0.39944) +2025-08-23,01:23:21 | INFO | Train Epoch: 7 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.37316 (0.38246) Boundary_loss: 0.015131 (0.015119) Loss: 0.38829 (0.39758) +2025-08-23,01:24:18 | INFO | Train Epoch: 7 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.53030 (0.40358) Boundary_loss: 0.015193 (0.015130) Loss: 0.54550 (0.41871) +2025-08-23,01:25:14 | INFO | Train Epoch: 7 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.37193 (0.39962) Boundary_loss: 0.015021 (0.015116) Loss: 0.38695 (0.41474) +2025-08-23,01:26:11 | INFO | Train Epoch: 7 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.36313 (0.39557) Boundary_loss: 0.014981 (0.015101) Loss: 0.37811 (0.41067) +2025-08-23,01:27:07 | INFO | Train Epoch: 7 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.40619 (0.39663) Boundary_loss: 0.015079 (0.015099) Loss: 0.42127 (0.41173) +2025-08-23,01:28:04 | INFO | Train Epoch: 7 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.37891 (0.39502) Boundary_loss: 0.015110 (0.015100) Loss: 0.39402 (0.41012) +2025-08-23,01:29:01 | INFO | Train Epoch: 7 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 49.432 Boundary Ratio: 0.252 Contrastive_loss: 0.35835 (0.39196) Boundary_loss: 0.015139 (0.015103) Loss: 0.37348 (0.40707) +2025-08-23,01:29:57 | INFO | Train Epoch: 7 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.492 Boundary Ratio: 0.247 Contrastive_loss: 0.42721 (0.39467) Boundary_loss: 0.015146 (0.015107) Loss: 0.44235 (0.40978) +2025-08-23,01:30:54 | INFO | Train Epoch: 7 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.37121 (0.39300) Boundary_loss: 0.015094 (0.015106) Loss: 0.38630 (0.40810) +2025-08-23,01:31:51 | INFO | Train Epoch: 7 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.26359 (0.38437) Boundary_loss: 0.015073 (0.015103) Loss: 0.27867 (0.39947) +2025-08-23,01:32:48 | INFO | Train Epoch: 7 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.37381 (0.38371) Boundary_loss: 0.015179 (0.015108) Loss: 0.38899 (0.39882) +2025-08-23,01:33:44 | INFO | Train Epoch: 7 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.090 Boundary Ratio: 0.245 Contrastive_loss: 0.28549 (0.37793) Boundary_loss: 0.015159 (0.015111) Loss: 0.30065 (0.39304) +2025-08-23,01:34:41 | INFO | Train Epoch: 7 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 47.965 Boundary Ratio: 0.245 Contrastive_loss: 0.40966 (0.37970) Boundary_loss: 0.015293 (0.015121) Loss: 0.42496 (0.39482) +2025-08-23,01:35:38 | INFO | Train Epoch: 7 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 47.947 Boundary Ratio: 0.245 Contrastive_loss: 0.39122 (0.38030) Boundary_loss: 0.015066 (0.015118) Loss: 0.40629 (0.39542) +2025-08-23,01:36:35 | INFO | Train Epoch: 7 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 0.34221 (0.37840) Boundary_loss: 0.015109 (0.015118) Loss: 0.35732 (0.39352) +2025-08-23,01:37:31 | INFO | Train Epoch: 7 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.33835 (0.37649) Boundary_loss: 0.015148 (0.015119) Loss: 0.35350 (0.39161) +2025-08-23,01:38:28 | INFO | Train Epoch: 7 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.39650 (0.37740) Boundary_loss: 0.015223 (0.015124) Loss: 0.41173 (0.39253) +2025-08-23,01:39:25 | INFO | Train Epoch: 7 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.40702 (0.37869) Boundary_loss: 0.015075 (0.015122) Loss: 0.42209 (0.39381) +2025-08-23,01:40:21 | INFO | Train Epoch: 7 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.34991 (0.37749) Boundary_loss: 0.015060 (0.015119) Loss: 0.36497 (0.39261) +2025-08-23,01:41:18 | INFO | Train Epoch: 7 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 0.40919 (0.37876) Boundary_loss: 0.015165 (0.015121) Loss: 0.42435 (0.39388) +2025-08-23,01:42:14 | INFO | Train Epoch: 7 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.40107 (0.37962) Boundary_loss: 0.015267 (0.015127) Loss: 0.41634 (0.39474) +2025-08-23,01:43:11 | INFO | Train Epoch: 7 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 49.326 Boundary Ratio: 0.252 Contrastive_loss: 0.30849 (0.37698) Boundary_loss: 0.015087 (0.015125) Loss: 0.32358 (0.39211) +2025-08-23,01:44:08 | INFO | Train Epoch: 7 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.385 Boundary Ratio: 0.247 Contrastive_loss: 0.38780 (0.37737) Boundary_loss: 0.015011 (0.015121) Loss: 0.40281 (0.39249) +2025-08-23,01:45:04 | INFO | Train Epoch: 7 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.36019 (0.37678) Boundary_loss: 0.015134 (0.015122) Loss: 0.37533 (0.39190) +2025-08-23,01:46:01 | INFO | Train Epoch: 7 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 0.42953 (0.37853) Boundary_loss: 0.015125 (0.015122) Loss: 0.44466 (0.39366) +2025-08-23,01:46:58 | INFO | Train Epoch: 7 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.32475 (0.37680) Boundary_loss: 0.014985 (0.015117) Loss: 0.33974 (0.39192) +2025-08-23,01:47:54 | INFO | Train Epoch: 7 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.36028 (0.37628) Boundary_loss: 0.015183 (0.015119) Loss: 0.37546 (0.39140) +2025-08-23,01:48:51 | INFO | Train Epoch: 7 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.35973 (0.37578) Boundary_loss: 0.015065 (0.015118) Loss: 0.37480 (0.39090) +2025-08-23,01:49:47 | INFO | Train Epoch: 7 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.33797 (0.37467) Boundary_loss: 0.015109 (0.015117) Loss: 0.35308 (0.38979) +2025-08-23,01:50:44 | INFO | Train Epoch: 7 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.33213 (0.37345) Boundary_loss: 0.015065 (0.015116) Loss: 0.34719 (0.38857) +2025-08-23,01:51:41 | INFO | Train Epoch: 7 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 0.29754 (0.37135) Boundary_loss: 0.015148 (0.015117) Loss: 0.31269 (0.38646) +2025-08-23,01:52:38 | INFO | Train Epoch: 7 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.29219 (0.36921) Boundary_loss: 0.015097 (0.015116) Loss: 0.30729 (0.38432) +2025-08-23,01:53:34 | INFO | Train Epoch: 7 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.50806 (0.37286) Boundary_loss: 0.014965 (0.015112) Loss: 0.52302 (0.38797) +2025-08-23,01:54:31 | INFO | Train Epoch: 7 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.35466 (0.37239) Boundary_loss: 0.015123 (0.015113) Loss: 0.36979 (0.38751) +2025-08-23,01:55:28 | INFO | Train Epoch: 7 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.29991 (0.37058) Boundary_loss: 0.015157 (0.015114) Loss: 0.31507 (0.38570) +2025-08-23,01:56:24 | INFO | Train Epoch: 7 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 0.31178 (0.36915) Boundary_loss: 0.015020 (0.015111) Loss: 0.32680 (0.38426) +2025-08-23,01:57:21 | INFO | Train Epoch: 7 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.38058 (0.36942) Boundary_loss: 0.014987 (0.015108) Loss: 0.39557 (0.38453) +2025-08-23,01:58:18 | INFO | Train Epoch: 7 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.36828 (0.36939) Boundary_loss: 0.015080 (0.015108) Loss: 0.38336 (0.38450) +2025-08-23,01:59:14 | INFO | Train Epoch: 7 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 49.701 Boundary Ratio: 0.254 Contrastive_loss: 0.38659 (0.36978) Boundary_loss: 0.015126 (0.015108) Loss: 0.40172 (0.38489) +2025-08-23,02:00:11 | INFO | Train Epoch: 7 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 49.582 Boundary Ratio: 0.253 Contrastive_loss: 0.30725 (0.36839) Boundary_loss: 0.015227 (0.015111) Loss: 0.32248 (0.38351) +2025-08-23,02:01:08 | INFO | Train Epoch: 7 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 49.244 Boundary Ratio: 0.251 Contrastive_loss: 0.32323 (0.36741) Boundary_loss: 0.015223 (0.015113) Loss: 0.33845 (0.38253) +2025-08-23,02:02:04 | INFO | Train Epoch: 7 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.43047 (0.36875) Boundary_loss: 0.015106 (0.015113) Loss: 0.44558 (0.38387) +2025-08-23,02:03:01 | INFO | Train Epoch: 7 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 0.44901 (0.37043) Boundary_loss: 0.015169 (0.015114) Loss: 0.46418 (0.38554) +2025-08-23,02:03:58 | INFO | Train Epoch: 7 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.32162 (0.36943) Boundary_loss: 0.015137 (0.015115) Loss: 0.33676 (0.38454) +2025-08-23,02:04:55 | INFO | Train Epoch: 7 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.35347 (0.36911) Boundary_loss: 0.015008 (0.015113) Loss: 0.36848 (0.38422) +2025-08-23,02:05:52 | INFO | Train Epoch: 7 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.090 Boundary Ratio: 0.245 Contrastive_loss: 0.33369 (0.36842) Boundary_loss: 0.015160 (0.015114) Loss: 0.34885 (0.38353) +2025-08-23,02:06:48 | INFO | Train Epoch: 7 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.35798 (0.36822) Boundary_loss: 0.015076 (0.015113) Loss: 0.37306 (0.38333) +2025-08-23,02:07:45 | INFO | Train Epoch: 7 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.44251 (0.36962) Boundary_loss: 0.015130 (0.015113) Loss: 0.45764 (0.38473) +2025-08-23,02:08:42 | INFO | Train Epoch: 7 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.36800 (0.36959) Boundary_loss: 0.015068 (0.015112) Loss: 0.38307 (0.38470) +2025-08-23,02:09:38 | INFO | Train Epoch: 7 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 0.39538 (0.37006) Boundary_loss: 0.015074 (0.015112) Loss: 0.41045 (0.38517) +2025-08-23,02:10:35 | INFO | Train Epoch: 7 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.31505 (0.36907) Boundary_loss: 0.015097 (0.015111) Loss: 0.33015 (0.38419) +2025-08-23,02:11:32 | INFO | Train Epoch: 7 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.35005 (0.36874) Boundary_loss: 0.015109 (0.015111) Loss: 0.36516 (0.38385) +2025-08-23,02:12:29 | INFO | Train Epoch: 7 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.32883 (0.36805) Boundary_loss: 0.015067 (0.015111) Loss: 0.34390 (0.38316) +2025-08-23,02:13:25 | INFO | Train Epoch: 7 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.172 Boundary Ratio: 0.246 Contrastive_loss: 0.42080 (0.36895) Boundary_loss: 0.015149 (0.015111) Loss: 0.43595 (0.38406) +2025-08-23,02:14:22 | INFO | Train Epoch: 7 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.43831 (0.37010) Boundary_loss: 0.015017 (0.015110) Loss: 0.45333 (0.38521) +2025-08-23,02:15:19 | INFO | Train Epoch: 7 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.39754 (0.37055) Boundary_loss: 0.015072 (0.015109) Loss: 0.41261 (0.38566) +2025-08-23,02:16:15 | INFO | Train Epoch: 7 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 49.830 Boundary Ratio: 0.254 Contrastive_loss: 0.51026 (0.37281) Boundary_loss: 0.015207 (0.015111) Loss: 0.52547 (0.38792) +2025-08-23,02:17:12 | INFO | Train Epoch: 7 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 49.527 Boundary Ratio: 0.253 Contrastive_loss: 0.48681 (0.37462) Boundary_loss: 0.015108 (0.015111) Loss: 0.50192 (0.38973) +2025-08-23,02:18:09 | INFO | Train Epoch: 7 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.44229 (0.37567) Boundary_loss: 0.015045 (0.015110) Loss: 0.45734 (0.39078) +2025-08-23,02:19:05 | INFO | Train Epoch: 7 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 0.36584 (0.37552) Boundary_loss: 0.015192 (0.015111) Loss: 0.38103 (0.39063) +2025-08-23,02:20:02 | INFO | Train Epoch: 7 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.33142 (0.37485) Boundary_loss: 0.015037 (0.015110) Loss: 0.34645 (0.38996) +2025-08-23,02:20:58 | INFO | Train Epoch: 7 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.30774 (0.37385) Boundary_loss: 0.015179 (0.015111) Loss: 0.32292 (0.38896) +2025-08-23,02:21:55 | INFO | Train Epoch: 7 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.207 Boundary Ratio: 0.246 Contrastive_loss: 0.38868 (0.37407) Boundary_loss: 0.015130 (0.015111) Loss: 0.40381 (0.38918) +2025-08-23,02:22:52 | INFO | Train Epoch: 7 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 0.38203 (0.37419) Boundary_loss: 0.015218 (0.015113) Loss: 0.39724 (0.38930) +2025-08-23,02:23:49 | INFO | Train Epoch: 7 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 0.37274 (0.37416) Boundary_loss: 0.015158 (0.015113) Loss: 0.38789 (0.38928) +2025-08-23,02:24:45 | INFO | Train Epoch: 7 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.37653 (0.37420) Boundary_loss: 0.015196 (0.015114) Loss: 0.39172 (0.38931) +2025-08-23,02:25:42 | INFO | Train Epoch: 7 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.39044 (0.37442) Boundary_loss: 0.015306 (0.015117) Loss: 0.40575 (0.38954) +2025-08-23,02:26:39 | INFO | Train Epoch: 7 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 49.555 Boundary Ratio: 0.253 Contrastive_loss: 0.33886 (0.37394) Boundary_loss: 0.015184 (0.015118) Loss: 0.35404 (0.38905) +2025-08-23,02:27:36 | INFO | Train Epoch: 7 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 0.38440 (0.37408) Boundary_loss: 0.015037 (0.015117) Loss: 0.39944 (0.38919) +2025-08-23,02:28:32 | INFO | Train Epoch: 7 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 49.578 Boundary Ratio: 0.253 Contrastive_loss: 0.31565 (0.37330) Boundary_loss: 0.015033 (0.015116) Loss: 0.33068 (0.38841) +2025-08-23,02:29:29 | INFO | Train Epoch: 7 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.859 Boundary Ratio: 0.254 Contrastive_loss: 0.37035 (0.37326) Boundary_loss: 0.015270 (0.015118) Loss: 0.38562 (0.38838) +2025-08-23,02:30:26 | INFO | Train Epoch: 7 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.35856 (0.37307) Boundary_loss: 0.015039 (0.015117) Loss: 0.37360 (0.38819) +2025-08-23,02:31:22 | INFO | Train Epoch: 7 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.41287 (0.37358) Boundary_loss: 0.015092 (0.015116) Loss: 0.42796 (0.38870) +2025-08-23,02:32:19 | INFO | Train Epoch: 7 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.37537 (0.37360) Boundary_loss: 0.015093 (0.015116) Loss: 0.39046 (0.38872) +2025-08-23,02:33:16 | INFO | Train Epoch: 7 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 49.402 Boundary Ratio: 0.252 Contrastive_loss: 0.34139 (0.37320) Boundary_loss: 0.015172 (0.015117) Loss: 0.35656 (0.38832) +2025-08-23,02:34:13 | INFO | Train Epoch: 7 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.31006 (0.37242) Boundary_loss: 0.015188 (0.015118) Loss: 0.32525 (0.38754) +2025-08-23,02:35:09 | INFO | Train Epoch: 7 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 0.29763 (0.37151) Boundary_loss: 0.015153 (0.015118) Loss: 0.31278 (0.38663) +2025-08-23,02:36:06 | INFO | Train Epoch: 7 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.44051 (0.37234) Boundary_loss: 0.015132 (0.015118) Loss: 0.45564 (0.38746) +2025-08-23,02:37:03 | INFO | Train Epoch: 7 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 0.43435 (0.37308) Boundary_loss: 0.015107 (0.015118) Loss: 0.44946 (0.38820) +2025-08-23,02:38:00 | INFO | Train Epoch: 7 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 47.869 Boundary Ratio: 0.244 Contrastive_loss: 0.43599 (0.37382) Boundary_loss: 0.015141 (0.015118) Loss: 0.45113 (0.38894) +2025-08-23,02:38:57 | INFO | Train Epoch: 7 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.38917 (0.37400) Boundary_loss: 0.015186 (0.015119) Loss: 0.40435 (0.38911) +2025-08-23,02:39:53 | INFO | Train Epoch: 7 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.34439 (0.37366) Boundary_loss: 0.015281 (0.015121) Loss: 0.35967 (0.38878) +2025-08-23,02:40:50 | INFO | Train Epoch: 7 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.33995 (0.37327) Boundary_loss: 0.015022 (0.015120) Loss: 0.35497 (0.38839) +2025-08-23,02:41:47 | INFO | Train Epoch: 7 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 49.746 Boundary Ratio: 0.254 Contrastive_loss: 0.41478 (0.37374) Boundary_loss: 0.015068 (0.015119) Loss: 0.42984 (0.38886) +2025-08-23,02:42:44 | INFO | Train Epoch: 7 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.33934 (0.37336) Boundary_loss: 0.015210 (0.015120) Loss: 0.35455 (0.38848) +2025-08-23,02:43:40 | INFO | Train Epoch: 7 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.31411 (0.37271) Boundary_loss: 0.015099 (0.015120) Loss: 0.32921 (0.38783) +2025-08-23,02:44:37 | INFO | Train Epoch: 7 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.32074 (0.37214) Boundary_loss: 0.014985 (0.015119) Loss: 0.33572 (0.38726) +2025-08-23,02:45:34 | INFO | Train Epoch: 7 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.44460 (0.37292) Boundary_loss: 0.015025 (0.015118) Loss: 0.45962 (0.38804) +2025-08-23,02:46:31 | INFO | Train Epoch: 7 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.33301 (0.37250) Boundary_loss: 0.015052 (0.015117) Loss: 0.34806 (0.38761) +2025-08-23,02:47:27 | INFO | Train Epoch: 7 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.43826 (0.37319) Boundary_loss: 0.015104 (0.015117) Loss: 0.45337 (0.38830) +2025-08-23,02:48:24 | INFO | Train Epoch: 7 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 0.31912 (0.37262) Boundary_loss: 0.015107 (0.015117) Loss: 0.33423 (0.38774) +2025-08-23,02:49:21 | INFO | Train Epoch: 7 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.131 Boundary Ratio: 0.246 Contrastive_loss: 0.40947 (0.37300) Boundary_loss: 0.015131 (0.015117) Loss: 0.42460 (0.38812) +2025-08-23,02:50:17 | INFO | Train Epoch: 7 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.27615 (0.37202) Boundary_loss: 0.015182 (0.015118) Loss: 0.29133 (0.38713) +2025-08-23,02:51:14 | INFO | Train Epoch: 7 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.33097 (0.37160) Boundary_loss: 0.015005 (0.015116) Loss: 0.34598 (0.38672) +2025-08-23,02:52:10 | INFO | Train Epoch: 7 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 0.45865 (0.37247) Boundary_loss: 0.015096 (0.015116) Loss: 0.47374 (0.38759) +2025-08-23,02:53:07 | INFO | Train Epoch: 7 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.26487 (0.37141) Boundary_loss: 0.015003 (0.015115) Loss: 0.27987 (0.38652) +2025-08-23,02:54:04 | INFO | Train Epoch: 7 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.51964 (0.37286) Boundary_loss: 0.015142 (0.015115) Loss: 0.53478 (0.38797) +2025-08-23,02:55:01 | INFO | Train Epoch: 7 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.35280 (0.37266) Boundary_loss: 0.015049 (0.015115) Loss: 0.36785 (0.38778) +2025-08-23,02:55:57 | INFO | Train Epoch: 7 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.38125 (0.37275) Boundary_loss: 0.015074 (0.015114) Loss: 0.39633 (0.38786) +2025-08-23,02:56:54 | INFO | Train Epoch: 7 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 0.38759 (0.37289) Boundary_loss: 0.015067 (0.015114) Loss: 0.40265 (0.38800) +2025-08-23,02:57:51 | INFO | Train Epoch: 7 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.30819 (0.37228) Boundary_loss: 0.015211 (0.015115) Loss: 0.32340 (0.38739) +2025-08-23,02:58:48 | INFO | Train Epoch: 7 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.42850 (0.37280) Boundary_loss: 0.015052 (0.015114) Loss: 0.44355 (0.38792) +2025-08-23,02:59:45 | INFO | Train Epoch: 7 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 0.37952 (0.37287) Boundary_loss: 0.015084 (0.015114) Loss: 0.39460 (0.38798) +2025-08-23,03:00:41 | INFO | Train Epoch: 7 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.38512 (0.37298) Boundary_loss: 0.015056 (0.015113) Loss: 0.40017 (0.38809) +2025-08-23,03:01:38 | INFO | Train Epoch: 7 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.38540 (0.37309) Boundary_loss: 0.014995 (0.015112) Loss: 0.40040 (0.38820) +2025-08-23,03:02:35 | INFO | Train Epoch: 7 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.29695 (0.37241) Boundary_loss: 0.015168 (0.015113) Loss: 0.31212 (0.38752) +2025-08-23,03:03:32 | INFO | Train Epoch: 7 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.260 Boundary Ratio: 0.251 Contrastive_loss: 0.36346 (0.37233) Boundary_loss: 0.015159 (0.015113) Loss: 0.37862 (0.38744) +2025-08-23,03:04:28 | INFO | Train Epoch: 7 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.34740 (0.37210) Boundary_loss: 0.015034 (0.015113) Loss: 0.36244 (0.38722) +2025-08-23,03:05:25 | INFO | Train Epoch: 7 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.35165 (0.37193) Boundary_loss: 0.015024 (0.015112) Loss: 0.36667 (0.38704) +2025-08-23,03:06:22 | INFO | Train Epoch: 7 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.35311 (0.37176) Boundary_loss: 0.015035 (0.015111) Loss: 0.36814 (0.38687) +2025-08-23,03:07:19 | INFO | Train Epoch: 7 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.43155 (0.37228) Boundary_loss: 0.014956 (0.015110) Loss: 0.44650 (0.38739) +2025-08-23,03:08:15 | INFO | Train Epoch: 7 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.35140 (0.37210) Boundary_loss: 0.015056 (0.015109) Loss: 0.36645 (0.38721) +2025-08-23,03:09:12 | INFO | Train Epoch: 7 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 49.189 Boundary Ratio: 0.251 Contrastive_loss: 0.45694 (0.37282) Boundary_loss: 0.014950 (0.015108) Loss: 0.47189 (0.38793) +2025-08-23,03:10:09 | INFO | Train Epoch: 7 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.36415 (0.37274) Boundary_loss: 0.015061 (0.015108) Loss: 0.37921 (0.38785) +2025-08-23,03:11:06 | INFO | Train Epoch: 7 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.209 Boundary Ratio: 0.246 Contrastive_loss: 0.32123 (0.37232) Boundary_loss: 0.015061 (0.015107) Loss: 0.33629 (0.38742) +2025-08-23,03:12:02 | INFO | Train Epoch: 7 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.28992 (0.37163) Boundary_loss: 0.015179 (0.015108) Loss: 0.30509 (0.38674) +2025-08-23,03:12:59 | INFO | Train Epoch: 7 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.41350 (0.37198) Boundary_loss: 0.015153 (0.015108) Loss: 0.42865 (0.38709) +2025-08-23,03:13:56 | INFO | Train Epoch: 7 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.34380 (0.37175) Boundary_loss: 0.015168 (0.015109) Loss: 0.35896 (0.38686) +2025-08-23,03:14:52 | INFO | Train Epoch: 7 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.32476 (0.37137) Boundary_loss: 0.015085 (0.015108) Loss: 0.33984 (0.38648) +2025-08-23,03:15:49 | INFO | Train Epoch: 7 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 0.31943 (0.37095) Boundary_loss: 0.015113 (0.015108) Loss: 0.33454 (0.38606) +2025-08-23,03:16:46 | INFO | Train Epoch: 7 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.30051 (0.37039) Boundary_loss: 0.015066 (0.015108) Loss: 0.31557 (0.38550) +2025-08-23,03:17:43 | INFO | Train Epoch: 7 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.33026 (0.37008) Boundary_loss: 0.015122 (0.015108) Loss: 0.34538 (0.38519) +2025-08-23,03:18:40 | INFO | Train Epoch: 7 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 47.855 Boundary Ratio: 0.244 Contrastive_loss: 0.37614 (0.37013) Boundary_loss: 0.015137 (0.015108) Loss: 0.39128 (0.38523) +2025-08-23,03:19:36 | INFO | Train Epoch: 7 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.38690 (0.37026) Boundary_loss: 0.015031 (0.015108) Loss: 0.40193 (0.38536) +2025-08-23,03:20:33 | INFO | Train Epoch: 7 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.148 Boundary Ratio: 0.251 Contrastive_loss: 0.36952 (0.37025) Boundary_loss: 0.015063 (0.015108) Loss: 0.38458 (0.38536) +2025-08-23,03:21:30 | INFO | Train Epoch: 7 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 0.39458 (0.37044) Boundary_loss: 0.015073 (0.015107) Loss: 0.40965 (0.38554) +2025-08-23,03:22:26 | INFO | Train Epoch: 7 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.39147 (0.37060) Boundary_loss: 0.015012 (0.015107) Loss: 0.40648 (0.38570) +2025-08-23,03:23:23 | INFO | Train Epoch: 7 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.701 Boundary Ratio: 0.254 Contrastive_loss: 0.35468 (0.37048) Boundary_loss: 0.015187 (0.015107) Loss: 0.36986 (0.38558) +2025-08-23,03:24:20 | INFO | Train Epoch: 7 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.40398 (0.37073) Boundary_loss: 0.015097 (0.015107) Loss: 0.41908 (0.38583) +2025-08-23,03:25:17 | INFO | Train Epoch: 7 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 0.35248 (0.37059) Boundary_loss: 0.015105 (0.015107) Loss: 0.36758 (0.38570) +2025-08-23,03:26:13 | INFO | Train Epoch: 7 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.42842 (0.37102) Boundary_loss: 0.015092 (0.015107) Loss: 0.44352 (0.38612) +2025-08-23,03:27:10 | INFO | Train Epoch: 7 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.44321 (0.37154) Boundary_loss: 0.015044 (0.015106) Loss: 0.45826 (0.38665) +2025-08-23,03:28:07 | INFO | Train Epoch: 7 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.31696 (0.37115) Boundary_loss: 0.015008 (0.015106) Loss: 0.33197 (0.38625) +2025-08-23,03:29:04 | INFO | Train Epoch: 7 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.34660 (0.37097) Boundary_loss: 0.015139 (0.015106) Loss: 0.36174 (0.38608) +2025-08-23,03:30:00 | INFO | Train Epoch: 7 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.26154 (0.37019) Boundary_loss: 0.015157 (0.015106) Loss: 0.27670 (0.38530) +2025-08-23,03:30:57 | INFO | Train Epoch: 7 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.35215 (0.37006) Boundary_loss: 0.015082 (0.015106) Loss: 0.36724 (0.38517) +2025-08-23,03:31:54 | INFO | Train Epoch: 7 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.36346 (0.37001) Boundary_loss: 0.015165 (0.015107) Loss: 0.37863 (0.38512) +2025-08-23,03:32:50 | INFO | Train Epoch: 7 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.43375 (0.37046) Boundary_loss: 0.015131 (0.015107) Loss: 0.44888 (0.38557) +2025-08-23,03:33:47 | INFO | Train Epoch: 7 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.31269 (0.37006) Boundary_loss: 0.015118 (0.015107) Loss: 0.32781 (0.38517) +2025-08-23,03:34:44 | INFO | Train Epoch: 7 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 49.318 Boundary Ratio: 0.252 Contrastive_loss: 0.38404 (0.37016) Boundary_loss: 0.015155 (0.015107) Loss: 0.39920 (0.38526) +2025-08-23,03:35:41 | INFO | Train Epoch: 7 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.33409 (0.36991) Boundary_loss: 0.015061 (0.015107) Loss: 0.34915 (0.38502) +2025-08-23,03:36:37 | INFO | Train Epoch: 7 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.297 Boundary Ratio: 0.246 Contrastive_loss: 0.30613 (0.36947) Boundary_loss: 0.015131 (0.015107) Loss: 0.32127 (0.38458) +2025-08-23,03:37:34 | INFO | Train Epoch: 7 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.35810 (0.36940) Boundary_loss: 0.014982 (0.015106) Loss: 0.37309 (0.38450) +2025-08-23,03:38:31 | INFO | Train Epoch: 7 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.443 Boundary Ratio: 0.252 Contrastive_loss: 0.30182 (0.36894) Boundary_loss: 0.015112 (0.015106) Loss: 0.31693 (0.38405) +2025-08-23,03:39:28 | INFO | Train Epoch: 7 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.31326 (0.36857) Boundary_loss: 0.015094 (0.015106) Loss: 0.32835 (0.38368) +2025-08-23,03:40:24 | INFO | Train Epoch: 7 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.32661 (0.36830) Boundary_loss: 0.015072 (0.015106) Loss: 0.34168 (0.38340) +2025-08-23,03:41:21 | INFO | Train Epoch: 7 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 0.40810 (0.36856) Boundary_loss: 0.015138 (0.015106) Loss: 0.42324 (0.38366) +2025-08-23,03:42:18 | INFO | Train Epoch: 7 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.33729 (0.36835) Boundary_loss: 0.015158 (0.015106) Loss: 0.35245 (0.38346) +2025-08-23,03:43:14 | INFO | Train Epoch: 7 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.33972 (0.36817) Boundary_loss: 0.015142 (0.015107) Loss: 0.35486 (0.38327) +2025-08-23,03:44:11 | INFO | Train Epoch: 7 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.39267 (0.36833) Boundary_loss: 0.014966 (0.015106) Loss: 0.40763 (0.38343) +2025-08-23,03:45:08 | INFO | Train Epoch: 7 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.225 Boundary Ratio: 0.246 Contrastive_loss: 0.27304 (0.36771) Boundary_loss: 0.015023 (0.015105) Loss: 0.28806 (0.38282) +2025-08-23,03:46:04 | INFO | Train Epoch: 7 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.36920 (0.36772) Boundary_loss: 0.015023 (0.015105) Loss: 0.38422 (0.38283) +2025-08-23,03:47:01 | INFO | Train Epoch: 7 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.35077 (0.36762) Boundary_loss: 0.015188 (0.015105) Loss: 0.36596 (0.38272) +2025-08-23,03:47:57 | INFO | Train Epoch: 7 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.31241 (0.36727) Boundary_loss: 0.015174 (0.015106) Loss: 0.32759 (0.38237) +2025-08-23,03:48:54 | INFO | Train Epoch: 7 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.38422 (0.36738) Boundary_loss: 0.015064 (0.015105) Loss: 0.39928 (0.38248) +2025-08-23,03:49:51 | INFO | Train Epoch: 7 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.39905 (0.36757) Boundary_loss: 0.015148 (0.015106) Loss: 0.41420 (0.38268) +2025-08-23,03:50:47 | INFO | Train Epoch: 7 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 47.693 Boundary Ratio: 0.243 Contrastive_loss: 0.29558 (0.36713) Boundary_loss: 0.015238 (0.015107) Loss: 0.31082 (0.38223) +2025-08-23,03:51:44 | INFO | Train Epoch: 7 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.33811 (0.36695) Boundary_loss: 0.015140 (0.015107) Loss: 0.35325 (0.38206) +2025-08-23,03:52:41 | INFO | Train Epoch: 7 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.29934 (0.36654) Boundary_loss: 0.015129 (0.015107) Loss: 0.31447 (0.38164) +2025-08-23,03:53:37 | INFO | Train Epoch: 7 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.41125 (0.36681) Boundary_loss: 0.015123 (0.015107) Loss: 0.42637 (0.38192) +2025-08-23,03:54:34 | INFO | Train Epoch: 7 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.33043 (0.36659) Boundary_loss: 0.015118 (0.015107) Loss: 0.34554 (0.38170) +2025-08-23,03:55:31 | INFO | Train Epoch: 7 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.33810 (0.36642) Boundary_loss: 0.015084 (0.015107) Loss: 0.35319 (0.38153) +2025-08-23,03:56:28 | INFO | Train Epoch: 7 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 0.30930 (0.36608) Boundary_loss: 0.015014 (0.015106) Loss: 0.32431 (0.38118) +2025-08-23,03:57:24 | INFO | Train Epoch: 7 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 0.34443 (0.36595) Boundary_loss: 0.015097 (0.015106) Loss: 0.35953 (0.38106) +2025-08-23,03:58:21 | INFO | Train Epoch: 7 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 49.434 Boundary Ratio: 0.252 Contrastive_loss: 0.34795 (0.36584) Boundary_loss: 0.015136 (0.015106) Loss: 0.36308 (0.38095) +2025-08-23,03:59:17 | INFO | Train Epoch: 7 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.35690 (0.36579) Boundary_loss: 0.014998 (0.015106) Loss: 0.37190 (0.38090) +2025-08-23,04:00:14 | INFO | Train Epoch: 7 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 49.346 Boundary Ratio: 0.252 Contrastive_loss: 0.38306 (0.36589) Boundary_loss: 0.015067 (0.015106) Loss: 0.39812 (0.38100) +2025-08-23,04:01:11 | INFO | Train Epoch: 7 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.219 Boundary Ratio: 0.246 Contrastive_loss: 0.37970 (0.36597) Boundary_loss: 0.015057 (0.015105) Loss: 0.39475 (0.38108) +2025-08-23,04:02:08 | INFO | Train Epoch: 7 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.32591 (0.36574) Boundary_loss: 0.015176 (0.015106) Loss: 0.34109 (0.38085) +2025-08-23,04:03:04 | INFO | Train Epoch: 7 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.32092 (0.36549) Boundary_loss: 0.015140 (0.015106) Loss: 0.33606 (0.38059) +2025-08-23,04:04:01 | INFO | Train Epoch: 7 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.121 Boundary Ratio: 0.246 Contrastive_loss: 0.37265 (0.36553) Boundary_loss: 0.015042 (0.015106) Loss: 0.38769 (0.38063) +2025-08-23,04:04:58 | INFO | Train Epoch: 7 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.27912 (0.36504) Boundary_loss: 0.015084 (0.015105) Loss: 0.29420 (0.38014) +2025-08-23,04:05:55 | INFO | Train Epoch: 7 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.40969 (0.36529) Boundary_loss: 0.015000 (0.015105) Loss: 0.42469 (0.38039) +2025-08-23,04:06:51 | INFO | Train Epoch: 7 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.38464 (0.36540) Boundary_loss: 0.015115 (0.015105) Loss: 0.39975 (0.38050) +2025-08-23,04:07:48 | INFO | Train Epoch: 7 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 49.594 Boundary Ratio: 0.253 Contrastive_loss: 0.38966 (0.36553) Boundary_loss: 0.015296 (0.015106) Loss: 0.40495 (0.38064) +2025-08-23,04:08:45 | INFO | Train Epoch: 7 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.32439 (0.36530) Boundary_loss: 0.015144 (0.015106) Loss: 0.33953 (0.38041) +2025-08-23,04:09:41 | INFO | Train Epoch: 7 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.37607 (0.36536) Boundary_loss: 0.015012 (0.015106) Loss: 0.39108 (0.38047) +2025-08-23,04:10:38 | INFO | Train Epoch: 7 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.36006 (0.36534) Boundary_loss: 0.015017 (0.015105) Loss: 0.37508 (0.38044) +2025-08-23,04:11:35 | INFO | Train Epoch: 7 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.37866 (0.36541) Boundary_loss: 0.015153 (0.015105) Loss: 0.39381 (0.38051) +2025-08-23,04:12:31 | INFO | Train Epoch: 7 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.38202 (0.36550) Boundary_loss: 0.015349 (0.015107) Loss: 0.39736 (0.38060) +2025-08-23,04:13:28 | INFO | Train Epoch: 7 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.39404 (0.36565) Boundary_loss: 0.015097 (0.015107) Loss: 0.40913 (0.38076) +2025-08-23,04:14:25 | INFO | Train Epoch: 7 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.035 Boundary Ratio: 0.245 Contrastive_loss: 0.30272 (0.36531) Boundary_loss: 0.015183 (0.015107) Loss: 0.31790 (0.38042) +2025-08-23,04:15:22 | INFO | Train Epoch: 7 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 49.490 Boundary Ratio: 0.253 Contrastive_loss: 0.31954 (0.36507) Boundary_loss: 0.015163 (0.015107) Loss: 0.33470 (0.38018) +2025-08-23,04:16:18 | INFO | Train Epoch: 7 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.35835 (0.36504) Boundary_loss: 0.015280 (0.015108) Loss: 0.37364 (0.38014) +2025-08-23,04:17:15 | INFO | Train Epoch: 7 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 49.109 Boundary Ratio: 0.251 Contrastive_loss: 0.31374 (0.36477) Boundary_loss: 0.015037 (0.015108) Loss: 0.32878 (0.37987) +2025-08-23,04:18:12 | INFO | Train Epoch: 7 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.36685 (0.36478) Boundary_loss: 0.015148 (0.015108) Loss: 0.38199 (0.37988) +2025-08-23,04:19:08 | INFO | Train Epoch: 7 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.35376 (0.36472) Boundary_loss: 0.014914 (0.015107) Loss: 0.36867 (0.37983) +2025-08-23,04:20:05 | INFO | Train Epoch: 7 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.36244 (0.36471) Boundary_loss: 0.015030 (0.015107) Loss: 0.37747 (0.37981) +2025-08-23,04:21:02 | INFO | Train Epoch: 7 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.37153 (0.36474) Boundary_loss: 0.015080 (0.015107) Loss: 0.38661 (0.37985) +2025-08-23,04:21:59 | INFO | Train Epoch: 7 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.168 Boundary Ratio: 0.246 Contrastive_loss: 0.43113 (0.36508) Boundary_loss: 0.015190 (0.015107) Loss: 0.44632 (0.38019) +2025-08-23,04:22:55 | INFO | Train Epoch: 7 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.39983 (0.36526) Boundary_loss: 0.015007 (0.015107) Loss: 0.41484 (0.38037) +2025-08-23,04:23:52 | INFO | Train Epoch: 7 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.33549 (0.36511) Boundary_loss: 0.015073 (0.015106) Loss: 0.35056 (0.38021) +2025-08-23,04:24:49 | INFO | Train Epoch: 7 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.37030 (0.36513) Boundary_loss: 0.015208 (0.015107) Loss: 0.38551 (0.38024) +2025-08-23,04:25:46 | INFO | Train Epoch: 7 [10138112/26365952 (38%)] Avg Boundaries (per batch): 49.328 Boundary Ratio: 0.252 Contrastive_loss: 0.27329 (0.36467) Boundary_loss: 0.015040 (0.015107) Loss: 0.28833 (0.37978) +2025-08-23,04:26:42 | INFO | Train Epoch: 7 [10189312/26365952 (39%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 0.36824 (0.36469) Boundary_loss: 0.015000 (0.015106) Loss: 0.38324 (0.37980) +2025-08-23,04:27:39 | INFO | Train Epoch: 7 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.34778 (0.36461) Boundary_loss: 0.015177 (0.015106) Loss: 0.36296 (0.37971) +2025-08-23,04:28:35 | INFO | Train Epoch: 7 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 0.37439 (0.36466) Boundary_loss: 0.015113 (0.015106) Loss: 0.38950 (0.37976) +2025-08-23,04:29:32 | INFO | Train Epoch: 7 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.109 Boundary Ratio: 0.245 Contrastive_loss: 0.27126 (0.36420) Boundary_loss: 0.015252 (0.015107) Loss: 0.28651 (0.37930) +2025-08-23,04:30:29 | INFO | Train Epoch: 7 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.34254 (0.36409) Boundary_loss: 0.015130 (0.015107) Loss: 0.35767 (0.37920) +2025-08-23,04:31:25 | INFO | Train Epoch: 7 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.37434 (0.36414) Boundary_loss: 0.014969 (0.015107) Loss: 0.38931 (0.37925) +2025-08-23,04:32:22 | INFO | Train Epoch: 7 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.28124 (0.36374) Boundary_loss: 0.015127 (0.015107) Loss: 0.29637 (0.37884) +2025-08-23,04:33:19 | INFO | Train Epoch: 7 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.30430 (0.36345) Boundary_loss: 0.015129 (0.015107) Loss: 0.31943 (0.37856) +2025-08-23,04:34:15 | INFO | Train Epoch: 7 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.31478 (0.36322) Boundary_loss: 0.015161 (0.015107) Loss: 0.32994 (0.37832) +2025-08-23,04:35:12 | INFO | Train Epoch: 7 [10650112/26365952 (40%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 0.32625 (0.36304) Boundary_loss: 0.015029 (0.015107) Loss: 0.34128 (0.37815) +2025-08-23,04:36:09 | INFO | Train Epoch: 7 [10701312/26365952 (41%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.30555 (0.36277) Boundary_loss: 0.015011 (0.015106) Loss: 0.32057 (0.37787) +2025-08-23,04:37:06 | INFO | Train Epoch: 7 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 0.34232 (0.36267) Boundary_loss: 0.015045 (0.015106) Loss: 0.35737 (0.37777) +2025-08-23,04:38:02 | INFO | Train Epoch: 7 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.32358 (0.36248) Boundary_loss: 0.015010 (0.015105) Loss: 0.33859 (0.37759) +2025-08-23,04:38:59 | INFO | Train Epoch: 7 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.230 Boundary Ratio: 0.246 Contrastive_loss: 0.39725 (0.36265) Boundary_loss: 0.015083 (0.015105) Loss: 0.41233 (0.37775) +2025-08-23,04:39:55 | INFO | Train Epoch: 7 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.32462 (0.36247) Boundary_loss: 0.015138 (0.015105) Loss: 0.33976 (0.37757) +2025-08-23,04:40:52 | INFO | Train Epoch: 7 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.36830 (0.36250) Boundary_loss: 0.015029 (0.015105) Loss: 0.38333 (0.37760) +2025-08-23,04:41:49 | INFO | Train Epoch: 7 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.33141 (0.36235) Boundary_loss: 0.015170 (0.015105) Loss: 0.34658 (0.37746) +2025-08-23,04:42:45 | INFO | Train Epoch: 7 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.34837 (0.36229) Boundary_loss: 0.015023 (0.015105) Loss: 0.36339 (0.37739) +2025-08-23,04:43:42 | INFO | Train Epoch: 7 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.40527 (0.36249) Boundary_loss: 0.014972 (0.015104) Loss: 0.42024 (0.37759) +2025-08-23,04:44:39 | INFO | Train Epoch: 7 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.217 Boundary Ratio: 0.246 Contrastive_loss: 0.35840 (0.36247) Boundary_loss: 0.015160 (0.015105) Loss: 0.37356 (0.37757) +2025-08-23,04:45:35 | INFO | Train Epoch: 7 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.38929 (0.36259) Boundary_loss: 0.015073 (0.015105) Loss: 0.40436 (0.37769) +2025-08-23,04:46:32 | INFO | Train Epoch: 7 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.508 Boundary Ratio: 0.247 Contrastive_loss: 0.37763 (0.36266) Boundary_loss: 0.015141 (0.015105) Loss: 0.39277 (0.37776) +2025-08-23,04:47:29 | INFO | Train Epoch: 7 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.34669 (0.36258) Boundary_loss: 0.015089 (0.015105) Loss: 0.36178 (0.37769) +2025-08-23,04:48:25 | INFO | Train Epoch: 7 [11366912/26365952 (43%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 0.34623 (0.36251) Boundary_loss: 0.015084 (0.015105) Loss: 0.36131 (0.37762) +2025-08-23,04:49:22 | INFO | Train Epoch: 7 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.33730 (0.36240) Boundary_loss: 0.015030 (0.015104) Loss: 0.35233 (0.37750) +2025-08-23,04:50:19 | INFO | Train Epoch: 7 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.094 Boundary Ratio: 0.245 Contrastive_loss: 0.28671 (0.36206) Boundary_loss: 0.015097 (0.015104) Loss: 0.30181 (0.37717) +2025-08-23,04:51:15 | INFO | Train Epoch: 7 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.35904 (0.36205) Boundary_loss: 0.015108 (0.015104) Loss: 0.37415 (0.37715) +2025-08-23,04:52:12 | INFO | Train Epoch: 7 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.29069 (0.36173) Boundary_loss: 0.015283 (0.015105) Loss: 0.30597 (0.37684) +2025-08-23,04:53:09 | INFO | Train Epoch: 7 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.42405 (0.36201) Boundary_loss: 0.015026 (0.015105) Loss: 0.43908 (0.37711) +2025-08-23,04:54:06 | INFO | Train Epoch: 7 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.258 Boundary Ratio: 0.251 Contrastive_loss: 0.37615 (0.36207) Boundary_loss: 0.015123 (0.015105) Loss: 0.39127 (0.37717) +2025-08-23,04:55:02 | INFO | Train Epoch: 7 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.35304 (0.36203) Boundary_loss: 0.015102 (0.015105) Loss: 0.36815 (0.37714) +2025-08-23,04:55:59 | INFO | Train Epoch: 7 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.29987 (0.36176) Boundary_loss: 0.015081 (0.015105) Loss: 0.31495 (0.37687) +2025-08-23,04:56:56 | INFO | Train Epoch: 7 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 0.30384 (0.36151) Boundary_loss: 0.015146 (0.015105) Loss: 0.31898 (0.37662) +2025-08-23,04:57:53 | INFO | Train Epoch: 7 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.211 Boundary Ratio: 0.246 Contrastive_loss: 0.34971 (0.36146) Boundary_loss: 0.015186 (0.015105) Loss: 0.36490 (0.37657) +2025-08-23,04:58:49 | INFO | Train Epoch: 7 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.38246 (0.36155) Boundary_loss: 0.015195 (0.015106) Loss: 0.39766 (0.37666) +2025-08-23,04:59:46 | INFO | Train Epoch: 7 [11981312/26365952 (45%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.39115 (0.36168) Boundary_loss: 0.015131 (0.015106) Loss: 0.40628 (0.37678) +2025-08-23,05:00:42 | INFO | Train Epoch: 7 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.31264 (0.36147) Boundary_loss: 0.015136 (0.015106) Loss: 0.32778 (0.37657) +2025-08-23,05:01:39 | INFO | Train Epoch: 7 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.38364 (0.36156) Boundary_loss: 0.015111 (0.015106) Loss: 0.39875 (0.37667) +2025-08-23,05:02:36 | INFO | Train Epoch: 7 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 0.38641 (0.36167) Boundary_loss: 0.014998 (0.015105) Loss: 0.40140 (0.37677) +2025-08-23,05:03:32 | INFO | Train Epoch: 7 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.34564 (0.36160) Boundary_loss: 0.015180 (0.015106) Loss: 0.36082 (0.37671) +2025-08-23,05:04:29 | INFO | Train Epoch: 7 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.31574 (0.36141) Boundary_loss: 0.015047 (0.015105) Loss: 0.33079 (0.37651) +2025-08-23,05:05:26 | INFO | Train Epoch: 7 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.32551 (0.36126) Boundary_loss: 0.015137 (0.015106) Loss: 0.34065 (0.37637) +2025-08-23,05:06:22 | INFO | Train Epoch: 7 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.35579 (0.36124) Boundary_loss: 0.015147 (0.015106) Loss: 0.37094 (0.37634) +2025-08-23,05:07:19 | INFO | Train Epoch: 7 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.47225 (0.36169) Boundary_loss: 0.015101 (0.015106) Loss: 0.48735 (0.37680) +2025-08-23,05:08:15 | INFO | Train Epoch: 7 [12442112/26365952 (47%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.37003 (0.36173) Boundary_loss: 0.015079 (0.015106) Loss: 0.38511 (0.37683) +2025-08-23,05:09:12 | INFO | Train Epoch: 7 [12493312/26365952 (47%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.33945 (0.36164) Boundary_loss: 0.015057 (0.015105) Loss: 0.35451 (0.37674) +2025-08-23,05:10:09 | INFO | Train Epoch: 7 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.41993 (0.36187) Boundary_loss: 0.014924 (0.015105) Loss: 0.43485 (0.37698) +2025-08-23,05:11:05 | INFO | Train Epoch: 7 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.36579 (0.36189) Boundary_loss: 0.015152 (0.015105) Loss: 0.38095 (0.37699) +2025-08-23,05:12:02 | INFO | Train Epoch: 7 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.311 Boundary Ratio: 0.246 Contrastive_loss: 0.32348 (0.36174) Boundary_loss: 0.015112 (0.015105) Loss: 0.33860 (0.37684) +2025-08-23,05:12:59 | INFO | Train Epoch: 7 [12698112/26365952 (48%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.37942 (0.36181) Boundary_loss: 0.015046 (0.015105) Loss: 0.39446 (0.37691) +2025-08-23,05:13:55 | INFO | Train Epoch: 7 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.46728 (0.36223) Boundary_loss: 0.015012 (0.015104) Loss: 0.48229 (0.37733) +2025-08-23,05:14:52 | INFO | Train Epoch: 7 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.027 Boundary Ratio: 0.245 Contrastive_loss: 0.29425 (0.36196) Boundary_loss: 0.015089 (0.015104) Loss: 0.30934 (0.37706) +2025-08-23,05:15:48 | INFO | Train Epoch: 7 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.38794 (0.36206) Boundary_loss: 0.015033 (0.015104) Loss: 0.40297 (0.37716) +2025-08-23,05:16:45 | INFO | Train Epoch: 7 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.33309 (0.36195) Boundary_loss: 0.015110 (0.015104) Loss: 0.34820 (0.37705) +2025-08-23,05:17:41 | INFO | Train Epoch: 7 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.31847 (0.36177) Boundary_loss: 0.015065 (0.015104) Loss: 0.33354 (0.37688) +2025-08-23,05:18:38 | INFO | Train Epoch: 7 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.121 Boundary Ratio: 0.246 Contrastive_loss: 0.30194 (0.36154) Boundary_loss: 0.015068 (0.015104) Loss: 0.31701 (0.37664) +2025-08-23,05:19:35 | INFO | Train Epoch: 7 [13056512/26365952 (50%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.34127 (0.36146) Boundary_loss: 0.015102 (0.015104) Loss: 0.35637 (0.37656) +2025-08-23,05:20:31 | INFO | Train Epoch: 7 [13107712/26365952 (50%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.35878 (0.36145) Boundary_loss: 0.015220 (0.015104) Loss: 0.37400 (0.37655) +2025-08-23,05:21:28 | INFO | Train Epoch: 7 [13158912/26365952 (50%)] Avg Boundaries (per batch): 50.098 Boundary Ratio: 0.256 Contrastive_loss: 0.32885 (0.36132) Boundary_loss: 0.015190 (0.015104) Loss: 0.34404 (0.37643) +2025-08-23,05:22:25 | INFO | Train Epoch: 7 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.34960 (0.36128) Boundary_loss: 0.015041 (0.015104) Loss: 0.36464 (0.37638) +2025-08-23,05:23:21 | INFO | Train Epoch: 7 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.29522 (0.36102) Boundary_loss: 0.014959 (0.015104) Loss: 0.31017 (0.37613) +2025-08-23,05:24:18 | INFO | Train Epoch: 7 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.31199 (0.36084) Boundary_loss: 0.015081 (0.015104) Loss: 0.32707 (0.37594) +2025-08-23,05:25:14 | INFO | Train Epoch: 7 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.30977 (0.36064) Boundary_loss: 0.015108 (0.015104) Loss: 0.32487 (0.37575) +2025-08-23,05:26:11 | INFO | Train Epoch: 7 [13414912/26365952 (51%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 0.35775 (0.36063) Boundary_loss: 0.015021 (0.015103) Loss: 0.37277 (0.37573) +2025-08-23,05:27:08 | INFO | Train Epoch: 7 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.28305 (0.36034) Boundary_loss: 0.015076 (0.015103) Loss: 0.29812 (0.37544) +2025-08-23,05:28:04 | INFO | Train Epoch: 7 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.012 Boundary Ratio: 0.245 Contrastive_loss: 0.34957 (0.36030) Boundary_loss: 0.015123 (0.015103) Loss: 0.36469 (0.37540) +2025-08-23,05:29:01 | INFO | Train Epoch: 7 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.34937 (0.36026) Boundary_loss: 0.015156 (0.015103) Loss: 0.36453 (0.37536) +2025-08-23,05:29:57 | INFO | Train Epoch: 7 [13619712/26365952 (52%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.28924 (0.35999) Boundary_loss: 0.015029 (0.015103) Loss: 0.30427 (0.37509) +2025-08-23,05:30:54 | INFO | Train Epoch: 7 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.28727 (0.35972) Boundary_loss: 0.015309 (0.015104) Loss: 0.30258 (0.37482) +2025-08-23,05:31:51 | INFO | Train Epoch: 7 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.34373 (0.35966) Boundary_loss: 0.015068 (0.015104) Loss: 0.35880 (0.37476) +2025-08-23,05:32:48 | INFO | Train Epoch: 7 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.38571 (0.35976) Boundary_loss: 0.015097 (0.015104) Loss: 0.40081 (0.37486) +2025-08-23,05:33:44 | INFO | Train Epoch: 7 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.32221 (0.35962) Boundary_loss: 0.015031 (0.015103) Loss: 0.33724 (0.37472) +2025-08-23,05:34:41 | INFO | Train Epoch: 7 [13875712/26365952 (53%)] Avg Boundaries (per batch): 47.861 Boundary Ratio: 0.244 Contrastive_loss: 0.35636 (0.35960) Boundary_loss: 0.015060 (0.015103) Loss: 0.37142 (0.37471) +2025-08-23,05:35:38 | INFO | Train Epoch: 7 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.34405 (0.35955) Boundary_loss: 0.015011 (0.015103) Loss: 0.35906 (0.37465) +2025-08-23,05:36:34 | INFO | Train Epoch: 7 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.36783 (0.35958) Boundary_loss: 0.014994 (0.015103) Loss: 0.38283 (0.37468) +2025-08-23,05:37:31 | INFO | Train Epoch: 7 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.37404 (0.35963) Boundary_loss: 0.014990 (0.015102) Loss: 0.38904 (0.37473) +2025-08-23,05:38:28 | INFO | Train Epoch: 7 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.36009 (0.35963) Boundary_loss: 0.015043 (0.015102) Loss: 0.37513 (0.37473) +2025-08-23,05:39:24 | INFO | Train Epoch: 7 [14131712/26365952 (54%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.25661 (0.35926) Boundary_loss: 0.015142 (0.015102) Loss: 0.27176 (0.37436) +2025-08-23,05:40:21 | INFO | Train Epoch: 7 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.30292 (0.35906) Boundary_loss: 0.015063 (0.015102) Loss: 0.31798 (0.37416) +2025-08-23,05:41:18 | INFO | Train Epoch: 7 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 0.33042 (0.35895) Boundary_loss: 0.015075 (0.015102) Loss: 0.34549 (0.37406) +2025-08-23,05:42:14 | INFO | Train Epoch: 7 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.32745 (0.35884) Boundary_loss: 0.015129 (0.015102) Loss: 0.34258 (0.37394) +2025-08-23,05:43:11 | INFO | Train Epoch: 7 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.35396 (0.35883) Boundary_loss: 0.015060 (0.015102) Loss: 0.36902 (0.37393) +2025-08-23,05:44:08 | INFO | Train Epoch: 7 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.40089 (0.35897) Boundary_loss: 0.015063 (0.015102) Loss: 0.41596 (0.37408) +2025-08-23,05:45:04 | INFO | Train Epoch: 7 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.36748 (0.35900) Boundary_loss: 0.015048 (0.015101) Loss: 0.38253 (0.37411) +2025-08-23,05:46:01 | INFO | Train Epoch: 7 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.32702 (0.35889) Boundary_loss: 0.015139 (0.015102) Loss: 0.34216 (0.37399) +2025-08-23,05:46:58 | INFO | Train Epoch: 7 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.29875 (0.35868) Boundary_loss: 0.014959 (0.015101) Loss: 0.31371 (0.37378) +2025-08-23,05:47:54 | INFO | Train Epoch: 7 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.31698 (0.35853) Boundary_loss: 0.014909 (0.015100) Loss: 0.33189 (0.37364) +2025-08-23,05:48:51 | INFO | Train Epoch: 7 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.36126 (0.35854) Boundary_loss: 0.014948 (0.015100) Loss: 0.37621 (0.37364) +2025-08-23,05:49:48 | INFO | Train Epoch: 7 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.34693 (0.35850) Boundary_loss: 0.015053 (0.015100) Loss: 0.36198 (0.37360) +2025-08-23,05:50:44 | INFO | Train Epoch: 7 [14746112/26365952 (56%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.35084 (0.35848) Boundary_loss: 0.015094 (0.015100) Loss: 0.36593 (0.37358) +2025-08-23,05:51:41 | INFO | Train Epoch: 7 [14797312/26365952 (56%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.41172 (0.35866) Boundary_loss: 0.015171 (0.015100) Loss: 0.42689 (0.37376) +2025-08-23,05:52:37 | INFO | Train Epoch: 7 [14848512/26365952 (56%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.41145 (0.35884) Boundary_loss: 0.015074 (0.015100) Loss: 0.42652 (0.37394) +2025-08-23,05:53:34 | INFO | Train Epoch: 7 [14899712/26365952 (57%)] Avg Boundaries (per batch): 49.545 Boundary Ratio: 0.253 Contrastive_loss: 0.33102 (0.35875) Boundary_loss: 0.015311 (0.015101) Loss: 0.34633 (0.37385) +2025-08-23,05:54:31 | INFO | Train Epoch: 7 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.32481 (0.35863) Boundary_loss: 0.015035 (0.015100) Loss: 0.33985 (0.37373) +2025-08-23,05:55:27 | INFO | Train Epoch: 7 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.34626 (0.35859) Boundary_loss: 0.015197 (0.015101) Loss: 0.36146 (0.37369) +2025-08-23,05:56:24 | INFO | Train Epoch: 7 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.35828 (0.35859) Boundary_loss: 0.015113 (0.015101) Loss: 0.37339 (0.37369) +2025-08-23,05:57:21 | INFO | Train Epoch: 7 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.36234 (0.35860) Boundary_loss: 0.014976 (0.015100) Loss: 0.37732 (0.37370) +2025-08-23,05:58:17 | INFO | Train Epoch: 7 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.28552 (0.35835) Boundary_loss: 0.015158 (0.015101) Loss: 0.30068 (0.37346) +2025-08-23,05:59:14 | INFO | Train Epoch: 7 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.39485 (0.35848) Boundary_loss: 0.015161 (0.015101) Loss: 0.41001 (0.37358) +2025-08-23,06:00:10 | INFO | Train Epoch: 7 [15258112/26365952 (58%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.31818 (0.35834) Boundary_loss: 0.015078 (0.015101) Loss: 0.33325 (0.37344) +2025-08-23,06:01:07 | INFO | Train Epoch: 7 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.34596 (0.35830) Boundary_loss: 0.015240 (0.015101) Loss: 0.36120 (0.37340) +2025-08-23,06:02:04 | INFO | Train Epoch: 7 [15360512/26365952 (58%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.30319 (0.35812) Boundary_loss: 0.015151 (0.015101) Loss: 0.31834 (0.37322) +2025-08-23,06:03:00 | INFO | Train Epoch: 7 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.32922 (0.35802) Boundary_loss: 0.015041 (0.015101) Loss: 0.34426 (0.37312) +2025-08-23,06:03:57 | INFO | Train Epoch: 7 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.39106 (0.35813) Boundary_loss: 0.015117 (0.015101) Loss: 0.40617 (0.37323) +2025-08-23,06:04:53 | INFO | Train Epoch: 7 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.34484 (0.35809) Boundary_loss: 0.015082 (0.015101) Loss: 0.35992 (0.37319) +2025-08-23,06:05:50 | INFO | Train Epoch: 7 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.24268 (0.35771) Boundary_loss: 0.015132 (0.015101) Loss: 0.25781 (0.37281) +2025-08-23,06:06:47 | INFO | Train Epoch: 7 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.133 Boundary Ratio: 0.246 Contrastive_loss: 0.33803 (0.35765) Boundary_loss: 0.015113 (0.015101) Loss: 0.35315 (0.37275) +2025-08-23,06:07:43 | INFO | Train Epoch: 7 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.43350 (0.35789) Boundary_loss: 0.015122 (0.015101) Loss: 0.44862 (0.37299) +2025-08-23,06:08:40 | INFO | Train Epoch: 7 [15718912/26365952 (60%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.34772 (0.35786) Boundary_loss: 0.015144 (0.015101) Loss: 0.36287 (0.37296) +2025-08-23,06:09:37 | INFO | Train Epoch: 7 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.31431 (0.35772) Boundary_loss: 0.015046 (0.015101) Loss: 0.32936 (0.37282) +2025-08-23,06:10:33 | INFO | Train Epoch: 7 [15821312/26365952 (60%)] Avg Boundaries (per batch): 49.662 Boundary Ratio: 0.253 Contrastive_loss: 0.32981 (0.35763) Boundary_loss: 0.014989 (0.015101) Loss: 0.34479 (0.37273) +2025-08-23,06:11:30 | INFO | Train Epoch: 7 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.32383 (0.35752) Boundary_loss: 0.015059 (0.015101) Loss: 0.33889 (0.37262) +2025-08-23,06:12:27 | INFO | Train Epoch: 7 [15923712/26365952 (60%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.41428 (0.35770) Boundary_loss: 0.015043 (0.015101) Loss: 0.42932 (0.37280) +2025-08-23,06:13:23 | INFO | Train Epoch: 7 [15974912/26365952 (61%)] Avg Boundaries (per batch): 49.215 Boundary Ratio: 0.251 Contrastive_loss: 0.36985 (0.35774) Boundary_loss: 0.014985 (0.015100) Loss: 0.38483 (0.37284) +2025-08-23,06:14:20 | INFO | Train Epoch: 7 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.33757 (0.35768) Boundary_loss: 0.015140 (0.015100) Loss: 0.35271 (0.37278) +2025-08-23,06:15:17 | INFO | Train Epoch: 7 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.35848 (0.35768) Boundary_loss: 0.015084 (0.015100) Loss: 0.37356 (0.37278) +2025-08-23,06:16:13 | INFO | Train Epoch: 7 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.23990 (0.35731) Boundary_loss: 0.015123 (0.015100) Loss: 0.25502 (0.37241) +2025-08-23,06:17:10 | INFO | Train Epoch: 7 [16179712/26365952 (61%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.33166 (0.35722) Boundary_loss: 0.015121 (0.015100) Loss: 0.34678 (0.37233) +2025-08-23,06:18:06 | INFO | Train Epoch: 7 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.44890 (0.35751) Boundary_loss: 0.015069 (0.015100) Loss: 0.46397 (0.37261) +2025-08-23,06:19:03 | INFO | Train Epoch: 7 [16282112/26365952 (62%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.39539 (0.35763) Boundary_loss: 0.015110 (0.015100) Loss: 0.41050 (0.37273) +2025-08-23,06:19:59 | INFO | Train Epoch: 7 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.35921 (0.35764) Boundary_loss: 0.014902 (0.015100) Loss: 0.37411 (0.37274) +2025-08-23,06:20:56 | INFO | Train Epoch: 7 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.45663 (0.35795) Boundary_loss: 0.015056 (0.015100) Loss: 0.47169 (0.37304) +2025-08-23,06:21:53 | INFO | Train Epoch: 7 [16435712/26365952 (62%)] Avg Boundaries (per batch): 49.350 Boundary Ratio: 0.252 Contrastive_loss: 0.29348 (0.35775) Boundary_loss: 0.015019 (0.015099) Loss: 0.30850 (0.37284) +2025-08-23,06:22:49 | INFO | Train Epoch: 7 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.406 Boundary Ratio: 0.247 Contrastive_loss: 0.31193 (0.35760) Boundary_loss: 0.015145 (0.015099) Loss: 0.32707 (0.37270) +2025-08-23,06:23:46 | INFO | Train Epoch: 7 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.176 Boundary Ratio: 0.246 Contrastive_loss: 0.37952 (0.35767) Boundary_loss: 0.015264 (0.015100) Loss: 0.39478 (0.37277) +2025-08-23,06:24:43 | INFO | Train Epoch: 7 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.281 Boundary Ratio: 0.246 Contrastive_loss: 0.38928 (0.35777) Boundary_loss: 0.014906 (0.015099) Loss: 0.40419 (0.37287) +2025-08-23,06:25:39 | INFO | Train Epoch: 7 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 0.30056 (0.35759) Boundary_loss: 0.014958 (0.015099) Loss: 0.31552 (0.37269) +2025-08-23,06:26:36 | INFO | Train Epoch: 7 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.32060 (0.35748) Boundary_loss: 0.015192 (0.015099) Loss: 0.33579 (0.37258) +2025-08-23,06:27:32 | INFO | Train Epoch: 7 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.37899 (0.35755) Boundary_loss: 0.015055 (0.015099) Loss: 0.39405 (0.37264) +2025-08-23,06:28:29 | INFO | Train Epoch: 7 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.28170 (0.35731) Boundary_loss: 0.015244 (0.015100) Loss: 0.29694 (0.37241) +2025-08-23,06:29:26 | INFO | Train Epoch: 7 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.37169 (0.35736) Boundary_loss: 0.015152 (0.015100) Loss: 0.38684 (0.37246) +2025-08-23,06:30:23 | INFO | Train Epoch: 7 [16896512/26365952 (64%)] Avg Boundaries (per batch): 49.359 Boundary Ratio: 0.252 Contrastive_loss: 0.32507 (0.35726) Boundary_loss: 0.015167 (0.015100) Loss: 0.34024 (0.37236) +2025-08-23,06:31:19 | INFO | Train Epoch: 7 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.35270 (0.35725) Boundary_loss: 0.015274 (0.015100) Loss: 0.36797 (0.37235) +2025-08-23,06:32:16 | INFO | Train Epoch: 7 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.322 Boundary Ratio: 0.247 Contrastive_loss: 0.31155 (0.35711) Boundary_loss: 0.015090 (0.015100) Loss: 0.32664 (0.37221) +2025-08-23,06:33:13 | INFO | Train Epoch: 7 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.36460 (0.35713) Boundary_loss: 0.014966 (0.015100) Loss: 0.37957 (0.37223) +2025-08-23,06:34:09 | INFO | Train Epoch: 7 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.36807 (0.35716) Boundary_loss: 0.015062 (0.015100) Loss: 0.38313 (0.37226) +2025-08-23,06:35:06 | INFO | Train Epoch: 7 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.32617 (0.35707) Boundary_loss: 0.015053 (0.015100) Loss: 0.34122 (0.37217) +2025-08-23,06:36:02 | INFO | Train Epoch: 7 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.29961 (0.35690) Boundary_loss: 0.015096 (0.015100) Loss: 0.31471 (0.37200) +2025-08-23,06:36:59 | INFO | Train Epoch: 7 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.37870 (0.35697) Boundary_loss: 0.015119 (0.015100) Loss: 0.39382 (0.37207) +2025-08-23,06:37:56 | INFO | Train Epoch: 7 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.36652 (0.35699) Boundary_loss: 0.015073 (0.015100) Loss: 0.38160 (0.37209) +2025-08-23,06:38:52 | INFO | Train Epoch: 7 [17357312/26365952 (66%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.30891 (0.35685) Boundary_loss: 0.015148 (0.015100) Loss: 0.32406 (0.37195) +2025-08-23,06:39:49 | INFO | Train Epoch: 7 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.31698 (0.35674) Boundary_loss: 0.015098 (0.015100) Loss: 0.33208 (0.37184) +2025-08-23,06:40:46 | INFO | Train Epoch: 7 [17459712/26365952 (66%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 0.42404 (0.35693) Boundary_loss: 0.015159 (0.015100) Loss: 0.43920 (0.37203) +2025-08-23,06:41:42 | INFO | Train Epoch: 7 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.38991 (0.35703) Boundary_loss: 0.015055 (0.015100) Loss: 0.40497 (0.37213) +2025-08-23,06:42:39 | INFO | Train Epoch: 7 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.33618 (0.35697) Boundary_loss: 0.015023 (0.015100) Loss: 0.35120 (0.37207) +2025-08-23,06:43:36 | INFO | Train Epoch: 7 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 0.38641 (0.35705) Boundary_loss: 0.015060 (0.015100) Loss: 0.40147 (0.37215) +2025-08-23,06:44:32 | INFO | Train Epoch: 7 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.35015 (0.35703) Boundary_loss: 0.015097 (0.015100) Loss: 0.36525 (0.37213) +2025-08-23,06:45:29 | INFO | Train Epoch: 7 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.32305 (0.35694) Boundary_loss: 0.014988 (0.015099) Loss: 0.33804 (0.37204) +2025-08-23,06:46:26 | INFO | Train Epoch: 7 [17766912/26365952 (67%)] Avg Boundaries (per batch): 49.307 Boundary Ratio: 0.252 Contrastive_loss: 0.39385 (0.35704) Boundary_loss: 0.015193 (0.015099) Loss: 0.40904 (0.37214) +2025-08-23,06:47:22 | INFO | Train Epoch: 7 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.39464 (0.35715) Boundary_loss: 0.015008 (0.015099) Loss: 0.40965 (0.37225) +2025-08-23,06:48:19 | INFO | Train Epoch: 7 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.29761 (0.35698) Boundary_loss: 0.015059 (0.015099) Loss: 0.31267 (0.37208) +2025-08-23,06:49:15 | INFO | Train Epoch: 7 [17920512/26365952 (68%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.28229 (0.35677) Boundary_loss: 0.015114 (0.015099) Loss: 0.29740 (0.37187) +2025-08-23,06:50:12 | INFO | Train Epoch: 7 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.36104 (0.35678) Boundary_loss: 0.015122 (0.015099) Loss: 0.37616 (0.37188) +2025-08-23,06:51:09 | INFO | Train Epoch: 7 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.34831 (0.35676) Boundary_loss: 0.015030 (0.015099) Loss: 0.36334 (0.37185) +2025-08-23,06:52:05 | INFO | Train Epoch: 7 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.219 Boundary Ratio: 0.246 Contrastive_loss: 0.37445 (0.35681) Boundary_loss: 0.015043 (0.015099) Loss: 0.38949 (0.37190) +2025-08-23,06:53:02 | INFO | Train Epoch: 7 [18125312/26365952 (69%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.37456 (0.35686) Boundary_loss: 0.015001 (0.015099) Loss: 0.38956 (0.37195) +2025-08-23,06:53:59 | INFO | Train Epoch: 7 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.316 Boundary Ratio: 0.247 Contrastive_loss: 0.36119 (0.35687) Boundary_loss: 0.015067 (0.015099) Loss: 0.37626 (0.37197) +2025-08-23,06:54:55 | INFO | Train Epoch: 7 [18227712/26365952 (69%)] Avg Boundaries (per batch): 49.361 Boundary Ratio: 0.252 Contrastive_loss: 0.36418 (0.35689) Boundary_loss: 0.015070 (0.015098) Loss: 0.37925 (0.37199) +2025-08-23,06:55:52 | INFO | Train Epoch: 7 [18278912/26365952 (69%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 0.34552 (0.35686) Boundary_loss: 0.015010 (0.015098) Loss: 0.36053 (0.37195) +2025-08-23,06:56:48 | INFO | Train Epoch: 7 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.32807 (0.35678) Boundary_loss: 0.014993 (0.015098) Loss: 0.34306 (0.37187) +2025-08-23,06:57:45 | INFO | Train Epoch: 7 [18381312/26365952 (70%)] Avg Boundaries (per batch): 49.334 Boundary Ratio: 0.252 Contrastive_loss: 0.31624 (0.35666) Boundary_loss: 0.015079 (0.015098) Loss: 0.33132 (0.37176) +2025-08-23,06:58:42 | INFO | Train Epoch: 7 [18432512/26365952 (70%)] Avg Boundaries (per batch): 49.285 Boundary Ratio: 0.251 Contrastive_loss: 0.37728 (0.35672) Boundary_loss: 0.015064 (0.015098) Loss: 0.39234 (0.37182) +2025-08-23,06:59:38 | INFO | Train Epoch: 7 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.35705 (0.35672) Boundary_loss: 0.015155 (0.015098) Loss: 0.37220 (0.37182) +2025-08-23,07:00:35 | INFO | Train Epoch: 7 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.43420 (0.35693) Boundary_loss: 0.014956 (0.015097) Loss: 0.44916 (0.37203) +2025-08-23,07:01:31 | INFO | Train Epoch: 7 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.38743 (0.35702) Boundary_loss: 0.014953 (0.015097) Loss: 0.40238 (0.37212) +2025-08-23,07:02:28 | INFO | Train Epoch: 7 [18637312/26365952 (71%)] Avg Boundaries (per batch): 49.449 Boundary Ratio: 0.252 Contrastive_loss: 0.29900 (0.35686) Boundary_loss: 0.015016 (0.015097) Loss: 0.31402 (0.37196) +2025-08-23,07:03:25 | INFO | Train Epoch: 7 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.28587 (0.35667) Boundary_loss: 0.015188 (0.015097) Loss: 0.30106 (0.37176) +2025-08-23,07:04:21 | INFO | Train Epoch: 7 [18739712/26365952 (71%)] Avg Boundaries (per batch): 50.098 Boundary Ratio: 0.256 Contrastive_loss: 0.38537 (0.35674) Boundary_loss: 0.015268 (0.015098) Loss: 0.40064 (0.37184) +2025-08-23,07:05:18 | INFO | Train Epoch: 7 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.39726 (0.35685) Boundary_loss: 0.015128 (0.015098) Loss: 0.41239 (0.37195) +2025-08-23,07:06:15 | INFO | Train Epoch: 7 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.38404 (0.35693) Boundary_loss: 0.015160 (0.015098) Loss: 0.39920 (0.37203) +2025-08-23,07:07:11 | INFO | Train Epoch: 7 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.34690 (0.35690) Boundary_loss: 0.015010 (0.015098) Loss: 0.36191 (0.37200) +2025-08-23,07:08:08 | INFO | Train Epoch: 7 [18944512/26365952 (72%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 0.37119 (0.35694) Boundary_loss: 0.015047 (0.015097) Loss: 0.38624 (0.37204) +2025-08-23,07:09:04 | INFO | Train Epoch: 7 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.42394 (0.35712) Boundary_loss: 0.015121 (0.015098) Loss: 0.43906 (0.37222) +2025-08-23,07:10:01 | INFO | Train Epoch: 7 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.42551 (0.35730) Boundary_loss: 0.015026 (0.015097) Loss: 0.44054 (0.37240) +2025-08-23,07:10:58 | INFO | Train Epoch: 7 [19098112/26365952 (72%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.35104 (0.35729) Boundary_loss: 0.015213 (0.015098) Loss: 0.36625 (0.37238) +2025-08-23,07:11:54 | INFO | Train Epoch: 7 [19149312/26365952 (73%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.34265 (0.35725) Boundary_loss: 0.014937 (0.015097) Loss: 0.35759 (0.37234) +2025-08-23,07:12:51 | INFO | Train Epoch: 7 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.36580 (0.35727) Boundary_loss: 0.015097 (0.015097) Loss: 0.38089 (0.37237) +2025-08-23,07:13:48 | INFO | Train Epoch: 7 [19251712/26365952 (73%)] Avg Boundaries (per batch): 49.236 Boundary Ratio: 0.251 Contrastive_loss: 0.34341 (0.35723) Boundary_loss: 0.015142 (0.015097) Loss: 0.35855 (0.37233) +2025-08-23,07:14:44 | INFO | Train Epoch: 7 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.39867 (0.35734) Boundary_loss: 0.015109 (0.015097) Loss: 0.41378 (0.37244) +2025-08-23,07:15:41 | INFO | Train Epoch: 7 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.34952 (0.35732) Boundary_loss: 0.015068 (0.015097) Loss: 0.36459 (0.37242) +2025-08-23,07:16:37 | INFO | Train Epoch: 7 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.29521 (0.35716) Boundary_loss: 0.015133 (0.015097) Loss: 0.31035 (0.37226) +2025-08-23,07:17:34 | INFO | Train Epoch: 7 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.506 Boundary Ratio: 0.253 Contrastive_loss: 0.34539 (0.35713) Boundary_loss: 0.015100 (0.015097) Loss: 0.36049 (0.37222) +2025-08-23,07:18:31 | INFO | Train Epoch: 7 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.35578 (0.35712) Boundary_loss: 0.015190 (0.015098) Loss: 0.37097 (0.37222) +2025-08-23,07:19:27 | INFO | Train Epoch: 7 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.42780 (0.35731) Boundary_loss: 0.015056 (0.015098) Loss: 0.44286 (0.37241) +2025-08-23,07:20:24 | INFO | Train Epoch: 7 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.31916 (0.35721) Boundary_loss: 0.015055 (0.015097) Loss: 0.33421 (0.37231) +2025-08-23,07:21:21 | INFO | Train Epoch: 7 [19661312/26365952 (75%)] Avg Boundaries (per batch): 49.652 Boundary Ratio: 0.253 Contrastive_loss: 0.40532 (0.35733) Boundary_loss: 0.015179 (0.015098) Loss: 0.42050 (0.37243) +2025-08-23,07:22:18 | INFO | Train Epoch: 7 [19712512/26365952 (75%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.31994 (0.35724) Boundary_loss: 0.015094 (0.015098) Loss: 0.33504 (0.37233) +2025-08-23,07:23:14 | INFO | Train Epoch: 7 [19763712/26365952 (75%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.37036 (0.35727) Boundary_loss: 0.015202 (0.015098) Loss: 0.38556 (0.37237) +2025-08-23,07:24:11 | INFO | Train Epoch: 7 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.254 Boundary Ratio: 0.251 Contrastive_loss: 0.42637 (0.35745) Boundary_loss: 0.015132 (0.015098) Loss: 0.44150 (0.37255) +2025-08-23,07:25:07 | INFO | Train Epoch: 7 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.39686 (0.35755) Boundary_loss: 0.015027 (0.015098) Loss: 0.41189 (0.37265) +2025-08-23,07:26:04 | INFO | Train Epoch: 7 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.39120 (0.35764) Boundary_loss: 0.015016 (0.015098) Loss: 0.40622 (0.37273) +2025-08-23,07:27:01 | INFO | Train Epoch: 7 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.38304 (0.35770) Boundary_loss: 0.015015 (0.015097) Loss: 0.39806 (0.37280) +2025-08-23,07:27:57 | INFO | Train Epoch: 7 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.34369 (0.35767) Boundary_loss: 0.015129 (0.015097) Loss: 0.35881 (0.37276) +2025-08-23,07:28:54 | INFO | Train Epoch: 7 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.34741 (0.35764) Boundary_loss: 0.015110 (0.015097) Loss: 0.36252 (0.37274) +2025-08-23,07:29:50 | INFO | Train Epoch: 7 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.39802 (0.35774) Boundary_loss: 0.015066 (0.015097) Loss: 0.41308 (0.37284) +2025-08-23,07:30:47 | INFO | Train Epoch: 7 [20173312/26365952 (77%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.36615 (0.35776) Boundary_loss: 0.015160 (0.015098) Loss: 0.38131 (0.37286) +2025-08-23,07:31:44 | INFO | Train Epoch: 7 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.32681 (0.35769) Boundary_loss: 0.015169 (0.015098) Loss: 0.34198 (0.37278) +2025-08-23,07:32:40 | INFO | Train Epoch: 7 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.41279 (0.35782) Boundary_loss: 0.015074 (0.015098) Loss: 0.42786 (0.37292) +2025-08-23,07:33:37 | INFO | Train Epoch: 7 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.32720 (0.35775) Boundary_loss: 0.015069 (0.015098) Loss: 0.34227 (0.37284) +2025-08-23,07:34:34 | INFO | Train Epoch: 7 [20378112/26365952 (77%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.27434 (0.35754) Boundary_loss: 0.015029 (0.015097) Loss: 0.28937 (0.37264) +2025-08-23,07:35:30 | INFO | Train Epoch: 7 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.40894 (0.35767) Boundary_loss: 0.014981 (0.015097) Loss: 0.42392 (0.37276) +2025-08-23,07:36:27 | INFO | Train Epoch: 7 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.34939 (0.35765) Boundary_loss: 0.015124 (0.015097) Loss: 0.36451 (0.37274) +2025-08-23,07:37:24 | INFO | Train Epoch: 7 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.42893 (0.35782) Boundary_loss: 0.015060 (0.015097) Loss: 0.44399 (0.37292) +2025-08-23,07:38:21 | INFO | Train Epoch: 7 [20582912/26365952 (78%)] Avg Boundaries (per batch): 47.865 Boundary Ratio: 0.244 Contrastive_loss: 0.34817 (0.35780) Boundary_loss: 0.015048 (0.015097) Loss: 0.36322 (0.37290) +2025-08-23,07:39:17 | INFO | Train Epoch: 7 [20634112/26365952 (78%)] Avg Boundaries (per batch): 49.420 Boundary Ratio: 0.252 Contrastive_loss: 0.39642 (0.35789) Boundary_loss: 0.015081 (0.015097) Loss: 0.41150 (0.37299) +2025-08-23,07:40:14 | INFO | Train Epoch: 7 [20685312/26365952 (78%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 0.35452 (0.35789) Boundary_loss: 0.015134 (0.015097) Loss: 0.36965 (0.37298) +2025-08-23,07:41:11 | INFO | Train Epoch: 7 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 0.37010 (0.35792) Boundary_loss: 0.015079 (0.015097) Loss: 0.38518 (0.37301) +2025-08-23,07:42:07 | INFO | Train Epoch: 7 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.574 Boundary Ratio: 0.253 Contrastive_loss: 0.33499 (0.35786) Boundary_loss: 0.015147 (0.015097) Loss: 0.35014 (0.37296) +2025-08-23,07:43:04 | INFO | Train Epoch: 7 [20838912/26365952 (79%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.32076 (0.35777) Boundary_loss: 0.015144 (0.015097) Loss: 0.33591 (0.37287) +2025-08-23,07:44:01 | INFO | Train Epoch: 7 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.39564 (0.35786) Boundary_loss: 0.015139 (0.015097) Loss: 0.41078 (0.37296) +2025-08-23,07:44:57 | INFO | Train Epoch: 7 [20941312/26365952 (79%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.30646 (0.35774) Boundary_loss: 0.015078 (0.015097) Loss: 0.32154 (0.37283) +2025-08-23,07:45:54 | INFO | Train Epoch: 7 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.32540 (0.35766) Boundary_loss: 0.015062 (0.015097) Loss: 0.34046 (0.37276) +2025-08-23,07:46:51 | INFO | Train Epoch: 7 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.38816 (0.35773) Boundary_loss: 0.015062 (0.015097) Loss: 0.40322 (0.37283) +2025-08-23,07:47:47 | INFO | Train Epoch: 7 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.34878 (0.35771) Boundary_loss: 0.014988 (0.015097) Loss: 0.36377 (0.37281) +2025-08-23,07:48:44 | INFO | Train Epoch: 7 [21146112/26365952 (80%)] Avg Boundaries (per batch): 47.811 Boundary Ratio: 0.244 Contrastive_loss: 0.38594 (0.35778) Boundary_loss: 0.015159 (0.015097) Loss: 0.40110 (0.37288) +2025-08-23,07:49:40 | INFO | Train Epoch: 7 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.30979 (0.35766) Boundary_loss: 0.015055 (0.015097) Loss: 0.32485 (0.37276) +2025-08-23,07:50:37 | INFO | Train Epoch: 7 [21248512/26365952 (81%)] Avg Boundaries (per batch): 49.395 Boundary Ratio: 0.252 Contrastive_loss: 0.32017 (0.35757) Boundary_loss: 0.015030 (0.015097) Loss: 0.33520 (0.37267) +2025-08-23,07:51:33 | INFO | Train Epoch: 7 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.31075 (0.35746) Boundary_loss: 0.015015 (0.015097) Loss: 0.32576 (0.37256) +2025-08-23,07:52:30 | INFO | Train Epoch: 7 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.303 Boundary Ratio: 0.252 Contrastive_loss: 0.29547 (0.35731) Boundary_loss: 0.015172 (0.015097) Loss: 0.31064 (0.37241) +2025-08-23,07:53:27 | INFO | Train Epoch: 7 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.30895 (0.35720) Boundary_loss: 0.015037 (0.015097) Loss: 0.32399 (0.37229) +2025-08-23,07:54:23 | INFO | Train Epoch: 7 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.42883 (0.35737) Boundary_loss: 0.015034 (0.015096) Loss: 0.44387 (0.37246) +2025-08-23,07:55:20 | INFO | Train Epoch: 7 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.44628 (0.35758) Boundary_loss: 0.015159 (0.015097) Loss: 0.46144 (0.37268) +2025-08-23,07:56:16 | INFO | Train Epoch: 7 [21555712/26365952 (82%)] Avg Boundaries (per batch): 49.379 Boundary Ratio: 0.252 Contrastive_loss: 0.38892 (0.35765) Boundary_loss: 0.015186 (0.015097) Loss: 0.40411 (0.37275) +2025-08-23,07:57:13 | INFO | Train Epoch: 7 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.30324 (0.35752) Boundary_loss: 0.015076 (0.015097) Loss: 0.31831 (0.37262) +2025-08-23,07:58:10 | INFO | Train Epoch: 7 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 0.33712 (0.35748) Boundary_loss: 0.015162 (0.015097) Loss: 0.35228 (0.37257) +2025-08-23,07:59:06 | INFO | Train Epoch: 7 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.25690 (0.35724) Boundary_loss: 0.015023 (0.015097) Loss: 0.27193 (0.37234) +2025-08-23,08:00:03 | INFO | Train Epoch: 7 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.39907 (0.35734) Boundary_loss: 0.015037 (0.015097) Loss: 0.41411 (0.37243) +2025-08-23,08:00:59 | INFO | Train Epoch: 7 [21811712/26365952 (83%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.32040 (0.35725) Boundary_loss: 0.015158 (0.015097) Loss: 0.33556 (0.37235) +2025-08-23,08:01:56 | INFO | Train Epoch: 7 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.28157 (0.35707) Boundary_loss: 0.015058 (0.015097) Loss: 0.29663 (0.37217) +2025-08-23,08:02:53 | INFO | Train Epoch: 7 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.35497 (0.35707) Boundary_loss: 0.015042 (0.015097) Loss: 0.37001 (0.37217) +2025-08-23,08:03:49 | INFO | Train Epoch: 7 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.34705 (0.35705) Boundary_loss: 0.015059 (0.015096) Loss: 0.36211 (0.37214) +2025-08-23,08:04:46 | INFO | Train Epoch: 7 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.29074 (0.35689) Boundary_loss: 0.015126 (0.015097) Loss: 0.30587 (0.37199) +2025-08-23,08:05:43 | INFO | Train Epoch: 7 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.36217 (0.35690) Boundary_loss: 0.014980 (0.015096) Loss: 0.37715 (0.37200) +2025-08-23,08:06:39 | INFO | Train Epoch: 7 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.42466 (0.35706) Boundary_loss: 0.015198 (0.015096) Loss: 0.43986 (0.37216) +2025-08-23,08:07:36 | INFO | Train Epoch: 7 [22170112/26365952 (84%)] Avg Boundaries (per batch): 49.682 Boundary Ratio: 0.253 Contrastive_loss: 0.31470 (0.35696) Boundary_loss: 0.014919 (0.015096) Loss: 0.32962 (0.37206) +2025-08-23,08:08:32 | INFO | Train Epoch: 7 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.35848 (0.35697) Boundary_loss: 0.015032 (0.015096) Loss: 0.37351 (0.37206) +2025-08-23,08:09:29 | INFO | Train Epoch: 7 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.30426 (0.35685) Boundary_loss: 0.014944 (0.015096) Loss: 0.31921 (0.37194) +2025-08-23,08:10:25 | INFO | Train Epoch: 7 [22323712/26365952 (85%)] Avg Boundaries (per batch): 49.414 Boundary Ratio: 0.252 Contrastive_loss: 0.36629 (0.35687) Boundary_loss: 0.015160 (0.015096) Loss: 0.38145 (0.37196) +2025-08-23,08:11:22 | INFO | Train Epoch: 7 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.252 Boundary Ratio: 0.246 Contrastive_loss: 0.36180 (0.35688) Boundary_loss: 0.015106 (0.015096) Loss: 0.37690 (0.37197) +2025-08-23,08:12:19 | INFO | Train Epoch: 7 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.30957 (0.35677) Boundary_loss: 0.015083 (0.015096) Loss: 0.32466 (0.37187) +2025-08-23,08:13:15 | INFO | Train Epoch: 7 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.39707 (0.35686) Boundary_loss: 0.014849 (0.015095) Loss: 0.41192 (0.37196) +2025-08-23,08:14:12 | INFO | Train Epoch: 7 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.32642 (0.35679) Boundary_loss: 0.015003 (0.015095) Loss: 0.34142 (0.37189) +2025-08-23,08:15:08 | INFO | Train Epoch: 7 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.26476 (0.35659) Boundary_loss: 0.015083 (0.015095) Loss: 0.27984 (0.37168) +2025-08-23,08:16:05 | INFO | Train Epoch: 7 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 0.29686 (0.35645) Boundary_loss: 0.015227 (0.015095) Loss: 0.31209 (0.37155) +2025-08-23,08:17:02 | INFO | Train Epoch: 7 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.42717 (0.35661) Boundary_loss: 0.015069 (0.015095) Loss: 0.44223 (0.37170) +2025-08-23,08:17:58 | INFO | Train Epoch: 7 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.35029 (0.35660) Boundary_loss: 0.015087 (0.015095) Loss: 0.36538 (0.37169) +2025-08-23,08:18:55 | INFO | Train Epoch: 7 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.393 Boundary Ratio: 0.247 Contrastive_loss: 0.34322 (0.35657) Boundary_loss: 0.014995 (0.015095) Loss: 0.35822 (0.37166) +2025-08-23,08:19:51 | INFO | Train Epoch: 7 [22835712/26365952 (87%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.33240 (0.35651) Boundary_loss: 0.014910 (0.015095) Loss: 0.34731 (0.37161) +2025-08-23,08:20:48 | INFO | Train Epoch: 7 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.221 Boundary Ratio: 0.246 Contrastive_loss: 0.34617 (0.35649) Boundary_loss: 0.015059 (0.015094) Loss: 0.36123 (0.37158) +2025-08-23,08:21:45 | INFO | Train Epoch: 7 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.36246 (0.35650) Boundary_loss: 0.015093 (0.015094) Loss: 0.37755 (0.37160) +2025-08-23,08:22:42 | INFO | Train Epoch: 7 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.34357 (0.35647) Boundary_loss: 0.014953 (0.015094) Loss: 0.35852 (0.37157) +2025-08-23,08:23:38 | INFO | Train Epoch: 7 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.40497 (0.35658) Boundary_loss: 0.014927 (0.015094) Loss: 0.41990 (0.37167) +2025-08-23,08:24:35 | INFO | Train Epoch: 7 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.35887 (0.35659) Boundary_loss: 0.015173 (0.015094) Loss: 0.37404 (0.37168) +2025-08-23,08:25:31 | INFO | Train Epoch: 7 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.34007 (0.35655) Boundary_loss: 0.015045 (0.015094) Loss: 0.35512 (0.37164) +2025-08-23,08:26:28 | INFO | Train Epoch: 7 [23194112/26365952 (88%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 0.24464 (0.35630) Boundary_loss: 0.015198 (0.015094) Loss: 0.25984 (0.37140) +2025-08-23,08:27:24 | INFO | Train Epoch: 7 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.37125 (0.35634) Boundary_loss: 0.015160 (0.015094) Loss: 0.38641 (0.37143) +2025-08-23,08:28:21 | INFO | Train Epoch: 7 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.34030 (0.35630) Boundary_loss: 0.015052 (0.015094) Loss: 0.35536 (0.37139) +2025-08-23,08:29:18 | INFO | Train Epoch: 7 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.291 Boundary Ratio: 0.246 Contrastive_loss: 0.34614 (0.35628) Boundary_loss: 0.015169 (0.015094) Loss: 0.36131 (0.37137) +2025-08-23,08:30:14 | INFO | Train Epoch: 7 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.209 Boundary Ratio: 0.246 Contrastive_loss: 0.37358 (0.35632) Boundary_loss: 0.015098 (0.015094) Loss: 0.38868 (0.37141) +2025-08-23,08:31:11 | INFO | Train Epoch: 7 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.38862 (0.35639) Boundary_loss: 0.014925 (0.015094) Loss: 0.40354 (0.37148) +2025-08-23,08:32:08 | INFO | Train Epoch: 7 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.41349 (0.35651) Boundary_loss: 0.015108 (0.015094) Loss: 0.42859 (0.37160) +2025-08-23,08:33:04 | INFO | Train Epoch: 7 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.34171 (0.35648) Boundary_loss: 0.015011 (0.015094) Loss: 0.35672 (0.37157) +2025-08-23,08:34:01 | INFO | Train Epoch: 7 [23603712/26365952 (90%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.35522 (0.35648) Boundary_loss: 0.015099 (0.015094) Loss: 0.37032 (0.37157) +2025-08-23,08:34:58 | INFO | Train Epoch: 7 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.27603 (0.35630) Boundary_loss: 0.015119 (0.015094) Loss: 0.29115 (0.37140) +2025-08-23,08:35:54 | INFO | Train Epoch: 7 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.40624 (0.35641) Boundary_loss: 0.015092 (0.015094) Loss: 0.42134 (0.37150) +2025-08-23,08:36:51 | INFO | Train Epoch: 7 [23757312/26365952 (90%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.39482 (0.35649) Boundary_loss: 0.015165 (0.015094) Loss: 0.40998 (0.37159) +2025-08-23,08:37:47 | INFO | Train Epoch: 7 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.33385 (0.35644) Boundary_loss: 0.015180 (0.015094) Loss: 0.34903 (0.37154) +2025-08-23,08:38:44 | INFO | Train Epoch: 7 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.39559 (0.35653) Boundary_loss: 0.015093 (0.015094) Loss: 0.41069 (0.37162) +2025-08-23,08:39:41 | INFO | Train Epoch: 7 [23910912/26365952 (91%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.26996 (0.35634) Boundary_loss: 0.015153 (0.015094) Loss: 0.28511 (0.37144) +2025-08-23,08:40:38 | INFO | Train Epoch: 7 [23962112/26365952 (91%)] Avg Boundaries (per batch): 49.367 Boundary Ratio: 0.252 Contrastive_loss: 0.36833 (0.35637) Boundary_loss: 0.015068 (0.015094) Loss: 0.38340 (0.37146) +2025-08-23,08:41:34 | INFO | Train Epoch: 7 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.33840 (0.35633) Boundary_loss: 0.015083 (0.015094) Loss: 0.35348 (0.37142) +2025-08-23,08:42:31 | INFO | Train Epoch: 7 [24064512/26365952 (91%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.36578 (0.35635) Boundary_loss: 0.015084 (0.015094) Loss: 0.38086 (0.37144) +2025-08-23,08:43:27 | INFO | Train Epoch: 7 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.33584 (0.35631) Boundary_loss: 0.015103 (0.015094) Loss: 0.35095 (0.37140) +2025-08-23,08:44:24 | INFO | Train Epoch: 7 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.945 Boundary Ratio: 0.255 Contrastive_loss: 0.32577 (0.35624) Boundary_loss: 0.015165 (0.015094) Loss: 0.34094 (0.37134) +2025-08-23,08:45:21 | INFO | Train Epoch: 7 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.502 Boundary Ratio: 0.253 Contrastive_loss: 0.42389 (0.35638) Boundary_loss: 0.015026 (0.015094) Loss: 0.43891 (0.37148) +2025-08-23,08:46:17 | INFO | Train Epoch: 7 [24269312/26365952 (92%)] Avg Boundaries (per batch): 49.467 Boundary Ratio: 0.252 Contrastive_loss: 0.32882 (0.35633) Boundary_loss: 0.015038 (0.015094) Loss: 0.34386 (0.37142) +2025-08-23,08:47:14 | INFO | Train Epoch: 7 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.42938 (0.35648) Boundary_loss: 0.014958 (0.015094) Loss: 0.44434 (0.37157) +2025-08-23,08:48:10 | INFO | Train Epoch: 7 [24371712/26365952 (92%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.33932 (0.35644) Boundary_loss: 0.015046 (0.015094) Loss: 0.35437 (0.37154) +2025-08-23,08:49:07 | INFO | Train Epoch: 7 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.30599 (0.35634) Boundary_loss: 0.015096 (0.015094) Loss: 0.32109 (0.37143) +2025-08-23,08:50:04 | INFO | Train Epoch: 7 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.066 Boundary Ratio: 0.245 Contrastive_loss: 0.36633 (0.35636) Boundary_loss: 0.015002 (0.015094) Loss: 0.38134 (0.37145) +2025-08-23,08:51:00 | INFO | Train Epoch: 7 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.33773 (0.35632) Boundary_loss: 0.015100 (0.015094) Loss: 0.35283 (0.37141) +2025-08-23,08:51:57 | INFO | Train Epoch: 7 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.42912 (0.35647) Boundary_loss: 0.015074 (0.015093) Loss: 0.44420 (0.37157) +2025-08-23,08:52:53 | INFO | Train Epoch: 7 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.41098 (0.35658) Boundary_loss: 0.015138 (0.015094) Loss: 0.42612 (0.37168) +2025-08-23,08:53:50 | INFO | Train Epoch: 7 [24678912/26365952 (94%)] Avg Boundaries (per batch): 49.477 Boundary Ratio: 0.252 Contrastive_loss: 0.31329 (0.35650) Boundary_loss: 0.015018 (0.015093) Loss: 0.32831 (0.37159) +2025-08-23,08:54:47 | INFO | Train Epoch: 7 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 0.30689 (0.35639) Boundary_loss: 0.015009 (0.015093) Loss: 0.32190 (0.37149) +2025-08-23,08:55:43 | INFO | Train Epoch: 7 [24781312/26365952 (94%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.37999 (0.35644) Boundary_loss: 0.015007 (0.015093) Loss: 0.39500 (0.37153) +2025-08-23,08:56:40 | INFO | Train Epoch: 7 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.37885 (0.35649) Boundary_loss: 0.015170 (0.015093) Loss: 0.39402 (0.37158) +2025-08-23,08:57:37 | INFO | Train Epoch: 7 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.28281 (0.35634) Boundary_loss: 0.015048 (0.015093) Loss: 0.29786 (0.37143) +2025-08-23,08:58:33 | INFO | Train Epoch: 7 [24934912/26365952 (95%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.32692 (0.35628) Boundary_loss: 0.015019 (0.015093) Loss: 0.34193 (0.37137) +2025-08-23,08:59:30 | INFO | Train Epoch: 7 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.39075 (0.35635) Boundary_loss: 0.015025 (0.015093) Loss: 0.40577 (0.37144) +2025-08-23,09:00:27 | INFO | Train Epoch: 7 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.38334 (0.35640) Boundary_loss: 0.015156 (0.015093) Loss: 0.39849 (0.37149) +2025-08-23,09:01:23 | INFO | Train Epoch: 7 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.35115 (0.35639) Boundary_loss: 0.015176 (0.015093) Loss: 0.36632 (0.37148) +2025-08-23,09:02:20 | INFO | Train Epoch: 7 [25139712/26365952 (95%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.43209 (0.35654) Boundary_loss: 0.014990 (0.015093) Loss: 0.44708 (0.37164) +2025-08-23,09:03:16 | INFO | Train Epoch: 7 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.398 Boundary Ratio: 0.247 Contrastive_loss: 0.31184 (0.35645) Boundary_loss: 0.015059 (0.015093) Loss: 0.32690 (0.37155) +2025-08-23,09:04:13 | INFO | Train Epoch: 7 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.30103 (0.35634) Boundary_loss: 0.015147 (0.015093) Loss: 0.31618 (0.37143) +2025-08-23,09:05:10 | INFO | Train Epoch: 7 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.283 Boundary Ratio: 0.246 Contrastive_loss: 0.36136 (0.35635) Boundary_loss: 0.014888 (0.015093) Loss: 0.37625 (0.37144) +2025-08-23,09:06:06 | INFO | Train Epoch: 7 [25344512/26365952 (96%)] Avg Boundaries (per batch): 49.277 Boundary Ratio: 0.251 Contrastive_loss: 0.39987 (0.35644) Boundary_loss: 0.014931 (0.015092) Loss: 0.41480 (0.37153) +2025-08-23,09:07:03 | INFO | Train Epoch: 7 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.38957 (0.35651) Boundary_loss: 0.015001 (0.015092) Loss: 0.40457 (0.37160) +2025-08-23,09:07:59 | INFO | Train Epoch: 7 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.37409 (0.35654) Boundary_loss: 0.015045 (0.015092) Loss: 0.38913 (0.37163) +2025-08-23,09:08:56 | INFO | Train Epoch: 7 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.496 Boundary Ratio: 0.253 Contrastive_loss: 0.39672 (0.35662) Boundary_loss: 0.015162 (0.015092) Loss: 0.41188 (0.37171) +2025-08-23,09:09:53 | INFO | Train Epoch: 7 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.35242 (0.35661) Boundary_loss: 0.015005 (0.015092) Loss: 0.36742 (0.37171) +2025-08-23,09:10:49 | INFO | Train Epoch: 7 [25600512/26365952 (97%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.34995 (0.35660) Boundary_loss: 0.015120 (0.015092) Loss: 0.36507 (0.37169) +2025-08-23,09:11:46 | INFO | Train Epoch: 7 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.35691 (0.35660) Boundary_loss: 0.015131 (0.015092) Loss: 0.37204 (0.37169) +2025-08-23,09:12:42 | INFO | Train Epoch: 7 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.225 Boundary Ratio: 0.246 Contrastive_loss: 0.39337 (0.35667) Boundary_loss: 0.015206 (0.015092) Loss: 0.40858 (0.37177) +2025-08-23,09:13:39 | INFO | Train Epoch: 7 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.314 Boundary Ratio: 0.247 Contrastive_loss: 0.29206 (0.35655) Boundary_loss: 0.015057 (0.015092) Loss: 0.30712 (0.37164) +2025-08-23,09:14:35 | INFO | Train Epoch: 7 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.38090 (0.35659) Boundary_loss: 0.015141 (0.015092) Loss: 0.39604 (0.37169) +2025-08-23,09:15:32 | INFO | Train Epoch: 7 [25856512/26365952 (98%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.31508 (0.35651) Boundary_loss: 0.015171 (0.015092) Loss: 0.33025 (0.37160) +2025-08-23,09:16:28 | INFO | Train Epoch: 7 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 0.32786 (0.35646) Boundary_loss: 0.014955 (0.015092) Loss: 0.34282 (0.37155) +2025-08-23,09:17:25 | INFO | Train Epoch: 7 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.31565 (0.35638) Boundary_loss: 0.014957 (0.015092) Loss: 0.33060 (0.37147) +2025-08-23,09:18:21 | INFO | Train Epoch: 7 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.27830 (0.35622) Boundary_loss: 0.015155 (0.015092) Loss: 0.29345 (0.37131) +2025-08-23,09:19:18 | INFO | Train Epoch: 7 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.43888 (0.35638) Boundary_loss: 0.015027 (0.015092) Loss: 0.45390 (0.37148) +2025-08-23,09:20:15 | INFO | Train Epoch: 7 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.36261 (0.35640) Boundary_loss: 0.015028 (0.015092) Loss: 0.37764 (0.37149) +2025-08-23,09:21:11 | INFO | Train Epoch: 7 [26163712/26365952 (99%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.35303 (0.35639) Boundary_loss: 0.015169 (0.015092) Loss: 0.36820 (0.37148) +2025-08-23,09:22:08 | INFO | Train Epoch: 7 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.44610 (0.35656) Boundary_loss: 0.015300 (0.015092) Loss: 0.46140 (0.37166) +2025-08-23,09:23:04 | INFO | Train Epoch: 7 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.28592 (0.35643) Boundary_loss: 0.014992 (0.015092) Loss: 0.30092 (0.37152) +2025-08-23,09:24:01 | INFO | Train Epoch: 7 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.33617 (0.35639) Boundary_loss: 0.014957 (0.015092) Loss: 0.35113 (0.37148) +2025-08-23,09:24:54 | INFO | Train Epoch: 7 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.40982 (0.35649) Boundary_loss: 0.014943 (0.015092) Loss: 0.42476 (0.37158) +2025-08-23,09:24:54 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-23,09:24:54 | INFO | [Epoch 7] Average Step Time: 0.568s | Average GPU Memory: 31.8 GB +2025-08-23,09:24:54 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-23,09:24:55 | INFO | Starting zero-shot imagenet. +2025-08-23,09:24:55 | INFO | Building zero-shot classifier +2025-08-23,09:25:04 | INFO | Using classifier +2025-08-23,09:25:50 | INFO | Finished zero-shot imagenet. +2025-08-23,09:25:50 | INFO | Eval Epoch: 8 imagenet-zeroshot-val-top1: 0.2682 imagenet-zeroshot-val-top5: 0.5269 +2025-08-23,09:25:51 | INFO | Start epoch 8 +2025-08-23,09:25:54 | INFO | Train Epoch: 8 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.26956 (0.26956) Boundary_loss: 0.015090 (0.015090) Loss: 0.28465 (0.28465) +2025-08-23,09:26:50 | INFO | Train Epoch: 8 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.35031 (0.30993) Boundary_loss: 0.014987 (0.015039) Loss: 0.36529 (0.32497) +2025-08-23,09:27:47 | INFO | Train Epoch: 8 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 49.289 Boundary Ratio: 0.251 Contrastive_loss: 0.35205 (0.32397) Boundary_loss: 0.014937 (0.015005) Loss: 0.36698 (0.33897) +2025-08-23,09:28:44 | INFO | Train Epoch: 8 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.35910 (0.33275) Boundary_loss: 0.015258 (0.015068) Loss: 0.37436 (0.34782) +2025-08-23,09:29:40 | INFO | Train Epoch: 8 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 0.33459 (0.33312) Boundary_loss: 0.015081 (0.015071) Loss: 0.34967 (0.34819) +2025-08-23,09:30:37 | INFO | Train Epoch: 8 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.30891 (0.32908) Boundary_loss: 0.014994 (0.015058) Loss: 0.32390 (0.34414) +2025-08-23,09:31:33 | INFO | Train Epoch: 8 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.32686 (0.32877) Boundary_loss: 0.015021 (0.015053) Loss: 0.34188 (0.34382) +2025-08-23,09:32:30 | INFO | Train Epoch: 8 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 0.40553 (0.33836) Boundary_loss: 0.015091 (0.015057) Loss: 0.42062 (0.35342) +2025-08-23,09:33:26 | INFO | Train Epoch: 8 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 49.314 Boundary Ratio: 0.252 Contrastive_loss: 0.30284 (0.33441) Boundary_loss: 0.015006 (0.015052) Loss: 0.31784 (0.34947) +2025-08-23,09:34:23 | INFO | Train Epoch: 8 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.27908 (0.32888) Boundary_loss: 0.015021 (0.015049) Loss: 0.29410 (0.34393) +2025-08-23,09:35:20 | INFO | Train Epoch: 8 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.40515 (0.33581) Boundary_loss: 0.014962 (0.015041) Loss: 0.42012 (0.35086) +2025-08-23,09:36:16 | INFO | Train Epoch: 8 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 47.951 Boundary Ratio: 0.245 Contrastive_loss: 0.30120 (0.33293) Boundary_loss: 0.015148 (0.015050) Loss: 0.31634 (0.34798) +2025-08-23,09:37:13 | INFO | Train Epoch: 8 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.27542 (0.32851) Boundary_loss: 0.014989 (0.015045) Loss: 0.29041 (0.34355) +2025-08-23,09:38:10 | INFO | Train Epoch: 8 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.26305 (0.32383) Boundary_loss: 0.015035 (0.015044) Loss: 0.27808 (0.33887) +2025-08-23,09:39:06 | INFO | Train Epoch: 8 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.29416 (0.32185) Boundary_loss: 0.015059 (0.015045) Loss: 0.30922 (0.33690) +2025-08-23,09:40:03 | INFO | Train Epoch: 8 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.33178 (0.32247) Boundary_loss: 0.015049 (0.015045) Loss: 0.34683 (0.33752) +2025-08-23,09:40:59 | INFO | Train Epoch: 8 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.36559 (0.32501) Boundary_loss: 0.015115 (0.015050) Loss: 0.38070 (0.34006) +2025-08-23,09:41:56 | INFO | Train Epoch: 8 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.34555 (0.32615) Boundary_loss: 0.014947 (0.015044) Loss: 0.36050 (0.34119) +2025-08-23,09:42:53 | INFO | Train Epoch: 8 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.30302 (0.32493) Boundary_loss: 0.015071 (0.015045) Loss: 0.31809 (0.33998) +2025-08-23,09:43:49 | INFO | Train Epoch: 8 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.406 Boundary Ratio: 0.247 Contrastive_loss: 0.29867 (0.32362) Boundary_loss: 0.015075 (0.015047) Loss: 0.31374 (0.33867) +2025-08-23,09:44:46 | INFO | Train Epoch: 8 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.182 Boundary Ratio: 0.251 Contrastive_loss: 0.36842 (0.32575) Boundary_loss: 0.015009 (0.015045) Loss: 0.38343 (0.34080) +2025-08-23,09:45:43 | INFO | Train Epoch: 8 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.31045 (0.32506) Boundary_loss: 0.015010 (0.015043) Loss: 0.32546 (0.34010) +2025-08-23,09:46:39 | INFO | Train Epoch: 8 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 49.100 Boundary Ratio: 0.251 Contrastive_loss: 0.29816 (0.32389) Boundary_loss: 0.015116 (0.015047) Loss: 0.31327 (0.33893) +2025-08-23,09:47:36 | INFO | Train Epoch: 8 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.36043 (0.32541) Boundary_loss: 0.015091 (0.015048) Loss: 0.37552 (0.34046) +2025-08-23,09:48:33 | INFO | Train Epoch: 8 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.31403 (0.32495) Boundary_loss: 0.015070 (0.015049) Loss: 0.32910 (0.34000) +2025-08-23,09:49:29 | INFO | Train Epoch: 8 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.36713 (0.32658) Boundary_loss: 0.015062 (0.015050) Loss: 0.38219 (0.34163) +2025-08-23,09:50:26 | INFO | Train Epoch: 8 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.37396 (0.32833) Boundary_loss: 0.014968 (0.015047) Loss: 0.38893 (0.34338) +2025-08-23,09:51:23 | INFO | Train Epoch: 8 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.31507 (0.32786) Boundary_loss: 0.014929 (0.015043) Loss: 0.33000 (0.34290) +2025-08-23,09:52:19 | INFO | Train Epoch: 8 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.191 Boundary Ratio: 0.246 Contrastive_loss: 0.35266 (0.32871) Boundary_loss: 0.015150 (0.015046) Loss: 0.36782 (0.34376) +2025-08-23,09:53:16 | INFO | Train Epoch: 8 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 49.225 Boundary Ratio: 0.251 Contrastive_loss: 0.31123 (0.32813) Boundary_loss: 0.014993 (0.015044) Loss: 0.32622 (0.34317) +2025-08-23,09:54:13 | INFO | Train Epoch: 8 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.31995 (0.32787) Boundary_loss: 0.015163 (0.015048) Loss: 0.33512 (0.34291) +2025-08-23,09:55:09 | INFO | Train Epoch: 8 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.29040 (0.32670) Boundary_loss: 0.015048 (0.015048) Loss: 0.30545 (0.34174) +2025-08-23,09:56:06 | INFO | Train Epoch: 8 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.32736 (0.32672) Boundary_loss: 0.015162 (0.015052) Loss: 0.34253 (0.34177) +2025-08-23,09:57:03 | INFO | Train Epoch: 8 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.34375 (0.32722) Boundary_loss: 0.014993 (0.015050) Loss: 0.35874 (0.34227) +2025-08-23,09:57:59 | INFO | Train Epoch: 8 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.23974 (0.32472) Boundary_loss: 0.015093 (0.015051) Loss: 0.25483 (0.33977) +2025-08-23,09:58:56 | INFO | Train Epoch: 8 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 47.986 Boundary Ratio: 0.245 Contrastive_loss: 0.28125 (0.32351) Boundary_loss: 0.015169 (0.015054) Loss: 0.29642 (0.33856) +2025-08-23,09:59:53 | INFO | Train Epoch: 8 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 47.863 Boundary Ratio: 0.244 Contrastive_loss: 0.36440 (0.32462) Boundary_loss: 0.015032 (0.015054) Loss: 0.37943 (0.33967) +2025-08-23,10:00:50 | INFO | Train Epoch: 8 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.32862 (0.32472) Boundary_loss: 0.014982 (0.015052) Loss: 0.34360 (0.33977) +2025-08-23,10:01:46 | INFO | Train Epoch: 8 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.27909 (0.32355) Boundary_loss: 0.015032 (0.015051) Loss: 0.29412 (0.33860) +2025-08-23,10:02:43 | INFO | Train Epoch: 8 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.29465 (0.32283) Boundary_loss: 0.015031 (0.015051) Loss: 0.30968 (0.33788) +2025-08-23,10:03:40 | INFO | Train Epoch: 8 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.32436 (0.32287) Boundary_loss: 0.015023 (0.015050) Loss: 0.33939 (0.33792) +2025-08-23,10:04:37 | INFO | Train Epoch: 8 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.084 Boundary Ratio: 0.245 Contrastive_loss: 0.40382 (0.32479) Boundary_loss: 0.015029 (0.015050) Loss: 0.41885 (0.33984) +2025-08-23,10:05:33 | INFO | Train Epoch: 8 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.32503 (0.32480) Boundary_loss: 0.015040 (0.015050) Loss: 0.34007 (0.33985) +2025-08-23,10:06:30 | INFO | Train Epoch: 8 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.27743 (0.32372) Boundary_loss: 0.014927 (0.015047) Loss: 0.29236 (0.33877) +2025-08-23,10:07:27 | INFO | Train Epoch: 8 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.26576 (0.32243) Boundary_loss: 0.015171 (0.015050) Loss: 0.28093 (0.33748) +2025-08-23,10:08:23 | INFO | Train Epoch: 8 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.32037 (0.32239) Boundary_loss: 0.015053 (0.015050) Loss: 0.33542 (0.33744) +2025-08-23,10:09:20 | INFO | Train Epoch: 8 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.32915 (0.32253) Boundary_loss: 0.015323 (0.015055) Loss: 0.34448 (0.33759) +2025-08-23,10:10:17 | INFO | Train Epoch: 8 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 0.31067 (0.32229) Boundary_loss: 0.015061 (0.015056) Loss: 0.32573 (0.33734) +2025-08-23,10:11:13 | INFO | Train Epoch: 8 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.31438 (0.32212) Boundary_loss: 0.014978 (0.015054) Loss: 0.32935 (0.33718) +2025-08-23,10:12:10 | INFO | Train Epoch: 8 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.33172 (0.32232) Boundary_loss: 0.015101 (0.015055) Loss: 0.34682 (0.33737) +2025-08-23,10:13:06 | INFO | Train Epoch: 8 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.33965 (0.32266) Boundary_loss: 0.015000 (0.015054) Loss: 0.35465 (0.33771) +2025-08-23,10:14:03 | INFO | Train Epoch: 8 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 0.34256 (0.32304) Boundary_loss: 0.015001 (0.015053) Loss: 0.35756 (0.33809) +2025-08-23,10:15:00 | INFO | Train Epoch: 8 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.457 Boundary Ratio: 0.247 Contrastive_loss: 0.26016 (0.32185) Boundary_loss: 0.015121 (0.015054) Loss: 0.27529 (0.33691) +2025-08-23,10:15:56 | INFO | Train Epoch: 8 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.27621 (0.32101) Boundary_loss: 0.014978 (0.015053) Loss: 0.29119 (0.33606) +2025-08-23,10:16:53 | INFO | Train Epoch: 8 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.35510 (0.32163) Boundary_loss: 0.014977 (0.015051) Loss: 0.37008 (0.33668) +2025-08-23,10:17:50 | INFO | Train Epoch: 8 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.30400 (0.32131) Boundary_loss: 0.015054 (0.015051) Loss: 0.31905 (0.33636) +2025-08-23,10:18:46 | INFO | Train Epoch: 8 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.36305 (0.32204) Boundary_loss: 0.015058 (0.015051) Loss: 0.37811 (0.33710) +2025-08-23,10:19:43 | INFO | Train Epoch: 8 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.38950 (0.32321) Boundary_loss: 0.015127 (0.015053) Loss: 0.40462 (0.33826) +2025-08-23,10:20:40 | INFO | Train Epoch: 8 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.31824 (0.32312) Boundary_loss: 0.015051 (0.015053) Loss: 0.33329 (0.33818) +2025-08-23,10:21:36 | INFO | Train Epoch: 8 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.34015 (0.32341) Boundary_loss: 0.015176 (0.015055) Loss: 0.35532 (0.33846) +2025-08-23,10:22:33 | INFO | Train Epoch: 8 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.35719 (0.32396) Boundary_loss: 0.014846 (0.015051) Loss: 0.37203 (0.33901) +2025-08-23,10:23:30 | INFO | Train Epoch: 8 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.32297 (0.32395) Boundary_loss: 0.014966 (0.015050) Loss: 0.33793 (0.33900) +2025-08-23,10:24:26 | INFO | Train Epoch: 8 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 47.984 Boundary Ratio: 0.245 Contrastive_loss: 0.33767 (0.32416) Boundary_loss: 0.015034 (0.015050) Loss: 0.35270 (0.33921) +2025-08-23,10:25:23 | INFO | Train Epoch: 8 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.31875 (0.32408) Boundary_loss: 0.015014 (0.015049) Loss: 0.33376 (0.33913) +2025-08-23,10:26:20 | INFO | Train Epoch: 8 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 49.514 Boundary Ratio: 0.253 Contrastive_loss: 0.37654 (0.32489) Boundary_loss: 0.015111 (0.015050) Loss: 0.39166 (0.33994) +2025-08-23,10:27:16 | INFO | Train Epoch: 8 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.22302 (0.32334) Boundary_loss: 0.015098 (0.015051) Loss: 0.23811 (0.33839) +2025-08-23,10:28:13 | INFO | Train Epoch: 8 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 49.699 Boundary Ratio: 0.254 Contrastive_loss: 0.28374 (0.32275) Boundary_loss: 0.015228 (0.015054) Loss: 0.29896 (0.33780) +2025-08-23,10:29:09 | INFO | Train Epoch: 8 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.139 Boundary Ratio: 0.246 Contrastive_loss: 0.33844 (0.32298) Boundary_loss: 0.015139 (0.015055) Loss: 0.35358 (0.33804) +2025-08-23,10:30:06 | INFO | Train Epoch: 8 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 49.650 Boundary Ratio: 0.253 Contrastive_loss: 0.38217 (0.32384) Boundary_loss: 0.015159 (0.015056) Loss: 0.39733 (0.33890) +2025-08-23,10:31:03 | INFO | Train Epoch: 8 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.31198 (0.32367) Boundary_loss: 0.014929 (0.015054) Loss: 0.32691 (0.33872) +2025-08-23,10:31:59 | INFO | Train Epoch: 8 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.26527 (0.32285) Boundary_loss: 0.015264 (0.015057) Loss: 0.28053 (0.33790) +2025-08-23,10:32:56 | INFO | Train Epoch: 8 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.30201 (0.32256) Boundary_loss: 0.015168 (0.015059) Loss: 0.31718 (0.33762) +2025-08-23,10:33:52 | INFO | Train Epoch: 8 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.32458 (0.32259) Boundary_loss: 0.015060 (0.015059) Loss: 0.33964 (0.33764) +2025-08-23,10:34:49 | INFO | Train Epoch: 8 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.33599 (0.32277) Boundary_loss: 0.015131 (0.015060) Loss: 0.35112 (0.33783) +2025-08-23,10:35:46 | INFO | Train Epoch: 8 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.29709 (0.32242) Boundary_loss: 0.015086 (0.015060) Loss: 0.31218 (0.33748) +2025-08-23,10:36:42 | INFO | Train Epoch: 8 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.404 Boundary Ratio: 0.252 Contrastive_loss: 0.21331 (0.32099) Boundary_loss: 0.015214 (0.015062) Loss: 0.22853 (0.33605) +2025-08-23,10:37:39 | INFO | Train Epoch: 8 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.316 Boundary Ratio: 0.252 Contrastive_loss: 0.36088 (0.32151) Boundary_loss: 0.015100 (0.015063) Loss: 0.37598 (0.33657) +2025-08-23,10:38:35 | INFO | Train Epoch: 8 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.30756 (0.32133) Boundary_loss: 0.015106 (0.015063) Loss: 0.32266 (0.33639) +2025-08-23,10:39:32 | INFO | Train Epoch: 8 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.28870 (0.32091) Boundary_loss: 0.015042 (0.015063) Loss: 0.30374 (0.33598) +2025-08-23,10:40:29 | INFO | Train Epoch: 8 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 49.445 Boundary Ratio: 0.252 Contrastive_loss: 0.38384 (0.32170) Boundary_loss: 0.015045 (0.015063) Loss: 0.39889 (0.33676) +2025-08-23,10:41:26 | INFO | Train Epoch: 8 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 49.258 Boundary Ratio: 0.251 Contrastive_loss: 0.27594 (0.32114) Boundary_loss: 0.015035 (0.015063) Loss: 0.29097 (0.33620) +2025-08-23,10:42:22 | INFO | Train Epoch: 8 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.29898 (0.32087) Boundary_loss: 0.015085 (0.015063) Loss: 0.31406 (0.33593) +2025-08-23,10:43:19 | INFO | Train Epoch: 8 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.385 Boundary Ratio: 0.247 Contrastive_loss: 0.21878 (0.31964) Boundary_loss: 0.015019 (0.015062) Loss: 0.23380 (0.33470) +2025-08-23,10:44:15 | INFO | Train Epoch: 8 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.24556 (0.31875) Boundary_loss: 0.015029 (0.015062) Loss: 0.26059 (0.33382) +2025-08-23,10:45:12 | INFO | Train Epoch: 8 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.32678 (0.31885) Boundary_loss: 0.015061 (0.015062) Loss: 0.34184 (0.33391) +2025-08-23,10:46:09 | INFO | Train Epoch: 8 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.32064 (0.31887) Boundary_loss: 0.015090 (0.015062) Loss: 0.33573 (0.33393) +2025-08-23,10:47:05 | INFO | Train Epoch: 8 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.30319 (0.31869) Boundary_loss: 0.015006 (0.015062) Loss: 0.31819 (0.33375) +2025-08-23,10:48:02 | INFO | Train Epoch: 8 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.27885 (0.31824) Boundary_loss: 0.015113 (0.015062) Loss: 0.29397 (0.33330) +2025-08-23,10:48:59 | INFO | Train Epoch: 8 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.29830 (0.31801) Boundary_loss: 0.015080 (0.015062) Loss: 0.31338 (0.33308) +2025-08-23,10:49:56 | INFO | Train Epoch: 8 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.508 Boundary Ratio: 0.247 Contrastive_loss: 0.25154 (0.31727) Boundary_loss: 0.015183 (0.015064) Loss: 0.26673 (0.33234) +2025-08-23,10:50:52 | INFO | Train Epoch: 8 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.37739 (0.31793) Boundary_loss: 0.014914 (0.015062) Loss: 0.39231 (0.33300) +2025-08-23,10:51:49 | INFO | Train Epoch: 8 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.28439 (0.31757) Boundary_loss: 0.015105 (0.015062) Loss: 0.29949 (0.33263) +2025-08-23,10:52:45 | INFO | Train Epoch: 8 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.25652 (0.31691) Boundary_loss: 0.014959 (0.015061) Loss: 0.27148 (0.33198) +2025-08-23,10:53:42 | INFO | Train Epoch: 8 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.35848 (0.31736) Boundary_loss: 0.015171 (0.015063) Loss: 0.37365 (0.33242) +2025-08-23,10:54:39 | INFO | Train Epoch: 8 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 49.514 Boundary Ratio: 0.253 Contrastive_loss: 0.33757 (0.31757) Boundary_loss: 0.015055 (0.015062) Loss: 0.35263 (0.33263) +2025-08-23,10:55:36 | INFO | Train Epoch: 8 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.30844 (0.31747) Boundary_loss: 0.015057 (0.015062) Loss: 0.32350 (0.33254) +2025-08-23,10:56:32 | INFO | Train Epoch: 8 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 0.39010 (0.31822) Boundary_loss: 0.014995 (0.015062) Loss: 0.40509 (0.33328) +2025-08-23,10:57:29 | INFO | Train Epoch: 8 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.266 Boundary Ratio: 0.246 Contrastive_loss: 0.32016 (0.31824) Boundary_loss: 0.014885 (0.015060) Loss: 0.33504 (0.33330) +2025-08-23,10:58:26 | INFO | Train Epoch: 8 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.324 Boundary Ratio: 0.252 Contrastive_loss: 0.32347 (0.31829) Boundary_loss: 0.015189 (0.015061) Loss: 0.33866 (0.33336) +2025-08-23,10:59:23 | INFO | Train Epoch: 8 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.28539 (0.31797) Boundary_loss: 0.014961 (0.015060) Loss: 0.30036 (0.33303) +2025-08-23,11:00:19 | INFO | Train Epoch: 8 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.34944 (0.31828) Boundary_loss: 0.015195 (0.015062) Loss: 0.36464 (0.33334) +2025-08-23,11:01:16 | INFO | Train Epoch: 8 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.32530 (0.31835) Boundary_loss: 0.015082 (0.015062) Loss: 0.34038 (0.33341) +2025-08-23,11:02:13 | INFO | Train Epoch: 8 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.22838 (0.31747) Boundary_loss: 0.015078 (0.015062) Loss: 0.24346 (0.33253) +2025-08-23,11:03:09 | INFO | Train Epoch: 8 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.31226 (0.31742) Boundary_loss: 0.015039 (0.015062) Loss: 0.32730 (0.33248) +2025-08-23,11:04:06 | INFO | Train Epoch: 8 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.26572 (0.31693) Boundary_loss: 0.015108 (0.015062) Loss: 0.28083 (0.33199) +2025-08-23,11:05:02 | INFO | Train Epoch: 8 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.25130 (0.31631) Boundary_loss: 0.015030 (0.015062) Loss: 0.26633 (0.33137) +2025-08-23,11:05:59 | INFO | Train Epoch: 8 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.36753 (0.31679) Boundary_loss: 0.015056 (0.015062) Loss: 0.38259 (0.33185) +2025-08-23,11:06:56 | INFO | Train Epoch: 8 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.471 Boundary Ratio: 0.252 Contrastive_loss: 0.35107 (0.31711) Boundary_loss: 0.014981 (0.015061) Loss: 0.36605 (0.33217) +2025-08-23,11:07:52 | INFO | Train Epoch: 8 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 0.39689 (0.31784) Boundary_loss: 0.015113 (0.015061) Loss: 0.41201 (0.33290) +2025-08-23,11:08:49 | INFO | Train Epoch: 8 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.33509 (0.31800) Boundary_loss: 0.015017 (0.015061) Loss: 0.35010 (0.33306) +2025-08-23,11:09:46 | INFO | Train Epoch: 8 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.24947 (0.31738) Boundary_loss: 0.015259 (0.015063) Loss: 0.26472 (0.33244) +2025-08-23,11:10:42 | INFO | Train Epoch: 8 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.29873 (0.31721) Boundary_loss: 0.014948 (0.015062) Loss: 0.31368 (0.33227) +2025-08-23,11:11:39 | INFO | Train Epoch: 8 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.27325 (0.31682) Boundary_loss: 0.014982 (0.015061) Loss: 0.28823 (0.33188) +2025-08-23,11:12:36 | INFO | Train Epoch: 8 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.31895 (0.31684) Boundary_loss: 0.015220 (0.015063) Loss: 0.33417 (0.33190) +2025-08-23,11:13:32 | INFO | Train Epoch: 8 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.31554 (0.31683) Boundary_loss: 0.014976 (0.015062) Loss: 0.33052 (0.33189) +2025-08-23,11:14:29 | INFO | Train Epoch: 8 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.42765 (0.31779) Boundary_loss: 0.015172 (0.015063) Loss: 0.44282 (0.33285) +2025-08-23,11:15:25 | INFO | Train Epoch: 8 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.30915 (0.31771) Boundary_loss: 0.015072 (0.015063) Loss: 0.32422 (0.33277) +2025-08-23,11:16:22 | INFO | Train Epoch: 8 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.34755 (0.31796) Boundary_loss: 0.014968 (0.015062) Loss: 0.36252 (0.33303) +2025-08-23,11:17:18 | INFO | Train Epoch: 8 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.32593 (0.31803) Boundary_loss: 0.015101 (0.015062) Loss: 0.34103 (0.33309) +2025-08-23,11:18:15 | INFO | Train Epoch: 8 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.32686 (0.31811) Boundary_loss: 0.015004 (0.015062) Loss: 0.34186 (0.33317) +2025-08-23,11:19:11 | INFO | Train Epoch: 8 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.30596 (0.31801) Boundary_loss: 0.014935 (0.015061) Loss: 0.32089 (0.33307) +2025-08-23,11:20:08 | INFO | Train Epoch: 8 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.32635 (0.31807) Boundary_loss: 0.015026 (0.015061) Loss: 0.34137 (0.33313) +2025-08-23,11:21:05 | INFO | Train Epoch: 8 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.27364 (0.31771) Boundary_loss: 0.015131 (0.015061) Loss: 0.28877 (0.33277) +2025-08-23,11:22:01 | INFO | Train Epoch: 8 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.30280 (0.31759) Boundary_loss: 0.015031 (0.015061) Loss: 0.31783 (0.33265) +2025-08-23,11:22:58 | INFO | Train Epoch: 8 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.34893 (0.31784) Boundary_loss: 0.015101 (0.015061) Loss: 0.36403 (0.33290) +2025-08-23,11:23:55 | INFO | Train Epoch: 8 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.30285 (0.31772) Boundary_loss: 0.015109 (0.015062) Loss: 0.31796 (0.33279) +2025-08-23,11:24:51 | INFO | Train Epoch: 8 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.262 Boundary Ratio: 0.246 Contrastive_loss: 0.31606 (0.31771) Boundary_loss: 0.015002 (0.015061) Loss: 0.33106 (0.33277) +2025-08-23,11:25:48 | INFO | Train Epoch: 8 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.31033 (0.31765) Boundary_loss: 0.015065 (0.015061) Loss: 0.32540 (0.33271) +2025-08-23,11:26:45 | INFO | Train Epoch: 8 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 49.648 Boundary Ratio: 0.253 Contrastive_loss: 0.25739 (0.31719) Boundary_loss: 0.015158 (0.015062) Loss: 0.27255 (0.33225) +2025-08-23,11:27:41 | INFO | Train Epoch: 8 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.357 Boundary Ratio: 0.252 Contrastive_loss: 0.28174 (0.31691) Boundary_loss: 0.015183 (0.015063) Loss: 0.29693 (0.33198) +2025-08-23,11:28:38 | INFO | Train Epoch: 8 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.28756 (0.31669) Boundary_loss: 0.015268 (0.015064) Loss: 0.30283 (0.33175) +2025-08-23,11:29:35 | INFO | Train Epoch: 8 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.26092 (0.31627) Boundary_loss: 0.014963 (0.015064) Loss: 0.27588 (0.33133) +2025-08-23,11:30:31 | INFO | Train Epoch: 8 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.33484 (0.31641) Boundary_loss: 0.014957 (0.015063) Loss: 0.34980 (0.33147) +2025-08-23,11:31:28 | INFO | Train Epoch: 8 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.26959 (0.31606) Boundary_loss: 0.015066 (0.015063) Loss: 0.28465 (0.33112) +2025-08-23,11:32:24 | INFO | Train Epoch: 8 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.26988 (0.31571) Boundary_loss: 0.015066 (0.015063) Loss: 0.28494 (0.33078) +2025-08-23,11:33:21 | INFO | Train Epoch: 8 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.30923 (0.31567) Boundary_loss: 0.014895 (0.015062) Loss: 0.32412 (0.33073) +2025-08-23,11:34:18 | INFO | Train Epoch: 8 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.27015 (0.31533) Boundary_loss: 0.014945 (0.015061) Loss: 0.28510 (0.33040) +2025-08-23,11:35:14 | INFO | Train Epoch: 8 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.29783 (0.31521) Boundary_loss: 0.015087 (0.015061) Loss: 0.31292 (0.33027) +2025-08-23,11:36:11 | INFO | Train Epoch: 8 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.27963 (0.31495) Boundary_loss: 0.015040 (0.015061) Loss: 0.29467 (0.33001) +2025-08-23,11:37:08 | INFO | Train Epoch: 8 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.30096 (0.31485) Boundary_loss: 0.014972 (0.015060) Loss: 0.31593 (0.32991) +2025-08-23,11:38:04 | INFO | Train Epoch: 8 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.35962 (0.31517) Boundary_loss: 0.015025 (0.015060) Loss: 0.37465 (0.33023) +2025-08-23,11:39:01 | INFO | Train Epoch: 8 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.26125 (0.31479) Boundary_loss: 0.015136 (0.015060) Loss: 0.27639 (0.32985) +2025-08-23,11:39:58 | INFO | Train Epoch: 8 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.33849 (0.31496) Boundary_loss: 0.015168 (0.015061) Loss: 0.35366 (0.33002) +2025-08-23,11:40:54 | INFO | Train Epoch: 8 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.32188 (0.31500) Boundary_loss: 0.015076 (0.015061) Loss: 0.33696 (0.33007) +2025-08-23,11:41:51 | INFO | Train Epoch: 8 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.312 Boundary Ratio: 0.246 Contrastive_loss: 0.35817 (0.31530) Boundary_loss: 0.015124 (0.015062) Loss: 0.37330 (0.33036) +2025-08-23,11:42:48 | INFO | Train Epoch: 8 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.32034 (0.31534) Boundary_loss: 0.015068 (0.015062) Loss: 0.33541 (0.33040) +2025-08-23,11:43:45 | INFO | Train Epoch: 8 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.28293 (0.31512) Boundary_loss: 0.015047 (0.015062) Loss: 0.29797 (0.33018) +2025-08-23,11:44:41 | INFO | Train Epoch: 8 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.32584 (0.31519) Boundary_loss: 0.015087 (0.015062) Loss: 0.34093 (0.33025) +2025-08-23,11:45:38 | INFO | Train Epoch: 8 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.342 Boundary Ratio: 0.252 Contrastive_loss: 0.29252 (0.31504) Boundary_loss: 0.015309 (0.015063) Loss: 0.30783 (0.33010) +2025-08-23,11:46:35 | INFO | Train Epoch: 8 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.23312 (0.31449) Boundary_loss: 0.014938 (0.015063) Loss: 0.24806 (0.32955) +2025-08-23,11:47:32 | INFO | Train Epoch: 8 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 49.381 Boundary Ratio: 0.252 Contrastive_loss: 0.32413 (0.31455) Boundary_loss: 0.015137 (0.015063) Loss: 0.33927 (0.32962) +2025-08-23,11:48:28 | INFO | Train Epoch: 8 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.28092 (0.31433) Boundary_loss: 0.014938 (0.015062) Loss: 0.29586 (0.32939) +2025-08-23,11:49:25 | INFO | Train Epoch: 8 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.28424 (0.31414) Boundary_loss: 0.014978 (0.015062) Loss: 0.29922 (0.32920) +2025-08-23,11:50:22 | INFO | Train Epoch: 8 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.24574 (0.31369) Boundary_loss: 0.014969 (0.015061) Loss: 0.26071 (0.32875) +2025-08-23,11:51:18 | INFO | Train Epoch: 8 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.27335 (0.31343) Boundary_loss: 0.015193 (0.015062) Loss: 0.28855 (0.32849) +2025-08-23,11:52:15 | INFO | Train Epoch: 8 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.37916 (0.31385) Boundary_loss: 0.015119 (0.015062) Loss: 0.39427 (0.32892) +2025-08-23,11:53:11 | INFO | Train Epoch: 8 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.32395 (0.31392) Boundary_loss: 0.015160 (0.015063) Loss: 0.33911 (0.32898) +2025-08-23,11:54:08 | INFO | Train Epoch: 8 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.33066 (0.31402) Boundary_loss: 0.015001 (0.015063) Loss: 0.34566 (0.32909) +2025-08-23,11:55:05 | INFO | Train Epoch: 8 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.29363 (0.31389) Boundary_loss: 0.015028 (0.015062) Loss: 0.30866 (0.32896) +2025-08-23,11:56:01 | INFO | Train Epoch: 8 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.30229 (0.31382) Boundary_loss: 0.015057 (0.015062) Loss: 0.31735 (0.32888) +2025-08-23,11:56:58 | INFO | Train Epoch: 8 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.31368 (0.31382) Boundary_loss: 0.014944 (0.015062) Loss: 0.32862 (0.32888) +2025-08-23,11:57:55 | INFO | Train Epoch: 8 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 47.910 Boundary Ratio: 0.244 Contrastive_loss: 0.26535 (0.31352) Boundary_loss: 0.015016 (0.015061) Loss: 0.28036 (0.32858) +2025-08-23,11:58:51 | INFO | Train Epoch: 8 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.32828 (0.31361) Boundary_loss: 0.015071 (0.015061) Loss: 0.34335 (0.32867) +2025-08-23,11:59:48 | INFO | Train Epoch: 8 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.35907 (0.31389) Boundary_loss: 0.015079 (0.015062) Loss: 0.37414 (0.32895) +2025-08-23,12:00:45 | INFO | Train Epoch: 8 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.27002 (0.31362) Boundary_loss: 0.015042 (0.015061) Loss: 0.28506 (0.32869) +2025-08-23,12:01:41 | INFO | Train Epoch: 8 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.318 Boundary Ratio: 0.252 Contrastive_loss: 0.31467 (0.31363) Boundary_loss: 0.015148 (0.015062) Loss: 0.32981 (0.32869) +2025-08-23,12:02:38 | INFO | Train Epoch: 8 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.29767 (0.31353) Boundary_loss: 0.015147 (0.015062) Loss: 0.31282 (0.32860) +2025-08-23,12:03:35 | INFO | Train Epoch: 8 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.29160 (0.31340) Boundary_loss: 0.015061 (0.015062) Loss: 0.30666 (0.32847) +2025-08-23,12:04:31 | INFO | Train Epoch: 8 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.28189 (0.31322) Boundary_loss: 0.015023 (0.015062) Loss: 0.29691 (0.32828) +2025-08-23,12:05:28 | INFO | Train Epoch: 8 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.33250 (0.31333) Boundary_loss: 0.015095 (0.015062) Loss: 0.34759 (0.32839) +2025-08-23,12:06:25 | INFO | Train Epoch: 8 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.389 Boundary Ratio: 0.247 Contrastive_loss: 0.31495 (0.31334) Boundary_loss: 0.015026 (0.015062) Loss: 0.32998 (0.32840) +2025-08-23,12:07:22 | INFO | Train Epoch: 8 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.23955 (0.31291) Boundary_loss: 0.015249 (0.015063) Loss: 0.25480 (0.32797) +2025-08-23,12:08:18 | INFO | Train Epoch: 8 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.30155 (0.31285) Boundary_loss: 0.014975 (0.015063) Loss: 0.31652 (0.32791) +2025-08-23,12:09:15 | INFO | Train Epoch: 8 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.25247 (0.31250) Boundary_loss: 0.015058 (0.015063) Loss: 0.26752 (0.32756) +2025-08-23,12:10:12 | INFO | Train Epoch: 8 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.26217 (0.31221) Boundary_loss: 0.015149 (0.015063) Loss: 0.27732 (0.32727) +2025-08-23,12:11:09 | INFO | Train Epoch: 8 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.33823 (0.31236) Boundary_loss: 0.015065 (0.015063) Loss: 0.35329 (0.32742) +2025-08-23,12:12:05 | INFO | Train Epoch: 8 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.31036 (0.31235) Boundary_loss: 0.015108 (0.015063) Loss: 0.32546 (0.32741) +2025-08-23,12:13:02 | INFO | Train Epoch: 8 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.29695 (0.31226) Boundary_loss: 0.015014 (0.015063) Loss: 0.31196 (0.32732) +2025-08-23,12:13:59 | INFO | Train Epoch: 8 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.28409 (0.31210) Boundary_loss: 0.015123 (0.015064) Loss: 0.29922 (0.32717) +2025-08-23,12:14:55 | INFO | Train Epoch: 8 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.24530 (0.31173) Boundary_loss: 0.014969 (0.015063) Loss: 0.26027 (0.32680) +2025-08-23,12:15:52 | INFO | Train Epoch: 8 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.30622 (0.31170) Boundary_loss: 0.015081 (0.015063) Loss: 0.32130 (0.32677) +2025-08-23,12:16:49 | INFO | Train Epoch: 8 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 0.26996 (0.31147) Boundary_loss: 0.014992 (0.015063) Loss: 0.28495 (0.32654) +2025-08-23,12:17:46 | INFO | Train Epoch: 8 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.30315 (0.31143) Boundary_loss: 0.014985 (0.015062) Loss: 0.31813 (0.32649) +2025-08-23,12:18:42 | INFO | Train Epoch: 8 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 0.37649 (0.31178) Boundary_loss: 0.015163 (0.015063) Loss: 0.39165 (0.32684) +2025-08-23,12:19:39 | INFO | Train Epoch: 8 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.37341 (0.31211) Boundary_loss: 0.014898 (0.015062) Loss: 0.38830 (0.32718) +2025-08-23,12:20:36 | INFO | Train Epoch: 8 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.012 Boundary Ratio: 0.245 Contrastive_loss: 0.29775 (0.31204) Boundary_loss: 0.015019 (0.015062) Loss: 0.31277 (0.32710) +2025-08-23,12:21:33 | INFO | Train Epoch: 8 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.23924 (0.31165) Boundary_loss: 0.015024 (0.015062) Loss: 0.25426 (0.32671) +2025-08-23,12:22:29 | INFO | Train Epoch: 8 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.30765 (0.31163) Boundary_loss: 0.015058 (0.015061) Loss: 0.32270 (0.32669) +2025-08-23,12:23:26 | INFO | Train Epoch: 8 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.24227 (0.31126) Boundary_loss: 0.015072 (0.015062) Loss: 0.25734 (0.32632) +2025-08-23,12:24:23 | INFO | Train Epoch: 8 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.35679 (0.31150) Boundary_loss: 0.015047 (0.015061) Loss: 0.37183 (0.32656) +2025-08-23,12:25:19 | INFO | Train Epoch: 8 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.26481 (0.31125) Boundary_loss: 0.015170 (0.015062) Loss: 0.27998 (0.32632) +2025-08-23,12:26:16 | INFO | Train Epoch: 8 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.33271 (0.31137) Boundary_loss: 0.014974 (0.015062) Loss: 0.34768 (0.32643) +2025-08-23,12:27:12 | INFO | Train Epoch: 8 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 47.891 Boundary Ratio: 0.244 Contrastive_loss: 0.32309 (0.31143) Boundary_loss: 0.015115 (0.015062) Loss: 0.33821 (0.32649) +2025-08-23,12:28:09 | INFO | Train Epoch: 8 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.246 Boundary Ratio: 0.246 Contrastive_loss: 0.21188 (0.31091) Boundary_loss: 0.014982 (0.015061) Loss: 0.22687 (0.32598) +2025-08-23,12:29:06 | INFO | Train Epoch: 8 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.23016 (0.31050) Boundary_loss: 0.014938 (0.015061) Loss: 0.24509 (0.32556) +2025-08-23,12:30:02 | INFO | Train Epoch: 8 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.34383 (0.31067) Boundary_loss: 0.015046 (0.015061) Loss: 0.35888 (0.32573) +2025-08-23,12:30:59 | INFO | Train Epoch: 8 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.207 Boundary Ratio: 0.246 Contrastive_loss: 0.31635 (0.31070) Boundary_loss: 0.014957 (0.015060) Loss: 0.33131 (0.32576) +2025-08-23,12:31:55 | INFO | Train Epoch: 8 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.26047 (0.31044) Boundary_loss: 0.015159 (0.015061) Loss: 0.27563 (0.32551) +2025-08-23,12:32:52 | INFO | Train Epoch: 8 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.20943 (0.30994) Boundary_loss: 0.015130 (0.015061) Loss: 0.22456 (0.32500) +2025-08-23,12:33:48 | INFO | Train Epoch: 8 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.28803 (0.30983) Boundary_loss: 0.015228 (0.015062) Loss: 0.30326 (0.32489) +2025-08-23,12:34:45 | INFO | Train Epoch: 8 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.309 Boundary Ratio: 0.252 Contrastive_loss: 0.35268 (0.31004) Boundary_loss: 0.014991 (0.015062) Loss: 0.36767 (0.32510) +2025-08-23,12:35:41 | INFO | Train Epoch: 8 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.30901 (0.31004) Boundary_loss: 0.014989 (0.015061) Loss: 0.32399 (0.32510) +2025-08-23,12:36:38 | INFO | Train Epoch: 8 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.381 Boundary Ratio: 0.252 Contrastive_loss: 0.38696 (0.31041) Boundary_loss: 0.014981 (0.015061) Loss: 0.40194 (0.32548) +2025-08-23,12:37:35 | INFO | Train Epoch: 8 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.26606 (0.31020) Boundary_loss: 0.014995 (0.015060) Loss: 0.28105 (0.32526) +2025-08-23,12:38:31 | INFO | Train Epoch: 8 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.28226 (0.31006) Boundary_loss: 0.014927 (0.015060) Loss: 0.29719 (0.32512) +2025-08-23,12:39:28 | INFO | Train Epoch: 8 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.28115 (0.30992) Boundary_loss: 0.015092 (0.015060) Loss: 0.29624 (0.32498) +2025-08-23,12:40:25 | INFO | Train Epoch: 8 [10547712/26365952 (40%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 0.33368 (0.31004) Boundary_loss: 0.014927 (0.015059) Loss: 0.34861 (0.32509) +2025-08-23,12:41:21 | INFO | Train Epoch: 8 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.31762 (0.31007) Boundary_loss: 0.015072 (0.015059) Loss: 0.33269 (0.32513) +2025-08-23,12:42:18 | INFO | Train Epoch: 8 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.31142 (0.31008) Boundary_loss: 0.015052 (0.015059) Loss: 0.32647 (0.32514) +2025-08-23,12:43:15 | INFO | Train Epoch: 8 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.24357 (0.30976) Boundary_loss: 0.014986 (0.015059) Loss: 0.25856 (0.32482) +2025-08-23,12:44:12 | INFO | Train Epoch: 8 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.348 Boundary Ratio: 0.252 Contrastive_loss: 0.33305 (0.30987) Boundary_loss: 0.015033 (0.015059) Loss: 0.34809 (0.32493) +2025-08-23,12:45:08 | INFO | Train Epoch: 8 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.33178 (0.30998) Boundary_loss: 0.015026 (0.015059) Loss: 0.34680 (0.32503) +2025-08-23,12:46:05 | INFO | Train Epoch: 8 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.24538 (0.30967) Boundary_loss: 0.015087 (0.015059) Loss: 0.26047 (0.32473) +2025-08-23,12:47:01 | INFO | Train Epoch: 8 [10906112/26365952 (41%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.29057 (0.30958) Boundary_loss: 0.015000 (0.015059) Loss: 0.30557 (0.32464) +2025-08-23,12:47:58 | INFO | Train Epoch: 8 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.170 Boundary Ratio: 0.246 Contrastive_loss: 0.33054 (0.30968) Boundary_loss: 0.015021 (0.015058) Loss: 0.34556 (0.32474) +2025-08-23,12:48:55 | INFO | Train Epoch: 8 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.32121 (0.30973) Boundary_loss: 0.015068 (0.015058) Loss: 0.33628 (0.32479) +2025-08-23,12:49:51 | INFO | Train Epoch: 8 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.29705 (0.30968) Boundary_loss: 0.015075 (0.015059) Loss: 0.31212 (0.32473) +2025-08-23,12:50:48 | INFO | Train Epoch: 8 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.32234 (0.30973) Boundary_loss: 0.015187 (0.015059) Loss: 0.33753 (0.32479) +2025-08-23,12:51:45 | INFO | Train Epoch: 8 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.32129 (0.30979) Boundary_loss: 0.015090 (0.015059) Loss: 0.33638 (0.32485) +2025-08-23,12:52:41 | INFO | Train Epoch: 8 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.31830 (0.30982) Boundary_loss: 0.014983 (0.015059) Loss: 0.33328 (0.32488) +2025-08-23,12:53:38 | INFO | Train Epoch: 8 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.230 Boundary Ratio: 0.246 Contrastive_loss: 0.30396 (0.30980) Boundary_loss: 0.015013 (0.015059) Loss: 0.31897 (0.32486) +2025-08-23,12:54:34 | INFO | Train Epoch: 8 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.20303 (0.30932) Boundary_loss: 0.014954 (0.015058) Loss: 0.21798 (0.32438) +2025-08-23,12:55:31 | INFO | Train Epoch: 8 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 0.28900 (0.30923) Boundary_loss: 0.015011 (0.015058) Loss: 0.30401 (0.32428) +2025-08-23,12:56:28 | INFO | Train Epoch: 8 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.332 Boundary Ratio: 0.247 Contrastive_loss: 0.23153 (0.30888) Boundary_loss: 0.014984 (0.015058) Loss: 0.24651 (0.32394) +2025-08-23,12:57:24 | INFO | Train Epoch: 8 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.30624 (0.30887) Boundary_loss: 0.015028 (0.015058) Loss: 0.32126 (0.32393) +2025-08-23,12:58:21 | INFO | Train Epoch: 8 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.34696 (0.30904) Boundary_loss: 0.014903 (0.015057) Loss: 0.36186 (0.32409) +2025-08-23,12:59:18 | INFO | Train Epoch: 8 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.33721 (0.30916) Boundary_loss: 0.015161 (0.015057) Loss: 0.35237 (0.32422) +2025-08-23,13:00:14 | INFO | Train Epoch: 8 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.36173 (0.30939) Boundary_loss: 0.014995 (0.015057) Loss: 0.37672 (0.32445) +2025-08-23,13:01:11 | INFO | Train Epoch: 8 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.26364 (0.30919) Boundary_loss: 0.014996 (0.015057) Loss: 0.27864 (0.32425) +2025-08-23,13:02:08 | INFO | Train Epoch: 8 [11725312/26365952 (44%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.30133 (0.30916) Boundary_loss: 0.014947 (0.015056) Loss: 0.31628 (0.32421) +2025-08-23,13:03:04 | INFO | Train Epoch: 8 [11776512/26365952 (45%)] Avg Boundaries (per batch): 49.549 Boundary Ratio: 0.253 Contrastive_loss: 0.32439 (0.30922) Boundary_loss: 0.015006 (0.015056) Loss: 0.33940 (0.32428) +2025-08-23,13:04:01 | INFO | Train Epoch: 8 [11827712/26365952 (45%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.30539 (0.30921) Boundary_loss: 0.014918 (0.015056) Loss: 0.32030 (0.32426) +2025-08-23,13:04:58 | INFO | Train Epoch: 8 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.31032 (0.30921) Boundary_loss: 0.015064 (0.015056) Loss: 0.32539 (0.32427) +2025-08-23,13:05:54 | INFO | Train Epoch: 8 [11930112/26365952 (45%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.23101 (0.30888) Boundary_loss: 0.014924 (0.015055) Loss: 0.24594 (0.32393) +2025-08-23,13:06:51 | INFO | Train Epoch: 8 [11981312/26365952 (45%)] Avg Boundaries (per batch): 49.568 Boundary Ratio: 0.253 Contrastive_loss: 0.32169 (0.30893) Boundary_loss: 0.014964 (0.015055) Loss: 0.33666 (0.32399) +2025-08-23,13:07:48 | INFO | Train Epoch: 8 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.29895 (0.30889) Boundary_loss: 0.015084 (0.015055) Loss: 0.31403 (0.32394) +2025-08-23,13:08:44 | INFO | Train Epoch: 8 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.22734 (0.30855) Boundary_loss: 0.014919 (0.015054) Loss: 0.24226 (0.32360) +2025-08-23,13:09:41 | INFO | Train Epoch: 8 [12134912/26365952 (46%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.25341 (0.30831) Boundary_loss: 0.014943 (0.015054) Loss: 0.26836 (0.32337) +2025-08-23,13:10:38 | INFO | Train Epoch: 8 [12186112/26365952 (46%)] Avg Boundaries (per batch): 49.221 Boundary Ratio: 0.251 Contrastive_loss: 0.33023 (0.30841) Boundary_loss: 0.015031 (0.015054) Loss: 0.34526 (0.32346) +2025-08-23,13:11:34 | INFO | Train Epoch: 8 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.32355 (0.30847) Boundary_loss: 0.015183 (0.015054) Loss: 0.33874 (0.32352) +2025-08-23,13:12:31 | INFO | Train Epoch: 8 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.28465 (0.30837) Boundary_loss: 0.015016 (0.015054) Loss: 0.29967 (0.32342) +2025-08-23,13:13:28 | INFO | Train Epoch: 8 [12339712/26365952 (47%)] Avg Boundaries (per batch): 47.828 Boundary Ratio: 0.244 Contrastive_loss: 0.28284 (0.30826) Boundary_loss: 0.015091 (0.015054) Loss: 0.29793 (0.32332) +2025-08-23,13:14:25 | INFO | Train Epoch: 8 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.32670 (0.30834) Boundary_loss: 0.014975 (0.015054) Loss: 0.34168 (0.32339) +2025-08-23,13:15:21 | INFO | Train Epoch: 8 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.26911 (0.30818) Boundary_loss: 0.015185 (0.015054) Loss: 0.28429 (0.32323) +2025-08-23,13:16:18 | INFO | Train Epoch: 8 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.32382 (0.30824) Boundary_loss: 0.015030 (0.015054) Loss: 0.33885 (0.32330) +2025-08-23,13:17:15 | INFO | Train Epoch: 8 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.23937 (0.30796) Boundary_loss: 0.015066 (0.015054) Loss: 0.25444 (0.32302) +2025-08-23,13:18:11 | INFO | Train Epoch: 8 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.29926 (0.30793) Boundary_loss: 0.014979 (0.015054) Loss: 0.31424 (0.32298) +2025-08-23,13:19:08 | INFO | Train Epoch: 8 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 0.31266 (0.30795) Boundary_loss: 0.015038 (0.015054) Loss: 0.32770 (0.32300) +2025-08-23,13:20:05 | INFO | Train Epoch: 8 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.29943 (0.30791) Boundary_loss: 0.015103 (0.015054) Loss: 0.31453 (0.32297) +2025-08-23,13:21:02 | INFO | Train Epoch: 8 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.29251 (0.30785) Boundary_loss: 0.015094 (0.015054) Loss: 0.30761 (0.32291) +2025-08-23,13:21:58 | INFO | Train Epoch: 8 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.31311 (0.30787) Boundary_loss: 0.015009 (0.015054) Loss: 0.32812 (0.32293) +2025-08-23,13:22:55 | INFO | Train Epoch: 8 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.240 Boundary Ratio: 0.246 Contrastive_loss: 0.35254 (0.30805) Boundary_loss: 0.015093 (0.015054) Loss: 0.36763 (0.32310) +2025-08-23,13:23:52 | INFO | Train Epoch: 8 [12902912/26365952 (49%)] Avg Boundaries (per batch): 47.949 Boundary Ratio: 0.245 Contrastive_loss: 0.22282 (0.30771) Boundary_loss: 0.015137 (0.015055) Loss: 0.23796 (0.32277) +2025-08-23,13:24:48 | INFO | Train Epoch: 8 [12954112/26365952 (49%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 0.27276 (0.30757) Boundary_loss: 0.015015 (0.015054) Loss: 0.28778 (0.32263) +2025-08-23,13:25:45 | INFO | Train Epoch: 8 [13005312/26365952 (49%)] Avg Boundaries (per batch): 49.305 Boundary Ratio: 0.252 Contrastive_loss: 0.29815 (0.30754) Boundary_loss: 0.015061 (0.015054) Loss: 0.31321 (0.32259) +2025-08-23,13:26:41 | INFO | Train Epoch: 8 [13056512/26365952 (50%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 0.30701 (0.30754) Boundary_loss: 0.015086 (0.015055) Loss: 0.32210 (0.32259) +2025-08-23,13:27:38 | INFO | Train Epoch: 8 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.31042 (0.30755) Boundary_loss: 0.014897 (0.015054) Loss: 0.32532 (0.32260) +2025-08-23,13:28:35 | INFO | Train Epoch: 8 [13158912/26365952 (50%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.26163 (0.30737) Boundary_loss: 0.015056 (0.015054) Loss: 0.27669 (0.32242) +2025-08-23,13:29:31 | INFO | Train Epoch: 8 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.31432 (0.30740) Boundary_loss: 0.014987 (0.015054) Loss: 0.32931 (0.32245) +2025-08-23,13:30:28 | INFO | Train Epoch: 8 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.33279 (0.30749) Boundary_loss: 0.015085 (0.015054) Loss: 0.34787 (0.32255) +2025-08-23,13:31:25 | INFO | Train Epoch: 8 [13312512/26365952 (50%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.33020 (0.30758) Boundary_loss: 0.015088 (0.015054) Loss: 0.34529 (0.32263) +2025-08-23,13:32:21 | INFO | Train Epoch: 8 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.27949 (0.30747) Boundary_loss: 0.014927 (0.015053) Loss: 0.29441 (0.32253) +2025-08-23,13:33:18 | INFO | Train Epoch: 8 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.30527 (0.30746) Boundary_loss: 0.015103 (0.015054) Loss: 0.32038 (0.32252) +2025-08-23,13:34:14 | INFO | Train Epoch: 8 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.30586 (0.30746) Boundary_loss: 0.015039 (0.015054) Loss: 0.32090 (0.32251) +2025-08-23,13:35:11 | INFO | Train Epoch: 8 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.30048 (0.30743) Boundary_loss: 0.015114 (0.015054) Loss: 0.31560 (0.32249) +2025-08-23,13:36:08 | INFO | Train Epoch: 8 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.438 Boundary Ratio: 0.247 Contrastive_loss: 0.26651 (0.30728) Boundary_loss: 0.015130 (0.015054) Loss: 0.28164 (0.32233) +2025-08-23,13:37:05 | INFO | Train Epoch: 8 [13619712/26365952 (52%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 0.24493 (0.30704) Boundary_loss: 0.015108 (0.015054) Loss: 0.26004 (0.32210) +2025-08-23,13:38:01 | INFO | Train Epoch: 8 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.25990 (0.30687) Boundary_loss: 0.015020 (0.015054) Loss: 0.27492 (0.32192) +2025-08-23,13:38:58 | INFO | Train Epoch: 8 [13722112/26365952 (52%)] Avg Boundaries (per batch): 47.973 Boundary Ratio: 0.245 Contrastive_loss: 0.24390 (0.30663) Boundary_loss: 0.015105 (0.015054) Loss: 0.25900 (0.32169) +2025-08-23,13:39:55 | INFO | Train Epoch: 8 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.35243 (0.30680) Boundary_loss: 0.015163 (0.015055) Loss: 0.36759 (0.32186) +2025-08-23,13:40:51 | INFO | Train Epoch: 8 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.172 Boundary Ratio: 0.246 Contrastive_loss: 0.32175 (0.30686) Boundary_loss: 0.015042 (0.015055) Loss: 0.33680 (0.32191) +2025-08-23,13:41:48 | INFO | Train Epoch: 8 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.30978 (0.30687) Boundary_loss: 0.015126 (0.015055) Loss: 0.32491 (0.32193) +2025-08-23,13:42:45 | INFO | Train Epoch: 8 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.326 Boundary Ratio: 0.247 Contrastive_loss: 0.28977 (0.30681) Boundary_loss: 0.014927 (0.015055) Loss: 0.30469 (0.32186) +2025-08-23,13:43:41 | INFO | Train Epoch: 8 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.174 Boundary Ratio: 0.246 Contrastive_loss: 0.23298 (0.30654) Boundary_loss: 0.015131 (0.015055) Loss: 0.24811 (0.32159) +2025-08-23,13:44:38 | INFO | Train Epoch: 8 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.40351 (0.30689) Boundary_loss: 0.014876 (0.015054) Loss: 0.41838 (0.32195) +2025-08-23,13:45:35 | INFO | Train Epoch: 8 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.164 Boundary Ratio: 0.246 Contrastive_loss: 0.27517 (0.30678) Boundary_loss: 0.015071 (0.015054) Loss: 0.29024 (0.32183) +2025-08-23,13:46:31 | INFO | Train Epoch: 8 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.29457 (0.30673) Boundary_loss: 0.015058 (0.015054) Loss: 0.30962 (0.32179) +2025-08-23,13:47:28 | INFO | Train Epoch: 8 [14182912/26365952 (54%)] Avg Boundaries (per batch): 49.357 Boundary Ratio: 0.252 Contrastive_loss: 0.29769 (0.30670) Boundary_loss: 0.015103 (0.015054) Loss: 0.31279 (0.32175) +2025-08-23,13:48:24 | INFO | Train Epoch: 8 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.32271 (0.30676) Boundary_loss: 0.014979 (0.015054) Loss: 0.33769 (0.32181) +2025-08-23,13:49:20 | INFO | Train Epoch: 8 [14285312/26365952 (54%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.26844 (0.30662) Boundary_loss: 0.014863 (0.015053) Loss: 0.28330 (0.32167) +2025-08-23,13:50:17 | INFO | Train Epoch: 8 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.021 Boundary Ratio: 0.245 Contrastive_loss: 0.34118 (0.30674) Boundary_loss: 0.015042 (0.015053) Loss: 0.35622 (0.32180) +2025-08-23,13:51:13 | INFO | Train Epoch: 8 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 0.26745 (0.30660) Boundary_loss: 0.014960 (0.015053) Loss: 0.28241 (0.32166) +2025-08-23,13:52:10 | INFO | Train Epoch: 8 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.117 Boundary Ratio: 0.245 Contrastive_loss: 0.24017 (0.30637) Boundary_loss: 0.015014 (0.015053) Loss: 0.25518 (0.32142) +2025-08-23,13:53:07 | INFO | Train Epoch: 8 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.27675 (0.30626) Boundary_loss: 0.014923 (0.015052) Loss: 0.29167 (0.32132) +2025-08-23,13:54:03 | INFO | Train Epoch: 8 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.30005 (0.30624) Boundary_loss: 0.015083 (0.015053) Loss: 0.31513 (0.32130) +2025-08-23,13:55:00 | INFO | Train Epoch: 8 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.30611 (0.30624) Boundary_loss: 0.014984 (0.015052) Loss: 0.32109 (0.32129) +2025-08-23,13:55:56 | INFO | Train Epoch: 8 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.357 Boundary Ratio: 0.252 Contrastive_loss: 0.32162 (0.30630) Boundary_loss: 0.015001 (0.015052) Loss: 0.33662 (0.32135) +2025-08-23,13:56:53 | INFO | Train Epoch: 8 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.26401 (0.30615) Boundary_loss: 0.015141 (0.015052) Loss: 0.27915 (0.32120) +2025-08-23,13:57:50 | INFO | Train Epoch: 8 [14746112/26365952 (56%)] Avg Boundaries (per batch): 49.553 Boundary Ratio: 0.253 Contrastive_loss: 0.25926 (0.30599) Boundary_loss: 0.015058 (0.015052) Loss: 0.27431 (0.32104) +2025-08-23,13:58:46 | INFO | Train Epoch: 8 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.29393 (0.30595) Boundary_loss: 0.015016 (0.015052) Loss: 0.30895 (0.32100) +2025-08-23,13:59:43 | INFO | Train Epoch: 8 [14848512/26365952 (56%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.35505 (0.30611) Boundary_loss: 0.015006 (0.015052) Loss: 0.37006 (0.32117) +2025-08-23,14:00:39 | INFO | Train Epoch: 8 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.37766 (0.30636) Boundary_loss: 0.015067 (0.015052) Loss: 0.39273 (0.32141) +2025-08-23,14:01:36 | INFO | Train Epoch: 8 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.33679 (0.30646) Boundary_loss: 0.015068 (0.015052) Loss: 0.35186 (0.32152) +2025-08-23,14:02:32 | INFO | Train Epoch: 8 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.34772 (0.30660) Boundary_loss: 0.014991 (0.015052) Loss: 0.36271 (0.32166) +2025-08-23,14:03:29 | INFO | Train Epoch: 8 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.35734 (0.30678) Boundary_loss: 0.014955 (0.015052) Loss: 0.37230 (0.32183) +2025-08-23,14:04:25 | INFO | Train Epoch: 8 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.27108 (0.30665) Boundary_loss: 0.015075 (0.015052) Loss: 0.28616 (0.32171) +2025-08-23,14:05:22 | INFO | Train Epoch: 8 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.32254 (0.30671) Boundary_loss: 0.015094 (0.015052) Loss: 0.33764 (0.32176) +2025-08-23,14:06:18 | INFO | Train Epoch: 8 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.30981 (0.30672) Boundary_loss: 0.014981 (0.015052) Loss: 0.32479 (0.32177) +2025-08-23,14:07:15 | INFO | Train Epoch: 8 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.31628 (0.30675) Boundary_loss: 0.015082 (0.015052) Loss: 0.33136 (0.32180) +2025-08-23,14:08:12 | INFO | Train Epoch: 8 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.25024 (0.30656) Boundary_loss: 0.015004 (0.015052) Loss: 0.26524 (0.32161) +2025-08-23,14:09:08 | INFO | Train Epoch: 8 [15360512/26365952 (58%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.28651 (0.30650) Boundary_loss: 0.015056 (0.015052) Loss: 0.30156 (0.32155) +2025-08-23,14:10:05 | INFO | Train Epoch: 8 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.36167 (0.30668) Boundary_loss: 0.015116 (0.015052) Loss: 0.37678 (0.32173) +2025-08-23,14:11:01 | INFO | Train Epoch: 8 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.166 Boundary Ratio: 0.246 Contrastive_loss: 0.30832 (0.30668) Boundary_loss: 0.015066 (0.015052) Loss: 0.32338 (0.32174) +2025-08-23,14:11:58 | INFO | Train Epoch: 8 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.30249 (0.30667) Boundary_loss: 0.015079 (0.015052) Loss: 0.31757 (0.32172) +2025-08-23,14:12:54 | INFO | Train Epoch: 8 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.25764 (0.30651) Boundary_loss: 0.014929 (0.015052) Loss: 0.27257 (0.32156) +2025-08-23,14:13:51 | INFO | Train Epoch: 8 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.25448 (0.30634) Boundary_loss: 0.015120 (0.015052) Loss: 0.26960 (0.32139) +2025-08-23,14:14:48 | INFO | Train Epoch: 8 [15667712/26365952 (59%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 0.30739 (0.30634) Boundary_loss: 0.014921 (0.015051) Loss: 0.32231 (0.32139) +2025-08-23,14:15:44 | INFO | Train Epoch: 8 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.25950 (0.30619) Boundary_loss: 0.014983 (0.015051) Loss: 0.27448 (0.32124) +2025-08-23,14:16:41 | INFO | Train Epoch: 8 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.369 Boundary Ratio: 0.247 Contrastive_loss: 0.27211 (0.30608) Boundary_loss: 0.014950 (0.015051) Loss: 0.28706 (0.32113) +2025-08-23,14:17:38 | INFO | Train Epoch: 8 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.30574 (0.30608) Boundary_loss: 0.014976 (0.015051) Loss: 0.32071 (0.32113) +2025-08-23,14:18:34 | INFO | Train Epoch: 8 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.27539 (0.30598) Boundary_loss: 0.015046 (0.015051) Loss: 0.29043 (0.32103) +2025-08-23,14:19:31 | INFO | Train Epoch: 8 [15923712/26365952 (60%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.23591 (0.30576) Boundary_loss: 0.015043 (0.015051) Loss: 0.25095 (0.32081) +2025-08-23,14:20:27 | INFO | Train Epoch: 8 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.393 Boundary Ratio: 0.247 Contrastive_loss: 0.41039 (0.30609) Boundary_loss: 0.015065 (0.015051) Loss: 0.42545 (0.32114) +2025-08-23,14:21:24 | INFO | Train Epoch: 8 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.346 Boundary Ratio: 0.247 Contrastive_loss: 0.28113 (0.30601) Boundary_loss: 0.015011 (0.015051) Loss: 0.29614 (0.32106) +2025-08-23,14:22:20 | INFO | Train Epoch: 8 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.387 Boundary Ratio: 0.247 Contrastive_loss: 0.32496 (0.30607) Boundary_loss: 0.015028 (0.015050) Loss: 0.33999 (0.32112) +2025-08-23,14:23:17 | INFO | Train Epoch: 8 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.28029 (0.30599) Boundary_loss: 0.015018 (0.015050) Loss: 0.29531 (0.32104) +2025-08-23,14:24:14 | INFO | Train Epoch: 8 [16179712/26365952 (61%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.33061 (0.30607) Boundary_loss: 0.014942 (0.015050) Loss: 0.34555 (0.32112) +2025-08-23,14:25:10 | INFO | Train Epoch: 8 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.29471 (0.30603) Boundary_loss: 0.015040 (0.015050) Loss: 0.30975 (0.32108) +2025-08-23,14:26:07 | INFO | Train Epoch: 8 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.33690 (0.30613) Boundary_loss: 0.014837 (0.015049) Loss: 0.35174 (0.32118) +2025-08-23,14:27:04 | INFO | Train Epoch: 8 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.32348 (0.30618) Boundary_loss: 0.015020 (0.015049) Loss: 0.33850 (0.32123) +2025-08-23,14:28:00 | INFO | Train Epoch: 8 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.27247 (0.30608) Boundary_loss: 0.015081 (0.015049) Loss: 0.28755 (0.32113) +2025-08-23,14:28:57 | INFO | Train Epoch: 8 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.29945 (0.30606) Boundary_loss: 0.015043 (0.015049) Loss: 0.31449 (0.32111) +2025-08-23,14:29:53 | INFO | Train Epoch: 8 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.322 Boundary Ratio: 0.252 Contrastive_loss: 0.33535 (0.30615) Boundary_loss: 0.015068 (0.015049) Loss: 0.35041 (0.32120) +2025-08-23,14:30:50 | INFO | Train Epoch: 8 [16538112/26365952 (63%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 0.25548 (0.30599) Boundary_loss: 0.015140 (0.015050) Loss: 0.27062 (0.32104) +2025-08-23,14:31:46 | INFO | Train Epoch: 8 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.25800 (0.30584) Boundary_loss: 0.015009 (0.015050) Loss: 0.27301 (0.32089) +2025-08-23,14:32:43 | INFO | Train Epoch: 8 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.578 Boundary Ratio: 0.253 Contrastive_loss: 0.28194 (0.30577) Boundary_loss: 0.015049 (0.015050) Loss: 0.29699 (0.32082) +2025-08-23,14:33:39 | INFO | Train Epoch: 8 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.28237 (0.30570) Boundary_loss: 0.015093 (0.015050) Loss: 0.29746 (0.32075) +2025-08-23,14:34:36 | INFO | Train Epoch: 8 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.24469 (0.30551) Boundary_loss: 0.014920 (0.015049) Loss: 0.25961 (0.32056) +2025-08-23,14:35:33 | INFO | Train Epoch: 8 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.23208 (0.30529) Boundary_loss: 0.015037 (0.015049) Loss: 0.24711 (0.32034) +2025-08-23,14:36:29 | INFO | Train Epoch: 8 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.182 Boundary Ratio: 0.246 Contrastive_loss: 0.28057 (0.30521) Boundary_loss: 0.014994 (0.015049) Loss: 0.29557 (0.32026) +2025-08-23,14:37:26 | INFO | Train Epoch: 8 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.336 Boundary Ratio: 0.247 Contrastive_loss: 0.37269 (0.30542) Boundary_loss: 0.015029 (0.015049) Loss: 0.38772 (0.32047) +2025-08-23,14:38:22 | INFO | Train Epoch: 8 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.27739 (0.30533) Boundary_loss: 0.014896 (0.015049) Loss: 0.29229 (0.32038) +2025-08-23,14:39:19 | INFO | Train Epoch: 8 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.21117 (0.30505) Boundary_loss: 0.014944 (0.015048) Loss: 0.22611 (0.32010) +2025-08-23,14:40:15 | INFO | Train Epoch: 8 [17050112/26365952 (65%)] Avg Boundaries (per batch): 49.160 Boundary Ratio: 0.251 Contrastive_loss: 0.29339 (0.30502) Boundary_loss: 0.014926 (0.015048) Loss: 0.30832 (0.32006) +2025-08-23,14:41:12 | INFO | Train Epoch: 8 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.32435 (0.30507) Boundary_loss: 0.014920 (0.015047) Loss: 0.33928 (0.32012) +2025-08-23,14:42:09 | INFO | Train Epoch: 8 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.346 Boundary Ratio: 0.247 Contrastive_loss: 0.26698 (0.30496) Boundary_loss: 0.015012 (0.015047) Loss: 0.28199 (0.32001) +2025-08-23,14:43:05 | INFO | Train Epoch: 8 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.30069 (0.30495) Boundary_loss: 0.014905 (0.015047) Loss: 0.31559 (0.31999) +2025-08-23,14:44:02 | INFO | Train Epoch: 8 [17254912/26365952 (65%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.27854 (0.30487) Boundary_loss: 0.014958 (0.015047) Loss: 0.29350 (0.31992) +2025-08-23,14:44:58 | INFO | Train Epoch: 8 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.369 Boundary Ratio: 0.252 Contrastive_loss: 0.28644 (0.30481) Boundary_loss: 0.015016 (0.015047) Loss: 0.30146 (0.31986) +2025-08-23,14:45:55 | INFO | Train Epoch: 8 [17357312/26365952 (66%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.30281 (0.30481) Boundary_loss: 0.015003 (0.015046) Loss: 0.31782 (0.31986) +2025-08-23,14:46:51 | INFO | Train Epoch: 8 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.25337 (0.30466) Boundary_loss: 0.014964 (0.015046) Loss: 0.26834 (0.31970) +2025-08-23,14:47:48 | INFO | Train Epoch: 8 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 0.27096 (0.30456) Boundary_loss: 0.014924 (0.015046) Loss: 0.28588 (0.31961) +2025-08-23,14:48:45 | INFO | Train Epoch: 8 [17510912/26365952 (66%)] Avg Boundaries (per batch): 49.373 Boundary Ratio: 0.252 Contrastive_loss: 0.36264 (0.30473) Boundary_loss: 0.015065 (0.015046) Loss: 0.37771 (0.31977) +2025-08-23,14:49:41 | INFO | Train Epoch: 8 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.35101 (0.30486) Boundary_loss: 0.014965 (0.015046) Loss: 0.36597 (0.31991) +2025-08-23,14:50:38 | INFO | Train Epoch: 8 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.36542 (0.30504) Boundary_loss: 0.015080 (0.015046) Loss: 0.38049 (0.32008) +2025-08-23,14:51:34 | INFO | Train Epoch: 8 [17664512/26365952 (67%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.36570 (0.30521) Boundary_loss: 0.015120 (0.015046) Loss: 0.38082 (0.32026) +2025-08-23,14:52:31 | INFO | Train Epoch: 8 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 0.25255 (0.30506) Boundary_loss: 0.014992 (0.015046) Loss: 0.26754 (0.32011) +2025-08-23,14:53:27 | INFO | Train Epoch: 8 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.26664 (0.30495) Boundary_loss: 0.015016 (0.015046) Loss: 0.28166 (0.32000) +2025-08-23,14:54:24 | INFO | Train Epoch: 8 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.26852 (0.30485) Boundary_loss: 0.014983 (0.015046) Loss: 0.28350 (0.31989) +2025-08-23,14:55:21 | INFO | Train Epoch: 8 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.30071 (0.30484) Boundary_loss: 0.014951 (0.015045) Loss: 0.31566 (0.31988) +2025-08-23,14:56:17 | INFO | Train Epoch: 8 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.166 Boundary Ratio: 0.246 Contrastive_loss: 0.28677 (0.30478) Boundary_loss: 0.014994 (0.015045) Loss: 0.30177 (0.31983) +2025-08-23,14:57:14 | INFO | Train Epoch: 8 [17971712/26365952 (68%)] Avg Boundaries (per batch): 49.463 Boundary Ratio: 0.252 Contrastive_loss: 0.29785 (0.30476) Boundary_loss: 0.015108 (0.015045) Loss: 0.31296 (0.31981) +2025-08-23,14:58:10 | INFO | Train Epoch: 8 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.221 Boundary Ratio: 0.246 Contrastive_loss: 0.27967 (0.30469) Boundary_loss: 0.014896 (0.015045) Loss: 0.29456 (0.31974) +2025-08-23,14:59:07 | INFO | Train Epoch: 8 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.146 Boundary Ratio: 0.246 Contrastive_loss: 0.32114 (0.30474) Boundary_loss: 0.015023 (0.015045) Loss: 0.33617 (0.31979) +2025-08-23,15:00:04 | INFO | Train Epoch: 8 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.25072 (0.30459) Boundary_loss: 0.014995 (0.015045) Loss: 0.26571 (0.31963) +2025-08-23,15:01:00 | INFO | Train Epoch: 8 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.35300 (0.30472) Boundary_loss: 0.015099 (0.015045) Loss: 0.36810 (0.31977) +2025-08-23,15:01:57 | INFO | Train Epoch: 8 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.31747 (0.30476) Boundary_loss: 0.015059 (0.015045) Loss: 0.33252 (0.31980) +2025-08-23,15:02:53 | INFO | Train Epoch: 8 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.31239 (0.30478) Boundary_loss: 0.015044 (0.015045) Loss: 0.32743 (0.31983) +2025-08-23,15:03:50 | INFO | Train Epoch: 8 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.27555 (0.30470) Boundary_loss: 0.015011 (0.015045) Loss: 0.29056 (0.31974) +2025-08-23,15:04:47 | INFO | Train Epoch: 8 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.34671 (0.30482) Boundary_loss: 0.014944 (0.015045) Loss: 0.36165 (0.31986) +2025-08-23,15:05:43 | INFO | Train Epoch: 8 [18432512/26365952 (70%)] Avg Boundaries (per batch): 47.768 Boundary Ratio: 0.244 Contrastive_loss: 0.30559 (0.30482) Boundary_loss: 0.015059 (0.015045) Loss: 0.32065 (0.31986) +2025-08-23,15:06:40 | INFO | Train Epoch: 8 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23498 (0.30463) Boundary_loss: 0.014962 (0.015044) Loss: 0.24995 (0.31967) +2025-08-23,15:07:36 | INFO | Train Epoch: 8 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.26552 (0.30452) Boundary_loss: 0.015051 (0.015044) Loss: 0.28057 (0.31956) +2025-08-23,15:08:33 | INFO | Train Epoch: 8 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.24579 (0.30436) Boundary_loss: 0.015056 (0.015044) Loss: 0.26084 (0.31940) +2025-08-23,15:09:29 | INFO | Train Epoch: 8 [18637312/26365952 (71%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.33333 (0.30444) Boundary_loss: 0.015014 (0.015044) Loss: 0.34835 (0.31948) +2025-08-23,15:10:26 | INFO | Train Epoch: 8 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.32874 (0.30450) Boundary_loss: 0.014957 (0.015044) Loss: 0.34369 (0.31955) +2025-08-23,15:11:23 | INFO | Train Epoch: 8 [18739712/26365952 (71%)] Avg Boundaries (per batch): 49.359 Boundary Ratio: 0.252 Contrastive_loss: 0.29020 (0.30446) Boundary_loss: 0.015062 (0.015044) Loss: 0.30526 (0.31951) +2025-08-23,15:12:19 | INFO | Train Epoch: 8 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.014 Boundary Ratio: 0.245 Contrastive_loss: 0.36278 (0.30462) Boundary_loss: 0.015108 (0.015044) Loss: 0.37789 (0.31967) +2025-08-23,15:13:16 | INFO | Train Epoch: 8 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.31979 (0.30466) Boundary_loss: 0.015084 (0.015044) Loss: 0.33488 (0.31971) +2025-08-23,15:14:12 | INFO | Train Epoch: 8 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.24796 (0.30451) Boundary_loss: 0.015048 (0.015044) Loss: 0.26301 (0.31955) +2025-08-23,15:15:09 | INFO | Train Epoch: 8 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.342 Boundary Ratio: 0.247 Contrastive_loss: 0.26766 (0.30441) Boundary_loss: 0.015141 (0.015045) Loss: 0.28281 (0.31945) +2025-08-23,15:16:06 | INFO | Train Epoch: 8 [18995712/26365952 (72%)] Avg Boundaries (per batch): 49.766 Boundary Ratio: 0.254 Contrastive_loss: 0.28586 (0.30436) Boundary_loss: 0.015179 (0.015045) Loss: 0.30104 (0.31941) +2025-08-23,15:17:02 | INFO | Train Epoch: 8 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.29648 (0.30434) Boundary_loss: 0.015015 (0.015045) Loss: 0.31150 (0.31938) +2025-08-23,15:17:59 | INFO | Train Epoch: 8 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.35282 (0.30447) Boundary_loss: 0.015099 (0.015045) Loss: 0.36792 (0.31951) +2025-08-23,15:18:55 | INFO | Train Epoch: 8 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.27936 (0.30440) Boundary_loss: 0.015042 (0.015045) Loss: 0.29440 (0.31945) +2025-08-23,15:19:52 | INFO | Train Epoch: 8 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.33321 (0.30448) Boundary_loss: 0.015032 (0.015045) Loss: 0.34824 (0.31952) +2025-08-23,15:20:49 | INFO | Train Epoch: 8 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.24862 (0.30433) Boundary_loss: 0.015024 (0.015045) Loss: 0.26364 (0.31938) +2025-08-23,15:21:45 | INFO | Train Epoch: 8 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.30822 (0.30434) Boundary_loss: 0.015055 (0.015045) Loss: 0.32328 (0.31939) +2025-08-23,15:22:42 | INFO | Train Epoch: 8 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.27464 (0.30426) Boundary_loss: 0.014964 (0.015045) Loss: 0.28960 (0.31931) +2025-08-23,15:23:39 | INFO | Train Epoch: 8 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.34236 (0.30436) Boundary_loss: 0.015069 (0.015045) Loss: 0.35743 (0.31941) +2025-08-23,15:24:35 | INFO | Train Epoch: 8 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.33886 (0.30445) Boundary_loss: 0.015025 (0.015045) Loss: 0.35388 (0.31950) +2025-08-23,15:25:32 | INFO | Train Epoch: 8 [19507712/26365952 (74%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 0.27502 (0.30438) Boundary_loss: 0.015029 (0.015045) Loss: 0.29005 (0.31942) +2025-08-23,15:26:29 | INFO | Train Epoch: 8 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.27353 (0.30430) Boundary_loss: 0.014912 (0.015044) Loss: 0.28845 (0.31934) +2025-08-23,15:27:26 | INFO | Train Epoch: 8 [19610112/26365952 (74%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.21762 (0.30407) Boundary_loss: 0.014991 (0.015044) Loss: 0.23261 (0.31911) +2025-08-23,15:28:22 | INFO | Train Epoch: 8 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.27178 (0.30399) Boundary_loss: 0.015063 (0.015044) Loss: 0.28684 (0.31903) +2025-08-23,15:29:19 | INFO | Train Epoch: 8 [19712512/26365952 (75%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.32578 (0.30404) Boundary_loss: 0.014979 (0.015044) Loss: 0.34076 (0.31909) +2025-08-23,15:30:16 | INFO | Train Epoch: 8 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.26074 (0.30393) Boundary_loss: 0.014994 (0.015044) Loss: 0.27573 (0.31897) +2025-08-23,15:31:12 | INFO | Train Epoch: 8 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.28877 (0.30389) Boundary_loss: 0.015080 (0.015044) Loss: 0.30385 (0.31894) +2025-08-23,15:32:09 | INFO | Train Epoch: 8 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.30451 (0.30389) Boundary_loss: 0.015041 (0.015044) Loss: 0.31955 (0.31894) +2025-08-23,15:33:05 | INFO | Train Epoch: 8 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.33835 (0.30398) Boundary_loss: 0.015078 (0.015044) Loss: 0.35343 (0.31903) +2025-08-23,15:34:02 | INFO | Train Epoch: 8 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.29029 (0.30395) Boundary_loss: 0.014930 (0.015044) Loss: 0.30522 (0.31899) +2025-08-23,15:34:59 | INFO | Train Epoch: 8 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.24717 (0.30380) Boundary_loss: 0.015012 (0.015044) Loss: 0.26218 (0.31885) +2025-08-23,15:35:55 | INFO | Train Epoch: 8 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.30812 (0.30381) Boundary_loss: 0.014947 (0.015044) Loss: 0.32307 (0.31886) +2025-08-23,15:36:52 | INFO | Train Epoch: 8 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.28310 (0.30376) Boundary_loss: 0.015020 (0.015044) Loss: 0.29812 (0.31880) +2025-08-23,15:37:49 | INFO | Train Epoch: 8 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.24983 (0.30362) Boundary_loss: 0.015012 (0.015043) Loss: 0.26484 (0.31867) +2025-08-23,15:38:46 | INFO | Train Epoch: 8 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 0.23571 (0.30345) Boundary_loss: 0.015005 (0.015043) Loss: 0.25072 (0.31850) +2025-08-23,15:39:42 | INFO | Train Epoch: 8 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.26532 (0.30336) Boundary_loss: 0.014934 (0.015043) Loss: 0.28025 (0.31840) +2025-08-23,15:40:39 | INFO | Train Epoch: 8 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.39005 (0.30357) Boundary_loss: 0.014962 (0.015043) Loss: 0.40501 (0.31862) +2025-08-23,15:41:36 | INFO | Train Epoch: 8 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.29280 (0.30355) Boundary_loss: 0.014884 (0.015042) Loss: 0.30768 (0.31859) +2025-08-23,15:42:32 | INFO | Train Epoch: 8 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.23258 (0.30337) Boundary_loss: 0.015052 (0.015043) Loss: 0.24764 (0.31841) +2025-08-23,15:43:29 | INFO | Train Epoch: 8 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.28870 (0.30333) Boundary_loss: 0.015049 (0.015043) Loss: 0.30375 (0.31838) +2025-08-23,15:44:26 | INFO | Train Epoch: 8 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.29634 (0.30332) Boundary_loss: 0.014975 (0.015042) Loss: 0.31132 (0.31836) +2025-08-23,15:45:22 | INFO | Train Epoch: 8 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.24435 (0.30317) Boundary_loss: 0.015195 (0.015043) Loss: 0.25955 (0.31821) +2025-08-23,15:46:19 | INFO | Train Epoch: 8 [20634112/26365952 (78%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.28579 (0.30313) Boundary_loss: 0.015121 (0.015043) Loss: 0.30091 (0.31817) +2025-08-23,15:47:15 | INFO | Train Epoch: 8 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.38115 (0.30332) Boundary_loss: 0.015096 (0.015043) Loss: 0.39625 (0.31836) +2025-08-23,15:48:12 | INFO | Train Epoch: 8 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.27513 (0.30325) Boundary_loss: 0.015061 (0.015043) Loss: 0.29019 (0.31829) +2025-08-23,15:49:09 | INFO | Train Epoch: 8 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.26181 (0.30315) Boundary_loss: 0.014965 (0.015043) Loss: 0.27678 (0.31819) +2025-08-23,15:50:05 | INFO | Train Epoch: 8 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.31849 (0.30318) Boundary_loss: 0.015033 (0.015043) Loss: 0.33352 (0.31823) +2025-08-23,15:51:02 | INFO | Train Epoch: 8 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.30629 (0.30319) Boundary_loss: 0.015087 (0.015043) Loss: 0.32138 (0.31824) +2025-08-23,15:51:59 | INFO | Train Epoch: 8 [20941312/26365952 (79%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 0.27369 (0.30312) Boundary_loss: 0.014969 (0.015043) Loss: 0.28866 (0.31816) +2025-08-23,15:52:55 | INFO | Train Epoch: 8 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.19695 (0.30286) Boundary_loss: 0.015198 (0.015043) Loss: 0.21215 (0.31791) +2025-08-23,15:53:52 | INFO | Train Epoch: 8 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.31053 (0.30288) Boundary_loss: 0.015007 (0.015043) Loss: 0.32554 (0.31792) +2025-08-23,15:54:48 | INFO | Train Epoch: 8 [21094912/26365952 (80%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.30421 (0.30288) Boundary_loss: 0.015009 (0.015043) Loss: 0.31922 (0.31793) +2025-08-23,15:55:45 | INFO | Train Epoch: 8 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.26778 (0.30280) Boundary_loss: 0.014939 (0.015043) Loss: 0.28272 (0.31784) +2025-08-23,15:56:42 | INFO | Train Epoch: 8 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.29436 (0.30278) Boundary_loss: 0.015038 (0.015043) Loss: 0.30940 (0.31782) +2025-08-23,15:57:39 | INFO | Train Epoch: 8 [21248512/26365952 (81%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 0.25077 (0.30265) Boundary_loss: 0.015038 (0.015043) Loss: 0.26581 (0.31770) +2025-08-23,15:58:35 | INFO | Train Epoch: 8 [21299712/26365952 (81%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 0.32010 (0.30270) Boundary_loss: 0.015024 (0.015043) Loss: 0.33513 (0.31774) +2025-08-23,15:59:32 | INFO | Train Epoch: 8 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.33848 (0.30278) Boundary_loss: 0.015058 (0.015043) Loss: 0.35354 (0.31782) +2025-08-23,16:00:28 | INFO | Train Epoch: 8 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.369 Boundary Ratio: 0.247 Contrastive_loss: 0.25882 (0.30268) Boundary_loss: 0.015011 (0.015043) Loss: 0.27383 (0.31772) +2025-08-23,16:01:25 | INFO | Train Epoch: 8 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.24241 (0.30253) Boundary_loss: 0.014920 (0.015042) Loss: 0.25733 (0.31758) +2025-08-23,16:02:22 | INFO | Train Epoch: 8 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.35854 (0.30267) Boundary_loss: 0.015102 (0.015043) Loss: 0.37364 (0.31771) +2025-08-23,16:03:18 | INFO | Train Epoch: 8 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.28903 (0.30263) Boundary_loss: 0.014855 (0.015042) Loss: 0.30388 (0.31768) +2025-08-23,16:04:15 | INFO | Train Epoch: 8 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.516 Boundary Ratio: 0.248 Contrastive_loss: 0.33744 (0.30272) Boundary_loss: 0.014963 (0.015042) Loss: 0.35240 (0.31776) +2025-08-23,16:05:12 | INFO | Train Epoch: 8 [21658112/26365952 (82%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.29010 (0.30269) Boundary_loss: 0.015201 (0.015042) Loss: 0.30530 (0.31773) +2025-08-23,16:06:08 | INFO | Train Epoch: 8 [21709312/26365952 (82%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.31849 (0.30272) Boundary_loss: 0.014979 (0.015042) Loss: 0.33347 (0.31777) +2025-08-23,16:07:05 | INFO | Train Epoch: 8 [21760512/26365952 (83%)] Avg Boundaries (per batch): 49.555 Boundary Ratio: 0.253 Contrastive_loss: 0.24117 (0.30258) Boundary_loss: 0.015137 (0.015042) Loss: 0.25631 (0.31762) +2025-08-23,16:08:02 | INFO | Train Epoch: 8 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.28754 (0.30254) Boundary_loss: 0.014942 (0.015042) Loss: 0.30248 (0.31759) +2025-08-23,16:08:58 | INFO | Train Epoch: 8 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.31749 (0.30258) Boundary_loss: 0.015105 (0.015042) Loss: 0.33260 (0.31762) +2025-08-23,16:09:55 | INFO | Train Epoch: 8 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.42589 (0.30287) Boundary_loss: 0.014999 (0.015042) Loss: 0.44089 (0.31791) +2025-08-23,16:10:51 | INFO | Train Epoch: 8 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.22466 (0.30268) Boundary_loss: 0.015084 (0.015042) Loss: 0.23974 (0.31773) +2025-08-23,16:11:48 | INFO | Train Epoch: 8 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.23054 (0.30252) Boundary_loss: 0.014949 (0.015042) Loss: 0.24549 (0.31756) +2025-08-23,16:12:45 | INFO | Train Epoch: 8 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.25041 (0.30240) Boundary_loss: 0.014928 (0.015042) Loss: 0.26533 (0.31744) +2025-08-23,16:13:41 | INFO | Train Epoch: 8 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 0.28716 (0.30236) Boundary_loss: 0.014982 (0.015042) Loss: 0.30214 (0.31740) +2025-08-23,16:14:38 | INFO | Train Epoch: 8 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.31365 (0.30239) Boundary_loss: 0.015064 (0.015042) Loss: 0.32871 (0.31743) +2025-08-23,16:15:35 | INFO | Train Epoch: 8 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.37895 (0.30256) Boundary_loss: 0.015050 (0.015042) Loss: 0.39400 (0.31760) +2025-08-23,16:16:31 | INFO | Train Epoch: 8 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.22029 (0.30237) Boundary_loss: 0.014976 (0.015042) Loss: 0.23527 (0.31742) +2025-08-23,16:17:28 | INFO | Train Epoch: 8 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.30223 (0.30237) Boundary_loss: 0.015095 (0.015042) Loss: 0.31733 (0.31742) +2025-08-23,16:18:24 | INFO | Train Epoch: 8 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.25506 (0.30227) Boundary_loss: 0.015083 (0.015042) Loss: 0.27014 (0.31731) +2025-08-23,16:19:21 | INFO | Train Epoch: 8 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.441 Boundary Ratio: 0.247 Contrastive_loss: 0.27300 (0.30220) Boundary_loss: 0.015130 (0.015042) Loss: 0.28813 (0.31724) +2025-08-23,16:20:18 | INFO | Train Epoch: 8 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.32155 (0.30224) Boundary_loss: 0.014953 (0.015042) Loss: 0.33650 (0.31729) +2025-08-23,16:21:14 | INFO | Train Epoch: 8 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.871 Boundary Ratio: 0.254 Contrastive_loss: 0.30626 (0.30225) Boundary_loss: 0.015191 (0.015042) Loss: 0.32145 (0.31729) +2025-08-23,16:22:11 | INFO | Train Epoch: 8 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 0.30850 (0.30227) Boundary_loss: 0.014948 (0.015042) Loss: 0.32345 (0.31731) +2025-08-23,16:23:07 | INFO | Train Epoch: 8 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.32559 (0.30232) Boundary_loss: 0.015053 (0.015042) Loss: 0.34064 (0.31736) +2025-08-23,16:24:04 | INFO | Train Epoch: 8 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 0.25878 (0.30222) Boundary_loss: 0.015014 (0.015042) Loss: 0.27379 (0.31726) +2025-08-23,16:25:01 | INFO | Train Epoch: 8 [22733312/26365952 (86%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.27877 (0.30217) Boundary_loss: 0.014928 (0.015042) Loss: 0.29370 (0.31721) +2025-08-23,16:25:57 | INFO | Train Epoch: 8 [22784512/26365952 (86%)] Avg Boundaries (per batch): 49.189 Boundary Ratio: 0.251 Contrastive_loss: 0.29055 (0.30214) Boundary_loss: 0.015138 (0.015042) Loss: 0.30569 (0.31718) +2025-08-23,16:26:54 | INFO | Train Epoch: 8 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.25543 (0.30204) Boundary_loss: 0.015064 (0.015042) Loss: 0.27049 (0.31708) +2025-08-23,16:27:51 | INFO | Train Epoch: 8 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.28636 (0.30200) Boundary_loss: 0.015028 (0.015042) Loss: 0.30139 (0.31704) +2025-08-23,16:28:48 | INFO | Train Epoch: 8 [22938112/26365952 (87%)] Avg Boundaries (per batch): 49.408 Boundary Ratio: 0.252 Contrastive_loss: 0.28932 (0.30197) Boundary_loss: 0.015121 (0.015042) Loss: 0.30444 (0.31702) +2025-08-23,16:29:44 | INFO | Train Epoch: 8 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.26932 (0.30190) Boundary_loss: 0.014915 (0.015042) Loss: 0.28424 (0.31694) +2025-08-23,16:30:41 | INFO | Train Epoch: 8 [23040512/26365952 (87%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.31809 (0.30194) Boundary_loss: 0.015019 (0.015042) Loss: 0.33311 (0.31698) +2025-08-23,16:31:37 | INFO | Train Epoch: 8 [23091712/26365952 (88%)] Avg Boundaries (per batch): 49.436 Boundary Ratio: 0.252 Contrastive_loss: 0.37190 (0.30209) Boundary_loss: 0.014969 (0.015041) Loss: 0.38687 (0.31713) +2025-08-23,16:32:34 | INFO | Train Epoch: 8 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.28265 (0.30205) Boundary_loss: 0.015201 (0.015042) Loss: 0.29785 (0.31709) +2025-08-23,16:33:31 | INFO | Train Epoch: 8 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.121 Boundary Ratio: 0.246 Contrastive_loss: 0.27462 (0.30199) Boundary_loss: 0.015006 (0.015042) Loss: 0.28963 (0.31703) +2025-08-23,16:34:27 | INFO | Train Epoch: 8 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.33757 (0.30207) Boundary_loss: 0.015016 (0.015042) Loss: 0.35259 (0.31711) +2025-08-23,16:35:24 | INFO | Train Epoch: 8 [23296512/26365952 (88%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 0.31641 (0.30210) Boundary_loss: 0.014967 (0.015042) Loss: 0.33137 (0.31714) +2025-08-23,16:36:20 | INFO | Train Epoch: 8 [23347712/26365952 (89%)] Avg Boundaries (per batch): 49.109 Boundary Ratio: 0.251 Contrastive_loss: 0.29155 (0.30208) Boundary_loss: 0.015109 (0.015042) Loss: 0.30666 (0.31712) +2025-08-23,16:37:17 | INFO | Train Epoch: 8 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.27144 (0.30201) Boundary_loss: 0.014997 (0.015042) Loss: 0.28643 (0.31705) +2025-08-23,16:38:14 | INFO | Train Epoch: 8 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.518 Boundary Ratio: 0.253 Contrastive_loss: 0.22427 (0.30184) Boundary_loss: 0.014967 (0.015041) Loss: 0.23924 (0.31688) +2025-08-23,16:39:10 | INFO | Train Epoch: 8 [23501312/26365952 (89%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.25978 (0.30175) Boundary_loss: 0.014983 (0.015041) Loss: 0.27476 (0.31679) +2025-08-23,16:40:07 | INFO | Train Epoch: 8 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.250 Boundary Ratio: 0.246 Contrastive_loss: 0.30911 (0.30176) Boundary_loss: 0.015026 (0.015041) Loss: 0.32414 (0.31681) +2025-08-23,16:41:04 | INFO | Train Epoch: 8 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.28649 (0.30173) Boundary_loss: 0.015083 (0.015041) Loss: 0.30157 (0.31677) +2025-08-23,16:42:00 | INFO | Train Epoch: 8 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.27744 (0.30168) Boundary_loss: 0.015012 (0.015041) Loss: 0.29245 (0.31672) +2025-08-23,16:42:57 | INFO | Train Epoch: 8 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.26566 (0.30160) Boundary_loss: 0.015200 (0.015042) Loss: 0.28086 (0.31664) +2025-08-23,16:43:54 | INFO | Train Epoch: 8 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.27620 (0.30155) Boundary_loss: 0.015151 (0.015042) Loss: 0.29135 (0.31659) +2025-08-23,16:44:50 | INFO | Train Epoch: 8 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.30330 (0.30155) Boundary_loss: 0.015053 (0.015042) Loss: 0.31836 (0.31659) +2025-08-23,16:45:47 | INFO | Train Epoch: 8 [23859712/26365952 (90%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.37836 (0.30171) Boundary_loss: 0.015137 (0.015042) Loss: 0.39350 (0.31676) +2025-08-23,16:46:44 | INFO | Train Epoch: 8 [23910912/26365952 (91%)] Avg Boundaries (per batch): 50.016 Boundary Ratio: 0.255 Contrastive_loss: 0.35528 (0.30183) Boundary_loss: 0.015101 (0.015042) Loss: 0.37038 (0.31687) +2025-08-23,16:47:40 | INFO | Train Epoch: 8 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.25959 (0.30174) Boundary_loss: 0.014980 (0.015042) Loss: 0.27457 (0.31678) +2025-08-23,16:48:37 | INFO | Train Epoch: 8 [24013312/26365952 (91%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.29812 (0.30173) Boundary_loss: 0.015093 (0.015042) Loss: 0.31322 (0.31677) +2025-08-23,16:49:33 | INFO | Train Epoch: 8 [24064512/26365952 (91%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.34396 (0.30182) Boundary_loss: 0.015022 (0.015042) Loss: 0.35899 (0.31686) +2025-08-23,16:50:30 | INFO | Train Epoch: 8 [24115712/26365952 (91%)] Avg Boundaries (per batch): 49.453 Boundary Ratio: 0.252 Contrastive_loss: 0.29862 (0.30181) Boundary_loss: 0.015033 (0.015042) Loss: 0.31366 (0.31686) +2025-08-23,16:51:27 | INFO | Train Epoch: 8 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.29248 (0.30179) Boundary_loss: 0.015099 (0.015042) Loss: 0.30758 (0.31684) +2025-08-23,16:52:23 | INFO | Train Epoch: 8 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 0.33423 (0.30186) Boundary_loss: 0.015036 (0.015042) Loss: 0.34926 (0.31691) +2025-08-23,16:53:20 | INFO | Train Epoch: 8 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.28179 (0.30182) Boundary_loss: 0.015039 (0.015042) Loss: 0.29683 (0.31686) +2025-08-23,16:54:16 | INFO | Train Epoch: 8 [24320512/26365952 (92%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.34312 (0.30191) Boundary_loss: 0.014936 (0.015042) Loss: 0.35805 (0.31695) +2025-08-23,16:55:13 | INFO | Train Epoch: 8 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.31472 (0.30193) Boundary_loss: 0.015075 (0.015042) Loss: 0.32980 (0.31698) +2025-08-23,16:56:10 | INFO | Train Epoch: 8 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.31144 (0.30195) Boundary_loss: 0.014883 (0.015042) Loss: 0.32633 (0.31700) +2025-08-23,16:57:06 | INFO | Train Epoch: 8 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.199 Boundary Ratio: 0.246 Contrastive_loss: 0.25807 (0.30186) Boundary_loss: 0.015102 (0.015042) Loss: 0.27318 (0.31690) +2025-08-23,16:58:03 | INFO | Train Epoch: 8 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.29972 (0.30186) Boundary_loss: 0.014861 (0.015042) Loss: 0.31459 (0.31690) +2025-08-23,16:59:00 | INFO | Train Epoch: 8 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.25791 (0.30177) Boundary_loss: 0.015056 (0.015042) Loss: 0.27297 (0.31681) +2025-08-23,16:59:56 | INFO | Train Epoch: 8 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.33693 (0.30184) Boundary_loss: 0.015128 (0.015042) Loss: 0.35206 (0.31688) +2025-08-23,17:00:52 | INFO | Train Epoch: 8 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.25294 (0.30174) Boundary_loss: 0.014971 (0.015042) Loss: 0.26791 (0.31678) +2025-08-23,17:01:49 | INFO | Train Epoch: 8 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.23733 (0.30161) Boundary_loss: 0.015004 (0.015041) Loss: 0.25234 (0.31665) +2025-08-23,17:02:45 | INFO | Train Epoch: 8 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 0.26228 (0.30152) Boundary_loss: 0.015037 (0.015041) Loss: 0.27731 (0.31657) +2025-08-23,17:03:42 | INFO | Train Epoch: 8 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.27912 (0.30148) Boundary_loss: 0.015152 (0.015042) Loss: 0.29428 (0.31652) +2025-08-23,17:04:38 | INFO | Train Epoch: 8 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.25532 (0.30138) Boundary_loss: 0.014911 (0.015041) Loss: 0.27023 (0.31642) +2025-08-23,17:05:35 | INFO | Train Epoch: 8 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.28794 (0.30136) Boundary_loss: 0.015158 (0.015042) Loss: 0.30310 (0.31640) +2025-08-23,17:06:32 | INFO | Train Epoch: 8 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 0.29887 (0.30135) Boundary_loss: 0.015165 (0.015042) Loss: 0.31403 (0.31639) +2025-08-23,17:07:28 | INFO | Train Epoch: 8 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.23802 (0.30122) Boundary_loss: 0.015105 (0.015042) Loss: 0.25312 (0.31626) +2025-08-23,17:08:25 | INFO | Train Epoch: 8 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.31059 (0.30124) Boundary_loss: 0.014958 (0.015042) Loss: 0.32555 (0.31628) +2025-08-23,17:09:21 | INFO | Train Epoch: 8 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.26750 (0.30117) Boundary_loss: 0.014959 (0.015042) Loss: 0.28246 (0.31621) +2025-08-23,17:10:18 | INFO | Train Epoch: 8 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.27617 (0.30112) Boundary_loss: 0.015014 (0.015042) Loss: 0.29118 (0.31616) +2025-08-23,17:11:14 | INFO | Train Epoch: 8 [25242112/26365952 (96%)] Avg Boundaries (per batch): 49.348 Boundary Ratio: 0.252 Contrastive_loss: 0.33830 (0.30120) Boundary_loss: 0.015079 (0.015042) Loss: 0.35338 (0.31624) +2025-08-23,17:12:11 | INFO | Train Epoch: 8 [25293312/26365952 (96%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 0.27628 (0.30115) Boundary_loss: 0.014963 (0.015042) Loss: 0.29125 (0.31619) +2025-08-23,17:13:08 | INFO | Train Epoch: 8 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.35290 (0.30125) Boundary_loss: 0.015077 (0.015042) Loss: 0.36797 (0.31629) +2025-08-23,17:14:04 | INFO | Train Epoch: 8 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.32999 (0.30131) Boundary_loss: 0.014960 (0.015041) Loss: 0.34495 (0.31635) +2025-08-23,17:15:01 | INFO | Train Epoch: 8 [25446912/26365952 (97%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.27286 (0.30125) Boundary_loss: 0.015160 (0.015042) Loss: 0.28802 (0.31629) +2025-08-23,17:15:57 | INFO | Train Epoch: 8 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.31227 (0.30127) Boundary_loss: 0.015003 (0.015042) Loss: 0.32727 (0.31632) +2025-08-23,17:16:54 | INFO | Train Epoch: 8 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.455 Boundary Ratio: 0.252 Contrastive_loss: 0.34548 (0.30136) Boundary_loss: 0.014909 (0.015041) Loss: 0.36039 (0.31640) +2025-08-23,17:17:50 | INFO | Train Epoch: 8 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.38871 (0.30154) Boundary_loss: 0.015014 (0.015041) Loss: 0.40372 (0.31658) +2025-08-23,17:18:47 | INFO | Train Epoch: 8 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.29082 (0.30151) Boundary_loss: 0.015074 (0.015041) Loss: 0.30589 (0.31656) +2025-08-23,17:19:43 | INFO | Train Epoch: 8 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.26289 (0.30144) Boundary_loss: 0.014898 (0.015041) Loss: 0.27779 (0.31648) +2025-08-23,17:20:40 | INFO | Train Epoch: 8 [25754112/26365952 (98%)] Avg Boundaries (per batch): 49.623 Boundary Ratio: 0.253 Contrastive_loss: 0.25426 (0.30134) Boundary_loss: 0.015046 (0.015041) Loss: 0.26931 (0.31639) +2025-08-23,17:21:37 | INFO | Train Epoch: 8 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.30573 (0.30135) Boundary_loss: 0.015089 (0.015041) Loss: 0.32082 (0.31639) +2025-08-23,17:22:33 | INFO | Train Epoch: 8 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.38182 (0.30151) Boundary_loss: 0.014971 (0.015041) Loss: 0.39679 (0.31655) +2025-08-23,17:23:30 | INFO | Train Epoch: 8 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.25626 (0.30142) Boundary_loss: 0.015041 (0.015041) Loss: 0.27130 (0.31646) +2025-08-23,17:24:26 | INFO | Train Epoch: 8 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.254 Boundary Ratio: 0.246 Contrastive_loss: 0.27775 (0.30138) Boundary_loss: 0.015008 (0.015041) Loss: 0.29276 (0.31642) +2025-08-23,17:25:23 | INFO | Train Epoch: 8 [26010112/26365952 (99%)] Avg Boundaries (per batch): 49.713 Boundary Ratio: 0.254 Contrastive_loss: 0.27277 (0.30132) Boundary_loss: 0.015102 (0.015041) Loss: 0.28787 (0.31636) +2025-08-23,17:26:19 | INFO | Train Epoch: 8 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.25009 (0.30122) Boundary_loss: 0.014981 (0.015041) Loss: 0.26507 (0.31626) +2025-08-23,17:27:16 | INFO | Train Epoch: 8 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.26296 (0.30114) Boundary_loss: 0.014996 (0.015041) Loss: 0.27796 (0.31619) +2025-08-23,17:28:13 | INFO | Train Epoch: 8 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 0.23490 (0.30102) Boundary_loss: 0.015032 (0.015041) Loss: 0.24993 (0.31606) +2025-08-23,17:29:09 | INFO | Train Epoch: 8 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.30848 (0.30103) Boundary_loss: 0.015095 (0.015041) Loss: 0.32358 (0.31607) +2025-08-23,17:30:06 | INFO | Train Epoch: 8 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.268 Boundary Ratio: 0.251 Contrastive_loss: 0.27941 (0.30099) Boundary_loss: 0.014973 (0.015041) Loss: 0.29438 (0.31603) +2025-08-23,17:31:03 | INFO | Train Epoch: 8 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.43077 (0.30124) Boundary_loss: 0.014978 (0.015041) Loss: 0.44575 (0.31628) +2025-08-23,17:31:56 | INFO | Train Epoch: 8 [26365952/26365952 (100%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.31634 (0.30127) Boundary_loss: 0.015173 (0.015041) Loss: 0.33151 (0.31631) +2025-08-23,17:31:56 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-23,17:31:56 | INFO | [Epoch 8] Average Step Time: 0.569s | Average GPU Memory: 31.7 GB +2025-08-23,17:31:56 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-23,17:31:56 | INFO | Starting zero-shot imagenet. +2025-08-23,17:31:56 | INFO | Building zero-shot classifier +2025-08-23,17:32:06 | INFO | Using classifier +2025-08-23,17:32:51 | INFO | Finished zero-shot imagenet. +2025-08-23,17:32:51 | INFO | Eval Epoch: 9 imagenet-zeroshot-val-top1: 0.2834 imagenet-zeroshot-val-top5: 0.5423 +2025-08-23,17:32:52 | INFO | Start epoch 9 +2025-08-23,17:32:55 | INFO | Train Epoch: 9 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.23991 (0.23991) Boundary_loss: 0.015056 (0.015056) Loss: 0.25497 (0.25497) +2025-08-23,17:33:51 | INFO | Train Epoch: 9 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.25477 (0.24734) Boundary_loss: 0.015003 (0.015030) Loss: 0.26977 (0.26237) +2025-08-23,17:34:48 | INFO | Train Epoch: 9 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 0.28951 (0.26140) Boundary_loss: 0.015000 (0.015020) Loss: 0.30451 (0.27642) +2025-08-23,17:35:44 | INFO | Train Epoch: 9 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.23060 (0.25370) Boundary_loss: 0.014987 (0.015012) Loss: 0.24559 (0.26871) +2025-08-23,17:36:41 | INFO | Train Epoch: 9 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.21240 (0.24544) Boundary_loss: 0.015024 (0.015014) Loss: 0.22742 (0.26045) +2025-08-23,17:37:37 | INFO | Train Epoch: 9 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.363 Boundary Ratio: 0.247 Contrastive_loss: 0.24972 (0.24615) Boundary_loss: 0.014922 (0.014999) Loss: 0.26464 (0.26115) +2025-08-23,17:38:34 | INFO | Train Epoch: 9 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.26325 (0.24859) Boundary_loss: 0.015100 (0.015013) Loss: 0.27835 (0.26361) +2025-08-23,17:39:30 | INFO | Train Epoch: 9 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.27329 (0.25168) Boundary_loss: 0.014951 (0.015006) Loss: 0.28824 (0.26669) +2025-08-23,17:40:27 | INFO | Train Epoch: 9 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.23569 (0.24990) Boundary_loss: 0.014989 (0.015004) Loss: 0.25068 (0.26491) +2025-08-23,17:41:23 | INFO | Train Epoch: 9 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.27205 (0.25212) Boundary_loss: 0.014994 (0.015003) Loss: 0.28704 (0.26712) +2025-08-23,17:42:20 | INFO | Train Epoch: 9 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.23596 (0.25065) Boundary_loss: 0.015046 (0.015007) Loss: 0.25100 (0.26566) +2025-08-23,17:43:16 | INFO | Train Epoch: 9 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.24011 (0.24977) Boundary_loss: 0.014965 (0.015003) Loss: 0.25507 (0.26477) +2025-08-23,17:44:13 | INFO | Train Epoch: 9 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.21681 (0.24724) Boundary_loss: 0.015059 (0.015007) Loss: 0.23187 (0.26224) +2025-08-23,17:45:09 | INFO | Train Epoch: 9 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.21448 (0.24490) Boundary_loss: 0.015081 (0.015013) Loss: 0.22956 (0.25991) +2025-08-23,17:46:06 | INFO | Train Epoch: 9 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.28004 (0.24724) Boundary_loss: 0.015091 (0.015018) Loss: 0.29514 (0.26226) +2025-08-23,17:47:03 | INFO | Train Epoch: 9 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.19930 (0.24424) Boundary_loss: 0.014936 (0.015013) Loss: 0.21424 (0.25926) +2025-08-23,17:47:59 | INFO | Train Epoch: 9 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.28843 (0.24684) Boundary_loss: 0.014941 (0.015009) Loss: 0.30337 (0.26185) +2025-08-23,17:48:56 | INFO | Train Epoch: 9 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 0.24079 (0.24651) Boundary_loss: 0.015087 (0.015013) Loss: 0.25588 (0.26152) +2025-08-23,17:49:53 | INFO | Train Epoch: 9 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.26249 (0.24735) Boundary_loss: 0.015026 (0.015014) Loss: 0.27752 (0.26236) +2025-08-23,17:50:49 | INFO | Train Epoch: 9 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.23912 (0.24694) Boundary_loss: 0.015059 (0.015016) Loss: 0.25417 (0.26195) +2025-08-23,17:51:45 | INFO | Train Epoch: 9 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.24055 (0.24663) Boundary_loss: 0.015052 (0.015018) Loss: 0.25561 (0.26165) +2025-08-23,17:52:42 | INFO | Train Epoch: 9 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.28815 (0.24852) Boundary_loss: 0.015007 (0.015017) Loss: 0.30316 (0.26354) +2025-08-23,17:53:39 | INFO | Train Epoch: 9 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.25867 (0.24896) Boundary_loss: 0.015080 (0.015020) Loss: 0.27375 (0.26398) +2025-08-23,17:54:35 | INFO | Train Epoch: 9 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.25902 (0.24938) Boundary_loss: 0.015003 (0.015019) Loss: 0.27402 (0.26440) +2025-08-23,17:55:32 | INFO | Train Epoch: 9 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 49.383 Boundary Ratio: 0.252 Contrastive_loss: 0.26250 (0.24990) Boundary_loss: 0.015046 (0.015020) Loss: 0.27755 (0.26492) +2025-08-23,17:56:28 | INFO | Train Epoch: 9 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.30098 (0.25187) Boundary_loss: 0.014961 (0.015018) Loss: 0.31594 (0.26689) +2025-08-23,17:57:25 | INFO | Train Epoch: 9 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.24252 (0.25152) Boundary_loss: 0.015224 (0.015026) Loss: 0.25774 (0.26655) +2025-08-23,17:58:21 | INFO | Train Epoch: 9 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.22255 (0.25049) Boundary_loss: 0.015013 (0.015025) Loss: 0.23757 (0.26551) +2025-08-23,17:59:18 | INFO | Train Epoch: 9 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.20020 (0.24875) Boundary_loss: 0.015028 (0.015025) Loss: 0.21523 (0.26378) +2025-08-23,18:00:15 | INFO | Train Epoch: 9 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 47.951 Boundary Ratio: 0.245 Contrastive_loss: 0.25867 (0.24908) Boundary_loss: 0.015170 (0.015030) Loss: 0.27383 (0.26411) +2025-08-23,18:01:11 | INFO | Train Epoch: 9 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.414 Boundary Ratio: 0.252 Contrastive_loss: 0.20383 (0.24762) Boundary_loss: 0.015115 (0.015033) Loss: 0.21895 (0.26266) +2025-08-23,18:02:08 | INFO | Train Epoch: 9 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.23076 (0.24710) Boundary_loss: 0.015128 (0.015036) Loss: 0.24588 (0.26213) +2025-08-23,18:03:05 | INFO | Train Epoch: 9 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.26593 (0.24767) Boundary_loss: 0.014979 (0.015034) Loss: 0.28091 (0.26270) +2025-08-23,18:04:01 | INFO | Train Epoch: 9 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.25883 (0.24800) Boundary_loss: 0.014981 (0.015032) Loss: 0.27381 (0.26303) +2025-08-23,18:04:58 | INFO | Train Epoch: 9 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.30384 (0.24959) Boundary_loss: 0.015084 (0.015034) Loss: 0.31893 (0.26463) +2025-08-23,18:05:54 | INFO | Train Epoch: 9 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.27089 (0.25018) Boundary_loss: 0.014937 (0.015031) Loss: 0.28583 (0.26521) +2025-08-23,18:06:51 | INFO | Train Epoch: 9 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.24155 (0.24995) Boundary_loss: 0.014877 (0.015027) Loss: 0.25643 (0.26498) +2025-08-23,18:07:48 | INFO | Train Epoch: 9 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.23397 (0.24953) Boundary_loss: 0.014908 (0.015024) Loss: 0.24888 (0.26455) +2025-08-23,18:08:44 | INFO | Train Epoch: 9 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.29971 (0.25082) Boundary_loss: 0.015051 (0.015025) Loss: 0.31476 (0.26584) +2025-08-23,18:09:41 | INFO | Train Epoch: 9 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.28853 (0.25176) Boundary_loss: 0.014924 (0.015022) Loss: 0.30345 (0.26678) +2025-08-23,18:10:37 | INFO | Train Epoch: 9 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.24296 (0.25154) Boundary_loss: 0.014973 (0.015021) Loss: 0.25794 (0.26657) +2025-08-23,18:11:34 | INFO | Train Epoch: 9 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.27378 (0.25207) Boundary_loss: 0.015069 (0.015022) Loss: 0.28885 (0.26710) +2025-08-23,18:12:30 | INFO | Train Epoch: 9 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.25621 (0.25217) Boundary_loss: 0.015070 (0.015023) Loss: 0.27128 (0.26719) +2025-08-23,18:13:27 | INFO | Train Epoch: 9 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 0.28735 (0.25297) Boundary_loss: 0.014958 (0.015022) Loss: 0.30230 (0.26799) +2025-08-23,18:14:23 | INFO | Train Epoch: 9 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.30236 (0.25407) Boundary_loss: 0.014980 (0.015021) Loss: 0.31734 (0.26909) +2025-08-23,18:15:20 | INFO | Train Epoch: 9 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 47.920 Boundary Ratio: 0.244 Contrastive_loss: 0.20563 (0.25301) Boundary_loss: 0.015010 (0.015021) Loss: 0.22064 (0.26803) +2025-08-23,18:16:17 | INFO | Train Epoch: 9 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.26806 (0.25333) Boundary_loss: 0.015002 (0.015020) Loss: 0.28307 (0.26835) +2025-08-23,18:17:13 | INFO | Train Epoch: 9 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.23317 (0.25291) Boundary_loss: 0.015038 (0.015021) Loss: 0.24820 (0.26793) +2025-08-23,18:18:10 | INFO | Train Epoch: 9 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.17740 (0.25137) Boundary_loss: 0.015115 (0.015022) Loss: 0.19252 (0.26640) +2025-08-23,18:19:06 | INFO | Train Epoch: 9 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.25495 (0.25144) Boundary_loss: 0.014937 (0.015021) Loss: 0.26989 (0.26647) +2025-08-23,18:20:03 | INFO | Train Epoch: 9 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 0.28536 (0.25211) Boundary_loss: 0.015179 (0.015024) Loss: 0.30054 (0.26713) +2025-08-23,18:20:59 | INFO | Train Epoch: 9 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.25982 (0.25226) Boundary_loss: 0.015014 (0.015024) Loss: 0.27483 (0.26728) +2025-08-23,18:21:56 | INFO | Train Epoch: 9 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.29848 (0.25313) Boundary_loss: 0.015029 (0.015024) Loss: 0.31351 (0.26815) +2025-08-23,18:22:52 | INFO | Train Epoch: 9 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.26708 (0.25339) Boundary_loss: 0.014963 (0.015023) Loss: 0.28204 (0.26841) +2025-08-23,18:23:49 | INFO | Train Epoch: 9 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.22870 (0.25294) Boundary_loss: 0.015087 (0.015024) Loss: 0.24379 (0.26796) +2025-08-23,18:24:45 | INFO | Train Epoch: 9 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 0.25165 (0.25292) Boundary_loss: 0.014902 (0.015022) Loss: 0.26655 (0.26794) +2025-08-23,18:25:42 | INFO | Train Epoch: 9 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.389 Boundary Ratio: 0.247 Contrastive_loss: 0.24183 (0.25272) Boundary_loss: 0.014940 (0.015020) Loss: 0.25677 (0.26774) +2025-08-23,18:26:39 | INFO | Train Epoch: 9 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.35879 (0.25455) Boundary_loss: 0.015081 (0.015021) Loss: 0.37387 (0.26957) +2025-08-23,18:27:35 | INFO | Train Epoch: 9 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.24587 (0.25440) Boundary_loss: 0.014969 (0.015020) Loss: 0.26084 (0.26942) +2025-08-23,18:28:32 | INFO | Train Epoch: 9 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.365 Boundary Ratio: 0.252 Contrastive_loss: 0.25579 (0.25443) Boundary_loss: 0.014989 (0.015020) Loss: 0.27078 (0.26945) +2025-08-23,18:29:29 | INFO | Train Epoch: 9 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.25725 (0.25447) Boundary_loss: 0.015026 (0.015020) Loss: 0.27227 (0.26949) +2025-08-23,18:30:25 | INFO | Train Epoch: 9 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.31666 (0.25548) Boundary_loss: 0.015015 (0.015020) Loss: 0.33167 (0.27050) +2025-08-23,18:31:22 | INFO | Train Epoch: 9 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.27416 (0.25577) Boundary_loss: 0.015110 (0.015021) Loss: 0.28927 (0.27079) +2025-08-23,18:32:18 | INFO | Train Epoch: 9 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.20932 (0.25505) Boundary_loss: 0.014960 (0.015020) Loss: 0.22428 (0.27007) +2025-08-23,18:33:15 | INFO | Train Epoch: 9 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.30855 (0.25587) Boundary_loss: 0.015068 (0.015021) Loss: 0.32362 (0.27089) +2025-08-23,18:34:11 | INFO | Train Epoch: 9 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.19582 (0.25496) Boundary_loss: 0.015082 (0.015022) Loss: 0.21090 (0.26998) +2025-08-23,18:35:08 | INFO | Train Epoch: 9 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.23157 (0.25461) Boundary_loss: 0.015044 (0.015022) Loss: 0.24661 (0.26963) +2025-08-23,18:36:05 | INFO | Train Epoch: 9 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.20414 (0.25387) Boundary_loss: 0.014996 (0.015022) Loss: 0.21913 (0.26889) +2025-08-23,18:37:01 | INFO | Train Epoch: 9 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.28487 (0.25432) Boundary_loss: 0.015174 (0.015024) Loss: 0.30004 (0.26934) +2025-08-23,18:37:58 | INFO | Train Epoch: 9 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.25767 (0.25437) Boundary_loss: 0.015003 (0.015024) Loss: 0.27267 (0.26939) +2025-08-23,18:38:54 | INFO | Train Epoch: 9 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.23927 (0.25415) Boundary_loss: 0.015090 (0.015025) Loss: 0.25436 (0.26918) +2025-08-23,18:39:51 | INFO | Train Epoch: 9 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.19824 (0.25338) Boundary_loss: 0.014936 (0.015024) Loss: 0.21317 (0.26840) +2025-08-23,18:40:47 | INFO | Train Epoch: 9 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.22628 (0.25301) Boundary_loss: 0.014969 (0.015023) Loss: 0.24125 (0.26803) +2025-08-23,18:41:44 | INFO | Train Epoch: 9 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.32268 (0.25395) Boundary_loss: 0.015129 (0.015024) Loss: 0.33781 (0.26897) +2025-08-23,18:42:40 | INFO | Train Epoch: 9 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.21957 (0.25349) Boundary_loss: 0.014984 (0.015024) Loss: 0.23455 (0.26851) +2025-08-23,18:43:37 | INFO | Train Epoch: 9 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.26146 (0.25359) Boundary_loss: 0.015120 (0.015025) Loss: 0.27658 (0.26862) +2025-08-23,18:44:34 | INFO | Train Epoch: 9 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 0.23041 (0.25329) Boundary_loss: 0.014992 (0.015025) Loss: 0.24540 (0.26832) +2025-08-23,18:45:30 | INFO | Train Epoch: 9 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.21497 (0.25280) Boundary_loss: 0.015129 (0.015026) Loss: 0.23010 (0.26783) +2025-08-23,18:46:27 | INFO | Train Epoch: 9 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.22174 (0.25241) Boundary_loss: 0.015091 (0.015027) Loss: 0.23683 (0.26743) +2025-08-23,18:47:24 | INFO | Train Epoch: 9 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.23182 (0.25215) Boundary_loss: 0.014921 (0.015025) Loss: 0.24674 (0.26718) +2025-08-23,18:48:20 | INFO | Train Epoch: 9 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.21768 (0.25172) Boundary_loss: 0.015096 (0.015026) Loss: 0.23278 (0.26675) +2025-08-23,18:49:17 | INFO | Train Epoch: 9 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.252 Boundary Ratio: 0.246 Contrastive_loss: 0.21315 (0.25125) Boundary_loss: 0.015080 (0.015027) Loss: 0.22823 (0.26628) +2025-08-23,18:50:13 | INFO | Train Epoch: 9 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.26296 (0.25140) Boundary_loss: 0.014957 (0.015026) Loss: 0.27792 (0.26642) +2025-08-23,18:51:10 | INFO | Train Epoch: 9 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.27978 (0.25173) Boundary_loss: 0.015122 (0.015027) Loss: 0.29490 (0.26676) +2025-08-23,18:52:06 | INFO | Train Epoch: 9 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.20475 (0.25118) Boundary_loss: 0.015069 (0.015028) Loss: 0.21982 (0.26621) +2025-08-23,18:53:03 | INFO | Train Epoch: 9 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.29263 (0.25166) Boundary_loss: 0.014950 (0.015027) Loss: 0.30758 (0.26669) +2025-08-23,18:53:59 | INFO | Train Epoch: 9 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.22872 (0.25140) Boundary_loss: 0.014968 (0.015026) Loss: 0.24369 (0.26643) +2025-08-23,18:54:56 | INFO | Train Epoch: 9 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 0.19193 (0.25072) Boundary_loss: 0.014963 (0.015025) Loss: 0.20689 (0.26575) +2025-08-23,18:55:52 | INFO | Train Epoch: 9 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.24875 (0.25070) Boundary_loss: 0.014992 (0.015025) Loss: 0.26374 (0.26573) +2025-08-23,18:56:49 | INFO | Train Epoch: 9 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.27518 (0.25097) Boundary_loss: 0.015019 (0.015025) Loss: 0.29020 (0.26600) +2025-08-23,18:57:45 | INFO | Train Epoch: 9 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 49.350 Boundary Ratio: 0.252 Contrastive_loss: 0.28869 (0.25139) Boundary_loss: 0.015069 (0.015025) Loss: 0.30376 (0.26641) +2025-08-23,18:58:42 | INFO | Train Epoch: 9 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.29807 (0.25189) Boundary_loss: 0.015145 (0.015027) Loss: 0.31322 (0.26692) +2025-08-23,18:59:38 | INFO | Train Epoch: 9 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 0.23508 (0.25171) Boundary_loss: 0.014921 (0.015026) Loss: 0.25001 (0.26674) +2025-08-23,19:00:35 | INFO | Train Epoch: 9 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.28849 (0.25211) Boundary_loss: 0.014942 (0.015025) Loss: 0.30343 (0.26713) +2025-08-23,19:01:32 | INFO | Train Epoch: 9 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.25342 (0.25212) Boundary_loss: 0.014919 (0.015024) Loss: 0.26834 (0.26714) +2025-08-23,19:02:28 | INFO | Train Epoch: 9 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.20572 (0.25164) Boundary_loss: 0.014993 (0.015023) Loss: 0.22071 (0.26666) +2025-08-23,19:03:25 | INFO | Train Epoch: 9 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.24220 (0.25154) Boundary_loss: 0.014995 (0.015023) Loss: 0.25720 (0.26656) +2025-08-23,19:04:21 | INFO | Train Epoch: 9 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.30853 (0.25212) Boundary_loss: 0.015054 (0.015023) Loss: 0.32359 (0.26714) +2025-08-23,19:05:18 | INFO | Train Epoch: 9 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.24179 (0.25202) Boundary_loss: 0.015045 (0.015024) Loss: 0.25684 (0.26704) +2025-08-23,19:06:15 | INFO | Train Epoch: 9 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.19938 (0.25149) Boundary_loss: 0.014931 (0.015023) Loss: 0.21431 (0.26651) +2025-08-23,19:07:11 | INFO | Train Epoch: 9 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.26834 (0.25166) Boundary_loss: 0.014908 (0.015021) Loss: 0.28325 (0.26668) +2025-08-23,19:08:08 | INFO | Train Epoch: 9 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 0.26009 (0.25174) Boundary_loss: 0.015052 (0.015022) Loss: 0.27514 (0.26676) +2025-08-23,19:09:04 | INFO | Train Epoch: 9 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.25486 (0.25177) Boundary_loss: 0.014972 (0.015021) Loss: 0.26983 (0.26679) +2025-08-23,19:10:01 | INFO | Train Epoch: 9 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.31771 (0.25240) Boundary_loss: 0.014969 (0.015021) Loss: 0.33268 (0.26742) +2025-08-23,19:10:57 | INFO | Train Epoch: 9 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.105 Boundary Ratio: 0.245 Contrastive_loss: 0.25406 (0.25242) Boundary_loss: 0.014972 (0.015020) Loss: 0.26903 (0.26744) +2025-08-23,19:11:54 | INFO | Train Epoch: 9 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.322 Boundary Ratio: 0.247 Contrastive_loss: 0.24049 (0.25231) Boundary_loss: 0.015085 (0.015021) Loss: 0.25558 (0.26733) +2025-08-23,19:12:51 | INFO | Train Epoch: 9 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.139 Boundary Ratio: 0.246 Contrastive_loss: 0.31256 (0.25287) Boundary_loss: 0.014931 (0.015020) Loss: 0.32749 (0.26789) +2025-08-23,19:13:47 | INFO | Train Epoch: 9 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.31955 (0.25349) Boundary_loss: 0.014856 (0.015019) Loss: 0.33441 (0.26851) +2025-08-23,19:14:44 | INFO | Train Epoch: 9 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.25826 (0.25353) Boundary_loss: 0.014989 (0.015018) Loss: 0.27325 (0.26855) +2025-08-23,19:15:41 | INFO | Train Epoch: 9 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.24826 (0.25348) Boundary_loss: 0.015037 (0.015018) Loss: 0.26330 (0.26850) +2025-08-23,19:16:37 | INFO | Train Epoch: 9 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.28389 (0.25376) Boundary_loss: 0.014934 (0.015018) Loss: 0.29882 (0.26877) +2025-08-23,19:17:34 | INFO | Train Epoch: 9 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.268 Boundary Ratio: 0.246 Contrastive_loss: 0.20556 (0.25333) Boundary_loss: 0.014995 (0.015017) Loss: 0.22056 (0.26834) +2025-08-23,19:18:30 | INFO | Train Epoch: 9 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.22854 (0.25311) Boundary_loss: 0.015033 (0.015018) Loss: 0.24358 (0.26812) +2025-08-23,19:19:27 | INFO | Train Epoch: 9 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 49.221 Boundary Ratio: 0.251 Contrastive_loss: 0.23477 (0.25295) Boundary_loss: 0.015027 (0.015018) Loss: 0.24980 (0.26796) +2025-08-23,19:20:24 | INFO | Train Epoch: 9 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.26805 (0.25308) Boundary_loss: 0.015191 (0.015019) Loss: 0.28324 (0.26810) +2025-08-23,19:21:20 | INFO | Train Epoch: 9 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.23909 (0.25296) Boundary_loss: 0.014944 (0.015019) Loss: 0.25403 (0.26798) +2025-08-23,19:22:17 | INFO | Train Epoch: 9 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.26080 (0.25302) Boundary_loss: 0.015084 (0.015019) Loss: 0.27589 (0.26804) +2025-08-23,19:23:13 | INFO | Train Epoch: 9 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 49.361 Boundary Ratio: 0.252 Contrastive_loss: 0.22425 (0.25278) Boundary_loss: 0.014936 (0.015018) Loss: 0.23919 (0.26780) +2025-08-23,19:24:10 | INFO | Train Epoch: 9 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.24862 (0.25275) Boundary_loss: 0.015129 (0.015019) Loss: 0.26375 (0.26776) +2025-08-23,19:25:06 | INFO | Train Epoch: 9 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.26522 (0.25285) Boundary_loss: 0.014963 (0.015019) Loss: 0.28018 (0.26787) +2025-08-23,19:26:03 | INFO | Train Epoch: 9 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.28215 (0.25309) Boundary_loss: 0.015036 (0.015019) Loss: 0.29718 (0.26811) +2025-08-23,19:26:59 | INFO | Train Epoch: 9 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.23369 (0.25293) Boundary_loss: 0.014974 (0.015019) Loss: 0.24866 (0.26795) +2025-08-23,19:27:56 | INFO | Train Epoch: 9 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 49.486 Boundary Ratio: 0.252 Contrastive_loss: 0.22833 (0.25273) Boundary_loss: 0.015187 (0.015020) Loss: 0.24352 (0.26775) +2025-08-23,19:28:53 | INFO | Train Epoch: 9 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 49.635 Boundary Ratio: 0.253 Contrastive_loss: 0.23283 (0.25257) Boundary_loss: 0.014993 (0.015020) Loss: 0.24782 (0.26759) +2025-08-23,19:29:49 | INFO | Train Epoch: 9 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.26325 (0.25266) Boundary_loss: 0.015106 (0.015021) Loss: 0.27835 (0.26768) +2025-08-23,19:30:46 | INFO | Train Epoch: 9 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.25184 (0.25265) Boundary_loss: 0.015135 (0.015021) Loss: 0.26697 (0.26767) +2025-08-23,19:31:42 | INFO | Train Epoch: 9 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.23927 (0.25255) Boundary_loss: 0.015024 (0.015021) Loss: 0.25429 (0.26757) +2025-08-23,19:32:39 | INFO | Train Epoch: 9 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.22027 (0.25229) Boundary_loss: 0.015018 (0.015021) Loss: 0.23529 (0.26731) +2025-08-23,19:33:36 | INFO | Train Epoch: 9 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 49.299 Boundary Ratio: 0.252 Contrastive_loss: 0.21972 (0.25204) Boundary_loss: 0.015111 (0.015022) Loss: 0.23483 (0.26706) +2025-08-23,19:34:32 | INFO | Train Epoch: 9 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.24246 (0.25197) Boundary_loss: 0.015012 (0.015022) Loss: 0.25747 (0.26699) +2025-08-23,19:35:29 | INFO | Train Epoch: 9 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.25021 (0.25195) Boundary_loss: 0.015137 (0.015023) Loss: 0.26535 (0.26698) +2025-08-23,19:36:25 | INFO | Train Epoch: 9 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.23155 (0.25180) Boundary_loss: 0.014929 (0.015022) Loss: 0.24648 (0.26682) +2025-08-23,19:37:22 | INFO | Train Epoch: 9 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 0.28879 (0.25208) Boundary_loss: 0.014968 (0.015022) Loss: 0.30376 (0.26710) +2025-08-23,19:38:18 | INFO | Train Epoch: 9 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 0.25083 (0.25207) Boundary_loss: 0.015028 (0.015022) Loss: 0.26586 (0.26709) +2025-08-23,19:39:15 | INFO | Train Epoch: 9 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.28887 (0.25234) Boundary_loss: 0.015003 (0.015022) Loss: 0.30388 (0.26736) +2025-08-23,19:40:12 | INFO | Train Epoch: 9 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 0.24835 (0.25231) Boundary_loss: 0.014974 (0.015021) Loss: 0.26333 (0.26733) +2025-08-23,19:41:08 | INFO | Train Epoch: 9 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.25348 (0.25232) Boundary_loss: 0.014972 (0.015021) Loss: 0.26846 (0.26734) +2025-08-23,19:42:05 | INFO | Train Epoch: 9 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.29120 (0.25260) Boundary_loss: 0.014989 (0.015021) Loss: 0.30619 (0.26762) +2025-08-23,19:43:01 | INFO | Train Epoch: 9 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.26566 (0.25270) Boundary_loss: 0.015057 (0.015021) Loss: 0.28072 (0.26772) +2025-08-23,19:43:58 | INFO | Train Epoch: 9 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 49.504 Boundary Ratio: 0.253 Contrastive_loss: 0.19132 (0.25226) Boundary_loss: 0.015198 (0.015022) Loss: 0.20652 (0.26728) +2025-08-23,19:44:54 | INFO | Train Epoch: 9 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.309 Boundary Ratio: 0.246 Contrastive_loss: 0.26609 (0.25236) Boundary_loss: 0.014970 (0.015022) Loss: 0.28106 (0.26738) +2025-08-23,19:45:51 | INFO | Train Epoch: 9 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.21778 (0.25211) Boundary_loss: 0.015043 (0.015022) Loss: 0.23283 (0.26713) +2025-08-23,19:46:47 | INFO | Train Epoch: 9 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.346 Boundary Ratio: 0.247 Contrastive_loss: 0.24632 (0.25207) Boundary_loss: 0.015019 (0.015022) Loss: 0.26134 (0.26709) +2025-08-23,19:47:44 | INFO | Train Epoch: 9 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.25371 (0.25208) Boundary_loss: 0.015076 (0.015022) Loss: 0.26879 (0.26711) +2025-08-23,19:48:40 | INFO | Train Epoch: 9 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.26241 (0.25215) Boundary_loss: 0.014997 (0.015022) Loss: 0.27740 (0.26718) +2025-08-23,19:49:37 | INFO | Train Epoch: 9 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.23844 (0.25206) Boundary_loss: 0.014941 (0.015022) Loss: 0.25338 (0.26708) +2025-08-23,19:50:33 | INFO | Train Epoch: 9 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.25230 (0.25206) Boundary_loss: 0.014998 (0.015022) Loss: 0.26729 (0.26708) +2025-08-23,19:51:30 | INFO | Train Epoch: 9 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21995 (0.25184) Boundary_loss: 0.015022 (0.015022) Loss: 0.23498 (0.26687) +2025-08-23,19:52:26 | INFO | Train Epoch: 9 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.23220 (0.25171) Boundary_loss: 0.015010 (0.015021) Loss: 0.24721 (0.26673) +2025-08-23,19:53:23 | INFO | Train Epoch: 9 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.29626 (0.25201) Boundary_loss: 0.015040 (0.015022) Loss: 0.31130 (0.26703) +2025-08-23,19:54:19 | INFO | Train Epoch: 9 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.25440 (0.25203) Boundary_loss: 0.015187 (0.015023) Loss: 0.26958 (0.26705) +2025-08-23,19:55:16 | INFO | Train Epoch: 9 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.334 Boundary Ratio: 0.247 Contrastive_loss: 0.23772 (0.25193) Boundary_loss: 0.015086 (0.015023) Loss: 0.25280 (0.26695) +2025-08-23,19:56:12 | INFO | Train Epoch: 9 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.25342 (0.25194) Boundary_loss: 0.014970 (0.015023) Loss: 0.26839 (0.26696) +2025-08-23,19:57:09 | INFO | Train Epoch: 9 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.25107 (0.25194) Boundary_loss: 0.015032 (0.015023) Loss: 0.26610 (0.26696) +2025-08-23,19:58:05 | INFO | Train Epoch: 9 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.21348 (0.25169) Boundary_loss: 0.014870 (0.015022) Loss: 0.22835 (0.26671) +2025-08-23,19:59:02 | INFO | Train Epoch: 9 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.25891 (0.25173) Boundary_loss: 0.015076 (0.015022) Loss: 0.27398 (0.26676) +2025-08-23,19:59:58 | INFO | Train Epoch: 9 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.24220 (0.25167) Boundary_loss: 0.015149 (0.015023) Loss: 0.25735 (0.26670) +2025-08-23,20:00:55 | INFO | Train Epoch: 9 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.29789 (0.25197) Boundary_loss: 0.014957 (0.015023) Loss: 0.31285 (0.26699) +2025-08-23,20:01:51 | INFO | Train Epoch: 9 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.26072 (0.25202) Boundary_loss: 0.015024 (0.015023) Loss: 0.27575 (0.26704) +2025-08-23,20:02:48 | INFO | Train Epoch: 9 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.23411 (0.25191) Boundary_loss: 0.015000 (0.015022) Loss: 0.24911 (0.26693) +2025-08-23,20:03:45 | INFO | Train Epoch: 9 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.23854 (0.25183) Boundary_loss: 0.015002 (0.015022) Loss: 0.25354 (0.26685) +2025-08-23,20:04:41 | INFO | Train Epoch: 9 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.31105 (0.25219) Boundary_loss: 0.015126 (0.015023) Loss: 0.32618 (0.26721) +2025-08-23,20:05:38 | INFO | Train Epoch: 9 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.20566 (0.25191) Boundary_loss: 0.014932 (0.015022) Loss: 0.22059 (0.26693) +2025-08-23,20:06:34 | INFO | Train Epoch: 9 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.25132 (0.25190) Boundary_loss: 0.015064 (0.015023) Loss: 0.26639 (0.26692) +2025-08-23,20:07:31 | INFO | Train Epoch: 9 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 49.324 Boundary Ratio: 0.252 Contrastive_loss: 0.18681 (0.25151) Boundary_loss: 0.014943 (0.015022) Loss: 0.20175 (0.26653) +2025-08-23,20:08:27 | INFO | Train Epoch: 9 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.24459 (0.25147) Boundary_loss: 0.015074 (0.015022) Loss: 0.25967 (0.26649) +2025-08-23,20:09:24 | INFO | Train Epoch: 9 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.21600 (0.25125) Boundary_loss: 0.014912 (0.015022) Loss: 0.23091 (0.26628) +2025-08-23,20:10:20 | INFO | Train Epoch: 9 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.26624 (0.25134) Boundary_loss: 0.014957 (0.015021) Loss: 0.28120 (0.26636) +2025-08-23,20:11:17 | INFO | Train Epoch: 9 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.24273 (0.25129) Boundary_loss: 0.015073 (0.015022) Loss: 0.25780 (0.26631) +2025-08-23,20:12:13 | INFO | Train Epoch: 9 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.26700 (0.25138) Boundary_loss: 0.014979 (0.015021) Loss: 0.28198 (0.26641) +2025-08-23,20:13:10 | INFO | Train Epoch: 9 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.361 Boundary Ratio: 0.247 Contrastive_loss: 0.28728 (0.25159) Boundary_loss: 0.014948 (0.015021) Loss: 0.30223 (0.26662) +2025-08-23,20:14:07 | INFO | Train Epoch: 9 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.396 Boundary Ratio: 0.247 Contrastive_loss: 0.18409 (0.25120) Boundary_loss: 0.015010 (0.015021) Loss: 0.19910 (0.26622) +2025-08-23,20:15:04 | INFO | Train Epoch: 9 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 0.25494 (0.25122) Boundary_loss: 0.015017 (0.015021) Loss: 0.26996 (0.26624) +2025-08-23,20:16:00 | INFO | Train Epoch: 9 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 49.494 Boundary Ratio: 0.253 Contrastive_loss: 0.22183 (0.25105) Boundary_loss: 0.015092 (0.015021) Loss: 0.23692 (0.26608) +2025-08-23,20:16:57 | INFO | Train Epoch: 9 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.23984 (0.25099) Boundary_loss: 0.014932 (0.015021) Loss: 0.25478 (0.26601) +2025-08-23,20:17:53 | INFO | Train Epoch: 9 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.25397 (0.25101) Boundary_loss: 0.014999 (0.015021) Loss: 0.26897 (0.26603) +2025-08-23,20:18:50 | INFO | Train Epoch: 9 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.18395 (0.25063) Boundary_loss: 0.014931 (0.015020) Loss: 0.19888 (0.26565) +2025-08-23,20:19:46 | INFO | Train Epoch: 9 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.21364 (0.25042) Boundary_loss: 0.014964 (0.015020) Loss: 0.22861 (0.26544) +2025-08-23,20:20:43 | INFO | Train Epoch: 9 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 0.21104 (0.25020) Boundary_loss: 0.015110 (0.015020) Loss: 0.22615 (0.26522) +2025-08-23,20:21:40 | INFO | Train Epoch: 9 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.24554 (0.25017) Boundary_loss: 0.015141 (0.015021) Loss: 0.26068 (0.26520) +2025-08-23,20:22:36 | INFO | Train Epoch: 9 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 49.098 Boundary Ratio: 0.250 Contrastive_loss: 0.25468 (0.25020) Boundary_loss: 0.015067 (0.015021) Loss: 0.26974 (0.26522) +2025-08-23,20:23:33 | INFO | Train Epoch: 9 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 0.23107 (0.25009) Boundary_loss: 0.015076 (0.015022) Loss: 0.24615 (0.26512) +2025-08-23,20:24:29 | INFO | Train Epoch: 9 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.27088 (0.25021) Boundary_loss: 0.014916 (0.015021) Loss: 0.28580 (0.26523) +2025-08-23,20:25:26 | INFO | Train Epoch: 9 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.22800 (0.25009) Boundary_loss: 0.015007 (0.015021) Loss: 0.24301 (0.26511) +2025-08-23,20:26:23 | INFO | Train Epoch: 9 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 0.22154 (0.24993) Boundary_loss: 0.015125 (0.015022) Loss: 0.23666 (0.26495) +2025-08-23,20:27:19 | INFO | Train Epoch: 9 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 47.908 Boundary Ratio: 0.244 Contrastive_loss: 0.31079 (0.25026) Boundary_loss: 0.015138 (0.015022) Loss: 0.32593 (0.26528) +2025-08-23,20:28:16 | INFO | Train Epoch: 9 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.26082 (0.25032) Boundary_loss: 0.015030 (0.015022) Loss: 0.27585 (0.26534) +2025-08-23,20:29:13 | INFO | Train Epoch: 9 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 0.27449 (0.25045) Boundary_loss: 0.015047 (0.015022) Loss: 0.28954 (0.26547) +2025-08-23,20:30:09 | INFO | Train Epoch: 9 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.26900 (0.25054) Boundary_loss: 0.014938 (0.015022) Loss: 0.28394 (0.26557) +2025-08-23,20:31:06 | INFO | Train Epoch: 9 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.28797 (0.25074) Boundary_loss: 0.014959 (0.015022) Loss: 0.30293 (0.26576) +2025-08-23,20:32:02 | INFO | Train Epoch: 9 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 0.24827 (0.25073) Boundary_loss: 0.015023 (0.015022) Loss: 0.26329 (0.26575) +2025-08-23,20:32:59 | INFO | Train Epoch: 9 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.24152 (0.25068) Boundary_loss: 0.014949 (0.015021) Loss: 0.25647 (0.26570) +2025-08-23,20:33:56 | INFO | Train Epoch: 9 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.33532 (0.25112) Boundary_loss: 0.015007 (0.015021) Loss: 0.35032 (0.26614) +2025-08-23,20:34:52 | INFO | Train Epoch: 9 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.29284 (0.25133) Boundary_loss: 0.015044 (0.015021) Loss: 0.30789 (0.26635) +2025-08-23,20:35:49 | INFO | Train Epoch: 9 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.785 Boundary Ratio: 0.254 Contrastive_loss: 0.27022 (0.25143) Boundary_loss: 0.015073 (0.015021) Loss: 0.28529 (0.26645) +2025-08-23,20:36:46 | INFO | Train Epoch: 9 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.23467 (0.25134) Boundary_loss: 0.014970 (0.015021) Loss: 0.24964 (0.26637) +2025-08-23,20:37:42 | INFO | Train Epoch: 9 [10035712/26365952 (38%)] Avg Boundaries (per batch): 49.305 Boundary Ratio: 0.252 Contrastive_loss: 0.18380 (0.25100) Boundary_loss: 0.015025 (0.015021) Loss: 0.19882 (0.26602) +2025-08-23,20:38:39 | INFO | Train Epoch: 9 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.25150 (0.25100) Boundary_loss: 0.015017 (0.015021) Loss: 0.26652 (0.26603) +2025-08-23,20:39:35 | INFO | Train Epoch: 9 [10138112/26365952 (38%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 0.19320 (0.25071) Boundary_loss: 0.015153 (0.015022) Loss: 0.20835 (0.26574) +2025-08-23,20:40:32 | INFO | Train Epoch: 9 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.287 Boundary Ratio: 0.246 Contrastive_loss: 0.20073 (0.25046) Boundary_loss: 0.015037 (0.015022) Loss: 0.21577 (0.26549) +2025-08-23,20:41:29 | INFO | Train Epoch: 9 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.28752 (0.25065) Boundary_loss: 0.014924 (0.015021) Loss: 0.30245 (0.26567) +2025-08-23,20:42:25 | INFO | Train Epoch: 9 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.21033 (0.25045) Boundary_loss: 0.015044 (0.015022) Loss: 0.22538 (0.26547) +2025-08-23,20:43:22 | INFO | Train Epoch: 9 [10342912/26365952 (39%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.28872 (0.25064) Boundary_loss: 0.015005 (0.015021) Loss: 0.30372 (0.26566) +2025-08-23,20:44:19 | INFO | Train Epoch: 9 [10394112/26365952 (39%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 0.20697 (0.25042) Boundary_loss: 0.014952 (0.015021) Loss: 0.22192 (0.26544) +2025-08-23,20:45:15 | INFO | Train Epoch: 9 [10445312/26365952 (40%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 0.23818 (0.25036) Boundary_loss: 0.015050 (0.015021) Loss: 0.25323 (0.26538) +2025-08-23,20:46:12 | INFO | Train Epoch: 9 [10496512/26365952 (40%)] Avg Boundaries (per batch): 49.564 Boundary Ratio: 0.253 Contrastive_loss: 0.30067 (0.25061) Boundary_loss: 0.015077 (0.015022) Loss: 0.31575 (0.26563) +2025-08-23,20:47:09 | INFO | Train Epoch: 9 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.23988 (0.25056) Boundary_loss: 0.015033 (0.015022) Loss: 0.25491 (0.26558) +2025-08-23,20:48:05 | INFO | Train Epoch: 9 [10598912/26365952 (40%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.20104 (0.25032) Boundary_loss: 0.014901 (0.015021) Loss: 0.21594 (0.26534) +2025-08-23,20:49:02 | INFO | Train Epoch: 9 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.29372 (0.25053) Boundary_loss: 0.014948 (0.015021) Loss: 0.30867 (0.26555) +2025-08-23,20:49:58 | INFO | Train Epoch: 9 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.26302 (0.25058) Boundary_loss: 0.014981 (0.015021) Loss: 0.27800 (0.26561) +2025-08-23,20:50:55 | INFO | Train Epoch: 9 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.18311 (0.25027) Boundary_loss: 0.014973 (0.015020) Loss: 0.19808 (0.26529) +2025-08-23,20:51:51 | INFO | Train Epoch: 9 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.31455 (0.25057) Boundary_loss: 0.015103 (0.015021) Loss: 0.32965 (0.26559) +2025-08-23,20:52:48 | INFO | Train Epoch: 9 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.19256 (0.25030) Boundary_loss: 0.014874 (0.015020) Loss: 0.20743 (0.26532) +2025-08-23,20:53:45 | INFO | Train Epoch: 9 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.25931 (0.25034) Boundary_loss: 0.014892 (0.015019) Loss: 0.27421 (0.26536) +2025-08-23,20:54:41 | INFO | Train Epoch: 9 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.26691 (0.25042) Boundary_loss: 0.015171 (0.015020) Loss: 0.28208 (0.26544) +2025-08-23,20:55:38 | INFO | Train Epoch: 9 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.25475 (0.25044) Boundary_loss: 0.014983 (0.015020) Loss: 0.26973 (0.26546) +2025-08-23,20:56:34 | INFO | Train Epoch: 9 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.27534 (0.25055) Boundary_loss: 0.015014 (0.015020) Loss: 0.29035 (0.26557) +2025-08-23,20:57:31 | INFO | Train Epoch: 9 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.25227 (0.25056) Boundary_loss: 0.014999 (0.015020) Loss: 0.26727 (0.26558) +2025-08-23,20:58:27 | INFO | Train Epoch: 9 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.27121 (0.25065) Boundary_loss: 0.015099 (0.015020) Loss: 0.28631 (0.26567) +2025-08-23,20:59:24 | INFO | Train Epoch: 9 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.316 Boundary Ratio: 0.247 Contrastive_loss: 0.23162 (0.25057) Boundary_loss: 0.015000 (0.015020) Loss: 0.24662 (0.26559) +2025-08-23,21:00:20 | INFO | Train Epoch: 9 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.22284 (0.25044) Boundary_loss: 0.014999 (0.015020) Loss: 0.23784 (0.26546) +2025-08-23,21:01:17 | INFO | Train Epoch: 9 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.26223 (0.25049) Boundary_loss: 0.014971 (0.015020) Loss: 0.27720 (0.26551) +2025-08-23,21:02:14 | INFO | Train Epoch: 9 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.21276 (0.25032) Boundary_loss: 0.015070 (0.015020) Loss: 0.22783 (0.26534) +2025-08-23,21:03:10 | INFO | Train Epoch: 9 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.26796 (0.25040) Boundary_loss: 0.015150 (0.015021) Loss: 0.28311 (0.26542) +2025-08-23,21:04:07 | INFO | Train Epoch: 9 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.16233 (0.25001) Boundary_loss: 0.014967 (0.015020) Loss: 0.17730 (0.26503) +2025-08-23,21:05:03 | INFO | Train Epoch: 9 [11520512/26365952 (44%)] Avg Boundaries (per batch): 49.273 Boundary Ratio: 0.251 Contrastive_loss: 0.25973 (0.25005) Boundary_loss: 0.015088 (0.015021) Loss: 0.27482 (0.26508) +2025-08-23,21:06:00 | INFO | Train Epoch: 9 [11571712/26365952 (44%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.21839 (0.24992) Boundary_loss: 0.015112 (0.015021) Loss: 0.23351 (0.26494) +2025-08-23,21:06:57 | INFO | Train Epoch: 9 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.303 Boundary Ratio: 0.246 Contrastive_loss: 0.23868 (0.24987) Boundary_loss: 0.015043 (0.015021) Loss: 0.25372 (0.26489) +2025-08-23,21:07:53 | INFO | Train Epoch: 9 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.21550 (0.24972) Boundary_loss: 0.015066 (0.015021) Loss: 0.23057 (0.26474) +2025-08-23,21:08:50 | INFO | Train Epoch: 9 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.30357 (0.24995) Boundary_loss: 0.014933 (0.015021) Loss: 0.31850 (0.26497) +2025-08-23,21:09:46 | INFO | Train Epoch: 9 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.23310 (0.24988) Boundary_loss: 0.015026 (0.015021) Loss: 0.24812 (0.26490) +2025-08-23,21:10:43 | INFO | Train Epoch: 9 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.17568 (0.24956) Boundary_loss: 0.015034 (0.015021) Loss: 0.19072 (0.26458) +2025-08-23,21:11:39 | INFO | Train Epoch: 9 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.21200 (0.24940) Boundary_loss: 0.014953 (0.015021) Loss: 0.22695 (0.26442) +2025-08-23,21:12:36 | INFO | Train Epoch: 9 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.32649 (0.24973) Boundary_loss: 0.015010 (0.015021) Loss: 0.34150 (0.26475) +2025-08-23,21:13:33 | INFO | Train Epoch: 9 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.22409 (0.24962) Boundary_loss: 0.015001 (0.015021) Loss: 0.23909 (0.26464) +2025-08-23,21:14:29 | INFO | Train Epoch: 9 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.25309 (0.24963) Boundary_loss: 0.014926 (0.015020) Loss: 0.26802 (0.26465) +2025-08-23,21:15:26 | INFO | Train Epoch: 9 [12083712/26365952 (46%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 0.28350 (0.24977) Boundary_loss: 0.014986 (0.015020) Loss: 0.29848 (0.26479) +2025-08-23,21:16:22 | INFO | Train Epoch: 9 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.24458 (0.24975) Boundary_loss: 0.014995 (0.015020) Loss: 0.25957 (0.26477) +2025-08-23,21:17:19 | INFO | Train Epoch: 9 [12186112/26365952 (46%)] Avg Boundaries (per batch): 49.664 Boundary Ratio: 0.253 Contrastive_loss: 0.25422 (0.24977) Boundary_loss: 0.014980 (0.015020) Loss: 0.26920 (0.26479) +2025-08-23,21:18:16 | INFO | Train Epoch: 9 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 0.26065 (0.24982) Boundary_loss: 0.015043 (0.015020) Loss: 0.27569 (0.26484) +2025-08-23,21:19:12 | INFO | Train Epoch: 9 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.236 Boundary Ratio: 0.246 Contrastive_loss: 0.20418 (0.24963) Boundary_loss: 0.014944 (0.015020) Loss: 0.21912 (0.26465) +2025-08-23,21:20:09 | INFO | Train Epoch: 9 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.24648 (0.24961) Boundary_loss: 0.015001 (0.015019) Loss: 0.26148 (0.26463) +2025-08-23,21:21:05 | INFO | Train Epoch: 9 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.23650 (0.24956) Boundary_loss: 0.014923 (0.015019) Loss: 0.25143 (0.26458) +2025-08-23,21:22:02 | INFO | Train Epoch: 9 [12442112/26365952 (47%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.22592 (0.24946) Boundary_loss: 0.015059 (0.015019) Loss: 0.24098 (0.26448) +2025-08-23,21:22:59 | INFO | Train Epoch: 9 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.27299 (0.24956) Boundary_loss: 0.014988 (0.015019) Loss: 0.28798 (0.26458) +2025-08-23,21:23:55 | INFO | Train Epoch: 9 [12544512/26365952 (48%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.24479 (0.24954) Boundary_loss: 0.015076 (0.015019) Loss: 0.25987 (0.26456) +2025-08-23,21:24:51 | INFO | Train Epoch: 9 [12595712/26365952 (48%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 0.27894 (0.24966) Boundary_loss: 0.015069 (0.015020) Loss: 0.29400 (0.26468) +2025-08-23,21:25:48 | INFO | Train Epoch: 9 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.21513 (0.24952) Boundary_loss: 0.014889 (0.015019) Loss: 0.23002 (0.26454) +2025-08-23,21:26:45 | INFO | Train Epoch: 9 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.22606 (0.24943) Boundary_loss: 0.015037 (0.015019) Loss: 0.24109 (0.26444) +2025-08-23,21:27:41 | INFO | Train Epoch: 9 [12749312/26365952 (48%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.22025 (0.24931) Boundary_loss: 0.015025 (0.015019) Loss: 0.23527 (0.26433) +2025-08-23,21:28:38 | INFO | Train Epoch: 9 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.26265 (0.24936) Boundary_loss: 0.014987 (0.015019) Loss: 0.27764 (0.26438) +2025-08-23,21:29:34 | INFO | Train Epoch: 9 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.26460 (0.24942) Boundary_loss: 0.014954 (0.015019) Loss: 0.27955 (0.26444) +2025-08-23,21:30:31 | INFO | Train Epoch: 9 [12902912/26365952 (49%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 0.22556 (0.24933) Boundary_loss: 0.014949 (0.015018) Loss: 0.24051 (0.26435) +2025-08-23,21:31:28 | INFO | Train Epoch: 9 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.25304 (0.24934) Boundary_loss: 0.015068 (0.015019) Loss: 0.26811 (0.26436) +2025-08-23,21:32:24 | INFO | Train Epoch: 9 [13005312/26365952 (49%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 0.32121 (0.24962) Boundary_loss: 0.015027 (0.015019) Loss: 0.33623 (0.26464) +2025-08-23,21:33:21 | INFO | Train Epoch: 9 [13056512/26365952 (50%)] Avg Boundaries (per batch): 47.930 Boundary Ratio: 0.245 Contrastive_loss: 0.20815 (0.24946) Boundary_loss: 0.014989 (0.015019) Loss: 0.22314 (0.26448) +2025-08-23,21:34:17 | INFO | Train Epoch: 9 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.20886 (0.24930) Boundary_loss: 0.015036 (0.015019) Loss: 0.22390 (0.26432) +2025-08-23,21:35:14 | INFO | Train Epoch: 9 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.36781 (0.24976) Boundary_loss: 0.015050 (0.015019) Loss: 0.38286 (0.26478) +2025-08-23,21:36:10 | INFO | Train Epoch: 9 [13210112/26365952 (50%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.27602 (0.24986) Boundary_loss: 0.015001 (0.015019) Loss: 0.29102 (0.26488) +2025-08-23,21:37:07 | INFO | Train Epoch: 9 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.23048 (0.24979) Boundary_loss: 0.014998 (0.015019) Loss: 0.24548 (0.26481) +2025-08-23,21:38:03 | INFO | Train Epoch: 9 [13312512/26365952 (50%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.17888 (0.24952) Boundary_loss: 0.015034 (0.015019) Loss: 0.19391 (0.26454) +2025-08-23,21:39:00 | INFO | Train Epoch: 9 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.30164 (0.24972) Boundary_loss: 0.015198 (0.015019) Loss: 0.31684 (0.26474) +2025-08-23,21:39:57 | INFO | Train Epoch: 9 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.22832 (0.24964) Boundary_loss: 0.015011 (0.015019) Loss: 0.24333 (0.26466) +2025-08-23,21:40:53 | INFO | Train Epoch: 9 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.23328 (0.24957) Boundary_loss: 0.014946 (0.015019) Loss: 0.24822 (0.26459) +2025-08-23,21:41:50 | INFO | Train Epoch: 9 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.293 Boundary Ratio: 0.246 Contrastive_loss: 0.22535 (0.24948) Boundary_loss: 0.014980 (0.015019) Loss: 0.24033 (0.26450) +2025-08-23,21:42:46 | INFO | Train Epoch: 9 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.28169 (0.24960) Boundary_loss: 0.014969 (0.015019) Loss: 0.29666 (0.26462) +2025-08-23,21:43:43 | INFO | Train Epoch: 9 [13619712/26365952 (52%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.30792 (0.24982) Boundary_loss: 0.014978 (0.015019) Loss: 0.32290 (0.26484) +2025-08-23,21:44:40 | INFO | Train Epoch: 9 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.26879 (0.24989) Boundary_loss: 0.015036 (0.015019) Loss: 0.28383 (0.26491) +2025-08-23,21:45:36 | INFO | Train Epoch: 9 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.29990 (0.25008) Boundary_loss: 0.014871 (0.015018) Loss: 0.31477 (0.26510) +2025-08-23,21:46:33 | INFO | Train Epoch: 9 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.19118 (0.24986) Boundary_loss: 0.014848 (0.015017) Loss: 0.20603 (0.26488) +2025-08-23,21:47:30 | INFO | Train Epoch: 9 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.20741 (0.24970) Boundary_loss: 0.014989 (0.015017) Loss: 0.22240 (0.26472) +2025-08-23,21:48:26 | INFO | Train Epoch: 9 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.23384 (0.24965) Boundary_loss: 0.015072 (0.015018) Loss: 0.24892 (0.26466) +2025-08-23,21:49:23 | INFO | Train Epoch: 9 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.23137 (0.24958) Boundary_loss: 0.014952 (0.015017) Loss: 0.24632 (0.26460) +2025-08-23,21:50:20 | INFO | Train Epoch: 9 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.26535 (0.24964) Boundary_loss: 0.014976 (0.015017) Loss: 0.28032 (0.26465) +2025-08-23,21:51:16 | INFO | Train Epoch: 9 [14029312/26365952 (53%)] Avg Boundaries (per batch): 49.293 Boundary Ratio: 0.251 Contrastive_loss: 0.28677 (0.24977) Boundary_loss: 0.015094 (0.015017) Loss: 0.30187 (0.26479) +2025-08-23,21:52:13 | INFO | Train Epoch: 9 [14080512/26365952 (53%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.22337 (0.24968) Boundary_loss: 0.015123 (0.015018) Loss: 0.23850 (0.26469) +2025-08-23,21:53:09 | INFO | Train Epoch: 9 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.18590 (0.24945) Boundary_loss: 0.014852 (0.015017) Loss: 0.20075 (0.26446) +2025-08-23,21:54:06 | INFO | Train Epoch: 9 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.30125 (0.24963) Boundary_loss: 0.014928 (0.015017) Loss: 0.31618 (0.26465) +2025-08-23,21:55:02 | INFO | Train Epoch: 9 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.31022 (0.24985) Boundary_loss: 0.014978 (0.015017) Loss: 0.32520 (0.26487) +2025-08-23,21:55:59 | INFO | Train Epoch: 9 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.28638 (0.24998) Boundary_loss: 0.015019 (0.015017) Loss: 0.30140 (0.26500) +2025-08-23,21:56:56 | INFO | Train Epoch: 9 [14336512/26365952 (54%)] Avg Boundaries (per batch): 49.477 Boundary Ratio: 0.252 Contrastive_loss: 0.22798 (0.24990) Boundary_loss: 0.015013 (0.015017) Loss: 0.24299 (0.26492) +2025-08-23,21:57:52 | INFO | Train Epoch: 9 [14387712/26365952 (55%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.25362 (0.24991) Boundary_loss: 0.014918 (0.015016) Loss: 0.26853 (0.26493) +2025-08-23,21:58:49 | INFO | Train Epoch: 9 [14438912/26365952 (55%)] Avg Boundaries (per batch): 49.457 Boundary Ratio: 0.252 Contrastive_loss: 0.24406 (0.24989) Boundary_loss: 0.015132 (0.015017) Loss: 0.25919 (0.26491) +2025-08-23,21:59:45 | INFO | Train Epoch: 9 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.24105 (0.24986) Boundary_loss: 0.015103 (0.015017) Loss: 0.25615 (0.26488) +2025-08-23,22:00:42 | INFO | Train Epoch: 9 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.22982 (0.24979) Boundary_loss: 0.014982 (0.015017) Loss: 0.24480 (0.26481) +2025-08-23,22:01:39 | INFO | Train Epoch: 9 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.31134 (0.25001) Boundary_loss: 0.014904 (0.015017) Loss: 0.32624 (0.26502) +2025-08-23,22:02:35 | INFO | Train Epoch: 9 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.29024 (0.25015) Boundary_loss: 0.015015 (0.015017) Loss: 0.30526 (0.26516) +2025-08-23,22:03:32 | INFO | Train Epoch: 9 [14694912/26365952 (56%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.21989 (0.25004) Boundary_loss: 0.015117 (0.015017) Loss: 0.23501 (0.26506) +2025-08-23,22:04:29 | INFO | Train Epoch: 9 [14746112/26365952 (56%)] Avg Boundaries (per batch): 49.406 Boundary Ratio: 0.252 Contrastive_loss: 0.18787 (0.24983) Boundary_loss: 0.014930 (0.015017) Loss: 0.20280 (0.26484) +2025-08-23,22:05:25 | INFO | Train Epoch: 9 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.29734 (0.24999) Boundary_loss: 0.015054 (0.015017) Loss: 0.31239 (0.26501) +2025-08-23,22:06:22 | INFO | Train Epoch: 9 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.19350 (0.24980) Boundary_loss: 0.014997 (0.015017) Loss: 0.20850 (0.26481) +2025-08-23,22:07:19 | INFO | Train Epoch: 9 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.28293 (0.24991) Boundary_loss: 0.014988 (0.015017) Loss: 0.29791 (0.26493) +2025-08-23,22:08:15 | INFO | Train Epoch: 9 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.30454 (0.25010) Boundary_loss: 0.015090 (0.015017) Loss: 0.31963 (0.26511) +2025-08-23,22:09:12 | INFO | Train Epoch: 9 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.24438 (0.25008) Boundary_loss: 0.015117 (0.015017) Loss: 0.25949 (0.26509) +2025-08-23,22:10:08 | INFO | Train Epoch: 9 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.22238 (0.24998) Boundary_loss: 0.014985 (0.015017) Loss: 0.23736 (0.26500) +2025-08-23,22:11:05 | INFO | Train Epoch: 9 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.28364 (0.25010) Boundary_loss: 0.015187 (0.015018) Loss: 0.29883 (0.26512) +2025-08-23,22:12:01 | INFO | Train Epoch: 9 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.28308 (0.25021) Boundary_loss: 0.014986 (0.015018) Loss: 0.29806 (0.26523) +2025-08-23,22:12:58 | INFO | Train Epoch: 9 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.28493 (0.25033) Boundary_loss: 0.014939 (0.015017) Loss: 0.29987 (0.26534) +2025-08-23,22:13:55 | INFO | Train Epoch: 9 [15258112/26365952 (58%)] Avg Boundaries (per batch): 49.289 Boundary Ratio: 0.251 Contrastive_loss: 0.25920 (0.25035) Boundary_loss: 0.015130 (0.015018) Loss: 0.27433 (0.26537) +2025-08-23,22:14:51 | INFO | Train Epoch: 9 [15309312/26365952 (58%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.20048 (0.25019) Boundary_loss: 0.014966 (0.015017) Loss: 0.21544 (0.26521) +2025-08-23,22:15:48 | INFO | Train Epoch: 9 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.22353 (0.25010) Boundary_loss: 0.014874 (0.015017) Loss: 0.23841 (0.26512) +2025-08-23,22:16:45 | INFO | Train Epoch: 9 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.25939 (0.25013) Boundary_loss: 0.014921 (0.015017) Loss: 0.27431 (0.26515) +2025-08-23,22:17:41 | INFO | Train Epoch: 9 [15462912/26365952 (59%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.23630 (0.25009) Boundary_loss: 0.014878 (0.015016) Loss: 0.25118 (0.26510) +2025-08-23,22:18:38 | INFO | Train Epoch: 9 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.492 Boundary Ratio: 0.247 Contrastive_loss: 0.21618 (0.24997) Boundary_loss: 0.015010 (0.015016) Loss: 0.23119 (0.26499) +2025-08-23,22:19:34 | INFO | Train Epoch: 9 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.27232 (0.25005) Boundary_loss: 0.015062 (0.015016) Loss: 0.28738 (0.26506) +2025-08-23,22:20:31 | INFO | Train Epoch: 9 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.24780 (0.25004) Boundary_loss: 0.014978 (0.015016) Loss: 0.26278 (0.26506) +2025-08-23,22:21:28 | INFO | Train Epoch: 9 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.31483 (0.25025) Boundary_loss: 0.015121 (0.015017) Loss: 0.32995 (0.26527) +2025-08-23,22:22:24 | INFO | Train Epoch: 9 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.092 Boundary Ratio: 0.245 Contrastive_loss: 0.19564 (0.25007) Boundary_loss: 0.014922 (0.015016) Loss: 0.21056 (0.26509) +2025-08-23,22:23:21 | INFO | Train Epoch: 9 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.27380 (0.25015) Boundary_loss: 0.014891 (0.015016) Loss: 0.28869 (0.26517) +2025-08-23,22:24:17 | INFO | Train Epoch: 9 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.18994 (0.24996) Boundary_loss: 0.015019 (0.015016) Loss: 0.20496 (0.26497) +2025-08-23,22:25:14 | INFO | Train Epoch: 9 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.25851 (0.24998) Boundary_loss: 0.015055 (0.015016) Loss: 0.27356 (0.26500) +2025-08-23,22:26:10 | INFO | Train Epoch: 9 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.27435 (0.25006) Boundary_loss: 0.014977 (0.015016) Loss: 0.28932 (0.26508) +2025-08-23,22:27:07 | INFO | Train Epoch: 9 [15974912/26365952 (61%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.20986 (0.24993) Boundary_loss: 0.015117 (0.015016) Loss: 0.22497 (0.26495) +2025-08-23,22:28:03 | INFO | Train Epoch: 9 [16026112/26365952 (61%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.23945 (0.24990) Boundary_loss: 0.015021 (0.015016) Loss: 0.25447 (0.26492) +2025-08-23,22:29:00 | INFO | Train Epoch: 9 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.314 Boundary Ratio: 0.247 Contrastive_loss: 0.25158 (0.24990) Boundary_loss: 0.014904 (0.015016) Loss: 0.26649 (0.26492) +2025-08-23,22:29:56 | INFO | Train Epoch: 9 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.20914 (0.24978) Boundary_loss: 0.014893 (0.015015) Loss: 0.22403 (0.26479) +2025-08-23,22:30:53 | INFO | Train Epoch: 9 [16179712/26365952 (61%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 0.26697 (0.24983) Boundary_loss: 0.014960 (0.015015) Loss: 0.28193 (0.26485) +2025-08-23,22:31:49 | INFO | Train Epoch: 9 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.19979 (0.24967) Boundary_loss: 0.015076 (0.015015) Loss: 0.21487 (0.26469) +2025-08-23,22:32:46 | INFO | Train Epoch: 9 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.19372 (0.24950) Boundary_loss: 0.015084 (0.015016) Loss: 0.20881 (0.26451) +2025-08-23,22:33:42 | INFO | Train Epoch: 9 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.25227 (0.24951) Boundary_loss: 0.015100 (0.015016) Loss: 0.26737 (0.26452) +2025-08-23,22:34:39 | INFO | Train Epoch: 9 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.23990 (0.24948) Boundary_loss: 0.015009 (0.015016) Loss: 0.25491 (0.26449) +2025-08-23,22:35:36 | INFO | Train Epoch: 9 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.28319 (0.24958) Boundary_loss: 0.014997 (0.015016) Loss: 0.29818 (0.26460) +2025-08-23,22:36:32 | INFO | Train Epoch: 9 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.29420 (0.24972) Boundary_loss: 0.014999 (0.015016) Loss: 0.30920 (0.26473) +2025-08-23,22:37:29 | INFO | Train Epoch: 9 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.17934 (0.24950) Boundary_loss: 0.015018 (0.015016) Loss: 0.19436 (0.26452) +2025-08-23,22:38:25 | INFO | Train Epoch: 9 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.24592 (0.24949) Boundary_loss: 0.014954 (0.015016) Loss: 0.26087 (0.26451) +2025-08-23,22:39:22 | INFO | Train Epoch: 9 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.28822 (0.24961) Boundary_loss: 0.015086 (0.015016) Loss: 0.30331 (0.26463) +2025-08-23,22:40:19 | INFO | Train Epoch: 9 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.22370 (0.24953) Boundary_loss: 0.015008 (0.015016) Loss: 0.23871 (0.26455) +2025-08-23,22:41:15 | INFO | Train Epoch: 9 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.26844 (0.24959) Boundary_loss: 0.014914 (0.015016) Loss: 0.28335 (0.26460) +2025-08-23,22:42:12 | INFO | Train Epoch: 9 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.21604 (0.24949) Boundary_loss: 0.014982 (0.015015) Loss: 0.23102 (0.26450) +2025-08-23,22:43:08 | INFO | Train Epoch: 9 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.26288 (0.24953) Boundary_loss: 0.015028 (0.015015) Loss: 0.27791 (0.26454) +2025-08-23,22:44:05 | INFO | Train Epoch: 9 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.31927 (0.24974) Boundary_loss: 0.015084 (0.015016) Loss: 0.33436 (0.26475) +2025-08-23,22:45:01 | INFO | Train Epoch: 9 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.32225 (0.24996) Boundary_loss: 0.014984 (0.015016) Loss: 0.33723 (0.26497) +2025-08-23,22:45:58 | INFO | Train Epoch: 9 [16998912/26365952 (64%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.22369 (0.24988) Boundary_loss: 0.015029 (0.015016) Loss: 0.23872 (0.26489) +2025-08-23,22:46:55 | INFO | Train Epoch: 9 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.24691 (0.24987) Boundary_loss: 0.015010 (0.015016) Loss: 0.26192 (0.26488) +2025-08-23,22:47:51 | INFO | Train Epoch: 9 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.23240 (0.24982) Boundary_loss: 0.015045 (0.015016) Loss: 0.24745 (0.26483) +2025-08-23,22:48:48 | INFO | Train Epoch: 9 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 0.21077 (0.24970) Boundary_loss: 0.015102 (0.015016) Loss: 0.22587 (0.26472) +2025-08-23,22:49:44 | INFO | Train Epoch: 9 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.27390 (0.24977) Boundary_loss: 0.015096 (0.015016) Loss: 0.28900 (0.26479) +2025-08-23,22:50:41 | INFO | Train Epoch: 9 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.22027 (0.24968) Boundary_loss: 0.015038 (0.015016) Loss: 0.23531 (0.26470) +2025-08-23,22:51:37 | INFO | Train Epoch: 9 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.16838 (0.24944) Boundary_loss: 0.014962 (0.015016) Loss: 0.18334 (0.26446) +2025-08-23,22:52:34 | INFO | Train Epoch: 9 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.26100 (0.24948) Boundary_loss: 0.015080 (0.015016) Loss: 0.27608 (0.26449) +2025-08-23,22:53:31 | INFO | Train Epoch: 9 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.100 Boundary Ratio: 0.245 Contrastive_loss: 0.29908 (0.24962) Boundary_loss: 0.015027 (0.015016) Loss: 0.31411 (0.26464) +2025-08-23,22:54:27 | INFO | Train Epoch: 9 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.23449 (0.24958) Boundary_loss: 0.015072 (0.015016) Loss: 0.24956 (0.26460) +2025-08-23,22:55:24 | INFO | Train Epoch: 9 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.28445 (0.24968) Boundary_loss: 0.015051 (0.015017) Loss: 0.29950 (0.26470) +2025-08-23,22:56:20 | INFO | Train Epoch: 9 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 0.20824 (0.24956) Boundary_loss: 0.015094 (0.015017) Loss: 0.22334 (0.26458) +2025-08-23,22:57:17 | INFO | Train Epoch: 9 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.26684 (0.24961) Boundary_loss: 0.015003 (0.015017) Loss: 0.28185 (0.26463) +2025-08-23,22:58:13 | INFO | Train Epoch: 9 [17664512/26365952 (67%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.19830 (0.24946) Boundary_loss: 0.014938 (0.015017) Loss: 0.21324 (0.26448) +2025-08-23,22:59:10 | INFO | Train Epoch: 9 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 0.24561 (0.24945) Boundary_loss: 0.015077 (0.015017) Loss: 0.26069 (0.26447) +2025-08-23,23:00:06 | INFO | Train Epoch: 9 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 0.26694 (0.24950) Boundary_loss: 0.014975 (0.015017) Loss: 0.28191 (0.26452) +2025-08-23,23:01:03 | INFO | Train Epoch: 9 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.22277 (0.24943) Boundary_loss: 0.015000 (0.015017) Loss: 0.23777 (0.26444) +2025-08-23,23:01:59 | INFO | Train Epoch: 9 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.21871 (0.24934) Boundary_loss: 0.014978 (0.015016) Loss: 0.23369 (0.26435) +2025-08-23,23:02:56 | INFO | Train Epoch: 9 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.406 Boundary Ratio: 0.247 Contrastive_loss: 0.24585 (0.24933) Boundary_loss: 0.014917 (0.015016) Loss: 0.26077 (0.26434) +2025-08-23,23:03:52 | INFO | Train Epoch: 9 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.22493 (0.24926) Boundary_loss: 0.015111 (0.015016) Loss: 0.24004 (0.26427) +2025-08-23,23:04:49 | INFO | Train Epoch: 9 [18022912/26365952 (68%)] Avg Boundaries (per batch): 47.914 Boundary Ratio: 0.244 Contrastive_loss: 0.27124 (0.24932) Boundary_loss: 0.015066 (0.015017) Loss: 0.28630 (0.26434) +2025-08-23,23:05:46 | INFO | Train Epoch: 9 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.381 Boundary Ratio: 0.247 Contrastive_loss: 0.23526 (0.24928) Boundary_loss: 0.014965 (0.015016) Loss: 0.25022 (0.26430) +2025-08-23,23:06:42 | INFO | Train Epoch: 9 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.24191 (0.24926) Boundary_loss: 0.015139 (0.015017) Loss: 0.25705 (0.26428) +2025-08-23,23:07:39 | INFO | Train Epoch: 9 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.23258 (0.24921) Boundary_loss: 0.015046 (0.015017) Loss: 0.24763 (0.26423) +2025-08-23,23:08:35 | INFO | Train Epoch: 9 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.17639 (0.24901) Boundary_loss: 0.014966 (0.015017) Loss: 0.19136 (0.26403) +2025-08-23,23:09:32 | INFO | Train Epoch: 9 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 0.27451 (0.24908) Boundary_loss: 0.015046 (0.015017) Loss: 0.28955 (0.26410) +2025-08-23,23:10:29 | INFO | Train Epoch: 9 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.26916 (0.24914) Boundary_loss: 0.015097 (0.015017) Loss: 0.28425 (0.26415) +2025-08-23,23:11:25 | INFO | Train Epoch: 9 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 0.27770 (0.24922) Boundary_loss: 0.015119 (0.015017) Loss: 0.29282 (0.26423) +2025-08-23,23:12:22 | INFO | Train Epoch: 9 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.28572 (0.24932) Boundary_loss: 0.014986 (0.015017) Loss: 0.30071 (0.26433) +2025-08-23,23:13:18 | INFO | Train Epoch: 9 [18483712/26365952 (70%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.23111 (0.24927) Boundary_loss: 0.015006 (0.015017) Loss: 0.24612 (0.26428) +2025-08-23,23:14:15 | INFO | Train Epoch: 9 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.24402 (0.24925) Boundary_loss: 0.014908 (0.015017) Loss: 0.25893 (0.26427) +2025-08-23,23:15:11 | INFO | Train Epoch: 9 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.26119 (0.24928) Boundary_loss: 0.015084 (0.015017) Loss: 0.27627 (0.26430) +2025-08-23,23:16:08 | INFO | Train Epoch: 9 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.31992 (0.24948) Boundary_loss: 0.015081 (0.015017) Loss: 0.33500 (0.26450) +2025-08-23,23:17:04 | INFO | Train Epoch: 9 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.24632 (0.24947) Boundary_loss: 0.014957 (0.015017) Loss: 0.26127 (0.26449) +2025-08-23,23:18:01 | INFO | Train Epoch: 9 [18739712/26365952 (71%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.27605 (0.24954) Boundary_loss: 0.015081 (0.015017) Loss: 0.29113 (0.26456) +2025-08-23,23:18:57 | INFO | Train Epoch: 9 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 0.25690 (0.24956) Boundary_loss: 0.015052 (0.015017) Loss: 0.27195 (0.26458) +2025-08-23,23:19:54 | INFO | Train Epoch: 9 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.22920 (0.24951) Boundary_loss: 0.014897 (0.015017) Loss: 0.24410 (0.26452) +2025-08-23,23:20:50 | INFO | Train Epoch: 9 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.23659 (0.24947) Boundary_loss: 0.015047 (0.015017) Loss: 0.25163 (0.26449) +2025-08-23,23:21:47 | INFO | Train Epoch: 9 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.21327 (0.24937) Boundary_loss: 0.014974 (0.015017) Loss: 0.22824 (0.26439) +2025-08-23,23:22:44 | INFO | Train Epoch: 9 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.28106 (0.24946) Boundary_loss: 0.014979 (0.015017) Loss: 0.29604 (0.26448) +2025-08-23,23:23:40 | INFO | Train Epoch: 9 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.27566 (0.24953) Boundary_loss: 0.014985 (0.015017) Loss: 0.29065 (0.26455) +2025-08-23,23:24:37 | INFO | Train Epoch: 9 [19098112/26365952 (72%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.23368 (0.24949) Boundary_loss: 0.015125 (0.015017) Loss: 0.24881 (0.26450) +2025-08-23,23:25:33 | INFO | Train Epoch: 9 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.20776 (0.24938) Boundary_loss: 0.014958 (0.015017) Loss: 0.22272 (0.26439) +2025-08-23,23:26:30 | INFO | Train Epoch: 9 [19200512/26365952 (73%)] Avg Boundaries (per batch): 49.557 Boundary Ratio: 0.253 Contrastive_loss: 0.28157 (0.24946) Boundary_loss: 0.015085 (0.015017) Loss: 0.29665 (0.26448) +2025-08-23,23:27:26 | INFO | Train Epoch: 9 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.20296 (0.24934) Boundary_loss: 0.015094 (0.015017) Loss: 0.21805 (0.26436) +2025-08-23,23:28:23 | INFO | Train Epoch: 9 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.25898 (0.24936) Boundary_loss: 0.014958 (0.015017) Loss: 0.27393 (0.26438) +2025-08-23,23:29:20 | INFO | Train Epoch: 9 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.305 Boundary Ratio: 0.246 Contrastive_loss: 0.27964 (0.24944) Boundary_loss: 0.014996 (0.015017) Loss: 0.29464 (0.26446) +2025-08-23,23:30:16 | INFO | Train Epoch: 9 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.26730 (0.24949) Boundary_loss: 0.014959 (0.015017) Loss: 0.28226 (0.26451) +2025-08-23,23:31:13 | INFO | Train Epoch: 9 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.24369 (0.24948) Boundary_loss: 0.014902 (0.015017) Loss: 0.25859 (0.26449) +2025-08-23,23:32:09 | INFO | Train Epoch: 9 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.31622 (0.24965) Boundary_loss: 0.015037 (0.015017) Loss: 0.33125 (0.26467) +2025-08-23,23:33:06 | INFO | Train Epoch: 9 [19558912/26365952 (74%)] Avg Boundaries (per batch): 49.506 Boundary Ratio: 0.253 Contrastive_loss: 0.18343 (0.24948) Boundary_loss: 0.015085 (0.015017) Loss: 0.19851 (0.26449) +2025-08-23,23:34:03 | INFO | Train Epoch: 9 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.21042 (0.24938) Boundary_loss: 0.015020 (0.015017) Loss: 0.22544 (0.26439) +2025-08-23,23:34:59 | INFO | Train Epoch: 9 [19661312/26365952 (75%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.23647 (0.24934) Boundary_loss: 0.015012 (0.015017) Loss: 0.25149 (0.26436) +2025-08-23,23:35:56 | INFO | Train Epoch: 9 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.25926 (0.24937) Boundary_loss: 0.014861 (0.015016) Loss: 0.27412 (0.26438) +2025-08-23,23:36:52 | INFO | Train Epoch: 9 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.26503 (0.24941) Boundary_loss: 0.014914 (0.015016) Loss: 0.27995 (0.26442) +2025-08-23,23:37:49 | INFO | Train Epoch: 9 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.297 Boundary Ratio: 0.252 Contrastive_loss: 0.22239 (0.24934) Boundary_loss: 0.015041 (0.015016) Loss: 0.23743 (0.26435) +2025-08-23,23:38:45 | INFO | Train Epoch: 9 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.23230 (0.24929) Boundary_loss: 0.015036 (0.015016) Loss: 0.24734 (0.26431) +2025-08-23,23:39:42 | INFO | Train Epoch: 9 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.21392 (0.24920) Boundary_loss: 0.014965 (0.015016) Loss: 0.22888 (0.26422) +2025-08-23,23:40:38 | INFO | Train Epoch: 9 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.408 Boundary Ratio: 0.252 Contrastive_loss: 0.24583 (0.24920) Boundary_loss: 0.015043 (0.015016) Loss: 0.26087 (0.26421) +2025-08-23,23:41:35 | INFO | Train Epoch: 9 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.078 Boundary Ratio: 0.245 Contrastive_loss: 0.27745 (0.24927) Boundary_loss: 0.014975 (0.015016) Loss: 0.29242 (0.26428) +2025-08-23,23:42:31 | INFO | Train Epoch: 9 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.24097 (0.24925) Boundary_loss: 0.014975 (0.015016) Loss: 0.25594 (0.26426) +2025-08-23,23:43:28 | INFO | Train Epoch: 9 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.27619 (0.24931) Boundary_loss: 0.015041 (0.015016) Loss: 0.29123 (0.26433) +2025-08-23,23:44:25 | INFO | Train Epoch: 9 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.27354 (0.24938) Boundary_loss: 0.014881 (0.015016) Loss: 0.28842 (0.26439) +2025-08-23,23:45:21 | INFO | Train Epoch: 9 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.29806 (0.24950) Boundary_loss: 0.014966 (0.015016) Loss: 0.31303 (0.26451) +2025-08-23,23:46:18 | INFO | Train Epoch: 9 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.21158 (0.24940) Boundary_loss: 0.015003 (0.015016) Loss: 0.22658 (0.26442) +2025-08-23,23:47:14 | INFO | Train Epoch: 9 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 0.25931 (0.24943) Boundary_loss: 0.014955 (0.015015) Loss: 0.27427 (0.26444) +2025-08-23,23:48:11 | INFO | Train Epoch: 9 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 0.25394 (0.24944) Boundary_loss: 0.015005 (0.015015) Loss: 0.26895 (0.26446) +2025-08-23,23:49:08 | INFO | Train Epoch: 9 [20429312/26365952 (77%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.21008 (0.24934) Boundary_loss: 0.014965 (0.015015) Loss: 0.22505 (0.26436) +2025-08-23,23:50:04 | INFO | Train Epoch: 9 [20480512/26365952 (78%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.24198 (0.24932) Boundary_loss: 0.014939 (0.015015) Loss: 0.25692 (0.26434) +2025-08-23,23:51:01 | INFO | Train Epoch: 9 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.21402 (0.24924) Boundary_loss: 0.015020 (0.015015) Loss: 0.22904 (0.26425) +2025-08-23,23:51:57 | INFO | Train Epoch: 9 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.29015 (0.24934) Boundary_loss: 0.014964 (0.015015) Loss: 0.30511 (0.26435) +2025-08-23,23:52:54 | INFO | Train Epoch: 9 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.26530 (0.24938) Boundary_loss: 0.014955 (0.015015) Loss: 0.28026 (0.26439) +2025-08-23,23:53:51 | INFO | Train Epoch: 9 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.27950 (0.24945) Boundary_loss: 0.014943 (0.015015) Loss: 0.29444 (0.26447) +2025-08-23,23:54:47 | INFO | Train Epoch: 9 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.26631 (0.24949) Boundary_loss: 0.015020 (0.015015) Loss: 0.28133 (0.26451) +2025-08-23,23:55:44 | INFO | Train Epoch: 9 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.32123 (0.24967) Boundary_loss: 0.014914 (0.015014) Loss: 0.33614 (0.26468) +2025-08-23,23:56:40 | INFO | Train Epoch: 9 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.316 Boundary Ratio: 0.247 Contrastive_loss: 0.28131 (0.24975) Boundary_loss: 0.015206 (0.015015) Loss: 0.29651 (0.26476) +2025-08-23,23:57:37 | INFO | Train Epoch: 9 [20890112/26365952 (79%)] Avg Boundaries (per batch): 49.637 Boundary Ratio: 0.253 Contrastive_loss: 0.29099 (0.24985) Boundary_loss: 0.015142 (0.015015) Loss: 0.30613 (0.26486) +2025-08-23,23:58:33 | INFO | Train Epoch: 9 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.16958 (0.24965) Boundary_loss: 0.015038 (0.015015) Loss: 0.18462 (0.26467) +2025-08-23,23:59:30 | INFO | Train Epoch: 9 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.26039 (0.24968) Boundary_loss: 0.015072 (0.015015) Loss: 0.27546 (0.26469) +2025-08-24,00:00:26 | INFO | Train Epoch: 9 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.15860 (0.24946) Boundary_loss: 0.014991 (0.015015) Loss: 0.17359 (0.26447) +2025-08-24,00:01:23 | INFO | Train Epoch: 9 [21094912/26365952 (80%)] Avg Boundaries (per batch): 49.178 Boundary Ratio: 0.251 Contrastive_loss: 0.22350 (0.24939) Boundary_loss: 0.014995 (0.015015) Loss: 0.23849 (0.26441) +2025-08-24,00:02:20 | INFO | Train Epoch: 9 [21146112/26365952 (80%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.26181 (0.24942) Boundary_loss: 0.014960 (0.015015) Loss: 0.27677 (0.26444) +2025-08-24,00:03:16 | INFO | Train Epoch: 9 [21197312/26365952 (80%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.29852 (0.24954) Boundary_loss: 0.015035 (0.015015) Loss: 0.31355 (0.26456) +2025-08-24,00:04:13 | INFO | Train Epoch: 9 [21248512/26365952 (81%)] Avg Boundaries (per batch): 49.248 Boundary Ratio: 0.251 Contrastive_loss: 0.18489 (0.24939) Boundary_loss: 0.014967 (0.015015) Loss: 0.19986 (0.26440) +2025-08-24,00:05:09 | INFO | Train Epoch: 9 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.24928 (0.24939) Boundary_loss: 0.014912 (0.015015) Loss: 0.26419 (0.26440) +2025-08-24,00:06:06 | INFO | Train Epoch: 9 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.279 Boundary Ratio: 0.251 Contrastive_loss: 0.24866 (0.24938) Boundary_loss: 0.014990 (0.015015) Loss: 0.26365 (0.26440) +2025-08-24,00:07:02 | INFO | Train Epoch: 9 [21402112/26365952 (81%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.24905 (0.24938) Boundary_loss: 0.015047 (0.015015) Loss: 0.26410 (0.26440) +2025-08-24,00:07:59 | INFO | Train Epoch: 9 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.246 Boundary Ratio: 0.251 Contrastive_loss: 0.20566 (0.24928) Boundary_loss: 0.015016 (0.015015) Loss: 0.22068 (0.26429) +2025-08-24,00:08:55 | INFO | Train Epoch: 9 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.31473 (0.24943) Boundary_loss: 0.015097 (0.015015) Loss: 0.32983 (0.26445) +2025-08-24,00:09:52 | INFO | Train Epoch: 9 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.23743 (0.24941) Boundary_loss: 0.015015 (0.015015) Loss: 0.25245 (0.26442) +2025-08-24,00:10:48 | INFO | Train Epoch: 9 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.30035 (0.24953) Boundary_loss: 0.015048 (0.015015) Loss: 0.31540 (0.26454) +2025-08-24,00:11:45 | INFO | Train Epoch: 9 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.23595 (0.24949) Boundary_loss: 0.015000 (0.015015) Loss: 0.25095 (0.26451) +2025-08-24,00:12:41 | INFO | Train Epoch: 9 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.28502 (0.24958) Boundary_loss: 0.014992 (0.015015) Loss: 0.30001 (0.26459) +2025-08-24,00:13:38 | INFO | Train Epoch: 9 [21760512/26365952 (83%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.23146 (0.24954) Boundary_loss: 0.014858 (0.015015) Loss: 0.24632 (0.26455) +2025-08-24,00:14:34 | INFO | Train Epoch: 9 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.25205 (0.24954) Boundary_loss: 0.014878 (0.015014) Loss: 0.26693 (0.26456) +2025-08-24,00:15:31 | INFO | Train Epoch: 9 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.22377 (0.24948) Boundary_loss: 0.014951 (0.015014) Loss: 0.23872 (0.26450) +2025-08-24,00:16:28 | INFO | Train Epoch: 9 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.291 Boundary Ratio: 0.246 Contrastive_loss: 0.27920 (0.24955) Boundary_loss: 0.014897 (0.015014) Loss: 0.29410 (0.26456) +2025-08-24,00:17:24 | INFO | Train Epoch: 9 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.24421 (0.24954) Boundary_loss: 0.014980 (0.015014) Loss: 0.25919 (0.26455) +2025-08-24,00:18:21 | INFO | Train Epoch: 9 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.26328 (0.24957) Boundary_loss: 0.014955 (0.015014) Loss: 0.27824 (0.26458) +2025-08-24,00:19:17 | INFO | Train Epoch: 9 [22067712/26365952 (84%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 0.20388 (0.24946) Boundary_loss: 0.015060 (0.015014) Loss: 0.21894 (0.26448) +2025-08-24,00:20:14 | INFO | Train Epoch: 9 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.23573 (0.24943) Boundary_loss: 0.014864 (0.015013) Loss: 0.25059 (0.26445) +2025-08-24,00:21:10 | INFO | Train Epoch: 9 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.29553 (0.24954) Boundary_loss: 0.015090 (0.015014) Loss: 0.31062 (0.26455) +2025-08-24,00:22:07 | INFO | Train Epoch: 9 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.26382 (0.24957) Boundary_loss: 0.014929 (0.015013) Loss: 0.27875 (0.26459) +2025-08-24,00:23:03 | INFO | Train Epoch: 9 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.22026 (0.24950) Boundary_loss: 0.014911 (0.015013) Loss: 0.23518 (0.26452) +2025-08-24,00:24:00 | INFO | Train Epoch: 9 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.26563 (0.24954) Boundary_loss: 0.014972 (0.015013) Loss: 0.28061 (0.26455) +2025-08-24,00:24:56 | INFO | Train Epoch: 9 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.19080 (0.24941) Boundary_loss: 0.014952 (0.015013) Loss: 0.20575 (0.26442) +2025-08-24,00:25:53 | INFO | Train Epoch: 9 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.22955 (0.24936) Boundary_loss: 0.015024 (0.015013) Loss: 0.24458 (0.26438) +2025-08-24,00:26:49 | INFO | Train Epoch: 9 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.24532 (0.24935) Boundary_loss: 0.015099 (0.015013) Loss: 0.26042 (0.26437) +2025-08-24,00:27:46 | INFO | Train Epoch: 9 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.20368 (0.24925) Boundary_loss: 0.014994 (0.015013) Loss: 0.21868 (0.26426) +2025-08-24,00:28:42 | INFO | Train Epoch: 9 [22579712/26365952 (86%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.22147 (0.24919) Boundary_loss: 0.015010 (0.015013) Loss: 0.23648 (0.26420) +2025-08-24,00:29:39 | INFO | Train Epoch: 9 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.23801 (0.24916) Boundary_loss: 0.015084 (0.015013) Loss: 0.25309 (0.26417) +2025-08-24,00:30:35 | INFO | Train Epoch: 9 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.19589 (0.24904) Boundary_loss: 0.014993 (0.015013) Loss: 0.21088 (0.26405) +2025-08-24,00:31:32 | INFO | Train Epoch: 9 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.29799 (0.24915) Boundary_loss: 0.015032 (0.015013) Loss: 0.31303 (0.26416) +2025-08-24,00:32:28 | INFO | Train Epoch: 9 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.23696 (0.24912) Boundary_loss: 0.015122 (0.015014) Loss: 0.25208 (0.26414) +2025-08-24,00:33:25 | INFO | Train Epoch: 9 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.25694 (0.24914) Boundary_loss: 0.014878 (0.015013) Loss: 0.27182 (0.26415) +2025-08-24,00:34:22 | INFO | Train Epoch: 9 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.20305 (0.24904) Boundary_loss: 0.015005 (0.015013) Loss: 0.21806 (0.26405) +2025-08-24,00:35:18 | INFO | Train Epoch: 9 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.297 Boundary Ratio: 0.246 Contrastive_loss: 0.28399 (0.24912) Boundary_loss: 0.014938 (0.015013) Loss: 0.29893 (0.26413) +2025-08-24,00:36:14 | INFO | Train Epoch: 9 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.22896 (0.24907) Boundary_loss: 0.014975 (0.015013) Loss: 0.24393 (0.26408) +2025-08-24,00:37:11 | INFO | Train Epoch: 9 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.107 Boundary Ratio: 0.245 Contrastive_loss: 0.20755 (0.24898) Boundary_loss: 0.014980 (0.015013) Loss: 0.22253 (0.26399) +2025-08-24,00:38:07 | INFO | Train Epoch: 9 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.29965 (0.24909) Boundary_loss: 0.014903 (0.015013) Loss: 0.31455 (0.26410) +2025-08-24,00:39:04 | INFO | Train Epoch: 9 [23142912/26365952 (88%)] Avg Boundaries (per batch): 49.246 Boundary Ratio: 0.251 Contrastive_loss: 0.21556 (0.24902) Boundary_loss: 0.015033 (0.015013) Loss: 0.23059 (0.26403) +2025-08-24,00:40:00 | INFO | Train Epoch: 9 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.27296 (0.24907) Boundary_loss: 0.014959 (0.015013) Loss: 0.28792 (0.26408) +2025-08-24,00:40:57 | INFO | Train Epoch: 9 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.24936 (0.24907) Boundary_loss: 0.015032 (0.015013) Loss: 0.26439 (0.26408) +2025-08-24,00:41:54 | INFO | Train Epoch: 9 [23296512/26365952 (88%)] Avg Boundaries (per batch): 49.408 Boundary Ratio: 0.252 Contrastive_loss: 0.27275 (0.24912) Boundary_loss: 0.015155 (0.015013) Loss: 0.28791 (0.26414) +2025-08-24,00:42:50 | INFO | Train Epoch: 9 [23347712/26365952 (89%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.24488 (0.24911) Boundary_loss: 0.014941 (0.015013) Loss: 0.25983 (0.26413) +2025-08-24,00:43:47 | INFO | Train Epoch: 9 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.17660 (0.24896) Boundary_loss: 0.014954 (0.015013) Loss: 0.19155 (0.26397) +2025-08-24,00:44:43 | INFO | Train Epoch: 9 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.27053 (0.24900) Boundary_loss: 0.014962 (0.015013) Loss: 0.28549 (0.26401) +2025-08-24,00:45:40 | INFO | Train Epoch: 9 [23501312/26365952 (89%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.21962 (0.24894) Boundary_loss: 0.015087 (0.015013) Loss: 0.23470 (0.26395) +2025-08-24,00:46:37 | INFO | Train Epoch: 9 [23552512/26365952 (89%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.26837 (0.24898) Boundary_loss: 0.014993 (0.015013) Loss: 0.28336 (0.26399) +2025-08-24,00:47:33 | INFO | Train Epoch: 9 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.15421 (0.24878) Boundary_loss: 0.015022 (0.015013) Loss: 0.16923 (0.26379) +2025-08-24,00:48:30 | INFO | Train Epoch: 9 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.26540 (0.24881) Boundary_loss: 0.015130 (0.015013) Loss: 0.28053 (0.26382) +2025-08-24,00:49:27 | INFO | Train Epoch: 9 [23706112/26365952 (90%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.21161 (0.24873) Boundary_loss: 0.015085 (0.015013) Loss: 0.22669 (0.26374) +2025-08-24,00:50:23 | INFO | Train Epoch: 9 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.28658 (0.24881) Boundary_loss: 0.015156 (0.015013) Loss: 0.30174 (0.26383) +2025-08-24,00:51:19 | INFO | Train Epoch: 9 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.23806 (0.24879) Boundary_loss: 0.014962 (0.015013) Loss: 0.25302 (0.26380) +2025-08-24,00:52:16 | INFO | Train Epoch: 9 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.201 Boundary Ratio: 0.246 Contrastive_loss: 0.23148 (0.24875) Boundary_loss: 0.015172 (0.015014) Loss: 0.24666 (0.26377) +2025-08-24,00:53:13 | INFO | Train Epoch: 9 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.19998 (0.24865) Boundary_loss: 0.015069 (0.015014) Loss: 0.21505 (0.26366) +2025-08-24,00:54:09 | INFO | Train Epoch: 9 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.068 Boundary Ratio: 0.245 Contrastive_loss: 0.24989 (0.24865) Boundary_loss: 0.015046 (0.015014) Loss: 0.26493 (0.26366) +2025-08-24,00:55:06 | INFO | Train Epoch: 9 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.21305 (0.24858) Boundary_loss: 0.014936 (0.015014) Loss: 0.22799 (0.26359) +2025-08-24,00:56:02 | INFO | Train Epoch: 9 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.24608 (0.24857) Boundary_loss: 0.014993 (0.015014) Loss: 0.26107 (0.26358) +2025-08-24,00:56:59 | INFO | Train Epoch: 9 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.29876 (0.24868) Boundary_loss: 0.014900 (0.015013) Loss: 0.31366 (0.26369) +2025-08-24,00:57:55 | INFO | Train Epoch: 9 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.22662 (0.24863) Boundary_loss: 0.015126 (0.015014) Loss: 0.24174 (0.26364) +2025-08-24,00:58:52 | INFO | Train Epoch: 9 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.20584 (0.24854) Boundary_loss: 0.015066 (0.015014) Loss: 0.22091 (0.26355) +2025-08-24,00:59:49 | INFO | Train Epoch: 9 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.24920 (0.24854) Boundary_loss: 0.014973 (0.015014) Loss: 0.26417 (0.26355) +2025-08-24,01:00:45 | INFO | Train Epoch: 9 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.23928 (0.24852) Boundary_loss: 0.015046 (0.015014) Loss: 0.25432 (0.26353) +2025-08-24,01:01:42 | INFO | Train Epoch: 9 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.303 Boundary Ratio: 0.246 Contrastive_loss: 0.23587 (0.24849) Boundary_loss: 0.015136 (0.015014) Loss: 0.25101 (0.26351) +2025-08-24,01:02:38 | INFO | Train Epoch: 9 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.26888 (0.24854) Boundary_loss: 0.015171 (0.015014) Loss: 0.28405 (0.26355) +2025-08-24,01:03:34 | INFO | Train Epoch: 9 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.21996 (0.24848) Boundary_loss: 0.014934 (0.015014) Loss: 0.23490 (0.26349) +2025-08-24,01:04:31 | INFO | Train Epoch: 9 [24525312/26365952 (93%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.20987 (0.24840) Boundary_loss: 0.015145 (0.015014) Loss: 0.22501 (0.26341) +2025-08-24,01:05:28 | INFO | Train Epoch: 9 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.25051 (0.24840) Boundary_loss: 0.015001 (0.015014) Loss: 0.26551 (0.26342) +2025-08-24,01:06:24 | INFO | Train Epoch: 9 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.25161 (0.24841) Boundary_loss: 0.014995 (0.015014) Loss: 0.26661 (0.26342) +2025-08-24,01:07:21 | INFO | Train Epoch: 9 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.21141 (0.24833) Boundary_loss: 0.015028 (0.015014) Loss: 0.22644 (0.26335) +2025-08-24,01:08:17 | INFO | Train Epoch: 9 [24730112/26365952 (94%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 0.21873 (0.24827) Boundary_loss: 0.014944 (0.015014) Loss: 0.23367 (0.26328) +2025-08-24,01:09:14 | INFO | Train Epoch: 9 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.28049 (0.24834) Boundary_loss: 0.015130 (0.015014) Loss: 0.29562 (0.26335) +2025-08-24,01:10:10 | INFO | Train Epoch: 9 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.28872 (0.24842) Boundary_loss: 0.014973 (0.015014) Loss: 0.30370 (0.26343) +2025-08-24,01:11:07 | INFO | Train Epoch: 9 [24883712/26365952 (94%)] Avg Boundaries (per batch): 49.326 Boundary Ratio: 0.252 Contrastive_loss: 0.24547 (0.24841) Boundary_loss: 0.015015 (0.015014) Loss: 0.26048 (0.26343) +2025-08-24,01:12:04 | INFO | Train Epoch: 9 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.21073 (0.24834) Boundary_loss: 0.015063 (0.015014) Loss: 0.22580 (0.26335) +2025-08-24,01:13:00 | INFO | Train Epoch: 9 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.28465 (0.24841) Boundary_loss: 0.014950 (0.015014) Loss: 0.29960 (0.26343) +2025-08-24,01:13:57 | INFO | Train Epoch: 9 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.26383 (0.24844) Boundary_loss: 0.015064 (0.015014) Loss: 0.27889 (0.26346) +2025-08-24,01:14:53 | INFO | Train Epoch: 9 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.24078 (0.24843) Boundary_loss: 0.015010 (0.015014) Loss: 0.25579 (0.26344) +2025-08-24,01:15:50 | INFO | Train Epoch: 9 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.22862 (0.24839) Boundary_loss: 0.015032 (0.015014) Loss: 0.24365 (0.26340) +2025-08-24,01:16:46 | INFO | Train Epoch: 9 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.174 Boundary Ratio: 0.246 Contrastive_loss: 0.26924 (0.24843) Boundary_loss: 0.014970 (0.015014) Loss: 0.28421 (0.26344) +2025-08-24,01:17:43 | INFO | Train Epoch: 9 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.26392 (0.24846) Boundary_loss: 0.014964 (0.015014) Loss: 0.27889 (0.26347) +2025-08-24,01:18:39 | INFO | Train Epoch: 9 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.26111 (0.24849) Boundary_loss: 0.014860 (0.015014) Loss: 0.27597 (0.26350) +2025-08-24,01:19:36 | INFO | Train Epoch: 9 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.21788 (0.24842) Boundary_loss: 0.015046 (0.015014) Loss: 0.23293 (0.26344) +2025-08-24,01:20:32 | INFO | Train Epoch: 9 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.23035 (0.24839) Boundary_loss: 0.014925 (0.015014) Loss: 0.24528 (0.26340) +2025-08-24,01:21:29 | INFO | Train Epoch: 9 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.27594 (0.24844) Boundary_loss: 0.015025 (0.015014) Loss: 0.29097 (0.26346) +2025-08-24,01:22:25 | INFO | Train Epoch: 9 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.24517 (0.24844) Boundary_loss: 0.015003 (0.015014) Loss: 0.26017 (0.26345) +2025-08-24,01:23:21 | INFO | Train Epoch: 9 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.23570 (0.24841) Boundary_loss: 0.014991 (0.015014) Loss: 0.25069 (0.26342) +2025-08-24,01:24:18 | INFO | Train Epoch: 9 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 0.25771 (0.24843) Boundary_loss: 0.015009 (0.015014) Loss: 0.27272 (0.26344) +2025-08-24,01:25:14 | INFO | Train Epoch: 9 [25651712/26365952 (97%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 0.22514 (0.24838) Boundary_loss: 0.015084 (0.015014) Loss: 0.24022 (0.26340) +2025-08-24,01:26:11 | INFO | Train Epoch: 9 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.34210 (0.24857) Boundary_loss: 0.014993 (0.015014) Loss: 0.35709 (0.26358) +2025-08-24,01:27:07 | INFO | Train Epoch: 9 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.26084 (0.24859) Boundary_loss: 0.015036 (0.015014) Loss: 0.27587 (0.26361) +2025-08-24,01:28:04 | INFO | Train Epoch: 9 [25805312/26365952 (98%)] Avg Boundaries (per batch): 49.461 Boundary Ratio: 0.252 Contrastive_loss: 0.28052 (0.24866) Boundary_loss: 0.015032 (0.015014) Loss: 0.29555 (0.26367) +2025-08-24,01:29:01 | INFO | Train Epoch: 9 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.25431 (0.24867) Boundary_loss: 0.015075 (0.015014) Loss: 0.26938 (0.26368) +2025-08-24,01:29:57 | INFO | Train Epoch: 9 [25907712/26365952 (98%)] Avg Boundaries (per batch): 49.297 Boundary Ratio: 0.252 Contrastive_loss: 0.22423 (0.24862) Boundary_loss: 0.014896 (0.015014) Loss: 0.23912 (0.26363) +2025-08-24,01:30:54 | INFO | Train Epoch: 9 [25958912/26365952 (98%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 0.18701 (0.24850) Boundary_loss: 0.015074 (0.015014) Loss: 0.20208 (0.26351) +2025-08-24,01:31:50 | INFO | Train Epoch: 9 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.17585 (0.24836) Boundary_loss: 0.015052 (0.015014) Loss: 0.19091 (0.26337) +2025-08-24,01:32:47 | INFO | Train Epoch: 9 [26061312/26365952 (99%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.19544 (0.24825) Boundary_loss: 0.015056 (0.015014) Loss: 0.21049 (0.26327) +2025-08-24,01:33:43 | INFO | Train Epoch: 9 [26112512/26365952 (99%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.22493 (0.24821) Boundary_loss: 0.015091 (0.015014) Loss: 0.24002 (0.26322) +2025-08-24,01:34:40 | INFO | Train Epoch: 9 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.26223 (0.24823) Boundary_loss: 0.015127 (0.015014) Loss: 0.27735 (0.26325) +2025-08-24,01:35:36 | INFO | Train Epoch: 9 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.31737 (0.24837) Boundary_loss: 0.015109 (0.015015) Loss: 0.33248 (0.26338) +2025-08-24,01:36:33 | INFO | Train Epoch: 9 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.22888 (0.24833) Boundary_loss: 0.014994 (0.015015) Loss: 0.24387 (0.26335) +2025-08-24,01:37:29 | INFO | Train Epoch: 9 [26317312/26365952 (100%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.24093 (0.24832) Boundary_loss: 0.015101 (0.015015) Loss: 0.25603 (0.26333) +2025-08-24,01:38:23 | INFO | Train Epoch: 9 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.24370 (0.24831) Boundary_loss: 0.014900 (0.015015) Loss: 0.25860 (0.26332) +2025-08-24,01:38:23 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-24,01:38:23 | INFO | [Epoch 9] Average Step Time: 0.568s | Average GPU Memory: 31.7 GB +2025-08-24,01:38:23 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-24,01:38:23 | INFO | Starting zero-shot imagenet. +2025-08-24,01:38:23 | INFO | Building zero-shot classifier +2025-08-24,01:38:32 | INFO | Using classifier +2025-08-24,01:39:17 | INFO | Finished zero-shot imagenet. +2025-08-24,01:39:17 | INFO | Eval Epoch: 10 imagenet-zeroshot-val-top1: 0.2873 imagenet-zeroshot-val-top5: 0.5475 +2025-08-24,01:39:18 | INFO | Start epoch 10 +2025-08-24,01:39:21 | INFO | Train Epoch: 10 [ 512/26365952 (0%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.15855 (0.15855) Boundary_loss: 0.015075 (0.015075) Loss: 0.17362 (0.17362) +2025-08-24,01:40:17 | INFO | Train Epoch: 10 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.18765 (0.17310) Boundary_loss: 0.014973 (0.015024) Loss: 0.20262 (0.18812) +2025-08-24,01:41:13 | INFO | Train Epoch: 10 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.16770 (0.17130) Boundary_loss: 0.015003 (0.015017) Loss: 0.18270 (0.18632) +2025-08-24,01:42:10 | INFO | Train Epoch: 10 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.22778 (0.18542) Boundary_loss: 0.014983 (0.015009) Loss: 0.24276 (0.20043) +2025-08-24,01:43:06 | INFO | Train Epoch: 10 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.354 Boundary Ratio: 0.247 Contrastive_loss: 0.20642 (0.18962) Boundary_loss: 0.014936 (0.014994) Loss: 0.22136 (0.20461) +2025-08-24,01:44:03 | INFO | Train Epoch: 10 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.516 Boundary Ratio: 0.248 Contrastive_loss: 0.19858 (0.19111) Boundary_loss: 0.014999 (0.014995) Loss: 0.21358 (0.20611) +2025-08-24,01:44:59 | INFO | Train Epoch: 10 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.23195 (0.19695) Boundary_loss: 0.014961 (0.014990) Loss: 0.24691 (0.21194) +2025-08-24,01:45:56 | INFO | Train Epoch: 10 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.22481 (0.20043) Boundary_loss: 0.014987 (0.014990) Loss: 0.23980 (0.21542) +2025-08-24,01:46:52 | INFO | Train Epoch: 10 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.15149 (0.19499) Boundary_loss: 0.014891 (0.014979) Loss: 0.16638 (0.20997) +2025-08-24,01:47:49 | INFO | Train Epoch: 10 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.19957 (0.19545) Boundary_loss: 0.014963 (0.014977) Loss: 0.21453 (0.21043) +2025-08-24,01:48:45 | INFO | Train Epoch: 10 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 0.17919 (0.19397) Boundary_loss: 0.014954 (0.014975) Loss: 0.19414 (0.20895) +2025-08-24,01:49:42 | INFO | Train Epoch: 10 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.21655 (0.19585) Boundary_loss: 0.015203 (0.014994) Loss: 0.23176 (0.21085) +2025-08-24,01:50:38 | INFO | Train Epoch: 10 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.23100 (0.19856) Boundary_loss: 0.015034 (0.014997) Loss: 0.24603 (0.21355) +2025-08-24,01:51:35 | INFO | Train Epoch: 10 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.193 Boundary Ratio: 0.246 Contrastive_loss: 0.21306 (0.19959) Boundary_loss: 0.015002 (0.014997) Loss: 0.22806 (0.21459) +2025-08-24,01:52:31 | INFO | Train Epoch: 10 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.23765 (0.20213) Boundary_loss: 0.014814 (0.014985) Loss: 0.25246 (0.21711) +2025-08-24,01:53:28 | INFO | Train Epoch: 10 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.18388 (0.20099) Boundary_loss: 0.015015 (0.014987) Loss: 0.19889 (0.21598) +2025-08-24,01:54:24 | INFO | Train Epoch: 10 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.18460 (0.20002) Boundary_loss: 0.014949 (0.014985) Loss: 0.19955 (0.21501) +2025-08-24,01:55:20 | INFO | Train Epoch: 10 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.16466 (0.19806) Boundary_loss: 0.014914 (0.014981) Loss: 0.17957 (0.21304) +2025-08-24,01:56:17 | INFO | Train Epoch: 10 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.19765 (0.19804) Boundary_loss: 0.014936 (0.014979) Loss: 0.21258 (0.21302) +2025-08-24,01:57:13 | INFO | Train Epoch: 10 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.20905 (0.19859) Boundary_loss: 0.014905 (0.014975) Loss: 0.22395 (0.21356) +2025-08-24,01:58:10 | INFO | Train Epoch: 10 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.19683 (0.19850) Boundary_loss: 0.015061 (0.014979) Loss: 0.21189 (0.21348) +2025-08-24,01:59:06 | INFO | Train Epoch: 10 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.22506 (0.19971) Boundary_loss: 0.014973 (0.014979) Loss: 0.24003 (0.21469) +2025-08-24,02:00:03 | INFO | Train Epoch: 10 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 0.18440 (0.19905) Boundary_loss: 0.014967 (0.014978) Loss: 0.19937 (0.21402) +2025-08-24,02:00:59 | INFO | Train Epoch: 10 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.22026 (0.19993) Boundary_loss: 0.014929 (0.014976) Loss: 0.23519 (0.21491) +2025-08-24,02:01:56 | INFO | Train Epoch: 10 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.19047 (0.19955) Boundary_loss: 0.014926 (0.014974) Loss: 0.20540 (0.21453) +2025-08-24,02:02:52 | INFO | Train Epoch: 10 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.23765 (0.20102) Boundary_loss: 0.015086 (0.014978) Loss: 0.25274 (0.21599) +2025-08-24,02:03:48 | INFO | Train Epoch: 10 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.19070 (0.20063) Boundary_loss: 0.014950 (0.014977) Loss: 0.20565 (0.21561) +2025-08-24,02:04:45 | INFO | Train Epoch: 10 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.15459 (0.19899) Boundary_loss: 0.015012 (0.014979) Loss: 0.16960 (0.21397) +2025-08-24,02:05:41 | INFO | Train Epoch: 10 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.18924 (0.19865) Boundary_loss: 0.014959 (0.014978) Loss: 0.20419 (0.21363) +2025-08-24,02:06:38 | INFO | Train Epoch: 10 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.17150 (0.19775) Boundary_loss: 0.015057 (0.014981) Loss: 0.18656 (0.21273) +2025-08-24,02:07:34 | INFO | Train Epoch: 10 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.20293 (0.19792) Boundary_loss: 0.014881 (0.014977) Loss: 0.21781 (0.21289) +2025-08-24,02:08:30 | INFO | Train Epoch: 10 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 0.24653 (0.19943) Boundary_loss: 0.014933 (0.014976) Loss: 0.26147 (0.21441) +2025-08-24,02:09:27 | INFO | Train Epoch: 10 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.16830 (0.19849) Boundary_loss: 0.015045 (0.014978) Loss: 0.18334 (0.21347) +2025-08-24,02:10:23 | INFO | Train Epoch: 10 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.20866 (0.19879) Boundary_loss: 0.014902 (0.014976) Loss: 0.22357 (0.21377) +2025-08-24,02:11:20 | INFO | Train Epoch: 10 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.20552 (0.19898) Boundary_loss: 0.014969 (0.014976) Loss: 0.22049 (0.21396) +2025-08-24,02:12:16 | INFO | Train Epoch: 10 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.29425 (0.20163) Boundary_loss: 0.015091 (0.014979) Loss: 0.30934 (0.21661) +2025-08-24,02:13:13 | INFO | Train Epoch: 10 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.22110 (0.20216) Boundary_loss: 0.015025 (0.014980) Loss: 0.23612 (0.21714) +2025-08-24,02:14:09 | INFO | Train Epoch: 10 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.24709 (0.20334) Boundary_loss: 0.015011 (0.014981) Loss: 0.26210 (0.21832) +2025-08-24,02:15:06 | INFO | Train Epoch: 10 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.23986 (0.20427) Boundary_loss: 0.015102 (0.014984) Loss: 0.25496 (0.21926) +2025-08-24,02:16:02 | INFO | Train Epoch: 10 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.21167 (0.20446) Boundary_loss: 0.015059 (0.014986) Loss: 0.22673 (0.21944) +2025-08-24,02:16:59 | INFO | Train Epoch: 10 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.20574 (0.20449) Boundary_loss: 0.015018 (0.014987) Loss: 0.22076 (0.21948) +2025-08-24,02:17:55 | INFO | Train Epoch: 10 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 49.354 Boundary Ratio: 0.252 Contrastive_loss: 0.18992 (0.20414) Boundary_loss: 0.015009 (0.014987) Loss: 0.20492 (0.21913) +2025-08-24,02:18:52 | INFO | Train Epoch: 10 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.23190 (0.20479) Boundary_loss: 0.015006 (0.014988) Loss: 0.24690 (0.21978) +2025-08-24,02:19:48 | INFO | Train Epoch: 10 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 0.19757 (0.20462) Boundary_loss: 0.014943 (0.014987) Loss: 0.21252 (0.21961) +2025-08-24,02:20:45 | INFO | Train Epoch: 10 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.264 Boundary Ratio: 0.246 Contrastive_loss: 0.20956 (0.20473) Boundary_loss: 0.015020 (0.014987) Loss: 0.22458 (0.21972) +2025-08-24,02:21:41 | INFO | Train Epoch: 10 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.16510 (0.20387) Boundary_loss: 0.014923 (0.014986) Loss: 0.18002 (0.21886) +2025-08-24,02:22:38 | INFO | Train Epoch: 10 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.19822 (0.20375) Boundary_loss: 0.015014 (0.014987) Loss: 0.21324 (0.21874) +2025-08-24,02:23:34 | INFO | Train Epoch: 10 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.22699 (0.20424) Boundary_loss: 0.014971 (0.014986) Loss: 0.24196 (0.21922) +2025-08-24,02:24:31 | INFO | Train Epoch: 10 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.20210 (0.20419) Boundary_loss: 0.014956 (0.014986) Loss: 0.21706 (0.21918) +2025-08-24,02:25:27 | INFO | Train Epoch: 10 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.18027 (0.20371) Boundary_loss: 0.015081 (0.014988) Loss: 0.19535 (0.21870) +2025-08-24,02:26:23 | INFO | Train Epoch: 10 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.256 Boundary Ratio: 0.246 Contrastive_loss: 0.22130 (0.20406) Boundary_loss: 0.015080 (0.014989) Loss: 0.23638 (0.21905) +2025-08-24,02:27:20 | INFO | Train Epoch: 10 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.21014 (0.20418) Boundary_loss: 0.014955 (0.014989) Loss: 0.22509 (0.21917) +2025-08-24,02:28:17 | INFO | Train Epoch: 10 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.23410 (0.20474) Boundary_loss: 0.014977 (0.014988) Loss: 0.24907 (0.21973) +2025-08-24,02:29:13 | INFO | Train Epoch: 10 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.19851 (0.20463) Boundary_loss: 0.014984 (0.014988) Loss: 0.21349 (0.21961) +2025-08-24,02:30:09 | INFO | Train Epoch: 10 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.21637 (0.20484) Boundary_loss: 0.015166 (0.014992) Loss: 0.23154 (0.21983) +2025-08-24,02:31:06 | INFO | Train Epoch: 10 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.23312 (0.20534) Boundary_loss: 0.015064 (0.014993) Loss: 0.24818 (0.22034) +2025-08-24,02:32:02 | INFO | Train Epoch: 10 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.19797 (0.20521) Boundary_loss: 0.015022 (0.014993) Loss: 0.21299 (0.22021) +2025-08-24,02:32:59 | INFO | Train Epoch: 10 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.18370 (0.20484) Boundary_loss: 0.014908 (0.014992) Loss: 0.19861 (0.21984) +2025-08-24,02:33:55 | INFO | Train Epoch: 10 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.22459 (0.20518) Boundary_loss: 0.015101 (0.014994) Loss: 0.23969 (0.22017) +2025-08-24,02:34:52 | INFO | Train Epoch: 10 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.17426 (0.20466) Boundary_loss: 0.014946 (0.014993) Loss: 0.18921 (0.21966) +2025-08-24,02:35:48 | INFO | Train Epoch: 10 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.26218 (0.20561) Boundary_loss: 0.014994 (0.014993) Loss: 0.27718 (0.22060) +2025-08-24,02:36:45 | INFO | Train Epoch: 10 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.20163 (0.20554) Boundary_loss: 0.015015 (0.014993) Loss: 0.21665 (0.22054) +2025-08-24,02:37:41 | INFO | Train Epoch: 10 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.16632 (0.20492) Boundary_loss: 0.015023 (0.014994) Loss: 0.18134 (0.21991) +2025-08-24,02:38:38 | INFO | Train Epoch: 10 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 0.17080 (0.20439) Boundary_loss: 0.015049 (0.014995) Loss: 0.18585 (0.21938) +2025-08-24,02:39:34 | INFO | Train Epoch: 10 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.22621 (0.20472) Boundary_loss: 0.014990 (0.014995) Loss: 0.24120 (0.21972) +2025-08-24,02:40:31 | INFO | Train Epoch: 10 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.20935 (0.20479) Boundary_loss: 0.014933 (0.014994) Loss: 0.22428 (0.21979) +2025-08-24,02:41:27 | INFO | Train Epoch: 10 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.264 Boundary Ratio: 0.246 Contrastive_loss: 0.23509 (0.20524) Boundary_loss: 0.015068 (0.014995) Loss: 0.25016 (0.22024) +2025-08-24,02:42:24 | INFO | Train Epoch: 10 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.19927 (0.20516) Boundary_loss: 0.015053 (0.014996) Loss: 0.21432 (0.22015) +2025-08-24,02:43:20 | INFO | Train Epoch: 10 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.22419 (0.20543) Boundary_loss: 0.014949 (0.014995) Loss: 0.23914 (0.22043) +2025-08-24,02:44:17 | INFO | Train Epoch: 10 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.16733 (0.20489) Boundary_loss: 0.014921 (0.014994) Loss: 0.18225 (0.21988) +2025-08-24,02:45:13 | INFO | Train Epoch: 10 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.15274 (0.20415) Boundary_loss: 0.014921 (0.014993) Loss: 0.16766 (0.21915) +2025-08-24,02:46:10 | INFO | Train Epoch: 10 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.22747 (0.20448) Boundary_loss: 0.014973 (0.014993) Loss: 0.24244 (0.21947) +2025-08-24,02:47:06 | INFO | Train Epoch: 10 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.24025 (0.20497) Boundary_loss: 0.014895 (0.014991) Loss: 0.25514 (0.21996) +2025-08-24,02:48:03 | INFO | Train Epoch: 10 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 49.133 Boundary Ratio: 0.251 Contrastive_loss: 0.20560 (0.20498) Boundary_loss: 0.015033 (0.014992) Loss: 0.22063 (0.21997) +2025-08-24,02:48:59 | INFO | Train Epoch: 10 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.20951 (0.20504) Boundary_loss: 0.015059 (0.014993) Loss: 0.22457 (0.22003) +2025-08-24,02:49:55 | INFO | Train Epoch: 10 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.105 Boundary Ratio: 0.245 Contrastive_loss: 0.21681 (0.20519) Boundary_loss: 0.015137 (0.014995) Loss: 0.23195 (0.22019) +2025-08-24,02:50:52 | INFO | Train Epoch: 10 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.22274 (0.20542) Boundary_loss: 0.014921 (0.014994) Loss: 0.23767 (0.22041) +2025-08-24,02:51:48 | INFO | Train Epoch: 10 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.21212 (0.20551) Boundary_loss: 0.014851 (0.014992) Loss: 0.22697 (0.22050) +2025-08-24,02:52:45 | INFO | Train Epoch: 10 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.24514 (0.20601) Boundary_loss: 0.015122 (0.014993) Loss: 0.26026 (0.22100) +2025-08-24,02:53:41 | INFO | Train Epoch: 10 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.25411 (0.20661) Boundary_loss: 0.014957 (0.014993) Loss: 0.26907 (0.22160) +2025-08-24,02:54:38 | INFO | Train Epoch: 10 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.27017 (0.20739) Boundary_loss: 0.015042 (0.014994) Loss: 0.28522 (0.22239) +2025-08-24,02:55:35 | INFO | Train Epoch: 10 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.25367 (0.20796) Boundary_loss: 0.014885 (0.014992) Loss: 0.26856 (0.22295) +2025-08-24,02:56:31 | INFO | Train Epoch: 10 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.23447 (0.20828) Boundary_loss: 0.015075 (0.014993) Loss: 0.24955 (0.22327) +2025-08-24,02:57:28 | INFO | Train Epoch: 10 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.18765 (0.20803) Boundary_loss: 0.015005 (0.014993) Loss: 0.20266 (0.22302) +2025-08-24,02:58:24 | INFO | Train Epoch: 10 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.21095 (0.20807) Boundary_loss: 0.015056 (0.014994) Loss: 0.22601 (0.22306) +2025-08-24,02:59:21 | INFO | Train Epoch: 10 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.20418 (0.20802) Boundary_loss: 0.014934 (0.014993) Loss: 0.21911 (0.22301) +2025-08-24,03:00:17 | INFO | Train Epoch: 10 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.20813 (0.20802) Boundary_loss: 0.014996 (0.014994) Loss: 0.22312 (0.22302) +2025-08-24,03:01:14 | INFO | Train Epoch: 10 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.18450 (0.20775) Boundary_loss: 0.014948 (0.014993) Loss: 0.19945 (0.22275) +2025-08-24,03:02:10 | INFO | Train Epoch: 10 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.19613 (0.20762) Boundary_loss: 0.014941 (0.014992) Loss: 0.21107 (0.22262) +2025-08-24,03:03:07 | INFO | Train Epoch: 10 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.25126 (0.20811) Boundary_loss: 0.015065 (0.014993) Loss: 0.26633 (0.22310) +2025-08-24,03:04:04 | INFO | Train Epoch: 10 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.22133 (0.20825) Boundary_loss: 0.015105 (0.014994) Loss: 0.23643 (0.22325) +2025-08-24,03:05:00 | INFO | Train Epoch: 10 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.25236 (0.20873) Boundary_loss: 0.015046 (0.014995) Loss: 0.26740 (0.22373) +2025-08-24,03:05:57 | INFO | Train Epoch: 10 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.24679 (0.20914) Boundary_loss: 0.014989 (0.014995) Loss: 0.26178 (0.22414) +2025-08-24,03:06:53 | INFO | Train Epoch: 10 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.19358 (0.20898) Boundary_loss: 0.014917 (0.014994) Loss: 0.20850 (0.22397) +2025-08-24,03:07:50 | INFO | Train Epoch: 10 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.18942 (0.20877) Boundary_loss: 0.014972 (0.014994) Loss: 0.20440 (0.22377) +2025-08-24,03:08:46 | INFO | Train Epoch: 10 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.494 Boundary Ratio: 0.247 Contrastive_loss: 0.20817 (0.20876) Boundary_loss: 0.014870 (0.014993) Loss: 0.22304 (0.22376) +2025-08-24,03:09:43 | INFO | Train Epoch: 10 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.15835 (0.20825) Boundary_loss: 0.014988 (0.014993) Loss: 0.17334 (0.22324) +2025-08-24,03:10:39 | INFO | Train Epoch: 10 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.23075 (0.20847) Boundary_loss: 0.014995 (0.014993) Loss: 0.24575 (0.22347) +2025-08-24,03:11:36 | INFO | Train Epoch: 10 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.23266 (0.20872) Boundary_loss: 0.014911 (0.014992) Loss: 0.24757 (0.22371) +2025-08-24,03:12:32 | INFO | Train Epoch: 10 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.17316 (0.20836) Boundary_loss: 0.014951 (0.014991) Loss: 0.18812 (0.22335) +2025-08-24,03:13:29 | INFO | Train Epoch: 10 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 0.21452 (0.20842) Boundary_loss: 0.015052 (0.014992) Loss: 0.22957 (0.22342) +2025-08-24,03:14:25 | INFO | Train Epoch: 10 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.16165 (0.20797) Boundary_loss: 0.014861 (0.014991) Loss: 0.17651 (0.22296) +2025-08-24,03:15:22 | INFO | Train Epoch: 10 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.28441 (0.20871) Boundary_loss: 0.014993 (0.014991) Loss: 0.29941 (0.22370) +2025-08-24,03:16:18 | INFO | Train Epoch: 10 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.20525 (0.20867) Boundary_loss: 0.015131 (0.014992) Loss: 0.22038 (0.22367) +2025-08-24,03:17:14 | INFO | Train Epoch: 10 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.18977 (0.20849) Boundary_loss: 0.014893 (0.014991) Loss: 0.20466 (0.22349) +2025-08-24,03:18:11 | INFO | Train Epoch: 10 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.24177 (0.20881) Boundary_loss: 0.014929 (0.014991) Loss: 0.25669 (0.22380) +2025-08-24,03:19:07 | INFO | Train Epoch: 10 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.25115 (0.20920) Boundary_loss: 0.015006 (0.014991) Loss: 0.26616 (0.22420) +2025-08-24,03:20:04 | INFO | Train Epoch: 10 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.287 Boundary Ratio: 0.246 Contrastive_loss: 0.21730 (0.20928) Boundary_loss: 0.014989 (0.014991) Loss: 0.23229 (0.22427) +2025-08-24,03:21:01 | INFO | Train Epoch: 10 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 0.22205 (0.20940) Boundary_loss: 0.014990 (0.014991) Loss: 0.23704 (0.22439) +2025-08-24,03:21:57 | INFO | Train Epoch: 10 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 49.252 Boundary Ratio: 0.251 Contrastive_loss: 0.20481 (0.20935) Boundary_loss: 0.015066 (0.014991) Loss: 0.21988 (0.22435) +2025-08-24,03:22:54 | INFO | Train Epoch: 10 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.21730 (0.20943) Boundary_loss: 0.015100 (0.014992) Loss: 0.23240 (0.22442) +2025-08-24,03:23:50 | INFO | Train Epoch: 10 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.21074 (0.20944) Boundary_loss: 0.014899 (0.014991) Loss: 0.22564 (0.22443) +2025-08-24,03:24:46 | INFO | Train Epoch: 10 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.25007 (0.20980) Boundary_loss: 0.015048 (0.014992) Loss: 0.26512 (0.22479) +2025-08-24,03:25:43 | INFO | Train Epoch: 10 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.20906 (0.20979) Boundary_loss: 0.014999 (0.014992) Loss: 0.22406 (0.22478) +2025-08-24,03:26:40 | INFO | Train Epoch: 10 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 0.22596 (0.20993) Boundary_loss: 0.015064 (0.014993) Loss: 0.24102 (0.22492) +2025-08-24,03:27:36 | INFO | Train Epoch: 10 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.20301 (0.20987) Boundary_loss: 0.015053 (0.014993) Loss: 0.21806 (0.22487) +2025-08-24,03:28:33 | INFO | Train Epoch: 10 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.273 Boundary Ratio: 0.246 Contrastive_loss: 0.18157 (0.20963) Boundary_loss: 0.015021 (0.014993) Loss: 0.19659 (0.22462) +2025-08-24,03:29:29 | INFO | Train Epoch: 10 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.18054 (0.20938) Boundary_loss: 0.015042 (0.014994) Loss: 0.19558 (0.22438) +2025-08-24,03:30:26 | INFO | Train Epoch: 10 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.20349 (0.20933) Boundary_loss: 0.015031 (0.014994) Loss: 0.21852 (0.22433) +2025-08-24,03:31:22 | INFO | Train Epoch: 10 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.22340 (0.20945) Boundary_loss: 0.015103 (0.014995) Loss: 0.23850 (0.22445) +2025-08-24,03:32:19 | INFO | Train Epoch: 10 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.19853 (0.20936) Boundary_loss: 0.014956 (0.014995) Loss: 0.21348 (0.22436) +2025-08-24,03:33:16 | INFO | Train Epoch: 10 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.18817 (0.20919) Boundary_loss: 0.014975 (0.014995) Loss: 0.20315 (0.22418) +2025-08-24,03:34:12 | INFO | Train Epoch: 10 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.21955 (0.20927) Boundary_loss: 0.014927 (0.014994) Loss: 0.23447 (0.22427) +2025-08-24,03:35:09 | INFO | Train Epoch: 10 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.23134 (0.20945) Boundary_loss: 0.015018 (0.014994) Loss: 0.24636 (0.22444) +2025-08-24,03:36:05 | INFO | Train Epoch: 10 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.24474 (0.20973) Boundary_loss: 0.014968 (0.014994) Loss: 0.25970 (0.22473) +2025-08-24,03:37:02 | INFO | Train Epoch: 10 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.23037 (0.20990) Boundary_loss: 0.015010 (0.014994) Loss: 0.24538 (0.22489) +2025-08-24,03:37:58 | INFO | Train Epoch: 10 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.318 Boundary Ratio: 0.252 Contrastive_loss: 0.18667 (0.20971) Boundary_loss: 0.015009 (0.014994) Loss: 0.20168 (0.22471) +2025-08-24,03:38:55 | INFO | Train Epoch: 10 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.19856 (0.20963) Boundary_loss: 0.014935 (0.014994) Loss: 0.21349 (0.22462) +2025-08-24,03:39:51 | INFO | Train Epoch: 10 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.20577 (0.20960) Boundary_loss: 0.014964 (0.014994) Loss: 0.22074 (0.22459) +2025-08-24,03:40:48 | INFO | Train Epoch: 10 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.17288 (0.20931) Boundary_loss: 0.015005 (0.014994) Loss: 0.18788 (0.22431) +2025-08-24,03:41:44 | INFO | Train Epoch: 10 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.23657 (0.20952) Boundary_loss: 0.015033 (0.014994) Loss: 0.25161 (0.22452) +2025-08-24,03:42:41 | INFO | Train Epoch: 10 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 49.312 Boundary Ratio: 0.252 Contrastive_loss: 0.23392 (0.20971) Boundary_loss: 0.014966 (0.014994) Loss: 0.24889 (0.22470) +2025-08-24,03:43:37 | INFO | Train Epoch: 10 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.404 Boundary Ratio: 0.247 Contrastive_loss: 0.17244 (0.20943) Boundary_loss: 0.014895 (0.014993) Loss: 0.18733 (0.22442) +2025-08-24,03:44:34 | INFO | Train Epoch: 10 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.20595 (0.20940) Boundary_loss: 0.014905 (0.014992) Loss: 0.22085 (0.22439) +2025-08-24,03:45:30 | INFO | Train Epoch: 10 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 49.242 Boundary Ratio: 0.251 Contrastive_loss: 0.21525 (0.20944) Boundary_loss: 0.014989 (0.014992) Loss: 0.23024 (0.22444) +2025-08-24,03:46:27 | INFO | Train Epoch: 10 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.21004 (0.20945) Boundary_loss: 0.014854 (0.014991) Loss: 0.22490 (0.22444) +2025-08-24,03:47:23 | INFO | Train Epoch: 10 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.20103 (0.20939) Boundary_loss: 0.014861 (0.014990) Loss: 0.21589 (0.22438) +2025-08-24,03:48:20 | INFO | Train Epoch: 10 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.23913 (0.20960) Boundary_loss: 0.014878 (0.014989) Loss: 0.25401 (0.22459) +2025-08-24,03:49:17 | INFO | Train Epoch: 10 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.17357 (0.20934) Boundary_loss: 0.014911 (0.014989) Loss: 0.18848 (0.22433) +2025-08-24,03:50:13 | INFO | Train Epoch: 10 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.15443 (0.20895) Boundary_loss: 0.014966 (0.014989) Loss: 0.16940 (0.22394) +2025-08-24,03:51:09 | INFO | Train Epoch: 10 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.19595 (0.20886) Boundary_loss: 0.014824 (0.014988) Loss: 0.21077 (0.22385) +2025-08-24,03:52:06 | INFO | Train Epoch: 10 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.21803 (0.20892) Boundary_loss: 0.014970 (0.014987) Loss: 0.23300 (0.22391) +2025-08-24,03:53:02 | INFO | Train Epoch: 10 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.20857 (0.20892) Boundary_loss: 0.014934 (0.014987) Loss: 0.22350 (0.22391) +2025-08-24,03:53:59 | INFO | Train Epoch: 10 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.19863 (0.20885) Boundary_loss: 0.014961 (0.014987) Loss: 0.21359 (0.22384) +2025-08-24,03:54:55 | INFO | Train Epoch: 10 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 49.463 Boundary Ratio: 0.252 Contrastive_loss: 0.25523 (0.20917) Boundary_loss: 0.015001 (0.014987) Loss: 0.27023 (0.22416) +2025-08-24,03:55:52 | INFO | Train Epoch: 10 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 0.21373 (0.20920) Boundary_loss: 0.014932 (0.014987) Loss: 0.22866 (0.22419) +2025-08-24,03:56:48 | INFO | Train Epoch: 10 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.21078 (0.20921) Boundary_loss: 0.014925 (0.014986) Loss: 0.22571 (0.22420) +2025-08-24,03:57:45 | INFO | Train Epoch: 10 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.20989 (0.20922) Boundary_loss: 0.014917 (0.014986) Loss: 0.22481 (0.22420) +2025-08-24,03:58:41 | INFO | Train Epoch: 10 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.270 Boundary Ratio: 0.251 Contrastive_loss: 0.20698 (0.20920) Boundary_loss: 0.014959 (0.014986) Loss: 0.22194 (0.22419) +2025-08-24,03:59:38 | INFO | Train Epoch: 10 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.18877 (0.20906) Boundary_loss: 0.014909 (0.014985) Loss: 0.20368 (0.22405) +2025-08-24,04:00:34 | INFO | Train Epoch: 10 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.17315 (0.20883) Boundary_loss: 0.014941 (0.014985) Loss: 0.18809 (0.22381) +2025-08-24,04:01:31 | INFO | Train Epoch: 10 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.15920 (0.20850) Boundary_loss: 0.014948 (0.014985) Loss: 0.17414 (0.22348) +2025-08-24,04:02:28 | INFO | Train Epoch: 10 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.22313 (0.20860) Boundary_loss: 0.014986 (0.014985) Loss: 0.23812 (0.22358) +2025-08-24,04:03:24 | INFO | Train Epoch: 10 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 0.23875 (0.20879) Boundary_loss: 0.014926 (0.014984) Loss: 0.25367 (0.22378) +2025-08-24,04:04:20 | INFO | Train Epoch: 10 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.25313 (0.20908) Boundary_loss: 0.015033 (0.014984) Loss: 0.26817 (0.22406) +2025-08-24,04:05:17 | INFO | Train Epoch: 10 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.299 Boundary Ratio: 0.246 Contrastive_loss: 0.14331 (0.20866) Boundary_loss: 0.015080 (0.014985) Loss: 0.15839 (0.22364) +2025-08-24,04:06:14 | INFO | Train Epoch: 10 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.15926 (0.20834) Boundary_loss: 0.015033 (0.014985) Loss: 0.17430 (0.22333) +2025-08-24,04:07:10 | INFO | Train Epoch: 10 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.22669 (0.20846) Boundary_loss: 0.014941 (0.014985) Loss: 0.24163 (0.22344) +2025-08-24,04:08:07 | INFO | Train Epoch: 10 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.17364 (0.20824) Boundary_loss: 0.015052 (0.014986) Loss: 0.18869 (0.22322) +2025-08-24,04:09:03 | INFO | Train Epoch: 10 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.17834 (0.20805) Boundary_loss: 0.014971 (0.014985) Loss: 0.19331 (0.22304) +2025-08-24,04:10:00 | INFO | Train Epoch: 10 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.301 Boundary Ratio: 0.246 Contrastive_loss: 0.21747 (0.20811) Boundary_loss: 0.015065 (0.014986) Loss: 0.23254 (0.22310) +2025-08-24,04:10:56 | INFO | Train Epoch: 10 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.21181 (0.20813) Boundary_loss: 0.015040 (0.014986) Loss: 0.22685 (0.22312) +2025-08-24,04:11:53 | INFO | Train Epoch: 10 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.19991 (0.20808) Boundary_loss: 0.014857 (0.014985) Loss: 0.21476 (0.22307) +2025-08-24,04:12:49 | INFO | Train Epoch: 10 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.25236 (0.20835) Boundary_loss: 0.014848 (0.014985) Loss: 0.26721 (0.22334) +2025-08-24,04:13:46 | INFO | Train Epoch: 10 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.19281 (0.20826) Boundary_loss: 0.015079 (0.014985) Loss: 0.20788 (0.22324) +2025-08-24,04:14:43 | INFO | Train Epoch: 10 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14179 (0.20786) Boundary_loss: 0.015033 (0.014985) Loss: 0.15683 (0.22284) +2025-08-24,04:15:39 | INFO | Train Epoch: 10 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.24722 (0.20809) Boundary_loss: 0.014863 (0.014985) Loss: 0.26208 (0.22308) +2025-08-24,04:16:36 | INFO | Train Epoch: 10 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 0.21413 (0.20813) Boundary_loss: 0.014995 (0.014985) Loss: 0.22913 (0.22311) +2025-08-24,04:17:32 | INFO | Train Epoch: 10 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.17320 (0.20792) Boundary_loss: 0.014971 (0.014985) Loss: 0.18817 (0.22291) +2025-08-24,04:18:29 | INFO | Train Epoch: 10 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 0.21219 (0.20795) Boundary_loss: 0.014937 (0.014984) Loss: 0.22713 (0.22293) +2025-08-24,04:19:25 | INFO | Train Epoch: 10 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.15844 (0.20766) Boundary_loss: 0.015031 (0.014985) Loss: 0.17348 (0.22264) +2025-08-24,04:20:22 | INFO | Train Epoch: 10 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.24101 (0.20785) Boundary_loss: 0.015029 (0.014985) Loss: 0.25603 (0.22284) +2025-08-24,04:21:18 | INFO | Train Epoch: 10 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.22103 (0.20793) Boundary_loss: 0.014997 (0.014985) Loss: 0.23602 (0.22291) +2025-08-24,04:22:15 | INFO | Train Epoch: 10 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.17250 (0.20772) Boundary_loss: 0.014863 (0.014984) Loss: 0.18737 (0.22271) +2025-08-24,04:23:12 | INFO | Train Epoch: 10 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.23221 (0.20786) Boundary_loss: 0.015069 (0.014985) Loss: 0.24728 (0.22285) +2025-08-24,04:24:08 | INFO | Train Epoch: 10 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.232 Boundary Ratio: 0.246 Contrastive_loss: 0.16476 (0.20762) Boundary_loss: 0.014993 (0.014985) Loss: 0.17975 (0.22260) +2025-08-24,04:25:05 | INFO | Train Epoch: 10 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 49.348 Boundary Ratio: 0.252 Contrastive_loss: 0.20857 (0.20763) Boundary_loss: 0.015059 (0.014985) Loss: 0.22362 (0.22261) +2025-08-24,04:26:01 | INFO | Train Epoch: 10 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.18347 (0.20749) Boundary_loss: 0.015125 (0.014986) Loss: 0.19860 (0.22248) +2025-08-24,04:26:58 | INFO | Train Epoch: 10 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.24082 (0.20768) Boundary_loss: 0.014947 (0.014986) Loss: 0.25577 (0.22266) +2025-08-24,04:27:55 | INFO | Train Epoch: 10 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.281 Boundary Ratio: 0.246 Contrastive_loss: 0.23607 (0.20783) Boundary_loss: 0.015135 (0.014987) Loss: 0.25120 (0.22282) +2025-08-24,04:28:51 | INFO | Train Epoch: 10 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.24587 (0.20804) Boundary_loss: 0.015168 (0.014988) Loss: 0.26103 (0.22303) +2025-08-24,04:29:47 | INFO | Train Epoch: 10 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.531 Boundary Ratio: 0.253 Contrastive_loss: 0.20760 (0.20804) Boundary_loss: 0.015003 (0.014988) Loss: 0.22261 (0.22303) +2025-08-24,04:30:44 | INFO | Train Epoch: 10 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.20312 (0.20801) Boundary_loss: 0.015085 (0.014988) Loss: 0.21821 (0.22300) +2025-08-24,04:31:41 | INFO | Train Epoch: 10 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 0.15656 (0.20773) Boundary_loss: 0.014962 (0.014988) Loss: 0.17152 (0.22272) +2025-08-24,04:32:37 | INFO | Train Epoch: 10 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.20164 (0.20770) Boundary_loss: 0.015051 (0.014989) Loss: 0.21669 (0.22269) +2025-08-24,04:33:34 | INFO | Train Epoch: 10 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.15251 (0.20740) Boundary_loss: 0.014912 (0.014988) Loss: 0.16742 (0.22239) +2025-08-24,04:34:30 | INFO | Train Epoch: 10 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.24433 (0.20760) Boundary_loss: 0.014952 (0.014988) Loss: 0.25928 (0.22259) +2025-08-24,04:35:27 | INFO | Train Epoch: 10 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.17544 (0.20743) Boundary_loss: 0.014985 (0.014988) Loss: 0.19042 (0.22242) +2025-08-24,04:36:23 | INFO | Train Epoch: 10 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.16468 (0.20720) Boundary_loss: 0.014934 (0.014988) Loss: 0.17962 (0.22219) +2025-08-24,04:37:20 | INFO | Train Epoch: 10 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.21126 (0.20723) Boundary_loss: 0.015032 (0.014988) Loss: 0.22629 (0.22221) +2025-08-24,04:38:17 | INFO | Train Epoch: 10 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.21068 (0.20724) Boundary_loss: 0.015016 (0.014988) Loss: 0.22570 (0.22223) +2025-08-24,04:39:13 | INFO | Train Epoch: 10 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.15229 (0.20696) Boundary_loss: 0.014927 (0.014988) Loss: 0.16722 (0.22195) +2025-08-24,04:40:10 | INFO | Train Epoch: 10 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.14602 (0.20664) Boundary_loss: 0.015013 (0.014988) Loss: 0.16103 (0.22163) +2025-08-24,04:41:06 | INFO | Train Epoch: 10 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 0.22493 (0.20674) Boundary_loss: 0.015032 (0.014988) Loss: 0.23996 (0.22172) +2025-08-24,04:42:03 | INFO | Train Epoch: 10 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.18294 (0.20661) Boundary_loss: 0.014858 (0.014987) Loss: 0.19780 (0.22160) +2025-08-24,04:42:59 | INFO | Train Epoch: 10 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 0.20024 (0.20658) Boundary_loss: 0.015095 (0.014988) Loss: 0.21533 (0.22157) +2025-08-24,04:43:56 | INFO | Train Epoch: 10 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.17958 (0.20645) Boundary_loss: 0.014886 (0.014987) Loss: 0.19447 (0.22143) +2025-08-24,04:44:53 | INFO | Train Epoch: 10 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.15526 (0.20619) Boundary_loss: 0.014978 (0.014987) Loss: 0.17024 (0.22117) +2025-08-24,04:45:49 | INFO | Train Epoch: 10 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.23953 (0.20635) Boundary_loss: 0.014889 (0.014987) Loss: 0.25442 (0.22134) +2025-08-24,04:46:46 | INFO | Train Epoch: 10 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.17972 (0.20622) Boundary_loss: 0.015022 (0.014987) Loss: 0.19474 (0.22121) +2025-08-24,04:47:42 | INFO | Train Epoch: 10 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.21406 (0.20626) Boundary_loss: 0.014855 (0.014986) Loss: 0.22891 (0.22125) +2025-08-24,04:48:39 | INFO | Train Epoch: 10 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.22672 (0.20636) Boundary_loss: 0.015081 (0.014987) Loss: 0.24180 (0.22135) +2025-08-24,04:49:35 | INFO | Train Epoch: 10 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.15883 (0.20613) Boundary_loss: 0.014967 (0.014987) Loss: 0.17380 (0.22111) +2025-08-24,04:50:32 | INFO | Train Epoch: 10 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.227 Boundary Ratio: 0.246 Contrastive_loss: 0.22826 (0.20624) Boundary_loss: 0.014982 (0.014987) Loss: 0.24324 (0.22122) +2025-08-24,04:51:28 | INFO | Train Epoch: 10 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.18824 (0.20615) Boundary_loss: 0.015013 (0.014987) Loss: 0.20325 (0.22113) +2025-08-24,04:52:25 | INFO | Train Epoch: 10 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.271 Boundary Ratio: 0.246 Contrastive_loss: 0.21583 (0.20619) Boundary_loss: 0.014911 (0.014986) Loss: 0.23075 (0.22118) +2025-08-24,04:53:21 | INFO | Train Epoch: 10 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.17236 (0.20603) Boundary_loss: 0.015059 (0.014987) Loss: 0.18741 (0.22102) +2025-08-24,04:54:18 | INFO | Train Epoch: 10 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.20510 (0.20603) Boundary_loss: 0.014872 (0.014986) Loss: 0.21997 (0.22101) +2025-08-24,04:55:14 | INFO | Train Epoch: 10 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.19681 (0.20598) Boundary_loss: 0.014902 (0.014986) Loss: 0.21171 (0.22097) +2025-08-24,04:56:11 | INFO | Train Epoch: 10 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.23141 (0.20610) Boundary_loss: 0.014954 (0.014986) Loss: 0.24636 (0.22109) +2025-08-24,04:57:07 | INFO | Train Epoch: 10 [10752512/26365952 (41%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.20641 (0.20611) Boundary_loss: 0.014984 (0.014986) Loss: 0.22139 (0.22109) +2025-08-24,04:58:04 | INFO | Train Epoch: 10 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.160 Boundary Ratio: 0.246 Contrastive_loss: 0.13625 (0.20578) Boundary_loss: 0.015065 (0.014986) Loss: 0.15132 (0.22076) +2025-08-24,04:59:00 | INFO | Train Epoch: 10 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 0.17013 (0.20561) Boundary_loss: 0.014919 (0.014986) Loss: 0.18505 (0.22059) +2025-08-24,04:59:57 | INFO | Train Epoch: 10 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.21332 (0.20564) Boundary_loss: 0.014988 (0.014986) Loss: 0.22831 (0.22063) +2025-08-24,05:00:53 | INFO | Train Epoch: 10 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.18465 (0.20555) Boundary_loss: 0.014967 (0.014986) Loss: 0.19962 (0.22053) +2025-08-24,05:01:50 | INFO | Train Epoch: 10 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.23058 (0.20566) Boundary_loss: 0.014944 (0.014986) Loss: 0.24552 (0.22065) +2025-08-24,05:02:47 | INFO | Train Epoch: 10 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.24791 (0.20586) Boundary_loss: 0.015006 (0.014986) Loss: 0.26291 (0.22084) +2025-08-24,05:03:43 | INFO | Train Epoch: 10 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.17846 (0.20573) Boundary_loss: 0.014960 (0.014985) Loss: 0.19342 (0.22072) +2025-08-24,05:04:40 | INFO | Train Epoch: 10 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.16224 (0.20553) Boundary_loss: 0.015067 (0.014986) Loss: 0.17731 (0.22052) +2025-08-24,05:05:36 | INFO | Train Epoch: 10 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.26687 (0.20581) Boundary_loss: 0.014861 (0.014985) Loss: 0.28173 (0.22080) +2025-08-24,05:06:33 | INFO | Train Epoch: 10 [11264512/26365952 (43%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.14115 (0.20552) Boundary_loss: 0.014949 (0.014985) Loss: 0.15610 (0.22050) +2025-08-24,05:07:29 | INFO | Train Epoch: 10 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.23036 (0.20563) Boundary_loss: 0.015031 (0.014985) Loss: 0.24539 (0.22062) +2025-08-24,05:08:26 | INFO | Train Epoch: 10 [11366912/26365952 (43%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.30532 (0.20608) Boundary_loss: 0.014996 (0.014985) Loss: 0.32032 (0.22106) +2025-08-24,05:09:22 | INFO | Train Epoch: 10 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.19594 (0.20603) Boundary_loss: 0.014878 (0.014985) Loss: 0.21081 (0.22102) +2025-08-24,05:10:19 | INFO | Train Epoch: 10 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.14797 (0.20577) Boundary_loss: 0.015050 (0.014985) Loss: 0.16302 (0.22076) +2025-08-24,05:11:16 | INFO | Train Epoch: 10 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.365 Boundary Ratio: 0.247 Contrastive_loss: 0.22037 (0.20584) Boundary_loss: 0.015049 (0.014985) Loss: 0.23542 (0.22082) +2025-08-24,05:12:12 | INFO | Train Epoch: 10 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.24764 (0.20602) Boundary_loss: 0.014916 (0.014985) Loss: 0.26255 (0.22101) +2025-08-24,05:13:08 | INFO | Train Epoch: 10 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.18503 (0.20593) Boundary_loss: 0.014937 (0.014985) Loss: 0.19997 (0.22092) +2025-08-24,05:14:05 | INFO | Train Epoch: 10 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.19194 (0.20587) Boundary_loss: 0.014927 (0.014985) Loss: 0.20686 (0.22086) +2025-08-24,05:15:02 | INFO | Train Epoch: 10 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.20364 (0.20586) Boundary_loss: 0.015022 (0.014985) Loss: 0.21867 (0.22085) +2025-08-24,05:15:58 | INFO | Train Epoch: 10 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.23817 (0.20600) Boundary_loss: 0.014882 (0.014984) Loss: 0.25306 (0.22099) +2025-08-24,05:16:55 | INFO | Train Epoch: 10 [11827712/26365952 (45%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.23285 (0.20612) Boundary_loss: 0.014906 (0.014984) Loss: 0.24776 (0.22110) +2025-08-24,05:17:51 | INFO | Train Epoch: 10 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.19902 (0.20609) Boundary_loss: 0.014930 (0.014984) Loss: 0.21395 (0.22107) +2025-08-24,05:18:48 | INFO | Train Epoch: 10 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.18008 (0.20597) Boundary_loss: 0.015080 (0.014984) Loss: 0.19516 (0.22096) +2025-08-24,05:19:44 | INFO | Train Epoch: 10 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.28117 (0.20629) Boundary_loss: 0.015054 (0.014985) Loss: 0.29622 (0.22128) +2025-08-24,05:20:41 | INFO | Train Epoch: 10 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.21493 (0.20633) Boundary_loss: 0.014907 (0.014984) Loss: 0.22984 (0.22132) +2025-08-24,05:21:38 | INFO | Train Epoch: 10 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.344 Boundary Ratio: 0.247 Contrastive_loss: 0.21066 (0.20635) Boundary_loss: 0.014900 (0.014984) Loss: 0.22556 (0.22133) +2025-08-24,05:22:34 | INFO | Train Epoch: 10 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.21937 (0.20640) Boundary_loss: 0.014977 (0.014984) Loss: 0.23435 (0.22139) +2025-08-24,05:23:31 | INFO | Train Epoch: 10 [12186112/26365952 (46%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.13682 (0.20611) Boundary_loss: 0.014933 (0.014984) Loss: 0.15175 (0.22110) +2025-08-24,05:24:27 | INFO | Train Epoch: 10 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 0.17295 (0.20597) Boundary_loss: 0.015025 (0.014984) Loss: 0.18798 (0.22096) +2025-08-24,05:25:24 | INFO | Train Epoch: 10 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.21481 (0.20601) Boundary_loss: 0.015023 (0.014984) Loss: 0.22984 (0.22100) +2025-08-24,05:26:21 | INFO | Train Epoch: 10 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.17585 (0.20589) Boundary_loss: 0.014989 (0.014984) Loss: 0.19084 (0.22087) +2025-08-24,05:27:17 | INFO | Train Epoch: 10 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.20266 (0.20587) Boundary_loss: 0.014945 (0.014984) Loss: 0.21760 (0.22086) +2025-08-24,05:28:14 | INFO | Train Epoch: 10 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.19738 (0.20584) Boundary_loss: 0.014957 (0.014984) Loss: 0.21234 (0.22082) +2025-08-24,05:29:10 | INFO | Train Epoch: 10 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.16058 (0.20565) Boundary_loss: 0.014828 (0.014983) Loss: 0.17541 (0.22064) +2025-08-24,05:30:07 | INFO | Train Epoch: 10 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.15230 (0.20544) Boundary_loss: 0.014937 (0.014983) Loss: 0.16724 (0.22042) +2025-08-24,05:31:03 | INFO | Train Epoch: 10 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17154 (0.20530) Boundary_loss: 0.014876 (0.014982) Loss: 0.18641 (0.22028) +2025-08-24,05:32:00 | INFO | Train Epoch: 10 [12646912/26365952 (48%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 0.21225 (0.20533) Boundary_loss: 0.015020 (0.014983) Loss: 0.22727 (0.22031) +2025-08-24,05:32:57 | INFO | Train Epoch: 10 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.17500 (0.20521) Boundary_loss: 0.014962 (0.014983) Loss: 0.18996 (0.22019) +2025-08-24,05:33:53 | INFO | Train Epoch: 10 [12749312/26365952 (48%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 0.19239 (0.20515) Boundary_loss: 0.014995 (0.014983) Loss: 0.20738 (0.22014) +2025-08-24,05:34:50 | INFO | Train Epoch: 10 [12800512/26365952 (49%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.19481 (0.20511) Boundary_loss: 0.015024 (0.014983) Loss: 0.20983 (0.22010) +2025-08-24,05:35:47 | INFO | Train Epoch: 10 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.16857 (0.20497) Boundary_loss: 0.014896 (0.014982) Loss: 0.18347 (0.21995) +2025-08-24,05:36:43 | INFO | Train Epoch: 10 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.13683 (0.20470) Boundary_loss: 0.014991 (0.014982) Loss: 0.15183 (0.21968) +2025-08-24,05:37:39 | INFO | Train Epoch: 10 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.17559 (0.20458) Boundary_loss: 0.014902 (0.014982) Loss: 0.19049 (0.21957) +2025-08-24,05:38:36 | INFO | Train Epoch: 10 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.18288 (0.20450) Boundary_loss: 0.014977 (0.014982) Loss: 0.19785 (0.21948) +2025-08-24,05:39:33 | INFO | Train Epoch: 10 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.18625 (0.20443) Boundary_loss: 0.015055 (0.014982) Loss: 0.20130 (0.21941) +2025-08-24,05:40:29 | INFO | Train Epoch: 10 [13107712/26365952 (50%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.21828 (0.20448) Boundary_loss: 0.014799 (0.014982) Loss: 0.23307 (0.21946) +2025-08-24,05:41:26 | INFO | Train Epoch: 10 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.22324 (0.20455) Boundary_loss: 0.014914 (0.014981) Loss: 0.23816 (0.21954) +2025-08-24,05:42:22 | INFO | Train Epoch: 10 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.17433 (0.20444) Boundary_loss: 0.014910 (0.014981) Loss: 0.18924 (0.21942) +2025-08-24,05:43:19 | INFO | Train Epoch: 10 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.19757 (0.20441) Boundary_loss: 0.014872 (0.014981) Loss: 0.21244 (0.21939) +2025-08-24,05:44:15 | INFO | Train Epoch: 10 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.15966 (0.20424) Boundary_loss: 0.015130 (0.014981) Loss: 0.17479 (0.21922) +2025-08-24,05:45:12 | INFO | Train Epoch: 10 [13363712/26365952 (51%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.22062 (0.20430) Boundary_loss: 0.014946 (0.014981) Loss: 0.23556 (0.21928) +2025-08-24,05:46:09 | INFO | Train Epoch: 10 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.17586 (0.20419) Boundary_loss: 0.014841 (0.014981) Loss: 0.19070 (0.21918) +2025-08-24,05:47:05 | INFO | Train Epoch: 10 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.20277 (0.20419) Boundary_loss: 0.014908 (0.014980) Loss: 0.21768 (0.21917) +2025-08-24,05:48:02 | INFO | Train Epoch: 10 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.15395 (0.20400) Boundary_loss: 0.014996 (0.014980) Loss: 0.16894 (0.21898) +2025-08-24,05:48:58 | INFO | Train Epoch: 10 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.17374 (0.20389) Boundary_loss: 0.015010 (0.014981) Loss: 0.18875 (0.21887) +2025-08-24,05:49:55 | INFO | Train Epoch: 10 [13619712/26365952 (52%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 0.19924 (0.20387) Boundary_loss: 0.014985 (0.014981) Loss: 0.21423 (0.21885) +2025-08-24,05:50:51 | INFO | Train Epoch: 10 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.17414 (0.20376) Boundary_loss: 0.014888 (0.014980) Loss: 0.18903 (0.21874) +2025-08-24,05:51:48 | INFO | Train Epoch: 10 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.16736 (0.20362) Boundary_loss: 0.014914 (0.014980) Loss: 0.18227 (0.21860) +2025-08-24,05:52:45 | INFO | Train Epoch: 10 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.19003 (0.20357) Boundary_loss: 0.014917 (0.014980) Loss: 0.20495 (0.21855) +2025-08-24,05:53:41 | INFO | Train Epoch: 10 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.19712 (0.20355) Boundary_loss: 0.014849 (0.014979) Loss: 0.21197 (0.21853) +2025-08-24,05:54:38 | INFO | Train Epoch: 10 [13875712/26365952 (53%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 0.17396 (0.20344) Boundary_loss: 0.014989 (0.014979) Loss: 0.18895 (0.21842) +2025-08-24,05:55:34 | INFO | Train Epoch: 10 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.15454 (0.20326) Boundary_loss: 0.014932 (0.014979) Loss: 0.16947 (0.21824) +2025-08-24,05:56:31 | INFO | Train Epoch: 10 [13978112/26365952 (53%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.16695 (0.20313) Boundary_loss: 0.014967 (0.014979) Loss: 0.18191 (0.21811) +2025-08-24,05:57:28 | INFO | Train Epoch: 10 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.16456 (0.20299) Boundary_loss: 0.014985 (0.014979) Loss: 0.17955 (0.21797) +2025-08-24,05:58:24 | INFO | Train Epoch: 10 [14080512/26365952 (53%)] Avg Boundaries (per batch): 49.398 Boundary Ratio: 0.252 Contrastive_loss: 0.18301 (0.20292) Boundary_loss: 0.015076 (0.014979) Loss: 0.19809 (0.21789) +2025-08-24,05:59:21 | INFO | Train Epoch: 10 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.27019 (0.20316) Boundary_loss: 0.014949 (0.014979) Loss: 0.28514 (0.21814) +2025-08-24,06:00:17 | INFO | Train Epoch: 10 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 0.18126 (0.20308) Boundary_loss: 0.014863 (0.014979) Loss: 0.19612 (0.21806) +2025-08-24,06:01:14 | INFO | Train Epoch: 10 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.543 Boundary Ratio: 0.253 Contrastive_loss: 0.21244 (0.20311) Boundary_loss: 0.014980 (0.014979) Loss: 0.22742 (0.21809) +2025-08-24,06:02:10 | INFO | Train Epoch: 10 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.16639 (0.20298) Boundary_loss: 0.014969 (0.014979) Loss: 0.18136 (0.21796) +2025-08-24,06:03:07 | INFO | Train Epoch: 10 [14336512/26365952 (54%)] Avg Boundaries (per batch): 49.260 Boundary Ratio: 0.251 Contrastive_loss: 0.19716 (0.20296) Boundary_loss: 0.014900 (0.014979) Loss: 0.21206 (0.21794) +2025-08-24,06:04:03 | INFO | Train Epoch: 10 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.20835 (0.20298) Boundary_loss: 0.014939 (0.014978) Loss: 0.22329 (0.21796) +2025-08-24,06:05:00 | INFO | Train Epoch: 10 [14438912/26365952 (55%)] Avg Boundaries (per batch): 49.170 Boundary Ratio: 0.251 Contrastive_loss: 0.15540 (0.20281) Boundary_loss: 0.014979 (0.014978) Loss: 0.17038 (0.21779) +2025-08-24,06:05:57 | INFO | Train Epoch: 10 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.14925 (0.20262) Boundary_loss: 0.014986 (0.014978) Loss: 0.16423 (0.21760) +2025-08-24,06:06:53 | INFO | Train Epoch: 10 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.13567 (0.20239) Boundary_loss: 0.015080 (0.014979) Loss: 0.15075 (0.21737) +2025-08-24,06:07:50 | INFO | Train Epoch: 10 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.22836 (0.20248) Boundary_loss: 0.015039 (0.014979) Loss: 0.24339 (0.21746) +2025-08-24,06:08:46 | INFO | Train Epoch: 10 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.14554 (0.20228) Boundary_loss: 0.014815 (0.014978) Loss: 0.16036 (0.21726) +2025-08-24,06:09:43 | INFO | Train Epoch: 10 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.18436 (0.20222) Boundary_loss: 0.014991 (0.014979) Loss: 0.19935 (0.21720) +2025-08-24,06:10:40 | INFO | Train Epoch: 10 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.15229 (0.20205) Boundary_loss: 0.014974 (0.014978) Loss: 0.16726 (0.21702) +2025-08-24,06:11:36 | INFO | Train Epoch: 10 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.21024 (0.20207) Boundary_loss: 0.015020 (0.014979) Loss: 0.22526 (0.21705) +2025-08-24,06:12:33 | INFO | Train Epoch: 10 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.20467 (0.20208) Boundary_loss: 0.014947 (0.014979) Loss: 0.21962 (0.21706) +2025-08-24,06:13:29 | INFO | Train Epoch: 10 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.27681 (0.20234) Boundary_loss: 0.014951 (0.014978) Loss: 0.29176 (0.21732) +2025-08-24,06:14:26 | INFO | Train Epoch: 10 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.15095 (0.20216) Boundary_loss: 0.014951 (0.014978) Loss: 0.16591 (0.21714) +2025-08-24,06:15:22 | INFO | Train Epoch: 10 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.18055 (0.20209) Boundary_loss: 0.015094 (0.014979) Loss: 0.19565 (0.21707) +2025-08-24,06:16:19 | INFO | Train Epoch: 10 [15053312/26365952 (57%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.17074 (0.20198) Boundary_loss: 0.014938 (0.014979) Loss: 0.18568 (0.21696) +2025-08-24,06:17:16 | INFO | Train Epoch: 10 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.20912 (0.20201) Boundary_loss: 0.014912 (0.014978) Loss: 0.22403 (0.21699) +2025-08-24,06:18:12 | INFO | Train Epoch: 10 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.19359 (0.20198) Boundary_loss: 0.015011 (0.014978) Loss: 0.20860 (0.21696) +2025-08-24,06:19:09 | INFO | Train Epoch: 10 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.17942 (0.20190) Boundary_loss: 0.014916 (0.014978) Loss: 0.19433 (0.21688) +2025-08-24,06:20:05 | INFO | Train Epoch: 10 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.20057 (0.20190) Boundary_loss: 0.014925 (0.014978) Loss: 0.21549 (0.21688) +2025-08-24,06:21:02 | INFO | Train Epoch: 10 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.18888 (0.20186) Boundary_loss: 0.014886 (0.014978) Loss: 0.20376 (0.21683) +2025-08-24,06:21:58 | INFO | Train Epoch: 10 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.23151 (0.20195) Boundary_loss: 0.015054 (0.014978) Loss: 0.24656 (0.21693) +2025-08-24,06:22:55 | INFO | Train Epoch: 10 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.19165 (0.20192) Boundary_loss: 0.014937 (0.014978) Loss: 0.20659 (0.21690) +2025-08-24,06:23:51 | INFO | Train Epoch: 10 [15462912/26365952 (59%)] Avg Boundaries (per batch): 49.129 Boundary Ratio: 0.251 Contrastive_loss: 0.18298 (0.20186) Boundary_loss: 0.015008 (0.014978) Loss: 0.19799 (0.21684) +2025-08-24,06:24:48 | INFO | Train Epoch: 10 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.16701 (0.20174) Boundary_loss: 0.014950 (0.014978) Loss: 0.18196 (0.21672) +2025-08-24,06:25:44 | INFO | Train Epoch: 10 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.434 Boundary Ratio: 0.247 Contrastive_loss: 0.19611 (0.20172) Boundary_loss: 0.015036 (0.014978) Loss: 0.21115 (0.21670) +2025-08-24,06:26:41 | INFO | Train Epoch: 10 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.16502 (0.20160) Boundary_loss: 0.014890 (0.014978) Loss: 0.17991 (0.21658) +2025-08-24,06:27:38 | INFO | Train Epoch: 10 [15667712/26365952 (59%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.17602 (0.20152) Boundary_loss: 0.015005 (0.014978) Loss: 0.19103 (0.21650) +2025-08-24,06:28:34 | INFO | Train Epoch: 10 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.19367 (0.20150) Boundary_loss: 0.014939 (0.014978) Loss: 0.20861 (0.21647) +2025-08-24,06:29:31 | INFO | Train Epoch: 10 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.23176 (0.20159) Boundary_loss: 0.014942 (0.014978) Loss: 0.24670 (0.21657) +2025-08-24,06:30:27 | INFO | Train Epoch: 10 [15821312/26365952 (60%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.22757 (0.20168) Boundary_loss: 0.014975 (0.014978) Loss: 0.24255 (0.21666) +2025-08-24,06:31:23 | INFO | Train Epoch: 10 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.19106 (0.20164) Boundary_loss: 0.015018 (0.014978) Loss: 0.20608 (0.21662) +2025-08-24,06:32:20 | INFO | Train Epoch: 10 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.17497 (0.20156) Boundary_loss: 0.014927 (0.014978) Loss: 0.18989 (0.21654) +2025-08-24,06:33:16 | INFO | Train Epoch: 10 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.22169 (0.20162) Boundary_loss: 0.014977 (0.014978) Loss: 0.23666 (0.21660) +2025-08-24,06:34:13 | INFO | Train Epoch: 10 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.529 Boundary Ratio: 0.248 Contrastive_loss: 0.19629 (0.20161) Boundary_loss: 0.014856 (0.014977) Loss: 0.21115 (0.21658) +2025-08-24,06:35:09 | INFO | Train Epoch: 10 [16077312/26365952 (61%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.19756 (0.20159) Boundary_loss: 0.014984 (0.014977) Loss: 0.21255 (0.21657) +2025-08-24,06:36:06 | INFO | Train Epoch: 10 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.16594 (0.20148) Boundary_loss: 0.014951 (0.014977) Loss: 0.18089 (0.21646) +2025-08-24,06:37:03 | INFO | Train Epoch: 10 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.15874 (0.20134) Boundary_loss: 0.015103 (0.014978) Loss: 0.17384 (0.21632) +2025-08-24,06:37:59 | INFO | Train Epoch: 10 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.17012 (0.20125) Boundary_loss: 0.014879 (0.014977) Loss: 0.18500 (0.21622) +2025-08-24,06:38:55 | INFO | Train Epoch: 10 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.22026 (0.20131) Boundary_loss: 0.014915 (0.014977) Loss: 0.23518 (0.21628) +2025-08-24,06:39:52 | INFO | Train Epoch: 10 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.18453 (0.20125) Boundary_loss: 0.014947 (0.014977) Loss: 0.19948 (0.21623) +2025-08-24,06:40:49 | INFO | Train Epoch: 10 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.23793 (0.20137) Boundary_loss: 0.014898 (0.014977) Loss: 0.25283 (0.21634) +2025-08-24,06:41:45 | INFO | Train Epoch: 10 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.18720 (0.20132) Boundary_loss: 0.014931 (0.014977) Loss: 0.20213 (0.21630) +2025-08-24,06:42:41 | INFO | Train Epoch: 10 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.14135 (0.20114) Boundary_loss: 0.014960 (0.014977) Loss: 0.15631 (0.21612) +2025-08-24,06:43:38 | INFO | Train Epoch: 10 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.24498 (0.20127) Boundary_loss: 0.015002 (0.014977) Loss: 0.25999 (0.21625) +2025-08-24,06:44:34 | INFO | Train Epoch: 10 [16589312/26365952 (63%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.19394 (0.20125) Boundary_loss: 0.015082 (0.014977) Loss: 0.20902 (0.21623) +2025-08-24,06:45:31 | INFO | Train Epoch: 10 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.16731 (0.20115) Boundary_loss: 0.014872 (0.014977) Loss: 0.18218 (0.21612) +2025-08-24,06:46:27 | INFO | Train Epoch: 10 [16691712/26365952 (63%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.20216 (0.20115) Boundary_loss: 0.015055 (0.014977) Loss: 0.21722 (0.21613) +2025-08-24,06:47:24 | INFO | Train Epoch: 10 [16742912/26365952 (64%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.19750 (0.20114) Boundary_loss: 0.014933 (0.014977) Loss: 0.21243 (0.21612) +2025-08-24,06:48:20 | INFO | Train Epoch: 10 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.12766 (0.20092) Boundary_loss: 0.014926 (0.014977) Loss: 0.14259 (0.21589) +2025-08-24,06:49:17 | INFO | Train Epoch: 10 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.21921 (0.20097) Boundary_loss: 0.014909 (0.014976) Loss: 0.23411 (0.21595) +2025-08-24,06:50:13 | INFO | Train Epoch: 10 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.17426 (0.20089) Boundary_loss: 0.015057 (0.014977) Loss: 0.18931 (0.21587) +2025-08-24,06:51:10 | INFO | Train Epoch: 10 [16947712/26365952 (64%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.19839 (0.20088) Boundary_loss: 0.014984 (0.014977) Loss: 0.21338 (0.21586) +2025-08-24,06:52:07 | INFO | Train Epoch: 10 [16998912/26365952 (64%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.18161 (0.20083) Boundary_loss: 0.014974 (0.014977) Loss: 0.19658 (0.21580) +2025-08-24,06:53:03 | INFO | Train Epoch: 10 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.260 Boundary Ratio: 0.246 Contrastive_loss: 0.23350 (0.20092) Boundary_loss: 0.014856 (0.014976) Loss: 0.24836 (0.21590) +2025-08-24,06:54:00 | INFO | Train Epoch: 10 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.191 Boundary Ratio: 0.246 Contrastive_loss: 0.19369 (0.20090) Boundary_loss: 0.014950 (0.014976) Loss: 0.20864 (0.21588) +2025-08-24,06:54:56 | INFO | Train Epoch: 10 [17152512/26365952 (65%)] Avg Boundaries (per batch): 49.412 Boundary Ratio: 0.252 Contrastive_loss: 0.18870 (0.20087) Boundary_loss: 0.015021 (0.014976) Loss: 0.20372 (0.21584) +2025-08-24,06:55:53 | INFO | Train Epoch: 10 [17203712/26365952 (65%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.19751 (0.20086) Boundary_loss: 0.015066 (0.014977) Loss: 0.21258 (0.21583) +2025-08-24,06:56:49 | INFO | Train Epoch: 10 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 0.23367 (0.20095) Boundary_loss: 0.014919 (0.014976) Loss: 0.24859 (0.21593) +2025-08-24,06:57:46 | INFO | Train Epoch: 10 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.17609 (0.20088) Boundary_loss: 0.015044 (0.014977) Loss: 0.19114 (0.21586) +2025-08-24,06:58:42 | INFO | Train Epoch: 10 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.19836 (0.20087) Boundary_loss: 0.014980 (0.014977) Loss: 0.21334 (0.21585) +2025-08-24,06:59:39 | INFO | Train Epoch: 10 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.14453 (0.20071) Boundary_loss: 0.014878 (0.014976) Loss: 0.15941 (0.21568) +2025-08-24,07:00:35 | INFO | Train Epoch: 10 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.17480 (0.20063) Boundary_loss: 0.014972 (0.014976) Loss: 0.18977 (0.21561) +2025-08-24,07:01:32 | INFO | Train Epoch: 10 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.25079 (0.20078) Boundary_loss: 0.015064 (0.014977) Loss: 0.26586 (0.21575) +2025-08-24,07:02:28 | INFO | Train Epoch: 10 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.14908 (0.20063) Boundary_loss: 0.014966 (0.014977) Loss: 0.16404 (0.21560) +2025-08-24,07:03:25 | INFO | Train Epoch: 10 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.21789 (0.20068) Boundary_loss: 0.015141 (0.014977) Loss: 0.23303 (0.21565) +2025-08-24,07:04:21 | INFO | Train Epoch: 10 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.22920 (0.20076) Boundary_loss: 0.015007 (0.014977) Loss: 0.24420 (0.21574) +2025-08-24,07:05:18 | INFO | Train Epoch: 10 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.14724 (0.20060) Boundary_loss: 0.015037 (0.014977) Loss: 0.16227 (0.21558) +2025-08-24,07:06:14 | INFO | Train Epoch: 10 [17766912/26365952 (67%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.20269 (0.20061) Boundary_loss: 0.014885 (0.014977) Loss: 0.21758 (0.21559) +2025-08-24,07:07:11 | INFO | Train Epoch: 10 [17818112/26365952 (68%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.20704 (0.20063) Boundary_loss: 0.014944 (0.014977) Loss: 0.22199 (0.21561) +2025-08-24,07:08:08 | INFO | Train Epoch: 10 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.19334 (0.20061) Boundary_loss: 0.014891 (0.014977) Loss: 0.20823 (0.21558) +2025-08-24,07:09:04 | INFO | Train Epoch: 10 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 0.21704 (0.20066) Boundary_loss: 0.014868 (0.014976) Loss: 0.23191 (0.21563) +2025-08-24,07:10:01 | INFO | Train Epoch: 10 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.22709 (0.20073) Boundary_loss: 0.015025 (0.014976) Loss: 0.24211 (0.21571) +2025-08-24,07:10:57 | INFO | Train Epoch: 10 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.19681 (0.20072) Boundary_loss: 0.014962 (0.014976) Loss: 0.21177 (0.21570) +2025-08-24,07:11:53 | INFO | Train Epoch: 10 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.22566 (0.20079) Boundary_loss: 0.014978 (0.014976) Loss: 0.24064 (0.21577) +2025-08-24,07:12:50 | INFO | Train Epoch: 10 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.22621 (0.20086) Boundary_loss: 0.014872 (0.014976) Loss: 0.24108 (0.21584) +2025-08-24,07:13:47 | INFO | Train Epoch: 10 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17805 (0.20080) Boundary_loss: 0.014977 (0.014976) Loss: 0.19302 (0.21577) +2025-08-24,07:14:43 | INFO | Train Epoch: 10 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.348 Boundary Ratio: 0.247 Contrastive_loss: 0.18221 (0.20074) Boundary_loss: 0.014965 (0.014976) Loss: 0.19718 (0.21572) +2025-08-24,07:15:40 | INFO | Train Epoch: 10 [18278912/26365952 (69%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.18897 (0.20071) Boundary_loss: 0.014836 (0.014976) Loss: 0.20381 (0.21569) +2025-08-24,07:16:36 | INFO | Train Epoch: 10 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.21966 (0.20076) Boundary_loss: 0.014818 (0.014975) Loss: 0.23448 (0.21574) +2025-08-24,07:17:33 | INFO | Train Epoch: 10 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.18173 (0.20071) Boundary_loss: 0.014990 (0.014975) Loss: 0.19672 (0.21569) +2025-08-24,07:18:29 | INFO | Train Epoch: 10 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.16220 (0.20061) Boundary_loss: 0.014923 (0.014975) Loss: 0.17712 (0.21558) +2025-08-24,07:19:26 | INFO | Train Epoch: 10 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.17923 (0.20055) Boundary_loss: 0.014951 (0.014975) Loss: 0.19419 (0.21552) +2025-08-24,07:20:22 | INFO | Train Epoch: 10 [18534912/26365952 (70%)] Avg Boundaries (per batch): 49.260 Boundary Ratio: 0.251 Contrastive_loss: 0.19775 (0.20054) Boundary_loss: 0.015077 (0.014975) Loss: 0.21282 (0.21551) +2025-08-24,07:21:19 | INFO | Train Epoch: 10 [18586112/26365952 (70%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.21793 (0.20059) Boundary_loss: 0.014945 (0.014975) Loss: 0.23288 (0.21556) +2025-08-24,07:22:15 | INFO | Train Epoch: 10 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.17830 (0.20053) Boundary_loss: 0.014900 (0.014975) Loss: 0.19320 (0.21550) +2025-08-24,07:23:12 | INFO | Train Epoch: 10 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.398 Boundary Ratio: 0.247 Contrastive_loss: 0.17150 (0.20045) Boundary_loss: 0.014913 (0.014975) Loss: 0.18641 (0.21542) +2025-08-24,07:24:08 | INFO | Train Epoch: 10 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.21947 (0.20050) Boundary_loss: 0.014918 (0.014975) Loss: 0.23439 (0.21547) +2025-08-24,07:25:05 | INFO | Train Epoch: 10 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.17788 (0.20044) Boundary_loss: 0.014844 (0.014974) Loss: 0.19273 (0.21541) +2025-08-24,07:26:02 | INFO | Train Epoch: 10 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.17613 (0.20037) Boundary_loss: 0.014918 (0.014974) Loss: 0.19105 (0.21534) +2025-08-24,07:26:58 | INFO | Train Epoch: 10 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.21527 (0.20041) Boundary_loss: 0.014809 (0.014974) Loss: 0.23008 (0.21538) +2025-08-24,07:27:55 | INFO | Train Epoch: 10 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.18258 (0.20036) Boundary_loss: 0.014923 (0.014974) Loss: 0.19750 (0.21534) +2025-08-24,07:28:51 | INFO | Train Epoch: 10 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.21789 (0.20041) Boundary_loss: 0.014805 (0.014973) Loss: 0.23269 (0.21538) +2025-08-24,07:29:48 | INFO | Train Epoch: 10 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.19717 (0.20040) Boundary_loss: 0.014982 (0.014973) Loss: 0.21216 (0.21537) +2025-08-24,07:30:44 | INFO | Train Epoch: 10 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 0.17514 (0.20033) Boundary_loss: 0.014982 (0.014973) Loss: 0.19012 (0.21531) +2025-08-24,07:31:40 | INFO | Train Epoch: 10 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.16924 (0.20025) Boundary_loss: 0.014859 (0.014973) Loss: 0.18409 (0.21522) +2025-08-24,07:32:37 | INFO | Train Epoch: 10 [19200512/26365952 (73%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.20341 (0.20026) Boundary_loss: 0.014981 (0.014973) Loss: 0.21839 (0.21523) +2025-08-24,07:33:34 | INFO | Train Epoch: 10 [19251712/26365952 (73%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.14342 (0.20011) Boundary_loss: 0.014906 (0.014973) Loss: 0.15833 (0.21508) +2025-08-24,07:34:30 | INFO | Train Epoch: 10 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.20984 (0.20013) Boundary_loss: 0.014948 (0.014973) Loss: 0.22479 (0.21511) +2025-08-24,07:35:27 | INFO | Train Epoch: 10 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.25797 (0.20029) Boundary_loss: 0.014919 (0.014973) Loss: 0.27289 (0.21526) +2025-08-24,07:36:23 | INFO | Train Epoch: 10 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.12727 (0.20009) Boundary_loss: 0.014928 (0.014973) Loss: 0.14220 (0.21507) +2025-08-24,07:37:20 | INFO | Train Epoch: 10 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 0.16678 (0.20001) Boundary_loss: 0.015052 (0.014973) Loss: 0.18183 (0.21498) +2025-08-24,07:38:17 | INFO | Train Epoch: 10 [19507712/26365952 (74%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.18098 (0.19996) Boundary_loss: 0.014934 (0.014973) Loss: 0.19591 (0.21493) +2025-08-24,07:39:13 | INFO | Train Epoch: 10 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.16638 (0.19987) Boundary_loss: 0.014885 (0.014972) Loss: 0.18126 (0.21484) +2025-08-24,07:40:10 | INFO | Train Epoch: 10 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.26726 (0.20005) Boundary_loss: 0.015043 (0.014973) Loss: 0.28230 (0.21502) +2025-08-24,07:41:06 | INFO | Train Epoch: 10 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.16861 (0.19996) Boundary_loss: 0.014916 (0.014972) Loss: 0.18352 (0.21494) +2025-08-24,07:42:03 | INFO | Train Epoch: 10 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.22068 (0.20002) Boundary_loss: 0.014932 (0.014972) Loss: 0.23561 (0.21499) +2025-08-24,07:42:59 | INFO | Train Epoch: 10 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.18813 (0.19999) Boundary_loss: 0.014819 (0.014972) Loss: 0.20295 (0.21496) +2025-08-24,07:43:56 | INFO | Train Epoch: 10 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.258 Boundary Ratio: 0.251 Contrastive_loss: 0.24639 (0.20011) Boundary_loss: 0.014986 (0.014972) Loss: 0.26137 (0.21508) +2025-08-24,07:44:52 | INFO | Train Epoch: 10 [19866112/26365952 (75%)] Avg Boundaries (per batch): 49.203 Boundary Ratio: 0.251 Contrastive_loss: 0.13713 (0.19994) Boundary_loss: 0.014919 (0.014972) Loss: 0.15205 (0.21492) +2025-08-24,07:45:49 | INFO | Train Epoch: 10 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.234 Boundary Ratio: 0.246 Contrastive_loss: 0.15764 (0.19984) Boundary_loss: 0.015017 (0.014972) Loss: 0.17266 (0.21481) +2025-08-24,07:46:46 | INFO | Train Epoch: 10 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.19585 (0.19983) Boundary_loss: 0.014955 (0.014972) Loss: 0.21080 (0.21480) +2025-08-24,07:47:42 | INFO | Train Epoch: 10 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.18926 (0.19980) Boundary_loss: 0.014864 (0.014972) Loss: 0.20412 (0.21477) +2025-08-24,07:48:39 | INFO | Train Epoch: 10 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.15500 (0.19968) Boundary_loss: 0.014923 (0.014971) Loss: 0.16992 (0.21466) +2025-08-24,07:49:35 | INFO | Train Epoch: 10 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.21537 (0.19972) Boundary_loss: 0.014898 (0.014971) Loss: 0.23027 (0.21470) +2025-08-24,07:50:31 | INFO | Train Epoch: 10 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.12604 (0.19954) Boundary_loss: 0.014998 (0.014971) Loss: 0.14104 (0.21451) +2025-08-24,07:51:28 | INFO | Train Epoch: 10 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.22008 (0.19959) Boundary_loss: 0.015051 (0.014972) Loss: 0.23513 (0.21456) +2025-08-24,07:52:24 | INFO | Train Epoch: 10 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.17713 (0.19953) Boundary_loss: 0.014902 (0.014971) Loss: 0.19203 (0.21450) +2025-08-24,07:53:21 | INFO | Train Epoch: 10 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.21773 (0.19958) Boundary_loss: 0.014996 (0.014971) Loss: 0.23273 (0.21455) +2025-08-24,07:54:17 | INFO | Train Epoch: 10 [20378112/26365952 (77%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.20062 (0.19958) Boundary_loss: 0.015018 (0.014972) Loss: 0.21564 (0.21455) +2025-08-24,07:55:14 | INFO | Train Epoch: 10 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.22830 (0.19965) Boundary_loss: 0.014968 (0.014972) Loss: 0.24327 (0.21462) +2025-08-24,07:56:11 | INFO | Train Epoch: 10 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.24358 (0.19976) Boundary_loss: 0.014866 (0.014971) Loss: 0.25845 (0.21473) +2025-08-24,07:57:07 | INFO | Train Epoch: 10 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.303 Boundary Ratio: 0.252 Contrastive_loss: 0.28925 (0.19999) Boundary_loss: 0.014970 (0.014971) Loss: 0.30422 (0.21496) +2025-08-24,07:58:03 | INFO | Train Epoch: 10 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.18114 (0.19994) Boundary_loss: 0.015031 (0.014971) Loss: 0.19617 (0.21491) +2025-08-24,07:59:00 | INFO | Train Epoch: 10 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.131 Boundary Ratio: 0.246 Contrastive_loss: 0.15919 (0.19984) Boundary_loss: 0.015013 (0.014972) Loss: 0.17420 (0.21481) +2025-08-24,07:59:57 | INFO | Train Epoch: 10 [20685312/26365952 (78%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.18213 (0.19979) Boundary_loss: 0.014914 (0.014971) Loss: 0.19705 (0.21477) +2025-08-24,08:00:53 | INFO | Train Epoch: 10 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.19270 (0.19978) Boundary_loss: 0.014853 (0.014971) Loss: 0.20756 (0.21475) +2025-08-24,08:01:50 | INFO | Train Epoch: 10 [20787712/26365952 (79%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.25468 (0.19991) Boundary_loss: 0.015073 (0.014971) Loss: 0.26976 (0.21488) +2025-08-24,08:02:46 | INFO | Train Epoch: 10 [20838912/26365952 (79%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.19187 (0.19989) Boundary_loss: 0.014978 (0.014971) Loss: 0.20685 (0.21486) +2025-08-24,08:03:43 | INFO | Train Epoch: 10 [20890112/26365952 (79%)] Avg Boundaries (per batch): 49.061 Boundary Ratio: 0.250 Contrastive_loss: 0.15008 (0.19977) Boundary_loss: 0.014897 (0.014971) Loss: 0.16498 (0.21474) +2025-08-24,08:04:39 | INFO | Train Epoch: 10 [20941312/26365952 (79%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.17106 (0.19970) Boundary_loss: 0.014921 (0.014971) Loss: 0.18598 (0.21467) +2025-08-24,08:05:35 | INFO | Train Epoch: 10 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.19014 (0.19968) Boundary_loss: 0.014992 (0.014971) Loss: 0.20514 (0.21465) +2025-08-24,08:06:32 | INFO | Train Epoch: 10 [21043712/26365952 (80%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.17209 (0.19961) Boundary_loss: 0.014901 (0.014971) Loss: 0.18699 (0.21458) +2025-08-24,08:07:28 | INFO | Train Epoch: 10 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.332 Boundary Ratio: 0.247 Contrastive_loss: 0.17591 (0.19955) Boundary_loss: 0.014989 (0.014971) Loss: 0.19090 (0.21452) +2025-08-24,08:08:25 | INFO | Train Epoch: 10 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.21316 (0.19959) Boundary_loss: 0.014894 (0.014971) Loss: 0.22806 (0.21456) +2025-08-24,08:09:21 | INFO | Train Epoch: 10 [21197312/26365952 (80%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.17318 (0.19952) Boundary_loss: 0.014905 (0.014971) Loss: 0.18808 (0.21449) +2025-08-24,08:10:18 | INFO | Train Epoch: 10 [21248512/26365952 (81%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.20534 (0.19954) Boundary_loss: 0.014931 (0.014971) Loss: 0.22027 (0.21451) +2025-08-24,08:11:14 | INFO | Train Epoch: 10 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.21037 (0.19956) Boundary_loss: 0.015020 (0.014971) Loss: 0.22539 (0.21453) +2025-08-24,08:12:11 | INFO | Train Epoch: 10 [21350912/26365952 (81%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.16565 (0.19948) Boundary_loss: 0.014994 (0.014971) Loss: 0.18065 (0.21445) +2025-08-24,08:13:07 | INFO | Train Epoch: 10 [21402112/26365952 (81%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.14244 (0.19934) Boundary_loss: 0.014973 (0.014971) Loss: 0.15741 (0.21432) +2025-08-24,08:14:04 | INFO | Train Epoch: 10 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.24847 (0.19946) Boundary_loss: 0.015095 (0.014971) Loss: 0.26356 (0.21443) +2025-08-24,08:15:00 | INFO | Train Epoch: 10 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.20488 (0.19947) Boundary_loss: 0.014965 (0.014971) Loss: 0.21985 (0.21445) +2025-08-24,08:15:57 | INFO | Train Epoch: 10 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.21819 (0.19952) Boundary_loss: 0.015004 (0.014971) Loss: 0.23319 (0.21449) +2025-08-24,08:16:53 | INFO | Train Epoch: 10 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.330 Boundary Ratio: 0.247 Contrastive_loss: 0.19718 (0.19951) Boundary_loss: 0.014977 (0.014971) Loss: 0.21216 (0.21448) +2025-08-24,08:17:50 | INFO | Train Epoch: 10 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.20601 (0.19953) Boundary_loss: 0.014981 (0.014971) Loss: 0.22099 (0.21450) +2025-08-24,08:18:46 | INFO | Train Epoch: 10 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.14139 (0.19939) Boundary_loss: 0.015075 (0.014971) Loss: 0.15647 (0.21436) +2025-08-24,08:19:43 | INFO | Train Epoch: 10 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.23444 (0.19947) Boundary_loss: 0.014940 (0.014971) Loss: 0.24938 (0.21445) +2025-08-24,08:20:39 | INFO | Train Epoch: 10 [21811712/26365952 (83%)] Avg Boundaries (per batch): 47.982 Boundary Ratio: 0.245 Contrastive_loss: 0.22731 (0.19954) Boundary_loss: 0.014852 (0.014971) Loss: 0.24217 (0.21451) +2025-08-24,08:21:36 | INFO | Train Epoch: 10 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.17867 (0.19949) Boundary_loss: 0.014961 (0.014971) Loss: 0.19363 (0.21446) +2025-08-24,08:22:32 | INFO | Train Epoch: 10 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.17444 (0.19943) Boundary_loss: 0.014937 (0.014971) Loss: 0.18938 (0.21440) +2025-08-24,08:23:29 | INFO | Train Epoch: 10 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.15353 (0.19933) Boundary_loss: 0.014991 (0.014971) Loss: 0.16852 (0.21430) +2025-08-24,08:24:25 | INFO | Train Epoch: 10 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.19437 (0.19931) Boundary_loss: 0.015003 (0.014971) Loss: 0.20938 (0.21428) +2025-08-24,08:25:22 | INFO | Train Epoch: 10 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.19919 (0.19931) Boundary_loss: 0.015068 (0.014971) Loss: 0.21426 (0.21428) +2025-08-24,08:26:18 | INFO | Train Epoch: 10 [22118912/26365952 (84%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.21116 (0.19934) Boundary_loss: 0.014886 (0.014971) Loss: 0.22605 (0.21431) +2025-08-24,08:27:15 | INFO | Train Epoch: 10 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.20155 (0.19935) Boundary_loss: 0.014975 (0.014971) Loss: 0.21653 (0.21432) +2025-08-24,08:28:11 | INFO | Train Epoch: 10 [22221312/26365952 (84%)] Avg Boundaries (per batch): 49.387 Boundary Ratio: 0.252 Contrastive_loss: 0.12489 (0.19917) Boundary_loss: 0.014929 (0.014971) Loss: 0.13982 (0.21415) +2025-08-24,08:29:08 | INFO | Train Epoch: 10 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 0.20036 (0.19918) Boundary_loss: 0.014989 (0.014971) Loss: 0.21535 (0.21415) +2025-08-24,08:30:04 | INFO | Train Epoch: 10 [22323712/26365952 (85%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.19799 (0.19917) Boundary_loss: 0.014809 (0.014971) Loss: 0.21279 (0.21415) +2025-08-24,08:31:01 | INFO | Train Epoch: 10 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.20171 (0.19918) Boundary_loss: 0.014901 (0.014971) Loss: 0.21662 (0.21415) +2025-08-24,08:31:57 | INFO | Train Epoch: 10 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.19544 (0.19917) Boundary_loss: 0.014887 (0.014970) Loss: 0.21033 (0.21414) +2025-08-24,08:32:54 | INFO | Train Epoch: 10 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.23790 (0.19926) Boundary_loss: 0.014995 (0.014970) Loss: 0.25289 (0.21423) +2025-08-24,08:33:50 | INFO | Train Epoch: 10 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.19300 (0.19925) Boundary_loss: 0.014904 (0.014970) Loss: 0.20790 (0.21422) +2025-08-24,08:34:47 | INFO | Train Epoch: 10 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.17844 (0.19920) Boundary_loss: 0.015020 (0.014970) Loss: 0.19346 (0.21417) +2025-08-24,08:35:43 | INFO | Train Epoch: 10 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.361 Boundary Ratio: 0.247 Contrastive_loss: 0.20370 (0.19921) Boundary_loss: 0.014956 (0.014970) Loss: 0.21866 (0.21418) +2025-08-24,08:36:40 | INFO | Train Epoch: 10 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.21443 (0.19924) Boundary_loss: 0.015090 (0.014971) Loss: 0.22952 (0.21421) +2025-08-24,08:37:36 | INFO | Train Epoch: 10 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.22709 (0.19931) Boundary_loss: 0.015009 (0.014971) Loss: 0.24210 (0.21428) +2025-08-24,08:38:33 | INFO | Train Epoch: 10 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.17311 (0.19925) Boundary_loss: 0.014981 (0.014971) Loss: 0.18809 (0.21422) +2025-08-24,08:39:29 | INFO | Train Epoch: 10 [22835712/26365952 (87%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.18685 (0.19922) Boundary_loss: 0.014965 (0.014971) Loss: 0.20181 (0.21419) +2025-08-24,08:40:26 | INFO | Train Epoch: 10 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.20349 (0.19923) Boundary_loss: 0.014922 (0.014971) Loss: 0.21841 (0.21420) +2025-08-24,08:41:22 | INFO | Train Epoch: 10 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.15294 (0.19913) Boundary_loss: 0.014945 (0.014971) Loss: 0.16789 (0.21410) +2025-08-24,08:42:19 | INFO | Train Epoch: 10 [22989312/26365952 (87%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.20879 (0.19915) Boundary_loss: 0.014969 (0.014971) Loss: 0.22376 (0.21412) +2025-08-24,08:43:15 | INFO | Train Epoch: 10 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.23356 (0.19922) Boundary_loss: 0.015092 (0.014971) Loss: 0.24865 (0.21419) +2025-08-24,08:44:12 | INFO | Train Epoch: 10 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.18225 (0.19919) Boundary_loss: 0.015077 (0.014971) Loss: 0.19733 (0.21416) +2025-08-24,08:45:08 | INFO | Train Epoch: 10 [23142912/26365952 (88%)] Avg Boundaries (per batch): 49.355 Boundary Ratio: 0.252 Contrastive_loss: 0.23181 (0.19926) Boundary_loss: 0.015069 (0.014971) Loss: 0.24688 (0.21423) +2025-08-24,08:46:05 | INFO | Train Epoch: 10 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.23875 (0.19934) Boundary_loss: 0.014939 (0.014971) Loss: 0.25369 (0.21432) +2025-08-24,08:47:01 | INFO | Train Epoch: 10 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.25609 (0.19947) Boundary_loss: 0.014907 (0.014971) Loss: 0.27099 (0.21444) +2025-08-24,08:47:58 | INFO | Train Epoch: 10 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.21007 (0.19949) Boundary_loss: 0.014968 (0.014971) Loss: 0.22504 (0.21446) +2025-08-24,08:48:54 | INFO | Train Epoch: 10 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.400 Boundary Ratio: 0.247 Contrastive_loss: 0.17560 (0.19944) Boundary_loss: 0.015049 (0.014971) Loss: 0.19065 (0.21441) +2025-08-24,08:49:50 | INFO | Train Epoch: 10 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.23703 (0.19952) Boundary_loss: 0.014930 (0.014971) Loss: 0.25196 (0.21449) +2025-08-24,08:50:47 | INFO | Train Epoch: 10 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.21364 (0.19955) Boundary_loss: 0.014904 (0.014971) Loss: 0.22854 (0.21452) +2025-08-24,08:51:43 | INFO | Train Epoch: 10 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.26142 (0.19969) Boundary_loss: 0.014940 (0.014971) Loss: 0.27636 (0.21466) +2025-08-24,08:52:40 | INFO | Train Epoch: 10 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.17382 (0.19963) Boundary_loss: 0.015043 (0.014971) Loss: 0.18887 (0.21460) +2025-08-24,08:53:36 | INFO | Train Epoch: 10 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.17733 (0.19958) Boundary_loss: 0.014956 (0.014971) Loss: 0.19229 (0.21455) +2025-08-24,08:54:33 | INFO | Train Epoch: 10 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.15413 (0.19949) Boundary_loss: 0.014991 (0.014971) Loss: 0.16912 (0.21446) +2025-08-24,08:55:29 | INFO | Train Epoch: 10 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.19854 (0.19948) Boundary_loss: 0.014904 (0.014971) Loss: 0.21344 (0.21445) +2025-08-24,08:56:26 | INFO | Train Epoch: 10 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.20712 (0.19950) Boundary_loss: 0.014973 (0.014971) Loss: 0.22210 (0.21447) +2025-08-24,08:57:22 | INFO | Train Epoch: 10 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.123 Boundary Ratio: 0.246 Contrastive_loss: 0.21730 (0.19954) Boundary_loss: 0.014927 (0.014971) Loss: 0.23223 (0.21451) +2025-08-24,08:58:19 | INFO | Train Epoch: 10 [23859712/26365952 (90%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.18707 (0.19951) Boundary_loss: 0.015011 (0.014971) Loss: 0.20208 (0.21448) +2025-08-24,08:59:15 | INFO | Train Epoch: 10 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.19626 (0.19950) Boundary_loss: 0.014969 (0.014971) Loss: 0.21123 (0.21448) +2025-08-24,09:00:12 | INFO | Train Epoch: 10 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.22694 (0.19956) Boundary_loss: 0.014999 (0.014971) Loss: 0.24194 (0.21453) +2025-08-24,09:01:08 | INFO | Train Epoch: 10 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.21938 (0.19960) Boundary_loss: 0.015017 (0.014971) Loss: 0.23440 (0.21458) +2025-08-24,09:02:05 | INFO | Train Epoch: 10 [24064512/26365952 (91%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.18963 (0.19958) Boundary_loss: 0.014931 (0.014971) Loss: 0.20456 (0.21455) +2025-08-24,09:03:01 | INFO | Train Epoch: 10 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.19672 (0.19958) Boundary_loss: 0.015002 (0.014971) Loss: 0.21173 (0.21455) +2025-08-24,09:03:58 | INFO | Train Epoch: 10 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.19111 (0.19956) Boundary_loss: 0.014986 (0.014971) Loss: 0.20609 (0.21453) +2025-08-24,09:04:54 | INFO | Train Epoch: 10 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.17257 (0.19950) Boundary_loss: 0.015052 (0.014971) Loss: 0.18762 (0.21447) +2025-08-24,09:05:51 | INFO | Train Epoch: 10 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.19566 (0.19949) Boundary_loss: 0.015032 (0.014971) Loss: 0.21069 (0.21447) +2025-08-24,09:06:47 | INFO | Train Epoch: 10 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.26828 (0.19964) Boundary_loss: 0.015006 (0.014971) Loss: 0.28329 (0.21461) +2025-08-24,09:07:44 | INFO | Train Epoch: 10 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.17946 (0.19960) Boundary_loss: 0.014943 (0.014971) Loss: 0.19441 (0.21457) +2025-08-24,09:08:40 | INFO | Train Epoch: 10 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.15124 (0.19950) Boundary_loss: 0.014859 (0.014971) Loss: 0.16610 (0.21447) +2025-08-24,09:09:37 | INFO | Train Epoch: 10 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.24038 (0.19958) Boundary_loss: 0.014877 (0.014971) Loss: 0.25525 (0.21455) +2025-08-24,09:10:33 | INFO | Train Epoch: 10 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.16561 (0.19951) Boundary_loss: 0.014954 (0.014971) Loss: 0.18056 (0.21448) +2025-08-24,09:11:29 | INFO | Train Epoch: 10 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.25060 (0.19962) Boundary_loss: 0.014904 (0.014971) Loss: 0.26551 (0.21459) +2025-08-24,09:12:26 | INFO | Train Epoch: 10 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.15011 (0.19951) Boundary_loss: 0.014940 (0.014971) Loss: 0.16505 (0.21448) +2025-08-24,09:13:22 | INFO | Train Epoch: 10 [24678912/26365952 (94%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.18688 (0.19949) Boundary_loss: 0.014966 (0.014971) Loss: 0.20184 (0.21446) +2025-08-24,09:14:19 | INFO | Train Epoch: 10 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.15774 (0.19940) Boundary_loss: 0.014907 (0.014971) Loss: 0.17264 (0.21437) +2025-08-24,09:15:15 | INFO | Train Epoch: 10 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.17785 (0.19936) Boundary_loss: 0.014840 (0.014970) Loss: 0.19269 (0.21433) +2025-08-24,09:16:12 | INFO | Train Epoch: 10 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.19927 (0.19936) Boundary_loss: 0.015060 (0.014970) Loss: 0.21433 (0.21433) +2025-08-24,09:17:08 | INFO | Train Epoch: 10 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.19037 (0.19934) Boundary_loss: 0.014943 (0.014970) Loss: 0.20531 (0.21431) +2025-08-24,09:18:05 | INFO | Train Epoch: 10 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.24608 (0.19943) Boundary_loss: 0.015020 (0.014971) Loss: 0.26110 (0.21440) +2025-08-24,09:19:02 | INFO | Train Epoch: 10 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.22525 (0.19949) Boundary_loss: 0.014930 (0.014970) Loss: 0.24018 (0.21446) +2025-08-24,09:19:58 | INFO | Train Epoch: 10 [25037312/26365952 (95%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.13197 (0.19935) Boundary_loss: 0.014889 (0.014970) Loss: 0.14686 (0.21432) +2025-08-24,09:20:55 | INFO | Train Epoch: 10 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.16051 (0.19927) Boundary_loss: 0.014863 (0.014970) Loss: 0.17538 (0.21424) +2025-08-24,09:21:51 | INFO | Train Epoch: 10 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.17777 (0.19923) Boundary_loss: 0.014982 (0.014970) Loss: 0.19276 (0.21420) +2025-08-24,09:22:47 | INFO | Train Epoch: 10 [25190912/26365952 (96%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.19315 (0.19921) Boundary_loss: 0.015008 (0.014970) Loss: 0.20815 (0.21418) +2025-08-24,09:23:44 | INFO | Train Epoch: 10 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.12776 (0.19907) Boundary_loss: 0.014954 (0.014970) Loss: 0.14272 (0.21404) +2025-08-24,09:24:40 | INFO | Train Epoch: 10 [25293312/26365952 (96%)] Avg Boundaries (per batch): 49.328 Boundary Ratio: 0.252 Contrastive_loss: 0.21102 (0.19909) Boundary_loss: 0.015080 (0.014970) Loss: 0.22610 (0.21406) +2025-08-24,09:25:37 | INFO | Train Epoch: 10 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.15467 (0.19900) Boundary_loss: 0.015013 (0.014970) Loss: 0.16969 (0.21397) +2025-08-24,09:26:33 | INFO | Train Epoch: 10 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.25118 (0.19911) Boundary_loss: 0.014892 (0.014970) Loss: 0.26607 (0.21408) +2025-08-24,09:27:30 | INFO | Train Epoch: 10 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.15378 (0.19902) Boundary_loss: 0.015109 (0.014971) Loss: 0.16889 (0.21399) +2025-08-24,09:28:27 | INFO | Train Epoch: 10 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.115 Boundary Ratio: 0.245 Contrastive_loss: 0.20064 (0.19902) Boundary_loss: 0.014875 (0.014970) Loss: 0.21551 (0.21399) +2025-08-24,09:29:23 | INFO | Train Epoch: 10 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.16562 (0.19895) Boundary_loss: 0.015028 (0.014970) Loss: 0.18065 (0.21392) +2025-08-24,09:30:20 | INFO | Train Epoch: 10 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.20598 (0.19897) Boundary_loss: 0.014974 (0.014970) Loss: 0.22095 (0.21394) +2025-08-24,09:31:16 | INFO | Train Epoch: 10 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.16088 (0.19889) Boundary_loss: 0.014920 (0.014970) Loss: 0.17580 (0.21386) +2025-08-24,09:32:13 | INFO | Train Epoch: 10 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.20627 (0.19891) Boundary_loss: 0.015105 (0.014971) Loss: 0.22138 (0.21388) +2025-08-24,09:33:09 | INFO | Train Epoch: 10 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.20071 (0.19891) Boundary_loss: 0.014860 (0.014970) Loss: 0.21557 (0.21388) +2025-08-24,09:34:06 | INFO | Train Epoch: 10 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.18018 (0.19887) Boundary_loss: 0.014967 (0.014970) Loss: 0.19515 (0.21384) +2025-08-24,09:35:02 | INFO | Train Epoch: 10 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.219 Boundary Ratio: 0.246 Contrastive_loss: 0.18043 (0.19884) Boundary_loss: 0.014993 (0.014970) Loss: 0.19543 (0.21381) +2025-08-24,09:35:59 | INFO | Train Epoch: 10 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.14758 (0.19874) Boundary_loss: 0.015107 (0.014971) Loss: 0.16269 (0.21371) +2025-08-24,09:36:55 | INFO | Train Epoch: 10 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.18953 (0.19872) Boundary_loss: 0.015010 (0.014971) Loss: 0.20454 (0.21369) +2025-08-24,09:37:52 | INFO | Train Epoch: 10 [26010112/26365952 (99%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 0.12119 (0.19857) Boundary_loss: 0.015046 (0.014971) Loss: 0.13624 (0.21354) +2025-08-24,09:38:48 | INFO | Train Epoch: 10 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.21757 (0.19860) Boundary_loss: 0.014912 (0.014971) Loss: 0.23249 (0.21357) +2025-08-24,09:39:45 | INFO | Train Epoch: 10 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.15587 (0.19852) Boundary_loss: 0.014981 (0.014971) Loss: 0.17085 (0.21349) +2025-08-24,09:40:41 | INFO | Train Epoch: 10 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.14201 (0.19841) Boundary_loss: 0.015010 (0.014971) Loss: 0.15702 (0.21338) +2025-08-24,09:41:37 | INFO | Train Epoch: 10 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.22040 (0.19845) Boundary_loss: 0.014958 (0.014971) Loss: 0.23536 (0.21342) +2025-08-24,09:42:34 | INFO | Train Epoch: 10 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.20253 (0.19846) Boundary_loss: 0.014995 (0.014971) Loss: 0.21753 (0.21343) +2025-08-24,09:43:30 | INFO | Train Epoch: 10 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.16313 (0.19839) Boundary_loss: 0.014926 (0.014971) Loss: 0.17805 (0.21336) +2025-08-24,09:44:24 | INFO | Train Epoch: 10 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.23345 (0.19846) Boundary_loss: 0.014931 (0.014971) Loss: 0.24838 (0.21343) +2025-08-24,09:44:24 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-24,09:44:24 | INFO | [Epoch 10] Average Step Time: 0.568s | Average GPU Memory: 31.7 GB +2025-08-24,09:44:24 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-24,09:44:24 | INFO | Starting zero-shot imagenet. +2025-08-24,09:44:24 | INFO | Building zero-shot classifier +2025-08-24,09:44:33 | INFO | Using classifier +2025-08-24,09:45:17 | INFO | Finished zero-shot imagenet. +2025-08-24,09:45:17 | INFO | Eval Epoch: 11 imagenet-zeroshot-val-top1: 0.3003 imagenet-zeroshot-val-top5: 0.5655 +2025-08-24,09:45:18 | INFO | Start epoch 11 +2025-08-24,09:45:21 | INFO | Train Epoch: 11 [ 512/26365952 (0%)] Avg Boundaries (per batch): 49.330 Boundary Ratio: 0.252 Contrastive_loss: 0.15830 (0.15830) Boundary_loss: 0.015057 (0.015057) Loss: 0.17335 (0.17335) +2025-08-24,09:46:17 | INFO | Train Epoch: 11 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.20848 (0.18339) Boundary_loss: 0.014939 (0.014998) Loss: 0.22342 (0.19839) +2025-08-24,09:47:13 | INFO | Train Epoch: 11 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.15547 (0.17408) Boundary_loss: 0.014930 (0.014975) Loss: 0.17040 (0.18906) +2025-08-24,09:48:10 | INFO | Train Epoch: 11 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.17744 (0.17492) Boundary_loss: 0.014928 (0.014963) Loss: 0.19237 (0.18988) +2025-08-24,09:49:06 | INFO | Train Epoch: 11 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.15005 (0.16995) Boundary_loss: 0.014907 (0.014952) Loss: 0.16496 (0.18490) +2025-08-24,09:50:02 | INFO | Train Epoch: 11 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.17363 (0.17056) Boundary_loss: 0.014906 (0.014944) Loss: 0.18854 (0.18551) +2025-08-24,09:50:59 | INFO | Train Epoch: 11 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.14522 (0.16694) Boundary_loss: 0.014900 (0.014938) Loss: 0.16012 (0.18188) +2025-08-24,09:51:55 | INFO | Train Epoch: 11 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.14777 (0.16454) Boundary_loss: 0.015000 (0.014946) Loss: 0.16277 (0.17949) +2025-08-24,09:52:52 | INFO | Train Epoch: 11 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.20463 (0.16900) Boundary_loss: 0.014888 (0.014939) Loss: 0.21952 (0.18394) +2025-08-24,09:53:48 | INFO | Train Epoch: 11 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.359 Boundary Ratio: 0.247 Contrastive_loss: 0.17094 (0.16919) Boundary_loss: 0.015121 (0.014957) Loss: 0.18607 (0.18415) +2025-08-24,09:54:44 | INFO | Train Epoch: 11 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.17339 (0.16958) Boundary_loss: 0.014952 (0.014957) Loss: 0.18835 (0.18453) +2025-08-24,09:55:41 | INFO | Train Epoch: 11 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13870 (0.16700) Boundary_loss: 0.014945 (0.014956) Loss: 0.15365 (0.18196) +2025-08-24,09:56:37 | INFO | Train Epoch: 11 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.12465 (0.16374) Boundary_loss: 0.015136 (0.014970) Loss: 0.13979 (0.17871) +2025-08-24,09:57:33 | INFO | Train Epoch: 11 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.15318 (0.16299) Boundary_loss: 0.014938 (0.014968) Loss: 0.16812 (0.17796) +2025-08-24,09:58:30 | INFO | Train Epoch: 11 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.17917 (0.16407) Boundary_loss: 0.014995 (0.014969) Loss: 0.19416 (0.17904) +2025-08-24,09:59:26 | INFO | Train Epoch: 11 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 49.172 Boundary Ratio: 0.251 Contrastive_loss: 0.13032 (0.16196) Boundary_loss: 0.015044 (0.014974) Loss: 0.14536 (0.17693) +2025-08-24,10:00:22 | INFO | Train Epoch: 11 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.21563 (0.16512) Boundary_loss: 0.015157 (0.014985) Loss: 0.23079 (0.18010) +2025-08-24,10:01:19 | INFO | Train Epoch: 11 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.12092 (0.16266) Boundary_loss: 0.014934 (0.014982) Loss: 0.13585 (0.17764) +2025-08-24,10:02:15 | INFO | Train Epoch: 11 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.15605 (0.16231) Boundary_loss: 0.014932 (0.014979) Loss: 0.17098 (0.17729) +2025-08-24,10:03:11 | INFO | Train Epoch: 11 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 0.12611 (0.16050) Boundary_loss: 0.015162 (0.014989) Loss: 0.14127 (0.17549) +2025-08-24,10:04:08 | INFO | Train Epoch: 11 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.301 Boundary Ratio: 0.252 Contrastive_loss: 0.19738 (0.16226) Boundary_loss: 0.014881 (0.014983) Loss: 0.21226 (0.17724) +2025-08-24,10:05:04 | INFO | Train Epoch: 11 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.13899 (0.16120) Boundary_loss: 0.015004 (0.014984) Loss: 0.15399 (0.17619) +2025-08-24,10:06:00 | INFO | Train Epoch: 11 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.16442 (0.16134) Boundary_loss: 0.014951 (0.014983) Loss: 0.17938 (0.17632) +2025-08-24,10:06:57 | INFO | Train Epoch: 11 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.11562 (0.15944) Boundary_loss: 0.015028 (0.014985) Loss: 0.13065 (0.17442) +2025-08-24,10:07:53 | INFO | Train Epoch: 11 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.15974 (0.15945) Boundary_loss: 0.015025 (0.014986) Loss: 0.17477 (0.17443) +2025-08-24,10:08:49 | INFO | Train Epoch: 11 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.12877 (0.15827) Boundary_loss: 0.014965 (0.014986) Loss: 0.14373 (0.17325) +2025-08-24,10:09:45 | INFO | Train Epoch: 11 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.19897 (0.15978) Boundary_loss: 0.014928 (0.014983) Loss: 0.21390 (0.17476) +2025-08-24,10:10:42 | INFO | Train Epoch: 11 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.13270 (0.15881) Boundary_loss: 0.014925 (0.014981) Loss: 0.14762 (0.17379) +2025-08-24,10:11:38 | INFO | Train Epoch: 11 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.19810 (0.16016) Boundary_loss: 0.014865 (0.014977) Loss: 0.21296 (0.17514) +2025-08-24,10:12:34 | INFO | Train Epoch: 11 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12758 (0.15908) Boundary_loss: 0.014973 (0.014977) Loss: 0.14256 (0.17405) +2025-08-24,10:13:31 | INFO | Train Epoch: 11 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.16983 (0.15942) Boundary_loss: 0.015035 (0.014979) Loss: 0.18487 (0.17440) +2025-08-24,10:14:27 | INFO | Train Epoch: 11 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.23967 (0.16193) Boundary_loss: 0.014894 (0.014976) Loss: 0.25457 (0.17691) +2025-08-24,10:15:23 | INFO | Train Epoch: 11 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.19769 (0.16302) Boundary_loss: 0.014934 (0.014975) Loss: 0.21262 (0.17799) +2025-08-24,10:16:20 | INFO | Train Epoch: 11 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.12800 (0.16199) Boundary_loss: 0.015015 (0.014976) Loss: 0.14301 (0.17696) +2025-08-24,10:17:16 | INFO | Train Epoch: 11 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.12366 (0.16089) Boundary_loss: 0.014874 (0.014973) Loss: 0.13853 (0.17586) +2025-08-24,10:18:12 | INFO | Train Epoch: 11 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.17033 (0.16115) Boundary_loss: 0.014909 (0.014972) Loss: 0.18524 (0.17612) +2025-08-24,10:19:09 | INFO | Train Epoch: 11 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.18457 (0.16179) Boundary_loss: 0.014934 (0.014971) Loss: 0.19951 (0.17676) +2025-08-24,10:20:05 | INFO | Train Epoch: 11 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.17892 (0.16224) Boundary_loss: 0.014885 (0.014968) Loss: 0.19380 (0.17721) +2025-08-24,10:21:02 | INFO | Train Epoch: 11 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.16277 (0.16225) Boundary_loss: 0.015041 (0.014970) Loss: 0.17781 (0.17722) +2025-08-24,10:21:58 | INFO | Train Epoch: 11 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.19939 (0.16318) Boundary_loss: 0.014930 (0.014969) Loss: 0.21432 (0.17815) +2025-08-24,10:22:54 | INFO | Train Epoch: 11 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.16271 (0.16317) Boundary_loss: 0.015016 (0.014970) Loss: 0.17773 (0.17814) +2025-08-24,10:23:50 | INFO | Train Epoch: 11 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.13128 (0.16241) Boundary_loss: 0.015042 (0.014972) Loss: 0.14633 (0.17738) +2025-08-24,10:24:46 | INFO | Train Epoch: 11 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.19288 (0.16312) Boundary_loss: 0.014951 (0.014972) Loss: 0.20783 (0.17809) +2025-08-24,10:25:43 | INFO | Train Epoch: 11 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.18729 (0.16367) Boundary_loss: 0.015121 (0.014975) Loss: 0.20241 (0.17864) +2025-08-24,10:26:39 | INFO | Train Epoch: 11 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.13606 (0.16305) Boundary_loss: 0.014902 (0.014973) Loss: 0.15096 (0.17803) +2025-08-24,10:27:35 | INFO | Train Epoch: 11 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.17790 (0.16338) Boundary_loss: 0.014889 (0.014971) Loss: 0.19279 (0.17835) +2025-08-24,10:28:32 | INFO | Train Epoch: 11 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.14458 (0.16298) Boundary_loss: 0.015018 (0.014972) Loss: 0.15960 (0.17795) +2025-08-24,10:29:28 | INFO | Train Epoch: 11 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.18260 (0.16338) Boundary_loss: 0.014953 (0.014972) Loss: 0.19756 (0.17836) +2025-08-24,10:30:25 | INFO | Train Epoch: 11 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.14941 (0.16310) Boundary_loss: 0.015042 (0.014973) Loss: 0.16445 (0.17807) +2025-08-24,10:31:21 | INFO | Train Epoch: 11 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.15535 (0.16294) Boundary_loss: 0.015006 (0.014974) Loss: 0.17035 (0.17792) +2025-08-24,10:32:17 | INFO | Train Epoch: 11 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 0.16108 (0.16291) Boundary_loss: 0.014934 (0.014973) Loss: 0.17601 (0.17788) +2025-08-24,10:33:14 | INFO | Train Epoch: 11 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.18545 (0.16334) Boundary_loss: 0.014995 (0.014974) Loss: 0.20044 (0.17832) +2025-08-24,10:34:10 | INFO | Train Epoch: 11 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.16355 (0.16335) Boundary_loss: 0.014943 (0.014973) Loss: 0.17849 (0.17832) +2025-08-24,10:35:07 | INFO | Train Epoch: 11 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.14224 (0.16295) Boundary_loss: 0.014940 (0.014973) Loss: 0.15718 (0.17793) +2025-08-24,10:36:03 | INFO | Train Epoch: 11 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 49.352 Boundary Ratio: 0.252 Contrastive_loss: 0.16423 (0.16298) Boundary_loss: 0.014789 (0.014969) Loss: 0.17902 (0.17795) +2025-08-24,10:37:00 | INFO | Train Epoch: 11 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.11762 (0.16217) Boundary_loss: 0.014866 (0.014967) Loss: 0.13248 (0.17714) +2025-08-24,10:37:56 | INFO | Train Epoch: 11 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.21391 (0.16308) Boundary_loss: 0.014913 (0.014966) Loss: 0.22883 (0.17804) +2025-08-24,10:38:53 | INFO | Train Epoch: 11 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.14945 (0.16284) Boundary_loss: 0.014900 (0.014965) Loss: 0.16435 (0.17781) +2025-08-24,10:39:49 | INFO | Train Epoch: 11 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.15021 (0.16263) Boundary_loss: 0.015017 (0.014966) Loss: 0.16522 (0.17759) +2025-08-24,10:40:46 | INFO | Train Epoch: 11 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.19642 (0.16319) Boundary_loss: 0.015035 (0.014967) Loss: 0.21146 (0.17816) +2025-08-24,10:41:42 | INFO | Train Epoch: 11 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.17649 (0.16341) Boundary_loss: 0.014979 (0.014968) Loss: 0.19147 (0.17838) +2025-08-24,10:42:38 | INFO | Train Epoch: 11 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.14943 (0.16318) Boundary_loss: 0.014989 (0.014968) Loss: 0.16442 (0.17815) +2025-08-24,10:43:35 | INFO | Train Epoch: 11 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.14119 (0.16283) Boundary_loss: 0.014856 (0.014966) Loss: 0.15604 (0.17780) +2025-08-24,10:44:31 | INFO | Train Epoch: 11 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 0.14429 (0.16254) Boundary_loss: 0.014940 (0.014966) Loss: 0.15923 (0.17751) +2025-08-24,10:45:28 | INFO | Train Epoch: 11 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.15671 (0.16245) Boundary_loss: 0.014994 (0.014966) Loss: 0.17170 (0.17742) +2025-08-24,10:46:24 | INFO | Train Epoch: 11 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.21481 (0.16325) Boundary_loss: 0.014969 (0.014966) Loss: 0.22978 (0.17821) +2025-08-24,10:47:20 | INFO | Train Epoch: 11 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.13993 (0.16290) Boundary_loss: 0.014891 (0.014965) Loss: 0.15482 (0.17786) +2025-08-24,10:48:17 | INFO | Train Epoch: 11 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.17287 (0.16305) Boundary_loss: 0.014847 (0.014963) Loss: 0.18771 (0.17801) +2025-08-24,10:49:13 | INFO | Train Epoch: 11 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.12728 (0.16253) Boundary_loss: 0.014912 (0.014963) Loss: 0.14219 (0.17749) +2025-08-24,10:50:09 | INFO | Train Epoch: 11 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 49.219 Boundary Ratio: 0.251 Contrastive_loss: 0.19467 (0.16299) Boundary_loss: 0.014963 (0.014963) Loss: 0.20963 (0.17795) +2025-08-24,10:51:06 | INFO | Train Epoch: 11 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.14937 (0.16279) Boundary_loss: 0.014927 (0.014962) Loss: 0.16429 (0.17776) +2025-08-24,10:52:02 | INFO | Train Epoch: 11 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.279 Boundary Ratio: 0.246 Contrastive_loss: 0.13793 (0.16245) Boundary_loss: 0.015080 (0.014964) Loss: 0.15301 (0.17741) +2025-08-24,10:52:59 | INFO | Train Epoch: 11 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.12740 (0.16197) Boundary_loss: 0.014888 (0.014963) Loss: 0.14228 (0.17693) +2025-08-24,10:53:55 | INFO | Train Epoch: 11 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.17433 (0.16214) Boundary_loss: 0.014989 (0.014963) Loss: 0.18932 (0.17710) +2025-08-24,10:54:51 | INFO | Train Epoch: 11 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.13757 (0.16181) Boundary_loss: 0.014831 (0.014961) Loss: 0.15240 (0.17677) +2025-08-24,10:55:48 | INFO | Train Epoch: 11 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.19104 (0.16219) Boundary_loss: 0.014904 (0.014960) Loss: 0.20595 (0.17715) +2025-08-24,10:56:44 | INFO | Train Epoch: 11 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.16825 (0.16227) Boundary_loss: 0.015012 (0.014961) Loss: 0.18326 (0.17723) +2025-08-24,10:57:41 | INFO | Train Epoch: 11 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.20666 (0.16284) Boundary_loss: 0.014914 (0.014961) Loss: 0.22157 (0.17780) +2025-08-24,10:58:37 | INFO | Train Epoch: 11 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.14429 (0.16261) Boundary_loss: 0.015017 (0.014961) Loss: 0.15931 (0.17757) +2025-08-24,10:59:34 | INFO | Train Epoch: 11 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.18185 (0.16285) Boundary_loss: 0.015153 (0.014964) Loss: 0.19700 (0.17781) +2025-08-24,11:00:30 | INFO | Train Epoch: 11 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.16041 (0.16282) Boundary_loss: 0.014895 (0.014963) Loss: 0.17530 (0.17778) +2025-08-24,11:01:27 | INFO | Train Epoch: 11 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.25248 (0.16391) Boundary_loss: 0.014961 (0.014963) Loss: 0.26744 (0.17887) +2025-08-24,11:02:23 | INFO | Train Epoch: 11 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.19736 (0.16431) Boundary_loss: 0.014895 (0.014962) Loss: 0.21225 (0.17927) +2025-08-24,11:03:19 | INFO | Train Epoch: 11 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.15484 (0.16420) Boundary_loss: 0.015142 (0.014964) Loss: 0.16998 (0.17916) +2025-08-24,11:04:16 | INFO | Train Epoch: 11 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.23502 (0.16503) Boundary_loss: 0.014951 (0.014964) Loss: 0.24997 (0.18000) +2025-08-24,11:05:12 | INFO | Train Epoch: 11 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.471 Boundary Ratio: 0.247 Contrastive_loss: 0.18381 (0.16525) Boundary_loss: 0.015025 (0.014965) Loss: 0.19883 (0.18022) +2025-08-24,11:06:09 | INFO | Train Epoch: 11 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 49.445 Boundary Ratio: 0.252 Contrastive_loss: 0.14620 (0.16503) Boundary_loss: 0.014917 (0.014964) Loss: 0.16111 (0.18000) +2025-08-24,11:07:05 | INFO | Train Epoch: 11 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.20406 (0.16548) Boundary_loss: 0.015020 (0.014965) Loss: 0.21908 (0.18044) +2025-08-24,11:08:02 | INFO | Train Epoch: 11 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.12786 (0.16505) Boundary_loss: 0.014942 (0.014964) Loss: 0.14280 (0.18002) +2025-08-24,11:08:58 | INFO | Train Epoch: 11 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.13202 (0.16469) Boundary_loss: 0.014880 (0.014964) Loss: 0.14690 (0.17965) +2025-08-24,11:09:54 | INFO | Train Epoch: 11 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.11041 (0.16409) Boundary_loss: 0.015004 (0.014964) Loss: 0.12541 (0.17905) +2025-08-24,11:10:50 | INFO | Train Epoch: 11 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.15189 (0.16396) Boundary_loss: 0.014987 (0.014964) Loss: 0.16688 (0.17892) +2025-08-24,11:11:47 | INFO | Train Epoch: 11 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.15154 (0.16382) Boundary_loss: 0.014846 (0.014963) Loss: 0.16639 (0.17879) +2025-08-24,11:12:43 | INFO | Train Epoch: 11 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.18112 (0.16401) Boundary_loss: 0.014892 (0.014962) Loss: 0.19602 (0.17897) +2025-08-24,11:13:39 | INFO | Train Epoch: 11 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.19394 (0.16432) Boundary_loss: 0.014859 (0.014961) Loss: 0.20880 (0.17928) +2025-08-24,11:14:36 | INFO | Train Epoch: 11 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.14623 (0.16413) Boundary_loss: 0.015085 (0.014962) Loss: 0.16131 (0.17910) +2025-08-24,11:15:32 | INFO | Train Epoch: 11 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.17501 (0.16425) Boundary_loss: 0.014887 (0.014962) Loss: 0.18990 (0.17921) +2025-08-24,11:16:28 | INFO | Train Epoch: 11 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.19419 (0.16455) Boundary_loss: 0.015021 (0.014962) Loss: 0.20921 (0.17951) +2025-08-24,11:17:25 | INFO | Train Epoch: 11 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.24559 (0.16537) Boundary_loss: 0.014933 (0.014962) Loss: 0.26052 (0.18033) +2025-08-24,11:18:21 | INFO | Train Epoch: 11 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.15653 (0.16528) Boundary_loss: 0.015134 (0.014964) Loss: 0.17166 (0.18025) +2025-08-24,11:19:18 | INFO | Train Epoch: 11 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.17152 (0.16534) Boundary_loss: 0.014955 (0.014964) Loss: 0.18647 (0.18031) +2025-08-24,11:20:14 | INFO | Train Epoch: 11 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.17343 (0.16542) Boundary_loss: 0.014957 (0.014964) Loss: 0.18839 (0.18039) +2025-08-24,11:21:11 | INFO | Train Epoch: 11 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.16796 (0.16545) Boundary_loss: 0.014963 (0.014964) Loss: 0.18292 (0.18041) +2025-08-24,11:22:07 | INFO | Train Epoch: 11 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.17445 (0.16553) Boundary_loss: 0.014940 (0.014963) Loss: 0.18939 (0.18050) +2025-08-24,11:23:04 | INFO | Train Epoch: 11 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.20289 (0.16589) Boundary_loss: 0.014892 (0.014963) Loss: 0.21778 (0.18085) +2025-08-24,11:24:00 | INFO | Train Epoch: 11 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.14896 (0.16573) Boundary_loss: 0.014864 (0.014962) Loss: 0.16382 (0.18069) +2025-08-24,11:24:57 | INFO | Train Epoch: 11 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.398 Boundary Ratio: 0.247 Contrastive_loss: 0.18078 (0.16587) Boundary_loss: 0.014925 (0.014961) Loss: 0.19570 (0.18083) +2025-08-24,11:25:53 | INFO | Train Epoch: 11 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 0.16902 (0.16590) Boundary_loss: 0.014848 (0.014960) Loss: 0.18387 (0.18086) +2025-08-24,11:26:49 | INFO | Train Epoch: 11 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 49.213 Boundary Ratio: 0.251 Contrastive_loss: 0.14908 (0.16575) Boundary_loss: 0.014939 (0.014960) Loss: 0.16402 (0.18071) +2025-08-24,11:27:46 | INFO | Train Epoch: 11 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.14679 (0.16557) Boundary_loss: 0.014934 (0.014960) Loss: 0.16172 (0.18053) +2025-08-24,11:28:42 | INFO | Train Epoch: 11 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.16523 (0.16557) Boundary_loss: 0.014778 (0.014958) Loss: 0.18001 (0.18053) +2025-08-24,11:29:39 | INFO | Train Epoch: 11 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.15459 (0.16547) Boundary_loss: 0.014999 (0.014959) Loss: 0.16959 (0.18043) +2025-08-24,11:30:35 | INFO | Train Epoch: 11 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.20460 (0.16582) Boundary_loss: 0.014950 (0.014958) Loss: 0.21955 (0.18078) +2025-08-24,11:31:32 | INFO | Train Epoch: 11 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.268 Boundary Ratio: 0.246 Contrastive_loss: 0.15865 (0.16576) Boundary_loss: 0.014938 (0.014958) Loss: 0.17359 (0.18071) +2025-08-24,11:32:28 | INFO | Train Epoch: 11 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.18197 (0.16590) Boundary_loss: 0.014910 (0.014958) Loss: 0.19688 (0.18085) +2025-08-24,11:33:24 | INFO | Train Epoch: 11 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 49.102 Boundary Ratio: 0.251 Contrastive_loss: 0.14193 (0.16569) Boundary_loss: 0.014990 (0.014958) Loss: 0.15692 (0.18065) +2025-08-24,11:34:21 | INFO | Train Epoch: 11 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.14795 (0.16554) Boundary_loss: 0.014890 (0.014958) Loss: 0.16284 (0.18050) +2025-08-24,11:35:18 | INFO | Train Epoch: 11 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.14917 (0.16540) Boundary_loss: 0.014966 (0.014958) Loss: 0.16413 (0.18036) +2025-08-24,11:36:14 | INFO | Train Epoch: 11 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.15614 (0.16532) Boundary_loss: 0.015004 (0.014958) Loss: 0.17115 (0.18028) +2025-08-24,11:37:10 | INFO | Train Epoch: 11 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.16961 (0.16536) Boundary_loss: 0.014916 (0.014958) Loss: 0.18453 (0.18032) +2025-08-24,11:38:07 | INFO | Train Epoch: 11 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.15527 (0.16527) Boundary_loss: 0.014989 (0.014958) Loss: 0.17025 (0.18023) +2025-08-24,11:39:03 | INFO | Train Epoch: 11 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.18767 (0.16546) Boundary_loss: 0.014930 (0.014958) Loss: 0.20260 (0.18042) +2025-08-24,11:40:00 | INFO | Train Epoch: 11 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.19030 (0.16566) Boundary_loss: 0.014842 (0.014957) Loss: 0.20514 (0.18062) +2025-08-24,11:40:56 | INFO | Train Epoch: 11 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.13914 (0.16545) Boundary_loss: 0.014847 (0.014956) Loss: 0.15399 (0.18040) +2025-08-24,11:41:53 | INFO | Train Epoch: 11 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.15580 (0.16537) Boundary_loss: 0.014969 (0.014956) Loss: 0.17077 (0.18032) +2025-08-24,11:42:49 | INFO | Train Epoch: 11 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.16287 (0.16535) Boundary_loss: 0.015023 (0.014957) Loss: 0.17789 (0.18031) +2025-08-24,11:43:46 | INFO | Train Epoch: 11 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.13778 (0.16513) Boundary_loss: 0.014986 (0.014957) Loss: 0.15276 (0.18009) +2025-08-24,11:44:42 | INFO | Train Epoch: 11 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.15308 (0.16504) Boundary_loss: 0.014907 (0.014956) Loss: 0.16799 (0.17999) +2025-08-24,11:45:39 | INFO | Train Epoch: 11 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.213 Boundary Ratio: 0.246 Contrastive_loss: 0.19059 (0.16524) Boundary_loss: 0.014958 (0.014956) Loss: 0.20555 (0.18019) +2025-08-24,11:46:35 | INFO | Train Epoch: 11 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.19322 (0.16545) Boundary_loss: 0.014862 (0.014956) Loss: 0.20808 (0.18041) +2025-08-24,11:47:31 | INFO | Train Epoch: 11 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.19319 (0.16566) Boundary_loss: 0.015000 (0.014956) Loss: 0.20819 (0.18062) +2025-08-24,11:48:28 | INFO | Train Epoch: 11 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.13555 (0.16543) Boundary_loss: 0.014995 (0.014956) Loss: 0.15055 (0.18039) +2025-08-24,11:49:24 | INFO | Train Epoch: 11 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.16104 (0.16540) Boundary_loss: 0.014935 (0.014956) Loss: 0.17598 (0.18036) +2025-08-24,11:50:21 | INFO | Train Epoch: 11 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.16445 (0.16539) Boundary_loss: 0.015005 (0.014957) Loss: 0.17945 (0.18035) +2025-08-24,11:51:18 | INFO | Train Epoch: 11 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.16552 (0.16540) Boundary_loss: 0.014906 (0.014956) Loss: 0.18042 (0.18035) +2025-08-24,11:52:14 | INFO | Train Epoch: 11 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.15204 (0.16530) Boundary_loss: 0.014954 (0.014956) Loss: 0.16699 (0.18025) +2025-08-24,11:53:11 | INFO | Train Epoch: 11 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.13434 (0.16507) Boundary_loss: 0.014952 (0.014956) Loss: 0.14929 (0.18003) +2025-08-24,11:54:07 | INFO | Train Epoch: 11 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.14560 (0.16493) Boundary_loss: 0.015014 (0.014957) Loss: 0.16062 (0.17989) +2025-08-24,11:55:04 | INFO | Train Epoch: 11 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.15331 (0.16485) Boundary_loss: 0.014879 (0.014956) Loss: 0.16819 (0.17980) +2025-08-24,11:56:00 | INFO | Train Epoch: 11 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.14707 (0.16472) Boundary_loss: 0.015084 (0.014957) Loss: 0.16215 (0.17968) +2025-08-24,11:56:57 | INFO | Train Epoch: 11 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.15926 (0.16468) Boundary_loss: 0.014826 (0.014956) Loss: 0.17409 (0.17964) +2025-08-24,11:57:53 | INFO | Train Epoch: 11 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 49.139 Boundary Ratio: 0.251 Contrastive_loss: 0.11666 (0.16434) Boundary_loss: 0.015010 (0.014956) Loss: 0.13167 (0.17930) +2025-08-24,11:58:49 | INFO | Train Epoch: 11 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.14979 (0.16424) Boundary_loss: 0.015001 (0.014957) Loss: 0.16479 (0.17920) +2025-08-24,11:59:46 | INFO | Train Epoch: 11 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.13414 (0.16403) Boundary_loss: 0.015068 (0.014957) Loss: 0.14921 (0.17899) +2025-08-24,12:00:42 | INFO | Train Epoch: 11 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.18718 (0.16419) Boundary_loss: 0.014841 (0.014957) Loss: 0.20202 (0.17915) +2025-08-24,12:01:39 | INFO | Train Epoch: 11 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.14147 (0.16404) Boundary_loss: 0.014936 (0.014956) Loss: 0.15640 (0.17899) +2025-08-24,12:02:35 | INFO | Train Epoch: 11 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.21506 (0.16438) Boundary_loss: 0.014885 (0.014956) Loss: 0.22995 (0.17934) +2025-08-24,12:03:32 | INFO | Train Epoch: 11 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.20041 (0.16463) Boundary_loss: 0.014884 (0.014955) Loss: 0.21530 (0.17958) +2025-08-24,12:04:28 | INFO | Train Epoch: 11 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.17076 (0.16467) Boundary_loss: 0.015036 (0.014956) Loss: 0.18579 (0.17962) +2025-08-24,12:05:25 | INFO | Train Epoch: 11 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.16006 (0.16464) Boundary_loss: 0.014973 (0.014956) Loss: 0.17503 (0.17959) +2025-08-24,12:06:21 | INFO | Train Epoch: 11 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.15803 (0.16459) Boundary_loss: 0.014911 (0.014956) Loss: 0.17294 (0.17955) +2025-08-24,12:07:18 | INFO | Train Epoch: 11 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.16502 (0.16460) Boundary_loss: 0.015036 (0.014956) Loss: 0.18005 (0.17955) +2025-08-24,12:08:15 | INFO | Train Epoch: 11 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.16732 (0.16461) Boundary_loss: 0.015091 (0.014957) Loss: 0.18242 (0.17957) +2025-08-24,12:09:11 | INFO | Train Epoch: 11 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.18478 (0.16474) Boundary_loss: 0.014966 (0.014957) Loss: 0.19974 (0.17970) +2025-08-24,12:10:08 | INFO | Train Epoch: 11 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.16694 (0.16476) Boundary_loss: 0.015033 (0.014958) Loss: 0.18197 (0.17972) +2025-08-24,12:11:04 | INFO | Train Epoch: 11 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.17898 (0.16485) Boundary_loss: 0.014920 (0.014958) Loss: 0.19390 (0.17981) +2025-08-24,12:12:01 | INFO | Train Epoch: 11 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.11751 (0.16455) Boundary_loss: 0.014887 (0.014957) Loss: 0.13240 (0.17951) +2025-08-24,12:12:57 | INFO | Train Epoch: 11 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.14998 (0.16446) Boundary_loss: 0.014924 (0.014957) Loss: 0.16491 (0.17941) +2025-08-24,12:13:54 | INFO | Train Epoch: 11 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.11704 (0.16416) Boundary_loss: 0.015026 (0.014957) Loss: 0.13207 (0.17912) +2025-08-24,12:14:50 | INFO | Train Epoch: 11 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.16533 (0.16417) Boundary_loss: 0.014872 (0.014957) Loss: 0.18020 (0.17912) +2025-08-24,12:15:47 | INFO | Train Epoch: 11 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 49.205 Boundary Ratio: 0.251 Contrastive_loss: 0.20030 (0.16439) Boundary_loss: 0.015042 (0.014957) Loss: 0.21534 (0.17935) +2025-08-24,12:16:43 | INFO | Train Epoch: 11 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 49.154 Boundary Ratio: 0.251 Contrastive_loss: 0.13418 (0.16420) Boundary_loss: 0.014895 (0.014957) Loss: 0.14908 (0.17916) +2025-08-24,12:17:40 | INFO | Train Epoch: 11 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.18726 (0.16434) Boundary_loss: 0.014879 (0.014956) Loss: 0.20214 (0.17930) +2025-08-24,12:18:36 | INFO | Train Epoch: 11 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.479 Boundary Ratio: 0.247 Contrastive_loss: 0.12896 (0.16413) Boundary_loss: 0.014925 (0.014956) Loss: 0.14389 (0.17909) +2025-08-24,12:19:33 | INFO | Train Epoch: 11 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.14667 (0.16402) Boundary_loss: 0.014947 (0.014956) Loss: 0.16162 (0.17898) +2025-08-24,12:20:29 | INFO | Train Epoch: 11 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.15575 (0.16397) Boundary_loss: 0.014962 (0.014956) Loss: 0.17071 (0.17893) +2025-08-24,12:21:26 | INFO | Train Epoch: 11 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.12534 (0.16374) Boundary_loss: 0.014980 (0.014956) Loss: 0.14032 (0.17870) +2025-08-24,12:22:22 | INFO | Train Epoch: 11 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.16127 (0.16373) Boundary_loss: 0.014960 (0.014956) Loss: 0.17623 (0.17868) +2025-08-24,12:23:19 | INFO | Train Epoch: 11 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.13069 (0.16353) Boundary_loss: 0.014902 (0.014956) Loss: 0.14560 (0.17849) +2025-08-24,12:24:15 | INFO | Train Epoch: 11 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.18319 (0.16365) Boundary_loss: 0.014912 (0.014956) Loss: 0.19811 (0.17860) +2025-08-24,12:25:11 | INFO | Train Epoch: 11 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.15345 (0.16359) Boundary_loss: 0.014933 (0.014956) Loss: 0.16839 (0.17854) +2025-08-24,12:26:08 | INFO | Train Epoch: 11 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.475 Boundary Ratio: 0.247 Contrastive_loss: 0.16635 (0.16360) Boundary_loss: 0.014764 (0.014955) Loss: 0.18111 (0.17856) +2025-08-24,12:27:04 | INFO | Train Epoch: 11 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.14305 (0.16349) Boundary_loss: 0.014879 (0.014954) Loss: 0.15793 (0.17844) +2025-08-24,12:28:01 | INFO | Train Epoch: 11 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 49.330 Boundary Ratio: 0.252 Contrastive_loss: 0.11851 (0.16323) Boundary_loss: 0.015105 (0.014955) Loss: 0.13362 (0.17818) +2025-08-24,12:28:57 | INFO | Train Epoch: 11 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.15388 (0.16317) Boundary_loss: 0.014949 (0.014955) Loss: 0.16882 (0.17813) +2025-08-24,12:29:54 | INFO | Train Epoch: 11 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.16831 (0.16320) Boundary_loss: 0.014935 (0.014955) Loss: 0.18325 (0.17816) +2025-08-24,12:30:50 | INFO | Train Epoch: 11 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.19229 (0.16337) Boundary_loss: 0.014883 (0.014954) Loss: 0.20717 (0.17832) +2025-08-24,12:31:47 | INFO | Train Epoch: 11 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.12891 (0.16317) Boundary_loss: 0.014986 (0.014955) Loss: 0.14390 (0.17813) +2025-08-24,12:32:43 | INFO | Train Epoch: 11 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.16602 (0.16319) Boundary_loss: 0.014978 (0.014955) Loss: 0.18100 (0.17814) +2025-08-24,12:33:40 | INFO | Train Epoch: 11 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.15666 (0.16315) Boundary_loss: 0.014947 (0.014955) Loss: 0.17161 (0.17811) +2025-08-24,12:34:36 | INFO | Train Epoch: 11 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.13556 (0.16300) Boundary_loss: 0.015014 (0.014955) Loss: 0.15057 (0.17796) +2025-08-24,12:35:33 | INFO | Train Epoch: 11 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.12652 (0.16280) Boundary_loss: 0.014871 (0.014955) Loss: 0.14139 (0.17775) +2025-08-24,12:36:29 | INFO | Train Epoch: 11 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.13984 (0.16267) Boundary_loss: 0.014881 (0.014954) Loss: 0.15472 (0.17763) +2025-08-24,12:37:26 | INFO | Train Epoch: 11 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.14208 (0.16256) Boundary_loss: 0.014932 (0.014954) Loss: 0.15701 (0.17752) +2025-08-24,12:38:22 | INFO | Train Epoch: 11 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.20343 (0.16278) Boundary_loss: 0.014931 (0.014954) Loss: 0.21836 (0.17774) +2025-08-24,12:39:18 | INFO | Train Epoch: 11 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.12182 (0.16256) Boundary_loss: 0.014929 (0.014954) Loss: 0.13675 (0.17752) +2025-08-24,12:40:15 | INFO | Train Epoch: 11 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.17324 (0.16262) Boundary_loss: 0.015033 (0.014954) Loss: 0.18827 (0.17757) +2025-08-24,12:41:12 | INFO | Train Epoch: 11 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.12013 (0.16239) Boundary_loss: 0.014985 (0.014954) Loss: 0.13512 (0.17735) +2025-08-24,12:42:08 | INFO | Train Epoch: 11 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.16629 (0.16242) Boundary_loss: 0.014808 (0.014954) Loss: 0.18110 (0.17737) +2025-08-24,12:43:04 | INFO | Train Epoch: 11 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 0.13831 (0.16229) Boundary_loss: 0.015094 (0.014954) Loss: 0.15341 (0.17724) +2025-08-24,12:44:01 | INFO | Train Epoch: 11 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.750 Boundary Ratio: 0.249 Contrastive_loss: 0.14164 (0.16218) Boundary_loss: 0.014843 (0.014954) Loss: 0.15649 (0.17713) +2025-08-24,12:44:57 | INFO | Train Epoch: 11 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.18412 (0.16229) Boundary_loss: 0.014915 (0.014954) Loss: 0.19903 (0.17725) +2025-08-24,12:45:54 | INFO | Train Epoch: 11 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 49.471 Boundary Ratio: 0.252 Contrastive_loss: 0.13944 (0.16218) Boundary_loss: 0.015040 (0.014954) Loss: 0.15448 (0.17713) +2025-08-24,12:46:50 | INFO | Train Epoch: 11 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 0.15682 (0.16215) Boundary_loss: 0.014925 (0.014954) Loss: 0.17174 (0.17710) +2025-08-24,12:47:47 | INFO | Train Epoch: 11 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.14847 (0.16208) Boundary_loss: 0.014887 (0.014954) Loss: 0.16335 (0.17703) +2025-08-24,12:48:43 | INFO | Train Epoch: 11 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.13738 (0.16195) Boundary_loss: 0.014910 (0.014953) Loss: 0.15229 (0.17691) +2025-08-24,12:49:40 | INFO | Train Epoch: 11 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.512 Boundary Ratio: 0.248 Contrastive_loss: 0.14784 (0.16188) Boundary_loss: 0.014964 (0.014953) Loss: 0.16280 (0.17683) +2025-08-24,12:50:36 | INFO | Train Epoch: 11 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.16814 (0.16191) Boundary_loss: 0.014905 (0.014953) Loss: 0.18305 (0.17687) +2025-08-24,12:51:33 | INFO | Train Epoch: 11 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.17916 (0.16200) Boundary_loss: 0.014880 (0.014953) Loss: 0.19404 (0.17695) +2025-08-24,12:52:29 | INFO | Train Epoch: 11 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.11518 (0.16176) Boundary_loss: 0.014979 (0.014953) Loss: 0.13016 (0.17672) +2025-08-24,12:53:26 | INFO | Train Epoch: 11 [10240512/26365952 (39%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.21390 (0.16202) Boundary_loss: 0.014875 (0.014953) Loss: 0.22877 (0.17698) +2025-08-24,12:54:23 | INFO | Train Epoch: 11 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.095832 (0.16170) Boundary_loss: 0.014995 (0.014953) Loss: 0.11083 (0.17665) +2025-08-24,12:55:19 | INFO | Train Epoch: 11 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.17895 (0.16178) Boundary_loss: 0.015014 (0.014953) Loss: 0.19397 (0.17673) +2025-08-24,12:56:16 | INFO | Train Epoch: 11 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.14943 (0.16172) Boundary_loss: 0.014899 (0.014953) Loss: 0.16433 (0.17667) +2025-08-24,12:57:12 | INFO | Train Epoch: 11 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.17620 (0.16179) Boundary_loss: 0.014977 (0.014953) Loss: 0.19118 (0.17674) +2025-08-24,12:58:09 | INFO | Train Epoch: 11 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.14740 (0.16172) Boundary_loss: 0.015035 (0.014953) Loss: 0.16244 (0.17667) +2025-08-24,12:59:05 | INFO | Train Epoch: 11 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.15828 (0.16170) Boundary_loss: 0.014909 (0.014953) Loss: 0.17319 (0.17666) +2025-08-24,13:00:02 | INFO | Train Epoch: 11 [10598912/26365952 (40%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.17038 (0.16175) Boundary_loss: 0.014941 (0.014953) Loss: 0.18532 (0.17670) +2025-08-24,13:00:58 | INFO | Train Epoch: 11 [10650112/26365952 (40%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.17163 (0.16179) Boundary_loss: 0.015013 (0.014953) Loss: 0.18664 (0.17675) +2025-08-24,13:01:55 | INFO | Train Epoch: 11 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.14592 (0.16172) Boundary_loss: 0.014884 (0.014953) Loss: 0.16080 (0.17667) +2025-08-24,13:02:51 | INFO | Train Epoch: 11 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.17207 (0.16177) Boundary_loss: 0.015031 (0.014953) Loss: 0.18710 (0.17672) +2025-08-24,13:03:48 | INFO | Train Epoch: 11 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.17016 (0.16181) Boundary_loss: 0.014901 (0.014953) Loss: 0.18506 (0.17676) +2025-08-24,13:04:44 | INFO | Train Epoch: 11 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.14145 (0.16171) Boundary_loss: 0.014852 (0.014953) Loss: 0.15630 (0.17666) +2025-08-24,13:05:41 | INFO | Train Epoch: 11 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.13706 (0.16160) Boundary_loss: 0.014954 (0.014953) Loss: 0.15201 (0.17655) +2025-08-24,13:06:37 | INFO | Train Epoch: 11 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.17052 (0.16164) Boundary_loss: 0.015005 (0.014953) Loss: 0.18553 (0.17659) +2025-08-24,13:07:34 | INFO | Train Epoch: 11 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.412 Boundary Ratio: 0.247 Contrastive_loss: 0.16184 (0.16164) Boundary_loss: 0.014921 (0.014953) Loss: 0.17676 (0.17659) +2025-08-24,13:08:30 | INFO | Train Epoch: 11 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.13945 (0.16154) Boundary_loss: 0.014935 (0.014953) Loss: 0.15439 (0.17649) +2025-08-24,13:09:27 | INFO | Train Epoch: 11 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.15096 (0.16149) Boundary_loss: 0.015023 (0.014953) Loss: 0.16599 (0.17644) +2025-08-24,13:10:23 | INFO | Train Epoch: 11 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.14586 (0.16142) Boundary_loss: 0.014868 (0.014953) Loss: 0.16073 (0.17637) +2025-08-24,13:11:20 | INFO | Train Epoch: 11 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.18176 (0.16151) Boundary_loss: 0.014853 (0.014952) Loss: 0.19661 (0.17646) +2025-08-24,13:12:16 | INFO | Train Epoch: 11 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.15497 (0.16148) Boundary_loss: 0.014908 (0.014952) Loss: 0.16988 (0.17643) +2025-08-24,13:13:13 | INFO | Train Epoch: 11 [11315712/26365952 (43%)] Avg Boundaries (per batch): 49.209 Boundary Ratio: 0.251 Contrastive_loss: 0.17031 (0.16152) Boundary_loss: 0.014935 (0.014952) Loss: 0.18524 (0.17647) +2025-08-24,13:14:09 | INFO | Train Epoch: 11 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.17853 (0.16160) Boundary_loss: 0.014946 (0.014952) Loss: 0.19348 (0.17655) +2025-08-24,13:15:06 | INFO | Train Epoch: 11 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.16117 (0.16159) Boundary_loss: 0.014851 (0.014951) Loss: 0.17603 (0.17655) +2025-08-24,13:16:02 | INFO | Train Epoch: 11 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.15797 (0.16158) Boundary_loss: 0.014903 (0.014951) Loss: 0.17287 (0.17653) +2025-08-24,13:16:58 | INFO | Train Epoch: 11 [11520512/26365952 (44%)] Avg Boundaries (per batch): 49.113 Boundary Ratio: 0.251 Contrastive_loss: 0.18842 (0.16170) Boundary_loss: 0.014859 (0.014951) Loss: 0.20328 (0.17665) +2025-08-24,13:17:55 | INFO | Train Epoch: 11 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.16242 (0.16170) Boundary_loss: 0.014942 (0.014951) Loss: 0.17736 (0.17665) +2025-08-24,13:18:51 | INFO | Train Epoch: 11 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.14384 (0.16162) Boundary_loss: 0.014944 (0.014951) Loss: 0.15878 (0.17657) +2025-08-24,13:19:48 | INFO | Train Epoch: 11 [11674112/26365952 (44%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.13726 (0.16151) Boundary_loss: 0.014885 (0.014950) Loss: 0.15214 (0.17647) +2025-08-24,13:20:44 | INFO | Train Epoch: 11 [11725312/26365952 (44%)] Avg Boundaries (per batch): 49.256 Boundary Ratio: 0.251 Contrastive_loss: 0.17577 (0.16158) Boundary_loss: 0.014950 (0.014950) Loss: 0.19072 (0.17653) +2025-08-24,13:21:41 | INFO | Train Epoch: 11 [11776512/26365952 (45%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 0.12538 (0.16142) Boundary_loss: 0.014889 (0.014950) Loss: 0.14027 (0.17637) +2025-08-24,13:22:38 | INFO | Train Epoch: 11 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.14204 (0.16134) Boundary_loss: 0.014858 (0.014950) Loss: 0.15690 (0.17629) +2025-08-24,13:23:34 | INFO | Train Epoch: 11 [11878912/26365952 (45%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.17237 (0.16138) Boundary_loss: 0.014934 (0.014950) Loss: 0.18731 (0.17633) +2025-08-24,13:24:30 | INFO | Train Epoch: 11 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.16275 (0.16139) Boundary_loss: 0.014895 (0.014949) Loss: 0.17765 (0.17634) +2025-08-24,13:25:27 | INFO | Train Epoch: 11 [11981312/26365952 (45%)] Avg Boundaries (per batch): 49.426 Boundary Ratio: 0.252 Contrastive_loss: 0.14379 (0.16131) Boundary_loss: 0.014896 (0.014949) Loss: 0.15868 (0.17626) +2025-08-24,13:26:23 | INFO | Train Epoch: 11 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.18707 (0.16142) Boundary_loss: 0.014887 (0.014949) Loss: 0.20196 (0.17637) +2025-08-24,13:27:20 | INFO | Train Epoch: 11 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.16126 (0.16142) Boundary_loss: 0.014891 (0.014949) Loss: 0.17615 (0.17637) +2025-08-24,13:28:16 | INFO | Train Epoch: 11 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.13823 (0.16133) Boundary_loss: 0.014959 (0.014949) Loss: 0.15319 (0.17627) +2025-08-24,13:29:13 | INFO | Train Epoch: 11 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.17217 (0.16137) Boundary_loss: 0.014930 (0.014949) Loss: 0.18710 (0.17632) +2025-08-24,13:30:09 | INFO | Train Epoch: 11 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.13209 (0.16125) Boundary_loss: 0.014939 (0.014949) Loss: 0.14703 (0.17620) +2025-08-24,13:31:06 | INFO | Train Epoch: 11 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.14152 (0.16117) Boundary_loss: 0.014897 (0.014948) Loss: 0.15642 (0.17612) +2025-08-24,13:32:02 | INFO | Train Epoch: 11 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.16871 (0.16120) Boundary_loss: 0.014871 (0.014948) Loss: 0.18358 (0.17615) +2025-08-24,13:32:59 | INFO | Train Epoch: 11 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.21381 (0.16142) Boundary_loss: 0.014999 (0.014948) Loss: 0.22881 (0.17636) +2025-08-24,13:33:56 | INFO | Train Epoch: 11 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.12793 (0.16128) Boundary_loss: 0.014981 (0.014948) Loss: 0.14291 (0.17623) +2025-08-24,13:34:52 | INFO | Train Epoch: 11 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.295 Boundary Ratio: 0.246 Contrastive_loss: 0.098088 (0.16102) Boundary_loss: 0.014972 (0.014949) Loss: 0.11306 (0.17597) +2025-08-24,13:35:48 | INFO | Train Epoch: 11 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.16590 (0.16104) Boundary_loss: 0.015042 (0.014949) Loss: 0.18095 (0.17599) +2025-08-24,13:36:45 | INFO | Train Epoch: 11 [12595712/26365952 (48%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.13101 (0.16092) Boundary_loss: 0.014972 (0.014949) Loss: 0.14599 (0.17587) +2025-08-24,13:37:41 | INFO | Train Epoch: 11 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.17471 (0.16097) Boundary_loss: 0.014895 (0.014949) Loss: 0.18960 (0.17592) +2025-08-24,13:38:38 | INFO | Train Epoch: 11 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.15571 (0.16095) Boundary_loss: 0.014918 (0.014949) Loss: 0.17063 (0.17590) +2025-08-24,13:39:34 | INFO | Train Epoch: 11 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.15397 (0.16092) Boundary_loss: 0.015048 (0.014949) Loss: 0.16902 (0.17587) +2025-08-24,13:40:31 | INFO | Train Epoch: 11 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.14177 (0.16085) Boundary_loss: 0.014889 (0.014949) Loss: 0.15666 (0.17580) +2025-08-24,13:41:27 | INFO | Train Epoch: 11 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.15262 (0.16082) Boundary_loss: 0.015000 (0.014949) Loss: 0.16762 (0.17576) +2025-08-24,13:42:24 | INFO | Train Epoch: 11 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.14251 (0.16074) Boundary_loss: 0.014816 (0.014948) Loss: 0.15733 (0.17569) +2025-08-24,13:43:20 | INFO | Train Epoch: 11 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.16597 (0.16076) Boundary_loss: 0.014947 (0.014948) Loss: 0.18092 (0.17571) +2025-08-24,13:44:17 | INFO | Train Epoch: 11 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.16201 (0.16077) Boundary_loss: 0.014790 (0.014948) Loss: 0.17680 (0.17572) +2025-08-24,13:45:13 | INFO | Train Epoch: 11 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14614 (0.16071) Boundary_loss: 0.015077 (0.014948) Loss: 0.16121 (0.17566) +2025-08-24,13:46:10 | INFO | Train Epoch: 11 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.18646 (0.16081) Boundary_loss: 0.014872 (0.014948) Loss: 0.20134 (0.17576) +2025-08-24,13:47:06 | INFO | Train Epoch: 11 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.12638 (0.16068) Boundary_loss: 0.014938 (0.014948) Loss: 0.14131 (0.17563) +2025-08-24,13:48:03 | INFO | Train Epoch: 11 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.16719 (0.16070) Boundary_loss: 0.014950 (0.014948) Loss: 0.18214 (0.17565) +2025-08-24,13:48:59 | INFO | Train Epoch: 11 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.15226 (0.16067) Boundary_loss: 0.014915 (0.014948) Loss: 0.16718 (0.17562) +2025-08-24,13:49:56 | INFO | Train Epoch: 11 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.18040 (0.16075) Boundary_loss: 0.015040 (0.014948) Loss: 0.19544 (0.17569) +2025-08-24,13:50:52 | INFO | Train Epoch: 11 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.15758 (0.16073) Boundary_loss: 0.015010 (0.014948) Loss: 0.17259 (0.17568) +2025-08-24,13:51:49 | INFO | Train Epoch: 11 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.18644 (0.16083) Boundary_loss: 0.015030 (0.014949) Loss: 0.20147 (0.17578) +2025-08-24,13:52:45 | INFO | Train Epoch: 11 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.16585 (0.16085) Boundary_loss: 0.014851 (0.014948) Loss: 0.18070 (0.17580) +2025-08-24,13:53:42 | INFO | Train Epoch: 11 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.12441 (0.16071) Boundary_loss: 0.014969 (0.014949) Loss: 0.13938 (0.17566) +2025-08-24,13:54:38 | INFO | Train Epoch: 11 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.186 Boundary Ratio: 0.246 Contrastive_loss: 0.13547 (0.16062) Boundary_loss: 0.014829 (0.014948) Loss: 0.15030 (0.17557) +2025-08-24,13:55:35 | INFO | Train Epoch: 11 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.18744 (0.16072) Boundary_loss: 0.014887 (0.014948) Loss: 0.20233 (0.17567) +2025-08-24,13:56:31 | INFO | Train Epoch: 11 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.14686 (0.16067) Boundary_loss: 0.014900 (0.014948) Loss: 0.16176 (0.17562) +2025-08-24,13:57:28 | INFO | Train Epoch: 11 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.12553 (0.16054) Boundary_loss: 0.015045 (0.014948) Loss: 0.14057 (0.17549) +2025-08-24,13:58:25 | INFO | Train Epoch: 11 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 0.14593 (0.16048) Boundary_loss: 0.014928 (0.014948) Loss: 0.16086 (0.17543) +2025-08-24,13:59:21 | INFO | Train Epoch: 11 [13824512/26365952 (52%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.17772 (0.16055) Boundary_loss: 0.015064 (0.014948) Loss: 0.19279 (0.17549) +2025-08-24,14:00:18 | INFO | Train Epoch: 11 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.17986 (0.16062) Boundary_loss: 0.014887 (0.014948) Loss: 0.19475 (0.17557) +2025-08-24,14:01:14 | INFO | Train Epoch: 11 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.15061 (0.16058) Boundary_loss: 0.014958 (0.014948) Loss: 0.16556 (0.17553) +2025-08-24,14:02:10 | INFO | Train Epoch: 11 [13978112/26365952 (53%)] Avg Boundaries (per batch): 49.371 Boundary Ratio: 0.252 Contrastive_loss: 0.15985 (0.16058) Boundary_loss: 0.014980 (0.014948) Loss: 0.17483 (0.17553) +2025-08-24,14:03:07 | INFO | Train Epoch: 11 [14029312/26365952 (53%)] Avg Boundaries (per batch): 49.275 Boundary Ratio: 0.251 Contrastive_loss: 0.14256 (0.16051) Boundary_loss: 0.014964 (0.014948) Loss: 0.15752 (0.17546) +2025-08-24,14:04:03 | INFO | Train Epoch: 11 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.15146 (0.16048) Boundary_loss: 0.014867 (0.014948) Loss: 0.16633 (0.17543) +2025-08-24,14:05:00 | INFO | Train Epoch: 11 [14131712/26365952 (54%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.16770 (0.16051) Boundary_loss: 0.014949 (0.014948) Loss: 0.18265 (0.17545) +2025-08-24,14:05:56 | INFO | Train Epoch: 11 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.16524 (0.16052) Boundary_loss: 0.014957 (0.014948) Loss: 0.18020 (0.17547) +2025-08-24,14:06:53 | INFO | Train Epoch: 11 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.13665 (0.16044) Boundary_loss: 0.014971 (0.014948) Loss: 0.15163 (0.17539) +2025-08-24,14:07:49 | INFO | Train Epoch: 11 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.15401 (0.16041) Boundary_loss: 0.014921 (0.014948) Loss: 0.16893 (0.17536) +2025-08-24,14:08:46 | INFO | Train Epoch: 11 [14336512/26365952 (54%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.13306 (0.16032) Boundary_loss: 0.014952 (0.014948) Loss: 0.14801 (0.17527) +2025-08-24,14:09:42 | INFO | Train Epoch: 11 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.16401 (0.16033) Boundary_loss: 0.014918 (0.014948) Loss: 0.17893 (0.17528) +2025-08-24,14:10:39 | INFO | Train Epoch: 11 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14287 (0.16027) Boundary_loss: 0.014947 (0.014948) Loss: 0.15782 (0.17522) +2025-08-24,14:11:35 | INFO | Train Epoch: 11 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.20987 (0.16044) Boundary_loss: 0.014815 (0.014948) Loss: 0.22469 (0.17539) +2025-08-24,14:12:32 | INFO | Train Epoch: 11 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.16442 (0.16046) Boundary_loss: 0.014805 (0.014947) Loss: 0.17922 (0.17540) +2025-08-24,14:13:28 | INFO | Train Epoch: 11 [14592512/26365952 (55%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.16770 (0.16048) Boundary_loss: 0.015135 (0.014948) Loss: 0.18284 (0.17543) +2025-08-24,14:14:25 | INFO | Train Epoch: 11 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.207 Boundary Ratio: 0.251 Contrastive_loss: 0.16675 (0.16050) Boundary_loss: 0.014921 (0.014948) Loss: 0.18167 (0.17545) +2025-08-24,14:15:21 | INFO | Train Epoch: 11 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.13833 (0.16043) Boundary_loss: 0.014883 (0.014947) Loss: 0.15321 (0.17537) +2025-08-24,14:16:17 | INFO | Train Epoch: 11 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.14110 (0.16036) Boundary_loss: 0.014931 (0.014947) Loss: 0.15603 (0.17531) +2025-08-24,14:17:14 | INFO | Train Epoch: 11 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.21056 (0.16053) Boundary_loss: 0.014972 (0.014947) Loss: 0.22553 (0.17548) +2025-08-24,14:18:10 | INFO | Train Epoch: 11 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.18574 (0.16062) Boundary_loss: 0.014905 (0.014947) Loss: 0.20065 (0.17557) +2025-08-24,14:19:07 | INFO | Train Epoch: 11 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.258 Boundary Ratio: 0.246 Contrastive_loss: 0.12352 (0.16049) Boundary_loss: 0.015091 (0.014948) Loss: 0.13861 (0.17544) +2025-08-24,14:20:04 | INFO | Train Epoch: 11 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.14143 (0.16043) Boundary_loss: 0.014866 (0.014947) Loss: 0.15630 (0.17538) +2025-08-24,14:21:00 | INFO | Train Epoch: 11 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.379 Boundary Ratio: 0.247 Contrastive_loss: 0.12392 (0.16030) Boundary_loss: 0.014964 (0.014948) Loss: 0.13888 (0.17525) +2025-08-24,14:21:56 | INFO | Train Epoch: 11 [15053312/26365952 (57%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.10621 (0.16012) Boundary_loss: 0.014921 (0.014947) Loss: 0.12113 (0.17507) +2025-08-24,14:22:53 | INFO | Train Epoch: 11 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.12874 (0.16001) Boundary_loss: 0.014968 (0.014947) Loss: 0.14371 (0.17496) +2025-08-24,14:23:49 | INFO | Train Epoch: 11 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.15033 (0.15998) Boundary_loss: 0.014901 (0.014947) Loss: 0.16523 (0.17493) +2025-08-24,14:24:46 | INFO | Train Epoch: 11 [15206912/26365952 (58%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.16755 (0.16001) Boundary_loss: 0.014978 (0.014947) Loss: 0.18253 (0.17495) +2025-08-24,14:25:42 | INFO | Train Epoch: 11 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.18408 (0.16009) Boundary_loss: 0.014873 (0.014947) Loss: 0.19896 (0.17503) +2025-08-24,14:26:39 | INFO | Train Epoch: 11 [15309312/26365952 (58%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.16974 (0.16012) Boundary_loss: 0.014879 (0.014947) Loss: 0.18462 (0.17507) +2025-08-24,14:27:35 | INFO | Train Epoch: 11 [15360512/26365952 (58%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.11073 (0.15996) Boundary_loss: 0.014940 (0.014947) Loss: 0.12567 (0.17490) +2025-08-24,14:28:31 | INFO | Train Epoch: 11 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.11787 (0.15982) Boundary_loss: 0.014869 (0.014947) Loss: 0.13274 (0.17476) +2025-08-24,14:29:28 | INFO | Train Epoch: 11 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.13936 (0.15975) Boundary_loss: 0.014909 (0.014947) Loss: 0.15427 (0.17470) +2025-08-24,14:30:24 | INFO | Train Epoch: 11 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.11982 (0.15962) Boundary_loss: 0.015018 (0.014947) Loss: 0.13483 (0.17456) +2025-08-24,14:31:20 | INFO | Train Epoch: 11 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.20337 (0.15976) Boundary_loss: 0.015151 (0.014947) Loss: 0.21852 (0.17471) +2025-08-24,14:32:17 | INFO | Train Epoch: 11 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.16881 (0.15979) Boundary_loss: 0.014846 (0.014947) Loss: 0.18366 (0.17474) +2025-08-24,14:33:13 | INFO | Train Epoch: 11 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 0.16283 (0.15980) Boundary_loss: 0.014938 (0.014947) Loss: 0.17777 (0.17475) +2025-08-24,14:34:10 | INFO | Train Epoch: 11 [15718912/26365952 (60%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.13241 (0.15971) Boundary_loss: 0.015012 (0.014947) Loss: 0.14742 (0.17466) +2025-08-24,14:35:06 | INFO | Train Epoch: 11 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.16504 (0.15973) Boundary_loss: 0.014867 (0.014947) Loss: 0.17991 (0.17468) +2025-08-24,14:36:02 | INFO | Train Epoch: 11 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.18106 (0.15980) Boundary_loss: 0.014910 (0.014947) Loss: 0.19597 (0.17474) +2025-08-24,14:36:59 | INFO | Train Epoch: 11 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.12121 (0.15967) Boundary_loss: 0.014829 (0.014947) Loss: 0.13603 (0.17462) +2025-08-24,14:37:55 | INFO | Train Epoch: 11 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.12291 (0.15956) Boundary_loss: 0.014873 (0.014946) Loss: 0.13778 (0.17450) +2025-08-24,14:38:52 | INFO | Train Epoch: 11 [15974912/26365952 (61%)] Avg Boundaries (per batch): 49.311 Boundary Ratio: 0.252 Contrastive_loss: 0.15751 (0.15955) Boundary_loss: 0.014813 (0.014946) Loss: 0.17232 (0.17450) +2025-08-24,14:39:48 | INFO | Train Epoch: 11 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.12097 (0.15943) Boundary_loss: 0.014991 (0.014946) Loss: 0.13597 (0.17437) +2025-08-24,14:40:45 | INFO | Train Epoch: 11 [16077312/26365952 (61%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 0.16280 (0.15944) Boundary_loss: 0.014942 (0.014946) Loss: 0.17774 (0.17438) +2025-08-24,14:41:41 | INFO | Train Epoch: 11 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.14833 (0.15940) Boundary_loss: 0.014965 (0.014946) Loss: 0.16330 (0.17435) +2025-08-24,14:42:38 | INFO | Train Epoch: 11 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.12711 (0.15930) Boundary_loss: 0.014899 (0.014946) Loss: 0.14201 (0.17425) +2025-08-24,14:43:34 | INFO | Train Epoch: 11 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.16365 (0.15931) Boundary_loss: 0.014811 (0.014946) Loss: 0.17847 (0.17426) +2025-08-24,14:44:30 | INFO | Train Epoch: 11 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.17994 (0.15938) Boundary_loss: 0.014943 (0.014946) Loss: 0.19488 (0.17432) +2025-08-24,14:45:27 | INFO | Train Epoch: 11 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.16328 (0.15939) Boundary_loss: 0.015009 (0.014946) Loss: 0.17829 (0.17434) +2025-08-24,14:46:23 | INFO | Train Epoch: 11 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.17434 (0.15944) Boundary_loss: 0.014918 (0.014946) Loss: 0.18926 (0.17438) +2025-08-24,14:47:20 | INFO | Train Epoch: 11 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.15718 (0.15943) Boundary_loss: 0.014935 (0.014946) Loss: 0.17212 (0.17438) +2025-08-24,14:48:16 | INFO | Train Epoch: 11 [16486912/26365952 (63%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.17258 (0.15947) Boundary_loss: 0.015088 (0.014946) Loss: 0.18767 (0.17442) +2025-08-24,14:49:12 | INFO | Train Epoch: 11 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.19627 (0.15958) Boundary_loss: 0.014958 (0.014946) Loss: 0.21123 (0.17453) +2025-08-24,14:50:09 | INFO | Train Epoch: 11 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.15196 (0.15956) Boundary_loss: 0.014987 (0.014946) Loss: 0.16695 (0.17451) +2025-08-24,14:51:05 | INFO | Train Epoch: 11 [16640512/26365952 (63%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.16371 (0.15957) Boundary_loss: 0.014909 (0.014946) Loss: 0.17862 (0.17452) +2025-08-24,14:52:02 | INFO | Train Epoch: 11 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.17095 (0.15961) Boundary_loss: 0.014846 (0.014946) Loss: 0.18580 (0.17455) +2025-08-24,14:52:58 | INFO | Train Epoch: 11 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.16573 (0.15963) Boundary_loss: 0.014874 (0.014946) Loss: 0.18060 (0.17457) +2025-08-24,14:53:55 | INFO | Train Epoch: 11 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.11008 (0.15948) Boundary_loss: 0.014892 (0.014945) Loss: 0.12497 (0.17442) +2025-08-24,14:54:51 | INFO | Train Epoch: 11 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.18130 (0.15954) Boundary_loss: 0.015022 (0.014946) Loss: 0.19632 (0.17449) +2025-08-24,14:55:47 | INFO | Train Epoch: 11 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.14031 (0.15948) Boundary_loss: 0.014791 (0.014945) Loss: 0.15510 (0.17443) +2025-08-24,14:56:44 | INFO | Train Epoch: 11 [16947712/26365952 (64%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.20845 (0.15963) Boundary_loss: 0.014921 (0.014945) Loss: 0.22338 (0.17458) +2025-08-24,14:57:40 | INFO | Train Epoch: 11 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.12178 (0.15952) Boundary_loss: 0.014923 (0.014945) Loss: 0.13670 (0.17446) +2025-08-24,14:58:37 | INFO | Train Epoch: 11 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.21821 (0.15969) Boundary_loss: 0.014876 (0.014945) Loss: 0.23308 (0.17464) +2025-08-24,14:59:33 | INFO | Train Epoch: 11 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.18117 (0.15976) Boundary_loss: 0.014885 (0.014945) Loss: 0.19605 (0.17470) +2025-08-24,15:00:30 | INFO | Train Epoch: 11 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.14704 (0.15972) Boundary_loss: 0.014916 (0.014945) Loss: 0.16195 (0.17466) +2025-08-24,15:01:26 | INFO | Train Epoch: 11 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 0.17495 (0.15977) Boundary_loss: 0.014902 (0.014944) Loss: 0.18986 (0.17471) +2025-08-24,15:02:23 | INFO | Train Epoch: 11 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.21729 (0.15994) Boundary_loss: 0.014951 (0.014944) Loss: 0.23224 (0.17488) +2025-08-24,15:03:19 | INFO | Train Epoch: 11 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.12197 (0.15982) Boundary_loss: 0.014828 (0.014944) Loss: 0.13680 (0.17477) +2025-08-24,15:04:16 | INFO | Train Epoch: 11 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13545 (0.15975) Boundary_loss: 0.014890 (0.014944) Loss: 0.15033 (0.17470) +2025-08-24,15:05:12 | INFO | Train Epoch: 11 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.14859 (0.15972) Boundary_loss: 0.014855 (0.014944) Loss: 0.16344 (0.17466) +2025-08-24,15:06:09 | INFO | Train Epoch: 11 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.15595 (0.15971) Boundary_loss: 0.014975 (0.014944) Loss: 0.17093 (0.17465) +2025-08-24,15:07:05 | INFO | Train Epoch: 11 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.15555 (0.15970) Boundary_loss: 0.015014 (0.014944) Loss: 0.17057 (0.17464) +2025-08-24,15:08:01 | INFO | Train Epoch: 11 [17562112/26365952 (67%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.15451 (0.15968) Boundary_loss: 0.015057 (0.014944) Loss: 0.16956 (0.17463) +2025-08-24,15:08:58 | INFO | Train Epoch: 11 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.16639 (0.15970) Boundary_loss: 0.014952 (0.014944) Loss: 0.18134 (0.17464) +2025-08-24,15:09:54 | INFO | Train Epoch: 11 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.13226 (0.15962) Boundary_loss: 0.014976 (0.014944) Loss: 0.14723 (0.17457) +2025-08-24,15:10:51 | INFO | Train Epoch: 11 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.13157 (0.15954) Boundary_loss: 0.014879 (0.014944) Loss: 0.14645 (0.17448) +2025-08-24,15:11:47 | INFO | Train Epoch: 11 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.18709 (0.15962) Boundary_loss: 0.014989 (0.014944) Loss: 0.20208 (0.17456) +2025-08-24,15:12:44 | INFO | Train Epoch: 11 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.18679 (0.15970) Boundary_loss: 0.014931 (0.014944) Loss: 0.20172 (0.17464) +2025-08-24,15:13:40 | INFO | Train Epoch: 11 [17869312/26365952 (68%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 0.16589 (0.15972) Boundary_loss: 0.014928 (0.014944) Loss: 0.18082 (0.17466) +2025-08-24,15:14:37 | INFO | Train Epoch: 11 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.14097 (0.15966) Boundary_loss: 0.014946 (0.014944) Loss: 0.15592 (0.17461) +2025-08-24,15:15:33 | INFO | Train Epoch: 11 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.11135 (0.15952) Boundary_loss: 0.015005 (0.014944) Loss: 0.12636 (0.17447) +2025-08-24,15:16:29 | INFO | Train Epoch: 11 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.20100 (0.15964) Boundary_loss: 0.015019 (0.014945) Loss: 0.21602 (0.17459) +2025-08-24,15:17:26 | INFO | Train Epoch: 11 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.14449 (0.15960) Boundary_loss: 0.014991 (0.014945) Loss: 0.15948 (0.17454) +2025-08-24,15:18:22 | INFO | Train Epoch: 11 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.15914 (0.15960) Boundary_loss: 0.015044 (0.014945) Loss: 0.17418 (0.17454) +2025-08-24,15:19:19 | INFO | Train Epoch: 11 [18176512/26365952 (69%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.14582 (0.15956) Boundary_loss: 0.014918 (0.014945) Loss: 0.16074 (0.17450) +2025-08-24,15:20:16 | INFO | Train Epoch: 11 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.15622 (0.15955) Boundary_loss: 0.014897 (0.014945) Loss: 0.17112 (0.17449) +2025-08-24,15:21:12 | INFO | Train Epoch: 11 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.418 Boundary Ratio: 0.247 Contrastive_loss: 0.17776 (0.15960) Boundary_loss: 0.014946 (0.014945) Loss: 0.19271 (0.17455) +2025-08-24,15:22:09 | INFO | Train Epoch: 11 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.14835 (0.15957) Boundary_loss: 0.015111 (0.014945) Loss: 0.16346 (0.17451) +2025-08-24,15:23:05 | INFO | Train Epoch: 11 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.21263 (0.15972) Boundary_loss: 0.015045 (0.014946) Loss: 0.22768 (0.17466) +2025-08-24,15:24:01 | INFO | Train Epoch: 11 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.16389 (0.15973) Boundary_loss: 0.014874 (0.014945) Loss: 0.17877 (0.17467) +2025-08-24,15:24:58 | INFO | Train Epoch: 11 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.13889 (0.15967) Boundary_loss: 0.014874 (0.014945) Loss: 0.15377 (0.17462) +2025-08-24,15:25:54 | INFO | Train Epoch: 11 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.15148 (0.15965) Boundary_loss: 0.015064 (0.014946) Loss: 0.16655 (0.17459) +2025-08-24,15:26:51 | INFO | Train Epoch: 11 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.13849 (0.15959) Boundary_loss: 0.014833 (0.014945) Loss: 0.15332 (0.17454) +2025-08-24,15:27:47 | INFO | Train Epoch: 11 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.277 Boundary Ratio: 0.246 Contrastive_loss: 0.16814 (0.15961) Boundary_loss: 0.015016 (0.014945) Loss: 0.18315 (0.17456) +2025-08-24,15:28:44 | INFO | Train Epoch: 11 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.12519 (0.15952) Boundary_loss: 0.014992 (0.014946) Loss: 0.14018 (0.17447) +2025-08-24,15:29:40 | INFO | Train Epoch: 11 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.11890 (0.15941) Boundary_loss: 0.014849 (0.014945) Loss: 0.13375 (0.17435) +2025-08-24,15:30:37 | INFO | Train Epoch: 11 [18790912/26365952 (71%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.19541 (0.15951) Boundary_loss: 0.014826 (0.014945) Loss: 0.21023 (0.17445) +2025-08-24,15:31:33 | INFO | Train Epoch: 11 [18842112/26365952 (71%)] Avg Boundaries (per batch): 49.377 Boundary Ratio: 0.252 Contrastive_loss: 0.16836 (0.15953) Boundary_loss: 0.014969 (0.014945) Loss: 0.18333 (0.17448) +2025-08-24,15:32:30 | INFO | Train Epoch: 11 [18893312/26365952 (72%)] Avg Boundaries (per batch): 49.080 Boundary Ratio: 0.250 Contrastive_loss: 0.15240 (0.15951) Boundary_loss: 0.014733 (0.014944) Loss: 0.16713 (0.17446) +2025-08-24,15:33:26 | INFO | Train Epoch: 11 [18944512/26365952 (72%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.16143 (0.15952) Boundary_loss: 0.014935 (0.014944) Loss: 0.17637 (0.17446) +2025-08-24,15:34:23 | INFO | Train Epoch: 11 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.11997 (0.15941) Boundary_loss: 0.014920 (0.014944) Loss: 0.13489 (0.17435) +2025-08-24,15:35:19 | INFO | Train Epoch: 11 [19046912/26365952 (72%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.13347 (0.15934) Boundary_loss: 0.014833 (0.014944) Loss: 0.14830 (0.17428) +2025-08-24,15:36:16 | INFO | Train Epoch: 11 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.15467 (0.15933) Boundary_loss: 0.015060 (0.014944) Loss: 0.16973 (0.17427) +2025-08-24,15:37:12 | INFO | Train Epoch: 11 [19149312/26365952 (73%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 0.11710 (0.15922) Boundary_loss: 0.014922 (0.014944) Loss: 0.13202 (0.17416) +2025-08-24,15:38:09 | INFO | Train Epoch: 11 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.11361 (0.15909) Boundary_loss: 0.015031 (0.014945) Loss: 0.12865 (0.17404) +2025-08-24,15:39:05 | INFO | Train Epoch: 11 [19251712/26365952 (73%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.20688 (0.15922) Boundary_loss: 0.014895 (0.014944) Loss: 0.22177 (0.17417) +2025-08-24,15:40:02 | INFO | Train Epoch: 11 [19302912/26365952 (73%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.16420 (0.15923) Boundary_loss: 0.014825 (0.014944) Loss: 0.17903 (0.17418) +2025-08-24,15:40:58 | INFO | Train Epoch: 11 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.16229 (0.15924) Boundary_loss: 0.014983 (0.014944) Loss: 0.17727 (0.17419) +2025-08-24,15:41:55 | INFO | Train Epoch: 11 [19405312/26365952 (74%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.18861 (0.15932) Boundary_loss: 0.014991 (0.014944) Loss: 0.20360 (0.17426) +2025-08-24,15:42:51 | INFO | Train Epoch: 11 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.16932 (0.15935) Boundary_loss: 0.014971 (0.014944) Loss: 0.18429 (0.17429) +2025-08-24,15:43:48 | INFO | Train Epoch: 11 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.12952 (0.15927) Boundary_loss: 0.014873 (0.014944) Loss: 0.14439 (0.17421) +2025-08-24,15:44:45 | INFO | Train Epoch: 11 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.12756 (0.15918) Boundary_loss: 0.014998 (0.014944) Loss: 0.14256 (0.17413) +2025-08-24,15:45:41 | INFO | Train Epoch: 11 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13138 (0.15911) Boundary_loss: 0.014858 (0.014944) Loss: 0.14624 (0.17406) +2025-08-24,15:46:37 | INFO | Train Epoch: 11 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.15171 (0.15909) Boundary_loss: 0.014879 (0.014944) Loss: 0.16659 (0.17404) +2025-08-24,15:47:34 | INFO | Train Epoch: 11 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.15984 (0.15910) Boundary_loss: 0.015055 (0.014944) Loss: 0.17490 (0.17404) +2025-08-24,15:48:30 | INFO | Train Epoch: 11 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.451 Boundary Ratio: 0.247 Contrastive_loss: 0.18275 (0.15916) Boundary_loss: 0.014799 (0.014944) Loss: 0.19755 (0.17410) +2025-08-24,15:49:27 | INFO | Train Epoch: 11 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.229 Boundary Ratio: 0.251 Contrastive_loss: 0.14689 (0.15912) Boundary_loss: 0.015009 (0.014944) Loss: 0.16190 (0.17407) +2025-08-24,15:50:23 | INFO | Train Epoch: 11 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.15313 (0.15911) Boundary_loss: 0.014876 (0.014944) Loss: 0.16800 (0.17405) +2025-08-24,15:51:20 | INFO | Train Epoch: 11 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.17118 (0.15914) Boundary_loss: 0.014801 (0.014943) Loss: 0.18598 (0.17408) +2025-08-24,15:52:16 | INFO | Train Epoch: 11 [19968512/26365952 (76%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.15787 (0.15914) Boundary_loss: 0.014953 (0.014944) Loss: 0.17283 (0.17408) +2025-08-24,15:53:12 | INFO | Train Epoch: 11 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.20349 (0.15925) Boundary_loss: 0.014954 (0.014944) Loss: 0.21844 (0.17419) +2025-08-24,15:54:09 | INFO | Train Epoch: 11 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.11867 (0.15915) Boundary_loss: 0.014892 (0.014943) Loss: 0.13357 (0.17409) +2025-08-24,15:55:05 | INFO | Train Epoch: 11 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.13786 (0.15909) Boundary_loss: 0.015134 (0.014944) Loss: 0.15300 (0.17404) +2025-08-24,15:56:02 | INFO | Train Epoch: 11 [20173312/26365952 (77%)] Avg Boundaries (per batch): 49.340 Boundary Ratio: 0.252 Contrastive_loss: 0.15426 (0.15908) Boundary_loss: 0.015056 (0.014944) Loss: 0.16932 (0.17402) +2025-08-24,15:56:58 | INFO | Train Epoch: 11 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.18452 (0.15914) Boundary_loss: 0.015075 (0.014945) Loss: 0.19959 (0.17409) +2025-08-24,15:57:54 | INFO | Train Epoch: 11 [20275712/26365952 (77%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.14892 (0.15912) Boundary_loss: 0.014847 (0.014944) Loss: 0.16376 (0.17406) +2025-08-24,15:58:51 | INFO | Train Epoch: 11 [20326912/26365952 (77%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.14182 (0.15908) Boundary_loss: 0.014895 (0.014944) Loss: 0.15671 (0.17402) +2025-08-24,15:59:47 | INFO | Train Epoch: 11 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.12976 (0.15900) Boundary_loss: 0.014958 (0.014944) Loss: 0.14471 (0.17395) +2025-08-24,16:00:44 | INFO | Train Epoch: 11 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.10747 (0.15887) Boundary_loss: 0.014896 (0.014944) Loss: 0.12237 (0.17382) +2025-08-24,16:01:40 | INFO | Train Epoch: 11 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.13781 (0.15882) Boundary_loss: 0.014870 (0.014944) Loss: 0.15268 (0.17376) +2025-08-24,16:02:37 | INFO | Train Epoch: 11 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.15893 (0.15882) Boundary_loss: 0.015055 (0.014944) Loss: 0.17399 (0.17377) +2025-08-24,16:03:33 | INFO | Train Epoch: 11 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.13483 (0.15876) Boundary_loss: 0.014866 (0.014944) Loss: 0.14970 (0.17371) +2025-08-24,16:04:30 | INFO | Train Epoch: 11 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.14153 (0.15872) Boundary_loss: 0.015098 (0.014944) Loss: 0.15663 (0.17366) +2025-08-24,16:05:26 | INFO | Train Epoch: 11 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.16097 (0.15872) Boundary_loss: 0.014937 (0.014944) Loss: 0.17590 (0.17367) +2025-08-24,16:06:22 | INFO | Train Epoch: 11 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.16875 (0.15875) Boundary_loss: 0.014907 (0.014944) Loss: 0.18366 (0.17369) +2025-08-24,16:07:19 | INFO | Train Epoch: 11 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.14515 (0.15872) Boundary_loss: 0.014915 (0.014944) Loss: 0.16007 (0.17366) +2025-08-24,16:08:15 | INFO | Train Epoch: 11 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.19196 (0.15880) Boundary_loss: 0.015013 (0.014944) Loss: 0.20697 (0.17374) +2025-08-24,16:09:12 | INFO | Train Epoch: 11 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.10356 (0.15866) Boundary_loss: 0.014911 (0.014944) Loss: 0.11847 (0.17361) +2025-08-24,16:10:08 | INFO | Train Epoch: 11 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.18072 (0.15872) Boundary_loss: 0.014911 (0.014944) Loss: 0.19563 (0.17366) +2025-08-24,16:11:05 | INFO | Train Epoch: 11 [20992512/26365952 (80%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.14626 (0.15869) Boundary_loss: 0.014929 (0.014944) Loss: 0.16119 (0.17363) +2025-08-24,16:12:01 | INFO | Train Epoch: 11 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.11504 (0.15858) Boundary_loss: 0.014976 (0.014944) Loss: 0.13001 (0.17352) +2025-08-24,16:12:58 | INFO | Train Epoch: 11 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 0.13771 (0.15853) Boundary_loss: 0.014841 (0.014944) Loss: 0.15255 (0.17347) +2025-08-24,16:13:54 | INFO | Train Epoch: 11 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.12528 (0.15845) Boundary_loss: 0.014880 (0.014944) Loss: 0.14016 (0.17339) +2025-08-24,16:14:51 | INFO | Train Epoch: 11 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.16246 (0.15846) Boundary_loss: 0.014808 (0.014943) Loss: 0.17727 (0.17340) +2025-08-24,16:15:47 | INFO | Train Epoch: 11 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.14774 (0.15843) Boundary_loss: 0.014945 (0.014943) Loss: 0.16269 (0.17338) +2025-08-24,16:16:44 | INFO | Train Epoch: 11 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.15077 (0.15841) Boundary_loss: 0.014834 (0.014943) Loss: 0.16560 (0.17336) +2025-08-24,16:17:40 | INFO | Train Epoch: 11 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.12773 (0.15834) Boundary_loss: 0.014996 (0.014943) Loss: 0.14272 (0.17328) +2025-08-24,16:18:36 | INFO | Train Epoch: 11 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.19936 (0.15844) Boundary_loss: 0.015107 (0.014944) Loss: 0.21446 (0.17338) +2025-08-24,16:19:33 | INFO | Train Epoch: 11 [21453312/26365952 (81%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.13238 (0.15838) Boundary_loss: 0.014949 (0.014944) Loss: 0.14733 (0.17332) +2025-08-24,16:20:29 | INFO | Train Epoch: 11 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.16262 (0.15839) Boundary_loss: 0.014993 (0.014944) Loss: 0.17761 (0.17333) +2025-08-24,16:21:26 | INFO | Train Epoch: 11 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.301 Boundary Ratio: 0.246 Contrastive_loss: 0.19651 (0.15848) Boundary_loss: 0.014903 (0.014944) Loss: 0.21141 (0.17342) +2025-08-24,16:22:22 | INFO | Train Epoch: 11 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.12191 (0.15839) Boundary_loss: 0.015084 (0.014944) Loss: 0.13700 (0.17333) +2025-08-24,16:23:19 | INFO | Train Epoch: 11 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.23110 (0.15856) Boundary_loss: 0.014901 (0.014944) Loss: 0.24600 (0.17351) +2025-08-24,16:24:15 | INFO | Train Epoch: 11 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 0.19704 (0.15865) Boundary_loss: 0.014875 (0.014944) Loss: 0.21191 (0.17360) +2025-08-24,16:25:12 | INFO | Train Epoch: 11 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.430 Boundary Ratio: 0.247 Contrastive_loss: 0.15829 (0.15865) Boundary_loss: 0.015036 (0.014944) Loss: 0.17333 (0.17360) +2025-08-24,16:26:08 | INFO | Train Epoch: 11 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.357 Boundary Ratio: 0.247 Contrastive_loss: 0.18168 (0.15871) Boundary_loss: 0.014992 (0.014944) Loss: 0.19668 (0.17365) +2025-08-24,16:27:05 | INFO | Train Epoch: 11 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.17668 (0.15875) Boundary_loss: 0.014920 (0.014944) Loss: 0.19160 (0.17369) +2025-08-24,16:28:01 | INFO | Train Epoch: 11 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.15432 (0.15874) Boundary_loss: 0.014946 (0.014944) Loss: 0.16927 (0.17368) +2025-08-24,16:28:58 | INFO | Train Epoch: 11 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.10583 (0.15861) Boundary_loss: 0.014810 (0.014944) Loss: 0.12064 (0.17356) +2025-08-24,16:29:54 | INFO | Train Epoch: 11 [22016512/26365952 (84%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.22816 (0.15878) Boundary_loss: 0.014890 (0.014944) Loss: 0.24305 (0.17372) +2025-08-24,16:30:50 | INFO | Train Epoch: 11 [22067712/26365952 (84%)] Avg Boundaries (per batch): 49.209 Boundary Ratio: 0.251 Contrastive_loss: 0.17178 (0.15881) Boundary_loss: 0.014714 (0.014943) Loss: 0.18649 (0.17375) +2025-08-24,16:31:47 | INFO | Train Epoch: 11 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.14883 (0.15878) Boundary_loss: 0.014860 (0.014943) Loss: 0.16369 (0.17373) +2025-08-24,16:32:43 | INFO | Train Epoch: 11 [22170112/26365952 (84%)] Avg Boundaries (per batch): 49.281 Boundary Ratio: 0.251 Contrastive_loss: 0.18954 (0.15885) Boundary_loss: 0.014888 (0.014943) Loss: 0.20442 (0.17380) +2025-08-24,16:33:40 | INFO | Train Epoch: 11 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.16381 (0.15887) Boundary_loss: 0.014977 (0.014943) Loss: 0.17879 (0.17381) +2025-08-24,16:34:36 | INFO | Train Epoch: 11 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.355 Boundary Ratio: 0.247 Contrastive_loss: 0.19975 (0.15896) Boundary_loss: 0.014851 (0.014943) Loss: 0.21460 (0.17390) +2025-08-24,16:35:33 | INFO | Train Epoch: 11 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.13324 (0.15890) Boundary_loss: 0.014933 (0.014943) Loss: 0.14817 (0.17384) +2025-08-24,16:36:29 | INFO | Train Epoch: 11 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.15934 (0.15890) Boundary_loss: 0.014954 (0.014943) Loss: 0.17429 (0.17384) +2025-08-24,16:37:25 | INFO | Train Epoch: 11 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.19820 (0.15899) Boundary_loss: 0.014851 (0.014942) Loss: 0.21305 (0.17393) +2025-08-24,16:38:22 | INFO | Train Epoch: 11 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.449 Boundary Ratio: 0.247 Contrastive_loss: 0.13240 (0.15893) Boundary_loss: 0.014970 (0.014943) Loss: 0.14737 (0.17387) +2025-08-24,16:39:18 | INFO | Train Epoch: 11 [22528512/26365952 (85%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.16010 (0.15893) Boundary_loss: 0.014901 (0.014942) Loss: 0.17500 (0.17388) +2025-08-24,16:40:14 | INFO | Train Epoch: 11 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.20790 (0.15904) Boundary_loss: 0.014828 (0.014942) Loss: 0.22273 (0.17399) +2025-08-24,16:41:11 | INFO | Train Epoch: 11 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 0.15901 (0.15904) Boundary_loss: 0.015105 (0.014943) Loss: 0.17412 (0.17399) +2025-08-24,16:42:07 | INFO | Train Epoch: 11 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.12612 (0.15897) Boundary_loss: 0.014982 (0.014943) Loss: 0.14110 (0.17391) +2025-08-24,16:43:04 | INFO | Train Epoch: 11 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.15764 (0.15897) Boundary_loss: 0.014967 (0.014943) Loss: 0.17261 (0.17391) +2025-08-24,16:44:00 | INFO | Train Epoch: 11 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.18451 (0.15902) Boundary_loss: 0.014974 (0.014943) Loss: 0.19948 (0.17397) +2025-08-24,16:44:57 | INFO | Train Epoch: 11 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.12592 (0.15895) Boundary_loss: 0.014916 (0.014943) Loss: 0.14084 (0.17389) +2025-08-24,16:45:53 | INFO | Train Epoch: 11 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.18122 (0.15900) Boundary_loss: 0.015017 (0.014943) Loss: 0.19624 (0.17394) +2025-08-24,16:46:50 | INFO | Train Epoch: 11 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.15398 (0.15899) Boundary_loss: 0.014936 (0.014943) Loss: 0.16891 (0.17393) +2025-08-24,16:47:46 | INFO | Train Epoch: 11 [22989312/26365952 (87%)] Avg Boundaries (per batch): 49.266 Boundary Ratio: 0.251 Contrastive_loss: 0.17463 (0.15902) Boundary_loss: 0.015024 (0.014943) Loss: 0.18965 (0.17397) +2025-08-24,16:48:43 | INFO | Train Epoch: 11 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.22769 (0.15918) Boundary_loss: 0.014904 (0.014943) Loss: 0.24259 (0.17412) +2025-08-24,16:49:39 | INFO | Train Epoch: 11 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.17314 (0.15921) Boundary_loss: 0.014997 (0.014943) Loss: 0.18814 (0.17415) +2025-08-24,16:50:36 | INFO | Train Epoch: 11 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.19942 (0.15929) Boundary_loss: 0.014877 (0.014943) Loss: 0.21430 (0.17424) +2025-08-24,16:51:32 | INFO | Train Epoch: 11 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.13514 (0.15924) Boundary_loss: 0.014946 (0.014943) Loss: 0.15008 (0.17418) +2025-08-24,16:52:28 | INFO | Train Epoch: 11 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.14219 (0.15920) Boundary_loss: 0.014924 (0.014943) Loss: 0.15711 (0.17415) +2025-08-24,16:53:25 | INFO | Train Epoch: 11 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.15753 (0.15920) Boundary_loss: 0.014922 (0.014943) Loss: 0.17245 (0.17414) +2025-08-24,16:54:21 | INFO | Train Epoch: 11 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.16677 (0.15922) Boundary_loss: 0.014898 (0.014943) Loss: 0.18166 (0.17416) +2025-08-24,16:55:18 | INFO | Train Epoch: 11 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.13263 (0.15916) Boundary_loss: 0.014968 (0.014943) Loss: 0.14759 (0.17410) +2025-08-24,16:56:14 | INFO | Train Epoch: 11 [23450112/26365952 (89%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.16560 (0.15917) Boundary_loss: 0.014850 (0.014943) Loss: 0.18045 (0.17412) +2025-08-24,16:57:11 | INFO | Train Epoch: 11 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.18324 (0.15923) Boundary_loss: 0.014917 (0.014943) Loss: 0.19816 (0.17417) +2025-08-24,16:58:07 | INFO | Train Epoch: 11 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.18403 (0.15928) Boundary_loss: 0.014913 (0.014942) Loss: 0.19895 (0.17422) +2025-08-24,16:59:04 | INFO | Train Epoch: 11 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.14107 (0.15924) Boundary_loss: 0.014957 (0.014943) Loss: 0.15603 (0.17418) +2025-08-24,17:00:00 | INFO | Train Epoch: 11 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.16953 (0.15926) Boundary_loss: 0.014794 (0.014942) Loss: 0.18432 (0.17420) +2025-08-24,17:00:56 | INFO | Train Epoch: 11 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.13825 (0.15922) Boundary_loss: 0.014818 (0.014942) Loss: 0.15307 (0.17416) +2025-08-24,17:01:53 | INFO | Train Epoch: 11 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.13844 (0.15917) Boundary_loss: 0.014843 (0.014942) Loss: 0.15329 (0.17411) +2025-08-24,17:02:49 | INFO | Train Epoch: 11 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.12520 (0.15910) Boundary_loss: 0.015000 (0.014942) Loss: 0.14020 (0.17404) +2025-08-24,17:03:46 | INFO | Train Epoch: 11 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.15916 (0.15910) Boundary_loss: 0.014993 (0.014942) Loss: 0.17416 (0.17404) +2025-08-24,17:04:42 | INFO | Train Epoch: 11 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11923 (0.15901) Boundary_loss: 0.015085 (0.014942) Loss: 0.13431 (0.17396) +2025-08-24,17:05:39 | INFO | Train Epoch: 11 [23962112/26365952 (91%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.16329 (0.15902) Boundary_loss: 0.014899 (0.014942) Loss: 0.17819 (0.17397) +2025-08-24,17:06:35 | INFO | Train Epoch: 11 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.18701 (0.15908) Boundary_loss: 0.015006 (0.014942) Loss: 0.20202 (0.17403) +2025-08-24,17:07:32 | INFO | Train Epoch: 11 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.14372 (0.15905) Boundary_loss: 0.014866 (0.014942) Loss: 0.15859 (0.17399) +2025-08-24,17:08:28 | INFO | Train Epoch: 11 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.12796 (0.15898) Boundary_loss: 0.014858 (0.014942) Loss: 0.14282 (0.17393) +2025-08-24,17:09:24 | INFO | Train Epoch: 11 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.158 Boundary Ratio: 0.251 Contrastive_loss: 0.12977 (0.15892) Boundary_loss: 0.014894 (0.014942) Loss: 0.14466 (0.17386) +2025-08-24,17:10:21 | INFO | Train Epoch: 11 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.15922 (0.15892) Boundary_loss: 0.015079 (0.014942) Loss: 0.17430 (0.17387) +2025-08-24,17:11:17 | INFO | Train Epoch: 11 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.13568 (0.15887) Boundary_loss: 0.014928 (0.014942) Loss: 0.15061 (0.17382) +2025-08-24,17:12:14 | INFO | Train Epoch: 11 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.13247 (0.15882) Boundary_loss: 0.014986 (0.014942) Loss: 0.14746 (0.17376) +2025-08-24,17:13:10 | INFO | Train Epoch: 11 [24371712/26365952 (92%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.15304 (0.15881) Boundary_loss: 0.014982 (0.014942) Loss: 0.16802 (0.17375) +2025-08-24,17:14:07 | INFO | Train Epoch: 11 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.10712 (0.15870) Boundary_loss: 0.015003 (0.014942) Loss: 0.12212 (0.17364) +2025-08-24,17:15:03 | INFO | Train Epoch: 11 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.16924 (0.15872) Boundary_loss: 0.014885 (0.014942) Loss: 0.18413 (0.17366) +2025-08-24,17:16:00 | INFO | Train Epoch: 11 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.14946 (0.15870) Boundary_loss: 0.014994 (0.014942) Loss: 0.16446 (0.17364) +2025-08-24,17:16:56 | INFO | Train Epoch: 11 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.11980 (0.15862) Boundary_loss: 0.014874 (0.014942) Loss: 0.13467 (0.17356) +2025-08-24,17:17:52 | INFO | Train Epoch: 11 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.14034 (0.15858) Boundary_loss: 0.014937 (0.014942) Loss: 0.15527 (0.17352) +2025-08-24,17:18:49 | INFO | Train Epoch: 11 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.15217 (0.15857) Boundary_loss: 0.015039 (0.014942) Loss: 0.16721 (0.17351) +2025-08-24,17:19:45 | INFO | Train Epoch: 11 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.14125 (0.15853) Boundary_loss: 0.014795 (0.014942) Loss: 0.15605 (0.17348) +2025-08-24,17:20:42 | INFO | Train Epoch: 11 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.13854 (0.15849) Boundary_loss: 0.014947 (0.014942) Loss: 0.15349 (0.17343) +2025-08-24,17:21:38 | INFO | Train Epoch: 11 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.14148 (0.15846) Boundary_loss: 0.014933 (0.014942) Loss: 0.15642 (0.17340) +2025-08-24,17:22:35 | INFO | Train Epoch: 11 [24883712/26365952 (94%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.16538 (0.15847) Boundary_loss: 0.015021 (0.014942) Loss: 0.18040 (0.17341) +2025-08-24,17:23:31 | INFO | Train Epoch: 11 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.398 Boundary Ratio: 0.247 Contrastive_loss: 0.14962 (0.15845) Boundary_loss: 0.014955 (0.014942) Loss: 0.16457 (0.17340) +2025-08-24,17:24:28 | INFO | Train Epoch: 11 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.201 Boundary Ratio: 0.251 Contrastive_loss: 0.16577 (0.15847) Boundary_loss: 0.014960 (0.014942) Loss: 0.18073 (0.17341) +2025-08-24,17:25:24 | INFO | Train Epoch: 11 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.16340 (0.15848) Boundary_loss: 0.014855 (0.014942) Loss: 0.17825 (0.17342) +2025-08-24,17:26:20 | INFO | Train Epoch: 11 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.17665 (0.15852) Boundary_loss: 0.014972 (0.014942) Loss: 0.19162 (0.17346) +2025-08-24,17:27:17 | INFO | Train Epoch: 11 [25139712/26365952 (95%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.12540 (0.15845) Boundary_loss: 0.014927 (0.014942) Loss: 0.14033 (0.17339) +2025-08-24,17:28:13 | INFO | Train Epoch: 11 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.14965 (0.15843) Boundary_loss: 0.014922 (0.014942) Loss: 0.16457 (0.17337) +2025-08-24,17:29:10 | INFO | Train Epoch: 11 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.16402 (0.15844) Boundary_loss: 0.014984 (0.014942) Loss: 0.17901 (0.17338) +2025-08-24,17:30:06 | INFO | Train Epoch: 11 [25293312/26365952 (96%)] Avg Boundaries (per batch): 49.221 Boundary Ratio: 0.251 Contrastive_loss: 0.12743 (0.15838) Boundary_loss: 0.014991 (0.014942) Loss: 0.14242 (0.17332) +2025-08-24,17:31:03 | INFO | Train Epoch: 11 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.14908 (0.15836) Boundary_loss: 0.014922 (0.014942) Loss: 0.16401 (0.17330) +2025-08-24,17:31:59 | INFO | Train Epoch: 11 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.14593 (0.15834) Boundary_loss: 0.014903 (0.014942) Loss: 0.16084 (0.17328) +2025-08-24,17:32:56 | INFO | Train Epoch: 11 [25446912/26365952 (97%)] Avg Boundaries (per batch): 49.357 Boundary Ratio: 0.252 Contrastive_loss: 0.16363 (0.15835) Boundary_loss: 0.015036 (0.014942) Loss: 0.17867 (0.17329) +2025-08-24,17:33:52 | INFO | Train Epoch: 11 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.12426 (0.15828) Boundary_loss: 0.015003 (0.014943) Loss: 0.13927 (0.17322) +2025-08-24,17:34:49 | INFO | Train Epoch: 11 [25549312/26365952 (97%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.12737 (0.15822) Boundary_loss: 0.015022 (0.014943) Loss: 0.14239 (0.17316) +2025-08-24,17:35:45 | INFO | Train Epoch: 11 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.18635 (0.15827) Boundary_loss: 0.014887 (0.014943) Loss: 0.20123 (0.17321) +2025-08-24,17:36:41 | INFO | Train Epoch: 11 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.15726 (0.15827) Boundary_loss: 0.014962 (0.014943) Loss: 0.17222 (0.17321) +2025-08-24,17:37:38 | INFO | Train Epoch: 11 [25702912/26365952 (97%)] Avg Boundaries (per batch): 49.250 Boundary Ratio: 0.251 Contrastive_loss: 0.12959 (0.15821) Boundary_loss: 0.014975 (0.014943) Loss: 0.14457 (0.17316) +2025-08-24,17:38:34 | INFO | Train Epoch: 11 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.14748 (0.15819) Boundary_loss: 0.015110 (0.014943) Loss: 0.16259 (0.17313) +2025-08-24,17:39:31 | INFO | Train Epoch: 11 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.434 Boundary Ratio: 0.247 Contrastive_loss: 0.13750 (0.15815) Boundary_loss: 0.014907 (0.014943) Loss: 0.15240 (0.17309) +2025-08-24,17:40:27 | INFO | Train Epoch: 11 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.20790 (0.15825) Boundary_loss: 0.015044 (0.014943) Loss: 0.22294 (0.17319) +2025-08-24,17:41:23 | INFO | Train Epoch: 11 [25907712/26365952 (98%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.15833 (0.15825) Boundary_loss: 0.014953 (0.014943) Loss: 0.17328 (0.17319) +2025-08-24,17:42:20 | INFO | Train Epoch: 11 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.14254 (0.15822) Boundary_loss: 0.014982 (0.014943) Loss: 0.15752 (0.17316) +2025-08-24,17:43:16 | INFO | Train Epoch: 11 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.10660 (0.15812) Boundary_loss: 0.014828 (0.014943) Loss: 0.12142 (0.17306) +2025-08-24,17:44:13 | INFO | Train Epoch: 11 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.12324 (0.15805) Boundary_loss: 0.014927 (0.014943) Loss: 0.13817 (0.17299) +2025-08-24,17:45:09 | INFO | Train Epoch: 11 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.19718 (0.15812) Boundary_loss: 0.014860 (0.014943) Loss: 0.21204 (0.17307) +2025-08-24,17:46:06 | INFO | Train Epoch: 11 [26163712/26365952 (99%)] Avg Boundaries (per batch): 49.305 Boundary Ratio: 0.252 Contrastive_loss: 0.14336 (0.15810) Boundary_loss: 0.014911 (0.014943) Loss: 0.15827 (0.17304) +2025-08-24,17:47:02 | INFO | Train Epoch: 11 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.17663 (0.15813) Boundary_loss: 0.014911 (0.014943) Loss: 0.19154 (0.17307) +2025-08-24,17:47:59 | INFO | Train Epoch: 11 [26266112/26365952 (100%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.11308 (0.15804) Boundary_loss: 0.014880 (0.014943) Loss: 0.12796 (0.17299) +2025-08-24,17:48:55 | INFO | Train Epoch: 11 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.414 Boundary Ratio: 0.247 Contrastive_loss: 0.15156 (0.15803) Boundary_loss: 0.015018 (0.014943) Loss: 0.16658 (0.17297) +2025-08-24,17:49:49 | INFO | Train Epoch: 11 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.14212 (0.15800) Boundary_loss: 0.014898 (0.014943) Loss: 0.15702 (0.17294) +2025-08-24,17:49:49 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-24,17:49:49 | INFO | [Epoch 11] Average Step Time: 0.567s | Average GPU Memory: 31.7 GB +2025-08-24,17:49:49 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-24,17:49:49 | INFO | Starting zero-shot imagenet. +2025-08-24,17:49:49 | INFO | Building zero-shot classifier +2025-08-24,17:49:58 | INFO | Using classifier +2025-08-24,17:50:45 | INFO | Finished zero-shot imagenet. +2025-08-24,17:50:45 | INFO | Eval Epoch: 12 imagenet-zeroshot-val-top1: 0.3020 imagenet-zeroshot-val-top5: 0.5671 +2025-08-24,17:50:46 | INFO | Start epoch 12 +2025-08-24,17:50:48 | INFO | Train Epoch: 12 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.11145 (0.11145) Boundary_loss: 0.014823 (0.014823) Loss: 0.12627 (0.12627) +2025-08-24,17:51:44 | INFO | Train Epoch: 12 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.15796 (0.13470) Boundary_loss: 0.014950 (0.014886) Loss: 0.17291 (0.14959) +2025-08-24,17:52:41 | INFO | Train Epoch: 12 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.18128 (0.15023) Boundary_loss: 0.014857 (0.014877) Loss: 0.19613 (0.16510) +2025-08-24,17:53:37 | INFO | Train Epoch: 12 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.15933 (0.15250) Boundary_loss: 0.014973 (0.014901) Loss: 0.17431 (0.16741) +2025-08-24,17:54:34 | INFO | Train Epoch: 12 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.11164 (0.14433) Boundary_loss: 0.014846 (0.014890) Loss: 0.12648 (0.15922) +2025-08-24,17:55:30 | INFO | Train Epoch: 12 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.10794 (0.13826) Boundary_loss: 0.015021 (0.014912) Loss: 0.12296 (0.15318) +2025-08-24,17:56:26 | INFO | Train Epoch: 12 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.16551 (0.14216) Boundary_loss: 0.014919 (0.014913) Loss: 0.18043 (0.15707) +2025-08-24,17:57:23 | INFO | Train Epoch: 12 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.13902 (0.14176) Boundary_loss: 0.014926 (0.014914) Loss: 0.15394 (0.15668) +2025-08-24,17:58:19 | INFO | Train Epoch: 12 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.11371 (0.13865) Boundary_loss: 0.014840 (0.014906) Loss: 0.12855 (0.15355) +2025-08-24,17:59:15 | INFO | Train Epoch: 12 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.13668 (0.13845) Boundary_loss: 0.015038 (0.014919) Loss: 0.15172 (0.15337) +2025-08-24,18:00:12 | INFO | Train Epoch: 12 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.10294 (0.13522) Boundary_loss: 0.015084 (0.014934) Loss: 0.11802 (0.15016) +2025-08-24,18:01:08 | INFO | Train Epoch: 12 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.12073 (0.13401) Boundary_loss: 0.015076 (0.014946) Loss: 0.13581 (0.14896) +2025-08-24,18:02:04 | INFO | Train Epoch: 12 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.172 Boundary Ratio: 0.246 Contrastive_loss: 0.11277 (0.13238) Boundary_loss: 0.014956 (0.014947) Loss: 0.12772 (0.14733) +2025-08-24,18:03:01 | INFO | Train Epoch: 12 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.12631 (0.13195) Boundary_loss: 0.014930 (0.014946) Loss: 0.14124 (0.14689) +2025-08-24,18:03:57 | INFO | Train Epoch: 12 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.15355 (0.13339) Boundary_loss: 0.014901 (0.014943) Loss: 0.16845 (0.14833) +2025-08-24,18:04:53 | INFO | Train Epoch: 12 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.12206 (0.13268) Boundary_loss: 0.014801 (0.014934) Loss: 0.13686 (0.14761) +2025-08-24,18:05:50 | INFO | Train Epoch: 12 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.12219 (0.13206) Boundary_loss: 0.014828 (0.014928) Loss: 0.13702 (0.14699) +2025-08-24,18:06:46 | INFO | Train Epoch: 12 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.10759 (0.13070) Boundary_loss: 0.014993 (0.014931) Loss: 0.12259 (0.14563) +2025-08-24,18:07:43 | INFO | Train Epoch: 12 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.14315 (0.13136) Boundary_loss: 0.014938 (0.014932) Loss: 0.15809 (0.14629) +2025-08-24,18:08:39 | INFO | Train Epoch: 12 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.14491 (0.13204) Boundary_loss: 0.014961 (0.014933) Loss: 0.15987 (0.14697) +2025-08-24,18:09:36 | INFO | Train Epoch: 12 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 0.10553 (0.13077) Boundary_loss: 0.015015 (0.014937) Loss: 0.12054 (0.14571) +2025-08-24,18:10:32 | INFO | Train Epoch: 12 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.13232 (0.13084) Boundary_loss: 0.014874 (0.014934) Loss: 0.14719 (0.14578) +2025-08-24,18:11:29 | INFO | Train Epoch: 12 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 49.223 Boundary Ratio: 0.251 Contrastive_loss: 0.13989 (0.13124) Boundary_loss: 0.014933 (0.014934) Loss: 0.15482 (0.14617) +2025-08-24,18:12:25 | INFO | Train Epoch: 12 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.13832 (0.13153) Boundary_loss: 0.014858 (0.014931) Loss: 0.15318 (0.14646) +2025-08-24,18:13:21 | INFO | Train Epoch: 12 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.12375 (0.13122) Boundary_loss: 0.014930 (0.014931) Loss: 0.13868 (0.14615) +2025-08-24,18:14:17 | INFO | Train Epoch: 12 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.15532 (0.13215) Boundary_loss: 0.014912 (0.014930) Loss: 0.17023 (0.14708) +2025-08-24,18:15:14 | INFO | Train Epoch: 12 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.14775 (0.13273) Boundary_loss: 0.014878 (0.014928) Loss: 0.16263 (0.14765) +2025-08-24,18:16:10 | INFO | Train Epoch: 12 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.13910 (0.13295) Boundary_loss: 0.015017 (0.014931) Loss: 0.15412 (0.14788) +2025-08-24,18:17:06 | INFO | Train Epoch: 12 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.15992 (0.13388) Boundary_loss: 0.014869 (0.014929) Loss: 0.17478 (0.14881) +2025-08-24,18:18:03 | INFO | Train Epoch: 12 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.14317 (0.13419) Boundary_loss: 0.014863 (0.014927) Loss: 0.15803 (0.14912) +2025-08-24,18:18:59 | INFO | Train Epoch: 12 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.422 Boundary Ratio: 0.247 Contrastive_loss: 0.14125 (0.13442) Boundary_loss: 0.015028 (0.014930) Loss: 0.15628 (0.14935) +2025-08-24,18:19:55 | INFO | Train Epoch: 12 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.11910 (0.13394) Boundary_loss: 0.014925 (0.014930) Loss: 0.13402 (0.14887) +2025-08-24,18:20:52 | INFO | Train Epoch: 12 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 49.291 Boundary Ratio: 0.251 Contrastive_loss: 0.17493 (0.13518) Boundary_loss: 0.014909 (0.014929) Loss: 0.18984 (0.15011) +2025-08-24,18:21:48 | INFO | Train Epoch: 12 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.11048 (0.13446) Boundary_loss: 0.014870 (0.014928) Loss: 0.12535 (0.14938) +2025-08-24,18:22:44 | INFO | Train Epoch: 12 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.11324 (0.13385) Boundary_loss: 0.014916 (0.014927) Loss: 0.12816 (0.14878) +2025-08-24,18:23:41 | INFO | Train Epoch: 12 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.273 Boundary Ratio: 0.246 Contrastive_loss: 0.089957 (0.13263) Boundary_loss: 0.014902 (0.014927) Loss: 0.10486 (0.14756) +2025-08-24,18:24:37 | INFO | Train Epoch: 12 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.098494 (0.13171) Boundary_loss: 0.014986 (0.014928) Loss: 0.11348 (0.14664) +2025-08-24,18:25:34 | INFO | Train Epoch: 12 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.14097 (0.13195) Boundary_loss: 0.015017 (0.014931) Loss: 0.15599 (0.14688) +2025-08-24,18:26:30 | INFO | Train Epoch: 12 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.13126 (0.13193) Boundary_loss: 0.014921 (0.014930) Loss: 0.14618 (0.14686) +2025-08-24,18:27:26 | INFO | Train Epoch: 12 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.14545 (0.13227) Boundary_loss: 0.014917 (0.014930) Loss: 0.16037 (0.14720) +2025-08-24,18:28:23 | INFO | Train Epoch: 12 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.12459 (0.13209) Boundary_loss: 0.015014 (0.014932) Loss: 0.13961 (0.14702) +2025-08-24,18:29:19 | INFO | Train Epoch: 12 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 49.121 Boundary Ratio: 0.251 Contrastive_loss: 0.15406 (0.13261) Boundary_loss: 0.014908 (0.014932) Loss: 0.16897 (0.14754) +2025-08-24,18:30:15 | INFO | Train Epoch: 12 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.14293 (0.13285) Boundary_loss: 0.014862 (0.014930) Loss: 0.15780 (0.14778) +2025-08-24,18:31:12 | INFO | Train Epoch: 12 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.14451 (0.13311) Boundary_loss: 0.014959 (0.014931) Loss: 0.15947 (0.14804) +2025-08-24,18:32:08 | INFO | Train Epoch: 12 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.11774 (0.13277) Boundary_loss: 0.014954 (0.014931) Loss: 0.13270 (0.14770) +2025-08-24,18:33:04 | INFO | Train Epoch: 12 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.10922 (0.13226) Boundary_loss: 0.014919 (0.014931) Loss: 0.12414 (0.14719) +2025-08-24,18:34:00 | INFO | Train Epoch: 12 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 0.099648 (0.13157) Boundary_loss: 0.015038 (0.014933) Loss: 0.11469 (0.14650) +2025-08-24,18:34:57 | INFO | Train Epoch: 12 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.15765 (0.13211) Boundary_loss: 0.014887 (0.014932) Loss: 0.17253 (0.14704) +2025-08-24,18:35:53 | INFO | Train Epoch: 12 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.551 Boundary Ratio: 0.248 Contrastive_loss: 0.13556 (0.13218) Boundary_loss: 0.014910 (0.014932) Loss: 0.15047 (0.14711) +2025-08-24,18:36:49 | INFO | Train Epoch: 12 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.076882 (0.13107) Boundary_loss: 0.014957 (0.014932) Loss: 0.091839 (0.14601) +2025-08-24,18:37:46 | INFO | Train Epoch: 12 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.16725 (0.13178) Boundary_loss: 0.014899 (0.014932) Loss: 0.18215 (0.14671) +2025-08-24,18:38:42 | INFO | Train Epoch: 12 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.342 Boundary Ratio: 0.247 Contrastive_loss: 0.11309 (0.13142) Boundary_loss: 0.014899 (0.014931) Loss: 0.12799 (0.14635) +2025-08-24,18:39:39 | INFO | Train Epoch: 12 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.13164 (0.13143) Boundary_loss: 0.014872 (0.014930) Loss: 0.14652 (0.14636) +2025-08-24,18:40:35 | INFO | Train Epoch: 12 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.14353 (0.13165) Boundary_loss: 0.014848 (0.014928) Loss: 0.15838 (0.14658) +2025-08-24,18:41:31 | INFO | Train Epoch: 12 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.13662 (0.13174) Boundary_loss: 0.014800 (0.014926) Loss: 0.15142 (0.14667) +2025-08-24,18:42:28 | INFO | Train Epoch: 12 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.17298 (0.13248) Boundary_loss: 0.014861 (0.014925) Loss: 0.18784 (0.14740) +2025-08-24,18:43:24 | INFO | Train Epoch: 12 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.15288 (0.13284) Boundary_loss: 0.014956 (0.014925) Loss: 0.16783 (0.14776) +2025-08-24,18:44:20 | INFO | Train Epoch: 12 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.13311 (0.13284) Boundary_loss: 0.014783 (0.014923) Loss: 0.14789 (0.14776) +2025-08-24,18:45:17 | INFO | Train Epoch: 12 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.14031 (0.13297) Boundary_loss: 0.014914 (0.014923) Loss: 0.15523 (0.14789) +2025-08-24,18:46:13 | INFO | Train Epoch: 12 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.20032 (0.13409) Boundary_loss: 0.015022 (0.014924) Loss: 0.21535 (0.14901) +2025-08-24,18:47:09 | INFO | Train Epoch: 12 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.088053 (0.13334) Boundary_loss: 0.014956 (0.014925) Loss: 0.10301 (0.14826) +2025-08-24,18:48:06 | INFO | Train Epoch: 12 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 49.219 Boundary Ratio: 0.251 Contrastive_loss: 0.094308 (0.13271) Boundary_loss: 0.014880 (0.014924) Loss: 0.10919 (0.14763) +2025-08-24,18:49:02 | INFO | Train Epoch: 12 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.11443 (0.13242) Boundary_loss: 0.014938 (0.014924) Loss: 0.12937 (0.14734) +2025-08-24,18:49:58 | INFO | Train Epoch: 12 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.13233 (0.13241) Boundary_loss: 0.014954 (0.014925) Loss: 0.14729 (0.14734) +2025-08-24,18:50:55 | INFO | Train Epoch: 12 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.13631 (0.13247) Boundary_loss: 0.014863 (0.014924) Loss: 0.15117 (0.14740) +2025-08-24,18:51:51 | INFO | Train Epoch: 12 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.10903 (0.13212) Boundary_loss: 0.014961 (0.014924) Loss: 0.12399 (0.14704) +2025-08-24,18:52:48 | INFO | Train Epoch: 12 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.12709 (0.13204) Boundary_loss: 0.015007 (0.014926) Loss: 0.14210 (0.14697) +2025-08-24,18:53:44 | INFO | Train Epoch: 12 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 0.12734 (0.13198) Boundary_loss: 0.014906 (0.014925) Loss: 0.14224 (0.14690) +2025-08-24,18:54:40 | INFO | Train Epoch: 12 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.10622 (0.13160) Boundary_loss: 0.014904 (0.014925) Loss: 0.12113 (0.14653) +2025-08-24,18:55:37 | INFO | Train Epoch: 12 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.14218 (0.13175) Boundary_loss: 0.014963 (0.014926) Loss: 0.15714 (0.14668) +2025-08-24,18:56:33 | INFO | Train Epoch: 12 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.12447 (0.13165) Boundary_loss: 0.014824 (0.014924) Loss: 0.13929 (0.14657) +2025-08-24,18:57:29 | INFO | Train Epoch: 12 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.11535 (0.13142) Boundary_loss: 0.014811 (0.014923) Loss: 0.13016 (0.14635) +2025-08-24,18:58:26 | INFO | Train Epoch: 12 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.16709 (0.13191) Boundary_loss: 0.015007 (0.014924) Loss: 0.18210 (0.14684) +2025-08-24,18:59:22 | INFO | Train Epoch: 12 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.11161 (0.13164) Boundary_loss: 0.015024 (0.014925) Loss: 0.12663 (0.14656) +2025-08-24,19:00:19 | INFO | Train Epoch: 12 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.14868 (0.13187) Boundary_loss: 0.015006 (0.014926) Loss: 0.16369 (0.14679) +2025-08-24,19:01:15 | INFO | Train Epoch: 12 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.13462 (0.13190) Boundary_loss: 0.014965 (0.014927) Loss: 0.14958 (0.14683) +2025-08-24,19:02:12 | INFO | Train Epoch: 12 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.12289 (0.13178) Boundary_loss: 0.014858 (0.014926) Loss: 0.13774 (0.14671) +2025-08-24,19:03:08 | INFO | Train Epoch: 12 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.099169 (0.13137) Boundary_loss: 0.014970 (0.014926) Loss: 0.11414 (0.14629) +2025-08-24,19:04:04 | INFO | Train Epoch: 12 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.14969 (0.13160) Boundary_loss: 0.014861 (0.014926) Loss: 0.16455 (0.14652) +2025-08-24,19:05:01 | INFO | Train Epoch: 12 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.11285 (0.13136) Boundary_loss: 0.015033 (0.014927) Loss: 0.12788 (0.14629) +2025-08-24,19:05:57 | INFO | Train Epoch: 12 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.11886 (0.13121) Boundary_loss: 0.014790 (0.014925) Loss: 0.13365 (0.14613) +2025-08-24,19:06:54 | INFO | Train Epoch: 12 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.10885 (0.13094) Boundary_loss: 0.014872 (0.014925) Loss: 0.12373 (0.14586) +2025-08-24,19:07:50 | INFO | Train Epoch: 12 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.12006 (0.13081) Boundary_loss: 0.015022 (0.014926) Loss: 0.13508 (0.14573) +2025-08-24,19:08:46 | INFO | Train Epoch: 12 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.12551 (0.13074) Boundary_loss: 0.014812 (0.014924) Loss: 0.14032 (0.14567) +2025-08-24,19:09:43 | INFO | Train Epoch: 12 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 49.287 Boundary Ratio: 0.251 Contrastive_loss: 0.14738 (0.13094) Boundary_loss: 0.014981 (0.014925) Loss: 0.16236 (0.14586) +2025-08-24,19:10:39 | INFO | Train Epoch: 12 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.19392 (0.13167) Boundary_loss: 0.014841 (0.014924) Loss: 0.20876 (0.14660) +2025-08-24,19:11:36 | INFO | Train Epoch: 12 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.11985 (0.13154) Boundary_loss: 0.014840 (0.014923) Loss: 0.13469 (0.14646) +2025-08-24,19:12:32 | INFO | Train Epoch: 12 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.605 Boundary Ratio: 0.248 Contrastive_loss: 0.11444 (0.13134) Boundary_loss: 0.014843 (0.014922) Loss: 0.12929 (0.14626) +2025-08-24,19:13:28 | INFO | Train Epoch: 12 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.14244 (0.13147) Boundary_loss: 0.014870 (0.014922) Loss: 0.15731 (0.14639) +2025-08-24,19:14:25 | INFO | Train Epoch: 12 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.13759 (0.13153) Boundary_loss: 0.014875 (0.014921) Loss: 0.15247 (0.14645) +2025-08-24,19:15:21 | INFO | Train Epoch: 12 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.13012 (0.13152) Boundary_loss: 0.014883 (0.014921) Loss: 0.14500 (0.14644) +2025-08-24,19:16:17 | INFO | Train Epoch: 12 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.10024 (0.13118) Boundary_loss: 0.014941 (0.014921) Loss: 0.11518 (0.14610) +2025-08-24,19:17:13 | INFO | Train Epoch: 12 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.439 Boundary Ratio: 0.247 Contrastive_loss: 0.13937 (0.13127) Boundary_loss: 0.014938 (0.014921) Loss: 0.15431 (0.14619) +2025-08-24,19:18:10 | INFO | Train Epoch: 12 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.10944 (0.13103) Boundary_loss: 0.014871 (0.014921) Loss: 0.12431 (0.14595) +2025-08-24,19:19:06 | INFO | Train Epoch: 12 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.18181 (0.13157) Boundary_loss: 0.014834 (0.014920) Loss: 0.19664 (0.14649) +2025-08-24,19:20:02 | INFO | Train Epoch: 12 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.12649 (0.13152) Boundary_loss: 0.014916 (0.014920) Loss: 0.14140 (0.14644) +2025-08-24,19:20:58 | INFO | Train Epoch: 12 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.11868 (0.13138) Boundary_loss: 0.015029 (0.014921) Loss: 0.13371 (0.14630) +2025-08-24,19:21:55 | INFO | Train Epoch: 12 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.12800 (0.13135) Boundary_loss: 0.014959 (0.014921) Loss: 0.14296 (0.14627) +2025-08-24,19:22:51 | INFO | Train Epoch: 12 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.11418 (0.13118) Boundary_loss: 0.014951 (0.014921) Loss: 0.12913 (0.14610) +2025-08-24,19:23:47 | INFO | Train Epoch: 12 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.14151 (0.13128) Boundary_loss: 0.014811 (0.014920) Loss: 0.15632 (0.14620) +2025-08-24,19:24:44 | INFO | Train Epoch: 12 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.10614 (0.13103) Boundary_loss: 0.014908 (0.014920) Loss: 0.12105 (0.14595) +2025-08-24,19:25:40 | INFO | Train Epoch: 12 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.13453 (0.13106) Boundary_loss: 0.014974 (0.014921) Loss: 0.14950 (0.14598) +2025-08-24,19:26:36 | INFO | Train Epoch: 12 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.12855 (0.13104) Boundary_loss: 0.014886 (0.014920) Loss: 0.14344 (0.14596) +2025-08-24,19:27:33 | INFO | Train Epoch: 12 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.275 Boundary Ratio: 0.246 Contrastive_loss: 0.14616 (0.13118) Boundary_loss: 0.014912 (0.014920) Loss: 0.16107 (0.14611) +2025-08-24,19:28:29 | INFO | Train Epoch: 12 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.13833 (0.13125) Boundary_loss: 0.014844 (0.014920) Loss: 0.15318 (0.14617) +2025-08-24,19:29:25 | INFO | Train Epoch: 12 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.16450 (0.13157) Boundary_loss: 0.014842 (0.014919) Loss: 0.17934 (0.14649) +2025-08-24,19:30:21 | INFO | Train Epoch: 12 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.14273 (0.13167) Boundary_loss: 0.014935 (0.014919) Loss: 0.15767 (0.14659) +2025-08-24,19:31:18 | INFO | Train Epoch: 12 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 0.11513 (0.13152) Boundary_loss: 0.014940 (0.014919) Loss: 0.13007 (0.14644) +2025-08-24,19:32:14 | INFO | Train Epoch: 12 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 49.328 Boundary Ratio: 0.252 Contrastive_loss: 0.097238 (0.13120) Boundary_loss: 0.014984 (0.014920) Loss: 0.11222 (0.14612) +2025-08-24,19:33:11 | INFO | Train Epoch: 12 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.10448 (0.13096) Boundary_loss: 0.014910 (0.014920) Loss: 0.11939 (0.14588) +2025-08-24,19:34:07 | INFO | Train Epoch: 12 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.15458 (0.13117) Boundary_loss: 0.014909 (0.014920) Loss: 0.16949 (0.14609) +2025-08-24,19:35:04 | INFO | Train Epoch: 12 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.13246 (0.13118) Boundary_loss: 0.014852 (0.014919) Loss: 0.14731 (0.14610) +2025-08-24,19:36:00 | INFO | Train Epoch: 12 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.11056 (0.13100) Boundary_loss: 0.014833 (0.014918) Loss: 0.12539 (0.14592) +2025-08-24,19:36:56 | INFO | Train Epoch: 12 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.15368 (0.13120) Boundary_loss: 0.015061 (0.014920) Loss: 0.16874 (0.14612) +2025-08-24,19:37:53 | INFO | Train Epoch: 12 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.14051 (0.13128) Boundary_loss: 0.014909 (0.014919) Loss: 0.15542 (0.14620) +2025-08-24,19:38:49 | INFO | Train Epoch: 12 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.14229 (0.13138) Boundary_loss: 0.014894 (0.014919) Loss: 0.15718 (0.14630) +2025-08-24,19:39:46 | INFO | Train Epoch: 12 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.12435 (0.13132) Boundary_loss: 0.014985 (0.014920) Loss: 0.13933 (0.14624) +2025-08-24,19:40:42 | INFO | Train Epoch: 12 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.11512 (0.13118) Boundary_loss: 0.014782 (0.014919) Loss: 0.12990 (0.14610) +2025-08-24,19:41:39 | INFO | Train Epoch: 12 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.416 Boundary Ratio: 0.247 Contrastive_loss: 0.14903 (0.13133) Boundary_loss: 0.015128 (0.014920) Loss: 0.16416 (0.14625) +2025-08-24,19:42:35 | INFO | Train Epoch: 12 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.19856 (0.13189) Boundary_loss: 0.014867 (0.014920) Loss: 0.21343 (0.14681) +2025-08-24,19:43:32 | INFO | Train Epoch: 12 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11681 (0.13177) Boundary_loss: 0.014866 (0.014919) Loss: 0.13168 (0.14668) +2025-08-24,19:44:28 | INFO | Train Epoch: 12 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.12966 (0.13175) Boundary_loss: 0.014919 (0.014919) Loss: 0.14458 (0.14667) +2025-08-24,19:45:24 | INFO | Train Epoch: 12 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.572 Boundary Ratio: 0.248 Contrastive_loss: 0.12776 (0.13172) Boundary_loss: 0.015022 (0.014920) Loss: 0.14278 (0.14664) +2025-08-24,19:46:21 | INFO | Train Epoch: 12 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.12021 (0.13162) Boundary_loss: 0.014780 (0.014919) Loss: 0.13499 (0.14654) +2025-08-24,19:47:17 | INFO | Train Epoch: 12 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.13994 (0.13169) Boundary_loss: 0.014901 (0.014919) Loss: 0.15484 (0.14661) +2025-08-24,19:48:13 | INFO | Train Epoch: 12 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.14650 (0.13181) Boundary_loss: 0.014925 (0.014919) Loss: 0.16143 (0.14673) +2025-08-24,19:49:10 | INFO | Train Epoch: 12 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.093131 (0.13150) Boundary_loss: 0.014847 (0.014919) Loss: 0.10798 (0.14642) +2025-08-24,19:50:06 | INFO | Train Epoch: 12 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.10064 (0.13126) Boundary_loss: 0.015013 (0.014919) Loss: 0.11565 (0.14618) +2025-08-24,19:51:03 | INFO | Train Epoch: 12 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.13529 (0.13129) Boundary_loss: 0.014927 (0.014919) Loss: 0.15021 (0.14621) +2025-08-24,19:51:59 | INFO | Train Epoch: 12 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.262 Boundary Ratio: 0.246 Contrastive_loss: 0.11553 (0.13117) Boundary_loss: 0.014933 (0.014919) Loss: 0.13046 (0.14609) +2025-08-24,19:52:56 | INFO | Train Epoch: 12 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.12042 (0.13109) Boundary_loss: 0.014971 (0.014920) Loss: 0.13539 (0.14601) +2025-08-24,19:53:52 | INFO | Train Epoch: 12 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.984 Boundary Ratio: 0.250 Contrastive_loss: 0.12634 (0.13105) Boundary_loss: 0.015055 (0.014921) Loss: 0.14139 (0.14597) +2025-08-24,19:54:48 | INFO | Train Epoch: 12 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.10507 (0.13086) Boundary_loss: 0.015018 (0.014922) Loss: 0.12009 (0.14578) +2025-08-24,19:55:45 | INFO | Train Epoch: 12 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.093927 (0.13058) Boundary_loss: 0.014859 (0.014921) Loss: 0.10879 (0.14550) +2025-08-24,19:56:41 | INFO | Train Epoch: 12 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.14812 (0.13071) Boundary_loss: 0.014861 (0.014921) Loss: 0.16298 (0.14563) +2025-08-24,19:57:38 | INFO | Train Epoch: 12 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.10666 (0.13054) Boundary_loss: 0.014904 (0.014921) Loss: 0.12156 (0.14546) +2025-08-24,19:58:34 | INFO | Train Epoch: 12 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.13033 (0.13053) Boundary_loss: 0.014799 (0.014920) Loss: 0.14513 (0.14545) +2025-08-24,19:59:31 | INFO | Train Epoch: 12 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10903 (0.13038) Boundary_loss: 0.014927 (0.014920) Loss: 0.12396 (0.14530) +2025-08-24,20:00:27 | INFO | Train Epoch: 12 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.11776 (0.13029) Boundary_loss: 0.015036 (0.014921) Loss: 0.13280 (0.14521) +2025-08-24,20:01:23 | INFO | Train Epoch: 12 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.11940 (0.13021) Boundary_loss: 0.014891 (0.014920) Loss: 0.13429 (0.14513) +2025-08-24,20:02:20 | INFO | Train Epoch: 12 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.10260 (0.13001) Boundary_loss: 0.014972 (0.014921) Loss: 0.11758 (0.14493) +2025-08-24,20:03:16 | INFO | Train Epoch: 12 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.10679 (0.12985) Boundary_loss: 0.014870 (0.014920) Loss: 0.12166 (0.14477) +2025-08-24,20:04:13 | INFO | Train Epoch: 12 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.12504 (0.12982) Boundary_loss: 0.014920 (0.014920) Loss: 0.13996 (0.14474) +2025-08-24,20:05:09 | INFO | Train Epoch: 12 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.13350 (0.12984) Boundary_loss: 0.014920 (0.014920) Loss: 0.14842 (0.14476) +2025-08-24,20:06:05 | INFO | Train Epoch: 12 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.12588 (0.12981) Boundary_loss: 0.014940 (0.014920) Loss: 0.14082 (0.14473) +2025-08-24,20:07:02 | INFO | Train Epoch: 12 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.13361 (0.12984) Boundary_loss: 0.014998 (0.014921) Loss: 0.14861 (0.14476) +2025-08-24,20:07:58 | INFO | Train Epoch: 12 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.14120 (0.12992) Boundary_loss: 0.014942 (0.014921) Loss: 0.15615 (0.14484) +2025-08-24,20:08:54 | INFO | Train Epoch: 12 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.13537 (0.12995) Boundary_loss: 0.014869 (0.014921) Loss: 0.15024 (0.14488) +2025-08-24,20:09:51 | INFO | Train Epoch: 12 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.12265 (0.12991) Boundary_loss: 0.014951 (0.014921) Loss: 0.13760 (0.14483) +2025-08-24,20:10:47 | INFO | Train Epoch: 12 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.10195 (0.12972) Boundary_loss: 0.014871 (0.014921) Loss: 0.11682 (0.14464) +2025-08-24,20:11:44 | INFO | Train Epoch: 12 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.17678 (0.13003) Boundary_loss: 0.014902 (0.014921) Loss: 0.19168 (0.14495) +2025-08-24,20:12:40 | INFO | Train Epoch: 12 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.10538 (0.12987) Boundary_loss: 0.014956 (0.014921) Loss: 0.12034 (0.14479) +2025-08-24,20:13:36 | INFO | Train Epoch: 12 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 49.217 Boundary Ratio: 0.251 Contrastive_loss: 0.12514 (0.12984) Boundary_loss: 0.014974 (0.014921) Loss: 0.14012 (0.14476) +2025-08-24,20:14:33 | INFO | Train Epoch: 12 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.17261 (0.13012) Boundary_loss: 0.014966 (0.014921) Loss: 0.18758 (0.14504) +2025-08-24,20:15:29 | INFO | Train Epoch: 12 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.13066 (0.13012) Boundary_loss: 0.014986 (0.014922) Loss: 0.14564 (0.14504) +2025-08-24,20:16:26 | INFO | Train Epoch: 12 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.13156 (0.13013) Boundary_loss: 0.014931 (0.014922) Loss: 0.14649 (0.14505) +2025-08-24,20:17:22 | INFO | Train Epoch: 12 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.12731 (0.13011) Boundary_loss: 0.015041 (0.014923) Loss: 0.14235 (0.14503) +2025-08-24,20:18:19 | INFO | Train Epoch: 12 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.13731 (0.13016) Boundary_loss: 0.014867 (0.014922) Loss: 0.15218 (0.14508) +2025-08-24,20:19:15 | INFO | Train Epoch: 12 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 49.109 Boundary Ratio: 0.251 Contrastive_loss: 0.16266 (0.13036) Boundary_loss: 0.014921 (0.014922) Loss: 0.17759 (0.14528) +2025-08-24,20:20:11 | INFO | Train Epoch: 12 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.443 Boundary Ratio: 0.247 Contrastive_loss: 0.18328 (0.13069) Boundary_loss: 0.014952 (0.014922) Loss: 0.19823 (0.14561) +2025-08-24,20:21:08 | INFO | Train Epoch: 12 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.13134 (0.13070) Boundary_loss: 0.014811 (0.014922) Loss: 0.14615 (0.14562) +2025-08-24,20:22:04 | INFO | Train Epoch: 12 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.12669 (0.13067) Boundary_loss: 0.014939 (0.014922) Loss: 0.14163 (0.14559) +2025-08-24,20:23:00 | INFO | Train Epoch: 12 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.10874 (0.13054) Boundary_loss: 0.014850 (0.014921) Loss: 0.12359 (0.14546) +2025-08-24,20:23:57 | INFO | Train Epoch: 12 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.451 Boundary Ratio: 0.252 Contrastive_loss: 0.11256 (0.13043) Boundary_loss: 0.014835 (0.014921) Loss: 0.12739 (0.14535) +2025-08-24,20:24:53 | INFO | Train Epoch: 12 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.15685 (0.13059) Boundary_loss: 0.014850 (0.014920) Loss: 0.17170 (0.14551) +2025-08-24,20:25:50 | INFO | Train Epoch: 12 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.186 Boundary Ratio: 0.251 Contrastive_loss: 0.17069 (0.13083) Boundary_loss: 0.015071 (0.014921) Loss: 0.18576 (0.14575) +2025-08-24,20:26:46 | INFO | Train Epoch: 12 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.520 Boundary Ratio: 0.248 Contrastive_loss: 0.15024 (0.13094) Boundary_loss: 0.014851 (0.014921) Loss: 0.16509 (0.14587) +2025-08-24,20:27:43 | INFO | Train Epoch: 12 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.11020 (0.13082) Boundary_loss: 0.014797 (0.014920) Loss: 0.12499 (0.14574) +2025-08-24,20:28:39 | INFO | Train Epoch: 12 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.434 Boundary Ratio: 0.247 Contrastive_loss: 0.091185 (0.13059) Boundary_loss: 0.014964 (0.014920) Loss: 0.10615 (0.14551) +2025-08-24,20:29:36 | INFO | Train Epoch: 12 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.13089 (0.13059) Boundary_loss: 0.014942 (0.014921) Loss: 0.14583 (0.14551) +2025-08-24,20:30:32 | INFO | Train Epoch: 12 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.12512 (0.13056) Boundary_loss: 0.014812 (0.014920) Loss: 0.13993 (0.14548) +2025-08-24,20:31:28 | INFO | Train Epoch: 12 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.15367 (0.13069) Boundary_loss: 0.014983 (0.014920) Loss: 0.16866 (0.14561) +2025-08-24,20:32:25 | INFO | Train Epoch: 12 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.15195 (0.13081) Boundary_loss: 0.014892 (0.014920) Loss: 0.16684 (0.14573) +2025-08-24,20:33:21 | INFO | Train Epoch: 12 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.10967 (0.13069) Boundary_loss: 0.014899 (0.014920) Loss: 0.12457 (0.14561) +2025-08-24,20:34:18 | INFO | Train Epoch: 12 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.087683 (0.13045) Boundary_loss: 0.014894 (0.014920) Loss: 0.10258 (0.14537) +2025-08-24,20:35:14 | INFO | Train Epoch: 12 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.12762 (0.13043) Boundary_loss: 0.015057 (0.014921) Loss: 0.14268 (0.14535) +2025-08-24,20:36:11 | INFO | Train Epoch: 12 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.13636 (0.13046) Boundary_loss: 0.014934 (0.014921) Loss: 0.15129 (0.14538) +2025-08-24,20:37:07 | INFO | Train Epoch: 12 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 49.033 Boundary Ratio: 0.250 Contrastive_loss: 0.093843 (0.13026) Boundary_loss: 0.014883 (0.014921) Loss: 0.10873 (0.14518) +2025-08-24,20:38:03 | INFO | Train Epoch: 12 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.324 Boundary Ratio: 0.247 Contrastive_loss: 0.12956 (0.13025) Boundary_loss: 0.014946 (0.014921) Loss: 0.14450 (0.14517) +2025-08-24,20:39:00 | INFO | Train Epoch: 12 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.14474 (0.13033) Boundary_loss: 0.015007 (0.014921) Loss: 0.15975 (0.14526) +2025-08-24,20:39:56 | INFO | Train Epoch: 12 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.10842 (0.13021) Boundary_loss: 0.014876 (0.014921) Loss: 0.12330 (0.14513) +2025-08-24,20:40:53 | INFO | Train Epoch: 12 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.15893 (0.13037) Boundary_loss: 0.014959 (0.014921) Loss: 0.17389 (0.14529) +2025-08-24,20:41:49 | INFO | Train Epoch: 12 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.13066 (0.13037) Boundary_loss: 0.014921 (0.014921) Loss: 0.14558 (0.14529) +2025-08-24,20:42:46 | INFO | Train Epoch: 12 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.13098 (0.13038) Boundary_loss: 0.015070 (0.014922) Loss: 0.14606 (0.14530) +2025-08-24,20:43:42 | INFO | Train Epoch: 12 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 49.230 Boundary Ratio: 0.251 Contrastive_loss: 0.11161 (0.13027) Boundary_loss: 0.014905 (0.014922) Loss: 0.12652 (0.14520) +2025-08-24,20:44:39 | INFO | Train Epoch: 12 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.098001 (0.13010) Boundary_loss: 0.014792 (0.014921) Loss: 0.11279 (0.14502) +2025-08-24,20:45:35 | INFO | Train Epoch: 12 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.11896 (0.13004) Boundary_loss: 0.014953 (0.014921) Loss: 0.13391 (0.14496) +2025-08-24,20:46:31 | INFO | Train Epoch: 12 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.14223 (0.13011) Boundary_loss: 0.014890 (0.014921) Loss: 0.15712 (0.14503) +2025-08-24,20:47:28 | INFO | Train Epoch: 12 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.13449 (0.13013) Boundary_loss: 0.014945 (0.014921) Loss: 0.14943 (0.14505) +2025-08-24,20:48:24 | INFO | Train Epoch: 12 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 49.037 Boundary Ratio: 0.250 Contrastive_loss: 0.13183 (0.13014) Boundary_loss: 0.015036 (0.014922) Loss: 0.14687 (0.14506) +2025-08-24,20:49:21 | INFO | Train Epoch: 12 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.12307 (0.13010) Boundary_loss: 0.014779 (0.014921) Loss: 0.13785 (0.14502) +2025-08-24,20:50:17 | INFO | Train Epoch: 12 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.500 Boundary Ratio: 0.247 Contrastive_loss: 0.097993 (0.12993) Boundary_loss: 0.014907 (0.014921) Loss: 0.11290 (0.14486) +2025-08-24,20:51:13 | INFO | Train Epoch: 12 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.10647 (0.12981) Boundary_loss: 0.014814 (0.014920) Loss: 0.12128 (0.14473) +2025-08-24,20:52:10 | INFO | Train Epoch: 12 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.10410 (0.12968) Boundary_loss: 0.014935 (0.014921) Loss: 0.11903 (0.14460) +2025-08-24,20:53:06 | INFO | Train Epoch: 12 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.11437 (0.12960) Boundary_loss: 0.014833 (0.014920) Loss: 0.12921 (0.14452) +2025-08-24,20:54:03 | INFO | Train Epoch: 12 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.10459 (0.12947) Boundary_loss: 0.014943 (0.014920) Loss: 0.11953 (0.14439) +2025-08-24,20:54:59 | INFO | Train Epoch: 12 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.13092 (0.12948) Boundary_loss: 0.015000 (0.014921) Loss: 0.14592 (0.14440) +2025-08-24,20:55:55 | INFO | Train Epoch: 12 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.14277 (0.12955) Boundary_loss: 0.014930 (0.014921) Loss: 0.15770 (0.14447) +2025-08-24,20:56:52 | INFO | Train Epoch: 12 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.16612 (0.12973) Boundary_loss: 0.014864 (0.014920) Loss: 0.18099 (0.14465) +2025-08-24,20:57:48 | INFO | Train Epoch: 12 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.11134 (0.12964) Boundary_loss: 0.014957 (0.014921) Loss: 0.12629 (0.14456) +2025-08-24,20:58:45 | INFO | Train Epoch: 12 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.15294 (0.12976) Boundary_loss: 0.014898 (0.014920) Loss: 0.16784 (0.14468) +2025-08-24,20:59:41 | INFO | Train Epoch: 12 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.13073 (0.12976) Boundary_loss: 0.015000 (0.014921) Loss: 0.14573 (0.14468) +2025-08-24,21:00:38 | INFO | Train Epoch: 12 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11201 (0.12967) Boundary_loss: 0.014959 (0.014921) Loss: 0.12697 (0.14459) +2025-08-24,21:01:34 | INFO | Train Epoch: 12 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.15161 (0.12978) Boundary_loss: 0.014885 (0.014921) Loss: 0.16650 (0.14470) +2025-08-24,21:02:30 | INFO | Train Epoch: 12 [10445312/26365952 (40%)] Avg Boundaries (per batch): 49.283 Boundary Ratio: 0.251 Contrastive_loss: 0.097071 (0.12962) Boundary_loss: 0.014931 (0.014921) Loss: 0.11200 (0.14454) +2025-08-24,21:03:27 | INFO | Train Epoch: 12 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.14154 (0.12968) Boundary_loss: 0.014884 (0.014921) Loss: 0.15642 (0.14460) +2025-08-24,21:04:24 | INFO | Train Epoch: 12 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.12489 (0.12966) Boundary_loss: 0.015053 (0.014921) Loss: 0.13994 (0.14458) +2025-08-24,21:05:20 | INFO | Train Epoch: 12 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.16472 (0.12982) Boundary_loss: 0.014870 (0.014921) Loss: 0.17959 (0.14475) +2025-08-24,21:06:16 | INFO | Train Epoch: 12 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.14158 (0.12988) Boundary_loss: 0.014989 (0.014921) Loss: 0.15657 (0.14480) +2025-08-24,21:07:13 | INFO | Train Epoch: 12 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.12180 (0.12984) Boundary_loss: 0.014824 (0.014921) Loss: 0.13663 (0.14476) +2025-08-24,21:08:09 | INFO | Train Epoch: 12 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.482 Boundary Ratio: 0.247 Contrastive_loss: 0.15375 (0.12996) Boundary_loss: 0.014946 (0.014921) Loss: 0.16870 (0.14488) +2025-08-24,21:09:06 | INFO | Train Epoch: 12 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13118 (0.12996) Boundary_loss: 0.014856 (0.014921) Loss: 0.14604 (0.14488) +2025-08-24,21:10:02 | INFO | Train Epoch: 12 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.12725 (0.12995) Boundary_loss: 0.014928 (0.014921) Loss: 0.14218 (0.14487) +2025-08-24,21:10:59 | INFO | Train Epoch: 12 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.12621 (0.12993) Boundary_loss: 0.014860 (0.014921) Loss: 0.14106 (0.14485) +2025-08-24,21:11:55 | INFO | Train Epoch: 12 [10957312/26365952 (42%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.15829 (0.13006) Boundary_loss: 0.015006 (0.014921) Loss: 0.17330 (0.14498) +2025-08-24,21:12:52 | INFO | Train Epoch: 12 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.15756 (0.13019) Boundary_loss: 0.014955 (0.014921) Loss: 0.17251 (0.14511) +2025-08-24,21:13:48 | INFO | Train Epoch: 12 [11059712/26365952 (42%)] Avg Boundaries (per batch): 49.164 Boundary Ratio: 0.251 Contrastive_loss: 0.12616 (0.13017) Boundary_loss: 0.015078 (0.014922) Loss: 0.14123 (0.14509) +2025-08-24,21:14:45 | INFO | Train Epoch: 12 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.14023 (0.13022) Boundary_loss: 0.015087 (0.014923) Loss: 0.15531 (0.14514) +2025-08-24,21:15:41 | INFO | Train Epoch: 12 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.15217 (0.13032) Boundary_loss: 0.014919 (0.014923) Loss: 0.16709 (0.14524) +2025-08-24,21:16:38 | INFO | Train Epoch: 12 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.15287 (0.13042) Boundary_loss: 0.014717 (0.014922) Loss: 0.16759 (0.14534) +2025-08-24,21:17:34 | INFO | Train Epoch: 12 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.10569 (0.13031) Boundary_loss: 0.014878 (0.014921) Loss: 0.12057 (0.14523) +2025-08-24,21:18:31 | INFO | Train Epoch: 12 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.14148 (0.13036) Boundary_loss: 0.014928 (0.014921) Loss: 0.15641 (0.14528) +2025-08-24,21:19:27 | INFO | Train Epoch: 12 [11366912/26365952 (43%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.10221 (0.13023) Boundary_loss: 0.014800 (0.014921) Loss: 0.11701 (0.14515) +2025-08-24,21:20:23 | INFO | Train Epoch: 12 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.13998 (0.13028) Boundary_loss: 0.014813 (0.014920) Loss: 0.15479 (0.14520) +2025-08-24,21:21:20 | INFO | Train Epoch: 12 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.12185 (0.13024) Boundary_loss: 0.014809 (0.014920) Loss: 0.13666 (0.14516) +2025-08-24,21:22:16 | INFO | Train Epoch: 12 [11520512/26365952 (44%)] Avg Boundaries (per batch): 49.195 Boundary Ratio: 0.251 Contrastive_loss: 0.10743 (0.13014) Boundary_loss: 0.014877 (0.014920) Loss: 0.12231 (0.14506) +2025-08-24,21:23:13 | INFO | Train Epoch: 12 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.17041 (0.13032) Boundary_loss: 0.014942 (0.014920) Loss: 0.18535 (0.14524) +2025-08-24,21:24:09 | INFO | Train Epoch: 12 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.11762 (0.13026) Boundary_loss: 0.014888 (0.014920) Loss: 0.13251 (0.14518) +2025-08-24,21:25:06 | INFO | Train Epoch: 12 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.11138 (0.13018) Boundary_loss: 0.014886 (0.014920) Loss: 0.12626 (0.14510) +2025-08-24,21:26:02 | INFO | Train Epoch: 12 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.12967 (0.13018) Boundary_loss: 0.014874 (0.014919) Loss: 0.14454 (0.14509) +2025-08-24,21:26:59 | INFO | Train Epoch: 12 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.12126 (0.13014) Boundary_loss: 0.014950 (0.014920) Loss: 0.13621 (0.14506) +2025-08-24,21:27:55 | INFO | Train Epoch: 12 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.516 Boundary Ratio: 0.248 Contrastive_loss: 0.16102 (0.13027) Boundary_loss: 0.014887 (0.014919) Loss: 0.17591 (0.14519) +2025-08-24,21:28:52 | INFO | Train Epoch: 12 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.10303 (0.13015) Boundary_loss: 0.014977 (0.014920) Loss: 0.11801 (0.14507) +2025-08-24,21:29:48 | INFO | Train Epoch: 12 [11930112/26365952 (45%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.094178 (0.13000) Boundary_loss: 0.014912 (0.014920) Loss: 0.10909 (0.14492) +2025-08-24,21:30:45 | INFO | Train Epoch: 12 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.11340 (0.12993) Boundary_loss: 0.014973 (0.014920) Loss: 0.12837 (0.14485) +2025-08-24,21:31:41 | INFO | Train Epoch: 12 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.330 Boundary Ratio: 0.247 Contrastive_loss: 0.085805 (0.12974) Boundary_loss: 0.014912 (0.014920) Loss: 0.10072 (0.14466) +2025-08-24,21:32:38 | INFO | Train Epoch: 12 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.12532 (0.12972) Boundary_loss: 0.014904 (0.014920) Loss: 0.14022 (0.14464) +2025-08-24,21:33:34 | INFO | Train Epoch: 12 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.11238 (0.12965) Boundary_loss: 0.014834 (0.014919) Loss: 0.12721 (0.14457) +2025-08-24,21:34:31 | INFO | Train Epoch: 12 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.11088 (0.12957) Boundary_loss: 0.014903 (0.014919) Loss: 0.12578 (0.14449) +2025-08-24,21:35:27 | INFO | Train Epoch: 12 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.11821 (0.12952) Boundary_loss: 0.014874 (0.014919) Loss: 0.13309 (0.14444) +2025-08-24,21:36:24 | INFO | Train Epoch: 12 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.11424 (0.12946) Boundary_loss: 0.014915 (0.014919) Loss: 0.12916 (0.14438) +2025-08-24,21:37:20 | INFO | Train Epoch: 12 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.16059 (0.12959) Boundary_loss: 0.014880 (0.014919) Loss: 0.17547 (0.14451) +2025-08-24,21:38:17 | INFO | Train Epoch: 12 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.521 Boundary Ratio: 0.248 Contrastive_loss: 0.13333 (0.12960) Boundary_loss: 0.014935 (0.014919) Loss: 0.14827 (0.14452) +2025-08-24,21:39:13 | INFO | Train Epoch: 12 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.11152 (0.12953) Boundary_loss: 0.014978 (0.014919) Loss: 0.12650 (0.14445) +2025-08-24,21:40:10 | INFO | Train Epoch: 12 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.15501 (0.12963) Boundary_loss: 0.014989 (0.014920) Loss: 0.17000 (0.14455) +2025-08-24,21:41:06 | INFO | Train Epoch: 12 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.11122 (0.12956) Boundary_loss: 0.014928 (0.014920) Loss: 0.12615 (0.14448) +2025-08-24,21:42:02 | INFO | Train Epoch: 12 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.12906 (0.12956) Boundary_loss: 0.014974 (0.014920) Loss: 0.14404 (0.14448) +2025-08-24,21:42:59 | INFO | Train Epoch: 12 [12646912/26365952 (48%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.11292 (0.12949) Boundary_loss: 0.014797 (0.014919) Loss: 0.12771 (0.14441) +2025-08-24,21:43:55 | INFO | Train Epoch: 12 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.13078 (0.12950) Boundary_loss: 0.014849 (0.014919) Loss: 0.14563 (0.14441) +2025-08-24,21:44:52 | INFO | Train Epoch: 12 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 0.11198 (0.12943) Boundary_loss: 0.014899 (0.014919) Loss: 0.12688 (0.14434) +2025-08-24,21:45:48 | INFO | Train Epoch: 12 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.14856 (0.12950) Boundary_loss: 0.014926 (0.014919) Loss: 0.16349 (0.14442) +2025-08-24,21:46:45 | INFO | Train Epoch: 12 [12851712/26365952 (49%)] Avg Boundaries (per batch): 49.199 Boundary Ratio: 0.251 Contrastive_loss: 0.14153 (0.12955) Boundary_loss: 0.014940 (0.014919) Loss: 0.15647 (0.14447) +2025-08-24,21:47:41 | INFO | Train Epoch: 12 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.12073 (0.12951) Boundary_loss: 0.014882 (0.014919) Loss: 0.13561 (0.14443) +2025-08-24,21:48:38 | INFO | Train Epoch: 12 [12954112/26365952 (49%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.20640 (0.12982) Boundary_loss: 0.014833 (0.014919) Loss: 0.22123 (0.14474) +2025-08-24,21:49:34 | INFO | Train Epoch: 12 [13005312/26365952 (49%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.12102 (0.12978) Boundary_loss: 0.014988 (0.014919) Loss: 0.13601 (0.14470) +2025-08-24,21:50:30 | INFO | Train Epoch: 12 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.097159 (0.12966) Boundary_loss: 0.014894 (0.014919) Loss: 0.11205 (0.14457) +2025-08-24,21:51:27 | INFO | Train Epoch: 12 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.492 Boundary Ratio: 0.247 Contrastive_loss: 0.12156 (0.12962) Boundary_loss: 0.014938 (0.014919) Loss: 0.13650 (0.14454) +2025-08-24,21:52:24 | INFO | Train Epoch: 12 [13158912/26365952 (50%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.10049 (0.12951) Boundary_loss: 0.014993 (0.014919) Loss: 0.11548 (0.14443) +2025-08-24,21:53:20 | INFO | Train Epoch: 12 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.13912 (0.12955) Boundary_loss: 0.014869 (0.014919) Loss: 0.15398 (0.14447) +2025-08-24,21:54:17 | INFO | Train Epoch: 12 [13261312/26365952 (50%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.12840 (0.12954) Boundary_loss: 0.014887 (0.014919) Loss: 0.14329 (0.14446) +2025-08-24,21:55:13 | INFO | Train Epoch: 12 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.15685 (0.12965) Boundary_loss: 0.014885 (0.014919) Loss: 0.17173 (0.14457) +2025-08-24,21:56:09 | INFO | Train Epoch: 12 [13363712/26365952 (51%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.12772 (0.12964) Boundary_loss: 0.014915 (0.014919) Loss: 0.14264 (0.14456) +2025-08-24,21:57:06 | INFO | Train Epoch: 12 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.11822 (0.12960) Boundary_loss: 0.014818 (0.014918) Loss: 0.13303 (0.14452) +2025-08-24,21:58:02 | INFO | Train Epoch: 12 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.10802 (0.12952) Boundary_loss: 0.014956 (0.014918) Loss: 0.12298 (0.14443) +2025-08-24,21:58:59 | INFO | Train Epoch: 12 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.469 Boundary Ratio: 0.247 Contrastive_loss: 0.089485 (0.12936) Boundary_loss: 0.014820 (0.014918) Loss: 0.10431 (0.14428) +2025-08-24,21:59:55 | INFO | Train Epoch: 12 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.13466 (0.12938) Boundary_loss: 0.014892 (0.014918) Loss: 0.14955 (0.14430) +2025-08-24,22:00:52 | INFO | Train Epoch: 12 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.11773 (0.12934) Boundary_loss: 0.014999 (0.014918) Loss: 0.13273 (0.14426) +2025-08-24,22:01:49 | INFO | Train Epoch: 12 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.13774 (0.12937) Boundary_loss: 0.014992 (0.014918) Loss: 0.15274 (0.14429) +2025-08-24,22:02:45 | INFO | Train Epoch: 12 [13722112/26365952 (52%)] Avg Boundaries (per batch): 49.238 Boundary Ratio: 0.251 Contrastive_loss: 0.14164 (0.12942) Boundary_loss: 0.014973 (0.014919) Loss: 0.15661 (0.14434) +2025-08-24,22:03:41 | INFO | Train Epoch: 12 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.091937 (0.12928) Boundary_loss: 0.014980 (0.014919) Loss: 0.10692 (0.14420) +2025-08-24,22:04:38 | INFO | Train Epoch: 12 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.13437 (0.12930) Boundary_loss: 0.014874 (0.014919) Loss: 0.14924 (0.14422) +2025-08-24,22:05:34 | INFO | Train Epoch: 12 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.091244 (0.12916) Boundary_loss: 0.014845 (0.014918) Loss: 0.10609 (0.14408) +2025-08-24,22:06:31 | INFO | Train Epoch: 12 [13926912/26365952 (53%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.11910 (0.12912) Boundary_loss: 0.015025 (0.014919) Loss: 0.13412 (0.14404) +2025-08-24,22:07:27 | INFO | Train Epoch: 12 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.11049 (0.12905) Boundary_loss: 0.014886 (0.014919) Loss: 0.12538 (0.14397) +2025-08-24,22:08:24 | INFO | Train Epoch: 12 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.11896 (0.12902) Boundary_loss: 0.014997 (0.014919) Loss: 0.13396 (0.14394) +2025-08-24,22:09:20 | INFO | Train Epoch: 12 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.096231 (0.12890) Boundary_loss: 0.014847 (0.014919) Loss: 0.11108 (0.14382) +2025-08-24,22:10:17 | INFO | Train Epoch: 12 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.11740 (0.12886) Boundary_loss: 0.014873 (0.014919) Loss: 0.13227 (0.14377) +2025-08-24,22:11:13 | INFO | Train Epoch: 12 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.13387 (0.12887) Boundary_loss: 0.014931 (0.014919) Loss: 0.14880 (0.14379) +2025-08-24,22:12:10 | INFO | Train Epoch: 12 [14234112/26365952 (54%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.12033 (0.12884) Boundary_loss: 0.014976 (0.014919) Loss: 0.13530 (0.14376) +2025-08-24,22:13:06 | INFO | Train Epoch: 12 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.12022 (0.12881) Boundary_loss: 0.014902 (0.014919) Loss: 0.13513 (0.14373) +2025-08-24,22:14:03 | INFO | Train Epoch: 12 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.367 Boundary Ratio: 0.247 Contrastive_loss: 0.14021 (0.12885) Boundary_loss: 0.014936 (0.014919) Loss: 0.15515 (0.14377) +2025-08-24,22:14:59 | INFO | Train Epoch: 12 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.11400 (0.12880) Boundary_loss: 0.014922 (0.014919) Loss: 0.12892 (0.14372) +2025-08-24,22:15:55 | INFO | Train Epoch: 12 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.14579 (0.12886) Boundary_loss: 0.014915 (0.014919) Loss: 0.16071 (0.14378) +2025-08-24,22:16:52 | INFO | Train Epoch: 12 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.402 Boundary Ratio: 0.247 Contrastive_loss: 0.10572 (0.12878) Boundary_loss: 0.014872 (0.014919) Loss: 0.12059 (0.14370) +2025-08-24,22:17:48 | INFO | Train Epoch: 12 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.10374 (0.12869) Boundary_loss: 0.014925 (0.014919) Loss: 0.11866 (0.14361) +2025-08-24,22:18:45 | INFO | Train Epoch: 12 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.12052 (0.12866) Boundary_loss: 0.014838 (0.014918) Loss: 0.13536 (0.14358) +2025-08-24,22:19:41 | INFO | Train Epoch: 12 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.16374 (0.12879) Boundary_loss: 0.014864 (0.014918) Loss: 0.17861 (0.14370) +2025-08-24,22:20:37 | INFO | Train Epoch: 12 [14694912/26365952 (56%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.11601 (0.12874) Boundary_loss: 0.014908 (0.014918) Loss: 0.13092 (0.14366) +2025-08-24,22:21:34 | INFO | Train Epoch: 12 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.12232 (0.12872) Boundary_loss: 0.014944 (0.014918) Loss: 0.13727 (0.14364) +2025-08-24,22:22:30 | INFO | Train Epoch: 12 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.14302 (0.12877) Boundary_loss: 0.014835 (0.014918) Loss: 0.15785 (0.14369) +2025-08-24,22:23:27 | INFO | Train Epoch: 12 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.14152 (0.12881) Boundary_loss: 0.014917 (0.014918) Loss: 0.15644 (0.14373) +2025-08-24,22:24:23 | INFO | Train Epoch: 12 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.14221 (0.12886) Boundary_loss: 0.014833 (0.014918) Loss: 0.15705 (0.14378) +2025-08-24,22:25:19 | INFO | Train Epoch: 12 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.088592 (0.12872) Boundary_loss: 0.015031 (0.014918) Loss: 0.10362 (0.14364) +2025-08-24,22:26:16 | INFO | Train Epoch: 12 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.10024 (0.12862) Boundary_loss: 0.014806 (0.014918) Loss: 0.11504 (0.14354) +2025-08-24,22:27:12 | INFO | Train Epoch: 12 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.12880 (0.12862) Boundary_loss: 0.014871 (0.014918) Loss: 0.14367 (0.14354) +2025-08-24,22:28:09 | INFO | Train Epoch: 12 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.10717 (0.12855) Boundary_loss: 0.014886 (0.014917) Loss: 0.12206 (0.14347) +2025-08-24,22:29:05 | INFO | Train Epoch: 12 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.13121 (0.12856) Boundary_loss: 0.014923 (0.014917) Loss: 0.14613 (0.14348) +2025-08-24,22:30:01 | INFO | Train Epoch: 12 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.12016 (0.12853) Boundary_loss: 0.014905 (0.014917) Loss: 0.13507 (0.14345) +2025-08-24,22:30:58 | INFO | Train Epoch: 12 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.11683 (0.12849) Boundary_loss: 0.014871 (0.014917) Loss: 0.13170 (0.14341) +2025-08-24,22:31:55 | INFO | Train Epoch: 12 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.12785 (0.12849) Boundary_loss: 0.014941 (0.014917) Loss: 0.14279 (0.14341) +2025-08-24,22:32:51 | INFO | Train Epoch: 12 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.408 Boundary Ratio: 0.247 Contrastive_loss: 0.11422 (0.12844) Boundary_loss: 0.014959 (0.014917) Loss: 0.12918 (0.14336) +2025-08-24,22:33:47 | INFO | Train Epoch: 12 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.11404 (0.12840) Boundary_loss: 0.014999 (0.014918) Loss: 0.12903 (0.14331) +2025-08-24,22:34:44 | INFO | Train Epoch: 12 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.11607 (0.12836) Boundary_loss: 0.014793 (0.014917) Loss: 0.13086 (0.14327) +2025-08-24,22:35:40 | INFO | Train Epoch: 12 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.12315 (0.12834) Boundary_loss: 0.015010 (0.014918) Loss: 0.13816 (0.14326) +2025-08-24,22:36:37 | INFO | Train Epoch: 12 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.14021 (0.12838) Boundary_loss: 0.014807 (0.014917) Loss: 0.15501 (0.14329) +2025-08-24,22:37:33 | INFO | Train Epoch: 12 [15616512/26365952 (59%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.13905 (0.12841) Boundary_loss: 0.014825 (0.014917) Loss: 0.15388 (0.14333) +2025-08-24,22:38:29 | INFO | Train Epoch: 12 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.10878 (0.12835) Boundary_loss: 0.014998 (0.014917) Loss: 0.12378 (0.14327) +2025-08-24,22:39:26 | INFO | Train Epoch: 12 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.099809 (0.12826) Boundary_loss: 0.014927 (0.014917) Loss: 0.11474 (0.14317) +2025-08-24,22:40:22 | INFO | Train Epoch: 12 [15770112/26365952 (60%)] Avg Boundaries (per batch): 49.244 Boundary Ratio: 0.251 Contrastive_loss: 0.14582 (0.12831) Boundary_loss: 0.014907 (0.014917) Loss: 0.16073 (0.14323) +2025-08-24,22:41:19 | INFO | Train Epoch: 12 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10528 (0.12824) Boundary_loss: 0.014918 (0.014917) Loss: 0.12020 (0.14316) +2025-08-24,22:42:15 | INFO | Train Epoch: 12 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.492 Boundary Ratio: 0.247 Contrastive_loss: 0.14090 (0.12828) Boundary_loss: 0.014867 (0.014917) Loss: 0.15576 (0.14320) +2025-08-24,22:43:11 | INFO | Train Epoch: 12 [15923712/26365952 (60%)] Avg Boundaries (per batch): 49.066 Boundary Ratio: 0.250 Contrastive_loss: 0.11442 (0.12823) Boundary_loss: 0.014872 (0.014917) Loss: 0.12929 (0.14315) +2025-08-24,22:44:08 | INFO | Train Epoch: 12 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.097629 (0.12814) Boundary_loss: 0.014926 (0.014917) Loss: 0.11256 (0.14305) +2025-08-24,22:45:04 | INFO | Train Epoch: 12 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.10795 (0.12807) Boundary_loss: 0.014955 (0.014917) Loss: 0.12291 (0.14299) +2025-08-24,22:46:01 | INFO | Train Epoch: 12 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.12875 (0.12807) Boundary_loss: 0.014935 (0.014917) Loss: 0.14368 (0.14299) +2025-08-24,22:46:57 | INFO | Train Epoch: 12 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.14625 (0.12813) Boundary_loss: 0.014978 (0.014917) Loss: 0.16123 (0.14305) +2025-08-24,22:47:53 | INFO | Train Epoch: 12 [16179712/26365952 (61%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.12318 (0.12812) Boundary_loss: 0.014779 (0.014917) Loss: 0.13796 (0.14303) +2025-08-24,22:48:50 | INFO | Train Epoch: 12 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.13062 (0.12812) Boundary_loss: 0.014867 (0.014917) Loss: 0.14549 (0.14304) +2025-08-24,22:49:46 | INFO | Train Epoch: 12 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.098122 (0.12803) Boundary_loss: 0.014956 (0.014917) Loss: 0.11308 (0.14295) +2025-08-24,22:50:43 | INFO | Train Epoch: 12 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.12566 (0.12802) Boundary_loss: 0.014944 (0.014917) Loss: 0.14061 (0.14294) +2025-08-24,22:51:39 | INFO | Train Epoch: 12 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.10459 (0.12795) Boundary_loss: 0.014893 (0.014917) Loss: 0.11948 (0.14287) +2025-08-24,22:52:35 | INFO | Train Epoch: 12 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.12951 (0.12795) Boundary_loss: 0.014905 (0.014917) Loss: 0.14441 (0.14287) +2025-08-24,22:53:32 | INFO | Train Epoch: 12 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.473 Boundary Ratio: 0.247 Contrastive_loss: 0.12767 (0.12795) Boundary_loss: 0.014923 (0.014917) Loss: 0.14260 (0.14287) +2025-08-24,22:54:28 | INFO | Train Epoch: 12 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.083581 (0.12782) Boundary_loss: 0.014926 (0.014917) Loss: 0.098507 (0.14273) +2025-08-24,22:55:25 | INFO | Train Epoch: 12 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.13934 (0.12785) Boundary_loss: 0.014835 (0.014917) Loss: 0.15417 (0.14277) +2025-08-24,22:56:21 | INFO | Train Epoch: 12 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.13931 (0.12789) Boundary_loss: 0.014838 (0.014916) Loss: 0.15414 (0.14280) +2025-08-24,22:57:17 | INFO | Train Epoch: 12 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.12998 (0.12789) Boundary_loss: 0.014845 (0.014916) Loss: 0.14483 (0.14281) +2025-08-24,22:58:14 | INFO | Train Epoch: 12 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.447 Boundary Ratio: 0.247 Contrastive_loss: 0.11914 (0.12787) Boundary_loss: 0.014876 (0.014916) Loss: 0.13402 (0.14278) +2025-08-24,22:59:10 | INFO | Train Epoch: 12 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.12819 (0.12787) Boundary_loss: 0.014901 (0.014916) Loss: 0.14310 (0.14278) +2025-08-24,23:00:06 | INFO | Train Epoch: 12 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.16485 (0.12798) Boundary_loss: 0.014855 (0.014916) Loss: 0.17971 (0.14290) +2025-08-24,23:01:03 | INFO | Train Epoch: 12 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.10468 (0.12791) Boundary_loss: 0.014890 (0.014916) Loss: 0.11956 (0.14283) +2025-08-24,23:01:59 | INFO | Train Epoch: 12 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.13979 (0.12795) Boundary_loss: 0.014919 (0.014916) Loss: 0.15471 (0.14286) +2025-08-24,23:02:56 | INFO | Train Epoch: 12 [16998912/26365952 (64%)] Avg Boundaries (per batch): 49.127 Boundary Ratio: 0.251 Contrastive_loss: 0.13203 (0.12796) Boundary_loss: 0.014884 (0.014916) Loss: 0.14692 (0.14287) +2025-08-24,23:03:52 | INFO | Train Epoch: 12 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.14697 (0.12801) Boundary_loss: 0.014977 (0.014916) Loss: 0.16195 (0.14293) +2025-08-24,23:04:48 | INFO | Train Epoch: 12 [17101312/26365952 (65%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.11611 (0.12798) Boundary_loss: 0.014984 (0.014916) Loss: 0.13109 (0.14289) +2025-08-24,23:05:45 | INFO | Train Epoch: 12 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11833 (0.12795) Boundary_loss: 0.014925 (0.014916) Loss: 0.13325 (0.14287) +2025-08-24,23:06:41 | INFO | Train Epoch: 12 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.15348 (0.12803) Boundary_loss: 0.014923 (0.014916) Loss: 0.16841 (0.14294) +2025-08-24,23:07:38 | INFO | Train Epoch: 12 [17254912/26365952 (65%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.10049 (0.12794) Boundary_loss: 0.014829 (0.014916) Loss: 0.11532 (0.14286) +2025-08-24,23:08:34 | INFO | Train Epoch: 12 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.014 Boundary Ratio: 0.250 Contrastive_loss: 0.16562 (0.12806) Boundary_loss: 0.014786 (0.014915) Loss: 0.18041 (0.14297) +2025-08-24,23:09:30 | INFO | Train Epoch: 12 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.12772 (0.12805) Boundary_loss: 0.014865 (0.014915) Loss: 0.14259 (0.14297) +2025-08-24,23:10:27 | INFO | Train Epoch: 12 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.13164 (0.12807) Boundary_loss: 0.015086 (0.014916) Loss: 0.14672 (0.14298) +2025-08-24,23:11:23 | INFO | Train Epoch: 12 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.10435 (0.12800) Boundary_loss: 0.014902 (0.014916) Loss: 0.11925 (0.14291) +2025-08-24,23:12:19 | INFO | Train Epoch: 12 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.13407 (0.12801) Boundary_loss: 0.014850 (0.014916) Loss: 0.14892 (0.14293) +2025-08-24,23:13:16 | INFO | Train Epoch: 12 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.143 Boundary Ratio: 0.251 Contrastive_loss: 0.13454 (0.12803) Boundary_loss: 0.014944 (0.014916) Loss: 0.14948 (0.14295) +2025-08-24,23:14:12 | INFO | Train Epoch: 12 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.12326 (0.12802) Boundary_loss: 0.014847 (0.014915) Loss: 0.13811 (0.14293) +2025-08-24,23:15:09 | INFO | Train Epoch: 12 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.10486 (0.12795) Boundary_loss: 0.014814 (0.014915) Loss: 0.11968 (0.14287) +2025-08-24,23:16:05 | INFO | Train Epoch: 12 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.10482 (0.12789) Boundary_loss: 0.014886 (0.014915) Loss: 0.11970 (0.14280) +2025-08-24,23:17:01 | INFO | Train Epoch: 12 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.10279 (0.12781) Boundary_loss: 0.014932 (0.014915) Loss: 0.11773 (0.14273) +2025-08-24,23:17:58 | INFO | Train Epoch: 12 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.11800 (0.12778) Boundary_loss: 0.014913 (0.014915) Loss: 0.13291 (0.14270) +2025-08-24,23:18:54 | INFO | Train Epoch: 12 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.13410 (0.12780) Boundary_loss: 0.014901 (0.014915) Loss: 0.14900 (0.14272) +2025-08-24,23:19:51 | INFO | Train Epoch: 12 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.11362 (0.12776) Boundary_loss: 0.014866 (0.014915) Loss: 0.12848 (0.14268) +2025-08-24,23:20:47 | INFO | Train Epoch: 12 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.13131 (0.12777) Boundary_loss: 0.014906 (0.014915) Loss: 0.14622 (0.14269) +2025-08-24,23:21:44 | INFO | Train Epoch: 12 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.10980 (0.12772) Boundary_loss: 0.014728 (0.014914) Loss: 0.12453 (0.14264) +2025-08-24,23:22:40 | INFO | Train Epoch: 12 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.13719 (0.12775) Boundary_loss: 0.014857 (0.014914) Loss: 0.15205 (0.14266) +2025-08-24,23:23:36 | INFO | Train Epoch: 12 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.11748 (0.12772) Boundary_loss: 0.014881 (0.014914) Loss: 0.13236 (0.14263) +2025-08-24,23:24:33 | INFO | Train Epoch: 12 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.10242 (0.12765) Boundary_loss: 0.014920 (0.014914) Loss: 0.11734 (0.14256) +2025-08-24,23:25:29 | INFO | Train Epoch: 12 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.074630 (0.12750) Boundary_loss: 0.014916 (0.014914) Loss: 0.089546 (0.14241) +2025-08-24,23:26:26 | INFO | Train Epoch: 12 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.16082 (0.12759) Boundary_loss: 0.014937 (0.014914) Loss: 0.17576 (0.14251) +2025-08-24,23:27:22 | INFO | Train Epoch: 12 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.082207 (0.12747) Boundary_loss: 0.014914 (0.014914) Loss: 0.097121 (0.14238) +2025-08-24,23:28:18 | INFO | Train Epoch: 12 [18381312/26365952 (70%)] Avg Boundaries (per batch): 49.109 Boundary Ratio: 0.251 Contrastive_loss: 0.12157 (0.12745) Boundary_loss: 0.014812 (0.014914) Loss: 0.13638 (0.14236) +2025-08-24,23:29:15 | INFO | Train Epoch: 12 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.13743 (0.12748) Boundary_loss: 0.014936 (0.014914) Loss: 0.15237 (0.14239) +2025-08-24,23:30:11 | INFO | Train Epoch: 12 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.14958 (0.12754) Boundary_loss: 0.014922 (0.014914) Loss: 0.16450 (0.14245) +2025-08-24,23:31:08 | INFO | Train Epoch: 12 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.12904 (0.12754) Boundary_loss: 0.014856 (0.014914) Loss: 0.14390 (0.14246) +2025-08-24,23:32:04 | INFO | Train Epoch: 12 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.11742 (0.12752) Boundary_loss: 0.014948 (0.014914) Loss: 0.13237 (0.14243) +2025-08-24,23:33:01 | INFO | Train Epoch: 12 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.15353 (0.12759) Boundary_loss: 0.014916 (0.014914) Loss: 0.16845 (0.14250) +2025-08-24,23:33:57 | INFO | Train Epoch: 12 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.11702 (0.12756) Boundary_loss: 0.014865 (0.014914) Loss: 0.13189 (0.14247) +2025-08-24,23:34:53 | INFO | Train Epoch: 12 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.496 Boundary Ratio: 0.247 Contrastive_loss: 0.099383 (0.12748) Boundary_loss: 0.014969 (0.014914) Loss: 0.11435 (0.14239) +2025-08-24,23:35:50 | INFO | Train Epoch: 12 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.10187 (0.12741) Boundary_loss: 0.014879 (0.014914) Loss: 0.11675 (0.14233) +2025-08-24,23:36:46 | INFO | Train Epoch: 12 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.12380 (0.12740) Boundary_loss: 0.014941 (0.014914) Loss: 0.13874 (0.14232) +2025-08-24,23:37:43 | INFO | Train Epoch: 12 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.12208 (0.12739) Boundary_loss: 0.014936 (0.014914) Loss: 0.13702 (0.14230) +2025-08-24,23:38:39 | INFO | Train Epoch: 12 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.10560 (0.12733) Boundary_loss: 0.014886 (0.014914) Loss: 0.12049 (0.14224) +2025-08-24,23:39:35 | INFO | Train Epoch: 12 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.12160 (0.12731) Boundary_loss: 0.014851 (0.014914) Loss: 0.13645 (0.14223) +2025-08-24,23:40:32 | INFO | Train Epoch: 12 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.11608 (0.12728) Boundary_loss: 0.014982 (0.014914) Loss: 0.13106 (0.14220) +2025-08-24,23:41:28 | INFO | Train Epoch: 12 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.11693 (0.12726) Boundary_loss: 0.014925 (0.014914) Loss: 0.13186 (0.14217) +2025-08-24,23:42:25 | INFO | Train Epoch: 12 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.10807 (0.12720) Boundary_loss: 0.014914 (0.014914) Loss: 0.12299 (0.14212) +2025-08-24,23:43:21 | INFO | Train Epoch: 12 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.098542 (0.12713) Boundary_loss: 0.014953 (0.014914) Loss: 0.11349 (0.14204) +2025-08-24,23:44:17 | INFO | Train Epoch: 12 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.12293 (0.12712) Boundary_loss: 0.014921 (0.014914) Loss: 0.13785 (0.14203) +2025-08-24,23:45:14 | INFO | Train Epoch: 12 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.455 Boundary Ratio: 0.247 Contrastive_loss: 0.14403 (0.12716) Boundary_loss: 0.014902 (0.014914) Loss: 0.15894 (0.14208) +2025-08-24,23:46:10 | INFO | Train Epoch: 12 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.089989 (0.12706) Boundary_loss: 0.014917 (0.014914) Loss: 0.10491 (0.14198) +2025-08-24,23:47:07 | INFO | Train Epoch: 12 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.11017 (0.12702) Boundary_loss: 0.014838 (0.014914) Loss: 0.12501 (0.14193) +2025-08-24,23:48:03 | INFO | Train Epoch: 12 [19456512/26365952 (74%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.15443 (0.12709) Boundary_loss: 0.014883 (0.014914) Loss: 0.16931 (0.14200) +2025-08-24,23:49:00 | INFO | Train Epoch: 12 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.11884 (0.12707) Boundary_loss: 0.014902 (0.014914) Loss: 0.13374 (0.14198) +2025-08-24,23:49:56 | INFO | Train Epoch: 12 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.14490 (0.12712) Boundary_loss: 0.015006 (0.014914) Loss: 0.15990 (0.14203) +2025-08-24,23:50:52 | INFO | Train Epoch: 12 [19610112/26365952 (74%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.10231 (0.12705) Boundary_loss: 0.014871 (0.014914) Loss: 0.11718 (0.14197) +2025-08-24,23:51:49 | INFO | Train Epoch: 12 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.13301 (0.12707) Boundary_loss: 0.014823 (0.014914) Loss: 0.14783 (0.14198) +2025-08-24,23:52:45 | INFO | Train Epoch: 12 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.10678 (0.12701) Boundary_loss: 0.014792 (0.014913) Loss: 0.12157 (0.14193) +2025-08-24,23:53:42 | INFO | Train Epoch: 12 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.12700 (0.12701) Boundary_loss: 0.015085 (0.014914) Loss: 0.14208 (0.14193) +2025-08-24,23:54:38 | INFO | Train Epoch: 12 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.12639 (0.12701) Boundary_loss: 0.014822 (0.014914) Loss: 0.14121 (0.14193) +2025-08-24,23:55:34 | INFO | Train Epoch: 12 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.12994 (0.12702) Boundary_loss: 0.014925 (0.014914) Loss: 0.14487 (0.14193) +2025-08-24,23:56:31 | INFO | Train Epoch: 12 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.13371 (0.12704) Boundary_loss: 0.015064 (0.014914) Loss: 0.14877 (0.14195) +2025-08-24,23:57:27 | INFO | Train Epoch: 12 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.12377 (0.12703) Boundary_loss: 0.014899 (0.014914) Loss: 0.13866 (0.14194) +2025-08-24,23:58:24 | INFO | Train Epoch: 12 [20019712/26365952 (76%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.15294 (0.12709) Boundary_loss: 0.014971 (0.014914) Loss: 0.16791 (0.14201) +2025-08-24,23:59:20 | INFO | Train Epoch: 12 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.14052 (0.12713) Boundary_loss: 0.014867 (0.014914) Loss: 0.15539 (0.14204) +2025-08-25,00:00:16 | INFO | Train Epoch: 12 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.11950 (0.12711) Boundary_loss: 0.014876 (0.014914) Loss: 0.13438 (0.14202) +2025-08-25,00:01:13 | INFO | Train Epoch: 12 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.13461 (0.12713) Boundary_loss: 0.014892 (0.014914) Loss: 0.14950 (0.14204) +2025-08-25,00:02:09 | INFO | Train Epoch: 12 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.14954 (0.12719) Boundary_loss: 0.014881 (0.014914) Loss: 0.16442 (0.14210) +2025-08-25,00:03:06 | INFO | Train Epoch: 12 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.13238 (0.12720) Boundary_loss: 0.014831 (0.014914) Loss: 0.14721 (0.14211) +2025-08-25,00:04:02 | INFO | Train Epoch: 12 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.16369 (0.12729) Boundary_loss: 0.014906 (0.014913) Loss: 0.17859 (0.14220) +2025-08-25,00:04:59 | INFO | Train Epoch: 12 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.10187 (0.12723) Boundary_loss: 0.014939 (0.014914) Loss: 0.11681 (0.14214) +2025-08-25,00:05:55 | INFO | Train Epoch: 12 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.484 Boundary Ratio: 0.247 Contrastive_loss: 0.12330 (0.12722) Boundary_loss: 0.014831 (0.014913) Loss: 0.13813 (0.14213) +2025-08-25,00:06:52 | INFO | Train Epoch: 12 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.13796 (0.12724) Boundary_loss: 0.014913 (0.014913) Loss: 0.15287 (0.14216) +2025-08-25,00:07:48 | INFO | Train Epoch: 12 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.092397 (0.12716) Boundary_loss: 0.014889 (0.014913) Loss: 0.10729 (0.14207) +2025-08-25,00:08:44 | INFO | Train Epoch: 12 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.11386 (0.12712) Boundary_loss: 0.014978 (0.014913) Loss: 0.12884 (0.14204) +2025-08-25,00:09:41 | INFO | Train Epoch: 12 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.15375 (0.12719) Boundary_loss: 0.014929 (0.014913) Loss: 0.16868 (0.14210) +2025-08-25,00:10:37 | INFO | Train Epoch: 12 [20685312/26365952 (78%)] Avg Boundaries (per batch): 49.199 Boundary Ratio: 0.251 Contrastive_loss: 0.13084 (0.12720) Boundary_loss: 0.015000 (0.014914) Loss: 0.14584 (0.14211) +2025-08-25,00:11:34 | INFO | Train Epoch: 12 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.10425 (0.12714) Boundary_loss: 0.015017 (0.014914) Loss: 0.11927 (0.14206) +2025-08-25,00:12:30 | INFO | Train Epoch: 12 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14395 (0.12718) Boundary_loss: 0.014863 (0.014914) Loss: 0.15881 (0.14210) +2025-08-25,00:13:27 | INFO | Train Epoch: 12 [20838912/26365952 (79%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.097446 (0.12711) Boundary_loss: 0.014920 (0.014914) Loss: 0.11237 (0.14202) +2025-08-25,00:14:23 | INFO | Train Epoch: 12 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.11257 (0.12707) Boundary_loss: 0.014800 (0.014914) Loss: 0.12736 (0.14199) +2025-08-25,00:15:20 | INFO | Train Epoch: 12 [20941312/26365952 (79%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.11948 (0.12706) Boundary_loss: 0.014875 (0.014913) Loss: 0.13435 (0.14197) +2025-08-25,00:16:16 | INFO | Train Epoch: 12 [20992512/26365952 (80%)] Avg Boundaries (per batch): 49.047 Boundary Ratio: 0.250 Contrastive_loss: 0.10153 (0.12699) Boundary_loss: 0.014962 (0.014914) Loss: 0.11649 (0.14191) +2025-08-25,00:17:13 | INFO | Train Epoch: 12 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.13479 (0.12701) Boundary_loss: 0.015010 (0.014914) Loss: 0.14980 (0.14193) +2025-08-25,00:18:09 | INFO | Train Epoch: 12 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.083468 (0.12691) Boundary_loss: 0.014946 (0.014914) Loss: 0.098414 (0.14182) +2025-08-25,00:19:05 | INFO | Train Epoch: 12 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.10038 (0.12684) Boundary_loss: 0.014866 (0.014914) Loss: 0.11524 (0.14176) +2025-08-25,00:20:02 | INFO | Train Epoch: 12 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.10941 (0.12680) Boundary_loss: 0.014811 (0.014914) Loss: 0.12422 (0.14172) +2025-08-25,00:20:58 | INFO | Train Epoch: 12 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.10069 (0.12674) Boundary_loss: 0.015018 (0.014914) Loss: 0.11571 (0.14165) +2025-08-25,00:21:55 | INFO | Train Epoch: 12 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.12721 (0.12674) Boundary_loss: 0.014839 (0.014914) Loss: 0.14205 (0.14165) +2025-08-25,00:22:51 | INFO | Train Epoch: 12 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.098171 (0.12667) Boundary_loss: 0.014935 (0.014914) Loss: 0.11311 (0.14159) +2025-08-25,00:23:48 | INFO | Train Epoch: 12 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.10754 (0.12663) Boundary_loss: 0.014938 (0.014914) Loss: 0.12248 (0.14154) +2025-08-25,00:24:44 | INFO | Train Epoch: 12 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.11260 (0.12659) Boundary_loss: 0.014769 (0.014913) Loss: 0.12737 (0.14151) +2025-08-25,00:25:41 | INFO | Train Epoch: 12 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.445 Boundary Ratio: 0.247 Contrastive_loss: 0.13046 (0.12660) Boundary_loss: 0.015005 (0.014914) Loss: 0.14546 (0.14152) +2025-08-25,00:26:37 | INFO | Train Epoch: 12 [21555712/26365952 (82%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.095548 (0.12653) Boundary_loss: 0.014916 (0.014914) Loss: 0.11046 (0.14144) +2025-08-25,00:27:34 | INFO | Train Epoch: 12 [21606912/26365952 (82%)] Avg Boundaries (per batch): 49.059 Boundary Ratio: 0.250 Contrastive_loss: 0.12879 (0.12653) Boundary_loss: 0.014789 (0.014913) Loss: 0.14358 (0.14145) +2025-08-25,00:28:30 | INFO | Train Epoch: 12 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.12101 (0.12652) Boundary_loss: 0.014871 (0.014913) Loss: 0.13588 (0.14143) +2025-08-25,00:29:26 | INFO | Train Epoch: 12 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.12512 (0.12652) Boundary_loss: 0.014953 (0.014913) Loss: 0.14007 (0.14143) +2025-08-25,00:30:23 | INFO | Train Epoch: 12 [21760512/26365952 (83%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.17402 (0.12663) Boundary_loss: 0.014847 (0.014913) Loss: 0.18886 (0.14154) +2025-08-25,00:31:19 | INFO | Train Epoch: 12 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.099633 (0.12657) Boundary_loss: 0.014900 (0.014913) Loss: 0.11453 (0.14148) +2025-08-25,00:32:15 | INFO | Train Epoch: 12 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.091000 (0.12648) Boundary_loss: 0.014839 (0.014913) Loss: 0.10584 (0.14140) +2025-08-25,00:33:12 | INFO | Train Epoch: 12 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.14094 (0.12652) Boundary_loss: 0.014831 (0.014913) Loss: 0.15577 (0.14143) +2025-08-25,00:34:08 | INFO | Train Epoch: 12 [21965312/26365952 (83%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.11444 (0.12649) Boundary_loss: 0.014827 (0.014913) Loss: 0.12926 (0.14140) +2025-08-25,00:35:05 | INFO | Train Epoch: 12 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.12676 (0.12649) Boundary_loss: 0.014889 (0.014912) Loss: 0.14165 (0.14140) +2025-08-25,00:36:01 | INFO | Train Epoch: 12 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.10018 (0.12643) Boundary_loss: 0.014943 (0.014913) Loss: 0.11512 (0.14134) +2025-08-25,00:36:58 | INFO | Train Epoch: 12 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.13793 (0.12645) Boundary_loss: 0.014816 (0.014912) Loss: 0.15275 (0.14137) +2025-08-25,00:37:54 | INFO | Train Epoch: 12 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.12548 (0.12645) Boundary_loss: 0.014966 (0.014912) Loss: 0.14045 (0.14136) +2025-08-25,00:38:51 | INFO | Train Epoch: 12 [22221312/26365952 (84%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.10576 (0.12640) Boundary_loss: 0.014968 (0.014913) Loss: 0.12073 (0.14132) +2025-08-25,00:39:47 | INFO | Train Epoch: 12 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.11038 (0.12637) Boundary_loss: 0.014927 (0.014913) Loss: 0.12530 (0.14128) +2025-08-25,00:40:44 | INFO | Train Epoch: 12 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.18022 (0.12649) Boundary_loss: 0.015045 (0.014913) Loss: 0.19527 (0.14140) +2025-08-25,00:41:40 | INFO | Train Epoch: 12 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.12652 (0.12649) Boundary_loss: 0.014981 (0.014913) Loss: 0.14150 (0.14140) +2025-08-25,00:42:37 | INFO | Train Epoch: 12 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.13016 (0.12650) Boundary_loss: 0.015002 (0.014913) Loss: 0.14516 (0.14141) +2025-08-25,00:43:33 | INFO | Train Epoch: 12 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.14012 (0.12653) Boundary_loss: 0.014844 (0.014913) Loss: 0.15496 (0.14144) +2025-08-25,00:44:30 | INFO | Train Epoch: 12 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.395 Boundary Ratio: 0.247 Contrastive_loss: 0.15303 (0.12659) Boundary_loss: 0.014821 (0.014913) Loss: 0.16786 (0.14150) +2025-08-25,00:45:26 | INFO | Train Epoch: 12 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.13784 (0.12662) Boundary_loss: 0.014914 (0.014913) Loss: 0.15275 (0.14153) +2025-08-25,00:46:22 | INFO | Train Epoch: 12 [22630912/26365952 (86%)] Avg Boundaries (per batch): 49.262 Boundary Ratio: 0.251 Contrastive_loss: 0.12390 (0.12661) Boundary_loss: 0.015017 (0.014913) Loss: 0.13892 (0.14152) +2025-08-25,00:47:19 | INFO | Train Epoch: 12 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.097817 (0.12654) Boundary_loss: 0.014978 (0.014913) Loss: 0.11280 (0.14146) +2025-08-25,00:48:15 | INFO | Train Epoch: 12 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.10490 (0.12650) Boundary_loss: 0.015061 (0.014914) Loss: 0.11996 (0.14141) +2025-08-25,00:49:12 | INFO | Train Epoch: 12 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.14296 (0.12653) Boundary_loss: 0.015105 (0.014914) Loss: 0.15807 (0.14145) +2025-08-25,00:50:08 | INFO | Train Epoch: 12 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.14494 (0.12657) Boundary_loss: 0.015000 (0.014914) Loss: 0.15994 (0.14149) +2025-08-25,00:51:04 | INFO | Train Epoch: 12 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.11408 (0.12655) Boundary_loss: 0.015039 (0.014915) Loss: 0.12912 (0.14146) +2025-08-25,00:52:01 | INFO | Train Epoch: 12 [22938112/26365952 (87%)] Avg Boundaries (per batch): 49.219 Boundary Ratio: 0.251 Contrastive_loss: 0.12492 (0.12654) Boundary_loss: 0.014876 (0.014914) Loss: 0.13980 (0.14146) +2025-08-25,00:52:57 | INFO | Train Epoch: 12 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.14501 (0.12658) Boundary_loss: 0.014925 (0.014914) Loss: 0.15994 (0.14150) +2025-08-25,00:53:54 | INFO | Train Epoch: 12 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.11853 (0.12657) Boundary_loss: 0.014802 (0.014914) Loss: 0.13333 (0.14148) +2025-08-25,00:54:50 | INFO | Train Epoch: 12 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.12675 (0.12657) Boundary_loss: 0.014853 (0.014914) Loss: 0.14161 (0.14148) +2025-08-25,00:55:47 | INFO | Train Epoch: 12 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.075320 (0.12645) Boundary_loss: 0.014942 (0.014914) Loss: 0.090262 (0.14137) +2025-08-25,00:56:43 | INFO | Train Epoch: 12 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.13170 (0.12646) Boundary_loss: 0.014911 (0.014914) Loss: 0.14661 (0.14138) +2025-08-25,00:57:39 | INFO | Train Epoch: 12 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.11579 (0.12644) Boundary_loss: 0.014830 (0.014914) Loss: 0.13062 (0.14136) +2025-08-25,00:58:36 | INFO | Train Epoch: 12 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.12144 (0.12643) Boundary_loss: 0.014930 (0.014914) Loss: 0.13637 (0.14134) +2025-08-25,00:59:32 | INFO | Train Epoch: 12 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11403 (0.12640) Boundary_loss: 0.015022 (0.014914) Loss: 0.12905 (0.14132) +2025-08-25,01:00:29 | INFO | Train Epoch: 12 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.16193 (0.12648) Boundary_loss: 0.014932 (0.014914) Loss: 0.17686 (0.14140) +2025-08-25,01:01:25 | INFO | Train Epoch: 12 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.086163 (0.12639) Boundary_loss: 0.014888 (0.014914) Loss: 0.10105 (0.14131) +2025-08-25,01:02:22 | INFO | Train Epoch: 12 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.13368 (0.12641) Boundary_loss: 0.014886 (0.014914) Loss: 0.14856 (0.14132) +2025-08-25,01:03:18 | INFO | Train Epoch: 12 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.098336 (0.12635) Boundary_loss: 0.014929 (0.014914) Loss: 0.11327 (0.14126) +2025-08-25,01:04:15 | INFO | Train Epoch: 12 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.10971 (0.12631) Boundary_loss: 0.014843 (0.014914) Loss: 0.12456 (0.14123) +2025-08-25,01:05:11 | INFO | Train Epoch: 12 [23654912/26365952 (90%)] Avg Boundaries (per batch): 49.240 Boundary Ratio: 0.251 Contrastive_loss: 0.15773 (0.12638) Boundary_loss: 0.014908 (0.014914) Loss: 0.17264 (0.14129) +2025-08-25,01:06:08 | INFO | Train Epoch: 12 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.12635 (0.12638) Boundary_loss: 0.014888 (0.014914) Loss: 0.14124 (0.14129) +2025-08-25,01:07:04 | INFO | Train Epoch: 12 [23757312/26365952 (90%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.14341 (0.12642) Boundary_loss: 0.014967 (0.014914) Loss: 0.15838 (0.14133) +2025-08-25,01:08:01 | INFO | Train Epoch: 12 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.15474 (0.12648) Boundary_loss: 0.014945 (0.014914) Loss: 0.16969 (0.14139) +2025-08-25,01:08:57 | INFO | Train Epoch: 12 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.11556 (0.12645) Boundary_loss: 0.014924 (0.014914) Loss: 0.13049 (0.14137) +2025-08-25,01:09:54 | INFO | Train Epoch: 12 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.11784 (0.12644) Boundary_loss: 0.014894 (0.014914) Loss: 0.13274 (0.14135) +2025-08-25,01:10:50 | INFO | Train Epoch: 12 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.12945 (0.12644) Boundary_loss: 0.014829 (0.014914) Loss: 0.14428 (0.14136) +2025-08-25,01:11:46 | INFO | Train Epoch: 12 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.076437 (0.12634) Boundary_loss: 0.014878 (0.014914) Loss: 0.091314 (0.14125) +2025-08-25,01:12:43 | INFO | Train Epoch: 12 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.079704 (0.12624) Boundary_loss: 0.014878 (0.014914) Loss: 0.094582 (0.14115) +2025-08-25,01:13:39 | INFO | Train Epoch: 12 [24115712/26365952 (91%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.12710 (0.12624) Boundary_loss: 0.015049 (0.014914) Loss: 0.14215 (0.14115) +2025-08-25,01:14:35 | INFO | Train Epoch: 12 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.12133 (0.12623) Boundary_loss: 0.014884 (0.014914) Loss: 0.13621 (0.14114) +2025-08-25,01:15:32 | INFO | Train Epoch: 12 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10994 (0.12619) Boundary_loss: 0.014825 (0.014914) Loss: 0.12476 (0.14111) +2025-08-25,01:16:29 | INFO | Train Epoch: 12 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.10097 (0.12614) Boundary_loss: 0.014868 (0.014914) Loss: 0.11584 (0.14105) +2025-08-25,01:17:25 | INFO | Train Epoch: 12 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12273 (0.12613) Boundary_loss: 0.014968 (0.014914) Loss: 0.13770 (0.14105) +2025-08-25,01:18:21 | INFO | Train Epoch: 12 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.12023 (0.12612) Boundary_loss: 0.014861 (0.014914) Loss: 0.13509 (0.14103) +2025-08-25,01:19:18 | INFO | Train Epoch: 12 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.14812 (0.12617) Boundary_loss: 0.014731 (0.014913) Loss: 0.16285 (0.14108) +2025-08-25,01:20:14 | INFO | Train Epoch: 12 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.11582 (0.12615) Boundary_loss: 0.014951 (0.014913) Loss: 0.13077 (0.14106) +2025-08-25,01:21:11 | INFO | Train Epoch: 12 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.10319 (0.12610) Boundary_loss: 0.014984 (0.014914) Loss: 0.11818 (0.14101) +2025-08-25,01:22:07 | INFO | Train Epoch: 12 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.371 Boundary Ratio: 0.247 Contrastive_loss: 0.13218 (0.12611) Boundary_loss: 0.014972 (0.014914) Loss: 0.14715 (0.14102) +2025-08-25,01:23:03 | INFO | Train Epoch: 12 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.14037 (0.12614) Boundary_loss: 0.014968 (0.014914) Loss: 0.15534 (0.14105) +2025-08-25,01:24:00 | INFO | Train Epoch: 12 [24678912/26365952 (94%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.13309 (0.12615) Boundary_loss: 0.014838 (0.014914) Loss: 0.14793 (0.14107) +2025-08-25,01:24:56 | INFO | Train Epoch: 12 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.12659 (0.12615) Boundary_loss: 0.014791 (0.014913) Loss: 0.14138 (0.14107) +2025-08-25,01:25:53 | INFO | Train Epoch: 12 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.12121 (0.12614) Boundary_loss: 0.014765 (0.014913) Loss: 0.13598 (0.14106) +2025-08-25,01:26:49 | INFO | Train Epoch: 12 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.13068 (0.12615) Boundary_loss: 0.014886 (0.014913) Loss: 0.14556 (0.14107) +2025-08-25,01:27:46 | INFO | Train Epoch: 12 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.12361 (0.12615) Boundary_loss: 0.014913 (0.014913) Loss: 0.13852 (0.14106) +2025-08-25,01:28:42 | INFO | Train Epoch: 12 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.10247 (0.12610) Boundary_loss: 0.014874 (0.014913) Loss: 0.11734 (0.14101) +2025-08-25,01:29:39 | INFO | Train Epoch: 12 [24986112/26365952 (95%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.10248 (0.12605) Boundary_loss: 0.014932 (0.014913) Loss: 0.11741 (0.14097) +2025-08-25,01:30:35 | INFO | Train Epoch: 12 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11847 (0.12604) Boundary_loss: 0.014943 (0.014913) Loss: 0.13341 (0.14095) +2025-08-25,01:31:31 | INFO | Train Epoch: 12 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.090141 (0.12596) Boundary_loss: 0.014857 (0.014913) Loss: 0.10500 (0.14088) +2025-08-25,01:32:28 | INFO | Train Epoch: 12 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.13011 (0.12597) Boundary_loss: 0.014922 (0.014913) Loss: 0.14503 (0.14088) +2025-08-25,01:33:24 | INFO | Train Epoch: 12 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.13399 (0.12599) Boundary_loss: 0.014971 (0.014913) Loss: 0.14896 (0.14090) +2025-08-25,01:34:21 | INFO | Train Epoch: 12 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.11332 (0.12596) Boundary_loss: 0.014934 (0.014913) Loss: 0.12825 (0.14088) +2025-08-25,01:35:17 | INFO | Train Epoch: 12 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.16330 (0.12604) Boundary_loss: 0.014919 (0.014913) Loss: 0.17822 (0.14095) +2025-08-25,01:36:13 | INFO | Train Epoch: 12 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.10805 (0.12600) Boundary_loss: 0.014860 (0.014913) Loss: 0.12291 (0.14091) +2025-08-25,01:37:10 | INFO | Train Epoch: 12 [25395712/26365952 (96%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.12268 (0.12600) Boundary_loss: 0.014935 (0.014913) Loss: 0.13761 (0.14091) +2025-08-25,01:38:07 | INFO | Train Epoch: 12 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.093129 (0.12593) Boundary_loss: 0.015069 (0.014913) Loss: 0.10820 (0.14084) +2025-08-25,01:39:03 | INFO | Train Epoch: 12 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.12892 (0.12594) Boundary_loss: 0.014920 (0.014913) Loss: 0.14384 (0.14085) +2025-08-25,01:40:00 | INFO | Train Epoch: 12 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.10635 (0.12590) Boundary_loss: 0.014836 (0.014913) Loss: 0.12118 (0.14081) +2025-08-25,01:40:56 | INFO | Train Epoch: 12 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.10565 (0.12586) Boundary_loss: 0.014828 (0.014913) Loss: 0.12048 (0.14077) +2025-08-25,01:41:52 | INFO | Train Epoch: 12 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.081087 (0.12577) Boundary_loss: 0.014870 (0.014913) Loss: 0.095956 (0.14068) +2025-08-25,01:42:49 | INFO | Train Epoch: 12 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.11521 (0.12575) Boundary_loss: 0.014982 (0.014913) Loss: 0.13019 (0.14066) +2025-08-25,01:43:45 | INFO | Train Epoch: 12 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.13909 (0.12577) Boundary_loss: 0.014879 (0.014913) Loss: 0.15397 (0.14068) +2025-08-25,01:44:42 | INFO | Train Epoch: 12 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.12758 (0.12578) Boundary_loss: 0.014904 (0.014913) Loss: 0.14249 (0.14069) +2025-08-25,01:45:38 | INFO | Train Epoch: 12 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.11743 (0.12576) Boundary_loss: 0.014932 (0.014913) Loss: 0.13237 (0.14067) +2025-08-25,01:46:35 | INFO | Train Epoch: 12 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.12462 (0.12576) Boundary_loss: 0.014914 (0.014913) Loss: 0.13953 (0.14067) +2025-08-25,01:47:31 | INFO | Train Epoch: 12 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.11857 (0.12574) Boundary_loss: 0.014964 (0.014913) Loss: 0.13353 (0.14066) +2025-08-25,01:48:28 | INFO | Train Epoch: 12 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.11656 (0.12572) Boundary_loss: 0.014833 (0.014913) Loss: 0.13139 (0.14064) +2025-08-25,01:49:24 | INFO | Train Epoch: 12 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.883 Boundary Ratio: 0.249 Contrastive_loss: 0.15543 (0.12578) Boundary_loss: 0.014822 (0.014913) Loss: 0.17025 (0.14070) +2025-08-25,01:50:21 | INFO | Train Epoch: 12 [26112512/26365952 (99%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.18710 (0.12590) Boundary_loss: 0.015028 (0.014913) Loss: 0.20213 (0.14082) +2025-08-25,01:51:17 | INFO | Train Epoch: 12 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.12556 (0.12590) Boundary_loss: 0.014908 (0.014913) Loss: 0.14046 (0.14082) +2025-08-25,01:52:13 | INFO | Train Epoch: 12 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.090879 (0.12583) Boundary_loss: 0.014985 (0.014913) Loss: 0.10586 (0.14075) +2025-08-25,01:53:10 | INFO | Train Epoch: 12 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.10653 (0.12580) Boundary_loss: 0.014883 (0.014913) Loss: 0.12141 (0.14071) +2025-08-25,01:54:06 | INFO | Train Epoch: 12 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.094880 (0.12574) Boundary_loss: 0.014992 (0.014913) Loss: 0.10987 (0.14065) +2025-08-25,01:55:00 | INFO | Train Epoch: 12 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.12103 (0.12573) Boundary_loss: 0.014920 (0.014913) Loss: 0.13595 (0.14064) +2025-08-25,01:55:00 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-25,01:55:00 | INFO | [Epoch 12] Average Step Time: 0.567s | Average GPU Memory: 31.6 GB +2025-08-25,01:55:00 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-25,01:55:00 | INFO | Starting zero-shot imagenet. +2025-08-25,01:55:00 | INFO | Building zero-shot classifier +2025-08-25,01:55:09 | INFO | Using classifier +2025-08-25,01:55:52 | INFO | Finished zero-shot imagenet. +2025-08-25,01:55:52 | INFO | Eval Epoch: 13 imagenet-zeroshot-val-top1: 0.3063 imagenet-zeroshot-val-top5: 0.5759 +2025-08-25,01:55:53 | INFO | Start epoch 13 +2025-08-25,01:55:55 | INFO | Train Epoch: 13 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.097723 (0.097723) Boundary_loss: 0.014857 (0.014857) Loss: 0.11258 (0.11258) +2025-08-25,01:56:51 | INFO | Train Epoch: 13 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.10437 (0.10105) Boundary_loss: 0.014944 (0.014901) Loss: 0.11931 (0.11595) +2025-08-25,01:57:47 | INFO | Train Epoch: 13 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.10538 (0.10249) Boundary_loss: 0.014914 (0.014905) Loss: 0.12029 (0.11739) +2025-08-25,01:58:44 | INFO | Train Epoch: 13 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.11264 (0.10503) Boundary_loss: 0.014935 (0.014913) Loss: 0.12758 (0.11994) +2025-08-25,01:59:40 | INFO | Train Epoch: 13 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.555 Boundary Ratio: 0.248 Contrastive_loss: 0.086500 (0.10132) Boundary_loss: 0.014919 (0.014914) Loss: 0.10142 (0.11624) +2025-08-25,02:00:36 | INFO | Train Epoch: 13 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.14408 (0.10845) Boundary_loss: 0.014990 (0.014927) Loss: 0.15907 (0.12338) +2025-08-25,02:01:33 | INFO | Train Epoch: 13 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.11995 (0.11009) Boundary_loss: 0.014862 (0.014917) Loss: 0.13481 (0.12501) +2025-08-25,02:02:29 | INFO | Train Epoch: 13 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.085211 (0.10698) Boundary_loss: 0.014836 (0.014907) Loss: 0.10005 (0.12189) +2025-08-25,02:03:25 | INFO | Train Epoch: 13 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.15048 (0.11181) Boundary_loss: 0.014794 (0.014895) Loss: 0.16527 (0.12671) +2025-08-25,02:04:22 | INFO | Train Epoch: 13 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.075395 (0.10817) Boundary_loss: 0.014959 (0.014901) Loss: 0.090354 (0.12307) +2025-08-25,02:05:18 | INFO | Train Epoch: 13 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.084002 (0.10598) Boundary_loss: 0.014922 (0.014903) Loss: 0.098925 (0.12088) +2025-08-25,02:06:14 | INFO | Train Epoch: 13 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 49.225 Boundary Ratio: 0.251 Contrastive_loss: 0.10679 (0.10604) Boundary_loss: 0.014971 (0.014909) Loss: 0.12176 (0.12095) +2025-08-25,02:07:10 | INFO | Train Epoch: 13 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.099536 (0.10554) Boundary_loss: 0.014894 (0.014907) Loss: 0.11443 (0.12045) +2025-08-25,02:08:06 | INFO | Train Epoch: 13 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.12675 (0.10706) Boundary_loss: 0.014897 (0.014907) Loss: 0.14165 (0.12196) +2025-08-25,02:09:03 | INFO | Train Epoch: 13 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.088379 (0.10581) Boundary_loss: 0.014879 (0.014905) Loss: 0.10326 (0.12072) +2025-08-25,02:09:59 | INFO | Train Epoch: 13 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.097698 (0.10531) Boundary_loss: 0.014964 (0.014909) Loss: 0.11266 (0.12021) +2025-08-25,02:10:55 | INFO | Train Epoch: 13 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.11107 (0.10564) Boundary_loss: 0.014940 (0.014910) Loss: 0.12601 (0.12055) +2025-08-25,02:11:51 | INFO | Train Epoch: 13 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.098108 (0.10523) Boundary_loss: 0.014896 (0.014910) Loss: 0.11300 (0.12014) +2025-08-25,02:12:48 | INFO | Train Epoch: 13 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.091383 (0.10450) Boundary_loss: 0.014958 (0.014912) Loss: 0.10634 (0.11941) +2025-08-25,02:13:44 | INFO | Train Epoch: 13 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.096505 (0.10410) Boundary_loss: 0.015047 (0.014919) Loss: 0.11155 (0.11902) +2025-08-25,02:14:40 | INFO | Train Epoch: 13 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.12160 (0.10493) Boundary_loss: 0.014983 (0.014922) Loss: 0.13658 (0.11985) +2025-08-25,02:15:37 | INFO | Train Epoch: 13 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.10520 (0.10494) Boundary_loss: 0.014915 (0.014922) Loss: 0.12012 (0.11986) +2025-08-25,02:16:33 | INFO | Train Epoch: 13 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.074254 (0.10361) Boundary_loss: 0.014838 (0.014918) Loss: 0.089091 (0.11853) +2025-08-25,02:17:29 | INFO | Train Epoch: 13 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 49.271 Boundary Ratio: 0.251 Contrastive_loss: 0.12215 (0.10438) Boundary_loss: 0.014887 (0.014917) Loss: 0.13704 (0.11930) +2025-08-25,02:18:25 | INFO | Train Epoch: 13 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 48.377 Boundary Ratio: 0.247 Contrastive_loss: 0.12239 (0.10510) Boundary_loss: 0.014840 (0.014914) Loss: 0.13723 (0.12002) +2025-08-25,02:19:22 | INFO | Train Epoch: 13 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.11486 (0.10548) Boundary_loss: 0.014739 (0.014907) Loss: 0.12960 (0.12038) +2025-08-25,02:20:18 | INFO | Train Epoch: 13 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.11653 (0.10589) Boundary_loss: 0.014958 (0.014909) Loss: 0.13149 (0.12080) +2025-08-25,02:21:14 | INFO | Train Epoch: 13 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.13853 (0.10705) Boundary_loss: 0.014795 (0.014905) Loss: 0.15332 (0.12196) +2025-08-25,02:22:10 | INFO | Train Epoch: 13 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 49.018 Boundary Ratio: 0.250 Contrastive_loss: 0.11709 (0.10740) Boundary_loss: 0.014869 (0.014904) Loss: 0.13196 (0.12230) +2025-08-25,02:23:07 | INFO | Train Epoch: 13 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.12908 (0.10812) Boundary_loss: 0.015007 (0.014907) Loss: 0.14409 (0.12303) +2025-08-25,02:24:03 | INFO | Train Epoch: 13 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 49.027 Boundary Ratio: 0.250 Contrastive_loss: 0.097756 (0.10779) Boundary_loss: 0.014801 (0.014904) Loss: 0.11256 (0.12269) +2025-08-25,02:24:59 | INFO | Train Epoch: 13 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.085363 (0.10709) Boundary_loss: 0.014807 (0.014901) Loss: 0.10017 (0.12199) +2025-08-25,02:25:55 | INFO | Train Epoch: 13 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.069895 (0.10596) Boundary_loss: 0.014933 (0.014902) Loss: 0.084828 (0.12086) +2025-08-25,02:26:52 | INFO | Train Epoch: 13 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.081530 (0.10524) Boundary_loss: 0.014780 (0.014898) Loss: 0.096310 (0.12014) +2025-08-25,02:27:48 | INFO | Train Epoch: 13 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.11095 (0.10540) Boundary_loss: 0.014988 (0.014901) Loss: 0.12594 (0.12030) +2025-08-25,02:28:44 | INFO | Train Epoch: 13 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.082724 (0.10477) Boundary_loss: 0.014846 (0.014899) Loss: 0.097569 (0.11967) +2025-08-25,02:29:41 | INFO | Train Epoch: 13 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.087474 (0.10431) Boundary_loss: 0.014840 (0.014897) Loss: 0.10231 (0.11920) +2025-08-25,02:30:37 | INFO | Train Epoch: 13 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.13142 (0.10502) Boundary_loss: 0.014846 (0.014896) Loss: 0.14626 (0.11992) +2025-08-25,02:31:33 | INFO | Train Epoch: 13 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.13226 (0.10572) Boundary_loss: 0.014946 (0.014897) Loss: 0.14720 (0.12062) +2025-08-25,02:32:29 | INFO | Train Epoch: 13 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.12326 (0.10616) Boundary_loss: 0.014914 (0.014898) Loss: 0.13818 (0.12105) +2025-08-25,02:33:26 | INFO | Train Epoch: 13 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.11001 (0.10625) Boundary_loss: 0.014718 (0.014893) Loss: 0.12473 (0.12114) +2025-08-25,02:34:22 | INFO | Train Epoch: 13 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.13979 (0.10705) Boundary_loss: 0.014921 (0.014894) Loss: 0.15471 (0.12194) +2025-08-25,02:35:18 | INFO | Train Epoch: 13 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.082843 (0.10649) Boundary_loss: 0.015032 (0.014897) Loss: 0.097875 (0.12138) +2025-08-25,02:36:15 | INFO | Train Epoch: 13 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.092512 (0.10617) Boundary_loss: 0.014912 (0.014898) Loss: 0.10742 (0.12107) +2025-08-25,02:37:11 | INFO | Train Epoch: 13 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.10616 (0.10617) Boundary_loss: 0.014814 (0.014896) Loss: 0.12097 (0.12106) +2025-08-25,02:38:07 | INFO | Train Epoch: 13 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.067827 (0.10533) Boundary_loss: 0.014908 (0.014896) Loss: 0.082735 (0.12023) +2025-08-25,02:39:04 | INFO | Train Epoch: 13 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.11651 (0.10557) Boundary_loss: 0.014800 (0.014894) Loss: 0.13130 (0.12047) +2025-08-25,02:40:00 | INFO | Train Epoch: 13 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.11979 (0.10587) Boundary_loss: 0.014772 (0.014891) Loss: 0.13456 (0.12076) +2025-08-25,02:40:56 | INFO | Train Epoch: 13 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.11816 (0.10612) Boundary_loss: 0.014802 (0.014890) Loss: 0.13296 (0.12101) +2025-08-25,02:41:52 | INFO | Train Epoch: 13 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.467 Boundary Ratio: 0.247 Contrastive_loss: 0.12190 (0.10644) Boundary_loss: 0.014826 (0.014888) Loss: 0.13673 (0.12132) +2025-08-25,02:42:49 | INFO | Train Epoch: 13 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.11131 (0.10653) Boundary_loss: 0.015002 (0.014891) Loss: 0.12632 (0.12142) +2025-08-25,02:43:45 | INFO | Train Epoch: 13 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.098567 (0.10638) Boundary_loss: 0.014861 (0.014890) Loss: 0.11343 (0.12127) +2025-08-25,02:44:41 | INFO | Train Epoch: 13 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.15507 (0.10730) Boundary_loss: 0.014871 (0.014890) Loss: 0.16994 (0.12219) +2025-08-25,02:45:38 | INFO | Train Epoch: 13 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.13211 (0.10776) Boundary_loss: 0.014929 (0.014890) Loss: 0.14704 (0.12265) +2025-08-25,02:46:34 | INFO | Train Epoch: 13 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.11356 (0.10786) Boundary_loss: 0.014874 (0.014890) Loss: 0.12844 (0.12275) +2025-08-25,02:47:30 | INFO | Train Epoch: 13 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.10752 (0.10786) Boundary_loss: 0.015039 (0.014893) Loss: 0.12256 (0.12275) +2025-08-25,02:48:26 | INFO | Train Epoch: 13 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.12085 (0.10808) Boundary_loss: 0.014947 (0.014894) Loss: 0.13580 (0.12298) +2025-08-25,02:49:23 | INFO | Train Epoch: 13 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.087903 (0.10774) Boundary_loss: 0.014926 (0.014894) Loss: 0.10283 (0.12263) +2025-08-25,02:50:19 | INFO | Train Epoch: 13 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.453 Boundary Ratio: 0.247 Contrastive_loss: 0.075472 (0.10719) Boundary_loss: 0.014741 (0.014892) Loss: 0.090214 (0.12208) +2025-08-25,02:51:16 | INFO | Train Epoch: 13 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.078878 (0.10672) Boundary_loss: 0.014831 (0.014891) Loss: 0.093709 (0.12161) +2025-08-25,02:52:12 | INFO | Train Epoch: 13 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.11847 (0.10691) Boundary_loss: 0.014913 (0.014891) Loss: 0.13338 (0.12180) +2025-08-25,02:53:08 | INFO | Train Epoch: 13 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.071912 (0.10635) Boundary_loss: 0.015023 (0.014893) Loss: 0.086936 (0.12124) +2025-08-25,02:54:05 | INFO | Train Epoch: 13 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.11683 (0.10651) Boundary_loss: 0.014948 (0.014894) Loss: 0.13178 (0.12141) +2025-08-25,02:55:01 | INFO | Train Epoch: 13 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.12010 (0.10672) Boundary_loss: 0.014879 (0.014894) Loss: 0.13498 (0.12162) +2025-08-25,02:55:57 | INFO | Train Epoch: 13 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.13055 (0.10709) Boundary_loss: 0.014930 (0.014894) Loss: 0.14548 (0.12198) +2025-08-25,02:56:54 | INFO | Train Epoch: 13 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.11862 (0.10727) Boundary_loss: 0.014803 (0.014893) Loss: 0.13343 (0.12216) +2025-08-25,02:57:50 | INFO | Train Epoch: 13 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.089837 (0.10701) Boundary_loss: 0.014904 (0.014893) Loss: 0.10474 (0.12190) +2025-08-25,02:58:47 | INFO | Train Epoch: 13 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.12717 (0.10730) Boundary_loss: 0.014879 (0.014893) Loss: 0.14205 (0.12219) +2025-08-25,02:59:43 | INFO | Train Epoch: 13 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.10787 (0.10731) Boundary_loss: 0.014953 (0.014894) Loss: 0.12282 (0.12220) +2025-08-25,03:00:39 | INFO | Train Epoch: 13 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.099799 (0.10720) Boundary_loss: 0.014944 (0.014894) Loss: 0.11474 (0.12210) +2025-08-25,03:01:35 | INFO | Train Epoch: 13 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.12104 (0.10740) Boundary_loss: 0.014795 (0.014893) Loss: 0.13583 (0.12229) +2025-08-25,03:02:32 | INFO | Train Epoch: 13 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.087542 (0.10712) Boundary_loss: 0.014948 (0.014894) Loss: 0.10249 (0.12202) +2025-08-25,03:03:28 | INFO | Train Epoch: 13 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 49.043 Boundary Ratio: 0.250 Contrastive_loss: 0.13153 (0.10746) Boundary_loss: 0.014888 (0.014894) Loss: 0.14642 (0.12235) +2025-08-25,03:04:25 | INFO | Train Epoch: 13 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.10758 (0.10746) Boundary_loss: 0.014944 (0.014894) Loss: 0.12253 (0.12235) +2025-08-25,03:05:21 | INFO | Train Epoch: 13 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 49.107 Boundary Ratio: 0.251 Contrastive_loss: 0.11486 (0.10756) Boundary_loss: 0.014933 (0.014895) Loss: 0.12979 (0.12245) +2025-08-25,03:06:17 | INFO | Train Epoch: 13 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.076929 (0.10715) Boundary_loss: 0.015019 (0.014897) Loss: 0.091949 (0.12205) +2025-08-25,03:07:13 | INFO | Train Epoch: 13 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.12535 (0.10739) Boundary_loss: 0.014936 (0.014897) Loss: 0.14029 (0.12229) +2025-08-25,03:08:10 | INFO | Train Epoch: 13 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.11012 (0.10742) Boundary_loss: 0.014741 (0.014895) Loss: 0.12486 (0.12232) +2025-08-25,03:09:06 | INFO | Train Epoch: 13 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.13331 (0.10775) Boundary_loss: 0.014905 (0.014895) Loss: 0.14822 (0.12265) +2025-08-25,03:10:03 | INFO | Train Epoch: 13 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.486 Boundary Ratio: 0.247 Contrastive_loss: 0.13399 (0.10808) Boundary_loss: 0.015030 (0.014897) Loss: 0.14902 (0.12298) +2025-08-25,03:10:59 | INFO | Train Epoch: 13 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10311 (0.10802) Boundary_loss: 0.014994 (0.014898) Loss: 0.11810 (0.12292) +2025-08-25,03:11:55 | INFO | Train Epoch: 13 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.10477 (0.10798) Boundary_loss: 0.014858 (0.014898) Loss: 0.11963 (0.12288) +2025-08-25,03:12:52 | INFO | Train Epoch: 13 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.13083 (0.10825) Boundary_loss: 0.014883 (0.014897) Loss: 0.14571 (0.12315) +2025-08-25,03:13:48 | INFO | Train Epoch: 13 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.15631 (0.10883) Boundary_loss: 0.014833 (0.014897) Loss: 0.17114 (0.12372) +2025-08-25,03:14:44 | INFO | Train Epoch: 13 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.629 Boundary Ratio: 0.248 Contrastive_loss: 0.089316 (0.10860) Boundary_loss: 0.014832 (0.014896) Loss: 0.10415 (0.12349) +2025-08-25,03:15:41 | INFO | Train Epoch: 13 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.11078 (0.10862) Boundary_loss: 0.014862 (0.014896) Loss: 0.12564 (0.12352) +2025-08-25,03:16:37 | INFO | Train Epoch: 13 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.098203 (0.10850) Boundary_loss: 0.014936 (0.014896) Loss: 0.11314 (0.12340) +2025-08-25,03:17:33 | INFO | Train Epoch: 13 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.092250 (0.10832) Boundary_loss: 0.014881 (0.014896) Loss: 0.10713 (0.12321) +2025-08-25,03:18:30 | INFO | Train Epoch: 13 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.090738 (0.10812) Boundary_loss: 0.014836 (0.014895) Loss: 0.10557 (0.12302) +2025-08-25,03:19:26 | INFO | Train Epoch: 13 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.099462 (0.10802) Boundary_loss: 0.014855 (0.014895) Loss: 0.11432 (0.12292) +2025-08-25,03:20:22 | INFO | Train Epoch: 13 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.11946 (0.10815) Boundary_loss: 0.014841 (0.014894) Loss: 0.13430 (0.12304) +2025-08-25,03:21:18 | INFO | Train Epoch: 13 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.14190 (0.10852) Boundary_loss: 0.014969 (0.014895) Loss: 0.15687 (0.12341) +2025-08-25,03:22:15 | INFO | Train Epoch: 13 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.650 Boundary Ratio: 0.248 Contrastive_loss: 0.11195 (0.10855) Boundary_loss: 0.014860 (0.014895) Loss: 0.12681 (0.12345) +2025-08-25,03:23:11 | INFO | Train Epoch: 13 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.12189 (0.10870) Boundary_loss: 0.014851 (0.014894) Loss: 0.13674 (0.12359) +2025-08-25,03:24:07 | INFO | Train Epoch: 13 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.11109 (0.10872) Boundary_loss: 0.014971 (0.014895) Loss: 0.12606 (0.12362) +2025-08-25,03:25:04 | INFO | Train Epoch: 13 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.086173 (0.10849) Boundary_loss: 0.014889 (0.014895) Loss: 0.10106 (0.12338) +2025-08-25,03:26:00 | INFO | Train Epoch: 13 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.13096 (0.10872) Boundary_loss: 0.014975 (0.014896) Loss: 0.14593 (0.12361) +2025-08-25,03:26:57 | INFO | Train Epoch: 13 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.934 Boundary Ratio: 0.250 Contrastive_loss: 0.10591 (0.10869) Boundary_loss: 0.014806 (0.014895) Loss: 0.12072 (0.12358) +2025-08-25,03:27:53 | INFO | Train Epoch: 13 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.078503 (0.10838) Boundary_loss: 0.015036 (0.014896) Loss: 0.093539 (0.12328) +2025-08-25,03:28:49 | INFO | Train Epoch: 13 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.093773 (0.10824) Boundary_loss: 0.014911 (0.014896) Loss: 0.10868 (0.12313) +2025-08-25,03:29:46 | INFO | Train Epoch: 13 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.080513 (0.10796) Boundary_loss: 0.014851 (0.014896) Loss: 0.095364 (0.12286) +2025-08-25,03:30:42 | INFO | Train Epoch: 13 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.080800 (0.10770) Boundary_loss: 0.014961 (0.014897) Loss: 0.095761 (0.12259) +2025-08-25,03:31:38 | INFO | Train Epoch: 13 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.13180 (0.10793) Boundary_loss: 0.014898 (0.014897) Loss: 0.14670 (0.12283) +2025-08-25,03:32:35 | INFO | Train Epoch: 13 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.13265 (0.10817) Boundary_loss: 0.014876 (0.014896) Loss: 0.14753 (0.12307) +2025-08-25,03:33:31 | INFO | Train Epoch: 13 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.093189 (0.10803) Boundary_loss: 0.014900 (0.014896) Loss: 0.10809 (0.12292) +2025-08-25,03:34:27 | INFO | Train Epoch: 13 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.10798 (0.10803) Boundary_loss: 0.014808 (0.014896) Loss: 0.12278 (0.12292) +2025-08-25,03:35:24 | INFO | Train Epoch: 13 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.094655 (0.10790) Boundary_loss: 0.014902 (0.014896) Loss: 0.10956 (0.12280) +2025-08-25,03:36:20 | INFO | Train Epoch: 13 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.10336 (0.10786) Boundary_loss: 0.014846 (0.014895) Loss: 0.11820 (0.12275) +2025-08-25,03:37:16 | INFO | Train Epoch: 13 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.10907 (0.10787) Boundary_loss: 0.015016 (0.014896) Loss: 0.12409 (0.12277) +2025-08-25,03:38:13 | INFO | Train Epoch: 13 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.11017 (0.10789) Boundary_loss: 0.014878 (0.014896) Loss: 0.12505 (0.12279) +2025-08-25,03:39:09 | INFO | Train Epoch: 13 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.098909 (0.10781) Boundary_loss: 0.014958 (0.014897) Loss: 0.11387 (0.12271) +2025-08-25,03:40:05 | INFO | Train Epoch: 13 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.090255 (0.10765) Boundary_loss: 0.014807 (0.014896) Loss: 0.10506 (0.12255) +2025-08-25,03:41:02 | INFO | Train Epoch: 13 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.12437 (0.10780) Boundary_loss: 0.014890 (0.014896) Loss: 0.13926 (0.12270) +2025-08-25,03:41:58 | INFO | Train Epoch: 13 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.062346 (0.10740) Boundary_loss: 0.014796 (0.014895) Loss: 0.077142 (0.12230) +2025-08-25,03:42:54 | INFO | Train Epoch: 13 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.10189 (0.10735) Boundary_loss: 0.015002 (0.014896) Loss: 0.11689 (0.12225) +2025-08-25,03:43:51 | INFO | Train Epoch: 13 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.081601 (0.10713) Boundary_loss: 0.014991 (0.014897) Loss: 0.096592 (0.12203) +2025-08-25,03:44:47 | INFO | Train Epoch: 13 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.099823 (0.10707) Boundary_loss: 0.015013 (0.014898) Loss: 0.11484 (0.12197) +2025-08-25,03:45:43 | INFO | Train Epoch: 13 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.087238 (0.10690) Boundary_loss: 0.015006 (0.014899) Loss: 0.10224 (0.12180) +2025-08-25,03:46:40 | INFO | Train Epoch: 13 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.086392 (0.10673) Boundary_loss: 0.014912 (0.014899) Loss: 0.10130 (0.12163) +2025-08-25,03:47:36 | INFO | Train Epoch: 13 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.10432 (0.10671) Boundary_loss: 0.014877 (0.014899) Loss: 0.11919 (0.12161) +2025-08-25,03:48:33 | INFO | Train Epoch: 13 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.514 Boundary Ratio: 0.248 Contrastive_loss: 0.10059 (0.10666) Boundary_loss: 0.014862 (0.014898) Loss: 0.11545 (0.12156) +2025-08-25,03:49:29 | INFO | Train Epoch: 13 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.096899 (0.10658) Boundary_loss: 0.015029 (0.014899) Loss: 0.11193 (0.12148) +2025-08-25,03:50:26 | INFO | Train Epoch: 13 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10096 (0.10653) Boundary_loss: 0.014922 (0.014899) Loss: 0.11588 (0.12143) +2025-08-25,03:51:22 | INFO | Train Epoch: 13 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.10307 (0.10651) Boundary_loss: 0.014790 (0.014899) Loss: 0.11786 (0.12140) +2025-08-25,03:52:18 | INFO | Train Epoch: 13 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.096179 (0.10642) Boundary_loss: 0.014860 (0.014898) Loss: 0.11104 (0.12132) +2025-08-25,03:53:15 | INFO | Train Epoch: 13 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.093280 (0.10632) Boundary_loss: 0.014808 (0.014898) Loss: 0.10809 (0.12122) +2025-08-25,03:54:11 | INFO | Train Epoch: 13 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.099068 (0.10626) Boundary_loss: 0.015019 (0.014899) Loss: 0.11409 (0.12116) +2025-08-25,03:55:07 | INFO | Train Epoch: 13 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.095889 (0.10618) Boundary_loss: 0.014913 (0.014899) Loss: 0.11080 (0.12108) +2025-08-25,03:56:04 | INFO | Train Epoch: 13 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.11873 (0.10628) Boundary_loss: 0.014813 (0.014898) Loss: 0.13355 (0.12118) +2025-08-25,03:57:00 | INFO | Train Epoch: 13 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.096603 (0.10620) Boundary_loss: 0.014933 (0.014898) Loss: 0.11154 (0.12110) +2025-08-25,03:57:56 | INFO | Train Epoch: 13 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.088300 (0.10607) Boundary_loss: 0.014838 (0.014898) Loss: 0.10314 (0.12096) +2025-08-25,03:58:53 | INFO | Train Epoch: 13 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.11038 (0.10610) Boundary_loss: 0.014914 (0.014898) Loss: 0.12530 (0.12100) +2025-08-25,03:59:49 | INFO | Train Epoch: 13 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.10662 (0.10610) Boundary_loss: 0.014892 (0.014898) Loss: 0.12151 (0.12100) +2025-08-25,04:00:45 | INFO | Train Epoch: 13 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.13807 (0.10634) Boundary_loss: 0.014887 (0.014898) Loss: 0.15295 (0.12124) +2025-08-25,04:01:42 | INFO | Train Epoch: 13 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.10484 (0.10633) Boundary_loss: 0.014824 (0.014897) Loss: 0.11967 (0.12123) +2025-08-25,04:02:38 | INFO | Train Epoch: 13 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.10497 (0.10632) Boundary_loss: 0.014863 (0.014897) Loss: 0.11983 (0.12122) +2025-08-25,04:03:35 | INFO | Train Epoch: 13 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.10257 (0.10629) Boundary_loss: 0.014988 (0.014898) Loss: 0.11756 (0.12119) +2025-08-25,04:04:31 | INFO | Train Epoch: 13 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.13449 (0.10650) Boundary_loss: 0.014903 (0.014898) Loss: 0.14939 (0.12140) +2025-08-25,04:05:27 | INFO | Train Epoch: 13 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.420 Boundary Ratio: 0.247 Contrastive_loss: 0.14284 (0.10676) Boundary_loss: 0.014866 (0.014897) Loss: 0.15770 (0.12166) +2025-08-25,04:06:24 | INFO | Train Epoch: 13 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.091744 (0.10665) Boundary_loss: 0.014845 (0.014897) Loss: 0.10659 (0.12155) +2025-08-25,04:07:20 | INFO | Train Epoch: 13 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.064103 (0.10635) Boundary_loss: 0.014774 (0.014896) Loss: 0.078877 (0.12125) +2025-08-25,04:08:17 | INFO | Train Epoch: 13 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.11708 (0.10643) Boundary_loss: 0.014949 (0.014897) Loss: 0.13203 (0.12132) +2025-08-25,04:09:13 | INFO | Train Epoch: 13 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.352 Boundary Ratio: 0.247 Contrastive_loss: 0.098259 (0.10637) Boundary_loss: 0.014827 (0.014896) Loss: 0.11309 (0.12126) +2025-08-25,04:10:09 | INFO | Train Epoch: 13 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 49.166 Boundary Ratio: 0.251 Contrastive_loss: 0.10881 (0.10639) Boundary_loss: 0.015015 (0.014897) Loss: 0.12383 (0.12128) +2025-08-25,04:11:06 | INFO | Train Epoch: 13 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.12163 (0.10649) Boundary_loss: 0.015037 (0.014898) Loss: 0.13667 (0.12139) +2025-08-25,04:12:02 | INFO | Train Epoch: 13 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.11493 (0.10655) Boundary_loss: 0.014930 (0.014898) Loss: 0.12986 (0.12145) +2025-08-25,04:12:58 | INFO | Train Epoch: 13 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.083259 (0.10639) Boundary_loss: 0.014876 (0.014898) Loss: 0.098135 (0.12129) +2025-08-25,04:13:55 | INFO | Train Epoch: 13 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.10830 (0.10640) Boundary_loss: 0.014889 (0.014898) Loss: 0.12319 (0.12130) +2025-08-25,04:14:51 | INFO | Train Epoch: 13 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.11386 (0.10645) Boundary_loss: 0.014905 (0.014898) Loss: 0.12877 (0.12135) +2025-08-25,04:15:47 | INFO | Train Epoch: 13 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.081463 (0.10629) Boundary_loss: 0.014880 (0.014898) Loss: 0.096343 (0.12118) +2025-08-25,04:16:44 | INFO | Train Epoch: 13 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.074802 (0.10608) Boundary_loss: 0.014876 (0.014898) Loss: 0.089677 (0.12098) +2025-08-25,04:17:40 | INFO | Train Epoch: 13 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.080087 (0.10591) Boundary_loss: 0.014874 (0.014898) Loss: 0.094961 (0.12080) +2025-08-25,04:18:36 | INFO | Train Epoch: 13 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.11350 (0.10596) Boundary_loss: 0.014940 (0.014898) Loss: 0.12844 (0.12085) +2025-08-25,04:19:33 | INFO | Train Epoch: 13 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.11033 (0.10598) Boundary_loss: 0.014908 (0.014898) Loss: 0.12524 (0.12088) +2025-08-25,04:20:29 | INFO | Train Epoch: 13 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.10573 (0.10598) Boundary_loss: 0.014908 (0.014898) Loss: 0.12064 (0.12088) +2025-08-25,04:21:26 | INFO | Train Epoch: 13 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.11331 (0.10603) Boundary_loss: 0.014927 (0.014898) Loss: 0.12824 (0.12093) +2025-08-25,04:22:22 | INFO | Train Epoch: 13 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10495 (0.10602) Boundary_loss: 0.014931 (0.014898) Loss: 0.11988 (0.12092) +2025-08-25,04:23:19 | INFO | Train Epoch: 13 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.082938 (0.10588) Boundary_loss: 0.014788 (0.014898) Loss: 0.097726 (0.12077) +2025-08-25,04:24:15 | INFO | Train Epoch: 13 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.11467 (0.10593) Boundary_loss: 0.014933 (0.014898) Loss: 0.12960 (0.12083) +2025-08-25,04:25:11 | INFO | Train Epoch: 13 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 48.262 Boundary Ratio: 0.246 Contrastive_loss: 0.091316 (0.10584) Boundary_loss: 0.014936 (0.014898) Loss: 0.10625 (0.12074) +2025-08-25,04:26:08 | INFO | Train Epoch: 13 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 0.15809 (0.10617) Boundary_loss: 0.015015 (0.014899) Loss: 0.17311 (0.12106) +2025-08-25,04:27:04 | INFO | Train Epoch: 13 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.098995 (0.10612) Boundary_loss: 0.014819 (0.014898) Loss: 0.11381 (0.12102) +2025-08-25,04:28:00 | INFO | Train Epoch: 13 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.11081 (0.10615) Boundary_loss: 0.014862 (0.014898) Loss: 0.12567 (0.12105) +2025-08-25,04:28:57 | INFO | Train Epoch: 13 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.10483 (0.10614) Boundary_loss: 0.014992 (0.014899) Loss: 0.11982 (0.12104) +2025-08-25,04:29:53 | INFO | Train Epoch: 13 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.10386 (0.10613) Boundary_loss: 0.014809 (0.014898) Loss: 0.11867 (0.12103) +2025-08-25,04:30:50 | INFO | Train Epoch: 13 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 49.049 Boundary Ratio: 0.250 Contrastive_loss: 0.11594 (0.10619) Boundary_loss: 0.014860 (0.014898) Loss: 0.13080 (0.12109) +2025-08-25,04:31:46 | INFO | Train Epoch: 13 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.091693 (0.10610) Boundary_loss: 0.014907 (0.014898) Loss: 0.10660 (0.12100) +2025-08-25,04:32:43 | INFO | Train Epoch: 13 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.093228 (0.10602) Boundary_loss: 0.014913 (0.014898) Loss: 0.10814 (0.12092) +2025-08-25,04:33:39 | INFO | Train Epoch: 13 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.11730 (0.10609) Boundary_loss: 0.014843 (0.014898) Loss: 0.13214 (0.12099) +2025-08-25,04:34:35 | INFO | Train Epoch: 13 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.14538 (0.10632) Boundary_loss: 0.014810 (0.014897) Loss: 0.16019 (0.12122) +2025-08-25,04:35:32 | INFO | Train Epoch: 13 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.12229 (0.10642) Boundary_loss: 0.014742 (0.014896) Loss: 0.13703 (0.12131) +2025-08-25,04:36:28 | INFO | Train Epoch: 13 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.11111 (0.10644) Boundary_loss: 0.014899 (0.014896) Loss: 0.12601 (0.12134) +2025-08-25,04:37:24 | INFO | Train Epoch: 13 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.13172 (0.10659) Boundary_loss: 0.014912 (0.014896) Loss: 0.14663 (0.12148) +2025-08-25,04:38:21 | INFO | Train Epoch: 13 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.11028 (0.10661) Boundary_loss: 0.014864 (0.014896) Loss: 0.12515 (0.12151) +2025-08-25,04:39:17 | INFO | Train Epoch: 13 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.098510 (0.10656) Boundary_loss: 0.014902 (0.014896) Loss: 0.11341 (0.12146) +2025-08-25,04:40:13 | INFO | Train Epoch: 13 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.083397 (0.10643) Boundary_loss: 0.015002 (0.014897) Loss: 0.098399 (0.12133) +2025-08-25,04:41:10 | INFO | Train Epoch: 13 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.096047 (0.10637) Boundary_loss: 0.015003 (0.014897) Loss: 0.11105 (0.12127) +2025-08-25,04:42:06 | INFO | Train Epoch: 13 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 49.086 Boundary Ratio: 0.250 Contrastive_loss: 0.10588 (0.10637) Boundary_loss: 0.014901 (0.014897) Loss: 0.12078 (0.12127) +2025-08-25,04:43:02 | INFO | Train Epoch: 13 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.099740 (0.10633) Boundary_loss: 0.014919 (0.014898) Loss: 0.11466 (0.12123) +2025-08-25,04:43:59 | INFO | Train Epoch: 13 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.11928 (0.10641) Boundary_loss: 0.014862 (0.014897) Loss: 0.13414 (0.12130) +2025-08-25,04:44:55 | INFO | Train Epoch: 13 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 49.045 Boundary Ratio: 0.250 Contrastive_loss: 0.097588 (0.10636) Boundary_loss: 0.014824 (0.014897) Loss: 0.11241 (0.12125) +2025-08-25,04:45:51 | INFO | Train Epoch: 13 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.10218 (0.10633) Boundary_loss: 0.014943 (0.014897) Loss: 0.11713 (0.12123) +2025-08-25,04:46:48 | INFO | Train Epoch: 13 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.13427 (0.10649) Boundary_loss: 0.014960 (0.014898) Loss: 0.14923 (0.12138) +2025-08-25,04:47:44 | INFO | Train Epoch: 13 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.099151 (0.10645) Boundary_loss: 0.014927 (0.014898) Loss: 0.11408 (0.12134) +2025-08-25,04:48:41 | INFO | Train Epoch: 13 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.10678 (0.10645) Boundary_loss: 0.014836 (0.014897) Loss: 0.12161 (0.12135) +2025-08-25,04:49:37 | INFO | Train Epoch: 13 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.502 Boundary Ratio: 0.247 Contrastive_loss: 0.10529 (0.10644) Boundary_loss: 0.014886 (0.014897) Loss: 0.12017 (0.12134) +2025-08-25,04:50:33 | INFO | Train Epoch: 13 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.11072 (0.10646) Boundary_loss: 0.014921 (0.014897) Loss: 0.12564 (0.12136) +2025-08-25,04:51:30 | INFO | Train Epoch: 13 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.10422 (0.10645) Boundary_loss: 0.014698 (0.014896) Loss: 0.11892 (0.12135) +2025-08-25,04:52:26 | INFO | Train Epoch: 13 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.095084 (0.10639) Boundary_loss: 0.014881 (0.014896) Loss: 0.10996 (0.12129) +2025-08-25,04:53:22 | INFO | Train Epoch: 13 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.12800 (0.10651) Boundary_loss: 0.014949 (0.014897) Loss: 0.14295 (0.12140) +2025-08-25,04:54:19 | INFO | Train Epoch: 13 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.13763 (0.10667) Boundary_loss: 0.014892 (0.014897) Loss: 0.15252 (0.12157) +2025-08-25,04:55:15 | INFO | Train Epoch: 13 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.11780 (0.10673) Boundary_loss: 0.014870 (0.014896) Loss: 0.13267 (0.12162) +2025-08-25,04:56:12 | INFO | Train Epoch: 13 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11919 (0.10679) Boundary_loss: 0.014895 (0.014896) Loss: 0.13408 (0.12169) +2025-08-25,04:57:08 | INFO | Train Epoch: 13 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.340 Boundary Ratio: 0.247 Contrastive_loss: 0.10253 (0.10677) Boundary_loss: 0.014845 (0.014896) Loss: 0.11737 (0.12167) +2025-08-25,04:58:05 | INFO | Train Epoch: 13 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.090380 (0.10669) Boundary_loss: 0.014869 (0.014896) Loss: 0.10525 (0.12158) +2025-08-25,04:59:01 | INFO | Train Epoch: 13 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.13315 (0.10682) Boundary_loss: 0.014977 (0.014896) Loss: 0.14813 (0.12172) +2025-08-25,04:59:57 | INFO | Train Epoch: 13 [10035712/26365952 (38%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.15632 (0.10707) Boundary_loss: 0.014922 (0.014897) Loss: 0.17124 (0.12197) +2025-08-25,05:00:54 | INFO | Train Epoch: 13 [10086912/26365952 (38%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.14202 (0.10725) Boundary_loss: 0.014858 (0.014896) Loss: 0.15688 (0.12215) +2025-08-25,05:01:50 | INFO | Train Epoch: 13 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.13729 (0.10740) Boundary_loss: 0.014864 (0.014896) Loss: 0.15216 (0.12230) +2025-08-25,05:02:47 | INFO | Train Epoch: 13 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.097928 (0.10735) Boundary_loss: 0.014875 (0.014896) Loss: 0.11280 (0.12225) +2025-08-25,05:03:43 | INFO | Train Epoch: 13 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.093441 (0.10728) Boundary_loss: 0.014795 (0.014896) Loss: 0.10824 (0.12218) +2025-08-25,05:04:39 | INFO | Train Epoch: 13 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.11380 (0.10732) Boundary_loss: 0.014923 (0.014896) Loss: 0.12873 (0.12221) +2025-08-25,05:05:36 | INFO | Train Epoch: 13 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.11443 (0.10735) Boundary_loss: 0.014883 (0.014896) Loss: 0.12931 (0.12225) +2025-08-25,05:06:32 | INFO | Train Epoch: 13 [10394112/26365952 (39%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.085492 (0.10724) Boundary_loss: 0.014955 (0.014896) Loss: 0.10045 (0.12214) +2025-08-25,05:07:28 | INFO | Train Epoch: 13 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.077520 (0.10710) Boundary_loss: 0.014858 (0.014896) Loss: 0.092379 (0.12199) +2025-08-25,05:08:25 | INFO | Train Epoch: 13 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.10379 (0.10708) Boundary_loss: 0.014887 (0.014896) Loss: 0.11868 (0.12198) +2025-08-25,05:09:21 | INFO | Train Epoch: 13 [10547712/26365952 (40%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.095887 (0.10703) Boundary_loss: 0.014821 (0.014895) Loss: 0.11071 (0.12192) +2025-08-25,05:10:18 | INFO | Train Epoch: 13 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.088389 (0.10694) Boundary_loss: 0.014812 (0.014895) Loss: 0.10320 (0.12183) +2025-08-25,05:11:14 | INFO | Train Epoch: 13 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.680 Boundary Ratio: 0.248 Contrastive_loss: 0.084072 (0.10683) Boundary_loss: 0.014816 (0.014895) Loss: 0.098888 (0.12172) +2025-08-25,05:12:10 | INFO | Train Epoch: 13 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.998 Boundary Ratio: 0.250 Contrastive_loss: 0.11748 (0.10688) Boundary_loss: 0.014850 (0.014894) Loss: 0.13234 (0.12177) +2025-08-25,05:13:07 | INFO | Train Epoch: 13 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.12236 (0.10695) Boundary_loss: 0.014844 (0.014894) Loss: 0.13721 (0.12185) +2025-08-25,05:14:03 | INFO | Train Epoch: 13 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.16647 (0.10723) Boundary_loss: 0.014889 (0.014894) Loss: 0.18136 (0.12213) +2025-08-25,05:14:59 | INFO | Train Epoch: 13 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.10151 (0.10721) Boundary_loss: 0.014809 (0.014894) Loss: 0.11632 (0.12210) +2025-08-25,05:15:56 | INFO | Train Epoch: 13 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.12667 (0.10730) Boundary_loss: 0.014957 (0.014894) Loss: 0.14163 (0.12219) +2025-08-25,05:16:52 | INFO | Train Epoch: 13 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.11953 (0.10735) Boundary_loss: 0.014940 (0.014894) Loss: 0.13447 (0.12225) +2025-08-25,05:17:48 | INFO | Train Epoch: 13 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.092688 (0.10729) Boundary_loss: 0.014861 (0.014894) Loss: 0.10755 (0.12218) +2025-08-25,05:18:45 | INFO | Train Epoch: 13 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.14198 (0.10745) Boundary_loss: 0.014967 (0.014894) Loss: 0.15695 (0.12234) +2025-08-25,05:19:41 | INFO | Train Epoch: 13 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.095553 (0.10739) Boundary_loss: 0.014955 (0.014895) Loss: 0.11051 (0.12229) +2025-08-25,05:20:38 | INFO | Train Epoch: 13 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.10958 (0.10740) Boundary_loss: 0.015032 (0.014895) Loss: 0.12461 (0.12230) +2025-08-25,05:21:34 | INFO | Train Epoch: 13 [11213312/26365952 (43%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.081219 (0.10728) Boundary_loss: 0.014925 (0.014895) Loss: 0.096144 (0.12218) +2025-08-25,05:22:30 | INFO | Train Epoch: 13 [11264512/26365952 (43%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.093023 (0.10722) Boundary_loss: 0.014817 (0.014895) Loss: 0.10784 (0.12211) +2025-08-25,05:23:27 | INFO | Train Epoch: 13 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.089566 (0.10714) Boundary_loss: 0.014852 (0.014895) Loss: 0.10442 (0.12203) +2025-08-25,05:24:23 | INFO | Train Epoch: 13 [11366912/26365952 (43%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.077033 (0.10700) Boundary_loss: 0.014969 (0.014895) Loss: 0.092002 (0.12190) +2025-08-25,05:25:20 | INFO | Train Epoch: 13 [11418112/26365952 (43%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.14150 (0.10716) Boundary_loss: 0.014758 (0.014895) Loss: 0.15626 (0.12205) +2025-08-25,05:26:16 | INFO | Train Epoch: 13 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.13445 (0.10728) Boundary_loss: 0.014841 (0.014894) Loss: 0.14929 (0.12217) +2025-08-25,05:27:13 | INFO | Train Epoch: 13 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.10701 (0.10728) Boundary_loss: 0.014882 (0.014894) Loss: 0.12189 (0.12217) +2025-08-25,05:28:09 | INFO | Train Epoch: 13 [11571712/26365952 (44%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.11689 (0.10732) Boundary_loss: 0.014954 (0.014895) Loss: 0.13185 (0.12222) +2025-08-25,05:29:05 | INFO | Train Epoch: 13 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.089658 (0.10724) Boundary_loss: 0.014903 (0.014895) Loss: 0.10456 (0.12214) +2025-08-25,05:30:02 | INFO | Train Epoch: 13 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.092166 (0.10718) Boundary_loss: 0.015004 (0.014895) Loss: 0.10717 (0.12207) +2025-08-25,05:30:58 | INFO | Train Epoch: 13 [11725312/26365952 (44%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.095463 (0.10713) Boundary_loss: 0.014817 (0.014895) Loss: 0.11028 (0.12202) +2025-08-25,05:31:54 | INFO | Train Epoch: 13 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.10277 (0.10711) Boundary_loss: 0.014884 (0.014895) Loss: 0.11765 (0.12200) +2025-08-25,05:32:51 | INFO | Train Epoch: 13 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.094729 (0.10705) Boundary_loss: 0.014877 (0.014895) Loss: 0.10961 (0.12195) +2025-08-25,05:33:47 | INFO | Train Epoch: 13 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.693 Boundary Ratio: 0.248 Contrastive_loss: 0.12091 (0.10711) Boundary_loss: 0.014905 (0.014895) Loss: 0.13582 (0.12201) +2025-08-25,05:34:43 | INFO | Train Epoch: 13 [11930112/26365952 (45%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.12089 (0.10717) Boundary_loss: 0.014947 (0.014895) Loss: 0.13584 (0.12207) +2025-08-25,05:35:40 | INFO | Train Epoch: 13 [11981312/26365952 (45%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.092943 (0.10711) Boundary_loss: 0.014849 (0.014895) Loss: 0.10779 (0.12201) +2025-08-25,05:36:36 | INFO | Train Epoch: 13 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.428 Boundary Ratio: 0.247 Contrastive_loss: 0.083660 (0.10701) Boundary_loss: 0.014948 (0.014895) Loss: 0.098609 (0.12191) +2025-08-25,05:37:32 | INFO | Train Epoch: 13 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.11420 (0.10704) Boundary_loss: 0.014987 (0.014895) Loss: 0.12919 (0.12194) +2025-08-25,05:38:29 | INFO | Train Epoch: 13 [12134912/26365952 (46%)] Avg Boundaries (per batch): 49.094 Boundary Ratio: 0.250 Contrastive_loss: 0.098922 (0.10701) Boundary_loss: 0.014812 (0.014895) Loss: 0.11373 (0.12190) +2025-08-25,05:39:25 | INFO | Train Epoch: 13 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.12945 (0.10710) Boundary_loss: 0.015079 (0.014896) Loss: 0.14453 (0.12200) +2025-08-25,05:40:22 | INFO | Train Epoch: 13 [12237312/26365952 (46%)] Avg Boundaries (per batch): 48.670 Boundary Ratio: 0.248 Contrastive_loss: 0.085353 (0.10701) Boundary_loss: 0.014890 (0.014896) Loss: 0.10024 (0.12191) +2025-08-25,05:41:18 | INFO | Train Epoch: 13 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.092108 (0.10695) Boundary_loss: 0.014862 (0.014896) Loss: 0.10697 (0.12185) +2025-08-25,05:42:14 | INFO | Train Epoch: 13 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.578 Boundary Ratio: 0.248 Contrastive_loss: 0.11835 (0.10700) Boundary_loss: 0.014883 (0.014896) Loss: 0.13323 (0.12189) +2025-08-25,05:43:11 | INFO | Train Epoch: 13 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.857 Boundary Ratio: 0.249 Contrastive_loss: 0.13486 (0.10711) Boundary_loss: 0.015001 (0.014896) Loss: 0.14986 (0.12201) +2025-08-25,05:44:07 | INFO | Train Epoch: 13 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.549 Boundary Ratio: 0.248 Contrastive_loss: 0.099672 (0.10708) Boundary_loss: 0.014964 (0.014896) Loss: 0.11464 (0.12198) +2025-08-25,05:45:04 | INFO | Train Epoch: 13 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.11572 (0.10712) Boundary_loss: 0.014936 (0.014896) Loss: 0.13066 (0.12201) +2025-08-25,05:46:00 | INFO | Train Epoch: 13 [12544512/26365952 (48%)] Avg Boundaries (per batch): 48.463 Boundary Ratio: 0.247 Contrastive_loss: 0.10705 (0.10712) Boundary_loss: 0.014799 (0.014896) Loss: 0.12185 (0.12201) +2025-08-25,05:46:57 | INFO | Train Epoch: 13 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.096417 (0.10707) Boundary_loss: 0.014909 (0.014896) Loss: 0.11133 (0.12197) +2025-08-25,05:47:53 | INFO | Train Epoch: 13 [12646912/26365952 (48%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.075564 (0.10695) Boundary_loss: 0.014997 (0.014896) Loss: 0.090561 (0.12184) +2025-08-25,05:48:49 | INFO | Train Epoch: 13 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.10585 (0.10694) Boundary_loss: 0.015027 (0.014897) Loss: 0.12088 (0.12184) +2025-08-25,05:49:46 | INFO | Train Epoch: 13 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.957 Boundary Ratio: 0.250 Contrastive_loss: 0.085256 (0.10686) Boundary_loss: 0.014770 (0.014896) Loss: 0.10003 (0.12175) +2025-08-25,05:50:42 | INFO | Train Epoch: 13 [12800512/26365952 (49%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.079693 (0.10675) Boundary_loss: 0.014876 (0.014896) Loss: 0.094569 (0.12164) +2025-08-25,05:51:38 | INFO | Train Epoch: 13 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.095479 (0.10670) Boundary_loss: 0.014831 (0.014896) Loss: 0.11031 (0.12160) +2025-08-25,05:52:34 | INFO | Train Epoch: 13 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.11416 (0.10673) Boundary_loss: 0.014902 (0.014896) Loss: 0.12906 (0.12163) +2025-08-25,05:53:31 | INFO | Train Epoch: 13 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.14900 (0.10690) Boundary_loss: 0.014860 (0.014896) Loss: 0.16386 (0.12179) +2025-08-25,05:54:27 | INFO | Train Epoch: 13 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.099244 (0.10687) Boundary_loss: 0.014880 (0.014896) Loss: 0.11412 (0.12176) +2025-08-25,05:55:23 | INFO | Train Epoch: 13 [13056512/26365952 (50%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.096729 (0.10683) Boundary_loss: 0.014966 (0.014896) Loss: 0.11170 (0.12172) +2025-08-25,05:56:20 | INFO | Train Epoch: 13 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.10485 (0.10682) Boundary_loss: 0.014842 (0.014896) Loss: 0.11969 (0.12172) +2025-08-25,05:57:16 | INFO | Train Epoch: 13 [13158912/26365952 (50%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.089406 (0.10675) Boundary_loss: 0.015008 (0.014896) Loss: 0.10441 (0.12165) +2025-08-25,05:58:13 | INFO | Train Epoch: 13 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.11023 (0.10677) Boundary_loss: 0.014909 (0.014896) Loss: 0.12514 (0.12166) +2025-08-25,05:59:09 | INFO | Train Epoch: 13 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.771 Boundary Ratio: 0.249 Contrastive_loss: 0.10708 (0.10677) Boundary_loss: 0.014736 (0.014896) Loss: 0.12181 (0.12166) +2025-08-25,06:00:05 | INFO | Train Epoch: 13 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.073234 (0.10664) Boundary_loss: 0.014987 (0.014896) Loss: 0.088221 (0.12154) +2025-08-25,06:01:02 | INFO | Train Epoch: 13 [13363712/26365952 (51%)] Avg Boundaries (per batch): 49.115 Boundary Ratio: 0.251 Contrastive_loss: 0.087562 (0.10657) Boundary_loss: 0.014998 (0.014897) Loss: 0.10256 (0.12146) +2025-08-25,06:01:58 | INFO | Train Epoch: 13 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.093265 (0.10652) Boundary_loss: 0.014847 (0.014896) Loss: 0.10811 (0.12141) +2025-08-25,06:02:55 | INFO | Train Epoch: 13 [13466112/26365952 (51%)] Avg Boundaries (per batch): 49.104 Boundary Ratio: 0.251 Contrastive_loss: 0.11500 (0.10655) Boundary_loss: 0.014846 (0.014896) Loss: 0.12985 (0.12144) +2025-08-25,06:03:51 | INFO | Train Epoch: 13 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.11406 (0.10658) Boundary_loss: 0.014872 (0.014896) Loss: 0.12893 (0.12147) +2025-08-25,06:04:47 | INFO | Train Epoch: 13 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.098401 (0.10655) Boundary_loss: 0.014955 (0.014896) Loss: 0.11336 (0.12144) +2025-08-25,06:05:44 | INFO | Train Epoch: 13 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.068916 (0.10640) Boundary_loss: 0.014954 (0.014897) Loss: 0.083869 (0.12130) +2025-08-25,06:06:40 | INFO | Train Epoch: 13 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.10568 (0.10640) Boundary_loss: 0.014893 (0.014897) Loss: 0.12057 (0.12130) +2025-08-25,06:07:36 | INFO | Train Epoch: 13 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.093233 (0.10635) Boundary_loss: 0.014860 (0.014896) Loss: 0.10809 (0.12125) +2025-08-25,06:08:33 | INFO | Train Epoch: 13 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.895 Boundary Ratio: 0.249 Contrastive_loss: 0.12271 (0.10641) Boundary_loss: 0.014875 (0.014896) Loss: 0.13759 (0.12131) +2025-08-25,06:09:29 | INFO | Train Epoch: 13 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.561 Boundary Ratio: 0.248 Contrastive_loss: 0.084932 (0.10633) Boundary_loss: 0.014907 (0.014896) Loss: 0.099839 (0.12123) +2025-08-25,06:10:26 | INFO | Train Epoch: 13 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.093183 (0.10629) Boundary_loss: 0.014815 (0.014896) Loss: 0.10800 (0.12118) +2025-08-25,06:11:22 | INFO | Train Epoch: 13 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.10840 (0.10629) Boundary_loss: 0.014973 (0.014896) Loss: 0.12337 (0.12119) +2025-08-25,06:12:18 | INFO | Train Epoch: 13 [13978112/26365952 (53%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.083624 (0.10621) Boundary_loss: 0.014940 (0.014897) Loss: 0.098563 (0.12111) +2025-08-25,06:13:15 | INFO | Train Epoch: 13 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.11484 (0.10624) Boundary_loss: 0.014893 (0.014897) Loss: 0.12973 (0.12114) +2025-08-25,06:14:11 | INFO | Train Epoch: 13 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.094131 (0.10620) Boundary_loss: 0.014815 (0.014896) Loss: 0.10895 (0.12109) +2025-08-25,06:15:08 | INFO | Train Epoch: 13 [14131712/26365952 (54%)] Avg Boundaries (per batch): 49.188 Boundary Ratio: 0.251 Contrastive_loss: 0.092695 (0.10615) Boundary_loss: 0.014947 (0.014896) Loss: 0.10764 (0.12105) +2025-08-25,06:16:04 | INFO | Train Epoch: 13 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.10868 (0.10616) Boundary_loss: 0.014912 (0.014896) Loss: 0.12359 (0.12106) +2025-08-25,06:17:00 | INFO | Train Epoch: 13 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.10616 (0.10616) Boundary_loss: 0.014953 (0.014897) Loss: 0.12112 (0.12106) +2025-08-25,06:17:57 | INFO | Train Epoch: 13 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.11410 (0.10619) Boundary_loss: 0.014909 (0.014897) Loss: 0.12901 (0.12108) +2025-08-25,06:18:53 | INFO | Train Epoch: 13 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.893 Boundary Ratio: 0.249 Contrastive_loss: 0.17659 (0.10644) Boundary_loss: 0.014774 (0.014896) Loss: 0.19136 (0.12133) +2025-08-25,06:19:49 | INFO | Train Epoch: 13 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.10645 (0.10644) Boundary_loss: 0.014827 (0.014896) Loss: 0.12127 (0.12133) +2025-08-25,06:20:46 | INFO | Train Epoch: 13 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.083939 (0.10636) Boundary_loss: 0.014971 (0.014896) Loss: 0.098910 (0.12125) +2025-08-25,06:21:42 | INFO | Train Epoch: 13 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.436 Boundary Ratio: 0.247 Contrastive_loss: 0.11402 (0.10639) Boundary_loss: 0.014956 (0.014897) Loss: 0.12897 (0.12128) +2025-08-25,06:22:38 | INFO | Train Epoch: 13 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.073399 (0.10627) Boundary_loss: 0.014863 (0.014896) Loss: 0.088262 (0.12117) +2025-08-25,06:23:35 | INFO | Train Epoch: 13 [14592512/26365952 (55%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.095590 (0.10623) Boundary_loss: 0.014889 (0.014896) Loss: 0.11048 (0.12113) +2025-08-25,06:24:31 | INFO | Train Epoch: 13 [14643712/26365952 (56%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.093847 (0.10619) Boundary_loss: 0.014886 (0.014896) Loss: 0.10873 (0.12109) +2025-08-25,06:25:28 | INFO | Train Epoch: 13 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.099228 (0.10616) Boundary_loss: 0.014962 (0.014897) Loss: 0.11419 (0.12106) +2025-08-25,06:26:24 | INFO | Train Epoch: 13 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.072372 (0.10605) Boundary_loss: 0.014903 (0.014897) Loss: 0.087274 (0.12094) +2025-08-25,06:27:20 | INFO | Train Epoch: 13 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.643 Boundary Ratio: 0.248 Contrastive_loss: 0.071430 (0.10593) Boundary_loss: 0.014852 (0.014896) Loss: 0.086282 (0.12083) +2025-08-25,06:28:17 | INFO | Train Epoch: 13 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.975 Boundary Ratio: 0.250 Contrastive_loss: 0.11947 (0.10598) Boundary_loss: 0.014842 (0.014896) Loss: 0.13431 (0.12087) +2025-08-25,06:29:13 | INFO | Train Epoch: 13 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.12952 (0.10606) Boundary_loss: 0.014972 (0.014896) Loss: 0.14450 (0.12095) +2025-08-25,06:30:09 | INFO | Train Epoch: 13 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.13851 (0.10617) Boundary_loss: 0.014925 (0.014897) Loss: 0.15344 (0.12106) +2025-08-25,06:31:06 | INFO | Train Epoch: 13 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.083657 (0.10609) Boundary_loss: 0.015006 (0.014897) Loss: 0.098663 (0.12099) +2025-08-25,06:32:02 | INFO | Train Epoch: 13 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.13552 (0.10619) Boundary_loss: 0.014884 (0.014897) Loss: 0.15040 (0.12109) +2025-08-25,06:32:58 | INFO | Train Epoch: 13 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.060917 (0.10604) Boundary_loss: 0.014837 (0.014897) Loss: 0.075754 (0.12093) +2025-08-25,06:33:55 | INFO | Train Epoch: 13 [15155712/26365952 (57%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.093936 (0.10600) Boundary_loss: 0.014871 (0.014897) Loss: 0.10881 (0.12089) +2025-08-25,06:34:51 | INFO | Train Epoch: 13 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.096734 (0.10596) Boundary_loss: 0.014855 (0.014896) Loss: 0.11159 (0.12086) +2025-08-25,06:35:47 | INFO | Train Epoch: 13 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.096918 (0.10593) Boundary_loss: 0.014848 (0.014896) Loss: 0.11177 (0.12083) +2025-08-25,06:36:44 | INFO | Train Epoch: 13 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.13729 (0.10604) Boundary_loss: 0.014899 (0.014896) Loss: 0.15219 (0.12094) +2025-08-25,06:37:40 | INFO | Train Epoch: 13 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.10382 (0.10603) Boundary_loss: 0.014782 (0.014896) Loss: 0.11860 (0.12093) +2025-08-25,06:38:37 | INFO | Train Epoch: 13 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.14345 (0.10616) Boundary_loss: 0.014880 (0.014896) Loss: 0.15833 (0.12105) +2025-08-25,06:39:33 | INFO | Train Epoch: 13 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.799 Boundary Ratio: 0.249 Contrastive_loss: 0.11052 (0.10617) Boundary_loss: 0.014972 (0.014896) Loss: 0.12550 (0.12107) +2025-08-25,06:40:29 | INFO | Train Epoch: 13 [15514112/26365952 (59%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.11493 (0.10620) Boundary_loss: 0.014942 (0.014896) Loss: 0.12987 (0.12110) +2025-08-25,06:41:26 | INFO | Train Epoch: 13 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.604 Boundary Ratio: 0.248 Contrastive_loss: 0.11693 (0.10623) Boundary_loss: 0.015024 (0.014897) Loss: 0.13196 (0.12113) +2025-08-25,06:42:22 | INFO | Train Epoch: 13 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.095324 (0.10620) Boundary_loss: 0.014924 (0.014897) Loss: 0.11025 (0.12110) +2025-08-25,06:43:18 | INFO | Train Epoch: 13 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.097653 (0.10617) Boundary_loss: 0.014875 (0.014897) Loss: 0.11253 (0.12107) +2025-08-25,06:44:15 | INFO | Train Epoch: 13 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.11006 (0.10618) Boundary_loss: 0.014857 (0.014897) Loss: 0.12491 (0.12108) +2025-08-25,06:45:11 | INFO | Train Epoch: 13 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.097137 (0.10615) Boundary_loss: 0.014894 (0.014897) Loss: 0.11203 (0.12105) +2025-08-25,06:46:07 | INFO | Train Epoch: 13 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.087757 (0.10609) Boundary_loss: 0.014924 (0.014897) Loss: 0.10268 (0.12099) +2025-08-25,06:47:04 | INFO | Train Epoch: 13 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.775 Boundary Ratio: 0.249 Contrastive_loss: 0.081399 (0.10602) Boundary_loss: 0.014870 (0.014897) Loss: 0.096269 (0.12091) +2025-08-25,06:48:00 | INFO | Train Epoch: 13 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.13377 (0.10610) Boundary_loss: 0.014963 (0.014897) Loss: 0.14873 (0.12100) +2025-08-25,06:48:56 | INFO | Train Epoch: 13 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.090948 (0.10606) Boundary_loss: 0.015001 (0.014897) Loss: 0.10595 (0.12095) +2025-08-25,06:49:52 | INFO | Train Epoch: 13 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.338 Boundary Ratio: 0.247 Contrastive_loss: 0.095965 (0.10602) Boundary_loss: 0.014785 (0.014897) Loss: 0.11075 (0.12092) +2025-08-25,06:50:49 | INFO | Train Epoch: 13 [16077312/26365952 (61%)] Avg Boundaries (per batch): 48.977 Boundary Ratio: 0.250 Contrastive_loss: 0.090734 (0.10598) Boundary_loss: 0.014832 (0.014897) Loss: 0.10557 (0.12087) +2025-08-25,06:51:45 | INFO | Train Epoch: 13 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.099333 (0.10595) Boundary_loss: 0.014885 (0.014897) Loss: 0.11422 (0.12085) +2025-08-25,06:52:41 | INFO | Train Epoch: 13 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.098374 (0.10593) Boundary_loss: 0.014965 (0.014897) Loss: 0.11334 (0.12083) +2025-08-25,06:53:38 | INFO | Train Epoch: 13 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.11498 (0.10596) Boundary_loss: 0.014902 (0.014897) Loss: 0.12989 (0.12086) +2025-08-25,06:54:34 | INFO | Train Epoch: 13 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.10401 (0.10595) Boundary_loss: 0.014850 (0.014897) Loss: 0.11886 (0.12085) +2025-08-25,06:55:30 | INFO | Train Epoch: 13 [16333312/26365952 (62%)] Avg Boundaries (per batch): 49.039 Boundary Ratio: 0.250 Contrastive_loss: 0.10496 (0.10595) Boundary_loss: 0.014974 (0.014897) Loss: 0.11993 (0.12085) +2025-08-25,06:56:27 | INFO | Train Epoch: 13 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.10484 (0.10595) Boundary_loss: 0.014811 (0.014897) Loss: 0.11965 (0.12084) +2025-08-25,06:57:23 | INFO | Train Epoch: 13 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.11144 (0.10596) Boundary_loss: 0.014858 (0.014896) Loss: 0.12630 (0.12086) +2025-08-25,06:58:20 | INFO | Train Epoch: 13 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.074292 (0.10586) Boundary_loss: 0.014920 (0.014897) Loss: 0.089212 (0.12076) +2025-08-25,06:59:16 | INFO | Train Epoch: 13 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.11046 (0.10588) Boundary_loss: 0.014887 (0.014897) Loss: 0.12535 (0.12078) +2025-08-25,07:00:12 | INFO | Train Epoch: 13 [16589312/26365952 (63%)] Avg Boundaries (per batch): 49.137 Boundary Ratio: 0.251 Contrastive_loss: 0.10188 (0.10587) Boundary_loss: 0.014854 (0.014896) Loss: 0.11674 (0.12076) +2025-08-25,07:01:09 | INFO | Train Epoch: 13 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.10861 (0.10588) Boundary_loss: 0.015045 (0.014897) Loss: 0.12365 (0.12077) +2025-08-25,07:02:05 | INFO | Train Epoch: 13 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.086015 (0.10581) Boundary_loss: 0.014902 (0.014897) Loss: 0.10092 (0.12071) +2025-08-25,07:03:01 | INFO | Train Epoch: 13 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.654 Boundary Ratio: 0.248 Contrastive_loss: 0.081885 (0.10574) Boundary_loss: 0.014879 (0.014897) Loss: 0.096763 (0.12064) +2025-08-25,07:03:58 | INFO | Train Epoch: 13 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.12133 (0.10579) Boundary_loss: 0.014949 (0.014897) Loss: 0.13628 (0.12069) +2025-08-25,07:04:54 | INFO | Train Epoch: 13 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.10205 (0.10578) Boundary_loss: 0.014749 (0.014897) Loss: 0.11680 (0.12067) +2025-08-25,07:05:51 | INFO | Train Epoch: 13 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.095071 (0.10575) Boundary_loss: 0.014913 (0.014897) Loss: 0.10998 (0.12064) +2025-08-25,07:06:47 | INFO | Train Epoch: 13 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.082014 (0.10567) Boundary_loss: 0.014855 (0.014896) Loss: 0.096869 (0.12057) +2025-08-25,07:07:44 | INFO | Train Epoch: 13 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.098302 (0.10565) Boundary_loss: 0.014958 (0.014897) Loss: 0.11326 (0.12055) +2025-08-25,07:08:40 | INFO | Train Epoch: 13 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.12192 (0.10570) Boundary_loss: 0.014832 (0.014896) Loss: 0.13675 (0.12060) +2025-08-25,07:09:36 | INFO | Train Epoch: 13 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.077309 (0.10562) Boundary_loss: 0.014948 (0.014897) Loss: 0.092256 (0.12051) +2025-08-25,07:10:33 | INFO | Train Epoch: 13 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.099053 (0.10560) Boundary_loss: 0.014891 (0.014897) Loss: 0.11394 (0.12049) +2025-08-25,07:11:29 | INFO | Train Epoch: 13 [17203712/26365952 (65%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.084700 (0.10553) Boundary_loss: 0.014827 (0.014896) Loss: 0.099528 (0.12043) +2025-08-25,07:12:25 | INFO | Train Epoch: 13 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.11638 (0.10557) Boundary_loss: 0.014934 (0.014896) Loss: 0.13131 (0.12046) +2025-08-25,07:13:22 | INFO | Train Epoch: 13 [17306112/26365952 (66%)] Avg Boundaries (per batch): 49.174 Boundary Ratio: 0.251 Contrastive_loss: 0.084020 (0.10550) Boundary_loss: 0.014968 (0.014897) Loss: 0.098988 (0.12040) +2025-08-25,07:14:18 | INFO | Train Epoch: 13 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.12187 (0.10555) Boundary_loss: 0.015009 (0.014897) Loss: 0.13688 (0.12045) +2025-08-25,07:15:14 | INFO | Train Epoch: 13 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.098955 (0.10553) Boundary_loss: 0.014850 (0.014897) Loss: 0.11380 (0.12043) +2025-08-25,07:16:11 | INFO | Train Epoch: 13 [17459712/26365952 (66%)] Avg Boundaries (per batch): 48.615 Boundary Ratio: 0.248 Contrastive_loss: 0.13436 (0.10562) Boundary_loss: 0.014932 (0.014897) Loss: 0.14929 (0.12051) +2025-08-25,07:17:07 | INFO | Train Epoch: 13 [17510912/26365952 (66%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.077855 (0.10553) Boundary_loss: 0.014927 (0.014897) Loss: 0.092782 (0.12043) +2025-08-25,07:18:04 | INFO | Train Epoch: 13 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.180 Boundary Ratio: 0.251 Contrastive_loss: 0.096899 (0.10551) Boundary_loss: 0.014894 (0.014897) Loss: 0.11179 (0.12041) +2025-08-25,07:19:00 | INFO | Train Epoch: 13 [17613312/26365952 (67%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.10788 (0.10552) Boundary_loss: 0.014894 (0.014897) Loss: 0.12277 (0.12041) +2025-08-25,07:19:56 | INFO | Train Epoch: 13 [17664512/26365952 (67%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.092379 (0.10548) Boundary_loss: 0.014811 (0.014897) Loss: 0.10719 (0.12038) +2025-08-25,07:20:53 | INFO | Train Epoch: 13 [17715712/26365952 (67%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.090084 (0.10543) Boundary_loss: 0.014891 (0.014897) Loss: 0.10498 (0.12033) +2025-08-25,07:21:49 | INFO | Train Epoch: 13 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.098338 (0.10541) Boundary_loss: 0.014867 (0.014897) Loss: 0.11320 (0.12031) +2025-08-25,07:22:45 | INFO | Train Epoch: 13 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.085255 (0.10536) Boundary_loss: 0.014883 (0.014897) Loss: 0.10014 (0.12025) +2025-08-25,07:23:42 | INFO | Train Epoch: 13 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.097082 (0.10533) Boundary_loss: 0.014801 (0.014896) Loss: 0.11188 (0.12023) +2025-08-25,07:24:38 | INFO | Train Epoch: 13 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.081060 (0.10526) Boundary_loss: 0.014896 (0.014896) Loss: 0.095957 (0.12016) +2025-08-25,07:25:35 | INFO | Train Epoch: 13 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.15147 (0.10539) Boundary_loss: 0.015026 (0.014897) Loss: 0.16649 (0.12029) +2025-08-25,07:26:31 | INFO | Train Epoch: 13 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.320 Boundary Ratio: 0.247 Contrastive_loss: 0.13737 (0.10549) Boundary_loss: 0.014796 (0.014896) Loss: 0.15217 (0.12038) +2025-08-25,07:27:28 | INFO | Train Epoch: 13 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.12280 (0.10553) Boundary_loss: 0.014792 (0.014896) Loss: 0.13760 (0.12043) +2025-08-25,07:28:24 | INFO | Train Epoch: 13 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.10174 (0.10552) Boundary_loss: 0.014869 (0.014896) Loss: 0.11661 (0.12042) +2025-08-25,07:29:20 | INFO | Train Epoch: 13 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.094248 (0.10549) Boundary_loss: 0.014941 (0.014896) Loss: 0.10919 (0.12039) +2025-08-25,07:30:16 | INFO | Train Epoch: 13 [18227712/26365952 (69%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.087126 (0.10544) Boundary_loss: 0.014873 (0.014896) Loss: 0.10200 (0.12034) +2025-08-25,07:31:13 | INFO | Train Epoch: 13 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.099903 (0.10542) Boundary_loss: 0.014953 (0.014896) Loss: 0.11486 (0.12032) +2025-08-25,07:32:09 | INFO | Train Epoch: 13 [18330112/26365952 (70%)] Avg Boundaries (per batch): 48.541 Boundary Ratio: 0.248 Contrastive_loss: 0.067472 (0.10532) Boundary_loss: 0.014892 (0.014896) Loss: 0.082363 (0.12022) +2025-08-25,07:33:05 | INFO | Train Epoch: 13 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.10471 (0.10532) Boundary_loss: 0.014871 (0.014896) Loss: 0.11958 (0.12021) +2025-08-25,07:34:02 | INFO | Train Epoch: 13 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.087933 (0.10527) Boundary_loss: 0.014842 (0.014896) Loss: 0.10278 (0.12017) +2025-08-25,07:34:58 | INFO | Train Epoch: 13 [18483712/26365952 (70%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.097192 (0.10525) Boundary_loss: 0.014906 (0.014896) Loss: 0.11210 (0.12014) +2025-08-25,07:35:54 | INFO | Train Epoch: 13 [18534912/26365952 (70%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.079071 (0.10517) Boundary_loss: 0.014903 (0.014896) Loss: 0.093974 (0.12007) +2025-08-25,07:36:51 | INFO | Train Epoch: 13 [18586112/26365952 (70%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.10045 (0.10516) Boundary_loss: 0.014796 (0.014896) Loss: 0.11525 (0.12006) +2025-08-25,07:37:47 | INFO | Train Epoch: 13 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.12467 (0.10522) Boundary_loss: 0.014950 (0.014896) Loss: 0.13962 (0.12011) +2025-08-25,07:38:44 | INFO | Train Epoch: 13 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.12005 (0.10526) Boundary_loss: 0.014887 (0.014896) Loss: 0.13493 (0.12015) +2025-08-25,07:39:40 | INFO | Train Epoch: 13 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.086693 (0.10521) Boundary_loss: 0.014949 (0.014896) Loss: 0.10164 (0.12010) +2025-08-25,07:40:37 | INFO | Train Epoch: 13 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.086183 (0.10515) Boundary_loss: 0.014828 (0.014896) Loss: 0.10101 (0.12005) +2025-08-25,07:41:33 | INFO | Train Epoch: 13 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.13349 (0.10523) Boundary_loss: 0.014821 (0.014896) Loss: 0.14831 (0.12013) +2025-08-25,07:42:29 | INFO | Train Epoch: 13 [18893312/26365952 (72%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.076109 (0.10515) Boundary_loss: 0.014859 (0.014896) Loss: 0.090968 (0.12005) +2025-08-25,07:43:26 | INFO | Train Epoch: 13 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.094312 (0.10512) Boundary_loss: 0.014846 (0.014896) Loss: 0.10916 (0.12002) +2025-08-25,07:44:22 | INFO | Train Epoch: 13 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.10553 (0.10512) Boundary_loss: 0.014851 (0.014895) Loss: 0.12038 (0.12002) +2025-08-25,07:45:18 | INFO | Train Epoch: 13 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.801 Boundary Ratio: 0.249 Contrastive_loss: 0.093002 (0.10509) Boundary_loss: 0.014817 (0.014895) Loss: 0.10782 (0.11999) +2025-08-25,07:46:14 | INFO | Train Epoch: 13 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.096706 (0.10507) Boundary_loss: 0.014884 (0.014895) Loss: 0.11159 (0.11996) +2025-08-25,07:47:11 | INFO | Train Epoch: 13 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.10011 (0.10506) Boundary_loss: 0.015021 (0.014895) Loss: 0.11513 (0.11995) +2025-08-25,07:48:07 | INFO | Train Epoch: 13 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.081873 (0.10499) Boundary_loss: 0.014951 (0.014896) Loss: 0.096823 (0.11989) +2025-08-25,07:49:04 | INFO | Train Epoch: 13 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.12904 (0.10506) Boundary_loss: 0.014859 (0.014896) Loss: 0.14389 (0.11995) +2025-08-25,07:50:00 | INFO | Train Epoch: 13 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.10834 (0.10507) Boundary_loss: 0.014783 (0.014895) Loss: 0.12312 (0.11996) +2025-08-25,07:50:56 | INFO | Train Epoch: 13 [19354112/26365952 (73%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.089302 (0.10502) Boundary_loss: 0.014909 (0.014895) Loss: 0.10421 (0.11992) +2025-08-25,07:51:53 | INFO | Train Epoch: 13 [19405312/26365952 (74%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.088636 (0.10498) Boundary_loss: 0.014830 (0.014895) Loss: 0.10347 (0.11988) +2025-08-25,07:52:49 | INFO | Train Epoch: 13 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.15370 (0.10511) Boundary_loss: 0.014934 (0.014895) Loss: 0.16864 (0.12000) +2025-08-25,07:53:46 | INFO | Train Epoch: 13 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.10201 (0.10510) Boundary_loss: 0.014906 (0.014895) Loss: 0.11691 (0.12000) +2025-08-25,07:54:42 | INFO | Train Epoch: 13 [19558912/26365952 (74%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.069037 (0.10501) Boundary_loss: 0.014887 (0.014895) Loss: 0.083924 (0.11990) +2025-08-25,07:55:38 | INFO | Train Epoch: 13 [19610112/26365952 (74%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.12379 (0.10506) Boundary_loss: 0.014930 (0.014895) Loss: 0.13872 (0.11995) +2025-08-25,07:56:35 | INFO | Train Epoch: 13 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.10171 (0.10505) Boundary_loss: 0.014911 (0.014895) Loss: 0.11662 (0.11994) +2025-08-25,07:57:31 | INFO | Train Epoch: 13 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.11412 (0.10507) Boundary_loss: 0.014874 (0.014895) Loss: 0.12899 (0.11997) +2025-08-25,07:58:27 | INFO | Train Epoch: 13 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.094283 (0.10504) Boundary_loss: 0.014878 (0.014895) Loss: 0.10916 (0.11994) +2025-08-25,07:59:24 | INFO | Train Epoch: 13 [19814912/26365952 (75%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.092778 (0.10501) Boundary_loss: 0.014805 (0.014895) Loss: 0.10758 (0.11991) +2025-08-25,08:00:20 | INFO | Train Epoch: 13 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.11452 (0.10504) Boundary_loss: 0.014779 (0.014895) Loss: 0.12930 (0.11993) +2025-08-25,08:01:17 | INFO | Train Epoch: 13 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.12247 (0.10508) Boundary_loss: 0.014979 (0.014895) Loss: 0.13745 (0.11998) +2025-08-25,08:02:13 | INFO | Train Epoch: 13 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.10053 (0.10507) Boundary_loss: 0.014915 (0.014895) Loss: 0.11544 (0.11996) +2025-08-25,08:03:10 | INFO | Train Epoch: 13 [20019712/26365952 (76%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.10498 (0.10507) Boundary_loss: 0.014966 (0.014895) Loss: 0.11995 (0.11996) +2025-08-25,08:04:06 | INFO | Train Epoch: 13 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.652 Boundary Ratio: 0.248 Contrastive_loss: 0.071086 (0.10498) Boundary_loss: 0.014871 (0.014895) Loss: 0.085956 (0.11988) +2025-08-25,08:05:03 | INFO | Train Epoch: 13 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.089581 (0.10494) Boundary_loss: 0.014890 (0.014895) Loss: 0.10447 (0.11984) +2025-08-25,08:05:59 | INFO | Train Epoch: 13 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.15546 (0.10507) Boundary_loss: 0.014919 (0.014895) Loss: 0.17038 (0.11997) +2025-08-25,08:06:55 | INFO | Train Epoch: 13 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.11011 (0.10508) Boundary_loss: 0.014945 (0.014895) Loss: 0.12506 (0.11998) +2025-08-25,08:07:52 | INFO | Train Epoch: 13 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.088467 (0.10504) Boundary_loss: 0.014710 (0.014895) Loss: 0.10318 (0.11994) +2025-08-25,08:08:48 | INFO | Train Epoch: 13 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.097360 (0.10502) Boundary_loss: 0.014847 (0.014895) Loss: 0.11221 (0.11992) +2025-08-25,08:09:45 | INFO | Train Epoch: 13 [20378112/26365952 (77%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.10801 (0.10503) Boundary_loss: 0.014960 (0.014895) Loss: 0.12297 (0.11992) +2025-08-25,08:10:41 | INFO | Train Epoch: 13 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.098289 (0.10501) Boundary_loss: 0.014818 (0.014895) Loss: 0.11311 (0.11991) +2025-08-25,08:11:38 | INFO | Train Epoch: 13 [20480512/26365952 (78%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.081444 (0.10495) Boundary_loss: 0.014785 (0.014894) Loss: 0.096229 (0.11985) +2025-08-25,08:12:34 | INFO | Train Epoch: 13 [20531712/26365952 (78%)] Avg Boundaries (per batch): 48.543 Boundary Ratio: 0.248 Contrastive_loss: 0.12318 (0.10500) Boundary_loss: 0.014953 (0.014895) Loss: 0.13813 (0.11989) +2025-08-25,08:13:31 | INFO | Train Epoch: 13 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.094468 (0.10497) Boundary_loss: 0.014779 (0.014894) Loss: 0.10925 (0.11987) +2025-08-25,08:14:27 | INFO | Train Epoch: 13 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.076589 (0.10490) Boundary_loss: 0.014852 (0.014894) Loss: 0.091442 (0.11980) +2025-08-25,08:15:24 | INFO | Train Epoch: 13 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.098719 (0.10489) Boundary_loss: 0.014905 (0.014894) Loss: 0.11362 (0.11978) +2025-08-25,08:16:20 | INFO | Train Epoch: 13 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.087486 (0.10485) Boundary_loss: 0.014930 (0.014894) Loss: 0.10242 (0.11974) +2025-08-25,08:17:16 | INFO | Train Epoch: 13 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.094623 (0.10482) Boundary_loss: 0.014909 (0.014894) Loss: 0.10953 (0.11971) +2025-08-25,08:18:13 | INFO | Train Epoch: 13 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.553 Boundary Ratio: 0.248 Contrastive_loss: 0.11347 (0.10484) Boundary_loss: 0.014864 (0.014894) Loss: 0.12834 (0.11974) +2025-08-25,08:19:09 | INFO | Train Epoch: 13 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.088402 (0.10480) Boundary_loss: 0.014840 (0.014894) Loss: 0.10324 (0.11970) +2025-08-25,08:20:05 | INFO | Train Epoch: 13 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.11341 (0.10482) Boundary_loss: 0.014928 (0.014894) Loss: 0.12834 (0.11972) +2025-08-25,08:21:02 | INFO | Train Epoch: 13 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.13392 (0.10489) Boundary_loss: 0.014836 (0.014894) Loss: 0.14875 (0.11979) +2025-08-25,08:21:58 | INFO | Train Epoch: 13 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.10692 (0.10490) Boundary_loss: 0.014971 (0.014894) Loss: 0.12189 (0.11979) +2025-08-25,08:22:54 | INFO | Train Epoch: 13 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.13681 (0.10497) Boundary_loss: 0.014838 (0.014894) Loss: 0.15165 (0.11987) +2025-08-25,08:23:51 | INFO | Train Epoch: 13 [21146112/26365952 (80%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.11609 (0.10500) Boundary_loss: 0.014864 (0.014894) Loss: 0.13096 (0.11990) +2025-08-25,08:24:47 | INFO | Train Epoch: 13 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.090951 (0.10497) Boundary_loss: 0.014920 (0.014894) Loss: 0.10587 (0.11986) +2025-08-25,08:25:44 | INFO | Train Epoch: 13 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.11690 (0.10500) Boundary_loss: 0.014817 (0.014894) Loss: 0.13172 (0.11989) +2025-08-25,08:26:40 | INFO | Train Epoch: 13 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.083725 (0.10495) Boundary_loss: 0.014875 (0.014894) Loss: 0.098600 (0.11984) +2025-08-25,08:27:36 | INFO | Train Epoch: 13 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.506 Boundary Ratio: 0.247 Contrastive_loss: 0.12199 (0.10499) Boundary_loss: 0.014913 (0.014894) Loss: 0.13690 (0.11988) +2025-08-25,08:28:33 | INFO | Train Epoch: 13 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.11466 (0.10501) Boundary_loss: 0.014821 (0.014894) Loss: 0.12949 (0.11990) +2025-08-25,08:29:29 | INFO | Train Epoch: 13 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.11602 (0.10504) Boundary_loss: 0.014977 (0.014894) Loss: 0.13100 (0.11993) +2025-08-25,08:30:26 | INFO | Train Epoch: 13 [21504512/26365952 (82%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.095113 (0.10501) Boundary_loss: 0.014836 (0.014894) Loss: 0.10995 (0.11991) +2025-08-25,08:31:22 | INFO | Train Epoch: 13 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.12471 (0.10506) Boundary_loss: 0.014758 (0.014893) Loss: 0.13946 (0.11995) +2025-08-25,08:32:19 | INFO | Train Epoch: 13 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.087196 (0.10502) Boundary_loss: 0.014946 (0.014894) Loss: 0.10214 (0.11991) +2025-08-25,08:33:15 | INFO | Train Epoch: 13 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.959 Boundary Ratio: 0.250 Contrastive_loss: 0.076259 (0.10495) Boundary_loss: 0.014878 (0.014894) Loss: 0.091137 (0.11984) +2025-08-25,08:34:11 | INFO | Train Epoch: 13 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.088231 (0.10491) Boundary_loss: 0.014836 (0.014893) Loss: 0.10307 (0.11980) +2025-08-25,08:35:08 | INFO | Train Epoch: 13 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.373 Boundary Ratio: 0.247 Contrastive_loss: 0.10846 (0.10492) Boundary_loss: 0.014896 (0.014893) Loss: 0.12336 (0.11981) +2025-08-25,08:36:04 | INFO | Train Epoch: 13 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.11731 (0.10495) Boundary_loss: 0.014941 (0.014894) Loss: 0.13225 (0.11984) +2025-08-25,08:37:00 | INFO | Train Epoch: 13 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.11329 (0.10497) Boundary_loss: 0.014838 (0.014893) Loss: 0.12813 (0.11986) +2025-08-25,08:37:57 | INFO | Train Epoch: 13 [21914112/26365952 (83%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.14502 (0.10506) Boundary_loss: 0.014954 (0.014894) Loss: 0.15998 (0.11995) +2025-08-25,08:38:53 | INFO | Train Epoch: 13 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.082310 (0.10501) Boundary_loss: 0.014847 (0.014893) Loss: 0.097157 (0.11990) +2025-08-25,08:39:50 | INFO | Train Epoch: 13 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.10332 (0.10500) Boundary_loss: 0.014898 (0.014893) Loss: 0.11822 (0.11990) +2025-08-25,08:40:46 | INFO | Train Epoch: 13 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.734 Boundary Ratio: 0.249 Contrastive_loss: 0.10635 (0.10501) Boundary_loss: 0.014809 (0.014893) Loss: 0.12116 (0.11990) +2025-08-25,08:41:42 | INFO | Train Epoch: 13 [22118912/26365952 (84%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.081407 (0.10495) Boundary_loss: 0.014909 (0.014893) Loss: 0.096317 (0.11984) +2025-08-25,08:42:39 | INFO | Train Epoch: 13 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.12082 (0.10499) Boundary_loss: 0.014901 (0.014893) Loss: 0.13572 (0.11988) +2025-08-25,08:43:35 | INFO | Train Epoch: 13 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.10307 (0.10498) Boundary_loss: 0.014890 (0.014893) Loss: 0.11796 (0.11988) +2025-08-25,08:44:31 | INFO | Train Epoch: 13 [22272512/26365952 (84%)] Avg Boundaries (per batch): 49.057 Boundary Ratio: 0.250 Contrastive_loss: 0.10001 (0.10497) Boundary_loss: 0.014952 (0.014893) Loss: 0.11497 (0.11987) +2025-08-25,08:45:28 | INFO | Train Epoch: 13 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.075809 (0.10491) Boundary_loss: 0.014866 (0.014893) Loss: 0.090676 (0.11980) +2025-08-25,08:46:24 | INFO | Train Epoch: 13 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.085794 (0.10486) Boundary_loss: 0.014996 (0.014894) Loss: 0.10079 (0.11976) +2025-08-25,08:47:21 | INFO | Train Epoch: 13 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.10432 (0.10486) Boundary_loss: 0.014986 (0.014894) Loss: 0.11931 (0.11975) +2025-08-25,08:48:17 | INFO | Train Epoch: 13 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.426 Boundary Ratio: 0.247 Contrastive_loss: 0.080950 (0.10481) Boundary_loss: 0.014885 (0.014894) Loss: 0.095835 (0.11970) +2025-08-25,08:49:14 | INFO | Train Epoch: 13 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.084960 (0.10476) Boundary_loss: 0.014852 (0.014894) Loss: 0.099812 (0.11966) +2025-08-25,08:50:10 | INFO | Train Epoch: 13 [22579712/26365952 (86%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.11712 (0.10479) Boundary_loss: 0.014854 (0.014894) Loss: 0.13197 (0.11968) +2025-08-25,08:51:07 | INFO | Train Epoch: 13 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.318 Boundary Ratio: 0.247 Contrastive_loss: 0.14333 (0.10488) Boundary_loss: 0.014853 (0.014894) Loss: 0.15818 (0.11977) +2025-08-25,08:52:03 | INFO | Train Epoch: 13 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.092153 (0.10485) Boundary_loss: 0.014893 (0.014894) Loss: 0.10705 (0.11974) +2025-08-25,08:52:59 | INFO | Train Epoch: 13 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.094504 (0.10482) Boundary_loss: 0.014838 (0.014893) Loss: 0.10934 (0.11972) +2025-08-25,08:53:56 | INFO | Train Epoch: 13 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.10186 (0.10482) Boundary_loss: 0.014836 (0.014893) Loss: 0.11669 (0.11971) +2025-08-25,08:54:52 | INFO | Train Epoch: 13 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.094943 (0.10480) Boundary_loss: 0.014921 (0.014893) Loss: 0.10986 (0.11969) +2025-08-25,08:55:49 | INFO | Train Epoch: 13 [22886912/26365952 (87%)] Avg Boundaries (per batch): 49.031 Boundary Ratio: 0.250 Contrastive_loss: 0.099752 (0.10478) Boundary_loss: 0.014990 (0.014894) Loss: 0.11474 (0.11968) +2025-08-25,08:56:45 | INFO | Train Epoch: 13 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.11277 (0.10480) Boundary_loss: 0.014888 (0.014894) Loss: 0.12766 (0.11970) +2025-08-25,08:57:41 | INFO | Train Epoch: 13 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.077471 (0.10474) Boundary_loss: 0.014815 (0.014893) Loss: 0.092286 (0.11963) +2025-08-25,08:58:38 | INFO | Train Epoch: 13 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.088113 (0.10470) Boundary_loss: 0.014823 (0.014893) Loss: 0.10294 (0.11960) +2025-08-25,08:59:34 | INFO | Train Epoch: 13 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.10742 (0.10471) Boundary_loss: 0.014837 (0.014893) Loss: 0.12226 (0.11960) +2025-08-25,09:00:31 | INFO | Train Epoch: 13 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.079693 (0.10466) Boundary_loss: 0.014946 (0.014893) Loss: 0.094639 (0.11955) +2025-08-25,09:01:27 | INFO | Train Epoch: 13 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.10945 (0.10467) Boundary_loss: 0.014986 (0.014893) Loss: 0.12444 (0.11956) +2025-08-25,09:02:24 | INFO | Train Epoch: 13 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.12633 (0.10471) Boundary_loss: 0.014931 (0.014893) Loss: 0.14126 (0.11961) +2025-08-25,09:03:20 | INFO | Train Epoch: 13 [23296512/26365952 (88%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.091993 (0.10469) Boundary_loss: 0.015016 (0.014894) Loss: 0.10701 (0.11958) +2025-08-25,09:04:16 | INFO | Train Epoch: 13 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.873 Boundary Ratio: 0.249 Contrastive_loss: 0.12614 (0.10473) Boundary_loss: 0.014917 (0.014894) Loss: 0.14105 (0.11963) +2025-08-25,09:05:13 | INFO | Train Epoch: 13 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.087485 (0.10469) Boundary_loss: 0.014953 (0.014894) Loss: 0.10244 (0.11959) +2025-08-25,09:06:09 | INFO | Train Epoch: 13 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.068030 (0.10462) Boundary_loss: 0.014870 (0.014894) Loss: 0.082901 (0.11951) +2025-08-25,09:07:06 | INFO | Train Epoch: 13 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.488 Boundary Ratio: 0.247 Contrastive_loss: 0.12365 (0.10466) Boundary_loss: 0.014949 (0.014894) Loss: 0.13860 (0.11955) +2025-08-25,09:08:02 | INFO | Train Epoch: 13 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.090697 (0.10463) Boundary_loss: 0.014861 (0.014894) Loss: 0.10556 (0.11952) +2025-08-25,09:08:58 | INFO | Train Epoch: 13 [23603712/26365952 (90%)] Avg Boundaries (per batch): 49.072 Boundary Ratio: 0.250 Contrastive_loss: 0.10471 (0.10463) Boundary_loss: 0.014910 (0.014894) Loss: 0.11962 (0.11952) +2025-08-25,09:09:55 | INFO | Train Epoch: 13 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.097625 (0.10461) Boundary_loss: 0.014919 (0.014894) Loss: 0.11254 (0.11951) +2025-08-25,09:10:51 | INFO | Train Epoch: 13 [23706112/26365952 (90%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.084996 (0.10457) Boundary_loss: 0.014876 (0.014894) Loss: 0.099872 (0.11946) +2025-08-25,09:11:48 | INFO | Train Epoch: 13 [23757312/26365952 (90%)] Avg Boundaries (per batch): 49.078 Boundary Ratio: 0.250 Contrastive_loss: 0.084911 (0.10453) Boundary_loss: 0.014859 (0.014894) Loss: 0.099770 (0.11942) +2025-08-25,09:12:44 | INFO | Train Epoch: 13 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.092823 (0.10450) Boundary_loss: 0.014903 (0.014894) Loss: 0.10773 (0.11940) +2025-08-25,09:13:40 | INFO | Train Epoch: 13 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.459 Boundary Ratio: 0.247 Contrastive_loss: 0.12139 (0.10454) Boundary_loss: 0.014911 (0.014894) Loss: 0.13630 (0.11943) +2025-08-25,09:14:37 | INFO | Train Epoch: 13 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.11521 (0.10456) Boundary_loss: 0.014818 (0.014894) Loss: 0.13003 (0.11945) +2025-08-25,09:15:33 | INFO | Train Epoch: 13 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.071232 (0.10449) Boundary_loss: 0.014874 (0.014894) Loss: 0.086107 (0.11938) +2025-08-25,09:16:30 | INFO | Train Epoch: 13 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11506 (0.10451) Boundary_loss: 0.014968 (0.014894) Loss: 0.13003 (0.11941) +2025-08-25,09:17:26 | INFO | Train Epoch: 13 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.14202 (0.10459) Boundary_loss: 0.014920 (0.014894) Loss: 0.15694 (0.11949) +2025-08-25,09:18:22 | INFO | Train Epoch: 13 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.097061 (0.10458) Boundary_loss: 0.014878 (0.014894) Loss: 0.11194 (0.11947) +2025-08-25,09:19:19 | INFO | Train Epoch: 13 [24166912/26365952 (92%)] Avg Boundaries (per batch): 49.268 Boundary Ratio: 0.251 Contrastive_loss: 0.095281 (0.10456) Boundary_loss: 0.014777 (0.014894) Loss: 0.11006 (0.11945) +2025-08-25,09:20:15 | INFO | Train Epoch: 13 [24218112/26365952 (92%)] Avg Boundaries (per batch): 49.176 Boundary Ratio: 0.251 Contrastive_loss: 0.10615 (0.10456) Boundary_loss: 0.014940 (0.014894) Loss: 0.12109 (0.11945) +2025-08-25,09:21:11 | INFO | Train Epoch: 13 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.564 Boundary Ratio: 0.248 Contrastive_loss: 0.088790 (0.10453) Boundary_loss: 0.014902 (0.014894) Loss: 0.10369 (0.11942) +2025-08-25,09:22:08 | INFO | Train Epoch: 13 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.10648 (0.10453) Boundary_loss: 0.014848 (0.014894) Loss: 0.12133 (0.11942) +2025-08-25,09:23:04 | INFO | Train Epoch: 13 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.099895 (0.10452) Boundary_loss: 0.014848 (0.014894) Loss: 0.11474 (0.11941) +2025-08-25,09:24:00 | INFO | Train Epoch: 13 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.090430 (0.10449) Boundary_loss: 0.014967 (0.014894) Loss: 0.10540 (0.11938) +2025-08-25,09:24:57 | INFO | Train Epoch: 13 [24474112/26365952 (93%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.10407 (0.10449) Boundary_loss: 0.014984 (0.014894) Loss: 0.11906 (0.11938) +2025-08-25,09:25:53 | INFO | Train Epoch: 13 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.10096 (0.10448) Boundary_loss: 0.014973 (0.014894) Loss: 0.11593 (0.11938) +2025-08-25,09:26:49 | INFO | Train Epoch: 13 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.12301 (0.10452) Boundary_loss: 0.014833 (0.014894) Loss: 0.13784 (0.11942) +2025-08-25,09:27:46 | INFO | Train Epoch: 13 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.096599 (0.10450) Boundary_loss: 0.015020 (0.014894) Loss: 0.11162 (0.11940) +2025-08-25,09:28:42 | INFO | Train Epoch: 13 [24678912/26365952 (94%)] Avg Boundaries (per batch): 49.234 Boundary Ratio: 0.251 Contrastive_loss: 0.095777 (0.10449) Boundary_loss: 0.014989 (0.014894) Loss: 0.11077 (0.11938) +2025-08-25,09:29:38 | INFO | Train Epoch: 13 [24730112/26365952 (94%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.091775 (0.10446) Boundary_loss: 0.014727 (0.014894) Loss: 0.10650 (0.11935) +2025-08-25,09:30:35 | INFO | Train Epoch: 13 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.11771 (0.10449) Boundary_loss: 0.014836 (0.014894) Loss: 0.13255 (0.11938) +2025-08-25,09:31:31 | INFO | Train Epoch: 13 [24832512/26365952 (94%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.11933 (0.10452) Boundary_loss: 0.014956 (0.014894) Loss: 0.13429 (0.11941) +2025-08-25,09:32:27 | INFO | Train Epoch: 13 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.674 Boundary Ratio: 0.248 Contrastive_loss: 0.087737 (0.10448) Boundary_loss: 0.014849 (0.014894) Loss: 0.10259 (0.11938) +2025-08-25,09:33:24 | INFO | Train Epoch: 13 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.875 Boundary Ratio: 0.249 Contrastive_loss: 0.12165 (0.10452) Boundary_loss: 0.014798 (0.014894) Loss: 0.13645 (0.11941) +2025-08-25,09:34:20 | INFO | Train Epoch: 13 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.088 Boundary Ratio: 0.250 Contrastive_loss: 0.092691 (0.10449) Boundary_loss: 0.014851 (0.014894) Loss: 0.10754 (0.11939) +2025-08-25,09:35:17 | INFO | Train Epoch: 13 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.085628 (0.10446) Boundary_loss: 0.014859 (0.014894) Loss: 0.10049 (0.11935) +2025-08-25,09:36:13 | INFO | Train Epoch: 13 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.073556 (0.10439) Boundary_loss: 0.014819 (0.014894) Loss: 0.088375 (0.11929) +2025-08-25,09:37:10 | INFO | Train Epoch: 13 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.082690 (0.10435) Boundary_loss: 0.014868 (0.014893) Loss: 0.097557 (0.11924) +2025-08-25,09:38:06 | INFO | Train Epoch: 13 [25190912/26365952 (96%)] Avg Boundaries (per batch): 48.637 Boundary Ratio: 0.248 Contrastive_loss: 0.080032 (0.10430) Boundary_loss: 0.015028 (0.014894) Loss: 0.095060 (0.11919) +2025-08-25,09:39:02 | INFO | Train Epoch: 13 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.533 Boundary Ratio: 0.248 Contrastive_loss: 0.11281 (0.10432) Boundary_loss: 0.014865 (0.014894) Loss: 0.12767 (0.11921) +2025-08-25,09:39:59 | INFO | Train Epoch: 13 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.992 Boundary Ratio: 0.250 Contrastive_loss: 0.077574 (0.10426) Boundary_loss: 0.014978 (0.014894) Loss: 0.092552 (0.11916) +2025-08-25,09:40:55 | INFO | Train Epoch: 13 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.10184 (0.10426) Boundary_loss: 0.014910 (0.014894) Loss: 0.11675 (0.11915) +2025-08-25,09:41:52 | INFO | Train Epoch: 13 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.14006 (0.10433) Boundary_loss: 0.014940 (0.014894) Loss: 0.15500 (0.11922) +2025-08-25,09:42:48 | INFO | Train Epoch: 13 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.074412 (0.10427) Boundary_loss: 0.014871 (0.014894) Loss: 0.089283 (0.11916) +2025-08-25,09:43:44 | INFO | Train Epoch: 13 [25498112/26365952 (97%)] Avg Boundaries (per batch): 49.055 Boundary Ratio: 0.250 Contrastive_loss: 0.12868 (0.10432) Boundary_loss: 0.014940 (0.014894) Loss: 0.14362 (0.11921) +2025-08-25,09:44:41 | INFO | Train Epoch: 13 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.087211 (0.10429) Boundary_loss: 0.014876 (0.014894) Loss: 0.10209 (0.11918) +2025-08-25,09:45:37 | INFO | Train Epoch: 13 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.085421 (0.10425) Boundary_loss: 0.014818 (0.014894) Loss: 0.10024 (0.11914) +2025-08-25,09:46:34 | INFO | Train Epoch: 13 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.10587 (0.10425) Boundary_loss: 0.014973 (0.014894) Loss: 0.12084 (0.11914) +2025-08-25,09:47:30 | INFO | Train Epoch: 13 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.094250 (0.10423) Boundary_loss: 0.014873 (0.014894) Loss: 0.10912 (0.11912) +2025-08-25,09:48:26 | INFO | Train Epoch: 13 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.094826 (0.10421) Boundary_loss: 0.014920 (0.014894) Loss: 0.10975 (0.11911) +2025-08-25,09:49:23 | INFO | Train Epoch: 13 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.10728 (0.10422) Boundary_loss: 0.014912 (0.014894) Loss: 0.12219 (0.11911) +2025-08-25,09:50:19 | INFO | Train Epoch: 13 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.11835 (0.10425) Boundary_loss: 0.014886 (0.014894) Loss: 0.13324 (0.11914) +2025-08-25,09:51:15 | INFO | Train Epoch: 13 [25907712/26365952 (98%)] Avg Boundaries (per batch): 49.135 Boundary Ratio: 0.251 Contrastive_loss: 0.10470 (0.10425) Boundary_loss: 0.015046 (0.014894) Loss: 0.11974 (0.11914) +2025-08-25,09:52:12 | INFO | Train Epoch: 13 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.11064 (0.10426) Boundary_loss: 0.014911 (0.014894) Loss: 0.12556 (0.11915) +2025-08-25,09:53:08 | INFO | Train Epoch: 13 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.576 Boundary Ratio: 0.248 Contrastive_loss: 0.084596 (0.10422) Boundary_loss: 0.014899 (0.014894) Loss: 0.099495 (0.11912) +2025-08-25,09:54:04 | INFO | Train Epoch: 13 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.072489 (0.10416) Boundary_loss: 0.014887 (0.014894) Loss: 0.087376 (0.11905) +2025-08-25,09:55:01 | INFO | Train Epoch: 13 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.10047 (0.10415) Boundary_loss: 0.014962 (0.014894) Loss: 0.11543 (0.11905) +2025-08-25,09:55:57 | INFO | Train Epoch: 13 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.10922 (0.10416) Boundary_loss: 0.014817 (0.014894) Loss: 0.12404 (0.11906) +2025-08-25,09:56:54 | INFO | Train Epoch: 13 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.095838 (0.10415) Boundary_loss: 0.014863 (0.014894) Loss: 0.11070 (0.11904) +2025-08-25,09:57:50 | INFO | Train Epoch: 13 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.568 Boundary Ratio: 0.248 Contrastive_loss: 0.10792 (0.10415) Boundary_loss: 0.014913 (0.014894) Loss: 0.12283 (0.11905) +2025-08-25,09:58:47 | INFO | Train Epoch: 13 [26317312/26365952 (100%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.088335 (0.10412) Boundary_loss: 0.014883 (0.014894) Loss: 0.10322 (0.11902) +2025-08-25,09:59:40 | INFO | Train Epoch: 13 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.093883 (0.10410) Boundary_loss: 0.014936 (0.014894) Loss: 0.10882 (0.11900) +2025-08-25,09:59:40 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-25,09:59:40 | INFO | [Epoch 13] Average Step Time: 0.566s | Average GPU Memory: 31.6 GB +2025-08-25,09:59:40 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-25,09:59:40 | INFO | Starting zero-shot imagenet. +2025-08-25,09:59:40 | INFO | Building zero-shot classifier +2025-08-25,09:59:49 | INFO | Using classifier +2025-08-25,10:00:29 | INFO | Finished zero-shot imagenet. +2025-08-25,10:00:29 | INFO | Eval Epoch: 14 imagenet-zeroshot-val-top1: 0.3096 imagenet-zeroshot-val-top5: 0.5783 +2025-08-25,10:00:31 | INFO | Start epoch 14 +2025-08-25,10:00:33 | INFO | Train Epoch: 14 [ 512/26365952 (0%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.10646 (0.10646) Boundary_loss: 0.014848 (0.014848) Loss: 0.12131 (0.12131) +2025-08-25,10:01:29 | INFO | Train Epoch: 14 [ 51712/26365952 (0%)] Avg Boundaries (per batch): 48.736 Boundary Ratio: 0.249 Contrastive_loss: 0.084293 (0.095377) Boundary_loss: 0.014865 (0.014857) Loss: 0.099158 (0.11023) +2025-08-25,10:02:25 | INFO | Train Epoch: 14 [ 102912/26365952 (0%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.13003 (0.10693) Boundary_loss: 0.014851 (0.014855) Loss: 0.14488 (0.12178) +2025-08-25,10:03:21 | INFO | Train Epoch: 14 [ 154112/26365952 (1%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.087200 (0.10200) Boundary_loss: 0.014875 (0.014860) Loss: 0.10208 (0.11686) +2025-08-25,10:04:17 | INFO | Train Epoch: 14 [ 205312/26365952 (1%)] Avg Boundaries (per batch): 48.531 Boundary Ratio: 0.248 Contrastive_loss: 0.098597 (0.10132) Boundary_loss: 0.014829 (0.014854) Loss: 0.11343 (0.11617) +2025-08-25,10:05:14 | INFO | Train Epoch: 14 [ 256512/26365952 (1%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.11119 (0.10296) Boundary_loss: 0.014791 (0.014843) Loss: 0.12598 (0.11781) +2025-08-25,10:06:10 | INFO | Train Epoch: 14 [ 307712/26365952 (1%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.097070 (0.10212) Boundary_loss: 0.014898 (0.014851) Loss: 0.11197 (0.11697) +2025-08-25,10:07:06 | INFO | Train Epoch: 14 [ 358912/26365952 (1%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.10312 (0.10225) Boundary_loss: 0.014889 (0.014856) Loss: 0.11801 (0.11710) +2025-08-25,10:08:02 | INFO | Train Epoch: 14 [ 410112/26365952 (2%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.082904 (0.10010) Boundary_loss: 0.014842 (0.014854) Loss: 0.097745 (0.11495) +2025-08-25,10:08:58 | INFO | Train Epoch: 14 [ 461312/26365952 (2%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.068190 (0.096906) Boundary_loss: 0.015013 (0.014870) Loss: 0.083203 (0.11178) +2025-08-25,10:09:55 | INFO | Train Epoch: 14 [ 512512/26365952 (2%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.11470 (0.098523) Boundary_loss: 0.014909 (0.014874) Loss: 0.12961 (0.11340) +2025-08-25,10:10:51 | INFO | Train Epoch: 14 [ 563712/26365952 (2%)] Avg Boundaries (per batch): 48.695 Boundary Ratio: 0.248 Contrastive_loss: 0.095902 (0.098304) Boundary_loss: 0.014898 (0.014876) Loss: 0.11080 (0.11318) +2025-08-25,10:11:47 | INFO | Train Epoch: 14 [ 614912/26365952 (2%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.066648 (0.095869) Boundary_loss: 0.015005 (0.014886) Loss: 0.081654 (0.11076) +2025-08-25,10:12:43 | INFO | Train Epoch: 14 [ 666112/26365952 (3%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.10901 (0.096808) Boundary_loss: 0.014935 (0.014889) Loss: 0.12395 (0.11170) +2025-08-25,10:13:40 | INFO | Train Epoch: 14 [ 717312/26365952 (3%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.063258 (0.094572) Boundary_loss: 0.014902 (0.014890) Loss: 0.078160 (0.10946) +2025-08-25,10:14:36 | INFO | Train Epoch: 14 [ 768512/26365952 (3%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.16294 (0.098845) Boundary_loss: 0.014839 (0.014887) Loss: 0.17778 (0.11373) +2025-08-25,10:15:32 | INFO | Train Epoch: 14 [ 819712/26365952 (3%)] Avg Boundaries (per batch): 48.498 Boundary Ratio: 0.247 Contrastive_loss: 0.12830 (0.10058) Boundary_loss: 0.014873 (0.014886) Loss: 0.14317 (0.11546) +2025-08-25,10:16:28 | INFO | Train Epoch: 14 [ 870912/26365952 (3%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.12155 (0.10174) Boundary_loss: 0.014948 (0.014889) Loss: 0.13650 (0.11663) +2025-08-25,10:17:25 | INFO | Train Epoch: 14 [ 922112/26365952 (3%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.060387 (0.099566) Boundary_loss: 0.014943 (0.014892) Loss: 0.075331 (0.11446) +2025-08-25,10:18:21 | INFO | Train Epoch: 14 [ 973312/26365952 (4%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.076012 (0.098388) Boundary_loss: 0.014980 (0.014897) Loss: 0.090992 (0.11328) +2025-08-25,10:19:17 | INFO | Train Epoch: 14 [ 1024512/26365952 (4%)] Avg Boundaries (per batch): 48.809 Boundary Ratio: 0.249 Contrastive_loss: 0.099984 (0.098464) Boundary_loss: 0.014866 (0.014895) Loss: 0.11485 (0.11336) +2025-08-25,10:20:13 | INFO | Train Epoch: 14 [ 1075712/26365952 (4%)] Avg Boundaries (per batch): 48.719 Boundary Ratio: 0.249 Contrastive_loss: 0.11538 (0.099233) Boundary_loss: 0.014825 (0.014892) Loss: 0.13021 (0.11413) +2025-08-25,10:21:10 | INFO | Train Epoch: 14 [ 1126912/26365952 (4%)] Avg Boundaries (per batch): 48.717 Boundary Ratio: 0.249 Contrastive_loss: 0.094379 (0.099022) Boundary_loss: 0.014999 (0.014897) Loss: 0.10938 (0.11392) +2025-08-25,10:22:06 | INFO | Train Epoch: 14 [ 1178112/26365952 (4%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.084831 (0.098431) Boundary_loss: 0.014814 (0.014893) Loss: 0.099645 (0.11332) +2025-08-25,10:23:02 | INFO | Train Epoch: 14 [ 1229312/26365952 (5%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.11007 (0.098896) Boundary_loss: 0.014936 (0.014895) Loss: 0.12501 (0.11379) +2025-08-25,10:23:58 | INFO | Train Epoch: 14 [ 1280512/26365952 (5%)] Avg Boundaries (per batch): 48.748 Boundary Ratio: 0.249 Contrastive_loss: 0.11473 (0.099505) Boundary_loss: 0.014890 (0.014895) Loss: 0.12962 (0.11440) +2025-08-25,10:24:55 | INFO | Train Epoch: 14 [ 1331712/26365952 (5%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.10939 (0.099871) Boundary_loss: 0.014870 (0.014894) Loss: 0.12426 (0.11477) +2025-08-25,10:25:51 | INFO | Train Epoch: 14 [ 1382912/26365952 (5%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.12657 (0.10082) Boundary_loss: 0.014937 (0.014895) Loss: 0.14150 (0.11572) +2025-08-25,10:26:47 | INFO | Train Epoch: 14 [ 1434112/26365952 (5%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.13937 (0.10215) Boundary_loss: 0.014896 (0.014895) Loss: 0.15427 (0.11705) +2025-08-25,10:27:44 | INFO | Train Epoch: 14 [ 1485312/26365952 (6%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.082828 (0.10151) Boundary_loss: 0.014921 (0.014896) Loss: 0.097749 (0.11641) +2025-08-25,10:28:40 | INFO | Train Epoch: 14 [ 1536512/26365952 (6%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.13050 (0.10245) Boundary_loss: 0.014918 (0.014897) Loss: 0.14542 (0.11734) +2025-08-25,10:29:36 | INFO | Train Epoch: 14 [ 1587712/26365952 (6%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.097704 (0.10230) Boundary_loss: 0.014940 (0.014898) Loss: 0.11264 (0.11720) +2025-08-25,10:30:33 | INFO | Train Epoch: 14 [ 1638912/26365952 (6%)] Avg Boundaries (per batch): 48.645 Boundary Ratio: 0.248 Contrastive_loss: 0.099191 (0.10220) Boundary_loss: 0.014870 (0.014897) Loss: 0.11406 (0.11710) +2025-08-25,10:31:29 | INFO | Train Epoch: 14 [ 1690112/26365952 (6%)] Avg Boundaries (per batch): 48.566 Boundary Ratio: 0.248 Contrastive_loss: 0.11860 (0.10269) Boundary_loss: 0.014841 (0.014896) Loss: 0.13345 (0.11758) +2025-08-25,10:32:25 | INFO | Train Epoch: 14 [ 1741312/26365952 (7%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.10765 (0.10283) Boundary_loss: 0.014888 (0.014896) Loss: 0.12254 (0.11772) +2025-08-25,10:33:21 | INFO | Train Epoch: 14 [ 1792512/26365952 (7%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.10811 (0.10297) Boundary_loss: 0.014883 (0.014895) Loss: 0.12299 (0.11787) +2025-08-25,10:34:18 | INFO | Train Epoch: 14 [ 1843712/26365952 (7%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.079449 (0.10234) Boundary_loss: 0.014878 (0.014895) Loss: 0.094327 (0.11723) +2025-08-25,10:35:14 | INFO | Train Epoch: 14 [ 1894912/26365952 (7%)] Avg Boundaries (per batch): 48.836 Boundary Ratio: 0.249 Contrastive_loss: 0.11571 (0.10269) Boundary_loss: 0.014957 (0.014896) Loss: 0.13066 (0.11759) +2025-08-25,10:36:10 | INFO | Train Epoch: 14 [ 1946112/26365952 (7%)] Avg Boundaries (per batch): 48.715 Boundary Ratio: 0.249 Contrastive_loss: 0.087354 (0.10230) Boundary_loss: 0.014983 (0.014899) Loss: 0.10234 (0.11720) +2025-08-25,10:37:07 | INFO | Train Epoch: 14 [ 1997312/26365952 (8%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.059214 (0.10122) Boundary_loss: 0.014878 (0.014898) Loss: 0.074093 (0.11612) +2025-08-25,10:38:03 | INFO | Train Epoch: 14 [ 2048512/26365952 (8%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.10837 (0.10139) Boundary_loss: 0.014813 (0.014896) Loss: 0.12318 (0.11629) +2025-08-25,10:38:59 | INFO | Train Epoch: 14 [ 2099712/26365952 (8%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.088142 (0.10108) Boundary_loss: 0.014886 (0.014896) Loss: 0.10303 (0.11597) +2025-08-25,10:39:55 | INFO | Train Epoch: 14 [ 2150912/26365952 (8%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.12778 (0.10170) Boundary_loss: 0.014917 (0.014896) Loss: 0.14269 (0.11660) +2025-08-25,10:40:52 | INFO | Train Epoch: 14 [ 2202112/26365952 (8%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.087168 (0.10137) Boundary_loss: 0.014838 (0.014895) Loss: 0.10201 (0.11626) +2025-08-25,10:41:48 | INFO | Train Epoch: 14 [ 2253312/26365952 (9%)] Avg Boundaries (per batch): 48.377 Boundary Ratio: 0.247 Contrastive_loss: 0.097751 (0.10129) Boundary_loss: 0.014980 (0.014897) Loss: 0.11273 (0.11619) +2025-08-25,10:42:44 | INFO | Train Epoch: 14 [ 2304512/26365952 (9%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.13181 (0.10195) Boundary_loss: 0.014997 (0.014899) Loss: 0.14680 (0.11685) +2025-08-25,10:43:41 | INFO | Train Epoch: 14 [ 2355712/26365952 (9%)] Avg Boundaries (per batch): 48.967 Boundary Ratio: 0.250 Contrastive_loss: 0.11674 (0.10227) Boundary_loss: 0.014911 (0.014899) Loss: 0.13165 (0.11717) +2025-08-25,10:44:37 | INFO | Train Epoch: 14 [ 2406912/26365952 (9%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.10249 (0.10227) Boundary_loss: 0.014924 (0.014900) Loss: 0.11741 (0.11717) +2025-08-25,10:45:33 | INFO | Train Epoch: 14 [ 2458112/26365952 (9%)] Avg Boundaries (per batch): 49.021 Boundary Ratio: 0.250 Contrastive_loss: 0.11185 (0.10247) Boundary_loss: 0.014821 (0.014898) Loss: 0.12667 (0.11736) +2025-08-25,10:46:30 | INFO | Train Epoch: 14 [ 2509312/26365952 (10%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.14300 (0.10328) Boundary_loss: 0.014917 (0.014899) Loss: 0.15792 (0.11818) +2025-08-25,10:47:26 | INFO | Train Epoch: 14 [ 2560512/26365952 (10%)] Avg Boundaries (per batch): 48.816 Boundary Ratio: 0.249 Contrastive_loss: 0.10609 (0.10333) Boundary_loss: 0.014881 (0.014898) Loss: 0.12097 (0.11823) +2025-08-25,10:48:22 | INFO | Train Epoch: 14 [ 2611712/26365952 (10%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.11547 (0.10357) Boundary_loss: 0.014885 (0.014898) Loss: 0.13035 (0.11846) +2025-08-25,10:49:19 | INFO | Train Epoch: 14 [ 2662912/26365952 (10%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.094846 (0.10340) Boundary_loss: 0.014783 (0.014896) Loss: 0.10963 (0.11830) +2025-08-25,10:50:15 | INFO | Train Epoch: 14 [ 2714112/26365952 (10%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.091576 (0.10318) Boundary_loss: 0.014830 (0.014895) Loss: 0.10641 (0.11808) +2025-08-25,10:51:11 | INFO | Train Epoch: 14 [ 2765312/26365952 (10%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.072206 (0.10262) Boundary_loss: 0.014886 (0.014894) Loss: 0.087091 (0.11751) +2025-08-25,10:52:07 | INFO | Train Epoch: 14 [ 2816512/26365952 (11%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.088202 (0.10236) Boundary_loss: 0.014821 (0.014893) Loss: 0.10302 (0.11725) +2025-08-25,10:53:04 | INFO | Train Epoch: 14 [ 2867712/26365952 (11%)] Avg Boundaries (per batch): 48.986 Boundary Ratio: 0.250 Contrastive_loss: 0.092476 (0.10219) Boundary_loss: 0.014947 (0.014894) Loss: 0.10742 (0.11708) +2025-08-25,10:54:00 | INFO | Train Epoch: 14 [ 2918912/26365952 (11%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.073727 (0.10170) Boundary_loss: 0.014916 (0.014894) Loss: 0.088643 (0.11659) +2025-08-25,10:54:56 | INFO | Train Epoch: 14 [ 2970112/26365952 (11%)] Avg Boundaries (per batch): 48.602 Boundary Ratio: 0.248 Contrastive_loss: 0.11117 (0.10186) Boundary_loss: 0.014850 (0.014894) Loss: 0.12602 (0.11675) +2025-08-25,10:55:52 | INFO | Train Epoch: 14 [ 3021312/26365952 (11%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.093510 (0.10172) Boundary_loss: 0.014859 (0.014893) Loss: 0.10837 (0.11661) +2025-08-25,10:56:49 | INFO | Train Epoch: 14 [ 3072512/26365952 (12%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.10550 (0.10178) Boundary_loss: 0.014943 (0.014894) Loss: 0.12044 (0.11668) +2025-08-25,10:57:45 | INFO | Train Epoch: 14 [ 3123712/26365952 (12%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.11674 (0.10202) Boundary_loss: 0.014915 (0.014894) Loss: 0.13166 (0.11692) +2025-08-25,10:58:41 | INFO | Train Epoch: 14 [ 3174912/26365952 (12%)] Avg Boundaries (per batch): 48.383 Boundary Ratio: 0.247 Contrastive_loss: 0.12555 (0.10240) Boundary_loss: 0.014805 (0.014893) Loss: 0.14036 (0.11729) +2025-08-25,10:59:37 | INFO | Train Epoch: 14 [ 3226112/26365952 (12%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.089143 (0.10219) Boundary_loss: 0.014949 (0.014894) Loss: 0.10409 (0.11708) +2025-08-25,11:00:34 | INFO | Train Epoch: 14 [ 3277312/26365952 (12%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.084864 (0.10192) Boundary_loss: 0.014961 (0.014895) Loss: 0.099824 (0.11682) +2025-08-25,11:01:30 | INFO | Train Epoch: 14 [ 3328512/26365952 (13%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.092844 (0.10178) Boundary_loss: 0.014939 (0.014895) Loss: 0.10778 (0.11668) +2025-08-25,11:02:26 | INFO | Train Epoch: 14 [ 3379712/26365952 (13%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.077271 (0.10142) Boundary_loss: 0.014851 (0.014895) Loss: 0.092122 (0.11631) +2025-08-25,11:03:22 | INFO | Train Epoch: 14 [ 3430912/26365952 (13%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.094833 (0.10132) Boundary_loss: 0.014782 (0.014893) Loss: 0.10961 (0.11622) +2025-08-25,11:04:19 | INFO | Train Epoch: 14 [ 3482112/26365952 (13%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.11179 (0.10147) Boundary_loss: 0.014853 (0.014892) Loss: 0.12664 (0.11637) +2025-08-25,11:05:15 | INFO | Train Epoch: 14 [ 3533312/26365952 (13%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.071120 (0.10104) Boundary_loss: 0.014881 (0.014892) Loss: 0.086001 (0.11593) +2025-08-25,11:06:12 | INFO | Train Epoch: 14 [ 3584512/26365952 (14%)] Avg Boundaries (per batch): 48.777 Boundary Ratio: 0.249 Contrastive_loss: 0.14973 (0.10173) Boundary_loss: 0.014760 (0.014890) Loss: 0.16449 (0.11662) +2025-08-25,11:07:08 | INFO | Train Epoch: 14 [ 3635712/26365952 (14%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.086024 (0.10151) Boundary_loss: 0.014793 (0.014889) Loss: 0.10082 (0.11640) +2025-08-25,11:08:05 | INFO | Train Epoch: 14 [ 3686912/26365952 (14%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.097753 (0.10146) Boundary_loss: 0.014968 (0.014890) Loss: 0.11272 (0.11635) +2025-08-25,11:09:01 | INFO | Train Epoch: 14 [ 3738112/26365952 (14%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.13816 (0.10195) Boundary_loss: 0.014903 (0.014890) Loss: 0.15306 (0.11684) +2025-08-25,11:09:57 | INFO | Train Epoch: 14 [ 3789312/26365952 (14%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.10726 (0.10202) Boundary_loss: 0.014927 (0.014891) Loss: 0.12219 (0.11691) +2025-08-25,11:10:54 | INFO | Train Epoch: 14 [ 3840512/26365952 (15%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.11501 (0.10219) Boundary_loss: 0.014797 (0.014890) Loss: 0.12981 (0.11708) +2025-08-25,11:11:50 | INFO | Train Epoch: 14 [ 3891712/26365952 (15%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.086328 (0.10199) Boundary_loss: 0.014965 (0.014891) Loss: 0.10129 (0.11688) +2025-08-25,11:12:46 | INFO | Train Epoch: 14 [ 3942912/26365952 (15%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.074385 (0.10163) Boundary_loss: 0.015037 (0.014892) Loss: 0.089422 (0.11653) +2025-08-25,11:13:42 | INFO | Train Epoch: 14 [ 3994112/26365952 (15%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.083923 (0.10141) Boundary_loss: 0.014904 (0.014893) Loss: 0.098826 (0.11630) +2025-08-25,11:14:38 | INFO | Train Epoch: 14 [ 4045312/26365952 (15%)] Avg Boundaries (per batch): 48.586 Boundary Ratio: 0.248 Contrastive_loss: 0.11109 (0.10153) Boundary_loss: 0.014960 (0.014893) Loss: 0.12605 (0.11642) +2025-08-25,11:15:35 | INFO | Train Epoch: 14 [ 4096512/26365952 (16%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.081088 (0.10128) Boundary_loss: 0.014869 (0.014893) Loss: 0.095956 (0.11617) +2025-08-25,11:16:31 | INFO | Train Epoch: 14 [ 4147712/26365952 (16%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.10229 (0.10129) Boundary_loss: 0.014886 (0.014893) Loss: 0.11718 (0.11618) +2025-08-25,11:17:27 | INFO | Train Epoch: 14 [ 4198912/26365952 (16%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.083600 (0.10108) Boundary_loss: 0.014806 (0.014892) Loss: 0.098406 (0.11597) +2025-08-25,11:18:24 | INFO | Train Epoch: 14 [ 4250112/26365952 (16%)] Avg Boundaries (per batch): 49.191 Boundary Ratio: 0.251 Contrastive_loss: 0.12190 (0.10133) Boundary_loss: 0.014821 (0.014891) Loss: 0.13672 (0.11622) +2025-08-25,11:19:20 | INFO | Train Epoch: 14 [ 4301312/26365952 (16%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.081256 (0.10109) Boundary_loss: 0.014906 (0.014891) Loss: 0.096162 (0.11598) +2025-08-25,11:20:16 | INFO | Train Epoch: 14 [ 4352512/26365952 (17%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.089801 (0.10096) Boundary_loss: 0.014860 (0.014891) Loss: 0.10466 (0.11585) +2025-08-25,11:21:12 | INFO | Train Epoch: 14 [ 4403712/26365952 (17%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.099858 (0.10095) Boundary_loss: 0.014908 (0.014891) Loss: 0.11477 (0.11584) +2025-08-25,11:22:09 | INFO | Train Epoch: 14 [ 4454912/26365952 (17%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.089123 (0.10081) Boundary_loss: 0.014867 (0.014891) Loss: 0.10399 (0.11570) +2025-08-25,11:23:05 | INFO | Train Epoch: 14 [ 4506112/26365952 (17%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.090964 (0.10070) Boundary_loss: 0.014809 (0.014890) Loss: 0.10577 (0.11559) +2025-08-25,11:24:01 | INFO | Train Epoch: 14 [ 4557312/26365952 (17%)] Avg Boundaries (per batch): 49.189 Boundary Ratio: 0.251 Contrastive_loss: 0.11472 (0.10086) Boundary_loss: 0.014884 (0.014890) Loss: 0.12960 (0.11575) +2025-08-25,11:24:58 | INFO | Train Epoch: 14 [ 4608512/26365952 (17%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.093243 (0.10077) Boundary_loss: 0.014984 (0.014891) Loss: 0.10823 (0.11566) +2025-08-25,11:25:54 | INFO | Train Epoch: 14 [ 4659712/26365952 (18%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.062606 (0.10036) Boundary_loss: 0.014927 (0.014891) Loss: 0.077533 (0.11525) +2025-08-25,11:26:50 | INFO | Train Epoch: 14 [ 4710912/26365952 (18%)] Avg Boundaries (per batch): 48.504 Boundary Ratio: 0.247 Contrastive_loss: 0.094795 (0.10030) Boundary_loss: 0.014863 (0.014891) Loss: 0.10966 (0.11519) +2025-08-25,11:27:46 | INFO | Train Epoch: 14 [ 4762112/26365952 (18%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.10501 (0.10035) Boundary_loss: 0.014798 (0.014890) Loss: 0.11981 (0.11524) +2025-08-25,11:28:43 | INFO | Train Epoch: 14 [ 4813312/26365952 (18%)] Avg Boundaries (per batch): 48.713 Boundary Ratio: 0.249 Contrastive_loss: 0.10324 (0.10038) Boundary_loss: 0.014901 (0.014890) Loss: 0.11814 (0.11527) +2025-08-25,11:29:39 | INFO | Train Epoch: 14 [ 4864512/26365952 (18%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.060149 (0.099960) Boundary_loss: 0.014841 (0.014890) Loss: 0.074990 (0.11485) +2025-08-25,11:30:35 | INFO | Train Epoch: 14 [ 4915712/26365952 (19%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.075799 (0.099710) Boundary_loss: 0.014888 (0.014890) Loss: 0.090687 (0.11460) +2025-08-25,11:31:32 | INFO | Train Epoch: 14 [ 4966912/26365952 (19%)] Avg Boundaries (per batch): 48.758 Boundary Ratio: 0.249 Contrastive_loss: 0.11885 (0.099906) Boundary_loss: 0.014859 (0.014889) Loss: 0.13371 (0.11480) +2025-08-25,11:32:28 | INFO | Train Epoch: 14 [ 5018112/26365952 (19%)] Avg Boundaries (per batch): 48.361 Boundary Ratio: 0.247 Contrastive_loss: 0.091441 (0.099820) Boundary_loss: 0.015000 (0.014890) Loss: 0.10644 (0.11471) +2025-08-25,11:33:24 | INFO | Train Epoch: 14 [ 5069312/26365952 (19%)] Avg Boundaries (per batch): 48.666 Boundary Ratio: 0.248 Contrastive_loss: 0.10620 (0.099884) Boundary_loss: 0.014892 (0.014890) Loss: 0.12109 (0.11477) +2025-08-25,11:34:21 | INFO | Train Epoch: 14 [ 5120512/26365952 (19%)] Avg Boundaries (per batch): 48.834 Boundary Ratio: 0.249 Contrastive_loss: 0.13193 (0.10020) Boundary_loss: 0.014896 (0.014891) Loss: 0.14682 (0.11509) +2025-08-25,11:35:17 | INFO | Train Epoch: 14 [ 5171712/26365952 (20%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.092069 (0.10012) Boundary_loss: 0.014855 (0.014890) Loss: 0.10692 (0.11501) +2025-08-25,11:36:13 | INFO | Train Epoch: 14 [ 5222912/26365952 (20%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.10853 (0.10020) Boundary_loss: 0.014873 (0.014890) Loss: 0.12341 (0.11509) +2025-08-25,11:37:10 | INFO | Train Epoch: 14 [ 5274112/26365952 (20%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.097904 (0.10018) Boundary_loss: 0.015021 (0.014891) Loss: 0.11293 (0.11507) +2025-08-25,11:38:06 | INFO | Train Epoch: 14 [ 5325312/26365952 (20%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.085381 (0.10004) Boundary_loss: 0.014869 (0.014891) Loss: 0.10025 (0.11493) +2025-08-25,11:39:02 | INFO | Train Epoch: 14 [ 5376512/26365952 (20%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.10365 (0.10007) Boundary_loss: 0.014827 (0.014890) Loss: 0.11848 (0.11496) +2025-08-25,11:39:59 | INFO | Train Epoch: 14 [ 5427712/26365952 (21%)] Avg Boundaries (per batch): 48.898 Boundary Ratio: 0.249 Contrastive_loss: 0.062894 (0.099727) Boundary_loss: 0.014878 (0.014890) Loss: 0.077773 (0.11462) +2025-08-25,11:40:55 | INFO | Train Epoch: 14 [ 5478912/26365952 (21%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.086058 (0.099600) Boundary_loss: 0.014877 (0.014890) Loss: 0.10093 (0.11449) +2025-08-25,11:41:51 | INFO | Train Epoch: 14 [ 5530112/26365952 (21%)] Avg Boundaries (per batch): 48.527 Boundary Ratio: 0.248 Contrastive_loss: 0.10120 (0.099615) Boundary_loss: 0.014959 (0.014891) Loss: 0.11616 (0.11451) +2025-08-25,11:42:48 | INFO | Train Epoch: 14 [ 5581312/26365952 (21%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.11452 (0.099750) Boundary_loss: 0.014845 (0.014890) Loss: 0.12937 (0.11464) +2025-08-25,11:43:44 | INFO | Train Epoch: 14 [ 5632512/26365952 (21%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.11969 (0.099930) Boundary_loss: 0.014822 (0.014890) Loss: 0.13451 (0.11482) +2025-08-25,11:44:41 | INFO | Train Epoch: 14 [ 5683712/26365952 (22%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.10932 (0.10001) Boundary_loss: 0.014896 (0.014890) Loss: 0.12421 (0.11490) +2025-08-25,11:45:37 | INFO | Train Epoch: 14 [ 5734912/26365952 (22%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.084236 (0.099874) Boundary_loss: 0.014875 (0.014890) Loss: 0.099111 (0.11476) +2025-08-25,11:46:33 | INFO | Train Epoch: 14 [ 5786112/26365952 (22%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.12875 (0.10013) Boundary_loss: 0.014941 (0.014890) Loss: 0.14370 (0.11502) +2025-08-25,11:47:30 | INFO | Train Epoch: 14 [ 5837312/26365952 (22%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.071926 (0.099882) Boundary_loss: 0.014923 (0.014890) Loss: 0.086849 (0.11477) +2025-08-25,11:48:26 | INFO | Train Epoch: 14 [ 5888512/26365952 (22%)] Avg Boundaries (per batch): 48.920 Boundary Ratio: 0.250 Contrastive_loss: 0.088735 (0.099786) Boundary_loss: 0.014902 (0.014891) Loss: 0.10364 (0.11468) +2025-08-25,11:49:23 | INFO | Train Epoch: 14 [ 5939712/26365952 (23%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.12617 (0.10001) Boundary_loss: 0.014918 (0.014891) Loss: 0.14109 (0.11490) +2025-08-25,11:50:19 | INFO | Train Epoch: 14 [ 5990912/26365952 (23%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.063871 (0.099705) Boundary_loss: 0.014909 (0.014891) Loss: 0.078781 (0.11460) +2025-08-25,11:51:15 | INFO | Train Epoch: 14 [ 6042112/26365952 (23%)] Avg Boundaries (per batch): 49.156 Boundary Ratio: 0.251 Contrastive_loss: 0.11674 (0.099849) Boundary_loss: 0.014922 (0.014891) Loss: 0.13166 (0.11474) +2025-08-25,11:52:12 | INFO | Train Epoch: 14 [ 6093312/26365952 (23%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.10680 (0.099906) Boundary_loss: 0.014900 (0.014891) Loss: 0.12170 (0.11480) +2025-08-25,11:53:08 | INFO | Train Epoch: 14 [ 6144512/26365952 (23%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.093776 (0.099856) Boundary_loss: 0.014936 (0.014892) Loss: 0.10871 (0.11475) +2025-08-25,11:54:04 | INFO | Train Epoch: 14 [ 6195712/26365952 (23%)] Avg Boundaries (per batch): 48.461 Boundary Ratio: 0.247 Contrastive_loss: 0.11032 (0.099942) Boundary_loss: 0.014883 (0.014892) Loss: 0.12520 (0.11483) +2025-08-25,11:55:01 | INFO | Train Epoch: 14 [ 6246912/26365952 (24%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10117 (0.099952) Boundary_loss: 0.014897 (0.014892) Loss: 0.11607 (0.11484) +2025-08-25,11:55:57 | INFO | Train Epoch: 14 [ 6298112/26365952 (24%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.14330 (0.10030) Boundary_loss: 0.014964 (0.014892) Loss: 0.15826 (0.11519) +2025-08-25,11:56:54 | INFO | Train Epoch: 14 [ 6349312/26365952 (24%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.070786 (0.10007) Boundary_loss: 0.014853 (0.014892) Loss: 0.085639 (0.11496) +2025-08-25,11:57:50 | INFO | Train Epoch: 14 [ 6400512/26365952 (24%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.10034 (0.10007) Boundary_loss: 0.014827 (0.014891) Loss: 0.11517 (0.11496) +2025-08-25,11:58:46 | INFO | Train Epoch: 14 [ 6451712/26365952 (24%)] Avg Boundaries (per batch): 49.053 Boundary Ratio: 0.250 Contrastive_loss: 0.085048 (0.099949) Boundary_loss: 0.014907 (0.014892) Loss: 0.099955 (0.11484) +2025-08-25,11:59:42 | INFO | Train Epoch: 14 [ 6502912/26365952 (25%)] Avg Boundaries (per batch): 48.990 Boundary Ratio: 0.250 Contrastive_loss: 0.10764 (0.10001) Boundary_loss: 0.014964 (0.014892) Loss: 0.12261 (0.11490) +2025-08-25,12:00:39 | INFO | Train Epoch: 14 [ 6554112/26365952 (25%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.088553 (0.099920) Boundary_loss: 0.014900 (0.014892) Loss: 0.10345 (0.11481) +2025-08-25,12:01:35 | INFO | Train Epoch: 14 [ 6605312/26365952 (25%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.076933 (0.099743) Boundary_loss: 0.014817 (0.014892) Loss: 0.091750 (0.11463) +2025-08-25,12:02:31 | INFO | Train Epoch: 14 [ 6656512/26365952 (25%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.053635 (0.099391) Boundary_loss: 0.014944 (0.014892) Loss: 0.068579 (0.11428) +2025-08-25,12:03:28 | INFO | Train Epoch: 14 [ 6707712/26365952 (25%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.094044 (0.099351) Boundary_loss: 0.014826 (0.014891) Loss: 0.10887 (0.11424) +2025-08-25,12:04:24 | INFO | Train Epoch: 14 [ 6758912/26365952 (26%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.10315 (0.099379) Boundary_loss: 0.014951 (0.014892) Loss: 0.11810 (0.11427) +2025-08-25,12:05:20 | INFO | Train Epoch: 14 [ 6810112/26365952 (26%)] Avg Boundaries (per batch): 48.545 Boundary Ratio: 0.248 Contrastive_loss: 0.097021 (0.099362) Boundary_loss: 0.014834 (0.014891) Loss: 0.11186 (0.11425) +2025-08-25,12:06:17 | INFO | Train Epoch: 14 [ 6861312/26365952 (26%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.088822 (0.099284) Boundary_loss: 0.014927 (0.014892) Loss: 0.10375 (0.11418) +2025-08-25,12:07:13 | INFO | Train Epoch: 14 [ 6912512/26365952 (26%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.10567 (0.099331) Boundary_loss: 0.014847 (0.014891) Loss: 0.12051 (0.11422) +2025-08-25,12:08:10 | INFO | Train Epoch: 14 [ 6963712/26365952 (26%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.095128 (0.099300) Boundary_loss: 0.014902 (0.014891) Loss: 0.11003 (0.11419) +2025-08-25,12:09:06 | INFO | Train Epoch: 14 [ 7014912/26365952 (27%)] Avg Boundaries (per batch): 49.029 Boundary Ratio: 0.250 Contrastive_loss: 0.098260 (0.099293) Boundary_loss: 0.014878 (0.014891) Loss: 0.11314 (0.11418) +2025-08-25,12:10:02 | INFO | Train Epoch: 14 [ 7066112/26365952 (27%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.062246 (0.099026) Boundary_loss: 0.014851 (0.014891) Loss: 0.077098 (0.11392) +2025-08-25,12:10:59 | INFO | Train Epoch: 14 [ 7117312/26365952 (27%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.10152 (0.099044) Boundary_loss: 0.014929 (0.014891) Loss: 0.11645 (0.11394) +2025-08-25,12:11:55 | INFO | Train Epoch: 14 [ 7168512/26365952 (27%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.085866 (0.098950) Boundary_loss: 0.014969 (0.014892) Loss: 0.10083 (0.11384) +2025-08-25,12:12:51 | INFO | Train Epoch: 14 [ 7219712/26365952 (27%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.091513 (0.098898) Boundary_loss: 0.014925 (0.014892) Loss: 0.10644 (0.11379) +2025-08-25,12:13:47 | INFO | Train Epoch: 14 [ 7270912/26365952 (28%)] Avg Boundaries (per batch): 48.525 Boundary Ratio: 0.248 Contrastive_loss: 0.10024 (0.098907) Boundary_loss: 0.014829 (0.014892) Loss: 0.11507 (0.11380) +2025-08-25,12:14:44 | INFO | Train Epoch: 14 [ 7322112/26365952 (28%)] Avg Boundaries (per batch): 48.764 Boundary Ratio: 0.249 Contrastive_loss: 0.12440 (0.099084) Boundary_loss: 0.014852 (0.014891) Loss: 0.13925 (0.11398) +2025-08-25,12:15:40 | INFO | Train Epoch: 14 [ 7373312/26365952 (28%)] Avg Boundaries (per batch): 48.936 Boundary Ratio: 0.250 Contrastive_loss: 0.062225 (0.098830) Boundary_loss: 0.014758 (0.014891) Loss: 0.076984 (0.11372) +2025-08-25,12:16:37 | INFO | Train Epoch: 14 [ 7424512/26365952 (28%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.10159 (0.098849) Boundary_loss: 0.015013 (0.014891) Loss: 0.11660 (0.11374) +2025-08-25,12:17:33 | INFO | Train Epoch: 14 [ 7475712/26365952 (28%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.085719 (0.098760) Boundary_loss: 0.014861 (0.014891) Loss: 0.10058 (0.11365) +2025-08-25,12:18:29 | INFO | Train Epoch: 14 [ 7526912/26365952 (29%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.11137 (0.098845) Boundary_loss: 0.014844 (0.014891) Loss: 0.12622 (0.11374) +2025-08-25,12:19:26 | INFO | Train Epoch: 14 [ 7578112/26365952 (29%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.091019 (0.098793) Boundary_loss: 0.014833 (0.014890) Loss: 0.10585 (0.11368) +2025-08-25,12:20:22 | INFO | Train Epoch: 14 [ 7629312/26365952 (29%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.076841 (0.098646) Boundary_loss: 0.014997 (0.014891) Loss: 0.091838 (0.11354) +2025-08-25,12:21:19 | INFO | Train Epoch: 14 [ 7680512/26365952 (29%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.10572 (0.098693) Boundary_loss: 0.014843 (0.014891) Loss: 0.12056 (0.11358) +2025-08-25,12:22:15 | INFO | Train Epoch: 14 [ 7731712/26365952 (29%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.11426 (0.098795) Boundary_loss: 0.014981 (0.014891) Loss: 0.12925 (0.11369) +2025-08-25,12:23:11 | INFO | Train Epoch: 14 [ 7782912/26365952 (30%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.076232 (0.098648) Boundary_loss: 0.015001 (0.014892) Loss: 0.091233 (0.11354) +2025-08-25,12:24:08 | INFO | Train Epoch: 14 [ 7834112/26365952 (30%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.081809 (0.098539) Boundary_loss: 0.014786 (0.014891) Loss: 0.096595 (0.11343) +2025-08-25,12:25:04 | INFO | Train Epoch: 14 [ 7885312/26365952 (30%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.077809 (0.098405) Boundary_loss: 0.014807 (0.014891) Loss: 0.092616 (0.11330) +2025-08-25,12:26:01 | INFO | Train Epoch: 14 [ 7936512/26365952 (30%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.085748 (0.098324) Boundary_loss: 0.014888 (0.014891) Loss: 0.10064 (0.11321) +2025-08-25,12:26:58 | INFO | Train Epoch: 14 [ 7987712/26365952 (30%)] Avg Boundaries (per batch): 48.961 Boundary Ratio: 0.250 Contrastive_loss: 0.11274 (0.098416) Boundary_loss: 0.014905 (0.014891) Loss: 0.12764 (0.11331) +2025-08-25,12:27:54 | INFO | Train Epoch: 14 [ 8038912/26365952 (30%)] Avg Boundaries (per batch): 48.820 Boundary Ratio: 0.249 Contrastive_loss: 0.11124 (0.098497) Boundary_loss: 0.014898 (0.014891) Loss: 0.12614 (0.11339) +2025-08-25,12:28:50 | INFO | Train Epoch: 14 [ 8090112/26365952 (31%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.082192 (0.098394) Boundary_loss: 0.014925 (0.014891) Loss: 0.097117 (0.11329) +2025-08-25,12:29:47 | INFO | Train Epoch: 14 [ 8141312/26365952 (31%)] Avg Boundaries (per batch): 49.193 Boundary Ratio: 0.251 Contrastive_loss: 0.082062 (0.098292) Boundary_loss: 0.014923 (0.014891) Loss: 0.096985 (0.11318) +2025-08-25,12:30:43 | INFO | Train Epoch: 14 [ 8192512/26365952 (31%)] Avg Boundaries (per batch): 48.742 Boundary Ratio: 0.249 Contrastive_loss: 0.078050 (0.098166) Boundary_loss: 0.014939 (0.014892) Loss: 0.092989 (0.11306) +2025-08-25,12:31:40 | INFO | Train Epoch: 14 [ 8243712/26365952 (31%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.079636 (0.098052) Boundary_loss: 0.014938 (0.014892) Loss: 0.094574 (0.11294) +2025-08-25,12:32:36 | INFO | Train Epoch: 14 [ 8294912/26365952 (31%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.063426 (0.097840) Boundary_loss: 0.014833 (0.014892) Loss: 0.078258 (0.11273) +2025-08-25,12:33:32 | INFO | Train Epoch: 14 [ 8346112/26365952 (32%)] Avg Boundaries (per batch): 48.838 Boundary Ratio: 0.249 Contrastive_loss: 0.098818 (0.097846) Boundary_loss: 0.014859 (0.014891) Loss: 0.11368 (0.11274) +2025-08-25,12:34:29 | INFO | Train Epoch: 14 [ 8397312/26365952 (32%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.089968 (0.097798) Boundary_loss: 0.014901 (0.014892) Loss: 0.10487 (0.11269) +2025-08-25,12:35:25 | INFO | Train Epoch: 14 [ 8448512/26365952 (32%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.078655 (0.097682) Boundary_loss: 0.014977 (0.014892) Loss: 0.093632 (0.11257) +2025-08-25,12:36:22 | INFO | Train Epoch: 14 [ 8499712/26365952 (32%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.084440 (0.097603) Boundary_loss: 0.014894 (0.014892) Loss: 0.099333 (0.11250) +2025-08-25,12:37:18 | INFO | Train Epoch: 14 [ 8550912/26365952 (32%)] Avg Boundaries (per batch): 48.941 Boundary Ratio: 0.250 Contrastive_loss: 0.11339 (0.097697) Boundary_loss: 0.014931 (0.014892) Loss: 0.12832 (0.11259) +2025-08-25,12:38:15 | INFO | Train Epoch: 14 [ 8602112/26365952 (33%)] Avg Boundaries (per batch): 48.660 Boundary Ratio: 0.248 Contrastive_loss: 0.076454 (0.097571) Boundary_loss: 0.014745 (0.014891) Loss: 0.091199 (0.11246) +2025-08-25,12:39:11 | INFO | Train Epoch: 14 [ 8653312/26365952 (33%)] Avg Boundaries (per batch): 48.793 Boundary Ratio: 0.249 Contrastive_loss: 0.085668 (0.097501) Boundary_loss: 0.014871 (0.014891) Loss: 0.10054 (0.11239) +2025-08-25,12:40:08 | INFO | Train Epoch: 14 [ 8704512/26365952 (33%)] Avg Boundaries (per batch): 48.480 Boundary Ratio: 0.247 Contrastive_loss: 0.11956 (0.097630) Boundary_loss: 0.014904 (0.014891) Loss: 0.13446 (0.11252) +2025-08-25,12:41:04 | INFO | Train Epoch: 14 [ 8755712/26365952 (33%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.11104 (0.097708) Boundary_loss: 0.014971 (0.014892) Loss: 0.12601 (0.11260) +2025-08-25,12:42:00 | INFO | Train Epoch: 14 [ 8806912/26365952 (33%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.082798 (0.097622) Boundary_loss: 0.014989 (0.014892) Loss: 0.097787 (0.11251) +2025-08-25,12:42:57 | INFO | Train Epoch: 14 [ 8858112/26365952 (34%)] Avg Boundaries (per batch): 49.150 Boundary Ratio: 0.251 Contrastive_loss: 0.11601 (0.097728) Boundary_loss: 0.014922 (0.014893) Loss: 0.13093 (0.11262) +2025-08-25,12:43:53 | INFO | Train Epoch: 14 [ 8909312/26365952 (34%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.088932 (0.097678) Boundary_loss: 0.014878 (0.014892) Loss: 0.10381 (0.11257) +2025-08-25,12:44:49 | INFO | Train Epoch: 14 [ 8960512/26365952 (34%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.10153 (0.097700) Boundary_loss: 0.014812 (0.014892) Loss: 0.11634 (0.11259) +2025-08-25,12:45:46 | INFO | Train Epoch: 14 [ 9011712/26365952 (34%)] Avg Boundaries (per batch): 49.068 Boundary Ratio: 0.250 Contrastive_loss: 0.10772 (0.097756) Boundary_loss: 0.014926 (0.014892) Loss: 0.12264 (0.11265) +2025-08-25,12:46:42 | INFO | Train Epoch: 14 [ 9062912/26365952 (34%)] Avg Boundaries (per batch): 48.943 Boundary Ratio: 0.250 Contrastive_loss: 0.087198 (0.097697) Boundary_loss: 0.014976 (0.014893) Loss: 0.10217 (0.11259) +2025-08-25,12:47:39 | INFO | Train Epoch: 14 [ 9114112/26365952 (35%)] Avg Boundaries (per batch): 48.854 Boundary Ratio: 0.249 Contrastive_loss: 0.088389 (0.097645) Boundary_loss: 0.014910 (0.014893) Loss: 0.10330 (0.11254) +2025-08-25,12:48:35 | INFO | Train Epoch: 14 [ 9165312/26365952 (35%)] Avg Boundaries (per batch): 48.438 Boundary Ratio: 0.247 Contrastive_loss: 0.10722 (0.097698) Boundary_loss: 0.014888 (0.014893) Loss: 0.12211 (0.11259) +2025-08-25,12:49:32 | INFO | Train Epoch: 14 [ 9216512/26365952 (35%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.11623 (0.097800) Boundary_loss: 0.014944 (0.014893) Loss: 0.13117 (0.11269) +2025-08-25,12:50:28 | INFO | Train Epoch: 14 [ 9267712/26365952 (35%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.087854 (0.097746) Boundary_loss: 0.014933 (0.014893) Loss: 0.10279 (0.11264) +2025-08-25,12:51:25 | INFO | Train Epoch: 14 [ 9318912/26365952 (35%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.10987 (0.097812) Boundary_loss: 0.014896 (0.014893) Loss: 0.12477 (0.11271) +2025-08-25,12:52:21 | INFO | Train Epoch: 14 [ 9370112/26365952 (36%)] Avg Boundaries (per batch): 48.648 Boundary Ratio: 0.248 Contrastive_loss: 0.063826 (0.097627) Boundary_loss: 0.014914 (0.014893) Loss: 0.078740 (0.11252) +2025-08-25,12:53:17 | INFO | Train Epoch: 14 [ 9421312/26365952 (36%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.12155 (0.097757) Boundary_loss: 0.014920 (0.014894) Loss: 0.13647 (0.11265) +2025-08-25,12:54:14 | INFO | Train Epoch: 14 [ 9472512/26365952 (36%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.091140 (0.097721) Boundary_loss: 0.014788 (0.014893) Loss: 0.10593 (0.11261) +2025-08-25,12:55:10 | INFO | Train Epoch: 14 [ 9523712/26365952 (36%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.057309 (0.097505) Boundary_loss: 0.014871 (0.014893) Loss: 0.072181 (0.11240) +2025-08-25,12:56:06 | INFO | Train Epoch: 14 [ 9574912/26365952 (36%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.072370 (0.097371) Boundary_loss: 0.014792 (0.014892) Loss: 0.087163 (0.11226) +2025-08-25,12:57:03 | INFO | Train Epoch: 14 [ 9626112/26365952 (37%)] Avg Boundaries (per batch): 48.879 Boundary Ratio: 0.249 Contrastive_loss: 0.073766 (0.097246) Boundary_loss: 0.014945 (0.014893) Loss: 0.088711 (0.11214) +2025-08-25,12:57:59 | INFO | Train Epoch: 14 [ 9677312/26365952 (37%)] Avg Boundaries (per batch): 49.145 Boundary Ratio: 0.251 Contrastive_loss: 0.13541 (0.097447) Boundary_loss: 0.014901 (0.014893) Loss: 0.15031 (0.11234) +2025-08-25,12:58:56 | INFO | Train Epoch: 14 [ 9728512/26365952 (37%)] Avg Boundaries (per batch): 48.709 Boundary Ratio: 0.249 Contrastive_loss: 0.11011 (0.097513) Boundary_loss: 0.014821 (0.014892) Loss: 0.12493 (0.11241) +2025-08-25,12:59:52 | INFO | Train Epoch: 14 [ 9779712/26365952 (37%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.13739 (0.097721) Boundary_loss: 0.014850 (0.014892) Loss: 0.15224 (0.11261) +2025-08-25,13:00:48 | INFO | Train Epoch: 14 [ 9830912/26365952 (37%)] Avg Boundaries (per batch): 49.012 Boundary Ratio: 0.250 Contrastive_loss: 0.11051 (0.097787) Boundary_loss: 0.014917 (0.014892) Loss: 0.12543 (0.11268) +2025-08-25,13:01:45 | INFO | Train Epoch: 14 [ 9882112/26365952 (37%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.096210 (0.097779) Boundary_loss: 0.014903 (0.014892) Loss: 0.11111 (0.11267) +2025-08-25,13:02:41 | INFO | Train Epoch: 14 [ 9933312/26365952 (38%)] Avg Boundaries (per batch): 48.662 Boundary Ratio: 0.248 Contrastive_loss: 0.11535 (0.097869) Boundary_loss: 0.014981 (0.014893) Loss: 0.13033 (0.11276) +2025-08-25,13:03:38 | INFO | Train Epoch: 14 [ 9984512/26365952 (38%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.087758 (0.097818) Boundary_loss: 0.014857 (0.014892) Loss: 0.10261 (0.11271) +2025-08-25,13:04:34 | INFO | Train Epoch: 14 [10035712/26365952 (38%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.094281 (0.097800) Boundary_loss: 0.014801 (0.014892) Loss: 0.10908 (0.11269) +2025-08-25,13:05:30 | INFO | Train Epoch: 14 [10086912/26365952 (38%)] Avg Boundaries (per batch): 49.152 Boundary Ratio: 0.251 Contrastive_loss: 0.073770 (0.097678) Boundary_loss: 0.014898 (0.014892) Loss: 0.088667 (0.11257) +2025-08-25,13:06:27 | INFO | Train Epoch: 14 [10138112/26365952 (38%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.093331 (0.097657) Boundary_loss: 0.014957 (0.014892) Loss: 0.10829 (0.11255) +2025-08-25,13:07:23 | INFO | Train Epoch: 14 [10189312/26365952 (39%)] Avg Boundaries (per batch): 48.609 Boundary Ratio: 0.248 Contrastive_loss: 0.10296 (0.097683) Boundary_loss: 0.014923 (0.014893) Loss: 0.11789 (0.11258) +2025-08-25,13:08:19 | INFO | Train Epoch: 14 [10240512/26365952 (39%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.093934 (0.097665) Boundary_loss: 0.014809 (0.014892) Loss: 0.10874 (0.11256) +2025-08-25,13:09:16 | INFO | Train Epoch: 14 [10291712/26365952 (39%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.11779 (0.097764) Boundary_loss: 0.014919 (0.014892) Loss: 0.13271 (0.11266) +2025-08-25,13:10:12 | INFO | Train Epoch: 14 [10342912/26365952 (39%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.082130 (0.097687) Boundary_loss: 0.015056 (0.014893) Loss: 0.097186 (0.11258) +2025-08-25,13:11:09 | INFO | Train Epoch: 14 [10394112/26365952 (39%)] Avg Boundaries (per batch): 49.000 Boundary Ratio: 0.250 Contrastive_loss: 0.086360 (0.097632) Boundary_loss: 0.014883 (0.014893) Loss: 0.10124 (0.11252) +2025-08-25,13:12:05 | INFO | Train Epoch: 14 [10445312/26365952 (40%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.11809 (0.097731) Boundary_loss: 0.014892 (0.014893) Loss: 0.13298 (0.11262) +2025-08-25,13:13:01 | INFO | Train Epoch: 14 [10496512/26365952 (40%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.11387 (0.097810) Boundary_loss: 0.014950 (0.014893) Loss: 0.12882 (0.11270) +2025-08-25,13:13:58 | INFO | Train Epoch: 14 [10547712/26365952 (40%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.11698 (0.097902) Boundary_loss: 0.014864 (0.014893) Loss: 0.13184 (0.11280) +2025-08-25,13:14:54 | INFO | Train Epoch: 14 [10598912/26365952 (40%)] Avg Boundaries (per batch): 48.723 Boundary Ratio: 0.249 Contrastive_loss: 0.082450 (0.097828) Boundary_loss: 0.014837 (0.014893) Loss: 0.097287 (0.11272) +2025-08-25,13:15:50 | INFO | Train Epoch: 14 [10650112/26365952 (40%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.10343 (0.097855) Boundary_loss: 0.014843 (0.014893) Loss: 0.11827 (0.11275) +2025-08-25,13:16:47 | INFO | Train Epoch: 14 [10701312/26365952 (41%)] Avg Boundaries (per batch): 48.598 Boundary Ratio: 0.248 Contrastive_loss: 0.11953 (0.097958) Boundary_loss: 0.014773 (0.014892) Loss: 0.13431 (0.11285) +2025-08-25,13:17:43 | INFO | Train Epoch: 14 [10752512/26365952 (41%)] Avg Boundaries (per batch): 48.592 Boundary Ratio: 0.248 Contrastive_loss: 0.088258 (0.097912) Boundary_loss: 0.014873 (0.014892) Loss: 0.10313 (0.11280) +2025-08-25,13:18:39 | INFO | Train Epoch: 14 [10803712/26365952 (41%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.075679 (0.097807) Boundary_loss: 0.014956 (0.014892) Loss: 0.090634 (0.11270) +2025-08-25,13:19:36 | INFO | Train Epoch: 14 [10854912/26365952 (41%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.079922 (0.097723) Boundary_loss: 0.014918 (0.014892) Loss: 0.094840 (0.11262) +2025-08-25,13:20:32 | INFO | Train Epoch: 14 [10906112/26365952 (41%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.072313 (0.097605) Boundary_loss: 0.014836 (0.014892) Loss: 0.087149 (0.11250) +2025-08-25,13:21:28 | INFO | Train Epoch: 14 [10957312/26365952 (42%)] Avg Boundaries (per batch): 49.064 Boundary Ratio: 0.250 Contrastive_loss: 0.11720 (0.097696) Boundary_loss: 0.014861 (0.014892) Loss: 0.13206 (0.11259) +2025-08-25,13:22:25 | INFO | Train Epoch: 14 [11008512/26365952 (42%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.089913 (0.097660) Boundary_loss: 0.014887 (0.014892) Loss: 0.10480 (0.11255) +2025-08-25,13:23:21 | INFO | Train Epoch: 14 [11059712/26365952 (42%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.11072 (0.097720) Boundary_loss: 0.014895 (0.014892) Loss: 0.12562 (0.11261) +2025-08-25,13:24:17 | INFO | Train Epoch: 14 [11110912/26365952 (42%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.069508 (0.097590) Boundary_loss: 0.014933 (0.014892) Loss: 0.084441 (0.11248) +2025-08-25,13:25:14 | INFO | Train Epoch: 14 [11162112/26365952 (42%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.073446 (0.097480) Boundary_loss: 0.014854 (0.014892) Loss: 0.088301 (0.11237) +2025-08-25,13:26:10 | INFO | Train Epoch: 14 [11213312/26365952 (43%)] Avg Boundaries (per batch): 49.008 Boundary Ratio: 0.250 Contrastive_loss: 0.11114 (0.097542) Boundary_loss: 0.014899 (0.014892) Loss: 0.12604 (0.11243) +2025-08-25,13:27:06 | INFO | Train Epoch: 14 [11264512/26365952 (43%)] Avg Boundaries (per batch): 49.264 Boundary Ratio: 0.251 Contrastive_loss: 0.12259 (0.097656) Boundary_loss: 0.015092 (0.014893) Loss: 0.13768 (0.11255) +2025-08-25,13:28:03 | INFO | Train Epoch: 14 [11315712/26365952 (43%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.093593 (0.097637) Boundary_loss: 0.014992 (0.014893) Loss: 0.10858 (0.11253) +2025-08-25,13:28:59 | INFO | Train Epoch: 14 [11366912/26365952 (43%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.18211 (0.098016) Boundary_loss: 0.014858 (0.014893) Loss: 0.19697 (0.11291) +2025-08-25,13:29:55 | INFO | Train Epoch: 14 [11418112/26365952 (43%)] Avg Boundaries (per batch): 49.016 Boundary Ratio: 0.250 Contrastive_loss: 0.10524 (0.098048) Boundary_loss: 0.014849 (0.014893) Loss: 0.12009 (0.11294) +2025-08-25,13:30:52 | INFO | Train Epoch: 14 [11469312/26365952 (44%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.087812 (0.098003) Boundary_loss: 0.014928 (0.014893) Loss: 0.10274 (0.11290) +2025-08-25,13:31:48 | INFO | Train Epoch: 14 [11520512/26365952 (44%)] Avg Boundaries (per batch): 48.762 Boundary Ratio: 0.249 Contrastive_loss: 0.10427 (0.098031) Boundary_loss: 0.014968 (0.014893) Loss: 0.11923 (0.11292) +2025-08-25,13:32:44 | INFO | Train Epoch: 14 [11571712/26365952 (44%)] Avg Boundaries (per batch): 49.131 Boundary Ratio: 0.251 Contrastive_loss: 0.091564 (0.098002) Boundary_loss: 0.014868 (0.014893) Loss: 0.10643 (0.11290) +2025-08-25,13:33:41 | INFO | Train Epoch: 14 [11622912/26365952 (44%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.10752 (0.098044) Boundary_loss: 0.014840 (0.014893) Loss: 0.12236 (0.11294) +2025-08-25,13:34:37 | INFO | Train Epoch: 14 [11674112/26365952 (44%)] Avg Boundaries (per batch): 49.051 Boundary Ratio: 0.250 Contrastive_loss: 0.094356 (0.098028) Boundary_loss: 0.014831 (0.014893) Loss: 0.10919 (0.11292) +2025-08-25,13:35:33 | INFO | Train Epoch: 14 [11725312/26365952 (44%)] Avg Boundaries (per batch): 49.184 Boundary Ratio: 0.251 Contrastive_loss: 0.094538 (0.098013) Boundary_loss: 0.014962 (0.014893) Loss: 0.10950 (0.11291) +2025-08-25,13:36:30 | INFO | Train Epoch: 14 [11776512/26365952 (45%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.073884 (0.097908) Boundary_loss: 0.014972 (0.014894) Loss: 0.088857 (0.11280) +2025-08-25,13:37:26 | INFO | Train Epoch: 14 [11827712/26365952 (45%)] Avg Boundaries (per batch): 48.904 Boundary Ratio: 0.250 Contrastive_loss: 0.10363 (0.097933) Boundary_loss: 0.014870 (0.014893) Loss: 0.11850 (0.11283) +2025-08-25,13:38:22 | INFO | Train Epoch: 14 [11878912/26365952 (45%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.086557 (0.097884) Boundary_loss: 0.014908 (0.014893) Loss: 0.10147 (0.11278) +2025-08-25,13:39:19 | INFO | Train Epoch: 14 [11930112/26365952 (45%)] Avg Boundaries (per batch): 49.090 Boundary Ratio: 0.250 Contrastive_loss: 0.10276 (0.097905) Boundary_loss: 0.014825 (0.014893) Loss: 0.11758 (0.11280) +2025-08-25,13:40:15 | INFO | Train Epoch: 14 [11981312/26365952 (45%)] Avg Boundaries (per batch): 49.227 Boundary Ratio: 0.251 Contrastive_loss: 0.10513 (0.097936) Boundary_loss: 0.014908 (0.014893) Loss: 0.12003 (0.11283) +2025-08-25,13:41:12 | INFO | Train Epoch: 14 [12032512/26365952 (46%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.090735 (0.097905) Boundary_loss: 0.014890 (0.014893) Loss: 0.10563 (0.11280) +2025-08-25,13:42:08 | INFO | Train Epoch: 14 [12083712/26365952 (46%)] Avg Boundaries (per batch): 48.760 Boundary Ratio: 0.249 Contrastive_loss: 0.10472 (0.097934) Boundary_loss: 0.014886 (0.014893) Loss: 0.11961 (0.11283) +2025-08-25,13:43:04 | INFO | Train Epoch: 14 [12134912/26365952 (46%)] Avg Boundaries (per batch): 48.916 Boundary Ratio: 0.250 Contrastive_loss: 0.092823 (0.097912) Boundary_loss: 0.015079 (0.014894) Loss: 0.10790 (0.11281) +2025-08-25,13:44:01 | INFO | Train Epoch: 14 [12186112/26365952 (46%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.084724 (0.097857) Boundary_loss: 0.014788 (0.014894) Loss: 0.099511 (0.11275) +2025-08-25,13:44:57 | INFO | Train Epoch: 14 [12237312/26365952 (46%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.083311 (0.097796) Boundary_loss: 0.014908 (0.014894) Loss: 0.098219 (0.11269) +2025-08-25,13:45:53 | INFO | Train Epoch: 14 [12288512/26365952 (47%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.082529 (0.097733) Boundary_loss: 0.014889 (0.014894) Loss: 0.097418 (0.11263) +2025-08-25,13:46:49 | INFO | Train Epoch: 14 [12339712/26365952 (47%)] Avg Boundaries (per batch): 48.865 Boundary Ratio: 0.249 Contrastive_loss: 0.096769 (0.097729) Boundary_loss: 0.014792 (0.014893) Loss: 0.11156 (0.11262) +2025-08-25,13:47:46 | INFO | Train Epoch: 14 [12390912/26365952 (47%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.090319 (0.097699) Boundary_loss: 0.015046 (0.014894) Loss: 0.10536 (0.11259) +2025-08-25,13:48:42 | INFO | Train Epoch: 14 [12442112/26365952 (47%)] Avg Boundaries (per batch): 48.590 Boundary Ratio: 0.248 Contrastive_loss: 0.069974 (0.097585) Boundary_loss: 0.014831 (0.014894) Loss: 0.084805 (0.11248) +2025-08-25,13:49:38 | INFO | Train Epoch: 14 [12493312/26365952 (47%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.097272 (0.097584) Boundary_loss: 0.014877 (0.014893) Loss: 0.11215 (0.11248) +2025-08-25,13:50:35 | INFO | Train Epoch: 14 [12544512/26365952 (48%)] Avg Boundaries (per batch): 49.244 Boundary Ratio: 0.251 Contrastive_loss: 0.053643 (0.097405) Boundary_loss: 0.014868 (0.014893) Loss: 0.068511 (0.11230) +2025-08-25,13:51:31 | INFO | Train Epoch: 14 [12595712/26365952 (48%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.071147 (0.097299) Boundary_loss: 0.014832 (0.014893) Loss: 0.085979 (0.11219) +2025-08-25,13:52:27 | INFO | Train Epoch: 14 [12646912/26365952 (48%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.077015 (0.097217) Boundary_loss: 0.014772 (0.014893) Loss: 0.091787 (0.11211) +2025-08-25,13:53:23 | INFO | Train Epoch: 14 [12698112/26365952 (48%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.086374 (0.097173) Boundary_loss: 0.014816 (0.014892) Loss: 0.10119 (0.11207) +2025-08-25,13:54:20 | INFO | Train Epoch: 14 [12749312/26365952 (48%)] Avg Boundaries (per batch): 48.477 Boundary Ratio: 0.247 Contrastive_loss: 0.10248 (0.097195) Boundary_loss: 0.014839 (0.014892) Loss: 0.11732 (0.11209) +2025-08-25,13:55:16 | INFO | Train Epoch: 14 [12800512/26365952 (49%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.083862 (0.097142) Boundary_loss: 0.014846 (0.014892) Loss: 0.098708 (0.11203) +2025-08-25,13:56:13 | INFO | Train Epoch: 14 [12851712/26365952 (49%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.12000 (0.097232) Boundary_loss: 0.014857 (0.014892) Loss: 0.13486 (0.11212) +2025-08-25,13:57:09 | INFO | Train Epoch: 14 [12902912/26365952 (49%)] Avg Boundaries (per batch): 48.973 Boundary Ratio: 0.250 Contrastive_loss: 0.068065 (0.097117) Boundary_loss: 0.014832 (0.014892) Loss: 0.082897 (0.11201) +2025-08-25,13:58:05 | INFO | Train Epoch: 14 [12954112/26365952 (49%)] Avg Boundaries (per batch): 48.848 Boundary Ratio: 0.249 Contrastive_loss: 0.075022 (0.097030) Boundary_loss: 0.015182 (0.014893) Loss: 0.090204 (0.11192) +2025-08-25,13:59:02 | INFO | Train Epoch: 14 [13005312/26365952 (49%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.16992 (0.097316) Boundary_loss: 0.014903 (0.014893) Loss: 0.18482 (0.11221) +2025-08-25,13:59:58 | INFO | Train Epoch: 14 [13056512/26365952 (50%)] Avg Boundaries (per batch): 48.791 Boundary Ratio: 0.249 Contrastive_loss: 0.071052 (0.097213) Boundary_loss: 0.014754 (0.014892) Loss: 0.085806 (0.11211) +2025-08-25,14:00:54 | INFO | Train Epoch: 14 [13107712/26365952 (50%)] Avg Boundaries (per batch): 48.711 Boundary Ratio: 0.249 Contrastive_loss: 0.10550 (0.097246) Boundary_loss: 0.014858 (0.014892) Loss: 0.12036 (0.11214) +2025-08-25,14:01:51 | INFO | Train Epoch: 14 [13158912/26365952 (50%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.074135 (0.097156) Boundary_loss: 0.014946 (0.014892) Loss: 0.089081 (0.11205) +2025-08-25,14:02:47 | INFO | Train Epoch: 14 [13210112/26365952 (50%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.081484 (0.097095) Boundary_loss: 0.014858 (0.014892) Loss: 0.096342 (0.11199) +2025-08-25,14:03:44 | INFO | Train Epoch: 14 [13261312/26365952 (50%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.091382 (0.097073) Boundary_loss: 0.014891 (0.014892) Loss: 0.10627 (0.11197) +2025-08-25,14:04:40 | INFO | Train Epoch: 14 [13312512/26365952 (50%)] Avg Boundaries (per batch): 48.980 Boundary Ratio: 0.250 Contrastive_loss: 0.073717 (0.096984) Boundary_loss: 0.014964 (0.014892) Loss: 0.088681 (0.11188) +2025-08-25,14:05:36 | INFO | Train Epoch: 14 [13363712/26365952 (51%)] Avg Boundaries (per batch): 49.062 Boundary Ratio: 0.250 Contrastive_loss: 0.086145 (0.096943) Boundary_loss: 0.014935 (0.014893) Loss: 0.10108 (0.11184) +2025-08-25,14:06:32 | INFO | Train Epoch: 14 [13414912/26365952 (51%)] Avg Boundaries (per batch): 48.613 Boundary Ratio: 0.248 Contrastive_loss: 0.10061 (0.096957) Boundary_loss: 0.014752 (0.014892) Loss: 0.11536 (0.11185) +2025-08-25,14:07:29 | INFO | Train Epoch: 14 [13466112/26365952 (51%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.087031 (0.096919) Boundary_loss: 0.014866 (0.014892) Loss: 0.10190 (0.11181) +2025-08-25,14:08:25 | INFO | Train Epoch: 14 [13517312/26365952 (51%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.069323 (0.096815) Boundary_loss: 0.014859 (0.014892) Loss: 0.084182 (0.11171) +2025-08-25,14:09:21 | INFO | Train Epoch: 14 [13568512/26365952 (51%)] Avg Boundaries (per batch): 48.510 Boundary Ratio: 0.247 Contrastive_loss: 0.078142 (0.096745) Boundary_loss: 0.014874 (0.014892) Loss: 0.093016 (0.11164) +2025-08-25,14:10:18 | INFO | Train Epoch: 14 [13619712/26365952 (52%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.054625 (0.096587) Boundary_loss: 0.014979 (0.014892) Loss: 0.069604 (0.11148) +2025-08-25,14:11:14 | INFO | Train Epoch: 14 [13670912/26365952 (52%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.073930 (0.096502) Boundary_loss: 0.014872 (0.014892) Loss: 0.088802 (0.11139) +2025-08-25,14:12:10 | INFO | Train Epoch: 14 [13722112/26365952 (52%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.13362 (0.096640) Boundary_loss: 0.014870 (0.014892) Loss: 0.14849 (0.11153) +2025-08-25,14:13:07 | INFO | Train Epoch: 14 [13773312/26365952 (52%)] Avg Boundaries (per batch): 48.881 Boundary Ratio: 0.249 Contrastive_loss: 0.10666 (0.096677) Boundary_loss: 0.014911 (0.014892) Loss: 0.12158 (0.11157) +2025-08-25,14:14:03 | INFO | Train Epoch: 14 [13824512/26365952 (52%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.10528 (0.096709) Boundary_loss: 0.014727 (0.014891) Loss: 0.12000 (0.11160) +2025-08-25,14:14:59 | INFO | Train Epoch: 14 [13875712/26365952 (53%)] Avg Boundaries (per batch): 48.996 Boundary Ratio: 0.250 Contrastive_loss: 0.094355 (0.096700) Boundary_loss: 0.014958 (0.014892) Loss: 0.10931 (0.11159) +2025-08-25,14:15:56 | INFO | Train Epoch: 14 [13926912/26365952 (53%)] Avg Boundaries (per batch): 48.686 Boundary Ratio: 0.248 Contrastive_loss: 0.10756 (0.096740) Boundary_loss: 0.014861 (0.014892) Loss: 0.12242 (0.11163) +2025-08-25,14:16:52 | INFO | Train Epoch: 14 [13978112/26365952 (53%)] Avg Boundaries (per batch): 49.125 Boundary Ratio: 0.251 Contrastive_loss: 0.093577 (0.096729) Boundary_loss: 0.014899 (0.014892) Loss: 0.10848 (0.11162) +2025-08-25,14:17:48 | INFO | Train Epoch: 14 [14029312/26365952 (53%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.10049 (0.096742) Boundary_loss: 0.014895 (0.014892) Loss: 0.11539 (0.11163) +2025-08-25,14:18:45 | INFO | Train Epoch: 14 [14080512/26365952 (53%)] Avg Boundaries (per batch): 48.703 Boundary Ratio: 0.248 Contrastive_loss: 0.089508 (0.096716) Boundary_loss: 0.014849 (0.014891) Loss: 0.10436 (0.11161) +2025-08-25,14:19:41 | INFO | Train Epoch: 14 [14131712/26365952 (54%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.065543 (0.096604) Boundary_loss: 0.014917 (0.014891) Loss: 0.080460 (0.11150) +2025-08-25,14:20:37 | INFO | Train Epoch: 14 [14182912/26365952 (54%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.098798 (0.096612) Boundary_loss: 0.014782 (0.014891) Loss: 0.11358 (0.11150) +2025-08-25,14:21:34 | INFO | Train Epoch: 14 [14234112/26365952 (54%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.090951 (0.096591) Boundary_loss: 0.014855 (0.014891) Loss: 0.10581 (0.11148) +2025-08-25,14:22:30 | INFO | Train Epoch: 14 [14285312/26365952 (54%)] Avg Boundaries (per batch): 48.236 Boundary Ratio: 0.246 Contrastive_loss: 0.12500 (0.096693) Boundary_loss: 0.014855 (0.014891) Loss: 0.13985 (0.11158) +2025-08-25,14:23:26 | INFO | Train Epoch: 14 [14336512/26365952 (54%)] Avg Boundaries (per batch): 48.867 Boundary Ratio: 0.249 Contrastive_loss: 0.10930 (0.096738) Boundary_loss: 0.014830 (0.014891) Loss: 0.12413 (0.11163) +2025-08-25,14:24:23 | INFO | Train Epoch: 14 [14387712/26365952 (55%)] Avg Boundaries (per batch): 48.988 Boundary Ratio: 0.250 Contrastive_loss: 0.086069 (0.096700) Boundary_loss: 0.014864 (0.014891) Loss: 0.10093 (0.11159) +2025-08-25,14:25:19 | INFO | Train Epoch: 14 [14438912/26365952 (55%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.073367 (0.096617) Boundary_loss: 0.014941 (0.014891) Loss: 0.088308 (0.11151) +2025-08-25,14:26:16 | INFO | Train Epoch: 14 [14490112/26365952 (55%)] Avg Boundaries (per batch): 48.924 Boundary Ratio: 0.250 Contrastive_loss: 0.099368 (0.096627) Boundary_loss: 0.014849 (0.014891) Loss: 0.11422 (0.11152) +2025-08-25,14:27:12 | INFO | Train Epoch: 14 [14541312/26365952 (55%)] Avg Boundaries (per batch): 48.600 Boundary Ratio: 0.248 Contrastive_loss: 0.085957 (0.096590) Boundary_loss: 0.014880 (0.014891) Loss: 0.10084 (0.11148) +2025-08-25,14:28:08 | INFO | Train Epoch: 14 [14592512/26365952 (55%)] Avg Boundaries (per batch): 49.105 Boundary Ratio: 0.251 Contrastive_loss: 0.088817 (0.096562) Boundary_loss: 0.014877 (0.014890) Loss: 0.10369 (0.11145) +2025-08-25,14:29:05 | INFO | Train Epoch: 14 [14643712/26365952 (56%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.091209 (0.096544) Boundary_loss: 0.014856 (0.014890) Loss: 0.10607 (0.11143) +2025-08-25,14:30:01 | INFO | Train Epoch: 14 [14694912/26365952 (56%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.11087 (0.096593) Boundary_loss: 0.014872 (0.014890) Loss: 0.12574 (0.11148) +2025-08-25,14:30:58 | INFO | Train Epoch: 14 [14746112/26365952 (56%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.10487 (0.096622) Boundary_loss: 0.015048 (0.014891) Loss: 0.11992 (0.11151) +2025-08-25,14:31:54 | INFO | Train Epoch: 14 [14797312/26365952 (56%)] Avg Boundaries (per batch): 48.789 Boundary Ratio: 0.249 Contrastive_loss: 0.068602 (0.096525) Boundary_loss: 0.014983 (0.014891) Loss: 0.083585 (0.11142) +2025-08-25,14:32:50 | INFO | Train Epoch: 14 [14848512/26365952 (56%)] Avg Boundaries (per batch): 48.830 Boundary Ratio: 0.249 Contrastive_loss: 0.10359 (0.096550) Boundary_loss: 0.014718 (0.014891) Loss: 0.11831 (0.11144) +2025-08-25,14:33:47 | INFO | Train Epoch: 14 [14899712/26365952 (57%)] Avg Boundaries (per batch): 48.979 Boundary Ratio: 0.250 Contrastive_loss: 0.095224 (0.096545) Boundary_loss: 0.014883 (0.014891) Loss: 0.11011 (0.11144) +2025-08-25,14:34:43 | INFO | Train Epoch: 14 [14950912/26365952 (57%)] Avg Boundaries (per batch): 48.902 Boundary Ratio: 0.250 Contrastive_loss: 0.079177 (0.096486) Boundary_loss: 0.014992 (0.014891) Loss: 0.094169 (0.11138) +2025-08-25,14:35:39 | INFO | Train Epoch: 14 [15002112/26365952 (57%)] Avg Boundaries (per batch): 48.623 Boundary Ratio: 0.248 Contrastive_loss: 0.12845 (0.096595) Boundary_loss: 0.014978 (0.014891) Loss: 0.14342 (0.11149) +2025-08-25,14:36:36 | INFO | Train Epoch: 14 [15053312/26365952 (57%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.11261 (0.096649) Boundary_loss: 0.014836 (0.014891) Loss: 0.12745 (0.11154) +2025-08-25,14:37:32 | INFO | Train Epoch: 14 [15104512/26365952 (57%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.090712 (0.096629) Boundary_loss: 0.014843 (0.014891) Loss: 0.10555 (0.11152) +2025-08-25,14:38:29 | INFO | Train Epoch: 14 [15155712/26365952 (57%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.073865 (0.096552) Boundary_loss: 0.014915 (0.014891) Loss: 0.088780 (0.11144) +2025-08-25,14:39:25 | INFO | Train Epoch: 14 [15206912/26365952 (58%)] Avg Boundaries (per batch): 48.770 Boundary Ratio: 0.249 Contrastive_loss: 0.13113 (0.096668) Boundary_loss: 0.014865 (0.014891) Loss: 0.14599 (0.11156) +2025-08-25,14:40:21 | INFO | Train Epoch: 14 [15258112/26365952 (58%)] Avg Boundaries (per batch): 48.840 Boundary Ratio: 0.249 Contrastive_loss: 0.11975 (0.096745) Boundary_loss: 0.014909 (0.014891) Loss: 0.13466 (0.11164) +2025-08-25,14:41:18 | INFO | Train Epoch: 14 [15309312/26365952 (58%)] Avg Boundaries (per batch): 48.738 Boundary Ratio: 0.249 Contrastive_loss: 0.097022 (0.096746) Boundary_loss: 0.014907 (0.014891) Loss: 0.11193 (0.11164) +2025-08-25,14:42:14 | INFO | Train Epoch: 14 [15360512/26365952 (58%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.11928 (0.096821) Boundary_loss: 0.014913 (0.014891) Loss: 0.13420 (0.11171) +2025-08-25,14:43:11 | INFO | Train Epoch: 14 [15411712/26365952 (58%)] Avg Boundaries (per batch): 48.746 Boundary Ratio: 0.249 Contrastive_loss: 0.069127 (0.096730) Boundary_loss: 0.014974 (0.014891) Loss: 0.084101 (0.11162) +2025-08-25,14:44:07 | INFO | Train Epoch: 14 [15462912/26365952 (59%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.12010 (0.096807) Boundary_loss: 0.014934 (0.014891) Loss: 0.13503 (0.11170) +2025-08-25,14:45:03 | INFO | Train Epoch: 14 [15514112/26365952 (59%)] Avg Boundaries (per batch): 49.025 Boundary Ratio: 0.250 Contrastive_loss: 0.067292 (0.096710) Boundary_loss: 0.014972 (0.014892) Loss: 0.082264 (0.11160) +2025-08-25,14:46:00 | INFO | Train Epoch: 14 [15565312/26365952 (59%)] Avg Boundaries (per batch): 48.518 Boundary Ratio: 0.248 Contrastive_loss: 0.074417 (0.096636) Boundary_loss: 0.014849 (0.014892) Loss: 0.089267 (0.11153) +2025-08-25,14:46:56 | INFO | Train Epoch: 14 [15616512/26365952 (59%)] Avg Boundaries (per batch): 48.537 Boundary Ratio: 0.248 Contrastive_loss: 0.12928 (0.096743) Boundary_loss: 0.014805 (0.014891) Loss: 0.14409 (0.11163) +2025-08-25,14:47:52 | INFO | Train Epoch: 14 [15667712/26365952 (59%)] Avg Boundaries (per batch): 48.691 Boundary Ratio: 0.248 Contrastive_loss: 0.11575 (0.096805) Boundary_loss: 0.015053 (0.014892) Loss: 0.13081 (0.11170) +2025-08-25,14:48:49 | INFO | Train Epoch: 14 [15718912/26365952 (60%)] Avg Boundaries (per batch): 48.732 Boundary Ratio: 0.249 Contrastive_loss: 0.10188 (0.096822) Boundary_loss: 0.014762 (0.014891) Loss: 0.11664 (0.11171) +2025-08-25,14:49:45 | INFO | Train Epoch: 14 [15770112/26365952 (60%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.071501 (0.096740) Boundary_loss: 0.014829 (0.014891) Loss: 0.086330 (0.11163) +2025-08-25,14:50:42 | INFO | Train Epoch: 14 [15821312/26365952 (60%)] Avg Boundaries (per batch): 48.795 Boundary Ratio: 0.249 Contrastive_loss: 0.10948 (0.096781) Boundary_loss: 0.014905 (0.014891) Loss: 0.12438 (0.11167) +2025-08-25,14:51:38 | INFO | Train Epoch: 14 [15872512/26365952 (60%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.10372 (0.096803) Boundary_loss: 0.014922 (0.014891) Loss: 0.11864 (0.11169) +2025-08-25,14:52:34 | INFO | Train Epoch: 14 [15923712/26365952 (60%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.12384 (0.096890) Boundary_loss: 0.014934 (0.014891) Loss: 0.13878 (0.11178) +2025-08-25,14:53:31 | INFO | Train Epoch: 14 [15974912/26365952 (61%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.071354 (0.096808) Boundary_loss: 0.014878 (0.014891) Loss: 0.086231 (0.11170) +2025-08-25,14:54:27 | INFO | Train Epoch: 14 [16026112/26365952 (61%)] Avg Boundaries (per batch): 48.594 Boundary Ratio: 0.248 Contrastive_loss: 0.062582 (0.096699) Boundary_loss: 0.014876 (0.014891) Loss: 0.077458 (0.11159) +2025-08-25,14:55:24 | INFO | Train Epoch: 14 [16077312/26365952 (61%)] Avg Boundaries (per batch): 49.041 Boundary Ratio: 0.250 Contrastive_loss: 0.085779 (0.096664) Boundary_loss: 0.014903 (0.014891) Loss: 0.10068 (0.11156) +2025-08-25,14:56:20 | INFO | Train Epoch: 14 [16128512/26365952 (61%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.096743 (0.096665) Boundary_loss: 0.014750 (0.014891) Loss: 0.11149 (0.11156) +2025-08-25,14:57:16 | INFO | Train Epoch: 14 [16179712/26365952 (61%)] Avg Boundaries (per batch): 48.797 Boundary Ratio: 0.249 Contrastive_loss: 0.087839 (0.096637) Boundary_loss: 0.014885 (0.014891) Loss: 0.10272 (0.11153) +2025-08-25,14:58:13 | INFO | Train Epoch: 14 [16230912/26365952 (62%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.084495 (0.096599) Boundary_loss: 0.014807 (0.014891) Loss: 0.099301 (0.11149) +2025-08-25,14:59:09 | INFO | Train Epoch: 14 [16282112/26365952 (62%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.080538 (0.096548) Boundary_loss: 0.014873 (0.014891) Loss: 0.095411 (0.11144) +2025-08-25,15:00:06 | INFO | Train Epoch: 14 [16333312/26365952 (62%)] Avg Boundaries (per batch): 48.781 Boundary Ratio: 0.249 Contrastive_loss: 0.11699 (0.096612) Boundary_loss: 0.015033 (0.014891) Loss: 0.13202 (0.11150) +2025-08-25,15:01:02 | INFO | Train Epoch: 14 [16384512/26365952 (62%)] Avg Boundaries (per batch): 48.672 Boundary Ratio: 0.248 Contrastive_loss: 0.098626 (0.096618) Boundary_loss: 0.014880 (0.014891) Loss: 0.11351 (0.11151) +2025-08-25,15:01:59 | INFO | Train Epoch: 14 [16435712/26365952 (62%)] Avg Boundaries (per batch): 48.891 Boundary Ratio: 0.249 Contrastive_loss: 0.093129 (0.096608) Boundary_loss: 0.014932 (0.014891) Loss: 0.10806 (0.11150) +2025-08-25,15:02:55 | INFO | Train Epoch: 14 [16486912/26365952 (63%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.084525 (0.096570) Boundary_loss: 0.014886 (0.014891) Loss: 0.099411 (0.11146) +2025-08-25,15:03:51 | INFO | Train Epoch: 14 [16538112/26365952 (63%)] Avg Boundaries (per batch): 48.684 Boundary Ratio: 0.248 Contrastive_loss: 0.081344 (0.096523) Boundary_loss: 0.015026 (0.014892) Loss: 0.096370 (0.11141) +2025-08-25,15:04:48 | INFO | Train Epoch: 14 [16589312/26365952 (63%)] Avg Boundaries (per batch): 48.812 Boundary Ratio: 0.249 Contrastive_loss: 0.099996 (0.096534) Boundary_loss: 0.014855 (0.014891) Loss: 0.11485 (0.11143) +2025-08-25,15:05:44 | INFO | Train Epoch: 14 [16640512/26365952 (63%)] Avg Boundaries (per batch): 48.625 Boundary Ratio: 0.248 Contrastive_loss: 0.081104 (0.096487) Boundary_loss: 0.014949 (0.014892) Loss: 0.096053 (0.11138) +2025-08-25,15:06:41 | INFO | Train Epoch: 14 [16691712/26365952 (63%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.099680 (0.096496) Boundary_loss: 0.014810 (0.014891) Loss: 0.11449 (0.11139) +2025-08-25,15:07:37 | INFO | Train Epoch: 14 [16742912/26365952 (64%)] Avg Boundaries (per batch): 48.432 Boundary Ratio: 0.247 Contrastive_loss: 0.11730 (0.096560) Boundary_loss: 0.014764 (0.014891) Loss: 0.13207 (0.11145) +2025-08-25,15:08:33 | INFO | Train Epoch: 14 [16794112/26365952 (64%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.095879 (0.096558) Boundary_loss: 0.014836 (0.014891) Loss: 0.11072 (0.11145) +2025-08-25,15:09:30 | INFO | Train Epoch: 14 [16845312/26365952 (64%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.091898 (0.096544) Boundary_loss: 0.014881 (0.014891) Loss: 0.10678 (0.11143) +2025-08-25,15:10:26 | INFO | Train Epoch: 14 [16896512/26365952 (64%)] Avg Boundaries (per batch): 48.945 Boundary Ratio: 0.250 Contrastive_loss: 0.12144 (0.096619) Boundary_loss: 0.014881 (0.014891) Loss: 0.13632 (0.11151) +2025-08-25,15:11:22 | INFO | Train Epoch: 14 [16947712/26365952 (64%)] Avg Boundaries (per batch): 48.557 Boundary Ratio: 0.248 Contrastive_loss: 0.097819 (0.096622) Boundary_loss: 0.014791 (0.014890) Loss: 0.11261 (0.11151) +2025-08-25,15:12:19 | INFO | Train Epoch: 14 [16998912/26365952 (64%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.10427 (0.096645) Boundary_loss: 0.014789 (0.014890) Loss: 0.11906 (0.11154) +2025-08-25,15:13:15 | INFO | Train Epoch: 14 [17050112/26365952 (65%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.075109 (0.096581) Boundary_loss: 0.015097 (0.014891) Loss: 0.090207 (0.11147) +2025-08-25,15:14:11 | INFO | Train Epoch: 14 [17101312/26365952 (65%)] Avg Boundaries (per batch): 48.729 Boundary Ratio: 0.249 Contrastive_loss: 0.090109 (0.096562) Boundary_loss: 0.014744 (0.014890) Loss: 0.10485 (0.11145) +2025-08-25,15:15:08 | INFO | Train Epoch: 14 [17152512/26365952 (65%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.084752 (0.096526) Boundary_loss: 0.014789 (0.014890) Loss: 0.099541 (0.11142) +2025-08-25,15:16:04 | INFO | Train Epoch: 14 [17203712/26365952 (65%)] Avg Boundaries (per batch): 48.621 Boundary Ratio: 0.248 Contrastive_loss: 0.093339 (0.096517) Boundary_loss: 0.014861 (0.014890) Loss: 0.10820 (0.11141) +2025-08-25,15:17:01 | INFO | Train Epoch: 14 [17254912/26365952 (65%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.10350 (0.096538) Boundary_loss: 0.014957 (0.014890) Loss: 0.11845 (0.11143) +2025-08-25,15:17:57 | INFO | Train Epoch: 14 [17306112/26365952 (66%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.066686 (0.096450) Boundary_loss: 0.014808 (0.014890) Loss: 0.081494 (0.11134) +2025-08-25,15:18:53 | INFO | Train Epoch: 14 [17357312/26365952 (66%)] Avg Boundaries (per batch): 48.951 Boundary Ratio: 0.250 Contrastive_loss: 0.099906 (0.096460) Boundary_loss: 0.014877 (0.014890) Loss: 0.11478 (0.11135) +2025-08-25,15:19:50 | INFO | Train Epoch: 14 [17408512/26365952 (66%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.090085 (0.096441) Boundary_loss: 0.014916 (0.014890) Loss: 0.10500 (0.11133) +2025-08-25,15:20:46 | INFO | Train Epoch: 14 [17459712/26365952 (66%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.12413 (0.096522) Boundary_loss: 0.014932 (0.014890) Loss: 0.13907 (0.11141) +2025-08-25,15:21:43 | INFO | Train Epoch: 14 [17510912/26365952 (66%)] Avg Boundaries (per batch): 49.035 Boundary Ratio: 0.250 Contrastive_loss: 0.10376 (0.096543) Boundary_loss: 0.014888 (0.014890) Loss: 0.11865 (0.11143) +2025-08-25,15:22:39 | INFO | Train Epoch: 14 [17562112/26365952 (67%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.092611 (0.096532) Boundary_loss: 0.015015 (0.014890) Loss: 0.10763 (0.11142) +2025-08-25,15:23:35 | INFO | Train Epoch: 14 [17613312/26365952 (67%)] Avg Boundaries (per batch): 49.162 Boundary Ratio: 0.251 Contrastive_loss: 0.076877 (0.096475) Boundary_loss: 0.014862 (0.014890) Loss: 0.091739 (0.11137) +2025-08-25,15:24:32 | INFO | Train Epoch: 14 [17664512/26365952 (67%)] Avg Boundaries (per batch): 49.092 Boundary Ratio: 0.250 Contrastive_loss: 0.089122 (0.096454) Boundary_loss: 0.014851 (0.014890) Loss: 0.10397 (0.11134) +2025-08-25,15:25:28 | INFO | Train Epoch: 14 [17715712/26365952 (67%)] Avg Boundaries (per batch): 49.119 Boundary Ratio: 0.251 Contrastive_loss: 0.080535 (0.096408) Boundary_loss: 0.014888 (0.014890) Loss: 0.095423 (0.11130) +2025-08-25,15:26:24 | INFO | Train Epoch: 14 [17766912/26365952 (67%)] Avg Boundaries (per batch): 48.965 Boundary Ratio: 0.250 Contrastive_loss: 0.093902 (0.096400) Boundary_loss: 0.014995 (0.014891) Loss: 0.10890 (0.11129) +2025-08-25,15:27:21 | INFO | Train Epoch: 14 [17818112/26365952 (68%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.092055 (0.096388) Boundary_loss: 0.014868 (0.014890) Loss: 0.10692 (0.11128) +2025-08-25,15:28:17 | INFO | Train Epoch: 14 [17869312/26365952 (68%)] Avg Boundaries (per batch): 48.596 Boundary Ratio: 0.248 Contrastive_loss: 0.088903 (0.096367) Boundary_loss: 0.014879 (0.014890) Loss: 0.10378 (0.11126) +2025-08-25,15:29:13 | INFO | Train Epoch: 14 [17920512/26365952 (68%)] Avg Boundaries (per batch): 48.721 Boundary Ratio: 0.249 Contrastive_loss: 0.092285 (0.096355) Boundary_loss: 0.014841 (0.014890) Loss: 0.10713 (0.11125) +2025-08-25,15:30:10 | INFO | Train Epoch: 14 [17971712/26365952 (68%)] Avg Boundaries (per batch): 48.570 Boundary Ratio: 0.248 Contrastive_loss: 0.069442 (0.096279) Boundary_loss: 0.014885 (0.014890) Loss: 0.084327 (0.11117) +2025-08-25,15:31:06 | INFO | Train Epoch: 14 [18022912/26365952 (68%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.11055 (0.096319) Boundary_loss: 0.014830 (0.014890) Loss: 0.12538 (0.11121) +2025-08-25,15:32:02 | INFO | Train Epoch: 14 [18074112/26365952 (69%)] Avg Boundaries (per batch): 48.926 Boundary Ratio: 0.250 Contrastive_loss: 0.10421 (0.096341) Boundary_loss: 0.014844 (0.014890) Loss: 0.11906 (0.11123) +2025-08-25,15:32:58 | INFO | Train Epoch: 14 [18125312/26365952 (69%)] Avg Boundaries (per batch): 48.725 Boundary Ratio: 0.249 Contrastive_loss: 0.10428 (0.096364) Boundary_loss: 0.014892 (0.014890) Loss: 0.11918 (0.11125) +2025-08-25,15:33:55 | INFO | Train Epoch: 14 [18176512/26365952 (69%)] Avg Boundaries (per batch): 48.574 Boundary Ratio: 0.248 Contrastive_loss: 0.10826 (0.096397) Boundary_loss: 0.014685 (0.014889) Loss: 0.12295 (0.11129) +2025-08-25,15:34:51 | INFO | Train Epoch: 14 [18227712/26365952 (69%)] Avg Boundaries (per batch): 48.607 Boundary Ratio: 0.248 Contrastive_loss: 0.092980 (0.096387) Boundary_loss: 0.014783 (0.014889) Loss: 0.10776 (0.11128) +2025-08-25,15:35:47 | INFO | Train Epoch: 14 [18278912/26365952 (69%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.11941 (0.096452) Boundary_loss: 0.014847 (0.014889) Loss: 0.13426 (0.11134) +2025-08-25,15:36:44 | INFO | Train Epoch: 14 [18330112/26365952 (70%)] Avg Boundaries (per batch): 49.084 Boundary Ratio: 0.250 Contrastive_loss: 0.14320 (0.096582) Boundary_loss: 0.014958 (0.014889) Loss: 0.15816 (0.11147) +2025-08-25,15:37:40 | INFO | Train Epoch: 14 [18381312/26365952 (70%)] Avg Boundaries (per batch): 48.932 Boundary Ratio: 0.250 Contrastive_loss: 0.098595 (0.096588) Boundary_loss: 0.014823 (0.014889) Loss: 0.11342 (0.11148) +2025-08-25,15:38:36 | INFO | Train Epoch: 14 [18432512/26365952 (70%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.12417 (0.096664) Boundary_loss: 0.014929 (0.014889) Loss: 0.13910 (0.11155) +2025-08-25,15:39:33 | INFO | Train Epoch: 14 [18483712/26365952 (70%)] Avg Boundaries (per batch): 49.004 Boundary Ratio: 0.250 Contrastive_loss: 0.096694 (0.096664) Boundary_loss: 0.014908 (0.014889) Loss: 0.11160 (0.11155) +2025-08-25,15:40:29 | INFO | Train Epoch: 14 [18534912/26365952 (70%)] Avg Boundaries (per batch): 49.117 Boundary Ratio: 0.251 Contrastive_loss: 0.092896 (0.096654) Boundary_loss: 0.014967 (0.014889) Loss: 0.10786 (0.11154) +2025-08-25,15:41:26 | INFO | Train Epoch: 14 [18586112/26365952 (70%)] Avg Boundaries (per batch): 48.547 Boundary Ratio: 0.248 Contrastive_loss: 0.11507 (0.096704) Boundary_loss: 0.014966 (0.014890) Loss: 0.13004 (0.11159) +2025-08-25,15:42:22 | INFO | Train Epoch: 14 [18637312/26365952 (71%)] Avg Boundaries (per batch): 48.633 Boundary Ratio: 0.248 Contrastive_loss: 0.087480 (0.096679) Boundary_loss: 0.014863 (0.014890) Loss: 0.10234 (0.11157) +2025-08-25,15:43:18 | INFO | Train Epoch: 14 [18688512/26365952 (71%)] Avg Boundaries (per batch): 48.744 Boundary Ratio: 0.249 Contrastive_loss: 0.056639 (0.096570) Boundary_loss: 0.015061 (0.014890) Loss: 0.071699 (0.11146) +2025-08-25,15:44:15 | INFO | Train Epoch: 14 [18739712/26365952 (71%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.091279 (0.096555) Boundary_loss: 0.014920 (0.014890) Loss: 0.10620 (0.11145) +2025-08-25,15:45:11 | INFO | Train Epoch: 14 [18790912/26365952 (71%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.10901 (0.096589) Boundary_loss: 0.014766 (0.014890) Loss: 0.12378 (0.11148) +2025-08-25,15:46:07 | INFO | Train Epoch: 14 [18842112/26365952 (71%)] Avg Boundaries (per batch): 48.754 Boundary Ratio: 0.249 Contrastive_loss: 0.078586 (0.096540) Boundary_loss: 0.014923 (0.014890) Loss: 0.093509 (0.11143) +2025-08-25,15:47:04 | INFO | Train Epoch: 14 [18893312/26365952 (72%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.083714 (0.096506) Boundary_loss: 0.014988 (0.014890) Loss: 0.098702 (0.11140) +2025-08-25,15:48:00 | INFO | Train Epoch: 14 [18944512/26365952 (72%)] Avg Boundaries (per batch): 48.588 Boundary Ratio: 0.248 Contrastive_loss: 0.10351 (0.096524) Boundary_loss: 0.014904 (0.014890) Loss: 0.11841 (0.11141) +2025-08-25,15:48:57 | INFO | Train Epoch: 14 [18995712/26365952 (72%)] Avg Boundaries (per batch): 48.861 Boundary Ratio: 0.249 Contrastive_loss: 0.085730 (0.096495) Boundary_loss: 0.014903 (0.014890) Loss: 0.10063 (0.11139) +2025-08-25,15:49:53 | INFO | Train Epoch: 14 [19046912/26365952 (72%)] Avg Boundaries (per batch): 48.508 Boundary Ratio: 0.247 Contrastive_loss: 0.10941 (0.096530) Boundary_loss: 0.014942 (0.014890) Loss: 0.12435 (0.11142) +2025-08-25,15:50:49 | INFO | Train Epoch: 14 [19098112/26365952 (72%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.10620 (0.096556) Boundary_loss: 0.014874 (0.014890) Loss: 0.12107 (0.11145) +2025-08-25,15:51:46 | INFO | Train Epoch: 14 [19149312/26365952 (73%)] Avg Boundaries (per batch): 48.730 Boundary Ratio: 0.249 Contrastive_loss: 0.078849 (0.096509) Boundary_loss: 0.014886 (0.014890) Loss: 0.093734 (0.11140) +2025-08-25,15:52:42 | INFO | Train Epoch: 14 [19200512/26365952 (73%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.10867 (0.096541) Boundary_loss: 0.014944 (0.014890) Loss: 0.12361 (0.11143) +2025-08-25,15:53:38 | INFO | Train Epoch: 14 [19251712/26365952 (73%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.12411 (0.096614) Boundary_loss: 0.014940 (0.014890) Loss: 0.13905 (0.11150) +2025-08-25,15:54:35 | INFO | Train Epoch: 14 [19302912/26365952 (73%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.10058 (0.096625) Boundary_loss: 0.014923 (0.014891) Loss: 0.11550 (0.11152) +2025-08-25,15:55:31 | INFO | Train Epoch: 14 [19354112/26365952 (73%)] Avg Boundaries (per batch): 49.074 Boundary Ratio: 0.250 Contrastive_loss: 0.10048 (0.096635) Boundary_loss: 0.014840 (0.014890) Loss: 0.11532 (0.11153) +2025-08-25,15:56:28 | INFO | Train Epoch: 14 [19405312/26365952 (74%)] Avg Boundaries (per batch): 49.111 Boundary Ratio: 0.251 Contrastive_loss: 0.082393 (0.096597) Boundary_loss: 0.014741 (0.014890) Loss: 0.097134 (0.11149) +2025-08-25,15:57:24 | INFO | Train Epoch: 14 [19456512/26365952 (74%)] Avg Boundaries (per batch): 48.828 Boundary Ratio: 0.249 Contrastive_loss: 0.080167 (0.096554) Boundary_loss: 0.014822 (0.014890) Loss: 0.094990 (0.11144) +2025-08-25,15:58:20 | INFO | Train Epoch: 14 [19507712/26365952 (74%)] Avg Boundaries (per batch): 48.707 Boundary Ratio: 0.249 Contrastive_loss: 0.10723 (0.096582) Boundary_loss: 0.014894 (0.014890) Loss: 0.12213 (0.11147) +2025-08-25,15:59:17 | INFO | Train Epoch: 14 [19558912/26365952 (74%)] Avg Boundaries (per batch): 49.146 Boundary Ratio: 0.251 Contrastive_loss: 0.073113 (0.096521) Boundary_loss: 0.014927 (0.014890) Loss: 0.088040 (0.11141) +2025-08-25,16:00:13 | INFO | Train Epoch: 14 [19610112/26365952 (74%)] Avg Boundaries (per batch): 49.020 Boundary Ratio: 0.250 Contrastive_loss: 0.084737 (0.096490) Boundary_loss: 0.014847 (0.014890) Loss: 0.099584 (0.11138) +2025-08-25,16:01:10 | INFO | Train Epoch: 14 [19661312/26365952 (75%)] Avg Boundaries (per batch): 48.639 Boundary Ratio: 0.248 Contrastive_loss: 0.10584 (0.096515) Boundary_loss: 0.014846 (0.014890) Loss: 0.12068 (0.11140) +2025-08-25,16:02:06 | INFO | Train Epoch: 14 [19712512/26365952 (75%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.11841 (0.096571) Boundary_loss: 0.014907 (0.014890) Loss: 0.13332 (0.11146) +2025-08-25,16:03:02 | INFO | Train Epoch: 14 [19763712/26365952 (75%)] Avg Boundaries (per batch): 48.939 Boundary Ratio: 0.250 Contrastive_loss: 0.078894 (0.096526) Boundary_loss: 0.014896 (0.014890) Loss: 0.093790 (0.11142) +2025-08-25,16:03:59 | INFO | Train Epoch: 14 [19814912/26365952 (75%)] Avg Boundaries (per batch): 48.779 Boundary Ratio: 0.249 Contrastive_loss: 0.11828 (0.096582) Boundary_loss: 0.014906 (0.014890) Loss: 0.13319 (0.11147) +2025-08-25,16:04:55 | INFO | Train Epoch: 14 [19866112/26365952 (75%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.14235 (0.096699) Boundary_loss: 0.014895 (0.014890) Loss: 0.15724 (0.11159) +2025-08-25,16:05:51 | INFO | Train Epoch: 14 [19917312/26365952 (76%)] Avg Boundaries (per batch): 48.523 Boundary Ratio: 0.248 Contrastive_loss: 0.083002 (0.096664) Boundary_loss: 0.014941 (0.014890) Loss: 0.097943 (0.11155) +2025-08-25,16:06:48 | INFO | Train Epoch: 14 [19968512/26365952 (76%)] Avg Boundaries (per batch): 48.826 Boundary Ratio: 0.249 Contrastive_loss: 0.088152 (0.096642) Boundary_loss: 0.014903 (0.014890) Loss: 0.10306 (0.11153) +2025-08-25,16:07:44 | INFO | Train Epoch: 14 [20019712/26365952 (76%)] Avg Boundaries (per batch): 49.502 Boundary Ratio: 0.253 Contrastive_loss: 0.097011 (0.096643) Boundary_loss: 0.014818 (0.014890) Loss: 0.11183 (0.11153) +2025-08-25,16:08:41 | INFO | Train Epoch: 14 [20070912/26365952 (76%)] Avg Boundaries (per batch): 48.807 Boundary Ratio: 0.249 Contrastive_loss: 0.10093 (0.096654) Boundary_loss: 0.014862 (0.014890) Loss: 0.11579 (0.11154) +2025-08-25,16:09:37 | INFO | Train Epoch: 14 [20122112/26365952 (76%)] Avg Boundaries (per batch): 48.678 Boundary Ratio: 0.248 Contrastive_loss: 0.068989 (0.096584) Boundary_loss: 0.015005 (0.014890) Loss: 0.083995 (0.11147) +2025-08-25,16:10:33 | INFO | Train Epoch: 14 [20173312/26365952 (77%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.092375 (0.096573) Boundary_loss: 0.014835 (0.014890) Loss: 0.10721 (0.11146) +2025-08-25,16:11:30 | INFO | Train Epoch: 14 [20224512/26365952 (77%)] Avg Boundaries (per batch): 48.896 Boundary Ratio: 0.249 Contrastive_loss: 0.085412 (0.096545) Boundary_loss: 0.014919 (0.014890) Loss: 0.10033 (0.11144) +2025-08-25,16:12:26 | INFO | Train Epoch: 14 [20275712/26365952 (77%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.068878 (0.096475) Boundary_loss: 0.014870 (0.014890) Loss: 0.083748 (0.11137) +2025-08-25,16:13:23 | INFO | Train Epoch: 14 [20326912/26365952 (77%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.083631 (0.096443) Boundary_loss: 0.014854 (0.014890) Loss: 0.098485 (0.11133) +2025-08-25,16:14:19 | INFO | Train Epoch: 14 [20378112/26365952 (77%)] Avg Boundaries (per batch): 49.141 Boundary Ratio: 0.251 Contrastive_loss: 0.091284 (0.096430) Boundary_loss: 0.014846 (0.014890) Loss: 0.10613 (0.11132) +2025-08-25,16:15:15 | INFO | Train Epoch: 14 [20429312/26365952 (77%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.11623 (0.096480) Boundary_loss: 0.014895 (0.014890) Loss: 0.13112 (0.11137) +2025-08-25,16:16:12 | INFO | Train Epoch: 14 [20480512/26365952 (78%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.084953 (0.096451) Boundary_loss: 0.014891 (0.014890) Loss: 0.099844 (0.11134) +2025-08-25,16:17:08 | INFO | Train Epoch: 14 [20531712/26365952 (78%)] Avg Boundaries (per batch): 49.082 Boundary Ratio: 0.250 Contrastive_loss: 0.089855 (0.096435) Boundary_loss: 0.015067 (0.014890) Loss: 0.10492 (0.11132) +2025-08-25,16:18:04 | INFO | Train Epoch: 14 [20582912/26365952 (78%)] Avg Boundaries (per batch): 48.539 Boundary Ratio: 0.248 Contrastive_loss: 0.078487 (0.096390) Boundary_loss: 0.014902 (0.014890) Loss: 0.093390 (0.11128) +2025-08-25,16:19:01 | INFO | Train Epoch: 14 [20634112/26365952 (78%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.10335 (0.096407) Boundary_loss: 0.014892 (0.014890) Loss: 0.11824 (0.11130) +2025-08-25,16:19:57 | INFO | Train Epoch: 14 [20685312/26365952 (78%)] Avg Boundaries (per batch): 48.682 Boundary Ratio: 0.248 Contrastive_loss: 0.078544 (0.096363) Boundary_loss: 0.014955 (0.014890) Loss: 0.093499 (0.11125) +2025-08-25,16:20:53 | INFO | Train Epoch: 14 [20736512/26365952 (79%)] Avg Boundaries (per batch): 48.699 Boundary Ratio: 0.248 Contrastive_loss: 0.081385 (0.096326) Boundary_loss: 0.014814 (0.014890) Loss: 0.096199 (0.11122) +2025-08-25,16:21:50 | INFO | Train Epoch: 14 [20787712/26365952 (79%)] Avg Boundaries (per batch): 48.619 Boundary Ratio: 0.248 Contrastive_loss: 0.085676 (0.096300) Boundary_loss: 0.014869 (0.014890) Loss: 0.10054 (0.11119) +2025-08-25,16:22:46 | INFO | Train Epoch: 14 [20838912/26365952 (79%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.11826 (0.096354) Boundary_loss: 0.014924 (0.014890) Loss: 0.13319 (0.11124) +2025-08-25,16:23:42 | INFO | Train Epoch: 14 [20890112/26365952 (79%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.074296 (0.096300) Boundary_loss: 0.014830 (0.014890) Loss: 0.089126 (0.11119) +2025-08-25,16:24:39 | INFO | Train Epoch: 14 [20941312/26365952 (79%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.11673 (0.096350) Boundary_loss: 0.014939 (0.014890) Loss: 0.13167 (0.11124) +2025-08-25,16:25:35 | INFO | Train Epoch: 14 [20992512/26365952 (80%)] Avg Boundaries (per batch): 48.701 Boundary Ratio: 0.248 Contrastive_loss: 0.099585 (0.096358) Boundary_loss: 0.014784 (0.014890) Loss: 0.11437 (0.11125) +2025-08-25,16:26:31 | INFO | Train Epoch: 14 [21043712/26365952 (80%)] Avg Boundaries (per batch): 48.969 Boundary Ratio: 0.250 Contrastive_loss: 0.12235 (0.096421) Boundary_loss: 0.014972 (0.014890) Loss: 0.13732 (0.11131) +2025-08-25,16:27:28 | INFO | Train Epoch: 14 [21094912/26365952 (80%)] Avg Boundaries (per batch): 48.697 Boundary Ratio: 0.248 Contrastive_loss: 0.097870 (0.096424) Boundary_loss: 0.014916 (0.014890) Loss: 0.11279 (0.11131) +2025-08-25,16:28:24 | INFO | Train Epoch: 14 [21146112/26365952 (80%)] Avg Boundaries (per batch): 48.656 Boundary Ratio: 0.248 Contrastive_loss: 0.079321 (0.096383) Boundary_loss: 0.014881 (0.014890) Loss: 0.094203 (0.11127) +2025-08-25,16:29:20 | INFO | Train Epoch: 14 [21197312/26365952 (80%)] Avg Boundaries (per batch): 48.664 Boundary Ratio: 0.248 Contrastive_loss: 0.11904 (0.096438) Boundary_loss: 0.014980 (0.014890) Loss: 0.13402 (0.11133) +2025-08-25,16:30:17 | INFO | Train Epoch: 14 [21248512/26365952 (81%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.11581 (0.096484) Boundary_loss: 0.014960 (0.014891) Loss: 0.13077 (0.11137) +2025-08-25,16:31:13 | INFO | Train Epoch: 14 [21299712/26365952 (81%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.12453 (0.096551) Boundary_loss: 0.014906 (0.014891) Loss: 0.13944 (0.11144) +2025-08-25,16:32:09 | INFO | Train Epoch: 14 [21350912/26365952 (81%)] Avg Boundaries (per batch): 48.627 Boundary Ratio: 0.248 Contrastive_loss: 0.10558 (0.096573) Boundary_loss: 0.014908 (0.014891) Loss: 0.12049 (0.11146) +2025-08-25,16:33:05 | INFO | Train Epoch: 14 [21402112/26365952 (81%)] Avg Boundaries (per batch): 48.822 Boundary Ratio: 0.249 Contrastive_loss: 0.12209 (0.096634) Boundary_loss: 0.014900 (0.014891) Loss: 0.13699 (0.11152) +2025-08-25,16:34:02 | INFO | Train Epoch: 14 [21453312/26365952 (81%)] Avg Boundaries (per batch): 48.850 Boundary Ratio: 0.249 Contrastive_loss: 0.061676 (0.096551) Boundary_loss: 0.014855 (0.014891) Loss: 0.076531 (0.11144) +2025-08-25,16:34:58 | INFO | Train Epoch: 14 [21504512/26365952 (82%)] Avg Boundaries (per batch): 49.010 Boundary Ratio: 0.250 Contrastive_loss: 0.062716 (0.096470) Boundary_loss: 0.014864 (0.014891) Loss: 0.077580 (0.11136) +2025-08-25,16:35:54 | INFO | Train Epoch: 14 [21555712/26365952 (82%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.13058 (0.096551) Boundary_loss: 0.014858 (0.014890) Loss: 0.14543 (0.11144) +2025-08-25,16:36:51 | INFO | Train Epoch: 14 [21606912/26365952 (82%)] Avg Boundaries (per batch): 48.689 Boundary Ratio: 0.248 Contrastive_loss: 0.13569 (0.096644) Boundary_loss: 0.014846 (0.014890) Loss: 0.15053 (0.11153) +2025-08-25,16:37:47 | INFO | Train Epoch: 14 [21658112/26365952 (82%)] Avg Boundaries (per batch): 48.490 Boundary Ratio: 0.247 Contrastive_loss: 0.13250 (0.096728) Boundary_loss: 0.014810 (0.014890) Loss: 0.14731 (0.11162) +2025-08-25,16:38:43 | INFO | Train Epoch: 14 [21709312/26365952 (82%)] Avg Boundaries (per batch): 48.928 Boundary Ratio: 0.250 Contrastive_loss: 0.091243 (0.096715) Boundary_loss: 0.014889 (0.014890) Loss: 0.10613 (0.11161) +2025-08-25,16:39:40 | INFO | Train Epoch: 14 [21760512/26365952 (83%)] Avg Boundaries (per batch): 48.900 Boundary Ratio: 0.249 Contrastive_loss: 0.10901 (0.096744) Boundary_loss: 0.014860 (0.014890) Loss: 0.12387 (0.11163) +2025-08-25,16:40:36 | INFO | Train Epoch: 14 [21811712/26365952 (83%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.095553 (0.096741) Boundary_loss: 0.014917 (0.014890) Loss: 0.11047 (0.11163) +2025-08-25,16:41:32 | INFO | Train Epoch: 14 [21862912/26365952 (83%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.10042 (0.096750) Boundary_loss: 0.014802 (0.014890) Loss: 0.11522 (0.11164) +2025-08-25,16:42:29 | INFO | Train Epoch: 14 [21914112/26365952 (83%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.074281 (0.096698) Boundary_loss: 0.014787 (0.014890) Loss: 0.089068 (0.11159) +2025-08-25,16:43:25 | INFO | Train Epoch: 14 [21965312/26365952 (83%)] Avg Boundaries (per batch): 48.846 Boundary Ratio: 0.249 Contrastive_loss: 0.073969 (0.096645) Boundary_loss: 0.014902 (0.014890) Loss: 0.088870 (0.11153) +2025-08-25,16:44:22 | INFO | Train Epoch: 14 [22016512/26365952 (84%)] Avg Boundaries (per batch): 48.938 Boundary Ratio: 0.250 Contrastive_loss: 0.075681 (0.096596) Boundary_loss: 0.014932 (0.014890) Loss: 0.090614 (0.11149) +2025-08-25,16:45:18 | INFO | Train Epoch: 14 [22067712/26365952 (84%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.095799 (0.096594) Boundary_loss: 0.014871 (0.014890) Loss: 0.11067 (0.11148) +2025-08-25,16:46:14 | INFO | Train Epoch: 14 [22118912/26365952 (84%)] Avg Boundaries (per batch): 48.766 Boundary Ratio: 0.249 Contrastive_loss: 0.055414 (0.096499) Boundary_loss: 0.014829 (0.014890) Loss: 0.070243 (0.11139) +2025-08-25,16:47:11 | INFO | Train Epoch: 14 [22170112/26365952 (84%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.12158 (0.096557) Boundary_loss: 0.014936 (0.014890) Loss: 0.13652 (0.11145) +2025-08-25,16:48:07 | INFO | Train Epoch: 14 [22221312/26365952 (84%)] Avg Boundaries (per batch): 48.768 Boundary Ratio: 0.249 Contrastive_loss: 0.10851 (0.096584) Boundary_loss: 0.014997 (0.014890) Loss: 0.12351 (0.11147) +2025-08-25,16:49:04 | INFO | Train Epoch: 14 [22272512/26365952 (84%)] Avg Boundaries (per batch): 48.787 Boundary Ratio: 0.249 Contrastive_loss: 0.096626 (0.096585) Boundary_loss: 0.014877 (0.014890) Loss: 0.11150 (0.11147) +2025-08-25,16:50:00 | INFO | Train Epoch: 14 [22323712/26365952 (85%)] Avg Boundaries (per batch): 48.914 Boundary Ratio: 0.250 Contrastive_loss: 0.081236 (0.096549) Boundary_loss: 0.015001 (0.014890) Loss: 0.096237 (0.11144) +2025-08-25,16:50:56 | INFO | Train Epoch: 14 [22374912/26365952 (85%)] Avg Boundaries (per batch): 48.844 Boundary Ratio: 0.249 Contrastive_loss: 0.063876 (0.096475) Boundary_loss: 0.014852 (0.014890) Loss: 0.078727 (0.11137) +2025-08-25,16:51:53 | INFO | Train Epoch: 14 [22426112/26365952 (85%)] Avg Boundaries (per batch): 48.559 Boundary Ratio: 0.248 Contrastive_loss: 0.12011 (0.096529) Boundary_loss: 0.014934 (0.014890) Loss: 0.13504 (0.11142) +2025-08-25,16:52:49 | INFO | Train Epoch: 14 [22477312/26365952 (85%)] Avg Boundaries (per batch): 48.584 Boundary Ratio: 0.248 Contrastive_loss: 0.093988 (0.096523) Boundary_loss: 0.014844 (0.014890) Loss: 0.10883 (0.11141) +2025-08-25,16:53:46 | INFO | Train Epoch: 14 [22528512/26365952 (85%)] Avg Boundaries (per batch): 48.611 Boundary Ratio: 0.248 Contrastive_loss: 0.10888 (0.096551) Boundary_loss: 0.014879 (0.014890) Loss: 0.12376 (0.11144) +2025-08-25,16:54:42 | INFO | Train Epoch: 14 [22579712/26365952 (86%)] Avg Boundaries (per batch): 48.955 Boundary Ratio: 0.250 Contrastive_loss: 0.071406 (0.096494) Boundary_loss: 0.014928 (0.014890) Loss: 0.086334 (0.11138) +2025-08-25,16:55:38 | INFO | Train Epoch: 14 [22630912/26365952 (86%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.10461 (0.096512) Boundary_loss: 0.014935 (0.014890) Loss: 0.11955 (0.11140) +2025-08-25,16:56:34 | INFO | Train Epoch: 14 [22682112/26365952 (86%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.071714 (0.096457) Boundary_loss: 0.014990 (0.014891) Loss: 0.086704 (0.11135) +2025-08-25,16:57:31 | INFO | Train Epoch: 14 [22733312/26365952 (86%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.096185 (0.096456) Boundary_loss: 0.014873 (0.014890) Loss: 0.11106 (0.11135) +2025-08-25,16:58:27 | INFO | Train Epoch: 14 [22784512/26365952 (86%)] Avg Boundaries (per batch): 48.535 Boundary Ratio: 0.248 Contrastive_loss: 0.093220 (0.096449) Boundary_loss: 0.014759 (0.014890) Loss: 0.10798 (0.11134) +2025-08-25,16:59:23 | INFO | Train Epoch: 14 [22835712/26365952 (87%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.072226 (0.096394) Boundary_loss: 0.014827 (0.014890) Loss: 0.087053 (0.11128) +2025-08-25,17:00:20 | INFO | Train Epoch: 14 [22886912/26365952 (87%)] Avg Boundaries (per batch): 48.877 Boundary Ratio: 0.249 Contrastive_loss: 0.11804 (0.096443) Boundary_loss: 0.014846 (0.014890) Loss: 0.13289 (0.11133) +2025-08-25,17:01:16 | INFO | Train Epoch: 14 [22938112/26365952 (87%)] Avg Boundaries (per batch): 48.773 Boundary Ratio: 0.249 Contrastive_loss: 0.084825 (0.096417) Boundary_loss: 0.014795 (0.014890) Loss: 0.099620 (0.11131) +2025-08-25,17:02:12 | INFO | Train Epoch: 14 [22989312/26365952 (87%)] Avg Boundaries (per batch): 48.617 Boundary Ratio: 0.248 Contrastive_loss: 0.079768 (0.096380) Boundary_loss: 0.014869 (0.014890) Loss: 0.094637 (0.11127) +2025-08-25,17:03:09 | INFO | Train Epoch: 14 [23040512/26365952 (87%)] Avg Boundaries (per batch): 48.562 Boundary Ratio: 0.248 Contrastive_loss: 0.078324 (0.096340) Boundary_loss: 0.014792 (0.014889) Loss: 0.093116 (0.11123) +2025-08-25,17:04:05 | INFO | Train Epoch: 14 [23091712/26365952 (88%)] Avg Boundaries (per batch): 48.580 Boundary Ratio: 0.248 Contrastive_loss: 0.097169 (0.096342) Boundary_loss: 0.014820 (0.014889) Loss: 0.11199 (0.11123) +2025-08-25,17:05:01 | INFO | Train Epoch: 14 [23142912/26365952 (88%)] Avg Boundaries (per batch): 48.646 Boundary Ratio: 0.248 Contrastive_loss: 0.11355 (0.096380) Boundary_loss: 0.014825 (0.014889) Loss: 0.12837 (0.11127) +2025-08-25,17:05:58 | INFO | Train Epoch: 14 [23194112/26365952 (88%)] Avg Boundaries (per batch): 48.740 Boundary Ratio: 0.249 Contrastive_loss: 0.11025 (0.096410) Boundary_loss: 0.014918 (0.014889) Loss: 0.12517 (0.11130) +2025-08-25,17:06:54 | INFO | Train Epoch: 14 [23245312/26365952 (88%)] Avg Boundaries (per batch): 48.818 Boundary Ratio: 0.249 Contrastive_loss: 0.070254 (0.096353) Boundary_loss: 0.014977 (0.014889) Loss: 0.085231 (0.11124) +2025-08-25,17:07:51 | INFO | Train Epoch: 14 [23296512/26365952 (88%)] Avg Boundaries (per batch): 49.070 Boundary Ratio: 0.250 Contrastive_loss: 0.091041 (0.096341) Boundary_loss: 0.014848 (0.014889) Loss: 0.10589 (0.11123) +2025-08-25,17:08:47 | INFO | Train Epoch: 14 [23347712/26365952 (89%)] Avg Boundaries (per batch): 48.805 Boundary Ratio: 0.249 Contrastive_loss: 0.10054 (0.096350) Boundary_loss: 0.014964 (0.014890) Loss: 0.11550 (0.11124) +2025-08-25,17:09:43 | INFO | Train Epoch: 14 [23398912/26365952 (89%)] Avg Boundaries (per batch): 48.676 Boundary Ratio: 0.248 Contrastive_loss: 0.097641 (0.096353) Boundary_loss: 0.014789 (0.014889) Loss: 0.11243 (0.11124) +2025-08-25,17:10:40 | INFO | Train Epoch: 14 [23450112/26365952 (89%)] Avg Boundaries (per batch): 49.168 Boundary Ratio: 0.251 Contrastive_loss: 0.098964 (0.096359) Boundary_loss: 0.014949 (0.014889) Loss: 0.11391 (0.11125) +2025-08-25,17:11:36 | INFO | Train Epoch: 14 [23501312/26365952 (89%)] Avg Boundaries (per batch): 48.930 Boundary Ratio: 0.250 Contrastive_loss: 0.11264 (0.096394) Boundary_loss: 0.014780 (0.014889) Loss: 0.12742 (0.11128) +2025-08-25,17:12:32 | INFO | Train Epoch: 14 [23552512/26365952 (89%)] Avg Boundaries (per batch): 48.641 Boundary Ratio: 0.248 Contrastive_loss: 0.095815 (0.096393) Boundary_loss: 0.014830 (0.014889) Loss: 0.11065 (0.11128) +2025-08-25,17:13:29 | INFO | Train Epoch: 14 [23603712/26365952 (90%)] Avg Boundaries (per batch): 48.963 Boundary Ratio: 0.250 Contrastive_loss: 0.10739 (0.096417) Boundary_loss: 0.014834 (0.014889) Loss: 0.12222 (0.11131) +2025-08-25,17:14:25 | INFO | Train Epoch: 14 [23654912/26365952 (90%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.076520 (0.096374) Boundary_loss: 0.014858 (0.014889) Loss: 0.091378 (0.11126) +2025-08-25,17:15:21 | INFO | Train Epoch: 14 [23706112/26365952 (90%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.10830 (0.096399) Boundary_loss: 0.014928 (0.014889) Loss: 0.12323 (0.11129) +2025-08-25,17:16:18 | INFO | Train Epoch: 14 [23757312/26365952 (90%)] Avg Boundaries (per batch): 49.023 Boundary Ratio: 0.250 Contrastive_loss: 0.088994 (0.096384) Boundary_loss: 0.014877 (0.014889) Loss: 0.10387 (0.11127) +2025-08-25,17:17:14 | INFO | Train Epoch: 14 [23808512/26365952 (90%)] Avg Boundaries (per batch): 48.783 Boundary Ratio: 0.249 Contrastive_loss: 0.10889 (0.096410) Boundary_loss: 0.014843 (0.014889) Loss: 0.12373 (0.11130) +2025-08-25,17:18:11 | INFO | Train Epoch: 14 [23859712/26365952 (90%)] Avg Boundaries (per batch): 48.705 Boundary Ratio: 0.248 Contrastive_loss: 0.094390 (0.096406) Boundary_loss: 0.014956 (0.014889) Loss: 0.10935 (0.11130) +2025-08-25,17:19:07 | INFO | Train Epoch: 14 [23910912/26365952 (91%)] Avg Boundaries (per batch): 48.982 Boundary Ratio: 0.250 Contrastive_loss: 0.095452 (0.096404) Boundary_loss: 0.014865 (0.014889) Loss: 0.11032 (0.11129) +2025-08-25,17:20:03 | INFO | Train Epoch: 14 [23962112/26365952 (91%)] Avg Boundaries (per batch): 48.971 Boundary Ratio: 0.250 Contrastive_loss: 0.11674 (0.096447) Boundary_loss: 0.014955 (0.014889) Loss: 0.13170 (0.11134) +2025-08-25,17:21:00 | INFO | Train Epoch: 14 [24013312/26365952 (91%)] Avg Boundaries (per batch): 48.869 Boundary Ratio: 0.249 Contrastive_loss: 0.11033 (0.096477) Boundary_loss: 0.014879 (0.014889) Loss: 0.12521 (0.11137) +2025-08-25,17:21:56 | INFO | Train Epoch: 14 [24064512/26365952 (91%)] Avg Boundaries (per batch): 48.424 Boundary Ratio: 0.247 Contrastive_loss: 0.068043 (0.096417) Boundary_loss: 0.014789 (0.014889) Loss: 0.082831 (0.11131) +2025-08-25,17:22:52 | INFO | Train Epoch: 14 [24115712/26365952 (91%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.099001 (0.096422) Boundary_loss: 0.014881 (0.014889) Loss: 0.11388 (0.11131) +2025-08-25,17:23:49 | INFO | Train Epoch: 14 [24166912/26365952 (92%)] Avg Boundaries (per batch): 48.756 Boundary Ratio: 0.249 Contrastive_loss: 0.063563 (0.096353) Boundary_loss: 0.014881 (0.014889) Loss: 0.078444 (0.11124) +2025-08-25,17:24:45 | INFO | Train Epoch: 14 [24218112/26365952 (92%)] Avg Boundaries (per batch): 48.811 Boundary Ratio: 0.249 Contrastive_loss: 0.091431 (0.096342) Boundary_loss: 0.014888 (0.014889) Loss: 0.10632 (0.11123) +2025-08-25,17:25:41 | INFO | Train Epoch: 14 [24269312/26365952 (92%)] Avg Boundaries (per batch): 48.752 Boundary Ratio: 0.249 Contrastive_loss: 0.11240 (0.096376) Boundary_loss: 0.014808 (0.014889) Loss: 0.12720 (0.11126) +2025-08-25,17:26:38 | INFO | Train Epoch: 14 [24320512/26365952 (92%)] Avg Boundaries (per batch): 48.814 Boundary Ratio: 0.249 Contrastive_loss: 0.070335 (0.096321) Boundary_loss: 0.014953 (0.014889) Loss: 0.085288 (0.11121) +2025-08-25,17:27:34 | INFO | Train Epoch: 14 [24371712/26365952 (92%)] Avg Boundaries (per batch): 48.852 Boundary Ratio: 0.249 Contrastive_loss: 0.066520 (0.096259) Boundary_loss: 0.014933 (0.014889) Loss: 0.081453 (0.11115) +2025-08-25,17:28:30 | INFO | Train Epoch: 14 [24422912/26365952 (93%)] Avg Boundaries (per batch): 48.803 Boundary Ratio: 0.249 Contrastive_loss: 0.075178 (0.096215) Boundary_loss: 0.014811 (0.014889) Loss: 0.089989 (0.11110) +2025-08-25,17:29:27 | INFO | Train Epoch: 14 [24474112/26365952 (93%)] Avg Boundaries (per batch): 49.123 Boundary Ratio: 0.251 Contrastive_loss: 0.063408 (0.096146) Boundary_loss: 0.014916 (0.014889) Loss: 0.078324 (0.11103) +2025-08-25,17:30:23 | INFO | Train Epoch: 14 [24525312/26365952 (93%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.078443 (0.096109) Boundary_loss: 0.014905 (0.014889) Loss: 0.093347 (0.11100) +2025-08-25,17:31:19 | INFO | Train Epoch: 14 [24576512/26365952 (93%)] Avg Boundaries (per batch): 48.785 Boundary Ratio: 0.249 Contrastive_loss: 0.081575 (0.096079) Boundary_loss: 0.014934 (0.014889) Loss: 0.096509 (0.11097) +2025-08-25,17:32:16 | INFO | Train Epoch: 14 [24627712/26365952 (93%)] Avg Boundaries (per batch): 48.582 Boundary Ratio: 0.248 Contrastive_loss: 0.069283 (0.096024) Boundary_loss: 0.014933 (0.014889) Loss: 0.084216 (0.11091) +2025-08-25,17:33:12 | INFO | Train Epoch: 14 [24678912/26365952 (94%)] Avg Boundaries (per batch): 49.096 Boundary Ratio: 0.250 Contrastive_loss: 0.10591 (0.096044) Boundary_loss: 0.014886 (0.014889) Loss: 0.12080 (0.11093) +2025-08-25,17:34:08 | INFO | Train Epoch: 14 [24730112/26365952 (94%)] Avg Boundaries (per batch): 49.006 Boundary Ratio: 0.250 Contrastive_loss: 0.074622 (0.096000) Boundary_loss: 0.014898 (0.014889) Loss: 0.089520 (0.11089) +2025-08-25,17:35:05 | INFO | Train Epoch: 14 [24781312/26365952 (94%)] Avg Boundaries (per batch): 48.889 Boundary Ratio: 0.249 Contrastive_loss: 0.085065 (0.095977) Boundary_loss: 0.014835 (0.014889) Loss: 0.099900 (0.11087) +2025-08-25,17:36:01 | INFO | Train Epoch: 14 [24832512/26365952 (94%)] Avg Boundaries (per batch): 48.668 Boundary Ratio: 0.248 Contrastive_loss: 0.079516 (0.095943) Boundary_loss: 0.014888 (0.014889) Loss: 0.094403 (0.11083) +2025-08-25,17:36:57 | INFO | Train Epoch: 14 [24883712/26365952 (94%)] Avg Boundaries (per batch): 48.906 Boundary Ratio: 0.250 Contrastive_loss: 0.11355 (0.095979) Boundary_loss: 0.014816 (0.014889) Loss: 0.12836 (0.11087) +2025-08-25,17:37:54 | INFO | Train Epoch: 14 [24934912/26365952 (95%)] Avg Boundaries (per batch): 48.908 Boundary Ratio: 0.250 Contrastive_loss: 0.12696 (0.096043) Boundary_loss: 0.014903 (0.014889) Loss: 0.14186 (0.11093) +2025-08-25,17:38:50 | INFO | Train Epoch: 14 [24986112/26365952 (95%)] Avg Boundaries (per batch): 49.002 Boundary Ratio: 0.250 Contrastive_loss: 0.083879 (0.096018) Boundary_loss: 0.014879 (0.014889) Loss: 0.098758 (0.11091) +2025-08-25,17:39:46 | INFO | Train Epoch: 14 [25037312/26365952 (95%)] Avg Boundaries (per batch): 48.922 Boundary Ratio: 0.250 Contrastive_loss: 0.10132 (0.096029) Boundary_loss: 0.014899 (0.014889) Loss: 0.11622 (0.11092) +2025-08-25,17:40:43 | INFO | Train Epoch: 14 [25088512/26365952 (95%)] Avg Boundaries (per batch): 48.947 Boundary Ratio: 0.250 Contrastive_loss: 0.089934 (0.096016) Boundary_loss: 0.014905 (0.014889) Loss: 0.10484 (0.11091) +2025-08-25,17:41:39 | INFO | Train Epoch: 14 [25139712/26365952 (95%)] Avg Boundaries (per batch): 48.859 Boundary Ratio: 0.249 Contrastive_loss: 0.087343 (0.095999) Boundary_loss: 0.014932 (0.014889) Loss: 0.10228 (0.11089) +2025-08-25,17:42:36 | INFO | Train Epoch: 14 [25190912/26365952 (96%)] Avg Boundaries (per batch): 49.076 Boundary Ratio: 0.250 Contrastive_loss: 0.11482 (0.096037) Boundary_loss: 0.014806 (0.014889) Loss: 0.12962 (0.11093) +2025-08-25,17:43:32 | INFO | Train Epoch: 14 [25242112/26365952 (96%)] Avg Boundaries (per batch): 48.887 Boundary Ratio: 0.249 Contrastive_loss: 0.098966 (0.096043) Boundary_loss: 0.014948 (0.014889) Loss: 0.11391 (0.11093) +2025-08-25,17:44:28 | INFO | Train Epoch: 14 [25293312/26365952 (96%)] Avg Boundaries (per batch): 48.824 Boundary Ratio: 0.249 Contrastive_loss: 0.098390 (0.096048) Boundary_loss: 0.014889 (0.014889) Loss: 0.11328 (0.11094) +2025-08-25,17:45:25 | INFO | Train Epoch: 14 [25344512/26365952 (96%)] Avg Boundaries (per batch): 48.832 Boundary Ratio: 0.249 Contrastive_loss: 0.080715 (0.096017) Boundary_loss: 0.014922 (0.014889) Loss: 0.095637 (0.11091) +2025-08-25,17:46:21 | INFO | Train Epoch: 14 [25395712/26365952 (96%)] Avg Boundaries (per batch): 48.871 Boundary Ratio: 0.249 Contrastive_loss: 0.12403 (0.096073) Boundary_loss: 0.014790 (0.014889) Loss: 0.13882 (0.11096) +2025-08-25,17:47:17 | INFO | Train Epoch: 14 [25446912/26365952 (97%)] Avg Boundaries (per batch): 48.465 Boundary Ratio: 0.247 Contrastive_loss: 0.085687 (0.096052) Boundary_loss: 0.014980 (0.014889) Loss: 0.10067 (0.11094) +2025-08-25,17:48:14 | INFO | Train Epoch: 14 [25498112/26365952 (97%)] Avg Boundaries (per batch): 48.631 Boundary Ratio: 0.248 Contrastive_loss: 0.092764 (0.096046) Boundary_loss: 0.014851 (0.014889) Loss: 0.10762 (0.11093) +2025-08-25,17:49:10 | INFO | Train Epoch: 14 [25549312/26365952 (97%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.092305 (0.096038) Boundary_loss: 0.014792 (0.014889) Loss: 0.10710 (0.11093) +2025-08-25,17:50:07 | INFO | Train Epoch: 14 [25600512/26365952 (97%)] Avg Boundaries (per batch): 48.949 Boundary Ratio: 0.250 Contrastive_loss: 0.094474 (0.096035) Boundary_loss: 0.014971 (0.014889) Loss: 0.10945 (0.11092) +2025-08-25,17:51:03 | INFO | Train Epoch: 14 [25651712/26365952 (97%)] Avg Boundaries (per batch): 48.658 Boundary Ratio: 0.248 Contrastive_loss: 0.090556 (0.096024) Boundary_loss: 0.014851 (0.014889) Loss: 0.10541 (0.11091) +2025-08-25,17:52:00 | INFO | Train Epoch: 14 [25702912/26365952 (97%)] Avg Boundaries (per batch): 48.910 Boundary Ratio: 0.250 Contrastive_loss: 0.098366 (0.096029) Boundary_loss: 0.014786 (0.014888) Loss: 0.11315 (0.11092) +2025-08-25,17:52:56 | INFO | Train Epoch: 14 [25754112/26365952 (98%)] Avg Boundaries (per batch): 48.912 Boundary Ratio: 0.250 Contrastive_loss: 0.11002 (0.096057) Boundary_loss: 0.014910 (0.014889) Loss: 0.12493 (0.11095) +2025-08-25,17:53:52 | INFO | Train Epoch: 14 [25805312/26365952 (98%)] Avg Boundaries (per batch): 48.727 Boundary Ratio: 0.249 Contrastive_loss: 0.12456 (0.096113) Boundary_loss: 0.014958 (0.014889) Loss: 0.13951 (0.11100) +2025-08-25,17:54:49 | INFO | Train Epoch: 14 [25856512/26365952 (98%)] Avg Boundaries (per batch): 48.410 Boundary Ratio: 0.247 Contrastive_loss: 0.060946 (0.096044) Boundary_loss: 0.014952 (0.014889) Loss: 0.075898 (0.11093) +2025-08-25,17:55:45 | INFO | Train Epoch: 14 [25907712/26365952 (98%)] Avg Boundaries (per batch): 48.863 Boundary Ratio: 0.249 Contrastive_loss: 0.12443 (0.096099) Boundary_loss: 0.014951 (0.014889) Loss: 0.13938 (0.11099) +2025-08-25,17:56:41 | INFO | Train Epoch: 14 [25958912/26365952 (98%)] Avg Boundaries (per batch): 48.994 Boundary Ratio: 0.250 Contrastive_loss: 0.091085 (0.096090) Boundary_loss: 0.014914 (0.014889) Loss: 0.10600 (0.11098) +2025-08-25,17:57:38 | INFO | Train Epoch: 14 [26010112/26365952 (99%)] Avg Boundaries (per batch): 48.885 Boundary Ratio: 0.249 Contrastive_loss: 0.066999 (0.096032) Boundary_loss: 0.014907 (0.014889) Loss: 0.081906 (0.11092) +2025-08-25,17:58:34 | INFO | Train Epoch: 14 [26061312/26365952 (99%)] Avg Boundaries (per batch): 48.953 Boundary Ratio: 0.250 Contrastive_loss: 0.068546 (0.095979) Boundary_loss: 0.014886 (0.014889) Loss: 0.083432 (0.11087) +2025-08-25,17:59:31 | INFO | Train Epoch: 14 [26112512/26365952 (99%)] Avg Boundaries (per batch): 48.635 Boundary Ratio: 0.248 Contrastive_loss: 0.086759 (0.095961) Boundary_loss: 0.014857 (0.014889) Loss: 0.10162 (0.11085) +2025-08-25,18:00:27 | INFO | Train Epoch: 14 [26163712/26365952 (99%)] Avg Boundaries (per batch): 48.842 Boundary Ratio: 0.249 Contrastive_loss: 0.10487 (0.095978) Boundary_loss: 0.014833 (0.014889) Loss: 0.11970 (0.11087) +2025-08-25,18:01:23 | INFO | Train Epoch: 14 [26214912/26365952 (99%)] Avg Boundaries (per batch): 48.688 Boundary Ratio: 0.248 Contrastive_loss: 0.12610 (0.096037) Boundary_loss: 0.014800 (0.014889) Loss: 0.14090 (0.11093) +2025-08-25,18:02:20 | INFO | Train Epoch: 14 [26266112/26365952 (100%)] Avg Boundaries (per batch): 48.855 Boundary Ratio: 0.249 Contrastive_loss: 0.088314 (0.096022) Boundary_loss: 0.014864 (0.014889) Loss: 0.10318 (0.11091) +2025-08-25,18:03:16 | INFO | Train Epoch: 14 [26317312/26365952 (100%)] Avg Boundaries (per batch): 49.197 Boundary Ratio: 0.251 Contrastive_loss: 0.066473 (0.095964) Boundary_loss: 0.014897 (0.014889) Loss: 0.081370 (0.11085) +2025-08-25,18:04:09 | INFO | Train Epoch: 14 [26365952/26365952 (100%)] Avg Boundaries (per batch): 48.918 Boundary Ratio: 0.250 Contrastive_loss: 0.085389 (0.095944) Boundary_loss: 0.014964 (0.014889) Loss: 0.10035 (0.11083) +2025-08-25,18:04:09 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-25,18:04:09 | INFO | [Epoch 14] Average Step Time: 0.567s | Average GPU Memory: 31.6 GB +2025-08-25,18:04:09 | INFO | ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ +2025-08-25,18:04:09 | INFO | Starting zero-shot imagenet. +2025-08-25,18:04:09 | INFO | Building zero-shot classifier +2025-08-25,18:04:19 | INFO | Using classifier +2025-08-25,18:05:06 | INFO | Finished zero-shot imagenet. +2025-08-25,18:05:06 | INFO | Eval Epoch: 15 imagenet-zeroshot-val-top1: 0.3101 imagenet-zeroshot-val-top5: 0.5770