[2026-07-18 18:01:33,647][__main__][INFO] - [rank: 0] Instantiating datamodule <fish_speech.datasets.semantic.SemanticDataModule>
[2026-07-18 18:01:33,662][datasets][INFO] - PyTorch version 2.8.0+cu128 available.
[2026-07-18 18:01:34,447][fish_speech.tokenizer][INFO] - Loaded Tokenizer. Semantic Range: 151678 -> 155773
[2026-07-18 18:01:34,960][fish_speech.tokenizer][INFO] - Loaded Tokenizer. Semantic Range: 151678 -> 155773
[2026-07-18 18:01:35,498][fish_speech.tokenizer][INFO] - Loaded Tokenizer. Semantic Range: 151678 -> 155773
[2026-07-18 18:01:35,501][__main__][INFO] - [rank: 0] Instantiating model <fish_speech.models.text2semantic.lit_module.TextToSemantic>
2026-07-18 18:01:35.510 | INFO     | fish_speech.models.text2semantic.llama:from_pretrained:493 - Override max_seq_len to 4096
[2026-07-18 18:01:36,017][fish_speech.tokenizer][INFO] - Loaded Tokenizer. Semantic Range: 151678 -> 155773
2026-07-18 18:01:36.020 | INFO     | fish_speech.models.text2semantic.llama:from_pretrained:504 - Injected Semantic IDs into Config: 151678-155773
2026-07-18 18:01:36.020 | INFO     | fish_speech.models.text2semantic.llama:from_pretrained:520 - Loading model from /opt/work/checkpoints/s2-pro, config: DualARModelArgs(model_type='dual_ar', vocab_size=155776, n_layer=36, n_head=32, dim=2560, intermediate_size=9728, n_local_heads=8, head_dim=128, rope_base=1000000, norm_eps=1e-06, max_seq_len=4096, dropout=0.0, tie_word_embeddings=True, attention_qkv_bias=False, attention_o_bias=False, attention_qk_norm=True, codebook_size=4096, num_codebooks=10, semantic_begin_id=151678, semantic_end_id=155773, use_gradient_checkpointing=True, initializer_range=0.01976423537605237, is_reward_model=False, scale_codebook_embeddings=True, audio_embed_dim=2560, n_fast_layer=4, fast_dim=2560, fast_n_head=32, fast_n_local_heads=8, fast_head_dim=128, fast_intermediate_size=9728, fast_attention_qkv_bias=False, fast_attention_qk_norm=False, fast_attention_o_bias=False, norm_fastlayer_input=True)
2026-07-18 18:02:13.011 | INFO     | fish_speech.models.text2semantic.llama:from_pretrained:552 - Loading sharded safetensors weights
2026-07-18 18:02:14.118 | INFO     | fish_speech.models.text2semantic.llama:from_pretrained:588 - Model weights loaded - Status: <All keys matched successfully>
2026-07-18 18:02:17.313 | INFO     | fish_speech.models.text2semantic.llama:from_pretrained:592 - LoRA setup: LoraConfig(r=32, lora_alpha=16, lora_dropout=0.1, target_modules=['fast_attention', 'fast_mlp', 'fast_embeddings', 'fast_output'])
[2026-07-18 18:02:17,314][__main__][INFO] - [rank: 0] Instantiating callbacks...
[2026-07-18 18:02:17,314][fish_speech.utils.instantiators][INFO] - [rank: 0] Instantiating callback <lightning.pytorch.callbacks.ModelCheckpoint>
[2026-07-18 18:02:17,316][fish_speech.utils.instantiators][INFO] - [rank: 0] Instantiating callback <lightning.pytorch.callbacks.ModelSummary>
[2026-07-18 18:02:17,316][fish_speech.utils.instantiators][INFO] - [rank: 0] Instantiating callback <lightning.pytorch.callbacks.LearningRateMonitor>
[2026-07-18 18:02:17,316][fish_speech.utils.instantiators][INFO] - [rank: 0] Instantiating callback <fish_speech.callbacks.GradNormMonitor>
[2026-07-18 18:02:17,317][fish_speech.utils.instantiators][INFO] - [rank: 0] Instantiating callback <fish_speech.callbacks.GradAccumProgressBar>
[2026-07-18 18:02:17,317][__main__][INFO] - [rank: 0] Instantiating loggers...
[2026-07-18 18:02:17,317][fish_speech.utils.instantiators][INFO] - [rank: 0] Instantiating logger <lightning.pytorch.loggers.tensorboard.TensorBoardLogger>
[2026-07-18 18:02:17,318][__main__][INFO] - [rank: 0] Instantiating trainer <lightning.pytorch.trainer.Trainer>
Trainer already configured with model summary callbacks: [<class 'lightning.pytorch.callbacks.model_summary.ModelSummary'>]. Skipping setting a default `ModelSummary` callback.
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
[2026-07-18 18:02:18,479][__main__][INFO] - [rank: 0] Logging hyperparameters!
[2026-07-18 18:02:18,525][__main__][INFO] - [rank: 0] Starting training!
[2026-07-18 18:02:18,527][__main__][INFO] - [rank: 0] Resuming from checkpoint: results/s2pro_egy_fast/checkpoints/step_000000200.ckpt
Initializing distributed: GLOBAL_RANK: 0, MEMBER: 1/1
----------------------------------------------------------------------------------------------------
distributed_backend=nccl
All distributed processes registered. Starting with 1 processes
----------------------------------------------------------------------------------------------------

/opt/work/fish-speech/.venv/lib/python3.12/site-packages/lightning/pytorch/callbacks/model_checkpoint.py:751: Checkpoint directory /opt/work/fish-speech/results/s2pro_egy_fast/checkpoints exists and is not empty.
Restoring states from the checkpoint path at results/s2pro_egy_fast/checkpoints/step_000000200.ckpt
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
[2026-07-18 18:02:20,535][fish_speech.models.text2semantic.lit_module][INFO] - [rank: 0] Set weight decay: 0.01 for 247 parameters
[2026-07-18 18:02:20,536][fish_speech.models.text2semantic.lit_module][INFO] - [rank: 0] Set weight decay: 0.0 for 155 parameters

  | Name                      | Type              | Params | Mode 
------------------------------------------------------------------------
0 | model                     | DualARTransformer | 4.6 B  | train
1 | model.embeddings          | Embedding         | 398 M  | train
2 | model.codebook_embeddings | Embedding         | 104 M  | train
3 | model.layers              | ModuleList        | 3.6 B  | train
4 | model.norm                | RMSNorm           | 2.6 K  | train
5 | model.fast_project_in     | Identity          | 0      | train
6 | model.fast_embeddings     | Embedding         | 10.7 M | train
7 | model.fast_layers         | ModuleList        | 410 M  | train
8 | model.fast_norm           | RMSNorm           | 2.6 K  | train
9 | model.fast_output         | Linear            | 10.7 M | train
------------------------------------------------------------------------
7.1 M     Trainable params
4.6 B     Non-trainable params
4.6 B     Total params
9,137.926 Total estimated model params size (MB)
503       Modules in train mode
0         Modules in eval mode
Restored all states from the checkpoint at results/s2pro_egy_fast/checkpoints/step_000000200.ckpt
[2026-07-18 18:02:20,856][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 2 / 6 files
[2026-07-18 18:02:20,856][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 6 files
[2026-07-18 18:02:20,857][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 2 / 6 files
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[2026-07-18 18:02:20,860][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 2 / 6 files
[2026-07-18 18:02:20,862][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 6 files
[2026-07-18 18:02:20,860][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 6 files
[2026-07-18 18:02:20,886][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 6 files
[2026-07-18 18:02:20,930][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 9 groups of data
[2026-07-18 18:02:20,935][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 33 groups of data
[2026-07-18 18:02:20,954][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 40 groups of data
[2026-07-18 18:02:20,977][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 2 groups of data
[2026-07-18 18:02:20,977][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 60 groups of data
[2026-07-18 18:02:20,986][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 36 groups of data
[2026-07-18 18:02:20,999][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 50 groups of data
[2026-07-18 18:02:21,022][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 12 groups of data

Training: |          | 0/? [00:00<?, ?it/s][2026-07-18 18:02:21,421][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 1 files
[2026-07-18 18:02:21,421][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 2 / 1 files
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[2026-07-18 18:02:21,425][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 1 files
[2026-07-18 18:02:21,427][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 21 groups of data
[2026-07-18 18:02:21,427][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 21 groups of data
[2026-07-18 18:02:21,427][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 1 files
[2026-07-18 18:02:21,429][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 21 groups of data
[2026-07-18 18:02:21,430][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 1 files
[2026-07-18 18:02:21,431][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 21 groups of data
[2026-07-18 18:02:21,434][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 42 groups of data
[2026-07-18 18:02:21,434][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 21 groups of data
[2026-07-18 18:02:21,437][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 21 groups of data
[2026-07-18 18:02:21,452][fish_speech.datasets.semantic][INFO] - [rank: 0] Reading 1 / 1 files
[2026-07-18 18:02:21,458][fish_speech.datasets.semantic][INFO] - [rank: 0] Read total 21 groups of data

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Training: |          | 821/? [00:22<00:00, 36.08it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00787]
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Training: |          | 823/? [00:24<00:00, 33.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00693]
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Training: |          | 830/? [00:32<00:00, 25.91it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00656]
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Training: |          | 831/? [00:33<00:00, 25.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0118] 
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Training: |          | 832/? [00:34<00:00, 24.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00818]
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Training: |          | 834/? [00:36<00:00, 23.08it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00787]
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Training: |          | 837/? [00:39<00:00, 21.34it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0083] 
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Training: |          | 838/? [00:40<00:00, 20.80it/s, v_num=2, train/loss=17.90, train/top_5_accuracy=0.00723]
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Training: |          | 839/? [00:41<00:00, 20.30it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00842]
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Training: |          | 840/? [00:42<00:00, 19.84it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00891]
Training: |          | 841/? [00:42<00:00, 19.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00891]
Training: |          | 841/? [00:43<00:00, 19.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00916]
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Training: |          | 842/? [00:44<00:00, 18.98it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00702]
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Training: |          | 843/? [00:45<00:00, 18.58it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.00995]
Training: |          | 844/? [00:45<00:00, 18.36it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.00995]
Training: |          | 844/? [00:46<00:00, 18.18it/s, v_num=2, train/loss=17.90, train/top_5_accuracy=0.00659]
Training: |          | 845/? [00:47<00:00, 17.97it/s, v_num=2, train/loss=17.90, train/top_5_accuracy=0.00659]
Training: |          | 845/? [00:47<00:00, 17.81it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00793]
Training: |          | 846/? [00:48<00:00, 17.61it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00793]
Training: |          | 846/? [00:48<00:00, 17.44it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00775]
Training: |          | 847/? [00:49<00:00, 17.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00775]
Training: |          | 847/? [00:49<00:00, 17.09it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101] 
Training: |          | 848/? [00:50<00:00, 16.92it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101]
Training: |          | 848/? [00:50<00:00, 16.77it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00848]
Training: |          | 849/? [00:51<00:00, 16.61it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00848]
Training: |          | 849/? [00:51<00:00, 16.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00983]
Training: |          | 850/? [00:52<00:00, 16.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00983]
Training: |          | 850/? [00:52<00:00, 16.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00812]
Training: |          | 851/? [00:53<00:00, 16.00it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00812]
Training: |          | 851/? [00:53<00:00, 15.88it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104] 
Training: |          | 852/? [00:54<00:00, 15.71it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104]
Training: |          | 852/? [00:54<00:00, 15.58it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008] 
Training: |          | 853/? [00:55<00:00, 15.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008]
Training: |          | 853/? [00:55<00:00, 15.31it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00952]
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Training: |          | 854/? [00:56<00:00, 15.03it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0083] 
Training: |          | 855/? [00:57<00:00, 14.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0083]
Training: |          | 855/? [00:57<00:00, 14.79it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114]
Training: |          | 856/? [00:58<00:00, 14.65it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114]
Training: |          | 856/? [00:58<00:00, 14.55it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094]
Training: |          | 857/? [00:59<00:00, 14.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094]
Training: |          | 857/? [00:59<00:00, 14.31it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00653]
Training: |          | 858/? [01:00<00:00, 14.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00653]
Training: |          | 858/? [01:00<00:00, 14.09it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00934]
Training: |          | 859/? [01:01<00:00, 13.96it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00934]
Training: |          | 859/? [01:01<00:00, 13.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00653]
Training: |          | 860/? [01:02<00:00, 13.76it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00653]
Training: |          | 860/? [01:02<00:00, 13.67it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106] 
Training: |          | 861/? [01:03<00:00, 13.55it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106]
Training: |          | 861/? [01:03<00:00, 13.46it/s, v_num=2, train/loss=18.20, train/top_5_accuracy=0.00574]
Training: |          | 862/? [01:04<00:00, 13.35it/s, v_num=2, train/loss=18.20, train/top_5_accuracy=0.00574]
Training: |          | 862/? [01:05<00:00, 13.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00891]
Training: |          | 863/? [01:05<00:00, 13.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00891]
Training: |          | 863/? [01:06<00:00, 13.08it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00708]
Training: |          | 864/? [01:06<00:00, 12.97it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00708]
Training: |          | 864/? [01:07<00:00, 12.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00781]
Training: |          | 865/? [01:07<00:00, 12.79it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00781]
Training: |          | 865/? [01:08<00:00, 12.71it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00714]
Training: |          | 866/? [01:08<00:00, 12.62it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00714]
Training: |          | 866/? [01:09<00:00, 12.53it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00754]
Training: |          | 867/? [01:09<00:00, 12.44it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00754]
Training: |          | 867/? [01:10<00:00, 12.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00836]
Training: |          | 868/? [01:10<00:00, 12.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00836]
Training: |          | 868/? [01:11<00:00, 12.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094] 
Training: |          | 869/? [01:11<00:00, 12.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094]
Training: |          | 869/? [01:12<00:00, 12.05it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836]
Training: |          | 870/? [01:12<00:00, 11.96it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836]
Training: |          | 870/? [01:13<00:00, 11.89it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00848]
Training: |          | 871/? [01:13<00:00, 11.81it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00848]
Training: |          | 871/? [01:14<00:00, 11.74it/s, v_num=2, train/loss=15.70, train/top_5_accuracy=0.0136] 
Training: |          | 872/? [01:14<00:00, 11.66it/s, v_num=2, train/loss=15.70, train/top_5_accuracy=0.0136]
Training: |          | 872/? [01:15<00:00, 11.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00824]
Training: |          | 873/? [01:15<00:00, 11.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00824]
Training: |          | 873/? [01:16<00:00, 11.45it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00748]
Training: |          | 874/? [01:16<00:00, 11.38it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00748]
Training: |          | 874/? [01:17<00:00, 11.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00995]
Training: |          | 875/? [01:17<00:00, 11.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00995]
Training: |          | 875/? [01:18<00:00, 11.18it/s, v_num=2, train/loss=18.20, train/top_5_accuracy=0.00546]
Training: |          | 876/? [01:18<00:00, 11.10it/s, v_num=2, train/loss=18.20, train/top_5_accuracy=0.00546]
Training: |          | 876/? [01:19<00:00, 11.04it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0115] 
Training: |          | 877/? [01:19<00:00, 10.97it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0115]
Training: |          | 877/? [01:20<00:00, 10.91it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0106]
Training: |          | 878/? [01:20<00:00, 10.84it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0106]
Training: |          | 878/? [01:21<00:00, 10.78it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00778]
Training: |          | 879/? [01:22<00:00, 10.71it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00778]
Training: |          | 879/? [01:22<00:00, 10.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00964]
Training: |          | 880/? [01:23<00:00, 10.59it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00964]
Training: |          | 880/? [01:23<00:00, 10.54it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873]
Training: |          | 881/? [01:24<00:00, 10.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873]
Training: |          | 881/? [01:24<00:00, 10.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00772]
Training: |          | 882/? [01:25<00:00, 10.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00772]
Training: |          | 882/? [01:25<00:00, 10.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836]
Training: |          | 883/? [01:26<00:00, 10.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836]
Training: |          | 883/? [01:26<00:00, 10.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854]
Training: |          | 884/? [01:27<00:00, 10.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854]
Training: |          | 884/? [01:27<00:00, 10.09it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989]
Training: |          | 885/? [01:28<00:00, 10.04it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989]
Training: |          | 885/? [01:28<00:00,  9.99it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0076] 
Training: |          | 886/? [01:29<00:00,  9.93it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0076]
Training: |          | 886/? [01:29<00:00,  9.88it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00916]
Training: |          | 887/? [01:30<00:00,  9.83it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00916]
Training: |          | 887/? [01:30<00:00,  9.78it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00787]
Training: |          | 888/? [01:31<00:00,  9.73it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00787]
Training: |          | 888/? [01:31<00:00,  9.68it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897]
Training: |          | 889/? [01:32<00:00,  9.63it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897]
Training: |          | 889/? [01:32<00:00,  9.59it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00897]
Training: |          | 890/? [01:33<00:00,  9.54it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00897]
Training: |          | 890/? [01:33<00:00,  9.49it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131] 
Training: |          | 891/? [01:34<00:00,  9.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131]
Training: |          | 891/? [01:34<00:00,  9.40it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00641]
Training: |          | 892/? [01:35<00:00,  9.35it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00641]
Training: |          | 892/? [01:35<00:00,  9.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094] 
Training: |          | 893/? [01:36<00:00,  9.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094]
Training: |          | 893/? [01:36<00:00,  9.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.008] 
Training: |          | 894/? [01:37<00:00,  9.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.008]
Training: |          | 894/? [01:37<00:00,  9.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012]
Training: |          | 895/? [01:38<00:00,  9.09it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012]
Training: |          | 895/? [01:38<00:00,  9.05it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0097]
Training: |          | 896/? [01:39<00:00,  9.00it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0097]
Training: |          | 896/? [01:39<00:00,  8.97it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861]
Training: |          | 897/? [01:40<00:00,  8.92it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861]
Training: |          | 897/? [01:40<00:00,  8.89it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00897]
Training: |          | 898/? [01:41<00:00,  8.84it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00897]
Training: |          | 898/? [01:41<00:00,  8.80it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0103] 
Training: |          | 899/? [01:42<00:00,  8.76it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0103]
Training: |          | 899/? [01:43<00:00,  8.73it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00793]
Training: |          | 900/? [01:43<00:00,  8.69it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00793]
Training: |          | 900/? [01:44<00:00,  8.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104] 

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Training: |          | 900/? [01:48<00:00,  8.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 901/? [01:49<00:00,  8.26it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 901/? [01:49<00:00,  8.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00836, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 902/? [01:50<00:00,  8.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00836, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 902/? [01:50<00:00,  8.17it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00668, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 903/? [01:51<00:00,  8.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00668, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 903/? [01:51<00:00,  8.10it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0076, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 904/? [01:52<00:00,  8.07it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0076, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 904/? [01:52<00:00,  8.04it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 905/? [01:53<00:00,  8.00it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 905/? [01:53<00:00,  7.97it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0113, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 906/? [01:54<00:00,  7.94it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0113, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 906/? [01:54<00:00,  7.91it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 907/? [01:55<00:00,  7.88it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 907/? [01:55<00:00,  7.85it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.012, val/loss=19.20, val/top_5_accuracy=0.00692]  
Training: |          | 908/? [01:56<00:00,  7.81it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.012, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 908/? [01:56<00:00,  7.79it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0118, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 909/? [01:57<00:00,  7.76it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0118, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 909/? [01:57<00:00,  7.73it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00729, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 910/? [01:58<00:00,  7.70it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00729, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 910/? [01:58<00:00,  7.67it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00772, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 911/? [01:59<00:00,  7.64it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00772, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 911/? [01:59<00:00,  7.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 912/? [02:00<00:00,  7.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 912/? [02:00<00:00,  7.56it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00793, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 913/? [02:01<00:00,  7.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00793, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 913/? [02:01<00:00,  7.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=19.20, val/top_5_accuracy=0.00692]  
Training: |          | 914/? [02:02<00:00,  7.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 914/? [02:02<00:00,  7.45it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0083, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 915/? [02:03<00:00,  7.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0083, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 915/? [02:03<00:00,  7.39it/s, v_num=2, train/loss=18.10, train/top_5_accuracy=0.00531, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 916/? [02:04<00:00,  7.36it/s, v_num=2, train/loss=18.10, train/top_5_accuracy=0.00531, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 916/? [02:04<00:00,  7.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00824, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 917/? [02:05<00:00,  7.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00824, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 917/? [02:05<00:00,  7.29it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00946, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 918/? [02:06<00:00,  7.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00946, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 918/? [02:06<00:00,  7.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 919/? [02:07<00:00,  7.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 919/? [02:07<00:00,  7.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0103, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 920/? [02:08<00:00,  7.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0103, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 920/? [02:08<00:00,  7.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 921/? [02:09<00:00,  7.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 921/? [02:09<00:00,  7.09it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0105, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 922/? [02:10<00:00,  7.06it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0105, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 922/? [02:11<00:00,  7.04it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00854, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 923/? [02:11<00:00,  7.01it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00854, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 923/? [02:12<00:00,  6.99it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 924/? [02:12<00:00,  6.97it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 924/? [02:13<00:00,  6.94it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 925/? [02:13<00:00,  6.92it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 925/? [02:14<00:00,  6.90it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 926/? [02:14<00:00,  6.87it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 926/? [02:15<00:00,  6.85it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692]  
Training: |          | 927/? [02:15<00:00,  6.83it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 927/? [02:16<00:00,  6.80it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0134, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 928/? [02:16<00:00,  6.78it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0134, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 928/? [02:17<00:00,  6.76it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 929/? [02:17<00:00,  6.74it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 929/? [02:18<00:00,  6.72it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692]  
Training: |          | 930/? [02:18<00:00,  6.70it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 930/? [02:19<00:00,  6.68it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 931/? [02:19<00:00,  6.65it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 931/? [02:20<00:00,  6.63it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 932/? [02:20<00:00,  6.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 932/? [02:21<00:00,  6.59it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 933/? [02:21<00:00,  6.57it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 933/? [02:22<00:00,  6.55it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00732, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 934/? [02:22<00:00,  6.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00732, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 934/? [02:23<00:00,  6.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 935/? [02:24<00:00,  6.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 935/? [02:24<00:00,  6.47it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 936/? [02:25<00:00,  6.45it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 936/? [02:25<00:00,  6.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 937/? [02:26<00:00,  6.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 937/? [02:26<00:00,  6.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00946, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 938/? [02:27<00:00,  6.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00946, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 938/? [02:27<00:00,  6.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00702, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 939/? [02:28<00:00,  6.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00702, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 939/? [02:28<00:00,  6.32it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00854, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 940/? [02:29<00:00,  6.30it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00854, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 940/? [02:29<00:00,  6.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00775, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 941/? [02:30<00:00,  6.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00775, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 941/? [02:30<00:00,  6.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00775, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 942/? [02:31<00:00,  6.23it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00775, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 942/? [02:31<00:00,  6.21it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00778, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 943/? [02:32<00:00,  6.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00778, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 943/? [02:32<00:00,  6.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0115, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 944/? [02:33<00:00,  6.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0115, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 944/? [02:33<00:00,  6.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00781, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 945/? [02:34<00:00,  6.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00781, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 945/? [02:34<00:00,  6.10it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00793, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 946/? [02:35<00:00,  6.09it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00793, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 946/? [02:35<00:00,  6.07it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 947/? [02:36<00:00,  6.05it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 947/? [02:36<00:00,  6.04it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 948/? [02:37<00:00,  6.02it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 948/? [02:37<00:00,  6.00it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 949/? [02:38<00:00,  5.99it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 949/? [02:38<00:00,  5.97it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00754, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 950/? [02:39<00:00,  5.95it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00754, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 950/? [02:40<00:00,  5.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 951/? [02:40<00:00,  5.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 951/? [02:41<00:00,  5.91it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 952/? [02:41<00:00,  5.89it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 952/? [02:42<00:00,  5.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00772, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 953/? [02:42<00:00,  5.86it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00772, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 953/? [02:43<00:00,  5.84it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00897, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 954/? [02:43<00:00,  5.83it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00897, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 954/? [02:44<00:00,  5.81it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0115, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 955/? [02:44<00:00,  5.80it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0115, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 955/? [02:45<00:00,  5.78it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 956/? [02:45<00:00,  5.77it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 956/? [02:46<00:00,  5.75it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00806, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 957/? [02:46<00:00,  5.74it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00806, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 957/? [02:47<00:00,  5.72it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00873, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 958/? [02:47<00:00,  5.71it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00873, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 958/? [02:48<00:00,  5.69it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 959/? [02:48<00:00,  5.68it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 959/? [02:49<00:00,  5.66it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0165, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 960/? [02:49<00:00,  5.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0165, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 960/? [02:50<00:00,  5.64it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 961/? [02:50<00:00,  5.62it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 961/? [02:51<00:00,  5.61it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00824, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 962/? [02:51<00:00,  5.59it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00824, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 962/? [02:52<00:00,  5.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00693, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 963/? [02:52<00:00,  5.57it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00693, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 963/? [02:53<00:00,  5.55it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00751, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 964/? [02:54<00:00,  5.54it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00751, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 964/? [02:54<00:00,  5.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00778, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 965/? [02:55<00:00,  5.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00778, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 965/? [02:55<00:00,  5.50it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00946, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 966/? [02:56<00:00,  5.49it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00946, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 966/? [02:56<00:00,  5.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 967/? [02:57<00:00,  5.46it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 967/? [02:57<00:00,  5.45it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0106, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 968/? [02:58<00:00,  5.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0106, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 968/? [02:58<00:00,  5.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00842, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 969/? [02:59<00:00,  5.41it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00842, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 969/? [02:59<00:00,  5.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 970/? [03:00<00:00,  5.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 970/? [03:00<00:00,  5.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 971/? [03:01<00:00,  5.36it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 971/? [03:01<00:00,  5.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 972/? [03:02<00:00,  5.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 972/? [03:02<00:00,  5.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00705, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 973/? [03:03<00:00,  5.31it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00705, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 973/? [03:03<00:00,  5.30it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00729, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 974/? [03:04<00:00,  5.28it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00729, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 974/? [03:04<00:00,  5.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00867, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 975/? [03:05<00:00,  5.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00867, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 975/? [03:05<00:00,  5.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.010, val/loss=19.20, val/top_5_accuracy=0.00692]  
Training: |          | 976/? [03:06<00:00,  5.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.010, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 976/? [03:06<00:00,  5.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 977/? [03:07<00:00,  5.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 977/? [03:07<00:00,  5.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 978/? [03:08<00:00,  5.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 978/? [03:08<00:00,  5.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00922, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 979/? [03:09<00:00,  5.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00922, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 979/? [03:09<00:00,  5.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 980/? [03:10<00:00,  5.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 980/? [03:10<00:00,  5.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 981/? [03:11<00:00,  5.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 981/? [03:11<00:00,  5.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00751, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 982/? [03:12<00:00,  5.10it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00751, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 982/? [03:12<00:00,  5.09it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00793, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 983/? [03:13<00:00,  5.08it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00793, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 983/? [03:13<00:00,  5.07it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00867, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 984/? [03:14<00:00,  5.06it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00867, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 984/? [03:14<00:00,  5.05it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 985/? [03:15<00:00,  5.04it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 985/? [03:16<00:00,  5.03it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0118, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 986/? [03:16<00:00,  5.01it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0118, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 986/? [03:17<00:00,  5.00it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0069, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 987/? [03:17<00:00,  4.99it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0069, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 987/? [03:18<00:00,  4.98it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0083, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 988/? [03:18<00:00,  4.97it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0083, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 988/? [03:19<00:00,  4.96it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00836, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 989/? [03:19<00:00,  4.95it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00836, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 989/? [03:20<00:00,  4.94it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00848, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 990/? [03:20<00:00,  4.93it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00848, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 990/? [03:21<00:00,  4.92it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0076, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 991/? [03:21<00:00,  4.91it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0076, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 991/? [03:22<00:00,  4.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0072, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 992/? [03:22<00:00,  4.89it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0072, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 992/? [03:23<00:00,  4.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 993/? [03:23<00:00,  4.87it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.008, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 993/? [03:24<00:00,  4.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00836, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 994/? [03:24<00:00,  4.85it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00836, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 994/? [03:25<00:00,  4.84it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00897, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 995/? [03:25<00:00,  4.83it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00897, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 995/? [03:26<00:00,  4.82it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00644, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 996/? [03:26<00:00,  4.81it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00644, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 996/? [03:27<00:00,  4.80it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 997/? [03:27<00:00,  4.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 997/? [03:28<00:00,  4.78it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 998/? [03:29<00:00,  4.77it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 998/? [03:29<00:00,  4.76it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00842, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 999/? [03:30<00:00,  4.76it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00842, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 999/? [03:30<00:00,  4.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=19.20, val/top_5_accuracy=0.00692] 
Training: |          | 1000/? [03:31<00:00,  4.74it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=19.20, val/top_5_accuracy=0.00692]
Training: |          | 1000/? [03:31<00:00,  4.73it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=19.20, val/top_5_accuracy=0.00692]

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Validation DataLoader 0: 100%|██████████| 20/20 [00:04<00:00,  4.10it/s]

                                                                        
Training: |          | 1000/? [03:36<00:00,  4.62it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1001/? [03:37<00:00,  4.61it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1001/? [03:37<00:00,  4.60it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00848, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1002/? [03:38<00:00,  4.60it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00848, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1002/? [03:38<00:00,  4.59it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00778, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1003/? [03:39<00:00,  4.58it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00778, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1003/? [03:39<00:00,  4.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1004/? [03:40<00:00,  4.56it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1004/? [03:40<00:00,  4.55it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1005/? [03:41<00:00,  4.54it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1005/? [03:41<00:00,  4.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1006/? [03:42<00:00,  4.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1006/? [03:42<00:00,  4.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1007/? [03:43<00:00,  4.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1007/? [03:43<00:00,  4.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1008/? [03:44<00:00,  4.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1008/? [03:44<00:00,  4.49it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00867, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1009/? [03:45<00:00,  4.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00867, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1009/? [03:45<00:00,  4.47it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.012, val/loss=18.60, val/top_5_accuracy=0.00718]  
Training: |          | 1010/? [03:46<00:00,  4.46it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.012, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1010/? [03:46<00:00,  4.45it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0119, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1011/? [03:47<00:00,  4.45it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0119, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1011/? [03:47<00:00,  4.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00763, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1012/? [03:48<00:00,  4.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00763, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1012/? [03:48<00:00,  4.42it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00812, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1013/? [03:49<00:00,  4.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00812, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1013/? [03:49<00:00,  4.41it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00653, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1014/? [03:50<00:00,  4.40it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00653, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1014/? [03:50<00:00,  4.39it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00922, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1015/? [03:51<00:00,  4.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00922, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1015/? [03:52<00:00,  4.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1016/? [03:52<00:00,  4.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1016/? [03:53<00:00,  4.36it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1017/? [03:53<00:00,  4.35it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1017/? [03:54<00:00,  4.35it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1018/? [03:54<00:00,  4.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1018/? [03:55<00:00,  4.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1019/? [03:55<00:00,  4.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1019/? [03:56<00:00,  4.32it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00812, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1020/? [03:56<00:00,  4.31it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00812, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1020/? [03:57<00:00,  4.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1021/? [03:57<00:00,  4.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1021/? [03:58<00:00,  4.29it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0083, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1022/? [03:58<00:00,  4.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0083, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1022/? [03:59<00:00,  4.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1023/? [03:59<00:00,  4.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1023/? [04:00<00:00,  4.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1024/? [04:00<00:00,  4.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1024/? [04:01<00:00,  4.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1025/? [04:01<00:00,  4.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1025/? [04:02<00:00,  4.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00824, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1026/? [04:02<00:00,  4.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00824, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1026/? [04:03<00:00,  4.22it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00693, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1027/? [04:03<00:00,  4.21it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00693, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1027/? [04:04<00:00,  4.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1028/? [04:04<00:00,  4.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1028/? [04:05<00:00,  4.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00763, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1029/? [04:06<00:00,  4.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00763, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1029/? [04:06<00:00,  4.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008, val/loss=18.60, val/top_5_accuracy=0.00718]  
Training: |          | 1030/? [04:07<00:00,  4.17it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.008, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1030/? [04:07<00:00,  4.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00787, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1031/? [04:08<00:00,  4.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00787, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1031/? [04:08<00:00,  4.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1032/? [04:09<00:00,  4.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1032/? [04:09<00:00,  4.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00989, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1033/? [04:10<00:00,  4.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00989, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1033/? [04:10<00:00,  4.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0083, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1034/? [04:11<00:00,  4.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0083, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1034/? [04:11<00:00,  4.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0116, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1035/? [04:12<00:00,  4.10it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0116, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1035/? [04:12<00:00,  4.10it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0083, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1036/? [04:13<00:00,  4.09it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0083, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1036/? [04:13<00:00,  4.09it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00897, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1037/? [04:14<00:00,  4.08it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00897, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1037/? [04:14<00:00,  4.07it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00903, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1038/? [04:15<00:00,  4.07it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00903, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1038/? [04:15<00:00,  4.06it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00946, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1039/? [04:16<00:00,  4.05it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00946, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1039/? [04:16<00:00,  4.05it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1040/? [04:17<00:00,  4.04it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1040/? [04:17<00:00,  4.03it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1041/? [04:18<00:00,  4.03it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1041/? [04:18<00:00,  4.02it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1042/? [04:19<00:00,  4.02it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1042/? [04:19<00:00,  4.01it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1043/? [04:20<00:00,  4.01it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1043/? [04:20<00:00,  4.00it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1044/? [04:21<00:00,  3.99it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1044/? [04:21<00:00,  3.99it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1045/? [04:22<00:00,  3.98it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1045/? [04:22<00:00,  3.98it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=18.60, val/top_5_accuracy=0.00718]  
Training: |          | 1046/? [04:23<00:00,  3.97it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1046/? [04:23<00:00,  3.96it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1047/? [04:24<00:00,  3.96it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1047/? [04:24<00:00,  3.95it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1048/? [04:25<00:00,  3.95it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1048/? [04:25<00:00,  3.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1049/? [04:26<00:00,  3.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1049/? [04:26<00:00,  3.93it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1050/? [04:27<00:00,  3.92it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1050/? [04:28<00:00,  3.92it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1051/? [04:28<00:00,  3.91it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1051/? [04:29<00:00,  3.91it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1052/? [04:29<00:00,  3.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1052/? [04:30<00:00,  3.90it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1053/? [04:30<00:00,  3.89it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1053/? [04:31<00:00,  3.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1054/? [04:31<00:00,  3.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1054/? [04:32<00:00,  3.87it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1055/? [04:32<00:00,  3.87it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1055/? [04:33<00:00,  3.86it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1056/? [04:33<00:00,  3.86it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1056/? [04:34<00:00,  3.85it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00891, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1057/? [04:34<00:00,  3.85it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00891, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1057/? [04:35<00:00,  3.84it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00723, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1058/? [04:35<00:00,  3.84it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00723, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1058/? [04:36<00:00,  3.83it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0114, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1059/? [04:36<00:00,  3.82it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0114, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1059/? [04:37<00:00,  3.82it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00754, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1060/? [04:37<00:00,  3.81it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00754, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1060/? [04:38<00:00,  3.81it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00714, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1061/? [04:39<00:00,  3.80it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00714, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1061/? [04:39<00:00,  3.80it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00775, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1062/? [04:40<00:00,  3.79it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00775, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1062/? [04:40<00:00,  3.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.60, val/top_5_accuracy=0.00718]  
Training: |          | 1063/? [04:41<00:00,  3.78it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1063/? [04:41<00:00,  3.77it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1064/? [04:42<00:00,  3.77it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1064/? [04:42<00:00,  3.76it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00885, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1065/? [04:43<00:00,  3.76it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00885, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1065/? [04:43<00:00,  3.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.60, val/top_5_accuracy=0.00718]  
Training: |          | 1066/? [04:44<00:00,  3.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1066/? [04:44<00:00,  3.74it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1067/? [04:45<00:00,  3.74it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1067/? [04:45<00:00,  3.73it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1068/? [04:46<00:00,  3.73it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1068/? [04:46<00:00,  3.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00754, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1069/? [04:47<00:00,  3.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00754, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1069/? [04:47<00:00,  3.71it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0103, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1070/? [04:48<00:00,  3.71it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0103, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1070/? [04:48<00:00,  3.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00854, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1071/? [04:49<00:00,  3.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00854, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1071/? [04:49<00:00,  3.69it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0127, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1072/? [04:50<00:00,  3.69it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0127, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1072/? [04:50<00:00,  3.69it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1073/? [04:51<00:00,  3.68it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1073/? [04:51<00:00,  3.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1074/? [04:52<00:00,  3.67it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1074/? [04:52<00:00,  3.67it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0113, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1075/? [04:53<00:00,  3.66it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0113, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1075/? [04:53<00:00,  3.66it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1076/? [04:54<00:00,  3.65it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1076/? [04:55<00:00,  3.65it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00946, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1077/? [04:55<00:00,  3.64it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00946, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1077/? [04:56<00:00,  3.64it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00818, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1078/? [04:56<00:00,  3.63it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00818, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1078/? [04:57<00:00,  3.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1079/? [04:57<00:00,  3.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1079/? [04:58<00:00,  3.62it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1080/? [04:58<00:00,  3.62it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1080/? [04:59<00:00,  3.61it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00922, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1081/? [04:59<00:00,  3.61it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00922, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1081/? [05:00<00:00,  3.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00848, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1082/? [05:00<00:00,  3.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00848, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1082/? [05:01<00:00,  3.59it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1083/? [05:01<00:00,  3.59it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1083/? [05:02<00:00,  3.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1084/? [05:02<00:00,  3.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1084/? [05:03<00:00,  3.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1085/? [05:03<00:00,  3.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1085/? [05:04<00:00,  3.57it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1086/? [05:04<00:00,  3.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1086/? [05:05<00:00,  3.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1087/? [05:05<00:00,  3.55it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00873, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1087/? [05:06<00:00,  3.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1088/? [05:06<00:00,  3.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1088/? [05:07<00:00,  3.54it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1089/? [05:07<00:00,  3.54it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1089/? [05:08<00:00,  3.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1090/? [05:08<00:00,  3.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1090/? [05:09<00:00,  3.52it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0124, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1091/? [05:09<00:00,  3.52it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0124, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1091/? [05:10<00:00,  3.51it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00699, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1092/? [05:11<00:00,  3.51it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00699, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1092/? [05:11<00:00,  3.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1093/? [05:12<00:00,  3.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1093/? [05:12<00:00,  3.50it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00989, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1094/? [05:13<00:00,  3.49it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00989, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1094/? [05:13<00:00,  3.49it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1095/? [05:14<00:00,  3.49it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1095/? [05:14<00:00,  3.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1096/? [05:15<00:00,  3.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1096/? [05:15<00:00,  3.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1097/? [05:16<00:00,  3.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1097/? [05:16<00:00,  3.47it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0116, val/loss=18.60, val/top_5_accuracy=0.00718] 
Training: |          | 1098/? [05:17<00:00,  3.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0116, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1098/? [05:17<00:00,  3.46it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0128, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1099/? [05:18<00:00,  3.45it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0128, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1099/? [05:18<00:00,  3.45it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1100/? [05:19<00:00,  3.45it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00836, val/loss=18.60, val/top_5_accuracy=0.00718]
Training: |          | 1100/? [05:19<00:00,  3.44it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.60, val/top_5_accuracy=0.00718]

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Validation DataLoader 0: 100%|██████████| 20/20 [00:04<00:00,  4.32it/s]

                                                                        
Training: |          | 1100/? [05:24<00:00,  3.39it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1101/? [05:24<00:00,  3.39it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1101/? [05:25<00:00,  3.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00824, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1102/? [05:26<00:00,  3.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00824, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1102/? [05:26<00:00,  3.38it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1103/? [05:27<00:00,  3.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1103/? [05:27<00:00,  3.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00748]  
Training: |          | 1104/? [05:28<00:00,  3.36it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1104/? [05:28<00:00,  3.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1105/? [05:29<00:00,  3.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1105/? [05:29<00:00,  3.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0094, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1106/? [05:30<00:00,  3.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0094, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1106/? [05:30<00:00,  3.34it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0123, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1107/? [05:31<00:00,  3.34it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0123, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1107/? [05:31<00:00,  3.34it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1108/? [05:32<00:00,  3.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1108/? [05:32<00:00,  3.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1109/? [05:33<00:00,  3.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1109/? [05:33<00:00,  3.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1110/? [05:34<00:00,  3.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1110/? [05:34<00:00,  3.32it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1111/? [05:35<00:00,  3.31it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1111/? [05:35<00:00,  3.31it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0123, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1112/? [05:36<00:00,  3.31it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0123, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1112/? [05:36<00:00,  3.30it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00787, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1113/? [05:37<00:00,  3.30it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00787, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1113/? [05:37<00:00,  3.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1114/? [05:38<00:00,  3.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1114/? [05:38<00:00,  3.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1115/? [05:39<00:00,  3.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1115/? [05:39<00:00,  3.28it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00891, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1116/? [05:40<00:00,  3.28it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00891, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1116/? [05:41<00:00,  3.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1117/? [05:41<00:00,  3.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1117/? [05:42<00:00,  3.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1118/? [05:42<00:00,  3.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1118/? [05:43<00:00,  3.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00812, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1119/? [05:43<00:00,  3.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00812, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1119/? [05:44<00:00,  3.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1120/? [05:44<00:00,  3.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1120/? [05:45<00:00,  3.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0065, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1121/? [05:45<00:00,  3.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0065, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1121/? [05:46<00:00,  3.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1122/? [05:46<00:00,  3.23it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1122/? [05:47<00:00,  3.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1123/? [05:47<00:00,  3.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1123/? [05:48<00:00,  3.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1124/? [05:48<00:00,  3.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1124/? [05:49<00:00,  3.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1125/? [05:49<00:00,  3.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1125/? [05:50<00:00,  3.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1126/? [05:51<00:00,  3.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1126/? [05:51<00:00,  3.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1127/? [05:52<00:00,  3.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1127/? [05:52<00:00,  3.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00867, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1128/? [05:53<00:00,  3.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00867, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1128/? [05:53<00:00,  3.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00977, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1129/? [05:54<00:00,  3.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00977, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1129/? [05:54<00:00,  3.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1130/? [05:55<00:00,  3.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1130/? [05:55<00:00,  3.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1131/? [05:56<00:00,  3.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1131/? [05:56<00:00,  3.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00742, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1132/? [05:57<00:00,  3.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00742, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1132/? [05:57<00:00,  3.16it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0113, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1133/? [05:58<00:00,  3.16it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0113, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1133/? [05:58<00:00,  3.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00818, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1134/? [05:59<00:00,  3.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00818, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1134/? [06:00<00:00,  3.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00818, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1135/? [06:00<00:00,  3.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00818, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1135/? [06:01<00:00,  3.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1136/? [06:01<00:00,  3.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1136/? [06:02<00:00,  3.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00723, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1137/? [06:02<00:00,  3.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00723, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1137/? [06:03<00:00,  3.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1138/? [06:03<00:00,  3.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1138/? [06:04<00:00,  3.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00922, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1139/? [06:04<00:00,  3.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00922, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1139/? [06:05<00:00,  3.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1140/? [06:05<00:00,  3.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1140/? [06:06<00:00,  3.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0118, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1141/? [06:06<00:00,  3.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0118, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1141/? [06:07<00:00,  3.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00748, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1142/? [06:07<00:00,  3.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00748, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1142/? [06:08<00:00,  3.10it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1143/? [06:08<00:00,  3.10it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1143/? [06:09<00:00,  3.10it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00748]  
Training: |          | 1144/? [06:09<00:00,  3.09it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1144/? [06:10<00:00,  3.09it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.008, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1145/? [06:10<00:00,  3.09it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.008, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1145/? [06:11<00:00,  3.08it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1146/? [06:11<00:00,  3.08it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1146/? [06:12<00:00,  3.08it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1147/? [06:13<00:00,  3.07it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1147/? [06:13<00:00,  3.07it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00778, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1148/? [06:14<00:00,  3.07it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00778, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1148/? [06:14<00:00,  3.06it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1149/? [06:15<00:00,  3.06it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1149/? [06:15<00:00,  3.06it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1150/? [06:16<00:00,  3.06it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1150/? [06:16<00:00,  3.05it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1151/? [06:17<00:00,  3.05it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1151/? [06:17<00:00,  3.05it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.40, val/top_5_accuracy=0.00748]  
Training: |          | 1152/? [06:18<00:00,  3.05it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1152/? [06:18<00:00,  3.04it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1153/? [06:19<00:00,  3.04it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1153/? [06:19<00:00,  3.04it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1154/? [06:20<00:00,  3.03it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1154/? [06:20<00:00,  3.03it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1155/? [06:21<00:00,  3.03it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1155/? [06:21<00:00,  3.03it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1156/? [06:22<00:00,  3.02it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1156/? [06:22<00:00,  3.02it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1157/? [06:23<00:00,  3.02it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1157/? [06:23<00:00,  3.01it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1158/? [06:24<00:00,  3.01it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1158/? [06:24<00:00,  3.01it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1159/? [06:25<00:00,  3.01it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1159/? [06:25<00:00,  3.00it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00748]  
Training: |          | 1160/? [06:26<00:00,  3.00it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1160/? [06:27<00:00,  3.00it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00726, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1161/? [06:27<00:00,  3.00it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00726, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1161/? [06:28<00:00,  2.99it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00909, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1162/? [06:28<00:00,  2.99it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00909, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1162/? [06:29<00:00,  2.99it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.40, val/top_5_accuracy=0.00748]  
Training: |          | 1163/? [06:29<00:00,  2.98it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1163/? [06:30<00:00,  2.98it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1164/? [06:30<00:00,  2.98it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1164/? [06:31<00:00,  2.98it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1165/? [06:31<00:00,  2.97it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1165/? [06:32<00:00,  2.97it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00922, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1166/? [06:32<00:00,  2.97it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00922, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1166/? [06:33<00:00,  2.96it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00806, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1167/? [06:33<00:00,  2.96it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00806, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1167/? [06:34<00:00,  2.96it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1168/? [06:34<00:00,  2.96it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1168/? [06:35<00:00,  2.95it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00818, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1169/? [06:35<00:00,  2.95it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00818, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1169/? [06:36<00:00,  2.95it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.010, val/loss=18.40, val/top_5_accuracy=0.00748]  
Training: |          | 1170/? [06:36<00:00,  2.95it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.010, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1170/? [06:37<00:00,  2.94it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1171/? [06:37<00:00,  2.94it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1171/? [06:38<00:00,  2.94it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1172/? [06:38<00:00,  2.94it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1172/? [06:39<00:00,  2.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1173/? [06:39<00:00,  2.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1173/? [06:40<00:00,  2.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1174/? [06:41<00:00,  2.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1174/? [06:41<00:00,  2.92it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00793, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1175/? [06:42<00:00,  2.92it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00793, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1175/? [06:42<00:00,  2.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1176/? [06:43<00:00,  2.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1176/? [06:43<00:00,  2.91it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1177/? [06:44<00:00,  2.91it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1177/? [06:44<00:00,  2.91it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00867, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1178/? [06:45<00:00,  2.91it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00867, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1178/? [06:45<00:00,  2.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1179/? [06:46<00:00,  2.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1179/? [06:46<00:00,  2.90it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1180/? [06:47<00:00,  2.90it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00842, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1180/? [06:47<00:00,  2.89it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1181/? [06:48<00:00,  2.89it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1181/? [06:48<00:00,  2.89it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1182/? [06:49<00:00,  2.89it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1182/? [06:49<00:00,  2.88it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00806, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1183/? [06:50<00:00,  2.88it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00806, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1183/? [06:50<00:00,  2.88it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1184/? [06:51<00:00,  2.88it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1184/? [06:51<00:00,  2.88it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1185/? [06:52<00:00,  2.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1185/? [06:52<00:00,  2.87it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0249, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1186/? [06:53<00:00,  2.87it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0249, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1186/? [06:53<00:00,  2.87it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1187/? [06:54<00:00,  2.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1187/? [06:54<00:00,  2.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00964, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1188/? [06:55<00:00,  2.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00964, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1188/? [06:55<00:00,  2.86it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1189/? [06:56<00:00,  2.85it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1189/? [06:56<00:00,  2.85it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1190/? [06:57<00:00,  2.85it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1190/? [06:57<00:00,  2.85it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1191/? [06:58<00:00,  2.85it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00879, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1191/? [06:59<00:00,  2.84it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1192/? [06:59<00:00,  2.84it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1192/? [07:00<00:00,  2.84it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1193/? [07:00<00:00,  2.84it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1193/? [07:01<00:00,  2.83it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1194/? [07:01<00:00,  2.83it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1194/? [07:02<00:00,  2.83it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1195/? [07:02<00:00,  2.83it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1195/? [07:03<00:00,  2.82it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00977, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1196/? [07:03<00:00,  2.82it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00977, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1196/? [07:04<00:00,  2.82it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1197/? [07:04<00:00,  2.82it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1197/? [07:05<00:00,  2.82it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.40, val/top_5_accuracy=0.00748] 
Training: |          | 1198/? [07:05<00:00,  2.81it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1198/? [07:06<00:00,  2.81it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1199/? [07:06<00:00,  2.81it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1199/? [07:07<00:00,  2.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1200/? [07:07<00:00,  2.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.40, val/top_5_accuracy=0.00748]
Training: |          | 1200/? [07:08<00:00,  2.80it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00748] 

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Validation DataLoader 0: 100%|██████████| 20/20 [00:06<00:00,  3.01it/s]

                                                                        
Training: |          | 1200/? [07:15<00:00,  2.76it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1201/? [07:15<00:00,  2.76it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1201/? [07:16<00:00,  2.75it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1202/? [07:16<00:00,  2.75it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1202/? [07:17<00:00,  2.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1203/? [07:17<00:00,  2.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1203/? [07:18<00:00,  2.75it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1204/? [07:18<00:00,  2.74it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1204/? [07:19<00:00,  2.74it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1205/? [07:19<00:00,  2.74it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1205/? [07:20<00:00,  2.74it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0072, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1206/? [07:20<00:00,  2.74it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0072, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1206/? [07:21<00:00,  2.73it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1207/? [07:21<00:00,  2.73it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1207/? [07:22<00:00,  2.73it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1208/? [07:22<00:00,  2.73it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1208/? [07:23<00:00,  2.72it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1209/? [07:23<00:00,  2.72it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1209/? [07:24<00:00,  2.72it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00729, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1210/? [07:24<00:00,  2.72it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00729, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1210/? [07:25<00:00,  2.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1211/? [07:25<00:00,  2.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1211/? [07:26<00:00,  2.71it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1212/? [07:27<00:00,  2.71it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1212/? [07:27<00:00,  2.71it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00793, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1213/? [07:28<00:00,  2.71it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00793, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1213/? [07:28<00:00,  2.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1214/? [07:29<00:00,  2.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1214/? [07:29<00:00,  2.70it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1215/? [07:30<00:00,  2.70it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1215/? [07:30<00:00,  2.70it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1216/? [07:31<00:00,  2.70it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1216/? [07:31<00:00,  2.69it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1217/? [07:32<00:00,  2.69it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1217/? [07:32<00:00,  2.69it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1218/? [07:33<00:00,  2.69it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1218/? [07:33<00:00,  2.69it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1219/? [07:34<00:00,  2.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1219/? [07:34<00:00,  2.68it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1220/? [07:35<00:00,  2.68it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1220/? [07:35<00:00,  2.68it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00766, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1221/? [07:36<00:00,  2.68it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00766, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1221/? [07:36<00:00,  2.67it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1222/? [07:37<00:00,  2.67it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1222/? [07:37<00:00,  2.67it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00711, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1223/? [07:38<00:00,  2.67it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00711, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1223/? [07:38<00:00,  2.67it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00952, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1224/? [07:39<00:00,  2.66it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00952, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1224/? [07:39<00:00,  2.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00806, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1225/? [07:40<00:00,  2.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00806, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1225/? [07:40<00:00,  2.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1226/? [07:41<00:00,  2.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1226/? [07:41<00:00,  2.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1227/? [07:42<00:00,  2.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1227/? [07:42<00:00,  2.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1228/? [07:43<00:00,  2.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1228/? [07:43<00:00,  2.65it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1229/? [07:44<00:00,  2.65it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1229/? [07:44<00:00,  2.64it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00748, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1230/? [07:45<00:00,  2.64it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00748, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1230/? [07:45<00:00,  2.64it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00824, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1231/? [07:46<00:00,  2.64it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00824, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1231/? [07:46<00:00,  2.64it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1232/? [07:47<00:00,  2.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1232/? [07:47<00:00,  2.63it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1233/? [07:48<00:00,  2.63it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00842, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1233/? [07:48<00:00,  2.63it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1234/? [07:49<00:00,  2.63it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1234/? [07:50<00:00,  2.63it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1235/? [07:50<00:00,  2.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1235/? [07:51<00:00,  2.62it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1236/? [07:51<00:00,  2.62it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1236/? [07:52<00:00,  2.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1237/? [07:52<00:00,  2.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1237/? [07:53<00:00,  2.61it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1238/? [07:53<00:00,  2.61it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1238/? [07:54<00:00,  2.61it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1239/? [07:54<00:00,  2.61it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1239/? [07:55<00:00,  2.61it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00793, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1240/? [07:55<00:00,  2.61it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00793, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1240/? [07:56<00:00,  2.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1241/? [07:56<00:00,  2.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1241/? [07:57<00:00,  2.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1242/? [07:57<00:00,  2.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1242/? [07:58<00:00,  2.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1243/? [07:58<00:00,  2.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1243/? [07:59<00:00,  2.59it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1244/? [07:59<00:00,  2.59it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1244/? [08:00<00:00,  2.59it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1245/? [08:00<00:00,  2.59it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1245/? [08:01<00:00,  2.59it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1246/? [08:01<00:00,  2.59it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1246/? [08:02<00:00,  2.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1247/? [08:02<00:00,  2.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1247/? [08:03<00:00,  2.58it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0162, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1248/? [08:03<00:00,  2.58it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0162, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1248/? [08:04<00:00,  2.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00909, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1249/? [08:04<00:00,  2.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00909, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1249/? [08:05<00:00,  2.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1250/? [08:05<00:00,  2.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1250/? [08:06<00:00,  2.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1251/? [08:06<00:00,  2.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1251/? [08:07<00:00,  2.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1252/? [08:08<00:00,  2.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1252/? [08:08<00:00,  2.56it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00839]  
Training: |          | 1253/? [08:09<00:00,  2.56it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1253/? [08:09<00:00,  2.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00812, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1254/? [08:10<00:00,  2.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00812, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1254/? [08:10<00:00,  2.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1255/? [08:11<00:00,  2.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1255/? [08:11<00:00,  2.55it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1256/? [08:12<00:00,  2.55it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1256/? [08:12<00:00,  2.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1257/? [08:13<00:00,  2.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1257/? [08:13<00:00,  2.55it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1258/? [08:14<00:00,  2.55it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1258/? [08:14<00:00,  2.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1259/? [08:15<00:00,  2.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1259/? [08:15<00:00,  2.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1260/? [08:16<00:00,  2.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1260/? [08:16<00:00,  2.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1261/? [08:17<00:00,  2.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1261/? [08:17<00:00,  2.53it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00723, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1262/? [08:18<00:00,  2.53it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00723, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1262/? [08:18<00:00,  2.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1263/? [08:19<00:00,  2.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1263/? [08:19<00:00,  2.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1264/? [08:20<00:00,  2.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1264/? [08:20<00:00,  2.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1265/? [08:21<00:00,  2.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1265/? [08:21<00:00,  2.52it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1266/? [08:22<00:00,  2.52it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1266/? [08:22<00:00,  2.52it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1267/? [08:23<00:00,  2.52it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1267/? [08:23<00:00,  2.51it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1268/? [08:24<00:00,  2.51it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1268/? [08:24<00:00,  2.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1269/? [08:25<00:00,  2.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1269/? [08:25<00:00,  2.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00812, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1270/? [08:26<00:00,  2.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00812, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1270/? [08:27<00:00,  2.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1271/? [08:27<00:00,  2.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1271/? [08:28<00:00,  2.50it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1272/? [08:28<00:00,  2.50it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1272/? [08:29<00:00,  2.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1273/? [08:29<00:00,  2.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1273/? [08:30<00:00,  2.50it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00818, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1274/? [08:30<00:00,  2.49it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00818, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1274/? [08:31<00:00,  2.49it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1275/? [08:31<00:00,  2.49it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1275/? [08:32<00:00,  2.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1276/? [08:32<00:00,  2.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1276/? [08:33<00:00,  2.49it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00848, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1277/? [08:33<00:00,  2.49it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00848, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1277/? [08:34<00:00,  2.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1278/? [08:34<00:00,  2.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1278/? [08:35<00:00,  2.48it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1279/? [08:35<00:00,  2.48it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1279/? [08:36<00:00,  2.48it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1280/? [08:36<00:00,  2.48it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1280/? [08:37<00:00,  2.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00897, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1281/? [08:37<00:00,  2.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00897, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1281/? [08:38<00:00,  2.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00861, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1282/? [08:38<00:00,  2.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00861, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1282/? [08:39<00:00,  2.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1283/? [08:39<00:00,  2.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1283/? [08:40<00:00,  2.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00839]  
Training: |          | 1284/? [08:40<00:00,  2.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1284/? [08:41<00:00,  2.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1285/? [08:41<00:00,  2.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1285/? [08:42<00:00,  2.46it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1286/? [08:43<00:00,  2.46it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00873, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1286/? [08:43<00:00,  2.46it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1287/? [08:44<00:00,  2.46it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1287/? [08:44<00:00,  2.45it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1288/? [08:45<00:00,  2.45it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1288/? [08:45<00:00,  2.45it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00995, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1289/? [08:46<00:00,  2.45it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00995, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1289/? [08:46<00:00,  2.45it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00848, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1290/? [08:47<00:00,  2.45it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00848, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1290/? [08:47<00:00,  2.45it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1291/? [08:48<00:00,  2.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1291/? [08:48<00:00,  2.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1292/? [08:49<00:00,  2.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1292/? [08:49<00:00,  2.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1293/? [08:50<00:00,  2.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1293/? [08:50<00:00,  2.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1294/? [08:51<00:00,  2.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1294/? [08:51<00:00,  2.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0072, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1295/? [08:52<00:00,  2.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0072, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1295/? [08:52<00:00,  2.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1296/? [08:53<00:00,  2.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1296/? [08:53<00:00,  2.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1297/? [08:54<00:00,  2.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1297/? [08:54<00:00,  2.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1298/? [08:55<00:00,  2.42it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1298/? [08:55<00:00,  2.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1299/? [08:56<00:00,  2.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1299/? [08:56<00:00,  2.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839] 
Training: |          | 1300/? [08:57<00:00,  2.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00839]
Training: |          | 1300/? [08:57<00:00,  2.42it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00839]

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Training: |          | 1300/? [09:04<00:00,  2.39it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1301/? [09:04<00:00,  2.39it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1301/? [09:05<00:00,  2.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1302/? [09:05<00:00,  2.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1302/? [09:06<00:00,  2.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1303/? [09:06<00:00,  2.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1303/? [09:07<00:00,  2.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1304/? [09:07<00:00,  2.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1304/? [09:08<00:00,  2.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1305/? [09:09<00:00,  2.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1305/? [09:09<00:00,  2.38it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1306/? [09:10<00:00,  2.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1306/? [09:10<00:00,  2.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1307/? [09:11<00:00,  2.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1307/? [09:11<00:00,  2.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1308/? [09:12<00:00,  2.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1308/? [09:12<00:00,  2.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1309/? [09:13<00:00,  2.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1309/? [09:13<00:00,  2.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1310/? [09:14<00:00,  2.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1310/? [09:14<00:00,  2.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00735, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1311/? [09:15<00:00,  2.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00735, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1311/? [09:15<00:00,  2.36it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1312/? [09:16<00:00,  2.36it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1312/? [09:16<00:00,  2.36it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1313/? [09:17<00:00,  2.36it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1313/? [09:17<00:00,  2.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1314/? [09:18<00:00,  2.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1314/? [09:18<00:00,  2.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1315/? [09:19<00:00,  2.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00873, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1315/? [09:19<00:00,  2.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1316/? [09:20<00:00,  2.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1316/? [09:20<00:00,  2.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1317/? [09:21<00:00,  2.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1317/? [09:21<00:00,  2.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1318/? [09:22<00:00,  2.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1318/? [09:22<00:00,  2.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1319/? [09:23<00:00,  2.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1319/? [09:23<00:00,  2.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1320/? [09:24<00:00,  2.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1320/? [09:24<00:00,  2.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1321/? [09:25<00:00,  2.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1321/? [09:25<00:00,  2.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1322/? [09:26<00:00,  2.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1322/? [09:26<00:00,  2.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1323/? [09:27<00:00,  2.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1323/? [09:27<00:00,  2.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1324/? [09:28<00:00,  2.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1324/? [09:28<00:00,  2.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1325/? [09:29<00:00,  2.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1325/? [09:29<00:00,  2.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1326/? [09:30<00:00,  2.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1326/? [09:30<00:00,  2.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1327/? [09:31<00:00,  2.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1327/? [09:31<00:00,  2.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1328/? [09:32<00:00,  2.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1328/? [09:33<00:00,  2.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1329/? [09:33<00:00,  2.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1329/? [09:34<00:00,  2.32it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0145, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1330/? [09:34<00:00,  2.31it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0145, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1330/? [09:35<00:00,  2.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1331/? [09:35<00:00,  2.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1331/? [09:36<00:00,  2.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1332/? [09:36<00:00,  2.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1332/? [09:37<00:00,  2.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1333/? [09:37<00:00,  2.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1333/? [09:38<00:00,  2.31it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1334/? [09:38<00:00,  2.30it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1334/? [09:39<00:00,  2.30it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1335/? [09:39<00:00,  2.30it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1335/? [09:40<00:00,  2.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0138, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1336/? [09:40<00:00,  2.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0138, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1336/? [09:41<00:00,  2.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1337/? [09:41<00:00,  2.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1337/? [09:42<00:00,  2.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1338/? [09:42<00:00,  2.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1338/? [09:43<00:00,  2.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1339/? [09:43<00:00,  2.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1339/? [09:44<00:00,  2.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00739, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1340/? [09:44<00:00,  2.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00739, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1340/? [09:45<00:00,  2.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1341/? [09:46<00:00,  2.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1341/? [09:46<00:00,  2.29it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1342/? [09:47<00:00,  2.29it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1342/? [09:47<00:00,  2.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1343/? [09:48<00:00,  2.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1343/? [09:48<00:00,  2.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1344/? [09:49<00:00,  2.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1344/? [09:49<00:00,  2.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1345/? [09:50<00:00,  2.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1345/? [09:50<00:00,  2.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1346/? [09:51<00:00,  2.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1346/? [09:51<00:00,  2.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1347/? [09:52<00:00,  2.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1347/? [09:52<00:00,  2.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1348/? [09:53<00:00,  2.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00787, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1348/? [09:53<00:00,  2.27it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00812, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1349/? [09:54<00:00,  2.27it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00812, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1349/? [09:54<00:00,  2.27it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00854, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1350/? [09:55<00:00,  2.27it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00854, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1350/? [09:55<00:00,  2.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1351/? [09:56<00:00,  2.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1351/? [09:56<00:00,  2.26it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1352/? [09:57<00:00,  2.26it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1352/? [09:57<00:00,  2.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1353/? [09:58<00:00,  2.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1353/? [09:58<00:00,  2.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1354/? [09:59<00:00,  2.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1354/? [09:59<00:00,  2.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1355/? [10:00<00:00,  2.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1355/? [10:00<00:00,  2.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1356/? [10:01<00:00,  2.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1356/? [10:01<00:00,  2.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1357/? [10:02<00:00,  2.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1357/? [10:02<00:00,  2.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.00824]  
Training: |          | 1358/? [10:03<00:00,  2.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1358/? [10:04<00:00,  2.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00867, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1359/? [10:04<00:00,  2.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00867, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1359/? [10:05<00:00,  2.25it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0141, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1360/? [10:05<00:00,  2.25it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0141, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1360/? [10:06<00:00,  2.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1361/? [10:06<00:00,  2.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1361/? [10:07<00:00,  2.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1362/? [10:07<00:00,  2.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1362/? [10:08<00:00,  2.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1363/? [10:08<00:00,  2.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1363/? [10:09<00:00,  2.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00775, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1364/? [10:09<00:00,  2.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00775, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1364/? [10:10<00:00,  2.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1365/? [10:10<00:00,  2.23it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1365/? [10:11<00:00,  2.23it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1366/? [10:11<00:00,  2.23it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1366/? [10:12<00:00,  2.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1367/? [10:12<00:00,  2.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00836, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1367/? [10:13<00:00,  2.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1368/? [10:13<00:00,  2.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1368/? [10:14<00:00,  2.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1369/? [10:14<00:00,  2.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1369/? [10:15<00:00,  2.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1370/? [10:15<00:00,  2.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1370/? [10:16<00:00,  2.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1371/? [10:17<00:00,  2.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1371/? [10:17<00:00,  2.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1372/? [10:18<00:00,  2.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1372/? [10:18<00:00,  2.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1373/? [10:19<00:00,  2.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1373/? [10:19<00:00,  2.22it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00598, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1374/? [10:20<00:00,  2.22it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00598, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1374/? [10:20<00:00,  2.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1375/? [10:21<00:00,  2.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1375/? [10:21<00:00,  2.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1376/? [10:22<00:00,  2.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1376/? [10:22<00:00,  2.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1377/? [10:23<00:00,  2.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1377/? [10:23<00:00,  2.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1378/? [10:24<00:00,  2.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1378/? [10:24<00:00,  2.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1379/? [10:25<00:00,  2.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1379/? [10:25<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1380/? [10:26<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1380/? [10:26<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0097, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1381/? [10:27<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0097, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1381/? [10:27<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1382/? [10:28<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1382/? [10:28<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1383/? [10:29<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1383/? [10:29<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00873, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1384/? [10:30<00:00,  2.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00873, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1384/? [10:30<00:00,  2.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1385/? [10:31<00:00,  2.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1385/? [10:31<00:00,  2.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1386/? [10:32<00:00,  2.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1386/? [10:32<00:00,  2.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1387/? [10:33<00:00,  2.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1387/? [10:33<00:00,  2.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1388/? [10:34<00:00,  2.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1388/? [10:34<00:00,  2.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1389/? [10:35<00:00,  2.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1389/? [10:35<00:00,  2.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1390/? [10:36<00:00,  2.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1390/? [10:36<00:00,  2.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1391/? [10:37<00:00,  2.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00867, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1391/? [10:37<00:00,  2.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1392/? [10:38<00:00,  2.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1392/? [10:39<00:00,  2.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00824] 
Training: |          | 1393/? [10:39<00:00,  2.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1393/? [10:40<00:00,  2.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1394/? [10:40<00:00,  2.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1394/? [10:41<00:00,  2.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1395/? [10:41<00:00,  2.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1395/? [10:42<00:00,  2.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1396/? [10:42<00:00,  2.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1396/? [10:43<00:00,  2.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1397/? [10:43<00:00,  2.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1397/? [10:44<00:00,  2.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1398/? [10:44<00:00,  2.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1398/? [10:45<00:00,  2.17it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1399/? [10:45<00:00,  2.17it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1399/? [10:46<00:00,  2.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1400/? [10:46<00:00,  2.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00824]
Training: |          | 1400/? [10:47<00:00,  2.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00824]

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Validation DataLoader 0:  95%|█████████▌| 19/20 [00:06<00:00,  3.11it/s]

Validation DataLoader 0: 100%|██████████| 20/20 [00:06<00:00,  3.02it/s]

                                                                        
Training: |          | 1400/? [10:53<00:00,  2.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1401/? [10:54<00:00,  2.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1401/? [10:54<00:00,  2.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1402/? [10:55<00:00,  2.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1402/? [10:55<00:00,  2.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1403/? [10:56<00:00,  2.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1403/? [10:56<00:00,  2.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1404/? [10:57<00:00,  2.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1404/? [10:57<00:00,  2.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1405/? [10:58<00:00,  2.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1405/? [10:58<00:00,  2.13it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1406/? [10:59<00:00,  2.13it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1406/? [10:59<00:00,  2.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1407/? [11:00<00:00,  2.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1407/? [11:00<00:00,  2.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1408/? [11:01<00:00,  2.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1408/? [11:01<00:00,  2.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1409/? [11:02<00:00,  2.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1409/? [11:02<00:00,  2.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1410/? [11:03<00:00,  2.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1410/? [11:04<00:00,  2.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1411/? [11:04<00:00,  2.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1411/? [11:05<00:00,  2.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00879, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1412/? [11:05<00:00,  2.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00879, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1412/? [11:06<00:00,  2.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1413/? [11:06<00:00,  2.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1413/? [11:07<00:00,  2.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1414/? [11:07<00:00,  2.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1414/? [11:08<00:00,  2.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1415/? [11:08<00:00,  2.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1415/? [11:09<00:00,  2.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1416/? [11:09<00:00,  2.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1416/? [11:10<00:00,  2.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0088]  
Training: |          | 1417/? [11:10<00:00,  2.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1417/? [11:11<00:00,  2.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1418/? [11:11<00:00,  2.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1418/? [11:12<00:00,  2.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1419/? [11:12<00:00,  2.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1419/? [11:13<00:00,  2.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1420/? [11:13<00:00,  2.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1420/? [11:14<00:00,  2.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.0088]  
Training: |          | 1421/? [11:14<00:00,  2.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1421/? [11:15<00:00,  2.10it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1422/? [11:15<00:00,  2.10it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1422/? [11:16<00:00,  2.10it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1423/? [11:16<00:00,  2.10it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1423/? [11:17<00:00,  2.10it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1424/? [11:17<00:00,  2.10it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1424/? [11:18<00:00,  2.10it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1425/? [11:18<00:00,  2.10it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1425/? [11:19<00:00,  2.10it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1426/? [11:19<00:00,  2.10it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1426/? [11:20<00:00,  2.10it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1427/? [11:20<00:00,  2.10it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1427/? [11:21<00:00,  2.09it/s, v_num=2, train/loss=17.90, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1428/? [11:21<00:00,  2.09it/s, v_num=2, train/loss=17.90, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1428/? [11:22<00:00,  2.09it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1429/? [11:23<00:00,  2.09it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1429/? [11:23<00:00,  2.09it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1430/? [11:24<00:00,  2.09it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1430/? [11:24<00:00,  2.09it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1431/? [11:25<00:00,  2.09it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1431/? [11:25<00:00,  2.09it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1432/? [11:26<00:00,  2.09it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1432/? [11:26<00:00,  2.09it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1433/? [11:27<00:00,  2.09it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1433/? [11:27<00:00,  2.08it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1434/? [11:28<00:00,  2.08it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1434/? [11:28<00:00,  2.08it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1435/? [11:29<00:00,  2.08it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1435/? [11:29<00:00,  2.08it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1436/? [11:30<00:00,  2.08it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1436/? [11:30<00:00,  2.08it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1437/? [11:31<00:00,  2.08it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1437/? [11:31<00:00,  2.08it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1438/? [11:32<00:00,  2.08it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1438/? [11:32<00:00,  2.08it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1439/? [11:33<00:00,  2.08it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1439/? [11:33<00:00,  2.07it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0097, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1440/? [11:34<00:00,  2.07it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0097, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1440/? [11:34<00:00,  2.07it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1441/? [11:35<00:00,  2.07it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1441/? [11:35<00:00,  2.07it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1442/? [11:36<00:00,  2.07it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1442/? [11:36<00:00,  2.07it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1443/? [11:37<00:00,  2.07it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1443/? [11:37<00:00,  2.07it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00885, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1444/? [11:38<00:00,  2.07it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00885, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1444/? [11:38<00:00,  2.07it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00751, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1445/? [11:39<00:00,  2.07it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00751, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1445/? [11:39<00:00,  2.06it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1446/? [11:40<00:00,  2.06it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1446/? [11:41<00:00,  2.06it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.0088]  
Training: |          | 1447/? [11:41<00:00,  2.06it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1447/? [11:42<00:00,  2.06it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1448/? [11:42<00:00,  2.06it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1448/? [11:43<00:00,  2.06it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1449/? [11:43<00:00,  2.06it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1449/? [11:44<00:00,  2.06it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1450/? [11:44<00:00,  2.06it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1450/? [11:45<00:00,  2.06it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1451/? [11:45<00:00,  2.06it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1451/? [11:46<00:00,  2.05it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1452/? [11:46<00:00,  2.05it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1452/? [11:47<00:00,  2.05it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1453/? [11:47<00:00,  2.05it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1453/? [11:48<00:00,  2.05it/s, v_num=2, train/loss=17.90, train/top_5_accuracy=0.0058, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1454/? [11:48<00:00,  2.05it/s, v_num=2, train/loss=17.90, train/top_5_accuracy=0.0058, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1454/? [11:49<00:00,  2.05it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1455/? [11:49<00:00,  2.05it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1455/? [11:50<00:00,  2.05it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.0088]  
Training: |          | 1456/? [11:50<00:00,  2.05it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1456/? [11:51<00:00,  2.05it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1457/? [11:51<00:00,  2.05it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00916, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1457/? [11:52<00:00,  2.05it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1458/? [11:52<00:00,  2.05it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1458/? [11:53<00:00,  2.04it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1459/? [11:53<00:00,  2.04it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1459/? [11:54<00:00,  2.04it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1460/? [11:54<00:00,  2.04it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1460/? [11:55<00:00,  2.04it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1461/? [11:55<00:00,  2.04it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1461/? [11:56<00:00,  2.04it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00812, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1462/? [11:56<00:00,  2.04it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00812, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1462/? [11:57<00:00,  2.04it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0097, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1463/? [11:58<00:00,  2.04it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0097, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1463/? [11:58<00:00,  2.04it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1464/? [11:59<00:00,  2.04it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1464/? [11:59<00:00,  2.03it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1465/? [12:00<00:00,  2.03it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1465/? [12:00<00:00,  2.03it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1466/? [12:01<00:00,  2.03it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1466/? [12:01<00:00,  2.03it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1467/? [12:02<00:00,  2.03it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1467/? [12:02<00:00,  2.03it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1468/? [12:03<00:00,  2.03it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1468/? [12:03<00:00,  2.03it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1469/? [12:04<00:00,  2.03it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1469/? [12:04<00:00,  2.03it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1470/? [12:05<00:00,  2.03it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1470/? [12:05<00:00,  2.03it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1471/? [12:06<00:00,  2.03it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1471/? [12:06<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1472/? [12:07<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1472/? [12:07<00:00,  2.02it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1473/? [12:08<00:00,  2.02it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1473/? [12:08<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1474/? [12:09<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1474/? [12:09<00:00,  2.02it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1475/? [12:10<00:00,  2.02it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1475/? [12:10<00:00,  2.02it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1476/? [12:11<00:00,  2.02it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1476/? [12:11<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1477/? [12:12<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1477/? [12:12<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1478/? [12:13<00:00,  2.02it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1478/? [12:13<00:00,  2.01it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1479/? [12:14<00:00,  2.01it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1479/? [12:14<00:00,  2.01it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1480/? [12:15<00:00,  2.01it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1480/? [12:15<00:00,  2.01it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1481/? [12:16<00:00,  2.01it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1481/? [12:16<00:00,  2.01it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00909, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1482/? [12:17<00:00,  2.01it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00909, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1482/? [12:17<00:00,  2.01it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1483/? [12:18<00:00,  2.01it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1483/? [12:18<00:00,  2.01it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00836, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1484/? [12:19<00:00,  2.01it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00836, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1484/? [12:19<00:00,  2.01it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0144, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1485/? [12:20<00:00,  2.01it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0144, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1485/? [12:20<00:00,  2.00it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1486/? [12:21<00:00,  2.00it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1486/? [12:21<00:00,  2.00it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1487/? [12:22<00:00,  2.00it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1487/? [12:22<00:00,  2.00it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1488/? [12:23<00:00,  2.00it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1488/? [12:24<00:00,  2.00it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1489/? [12:24<00:00,  2.00it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1489/? [12:25<00:00,  2.00it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1490/? [12:25<00:00,  2.00it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1490/? [12:26<00:00,  2.00it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1491/? [12:26<00:00,  2.00it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1491/? [12:27<00:00,  2.00it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1492/? [12:27<00:00,  2.00it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1492/? [12:28<00:00,  1.99it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1493/? [12:28<00:00,  1.99it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1493/? [12:29<00:00,  1.99it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1494/? [12:29<00:00,  1.99it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00848, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1494/? [12:30<00:00,  1.99it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00818, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1495/? [12:30<00:00,  1.99it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00818, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1495/? [12:31<00:00,  1.99it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1496/? [12:31<00:00,  1.99it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1496/? [12:32<00:00,  1.99it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1497/? [12:32<00:00,  1.99it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1497/? [12:33<00:00,  1.99it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1498/? [12:33<00:00,  1.99it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1498/? [12:34<00:00,  1.99it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0088] 
Training: |          | 1499/? [12:34<00:00,  1.99it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1499/? [12:35<00:00,  1.98it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1500/? [12:35<00:00,  1.98it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0088]
Training: |          | 1500/? [12:36<00:00,  1.98it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.30, val/top_5_accuracy=0.0088] 

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Validation DataLoader 0:  85%|████████▌ | 17/20 [00:04<00:00,  3.87it/s]

Validation DataLoader 0:  90%|█████████ | 18/20 [00:04<00:00,  3.66it/s]

Validation DataLoader 0:  95%|█████████▌| 19/20 [00:05<00:00,  3.50it/s]

Validation DataLoader 0: 100%|██████████| 20/20 [00:05<00:00,  3.66it/s]

                                                                        
Training: |          | 1500/? [12:41<00:00,  1.97it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1501/? [12:42<00:00,  1.97it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1501/? [12:42<00:00,  1.97it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1502/? [12:43<00:00,  1.97it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1502/? [12:43<00:00,  1.97it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1503/? [12:44<00:00,  1.97it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1503/? [12:44<00:00,  1.96it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1504/? [12:45<00:00,  1.96it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1504/? [12:45<00:00,  1.96it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1505/? [12:46<00:00,  1.96it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1505/? [12:47<00:00,  1.96it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1506/? [12:47<00:00,  1.96it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1506/? [12:48<00:00,  1.96it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1507/? [12:48<00:00,  1.96it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1507/? [12:49<00:00,  1.96it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1508/? [12:49<00:00,  1.96it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1508/? [12:50<00:00,  1.96it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1509/? [12:50<00:00,  1.96it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1509/? [12:51<00:00,  1.96it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1510/? [12:51<00:00,  1.96it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1510/? [12:52<00:00,  1.96it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1511/? [12:52<00:00,  1.96it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1511/? [12:53<00:00,  1.95it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1512/? [12:53<00:00,  1.95it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1512/? [12:54<00:00,  1.95it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1513/? [12:54<00:00,  1.95it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1513/? [12:55<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00793, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1514/? [12:55<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00793, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1514/? [12:56<00:00,  1.95it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1515/? [12:56<00:00,  1.95it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1515/? [12:57<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1516/? [12:57<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1516/? [12:58<00:00,  1.95it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1517/? [12:58<00:00,  1.95it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1517/? [12:59<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1518/? [12:59<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1518/? [13:00<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1519/? [13:00<00:00,  1.95it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1519/? [13:01<00:00,  1.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00818, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1520/? [13:02<00:00,  1.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00818, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1520/? [13:02<00:00,  1.94it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1521/? [13:03<00:00,  1.94it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1521/? [13:03<00:00,  1.94it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1522/? [13:04<00:00,  1.94it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1522/? [13:04<00:00,  1.94it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1523/? [13:05<00:00,  1.94it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1523/? [13:05<00:00,  1.94it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1524/? [13:06<00:00,  1.94it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1524/? [13:06<00:00,  1.94it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1525/? [13:07<00:00,  1.94it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1525/? [13:07<00:00,  1.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1526/? [13:08<00:00,  1.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1526/? [13:08<00:00,  1.94it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1527/? [13:09<00:00,  1.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1527/? [13:09<00:00,  1.93it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1528/? [13:10<00:00,  1.93it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1528/? [13:10<00:00,  1.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1529/? [13:11<00:00,  1.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1529/? [13:11<00:00,  1.93it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1530/? [13:12<00:00,  1.93it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1530/? [13:12<00:00,  1.93it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1531/? [13:13<00:00,  1.93it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1531/? [13:13<00:00,  1.93it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1532/? [13:14<00:00,  1.93it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1532/? [13:14<00:00,  1.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1533/? [13:15<00:00,  1.93it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1533/? [13:15<00:00,  1.93it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00873, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1534/? [13:16<00:00,  1.93it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00873, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1534/? [13:16<00:00,  1.93it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]  
Training: |          | 1535/? [13:17<00:00,  1.92it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1535/? [13:17<00:00,  1.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1536/? [13:18<00:00,  1.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1536/? [13:18<00:00,  1.92it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1537/? [13:19<00:00,  1.92it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1537/? [13:19<00:00,  1.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1538/? [13:20<00:00,  1.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1538/? [13:20<00:00,  1.92it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]  
Training: |          | 1539/? [13:21<00:00,  1.92it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1539/? [13:21<00:00,  1.92it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1540/? [13:22<00:00,  1.92it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1540/? [13:22<00:00,  1.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1541/? [13:23<00:00,  1.92it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1541/? [13:23<00:00,  1.92it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1542/? [13:24<00:00,  1.92it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1542/? [13:25<00:00,  1.92it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00836, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1543/? [13:25<00:00,  1.92it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00836, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1543/? [13:26<00:00,  1.91it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00786]  
Training: |          | 1544/? [13:26<00:00,  1.91it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1544/? [13:27<00:00,  1.91it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1545/? [13:27<00:00,  1.91it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1545/? [13:28<00:00,  1.91it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1546/? [13:28<00:00,  1.91it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1546/? [13:29<00:00,  1.91it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1547/? [13:29<00:00,  1.91it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1547/? [13:30<00:00,  1.91it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1548/? [13:30<00:00,  1.91it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1548/? [13:31<00:00,  1.91it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1549/? [13:31<00:00,  1.91it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1549/? [13:32<00:00,  1.91it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1550/? [13:32<00:00,  1.91it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1550/? [13:33<00:00,  1.91it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1551/? [13:33<00:00,  1.91it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1551/? [13:34<00:00,  1.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1552/? [13:34<00:00,  1.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1552/? [13:35<00:00,  1.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1553/? [13:35<00:00,  1.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1553/? [13:36<00:00,  1.90it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1554/? [13:36<00:00,  1.90it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1554/? [13:37<00:00,  1.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1555/? [13:37<00:00,  1.90it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1555/? [13:38<00:00,  1.90it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1556/? [13:38<00:00,  1.90it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1556/? [13:39<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1557/? [13:40<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1557/? [13:40<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1558/? [13:41<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1558/? [13:41<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1559/? [13:42<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1559/? [13:42<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1560/? [13:43<00:00,  1.90it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1560/? [13:43<00:00,  1.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]  
Training: |          | 1561/? [13:44<00:00,  1.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1561/? [13:44<00:00,  1.89it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1562/? [13:45<00:00,  1.89it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1562/? [13:45<00:00,  1.89it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1563/? [13:46<00:00,  1.89it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1563/? [13:46<00:00,  1.89it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00786]  
Training: |          | 1564/? [13:47<00:00,  1.89it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1564/? [13:47<00:00,  1.89it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1565/? [13:48<00:00,  1.89it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1565/? [13:48<00:00,  1.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1566/? [13:49<00:00,  1.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1566/? [13:49<00:00,  1.89it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1567/? [13:50<00:00,  1.89it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1567/? [13:50<00:00,  1.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0141, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1568/? [13:51<00:00,  1.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0141, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1568/? [13:51<00:00,  1.89it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00934, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1569/? [13:52<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00934, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1569/? [13:52<00:00,  1.88it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1570/? [13:53<00:00,  1.88it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1570/? [13:53<00:00,  1.88it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786]  
Training: |          | 1571/? [13:54<00:00,  1.88it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1571/? [13:54<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1572/? [13:55<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1572/? [13:55<00:00,  1.88it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]  
Training: |          | 1573/? [13:56<00:00,  1.88it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1573/? [13:56<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1574/? [13:57<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1574/? [13:57<00:00,  1.88it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1575/? [13:58<00:00,  1.88it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1575/? [13:59<00:00,  1.88it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1576/? [13:59<00:00,  1.88it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1576/? [14:00<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1577/? [14:00<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1577/? [14:01<00:00,  1.88it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1578/? [14:01<00:00,  1.87it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1578/? [14:02<00:00,  1.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1579/? [14:02<00:00,  1.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1579/? [14:03<00:00,  1.87it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1580/? [14:03<00:00,  1.87it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1580/? [14:04<00:00,  1.87it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00934, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1581/? [14:04<00:00,  1.87it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00934, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1581/? [14:05<00:00,  1.87it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1582/? [14:05<00:00,  1.87it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1582/? [14:06<00:00,  1.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1583/? [14:06<00:00,  1.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1583/? [14:07<00:00,  1.87it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1584/? [14:07<00:00,  1.87it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1584/? [14:08<00:00,  1.87it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1585/? [14:08<00:00,  1.87it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1585/? [14:09<00:00,  1.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1586/? [14:09<00:00,  1.87it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1586/? [14:10<00:00,  1.87it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1587/? [14:10<00:00,  1.87it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1587/? [14:11<00:00,  1.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1588/? [14:11<00:00,  1.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1588/? [14:12<00:00,  1.86it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1589/? [14:12<00:00,  1.86it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1589/? [14:13<00:00,  1.86it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.008, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1590/? [14:14<00:00,  1.86it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.008, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1590/? [14:14<00:00,  1.86it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00775, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1591/? [14:15<00:00,  1.86it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00775, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1591/? [14:15<00:00,  1.86it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1592/? [14:16<00:00,  1.86it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1592/? [14:16<00:00,  1.86it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1593/? [14:17<00:00,  1.86it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1593/? [14:17<00:00,  1.86it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1594/? [14:18<00:00,  1.86it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1594/? [14:18<00:00,  1.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1595/? [14:19<00:00,  1.86it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1595/? [14:19<00:00,  1.86it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00754, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1596/? [14:20<00:00,  1.86it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00754, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1596/? [14:20<00:00,  1.85it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1597/? [14:21<00:00,  1.85it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1597/? [14:21<00:00,  1.85it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1598/? [14:22<00:00,  1.85it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1598/? [14:22<00:00,  1.85it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00786] 
Training: |          | 1599/? [14:23<00:00,  1.85it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1599/? [14:23<00:00,  1.85it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0142, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1600/? [14:24<00:00,  1.85it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0142, val/loss=18.10, val/top_5_accuracy=0.00786]
Training: |          | 1600/? [14:24<00:00,  1.85it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00786]

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Training: |          | 1600/? [14:31<00:00,  1.84it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1601/? [14:32<00:00,  1.84it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1601/? [14:32<00:00,  1.84it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1602/? [14:33<00:00,  1.83it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1602/? [14:33<00:00,  1.83it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1603/? [14:34<00:00,  1.83it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1603/? [14:34<00:00,  1.83it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1604/? [14:35<00:00,  1.83it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1604/? [14:35<00:00,  1.83it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1605/? [14:36<00:00,  1.83it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1605/? [14:36<00:00,  1.83it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1606/? [14:37<00:00,  1.83it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1606/? [14:37<00:00,  1.83it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1607/? [14:38<00:00,  1.83it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1607/? [14:38<00:00,  1.83it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]  
Training: |          | 1608/? [14:39<00:00,  1.83it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1608/? [14:39<00:00,  1.83it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1609/? [14:40<00:00,  1.83it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1609/? [14:40<00:00,  1.83it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1610/? [14:41<00:00,  1.83it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1610/? [14:41<00:00,  1.83it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0139, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1611/? [14:42<00:00,  1.83it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0139, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1611/? [14:42<00:00,  1.83it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1612/? [14:43<00:00,  1.82it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1612/? [14:43<00:00,  1.82it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1613/? [14:44<00:00,  1.82it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1613/? [14:44<00:00,  1.82it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00812, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1614/? [14:45<00:00,  1.82it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00812, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1614/? [14:45<00:00,  1.82it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1615/? [14:46<00:00,  1.82it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1615/? [14:46<00:00,  1.82it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1616/? [14:47<00:00,  1.82it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1616/? [14:47<00:00,  1.82it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1617/? [14:48<00:00,  1.82it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1617/? [14:48<00:00,  1.82it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0166, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1618/? [14:49<00:00,  1.82it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0166, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1618/? [14:49<00:00,  1.82it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00812, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1619/? [14:50<00:00,  1.82it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00812, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1619/? [14:50<00:00,  1.82it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1620/? [14:51<00:00,  1.82it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1620/? [14:51<00:00,  1.82it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1621/? [14:52<00:00,  1.82it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1621/? [14:52<00:00,  1.82it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1622/? [14:53<00:00,  1.82it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1622/? [14:54<00:00,  1.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1623/? [14:54<00:00,  1.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1623/? [14:55<00:00,  1.81it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00983, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1624/? [14:55<00:00,  1.81it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00983, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1624/? [14:56<00:00,  1.81it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00867, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1625/? [14:56<00:00,  1.81it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00867, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1625/? [14:57<00:00,  1.81it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1626/? [14:57<00:00,  1.81it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1626/? [14:58<00:00,  1.81it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1627/? [14:58<00:00,  1.81it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1627/? [14:59<00:00,  1.81it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1628/? [14:59<00:00,  1.81it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1628/? [15:00<00:00,  1.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1629/? [15:00<00:00,  1.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1629/? [15:01<00:00,  1.81it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1630/? [15:01<00:00,  1.81it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1630/? [15:02<00:00,  1.81it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1631/? [15:02<00:00,  1.81it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1631/? [15:03<00:00,  1.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1632/? [15:03<00:00,  1.81it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1632/? [15:04<00:00,  1.80it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00952, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1633/? [15:04<00:00,  1.80it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00952, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1633/? [15:05<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1634/? [15:05<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1634/? [15:06<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1635/? [15:06<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1635/? [15:07<00:00,  1.80it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1636/? [15:07<00:00,  1.80it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00977, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1636/? [15:08<00:00,  1.80it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1637/? [15:08<00:00,  1.80it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1637/? [15:09<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00989, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1638/? [15:09<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00989, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1638/? [15:10<00:00,  1.80it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00983, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1639/? [15:10<00:00,  1.80it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00983, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1639/? [15:11<00:00,  1.80it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1640/? [15:11<00:00,  1.80it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1640/? [15:12<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1641/? [15:12<00:00,  1.80it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1641/? [15:13<00:00,  1.80it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0108, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1642/? [15:14<00:00,  1.80it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0108, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1642/? [15:14<00:00,  1.80it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0168, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1643/? [15:15<00:00,  1.80it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0168, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1643/? [15:15<00:00,  1.79it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1644/? [15:16<00:00,  1.79it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1644/? [15:16<00:00,  1.79it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1645/? [15:17<00:00,  1.79it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1645/? [15:17<00:00,  1.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00897, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1646/? [15:18<00:00,  1.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00897, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1646/? [15:18<00:00,  1.79it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1647/? [15:19<00:00,  1.79it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1647/? [15:19<00:00,  1.79it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1648/? [15:20<00:00,  1.79it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1648/? [15:20<00:00,  1.79it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1649/? [15:21<00:00,  1.79it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1649/? [15:21<00:00,  1.79it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1650/? [15:22<00:00,  1.79it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1650/? [15:22<00:00,  1.79it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1651/? [15:23<00:00,  1.79it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1651/? [15:23<00:00,  1.79it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1652/? [15:24<00:00,  1.79it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1652/? [15:24<00:00,  1.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1653/? [15:25<00:00,  1.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1653/? [15:25<00:00,  1.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1654/? [15:26<00:00,  1.79it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1654/? [15:26<00:00,  1.78it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1655/? [15:27<00:00,  1.78it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1655/? [15:27<00:00,  1.78it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1656/? [15:28<00:00,  1.78it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1656/? [15:28<00:00,  1.78it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1657/? [15:29<00:00,  1.78it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1657/? [15:29<00:00,  1.78it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00989, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1658/? [15:30<00:00,  1.78it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00989, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1658/? [15:30<00:00,  1.78it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.60, val/top_5_accuracy=0.0093]  
Training: |          | 1659/? [15:31<00:00,  1.78it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1659/? [15:31<00:00,  1.78it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1660/? [15:32<00:00,  1.78it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1660/? [15:32<00:00,  1.78it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1661/? [15:33<00:00,  1.78it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1661/? [15:34<00:00,  1.78it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1662/? [15:34<00:00,  1.78it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1662/? [15:35<00:00,  1.78it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1663/? [15:35<00:00,  1.78it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1663/? [15:36<00:00,  1.78it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1664/? [15:36<00:00,  1.78it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1664/? [15:37<00:00,  1.78it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1665/? [15:37<00:00,  1.78it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1665/? [15:38<00:00,  1.77it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1666/? [15:38<00:00,  1.77it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1666/? [15:39<00:00,  1.77it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1667/? [15:39<00:00,  1.77it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1667/? [15:40<00:00,  1.77it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1668/? [15:40<00:00,  1.77it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1668/? [15:41<00:00,  1.77it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1669/? [15:41<00:00,  1.77it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1669/? [15:42<00:00,  1.77it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1670/? [15:42<00:00,  1.77it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1670/? [15:43<00:00,  1.77it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1671/? [15:43<00:00,  1.77it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1671/? [15:44<00:00,  1.77it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1672/? [15:44<00:00,  1.77it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1672/? [15:45<00:00,  1.77it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1673/? [15:45<00:00,  1.77it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1673/? [15:46<00:00,  1.77it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0097, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1674/? [15:46<00:00,  1.77it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0097, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1674/? [15:47<00:00,  1.77it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1675/? [15:48<00:00,  1.77it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1675/? [15:48<00:00,  1.77it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1676/? [15:49<00:00,  1.77it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1676/? [15:49<00:00,  1.77it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00922, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1677/? [15:50<00:00,  1.77it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00922, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1677/? [15:50<00:00,  1.76it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1678/? [15:51<00:00,  1.76it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1678/? [15:51<00:00,  1.76it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1679/? [15:52<00:00,  1.76it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1679/? [15:52<00:00,  1.76it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1680/? [15:53<00:00,  1.76it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1680/? [15:53<00:00,  1.76it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1681/? [15:54<00:00,  1.76it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1681/? [15:54<00:00,  1.76it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1682/? [15:55<00:00,  1.76it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1682/? [15:55<00:00,  1.76it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1683/? [15:56<00:00,  1.76it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1683/? [15:56<00:00,  1.76it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1684/? [15:57<00:00,  1.76it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1684/? [15:57<00:00,  1.76it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0093]  
Training: |          | 1685/? [15:58<00:00,  1.76it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1685/? [15:58<00:00,  1.76it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1686/? [15:59<00:00,  1.76it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1686/? [15:59<00:00,  1.76it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00867, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1687/? [16:00<00:00,  1.76it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00867, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1687/? [16:00<00:00,  1.76it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1688/? [16:01<00:00,  1.76it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1688/? [16:01<00:00,  1.75it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1689/? [16:02<00:00,  1.75it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1689/? [16:02<00:00,  1.75it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1690/? [16:03<00:00,  1.75it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1690/? [16:03<00:00,  1.75it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1691/? [16:04<00:00,  1.75it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1691/? [16:04<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1692/? [16:05<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1692/? [16:05<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1693/? [16:06<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1693/? [16:06<00:00,  1.75it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1694/? [16:07<00:00,  1.75it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1694/? [16:08<00:00,  1.75it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1695/? [16:08<00:00,  1.75it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1695/? [16:09<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1696/? [16:09<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1696/? [16:10<00:00,  1.75it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093] 
Training: |          | 1697/? [16:10<00:00,  1.75it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1697/? [16:11<00:00,  1.75it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1698/? [16:11<00:00,  1.75it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1698/? [16:12<00:00,  1.75it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1699/? [16:12<00:00,  1.75it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1699/? [16:13<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1700/? [16:13<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0093]
Training: |          | 1700/? [16:14<00:00,  1.75it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0093]

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Training: |          | 1700/? [16:21<00:00,  1.73it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1701/? [16:22<00:00,  1.73it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1701/? [16:22<00:00,  1.73it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1702/? [16:23<00:00,  1.73it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1702/? [16:23<00:00,  1.73it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1703/? [16:24<00:00,  1.73it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1703/? [16:24<00:00,  1.73it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1704/? [16:25<00:00,  1.73it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1704/? [16:25<00:00,  1.73it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1705/? [16:26<00:00,  1.73it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1705/? [16:26<00:00,  1.73it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1706/? [16:27<00:00,  1.73it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1706/? [16:28<00:00,  1.73it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1707/? [16:28<00:00,  1.73it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1707/? [16:29<00:00,  1.73it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1708/? [16:29<00:00,  1.73it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1708/? [16:30<00:00,  1.73it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1709/? [16:30<00:00,  1.73it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1709/? [16:31<00:00,  1.72it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00674, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1710/? [16:31<00:00,  1.72it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00674, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1710/? [16:32<00:00,  1.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1711/? [16:32<00:00,  1.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1711/? [16:33<00:00,  1.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1712/? [16:33<00:00,  1.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1712/? [16:34<00:00,  1.72it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1713/? [16:34<00:00,  1.72it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1713/? [16:35<00:00,  1.72it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1714/? [16:35<00:00,  1.72it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1714/? [16:36<00:00,  1.72it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1715/? [16:36<00:00,  1.72it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1715/? [16:37<00:00,  1.72it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00742, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1716/? [16:37<00:00,  1.72it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00742, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1716/? [16:38<00:00,  1.72it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00903, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1717/? [16:38<00:00,  1.72it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00903, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1717/? [16:39<00:00,  1.72it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1718/? [16:39<00:00,  1.72it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1718/? [16:40<00:00,  1.72it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00885, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1719/? [16:40<00:00,  1.72it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00885, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1719/? [16:41<00:00,  1.72it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1720/? [16:42<00:00,  1.72it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1720/? [16:42<00:00,  1.72it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1721/? [16:43<00:00,  1.72it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1721/? [16:43<00:00,  1.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1722/? [16:44<00:00,  1.72it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1722/? [16:44<00:00,  1.71it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1723/? [16:45<00:00,  1.71it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1723/? [16:45<00:00,  1.71it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1724/? [16:46<00:00,  1.71it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1724/? [16:46<00:00,  1.71it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1725/? [16:47<00:00,  1.71it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1725/? [16:47<00:00,  1.71it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1726/? [16:48<00:00,  1.71it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1726/? [16:48<00:00,  1.71it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1727/? [16:49<00:00,  1.71it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1727/? [16:49<00:00,  1.71it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1728/? [16:50<00:00,  1.71it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1728/? [16:50<00:00,  1.71it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1729/? [16:51<00:00,  1.71it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1729/? [16:51<00:00,  1.71it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1730/? [16:52<00:00,  1.71it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1730/? [16:52<00:00,  1.71it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1731/? [16:53<00:00,  1.71it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1731/? [16:53<00:00,  1.71it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1732/? [16:54<00:00,  1.71it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1732/? [16:54<00:00,  1.71it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1733/? [16:55<00:00,  1.71it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1733/? [16:55<00:00,  1.71it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1734/? [16:56<00:00,  1.71it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1734/? [16:56<00:00,  1.71it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1735/? [16:57<00:00,  1.71it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1735/? [16:57<00:00,  1.70it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1736/? [16:58<00:00,  1.70it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1736/? [16:58<00:00,  1.70it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1737/? [16:59<00:00,  1.70it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1737/? [16:59<00:00,  1.70it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1738/? [17:00<00:00,  1.70it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1738/? [17:00<00:00,  1.70it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1739/? [17:01<00:00,  1.70it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1739/? [17:01<00:00,  1.70it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1740/? [17:02<00:00,  1.70it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1740/? [17:02<00:00,  1.70it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1741/? [17:03<00:00,  1.70it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1741/? [17:03<00:00,  1.70it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1742/? [17:04<00:00,  1.70it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1742/? [17:04<00:00,  1.70it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1743/? [17:05<00:00,  1.70it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1743/? [17:06<00:00,  1.70it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00949]  
Training: |          | 1744/? [17:06<00:00,  1.70it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1744/? [17:07<00:00,  1.70it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1745/? [17:07<00:00,  1.70it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1745/? [17:08<00:00,  1.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1746/? [17:08<00:00,  1.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1746/? [17:09<00:00,  1.70it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1747/? [17:09<00:00,  1.70it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1747/? [17:10<00:00,  1.70it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1748/? [17:10<00:00,  1.70it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1748/? [17:11<00:00,  1.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1749/? [17:11<00:00,  1.70it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1749/? [17:12<00:00,  1.69it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1750/? [17:12<00:00,  1.69it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1750/? [17:13<00:00,  1.69it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1751/? [17:13<00:00,  1.69it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1751/? [17:14<00:00,  1.69it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1752/? [17:14<00:00,  1.69it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1752/? [17:15<00:00,  1.69it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1753/? [17:15<00:00,  1.69it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1753/? [17:16<00:00,  1.69it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1754/? [17:16<00:00,  1.69it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1754/? [17:17<00:00,  1.69it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1755/? [17:17<00:00,  1.69it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1755/? [17:18<00:00,  1.69it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00909, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1756/? [17:18<00:00,  1.69it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00909, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1756/? [17:19<00:00,  1.69it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1757/? [17:19<00:00,  1.69it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1757/? [17:20<00:00,  1.69it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00891, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1758/? [17:21<00:00,  1.69it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00891, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1758/? [17:21<00:00,  1.69it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00842, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1759/? [17:22<00:00,  1.69it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00842, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1759/? [17:22<00:00,  1.69it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1760/? [17:23<00:00,  1.69it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1760/? [17:23<00:00,  1.69it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0105, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1761/? [17:24<00:00,  1.69it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0105, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1761/? [17:24<00:00,  1.69it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1762/? [17:25<00:00,  1.69it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1762/? [17:25<00:00,  1.69it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1763/? [17:26<00:00,  1.69it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1763/? [17:26<00:00,  1.68it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0105, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1764/? [17:27<00:00,  1.68it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0105, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1764/? [17:27<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1765/? [17:28<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1765/? [17:28<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1766/? [17:29<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00854, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1766/? [17:29<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1767/? [17:30<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1767/? [17:30<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1768/? [17:31<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1768/? [17:31<00:00,  1.68it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1769/? [17:32<00:00,  1.68it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1769/? [17:32<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1770/? [17:33<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1770/? [17:33<00:00,  1.68it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1771/? [17:34<00:00,  1.68it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1771/? [17:34<00:00,  1.68it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1772/? [17:35<00:00,  1.68it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1772/? [17:35<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1773/? [17:36<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1773/? [17:36<00:00,  1.68it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1774/? [17:37<00:00,  1.68it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1774/? [17:37<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1775/? [17:38<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1775/? [17:38<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1776/? [17:39<00:00,  1.68it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1776/? [17:39<00:00,  1.68it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1777/? [17:40<00:00,  1.68it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1777/? [17:40<00:00,  1.67it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1778/? [17:41<00:00,  1.68it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1778/? [17:41<00:00,  1.67it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1779/? [17:42<00:00,  1.67it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1779/? [17:42<00:00,  1.67it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1780/? [17:43<00:00,  1.67it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1780/? [17:43<00:00,  1.67it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00922, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1781/? [17:44<00:00,  1.67it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00922, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1781/? [17:44<00:00,  1.67it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1782/? [17:45<00:00,  1.67it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1782/? [17:45<00:00,  1.67it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1783/? [17:46<00:00,  1.67it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1783/? [17:47<00:00,  1.67it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1784/? [17:47<00:00,  1.67it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1784/? [17:48<00:00,  1.67it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1785/? [17:48<00:00,  1.67it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1785/? [17:49<00:00,  1.67it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1786/? [17:49<00:00,  1.67it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1786/? [17:50<00:00,  1.67it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00861, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1787/? [17:50<00:00,  1.67it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00861, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1787/? [17:51<00:00,  1.67it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1788/? [17:51<00:00,  1.67it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1788/? [17:52<00:00,  1.67it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1789/? [17:52<00:00,  1.67it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1789/? [17:53<00:00,  1.67it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0105, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1790/? [17:53<00:00,  1.67it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0105, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1790/? [17:54<00:00,  1.67it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1791/? [17:54<00:00,  1.67it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1791/? [17:55<00:00,  1.67it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1792/? [17:55<00:00,  1.67it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1792/? [17:56<00:00,  1.67it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1793/? [17:56<00:00,  1.67it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1793/? [17:57<00:00,  1.66it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1794/? [17:57<00:00,  1.66it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1794/? [17:58<00:00,  1.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1795/? [17:58<00:00,  1.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1795/? [17:59<00:00,  1.66it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1796/? [17:59<00:00,  1.66it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1796/? [18:00<00:00,  1.66it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1797/? [18:00<00:00,  1.66it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1797/? [18:01<00:00,  1.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1798/? [18:01<00:00,  1.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1798/? [18:02<00:00,  1.66it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1799/? [18:02<00:00,  1.66it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1799/? [18:03<00:00,  1.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00949] 
Training: |          | 1800/? [18:04<00:00,  1.66it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00949]
Training: |          | 1800/? [18:04<00:00,  1.66it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00949]

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Training: |          | 1800/? [18:08<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1801/? [18:08<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1801/? [18:09<00:00,  1.65it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1802/? [18:09<00:00,  1.65it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1802/? [18:10<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1803/? [18:10<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1803/? [18:11<00:00,  1.65it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1804/? [18:11<00:00,  1.65it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1804/? [18:12<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1805/? [18:12<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1805/? [18:13<00:00,  1.65it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1806/? [18:14<00:00,  1.65it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1806/? [18:14<00:00,  1.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1807/? [18:15<00:00,  1.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1807/? [18:15<00:00,  1.65it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1808/? [18:16<00:00,  1.65it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1808/? [18:16<00:00,  1.65it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1809/? [18:17<00:00,  1.65it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1809/? [18:17<00:00,  1.65it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1810/? [18:18<00:00,  1.65it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1810/? [18:18<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1811/? [18:19<00:00,  1.65it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1811/? [18:19<00:00,  1.65it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1812/? [18:20<00:00,  1.65it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1812/? [18:20<00:00,  1.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1813/? [18:21<00:00,  1.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1813/? [18:21<00:00,  1.65it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1814/? [18:22<00:00,  1.65it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1814/? [18:22<00:00,  1.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00861, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1815/? [18:23<00:00,  1.65it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00861, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1815/? [18:23<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1816/? [18:24<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1816/? [18:24<00:00,  1.64it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1817/? [18:25<00:00,  1.64it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1817/? [18:25<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1818/? [18:26<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1818/? [18:26<00:00,  1.64it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1819/? [18:27<00:00,  1.64it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1819/? [18:27<00:00,  1.64it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1820/? [18:28<00:00,  1.64it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1820/? [18:28<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1821/? [18:29<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1821/? [18:29<00:00,  1.64it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00842, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1822/? [18:30<00:00,  1.64it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00842, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1822/? [18:30<00:00,  1.64it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00964, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1823/? [18:31<00:00,  1.64it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00964, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1823/? [18:32<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1824/? [18:32<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1824/? [18:33<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1825/? [18:33<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1825/? [18:34<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1826/? [18:34<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1826/? [18:35<00:00,  1.64it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1827/? [18:35<00:00,  1.64it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1827/? [18:36<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1828/? [18:36<00:00,  1.64it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1828/? [18:37<00:00,  1.64it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1829/? [18:37<00:00,  1.64it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1829/? [18:38<00:00,  1.64it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1830/? [18:38<00:00,  1.64it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1830/? [18:39<00:00,  1.64it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1831/? [18:39<00:00,  1.64it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1831/? [18:40<00:00,  1.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1832/? [18:40<00:00,  1.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1832/? [18:41<00:00,  1.63it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1833/? [18:41<00:00,  1.63it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1833/? [18:42<00:00,  1.63it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1834/? [18:42<00:00,  1.63it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1834/? [18:43<00:00,  1.63it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1835/? [18:43<00:00,  1.63it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1835/? [18:44<00:00,  1.63it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1836/? [18:44<00:00,  1.63it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1836/? [18:45<00:00,  1.63it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1837/? [18:45<00:00,  1.63it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1837/? [18:46<00:00,  1.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1838/? [18:46<00:00,  1.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1838/? [18:47<00:00,  1.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1839/? [18:47<00:00,  1.63it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1839/? [18:48<00:00,  1.63it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1840/? [18:48<00:00,  1.63it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1840/? [18:49<00:00,  1.63it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1841/? [18:50<00:00,  1.63it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1841/? [18:50<00:00,  1.63it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1842/? [18:50<00:00,  1.63it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1842/? [18:51<00:00,  1.63it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1843/? [18:52<00:00,  1.63it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1843/? [18:52<00:00,  1.63it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1844/? [18:53<00:00,  1.63it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1844/? [18:53<00:00,  1.63it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0145, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1845/? [18:54<00:00,  1.63it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0145, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1845/? [18:54<00:00,  1.63it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1846/? [18:55<00:00,  1.63it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1846/? [18:55<00:00,  1.63it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1847/? [18:56<00:00,  1.63it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1847/? [18:56<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1848/? [18:57<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1848/? [18:57<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1849/? [18:58<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1849/? [18:58<00:00,  1.62it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0148, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1850/? [18:59<00:00,  1.62it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0148, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1850/? [18:59<00:00,  1.62it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1851/? [19:00<00:00,  1.62it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1851/? [19:00<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1852/? [19:01<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1852/? [19:01<00:00,  1.62it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0145, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1853/? [19:02<00:00,  1.62it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0145, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1853/? [19:02<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1854/? [19:03<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1854/? [19:03<00:00,  1.62it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1855/? [19:04<00:00,  1.62it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1855/? [19:04<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1856/? [19:05<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1856/? [19:05<00:00,  1.62it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1857/? [19:06<00:00,  1.62it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1857/? [19:06<00:00,  1.62it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1858/? [19:07<00:00,  1.62it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1858/? [19:07<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1859/? [19:08<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1859/? [19:08<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1860/? [19:09<00:00,  1.62it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00922, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1860/? [19:09<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1861/? [19:10<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1861/? [19:10<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1862/? [19:11<00:00,  1.62it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1862/? [19:12<00:00,  1.62it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1863/? [19:12<00:00,  1.62it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1863/? [19:13<00:00,  1.62it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1864/? [19:13<00:00,  1.62it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1864/? [19:14<00:00,  1.62it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1865/? [19:14<00:00,  1.62it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1865/? [19:15<00:00,  1.61it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1866/? [19:15<00:00,  1.61it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1866/? [19:16<00:00,  1.61it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1867/? [19:16<00:00,  1.61it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1867/? [19:17<00:00,  1.61it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1868/? [19:17<00:00,  1.61it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1868/? [19:18<00:00,  1.61it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1869/? [19:18<00:00,  1.61it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1869/? [19:19<00:00,  1.61it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1870/? [19:19<00:00,  1.61it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1870/? [19:20<00:00,  1.61it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1871/? [19:20<00:00,  1.61it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1871/? [19:21<00:00,  1.61it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1872/? [19:21<00:00,  1.61it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1872/? [19:22<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1873/? [19:22<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1873/? [19:23<00:00,  1.61it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1874/? [19:23<00:00,  1.61it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1874/? [19:24<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1875/? [19:25<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1875/? [19:25<00:00,  1.61it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1876/? [19:26<00:00,  1.61it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1876/? [19:26<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1877/? [19:27<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1877/? [19:27<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1878/? [19:28<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1878/? [19:28<00:00,  1.61it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1879/? [19:29<00:00,  1.61it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1879/? [19:29<00:00,  1.61it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1880/? [19:30<00:00,  1.61it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1880/? [19:30<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1881/? [19:31<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1881/? [19:31<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1882/? [19:32<00:00,  1.61it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1882/? [19:32<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1883/? [19:33<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1883/? [19:33<00:00,  1.60it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1884/? [19:34<00:00,  1.60it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1884/? [19:34<00:00,  1.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1885/? [19:35<00:00,  1.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1885/? [19:35<00:00,  1.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1886/? [19:36<00:00,  1.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1886/? [19:36<00:00,  1.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1887/? [19:37<00:00,  1.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00977, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1887/? [19:37<00:00,  1.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1888/? [19:38<00:00,  1.60it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1888/? [19:38<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1889/? [19:39<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1889/? [19:39<00:00,  1.60it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1890/? [19:40<00:00,  1.60it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1890/? [19:40<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1891/? [19:41<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1891/? [19:41<00:00,  1.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1892/? [19:42<00:00,  1.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.00946, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1892/? [19:42<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1893/? [19:43<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1893/? [19:43<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1894/? [19:44<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1894/? [19:45<00:00,  1.60it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1895/? [19:45<00:00,  1.60it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1895/? [19:46<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0153, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1896/? [19:46<00:00,  1.60it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0153, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1896/? [19:47<00:00,  1.60it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1897/? [19:47<00:00,  1.60it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1897/? [19:48<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1898/? [19:48<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1898/? [19:49<00:00,  1.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879] 
Training: |          | 1899/? [19:49<00:00,  1.60it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1899/? [19:50<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1900/? [19:50<00:00,  1.60it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00879]
Training: |          | 1900/? [19:51<00:00,  1.59it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0145, val/loss=18.30, val/top_5_accuracy=0.00879]

Validation: |          | 0/? [00:00<?, ?it/s]

Validation: |          | 0/? [00:00<?, ?it/s]

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Training: |          | 1900/? [19:58<00:00,  1.59it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0145, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1901/? [19:59<00:00,  1.59it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0145, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1901/? [19:59<00:00,  1.58it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1902/? [20:00<00:00,  1.58it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1902/? [20:00<00:00,  1.58it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1903/? [20:01<00:00,  1.58it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1903/? [20:01<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1904/? [20:02<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1904/? [20:02<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1905/? [20:03<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1905/? [20:03<00:00,  1.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1906/? [20:04<00:00,  1.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1906/? [20:04<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1907/? [20:05<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1907/? [20:05<00:00,  1.58it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1908/? [20:06<00:00,  1.58it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1908/? [20:06<00:00,  1.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1909/? [20:07<00:00,  1.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1909/? [20:07<00:00,  1.58it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1910/? [20:08<00:00,  1.58it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1910/? [20:08<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0097, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1911/? [20:09<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0097, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1911/? [20:09<00:00,  1.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1912/? [20:10<00:00,  1.58it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1912/? [20:10<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1913/? [20:11<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1913/? [20:11<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1914/? [20:12<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1914/? [20:12<00:00,  1.58it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1915/? [20:13<00:00,  1.58it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1915/? [20:13<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1916/? [20:14<00:00,  1.58it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1916/? [20:14<00:00,  1.58it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1917/? [20:15<00:00,  1.58it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1917/? [20:15<00:00,  1.58it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1918/? [20:16<00:00,  1.58it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1918/? [20:16<00:00,  1.58it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1919/? [20:17<00:00,  1.58it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1919/? [20:18<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1920/? [20:18<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1920/? [20:19<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1921/? [20:19<00:00,  1.58it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00952, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1921/? [20:20<00:00,  1.57it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1922/? [20:20<00:00,  1.57it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1922/? [20:21<00:00,  1.57it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0137, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1923/? [20:21<00:00,  1.57it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0137, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1923/? [20:22<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00964, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1924/? [20:22<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00964, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1924/? [20:23<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1925/? [20:23<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1925/? [20:24<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1926/? [20:24<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1926/? [20:25<00:00,  1.57it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1927/? [20:25<00:00,  1.57it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1927/? [20:26<00:00,  1.57it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1928/? [20:26<00:00,  1.57it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1928/? [20:27<00:00,  1.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1929/? [20:27<00:00,  1.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1929/? [20:28<00:00,  1.57it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.013, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1930/? [20:28<00:00,  1.57it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.013, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1930/? [20:29<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1931/? [20:29<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1931/? [20:30<00:00,  1.57it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00879, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1932/? [20:30<00:00,  1.57it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00879, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1932/? [20:31<00:00,  1.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1933/? [20:31<00:00,  1.57it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1933/? [20:32<00:00,  1.57it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1934/? [20:33<00:00,  1.57it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1934/? [20:33<00:00,  1.57it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1935/? [20:34<00:00,  1.57it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1935/? [20:34<00:00,  1.57it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1936/? [20:35<00:00,  1.57it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1936/? [20:35<00:00,  1.57it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1937/? [20:36<00:00,  1.57it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1937/? [20:36<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1938/? [20:37<00:00,  1.57it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1938/? [20:37<00:00,  1.57it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1939/? [20:38<00:00,  1.57it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1939/? [20:38<00:00,  1.57it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1940/? [20:39<00:00,  1.57it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1940/? [20:39<00:00,  1.57it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1941/? [20:40<00:00,  1.57it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1941/? [20:40<00:00,  1.56it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0124, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1942/? [20:41<00:00,  1.56it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0124, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1942/? [20:41<00:00,  1.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1943/? [20:42<00:00,  1.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1943/? [20:42<00:00,  1.56it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1944/? [20:43<00:00,  1.56it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1944/? [20:43<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1945/? [20:44<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1945/? [20:44<00:00,  1.56it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0146, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1946/? [20:45<00:00,  1.56it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0146, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1946/? [20:45<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1947/? [20:46<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1947/? [20:46<00:00,  1.56it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1948/? [20:47<00:00,  1.56it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1948/? [20:47<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1949/? [20:48<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1949/? [20:48<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1950/? [20:49<00:00,  1.56it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1950/? [20:49<00:00,  1.56it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1951/? [20:50<00:00,  1.56it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1951/? [20:50<00:00,  1.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1952/? [20:51<00:00,  1.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1952/? [20:51<00:00,  1.56it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1953/? [20:52<00:00,  1.56it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1953/? [20:52<00:00,  1.56it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1954/? [20:53<00:00,  1.56it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1954/? [20:53<00:00,  1.56it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0144, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1955/? [20:54<00:00,  1.56it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0144, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1955/? [20:54<00:00,  1.56it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1956/? [20:55<00:00,  1.56it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1956/? [20:56<00:00,  1.56it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1957/? [20:56<00:00,  1.56it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1957/? [20:57<00:00,  1.56it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1958/? [20:57<00:00,  1.56it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1958/? [20:58<00:00,  1.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00879, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1959/? [20:58<00:00,  1.56it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00879, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1959/? [20:59<00:00,  1.56it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1960/? [20:59<00:00,  1.56it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1960/? [21:00<00:00,  1.56it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1961/? [21:00<00:00,  1.56it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1961/? [21:01<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1962/? [21:01<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1962/? [21:02<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1963/? [21:02<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1963/? [21:03<00:00,  1.55it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1964/? [21:03<00:00,  1.55it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1964/? [21:04<00:00,  1.55it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1965/? [21:04<00:00,  1.55it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1965/? [21:05<00:00,  1.55it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1966/? [21:05<00:00,  1.55it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0083, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1966/? [21:06<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1967/? [21:06<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1967/? [21:07<00:00,  1.55it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1968/? [21:07<00:00,  1.55it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1968/? [21:08<00:00,  1.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1969/? [21:08<00:00,  1.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1969/? [21:09<00:00,  1.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1970/? [21:09<00:00,  1.55it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1970/? [21:10<00:00,  1.55it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0211, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1971/? [21:10<00:00,  1.55it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0211, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1971/? [21:11<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1972/? [21:11<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1972/? [21:12<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1973/? [21:12<00:00,  1.55it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1973/? [21:13<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1974/? [21:14<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1974/? [21:14<00:00,  1.55it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1975/? [21:15<00:00,  1.55it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1975/? [21:15<00:00,  1.55it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1976/? [21:16<00:00,  1.55it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1976/? [21:16<00:00,  1.55it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1977/? [21:17<00:00,  1.55it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1977/? [21:17<00:00,  1.55it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1978/? [21:18<00:00,  1.55it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1978/? [21:18<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1979/? [21:19<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1979/? [21:19<00:00,  1.55it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1980/? [21:20<00:00,  1.55it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1980/? [21:20<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1981/? [21:21<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1981/? [21:21<00:00,  1.55it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00977, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1982/? [21:22<00:00,  1.55it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00977, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1982/? [21:22<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1983/? [21:23<00:00,  1.55it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1983/? [21:23<00:00,  1.54it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0161, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1984/? [21:24<00:00,  1.54it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0161, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1984/? [21:24<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1985/? [21:25<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1985/? [21:25<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1986/? [21:26<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1986/? [21:26<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1987/? [21:27<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1987/? [21:27<00:00,  1.54it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00751, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1988/? [21:28<00:00,  1.54it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00751, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1988/? [21:28<00:00,  1.54it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978]  
Training: |          | 1989/? [21:29<00:00,  1.54it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1989/? [21:29<00:00,  1.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00854, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1990/? [21:30<00:00,  1.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00854, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1990/? [21:30<00:00,  1.54it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00952, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1991/? [21:31<00:00,  1.54it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00952, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1991/? [21:31<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1992/? [21:32<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1992/? [21:32<00:00,  1.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1993/? [21:33<00:00,  1.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1993/? [21:33<00:00,  1.54it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0157, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1994/? [21:34<00:00,  1.54it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0157, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1994/? [21:34<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1995/? [21:35<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1995/? [21:36<00:00,  1.54it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0152, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1996/? [21:36<00:00,  1.54it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0152, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1996/? [21:37<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1997/? [21:37<00:00,  1.54it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1997/? [21:38<00:00,  1.54it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00687, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1998/? [21:38<00:00,  1.54it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00687, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1998/? [21:39<00:00,  1.54it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978] 
Training: |          | 1999/? [21:39<00:00,  1.54it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 1999/? [21:40<00:00,  1.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 2000/? [21:40<00:00,  1.54it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.00978]
Training: |          | 2000/? [21:41<00:00,  1.54it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.00978]

Validation: |          | 0/? [00:00<?, ?it/s]

Validation: |          | 0/? [00:00<?, ?it/s]

Validation DataLoader 0:   0%|          | 0/20 [00:00<?, ?it/s]

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Training: |          | 2000/? [21:45<00:00,  1.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2001/? [21:45<00:00,  1.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2001/? [21:46<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2002/? [21:46<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2002/? [21:47<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2003/? [21:47<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2003/? [21:48<00:00,  1.53it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0129, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2004/? [21:48<00:00,  1.53it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0129, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2004/? [21:49<00:00,  1.53it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0167, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2005/? [21:49<00:00,  1.53it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0167, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2005/? [21:50<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2006/? [21:50<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2006/? [21:51<00:00,  1.53it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2007/? [21:52<00:00,  1.53it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2007/? [21:52<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2008/? [21:53<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2008/? [21:53<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2009/? [21:53<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2009/? [21:54<00:00,  1.53it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2010/? [21:55<00:00,  1.53it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2010/? [21:55<00:00,  1.53it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2011/? [21:56<00:00,  1.53it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2011/? [21:56<00:00,  1.53it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0108, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2012/? [21:57<00:00,  1.53it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0108, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2012/? [21:57<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2013/? [21:58<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2013/? [21:58<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2014/? [21:59<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2014/? [21:59<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2015/? [22:00<00:00,  1.53it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2015/? [22:00<00:00,  1.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2016/? [22:01<00:00,  1.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2016/? [22:01<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2017/? [22:02<00:00,  1.53it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2017/? [22:02<00:00,  1.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2018/? [22:03<00:00,  1.53it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2018/? [22:03<00:00,  1.52it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2019/? [22:04<00:00,  1.52it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2019/? [22:04<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2020/? [22:05<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2020/? [22:05<00:00,  1.52it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2021/? [22:06<00:00,  1.52it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2021/? [22:06<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00806, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2022/? [22:07<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00806, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2022/? [22:07<00:00,  1.52it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2023/? [22:08<00:00,  1.52it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2023/? [22:08<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2024/? [22:09<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2024/? [22:09<00:00,  1.52it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2025/? [22:10<00:00,  1.52it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2025/? [22:10<00:00,  1.52it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2026/? [22:11<00:00,  1.52it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2026/? [22:11<00:00,  1.52it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2027/? [22:12<00:00,  1.52it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2027/? [22:12<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2028/? [22:13<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2028/? [22:13<00:00,  1.52it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2029/? [22:14<00:00,  1.52it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2029/? [22:14<00:00,  1.52it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0126, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2030/? [22:15<00:00,  1.52it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0126, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2030/? [22:15<00:00,  1.52it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2031/? [22:16<00:00,  1.52it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2031/? [22:17<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2032/? [22:17<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2032/? [22:18<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2033/? [22:18<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2033/? [22:19<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2034/? [22:19<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2034/? [22:20<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0097, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2035/? [22:20<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0097, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2035/? [22:21<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2036/? [22:21<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00958, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2036/? [22:22<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2037/? [22:22<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2037/? [22:23<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2038/? [22:23<00:00,  1.52it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2038/? [22:24<00:00,  1.52it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2039/? [22:24<00:00,  1.52it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0094, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2039/? [22:25<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2040/? [22:25<00:00,  1.52it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2040/? [22:26<00:00,  1.52it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2041/? [22:26<00:00,  1.52it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2041/? [22:27<00:00,  1.51it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2042/? [22:27<00:00,  1.51it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2042/? [22:28<00:00,  1.51it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2043/? [22:28<00:00,  1.51it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2043/? [22:29<00:00,  1.51it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2044/? [22:29<00:00,  1.51it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2044/? [22:30<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2045/? [22:30<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2045/? [22:31<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2046/? [22:32<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00928, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2046/? [22:32<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2047/? [22:33<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2047/? [22:33<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2048/? [22:34<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2048/? [22:34<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2049/? [22:35<00:00,  1.51it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2049/? [22:35<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2050/? [22:36<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2050/? [22:36<00:00,  1.51it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2051/? [22:37<00:00,  1.51it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2051/? [22:37<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2052/? [22:38<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2052/? [22:38<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2053/? [22:39<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2053/? [22:39<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2054/? [22:40<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2054/? [22:40<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2055/? [22:41<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2055/? [22:41<00:00,  1.51it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2056/? [22:42<00:00,  1.51it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2056/? [22:42<00:00,  1.51it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2057/? [22:43<00:00,  1.51it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2057/? [22:43<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2058/? [22:44<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2058/? [22:44<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2059/? [22:45<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2059/? [22:45<00:00,  1.51it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2060/? [22:46<00:00,  1.51it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2060/? [22:46<00:00,  1.51it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.013, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2061/? [22:47<00:00,  1.51it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.013, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2061/? [22:47<00:00,  1.51it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2062/? [22:48<00:00,  1.51it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2062/? [22:49<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2063/? [22:49<00:00,  1.51it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2063/? [22:50<00:00,  1.51it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0182, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2064/? [22:50<00:00,  1.51it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0182, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2064/? [22:51<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2065/? [22:51<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2065/? [22:52<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2066/? [22:52<00:00,  1.51it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2066/? [22:53<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0142, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2067/? [22:53<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0142, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2067/? [22:54<00:00,  1.50it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2068/? [22:54<00:00,  1.50it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2068/? [22:55<00:00,  1.50it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2069/? [22:55<00:00,  1.50it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2069/? [22:56<00:00,  1.50it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2070/? [22:56<00:00,  1.50it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2070/? [22:57<00:00,  1.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2071/? [22:57<00:00,  1.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2071/? [22:58<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2072/? [22:58<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2072/? [22:59<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0116, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2073/? [22:59<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0116, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2073/? [23:00<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2074/? [23:00<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2074/? [23:01<00:00,  1.50it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2075/? [23:01<00:00,  1.50it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2075/? [23:02<00:00,  1.50it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00723, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2076/? [23:02<00:00,  1.50it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00723, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2076/? [23:03<00:00,  1.50it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2077/? [23:04<00:00,  1.50it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2077/? [23:04<00:00,  1.50it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0111, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2078/? [23:05<00:00,  1.50it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0111, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2078/? [23:05<00:00,  1.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2079/? [23:06<00:00,  1.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2079/? [23:06<00:00,  1.50it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.015, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2080/? [23:07<00:00,  1.50it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.015, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2080/? [23:07<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2081/? [23:08<00:00,  1.50it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2081/? [23:08<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2082/? [23:09<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2082/? [23:09<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2083/? [23:10<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2083/? [23:10<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2084/? [23:11<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2084/? [23:11<00:00,  1.50it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2085/? [23:12<00:00,  1.50it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2085/? [23:12<00:00,  1.50it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2086/? [23:13<00:00,  1.50it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2086/? [23:13<00:00,  1.50it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2087/? [23:14<00:00,  1.50it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2087/? [23:14<00:00,  1.50it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2088/? [23:15<00:00,  1.50it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2088/? [23:15<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2089/? [23:16<00:00,  1.50it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2089/? [23:16<00:00,  1.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805] 
Training: |          | 2090/? [23:17<00:00,  1.50it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2090/? [23:17<00:00,  1.50it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0154, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2091/? [23:18<00:00,  1.50it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0154, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2091/? [23:18<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2092/? [23:19<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2092/? [23:19<00:00,  1.49it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2093/? [23:20<00:00,  1.49it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2093/? [23:20<00:00,  1.49it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2094/? [23:21<00:00,  1.49it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2094/? [23:21<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2095/? [23:22<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2095/? [23:22<00:00,  1.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2096/? [23:23<00:00,  1.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2096/? [23:23<00:00,  1.49it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0106, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2097/? [23:24<00:00,  1.49it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0106, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2097/? [23:24<00:00,  1.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2098/? [23:25<00:00,  1.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2098/? [23:25<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2099/? [23:26<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2099/? [23:26<00:00,  1.49it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2100/? [23:27<00:00,  1.49it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=18.80, val/top_5_accuracy=0.00805]
Training: |          | 2100/? [23:28<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=18.80, val/top_5_accuracy=0.00805]

Validation: |          | 0/? [00:00<?, ?it/s]

Validation: |          | 0/? [00:00<?, ?it/s]

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Training: |          | 2100/? [23:32<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2101/? [23:33<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2101/? [23:33<00:00,  1.49it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.008, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2102/? [23:34<00:00,  1.49it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.008, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2102/? [23:34<00:00,  1.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2103/? [23:35<00:00,  1.49it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2103/? [23:36<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2104/? [23:36<00:00,  1.49it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2104/? [23:37<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2105/? [23:37<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2105/? [23:38<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2106/? [23:38<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2106/? [23:39<00:00,  1.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2107/? [23:39<00:00,  1.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2107/? [23:40<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2108/? [23:40<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2108/? [23:41<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2109/? [23:41<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2109/? [23:42<00:00,  1.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2110/? [23:42<00:00,  1.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2110/? [23:43<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2111/? [23:43<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2111/? [23:44<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2112/? [23:44<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2112/? [23:45<00:00,  1.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2113/? [23:45<00:00,  1.48it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2113/? [23:46<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2114/? [23:46<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2114/? [23:47<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2115/? [23:47<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2115/? [23:48<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2116/? [23:48<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2116/? [23:49<00:00,  1.48it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0172, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2117/? [23:49<00:00,  1.48it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0172, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2117/? [23:50<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2118/? [23:50<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2118/? [23:51<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2119/? [23:51<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2119/? [23:52<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2120/? [23:53<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2120/? [23:53<00:00,  1.48it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2121/? [23:54<00:00,  1.48it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2121/? [23:54<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2122/? [23:55<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2122/? [23:55<00:00,  1.48it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2123/? [23:56<00:00,  1.48it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2123/? [23:56<00:00,  1.48it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00891, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2124/? [23:57<00:00,  1.48it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.00891, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2124/? [23:57<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2125/? [23:58<00:00,  1.48it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2125/? [23:58<00:00,  1.48it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2126/? [23:59<00:00,  1.48it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2126/? [23:59<00:00,  1.48it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2127/? [24:00<00:00,  1.48it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2127/? [24:00<00:00,  1.48it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2128/? [24:01<00:00,  1.48it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2128/? [24:01<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2129/? [24:02<00:00,  1.48it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2129/? [24:02<00:00,  1.48it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2130/? [24:03<00:00,  1.48it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2130/? [24:03<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2131/? [24:04<00:00,  1.48it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2131/? [24:04<00:00,  1.48it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00879, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2132/? [24:05<00:00,  1.48it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00879, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2132/? [24:05<00:00,  1.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00932]  
Training: |          | 2133/? [24:06<00:00,  1.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2133/? [24:06<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2134/? [24:07<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2134/? [24:07<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2135/? [24:08<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2135/? [24:08<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2136/? [24:09<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2136/? [24:09<00:00,  1.47it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2137/? [24:10<00:00,  1.47it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2137/? [24:10<00:00,  1.47it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2138/? [24:11<00:00,  1.47it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2138/? [24:11<00:00,  1.47it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2139/? [24:12<00:00,  1.47it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2139/? [24:12<00:00,  1.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2140/? [24:13<00:00,  1.47it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2140/? [24:13<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2141/? [24:14<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2141/? [24:15<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2142/? [24:15<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2142/? [24:16<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2143/? [24:16<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2143/? [24:17<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2144/? [24:17<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2144/? [24:18<00:00,  1.47it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0147, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2145/? [24:18<00:00,  1.47it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0147, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2145/? [24:19<00:00,  1.47it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2146/? [24:19<00:00,  1.47it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2146/? [24:20<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2147/? [24:20<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2147/? [24:21<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2148/? [24:21<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2148/? [24:22<00:00,  1.47it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2149/? [24:22<00:00,  1.47it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2149/? [24:23<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2150/? [24:23<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2150/? [24:24<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2151/? [24:24<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2151/? [24:25<00:00,  1.47it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2152/? [24:25<00:00,  1.47it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2152/? [24:26<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2153/? [24:26<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2153/? [24:27<00:00,  1.47it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2154/? [24:27<00:00,  1.47it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2154/? [24:28<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2155/? [24:29<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2155/? [24:29<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2156/? [24:30<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2156/? [24:30<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2157/? [24:31<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2157/? [24:31<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2158/? [24:32<00:00,  1.47it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2158/? [24:32<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2159/? [24:33<00:00,  1.47it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2159/? [24:33<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2160/? [24:34<00:00,  1.47it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2160/? [24:34<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2161/? [24:35<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2161/? [24:35<00:00,  1.46it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2162/? [24:36<00:00,  1.46it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2162/? [24:36<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2163/? [24:37<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2163/? [24:37<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2164/? [24:38<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2164/? [24:38<00:00,  1.46it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0153, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2165/? [24:39<00:00,  1.46it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0153, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2165/? [24:39<00:00,  1.46it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2166/? [24:40<00:00,  1.46it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2166/? [24:40<00:00,  1.46it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2167/? [24:41<00:00,  1.46it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2167/? [24:41<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2168/? [24:42<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2168/? [24:42<00:00,  1.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2169/? [24:43<00:00,  1.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2169/? [24:43<00:00,  1.46it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0176, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2170/? [24:44<00:00,  1.46it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0176, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2170/? [24:44<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2171/? [24:45<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2171/? [24:45<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2172/? [24:46<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2172/? [24:46<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2173/? [24:47<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2173/? [24:47<00:00,  1.46it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2174/? [24:48<00:00,  1.46it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2174/? [24:48<00:00,  1.46it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00958, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2175/? [24:49<00:00,  1.46it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00958, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2175/? [24:50<00:00,  1.46it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2176/? [24:50<00:00,  1.46it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2176/? [24:51<00:00,  1.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2177/? [24:51<00:00,  1.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2177/? [24:52<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2178/? [24:52<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2178/? [24:53<00:00,  1.46it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2179/? [24:53<00:00,  1.46it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2179/? [24:54<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2180/? [24:54<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2180/? [24:55<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2181/? [24:55<00:00,  1.46it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2181/? [24:56<00:00,  1.46it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00854, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2182/? [24:56<00:00,  1.46it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00854, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2182/? [24:57<00:00,  1.46it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0083, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2183/? [24:57<00:00,  1.46it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0083, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2183/? [24:58<00:00,  1.46it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2184/? [24:58<00:00,  1.46it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2184/? [24:59<00:00,  1.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2185/? [24:59<00:00,  1.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2185/? [25:00<00:00,  1.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2186/? [25:00<00:00,  1.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2186/? [25:01<00:00,  1.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2187/? [25:01<00:00,  1.46it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2187/? [25:02<00:00,  1.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2188/? [25:03<00:00,  1.46it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2188/? [25:03<00:00,  1.46it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00964, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2189/? [25:04<00:00,  1.46it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00964, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2189/? [25:04<00:00,  1.45it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2190/? [25:05<00:00,  1.46it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2190/? [25:05<00:00,  1.45it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2191/? [25:06<00:00,  1.45it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2191/? [25:06<00:00,  1.45it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2192/? [25:07<00:00,  1.45it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2192/? [25:07<00:00,  1.45it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2193/? [25:08<00:00,  1.45it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2193/? [25:08<00:00,  1.45it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0217, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2194/? [25:09<00:00,  1.45it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0217, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2194/? [25:09<00:00,  1.45it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2195/? [25:10<00:00,  1.45it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2195/? [25:10<00:00,  1.45it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2196/? [25:11<00:00,  1.45it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2196/? [25:11<00:00,  1.45it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2197/? [25:12<00:00,  1.45it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2197/? [25:12<00:00,  1.45it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2198/? [25:13<00:00,  1.45it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2198/? [25:13<00:00,  1.45it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00867, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2199/? [25:14<00:00,  1.45it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00867, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2199/? [25:14<00:00,  1.45it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00932] 
Training: |          | 2200/? [25:15<00:00,  1.45it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00932]
Training: |          | 2200/? [25:15<00:00,  1.45it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00932]

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Training: |          | 2200/? [25:22<00:00,  1.45it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2201/? [25:22<00:00,  1.45it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2201/? [25:23<00:00,  1.45it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2202/? [25:23<00:00,  1.45it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2202/? [25:24<00:00,  1.44it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2203/? [25:24<00:00,  1.44it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2203/? [25:25<00:00,  1.44it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2204/? [25:25<00:00,  1.44it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2204/? [25:26<00:00,  1.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2205/? [25:26<00:00,  1.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2205/? [25:27<00:00,  1.44it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2206/? [25:27<00:00,  1.44it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2206/? [25:28<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2207/? [25:28<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2207/? [25:29<00:00,  1.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2208/? [25:29<00:00,  1.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2208/? [25:30<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2209/? [25:30<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2209/? [25:31<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2210/? [25:31<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2210/? [25:32<00:00,  1.44it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2211/? [25:32<00:00,  1.44it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2211/? [25:33<00:00,  1.44it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2212/? [25:33<00:00,  1.44it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2212/? [25:34<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2213/? [25:34<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2213/? [25:35<00:00,  1.44it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0129, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2214/? [25:35<00:00,  1.44it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0129, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2214/? [25:36<00:00,  1.44it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2215/? [25:37<00:00,  1.44it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2215/? [25:37<00:00,  1.44it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2216/? [25:38<00:00,  1.44it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2216/? [25:38<00:00,  1.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2217/? [25:39<00:00,  1.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2217/? [25:39<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2218/? [25:40<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2218/? [25:40<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2219/? [25:41<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2219/? [25:41<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2220/? [25:42<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2220/? [25:42<00:00,  1.44it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2221/? [25:43<00:00,  1.44it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2221/? [25:43<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2222/? [25:44<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2222/? [25:44<00:00,  1.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2223/? [25:45<00:00,  1.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2223/? [25:45<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2224/? [25:46<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2224/? [25:46<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2225/? [25:47<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2225/? [25:47<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2226/? [25:48<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2226/? [25:48<00:00,  1.44it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2227/? [25:49<00:00,  1.44it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2227/? [25:49<00:00,  1.44it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2228/? [25:50<00:00,  1.44it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2228/? [25:50<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2229/? [25:51<00:00,  1.44it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2229/? [25:51<00:00,  1.44it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0151, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2230/? [25:52<00:00,  1.44it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0151, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2230/? [25:52<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2231/? [25:53<00:00,  1.44it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2231/? [25:53<00:00,  1.44it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2232/? [25:54<00:00,  1.44it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2232/? [25:54<00:00,  1.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2233/? [25:55<00:00,  1.44it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2233/? [25:55<00:00,  1.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2234/? [25:56<00:00,  1.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2234/? [25:56<00:00,  1.43it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2235/? [25:57<00:00,  1.44it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2235/? [25:57<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00977, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2236/? [25:58<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00977, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2236/? [25:58<00:00,  1.43it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2237/? [25:59<00:00,  1.43it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2237/? [25:59<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2238/? [26:00<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2238/? [26:01<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2239/? [26:01<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2239/? [26:02<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2240/? [26:02<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2240/? [26:03<00:00,  1.43it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0193, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2241/? [26:03<00:00,  1.43it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0193, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2241/? [26:04<00:00,  1.43it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2242/? [26:04<00:00,  1.43it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2242/? [26:05<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2243/? [26:05<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2243/? [26:06<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2244/? [26:06<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2244/? [26:07<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2245/? [26:07<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2245/? [26:08<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2246/? [26:08<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2246/? [26:09<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2247/? [26:09<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2247/? [26:10<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2248/? [26:10<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2248/? [26:11<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2249/? [26:11<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2249/? [26:12<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2250/? [26:12<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2250/? [26:13<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2251/? [26:13<00:00,  1.43it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2251/? [26:14<00:00,  1.43it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0119, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2252/? [26:14<00:00,  1.43it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0119, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2252/? [26:15<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2253/? [26:16<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2253/? [26:16<00:00,  1.43it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2254/? [26:17<00:00,  1.43it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2254/? [26:17<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2255/? [26:18<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2255/? [26:18<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2256/? [26:19<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2256/? [26:19<00:00,  1.43it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2257/? [26:20<00:00,  1.43it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2257/? [26:20<00:00,  1.43it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2258/? [26:21<00:00,  1.43it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2258/? [26:21<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2259/? [26:22<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2259/? [26:22<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2260/? [26:23<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2260/? [26:23<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2261/? [26:24<00:00,  1.43it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2261/? [26:24<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2262/? [26:25<00:00,  1.43it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2262/? [26:25<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2263/? [26:26<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2263/? [26:26<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2264/? [26:27<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2264/? [26:27<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2265/? [26:28<00:00,  1.43it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2265/? [26:28<00:00,  1.43it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2266/? [26:29<00:00,  1.43it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2266/? [26:29<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2267/? [26:30<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2267/? [26:30<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2268/? [26:31<00:00,  1.43it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2268/? [26:31<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2269/? [26:32<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2269/? [26:32<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00964, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2270/? [26:33<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00964, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2270/? [26:33<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2271/? [26:34<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2271/? [26:34<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2272/? [26:35<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2272/? [26:35<00:00,  1.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2273/? [26:36<00:00,  1.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2273/? [26:36<00:00,  1.42it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2274/? [26:37<00:00,  1.42it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2274/? [26:37<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2275/? [26:38<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2275/? [26:38<00:00,  1.42it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00946, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2276/? [26:39<00:00,  1.42it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00946, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2276/? [26:40<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2277/? [26:40<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2277/? [26:41<00:00,  1.42it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2278/? [26:41<00:00,  1.42it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2278/? [26:42<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2279/? [26:42<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00995, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2279/? [26:43<00:00,  1.42it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=17.70, val/top_5_accuracy=0.0094]  
Training: |          | 2280/? [26:43<00:00,  1.42it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2280/? [26:44<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2281/? [26:44<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2281/? [26:45<00:00,  1.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0162, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2282/? [26:45<00:00,  1.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0162, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2282/? [26:46<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2283/? [26:46<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2283/? [26:47<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2284/? [26:47<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2284/? [26:48<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2285/? [26:48<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2285/? [26:49<00:00,  1.42it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2286/? [26:49<00:00,  1.42it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2286/? [26:50<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2287/? [26:50<00:00,  1.42it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2287/? [26:51<00:00,  1.42it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0108, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2288/? [26:51<00:00,  1.42it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0108, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2288/? [26:52<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2289/? [26:52<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2289/? [26:53<00:00,  1.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2290/? [26:53<00:00,  1.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2290/? [26:54<00:00,  1.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0121, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2291/? [26:54<00:00,  1.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0121, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2291/? [26:55<00:00,  1.42it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2292/? [26:56<00:00,  1.42it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2292/? [26:56<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0159, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2293/? [26:57<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0159, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2293/? [26:57<00:00,  1.42it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.008, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2294/? [26:58<00:00,  1.42it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.008, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2294/? [26:58<00:00,  1.42it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2295/? [26:59<00:00,  1.42it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2295/? [26:59<00:00,  1.42it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2296/? [27:00<00:00,  1.42it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2296/? [27:00<00:00,  1.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2297/? [27:01<00:00,  1.42it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2297/? [27:01<00:00,  1.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0133, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2298/? [27:02<00:00,  1.42it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0133, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2298/? [27:02<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2299/? [27:03<00:00,  1.42it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2299/? [27:03<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094] 
Training: |          | 2300/? [27:04<00:00,  1.42it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0094]
Training: |          | 2300/? [27:04<00:00,  1.42it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=17.70, val/top_5_accuracy=0.0094]

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Training: |          | 2300/? [27:11<00:00,  1.41it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2301/? [27:11<00:00,  1.41it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2301/? [27:12<00:00,  1.41it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2302/? [27:12<00:00,  1.41it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2302/? [27:13<00:00,  1.41it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2303/? [27:13<00:00,  1.41it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2303/? [27:14<00:00,  1.41it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2304/? [27:14<00:00,  1.41it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2304/? [27:15<00:00,  1.41it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2305/? [27:15<00:00,  1.41it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2305/? [27:16<00:00,  1.41it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2306/? [27:16<00:00,  1.41it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2306/? [27:17<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2307/? [27:17<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2307/? [27:18<00:00,  1.41it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2308/? [27:18<00:00,  1.41it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2308/? [27:19<00:00,  1.41it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2309/? [27:19<00:00,  1.41it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2309/? [27:20<00:00,  1.41it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2310/? [27:20<00:00,  1.41it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2310/? [27:21<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2311/? [27:21<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2311/? [27:22<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2312/? [27:22<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2312/? [27:23<00:00,  1.41it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2313/? [27:23<00:00,  1.41it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2313/? [27:24<00:00,  1.41it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2314/? [27:24<00:00,  1.41it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2314/? [27:25<00:00,  1.41it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2315/? [27:25<00:00,  1.41it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2315/? [27:26<00:00,  1.41it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.017, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2316/? [27:27<00:00,  1.41it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.017, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2316/? [27:27<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2317/? [27:28<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2317/? [27:28<00:00,  1.41it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00772, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2318/? [27:29<00:00,  1.41it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00772, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2318/? [27:29<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904]  
Training: |          | 2319/? [27:30<00:00,  1.41it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2319/? [27:30<00:00,  1.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2320/? [27:31<00:00,  1.41it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2320/? [27:31<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2321/? [27:32<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2321/? [27:32<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2322/? [27:33<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2322/? [27:33<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2323/? [27:34<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2323/? [27:34<00:00,  1.40it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2324/? [27:35<00:00,  1.40it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2324/? [27:35<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2325/? [27:36<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2325/? [27:36<00:00,  1.40it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2326/? [27:37<00:00,  1.40it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2326/? [27:37<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2327/? [27:38<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2327/? [27:38<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2328/? [27:39<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2328/? [27:39<00:00,  1.40it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2329/? [27:40<00:00,  1.40it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2329/? [27:40<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2330/? [27:41<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2330/? [27:41<00:00,  1.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2331/? [27:42<00:00,  1.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2331/? [27:42<00:00,  1.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2332/? [27:43<00:00,  1.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2332/? [27:43<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2333/? [27:44<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2333/? [27:44<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2334/? [27:45<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2334/? [27:45<00:00,  1.40it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2335/? [27:46<00:00,  1.40it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2335/? [27:46<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2336/? [27:47<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2336/? [27:47<00:00,  1.40it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2337/? [27:48<00:00,  1.40it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2337/? [27:49<00:00,  1.40it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2338/? [27:49<00:00,  1.40it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2338/? [27:50<00:00,  1.40it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2339/? [27:50<00:00,  1.40it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2339/? [27:51<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2340/? [27:51<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2340/? [27:52<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2341/? [27:52<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2341/? [27:53<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2342/? [27:53<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2342/? [27:54<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2343/? [27:54<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2343/? [27:55<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2344/? [27:55<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2344/? [27:56<00:00,  1.40it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2345/? [27:56<00:00,  1.40it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2345/? [27:57<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2346/? [27:57<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2346/? [27:58<00:00,  1.40it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2347/? [27:58<00:00,  1.40it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2347/? [27:59<00:00,  1.40it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0175, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2348/? [27:59<00:00,  1.40it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0175, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2348/? [28:00<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2349/? [28:00<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2349/? [28:01<00:00,  1.40it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2350/? [28:01<00:00,  1.40it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2350/? [28:02<00:00,  1.40it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2351/? [28:02<00:00,  1.40it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2351/? [28:03<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2352/? [28:03<00:00,  1.40it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2352/? [28:04<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2353/? [28:05<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2353/? [28:05<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2354/? [28:05<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2354/? [28:06<00:00,  1.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2355/? [28:07<00:00,  1.40it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2355/? [28:07<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2356/? [28:08<00:00,  1.40it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2356/? [28:08<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2357/? [28:09<00:00,  1.40it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2357/? [28:09<00:00,  1.40it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2358/? [28:10<00:00,  1.40it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2358/? [28:10<00:00,  1.39it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2359/? [28:11<00:00,  1.39it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2359/? [28:11<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2360/? [28:12<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2360/? [28:12<00:00,  1.39it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2361/? [28:13<00:00,  1.39it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2361/? [28:13<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2362/? [28:14<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2362/? [28:14<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2363/? [28:15<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2363/? [28:15<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2364/? [28:16<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2364/? [28:16<00:00,  1.39it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2365/? [28:17<00:00,  1.39it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2365/? [28:17<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2366/? [28:18<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2366/? [28:18<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2367/? [28:19<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2367/? [28:19<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2368/? [28:20<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2368/? [28:20<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2369/? [28:21<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2369/? [28:21<00:00,  1.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2370/? [28:22<00:00,  1.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2370/? [28:22<00:00,  1.39it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2371/? [28:23<00:00,  1.39it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2371/? [28:23<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2372/? [28:24<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2372/? [28:24<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2373/? [28:25<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2373/? [28:25<00:00,  1.39it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2374/? [28:26<00:00,  1.39it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2374/? [28:26<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2375/? [28:27<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2375/? [28:27<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2376/? [28:28<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2376/? [28:28<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2377/? [28:29<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2377/? [28:29<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2378/? [28:30<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2378/? [28:30<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2379/? [28:31<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2379/? [28:31<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2380/? [28:32<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2380/? [28:33<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2381/? [28:33<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2381/? [28:34<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2382/? [28:34<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2382/? [28:35<00:00,  1.39it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00946, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2383/? [28:35<00:00,  1.39it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00946, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2383/? [28:36<00:00,  1.39it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2384/? [28:36<00:00,  1.39it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2384/? [28:37<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2385/? [28:37<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2385/? [28:38<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0147, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2386/? [28:38<00:00,  1.39it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0147, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2386/? [28:39<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2387/? [28:39<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2387/? [28:40<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2388/? [28:40<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2388/? [28:41<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2389/? [28:41<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2389/? [28:42<00:00,  1.39it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2390/? [28:42<00:00,  1.39it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2390/? [28:43<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2391/? [28:43<00:00,  1.39it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2391/? [28:44<00:00,  1.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0173, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2392/? [28:44<00:00,  1.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0173, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2392/? [28:45<00:00,  1.39it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2393/? [28:45<00:00,  1.39it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2393/? [28:46<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2394/? [28:46<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2394/? [28:47<00:00,  1.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.017, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2395/? [28:47<00:00,  1.39it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.017, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2395/? [28:48<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2396/? [28:49<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2396/? [28:49<00:00,  1.39it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0165, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2397/? [28:50<00:00,  1.39it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0165, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2397/? [28:50<00:00,  1.39it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00708, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2398/? [28:51<00:00,  1.39it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00708, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2398/? [28:51<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904] 
Training: |          | 2399/? [28:52<00:00,  1.39it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2399/? [28:52<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2400/? [28:53<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00904]
Training: |          | 2400/? [28:53<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00904]

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Training: |          | 2400/? [28:58<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2401/? [28:58<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2401/? [28:59<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2402/? [28:59<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2402/? [29:00<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2403/? [29:00<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2403/? [29:01<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2404/? [29:01<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2404/? [29:02<00:00,  1.38it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2405/? [29:02<00:00,  1.38it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2405/? [29:03<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2406/? [29:03<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2406/? [29:04<00:00,  1.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2407/? [29:04<00:00,  1.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2407/? [29:05<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2408/? [29:05<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2408/? [29:06<00:00,  1.38it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2409/? [29:06<00:00,  1.38it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2409/? [29:07<00:00,  1.38it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2410/? [29:07<00:00,  1.38it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2410/? [29:08<00:00,  1.38it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2411/? [29:08<00:00,  1.38it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2411/? [29:09<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2412/? [29:10<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2412/? [29:10<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2413/? [29:11<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2413/? [29:11<00:00,  1.38it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2414/? [29:12<00:00,  1.38it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2414/? [29:12<00:00,  1.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2415/? [29:13<00:00,  1.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2415/? [29:13<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2416/? [29:14<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2416/? [29:14<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2417/? [29:15<00:00,  1.38it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2417/? [29:15<00:00,  1.38it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2418/? [29:16<00:00,  1.38it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2418/? [29:16<00:00,  1.38it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2419/? [29:17<00:00,  1.38it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2419/? [29:17<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2420/? [29:18<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2420/? [29:18<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2421/? [29:19<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2421/? [29:19<00:00,  1.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00751, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2422/? [29:20<00:00,  1.38it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00751, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2422/? [29:20<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2423/? [29:21<00:00,  1.38it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2423/? [29:21<00:00,  1.38it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2424/? [29:22<00:00,  1.38it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2424/? [29:22<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2425/? [29:23<00:00,  1.38it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2425/? [29:23<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2426/? [29:24<00:00,  1.38it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2426/? [29:24<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2427/? [29:25<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2427/? [29:25<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2428/? [29:26<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2428/? [29:26<00:00,  1.37it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2429/? [29:27<00:00,  1.37it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2429/? [29:27<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2430/? [29:28<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2430/? [29:28<00:00,  1.37it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2431/? [29:29<00:00,  1.37it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0117, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2431/? [29:29<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2432/? [29:30<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2432/? [29:30<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2433/? [29:31<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2433/? [29:31<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2434/? [29:32<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2434/? [29:32<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2435/? [29:33<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2435/? [29:33<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2436/? [29:34<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2436/? [29:34<00:00,  1.37it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2437/? [29:35<00:00,  1.37it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2437/? [29:36<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2438/? [29:36<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2438/? [29:37<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2439/? [29:37<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2439/? [29:38<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2440/? [29:38<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2440/? [29:39<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2441/? [29:39<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2441/? [29:40<00:00,  1.37it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2442/? [29:40<00:00,  1.37it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2442/? [29:41<00:00,  1.37it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2443/? [29:41<00:00,  1.37it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2443/? [29:42<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2444/? [29:42<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2444/? [29:43<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2445/? [29:43<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2445/? [29:44<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2446/? [29:44<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2446/? [29:45<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2447/? [29:45<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2447/? [29:46<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2448/? [29:46<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2448/? [29:47<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2449/? [29:47<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2449/? [29:48<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2450/? [29:48<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2450/? [29:49<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2451/? [29:49<00:00,  1.37it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2451/? [29:50<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2452/? [29:51<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2452/? [29:51<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2453/? [29:52<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2453/? [29:52<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2454/? [29:53<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2454/? [29:53<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2455/? [29:54<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2455/? [29:54<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2456/? [29:55<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2456/? [29:55<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2457/? [29:56<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2457/? [29:56<00:00,  1.37it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0154, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2458/? [29:57<00:00,  1.37it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0154, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2458/? [29:57<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2459/? [29:58<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2459/? [29:58<00:00,  1.37it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2460/? [29:59<00:00,  1.37it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2460/? [29:59<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2461/? [30:00<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2461/? [30:00<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2462/? [30:01<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2462/? [30:01<00:00,  1.37it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2463/? [30:02<00:00,  1.37it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2463/? [30:02<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2464/? [30:03<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2464/? [30:03<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2465/? [30:04<00:00,  1.37it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2465/? [30:04<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2466/? [30:05<00:00,  1.37it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2466/? [30:05<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2467/? [30:06<00:00,  1.37it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2467/? [30:06<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2468/? [30:07<00:00,  1.37it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2468/? [30:07<00:00,  1.37it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0175, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2469/? [30:08<00:00,  1.37it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0175, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2469/? [30:08<00:00,  1.36it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2470/? [30:09<00:00,  1.37it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2470/? [30:09<00:00,  1.36it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2471/? [30:10<00:00,  1.36it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2471/? [30:10<00:00,  1.36it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2472/? [30:11<00:00,  1.36it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2472/? [30:11<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2473/? [30:12<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2473/? [30:13<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0179, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2474/? [30:13<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0179, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2474/? [30:14<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2475/? [30:14<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2475/? [30:15<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2476/? [30:15<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2476/? [30:16<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2477/? [30:16<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2477/? [30:17<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2478/? [30:17<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00891, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2478/? [30:18<00:00,  1.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2479/? [30:18<00:00,  1.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2479/? [30:19<00:00,  1.36it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2480/? [30:19<00:00,  1.36it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2480/? [30:20<00:00,  1.36it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2481/? [30:20<00:00,  1.36it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2481/? [30:21<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2482/? [30:21<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2482/? [30:22<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2483/? [30:22<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2483/? [30:23<00:00,  1.36it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0134, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2484/? [30:23<00:00,  1.36it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0134, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2484/? [30:24<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2485/? [30:24<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2485/? [30:25<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2486/? [30:25<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2486/? [30:26<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2487/? [30:26<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2487/? [30:27<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2488/? [30:27<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2488/? [30:28<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2489/? [30:28<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2489/? [30:29<00:00,  1.36it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2490/? [30:30<00:00,  1.36it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2490/? [30:30<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0137, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2491/? [30:31<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0137, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2491/? [30:31<00:00,  1.36it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2492/? [30:32<00:00,  1.36it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2492/? [30:32<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2493/? [30:33<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2493/? [30:33<00:00,  1.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2494/? [30:34<00:00,  1.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00934, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2494/? [30:34<00:00,  1.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087] 
Training: |          | 2495/? [30:35<00:00,  1.36it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2495/? [30:35<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2496/? [30:36<00:00,  1.36it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2496/? [30:36<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2497/? [30:37<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2497/? [30:37<00:00,  1.36it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2498/? [30:38<00:00,  1.36it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2498/? [30:38<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2499/? [30:39<00:00,  1.36it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2499/? [30:39<00:00,  1.36it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2500/? [30:40<00:00,  1.36it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.0087]
Training: |          | 2500/? [30:40<00:00,  1.36it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.0087]

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Training: |          | 2500/? [30:45<00:00,  1.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2501/? [30:46<00:00,  1.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2501/? [30:46<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2502/? [30:47<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2502/? [30:47<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2503/? [30:48<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2503/? [30:48<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0173, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2504/? [30:49<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0173, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2504/? [30:49<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2505/? [30:50<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2505/? [30:50<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2506/? [30:51<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2506/? [30:51<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2507/? [30:52<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2507/? [30:52<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2508/? [30:53<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2508/? [30:53<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0105, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2509/? [30:54<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0105, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2509/? [30:54<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2510/? [30:55<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2510/? [30:56<00:00,  1.35it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2511/? [30:56<00:00,  1.35it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2511/? [30:57<00:00,  1.35it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0153, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2512/? [30:57<00:00,  1.35it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0153, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2512/? [30:58<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2513/? [30:58<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00958, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2513/? [30:59<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0162, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2514/? [30:59<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0162, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2514/? [31:00<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2515/? [31:00<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2515/? [31:01<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2516/? [31:01<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2516/? [31:02<00:00,  1.35it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2517/? [31:02<00:00,  1.35it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00873, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2517/? [31:03<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2518/? [31:03<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2518/? [31:04<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2519/? [31:04<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2519/? [31:05<00:00,  1.35it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0155, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2520/? [31:05<00:00,  1.35it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0155, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2520/? [31:06<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2521/? [31:07<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2521/? [31:07<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2522/? [31:08<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2522/? [31:08<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2523/? [31:09<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2523/? [31:09<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2524/? [31:10<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2524/? [31:10<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2525/? [31:11<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2525/? [31:11<00:00,  1.35it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0125, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2526/? [31:12<00:00,  1.35it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0125, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2526/? [31:12<00:00,  1.35it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2527/? [31:13<00:00,  1.35it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00885, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2527/? [31:13<00:00,  1.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2528/? [31:14<00:00,  1.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2528/? [31:14<00:00,  1.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2529/? [31:15<00:00,  1.35it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2529/? [31:15<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2530/? [31:16<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2530/? [31:16<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2531/? [31:17<00:00,  1.35it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2531/? [31:17<00:00,  1.35it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2532/? [31:18<00:00,  1.35it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2532/? [31:18<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2533/? [31:19<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2533/? [31:19<00:00,  1.35it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2534/? [31:20<00:00,  1.35it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2534/? [31:20<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2535/? [31:21<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2535/? [31:21<00:00,  1.35it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0181, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2536/? [31:22<00:00,  1.35it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0181, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2536/? [31:22<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2537/? [31:23<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2537/? [31:23<00:00,  1.35it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0132, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2538/? [31:24<00:00,  1.35it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0132, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2538/? [31:24<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2539/? [31:25<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2539/? [31:25<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2540/? [31:26<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00891, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2540/? [31:26<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2541/? [31:27<00:00,  1.35it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2541/? [31:27<00:00,  1.35it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2542/? [31:28<00:00,  1.35it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2542/? [31:28<00:00,  1.35it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2543/? [31:29<00:00,  1.35it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00928, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2543/? [31:29<00:00,  1.35it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2544/? [31:30<00:00,  1.35it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2544/? [31:30<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2545/? [31:31<00:00,  1.35it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2545/? [31:32<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2546/? [31:32<00:00,  1.35it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2546/? [31:33<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0127, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2547/? [31:33<00:00,  1.35it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0127, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2547/? [31:34<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2548/? [31:34<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2548/? [31:35<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2549/? [31:35<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2549/? [31:36<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2550/? [31:36<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2550/? [31:37<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2551/? [31:37<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2551/? [31:38<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2552/? [31:38<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2552/? [31:39<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2553/? [31:39<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2553/? [31:40<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2554/? [31:40<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2554/? [31:41<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2555/? [31:41<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2555/? [31:42<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0153, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2556/? [31:42<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0153, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2556/? [31:43<00:00,  1.34it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00964, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2557/? [31:43<00:00,  1.34it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00964, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2557/? [31:44<00:00,  1.34it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2558/? [31:44<00:00,  1.34it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2558/? [31:45<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2559/? [31:45<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2559/? [31:46<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0141, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2560/? [31:46<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0141, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2560/? [31:47<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2561/? [31:47<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2561/? [31:48<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2562/? [31:48<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2562/? [31:49<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2563/? [31:50<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2563/? [31:50<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2564/? [31:51<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2564/? [31:51<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2565/? [31:52<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2565/? [31:52<00:00,  1.34it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2566/? [31:53<00:00,  1.34it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2566/? [31:53<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2567/? [31:54<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2567/? [31:54<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2568/? [31:55<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2568/? [31:55<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2569/? [31:56<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2569/? [31:56<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2570/? [31:57<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2570/? [31:57<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2571/? [31:58<00:00,  1.34it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2571/? [31:58<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2572/? [31:59<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2572/? [31:59<00:00,  1.34it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.010, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2573/? [32:00<00:00,  1.34it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.010, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2573/? [32:00<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2574/? [32:01<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2574/? [32:01<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2575/? [32:02<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2575/? [32:02<00:00,  1.34it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2576/? [32:03<00:00,  1.34it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2576/? [32:03<00:00,  1.34it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2577/? [32:04<00:00,  1.34it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2577/? [32:04<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2578/? [32:05<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2578/? [32:05<00:00,  1.34it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0187, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2579/? [32:06<00:00,  1.34it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0187, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2579/? [32:06<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2580/? [32:07<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2580/? [32:07<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2581/? [32:08<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2581/? [32:08<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2582/? [32:09<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2582/? [32:09<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2583/? [32:10<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2583/? [32:10<00:00,  1.34it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2584/? [32:11<00:00,  1.34it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2584/? [32:12<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2585/? [32:12<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2585/? [32:13<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2586/? [32:13<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2586/? [32:14<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2587/? [32:14<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2587/? [32:15<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2588/? [32:15<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2588/? [32:16<00:00,  1.34it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00848, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2589/? [32:16<00:00,  1.34it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00848, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2589/? [32:17<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2590/? [32:17<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2590/? [32:18<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2591/? [32:18<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2591/? [32:19<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2592/? [32:19<00:00,  1.34it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2592/? [32:20<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2593/? [32:20<00:00,  1.34it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2593/? [32:21<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00873] 
Training: |          | 2594/? [32:21<00:00,  1.34it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2594/? [32:22<00:00,  1.34it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0151, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2595/? [32:22<00:00,  1.34it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0151, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2595/? [32:23<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2596/? [32:23<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2596/? [32:24<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2597/? [32:24<00:00,  1.34it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2597/? [32:25<00:00,  1.33it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0126, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2598/? [32:26<00:00,  1.34it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0126, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2598/? [32:26<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2599/? [32:27<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2599/? [32:27<00:00,  1.33it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2600/? [32:28<00:00,  1.33it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.40, val/top_5_accuracy=0.00873]
Training: |          | 2600/? [32:28<00:00,  1.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=18.40, val/top_5_accuracy=0.00873]

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Training: |          | 2600/? [32:33<00:00,  1.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2601/? [32:34<00:00,  1.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2601/? [32:34<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2602/? [32:35<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2602/? [32:35<00:00,  1.33it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2603/? [32:36<00:00,  1.33it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2603/? [32:36<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00946, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2604/? [32:37<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00946, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2604/? [32:37<00:00,  1.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2605/? [32:38<00:00,  1.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2605/? [32:38<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0153, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2606/? [32:39<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0153, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2606/? [32:39<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2607/? [32:40<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2607/? [32:40<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2608/? [32:41<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2608/? [32:41<00:00,  1.33it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2609/? [32:42<00:00,  1.33it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2609/? [32:42<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2610/? [32:43<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2610/? [32:43<00:00,  1.33it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0186, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2611/? [32:44<00:00,  1.33it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0186, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2611/? [32:44<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2612/? [32:45<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2612/? [32:45<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00897, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2613/? [32:46<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00897, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2613/? [32:46<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2614/? [32:47<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2614/? [32:47<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2615/? [32:48<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2615/? [32:48<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2616/? [32:49<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2616/? [32:49<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2617/? [32:50<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2617/? [32:50<00:00,  1.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2618/? [32:51<00:00,  1.33it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2618/? [32:51<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2619/? [32:52<00:00,  1.33it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2619/? [32:52<00:00,  1.33it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2620/? [32:53<00:00,  1.33it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2620/? [32:54<00:00,  1.33it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2621/? [32:54<00:00,  1.33it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2621/? [32:55<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2622/? [32:55<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2622/? [32:56<00:00,  1.33it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2623/? [32:56<00:00,  1.33it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2623/? [32:57<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2624/? [32:57<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2624/? [32:58<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2625/? [32:58<00:00,  1.33it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2625/? [32:59<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2626/? [32:59<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2626/? [33:00<00:00,  1.33it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2627/? [33:00<00:00,  1.33it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2627/? [33:01<00:00,  1.33it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0184, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2628/? [33:01<00:00,  1.33it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0184, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2628/? [33:02<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2629/? [33:02<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2629/? [33:03<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2630/? [33:03<00:00,  1.33it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2630/? [33:04<00:00,  1.33it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00995, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2631/? [33:04<00:00,  1.33it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00995, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2631/? [33:05<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2632/? [33:05<00:00,  1.33it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2632/? [33:06<00:00,  1.33it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2633/? [33:06<00:00,  1.33it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2633/? [33:07<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2634/? [33:07<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2634/? [33:08<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2635/? [33:09<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2635/? [33:09<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2636/? [33:10<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2636/? [33:10<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2637/? [33:11<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2637/? [33:11<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2638/? [33:12<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2638/? [33:12<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2639/? [33:13<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2639/? [33:13<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2640/? [33:14<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2640/? [33:14<00:00,  1.32it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2641/? [33:15<00:00,  1.32it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2641/? [33:15<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2642/? [33:16<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2642/? [33:16<00:00,  1.32it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2643/? [33:17<00:00,  1.32it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2643/? [33:17<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2644/? [33:18<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2644/? [33:18<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2645/? [33:19<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2645/? [33:19<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2646/? [33:20<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2646/? [33:20<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2647/? [33:21<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2647/? [33:21<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]  
Training: |          | 2648/? [33:22<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2648/? [33:22<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2649/? [33:23<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2649/? [33:23<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2650/? [33:24<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2650/? [33:24<00:00,  1.32it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2651/? [33:25<00:00,  1.32it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2651/? [33:25<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2652/? [33:26<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2652/? [33:26<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2653/? [33:27<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2653/? [33:27<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2654/? [33:28<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2654/? [33:29<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2655/? [33:29<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2655/? [33:30<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2656/? [33:30<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2656/? [33:31<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2657/? [33:31<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2657/? [33:32<00:00,  1.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2658/? [33:32<00:00,  1.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2658/? [33:33<00:00,  1.32it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2659/? [33:33<00:00,  1.32it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2659/? [33:34<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2660/? [33:34<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2660/? [33:35<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2661/? [33:35<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2661/? [33:36<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2662/? [33:36<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2662/? [33:37<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2663/? [33:37<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2663/? [33:38<00:00,  1.32it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0149, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2664/? [33:38<00:00,  1.32it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0149, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2664/? [33:39<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2665/? [33:39<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2665/? [33:40<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2666/? [33:40<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2666/? [33:41<00:00,  1.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2667/? [33:41<00:00,  1.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2667/? [33:42<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2668/? [33:42<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2668/? [33:43<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2669/? [33:44<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2669/? [33:44<00:00,  1.32it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2670/? [33:45<00:00,  1.32it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2670/? [33:45<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2671/? [33:46<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00922, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2671/? [33:46<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2672/? [33:47<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2672/? [33:47<00:00,  1.32it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2673/? [33:48<00:00,  1.32it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2673/? [33:48<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2674/? [33:49<00:00,  1.32it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2674/? [33:49<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2675/? [33:50<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2675/? [33:50<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2676/? [33:51<00:00,  1.32it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2676/? [33:51<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2677/? [33:52<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2677/? [33:52<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2678/? [33:53<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2678/? [33:53<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0105, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2679/? [33:54<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0105, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2679/? [33:54<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2680/? [33:55<00:00,  1.32it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2680/? [33:55<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2681/? [33:56<00:00,  1.32it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2681/? [33:56<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2682/? [33:57<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2682/? [33:57<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2683/? [33:58<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2683/? [33:58<00:00,  1.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2684/? [33:59<00:00,  1.32it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2684/? [33:59<00:00,  1.32it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2685/? [34:00<00:00,  1.32it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2685/? [34:01<00:00,  1.32it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0141, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2686/? [34:01<00:00,  1.32it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0141, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2686/? [34:02<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2687/? [34:02<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2687/? [34:03<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2688/? [34:03<00:00,  1.32it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2688/? [34:04<00:00,  1.31it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2689/? [34:04<00:00,  1.32it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2689/? [34:05<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2690/? [34:05<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2690/? [34:06<00:00,  1.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2691/? [34:06<00:00,  1.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2691/? [34:07<00:00,  1.31it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2692/? [34:07<00:00,  1.31it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2692/? [34:08<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2693/? [34:08<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2693/? [34:09<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2694/? [34:09<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2694/? [34:10<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2695/? [34:10<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2695/? [34:11<00:00,  1.31it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2696/? [34:11<00:00,  1.31it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2696/? [34:12<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2697/? [34:12<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2697/? [34:13<00:00,  1.31it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2698/? [34:13<00:00,  1.31it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2698/? [34:14<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2699/? [34:15<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2699/? [34:15<00:00,  1.31it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00894] 
Training: |          | 2700/? [34:16<00:00,  1.31it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00894]
Training: |          | 2700/? [34:16<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00894]

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Training: |          | 2700/? [34:23<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2701/? [34:24<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2701/? [34:24<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2702/? [34:25<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2702/? [34:25<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2703/? [34:26<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2703/? [34:26<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2704/? [34:27<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2704/? [34:27<00:00,  1.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2705/? [34:28<00:00,  1.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2705/? [34:28<00:00,  1.31it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2706/? [34:29<00:00,  1.31it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2706/? [34:29<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2707/? [34:30<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2707/? [34:30<00:00,  1.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2708/? [34:31<00:00,  1.31it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2708/? [34:31<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2709/? [34:32<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2709/? [34:32<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2710/? [34:33<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2710/? [34:33<00:00,  1.31it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2711/? [34:34<00:00,  1.31it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2711/? [34:34<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2712/? [34:35<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2712/? [34:35<00:00,  1.31it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2713/? [34:36<00:00,  1.31it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2713/? [34:36<00:00,  1.31it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0199, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2714/? [34:37<00:00,  1.31it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0199, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2714/? [34:37<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2715/? [34:38<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2715/? [34:38<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2716/? [34:39<00:00,  1.31it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2716/? [34:40<00:00,  1.31it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2717/? [34:40<00:00,  1.31it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00891, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2717/? [34:41<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2718/? [34:41<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2718/? [34:42<00:00,  1.31it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2719/? [34:42<00:00,  1.31it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2719/? [34:43<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2720/? [34:43<00:00,  1.31it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2720/? [34:44<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2721/? [34:44<00:00,  1.31it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2721/? [34:45<00:00,  1.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2722/? [34:45<00:00,  1.31it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2722/? [34:46<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2723/? [34:46<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2723/? [34:47<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2724/? [34:47<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2724/? [34:48<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2725/? [34:48<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2725/? [34:49<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2726/? [34:49<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2726/? [34:50<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2727/? [34:50<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2727/? [34:51<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2728/? [34:51<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2728/? [34:52<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2729/? [34:52<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2729/? [34:53<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2730/? [34:54<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2730/? [34:54<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2731/? [34:55<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2731/? [34:55<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2732/? [34:56<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2732/? [34:56<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2733/? [34:57<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2733/? [34:57<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2734/? [34:58<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2734/? [34:58<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2735/? [34:59<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2735/? [34:59<00:00,  1.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2736/? [35:00<00:00,  1.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2736/? [35:00<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2737/? [35:01<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2737/? [35:01<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0175, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2738/? [35:02<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0175, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2738/? [35:02<00:00,  1.30it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2739/? [35:03<00:00,  1.30it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2739/? [35:03<00:00,  1.30it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2740/? [35:04<00:00,  1.30it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2740/? [35:04<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2741/? [35:05<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2741/? [35:05<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2742/? [35:06<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2742/? [35:06<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2743/? [35:07<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2743/? [35:07<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2744/? [35:08<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2744/? [35:08<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2745/? [35:09<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2745/? [35:09<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2746/? [35:10<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2746/? [35:10<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2747/? [35:11<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2747/? [35:11<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2748/? [35:12<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2748/? [35:12<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2749/? [35:13<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2749/? [35:13<00:00,  1.30it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00641, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2750/? [35:14<00:00,  1.30it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00641, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2750/? [35:14<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2751/? [35:15<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2751/? [35:15<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2752/? [35:16<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2752/? [35:16<00:00,  1.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2753/? [35:17<00:00,  1.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2753/? [35:18<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2754/? [35:18<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2754/? [35:19<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2755/? [35:19<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2755/? [35:20<00:00,  1.30it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00705, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2756/? [35:20<00:00,  1.30it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.00705, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2756/? [35:21<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0105]  
Training: |          | 2757/? [35:21<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2757/? [35:22<00:00,  1.30it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0157, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2758/? [35:22<00:00,  1.30it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0157, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2758/? [35:23<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2759/? [35:23<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2759/? [35:24<00:00,  1.30it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2760/? [35:24<00:00,  1.30it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2760/? [35:25<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2761/? [35:25<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2761/? [35:26<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2762/? [35:26<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2762/? [35:27<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2763/? [35:27<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2763/? [35:28<00:00,  1.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2764/? [35:28<00:00,  1.30it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2764/? [35:29<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2765/? [35:29<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2765/? [35:30<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2766/? [35:30<00:00,  1.30it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2766/? [35:31<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2767/? [35:32<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2767/? [35:32<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2768/? [35:33<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2768/? [35:33<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2769/? [35:34<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2769/? [35:34<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2770/? [35:35<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2770/? [35:35<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0138, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2771/? [35:36<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0138, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2771/? [35:36<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2772/? [35:37<00:00,  1.30it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2772/? [35:37<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2773/? [35:38<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2773/? [35:38<00:00,  1.30it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2774/? [35:39<00:00,  1.30it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2774/? [35:39<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2775/? [35:40<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2775/? [35:40<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2776/? [35:41<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2776/? [35:41<00:00,  1.30it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2777/? [35:42<00:00,  1.30it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2777/? [35:42<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0175, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2778/? [35:43<00:00,  1.30it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0175, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2778/? [35:43<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2779/? [35:44<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2779/? [35:44<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2780/? [35:45<00:00,  1.30it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2780/? [35:45<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2781/? [35:46<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2781/? [35:46<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2782/? [35:47<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2782/? [35:48<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2783/? [35:48<00:00,  1.30it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2783/? [35:49<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2784/? [35:49<00:00,  1.30it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2784/? [35:50<00:00,  1.29it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2785/? [35:50<00:00,  1.29it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2785/? [35:51<00:00,  1.29it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2786/? [35:51<00:00,  1.29it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2786/? [35:52<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2787/? [35:52<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2787/? [35:53<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2788/? [35:53<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2788/? [35:54<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2789/? [35:54<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2789/? [35:55<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2790/? [35:55<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2790/? [35:56<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2791/? [35:56<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2791/? [35:57<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2792/? [35:57<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2792/? [35:58<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2793/? [35:58<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2793/? [35:59<00:00,  1.29it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0171, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2794/? [35:59<00:00,  1.29it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0171, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2794/? [36:00<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2795/? [36:00<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2795/? [36:01<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2796/? [36:01<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2796/? [36:02<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2797/? [36:02<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2797/? [36:03<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2798/? [36:03<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2798/? [36:04<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.0105] 
Training: |          | 2799/? [36:04<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2799/? [36:05<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2800/? [36:05<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.0105]
Training: |          | 2800/? [36:06<00:00,  1.29it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.0105]

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Training: |          | 2800/? [36:10<00:00,  1.29it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2801/? [36:11<00:00,  1.29it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2801/? [36:11<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2802/? [36:12<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2802/? [36:13<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0139, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2803/? [36:13<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0139, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2803/? [36:14<00:00,  1.29it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2804/? [36:14<00:00,  1.29it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2804/? [36:15<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2805/? [36:15<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2805/? [36:16<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2806/? [36:16<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2806/? [36:17<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00952, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2807/? [36:17<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00952, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2807/? [36:18<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2808/? [36:18<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2808/? [36:19<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2809/? [36:19<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00861, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2809/? [36:20<00:00,  1.29it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2810/? [36:20<00:00,  1.29it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2810/? [36:21<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2811/? [36:21<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2811/? [36:22<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2812/? [36:22<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2812/? [36:23<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2813/? [36:23<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2813/? [36:24<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2814/? [36:24<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2814/? [36:25<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2815/? [36:25<00:00,  1.29it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2815/? [36:26<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2816/? [36:26<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2816/? [36:27<00:00,  1.29it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2817/? [36:27<00:00,  1.29it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2817/? [36:28<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2818/? [36:28<00:00,  1.29it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2818/? [36:29<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2819/? [36:30<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2819/? [36:30<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2820/? [36:31<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2820/? [36:31<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2821/? [36:32<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2821/? [36:32<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00861, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2822/? [36:33<00:00,  1.29it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00861, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2822/? [36:33<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2823/? [36:34<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2823/? [36:34<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2824/? [36:35<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2824/? [36:35<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2825/? [36:36<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2825/? [36:36<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2826/? [36:37<00:00,  1.29it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2826/? [36:37<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2827/? [36:38<00:00,  1.29it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2827/? [36:38<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2828/? [36:39<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2828/? [36:39<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2829/? [36:40<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2829/? [36:40<00:00,  1.29it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2830/? [36:41<00:00,  1.29it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2830/? [36:41<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2831/? [36:42<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2831/? [36:42<00:00,  1.29it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0175, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2832/? [36:43<00:00,  1.29it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0175, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2832/? [36:43<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2833/? [36:44<00:00,  1.29it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2833/? [36:44<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2834/? [36:45<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2834/? [36:45<00:00,  1.28it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0178, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2835/? [36:46<00:00,  1.28it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0178, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2835/? [36:46<00:00,  1.28it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2836/? [36:47<00:00,  1.28it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2836/? [36:47<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2837/? [36:48<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2837/? [36:48<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2838/? [36:49<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2838/? [36:49<00:00,  1.28it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2839/? [36:50<00:00,  1.28it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2839/? [36:50<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2840/? [36:51<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2840/? [36:52<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2841/? [36:52<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2841/? [36:53<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2842/? [36:53<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2842/? [36:54<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2843/? [36:54<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2843/? [36:55<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2844/? [36:55<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2844/? [36:56<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2845/? [36:56<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2845/? [36:57<00:00,  1.28it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2846/? [36:57<00:00,  1.28it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2846/? [36:58<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2847/? [36:58<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2847/? [36:59<00:00,  1.28it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2848/? [36:59<00:00,  1.28it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2848/? [37:00<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2849/? [37:00<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2849/? [37:01<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2850/? [37:01<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2850/? [37:02<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2851/? [37:02<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2851/? [37:03<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2852/? [37:03<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2852/? [37:04<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2853/? [37:05<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2853/? [37:05<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2854/? [37:06<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2854/? [37:06<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2855/? [37:07<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2855/? [37:07<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2856/? [37:08<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2856/? [37:08<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2857/? [37:09<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2857/? [37:09<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2858/? [37:10<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2858/? [37:10<00:00,  1.28it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2859/? [37:11<00:00,  1.28it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2859/? [37:11<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2860/? [37:12<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2860/? [37:12<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2861/? [37:13<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2861/? [37:13<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2862/? [37:14<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2862/? [37:14<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2863/? [37:15<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2863/? [37:15<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0165, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2864/? [37:16<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0165, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2864/? [37:16<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2865/? [37:17<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2865/? [37:17<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2866/? [37:18<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2866/? [37:18<00:00,  1.28it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2867/? [37:19<00:00,  1.28it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2867/? [37:19<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0165, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2868/? [37:20<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0165, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2868/? [37:20<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2869/? [37:21<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2869/? [37:21<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2870/? [37:22<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2870/? [37:23<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2871/? [37:23<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2871/? [37:24<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0154, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2872/? [37:24<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0154, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2872/? [37:25<00:00,  1.28it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2873/? [37:25<00:00,  1.28it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2873/? [37:26<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0176, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2874/? [37:26<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0176, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2874/? [37:27<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2875/? [37:27<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2875/? [37:28<00:00,  1.28it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0164, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2876/? [37:28<00:00,  1.28it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0164, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2876/? [37:29<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2877/? [37:29<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2877/? [37:30<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2878/? [37:30<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2878/? [37:31<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2879/? [37:31<00:00,  1.28it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2879/? [37:32<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2880/? [37:32<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2880/? [37:33<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2881/? [37:33<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2881/? [37:34<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2882/? [37:34<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2882/? [37:35<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2883/? [37:35<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2883/? [37:36<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2884/? [37:36<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2884/? [37:37<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2885/? [37:37<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2885/? [37:38<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2886/? [37:39<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2886/? [37:39<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2887/? [37:40<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2887/? [37:40<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2888/? [37:41<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2888/? [37:41<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2889/? [37:42<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2889/? [37:42<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2890/? [37:43<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2890/? [37:43<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2891/? [37:44<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2891/? [37:44<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2892/? [37:45<00:00,  1.28it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2892/? [37:45<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2893/? [37:46<00:00,  1.28it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2893/? [37:46<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2894/? [37:47<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2894/? [37:47<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2895/? [37:48<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2895/? [37:48<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2896/? [37:49<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2896/? [37:49<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2897/? [37:50<00:00,  1.28it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2897/? [37:50<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2898/? [37:51<00:00,  1.28it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2898/? [37:51<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0147, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2899/? [37:52<00:00,  1.28it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0147, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2899/? [37:52<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095] 
Training: |          | 2900/? [37:53<00:00,  1.28it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.0095]
Training: |          | 2900/? [37:53<00:00,  1.28it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=18.20, val/top_5_accuracy=0.0095]

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Training: |          | 2900/? [37:59<00:00,  1.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2901/? [37:59<00:00,  1.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2901/? [38:00<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2902/? [38:00<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2902/? [38:01<00:00,  1.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2903/? [38:01<00:00,  1.27it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2903/? [38:02<00:00,  1.27it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00903, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2904/? [38:03<00:00,  1.27it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00903, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2904/? [38:03<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00933]  
Training: |          | 2905/? [38:04<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2905/? [38:04<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2906/? [38:05<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2906/? [38:05<00:00,  1.27it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2907/? [38:06<00:00,  1.27it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2907/? [38:06<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2908/? [38:07<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2908/? [38:07<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2909/? [38:08<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2909/? [38:08<00:00,  1.27it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2910/? [38:09<00:00,  1.27it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2910/? [38:09<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2911/? [38:10<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2911/? [38:10<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2912/? [38:11<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2912/? [38:11<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2913/? [38:12<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2913/? [38:12<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2914/? [38:13<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2914/? [38:13<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2915/? [38:14<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2915/? [38:14<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2916/? [38:15<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2916/? [38:15<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2917/? [38:16<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2917/? [38:16<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2918/? [38:17<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2918/? [38:17<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2919/? [38:18<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2919/? [38:18<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2920/? [38:19<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2920/? [38:19<00:00,  1.27it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0233, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2921/? [38:20<00:00,  1.27it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0233, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2921/? [38:20<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2922/? [38:21<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2922/? [38:21<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2923/? [38:22<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2923/? [38:22<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2924/? [38:23<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2924/? [38:23<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2925/? [38:24<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2925/? [38:24<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2926/? [38:25<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2926/? [38:26<00:00,  1.27it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2927/? [38:26<00:00,  1.27it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2927/? [38:27<00:00,  1.27it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2928/? [38:27<00:00,  1.27it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2928/? [38:28<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2929/? [38:28<00:00,  1.27it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2929/? [38:29<00:00,  1.27it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2930/? [38:29<00:00,  1.27it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2930/? [38:30<00:00,  1.27it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2931/? [38:30<00:00,  1.27it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2931/? [38:31<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2932/? [38:31<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2932/? [38:32<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2933/? [38:32<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2933/? [38:33<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2934/? [38:33<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2934/? [38:34<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2935/? [38:34<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2935/? [38:35<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2936/? [38:35<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2936/? [38:36<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2937/? [38:36<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2937/? [38:37<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2938/? [38:37<00:00,  1.27it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2938/? [38:38<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2939/? [38:38<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2939/? [38:39<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2940/? [38:39<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2940/? [38:40<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2941/? [38:40<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2941/? [38:41<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2942/? [38:41<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2942/? [38:42<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2943/? [38:42<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2943/? [38:43<00:00,  1.27it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2944/? [38:43<00:00,  1.27it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2944/? [38:44<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2945/? [38:45<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2945/? [38:45<00:00,  1.27it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2946/? [38:46<00:00,  1.27it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2946/? [38:46<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2947/? [38:47<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2947/? [38:47<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2948/? [38:48<00:00,  1.27it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2948/? [38:48<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2949/? [38:49<00:00,  1.27it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2949/? [38:49<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2950/? [38:50<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2950/? [38:50<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2951/? [38:51<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2951/? [38:51<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2952/? [38:52<00:00,  1.27it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2952/? [38:52<00:00,  1.27it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2953/? [38:53<00:00,  1.27it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2953/? [38:53<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2954/? [38:54<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2954/? [38:54<00:00,  1.27it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2955/? [38:55<00:00,  1.27it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2955/? [38:55<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2956/? [38:56<00:00,  1.27it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2956/? [38:56<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2957/? [38:57<00:00,  1.27it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2957/? [38:57<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00897, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2958/? [38:58<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00897, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2958/? [38:58<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2959/? [38:59<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2959/? [38:59<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2960/? [39:00<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2960/? [39:00<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2961/? [39:01<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2961/? [39:01<00:00,  1.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2962/? [39:02<00:00,  1.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2962/? [39:02<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2963/? [39:03<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2963/? [39:03<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2964/? [39:04<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2964/? [39:04<00:00,  1.26it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0164, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2965/? [39:05<00:00,  1.26it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0164, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2965/? [39:05<00:00,  1.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2966/? [39:06<00:00,  1.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2966/? [39:06<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2967/? [39:07<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2967/? [39:07<00:00,  1.26it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2968/? [39:08<00:00,  1.26it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2968/? [39:09<00:00,  1.26it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2969/? [39:09<00:00,  1.26it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2969/? [39:10<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2970/? [39:10<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2970/? [39:11<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2971/? [39:11<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2971/? [39:12<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2972/? [39:12<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2972/? [39:13<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2973/? [39:13<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2973/? [39:14<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2974/? [39:14<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2974/? [39:15<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2975/? [39:15<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2975/? [39:16<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2976/? [39:16<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2976/? [39:17<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2977/? [39:17<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2977/? [39:18<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00952, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2978/? [39:18<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00952, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2978/? [39:19<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2979/? [39:19<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2979/? [39:20<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2980/? [39:20<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2980/? [39:21<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2981/? [39:22<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2981/? [39:22<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2982/? [39:23<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2982/? [39:23<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2983/? [39:24<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2983/? [39:24<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2984/? [39:25<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2984/? [39:25<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2985/? [39:26<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2985/? [39:26<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2986/? [39:27<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2986/? [39:27<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2987/? [39:28<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2987/? [39:28<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2988/? [39:29<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2988/? [39:29<00:00,  1.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2989/? [39:30<00:00,  1.26it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2989/? [39:30<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2990/? [39:31<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2990/? [39:31<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2991/? [39:32<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2991/? [39:32<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2992/? [39:33<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2992/? [39:33<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2993/? [39:34<00:00,  1.26it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2993/? [39:34<00:00,  1.26it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0183, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2994/? [39:35<00:00,  1.26it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0183, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2994/? [39:35<00:00,  1.26it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0183, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2995/? [39:36<00:00,  1.26it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0183, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2995/? [39:36<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2996/? [39:37<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2996/? [39:37<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2997/? [39:38<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2997/? [39:38<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00977, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2998/? [39:39<00:00,  1.26it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00977, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2998/? [39:39<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00933] 
Training: |          | 2999/? [39:40<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 2999/? [39:40<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0175, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 3000/? [39:41<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0175, val/loss=17.90, val/top_5_accuracy=0.00933]
Training: |          | 3000/? [39:41<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=17.90, val/top_5_accuracy=0.00933]

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Training: |          | 3000/? [39:46<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3001/? [39:47<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3001/? [39:47<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3002/? [39:48<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3002/? [39:48<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3003/? [39:49<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3003/? [39:49<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00922, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3004/? [39:50<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00922, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3004/? [39:50<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3005/? [39:51<00:00,  1.26it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3005/? [39:51<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3006/? [39:52<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3006/? [39:52<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3007/? [39:53<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3007/? [39:53<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0175, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3008/? [39:54<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0175, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3008/? [39:54<00:00,  1.26it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3009/? [39:55<00:00,  1.26it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3009/? [39:55<00:00,  1.26it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3010/? [39:56<00:00,  1.26it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3010/? [39:56<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3011/? [39:57<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3011/? [39:57<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3012/? [39:58<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3012/? [39:58<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3013/? [39:59<00:00,  1.26it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3013/? [39:59<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3014/? [40:00<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3014/? [40:00<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3015/? [40:01<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3015/? [40:02<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3016/? [40:02<00:00,  1.26it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3016/? [40:03<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3017/? [40:03<00:00,  1.26it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3017/? [40:04<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3018/? [40:04<00:00,  1.26it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00879, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3018/? [40:05<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3019/? [40:05<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3019/? [40:06<00:00,  1.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3020/? [40:06<00:00,  1.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3020/? [40:07<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3021/? [40:07<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3021/? [40:08<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3022/? [40:08<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3022/? [40:09<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3023/? [40:09<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3023/? [40:10<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3024/? [40:10<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3024/? [40:11<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3025/? [40:11<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3025/? [40:12<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3026/? [40:12<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3026/? [40:13<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3027/? [40:13<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3027/? [40:14<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3028/? [40:14<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3028/? [40:15<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3029/? [40:15<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3029/? [40:16<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3030/? [40:16<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3030/? [40:17<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3031/? [40:18<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3031/? [40:18<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3032/? [40:19<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3032/? [40:19<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3033/? [40:20<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3033/? [40:20<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3034/? [40:21<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3034/? [40:21<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3035/? [40:22<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3035/? [40:22<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3036/? [40:23<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3036/? [40:23<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3037/? [40:24<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3037/? [40:24<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3038/? [40:25<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3038/? [40:25<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3039/? [40:26<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3039/? [40:26<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3040/? [40:27<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3040/? [40:27<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3041/? [40:28<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3041/? [40:28<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3042/? [40:29<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3042/? [40:29<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3043/? [40:30<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3043/? [40:30<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3044/? [40:31<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3044/? [40:31<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3045/? [40:32<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3045/? [40:32<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3046/? [40:33<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3046/? [40:33<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3047/? [40:34<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3047/? [40:34<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3048/? [40:35<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3048/? [40:35<00:00,  1.25it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3049/? [40:36<00:00,  1.25it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3049/? [40:36<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3050/? [40:37<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3050/? [40:37<00:00,  1.25it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3051/? [40:38<00:00,  1.25it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3051/? [40:38<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3052/? [40:39<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00897, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3052/? [40:39<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00951]  
Training: |          | 3053/? [40:40<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3053/? [40:40<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3054/? [40:41<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3054/? [40:42<00:00,  1.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3055/? [40:42<00:00,  1.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3055/? [40:43<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3056/? [40:43<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3056/? [40:44<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3057/? [40:44<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3057/? [40:45<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3058/? [40:45<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3058/? [40:46<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3059/? [40:46<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3059/? [40:47<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3060/? [40:47<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3060/? [40:48<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3061/? [40:48<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3061/? [40:49<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3062/? [40:49<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3062/? [40:50<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3063/? [40:50<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00928, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3063/? [40:51<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3064/? [40:51<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3064/? [40:52<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3065/? [40:52<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3065/? [40:53<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3066/? [40:54<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3066/? [40:54<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3067/? [40:55<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3067/? [40:55<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3068/? [40:56<00:00,  1.25it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3068/? [40:56<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3069/? [40:57<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3069/? [40:57<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3070/? [40:58<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3070/? [40:58<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3071/? [40:59<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3071/? [40:59<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3072/? [41:00<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3072/? [41:00<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3073/? [41:01<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3073/? [41:01<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3074/? [41:02<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3074/? [41:02<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3075/? [41:03<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3075/? [41:03<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3076/? [41:04<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3076/? [41:04<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3077/? [41:05<00:00,  1.25it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3077/? [41:05<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3078/? [41:06<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3078/? [41:06<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3079/? [41:07<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3079/? [41:07<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3080/? [41:08<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3080/? [41:08<00:00,  1.25it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3081/? [41:09<00:00,  1.25it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3081/? [41:09<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3082/? [41:10<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0108, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3082/? [41:10<00:00,  1.25it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3083/? [41:11<00:00,  1.25it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3083/? [41:11<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00806, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3084/? [41:12<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00806, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3084/? [41:13<00:00,  1.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3085/? [41:13<00:00,  1.25it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3085/? [41:14<00:00,  1.25it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3086/? [41:14<00:00,  1.25it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3086/? [41:15<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3087/? [41:15<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3087/? [41:16<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3088/? [41:16<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3088/? [41:17<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3089/? [41:17<00:00,  1.25it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0137, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3089/? [41:18<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3090/? [41:18<00:00,  1.25it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3090/? [41:19<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3091/? [41:19<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3091/? [41:20<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3092/? [41:20<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3092/? [41:21<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3093/? [41:21<00:00,  1.25it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3093/? [41:22<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3094/? [41:22<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3094/? [41:23<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3095/? [41:23<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3095/? [41:24<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0168, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3096/? [41:24<00:00,  1.25it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0168, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3096/? [41:25<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00951] 
Training: |          | 3097/? [41:25<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3097/? [41:26<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3098/? [41:26<00:00,  1.25it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3098/? [41:27<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0155, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3099/? [41:27<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0155, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3099/? [41:28<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3100/? [41:28<00:00,  1.25it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00951]
Training: |          | 3100/? [41:29<00:00,  1.25it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00951]

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Training: |          | 3100/? [41:36<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3101/? [41:36<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3101/? [41:37<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3102/? [41:37<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3102/? [41:38<00:00,  1.24it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3103/? [41:38<00:00,  1.24it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3103/? [41:39<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3104/? [41:39<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3104/? [41:40<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3105/? [41:40<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3105/? [41:41<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3106/? [41:41<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3106/? [41:42<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3107/? [41:42<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3107/? [41:43<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3108/? [41:44<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3108/? [41:44<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3109/? [41:45<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3109/? [41:45<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3110/? [41:46<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3110/? [41:46<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3111/? [41:47<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3111/? [41:47<00:00,  1.24it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0172, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3112/? [41:48<00:00,  1.24it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0172, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3112/? [41:48<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3113/? [41:49<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3113/? [41:49<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3114/? [41:50<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3114/? [41:50<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3115/? [41:51<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3115/? [41:51<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3116/? [41:52<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3116/? [41:52<00:00,  1.24it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3117/? [41:53<00:00,  1.24it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3117/? [41:53<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3118/? [41:54<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3118/? [41:54<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3119/? [41:55<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3119/? [41:55<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3120/? [41:56<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3120/? [41:56<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3121/? [41:57<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3121/? [41:57<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3122/? [41:58<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3122/? [41:58<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.017, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3123/? [41:59<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.017, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3123/? [41:59<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3124/? [42:00<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3124/? [42:01<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3125/? [42:01<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3125/? [42:02<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3126/? [42:02<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3126/? [42:03<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3127/? [42:03<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3127/? [42:04<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0127, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3128/? [42:04<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0127, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3128/? [42:05<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3129/? [42:05<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3129/? [42:06<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3130/? [42:06<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3130/? [42:07<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3131/? [42:07<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3131/? [42:08<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3132/? [42:08<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3132/? [42:09<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3133/? [42:09<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3133/? [42:10<00:00,  1.24it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3134/? [42:10<00:00,  1.24it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3134/? [42:11<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0101]  
Training: |          | 3135/? [42:11<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3135/? [42:12<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3136/? [42:12<00:00,  1.24it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3136/? [42:13<00:00,  1.24it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3137/? [42:13<00:00,  1.24it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3137/? [42:14<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3138/? [42:14<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3138/? [42:15<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3139/? [42:16<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3139/? [42:16<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0141, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3140/? [42:17<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0141, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3140/? [42:17<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3141/? [42:18<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3141/? [42:18<00:00,  1.24it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3142/? [42:19<00:00,  1.24it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3142/? [42:19<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0127, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3143/? [42:20<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0127, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3143/? [42:20<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3144/? [42:21<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3144/? [42:21<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3145/? [42:22<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0107, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3145/? [42:22<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3146/? [42:23<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3146/? [42:23<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3147/? [42:24<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3147/? [42:24<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3148/? [42:25<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3148/? [42:25<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3149/? [42:26<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3149/? [42:26<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3150/? [42:27<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.010, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3150/? [42:27<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3151/? [42:28<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3151/? [42:28<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3152/? [42:29<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3152/? [42:29<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3153/? [42:30<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3153/? [42:30<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0148, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3154/? [42:31<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0148, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3154/? [42:31<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3155/? [42:32<00:00,  1.24it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3155/? [42:32<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3156/? [42:33<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3156/? [42:33<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3157/? [42:34<00:00,  1.24it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0156, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3157/? [42:34<00:00,  1.24it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3158/? [42:35<00:00,  1.24it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3158/? [42:35<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3159/? [42:36<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3159/? [42:36<00:00,  1.24it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3160/? [42:37<00:00,  1.24it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3160/? [42:37<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3161/? [42:38<00:00,  1.24it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3161/? [42:39<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3162/? [42:39<00:00,  1.24it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3162/? [42:40<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3163/? [42:40<00:00,  1.24it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3163/? [42:41<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3164/? [42:41<00:00,  1.24it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3164/? [42:42<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3165/? [42:42<00:00,  1.24it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3165/? [42:43<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3166/? [42:43<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3166/? [42:44<00:00,  1.23it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3167/? [42:44<00:00,  1.23it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3167/? [42:45<00:00,  1.23it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3168/? [42:45<00:00,  1.23it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3168/? [42:46<00:00,  1.23it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3169/? [42:46<00:00,  1.23it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3169/? [42:47<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0168, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3170/? [42:47<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0168, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3170/? [42:48<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3171/? [42:48<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3171/? [42:49<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00818, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3172/? [42:49<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00818, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3172/? [42:50<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3173/? [42:50<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3173/? [42:51<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3174/? [42:51<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3174/? [42:52<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3175/? [42:52<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3175/? [42:53<00:00,  1.23it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3176/? [42:54<00:00,  1.23it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3176/? [42:54<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0141, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3177/? [42:55<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0141, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3177/? [42:55<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3178/? [42:56<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3178/? [42:56<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3179/? [42:57<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3179/? [42:57<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3180/? [42:58<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3180/? [42:58<00:00,  1.23it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0097, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3181/? [42:59<00:00,  1.23it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0097, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3181/? [42:59<00:00,  1.23it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3182/? [43:00<00:00,  1.23it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3182/? [43:00<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3183/? [43:01<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3183/? [43:01<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0173, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3184/? [43:02<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0173, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3184/? [43:02<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3185/? [43:03<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3185/? [43:03<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3186/? [43:04<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3186/? [43:04<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3187/? [43:05<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3187/? [43:05<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3188/? [43:06<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3188/? [43:06<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3189/? [43:07<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3189/? [43:07<00:00,  1.23it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3190/? [43:08<00:00,  1.23it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3190/? [43:08<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3191/? [43:09<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3191/? [43:09<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3192/? [43:10<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3192/? [43:10<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3193/? [43:11<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3193/? [43:11<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3194/? [43:12<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3194/? [43:12<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=17.60, val/top_5_accuracy=0.0101] 
Training: |          | 3195/? [43:13<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3195/? [43:13<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0154, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3196/? [43:14<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0154, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3196/? [43:14<00:00,  1.23it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3197/? [43:15<00:00,  1.23it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3197/? [43:16<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3198/? [43:16<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3198/? [43:17<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3199/? [43:17<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3199/? [43:18<00:00,  1.23it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0173, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3200/? [43:18<00:00,  1.23it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0173, val/loss=17.60, val/top_5_accuracy=0.0101]
Training: |          | 3200/? [43:19<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0101]

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Training: |          | 3200/? [43:25<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3201/? [43:26<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3201/? [43:26<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3202/? [43:27<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3202/? [43:27<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3203/? [43:28<00:00,  1.23it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3203/? [43:28<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3204/? [43:29<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3204/? [43:29<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3205/? [43:30<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3205/? [43:30<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3206/? [43:31<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3206/? [43:31<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3207/? [43:32<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3207/? [43:32<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3208/? [43:33<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3208/? [43:33<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3209/? [43:34<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3209/? [43:34<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3210/? [43:35<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3210/? [43:35<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3211/? [43:36<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3211/? [43:36<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3212/? [43:37<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3212/? [43:37<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3213/? [43:38<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3213/? [43:38<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3214/? [43:39<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3214/? [43:39<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3215/? [43:40<00:00,  1.23it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3215/? [43:40<00:00,  1.23it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3216/? [43:41<00:00,  1.23it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3216/? [43:41<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3217/? [43:42<00:00,  1.23it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3217/? [43:42<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3218/? [43:43<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3218/? [43:43<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3219/? [43:44<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3219/? [43:44<00:00,  1.23it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3220/? [43:45<00:00,  1.23it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3220/? [43:46<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3221/? [43:46<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3221/? [43:47<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3222/? [43:47<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3222/? [43:48<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3223/? [43:48<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3223/? [43:49<00:00,  1.23it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3224/? [43:49<00:00,  1.23it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3224/? [43:50<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3225/? [43:50<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3225/? [43:51<00:00,  1.23it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3226/? [43:51<00:00,  1.23it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3226/? [43:52<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3227/? [43:52<00:00,  1.23it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3227/? [43:53<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3228/? [43:53<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3228/? [43:54<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3229/? [43:54<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3229/? [43:55<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3230/? [43:55<00:00,  1.23it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3230/? [43:56<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3231/? [43:56<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3231/? [43:57<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3232/? [43:57<00:00,  1.23it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3232/? [43:58<00:00,  1.23it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3233/? [43:58<00:00,  1.23it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3233/? [43:59<00:00,  1.22it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3234/? [43:59<00:00,  1.23it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3234/? [44:00<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3235/? [44:00<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3235/? [44:01<00:00,  1.22it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00626, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3236/? [44:01<00:00,  1.22it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00626, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3236/? [44:02<00:00,  1.22it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0172, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3237/? [44:02<00:00,  1.22it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0172, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3237/? [44:03<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3238/? [44:03<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3238/? [44:04<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3239/? [44:04<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3239/? [44:05<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3240/? [44:06<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3240/? [44:06<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3241/? [44:07<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3241/? [44:07<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3242/? [44:08<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3242/? [44:08<00:00,  1.22it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0178, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3243/? [44:09<00:00,  1.22it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0178, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3243/? [44:09<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3244/? [44:10<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3244/? [44:10<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3245/? [44:11<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3245/? [44:11<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3246/? [44:12<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3246/? [44:12<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3247/? [44:13<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3247/? [44:13<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3248/? [44:14<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3248/? [44:14<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3249/? [44:15<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3249/? [44:15<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3250/? [44:16<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3250/? [44:16<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3251/? [44:17<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3251/? [44:17<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3252/? [44:18<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3252/? [44:18<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3253/? [44:19<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3253/? [44:19<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3254/? [44:20<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3254/? [44:20<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3255/? [44:21<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3255/? [44:21<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3256/? [44:22<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3256/? [44:22<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3257/? [44:23<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3257/? [44:23<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3258/? [44:24<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3258/? [44:24<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3259/? [44:25<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3259/? [44:25<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3260/? [44:26<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3260/? [44:27<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3261/? [44:27<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3261/? [44:28<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3262/? [44:28<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3262/? [44:29<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3263/? [44:29<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3263/? [44:30<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3264/? [44:30<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3264/? [44:31<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3265/? [44:31<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3265/? [44:32<00:00,  1.22it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3266/? [44:32<00:00,  1.22it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3266/? [44:33<00:00,  1.22it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3267/? [44:33<00:00,  1.22it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3267/? [44:34<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3268/? [44:34<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3268/? [44:35<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3269/? [44:35<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3269/? [44:36<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3270/? [44:36<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3270/? [44:37<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3271/? [44:37<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3271/? [44:38<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3272/? [44:38<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3272/? [44:39<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3273/? [44:40<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3273/? [44:40<00:00,  1.22it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0178, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3274/? [44:41<00:00,  1.22it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0178, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3274/? [44:41<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3275/? [44:42<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3275/? [44:42<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3276/? [44:43<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3276/? [44:43<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3277/? [44:44<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3277/? [44:44<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3278/? [44:45<00:00,  1.22it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3278/? [44:45<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3279/? [44:46<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3279/? [44:46<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3280/? [44:47<00:00,  1.22it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3280/? [44:47<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3281/? [44:48<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3281/? [44:48<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3282/? [44:49<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3282/? [44:49<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3283/? [44:50<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3283/? [44:50<00:00,  1.22it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3284/? [44:51<00:00,  1.22it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3284/? [44:51<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3285/? [44:52<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3285/? [44:52<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3286/? [44:53<00:00,  1.22it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00928, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3286/? [44:53<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3287/? [44:54<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3287/? [44:54<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3288/? [44:55<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3288/? [44:55<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3289/? [44:56<00:00,  1.22it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3289/? [44:56<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3290/? [44:57<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3290/? [44:57<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3291/? [44:58<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3291/? [44:58<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3292/? [44:59<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3292/? [44:59<00:00,  1.22it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0194, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3293/? [45:00<00:00,  1.22it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0194, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3293/? [45:00<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3294/? [45:01<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3294/? [45:02<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3295/? [45:02<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3295/? [45:03<00:00,  1.22it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00985]  
Training: |          | 3296/? [45:03<00:00,  1.22it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3296/? [45:04<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3297/? [45:04<00:00,  1.22it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3297/? [45:05<00:00,  1.22it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0188, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3298/? [45:05<00:00,  1.22it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0188, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3298/? [45:06<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3299/? [45:06<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3299/? [45:07<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985] 
Training: |          | 3300/? [45:07<00:00,  1.22it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00985]
Training: |          | 3300/? [45:08<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00985]

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Training: |          | 3300/? [45:16<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3301/? [45:16<00:00,  1.22it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3301/? [45:17<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3302/? [45:17<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3302/? [45:18<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3303/? [45:18<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3303/? [45:19<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3304/? [45:19<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3304/? [45:20<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3305/? [45:20<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3305/? [45:21<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3306/? [45:21<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3306/? [45:22<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3307/? [45:22<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3307/? [45:23<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3308/? [45:23<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3308/? [45:24<00:00,  1.21it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00934, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3309/? [45:24<00:00,  1.21it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00934, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3309/? [45:25<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3310/? [45:25<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3310/? [45:26<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3311/? [45:27<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3311/? [45:27<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3312/? [45:28<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3312/? [45:28<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3313/? [45:29<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3313/? [45:29<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3314/? [45:30<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3314/? [45:30<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3315/? [45:31<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3315/? [45:31<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3316/? [45:32<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3316/? [45:32<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3317/? [45:33<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3317/? [45:33<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3318/? [45:34<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3318/? [45:34<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3319/? [45:35<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3319/? [45:35<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0175, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3320/? [45:36<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0175, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3320/? [45:36<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0131, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3321/? [45:37<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0131, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3321/? [45:37<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3322/? [45:38<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3322/? [45:38<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3323/? [45:39<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3323/? [45:39<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3324/? [45:40<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3324/? [45:40<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3325/? [45:41<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3325/? [45:42<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3326/? [45:42<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3326/? [45:43<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3327/? [45:43<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3327/? [45:44<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3328/? [45:44<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3328/? [45:45<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3329/? [45:45<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3329/? [45:46<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3330/? [45:46<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3330/? [45:47<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3331/? [45:47<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3331/? [45:48<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3332/? [45:48<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.010, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3332/? [45:49<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3333/? [45:49<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0123, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3333/? [45:50<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3334/? [45:50<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3334/? [45:51<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3335/? [45:51<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3335/? [45:52<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3336/? [45:52<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3336/? [45:53<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.00946, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3337/? [45:53<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.00946, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3337/? [45:54<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3338/? [45:54<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3338/? [45:55<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3339/? [45:55<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3339/? [45:56<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0164, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3340/? [45:57<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0164, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3340/? [45:57<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3341/? [45:58<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3341/? [45:58<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3342/? [45:59<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3342/? [45:59<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3343/? [46:00<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3343/? [46:00<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3344/? [46:01<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3344/? [46:01<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3345/? [46:02<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3345/? [46:02<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3346/? [46:03<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3346/? [46:03<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3347/? [46:04<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3347/? [46:04<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3348/? [46:05<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3348/? [46:05<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3349/? [46:06<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3349/? [46:06<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3350/? [46:07<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3350/? [46:07<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3351/? [46:08<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3351/? [46:08<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3352/? [46:09<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3352/? [46:09<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3353/? [46:10<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3353/? [46:10<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3354/? [46:11<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3354/? [46:11<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3355/? [46:12<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3355/? [46:12<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3356/? [46:13<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3356/? [46:13<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3357/? [46:14<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3357/? [46:14<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3358/? [46:15<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3358/? [46:15<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3359/? [46:16<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3359/? [46:17<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0183, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3360/? [46:17<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0183, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3360/? [46:18<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3361/? [46:18<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3361/? [46:19<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0162, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3362/? [46:19<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0162, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3362/? [46:20<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3363/? [46:20<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3363/? [46:21<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3364/? [46:21<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3364/? [46:22<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3365/? [46:22<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3365/? [46:23<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0188, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3366/? [46:23<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0188, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3366/? [46:24<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3367/? [46:24<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3367/? [46:25<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3368/? [46:25<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3368/? [46:26<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3369/? [46:26<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3369/? [46:27<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.012, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3370/? [46:27<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.012, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3370/? [46:28<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3371/? [46:28<00:00,  1.21it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0153, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3371/? [46:29<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3372/? [46:29<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3372/? [46:30<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3373/? [46:30<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3373/? [46:31<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3374/? [46:32<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3374/? [46:32<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3375/? [46:33<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3375/? [46:33<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3376/? [46:34<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3376/? [46:34<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3377/? [46:35<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0126, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3377/? [46:35<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3378/? [46:36<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3378/? [46:36<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3379/? [46:37<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3379/? [46:37<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3380/? [46:38<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3380/? [46:38<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3381/? [46:39<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3381/? [46:39<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3382/? [46:40<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.011, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3382/? [46:40<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3383/? [46:41<00:00,  1.21it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3383/? [46:41<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0171, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3384/? [46:42<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0171, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3384/? [46:42<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3385/? [46:43<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3385/? [46:43<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.0107] 
Training: |          | 3386/? [46:44<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3386/? [46:44<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.017, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3387/? [46:45<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.017, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3387/? [46:45<00:00,  1.21it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0168, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3388/? [46:46<00:00,  1.21it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0168, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3388/? [46:46<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3389/? [46:47<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3389/? [46:47<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3390/? [46:48<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3390/? [46:48<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3391/? [46:49<00:00,  1.21it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3391/? [46:49<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3392/? [46:50<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3392/? [46:50<00:00,  1.21it/s, v_num=2, train/loss=15.40, train/top_5_accuracy=0.0249, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3393/? [46:51<00:00,  1.21it/s, v_num=2, train/loss=15.40, train/top_5_accuracy=0.0249, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3393/? [46:52<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3394/? [46:52<00:00,  1.21it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3394/? [46:53<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3395/? [46:53<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3395/? [46:54<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3396/? [46:54<00:00,  1.21it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3396/? [46:55<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3397/? [46:55<00:00,  1.21it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3397/? [46:56<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0139, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3398/? [46:56<00:00,  1.21it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0139, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3398/? [46:57<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3399/? [46:57<00:00,  1.21it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3399/? [46:58<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3400/? [46:58<00:00,  1.21it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.50, val/top_5_accuracy=0.0107]
Training: |          | 3400/? [46:59<00:00,  1.21it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=17.50, val/top_5_accuracy=0.0107]

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Training: |          | 3400/? [47:05<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3401/? [47:05<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3401/? [47:06<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3402/? [47:06<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3402/? [47:07<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3403/? [47:07<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3403/? [47:08<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3404/? [47:08<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3404/? [47:09<00:00,  1.20it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3405/? [47:09<00:00,  1.20it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3405/? [47:10<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3406/? [47:10<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3406/? [47:11<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3407/? [47:12<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3407/? [47:12<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3408/? [47:13<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3408/? [47:13<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3409/? [47:14<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3409/? [47:14<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3410/? [47:15<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3410/? [47:15<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3411/? [47:16<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3411/? [47:16<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3412/? [47:17<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3412/? [47:17<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3413/? [47:18<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3413/? [47:18<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3414/? [47:19<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3414/? [47:19<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3415/? [47:20<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3415/? [47:20<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3416/? [47:21<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3416/? [47:21<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3417/? [47:22<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3417/? [47:22<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3418/? [47:23<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3418/? [47:23<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3419/? [47:24<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3419/? [47:24<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3420/? [47:25<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3420/? [47:25<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3421/? [47:26<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3421/? [47:26<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3422/? [47:27<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3422/? [47:27<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3423/? [47:28<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3423/? [47:28<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3424/? [47:29<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3424/? [47:29<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3425/? [47:30<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3425/? [47:30<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3426/? [47:31<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3426/? [47:31<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3427/? [47:32<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3427/? [47:32<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3428/? [47:33<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3428/? [47:33<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3429/? [47:34<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3429/? [47:35<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3430/? [47:35<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3430/? [47:36<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3431/? [47:36<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3431/? [47:37<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0181, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3432/? [47:37<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0181, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3432/? [47:38<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3433/? [47:38<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3433/? [47:39<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3434/? [47:39<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3434/? [47:40<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3435/? [47:40<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3435/? [47:41<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3436/? [47:41<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3436/? [47:42<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3437/? [47:42<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3437/? [47:43<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3438/? [47:43<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3438/? [47:44<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3439/? [47:44<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3439/? [47:45<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3440/? [47:45<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3440/? [47:46<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3441/? [47:46<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3441/? [47:47<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3442/? [47:47<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3442/? [47:48<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3443/? [47:48<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3443/? [47:49<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3444/? [47:49<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3444/? [47:50<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3445/? [47:51<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3445/? [47:51<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3446/? [47:52<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3446/? [47:52<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3447/? [47:53<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3447/? [47:53<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3448/? [47:54<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3448/? [47:54<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3449/? [47:55<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3449/? [47:55<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3450/? [47:56<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3450/? [47:56<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3451/? [47:57<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3451/? [47:57<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3452/? [47:58<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3452/? [47:58<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3453/? [47:59<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3453/? [47:59<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3454/? [48:00<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3454/? [48:00<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3455/? [48:01<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3455/? [48:01<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0179, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3456/? [48:02<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0179, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3456/? [48:02<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00909, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3457/? [48:03<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00909, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3457/? [48:03<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3458/? [48:04<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3458/? [48:04<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3459/? [48:05<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3459/? [48:05<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3460/? [48:06<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3460/? [48:06<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0171, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3461/? [48:07<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0171, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3461/? [48:07<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3462/? [48:08<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3462/? [48:08<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3463/? [48:09<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3463/? [48:09<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3464/? [48:10<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3464/? [48:10<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3465/? [48:11<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3465/? [48:12<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3466/? [48:12<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3466/? [48:13<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3467/? [48:13<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3467/? [48:14<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3468/? [48:14<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3468/? [48:15<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3469/? [48:15<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3469/? [48:16<00:00,  1.20it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0072, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3470/? [48:16<00:00,  1.20it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0072, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3470/? [48:17<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3471/? [48:17<00:00,  1.20it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3471/? [48:18<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3472/? [48:18<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3472/? [48:19<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3473/? [48:19<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3473/? [48:20<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3474/? [48:20<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3474/? [48:21<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0144, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3475/? [48:21<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0144, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3475/? [48:22<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3476/? [48:22<00:00,  1.20it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3476/? [48:23<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0173, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3477/? [48:23<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0173, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3477/? [48:24<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3478/? [48:24<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3478/? [48:25<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3479/? [48:25<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3479/? [48:26<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3480/? [48:27<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3480/? [48:27<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3481/? [48:28<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3481/? [48:28<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3482/? [48:29<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3482/? [48:29<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.00934, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3483/? [48:30<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.00934, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3483/? [48:30<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3484/? [48:31<00:00,  1.20it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3484/? [48:31<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3485/? [48:32<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3485/? [48:32<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3486/? [48:33<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3486/? [48:33<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3487/? [48:34<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3487/? [48:34<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3488/? [48:35<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3488/? [48:35<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3489/? [48:36<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3489/? [48:36<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3490/? [48:37<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3490/? [48:37<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3491/? [48:38<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3491/? [48:38<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3492/? [48:39<00:00,  1.20it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3492/? [48:39<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3493/? [48:40<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3493/? [48:40<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3494/? [48:41<00:00,  1.20it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3494/? [48:41<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3495/? [48:42<00:00,  1.20it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3495/? [48:42<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00943] 
Training: |          | 3496/? [48:43<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3496/? [48:43<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3497/? [48:44<00:00,  1.20it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3497/? [48:44<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3498/? [48:45<00:00,  1.20it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3498/? [48:45<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3499/? [48:46<00:00,  1.20it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3499/? [48:46<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3500/? [48:47<00:00,  1.20it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00943]
Training: |          | 3500/? [48:48<00:00,  1.20it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=17.90, val/top_5_accuracy=0.00943]

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Training: |          | 3500/? [48:53<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3501/? [48:53<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0105, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3501/? [48:54<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3502/? [48:54<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3502/? [48:55<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3503/? [48:55<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3503/? [48:56<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3504/? [48:56<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3504/? [48:57<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3505/? [48:57<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3505/? [48:58<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3506/? [48:58<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3506/? [48:59<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3507/? [48:59<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0144, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3507/? [49:00<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3508/? [49:00<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3508/? [49:01<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3509/? [49:01<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3509/? [49:02<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3510/? [49:02<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3510/? [49:03<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3511/? [49:03<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3511/? [49:04<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3512/? [49:04<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3512/? [49:05<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3513/? [49:05<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3513/? [49:06<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3514/? [49:06<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3514/? [49:07<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3515/? [49:07<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3515/? [49:08<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3516/? [49:09<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3516/? [49:09<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3517/? [49:10<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3517/? [49:10<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3518/? [49:11<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3518/? [49:11<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3519/? [49:12<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3519/? [49:12<00:00,  1.19it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0167, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3520/? [49:13<00:00,  1.19it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0167, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3520/? [49:13<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3521/? [49:14<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3521/? [49:14<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3522/? [49:15<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3522/? [49:15<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3523/? [49:16<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3523/? [49:16<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3524/? [49:17<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3524/? [49:17<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3525/? [49:18<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3525/? [49:18<00:00,  1.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3526/? [49:19<00:00,  1.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3526/? [49:19<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3527/? [49:20<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3527/? [49:20<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3528/? [49:21<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3528/? [49:21<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3529/? [49:22<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3529/? [49:22<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3530/? [49:23<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3530/? [49:23<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3531/? [49:24<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3531/? [49:24<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3532/? [49:25<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3532/? [49:25<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3533/? [49:26<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3533/? [49:26<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3534/? [49:27<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3534/? [49:27<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3535/? [49:28<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00989, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3535/? [49:29<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3536/? [49:29<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3536/? [49:30<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3537/? [49:30<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3537/? [49:31<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3538/? [49:31<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3538/? [49:32<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3539/? [49:32<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0162, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3539/? [49:33<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3540/? [49:33<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3540/? [49:34<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3541/? [49:34<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3541/? [49:35<00:00,  1.19it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0167, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3542/? [49:35<00:00,  1.19it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0167, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3542/? [49:36<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3543/? [49:36<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3543/? [49:37<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3544/? [49:37<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3544/? [49:38<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0154, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3545/? [49:38<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0154, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3545/? [49:39<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3546/? [49:39<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3546/? [49:40<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3547/? [49:40<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3547/? [49:41<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3548/? [49:41<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3548/? [49:42<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3549/? [49:42<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0128, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3549/? [49:43<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3550/? [49:43<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3550/? [49:44<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3551/? [49:44<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3551/? [49:45<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3552/? [49:45<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3552/? [49:46<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3553/? [49:46<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3553/? [49:47<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3554/? [49:47<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3554/? [49:48<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3555/? [49:49<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0138, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3555/? [49:49<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3556/? [49:50<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3556/? [49:50<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3557/? [49:51<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3557/? [49:51<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3558/? [49:52<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3558/? [49:52<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3559/? [49:53<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3559/? [49:53<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3560/? [49:54<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3560/? [49:54<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3561/? [49:55<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3561/? [49:55<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3562/? [49:56<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3562/? [49:56<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3563/? [49:57<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3563/? [49:57<00:00,  1.19it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00623, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3564/? [49:58<00:00,  1.19it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00623, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3564/? [49:58<00:00,  1.19it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3565/? [49:59<00:00,  1.19it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3565/? [49:59<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3566/? [50:00<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0109, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3566/? [50:00<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3567/? [50:01<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3567/? [50:01<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3568/? [50:02<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3568/? [50:02<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3569/? [50:03<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3569/? [50:03<00:00,  1.19it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3570/? [50:04<00:00,  1.19it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3570/? [50:04<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3571/? [50:05<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0143, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3571/? [50:05<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3572/? [50:06<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3572/? [50:06<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3573/? [50:07<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3573/? [50:07<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3574/? [50:08<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3574/? [50:08<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3575/? [50:09<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3575/? [50:09<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3576/? [50:10<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3576/? [50:10<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3577/? [50:11<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3577/? [50:11<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3578/? [50:12<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3578/? [50:12<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3579/? [50:13<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3579/? [50:13<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0164, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3580/? [50:14<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0164, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3580/? [50:15<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3581/? [50:15<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3581/? [50:16<00:00,  1.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3582/? [50:16<00:00,  1.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3582/? [50:17<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3583/? [50:17<00:00,  1.19it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3583/? [50:18<00:00,  1.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3584/? [50:18<00:00,  1.19it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3584/? [50:19<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3585/? [50:19<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0127, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3585/? [50:20<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3586/? [50:20<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3586/? [50:21<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3587/? [50:21<00:00,  1.19it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3587/? [50:22<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3588/? [50:22<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3588/? [50:23<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3589/? [50:23<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3589/? [50:24<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3590/? [50:24<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0157, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3590/? [50:25<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3591/? [50:25<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3591/? [50:26<00:00,  1.19it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.019, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3592/? [50:26<00:00,  1.19it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.019, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3592/? [50:27<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3593/? [50:27<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3593/? [50:28<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3594/? [50:28<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.016, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3594/? [50:29<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3595/? [50:29<00:00,  1.19it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3595/? [50:30<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0155, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3596/? [50:30<00:00,  1.19it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0155, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3596/? [50:31<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00998] 
Training: |          | 3597/? [50:32<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3597/? [50:32<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3598/? [50:33<00:00,  1.19it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3598/? [50:33<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3599/? [50:34<00:00,  1.19it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3599/? [50:34<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0177, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3600/? [50:35<00:00,  1.19it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0177, val/loss=18.20, val/top_5_accuracy=0.00998]
Training: |          | 3600/? [50:35<00:00,  1.19it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.20, val/top_5_accuracy=0.00998] 

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Training: |          | 3600/? [50:42<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3601/? [50:43<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3601/? [50:43<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3602/? [50:44<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3602/? [50:45<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3603/? [50:45<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3603/? [50:46<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3604/? [50:46<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3604/? [50:47<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3605/? [50:47<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3605/? [50:48<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3606/? [50:48<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3606/? [50:49<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3607/? [50:49<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3607/? [50:50<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3608/? [50:50<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3608/? [50:51<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3609/? [50:51<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3609/? [50:52<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3610/? [50:52<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3610/? [50:53<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3611/? [50:53<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3611/? [50:54<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3612/? [50:54<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3612/? [50:55<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3613/? [50:55<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3613/? [50:56<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3614/? [50:56<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3614/? [50:57<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3615/? [50:57<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00854, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3615/? [50:58<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104]  
Training: |          | 3616/? [50:58<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3616/? [50:59<00:00,  1.18it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0192, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3617/? [51:00<00:00,  1.18it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0192, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3617/? [51:00<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3618/? [51:01<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3618/? [51:01<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0142, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3619/? [51:02<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0142, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3619/? [51:02<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3620/? [51:03<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3620/? [51:03<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3621/? [51:04<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3621/? [51:04<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3622/? [51:05<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3622/? [51:05<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3623/? [51:06<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0116, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3623/? [51:06<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3624/? [51:07<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3624/? [51:07<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0155, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3625/? [51:08<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0155, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3625/? [51:08<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3626/? [51:09<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3626/? [51:09<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3627/? [51:10<00:00,  1.18it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3627/? [51:10<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3628/? [51:11<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3628/? [51:11<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3629/? [51:12<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3629/? [51:12<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3630/? [51:13<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3630/? [51:13<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3631/? [51:14<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3631/? [51:14<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0152, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3632/? [51:15<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0152, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3632/? [51:15<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3633/? [51:16<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3633/? [51:17<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3634/? [51:17<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3634/? [51:17<00:00,  1.18it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0177, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3635/? [51:18<00:00,  1.18it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0177, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3635/? [51:19<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0147, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3636/? [51:19<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0147, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3636/? [51:20<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3637/? [51:20<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3637/? [51:21<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3638/? [51:21<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.013, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3638/? [51:22<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3639/? [51:22<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3639/? [51:23<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3640/? [51:23<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3640/? [51:24<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3641/? [51:24<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3641/? [51:25<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3642/? [51:25<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3642/? [51:26<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3643/? [51:26<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3643/? [51:27<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3644/? [51:27<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0102, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3644/? [51:28<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3645/? [51:28<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3645/? [51:29<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3646/? [51:29<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3646/? [51:30<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3647/? [51:30<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3647/? [51:31<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3648/? [51:31<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3648/? [51:32<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3649/? [51:32<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3649/? [51:33<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3650/? [51:33<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3650/? [51:34<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3651/? [51:34<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3651/? [51:35<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3652/? [51:36<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3652/? [51:36<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3653/? [51:37<00:00,  1.18it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00885, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3653/? [51:37<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3654/? [51:38<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3654/? [51:38<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3655/? [51:39<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3655/? [51:39<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3656/? [51:40<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3656/? [51:40<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3657/? [51:41<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3657/? [51:41<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3658/? [51:42<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3658/? [51:42<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3659/? [51:43<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3659/? [51:43<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3660/? [51:44<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3660/? [51:44<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3661/? [51:45<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3661/? [51:45<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3662/? [51:46<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3662/? [51:46<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3663/? [51:47<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3663/? [51:47<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3664/? [51:48<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3664/? [51:48<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3665/? [51:49<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3665/? [51:49<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3666/? [51:50<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3666/? [51:50<00:00,  1.18it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.017, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3667/? [51:51<00:00,  1.18it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.017, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3667/? [51:51<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3668/? [51:52<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3668/? [51:52<00:00,  1.18it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3669/? [51:53<00:00,  1.18it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3669/? [51:53<00:00,  1.18it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3670/? [51:54<00:00,  1.18it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3670/? [51:54<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3671/? [51:55<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3671/? [51:56<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3672/? [51:56<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3672/? [51:57<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3673/? [51:57<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3673/? [51:58<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3674/? [51:58<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3674/? [51:59<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3675/? [51:59<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.011, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3675/? [52:00<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3676/? [52:00<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3676/? [52:01<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0151, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3677/? [52:01<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0151, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3677/? [52:02<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3678/? [52:02<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3678/? [52:03<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3679/? [52:03<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3679/? [52:04<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3680/? [52:04<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3680/? [52:05<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3681/? [52:05<00:00,  1.18it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3681/? [52:06<00:00,  1.18it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00879, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3682/? [52:06<00:00,  1.18it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00879, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3682/? [52:07<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3683/? [52:07<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3683/? [52:08<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3684/? [52:08<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3684/? [52:09<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3685/? [52:09<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3685/? [52:10<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3686/? [52:10<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3686/? [52:11<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3687/? [52:12<00:00,  1.18it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3687/? [52:12<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3688/? [52:13<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3688/? [52:13<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3689/? [52:14<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0142, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3689/? [52:14<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3690/? [52:15<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0167, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3690/? [52:15<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3691/? [52:16<00:00,  1.18it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3691/? [52:16<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3692/? [52:17<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3692/? [52:17<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3693/? [52:18<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3693/? [52:18<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0171, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3694/? [52:19<00:00,  1.18it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0171, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3694/? [52:19<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3695/? [52:20<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3695/? [52:20<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3696/? [52:21<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0136, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3696/? [52:21<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3697/? [52:22<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3697/? [52:22<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3698/? [52:23<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.015, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3698/? [52:23<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3699/? [52:24<00:00,  1.18it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3699/? [52:24<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104] 
Training: |          | 3700/? [52:25<00:00,  1.18it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.012, val/loss=17.60, val/top_5_accuracy=0.0104]
Training: |          | 3700/? [52:25<00:00,  1.18it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=17.60, val/top_5_accuracy=0.0104]

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Training: |          | 3700/? [52:30<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3701/? [52:31<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3701/? [52:31<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3702/? [52:32<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3702/? [52:32<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3703/? [52:33<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3703/? [52:33<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3704/? [52:34<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3704/? [52:34<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3705/? [52:35<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3705/? [52:35<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3706/? [52:36<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3706/? [52:36<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3707/? [52:37<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3707/? [52:38<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3708/? [52:38<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3708/? [52:39<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3709/? [52:39<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3709/? [52:40<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3710/? [52:40<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3710/? [52:41<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3711/? [52:41<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3711/? [52:42<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3712/? [52:42<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3712/? [52:43<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3713/? [52:43<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0131, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3713/? [52:44<00:00,  1.17it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0184, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3714/? [52:44<00:00,  1.17it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0184, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3714/? [52:45<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3715/? [52:45<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3715/? [52:46<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3716/? [52:46<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3716/? [52:47<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3717/? [52:47<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3717/? [52:48<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3718/? [52:48<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3718/? [52:49<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3719/? [52:49<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3719/? [52:50<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3720/? [52:50<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3720/? [52:51<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3721/? [52:51<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3721/? [52:52<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3722/? [52:52<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3722/? [52:53<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3723/? [52:53<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3723/? [52:54<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3724/? [52:54<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3724/? [52:55<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3725/? [52:56<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3725/? [52:56<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3726/? [52:57<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00842, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3726/? [52:57<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3727/? [52:58<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3727/? [52:58<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3728/? [52:59<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3728/? [52:59<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3729/? [53:00<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3729/? [53:00<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3730/? [53:01<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3730/? [53:01<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3731/? [53:02<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3731/? [53:02<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3732/? [53:03<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3732/? [53:03<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0141, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3733/? [53:04<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0141, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3733/? [53:04<00:00,  1.17it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3734/? [53:05<00:00,  1.17it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3734/? [53:05<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3735/? [53:06<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3735/? [53:06<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3736/? [53:07<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3736/? [53:07<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3737/? [53:08<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3737/? [53:08<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3738/? [53:09<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3738/? [53:09<00:00,  1.17it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3739/? [53:10<00:00,  1.17it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3739/? [53:10<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3740/? [53:11<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3740/? [53:11<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3741/? [53:12<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3741/? [53:12<00:00,  1.17it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3742/? [53:13<00:00,  1.17it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3742/? [53:13<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3743/? [53:14<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3743/? [53:14<00:00,  1.17it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0199, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3744/? [53:15<00:00,  1.17it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0199, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3744/? [53:15<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3745/? [53:16<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3745/? [53:17<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3746/? [53:17<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3746/? [53:18<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3747/? [53:18<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3747/? [53:19<00:00,  1.17it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0151, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3748/? [53:19<00:00,  1.17it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0151, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3748/? [53:20<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3749/? [53:20<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3749/? [53:21<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3750/? [53:21<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3750/? [53:22<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3751/? [53:22<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3751/? [53:23<00:00,  1.17it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0217, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3752/? [53:23<00:00,  1.17it/s, v_num=2, train/loss=15.60, train/top_5_accuracy=0.0217, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3752/? [53:24<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3753/? [53:24<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3753/? [53:25<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3754/? [53:25<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.013, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3754/? [53:26<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3755/? [53:26<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3755/? [53:27<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3756/? [53:27<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3756/? [53:28<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3757/? [53:28<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3757/? [53:29<00:00,  1.17it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3758/? [53:29<00:00,  1.17it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3758/? [53:30<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3759/? [53:31<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3759/? [53:31<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3760/? [53:32<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3760/? [53:32<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3761/? [53:33<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3761/? [53:33<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3762/? [53:34<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3762/? [53:34<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3763/? [53:35<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3763/? [53:35<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3764/? [53:36<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3764/? [53:36<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3765/? [53:37<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3765/? [53:37<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3766/? [53:38<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0106, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3766/? [53:38<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3767/? [53:39<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3767/? [53:39<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3768/? [53:40<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3768/? [53:40<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3769/? [53:41<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3769/? [53:41<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3770/? [53:42<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3770/? [53:42<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3771/? [53:43<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3771/? [53:43<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3772/? [53:44<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3772/? [53:44<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.015, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3773/? [53:45<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.015, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3773/? [53:45<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3774/? [53:46<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0133, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3774/? [53:46<00:00,  1.17it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00806, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3775/? [53:47<00:00,  1.17it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00806, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3775/? [53:47<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3776/? [53:48<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3776/? [53:48<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3777/? [53:49<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0123, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3777/? [53:49<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0165, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3778/? [53:50<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0165, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3778/? [53:50<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3779/? [53:51<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3779/? [53:51<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3780/? [53:52<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3780/? [53:52<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3781/? [53:53<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3781/? [53:53<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3782/? [53:54<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3782/? [53:55<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3783/? [53:55<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3783/? [53:56<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3784/? [53:56<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3784/? [53:57<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3785/? [53:57<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0111, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3785/? [53:58<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3786/? [53:58<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3786/? [53:59<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3787/? [53:59<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3787/? [54:00<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3788/? [54:00<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3788/? [54:01<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3789/? [54:01<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3789/? [54:02<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3790/? [54:02<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3790/? [54:03<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3791/? [54:03<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3791/? [54:04<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3792/? [54:04<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3792/? [54:05<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3793/? [54:05<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3793/? [54:06<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0141, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3794/? [54:06<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0141, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3794/? [54:07<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3795/? [54:07<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3795/? [54:08<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3796/? [54:09<00:00,  1.17it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3796/? [54:09<00:00,  1.17it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3797/? [54:10<00:00,  1.17it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3797/? [54:10<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00901] 
Training: |          | 3798/? [54:11<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0152, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3798/? [54:11<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3799/? [54:12<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3799/? [54:12<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0175, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3800/? [54:13<00:00,  1.17it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0175, val/loss=18.30, val/top_5_accuracy=0.00901]
Training: |          | 3800/? [54:13<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.30, val/top_5_accuracy=0.00901]

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Training: |          | 3800/? [54:19<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3801/? [54:20<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3801/? [54:20<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3802/? [54:21<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3802/? [54:21<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3803/? [54:22<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3803/? [54:22<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3804/? [54:23<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3804/? [54:23<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3805/? [54:24<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3805/? [54:24<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3806/? [54:25<00:00,  1.17it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3806/? [54:26<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3807/? [54:26<00:00,  1.17it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3807/? [54:27<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3808/? [54:27<00:00,  1.17it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3808/? [54:28<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3809/? [54:28<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3809/? [54:29<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3810/? [54:29<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3810/? [54:30<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3811/? [54:30<00:00,  1.17it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3811/? [54:31<00:00,  1.17it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0161, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3812/? [54:31<00:00,  1.17it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0161, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3812/? [54:32<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3813/? [54:32<00:00,  1.17it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3813/? [54:33<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3814/? [54:33<00:00,  1.17it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3814/? [54:34<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3815/? [54:34<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3815/? [54:35<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3816/? [54:35<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3816/? [54:36<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3817/? [54:36<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3817/? [54:37<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3818/? [54:37<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3818/? [54:38<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3819/? [54:38<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3819/? [54:39<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3820/? [54:39<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3820/? [54:40<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3821/? [54:40<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3821/? [54:41<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3822/? [54:42<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3822/? [54:42<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3823/? [54:43<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3823/? [54:43<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3824/? [54:44<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3824/? [54:44<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3825/? [54:45<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3825/? [54:45<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3826/? [54:46<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3826/? [54:46<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3827/? [54:47<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3827/? [54:47<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3828/? [54:48<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3828/? [54:48<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3829/? [54:49<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3829/? [54:49<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3830/? [54:50<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3830/? [54:50<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3831/? [54:51<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3831/? [54:51<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3832/? [54:52<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3832/? [54:52<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3833/? [54:53<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3833/? [54:53<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0147, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3834/? [54:54<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0147, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3834/? [54:54<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3835/? [54:55<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3835/? [54:55<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3836/? [54:56<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3836/? [54:56<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3837/? [54:57<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3837/? [54:57<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3838/? [54:58<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3838/? [54:58<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3839/? [54:59<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3839/? [54:59<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3840/? [55:00<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3840/? [55:00<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3841/? [55:01<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3841/? [55:01<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3842/? [55:02<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3842/? [55:02<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3843/? [55:03<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3843/? [55:04<00:00,  1.16it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3844/? [55:04<00:00,  1.16it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3844/? [55:05<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3845/? [55:05<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3845/? [55:06<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3846/? [55:06<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3846/? [55:07<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3847/? [55:07<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3847/? [55:08<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3848/? [55:08<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3848/? [55:09<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3849/? [55:09<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3849/? [55:10<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3850/? [55:10<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3850/? [55:11<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3851/? [55:11<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3851/? [55:12<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3852/? [55:12<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3852/? [55:13<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3853/? [55:13<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3853/? [55:14<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3854/? [55:14<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3854/? [55:15<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3855/? [55:15<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3855/? [55:16<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3856/? [55:16<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3856/? [55:17<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3857/? [55:17<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3857/? [55:18<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3858/? [55:18<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3858/? [55:19<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3859/? [55:19<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3859/? [55:20<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0141, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3860/? [55:21<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0141, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3860/? [55:21<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3861/? [55:22<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3861/? [55:22<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3862/? [55:23<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3862/? [55:23<00:00,  1.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3863/? [55:24<00:00,  1.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3863/? [55:24<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3864/? [55:25<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3864/? [55:25<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0138, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3865/? [55:26<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0138, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3865/? [55:26<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3866/? [55:27<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3866/? [55:27<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3867/? [55:28<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3867/? [55:28<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3868/? [55:29<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00958, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3868/? [55:29<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3869/? [55:30<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3869/? [55:30<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3870/? [55:31<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3870/? [55:31<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3871/? [55:32<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3871/? [55:32<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3872/? [55:33<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3872/? [55:33<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3873/? [55:34<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3873/? [55:34<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3874/? [55:35<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3874/? [55:35<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0152, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3875/? [55:36<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0152, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3875/? [55:36<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3876/? [55:37<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3876/? [55:37<00:00,  1.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3877/? [55:38<00:00,  1.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3877/? [55:38<00:00,  1.16it/s, v_num=2, train/loss=15.50, train/top_5_accuracy=0.0308, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3878/? [55:39<00:00,  1.16it/s, v_num=2, train/loss=15.50, train/top_5_accuracy=0.0308, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3878/? [55:39<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3879/? [55:40<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3879/? [55:40<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3880/? [55:41<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3880/? [55:41<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3881/? [55:42<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3881/? [55:42<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3882/? [55:43<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3882/? [55:44<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3883/? [55:44<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3883/? [55:45<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3884/? [55:45<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3884/? [55:46<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3885/? [55:46<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3885/? [55:47<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3886/? [55:47<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3886/? [55:48<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3887/? [55:48<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3887/? [55:49<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0173, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3888/? [55:49<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0173, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3888/? [55:50<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3889/? [55:50<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3889/? [55:51<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3890/? [55:51<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3890/? [55:52<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3891/? [55:52<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3891/? [55:53<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3892/? [55:53<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3892/? [55:54<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3893/? [55:54<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3893/? [55:55<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3894/? [55:55<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3894/? [55:56<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3895/? [55:57<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3895/? [55:57<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0171, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3896/? [55:58<00:00,  1.16it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0171, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3896/? [55:58<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3897/? [55:59<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3897/? [55:59<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3898/? [56:00<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3898/? [56:00<00:00,  1.16it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00961] 
Training: |          | 3899/? [56:01<00:00,  1.16it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3899/? [56:01<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3900/? [56:02<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.015, val/loss=18.10, val/top_5_accuracy=0.00961]
Training: |          | 3900/? [56:02<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00961]

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Training: |          | 3900/? [56:07<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3901/? [56:08<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3901/? [56:08<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3902/? [56:09<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3902/? [56:09<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3903/? [56:10<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3903/? [56:10<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3904/? [56:11<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3904/? [56:11<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3905/? [56:12<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3905/? [56:12<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3906/? [56:13<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3906/? [56:13<00:00,  1.16it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0168, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3907/? [56:14<00:00,  1.16it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0168, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3907/? [56:14<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3908/? [56:15<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3908/? [56:15<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3909/? [56:16<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3909/? [56:16<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3910/? [56:17<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3910/? [56:17<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3911/? [56:18<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3911/? [56:19<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3912/? [56:19<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3912/? [56:20<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3913/? [56:20<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3913/? [56:21<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0172, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3914/? [56:21<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0172, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3914/? [56:22<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3915/? [56:22<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3915/? [56:23<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3916/? [56:23<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0155, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3916/? [56:24<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3917/? [56:24<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3917/? [56:25<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3918/? [56:25<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3918/? [56:26<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3919/? [56:26<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3919/? [56:27<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3920/? [56:27<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3920/? [56:28<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3921/? [56:28<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3921/? [56:29<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3922/? [56:29<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3922/? [56:30<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3923/? [56:30<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3923/? [56:31<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3924/? [56:31<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3924/? [56:32<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3925/? [56:32<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3925/? [56:33<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3926/? [56:33<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3926/? [56:34<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3927/? [56:34<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3927/? [56:35<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3928/? [56:35<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3928/? [56:36<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3929/? [56:36<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3929/? [56:37<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3930/? [56:38<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3930/? [56:38<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3931/? [56:38<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3931/? [56:39<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3932/? [56:40<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3932/? [56:40<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3933/? [56:41<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3933/? [56:41<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3934/? [56:42<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3934/? [56:42<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3935/? [56:43<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3935/? [56:43<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3936/? [56:44<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3936/? [56:44<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3937/? [56:45<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3937/? [56:45<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3938/? [56:46<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3938/? [56:46<00:00,  1.16it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3939/? [56:47<00:00,  1.16it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0171, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3939/? [56:47<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3940/? [56:48<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3940/? [56:48<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3941/? [56:49<00:00,  1.16it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3941/? [56:49<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3942/? [56:50<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3942/? [56:50<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3943/? [56:51<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3943/? [56:51<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3944/? [56:52<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3944/? [56:52<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3945/? [56:53<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3945/? [56:53<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3946/? [56:54<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0124, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3946/? [56:54<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3947/? [56:55<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3947/? [56:55<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0124, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3948/? [56:56<00:00,  1.16it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0124, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3948/? [56:56<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3949/? [56:57<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3949/? [56:57<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3950/? [56:58<00:00,  1.16it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3950/? [56:58<00:00,  1.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3951/? [56:59<00:00,  1.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3951/? [56:59<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3952/? [57:00<00:00,  1.16it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0151, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3952/? [57:00<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3953/? [57:01<00:00,  1.16it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3953/? [57:01<00:00,  1.16it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0187, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3954/? [57:02<00:00,  1.16it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0187, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3954/? [57:03<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3955/? [57:03<00:00,  1.16it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3955/? [57:04<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3956/? [57:04<00:00,  1.16it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3956/? [57:05<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3957/? [57:05<00:00,  1.16it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3957/? [57:06<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00922, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3958/? [57:06<00:00,  1.16it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00922, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3958/? [57:07<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3959/? [57:07<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3959/? [57:08<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3960/? [57:08<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3960/? [57:09<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3961/? [57:09<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3961/? [57:10<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3962/? [57:10<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3962/? [57:11<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3963/? [57:11<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3963/? [57:12<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0167, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3964/? [57:12<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0167, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3964/? [57:13<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3965/? [57:13<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3965/? [57:14<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3966/? [57:14<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3966/? [57:15<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3967/? [57:15<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3967/? [57:16<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3968/? [57:16<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3968/? [57:17<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3969/? [57:17<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3969/? [57:18<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3970/? [57:18<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3970/? [57:19<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3971/? [57:20<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3971/? [57:20<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3972/? [57:21<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3972/? [57:21<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3973/? [57:22<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3973/? [57:22<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3974/? [57:23<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3974/? [57:23<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3975/? [57:24<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3975/? [57:24<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3976/? [57:25<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3976/? [57:25<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3977/? [57:26<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3977/? [57:26<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0164, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3978/? [57:27<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0164, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3978/? [57:27<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3979/? [57:28<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3979/? [57:28<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3980/? [57:29<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3980/? [57:29<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3981/? [57:30<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3981/? [57:30<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00922, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3982/? [57:31<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00922, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3982/? [57:31<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902]  
Training: |          | 3983/? [57:32<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3983/? [57:32<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3984/? [57:33<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0108, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3984/? [57:33<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3985/? [57:34<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3985/? [57:34<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3986/? [57:35<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3986/? [57:35<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3987/? [57:36<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3987/? [57:36<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3988/? [57:37<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3988/? [57:37<00:00,  1.15it/s, v_num=2, train/loss=15.10, train/top_5_accuracy=0.032, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3989/? [57:38<00:00,  1.15it/s, v_num=2, train/loss=15.10, train/top_5_accuracy=0.032, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3989/? [57:38<00:00,  1.15it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3990/? [57:39<00:00,  1.15it/s, v_num=2, train/loss=17.80, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3990/? [57:39<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3991/? [57:40<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3991/? [57:40<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3992/? [57:41<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3992/? [57:41<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3993/? [57:42<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3993/? [57:42<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.00902] 
Training: |          | 3994/? [57:43<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3994/? [57:44<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3995/? [57:44<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3995/? [57:45<00:00,  1.15it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3996/? [57:45<00:00,  1.15it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3996/? [57:46<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3997/? [57:46<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3997/? [57:47<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3998/? [57:47<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3998/? [57:48<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3999/? [57:48<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 3999/? [57:49<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 4000/? [57:49<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.00902]
Training: |          | 4000/? [57:50<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00902]

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Training: |          | 4000/? [57:55<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0143, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4001/? [57:55<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0143, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4001/? [57:56<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4002/? [57:56<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4002/? [57:57<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4003/? [57:57<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4003/? [57:58<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4004/? [57:59<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4004/? [57:59<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4005/? [58:00<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4005/? [58:00<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4006/? [58:01<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4006/? [58:01<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4007/? [58:02<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4007/? [58:02<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4008/? [58:03<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4008/? [58:03<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4009/? [58:04<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4009/? [58:04<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4010/? [58:05<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4010/? [58:05<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4011/? [58:06<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0159, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4011/? [58:06<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4012/? [58:07<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4012/? [58:07<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4013/? [58:08<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4013/? [58:08<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0157, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4014/? [58:09<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0157, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4014/? [58:09<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4015/? [58:10<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4015/? [58:10<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4016/? [58:11<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4016/? [58:11<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4017/? [58:12<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4017/? [58:12<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4018/? [58:13<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4018/? [58:13<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4019/? [58:14<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4019/? [58:14<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4020/? [58:15<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4020/? [58:15<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4021/? [58:16<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4021/? [58:16<00:00,  1.15it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0186, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4022/? [58:17<00:00,  1.15it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0186, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4022/? [58:17<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4023/? [58:18<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00977, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4023/? [58:18<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4024/? [58:19<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4024/? [58:20<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4025/? [58:20<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4025/? [58:21<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0156, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4026/? [58:21<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0156, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4026/? [58:22<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4027/? [58:22<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4027/? [58:23<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4028/? [58:23<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4028/? [58:24<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4029/? [58:24<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4029/? [58:25<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4030/? [58:25<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0133, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4030/? [58:26<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4031/? [58:26<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4031/? [58:27<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4032/? [58:27<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4032/? [58:28<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4033/? [58:28<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4033/? [58:29<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4034/? [58:29<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4034/? [58:30<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4035/? [58:30<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4035/? [58:31<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4036/? [58:31<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4036/? [58:32<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4037/? [58:33<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4037/? [58:33<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4038/? [58:34<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4038/? [58:34<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4039/? [58:35<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4039/? [58:35<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4040/? [58:36<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0121, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4040/? [58:36<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4041/? [58:37<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.014, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4041/? [58:37<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4042/? [58:38<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0119, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4042/? [58:38<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4043/? [58:39<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4043/? [58:39<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00748, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4044/? [58:40<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00748, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4044/? [58:40<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4045/? [58:41<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4045/? [58:41<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4046/? [58:42<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4046/? [58:42<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4047/? [58:43<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4047/? [58:43<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4048/? [58:44<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4048/? [58:44<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4049/? [58:45<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4049/? [58:45<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4050/? [58:46<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4050/? [58:46<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4051/? [58:47<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4051/? [58:47<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4052/? [58:48<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4052/? [58:48<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4053/? [58:49<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4053/? [58:49<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4054/? [58:50<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4054/? [58:50<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4055/? [58:51<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4055/? [58:52<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4056/? [58:52<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4056/? [58:53<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0148, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4057/? [58:53<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0148, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4057/? [58:54<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4058/? [58:54<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4058/? [58:55<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4059/? [58:55<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0177, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4059/? [58:56<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4060/? [58:56<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4060/? [58:57<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4061/? [58:57<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4061/? [58:58<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4062/? [58:58<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00903, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4062/? [58:59<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4063/? [58:59<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4063/? [59:00<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0166, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4064/? [59:00<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0166, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4064/? [59:01<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4065/? [59:01<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.016, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4065/? [59:02<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4066/? [59:02<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4066/? [59:03<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0165, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4067/? [59:03<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0165, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4067/? [59:04<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.017, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4068/? [59:04<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.017, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4068/? [59:05<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4069/? [59:05<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00952, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4069/? [59:06<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4070/? [59:06<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0116, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4070/? [59:07<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4071/? [59:08<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4071/? [59:08<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4072/? [59:09<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4072/? [59:09<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4073/? [59:10<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4073/? [59:10<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4074/? [59:11<00:00,  1.15it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0155, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4074/? [59:11<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0178, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4075/? [59:12<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0178, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4075/? [59:12<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4076/? [59:13<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4076/? [59:13<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0178, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4077/? [59:14<00:00,  1.15it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0178, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4077/? [59:14<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4078/? [59:15<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4078/? [59:15<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4079/? [59:16<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4079/? [59:16<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4080/? [59:17<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4080/? [59:17<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4081/? [59:18<00:00,  1.15it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4081/? [59:18<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4082/? [59:19<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4082/? [59:19<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4083/? [59:20<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4083/? [59:20<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4084/? [59:21<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.016, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4084/? [59:21<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4085/? [59:22<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4085/? [59:22<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4086/? [59:23<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4086/? [59:23<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4087/? [59:24<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4087/? [59:24<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4088/? [59:25<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4088/? [59:25<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00964, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4089/? [59:26<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00964, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4089/? [59:27<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4090/? [59:27<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4090/? [59:28<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4091/? [59:28<00:00,  1.15it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4091/? [59:29<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4092/? [59:29<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4092/? [59:30<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4093/? [59:30<00:00,  1.15it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4093/? [59:31<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4094/? [59:31<00:00,  1.15it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4094/? [59:32<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4095/? [59:32<00:00,  1.15it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4095/? [59:33<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4096/? [59:33<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4096/? [59:34<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4097/? [59:34<00:00,  1.15it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0146, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4097/? [59:35<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4098/? [59:35<00:00,  1.15it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4098/? [59:36<00:00,  1.15it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0188, val/loss=18.10, val/top_5_accuracy=0.00908] 
Training: |          | 4099/? [59:36<00:00,  1.15it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0188, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4099/? [59:37<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4100/? [59:37<00:00,  1.15it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=18.10, val/top_5_accuracy=0.00908]
Training: |          | 4100/? [59:38<00:00,  1.15it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=18.10, val/top_5_accuracy=0.00908]

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Validation DataLoader 0: 100%|██████████| 20/20 [00:06<00:00,  3.18it/s]

                                                                        
Training: |          | 4100/? [59:44<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4101/? [59:45<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4101/? [59:45<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4102/? [59:46<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4102/? [59:46<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4103/? [59:47<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4103/? [59:47<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4104/? [59:48<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4104/? [59:48<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4105/? [59:49<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4105/? [59:49<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4106/? [59:50<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4106/? [59:50<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4107/? [59:51<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4107/? [59:51<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4108/? [59:52<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4108/? [59:52<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4109/? [59:53<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4109/? [59:53<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4110/? [59:54<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4110/? [59:54<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4111/? [59:55<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4111/? [59:55<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4112/? [59:56<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4112/? [59:56<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4113/? [59:57<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4113/? [59:57<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4114/? [59:58<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4114/? [59:58<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4115/? [59:59<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4115/? [59:59<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4116/? [1:00:00<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4116/? [1:00:00<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4117/? [1:00:01<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4117/? [1:00:01<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4118/? [1:00:02<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4118/? [1:00:03<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4119/? [1:00:03<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.016, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4119/? [1:00:04<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4120/? [1:00:04<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4120/? [1:00:05<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4121/? [1:00:05<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4121/? [1:00:06<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4122/? [1:00:06<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4122/? [1:00:07<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4123/? [1:00:07<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4123/? [1:00:08<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4124/? [1:00:08<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4124/? [1:00:09<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4125/? [1:00:09<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4125/? [1:00:10<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4126/? [1:00:10<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4126/? [1:00:11<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4127/? [1:00:11<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4127/? [1:00:12<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4128/? [1:00:12<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4128/? [1:00:13<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4129/? [1:00:13<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4129/? [1:00:14<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4130/? [1:00:14<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0165, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4130/? [1:00:15<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4131/? [1:00:15<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4131/? [1:00:16<00:00,  1.14it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00934, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4132/? [1:00:16<00:00,  1.14it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00934, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4132/? [1:00:17<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4133/? [1:00:17<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4133/? [1:00:18<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4134/? [1:00:18<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4134/? [1:00:19<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4135/? [1:00:20<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4135/? [1:00:20<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4136/? [1:00:21<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4136/? [1:00:21<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4137/? [1:00:22<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4137/? [1:00:22<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4138/? [1:00:23<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0151, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4138/? [1:00:23<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4139/? [1:00:24<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4139/? [1:00:24<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4140/? [1:00:25<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4140/? [1:00:25<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4141/? [1:00:26<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4141/? [1:00:26<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4142/? [1:00:27<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4142/? [1:00:27<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4143/? [1:00:28<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4143/? [1:00:28<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4144/? [1:00:29<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4144/? [1:00:29<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4145/? [1:00:30<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4145/? [1:00:30<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4146/? [1:00:31<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4146/? [1:00:31<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4147/? [1:00:32<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0153, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4147/? [1:00:32<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4148/? [1:00:33<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4148/? [1:00:33<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00873, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4149/? [1:00:34<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00873, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4149/? [1:00:34<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4150/? [1:00:35<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4150/? [1:00:35<00:00,  1.14it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4151/? [1:00:36<00:00,  1.14it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4151/? [1:00:36<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0162, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4152/? [1:00:37<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0162, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4152/? [1:00:37<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4153/? [1:00:38<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4153/? [1:00:38<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4154/? [1:00:39<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4154/? [1:00:39<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4155/? [1:00:40<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4155/? [1:00:40<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4156/? [1:00:41<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4156/? [1:00:41<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4157/? [1:00:42<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4157/? [1:00:42<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4158/? [1:00:43<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4158/? [1:00:44<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4159/? [1:00:44<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4159/? [1:00:45<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4160/? [1:00:45<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4160/? [1:00:46<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4161/? [1:00:46<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4161/? [1:00:47<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4162/? [1:00:47<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4162/? [1:00:48<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4163/? [1:00:48<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4163/? [1:00:49<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4164/? [1:00:49<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4164/? [1:00:50<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4165/? [1:00:50<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4165/? [1:00:51<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4166/? [1:00:51<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4166/? [1:00:52<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4167/? [1:00:52<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4167/? [1:00:53<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4168/? [1:00:53<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4168/? [1:00:54<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4169/? [1:00:54<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4169/? [1:00:55<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4170/? [1:00:55<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4170/? [1:00:56<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4171/? [1:00:56<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4171/? [1:00:57<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4172/? [1:00:57<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4172/? [1:00:58<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4173/? [1:00:58<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4173/? [1:00:59<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4174/? [1:00:59<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4174/? [1:01:00<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4175/? [1:01:00<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4175/? [1:01:01<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4176/? [1:01:01<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4176/? [1:01:02<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4177/? [1:01:02<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4177/? [1:01:03<00:00,  1.14it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4178/? [1:01:03<00:00,  1.14it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4178/? [1:01:04<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4179/? [1:01:05<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4179/? [1:01:05<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4180/? [1:01:06<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4180/? [1:01:06<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4181/? [1:01:07<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4181/? [1:01:07<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4182/? [1:01:08<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0135, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4182/? [1:01:08<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4183/? [1:01:09<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4183/? [1:01:09<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4184/? [1:01:10<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4184/? [1:01:10<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4185/? [1:01:11<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4185/? [1:01:11<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4186/? [1:01:12<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4186/? [1:01:12<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4187/? [1:01:13<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4187/? [1:01:13<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4188/? [1:01:14<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4188/? [1:01:14<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4189/? [1:01:15<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4189/? [1:01:15<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4190/? [1:01:16<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4190/? [1:01:16<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4191/? [1:01:17<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4191/? [1:01:17<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4192/? [1:01:18<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4192/? [1:01:18<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4193/? [1:01:19<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4193/? [1:01:19<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4194/? [1:01:20<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4194/? [1:01:20<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4195/? [1:01:21<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00977, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4195/? [1:01:21<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4196/? [1:01:22<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4196/? [1:01:22<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4197/? [1:01:23<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0126, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4197/? [1:01:23<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4198/? [1:01:24<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4198/? [1:01:24<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4199/? [1:01:25<00:00,  1.14it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00983, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4199/? [1:01:25<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=17.90, val/top_5_accuracy=0.00978] 
Training: |          | 4200/? [1:01:26<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=17.90, val/top_5_accuracy=0.00978]
Training: |          | 4200/? [1:01:26<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00978]

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Training: |          | 4200/? [1:01:35<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4201/? [1:01:35<00:00,  1.14it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4201/? [1:01:36<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4202/? [1:01:36<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4202/? [1:01:37<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0133, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4203/? [1:01:37<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0133, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4203/? [1:01:38<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4204/? [1:01:38<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4204/? [1:01:39<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4205/? [1:01:39<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4205/? [1:01:40<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4206/? [1:01:41<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4206/? [1:01:41<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4207/? [1:01:42<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4207/? [1:01:42<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4208/? [1:01:43<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4208/? [1:01:43<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4209/? [1:01:44<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4209/? [1:01:44<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4210/? [1:01:45<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4210/? [1:01:45<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4211/? [1:01:46<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4211/? [1:01:46<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4212/? [1:01:47<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4212/? [1:01:47<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4213/? [1:01:48<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4213/? [1:01:48<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4214/? [1:01:49<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4214/? [1:01:49<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4215/? [1:01:50<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4215/? [1:01:50<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4216/? [1:01:51<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4216/? [1:01:51<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4217/? [1:01:52<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0129, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4217/? [1:01:52<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4218/? [1:01:53<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4218/? [1:01:53<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0118, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4219/? [1:01:54<00:00,  1.14it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0118, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4219/? [1:01:54<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4220/? [1:01:55<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0157, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4220/? [1:01:55<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4221/? [1:01:56<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4221/? [1:01:56<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4222/? [1:01:57<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0151, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4222/? [1:01:57<00:00,  1.14it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00989, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4223/? [1:01:58<00:00,  1.14it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00989, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4223/? [1:01:58<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4224/? [1:01:59<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4224/? [1:01:59<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.011, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4225/? [1:02:00<00:00,  1.14it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.011, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4225/? [1:02:00<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4226/? [1:02:01<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4226/? [1:02:01<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4227/? [1:02:02<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4227/? [1:02:02<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4228/? [1:02:03<00:00,  1.14it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0167, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4228/? [1:02:04<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4229/? [1:02:04<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4229/? [1:02:05<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4230/? [1:02:05<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4230/? [1:02:06<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4231/? [1:02:06<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4231/? [1:02:07<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4232/? [1:02:07<00:00,  1.14it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4232/? [1:02:08<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4233/? [1:02:08<00:00,  1.14it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4233/? [1:02:09<00:00,  1.14it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0178, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4234/? [1:02:09<00:00,  1.14it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0178, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4234/? [1:02:10<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4235/? [1:02:10<00:00,  1.14it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4235/? [1:02:11<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4236/? [1:02:11<00:00,  1.14it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4236/? [1:02:12<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4237/? [1:02:12<00:00,  1.14it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4237/? [1:02:13<00:00,  1.13it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00781, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4238/? [1:02:13<00:00,  1.14it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00781, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4238/? [1:02:14<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4239/? [1:02:14<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4239/? [1:02:15<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0168, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4240/? [1:02:15<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0168, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4240/? [1:02:16<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4241/? [1:02:16<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4241/? [1:02:17<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4242/? [1:02:17<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4242/? [1:02:18<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4243/? [1:02:18<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4243/? [1:02:19<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4244/? [1:02:19<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4244/? [1:02:20<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4245/? [1:02:21<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.010, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4245/? [1:02:21<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4246/? [1:02:22<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4246/? [1:02:22<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4247/? [1:02:23<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4247/? [1:02:23<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0142, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4248/? [1:02:24<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0142, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4248/? [1:02:24<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4249/? [1:02:25<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4249/? [1:02:25<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4250/? [1:02:26<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0108, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4250/? [1:02:26<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4251/? [1:02:27<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0121, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4251/? [1:02:27<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0125, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4252/? [1:02:28<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0125, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4252/? [1:02:28<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4253/? [1:02:29<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4253/? [1:02:29<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4254/? [1:02:30<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4254/? [1:02:30<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4255/? [1:02:31<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4255/? [1:02:31<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4256/? [1:02:32<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4256/? [1:02:32<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4257/? [1:02:33<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4257/? [1:02:33<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4258/? [1:02:34<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4258/? [1:02:34<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4259/? [1:02:35<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0159, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4259/? [1:02:35<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0146, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4260/? [1:02:36<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0146, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4260/? [1:02:36<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0133, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4261/? [1:02:37<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0133, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4261/? [1:02:37<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4262/? [1:02:38<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00903, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4262/? [1:02:38<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4263/? [1:02:39<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4263/? [1:02:39<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4264/? [1:02:40<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4264/? [1:02:40<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4265/? [1:02:41<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4265/? [1:02:41<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4266/? [1:02:42<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4266/? [1:02:42<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0162, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4267/? [1:02:43<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0162, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4267/? [1:02:44<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4268/? [1:02:44<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4268/? [1:02:45<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4269/? [1:02:45<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00897, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4269/? [1:02:46<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4270/? [1:02:46<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0132, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4270/? [1:02:47<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4271/? [1:02:47<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4271/? [1:02:48<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4272/? [1:02:48<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4272/? [1:02:49<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4273/? [1:02:49<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0156, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4273/? [1:02:50<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4274/? [1:02:50<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4274/? [1:02:51<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4275/? [1:02:51<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4275/? [1:02:52<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4276/? [1:02:52<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4276/? [1:02:53<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4277/? [1:02:53<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4277/? [1:02:54<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4278/? [1:02:54<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4278/? [1:02:55<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4279/? [1:02:55<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4279/? [1:02:56<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4280/? [1:02:56<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4280/? [1:02:57<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4281/? [1:02:58<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4281/? [1:02:58<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4282/? [1:02:59<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4282/? [1:02:59<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4283/? [1:03:00<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4283/? [1:03:00<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0151, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4284/? [1:03:01<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0151, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4284/? [1:03:01<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4285/? [1:03:02<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4285/? [1:03:02<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4286/? [1:03:03<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0107, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4286/? [1:03:03<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4287/? [1:03:04<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4287/? [1:03:04<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4288/? [1:03:05<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4288/? [1:03:05<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0134, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4289/? [1:03:06<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0134, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4289/? [1:03:06<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4290/? [1:03:07<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4290/? [1:03:07<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4291/? [1:03:08<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0119, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4291/? [1:03:08<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4292/? [1:03:09<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4292/? [1:03:09<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0144, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4293/? [1:03:10<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0144, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4293/? [1:03:10<00:00,  1.13it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00671, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4294/? [1:03:11<00:00,  1.13it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00671, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4294/? [1:03:11<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0102, val/loss=17.10, val/top_5_accuracy=0.0114] 
Training: |          | 4295/? [1:03:12<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0102, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4295/? [1:03:12<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4296/? [1:03:13<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4296/? [1:03:13<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4297/? [1:03:14<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4297/? [1:03:14<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4298/? [1:03:15<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4298/? [1:03:15<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0122, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4299/? [1:03:16<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0122, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4299/? [1:03:16<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4300/? [1:03:17<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.10, val/top_5_accuracy=0.0114]
Training: |          | 4300/? [1:03:17<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.10, val/top_5_accuracy=0.0114]

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Training: |          | 4300/? [1:03:23<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4301/? [1:03:24<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0094, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4301/? [1:03:24<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4302/? [1:03:25<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4302/? [1:03:25<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4303/? [1:03:26<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00946, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4303/? [1:03:26<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0177, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4304/? [1:03:27<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0177, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4304/? [1:03:27<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4305/? [1:03:28<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4305/? [1:03:28<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4306/? [1:03:29<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4306/? [1:03:29<00:00,  1.13it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0182, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4307/? [1:03:30<00:00,  1.13it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0182, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4307/? [1:03:30<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4308/? [1:03:31<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4308/? [1:03:31<00:00,  1.13it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4309/? [1:03:32<00:00,  1.13it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4309/? [1:03:32<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4310/? [1:03:33<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4310/? [1:03:33<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4311/? [1:03:34<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4311/? [1:03:34<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4312/? [1:03:35<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4312/? [1:03:35<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4313/? [1:03:36<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0123, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4313/? [1:03:36<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4314/? [1:03:37<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4314/? [1:03:37<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4315/? [1:03:38<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4315/? [1:03:38<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4316/? [1:03:39<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4316/? [1:03:39<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4317/? [1:03:40<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4317/? [1:03:40<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4318/? [1:03:41<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4318/? [1:03:41<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4319/? [1:03:42<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4319/? [1:03:42<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4320/? [1:03:43<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4320/? [1:03:43<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4321/? [1:03:44<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4321/? [1:03:45<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4322/? [1:03:45<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4322/? [1:03:46<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4323/? [1:03:46<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4323/? [1:03:47<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00983, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4324/? [1:03:47<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.00983, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4324/? [1:03:48<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4325/? [1:03:48<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4325/? [1:03:49<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4326/? [1:03:49<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4326/? [1:03:50<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4327/? [1:03:50<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4327/? [1:03:51<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4328/? [1:03:51<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4328/? [1:03:52<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4329/? [1:03:52<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4329/? [1:03:53<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4330/? [1:03:53<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4330/? [1:03:54<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4331/? [1:03:54<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4331/? [1:03:55<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4332/? [1:03:55<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4332/? [1:03:56<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4333/? [1:03:56<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4333/? [1:03:57<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4334/? [1:03:57<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4334/? [1:03:58<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4335/? [1:03:58<00:00,  1.13it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4335/? [1:03:59<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4336/? [1:03:59<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4336/? [1:04:00<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4337/? [1:04:00<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4337/? [1:04:01<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4338/? [1:04:01<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4338/? [1:04:02<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4339/? [1:04:02<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4339/? [1:04:03<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4340/? [1:04:04<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.015, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4340/? [1:04:04<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4341/? [1:04:05<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4341/? [1:04:05<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4342/? [1:04:06<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4342/? [1:04:06<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4343/? [1:04:07<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4343/? [1:04:07<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4344/? [1:04:08<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4344/? [1:04:08<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4345/? [1:04:09<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4345/? [1:04:09<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4346/? [1:04:10<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4346/? [1:04:10<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4347/? [1:04:11<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4347/? [1:04:11<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4348/? [1:04:12<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4348/? [1:04:12<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4349/? [1:04:13<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4349/? [1:04:13<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4350/? [1:04:14<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4350/? [1:04:14<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4351/? [1:04:15<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4351/? [1:04:15<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4352/? [1:04:16<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4352/? [1:04:16<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4353/? [1:04:17<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4353/? [1:04:17<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4354/? [1:04:18<00:00,  1.13it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4354/? [1:04:18<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4355/? [1:04:19<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4355/? [1:04:19<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4356/? [1:04:20<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4356/? [1:04:20<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4357/? [1:04:21<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4357/? [1:04:21<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4358/? [1:04:22<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4358/? [1:04:22<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4359/? [1:04:23<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4359/? [1:04:23<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4360/? [1:04:24<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4360/? [1:04:24<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4361/? [1:04:25<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4361/? [1:04:25<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4362/? [1:04:26<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4362/? [1:04:26<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4363/? [1:04:27<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4363/? [1:04:27<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4364/? [1:04:28<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4364/? [1:04:28<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4365/? [1:04:29<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4365/? [1:04:30<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4366/? [1:04:30<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4366/? [1:04:31<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4367/? [1:04:31<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4367/? [1:04:32<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4368/? [1:04:32<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4368/? [1:04:33<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4369/? [1:04:33<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0152, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4369/? [1:04:34<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4370/? [1:04:34<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4370/? [1:04:35<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4371/? [1:04:35<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4371/? [1:04:36<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.019, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4372/? [1:04:36<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.019, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4372/? [1:04:37<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4373/? [1:04:37<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4373/? [1:04:38<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4374/? [1:04:38<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4374/? [1:04:39<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4375/? [1:04:39<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4375/? [1:04:40<00:00,  1.13it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0178, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4376/? [1:04:41<00:00,  1.13it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0178, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4376/? [1:04:41<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4377/? [1:04:42<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4377/? [1:04:42<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4378/? [1:04:43<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0132, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4378/? [1:04:43<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4379/? [1:04:44<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4379/? [1:04:44<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4380/? [1:04:45<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4380/? [1:04:45<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0175, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4381/? [1:04:46<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0175, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4381/? [1:04:46<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4382/? [1:04:47<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4382/? [1:04:47<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4383/? [1:04:48<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4383/? [1:04:48<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4384/? [1:04:49<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4384/? [1:04:49<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4385/? [1:04:50<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4385/? [1:04:50<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4386/? [1:04:51<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4386/? [1:04:51<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4387/? [1:04:52<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4387/? [1:04:52<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4388/? [1:04:53<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4388/? [1:04:53<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4389/? [1:04:54<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4389/? [1:04:54<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00967] 
Training: |          | 4390/? [1:04:55<00:00,  1.13it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4390/? [1:04:55<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4391/? [1:04:56<00:00,  1.13it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4391/? [1:04:56<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4392/? [1:04:57<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4392/? [1:04:57<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4393/? [1:04:58<00:00,  1.13it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4393/? [1:04:58<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4394/? [1:04:59<00:00,  1.13it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4394/? [1:04:59<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0183, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4395/? [1:05:00<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0183, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4395/? [1:05:00<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4396/? [1:05:01<00:00,  1.13it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4396/? [1:05:01<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0175, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4397/? [1:05:02<00:00,  1.13it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0175, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4397/? [1:05:02<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4398/? [1:05:03<00:00,  1.13it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4398/? [1:05:03<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4399/? [1:05:04<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4399/? [1:05:05<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4400/? [1:05:05<00:00,  1.13it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00958, val/loss=17.90, val/top_5_accuracy=0.00967]
Training: |          | 4400/? [1:05:06<00:00,  1.13it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00967] 

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Training: |          | 4400/? [1:05:12<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4401/? [1:05:12<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0133, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4401/? [1:05:13<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4402/? [1:05:13<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4402/? [1:05:14<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4403/? [1:05:14<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4403/? [1:05:15<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4404/? [1:05:15<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4404/? [1:05:16<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4405/? [1:05:17<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4405/? [1:05:17<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4406/? [1:05:18<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4406/? [1:05:18<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4407/? [1:05:19<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4407/? [1:05:19<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4408/? [1:05:20<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4408/? [1:05:20<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4409/? [1:05:21<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4409/? [1:05:21<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4410/? [1:05:22<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4410/? [1:05:22<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4411/? [1:05:23<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4411/? [1:05:23<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4412/? [1:05:24<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4412/? [1:05:24<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4413/? [1:05:25<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4413/? [1:05:25<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4414/? [1:05:26<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4414/? [1:05:26<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4415/? [1:05:27<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4415/? [1:05:27<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4416/? [1:05:28<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4416/? [1:05:28<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4417/? [1:05:29<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4417/? [1:05:29<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0168, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4418/? [1:05:30<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0168, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4418/? [1:05:30<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4419/? [1:05:31<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4419/? [1:05:31<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4420/? [1:05:32<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4420/? [1:05:32<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4421/? [1:05:33<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4421/? [1:05:33<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4422/? [1:05:34<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4422/? [1:05:34<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4423/? [1:05:35<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4423/? [1:05:35<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4424/? [1:05:36<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4424/? [1:05:36<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4425/? [1:05:37<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4425/? [1:05:37<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4426/? [1:05:38<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4426/? [1:05:38<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4427/? [1:05:39<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4427/? [1:05:39<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4428/? [1:05:40<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4428/? [1:05:40<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4429/? [1:05:41<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4429/? [1:05:41<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4430/? [1:05:42<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4430/? [1:05:43<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4431/? [1:05:43<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4431/? [1:05:44<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4432/? [1:05:44<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4432/? [1:05:45<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4433/? [1:05:45<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4433/? [1:05:46<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4434/? [1:05:46<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4434/? [1:05:47<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4435/? [1:05:47<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4435/? [1:05:48<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4436/? [1:05:48<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4436/? [1:05:49<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4437/? [1:05:49<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4437/? [1:05:50<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4438/? [1:05:50<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4438/? [1:05:51<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4439/? [1:05:51<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4439/? [1:05:52<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4440/? [1:05:52<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4440/? [1:05:53<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4441/? [1:05:53<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4441/? [1:05:54<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4442/? [1:05:54<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4442/? [1:05:55<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4443/? [1:05:55<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4443/? [1:05:56<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4444/? [1:05:57<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4444/? [1:05:57<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4445/? [1:05:58<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4445/? [1:05:58<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4446/? [1:05:59<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4446/? [1:05:59<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4447/? [1:06:00<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4447/? [1:06:00<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4448/? [1:06:01<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4448/? [1:06:01<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4449/? [1:06:02<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0138, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4449/? [1:06:02<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4450/? [1:06:03<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4450/? [1:06:03<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4451/? [1:06:04<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4451/? [1:06:04<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4452/? [1:06:05<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4452/? [1:06:05<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4453/? [1:06:06<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4453/? [1:06:06<00:00,  1.12it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.019, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4454/? [1:06:07<00:00,  1.12it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.019, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4454/? [1:06:07<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4455/? [1:06:08<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4455/? [1:06:08<00:00,  1.12it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0231, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4456/? [1:06:09<00:00,  1.12it/s, v_num=2, train/loss=15.80, train/top_5_accuracy=0.0231, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4456/? [1:06:09<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4457/? [1:06:10<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4457/? [1:06:10<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4458/? [1:06:11<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4458/? [1:06:11<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4459/? [1:06:12<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4459/? [1:06:12<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4460/? [1:06:13<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4460/? [1:06:13<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4461/? [1:06:14<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4461/? [1:06:14<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4462/? [1:06:15<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4462/? [1:06:15<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4463/? [1:06:16<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4463/? [1:06:17<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4464/? [1:06:17<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4464/? [1:06:18<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4465/? [1:06:18<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4465/? [1:06:19<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4466/? [1:06:19<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4466/? [1:06:20<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4467/? [1:06:20<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4467/? [1:06:21<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4468/? [1:06:21<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4468/? [1:06:22<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4469/? [1:06:22<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4469/? [1:06:23<00:00,  1.12it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00916, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4470/? [1:06:23<00:00,  1.12it/s, v_num=2, train/loss=17.60, train/top_5_accuracy=0.00916, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4470/? [1:06:24<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4471/? [1:06:24<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0102, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4471/? [1:06:25<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4472/? [1:06:25<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0105, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4472/? [1:06:26<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4473/? [1:06:26<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4473/? [1:06:27<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4474/? [1:06:27<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4474/? [1:06:28<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4475/? [1:06:28<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4475/? [1:06:29<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4476/? [1:06:29<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4476/? [1:06:30<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4477/? [1:06:30<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4477/? [1:06:31<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4478/? [1:06:31<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4478/? [1:06:32<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4479/? [1:06:32<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00928, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4479/? [1:06:33<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4480/? [1:06:34<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4480/? [1:06:34<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4481/? [1:06:35<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4481/? [1:06:35<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4482/? [1:06:36<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4482/? [1:06:36<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4483/? [1:06:37<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4483/? [1:06:37<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4484/? [1:06:38<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4484/? [1:06:38<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4485/? [1:06:39<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4485/? [1:06:39<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4486/? [1:06:40<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0154, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4486/? [1:06:40<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4487/? [1:06:41<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00964, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4487/? [1:06:41<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0147, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4488/? [1:06:42<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0147, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4488/? [1:06:42<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4489/? [1:06:43<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4489/? [1:06:43<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4490/? [1:06:44<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4490/? [1:06:44<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4491/? [1:06:45<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4491/? [1:06:45<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4492/? [1:06:46<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0097, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4492/? [1:06:46<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4493/? [1:06:47<00:00,  1.12it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00934, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4493/? [1:06:47<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4494/? [1:06:48<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4494/? [1:06:48<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4495/? [1:06:49<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4495/? [1:06:49<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00989, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4496/? [1:06:50<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00989, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4496/? [1:06:50<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0103] 
Training: |          | 4497/? [1:06:51<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4497/? [1:06:51<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4498/? [1:06:52<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4498/? [1:06:52<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4499/? [1:06:53<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0138, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4499/? [1:06:53<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4500/? [1:06:54<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.0103]
Training: |          | 4500/? [1:06:54<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=18.00, val/top_5_accuracy=0.0103]

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Training: |          | 4500/? [1:07:01<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4501/? [1:07:01<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0168, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4501/? [1:07:02<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4502/? [1:07:02<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4502/? [1:07:03<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4503/? [1:07:03<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4503/? [1:07:04<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4504/? [1:07:04<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0172, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4504/? [1:07:05<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4505/? [1:07:05<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4505/? [1:07:06<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4506/? [1:07:06<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4506/? [1:07:07<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4507/? [1:07:07<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4507/? [1:07:08<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4508/? [1:07:08<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0154, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4508/? [1:07:09<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.014, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4509/? [1:07:09<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.014, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4509/? [1:07:10<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4510/? [1:07:10<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0131, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4510/? [1:07:11<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4511/? [1:07:11<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4511/? [1:07:12<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0155, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4512/? [1:07:13<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0155, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4512/? [1:07:13<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4513/? [1:07:14<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4513/? [1:07:14<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4514/? [1:07:15<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4514/? [1:07:15<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4515/? [1:07:16<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4515/? [1:07:16<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4516/? [1:07:17<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0127, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4516/? [1:07:17<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4517/? [1:07:18<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0134, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4517/? [1:07:18<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0141, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4518/? [1:07:19<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0141, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4518/? [1:07:19<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4519/? [1:07:20<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00903, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4519/? [1:07:20<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4520/? [1:07:21<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0127, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4520/? [1:07:21<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4521/? [1:07:22<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4521/? [1:07:22<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.010, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4522/? [1:07:23<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.010, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4522/? [1:07:23<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4523/? [1:07:24<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00995, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4523/? [1:07:24<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4524/? [1:07:25<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4524/? [1:07:25<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4525/? [1:07:26<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4525/? [1:07:26<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4526/? [1:07:27<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4526/? [1:07:27<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4527/? [1:07:28<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4527/? [1:07:28<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4528/? [1:07:29<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4528/? [1:07:29<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4529/? [1:07:30<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4529/? [1:07:30<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4530/? [1:07:31<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4530/? [1:07:31<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4531/? [1:07:32<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4531/? [1:07:32<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4532/? [1:07:33<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.013, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4532/? [1:07:33<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4533/? [1:07:34<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4533/? [1:07:35<00:00,  1.12it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0148, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4534/? [1:07:35<00:00,  1.12it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0148, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4534/? [1:07:36<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4535/? [1:07:36<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4535/? [1:07:37<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.019, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4536/? [1:07:37<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.019, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4536/? [1:07:38<00:00,  1.12it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0157, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4537/? [1:07:38<00:00,  1.12it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0157, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4537/? [1:07:39<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4538/? [1:07:39<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4538/? [1:07:40<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4539/? [1:07:40<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4539/? [1:07:41<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4540/? [1:07:41<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4540/? [1:07:42<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4541/? [1:07:42<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4541/? [1:07:43<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4542/? [1:07:43<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4542/? [1:07:44<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4543/? [1:07:44<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4543/? [1:07:45<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4544/? [1:07:45<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0155, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4544/? [1:07:46<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0143, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4545/? [1:07:46<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0143, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4545/? [1:07:47<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4546/? [1:07:47<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4546/? [1:07:48<00:00,  1.12it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0188, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4547/? [1:07:48<00:00,  1.12it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0188, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4547/? [1:07:49<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4548/? [1:07:49<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0132, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4548/? [1:07:50<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4549/? [1:07:50<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0123, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4549/? [1:07:51<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4550/? [1:07:52<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4550/? [1:07:52<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4551/? [1:07:53<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0101, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4551/? [1:07:53<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0177, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4552/? [1:07:54<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0177, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4552/? [1:07:54<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4553/? [1:07:55<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4553/? [1:07:55<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4554/? [1:07:56<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4554/? [1:07:56<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4555/? [1:07:57<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4555/? [1:07:57<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4556/? [1:07:58<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4556/? [1:07:58<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4557/? [1:07:59<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0126, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4557/? [1:07:59<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4558/? [1:08:00<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4558/? [1:08:00<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4559/? [1:08:01<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0106, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4559/? [1:08:01<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4560/? [1:08:02<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4560/? [1:08:02<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4561/? [1:08:03<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4561/? [1:08:03<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4562/? [1:08:04<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0161, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4562/? [1:08:04<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4563/? [1:08:05<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00946, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4563/? [1:08:05<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4564/? [1:08:06<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0108, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4564/? [1:08:06<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4565/? [1:08:07<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4565/? [1:08:07<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4566/? [1:08:08<00:00,  1.12it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4566/? [1:08:08<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4567/? [1:08:09<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4567/? [1:08:09<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4568/? [1:08:10<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4568/? [1:08:10<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4569/? [1:08:11<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0156, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4569/? [1:08:11<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4570/? [1:08:12<00:00,  1.12it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4570/? [1:08:12<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0172, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4571/? [1:08:13<00:00,  1.12it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0172, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4571/? [1:08:13<00:00,  1.12it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00671, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4572/? [1:08:14<00:00,  1.12it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00671, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4572/? [1:08:14<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4573/? [1:08:15<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0161, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4573/? [1:08:15<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4574/? [1:08:16<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0137, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4574/? [1:08:16<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4575/? [1:08:17<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0117, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4575/? [1:08:17<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4576/? [1:08:18<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4576/? [1:08:19<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4577/? [1:08:19<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0142, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4577/? [1:08:20<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4578/? [1:08:20<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0103, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4578/? [1:08:21<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4579/? [1:08:21<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0119, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4579/? [1:08:22<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0164, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4580/? [1:08:22<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0164, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4580/? [1:08:23<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4581/? [1:08:23<00:00,  1.12it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4581/? [1:08:24<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4582/? [1:08:24<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4582/? [1:08:25<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4583/? [1:08:25<00:00,  1.12it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.011, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4583/? [1:08:26<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0164, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4584/? [1:08:26<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0164, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4584/? [1:08:27<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4585/? [1:08:27<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4585/? [1:08:28<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4586/? [1:08:28<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0135, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4586/? [1:08:29<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4587/? [1:08:29<00:00,  1.12it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0114, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4587/? [1:08:30<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4588/? [1:08:30<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0146, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4588/? [1:08:31<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4589/? [1:08:31<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4589/? [1:08:32<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4590/? [1:08:32<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4590/? [1:08:33<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4591/? [1:08:33<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4591/? [1:08:34<00:00,  1.12it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.019, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4592/? [1:08:35<00:00,  1.12it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.019, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4592/? [1:08:35<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4593/? [1:08:36<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4593/? [1:08:36<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4594/? [1:08:37<00:00,  1.12it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0151, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4594/? [1:08:37<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4595/? [1:08:38<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0125, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4595/? [1:08:38<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4596/? [1:08:39<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4596/? [1:08:39<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4597/? [1:08:40<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0129, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4597/? [1:08:40<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4598/? [1:08:41<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0122, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4598/? [1:08:41<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4599/? [1:08:42<00:00,  1.12it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00983, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4599/? [1:08:42<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0101] 
Training: |          | 4600/? [1:08:43<00:00,  1.12it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0124, val/loss=17.70, val/top_5_accuracy=0.0101]
Training: |          | 4600/? [1:08:43<00:00,  1.12it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.70, val/top_5_accuracy=0.0101]

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Validation DataLoader 0:  85%|████████▌ | 17/20 [00:05<00:00,  3.24it/s]

Validation DataLoader 0:  90%|█████████ | 18/20 [00:05<00:00,  3.41it/s]

Validation DataLoader 0:  95%|█████████▌| 19/20 [00:05<00:00,  3.56it/s]

Validation DataLoader 0: 100%|██████████| 20/20 [00:05<00:00,  3.42it/s]

                                                                        
Training: |          | 4600/? [1:08:49<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4601/? [1:08:50<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4601/? [1:08:50<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4602/? [1:08:51<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4602/? [1:08:51<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4603/? [1:08:52<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0159, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4603/? [1:08:52<00:00,  1.11it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0173, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4604/? [1:08:53<00:00,  1.11it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0173, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4604/? [1:08:53<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4605/? [1:08:54<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4605/? [1:08:54<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4606/? [1:08:55<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00909, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4606/? [1:08:55<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4607/? [1:08:56<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4607/? [1:08:56<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4608/? [1:08:57<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4608/? [1:08:57<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4609/? [1:08:58<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4609/? [1:08:58<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4610/? [1:08:59<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4610/? [1:08:59<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4611/? [1:09:00<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4611/? [1:09:00<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4612/? [1:09:01<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4612/? [1:09:01<00:00,  1.11it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0192, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4613/? [1:09:02<00:00,  1.11it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0192, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4613/? [1:09:02<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4614/? [1:09:03<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4614/? [1:09:04<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4615/? [1:09:04<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4615/? [1:09:05<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4616/? [1:09:05<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0131, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4616/? [1:09:06<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4617/? [1:09:06<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4617/? [1:09:07<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4618/? [1:09:07<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4618/? [1:09:08<00:00,  1.11it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0194, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4619/? [1:09:08<00:00,  1.11it/s, v_num=2, train/loss=15.90, train/top_5_accuracy=0.0194, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4619/? [1:09:09<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4620/? [1:09:09<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4620/? [1:09:10<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4621/? [1:09:10<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4621/? [1:09:11<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4622/? [1:09:11<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4622/? [1:09:12<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4623/? [1:09:12<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4623/? [1:09:13<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4624/? [1:09:13<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4624/? [1:09:14<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4625/? [1:09:14<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4625/? [1:09:15<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0147, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4626/? [1:09:15<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0147, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4626/? [1:09:16<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4627/? [1:09:16<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4627/? [1:09:17<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4628/? [1:09:17<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4628/? [1:09:18<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4629/? [1:09:19<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4629/? [1:09:19<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4630/? [1:09:20<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4630/? [1:09:20<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00854, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4631/? [1:09:21<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.00854, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4631/? [1:09:21<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4632/? [1:09:22<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4632/? [1:09:22<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4633/? [1:09:23<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0117, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4633/? [1:09:23<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4634/? [1:09:24<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4634/? [1:09:24<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4635/? [1:09:25<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0154, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4635/? [1:09:25<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4636/? [1:09:26<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4636/? [1:09:26<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4637/? [1:09:27<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4637/? [1:09:27<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4638/? [1:09:28<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4638/? [1:09:28<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4639/? [1:09:29<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4639/? [1:09:29<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4640/? [1:09:30<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4640/? [1:09:30<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4641/? [1:09:31<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4641/? [1:09:31<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4642/? [1:09:32<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4642/? [1:09:32<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4643/? [1:09:33<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4643/? [1:09:33<00:00,  1.11it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0187, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4644/? [1:09:34<00:00,  1.11it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0187, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4644/? [1:09:34<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4645/? [1:09:35<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4645/? [1:09:35<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4646/? [1:09:36<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4646/? [1:09:36<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4647/? [1:09:37<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4647/? [1:09:38<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0164, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4648/? [1:09:38<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0164, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4648/? [1:09:39<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4649/? [1:09:39<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0142, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4649/? [1:09:40<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4650/? [1:09:40<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4650/? [1:09:41<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0147, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4651/? [1:09:41<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0147, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4651/? [1:09:42<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4652/? [1:09:42<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4652/? [1:09:43<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4653/? [1:09:43<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4653/? [1:09:44<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4654/? [1:09:44<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0129, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4654/? [1:09:45<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4655/? [1:09:45<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4655/? [1:09:46<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4656/? [1:09:46<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4656/? [1:09:47<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4657/? [1:09:47<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0137, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4657/? [1:09:48<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4658/? [1:09:48<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4658/? [1:09:49<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4659/? [1:09:49<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4659/? [1:09:50<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4660/? [1:09:50<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4660/? [1:09:51<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4661/? [1:09:51<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4661/? [1:09:52<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4662/? [1:09:53<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0136, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4662/? [1:09:53<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4663/? [1:09:54<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4663/? [1:09:54<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4664/? [1:09:55<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0122, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4664/? [1:09:55<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4665/? [1:09:56<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.014, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4665/? [1:09:56<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4666/? [1:09:57<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4666/? [1:09:57<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4667/? [1:09:58<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00916, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4667/? [1:09:58<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4668/? [1:09:59<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4668/? [1:09:59<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4669/? [1:10:00<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4669/? [1:10:00<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4670/? [1:10:01<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4670/? [1:10:01<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4671/? [1:10:02<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4671/? [1:10:02<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4672/? [1:10:03<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4672/? [1:10:03<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4673/? [1:10:04<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4673/? [1:10:04<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4674/? [1:10:05<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0104, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4674/? [1:10:05<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4675/? [1:10:06<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0115, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4675/? [1:10:06<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4676/? [1:10:07<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.012, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4676/? [1:10:07<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4677/? [1:10:08<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0146, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4677/? [1:10:08<00:00,  1.11it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4678/? [1:10:09<00:00,  1.11it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0145, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4678/? [1:10:09<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4679/? [1:10:10<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0112, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4679/? [1:10:10<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4680/? [1:10:11<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0125, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4680/? [1:10:11<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4681/? [1:10:12<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4681/? [1:10:13<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4682/? [1:10:13<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0101, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4682/? [1:10:14<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4683/? [1:10:14<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0128, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4683/? [1:10:15<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4684/? [1:10:15<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0114, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4684/? [1:10:16<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4685/? [1:10:16<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4685/? [1:10:17<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4686/? [1:10:17<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0103, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4686/? [1:10:18<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4687/? [1:10:18<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.00995, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4687/? [1:10:19<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4688/? [1:10:19<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0157, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4688/? [1:10:20<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4689/? [1:10:20<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0116, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4689/? [1:10:21<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4690/? [1:10:21<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0161, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4690/? [1:10:22<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4691/? [1:10:22<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0111, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4691/? [1:10:23<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4692/? [1:10:23<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0141, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4692/? [1:10:24<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4693/? [1:10:24<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0133, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4693/? [1:10:25<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4694/? [1:10:25<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0148, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4694/? [1:10:26<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4695/? [1:10:26<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0106, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4695/? [1:10:27<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4696/? [1:10:28<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0107, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4696/? [1:10:28<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00966] 
Training: |          | 4697/? [1:10:29<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4697/? [1:10:29<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4698/? [1:10:30<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0149, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4698/? [1:10:30<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0167, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4699/? [1:10:31<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0167, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4699/? [1:10:31<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4700/? [1:10:32<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0134, val/loss=17.90, val/top_5_accuracy=0.00966]
Training: |          | 4700/? [1:10:32<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0165, val/loss=17.90, val/top_5_accuracy=0.00966]

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Training: |          | 4700/? [1:10:38<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0165, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4701/? [1:10:38<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0165, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4701/? [1:10:39<00:00,  1.11it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00745, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4702/? [1:10:40<00:00,  1.11it/s, v_num=2, train/loss=18.00, train/top_5_accuracy=0.00745, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4702/? [1:10:40<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00981]  
Training: |          | 4703/? [1:10:41<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.010, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4703/? [1:10:41<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4704/? [1:10:42<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4704/? [1:10:42<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4705/? [1:10:43<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0142, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4705/? [1:10:43<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4706/? [1:10:44<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4706/? [1:10:44<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4707/? [1:10:45<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0104, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4707/? [1:10:45<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4708/? [1:10:46<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4708/? [1:10:46<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4709/? [1:10:47<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4709/? [1:10:47<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4710/? [1:10:48<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4710/? [1:10:48<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4711/? [1:10:49<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4711/? [1:10:49<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4712/? [1:10:50<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4712/? [1:10:50<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4713/? [1:10:51<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.00983, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4713/? [1:10:51<00:00,  1.11it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0171, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4714/? [1:10:52<00:00,  1.11it/s, v_num=2, train/loss=16.10, train/top_5_accuracy=0.0171, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4714/? [1:10:52<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4715/? [1:10:53<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4715/? [1:10:53<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0182, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4716/? [1:10:54<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0182, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4716/? [1:10:54<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4717/? [1:10:55<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4717/? [1:10:55<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4718/? [1:10:56<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4718/? [1:10:56<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4719/? [1:10:57<00:00,  1.11it/s, v_num=2, train/loss=17.40, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4719/? [1:10:57<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4720/? [1:10:58<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4720/? [1:10:58<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4721/? [1:10:59<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4721/? [1:11:00<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4722/? [1:11:00<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4722/? [1:11:01<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4723/? [1:11:01<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0152, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4723/? [1:11:02<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4724/? [1:11:02<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4724/? [1:11:03<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4725/? [1:11:03<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.013, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4725/? [1:11:04<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4726/? [1:11:04<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4726/? [1:11:05<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4727/? [1:11:05<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4727/? [1:11:06<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4728/? [1:11:06<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4728/? [1:11:07<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4729/? [1:11:07<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4729/? [1:11:08<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4730/? [1:11:08<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0139, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4730/? [1:11:09<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4731/? [1:11:10<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4731/? [1:11:11<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4732/? [1:11:11<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00989, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4732/? [1:11:12<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4733/? [1:11:12<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4733/? [1:11:13<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4734/? [1:11:13<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.011, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4734/? [1:11:14<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4735/? [1:11:14<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4735/? [1:11:15<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4736/? [1:11:15<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0141, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4736/? [1:11:16<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4737/? [1:11:16<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0114, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4737/? [1:11:17<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0178, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4738/? [1:11:17<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0178, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4738/? [1:11:18<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4739/? [1:11:18<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.016, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4739/? [1:11:19<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4740/? [1:11:19<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0128, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4740/? [1:11:20<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4741/? [1:11:20<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0148, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4741/? [1:11:21<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4742/? [1:11:21<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0102, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4742/? [1:11:22<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4743/? [1:11:22<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4743/? [1:11:23<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0177, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4744/? [1:11:23<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0177, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4744/? [1:11:24<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4745/? [1:11:24<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4745/? [1:11:25<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4746/? [1:11:25<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4746/? [1:11:26<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4747/? [1:11:27<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0164, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4747/? [1:11:27<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4748/? [1:11:28<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0101, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4748/? [1:11:28<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4749/? [1:11:29<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0109, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4749/? [1:11:29<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4750/? [1:11:30<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0122, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4750/? [1:11:30<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4751/? [1:11:31<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4751/? [1:11:31<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4752/? [1:11:32<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0162, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4752/? [1:11:32<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4753/? [1:11:33<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4753/? [1:11:33<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4754/? [1:11:34<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4754/? [1:11:34<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4755/? [1:11:35<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0176, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4755/? [1:11:35<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4756/? [1:11:36<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4756/? [1:11:36<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4757/? [1:11:37<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4757/? [1:11:37<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4758/? [1:11:38<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4758/? [1:11:38<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4759/? [1:11:39<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4759/? [1:11:39<00:00,  1.11it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0187, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4760/? [1:11:40<00:00,  1.11it/s, v_num=2, train/loss=16.00, train/top_5_accuracy=0.0187, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4760/? [1:11:40<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4761/? [1:11:41<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0137, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4761/? [1:11:41<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4762/? [1:11:42<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0094, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4762/? [1:11:42<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4763/? [1:11:43<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4763/? [1:11:43<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4764/? [1:11:44<00:00,  1.11it/s, v_num=2, train/loss=17.50, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4764/? [1:11:44<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0147, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4765/? [1:11:45<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0147, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4765/? [1:11:45<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4766/? [1:11:46<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.00952, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4766/? [1:11:46<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4767/? [1:11:47<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4767/? [1:11:47<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4768/? [1:11:48<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0123, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4768/? [1:11:48<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4769/? [1:11:49<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4769/? [1:11:50<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4770/? [1:11:50<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.0179, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4770/? [1:11:51<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4771/? [1:11:51<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.014, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4771/? [1:11:52<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4772/? [1:11:52<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4772/? [1:11:53<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4773/? [1:11:53<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0144, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4773/? [1:11:54<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4774/? [1:11:54<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0145, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4774/? [1:11:55<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4775/? [1:11:55<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0118, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4775/? [1:11:56<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4776/? [1:11:56<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0156, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4776/? [1:11:57<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4777/? [1:11:57<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.012, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4777/? [1:11:58<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4778/? [1:11:58<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0129, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4778/? [1:11:59<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4779/? [1:11:59<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4779/? [1:12:00<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4780/? [1:12:00<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.00995, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4780/? [1:12:01<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4781/? [1:12:01<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0136, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4781/? [1:12:02<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4782/? [1:12:03<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0132, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4782/? [1:12:03<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4783/? [1:12:04<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0126, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4783/? [1:12:04<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4784/? [1:12:05<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4784/? [1:12:05<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4785/? [1:12:06<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0115, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4785/? [1:12:06<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4786/? [1:12:07<00:00,  1.11it/s, v_num=2, train/loss=16.60, train/top_5_accuracy=0.0135, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4786/? [1:12:07<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4787/? [1:12:08<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4787/? [1:12:08<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4788/? [1:12:09<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0127, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4788/? [1:12:09<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4789/? [1:12:10<00:00,  1.11it/s, v_num=2, train/loss=17.10, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4789/? [1:12:10<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4790/? [1:12:11<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0113, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4790/? [1:12:11<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4791/? [1:12:12<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0112, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4791/? [1:12:12<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4792/? [1:12:13<00:00,  1.11it/s, v_num=2, train/loss=16.80, train/top_5_accuracy=0.0143, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4792/? [1:12:13<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4793/? [1:12:14<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4793/? [1:12:14<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4794/? [1:12:15<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0111, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4794/? [1:12:15<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4795/? [1:12:16<00:00,  1.11it/s, v_num=2, train/loss=16.90, train/top_5_accuracy=0.0146, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4795/? [1:12:16<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.00981] 
Training: |          | 4796/? [1:12:17<00:00,  1.11it/s, v_num=2, train/loss=16.20, train/top_5_accuracy=0.015, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4796/? [1:12:17<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4797/? [1:12:18<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0121, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4797/? [1:12:18<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4798/? [1:12:19<00:00,  1.11it/s, v_num=2, train/loss=16.40, train/top_5_accuracy=0.0116, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4798/? [1:12:19<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4799/? [1:12:20<00:00,  1.11it/s, v_num=2, train/loss=17.20, train/top_5_accuracy=0.0107, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4799/? [1:12:20<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4800/? [1:12:21<00:00,  1.11it/s, v_num=2, train/loss=16.50, train/top_5_accuracy=0.0166, val/loss=18.00, val/top_5_accuracy=0.00981]
Training: |          | 4800/? [1:12:21<00:00,  1.11it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=18.00, val/top_5_accuracy=0.00981]

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Training: |          | 4800/? [1:12:28<00:00,  1.10it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0105] 
Training: |          | 4800/? [1:12:28<00:00,  1.10it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0105]`Trainer.fit` stopped: `max_steps=1200` reached.

Training: |          | 4800/? [1:12:28<00:00,  1.10it/s, v_num=2, train/loss=17.00, train/top_5_accuracy=0.0117, val/loss=17.60, val/top_5_accuracy=0.0105]
[2026-07-18 19:14:54,884][fish_speech.utils.utils][INFO] - [rank: 0] Output dir: results/s2pro_egy_fast